# Building Information Modeling Impact on Cost Overrun Risk Factors and Interrelationships
## 4 Results and Discussion  
### Significant Cost Overrun Risk Factors Using BIM  
The main purpose of outer model evaluation is to recognize and remove insignificant risk factors. Upon conducting an outer evaluation of seven models, it was observed that the results of the outer evaluation were consistent across all seven models. Therefore, findings from the outer evaluation of the first model are deemed sufficient. Figure 4 illustrates significant factors and their corresponding outer loading values, which satisfy construct and discriminant validity criteria. Regarding construct validity, Table 4 presents values for Cronbach's Alpha, CR, and AVE for three groups. These values surpass acceptable thresholds of 0.7 for both Cronbach's Alpha and CR, as well as 0.5 for AVE, thereby validating the model's construct validity. Moving on to discriminant validity, Table 5 displays the Cornell-Larcker criterion, showcasing discriminant validity among groups. The square root of AVE for each group (found at the intersection of row and column for the same group in Table 5) exceeds correlation coefficients between that group and other groups. This result confirms the presence of discriminant validity. Additionally, the cross-loading value is used to assess discriminant validity. This indicates how strongly an indicator (risk factor) correlates with its associated group construct compared to other groups. Table 6 provides cross-loading values between risk factors and three groups. The cross-loading values for risk factors within their respective groups are higher than those with other groups, as indicated by shaded cells in Table 6.  
An inner model assessment was conducted to identify and rank significant risk factors. This assessment involved performing hypothesis tests on Model 1. Results revealed that \(p\)-values of H1, H2, and H3 were below threshold value, indicating that all three hypotheses were accepted and suggesting that the three groups examined significantly impact cost overrun. Furthermore, weight loadings of the remaining ten risk factors were normalized and ranked in descending order, as depicted in Figure 5. The two highest-ranked risk factors were EXP3 and EXP1, indicating their strong influence. Several intermediate significant risk factors were identified, including FIN3, FIN1, TIM1, TIM2, and TIM3. On the other hand, the remaining risk factors (FIN2, TIM4, and FIN4) exhibited lower significance levels. The risk factor of unqualified or inexperienced labor (EXP3) significantly influences cost overrun when using BIM in the construction stage of a project due to several interconnected reasons. Firstly, lack of knowledge and experience among human resources is identified as one of the most critical risks impacting cost overruns, as it directly affects the efficiency and accuracy of project execution [37]. Inadequate supervision and poor management at the site, which are often consequences of employing unqualified labor, further exacerbate this issue by leading to frequent changes and delays during construction [19]. The risk of a lack of contractor experience and managerial skills (EXP1) significantly influences cost overrun during the construction stage of a project, even when using BIM, due to several interconnected factors. Firstly, while BIM technology offers substantial benefits in project visualization, coordination, and delay reduction, its effectiveness depends on user proficiency. Inexperienced contractors may need help in fully leveraging BIM's capabilities, leading to suboptimal project management and cost control [38]. Additionally, a lack of managerial skills can exacerbate issues such as inadequate control and monitoring, poor