Decoding BIM Adoption: A Meta-Analysis of 10 Years of Research—Exploring the Influence of Sample Size, Economic Level, and National Culture
Author(s): |
Kaiyang Wang
Min Guo Luigi Di Sarno Yao Sun |
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Medium: | journal article |
Language(s): | English |
Published in: | Buildings, 27 March 2024, n. 4, v. 14 |
Page(s): | 920 |
DOI: | 10.3390/buildings14040920 |
Abstract: |
In recent years, some studies have explored the determinants of Building Information Modeling (BIM) adoption. However, the findings of these studies are varied and sometimes contradicting. Consequently, this study undertakes an in-depth exploration of the relationship between influencing factors and behavioral intention. This analysis is achieved through a synthesis of findings from prior empirical studies, considering the nuanced impacts of specific contextual factors, including sample size, national culture, and economic level, on these relationships. In total, this meta-analysis encompasses 57 articles, and as of 31 December 2023, incorporates 63 datasets comprising a collective sample size of 13,301. An extended Unified Theory of Acceptance and Use of Technology (UTAUT) model was developed based on the most frequently studied constructs relevant to BIM adoption. The analysis reveals that BIM adoption is primarily affected by performance expectancy, social influence, facilitating conditions, effort expectancy, and perceived value. The moderator analysis indicates that sample size statistically significantly moderates the relationships between facilitating conditions and use behavior. Moreover, the extent of individualism in each national culture significantly moderates the associations between facilitating conditions and user behavior. The research serves to enrich the existing body of literature on BIM acceptance by addressing contradictory and mixed results found in empirical studies. It represents one of the first attempts to explore the influence of sample size, economic level, and Hofstede’s six cultural dimensions as moderators in the field of BIM utilizing meta-analytic techniques. |
Copyright: | © 2024 by the authors; licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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10773317 - Published on:
29/04/2024 - Last updated on:
05/06/2024