# Evaluating the Perceived Quality of Mobile Banking Applications in Croatia: An Empirical Study
## 4 Results
### Model Assessment
As shown in Table 1, this appeared to be true for all items in the measurement model of the proposed research framework, which suggests that the requirements of the first measure of discriminant validity have been met. The Cornell-Larcker criterion [68] states that the square root of the AVE of each construct should be greater than its highest correlation with any other construct in the model. Results presented in Table 3 indicate that each construct shares more variance with items that are allocated to it (bold values on the diagonal) than with remaining constructs in the model, thus confirming that the requirements of the second measure of discriminant validity are met. The Cornell-Larcker criterion is less effective when item loadings on a construct differ by a small amount [66], so [PERSON] et al. [69] proposed the Heterotrait-Monotrait ratio (HTMT) of the correlations as an alternative measure of discriminant validity. HTMT \begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Constructs** & **Cronbach’s Alpha** & **rho_A** & **rho_C** & **AVE** \\ \hline Behavioral Intention (BEH) & 0.842 & 0.852 & 0.896 & 0.684 \\ \hline Ease of Use (EASE) & 0.771 & 0.785 & 0.853 & 0.592 \\ \hline Efficiency (EFF) & 0.796 & 0.802 & 0.881 & 0.712 \\ \hline Feedback Quality (FEDQ) & 0.843 & 0.858 & 0.894 & 0.679 \\ \hline Responsiveness (RES) & 0.740 & 0.773 & 0.854 & 0.662 \\ \hline Satisfaction (SAT) & 0.867 & 0.873 & 0.910 & 0.716 \\ \hline Security of Personal Data (SEC) & 0.921 & 0.944 & 0.949 & 0.862 \\ \hline Usefulness (USE) & 0.778 & 0.807 & 0.856 & 0.598 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Convergent validity and internal consistency of constructs. \begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline  & **BEH** & **EASE** & **EFF** & **FEDQ** & **RES** & **SAT** & **SEC** & **USE** \\ \hline
**BEH** & **0.827** & & & & & & \\ \hline
**EASE** & 0.367 & **0.770** & & & & & \\ \hline
**EFF** & 0.545 & 0.647 & **0.844** & & & & \\ \hline
**FEDQ** & 0.403 & 0.504 & 0.534 & **0.824** & & & \\ \hline
**RES** & 0.410 & 0.596 & 0.460 & 0.483 & **0.814** & & \\ \hline
**SAT** & 0.634 & 0.650 & 0.596 & 0.603 & 0.684 & **0.846** & \\ \hline
**SEC** & 0.379 & 0.381 & 0.317 & 0.508 & 0.363 & 0.487 & **0.928** & \\ \hline
**USE** & 0.498 & 0.616 & 0.619 & 0.473 & 0.600 & 0.711 & 0.331 & **0.773** \\ \hline \hline \end{tabular} Note that bold values on the diagonal represent the square root of AVE of each construct.  
\end{table} 
Table 3: Fornell–Larcker criterion. represents the ratio of the mean value of all correlations of indicators that measure different constructs and the mean value of correlations of indicators that measure the same construct. If there are related constructs in the model, then values above 0.90 imply the absence of discriminant validity, while in the case of conceptually different constructs in the model, the threshold value is set to 0.85 [67]. As presented in Table 4, the HTMT of all constructs in the research framework is below the cut-off value, which indicates that the requirements of the third and last measure of discriminant validity have been met and that constructs are sufficiently different. All of the above confirms that the measurement model is quite reliable and valid. As soon as the measurement model was determined to be adequate, the appropriateness of the structural model was examined by testing collinearity, path significance, coefficient of determination, effect size, relative measure of predictive relevance, and prediction-oriented results assessment. The evaluation of the structural model includes the estimation of many regression equations which represent the relationships between constructs. If two or more constructs in the structural model capture similar concepts, they will exhibit too much collinearity, and as a result, estimated partial regression coefficients could potentially be biased. Variance Inflation Factor (VIF) is a commonly used indicator for determining if collinearity among predictor constructs in the structural model exists.