## 3 Related Works  
The determinants of smart metering technology were thoroughly examined in recent years. However, on the basis of reviewing the related literature, it was noticed that only a limited understanding exists on the factors that influence the acceptance of smart meters. In an online survey-based research, [PERSON] et al. [41] applied TAM and included additional variable, such as subjective control (which refers to the ability to control a technology), in addition to perceived usefulness and perceived ease of use. This work found that perceived usefulness, perceived ease of use, and subjective control had a significant influence on attitude toward the use of technology. In another study, 1365 households were polled about the smart gas meter deployment [42]. The aim of the study is linking end-user characteristics (age, education, social class, and employment status) to their views on saving resources, improving home behaviour, and lowering carbon emissions. When this research was conducted, it discovered a statistically significant correlation between certain attributes of end-users and using the smart meter. The data indicate that the households's employment status, age, and social class have statistical significance on the end-users' variance, particularly when it comes to lowering their bill and changing their behaviour around the house. The authors of [43] investigated the determinants of consumers' intention to continue using smart metering technology through TAM as well. They conducted a survey to 212 smart meter customers in Southern Germany and found that perceived usefulness, perceived ease of use, and subjective control, and attitude toward use had a significant influence on intention to use the smart metering. Furthermore, the authors of [44] took a quantitative approach and performed several experiments to determine the motives, processes and outcomes of the development of smart grid in the South Korean context and also to identify the relationships between macroeconomic policy and the government role. The study showed that smart grid systems are being adopted by participants as a solution to climate change and energy problems. They preferred renewable energy and energy saving to address these concerns. In the same line of work, behavioural decision-making experiments to assess the perceptions of consumers in Korea was conducted by [PERSON] et al. [9], who found that participants preferred the smart meters. However, the participants expected instant savings to be achieved. Some threats were also viewed by them, including less control over their use of electricity, privacy breaches, and higher costs. Regarding the aforementioned theories and models used in smart meters, TAM was frequently cited by several authors (e.g., [45; 46]). Meanwhile, other scholars such as [PERSON] [32] used UTAUT2 to explore smart meters acceptance in Indonesia. The authors have not examined the experience and habit factors, as their primary concern was about the behavioural intention towards the use of smart meters rather than its actual use. The literature review indicates that there are several opportunities for improvement in various domains. Many studies on smart meters have investigated the acceptance of individuals, yet there are limited studies that examine the exogenous factors that determine its acceptance. Table 2 illustrates and summarizes additional studies regarding the smart meter acceptance, the extracted data from these studies are based on their targeted case, observed behaviour, models used and main findings. Firstly, the targeted case represents the type of participants involved in these studies. Most of the participants were electricity consumers who were users of smart meters. However, no study has examined the users of smart meters. Secondly, the observed behaviour describes the outcome variables. Several behaviours were observed, such as intention, support, acceptance, attitude, and adoption. Furthermore, the intention to use was the dominant variable among these studies.