# Definition of Discrete Choice Models of EV Owners Based on Different Socio-Demographic Aspects
### Gender  
The other characteristic that the participants in the survey were asked about was their gender. The hypothesis was that participants who identify themselves with different gender could have different preferences and different valuations of attributes. Based on the responses, the participants were divided into three main groups, i.e., women, men, and others. The percentage ratio of respondents within each group is shown in Figure 2. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Estimated**} & \multicolumn{2}{c}{**All Parameters**} & \multicolumn{2}{c}{\(ASC_{1,1}\)**, \(\beta_{\text{CC}}\) Set to 0**} \\ \cline{2-5}  & **Mean Value** & **SEM** & **Mean Value** & **SEM** \\ \hline \(ASC_{1,1}\) & \(-0.0455\) & \(0.139\) & \(0\) & **-** \\ \(ASC_{1,0}\) & \(0.355\) & \(0.0967\) & \(0.362\) & \(0.0591\) \\ \hline \(ASC_{2}\) & \(0.510\) & \(0.139\) & \(0.459\) & \(0.0467\) \\ \hline \(ASC_{3}\) & \(-1.78\) & \(0.224\) & \(-1.79\) & \(0.223\) \\ \hline \(\beta_{Soc}\) & \(0.817\) & \(0.110\) & \(0.900\) & \(0.0928\) \\ \hline \(\beta_{p,1}\) & \(2.63\) & \(0.172\) & \(2.58\) & \(0.160\) \\ \(\beta_{p,0}\) & \(2.12\) & \(0.119\) & \(2.10\) & \(0.116\) \\ \hline \(\beta_{\text{CC}}\) & \(0.379\) & \(0.384\) & \(0\) & **-** \\ \hline \(\beta_{\text{BC}}\) & \(2.00\) & \(0.430\) & \(1.97\) & \(0.422\) \\ \hline \(\beta_{E}\) & \(-3.40\) & \(0.640\) & \(-3.31\) & \(0.624\) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Estimated parameters of the model with the experience characteristic. Figure 2: The percentage ratio of responses to a question about gender. The percentage of the respondents who identify themselves within the others group is very low, and so there is not enough data for the prediction model. Therefore, all estimated parameters for this group cannot be determined to have values other than zero; the general model presented in Section 2.1 or in [17] is recommended to represent this group. The percentage of respondents identifying themselves as women is also low in comparison with the men. The dissemination process of the survey could cause this low representation. A lot of Slovak automotive groups were approached, and men usually prevail in these groups in Slovakia. However, in comparison to the group labeled as others, there is enough data to represent this group within the prediction model. The model representing these two above-mentioned groups of this characteristic individually was compared with the model in (5-8) using the likelihood ratio test. The result was that this model is preferred over the model in (5-8). The t-test of the parameters showed that the null hypothesis that these parameters do not differ between the groups can be rejected for most of the parameters. There are only two parameters where this null hypothesis cannot be rejected, and they are the SoC and cost of charging attributes' parameters, which means that women and men value the SoC of their EV and the cost of charging the same way. Therefore, the most suitable model to represent data divided based on the gender characteristic was defined using the following equations:  
\[V_{1}= \left\{ \begin{array}{ll}ASC_{1,1}-\beta_{SoC}\cdot SoC+\beta_{p,1} \cdot p-\beta_{C\text{C}}\cdot C_{\text{C1}},&G=1,\\ ASC_{1,0}-\beta_{SoC}\cdot SoC+\beta_{p,0}\cdot p-\beta_{C\text{C}}\cdot C_{ \text{C1}},&G=0,\end{array} \right. \tag{13}\] \[V_{2}= \left\{ \begin{array}{ll}ASC_{2,1}-\beta_{SoC}\cdot SoC+\beta_{p,1 }\cdot p-\beta_{C\text{C}}\cdot C_{\text{C2}},&G=1,\\ ASC_{2,0}-\beta_{SoC}\cdot SoC+\beta_{p,0}\cdot p-\beta_{C\text{C}}\cdot C_{ \text{C2}},&G=0,\end{array} \right.\] (14) \[V_{3}= \left\{ \begin{array}{ll}ASC_{3,1}+\beta_{SoC}\cdot SoC-\beta_{p,1 }\cdot p+\beta_{\text{RC},1}\cdot R_{\text{c}}-\beta_{E,1}\cdot E,&G=1,\\ ASC_{3,0}+\beta_{SoC}\cdot SoC-\beta_{p,0}\cdot p+\beta_{\text{RC},0}\cdot R _{\text{c}}-\beta_{E,0}\cdot E,&G=0,\end{array} \right.\] (15) \[V_{4}= \;ASC_{4}, \tag{16}\]  
where parameter \(G\) defines if a respondent identifies herself/himself as a woman (\(G=1\)) or a man (\(G=0\)).