## 3 Materials and Methods
### Statistical Processing Methods for Hypothesis Testing
#### 3.3.1 Assessment of Measurement Model  
The model's suitability was measured using reliability and validity tests, conducted with the Partial Least Squares (PLS) algorithm. As shown in Table 3, to verify the constructs' reliability, Cronbach's alpha (\(\alpha\)), rho_A, and Composite Reliability (CR) values were examined. Values exceeding the 0.7 threshold indicate adequate internal consistency and reliability of the constructs [95; 96]. The analysis results showed that Cronbach's \(\alpha\) values ranged from 0.847 to 0.938, rho_A values from 0.847 to 0.939, and CR values from 0.897 to 0.948, all of which exceed the 0.7 threshold, confirming adequate reliability. \begin{table}
\begin{tabular}{c c c c} \hline
**Classification** & **Distribution** & **Frequency** & **Percentage** \\ \hline \multirow{2}{*}{Gender} & Male & 133 & 46.7\% \\  & Female & 152 & 53.3\% \\ \hline \multirow{6}{*}{Age} & Under 20s (<20 years old) & 37 & 13.0\% \\  & 20s (20 to 29 years old) & 72 & 25.2\% \\  & 30s (30 to 39 years old) & 72 & 25.2\% \\  & 40s (40 to 49 years old) & 62 & 21.8\% \\  & 50s (50 to 59 years old) & 39 & 13.7\% \\  & 60 or Older (= or >60 years old) & 3 & 1.1\% \\ \hline \multirow{4}{*}{Educational Background} & High school or below & 65 & 22.8\% \\  & Currently in College (excluding Junior College) & 73 & 25.6\% \\  & College Graduate (excluding Junior College) & 71 & 24.9\% \\  & Postgraduate or higher & 76 & 26.7\% \\ \hline \multirow{4}{*}{Occupational Background} & Student & 53 & 18.6\% \\  & Company employee (IT industry) & 99 & 34.7\% \\  & Company employee (non-IT industry) & 96 & 33.7\% \\  & Housewife & 37 & 13.0\% \\ \hline \multirow{4}{*}{Usage Duration} & Less than 1 month & 70 & 24.6\% \\  & 1 to 3 months & 58 & 20.4\% \\  & 3 to 6 months & 53 & 18.6\% \\  & 6 to 12 months & 46 & 16.1\% \\  & Over 12 months & 58 & 20.3\% \\ \hline \multirow{4}{*}{Usage Frequency} & Almost every day & 7 & 2.5\% \\  & 3 to 4 times a week & 53 & 18.6\% \\ \cline{1-1}  & Once a week & 111 & 38.9\% \\ \cline{1-1}  & 2 to 3 times a month & 55 & 19.3\% \\ \cline{1-1}  & Less than once a month & 59 & 20.7\% \\ \hline \multirow{4}{*}{Usage Purpose (multiple choices allowed)} & Daily conversations and entertainment & 101 & 35.4\% \\ \cline{1-1}  & Translation and writing assistance & 156 & 54.7\% \\ \cline{1-1}  & Information and knowledge search & 130 & 45.6\% \\ \cline{1-1}  & Professional questions and consultations & 76 & 26.7\% \\ \cline{1-1}  & Programming and technical support & 16 & 5.6\% \\ \cline{1-1}  & Creative and content creation assistance & 112 & 39.3\% \\ \hline \end{tabular} Source(s): Table by the Author.  
\end{table} 
Table 2: Participant demographics (N = 285). To verify the constructs' validity, we assessed both convergent and discriminant validity. Regarding convergent validity, the Outer Loadings (\(\lambda\)) of each construct exceeded 0.781, well above the threshold of 0.7. The Average Variance Extracted (AVE) values for each construct also exceeded the minimum value of 0.5, with values ranging from 0.668 to 0.731, demonstrating good convergent validity [102]. For discriminant validity, as confirmed by the Fornell and Larcker criterion [103], the square root of the AVE for each construct was greater than its highest correlation with any other construct. We employed the Heterotrait-Monotrait (HTMT) ratio to further ensure discriminant validity. Values