# Continuance Use of Cloud Computing in Higher Education Institutions: A Conceptual Model
## 6 Preliminary Results
### Reflective Measurement Model Evaluation  
Assessment of the reflective measurement model involved taking an estimate of internal consistency, along with convergent and discriminant validity (see Table 6). The reliability of the instrument was acceptable, with reflective factor loadings in excess of 0.505 (i.e., greater than the recommended level of 0.5) [209]. CR was also acceptable, where every construct's value was greater than 0.852 [238].  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Construct** & **No. Items** & **Min Inter-Item Correlation** & **Max Inter-Item Correlation** & **Cronbach’s Alpha** \\ \hline CC Continuance Use & 3 & 0.656 & 0.828 & 0.907 \\ \hline Satisfaction & 4 & 0.684 & 0.81 & 0.916 \\ \hline Confirmation & 5 & 0.124 & 0.795 & 0.78 \\ \hline Net Benefit & 13 & - & - & 0.916 \\ \hline Technical Integration & 3 & 0.711 & 0.788 & 0.891 \\ \hline System Quality & 13 & - & - & 0.927 \\ \hline Information Quality & 7 & - & - & 0.928 \\ \hline System Investment & 3 & 0.67 & 0.731 & 0.836 \\ \hline Collaboration & 5 & 0.504 & 0.742 & 0.899 \\ \hline Regulatory Policy & 5 & 0.398 & 0.821 & 0.894 \\ \hline Competitive Pressure & 4 & 0.577 & 0.772 & 0.86 \\ \hline
**All Items** & **65** & & **0.862** & **0.913** \\ \hline \hline \end{tabular}
\end{table}
Table 5: Reliability Statistics.  
In the case of convergent validity, this was computed as the average variance extracted (AVE) for every construct, and it was greater than 0.5 in each case ([PERSON] et al., 2018). Every square root for the AVEs was greater than the corresponding latent variable correlation, thereby indicating a satisfactory level of discriminant validity (see Table 7).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Cloud Computing Confluance Use (Reflective)** & **Loadings 1** & **AVE 2** & **CR 3** \\ \hline CCCU1 & 0.896 & 0.845 & 0.942 \\ CCCU2 & 0.961 & & \\ CCCU3 & 0.898 & & \\ \hline Confirmation (Reflective) & Loadings & AVE & CR \\ \hline CON1 & 0.505 & 0.544 & 0.852 \\ CON2 & 0.622 & & \\ CON3 & 0.876 & & \\ CON4 & 0.786 & & \\ CON5 & 0.832 & & \\ \hline Satisfaction (Reflective) & Loadings & AVE & CR \\ \hline SAT1 & 0.872 & 0.798 & 0.941 \\ SAT2 & 0.887 & & \\ SAT3 & 0.917 & & \\ SAT4 & 0.897 & & \\ \hline Technical Integration (Reflective) & Loadings & AVE & CR \\ \hline TE1 & 0.923 & 0.824 & 0.934 \\ TE2 & 0.876 & & \\ TE3 & 0.924 & & \\ \hline System Investment (Reflective) & Loadings & AVE & CR \\ \hline SI1 & 0.91 & 0.799 & 0.923 \\ SI2 & 0.871 & & \\ SI3 & 0.901 & & \\ \hline Collaboration (Reflective) & Loadings & AVE & CR \\ \hline COL1 & 0.88 & 0.716 & 0.926 \\ COL2 & 0.775 & & \\ COL3 & 0.835 & & \\ COL4 & 0.867 & & \\ COL5 & 0.87 & & \\ \hline Regulatory Policy (Reflective) & Loadings & AVE & CR \\ \hline RP1 & 0.809 & 0.697 & 0.92 \\ RP2 & 0.84 & & \\ RP3 & 0.859 & & \\ RP4 & 0.853 & & \\ RP5 & 0.812 & & \\ \hline Competitive Pressure (Reflective) & Loadings & AVE & CR \\ \hline CP1 & 0.776 & 0.748 & 0.922 \\ CP2 & 0.904 & & \\ CP3 & 0.878 & & \\ CP4 & 0.895 & & \\ \hline \end{tabular} \({}^{1}\) All Item Loading \(>\) 0.5 Indicates Indicator Reliability; 2 All Average Variance Expected (AVE) \(>\) 0.5 as indicates Convergent Reliability; 3 All Composite Reliability \(>\) 0.7 Indicates Internal Consistency.  
\end{table}
Table 6: Quantitative Assessment of Measurement Model (Reflective).