## 5 Discussion
The results of the research allow for the outline of directions to focus efforts and more intensively promote these technologies--both at the level of public authority and companies in industry--in the context of increasingly pressing needs to reduce energy consumption. First, in terms of communication in the public space, a more pragmatic and diversified approach to concrete solutions to change voluntary consumption behavior is needed in order to increase energy efficiency, including through the purchase of EESS solutions. The research results currently indicate a higher level of receptivity based on information from the public space in the case of the expected performance of these technologies, without emphasizing the issues related to the use and benefits obtained, which also influence the adoption of EESS solutions as shown in previous research. The study highlighted the direct positive impact of communication through social networks in stimulating the effect of the network and accelerating the spread of EESS. Public policies should, in this context, focus mainly on online communication actions and social media campaigns rather than on traditional communication channels that are shown to be less effective in the EESS situation. In the case of companies producing or marketing EESS, marketing policies should emphasize the pleasant nature of the EESS, as research has shown the significant impact of hedonic motivation as a factor in mediating between the social influence (SI) and behavioral intention to use these technologies (BIOU). In terms of theoretical contributions, this research brings a number of new elements. The use of the TAM model in the field of EESS is a less common research approach in the literature, although the pace of propagation of these technologies is very high, especially in the context of the energy challenges of the current period. For increased accuracy of the analysis of the correlations between the social influence (SI) and the other constructs of \begin{table}
\begin{tabular}{c c c c c} \hline \hline  & **N** & **\%** & **Valid \%** & **Cumulative \%** \\ \hline \multicolumn{5}{c}{Subsides for energy consumption} \\ \hline No & 214 & 70.861 & 70.861 & 70.861 \\ \hline Yes & 88 & 29.139 & 29.139 & 100.000 \\ \hline Total & 302 & 100.000 & 100.000 & \\ \hline \multicolumn{5}{c}{Subsides for EESS} \\ \hline No & 262 & 86.755 & 86.755 & 86.755 \\ Yes & 40 & 13.245 & 13.245 & 100.000 \\ Total & 302 & 100.000 & 100.000 & \\ \hline \hline \end{tabular} N—number of cases.  
\end{table} 
Table 7: Demographic data—subsides for energy efficiency. the conceptual model, two dimensions (SI_FF and SI_PS) are used, the analysis of which reveals, significant differences in perception, thus allowing a more efficient calibration of policy proposals resulting from the analysis. Correlations between social influence, on the one hand, and perceived ease of use (PEOU), perceived usefulness (PU), hedonic motivation (HM), and expected performance (PE), on the other hand, were also studied from two perspectives. First, the direct effect of social influence on these last four constructs was assessed, and second, their indirect role was analyzed as a factor in mediating the relationship between social influence and the behavioral intention to use EESS (BIOU). Last but not least, the research puts forward a number of proposals for the calibration of public policies in the field of energy efficiency by integrating measures to accelerate the growth rate of the EESS market and the use of these technologies at the home consumer level.