How Are Consumer Perspectives of PV Rooftops and New Business Initiatives in Indonesia’s Energy Transition?

Abstract

In the evolving landscape of the energy sector, it is vital for energy companies to grasp consumer behaviors to foresee future business prospects and risks. This study delves into how consumers react to Indonesia’s Electricity Company’s innovative business propositions, particularly the PV rooftop product. It also seeks to understand market reactions to other novel business concepts beyond the PV rooftop product. This research employs a quantitative approach, utilizing surveys for data gathering and statistical methods for analysis. Key variables examined include Attitude, Environmental Concern, Subjective Norm, Perceived Behavior Control, Personal Norm, and Regulation, with the primary focus on the Purchase Intention for the PV rooftop product. The findings reveal that key variables, specifically Personal Norm, Subjective Norm, and Regulation, significantly influence consumer behavior toward rooftop PV. This study also uncovers a high market demand for yet-to-be-launched services like electrical repairs, smart home consultancy, and micro-loans, indicating a diverse market potential for these innovative ideas. This research highlights the importance of analyzing consumer behavior in predicting the potential for both opportunities and challenges in a company’s new business ventures, particularly in the renewable energy sector. The results underscore the significant impact of sociocultural factors and regulatory frameworks on consumer decision-making processes. These insights offer critical guidance for Indonesia’s energy stakeholders in developing countries, aiding in formulating new business strategies and identifying market opportunities amidst the global shift towards renewable energy. This study’s key results emphasize the need for energy companies to adapt and innovate in response to consumer preferences and regulatory environments in order to capitalize on emerging market trends.

1. Introduction

The electricity industry is currently undergoing an energy transition characterized by a shift towards renewable energy sources and a reduction in the use of fossil fuels [1,2]. This transition is driven by various factors, such as climate change, environmental concerns, and government policies [2,3]. As a result, electricity companies, including the state-owned Perusahaan Listrik Negara (PLN) in Indonesia, are facing new challenges and opportunities in the market. PLN has to adapt to these changes to remain competitive. The company has identified new business ideas that can be developed in the future, such as the launch of the rooftop PV or Pembangkit Listrik Tenaga Surya (PLTS) rooftop product. However, it is crucial to understand customer behavior and identify potential opportunities and threats for PLNs future business development. Although the growth of electricity sales (kWh) and the number of PLN customers has been steady, growth rates have slowed [4,5]. Therefore, research is required to identify the potential opportunities and threats of new businesses in the future. Furthermore, mapping the market response to new business ideas other than PV rooftop products is critical, as this will provide insight into customer preferences and needs in the shifting electricity market.

In light of these issues, Indonesia’s electricity company (PLN) has introduced new business ideas, both related and unrelated to electricity sales. These ideas include a green energy ecosystem consisting of PV, batteries, and a Renewable Energy Certificate (REC). Additionally, ideas related to converting non-electric household appliances to electric include internet facilities, electrical repair services for households, micro-loans for small and medium-sized businesses, and smart home construction [6]. Currently, the green energy ecosystem, specifically the PV rooftop product and REC, has been officially launched to customers. The PV rooftop product is mainly marketed to household customers, while the REC is marketed to industrial customers to meet export requirements. The implementation of these new business ideas is crucial to the sustainability of PLNs business and is also important considering the global trend towards promoting the use of green energy to preserve the environment [7].

Given the global trend towards the use of rooftop solar panels, it is likely that this trend will also occur in Indonesia in the near future [8]. In Indonesia, the use of rooftop solar panels has been increasing in recent years. The number of rooftop solar panel users in Indonesia was 351 at the beginning of 2018, then increased to 609 at the end of 2018, and continued to increase to 1580 at the end of 2019. As of June 2020, the number of rooftop solar panel users in Indonesia had reached 2346 [5]. However, when compared to the millions of PLN customers, the number of rooftop solar panel users as of June 2020 is still relatively small, but with significant growth potential, making the market for rooftop solar panels still wide open [8,9].

In addition to sustainability concerns for businesses and global trends, the decline in the cost of rooftop solar panels is also an important factor to consider in the widespread adoption of rooftop solar panels. Globally, the cost of rooftop solar panels has decreased as a result of cheaper production technologies, as shown in [10]. Therefore, as PLN has launched a new business in the sale of rooftop solar panels, it is necessary to analyze customer behavior to determine the potential market acceptance of the launched product. This will allow for an estimation of potential opportunities and threats in the marketing of rooftop solar panels from the perspective of customer behavior and can aid in developing appropriate marketing strategies to target customers in Indonesia.

The decreasing growth in electricity sales to household customers has prompted PLN to develop new and innovative business ideas, both within and outside of the electricity industry. Currently, one of the officially launched products for household customers is the PV rooftop product. In order to effectively market this product, it is important to understand the behavior of Indonesia’s customers. Additionally, as new business ideas that have not yet been officially launched are proposed, it is necessary to conduct an analysis to assess their potential market acceptance. Through this research, we aim to identify potential opportunities and threats that may arise from customer behavior. To achieve this goal, the following research questions will be addressed:

• What is the impact of customer behavior on consumers’ intentions to purchase PV rooftops?
• What is the potential market acceptance for new business ideas?

This research aims to understand the potential opportunities and threats for the development of new business by analyzing customer behavior towards PLNs new business ideas, specifically the PV rooftop product. This study also aims to map the market response to other new business ideas beyond the PV rooftop product. This research will use a quantitative method, with surveys as the data collection technique and statistical procedures for data analysis. The independent variables in this study are Attitude, Environmental Concern, Subjective Norm, Perceived behavior control, Personal Norm, and Regulation. The dependent variable is the Purchase intention of PV rooftop products.

Notable studies have already been conducted to analyze consumer behavior and the new business of Indonesia’s energy transition, including the electric vehicle (EV) and EV charging station [11], PV plant and PV rooftop [4,5,12,13], and induction stove [14,15]. However, the study of Indonesia’s consumer behavior on PV rooftops is still limited. This study stands out as the first to comprehensively analyze consumer behavior regarding PV and new business alternatives for electricity companies in Indonesia. This research provides valuable insights for Indonesia’s energy stakeholders to consider when developing new business strategies and identifying potential opportunities in the market.

This paper consists of several chapters to examine consumer viewpoints on Photovoltaic (PV) systems. In Section 1: Introduction, this research aims and background are presented to establish the foundation. Section 2, under Review and Research Design, offers a comprehensive examination of relevant academic literature and outlines the specific methodological approach employed in this study. Section 3: Results and Discussion provides a comprehensive account of the statistical findings and thoroughly examines their ramifications within this research field. The document concludes with Section 4 Conclusion, which synthesizes the key findings and possible impacts on the sector.

2. Review and Research Method

Consumer behavior refers to the actions and decisions of individuals in relation to obtaining and using goods and services. This encompasses both the cognitive and physical aspects of the process, including the decision-making process and the actual actions taken in evaluating, purchasing, and utilizing these goods and services [16]. According to [17], consumer behavior can be divided into two main components: the decision-making process, which includes evaluating options, seeking information, and determining preferences; and the physical activities, which involve obtaining and using the chosen product or service. Understanding consumer behavior is crucial for businesses and marketers, as it helps to predict and influence purchasing decisions, ultimately leading to successful product development and marketing strategies.

To understand consumer behavior toward purchasing PV rooftop systems, a modification of the Theory of Planned Behavior (TPB) is used. TPB is a widely accepted framework that aims to explain human behavior, particularly in the context of decision-making processes. It is particularly useful in understanding environmental behavior, as it takes into account the individual’s attitudes, subjective norms, and perceived behavioral control towards a particular behavior [18]. The theory is an expansion of the Theory of Reasoned Action (TRA), which is limited in its ability to explain behavior that is not under complete volitional control [19]. TRA posits that behavior is the result of a rational process where individuals consider their options, evaluate the consequences and outcomes, and decide whether to perform the behavior or not. This decision is reflected in their intention, which has a strong influence on the behavior that follows.

Consumer behavior is a complex and dynamic process that is shaped by a variety of factors, including individual characteristics, social and cultural influences, and situational context. Understanding consumer behavior is crucial for businesses, as it allows them to effectively design and target marketing strategies and products that appeal to their target audience [20]. The Theory of Planned Behavior (TPB) is a widely used framework that helps to explain how individuals make decisions and engage in specific behaviors. In particular, the TPB has been used to study consumer behavior in the environmental field, including the adoption of renewable energy sources such as PLTS rooftop systems [21,22,23]. In this study, we will utilize a modified version of the TPB to explore the factors that influence consumer behavior toward purchasing PV rooftop systems as an energy source for households. By identifying these factors, we aim to gain a better understanding of how to design effective marketing strategies and products that will appeal to consumers and encourage them to adopt PV rooftop systems as an energy source.

In the context of purchasing Plug-in Hybrid Electric Vehicle (PHEVs), previous research has shown that these factors play a significant role in determining consumer behavior and purchase intention. Additionally, these factors have a simultaneous effect on purchase intention, with perceived behavioral control having the most dominant impact [24]. Understanding consumer behavior using frameworks such as the Theory of Planned Behavior (TPB) can provide insight into the underlying factors that influence consumer behavior toward purchasing PV rooftop systems as an energy source for households. This knowledge can be used to develop marketing strategies that effectively target specific consumer segments and identify potential new business ventures that are in demand among the public. By examining the influence of consumer behavior on the purchase intention of PV rooftops, this study aims to contribute to a broader understanding of consumer behavior and decision-making in the context of sustainable energy systems.

This study adopts a quantitative research approach, focusing on evaluating theoretical hypotheses using numerical measures and statistical analysis tools [25]. Additionally, comparative causal research design is also used to investigate the factors that lead to the occurrence or emergence of a particular phenomenon. It is widely used to investigate the cause-and-effect correlations between variables [26]. The dependent variable in this study is purchase intention, while the independent variables include attitude, environmental concern, subjective norm, perceived behavioral control, personal norm, and regulation.

This study was conducted with a sample of Indonesia’s customers and prospective consumers. The survey method were utilized for data collection, and snowball sampling was used to collect the sample. The collection of data began in November 2020 and continued until December 2020.

The first steps in this research involve determining this research topic and determining critical variables involved in this study of consumer behavior, including attitude, personal norm, perceived behavioral control, environmental concern, subjective norm, and regulation. Following that, the data collection method were determined, and a survey of PLN household customers was conducted. The operationalization process was carried out, which involved translating the concept of customer behavior into questions in the questionnaire. A pilot survey was undertaken to verify the validity and reliability of the questionnaire and ensure its quality. Based on the results of the pilot survey, improvements were made to the questionnaire, resulting in the final questionnaire shown in Appendix A.

Once the final questionnaire was established, this research sample size was calculated using the Slovin method, which determined that 400 respondents were required for this study with a 95% confidence level. To account for possible invalid responses, the questionnaire was distributed to a total of 686 respondents to assure reliable results. The subsequent step was to distribute the questionnaire and collect this research data, which would then be subjected to parametric analysis for the discussion of rooftop PV and non-parametric analysis to evaluate the suitability of PLNs new business to customer needs. This analysis method aims to provide a thorough understanding of customer attitudes and behaviors regarding rooftop PV use, as well as to investigate the viability of PLNS new business strategies in meeting customer wants and preferences.

3. Results and Discussion

3.1. Demographic

In conducting the survey, demographic data of the respondents were collected, consisting of age, education, occupation, income, and location, as well as the impact of COVID-19 on decision-making. From the survey results, the obtained demographic data are presented in Figure 1.

From the demographic data, it is known that the majority of the respondents are aged between 20 and 30 years old, have completed a bachelor’s degree, are employed in permanent jobs, earn less than five million Indonesian Rupiah, reside outside Jakarta Metropolitan Area, i.e., Jakarta-Bogor-Depok-Bekasi (Jabodetabek), and have opinions related to the COVID-19 pandemic that affects their financial decision-making.

The attitude construct describes the respondents’ attitudes towards the agreement items given in the survey. There are four statements that are considered to represent the attitude construct. The survey results obtained for these four questions are presented in Figure 2. When looking at each question, it is found that for the attitude construct, ATT3 is the most agreed statement by the respondents, which is ‘I like PV Rooftop because it is environmentally friendly’.

The environmental concern construct describes the respondents’ concern for environmental issues, such as the agreement items given in the survey. There are four statements that are considered to represent the environmental concern construct. The survey results obtained for these four questions are presented in Figure 3. When looking at each question, it is found that for the environmental concern construct, EC3 is the most agreed statement by the respondents, which is ‘In my opinion, every individual has a responsibility to protect the environment.

The subjective norm construct describes the social influence of the respondents with the agreement items provided in the survey. There are four statements considered to represent the subjective norm construct, namely statements SN1 to SN4. The survey results obtained for these four questions are shown in Figure 4. When looking at each question individually, it can be observed that for the subjective norm construct, SN1, SN3, and SN4 have almost the same value. These three constructs are the statements most agreed upon by the respondents, namely, “I think people around me believe that I should use PV Rooftop in the near future.”, “I feel that if I buy PV Rooftop, people around me will also buy PV Rooftop”, and “I feel that I will use PV Rooftop if my neighbor uses it”.

The perceived behavioral control construct describes the behavioral control of the respondents towards an action (how easy or difficult it is to do something) with the agreement items provided in the survey. There are four statements considered to represent the perceived behavioral control construct, namely statements PBC1 to PBC4. The survey results obtained for these four questions are shown in Figure 5. When looking at each question individually, it can be observed that for the perceived behavioral control construct, PBC1 is the statement most agreed upon by the respondents, which is “I think the price is an important factor for me when deciding to buy PV Rooftop”.

The personal norm construct describes the personal norms of the respondents towards the agreement items provided in the survey. There are three statements considered to represent the personal norm construct, namely statements PN1 to PN3. The survey results obtained for these three questions are shown in Figure 6. When looking at each question individually, it can be observed that for the personal norm construct, PN3 is the statement most agreed upon by the respondents, which is “I feel obligated to consider the environmental consequences of using generators that utilize fossil fuels”.

The regulation construct describes the respondents’ views on the items of agreement with the regulations provided in the survey. There are three statements considered to represent the regulation construct, namely statements RG1 to RG3. The survey results obtained for these three questions are shown in Figure 7. When looking at each question individually, it can be observed that for the regulation construct, RG1 is the statement most agreed upon by the respondents, which is “I think the availability of installment packages, promotions, or discounts will increase interest in buying PV Rooftop”.

The construct of purchase intention is used to describe the respondents’ perceptions of agreement with the regulations provided in the survey. For the regulation construct, seven statements were identified as representative. These statements are labeled INT1 through INT7. The survey results for these seven questions are shown in Figure 8. When analyzing each statement individually, it was found that for the purchase intention construct, INT7 was the statement most agreed upon by the respondents: “I feel more comfortable buying PLTS from PLN than from other companies”.

Validity testing was performed on 50 randomly selected samples. For the validity test with a sample size of 50, the reference correlation coefficient used for validity is 0.2353. The test results (highlighted in red) indicate that all questionnaire items have correlation values greater than the reference value, demonstrating that the questionnaire used for data collection are valid. Reliability testing was conducted on 50 randomly selected samples. The basis for determining the reliability of a questionnaire is to look at the Cronbach’s alpha value resulting from the calculation. If the Cronbach’s alpha value is greater than 0.6, the questionnaire is considered reliable. Conversely, if the Cronbach’s alpha value is less than 0.6, the questionnaire is considered unreliable. The questionnaire results are deemed reliable, as the calculated Cronbach’s alpha value is 0.992.

Once it was established that this research instrument (the survey questionnaire) had valid and reliable testing results, the next step was to conduct an analysis of customer behavior modeling using multiple linear regression. To apply the multiple linear regression model, there are several prerequisites that must be met, including the normal distribution of residual data, the absence of collinearity, and the absence of heteroscedasticity in the data. To determine these prerequisites, a series of tests were conducted as follows:

3.2. Residual Normality Test Result

The normality test of residuals was conducted on 602 out of 686 respondents. This was carried out because 82 data points were eliminated due to indiscriminate questionnaire completion (44 individuals) and the presence of outlier data (38 individuals). The tendency toward indiscriminate completion was shown by the standard deviation value between the question items being zero. Meanwhile, the occurrence of outlier data were indicated by the normality analysis of residuals.

Multiple linear regression analysis modeling was conducted for two respondent groups: those with income below five million rupiahs and those with income above five million rupiahs. Respondent grouping based on income was chosen because individual survey results on the perceived behavior control (PBC) construct showed that price was the most important factor. In other words, financial factors were the biggest consideration in the decision-making process for purchasing rooftop solar panels, including respondent income.

For respondents with income below five million rupiahs, the Kolmogorov–Smirnov method resulted in a test value of 0.055, as shown in

Table 1. Residual normality test results for respondents with incomes lower than five million rupiahs.

Test of Normality
	Kolmogorov–Smirnov a			Shapiro-Wilk
	Statistic	df	Sig.	Statistic	df	Sig.
Standardized Residual	0.052	292	0.055	0.988	292	0.014

^a. Lilliefors Significance Correction.

. The significance of the Kolmogorov–Smirnov method calculation was greater than 0.05, indicating that the null hypothesis of normality of the residual data distribution could not be rejected. Therefore, it can be concluded that the normality test of residuals was met.

Subsequently, a normality test was conducted for respondents with an income of more than five million rupiahs. The Kolmogorov–Smirnov test were used to analyze the data, resulting in a value of 0.07. The significance value obtained from the Kolmogorov–Smirnov test was greater than 0.05, indicating that the null hypothesis, which states that the residual data are normally distributed, cannot be rejected. Thus, it can be concluded that the normality test for the residuals is satisfied.

The results of the normality test for the residuals of respondents with incomes less than five million rupiahs and more than five million rupiahs showed that the residuals were distributed following a normal distribution pattern. Therefore, the next test, which is the collinearity test, can be conducted.

3.3. Collinearity Test Results

The multicollinearity test is conducted to examine whether there is a high correlation among independent variables, and then the relationship between the independent variables and the dependent variable becomes disrupted. The results of the collinearity test on the variables ATT, EC, PBC, SN, PN, and RG show that the variable inflation factor (VIF) values are less than 4. Variance inflation factors (VIF) < 5 indicate that there is no collinearity relationship between the independent variables, so the collinearity test is met for both respondents with income less than five million rupiahs and those with income greater than five million rupiahs. After the collinearity test for each independent variable is met, the next step is to conduct a heteroscedasticity test.

3.4. Heteroscedasticity Test Result

The heteroscedasticity test is used to examine whether there is inequality in the variance of residuals from one observation to another. A multiple linear regression model that meets the requirements is one that has equal variances of residuals from one observation to another, or what is called homoscedasticity. Based on the heteroscedasticity test, it was found that the significance value of the linear regression of the variables against the absolute residuals was greater than 0.05. This indicates that there are no heteroscedasticity in the data for both respondents with income of less than five million rupiahs and those with income of more than five million rupiahs.

From the results of the tests for normality of residuals, multicollinearity, and heteroscedasticity, it can be concluded that all the tests meet the requirements for forming a multiple linear regression model, both for respondents with income less than five million rupiahs and those with income more than five million rupiahs. Subsequently, multiple linear regression modeling was carried out for each group of respondents (those with incomes less than and more than five million rupiahs).

3.5. The Result of Multiple Linear Regression Analysis for Interest in Purchasing Solar PV

Multiple linear regression was conducted to examine the influence of the independent variables, namely attitude, social norms, personal norms, perceived behavioral control, regulation, and environmental concern, on the intention to purchase solar panels. The results of the multiple linear regression modeling for respondents with an income of less than or more than five million rupiahs are presented in

Table 2. Multiple linear regression modeling results for respondents with an income of less than five million Indonesian rupiah.

Respondents with an Income of Less Than Five Million Indonesian Rupiah
Model	Unstandardized Coefficients		Standardized Coefficients	1	Sig.
	B	Std. Error	Beta
1 (Constant)	0.172	0.345		0.499	0.618
ATT	0.156	0.057	0.130	2.750	0.006
EC	−0.185	0.060	−0.110	−3.085	0.002
SN	0.204	0.035	0.234	5.779	0.000
PBC	0.084	0.048	0.070	1.759	0.080
PN	0.348	0.051	0.342	6.863	0.000
RG	0.308	0.047	0.296	6.548	0.000
Respondents with an Income of More Than Five Million Indonesian Rupiah
Model	Unstandardized Coefficients		Standardized Coefficients	1	Sig.
	B	Std. Error	Beta
1 (Constant)	−0.269	0.350		−0.769	0.442
ATT	0.071	0.052	0.054	1.375	0.170
EC	−0.056	0.060	−0.033	−0.943	0.346
SN	0.245	0.037	0.272	6.698	0.000
PBC	0.047	0.044	0.036	1.063	0.289
PN	0.415	0.042	0.422	9.833	0.000
RG	0.261	0.041	0.255	6.329	0.000

.

For respondents with income less than five million rupiahs, the significance value for all variables except PBC is t < 0.05, indicating that variables other than PBC have a significant effect but have the largest regression coefficients on Personal Norm, Regulation, and Subjective Norm. Thus, the multiple linear regression equation for respondents with incomes less than five million rupiahs is given by Equation (1).

INT = 0.342PN + 0.296RG + 0.234SN + 0.130ATT − 0.110EC

(1)

Meanwhile, for respondents with incomes greater than five million rupiahs, the significance value for all variables PN, SN, and RG is t < 0.05, indicating that these variables have a significant effect with the largest regression coefficients on the Personal Norm, Subjective Norm, and Regulation. Thus, the multiple linear regression equation for respondents with incomes greater than five million rupiahs is given by Equation (2).

INT = 0.415PN + 0.255RG + 0.272SN

(2)

The multiple linear regression model in Equation (1) has an R-Square value of 0.740. This indicates that the proportion of the variance of the dependent variable explained by the independent variables is 74%. This means that variables outside the model have a proportional influence of 26%. In addition, the probability value of the F test (sig.) is 0.000, which is smaller than the significance level of 0.05, thus indicating that the estimated multiple linear regression model is fit for use.

A similar situation also occurred among respondents with a monthly income exceeding five million rupiahs. The multiple linear regression model in Equation (2) has an R-Square value of 0.728. This indicates that the proportion of the independent variables’ influence on the dependent variable is 72.8%. In other words, variables outside the model have a proportional influence of 27.2%. Additionally, the calculated F probability value (sig.) is 0.001, which is smaller than the significance of 0.05, indicating that the estimated linear regression model is appropriate to use.

3.6. The Mapping of Interest for New Products

After obtaining customer behavior data for the rooftop solar power products, the data related to customers’ needs for new business ideas that can be offered by PLN is presented next. In this case, there are seven new business ideas offered that the respondents’ opinions are sought regarding. These seven new business ideas are as follows: combining internet with electricity credit services; transitioning from gasoline-powered vehicles to electric vehicles; transitioning from gas stoves to electric stoves; transitioning from water heating devices to electric devices; home electrical repair services; micro, small, and medium-sized business loan facilities; and consultation services for the development of smart homes. The survey results to determine respondents’ opinions about the needed new products are presented in Figure 9.

3.7. Discussion

The classic assumption test consisting of residual normality testing, collinearity testing, and heteroscedasticity testing on groups of respondents with income below and above five million rupiahs has been conducted, and all requirements have been met, enabling multiple linear regression analysis to be performed.

Among respondents with income below five million rupiahs, the variables with the largest regression coefficients are personal norm (PN), regulation (RG), and subjective norm (SN), respectively. Meanwhile, among respondents with incomes above five million rupiahs, the variables with the largest regression coefficients are personal norm (PN), subjective norm (SN), and regulation (RG), respectively. This shows that PN is the most significant factor among all respondents.

These three variables indicate that the character of society in responding to rooftop solar panel products tends to adhere to the personal norm principle. This is important to consider because communities with strong personal norm characteristics need specific marketing techniques to change their personal norms. Marketing techniques for communities with strong personal norms can be carried out by building a good image of the product. In addition, communities with strong personal norms need to have personal experience before deciding whether to accept or reject a product.

After considering the influence of personal norms, this study finds that regulatory and social norms also significantly affect public interest in purchasing rooftop solar panel products. The implementation of policies such as discounts or promotions and the possibility of direct electricity trading between individuals without involving the electricity utility company can boost public enthusiasm for these products. Should these regulations be enacted, they may pose a challenge to the electricity utility company if it does not engage in the rooftop solar panel market. The company could face dual threats: missing out on the rooftop solar panel market and dealing with surplus energy as more individuals start generating their own power using these products.

Alternatively, the community perceives that social factors significantly influence their interest in purchasing PV Rooftop systems. Individuals are often motivated by their surroundings to consider PV Rooftop, with societal tendencies like the “keeping up with the Joneses” effect further amplifying this interest. This scenario offers a unique marketing avenue for PV Rooftop systems, especially by installing them in highly visible parts of houses to inspire neighbors to adopt similar solutions. This approach could foster a competitive spirit among neighbors, thereby enhancing the sales potential of PV Rooftop systems. Such a marketing strategy may be particularly effective in residential communities where houses are situated close to each other, enabling residents to easily notice the home enhancements of their neighbors.

Furthermore, a detailed examination of the responses to statement INT7 reveals a higher level of trust among respondents in purchasing rooftop solar PV systems from PLN. However, it is important to recognize that, according to statement PBC1, pricing is a critical factor in these purchasing decisions. The comparative ranking of responses shows that PBC1 scores higher than INT7. This suggests that while respondents are inclined to purchase rooftop solar panels from PLN, their decision is price-sensitive. If PLNs pricing is not significantly higher, they prefer PLN, but they are open to choosing other vendors offering substantially lower prices. This presents a potential challenge for PLN, especially if competitors introduce rooftop solar PV at much lower prices. Hence, continuous market surveillance is essential for PLN to track the lowest possible prices for rooftop solar panels, ensuring their pricing is competitive and not substantially higher than the market’s lowest.

On the other hand, mapping the community’s needs for new product ideas has already been conducted. Based on the analysis of new product ideas, the community’s most pressing needs for new products include electrical repair services, smart home consulting, and microloans for small and medium-sized enterprises. Conversely, offerings such as internet packages and the conversion of non-electric items to electric versions (like electric vehicles and electric stoves) are not as favored by the public. These findings suggest that PLN has opportunities to expand into businesses that are in high demand within the community. However, if PLN plans to enter the market for converting non-electric equipment to electric versions, such as electric vehicles and stoves, a push may be necessary to motivate the community to adopt these products. This push could come in the form of government regulations promoting the switch from non-electric to electric equipment, given the natural reluctance of the community to transition to such electric appliances.

4. Conclusions

Consumer behavior is a key factor affecting interest in buying rooftop PV. The influence is shaped by various regression coefficients, including those that are significant and those that are not. Specifically, variables like personal norm (PN), subjective or social norm (SN), and regulation (RG) are significantly impactful. Additionally, the market’s receptiveness to new product ideas not yet introduced by the company shows variation. Of these concepts, services related to electrical repairs, smart home consultations, and microcredit facilities are the most in demand.

Studying customer behavior is instrumental in assessing potential opportunities and challenges for a company venturing into new business areas. For the company to successfully realize new business concepts demanded by the community, a comprehensive analysis of customer behavior is essential. In marketing rooftop solar photovoltaic (PV) systems effectively, the electricity company should consider elements like personal norm (PN), subjective or social norm (SN), and regulation (RG). Additionally, incorporating one of the marketing strategies discussed earlier could enhance this effort.

To enhance the adoption of rooftop PV systems, our research suggests several key strategies: Awareness campaigns to educate the public on the benefits of PV systems; community engagement to leverage social norms; regulatory incentives like subsidies and tax rebates; financial assistance programs to address cost barriers; tailored marketing to highlight PV system benefits; and sharing success stories to build trust. These combined efforts aim to positively influence personal and subjective norms, regulatory perceptions, and attitudes, thereby boosting rooftop PV adoption and supporting renewable energy initiatives.

The results of this study clearly indicate promising opportunities for the commercialization of solar PV technology in Indonesia. To maximize the potential in this area, several lines of inquiry could be explored in future research. This includes investigating the customers’ willingness to pay, considering their income levels, and exploring the relationship between other products offered by PLN using similar research approaches.