## 6 Discussion
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Variables** & **Importance** & **Normalized Importance** \\ \hline
**TMS** & 0.077 & 39.50\% \\ \hline
**CX** & 0.11 & 56.20\% \\ \hline
**CT** & 0.129 & 66.00\% \\ \hline
**CS** & 0.13 & 66.40\% \\ \hline
**TR** & 0.196 & 100.00\% \\ \hline
**CP** & 0.171 & 87.30\% \\ \hline
**SC** & 0.188 & 96.00\% \\ \hline \hline \end{tabular} Note: Compatibility (CT); Competitive pressure (CP); Complexity (CX); Cost saving (CS); Technology readiness (TR); Top manager’s support (TMS); Security (SC).  
\end{table} 
Table 9: Normalized importance of variables. According to this research, cost savings is the reduced capital investment required in an institution for IT service in terms of leased resources and hardware solutions [136]. The stipulation of hypothesis H5 is that vendor support has a positive impact on the adoption of CC in HEIs. According to [142; 143], vendors or IT service providers are important in deciding the adoption of IT services. As shown in the results of this study, there is no significant impact of vendor support on CC adoption in HEIs, because \(\beta\), \(t\)-value, and \(p\)-value of the result are 0.112, 1.447 respectively, which is not significant as \(p>0.05\). Hence, H5 significance was unconfirmed, and the output of vendor support was insignificant, which might be due to the indicators utilized in measuring this factor being feeble. Accordingly, the study output is suggesting that further studies need to focus on the selection of powerful indicators of this construct. The output of this measurement model shows a positive influence of technology readiness on CC adoption. The \(\beta\), \(t\)-value, and \(p\)-value of the result is 0.285, 4.888, respectively, which is significant at the level of \(p<0.01\). These values demonstrate support for this hypothesis. Besides, the ANN output revealed that the variable \"technology readiness\" is the second crucial factor in the prediction of the CC adoption in HEIs. Therefore, the adoption of CC is significantly affected by technology readiness. The result corroborates what was observed in past studies [18; 33; 39; 84; 147]. According to this research, technology readiness secures the internal technical resources of an organization [112]. Before the adoption of CC technology, the readiness of the institution needs to be determined. That is, HEIs must facilitate the readiness of CC technology so that the internet bandwidth needs to be adequate for student and teacher cloud accessibility. The output of this measurement model shows a positive influence of top management support on CC adoption (H7). The \(\beta\), \(t\)-value, and \(p\)-value of the result are 0.129, 1.978 respectively, which is significant at the level of \(p<0.05\). These values demonstrate support for this hypothesis. Hence, the adoption of CC is significantly affected by top management support. This result is in line with the findings of past studies [81; 82; 83; 84; 102; 103; 106; 108; 109; 110; 160; 161; 168]. According to this research, the attitude of top management is important in terms of the technology involved and the degree of support provided for the adoption [18]. The knowledge and agreement of decision-makers are crucial. When they provide the necessary support, it will facilitate the needs of cloud services and the appropriate cloud deployment for HEIs settings. Hypothesis H8 stipulates that security possesses a negative impact on the adoption of CC in HEIs. According to [37; 31], security in CC is still the most remarkable challenge in adopting CC services. Security is a critical technical problem when it comes to adopting CC. Cloud vendors are making attempts towards the simulation of the typical principles of confidentiality, availability, and integrity usually within physical systems for distributed, virtualized, and dynamic cloud systems that users access online [150].