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the purchase of “green” electricity, among which it may include non-energy services/products; the type of renewable
energy source used to produce “green” electricity; et al. Also, it is worth noting that there is a positive relationship
between customer satisfaction and the willingness to pay since satisfied customers are willing to pay more for “green”
products or services. When customers are satisfied, they perceive a high outcome of exchange and therefore are willing
to pay more (i.e. more than less satisfied customers) because this still results in a beneficial ratio of outcome to money
spent. Similarly, when satisfaction is low, customers perceive a low payment as adequate to establish a fair exchange
(Homburg, Koschate, Hoyer, 2005). This paper aims to establish the features contributing to the consumer’s willingness
to pay more for electricity obtained from renewables.

STUDY DESIGN/METHODOLOGY/APPROACH

The method used in this research is quantitative research methods. The research data consisted of primary data,
obtained through the questionnaire filling method using a smartphone device. Respondents were scattered in various
groups in Indonesia and China with a total of 5,150 respondents. This questionnaire is empirical with survey method
being used to collect the data, we surveyed a random of ages. The purpose of the survey is to measures WTP for green
electricity, to discover the factors shaping public opinion about renewable energy sources. In processing data from the
survey results used is IBM SPSS Statistics 26 software.

The method is based on the consideration that in this study there is a relationship of gender, education, income, age,
knowledge, jobs, beliefs, and behavior towards a willingness to pay so that the focus of the analysis shifts from the only
estimation and significant interpretation of parameters to validity and accuracy of predictions.

FINDINGS

Based on the results of the analysis and discussion conducted on WTP for Green Electricity is influenced by the level
of knowledge of someone about green electricity (statistical T- calculate 1,623,413> T-table 1,960), the level of one’s
initiative to find out information on green electricity from social media (statistical T-calculate 1,781,682> T-table 1,960),
power generation methods that play a role in green electricity (statistical T-calculate 6,734,760> T- table 1,960425),
understanding someone in responding to regulations regarding renewable energy to overcome pollution (statistical
T-calculate 2,440,285> T-table 1,960), the impact of government policies on the environment (statistical T-calculate
3,555,509> T-table 1,960), and supporting factors someone is willing to pay dearly in deciding to use green electricity
(statistical T-calculate 354,849> T-table 1,960).

The level of one’s knowledge about green electricity, the level of one’s initiative to find out green electricity information
from social media, the methods of generating electricity that play a role in green electricity, understanding someone in
responding to regulations regarding renewable energy to overcome pollution, the impact of government policies on
the environment, and one’s supporting factors willing to pay dearly in deciding to use green electricity together has a
significant effect on the level of WTP for Green Electricity. This is evidenced by the results of the F statistical test which
showed a significance value of 0,000 <0.05 (level of research significance).

ORIGINALITY/VALUE

The government is expected to be able to improvise policies on the importance of protecting the environment and
campaigning to the community for factors in deciding to use green electricity.

Keywords
Green electricity, Willingness to Pay

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