## 4 Results
### Evaluation of SEM Models (Structural Equations Modeling)
#### 4.3.1 Measurement Model Evaluation  
According to [PERSON] [76], evaluating a reflective measurement model involves testing internal consistency (reliability) and convergent and discriminant validity. Given that the present study intends to compare data analysis between two generations. We will analyse both results of evaluating the consistency and validity of the measurement model simultaneously. Tables 8 and 9 show, respectively, the results relating to internal consistency ([PERSON]'s Alpha and Composite Internal Consistency) and convergent validity (AVE) of the Millennial and Centennial groups. \begin{table}
\begin{tabular}{c c c c} \hline \hline Tourist products that you feel most influenced to buy: & Centennials & Millennials & Overall Total \\ Airline Tickets & & & \\ \hline No & 72.8\% & 76.1\% & 73.7\% \\ Yes & 27.2\% & 23.9\% & 26.3\% \\ \hline Tourist products that you feel most influenced to buy: & Centennials & Millennials & Overall Total \\ Holiday Packages & & & \\ \hline No & 76.3\% & 71.6\% & 75.0\% \\ Yes & 23.7\% & 28.4\% & 25.0\% \\ \hline Tourist products that you feel most influenced to & Centennials & Millennials & Overall Total \\ buy: Excursions & & & \\ \hline No & 88.8\% & 89.6\% & 89.0\% \\ Yes & 11.2\% & 10.5\% & 11.0\% \\ \hline \hline \end{tabular}
\end{table} 
Table 7: _Cont._ \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Latent Variables:** & **Cronbach’s** & **Composite** & **Composite** \\
**Millennials** & **Alpha** & **Reliability: Rho A** & **Reliability: Rho C** \\ \hline PC & 0.912 & 0.916 & 0.938 \\ SI & 0.865 & 0.892 & 0.908 \\ NI & 0.774 & 15.874 & 0.827 \\ PI & 0.865 & 0.890 & 0.917 \\ PR & 0.817 & 1.034 & 0.879 \\ UI & 0.883 & 0.886 & 0.945 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Internal Consistency and Convergent Validity (Millennials). Source: Own elaboration. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Latent Variables:** & **Cronbach’s** & **Composite** & **Composite** \\
**Centennials** & **Alpha** & **Reliability: Rho A** & **Reliability: Rho C** \\ \hline PC & 0.820 & 0.836 & 0.880 \\ SI & 0.811 & 0.824 & 0.876 \\ NI & 0.735 & 0.746 & 0.882 \\ PI & 0.833 & 0.862 & 0.899 \\ PR & 0.810 & 0.962 & 0.866 \\ UI & 0.820 & 0.823 & 0.917 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Internal Consistency and Convergent Validity (Centennials). Source: Own elaboration. According to [PERSON] et al. [77], the first criterion to be evaluated in a reflective measurement model is internal consistency and can be tested using [PERSON]'s Alpha criterion, whose reference value must be greater than 0.6 to be considered acceptable and greater than 0.7 desirably [78]. Alternatively, it can be tested using the composite internal consistency criterion (Rho A and Rho C), whose acceptable value is 0.7 and desirable value is 0.9 [77]. In the context of this study, we chose to test the constructions using both criteria. By observing Table 8 (Millennials) and Table 9 (Centennials), it is possible to confirm that. The Cronbach Alpha measurement criterion, as the composite internal consistency criterion, is acceptable for both generations under study since they present values greater than 0.6 and 0.7, respectively. To assess convergent validity, the AVE (Average Variance Extracted) measurement criterion is used, which, according to [PERSON] et al. [78], must be greater than or equal to 0.5 to be considered sufficient. When it is, it means that the latent variable explains, on average, more than half of the variance of its indicators. All variables pass the convergent validity test given that all values are greater than 0.5, as shown in Table 8 (Millennials) and Table 9 (Centennials), being therefore in accordance with the evaluated metric reference values (AVE > 0.5). According to [PERSON] [76] (p. 48), the purpose associated with the discriminant validity test \"is that, if two theoretical concepts are different, then the indicators that measure them must be sufficiently distinct\".