## 5 Discussion
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Hypotheses** & **Relationships** & **Beta** & **ST. DEV.** & **T Statistic** & **BCCI** & \(f^{2}\) &
\begin{tabular}{c} **Supported/** \\ **Not Supported** \\ \end{tabular} \\ \hline H1a & SI\_FF \(\rightarrow\) PEOU & 0.402 *** & 0.068 & 5.948 & 0.284, 0.510 & 0.098 ** & Supported \\ \hline H1b & SI\_PS \(\rightarrow\) PEOU & 0.071 & 0.077 & 0.923 & \(-\)0.059, 0.195 & 0.003 & Not supported \\ \hline H2a & SI\_FF \(\rightarrow\) PEOU \(\rightarrow\) BIOU & 0.063 * & 0.029 & 2.217 & 0.024, 0.119 & - & Supported \\ \hline H2b & SI\_PS \(\rightarrow\) PEOU \(\rightarrow\) BIOU & 0.011 & 0.014 & 0.796 & \(-\)0.006, 0.041 & - & Not supported \\ \hline H3a & SI\_FF \(\rightarrow\) PU & 0.430 *** & 0.069 & 6.225 & 0.306, 0.535 & 0.109 ** & Supported \\ \hline H3b & SI\_PS \(\rightarrow\) PU & \(-\)0.010 & 0.079 & 0.132 & \(-\)0.138, 0.121 & 0.000 & Not supported \\ \hline H4a & SI\_FF \(\rightarrow\) PU \(\rightarrow\) BIOU & 0.025 & 0.024 & 1.048 & \(-\)0.013, 0.066 & - & Not supported \\ \hline H4b & SI\_PS \(\rightarrow\) PU \(\rightarrow\) BIOU & \(-\)0.001 & 0.006 & 0.096 & \(-\)0.014, 0.007 & - & Not supported \\ \hline H5a & SI\_FF \(\rightarrow\) HM & 0.404 *** & 0.072 & 5.623 & 0.274, 0.513 & 0.105 ** & Supported \\ \hline H5b & SI\_PS \(\rightarrow\) HM & 0.129 & 0.082 & 1.572 & \(-\)0.006, 0.265 & 0.011 & Not supported \\ \hline H6a & SI\_FF \(\rightarrow\) HM \(\rightarrow\) BIOU & 0.085 ** & 0.028 & 2.999 & 0.045, 0.139 & - & Supported \\ \hline H6b & SI\_PS \(\rightarrow\) HM \(\rightarrow\) BIOU & 0.027 & 0.020 & 1.360 & 0.002, 0.068 & - & Supported \\ \hline H7a & SI\_FF \(\rightarrow\) PE & 0.461 *** & 0.065 & 7.119 & 0.347, 0.560 & 0.149 ** & Supported \\ \hline H7b & SI\_PS \(\rightarrow\) PE & 0.127 * & 0.073 & 1.733 & 0.010, 0.254 & 0.011 & Supported \\ \hline H8a & SI\_FF \(\rightarrow\) PE \(\rightarrow\) BIOU & 0.253 *** & 0.049 & 5.208 & 0.178, 0.338 & - & Supported \\ \hline H8b & SI\_PS \(\rightarrow\) PE \(\rightarrow\) BIOU & 0.070 * & 0.041 & 1.690 & 0.009, 0.146 & - & Supported \\ \hline \hline \end{tabular}  
* Beta—Standardized path coefficient; *—\(p<0.05\); **–\(p<0.01\); **–\(p<0.001\); T statistic—\(t\)-test value; BCCI—Bias corrected confidence intervals; \(f^{2}\)—effect size. Source: authors with SmartPLS 4 [50].  
\end{table} 
Table 6: Research hypotheses. The research results indicate a significant impact of social influence from the perspective network of friends, colleagues, or family (SI_FF) on PEOU, PU, HM and PE, confirming part of the study hypotheses. The results also confirm previous research, which demonstrate the role of social networks as a factor in accepting technology [19,40], the role of the network effect or influence maximization as a multiplier in this process [9,41], the correlation between the opinions of colleagues or friends, and the attitude towards the adoption of these technologies, [39]. If social influence is relevant from both perspectives analyzed (SI_FF and SI_PS) in the case of expected performance (PE), the network of friends, colleagues, or family plays a leading role in influencing the decision to adopt EESS technologies from the perspective of perceived ease of use, hedonic motivation, and perceived usefulness. The relevance of these three model constructs is even greater if we consider the software component of EESS technologies, the operation of which is most often controlled through mobile applications. In this context, the ergonomics of these applications, ease of use, specific functions (such as: remote access, automatic programming, dashboards, etc. ), or enjoyable character are essential factors in accepting EESS. Moreover, these applications usually include certain collaborative facilities that allow the establishment of social networks in the field of EESS, accelerating the adoption of these technologies through the network effect.