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Quality of planning and design (QPD) is crucial for the success of highway infrastructure projects. Inadequate planning and design often lead to costly change orders, rework, and delays. Although previous studies have explored various applications of Building Information Modeling (BIM) in improving the planning and design of highway projects, a critical gap exists in quantifying BIM’s impact on QPD. Addressing this gap can foster evidence-based planning and strategic use of BIM features. This study attempts to fill this gap using structural equation modeling (SEM). Exploratory factor analysis (EFA) with principal component extraction clustered 17 BIM features into four categories: visualization and coordination (V&C), analysis and simulation (A&S), site conditions and safety management (SC&SM), and operations and maintenance (O&M). Confirmatory factor analysis (CFA) validated the factor structure derived from EFA using various model fitness indices, composite reliability, and construct validity assessments and an acceptable measurement model encompassing 15 BIM features was achieved. The final SEM model, developed in AMOS and analyzed using maximum likelihood estimation, revealed that V&C (β=0.50) and A&S features (β=0.20) had a positive and statistically significant effect on QPD (p<0.05 for both). In contrast, SC&SM (β=0.04, p=0.636) and O&M features (β=0.07, p=0.377) demonstrated a positive but statistically insignificant influence. The SEM model showed that 31% of the variance in QPD was collectively explained by 15 BIM features. Despite certain limitations, this study offers a novel quantitative perspective on how specific BIM features can affect QPD in highway projects.
Mushtaq et al. (Tue,) studied this question.