## 4 Results
### First-Order Measurement Model  
The SEM presented in Figure 4 signifies the study's conceptual model in Figure 1. From Tables 1 and 2, each BIM and OPS build of the model was described as well classified based on prior research. [PERSON] et al. 's analysis of model measurement involves the (1) estimations and consistency of the first indicator, (2) combined dependability, (3) extracted average variance (AVE), and (4) discriminant validity [30]. For our study, the PLS method adheres to [PERSON], [PERSON], and [PERSON]'s recommendations for the weighting scheme, data measure, maximum iterations, abort criteria, and starting weights [7]. The scale should only eliminate indicators with outside loadings between 0.40 and 0.65 if doing so significantly increases composite reliability and AVE [8]. It was determined that external load variables smaller than 0.65 did not meet this condition, and, as advised, additional research was deemed unnecessary [3]. This is the threshold at which about half of the indicator's variation is described by its component, and the variance explained exceeds the variance of error [64]. The external loadings with all variables in the basic measurement model can be seen in Table 6 and Figure 4. Therefore, all outside loads for items connected to the stages of knowledge, function, regulations, normalization, creativity, and evaluation had loading factors more than 0.65 based on the original measurement model, indicating their substantial effect on the associated constructs. \begin{table}
\begin{tabular}{c c c c c c} \hline
**BIM Stages** & **Assigned Code** & **Loadings** & **Cronbach Alpha** & **Composite Reliability** & **AVE** \\ \hline \multirow{4}{*}{Knowledge} & BIM.SK2 & 0.867 & 0.853 & 0.901 & 0.695 \\ \cline{2-6}  & BIM.SK3 & 0.803 & - & - & - \\ \cline{2-6}  & BIM.SK4 & 0.807 & - & - & - \\ \cline{2-6}  & BIM.SK5 & 0.855 & - & - & - \\ \hline \multirow{4}{*}{Function} & BIM.SF1 & 0.790 & 0.802 & 0.862 & 0.558 \\ \cline{2-6}  & BIM.SF2 & 0.751 & - & - & - \\ \cline{2-6}  & BIM.SF3 & 0.695 & - & - & - \\ \cline{2-6}  & BIM.SF4 & 0.707 & - & - & - \\ \cline{2-6}  & BIM.SF5 & 0.781 & - & - & - \\ \hline \multirow{4}{*}{Evaluation} & BIM.SE1 & 0.919 & 0.873 & 0.922 & 0.798 \\ \cline{2-6}  & BIM.SE2 & 0.914 & - & - & - \\ \cline{2-6}  & BIM.SE3 & 0.845 & - & - & - \\ \hline \multirow{4}{*}{Creativity} & BIM.SC1 & 0.816 & 0.806 & 0.885 & 0.720 \\ \cline{2-6}  & BIM.SC2 & 0.868 & - & - & - \\ \cline{2-6}  & BIM.SC3 & 0.861 & - & - & - \\ \hline \multirow{4}{*}{Regulations} & BIM.SR1 & 0.737 & 0.736 & 0.848 & 0.651 \\ \cline{2-6}  & BIM.SR2 & 0.840 & - & - & - \\ \cline{2-6}  & BIM.SR3 & 0.841 & - & - & - \\ \hline \multirow{2}{*}{Normalization} & BIM.SN1 & 0.921 & 0.844 & 0.927 & 0.865 \\ \cline{2-6}  & BIM.SN2 & 0.939 & - & - & - \\ \hline \end{tabular}
\end{table} 
Table 6: Check for validity and reliability in the construct. [PERSON], [PERSON], and [PERSON] evaluated the internal reliability for composite reliability (C.R.) using Cronbach's alpha, which measures sensitivity concerning the number of constituents [31]. According to [PERSON] et al., values over 0.65 are suitable for any study, as well as above 0.50, particularly for exploratory research [32]. The models fall accordingly to the C.R. > 0.70 criterion and are so accepted, as shown in Table 6. AVE works as a typical metric for assessing the convergent validity of model structures, with values over 0.50 indicating an excellent convergent value [34]. According to Table 4, all constructions pass this criterion. When the idea differs from other conceptions based on observable criteria, discriminant validity has been demonstrated. As a result, the construct is distinct. It captures events poorly described by other constructs in the model, as seen by the construct's discriminatory validity, according to [PERSON], [PERSON], and [PERSON] [33]. There are three ways to measure discriminant validity: the [PERSON] et al. criteria, the HTMT or Heterotrait-Monotrait ratio of the correlations criterion, and the cross-loading criterion [9].