# Definition of Discrete Choice Models of EV Owners Based on Different Socio-Demographic Aspects
### Residence  
The last characteristic that the survey participants were asked about was their residence within the Regions of Slovakia. Since there is a difference between the regions in Slovakia, especially in the standard of living, authors have assumed that it can affect the EVs charging decision making. There are eight regions in Slovakia (namely Banskobystricky, Bratislavsky, Kosicky, Nitriansky, Presovsky, Trenciansky, Trnavsky, and Zilinsky). The percentage ratio of the respondents that live in each of the regions is shown in Figure 6a. However, most of the regions are underrepresented in the sample. This underrepresentation results in a high SEM of parameters in most of the regions. Therefore, the authors have decided to divide the respondents based on the area of Slovakia, where they reside. The specific regions are situated in the specific area of Slovakia, i.e., Bratislavky, Nitriansky, Trenciansky, and Trnavsky Regions are placed in West Slovakia; Zilinsky and Banskobystricky Regions are in Center Slovakia, and Kosicky and Presovsky Regions are in East Slovakia. Based on these assumptions, the respondents were divided into these three groups. The percentage ratio of the respondents that resides in these areas is presented in Figure 6b. The model representing these three groups of the residence 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 parameters' \(t\)-tests showed that  
Figure 6: The percentage ratio of responses to a question about the place in which respondents live within Slovakia. (**a**) Distribution over the regions of Slovakia. (**b**) Distribution over the area of Slovakia. the null hypothesis that these parameters do not differ between the groups cannot be rejected for most of the parameters. The parameters that are the same across all groups are the alternative specific constant of the fast charging alternative and the parameters of the reward for 1 kWh of sold energy, the amount of required energy, and the cost of charging attributes. This means that regardless of respondents' residence, they value the requirement for the amount of energy to sell from their EV and their price or gain for the charging/discharging the same. Therefore, the resulting and most suitable model to represent data divided based on the age characteristic was defined using the following equations:  
\[V_{1}=\ \left\{ \begin{array}{ll}ASC_{1,0}-\beta_{SoC,0}\cdot SoC+\beta_{p,0} \cdot p-\beta_{CC}\cdot C_{C1},&R=0,\\ ASC_{1,1}-\beta_{SoC,1}\cdot SoC+\beta_{p,1}\cdot p-\beta_{CC}\cdot C_{C1},&R=1, \\ ASC_{1,2}-\beta_{SoC,0}\cdot SoC+\beta_{p,1}\cdot p-\beta_{CC}\cdot C_{C1},&R=2, \end{array} \right. \tag{25}\]  
\[V_{2}=\ \left\{ \begin{array}{ll}ASC_{2}-\beta_{SoC,0}\cdot SoC+\beta_{p,0} \cdot p-\beta_{CC}\cdot C_{C2},&R=0,\\ ASC_{2}-\beta_{SoC,1}\cdot SoC+\beta_{p,1}\cdot p-\beta_{CC}\cdot C_{C2},&R=1, \\ ASC_{2}-\beta_{SoC,0}\cdot SoC+\beta_{p,1}\cdot p-\beta_{CC}\cdot C_{C2},&R=2, \end{array} \right. \tag{26}\]  
\[V_{3}=\ \left\{ \begin{array}{ll}ASC_{3,0}+\beta_{SoC,0}\cdot SoC-\beta_{p,0} \cdot p+\beta_{R\in\mathcal{O}}\cdot R_{\mathsf{C}}-\beta_{E}\cdot E,&R=0,\\ ASC_{3,1}+\beta_{SoC,1}\cdot SoC-\beta_{p,1}\cdot p+\beta_{R\in\mathcal{O}} \cdot R_{\mathsf{C}}-\beta_{E}\cdot E,&R=1,\\ ASC_{3,2}+\beta_{SoC,0}\cdot SoC-\beta_{p,1}\cdot p+\beta_{R\in\mathcal{O}} \cdot R_{\mathsf{C}}-\beta_{E}\cdot E,&R=2,\end{array} \right. \tag{27}\]  
\[V_{4}=\ ASC_{4}, \tag{28}\]  
where parameter \(R\) defines if a respondent belongs to the group of respondents with the area of residence in West Slovakia (\(R=0\)), Central Slovakia (\(R=1\)), or East Slovakia (\(R=2\)). The parameters of the attributes that are different between the groups are distinguished in the subscript with symbols '0', '1', or '2' in case of a respondent with residence in West Slovakia, Central Slovakia, or East Slovakia, respectively.