# Dynamic BIM Adoption Impact on Contract Cost Variance Factors Using PLS-SEM Techniques
## 3 Methodology
### Develop the Causal Model Using the PLS-SEM Model (Component 1)
#### 3.1.2 Build the Causal Model
The flow charts of the first, second, and third stages are shown in Figure 4a, b, and c, respectively. More details of each stage and their results are displayed in the following sections. The primary objective of the first stage is to pinpoint latent groups that do not impact CCV and subsequently eliminate these groups from the forthcoming causal model construction (that will be built in the third stage). The latent groups under scrutiny include IQ, EP, PC, CP, and EF. This phase entails conducting individual hypothesis tests on each of these five latent groups about CCV. The outcome of these tests determines whether a latent group is deemed significant and included in the final causal model or non-significant and excluded. This decision hinges on the significance level of the \(p\)-value, where a \(p\)-value below 0.10 indicates inclusion (significant latent group), and a \(p\)-value exceeding 0.10 signifies exclusion (non-significant latent group). The process of this stage is illustrated in Figure 5a. Given the five latent groups involved, five distinct models (IQ\(\rightarrow\)CCV, EP\(\rightarrow\)CCV, PC\(\rightarrow\)CCV, CP\(\rightarrow\)CCV, and EF\(\rightarrow\)CCV) were executed during this first stage. Before performing the hypothesis test of the five models, the model was evaluated in terms of construct and discriminant validity. Table 5 displays the construct validity of the five models at the first stage, and Table 5 also shows the significant CCV factors for each model. For construct validity, it is noticed in Table 4 that [PERSON]'s alpha and composite reliability of the latent groups for all five models exceeded the threshold value (0.7). In addition, their AVE values were more than the acceptable value (0.5), as shown in Table 4. These results indicate that the construct validity was satisfied. The discriminant validity was unnecessary because each model had only one latent group. The third column of Table 5 shows the significant factors for each latent group that satisfied the construct validity. For hypothesis test results, Table 6 shows the test results of the first stage. The direction of the path is one way from the latent group (EP, PC, EF, and IQ) to the CCV. The \(p\)-value test ranged from 0.0002 to 0.02, less than 0.1. The test indicated accepting the alternative hypothesis (b\(\
eq\)0) that stated a relationship and coefficient (b\(\_\)i \(\
eq\) 0) between latent groups to CCV. Therefore, the five latent groups are significant in the CCV. \begin{table}
\begin{tabular}{l c c c c c c c c c c c} \hline \hline
**Year** & **2010** & **2011** & **2012** & **2013** & **2014** & **2015** & **2016** & **2017** & **2018** & **2019** & **2020** & **2021** \\ \hline Average of & 12.99 & 9.48 & 9.74 & 10.39 & 32.40 & 4.79 & 1.22 & 11.53 & 24.12 & 7.84 & 5.75 & 5.43 \\ Mean of & & & & & & & & & & & & \\ average & & & & & & & & & & & & \\ CCV (\%) & & & & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Average of the CCV from 2010 to 2021. Figure 4: _Cont._  
Figure 4: _Cont_. Figure 4: Flow chart of building causal CCV model (**a**) first stage, (**b**) second stage, (**c**) third stage. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Stage One Model** & **Hypothesis Model Code** & _p-Value_ & **Status** \\ \hline Model 1 & EP \(\rightarrow\) CCV & 0.02 & Accept \\ Model 2 & PC \(\rightarrow\) CCV & 0.01 & Accept \\ Model 3 & EF \(\rightarrow\) CCV & 0.002 & Accept \\ Model 4 & IQ \(\rightarrow\) CCV & 0.008 & Accept \\ Model 5 & CP \(\rightarrow\) CCV & 0.02 & Accept \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Models of Stage 1. Figure 5: Summarize and visualize the steps of building the developed causal model. The second stage examines any two influences of any two latent groups on CCV. First, there is a need to determine the number models that performed in the second stage, including two logic hypothesis relationships.