## 1 Introduction  
Voluntary change in the consumption behavior of household users is an ongoing concern at the European level in order to increase energy efficiency, an aspect highlighted by key policy documents such as the REPowerEU Program [1] or the \"Playing my part\" plan [2]. On the other hand, digital transformation is now imperative for all businesses willing to adapt to the rapidly changing business environment [3], including EU strategic directions on energy efficiency. Among the concrete measures proposed at the strategic level are those aimed at the adoption of new intelligent devices to control energy consumption. It is estimated [2] that these measures would lead to a 15% reduction in energy consumption. Given the voluntary nature of these measures, this research examines how the generalization of green technologies such as smart meters, smart light bulbs, or smart sockets (hereafter referred to as EESS--Energy Efficiency Smart Solutions), could be stimulated at the public level based on social influence relationships that have a significant impact on users' behavioral adoption intentions. The perspective of the determinants influencing the adoption of technology can be found in research that addresses various technologies attributed to EESS, such as smart energy technologies (SET), which integrate various energy-saving technologies based on automatic sensor control [4; 5; 6]; smart home solutions, including automation and control solutions for energy or lighting systems [7; 8; 9]; home energy management system (HEMS) technologies [10; 11; 12]; building energy management systems (BEMS) [11]; smart connected objects (SCO) [13]; or even electric vehicles [6]. Most of the analyzed studies are based on the variables of the technology acceptance model (TAM) in the initial variants [14], the extended Unified Theory of Acceptance and Use of Technology (UTAUT) [15], and UTAUT2 [16], using main constructs such as behavioral intent, social influence, or hedonic motivation. The availability of users in the direction of accepting EESS technologies is also addressed under the influence of other varied determinants, such as awareness of the benefits of using energy-efficient technologies [9; 17], the attitude towards environmental protection [4; 5; 18], internalizing objectives [11], trust in technology [8], or public policies to stimulate the adoption of EESS technologies [4; 6; 19]. Among the above mentioned elements, social influence (SI) is a construct of the technology acceptance model developed within the UTAUT variants [15] and UTAUT2 [16], in addition to the four main constructs of the original model [14]--the attitude regarding the use, perceived utility, intention, and ease of use. In the context of the model of acceptance of technology, social influence is defined as \"the degree to which an individual perceives that important others believe he or she should use a particular technology\" [15] (p. 451). In fact, UTAUT2 is the model that highlights the important role of social influence [13]. Other authors [20] approach social influence from the perspective of social pressures that individuals perceive, and on the basis of which they approach a certain way of action. Social influence directs users to specific behavioral patterns under the impact of individuals, groups and societal norms [21]. From the perspective of EESS technologies, the analysis of the specialized literature revealed a series of studies based on the TAM model that use social influence as the main construct. According to [PERSON] and [PERSON] [22], social influence is among the top 10 factors that decisively influence the acceptance and adoption of energy technologies. Social influence is one of the main determinants of the acceptance of smart meters, an aspect less addressed in previous research in the field [18]. The study by [PERSON], [PERSON], and [PERSON] [4] indicated the relevance of beliefs related to social influence as a factor in the adoption of new green technologies.