Determining Factors Influencing BIM Adoption: A Competency-Driven Approach
Publication: Journal of Construction Engineering and Management
Volume 150, Issue 8
Abstract
Building information modeling (BIM) adoption has received increasing attention over the past two decades due to its potential to revolutionize the built asset industry. Several different characteristics, facilitators, and drivers of BIM adoption have been identified, which has led to the development of BIM adoption frameworks and guidelines. Many of these elements and frameworks have focused on specific organizational-, project-, or industry-level characteristics. Few have taken a competency-based approach to BIM adoption. Thus, this paper aims to empirically evaluate and validate the factors influencing BIM adoption within organizations operating in the built asset industry as understood through the evolution of their BIM competency profiles. The research consists of a mixed-method data collection on a sample set of 368 organizations participating in the Initiative Québécoise pour la Construction 4.0 (IQC 4.0). The research method of analysis is based on a bivariate approach for testing the correlation between the variables concerning the organization’s internal characteristics and their BIM competency development level. The findings show that the factors, which include field of activity, BIM experience, size, financial capacity, and geographical location, are correlated to an organization’s BIM competency development level; in parallel, an organization’s perceived maturity is strongly correlated. The results from this research can be potentially useful to properly guide and structure governmental initiatives supporting competency development for digital transformation.
Practical Applications
Government initiatives have been undertaken to promote the adoption of BIM in the built asset industry and to encourage organizations to undertake their digital transformation. The province of Quebec, Canada, has established a governmental roadmap for BIM adoption that identifies the key actions to be undertaken by all public bodies in the province to ensure a consistent approach to BIM adoption, and a targeted initiative supporting the digitalization of companies called IQC 4.0. The paper discusses the factors impacting BIM adoption through the lens of organizational competency, an approach not yet covered in the literature. The organizational competencies include managerial, administrative, functional, operational, technical, implementation, supportive, research and development, and normative (ISO) ones. Factors such as an organization’s size, field of activity, financial capacity, and location can influence the development of organizational competencies that impact BIM adoption. Moreover, the internal characteristics of an organization may have varying effects depending on the competencies involved. Those results will provide feedback and potentially inform governmental and organizational initiatives.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The research was funded in part by the Quebec Ministry of Economy, Innovation and Energy. The data collection was conducted in collaboration with the Groupe BIM du Québec.
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Journal of Construction Engineering and Management
Volume 150 • Issue 8 • August 2024
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© 2024 American Society of Civil Engineers.
History
Received: Sep 14, 2023
Accepted: Feb 23, 2024
Published online: May 23, 2024
Published in print: Aug 1, 2024
Discussion open until: Oct 23, 2024
ASCE Technical Topics:
- Architectural engineering
- Asset management
- Building information modeling
- Building management
- Buildings
- Business management
- Construction engineering
- Construction management
- Driver behavior
- Financial management
- Industries
- Infrastructure
- Organizations
- Practice and Profession
- Project management
- Structural engineering
- Structures (by type)
- Traffic engineering
- Transportation engineering
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