## 4 Research Methodology
### Data Analysis  
In descriptive statistics, the categorical data was examined, in which we evaluated online games' users. Hence, Table 2 presents the users, i.e., age group from 16 to 20 years old, and people who are more involved in online games, in which 132 total respondents are involved in this category, where 102 were male, and 30 were female. Similarly, in another category, of 21 to 25 years old, the total of respondents was 90, in which there were 48 males and 42 females. Next, in the 26 to 30 age group, the total was 54, with 37 males and 17 females. At last, in the age group of 31 to 35 year old people, the total number was 28, in which 20 were male, and 8 were female. Therefore, the total number of respondents was 304, in which 207 were male, and 97 were female. In Figure 3, the percentage of males and females who participated is represented.  
Next, to evaluate and validate the originality of data, the first method was implemented to conduct data standardization. In this process, we measured the average (Avg) and standard deviation (SD) of all latent variables result and the average for each item; Table 3 displays the results in that the average of all factors is above 5; therefore, these assumptive constructs are standard. In addition to the analysis, the Cronbach's alpha value was demonstrated to determine the internal consistency and convergent validity of the latent variables mentioned below in Table 3, also represented graphically in Figure 4.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Age Group** & **Male** & **Female** & **Total** \\ \hline
16–20 & 102 & 30 & 132 \\
21–25 & 48 & 42 & 90 \\
26–30 & 37 & 17 & 54 \\
31–35 & 20 & 8 & 28 \\
**Total** & **207** & **97** & **304** \\ \hline \hline \end{tabular}
\end{table}
Table 2: Descriptive analysis.  
Figure 3: Piechart representation for males and females of different ages involved in percentage.  
In addition to reliability and validity of data, the discriminant validity measurement is very important for symmetric construct valuation. It is shown by evidence of systemic indicators which, logically, should not be very closely related or, in fact, not be proven to be strongly correlated. However, the values of all constructs and their level of correlation and symmetry are mentioned in Table 4. Therefore, the values were found to be appropriate in study.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**S.No** & **Latent Variables** & **Items** & **Avg** & **SD** & **Avg** & **Cronbach** \\ \hline \multirow{4}{*}{1} & \multirow{4}{*}{Use Context} & UC1 & 6.13 & 0.844 & \multirow{4}{*}{5.73} & \multirow{4}{*}{0.798} \\  & & UC2 & 6.05 & 0.951 & & \\  & & UC3 & 5.01 & 0.956 & & \\  & & SI1 & 5.89 & 0.934 & & \\
2 & \multirow{2}{*}{Social Interaction} & SI2 & 5.68 & 1.08 & 5.76 & 0.788 \\  & & SI3 & 5.72 & 1.076 & & \\  & & PEU1 & 5.83 & 0.766 & & \\
3 & \multirow{2}{*}{Perceived ease of use} & PEU2 & 6.06 & 0.778 & 5.94 & 0.871 \\  & & PU1 & 5.37 & 1.32 & & \\
4 & \multirow{2}{*}{Perceived usefulness} & PU2 & 5.42 & 1.143 & 5.35 & 0.719 \\  & & PU3 & 5.27 & 1.312 & & \\  & & PE1 & 5.77 & 0.988 & & \\
5 & \multirow{2}{*}{Perceived enjoyment} & PE2 & 5.87 & 0.910 & 5.87 & 0.748 \\  & & PE3 & 5.90 & 0.967 & & \\  & & ATT1 & 5.88 & 0.957 & & \\
6 & \multirow{2}{*}{Attitude} & ATT2 & 5.86 & 0.928 & 5.87 & 0.787 \\  & & ATT3 & 5.87 & 0.938 & & \\  & & FL1 & 5.31 & 1.256 & & \\
7 & \multirow{2}{*}{Flow} & FL2 & 5.6 & 1.045 & 5.47 & 0.729 \\  & & FL3 & 5.52 & 1.158 & & \\  & & BI1 & 5.89 & 0.96 & & \\
8 & \multirow{2}{*}{Behavior intention} & BI2 & 6.13 & 0.96 & 5.97 & 0.737 \\  & & BI3 & 5.90 & 1.10 & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Data validation assessment.  
Figure 4: Graphical representation of Cronbach’s alpha value.