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Original Articles

Exploring the adoption of BIM amidst the COVID-19 crisis in China

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Pages 930-947 | Received 09 Feb 2021, Accepted 19 Apr 2021, Published online: 12 May 2021
 

ABSTRACT

The outbreak of COVID-19 has introduced critical challenges in the architecture, engineering, and construction (AEC) industry; to address these challenges, building information modelling (BIM) can be applied as a project management tool to help enhance collaboration among stakeholders and improve business performance. Amidst the COVID-19 crisis, there is a greater need to explore and implement effective strategies to promote a wider adoption of BIM. However, increasing the willingness of project participants to adopt BIM through event management has not received much attention. Therefore, based on event system theory and innovation diffusion theory, we developed a model to explore the influence of the COVID-19 crisis on the willingness of AEC participants to adopt BIM. Structural equation modelling was performed to test the hypotheses. The results demonstrate that the intention of the AEC project participants to adopt BIM is directly driven by the COVID-19 event criticality and perceived usefulness of BIM. Moreover, the event criticality and BIM technical features (relative advantage, compatibility, and complexity) can indirectly affect this intention, through the perceived usefulness. However, the impact of event disruption and novelty on the BIM adoption intention is not significant. Several recommendations are provided to improve the BIM adoption intention of AEC participants during and after the pandemic.

Acknowledgements

The authors are grateful to all survey participants, the editors, and the reviewers.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by Humanities and Social Sciences Project of Ministry of Education in China: [Grant Number 17JDGC039]; National Natural Science Foundation of China: [Grant Number 19FGLB058]; National Natural Science Foundation of China: [Grant Number 71901206].

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