## 6 Conclusion and Insights  
### Main Findings  
The study has yielded various interesting findings. First and foremost, before the effects of privacy fatigue arose, it is valid to claim that a positive influence is engendered by privacy concerns as to the intention for privacy protection behavior. This is consistent with prior studies in academia [27, 37]. Privacy concerns are the core factor highlighting user adoption of privacy protection behaviors on social media. At the same time, they further \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Variable**} & \multicolumn{2}{c}{**Intensity of WeChat Usage**} & \multicolumn{2}{c}{**Number of Friends on WeChat**} \\ \cline{2-5}  & **Under 3 h Daily** & **Over 3 h Daily** & **Under 100** & **Over 100** \\ \hline pc1 & 0.105 *** & 0.041 & 0.066 ** & 0.061 ** \\  & (\(-\)0.027) & (\(-\)0.026) & (\(-\)0.028) & (\(-\)0.025) \\ pc1 \(\times\) cy & \(-\)0.155 *** & \(-\)0.126 *** & \(-\)0.158 *** & \(-\)0.125 *** \\  & (\(-\)0.024) & (\(-\)0.024) & (\(-\)0.026) & (\(-\)0.023) \\ age & 0.004 & \(-\)0.137 & \(-\)0.028 & \(-\)0.057 \\  & (\(-\)0.080) & (\(-\)0.095) & (\(-\)0.084) & (\(-\)0.092) \\ edu & \(-\)0.049 & 0.094 ** & 0.021 & \(-\)0.005 \\  & (\(-\)0.034) & (\(-\)0.045) & (\(-\)0.036) & (\(-\)0.045) \\ freq & \(-\)0.037 & 0.045 & \(-\)0.027 & 0.004 \\  & (\(-\)0.075) & (\(-\)0.057) & (\(-\)0.102) & (\(-\)0.050) \\ friends & 0.034 & \(-\)0.019 & \(-\)0.043 & \(-\)0.024 \\  & (\(-\)0.060) & (\(-\)0.038) & (\(-\)0.036) & (\(-\)0.030) \\ pro & 0.020 & \(-\)0.010 & 0.041 & \(-\)0.005 \\  & (\(-\)0.029) & (\(-\)0.015) & (\(-\)0.049) & (\(-\)0.014) \\ Constant & 1.845 *** & 2.459 *** & 1.598 * & 2.529 *** \\  & (\(-\)0.558) & (\(-\)0.338) & (\(-\)0.895) & (\(-\)0.327) \\ \hline Observations & 581 & 668 & 555 & 694 \\ R-squared & 0.089 & 0.052 & 0.077 & 0.049 \\ \hline \hline \end{tabular} Notes: * ** and *** respectively denote significance on the 10%, 5% and 1% levels, and standard error is in parentheses.  
\end{table} 
Table 10: The heterogeneity analysis of usage characteristics. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Variable**} & \multicolumn{2}{c}{**Sex**} & \multicolumn{2}{c}{**Age**} & \multicolumn{2}{c}{**Level of Education**} \\ \cline{2-7}  & **Male** & **Female** & **Under 30** & **Over 30** & **Lower Education** & **Higher Education** \\  & **Male** & **Female** & **Under 30** & **Over 30** & **Levels** & **Levels** \\ \hline pc1 & 0.074 * & 0.063 *** & 0.085 ** & 0.060 *** & 0.081 *** & 0.034 \\  & (\(-\)0.041) & (\(-\)0.021) & (\(-\)0.037) & (\(-\)0.021) & (\(-\)0.023) & (\(-\)0.032) \\ pc1 \(\times\) cy & \(-\)0.181 *** & \(-\)0.132 *** & \(-\)0.179 *** & \(-\)0.122 *** & \(-\)0.20 illustrated the presence of the emerging prerequisite for privacy paradox under the social media context. Second, for this set of relationship between privacy concerns and intention for privacy protection behavior, owing to the emergence of privacy fatigue, wholesale changes have erupted. Among these, cynicism turns the positive influence between privacy concern and intention for privacy protection behavior into negative influence, while emotional exhaustion would attenuate the positive influence relationship between the two. This discovery echoed the conclusion proffered by academics that the influence from privacy fatigue exceeded privacy concerns [9]. It further confirmed that privacy fatigue could become an explanation for privacy paradox. Third, personal traits and usage characteristics lead to dissimilar heterogeneous contributions in privacy fatigue's explanation on privacy paradox. For users who are male, lower levels of education and younger age are personal traits with greater explanatory strength of individuals' privacy fatigue concerning the privacy paradox. Regarding usage characteristics, the explanatory power is stronger for interviewees with a longer WeChat using duration and having fewer WeChat friends.