## 5 Data Analysis and Results
### Analysis of PLS-SEM Results
#### 5.1.2 Structural Model Assessment  
In the PLS-SEM analysis, after analyzing the measurement model for getting approval for the reliability and validity of the defined constructs, the next step was the structural model assessment. In PLS-SEM as recommend by [PERSON], [PERSON] [116], for testing the predictive power of the structural model, researchers measured R-Square, and path coefficient between the constructs was used. Total predicted R\({}^{2}\) for the dependent variable (intention) is 0.81, which represents substantial coefficients of determination [116]. The result of the hypothesis testing and path coefficients for the structural model was measured, and the findings are shown in Table 7. The values for \"_t_ = 3.091\" and \"_p_ \(<\) 0.001\", \"_t_ = 2.326\" and \"_p_ \(<\) 0.01\", and \"_t_ = 1.645\" and \"_p_ \(<\) 0.05\" can be accepted for _t_-value at various significance levels [138]. The result of the hypotheses calculation by running bootstrapping shows that all the proposed CC adoption antecedent factors had a significant influence on it, except vendor support. Based on the analysis, CC adoption is positively influenced by compatibility (\(\beta\) = 0.249, _t_-value = 4.311, \(p\) \(<\) 0.01). Thus, this hypothesis supported. Competitive pressure (\(\beta\) = 0.381, _t_-value = 5.516, \(p\) \(<\) 0.01) \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Censtructs** & **Items** & **OL (\(\mathbf{>}\)0.7)** & **CA (\(\mathbf{>}\)0.6)** & **CR (\(\mathbf{>}\)0.7)** & **AVE (\(\mathbf{>}\)0.9)** \\ \hline \multirow{3}{*}{Competitive pressure} & CP1 & 0.783 & & & & & \\  & CP2 & 0.856 & 0.71 & 0.836 & 0.63 & \\  & CP3 & 0.737 & & & & & \\ \hline \multirow{3}{*}{Complexity} & CX1 & 0.814 & & & & & \\  & CX2 & 0.84 & & & & & \\  & CX3 & 0.922 & & 0.879 & 0.916 & 0.732 \\  & CX4 & 0.843 & & & & & \\ \hline \multirow{3}{*}{Cost saving} & CS1 & 0.757 & & & & & \\  & CS2 & 0.756 & & 0.772 & 0.852 & 0.59 \\  & CS4 & 0.768 & & & & & \\ \hline \multirow{3}{*}{Vendor support} & VS1 & 0.806 & & & & & \\  & VS2 & 0.771 & & & & & \\  & VS3 & 0.788 & & 0.832 & 0.881 & 0.597 \\  & VS4 & 0.751 & & & & & \\  & VS5 & 0.746 & & & & & \\ \hline \multirow{3}{*}{Technology readiness} & TR1 & 0.762 & & & & & \\  & TR2 & 0.742 & & & & & \\  & TR3 & 0.868 & & & & & \\  & TR4 & 0.825 & & & & & \\ \hline \multirow{3}{*}{Top Manager’s support} & TMS1 & 0.828 & & & & & \\  & TMS3 & 0.772 & & & & & \\ \hline \multirow{3}{*}{Security} & SC1 & 0.828 & & & & & & \\  & SC2 & 0.846 & & & & & \\  & SC3 & 0.803 & & & & & \\  & SC4 & 0.837 & & & & & \\  & SCS & \(-\)0.016 & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: _Cont._has positive significant influence on CC adoption. The complexity has a negative significant influence on CC adoption (\(\beta=-0.153\), \(t\)-value = 2.887, \(p<0.01\)); therefore, this hypothesis is also supported. Cost saving is another factor which had significant and positive influence on CC adoption (\(\beta=0.102\), \(t\)-value = 2.266, \(p<0.05\)). However, vendor support (\(\beta=0.112\), \(t\)-value = 1.447, \(p\)\(>0.05\)) does not have a significant influence on CC adoption, and this hypothesis is not supported. Furthermore, from the analysis, CC adoption is positively influenced by technology readiness (\(\beta=0.285\), \(t\)-value = 4.888, \(p<0.01\)). The results indicated that the top manager's support has a positive and significant influence on CC adoption (\(\beta=0.129\), \(t\)-value = 1.978, \(p<0.05\)). Meanwhile, from the analysis, it shows that CC adoption is negatively and significantly influenced by security (\(\beta=-0.173\), \(t\)-value = 2.226, \(p<0.05\)). It is clear from the result that among all the constructs, competitive pressure had the highest significant level and was the most significant factor that was selected and influenced the individuals' intention for the adoption of CC in higher education, followed by the technology readiness, which had higher significance in bootstrapping analysis.