Comparative Modeling Approach to Capture the Differences in BIM Adoption Decision-Making Process in Australia and China
Publication: Journal of Construction Engineering and Management
Volume 146, Issue 2
Abstract
The growing rate of building information modeling (BIM) adoption inevitability adds to the importance of understanding the BIM adoption decision-making process. Several models based on systematic surveys are available in the literature to formulate the BIM adoption decision-making process. It is still, however, not clear whether the decision parameters in these models are universally important. This study examines the main attributes of the BIM adoption decision-making process in China and Australia. An adoption model developed earlier for Australia is tested for Chinese data collected from 103 small and medium construction companies (SMEs). By highlighting model fitness issues, the model is then reconstructed for comparing BIM adoption in cross-cultural contexts. Data are analyzed using a logistic regression to understand the main factors impacting BIM adoption. Structural equation modeling based on multigroup analysis is also adopted in the analysis. The analysis indicates that Australian construction SMEs adopt BIM to solve organizational collaboration problems and improve workflow efficiency, whereas Chinese construction SMEs adopt BIM to improve organizational technical ability. The results of this study highlighted the Chinse companies tend to be more careful during the implementation of new technology to minimize uncertainty, whereas BIM adoption decision makers in Australian companies are more focused on change management and empowering subordinates.
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Data Availability Statement
Data generated or analyzed during the study are available from the corresponding author by request.
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Journal of Construction Engineering and Management
Volume 146 • Issue 2 • February 2020
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©2019 American Society of Civil Engineers.
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Received: Oct 12, 2018
Accepted: May 30, 2019
Published online: Nov 30, 2019
Published in print: Feb 1, 2020
Discussion open until: Apr 30, 2020
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