## 4 Results
### Structural Model  
Based on the discerned outcomes presented in Table 3, the statistical analyses yield the following results: a Chi-square (\(\chi^{2}\)) value of 930.482, characterized by a Degrees of Freedom (df) of 584, thereby yielding an \(\chi^{2}\)/df ratio of 1.593. Furthermore, an evaluation of key fit indices reveals a Comparative Fit Index (CFI) of 0.978, a Normed Fit Index (NFI) of 0.943, a Non-Normed Fit Index (NNFI) of 0.975, and a Root Mean Square Error of Approximation (RMSEA) measuring 0.03. These outcomes collectively confirm that the established parameters integral to the structural equation model are notably satisfied, subsequently demonstrating the notable alignment of the proposed structural model with the empirical data.  
To assess the hypothesized relationships, the articulated pathways between constructs are diligently scrutinized. The explanatory capacity of satisfaction registers at an appreciable 45.7%, while the power of behavioral intention substantiates itself with a robust explanatory power of 55.3%. Evidently, the outcome of the hypothesis testing attests to the following observations (see Table 4 and Figure 2): PE exerts a positively significant influence on behavioral intention (\(\beta_{\text{ PE}\rightarrow\text{BI}}=0.207\), t = 5.006, \(p<0.001\)). EE yields a favorable and statistically significant impact on behavioral intention (\(\beta_{\text{ EE}\rightarrow\text{BI}}=0.314\), t = 9.129, \(p<0.001\)). SI engenders a positive and statistically significant influence on behavioral intention (\(\beta_{\text{ SI}\rightarrow\text{BI}}=0.146\), t = 3.866, \(p<0.001\)). Facilitations Conditions elicit a constructive and statistically significant impact on behavioral intention (\(\beta_{\text{ PC}\rightarrow\text{BI}}=0.087\), t = 2.431, \(p<0.05\)). Satisfaction notably has a positive and statistically significant effect on behavioral intention (\(\beta_{\text{ SA}\rightarrow\text{BI}}=0.371\), t = 7.951, \(p<0.001\)). Perceived risk, while evoking a positive influence on behavioral intention and satisfaction, does so with a significantly negative magnitude (\(\beta_{\text{ PR}\rightarrow\text{BI}}=-0.125\), t = \(-2.687\), \(p<0.01\); \(\beta_{\text{ PR}\rightarrow\text{SA}}=-0.431\), t = \(-10.724\), \(p<0.001\)). Perceived Functional Value materialy and positively impacts satisfaction (\(\beta_{\text{ PEV}\rightarrow\text{SA}}=0.318\), t = 8.592, \(p<0.001\)). Similarly, Perceived Emotional Value significantly affects satisfaction (\(\beta_{\text{ PEV}\rightarrow\text{SA}}=0.098\), t = 2.705, \(p<0.01\)). Finally, Perceived Price Value has a constructive and statistically significant effect on satisfaction (\(\beta_{\text{ PPV}\rightarrow\text{SA}}=0.118\), t = 3.057, \(p<0.01\)). These empirical findings collectively underpin the rigorous validation of the articulated research model and the nuanced relationships encapsulated within it.  
In summary, the outcomes gleaned from this study confirm the robust validation of the UTAUT within the scope of technological acceptance. While it remains evident that all factors exert a positive influence on behavioral intentions, the discernment of nuanced differentials also attests to the existence of certain pragmatic intricacies. Furthermore, the conclusions drawn from the three perceptual measurement dimensions of satisfaction concisely corroborate the underpinning hypotheses of this study. This confirmation substantiates the indispensability of altering extrinsic factors aligned with the psychological domain for the discernment of technology utilization within the context of leisure pursuits.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline
**AVE** & **PE** & **EE** & **SI** & **FC** & **BI** & **PR** & **SA** & **PFV** & **PEV** & **PPV** & **Items** & **Factor Loading** \\ \hline CR & 0.906 & 0.906 & 0.912 & 0.867 & 0.837 & 0.874 & 0.865 & 0.930 & 0.883 & 0.900 & Model fit & \multirow{2}{*}{\(\chi^{2}\)/df = 930.482/584 = 1.593} \\ \cline{6-11} \cline{6-