## 6 Discussion  
More organizations are beginning to invest significant effort into providing their employees with online learning opportunities for sustainable development. While many studies have provided constructive comments on specialized e-learning platforms and online training models, few studies have focused on the experience and effectiveness of applying e-learning modules in office applications. The use of such online learning modules offers significant advantages and greater employee spontaneity. To tackle this, the research centers on examining the connection between motivational factors of user experience and determinants, grounded in a modified version of the Unified Theory of Acceptance and Use of Technology (UTAUT) model, and employees' intentions towards sustainable learning. This study found that four determinants (performance expectancy, effort expectancy, social influence, facilitating conditions) based on an adaptation of the UTAUT model incorporated into the UTAUT model were meaningful in explaining employees' willingness to use the online learning module of office apps for continuous learning. Among them, performance expectancy (\(\beta\) = 0.400, \(p\)\(\leq\) 0.05) possesses a strong correlation with employees' sustainable intention to learn online, and effort expectancy (\(\beta\) = 0.191, \(p\)\(\leq\) 0.05) also has some positive effects on employees' sustainable intention to learn online. Performance expectancy and effort expectancy on the behavioral impact of online learning were confirmed in line with [PERSON]'s [47] study. Acceptance of online learning modules for office apps is also part of employees' acceptance of the company's digital transformation, and [PERSON] and [PERSON]'s [84] findings indicate that performance expectancy and effort expectancy significantly influence employees' acceptance of digital transformation, consistent with this paper. There is also consistency between the findings of this study and other studies on online learning concerning the effects of performance expectancy and effort expectancy on learning behavior [45]. Moreover, social influence (\(\beta\) = 0.211, \(p\)\(\leq\) 0.05) and facilitating conditions (\(\beta\) = 0.185, \(p\)\(\leq\) 0.05) were also positively correlated with the influence of employees' behavioral intention to learn sustainably. This is in line with the findings [85] that the significant \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Hypothesis and Path**} & \multicolumn{2}{c}{**STD.**} & \multicolumn{1}{c}{**S.E.**} & \multicolumn{1}{c}{**C.R.**} & \multicolumn{1}{c}{**P**} & \multicolumn{1}{c}{**R\({}^{2}\)**} & \multicolumn{1}{c}{**Result**} \\ \hline H3 & Effort Expectancy & \(\leftarrow\) & Self-Management & 0.338 & 0.043 & 6.481 & *** & & Valid \\ \hline H4 & Effort Expectancy & \(\leftarrow\) & Learning Experience & 0.058 & 0.038 & 1.217 & 0.224 & & Invalid \\ \hline H5 & Social Influence & \(\leftarrow\) & Company Atmosphere & 0.079 & 0.037 & 1.599 & 0.110 & & Invalid \\ \hline H6 & Social Influence & \(\leftarrow\) & External Pressure & 0.365 & 0.039 & 6.861 & *** & & Valid \\ \hline H7 & Facilitating Conditions & \(\leftarrow\) & Company Support & 0.203 & 0.056 & 4.339 & *** & & Valid \\ \hline H8 & Facilitating Conditions & \(\leftarrow\) & Course Quality & 0.257 & 0.047 & 5.447 & *** & & Valid \\ \hline H9 & Behavioral & \(\leftarrow\) & Performance Expectancy & 0.400 & 0.066 & 7.966 & *** & & Valid \\ \hline H10 & Behavioral & \(\leftarrow\) & Effort Expectancy & 0.191 & 0.055 & 4.263 & *** & & Valid \\ \hline H11 & Behavioral & \(\leftarrow\) & Social Influence & 0.211 & 0.061 & 4.710 & *** & & Valid \\ \hline H12 & Behavioral & \(\leftarrow\) & Facilitating Conditions & 0.185 & 0.04 & 4.400 & *** & & Valid \\ \hline \hline \end{tabular} \({}^{*}\)_p_ < 0.05, **_p_ < 0.01, ***_p_ < 0.001.  
\end{table} 
Table 7: _Cont._factors of behavioral intention to use an online learning system are social influence and learning facilitating conditions.