Impacts of Policy Mix Comprehensiveness on BIM Implementation: Moderating Effects of Environmental State and Response Uncertainty
Publication: Journal of Construction Engineering and Management
Volume 149, Issue 2
Abstract
Due to the great potential but limited use of building information modeling (BIM) as a milestone technology to reshape traditional design and construction practices, governments in many regions of the world have formulated specific sets of complementary policy instruments, namely, policy mixes, to facilitate the development of BIM in the construction industry. Drawing on institutional theory and the organizational sensemaking literature, this study aims to examine how regional institutional policies impact organizational BIM implementation practices and how these impacts are moderated by different sources of uncertainty related to policy making and enforcement from a policy mix comprehensiveness perspective. The effects were empirically tested with a panel data set of 992 high-tech construction firms from 31 provincial jurisdictions in China during 2011–2021. The results provide clear evidence that while regional policy mix comprehensiveness positively impacts the level of BIM implementation at the organizational level, this relationship becomes stronger when firms are experiencing higher levels of environmental state uncertainty derived from regional politician turnover but weaker when firms are experiencing higher levels of response uncertainty derived from organizational top management team (TMT) turnover. As an exploratory effort to empirically assess the impacts of policy environments in the conservative construction industry through integrating the complexity of both regional policy instruments and organizational decision-making processes, this study contributes to a deepened understanding of how construction firms interact with external environments to implement innovative technologies under institutional pressures. The findings reinforce the need to devise policies for innovation diffusion in the construction industry from a more systemic and contingent perspective.
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Data Availability Statement
All data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors gratefully acknowledge the financial support of the National Natural Science Foundation of China (Grant Nos. 71802150 and 72271186).
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Journal of Construction Engineering and Management
Volume 149 • Issue 2 • February 2023
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© 2022 American Society of Civil Engineers.
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Received: May 19, 2022
Accepted: Oct 18, 2022
Published online: Dec 6, 2022
Published in print: Feb 1, 2023
Discussion open until: May 6, 2023
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