Dynamic BIM Adoption Impact on Contract Cost Variance Factors Using PLS-SEM Techniques

Abstract

This paper investigates the Building Information Modeling (BIM) adoption impact on the factors of Contract Cost Variance (CCV) over time. The study considers qualitative and quantitative data to identify the most common causes of CCV through pre-tendering. A partial least square-structure model (PLS-SEM) procedure was used to develop a causal model and rank CCV factors based on their effect, partially based on prior survey raw data conducted in 2022 and the data from 94 projects. Construction industry experts assessed the prior five-year rate of BIM adoption on construction projects to infer the expected trend in BIM adoption in the future (until 2037). Based on the causal model of CCV factors and the future rates of BIM adoption, the dynamic impact of BIM on CCV factors over time was modeled and analyzed. The analysis shows that BIM reduces CCV over time by improving Estimator Performance (EP), Information Quality (IQ), and contractual procedure (CP). The results showed that the CP, EP, and EF have directly impacted CCV, and the PC and IQ indirectly affect the CCV. This paper considers the temporal aspect, examining how the impact of BIM on CCV factors evolves. This dynamic analysis is crucial for long-term strategic planning in construction management.

Keywords

• cost estimation
• PLS-SEM
• CCV-factors
• information quality
• BIM
• causal model