## 4 Discussion  
The purpose of this study was to investigate whether the perceived color of a car's exterior could influence the perceived quality (PQ) of its interior. To this end, we exploited immersive virtual reality (IVR) simulations of an unbranded car by integrating eye-tracking technology and explicit PQ subjective measures. As regards the eye-tracking data, partially in line with our hypotheses, the results showed that attentional processes towards color aesthetic features of car interiors can be different after visually exploring its exteriors. Indeed, with respect to all other conditions, when the white and red exteriors were combined with gray and black interiors, the fixation duration was longer for the gray than the black color. As we expected, the color combinations with red received more attention presumably because they were less familiar (or unexpected). This result would seem to be consistent with attentional processing perspectives on shifting attention from a familiar (or known) to an unfamiliar (or unexpected) visual target [45; 46; 47]. However, participants also showed the same eye-tracking patterns with color combinations that should be considered more familiar (i.e., color combinations with white). Presumably this could depend on subjective color preferences (i.e. what people like or dislike) [5]. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline  & **B** & **St. Err** & **Beta (\(\beta\))** & **t** & \(p\)** \\ \hline
**RR-uncomfortable** & \(-\)0.26 & 0.12 & \(-\)0.64 & \(-\)2.15 & 0.04 \\
**RR-unpleasant** & 0.11 & 0.10 & 0.36 & 1.21 & 0.24 \\
**RR-banal** & 0.11 & 0.10 & 0.22 & 1.19 & 0.24 \\ \hline \hline \end{tabular}
\end{table} 
Table 10: The table shows the effect of subjective PQ evaluations on fixation duration when participants visually explored the red interior after seeing the red car exterior. Unstandardized (B) and standardized (Beta) coefficients, standard error, t values, and significance levels are reported. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline  & **B** & **St. Err** & **Beta (\(\beta\))** & **t** & \(p\)** \\ \hline
**RG-uncomfortable** & 0.36 & 0.14 & 0.69 & 1.69 & 0.02 \\
**RG-relaxing** & 0.24 & 0.13 & 0.40 & 1.74 & 0.09 \\
**RG-poor quality** & \(-\)0.21 & 0.12 & \(-\)0.37 & \(-\)1.69 & 0.10 \\ \hline \hline \end{tabular}
\end{table} 
Table 11: The table shows the effect of subjective PQ evaluations on fixation duration when participants visually explored the gray interior after seeing the red car exterior. Unstandardized (B) and standardized (Beta) coefficients, standard error, t values, and significance levels are reported. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline  & **B** & **St. Err** & **Beta (\(\beta\))** & **t** & \(p\)** \\ \hline
**GB-disturbing** & 0.63 & 0.15 & 0.85 & 4.08 & 0.0003 \\
**GB-banal** & 0.20 & 0.09 & 0.31 & 2.25 & 0.03 \\
**GB-relaxing** & 0.20 & 0.11 & 0.33 & 1.79 & 0.08 \\
**GB-poor quality** & \(-\)0.22 & 0.15 & \(-\)0.26 & \(-\)1.47 & 0.15 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: The table shows the effect of subjective PQ evaluations on fixation duration when participants visually explored the black interior after seeing the gray car exterior. Unstandardized (B) and standardized (Beta) coefficients, standard error, t values, and significance levels are reported. As regards the subjective PQ evaluations, the regression analysis showed that individual preferences for color combinations have a role in allocating attentional resources to the vehicle. Indeed, as the negative evaluations for car appearance increased, the fixation duration on car interiors also increased.