## 3 Results
### Regression Analysis  
Only significant results were reported. White exterior/black interior color combinations. The results showed that the model with the dimension \"poor quality\" was significant (F(1,32) = 6.94, \(p\) < 0.05, R = 0.42, R\({}^{2}\) = 0.18). As shown in Table 5, as the negative PQ evaluation increased, the fixation duration for the black interior also increased. Black exterior/black interior color combinations. The model with four predictors was significant (F(4,29) = 3.49, \(p\) < 0.05, R = 0.57, R\({}^{2}\) = 0.32); however, only the dimension \"disturbing\" significantly contributed to the model. As shown in Table 6, as the negative PQ evaluation increased, the fixation duration for the black interior also increased. \begin{table}
\begin{tabular}{l c c c c c} \hline  & **F** & **Num df** & **Den df** & \(p\) & **ICC** \\ \hline
**COND** & 2.514 & 4 & 128.0 & 0.045 & 0.25 * \\
**GENDER** & 0.121 & 1 & 32.0 & 0.730 & \\
**COND*** & 0.758 & 4 & 128.0 & 0.554 & \\
**GENDER** & & & & & \\ \hline \end{tabular}  
* ICC for random intercept for subjects. Satterthwaite method for degrees of freedom.  
\end{table} 
Table 4: Mixed model analysis for red exterior and interior color combinations (white, black, gray, and red). \begin{table}
\begin{tabular}{l c c c c c} \hline  & **F** & **Num df** & **Den df** & \(p\) & **ICC** \\ \hline
**COND** & 0.778 & 3 & 96.0 & 0.509 & 0.82 * \\
**GENDER** & 0.195 & 1 & 32.0 & 0.662 & \\
**COND*** & 0.979 & 3 & 96.0 & 0.406 & \\
**GENDER** & & & & & \\ \hline \end{tabular}  
* ICC for random intercept for subjects. Satterthwaite method for degrees of freedom.  
\end{table} 
Table 2: Mixed model analysis for car exterior colors (white, black, gray, and red). \begin{table}
\begin{tabular}{l c c c c} \hline  & **F** & **Num df** & **Den df** & \(p\) & **ICC** \\ \hline
**COND** & 2.503 & 4 & 128.0 & 0.046 & 0.28 * \\
**GENDER** & 0.637 & 1 & 32.0 & 0.431 & \\
**COND*** & 0.908 & 4 & 128.0 & 0.461 & \\ \hline \end{tabular}  
* ICC for random intercept for subjects. Satterthwaite method for degrees of freedom.  
\end{table} 
Table 3: Mixed model analysis for white exterior and interior color combinations (white, black, gray, and red). Black exterior/gray interior color combinations. The model with three predictors was significant (F(3,30) = 3.31, \(p\) < 0.05, R = 0.50, R\({}^{2}\) = 0.25); however, only the dimensions \"disturbing\" and \"uncomfortable\" significantly contributed to the model. As shown in Table 7, as both the negative PQ evaluations increased, the fixation duration for the gray interior also increased. Gray exterior/gray interior color combinations. The model with three predictors was significant (F(3,30) = 3.27, \(p\) < 0.05, R = 0.50, R\({}^{2}\) = 0.25); however, only the dimension \"poor quality\" significantly contributed to the model. As shown in Table 8, as the negative PQ evaluation increased, the fixation duration for the gray interior also increased. Gray exterior/black interior color combinations. The model with four predictors is significant (F(4,29) = 5.99, \(p\) < 0.01, R = 0.67, R\({}^{2}\) = 0.45); however, only the dimensions \"disturbing\" and \"banal\" significantly contributed to the model. As shown in Table 9, as the negative PQ evaluations increased, the fixation duration for the black interior also increased. \begin{table}
\begin{tabular}{l c c c c c} \hline  & **B** & **St. Err** & **Beta (B)** & **t** & \(p\)** \\ \hline
**BB-disturbing** & 0.60 & 0.87 & 0.98 & 3.72 & 0.001 \\
**BB-uncomfortable** & \(-\)0.22 & 0.20 & \(-\)0.28 & \(-\)1.10 & 0.28 \\
**BB-relaxing** & 0.19 & 0.09 & 0.42 & 1.95 & 0.06 \\
**BB-poor quality** & \(-\)0.20 & 0.14 & 0.30 & \(-\)1.42 & 0.16 \\ \hline \end{tabular}
\end{table} 
Table 6: The table shows the effect of subjective PQ evaluations on fixation duration when participants visually explored the black interior after seeing the black car exterior. Unstandardized (B) and standardized (Beta) coefficients, standard error, t values, and significance levels are reported.