## 5 Analysis of the Data and Results
### Analysis Model  
Figure 1's conceptual model from the study is replicated by the SEM shown in Figure 3. According to [PERSON], et al. [65], the consistency of each indication, the overall consistency, the average extracted variance (AVE), and the discriminant validity must all be estimated for the measurement model assessment. The PLS algorithm throughout this work responds to the advice of [PERSON] [49]: weighting scheme: path weighing; data metric with mean 0 and variance 1; 300 maximum iterations; 1 \(\times\) 10\({}^{5}\)'' 1.0E-5 abort criteria; and initial weights of 1.0. In general, indicators with outer loadings of 0.40 to 0.70 should only be taken into account for exclusion from the scale if doing so leads to a considerably greater composite reliability and AVE [66]. It has been determined that outer load variables with values lower than 0.6 do not meet this condition and should not be the subject of future research [65]. At this level, the variance explained by an indicator's component accounts for \begin{table}
\begin{tabular}{c c c} \hline \hline
**Variable** & **Characteristics** & **(\%)** \\ \hline \multirow{8}{*}{Experience (Years)} & Less than five & 19 \\  & 5–10 & 16.0 \\  & 11–15 & 28 \\  & 16–25 & 22. \\  & More than 25 & 16 \\  & Architect & 26.5 \\  & Civil Engineering & 31 \\ Field & Electrical Engineering & 19 \\  & Mechanical Engineering & 16.0 \\  & Quantity surveying & 9.0 \\  & Director & 5.0 \\  & Senior Manager & 10 \\ Position & Manager & 30.0 \\  & Design Engineer & 18 \\  & Site Engineer & 35.0 \\  & Diploma & 7.0 \\  & Bachelor’s degree & 11 \\ Educational & Master’s degree & 47 \\  & PhD & 24 \\  & Others & 18 \\  & Client/Developer & 38.0 \\ Function of Organization & Consultant & 28.7 \\  & Contractor & 33.3 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Demographic characteristic frequency distribution. almost half of its variance and the percentage of variance exceeds the uncertainty variable. Figure 3 displays the outside loadings for each variable in the existing and updated measurement scales. Therefore, the previous research instrument was removed together with all exterior loads, except maybe one item connected to the unsupportive industry norm \"B3\"; it was discarded because it had a rating of less than 0.6, indicating that it had little impact on the critical factors. After these variables were removed, a modified model was examined further. Cronbach alpha limits, a measure of sensitivity to the amount of elements included, have been used to assess the internal consistency of composite reliability (cr) [PERSON], et al. [65]. [PERSON], et al. [65] state that values above 0.70 are appropriate for all types of analysis and that values above 0.60 are ideal for exploratory research  
Discriminant validity is well-defined once the construct appropriately differs from all the other constructs by the observed standards. So, the construct is unique and covers occurrences that aren't specified by additional model constructs according to its founding discriminatory validity [67]. [PERSON]'s (1981) and the cross-loading criteria can be used to test discriminant validity, respectively. By comparing the square root of the AVE of each construct to the correlations of a particular construct with any other constructs, one can evaluate the discriminating validity of the construct. [PERSON] and [PERSON] [47] rules dictate that the square root of the AVE must be greater than the correlation between the latent variables. Table 4 indicates that the outcome supports the measurement model's discriminant validity [68]. However, many academics disagree with the [PERSON] and [PERSON] [47] definition of distinctive validity for discrimination. This study also employed the cross-loading criterion, which [PERSON], et al. [69] proposed as an important way of evaluating discriminatory validity to ascertain discriminatory validity. According to this strategy, indicators should load more heavily on a particular latent construct than they should on all other latent constructs combined.