## 4 Methodology
### Sampling and Data Collection  
Quantitative studies can utilize probability as well as non-probability sampling approaches. However, the non-probability sampling approach is mainly used for qualitative studies [174]. Generalizing the results driven from a small group of people to large groups is the key advantage of the quantitative research method. [175]. [PERSON] [174] declared that \"in purposive sampling researcher purposely selects the elements because they satisfy specific inclusion and exclusion criteria for participation in the study.\" Purposive sampling is suitable for the initial phases of study where subjects have not much experience with a particular event under investigation [176]. Therefore, this study adopted a purposive sampling approach, and the target population of the study is the individuals who are related to the decision of adopting CC services in the institution (e.g., ICT directors, administrators, information technology officers, etc.) and can provide recommendations regarding the adoption of CC services. The summary of the respondent's characteristics in Table 2 shows that most of the respondents have advance or expert level in computer literature (i.e., 57.46% and 35.07% respectively) and 1-5 years or 6-10 years of experience in the field (i.e., 81.34% and 15.67% respectively). Face validity, content validity, and a pilot study were performed to ensure the validity and reliability of the questionnaire. For most scholars, a pilot study sample size of 20-40 is reasonable [177, 178, 179, 180, 181, 182]. In this regard, our pilot study's reliability statistic was based on 30 online completed questionnaires. Structural equation modeling (SEM) was applied to the pilot data with SmartPLS 3.0 [116]. The results of a pilot study, conducted through a survey with ICT decision-makers, and based on the proposed conceptual model, indicate that the instrument is both reliable and valid, and so point the way towards further research. It is worth drawing attention to the fact that the questions were adapted from prior empirical literature that had been validated by previous researchers (see Appendix A). Data were collected online from May to July 2019. After three months, a total of 148 responses to the survey questionnaire were received by researchers. After data screening, some questionnaires with a missing value were excluded, and a total of 134 responses were found valid for the analysis. The demographic information of the respondents is presented in Table 4.  
\begin{table}
\begin{tabular}{l c c} \hline \hline \multicolumn{3}{c}{**Respondents Information**} \\ \hline  & **Frequency** & **Percentage** \\ \hline
**Computer literacy level** & & \\ Beginner & 1 & 0.75\% \\ Intermediate & 9 & 6.72\% \\ Advanced & 77 & 57.46\% \\ Expert & 47 & 35.07\% \\ \hline
**Experience** & & \\
1–5 years & 109 & 81.34\% \\
6–10 years & 21 & 15.67\% \\
11–15 years & 4 & 2.99\% \\ More than 15 years & 0 & 0 \\ \hline
**Job title** & & \\ Administrator & 19 & 14.17\% \\ Lecturer & 13 & 9.70\% \\ Teaching staff & 3 & 2.38\% \\ ICT director & 26 & 19.40\% \\ Chief information officer & 11 & 8.21\% \\ IT specialist & 4 & 2.98\% \\ Business analyst & 2 & 1.49\% \\ Researcher & 53 & 39.55\% \\ Associate professor & 3 & 2.23\% \\ \hline \hline \end{tabular}
\end{table}
Table 4: Characteristics of the respondents.