# Assessing the Effect of Drivers' Gender on Their Intention to Use Fully Automated Vehicles
## 3 Results
### Structural Analyses
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Variable**} & \multirow{2}{*}{**Group**} & \multicolumn{2}{c}{**Descriptives**} & \multicolumn{4}{c}{**Brown–Forsythe Test**} \\ \cline{3-8}  & & **Mean** & **SD** & **Statistic \({}^{\text{a}}\)** & **df1 \({}^{\text{b}}\)** & **df2 \({}^{\text{c}}\)** & **Sig.** \\ \hline \multirow{2}{*}{Interaction with ITCs} & Males & 2.75 & 0.94 & 4.921 & 1 & 847.620 & \textless{}0.001 *** \\  & Females & 2.90 & 1.01 & & 3.259 & 1 & 653.656 & 0.072 N\({}^{\text{/S}}\) \\ \hline \multirow{2}{*}{Greater connectivity} & Males & 3.11 & 2.00 & \multirow{2}{*}{3.259} & \multirow{2}{*}{1} & \multirow{2}{*}{653.961} & \multirow{2}{*}{0.192 N\({}^{\text{/S}}\)} \\  & Females & 3.39 & 1.96 & & & & \\ \hline \multirow{2}{*}{Reduced driving demands} & Males & 1.81 & 1.61 & \multirow{2}{*}{1.705} & \multirow{2}{*}{1} & \multirow{2}{*}{653.961} & \multirow{2}{*}{0.192 N\({}^{\text{/S}}\)} \\  & Females & 1.98 & 1.73 & & & & \\ \hline \multirow{2}{*}{Fuel/energy consumption saving} & Males & 3.52 & 1.02 & \multirow{2}{*}{9.785} & \multirow{2}{*}{1} & \multirow{2}{*}{853.793} & \multirow{2}{*}{0.008 \({}^{\text{*}}\)} \\  & Females & 3.30 & 0.98 & & & & \\ \hline \multirow{2}{*}{Travel efficiency} & Males & 3.44 & 0.95 & \multirow{2}{*}{23.882} & \multirow{2}{*}{1} & \multirow{2}{*}{853.707} & \textless{}0.001 *** \\  & Females & 3.13 & 0.91 & & & & \\ \hline \multirow{2}{*}{Increased safety} & Males & 2.73 & 0.70 & \multirow{2}{*}{21.911} & \multirow{2}{*}{1} & \multirow{2}{*}{850.655} & \textless{}0.001 *** \\  & Females & 2.52 & 0.64 & & & & \\ \hline \multirow{2}{*}{Intention to use} & Males & 2.86 & 0.60 & \multirow{2}{*}{6.413} & \multirow{2}{*}{1} & \multirow{2}{*}{852.986} & \multirow{2}{*}{0.035 \({}^{\text{*}}\)} \\  & Females & 2.76 & 0.61 & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Descriptive statistics and mean comparisons by driver’s gender. The Standardized Path Coefficients (SPCs) and their significance values (see solid lines in Figure 2 and the right column of Table 4) in the bias-corrected MGSEM suggest that there exist both structural similarities and differences, as follows:  
In regard to structural similarities, the MGSEM results show only two akin path relationships between male and female drivers, namely: (i) drivers' valuation of trip efficiency, and (ii) safety improvements of automated vehicles significantly predict their intention to use them. On the other hand, and as for structural differences, it was found that: (i) drivers' degree of interaction with Information and Communication Technologies (ITCs) are a significant predictor of intention among males, but it remains non-significant for the case of female drivers; (ii) unlike the case of females, a greater connectivity seems to significantly decrease the self-reported intention among male drivers; (iii) reduction of driving demands is a significant predictor only among female drivers, and (iv) fuel/energy consumption saving significantly increases intention to use AVs only among male drivers.