## 4 Results  
To begin with, in order to validate the factorial structure of the model, a factor loadings analysis of the items was conducted, ensuring that all loadings were close to 0.7 [32], which guarantees adequate convergent validity (Table 3). \begin{table}
\begin{tabular}{c c c} \hline
**Dimension** & **Mean** & **SD** \\ \hline Performance Expectancy (PE) & 5.81 & 1.303 \\ Effort Expectancy (EE) & 6.13 & 1.160 \\ Social Influence (SI) & 4.33 & 1.933 \\ Facilitating Conditions (FC) & 6.21 & 1.059 \\ Behavioral Intention (BI) & 5.41 & 1.651 \\ Usage Behavior (UB) & 4.46 & 1.688 \\ \hline \end{tabular}
\end{table} 
Table 2: Mean scores and standard deviations. \begin{table}
\begin{tabular}{c c c c c c} \hline
**BI** & **EE** & **FC** & **PE** & **SI** & **UB** \\ \hline BI1 & 0.858 & & & & \\ BI2 & 0.939 & & & & \\ BI3 & 0.954 & 0.847 & & & \\ EE1 & 0.885 & & & & \\ EE3 & 0.868 & & & & \\ EE4 & 0.835 & & & & \\ FC1 & & 0.879 & & & \\ FC2 & & 0.893 & & & \\ FC3 & & 0.650 & & & \\ FC4 & & 0.693 & 0.895 & & \\ PE1 & & & 0.857 & & \\ PE3 & & & 0.825 & & \\ PE4 & & & 0.839 & & \\ SI1 & & & & 0.904 & \\ SI2 & & & & 0.964 & \\ SI3 & & & & 0.941 & \\ UB & & & & 1.000 \\ \hline \end{tabular}
\end{table} 
Table 3: Factor loadings. The results confirm adequate convergent validity of the measurement model, as most items exhibit factor loadings above 0.7, indicating that each item significantly contributes to its respective construct. For behavioral intention (BI), the factor loadings range between 0.858 and 0.954, reflecting a strong correlation between the items and the construct. Perceived ease of use (EE) also shows high values, with loadings between 0.835 and 0.885. Regarding facilitating conditions (FC), three of its items show adequate values (FC1 and FC2 above 0.87), although FC3 (0.650) and FC4 (0.693) exhibit slightly lower loadings, which might suggest a weaker contribution of these items to the construct. Performance expectancy (PE) presents factor loadings ranging from 0.825 to 0.895, while social influence (SI) displays particularly high values, with loadings above 0.90 for all its items. Finally, actual use (UB) has a value of 1.000, indicating that it is measured with a single item. After confirming that the factor loadings met the recommended threshold, we proceeded to evaluate the internal consistency of the constructs to ensure the reliability of the measurement model. Internal consistency was assessed using [PERSON]'s alpha, composite reliability (CR), and average variance extracted (AVE). The results are presented in Table 4.  
The results confirm the adequate internal consistency of the model's constructs [33]. First, all [PERSON]'s alpha values exceed the recommended threshold of 0.7, indicating high internal reliability of the items within each construct. In particular, the social influence (SI) construct shows the highest value (0.930), followed by behavioral intention (BI) with 0.906, reflecting strong coherence among its items. The composite reliability (CR) also reaches satisfactory values in all cases, exceeding the 0.7 threshold and approaching or surpassing 0.9 in several constructs, reinforcing the robustness of the model. Finally, the AVE (average variance extracted), which measures the amount of variance explained by the items relative to the error, presents values above the minimum criterion of 0.5, except for facilitating conditions (FC), which shows a value of 0.618--slightly lower than the others but still within acceptable ranges. After establishing internal consistency, we assessed discriminant validity using the Cornell-Larcker criterion (Table 5). According to this criterion, a construct should share more variance with its own indicators than with other constructs in the model. This is confirmed when the square root of the AVE for each construct (values on the diagonal) is greater than the correlations between constructs (values outside the diagonal).