# Dynamic BIM Adoption Impact on Contract Cost Variance Factors Using PLS-SEM Techniques
## 4 Results and Discussion
### Significant CCV Factors with Their Interdependencies Using a Developed Causal Model  
The developed causal model was illustrated by showcasing the significant CCV factors interdependencies among group factors, along with the results demonstrating the construct and discriminant validity of the developed causal model.  
Figure 7 depicts the developed causal model highlighting the significant CCV factors. Specifically, the significant components for the factor EF are EF1, EF7, EF8, EF9, EF10, EF12, and EF13. Concerning CP, the noteworthy factors encompass CP1, CP3, CP5, CP6, CP7, CP8, and CP9 within the CP1-CP range. The pivotal factors for PC consist of PC1, PC2, PC3, PC5, PC6, PC8, and PC9. Additionally, the significant factors related to EP are EP4, EP5, EP6, and EP7, while for IQ, they are IQ1 and IQ2.  
The satisfied construct and reliability validity of the developed model are shown in Table 10. The AVE, composite reliability, and Cronbach's alpha threshold values were 0.5, 0.7, and 0.7, respectively. In addition, the _discriminant_ validity of the developed model in terms of Cornell-Larker and cross-loading was shown in Tables 11 and 12, respectively.  
Figure 6: Relative weight of factors computation outline.  
The developed model elucidated that PC directly influences CCV and indirect impact through CP. Simultaneously, EF, CP, and EP directly influence CCV. Conversely, IQ indirectly impacts CCV at the bidding stage) through EP, as illustrated in Figure 7.  
Project Characteristics, such as project scale, complexity, and scope, can directly impact CCV. For instance, larger projects may inherently have more variables, leading to potential cost variations. Also, PC can indirectly affect CCV through its influence on Contractual Procedures. How Project Characteristics project characteristics are managed through contractual agreements can impact cost variance. For example, more explicit contracts or frequent scope changes can lead to cost discrepancies.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Cronbach’s Alpha** & \
\begin{tabular}{c} **Composite** \\ **Reliability** \\ \end{tabular} &
\begin{tabular}{c} **Average Variance Extracted** \\ **(AVE)** \\ \end{tabular} \\ \hline CP & 0.881 & 0.907 & 0.557 \\ EF & 0.832 & 0.873 & 0.507 \\ EP & 0.786 & 0.860 & 0.607 \\ IQ & 0.775 & 0.897 & 0.814 \\ PC & 0.896 & 0.917 & 0.582 \\ \hline \hline \end{tabular}
\end{table}
Table 10: Construct and reliability validity of the developed model.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **CP** & **EF** & **EP** & **IQ** & **PC** \\ \hline CP & 0.746 & & & & \\ EF & \(-\)0.043 & 0.712 & & & \\ EP & 0.407 & 0.011 & 0.779 & & \\ IQ & 0.131 & 0.096 & 0.489 & 0.902 & \\ PC & 0.607 & 0.073 & 0.290 & 0.081 & 0.763 \\ \hline \hline \end{tabular}
\end{table}
Table 11: Discriminant validity of latent group (Fornell–Larcker).  
Figure 7: Causal model with impact factors.  
External Factors, such as economic conditions, regulatory changes, or market dynamics, directly influence CCV. For instance, changes in external regulations can directly impact project costs. These factors, along with Contractual Procedures and Estimator Performance, are crucial elements that need to be monitored and adapted to manage CCV effectively.  
Information Quality indirectly affects CCV through its influence on Estimator Performance. High-quality information provided to estimators can lead to more accurate cost estimations, impacting the final contract cost. If incomplete or inaccurate information is accurate, estimators may make errors, leading to cost variances.  
Based on the above information, PC directly impacts CCV, with larger projects potentially leading to more cost variations. PC indirectly affects CCV through its influence on CP. External Factors directly influence CCV, along with CP and EP, essential for effective CCV management. IQ impacts CCV indirectly through EP, emphasizing the importance of accurate information for precise cost estimations.