Optimal Government Strategies for BIM Implementation in Low-Income Economies: A Case Study in Syria
Building information modeling (BIM) enables substantial improvement in the architecture, engineering, and construction (AEC) industry. As a leading actor in the AEC industry, policymakers have the means to develop appropriate strategies for addressing the factor affecting BIM implementation. However...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
American Society of Civil Engineers (ASCE)
2024
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/41178/1/optimal-government-strategies-for-bim-implementation-in-low-income-economies.pdf http://umpir.ump.edu.my/id/eprint/41178/2/optimal-government-strategies-for-bim-implementation-in-low-income-economies-a-case-study-in%20Syria.pdf http://umpir.ump.edu.my/id/eprint/41178/ https://doi.org/10.1061/JAEIED.AEENG-1707 |
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| Summary: | Building information modeling (BIM) enables substantial improvement in the architecture, engineering, and construction (AEC) industry. As a leading actor in the AEC industry, policymakers have the means to develop appropriate strategies for addressing the factor affecting BIM implementation. However, the lack of empirical investigation on the relationships between factors to implementing BIM and government strategies prevents the strategies from being effective. This study aimed to establish relationships between critical factors and government strategies for implementing BIM using Syria as a case study. A systematic literature review and semistructured interviews with AEC professionals yielded 27 factors and 12 government strategies for implementing BIM. The collected data were analyzed using descriptive statistics, a chi-squared test, exploratory factor analysis (EFA), and partial least-squares structural equation modeling (PLS-SEM). The EFA classified the factors into four underlying constructs (technology, project environment, governmental and organizational, and people) and government strategies into two underlying constructs (soft and hard strategies). The structural equation model revealed that soft strategies positively affect technology, project environment, and people. Moreover, hard strategies positively affect technology. These findings provide new insights into the body of knowledge on optimal government strategies for implementing BIM in low-income economies. Policymakers can use the findings of this study to prioritize efforts and resources when promoting BIM implementation in the local AEC industry. |
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