# Buy and/or Pay Disparity: Evidence from Fully Autonomous Vehicles
## 3 Methodology
### Empirical Strategy
#### 3.2.1 Identifying Latent Constructs  
We first identified the latent variables that can be related to WTB and PV for FAV based on the process used by previous studies (e.g., [85]), as shown in Table 3. We chose four categories: fear (fear of FAV technology), merits (advantages and benefits of FAV technology), pollution (concerns about pollution), and nature (concerns about conserving natural environments) as the latent variables. We conducted an extensive literature review and factor analysis to sufficiently validate our latent variable construction process. To do so, we focused on the merits of FAVs and focus on the disadvantages that FAVs would possibly bring. First, the latent variables and statements (questions) for each survey were based, whenever possible, on statements previously used and found to be effective in the literature. Second, we constructed the latent variables according to our research hypothesis, exploratory factor analysis (EFA) and previous works. First, using EFA, we explored the latent variables that represent the respondents' awareness and attitudes toward issues related to FAV and the natural environment--as a rotation method, we adopted the promax method, one of the oblique rotations, to assume that latent variables can be correlated with each other. In previous studies, orthogonal rotation methods are frequently used for setting no correlation between latents. However, it is debated that the uncorrelation assumption is unrealistic: in social science, attitudes and perceptions tend to be mutually related [86]. From the EFA, we obtained four latent variables: fear, merits, pollutions, and nature. These latent variables were derived from the indicator variables shown in Table 3. Cronbach's alpha values of merit, fear, pollution, and nature were 0.559, 0.734, 0.953, and 0.914, respectively. Cronbach's alpha is regarded as a measure of scale reliability, whose acceptable range is >0.6. Only merit did not satisfy this condition, but its Cronbach's alpha value was not too far from 0.6 [87]. The correlation between indicator variables is shown in Tables A3-A6 in Appendix A. Next, using the relationship between latent and indicator variables obtained from the EFA, we conducted a confirmatory factor analysis (CFA) to estimate the coefficient of latents on indicators, and calculate the score of each latent variable. In the CFA process, we can assume the correlations between error terms of indicator variables. Suppose that one latent construct is measured by five indicator variables. The error terms of the indicator variables are calculated as their unique variance that is not related to the latent construct. If two specific indicator variables are similar compared to the other three, the two share common variances that are not captured by the latent. In such a situation, setting a correlation between the error terms of those two indicators can explain such a similarity and improve the overall model fit. We decided which error terms should be correlated with each other according to the goodness-of-fit indices and the strength of the correlations between indicator variables. Finally, we included the four latent variables obtained by the EFA and CFA processes in our SEM model. These latent variables were used as the exploratory variables for purchasing decisions and PV for FAV. In addition, we included gender, individual income, age, and commute time as the control variables for purchasing decisions and PV for FAV because these individual characteristics may affect purchasing intention and PV as well as latent awareness and attitudes. The first latent construct, fear, represents an individual's concerns toward possible accidents, malfunctions, or responsibility issues (i.e., who would be responsible when there is an accident) toward FAVs. Numerous works and experts argue that FAVs will eliminate human errors, therefore creating safer traffic environments. Nevertheless, many members of the public are concerned about potential problems.