## 3 Research Methodology and Empirical Analysis
### Structural Equation Modeling and Hypothesis Validation  
Exploratory factor analysis (EFA) was conducted on the final valid data to assess construct validity. Using JAMOVI 2.3.21, principal components extraction with varimax rotation was performed. Components with eigenvalues greater than 1.0 were retained based on the scree test and [PERSON]'s criterion. Item loadings exceeded the minimum threshold of 0.55, a level deemed suitable for principal component analysis [59]. Reliability was evaluated using [PERSON]'s \(\alpha\). The EFA extracted the following six factors: three trust impact factors, two reliance behavior outcomes, and one trust factor comprising marker variables. The initial scale data for SEM analysis excluded Automation Capability Redundancy Q1 due to its low factor loading (0.353). All other items exhibited ideal factor loadings, as shown in Table 4. The Kaiser-Meyer-Olkin Test for sampling adequacy was 0.80, [PERSON]'s test of sphericity was significant (\(p\) < 0.001), and the six factors accounted for 76.9% of the total variance, supporting the continuation of structural equation modeling analysis. The measurement model fitted the data well, as shown in Table 5. The results of the measurement model and the reliability of each construct are presented in Table 5. All factoring loading values were significantly greater than 0.55, and all AVE were over 0.50, indicating that convergent validity was adequately achieved [60]. \begin{table}
\begin{tabular}{c c c c c c c} \hline  & **Age** & **Years of Service** & \multicolumn{3}{c}{**Years of Experience**} & \\  & **Age** & **Years of Service** & \multicolumn{3}{c}{**in Dispatching**} & **Educational Background** \\ \hline
24–33: & 99 (46.3\%) & 1–10: & 84 (39.3\%) & 1–9: & 150 (70.1\%) & Bachelor’s Degree: & 189 (88.3\%) \\
34–43: & 102 (47.7\%) & 11–20: & 100 (46.7\%) & 10–19: & 57 (26.6\%) & Associate Degree: & 17 (7.9\%) \\
44–53: & 11 (5.1\%) & 21–30: & 27 (12.6\%) & 20–29: & 4 (1.9\%) & Graduate Degree: & 8 (3.7\%) \\
54–63: & 2 (0.9\%) & 31–40: & 3 (1.4\%) & 30–39: & 3 (1.4\%) & & \\ \hline \end{tabular}
\end{table} 
Table 3: Survey participant demographics. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Descriptives**} & \multicolumn{4}{c}{**Factor Loadings**} & \\
**Item** & **Mean** & **SD** & **F1** & **F2** & **F3** & **F4** & **F5** & **F6** \\ \hline ACR Q1 (excluded due to low factor loading) & 3.701 & 1.758 & & & & & & 0.353 \\ ACR Q2 & 4.206 & 1.530 & & & & & 0.870 \\ ACR Q3 & 3.775 & 1.890 & & & & & 0.853 \\ \hline ASK Q1 & 4.713 & 1.334 & & & & 0.769 & \\ ASK Q2 & 5.112 & 1.534 & & & & 0.863 & \\ ASK Q3 & 5.037 & 1.378 & & & & 0.890 & \\ \hline TAI Q1 & 3.938 & 1.482 & & 0.785 & & & \\ TAI Q2 & 4.169 & 1.727 & & 0.932 & & & \\ TAI Q3 & 3.681 & 1.531 & & 0.851 & & & \\ \hline DTA Q1 & 3.619 & 1.693 & & & 0.844 & & \\ DTA Q2 & 3.737 & 1.523 & & & 0.897 & & \\ DTA Q3 & 3.337 & 1.533 & & & 0.820 & & \\ \hline RBR Q1 & 4.875 & 1.444 & 0.868 & & & & \\ RBR Q2 & 5.088 & 1.490 & 0.946 & & & & \\ RBR Q3 & 4.938 & 1.512 & 0.842 & & & & \\ \hline RBE Q1 & 5.675 & 1.315 & & & & 0.932 & & \\ RBE Q2 & 5.094 & 1.268 & & & & 0.805 & & \\ RBE Q3 & 5.506 & 1.274 & & & & 0.834 & & \\ \hline Explained Variance (\%) & & & 14.14 & 13.62 & 13.32 & 13.26 & 13.17 & 9.42 \\ Cumulative Explained Variance (\%) & & & 14.14 & 27.76 & 41.08 & 54.34 & 67.51 & 76.93 \\ \hline Cronbach’s \(\alpha\) & & & 0.918 & 0.910 & 0.893 & 0.898 & 0.891 & 0.860 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Final factor loadings, Cronbach’s \(\alpha\), and explained variance after excluding low-loading items (with pre-exclusion values for excluded items).