## 5 Results
### Results of the Product Emotion Evaluation Questionnaire  
As mentioned in Section 3.3.1, the product emotion evaluation questionnaire used the difference from the midpoint value of 4 (no appropriate description) to measure how well each environment conveyed product emotion. The analysis was performed using SPSS for Windows. We designated the product information provision method as an independent variable and performed an independent sample \(t\)-test. Each test was analyzed separately for each product under study. The combined analysis results for all shoe models showed that out of 15 items, 9 items (i.e., 1, 2, 3, 4, 6, 7, 10, 13, 15) demonstrated a larger difference in scores in favor of the VR shopping information provision method over the existing e-commerce method. However, only item 3, with a \(t\)-value of \(-\)2.786, showed a statistically significant difference in product information provision methods (see Figure 6).  
The analysis results by individual shoe models showed a different pattern compared to the consolidated results. This difference is due to the unique product emotions associated with each shoe model, which can offset the combined results. Specifically, Model 1 displayed a greater score difference in four items (i.e., 3, 6, 10, 11) favoring the VR shopping information provision method over the existing e-commerce method. In terms of standard deviation, which indicates the consistency of product emotion information delivery, VR shopping showed relatively smaller variations in nine items (i.e., 1, 2, 4, 6, 7, 8, 9, 10, 12). Similarly, Model 2 displayed significant differences in 4 items (i.e., 3, 9, 10, 11) with VR shopping and showed relatively smaller variances in 11 items (i.e., 1, 2, 3, 4, 7, 8, 9, 10, 11, 13, 15). For Model 3, the VR shopping information provision method showed considerable differences in five items (i.e., 3, 6, 13, 14, 15) relative to the median, and smaller variances  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Characteristics** & **Category** & **Group** & **Total** & **Rate** \\ \hline \multirow{4}{*}{Gender (people)} & \multirow{2}{*}{Male} & ALL & 14 & 50\% \\  & & CG & 8 & 57\% \\  & & EG & 6 & 43\% \\ \cline{2-5}  & \multirow{2}{*}{Female} & ALL & 14 & 50\% \\  & & CG & 6 & 43\% \\  & & EG & 8 & 57\% \\ \hline Age Distribution (people) & 20\(\sim\)25 & ALL & 28 & 100\% \\ \hline \multirow{2}{*}{Average Weekly Usage of Online Shopping Platform (times)} & ALL & 6 & \multirow{2}{*}{} \\  & & CG & 4.5 & \\ \cline{1-1}  & & EG & 7.8 & \\ \hline \multirow{4}{*}{Frequency of Purchasing Shoes Online (people)} & \multirow{2}{*}{Yes} & ALL & 18 & 64\% \\ \cline{1-1}  & & CG & 10 & 71\% \\ \cline{1-1}  & & EG & 8 & 57\% \\ \cline{1-1} \cline{2-5}  & \multirow{2}{*}{No} & ALL & 10 & 36\% \\ \cline{1-1}  & & CG & 4 & 29\% \\ \cline{1-1}  & & EG & 6 & 43\% \\ \hline \hline Number of VR Experiences & \multirow{2}{*}{EG} & \multirow{2}{*}{1.7} \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & & & \\ \cline{1-1}  & & EG & 1.7 & \\ \hline \end{tabular} This table summarizes the characteristics of participants based on gender, age, and various metrics related to online shopping and VR experiences.  
\end{table}
Table 3: Characteristics of participants.  
in all items except 12. In Model 4, VR shopping demonstrated significant differences in five items (i.e., 2, 3, 6, 7, 9) relative to the median, with smaller variances observed in all but three items (i.e., 3, 4, 5). Lastly, Model 5's VR shopping method revealed significant differences in 5 items (i.e., 3, 10, 11, 13, 15) relative to the median, and the standard deviation was smaller in 11 of the items, excluding 4 items (i.e., 3, 6, 9, 12). The shoe model analysis revealed that statistically significant differences were absent in all items for Model 3 except for item 1.