## 5 Results and Analysis  
### Measurement Model  
During this step, an evaluation was conducted to establish the reliability and validity of the measurement model [52; 53]. The indicator reliability aimed to assess the trustworthiness and the ability of each item to accurately measure its respective construct, whereas Cronbach's alpha and CR measured internal consistency [54]. This means they evaluated how well a set of items consistently reflected their corresponding construct. The results shown in Table 3 revealed that all 22 items exhibited loading factors surpassing 0.7, indicating that the threshold for indicator reliability was met. Moreover, both Cronbach's alpha and CR exceeded 0.70, suggesting that the above criterion was satisfied, as both measures demonstrated values above 0.7, thus indicating an adequate level of internal consistency.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Variable**} & \multirow{2}{*}{**Items**} & **Indicator** & **Cronbach’s** & **Composite** & \multirow{2}{*}{**AVE**} \\  & & **Loading** & **Alpha** & **Reliability** & \\ \hline \multirow{4}{*}{**SysQ**} & SysQ1 & 0.888 & & & \\  & SysQ2 & 0.703 & & & \\  & SysQ3 & 0.847 & & & \\  & SysQ4 & 0.877 & & & \\ \hline \multirow{4}{*}{**SerQ**} & SeEQ1 & 0.792 & & & \\  & SeEQ2 & 0.996 & 0.907 & 0.904 & 0.760 \\  & SeEQ3 & 0.813 & & & \\ \hline \multirow{4}{*}{**IQ**} & IQ1 & 0.735 & & & \\  & IQ2 & 0.884 & & & \\  & IQ3 & 0.884 & 0.861 & 0.904 & 0.702 \\  & IQ4 & 0.841 & & & \\ \hline \multirow{4}{*}{**SSI**} & SSI1 & 0.839 & & & \\  & SSI2 & 0.888 & 0.871 & 0.911 & 0.719 \\  & SSI3 & 0.878 & & & \\  & SSI4 & 0.781 & & & \\ \hline \multirow{4}{*}{**SDL**} & SDL1 & 0.850 & & & \\  & SDL2 & 0.887 & 0.893 & 0.925 & 0.754 \\  & SDL3 & 0.884 & & & \\  & SDL4 & 0.852 & & & \\ \hline \multirow{4}{*}{**SS**} & SSI1 & 0.930 & & & \\  & SS2 & 0.946 & 0.893 & 0.933 & 0.823 \\ \cline{1-1}  & SS4 & 0.842 & & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: The measurement model statistics.  
With regard to the validity of the measurement model, it was evaluated through convergent validity and discriminant validity. Convergent validity, the degree to which two distinct measures or items effectively capture and assess the same construct, was evaluated using the average variance extracted (AVE), which required the AVE value to exceed 0. According to Table 3, all values of AVE for all constructs fell within the range of 0.692 to 0.823, which indicated that the requirement of convergent validity was satisfied. Table 4 displays the square root of AVE for all constructs and indicates that these values exceed the correlations of each construct with other constructs.  
With regard to the criteria of cross-loading, it is essential that a particular item demonstrates higher loadings on its perspective construct compared with its loading on other constructs that are being addressed in the study. The values of the cross-factor for all items are presented in Table 5, which confirms that the requirement for cross-loading was met.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Variables** & **IQ** & **SDL** & **SerQ** & **SSI** & **SSS** & **SysQ** \\ \hline
**IQ** & 0.838 & & & & & \\ \hline
**SDL** & 0.325 & 0.868 & & & & \\ \hline
**SerQ** & 0.342 & 0.071 & 0.872 & & & \\ \hline
**SSI** & 0.500 & 0.334 & 0.352 & 0.848 & & \\ \hline
**SSS** & 0.180 & 0.389 & 0.020 & 0.218 & 0.907 & \\ \hline
**SysQ** & 0.572 & 0.318 & 0.346 & 0.631 & 0.276 & 0.832 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Discriminant validity: square root of AVE.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Variables** & **IQ** & **SDL** & **SerQ** & **SSI** & **SSS** & **SysQ** \\ \hline  
\hline \end{tabular}
\end{table}
Table 5: Cross-loading values.  
After evaluating the reliability and validity of the measurement model, the next step is assessing the structural model, which was performed as shown in the following section.