1. Introduction
Solar is a popular source of renewable energy in the world as it is abundant, clean, reliable, and reduces greenhouse gas emissions [
1]. Households are considered an increasingly important target market for solar PV deployment around the world as they consume more energy and are considered small-scale energy generators [
2,
3]. Many studies revealed that households’ willingness to install solar PV systems depends on the financial rebates given by governments, feed-in-tariff (FiT) benefits, and long-term financial benefits of energy consumption [
2,
4,
5,
6,
7]. In addition to obvious benefits such as lowering energy bills, several economic, social, personal, and psychological determinants impact the solar PV investment decision [
8,
9,
10,
11]. Findings revealed that not only socioeconomic factors but also health, environment, and demographic indicators contribute to clean energy adoption trends [
12,
13]. Further, another study found that social influence has a significant impact on intention to install solar PV [
14]. Hence, it is essential to investigate the heterogeneous behaviour of households in a holistic manner.
Most of the research on solar PV intention utilised behaviour-intention models or the diffusion of innovation (DOI) model to evaluate households’ intention to install solar PV systems [
10,
15]. A systematic review on solar PV adoption behaviour revealed that among many theories that explain the complexity of decision-making, the top-ranked are DOI and the theory of planned behaviour [
2]. Solar PV adoption was extensively examined through various perspectives, including factors affecting adoption [
6,
16], expected financial gain [
17], barriers to adoption [
18], and peer influence on adoption decisions [
19]. However, little attention has been paid to understanding consumer characteristics, especially the psychological determinants that affect their decision-making. These psychological factors include attitude, subjective norms, perceived behavioural control, values, beliefs, norms, etc. [
20]. A few studies attempted to uncover the psychological determinants through the lenses of environmental values [
10,
21]. For example, Wolske et al. (2017) [
10] used biospheric altruism, social altruism, self-interest, traditional values, and openness to change to measure the influence of values on residential solar PV installation, while Schelly focused on the environmental concern of residents on their solar PV adoption. Even though a few studies used psychological factors on solar adoption, there is more room to investigate this phenomenon. Hence, this lack of understanding of psychological perspective represents a significant gap in the solar PV literature, and it is imperative to address this gap through multiple theories in a more holistic manner.
In this study, we address this gap by integrating some well-known behavioural theories to investigate the psychological determinants of households’ willingness to install solar PV systems, as it gives a more comprehensive understanding of psychological determinants influencing their behaviour. The study includes three prominent theories from the environment psychological domain: values orientation theory (VOT); value, beliefs, and norms theory (VBN); and the theory of planned behaviour (TPB) to study this phenomenon.
VOT is utilised to scrutinise households’ future-oriented behaviour, a distinctive psychological factor influencing consumer decision-making. While Future Orientation (FO) has been employed in other pro-environmental studies, its application in the context of solar energy behaviour remains unexplored. Households invest in solar PV systems with the anticipation of significant long-term energy cost reductions. Additionally, property owners may install PV systems to enhance their investment returns. Therefore, understanding the role of FO in solar energy research becomes crucial. Thus, this research stands as a pioneering endeavour, being among the initial studies to employ FO in the solar PV domain.
Furthermore, given that solar energy is a renewable and environmentally friendly source, it is pertinent to examine households’ intentions to invest in it using theories related to pro-environmental behaviour. VBN is employed to gauge the environmental values of households and their readiness to install solar PV systems. As solar PV systems are expensive, it requires more household involvement in decision-making before installing them. Hence, TPB is applied to assess the purchase determinants, encompassing positive attitudes, social pressures, and perceived ease or difficulty in adopting the behaviour.
Therefore, this paper aims to explore the psychological factors influencing households’ willingness to install solar PV systems through an integrated theoretical model. By adopting an integrative approach, we seek to provide a more comprehensive perspective on examining households’ willingness to adopt solar PV systems.
The remainder of the paper is organised as follows:
Section 2 discusses how FO, environmental values, and purchase determinants variables explain the willingness to install solar PV systems through the three theories mentioned above.
Section 3 presents the integrated theoretical model, and
Section 4 presents methodology to test the model.
Section 5 presents results, and
Section 6 contains the discussion.
Section 7 discusses the implications, and
Section 8 presents the limitations of the study. Finally,
Section 9 presents the conclusion of the study.
3. Conceptual Framework
The conceptual model is developed based on the above-discussed three theories: theory of planned behaviour, value, beliefs, and norm theory, and values orientation theory. The dependent variable of the proposed model is the willingness to install a solar PV system; thus, it measures the homeowner’s intention to install solar PV systems. The proposed model consists of personal values (biospheric, altruistic, and egoistic values) and future orientation as the independent variables. Schwartz [
82] defined values as “desirable goals, varying in importance, that serve as the guiding principles in people’s life” (p. 21). Therefore, values can influence psychological factors such as beliefs, attitude, norms, and behaviour simultaneously [
83]. FO, on the other hand, is a time-based construct embedded in both a social–cultural and personal–psychological context [
44]. Therefore, personal values and FO have their roots in the psychological domain. Thus, these two perspectives can be better at predicting the psychological viewpoint of households’ willingness to install solar PV systems. Personal values, on the one hand, will predict how households are likely to prioritise various values in different situations, and on the other hand, FO will determine households’ future-oriented behaviour in terms of planning and investing by delaying their present satisfaction. The unique contribution of this study is the investigation of the FO, as no other study examined FO in the solar PV domain. Further, values have been included in the model to minimise the gap between motivational factors and behavioural intention, as suggested by Jager [
84].
Purchase determinant variables, namely attitude towards solar PV systems, subjective norms, and perceived behavioural control, were derived from TPB and included in the model. As values are deep-rooted end-states of people, they may affect beliefs, attitudes, norms, intention, and behaviour in different ways [
83,
85]. Hence, the purchase determinant variables were included as the mediating variables in the proposed conceptual model. The proposed conceptual model is depicted in
Figure 1.
4. Methodology
The conceptual model was tested using an online survey method that examined the relationship between independent and dependent variables. The study was conducted in Australia, which has been identified as the highest average solar radiation per square metre of any continent in the world [
86]. The population of this study is the general public in Australia who are age 18 and above, a decision-maker of the household and owns or has a mortgage of the free-standing house. The sample size is 179 respondents representing all states and territories of Australia and who have not installed solar PV systems on their rooftop. Sample size can be determined depending on the statistical technique selected by the researcher [
87]. The analytical technique applied in this study is PLS path modelling. Many studies confirm that PLS supports a small sample size [
88,
89,
90]. Because accessing data was intricate, the study employed a limited sample size, with a focus on leveraging the primary analytical method of PLS-SEM. According to Hair et al. [
91], the minimum ratio of observations to variables is 5:1. It is accepted that a sample size between 30 and 500 is appropriate to undertake any statistical analysis [
92].
In this study, a purposive sampling method was adopted to select respondents since it would enable us to choose a suitable sample that would represent the characteristics of the population. The purposive sampling technique is used when the researcher needs judgement to select cases that will best enable answers to the research questions and to meet research objectives [
87]. According to the study, it is imperative to select respondents aged 18 and above who own or mortgage a free-standing house in Australia and have not installed solar PV systems. The sample was selected from six main states and two territories of Australia: Western Australia, New South Wales, Queensland, Victoria, South Australia, Tasmania, Northern Territory, and Australian Capital Territory.
The data were collected using Qualtrics research company in Australia. Initially, we collected data from 195 respondents. After collecting data, screening was carried out. No missing data were identified during the screening procedure, as the survey instrument has enabled the forced response to each question. There were six univariate outliers, and ten multivariate outliers were identified during the screening process. After deleting the outliers, the effective sample size of the main study was 179 respondents.
The survey consists of five sections.
Section 1 contains individual consequences relating to the purchase of solar panels. These factors are attitude towards solar panels, subjective norms, and perceived behavioural control.
Section 2 explains value orientation by including biospheric, altruistic, and egoistic values.
Section 3 describes future orientation behaviour. Household’s willingness to install solar panels is listed in
Section 4. Respondents are requested to provide information on their intention to install solar panels. Finally,
Section 5 deals with personal information relating to households. This contains information such as gender, age, marital status, level of education, number of dependent children, average monthly electricity bill, an annual household income before tax, and state/territory where they live in Australia. The constructs that were used in the survey were developed based on the measurements in previous studies. The questionnaire adopts seven-point Likert scales to understand the opinion of respondents on selective statements ranging from 1 (strongly disagree) to 7 (strongly agree).
Using clear, concise questions reduces ambiguity and limits biassed responses, while pilot testing helps identify and correct issues such as unclear instructions or biases, both of which are essential for minimising common method variance (CMV) and enhancing the accuracy of the final measurement instrument [
93]. This ensures that the final instrument more accurately measures the intended constructs, reducing the likelihood of CMV by enhancing the reliability and validity of the data collection process. Therefore, the researchers used the validated scales from previous studies and conducted a pilot study to test the validity and reliability of the survey instrument.
The conceptual model includes eight constructs, each measured using items derived from validated scales. The researchers assessed the validity and reliability of these constructs, with face validity used to check validity and Cronbach’s alpha employed to evaluate reliability. Therefore, all the constructs with their measurement items, reliability, and sources of items are presented in
Table 1.
The first stage of data analysis was carried out using SPSS version 26, which involved data screening, cleaning, testing the reliability of the constructs, and descriptive data analysis. The research model was analysed by the partial least squares structural equation modelling (PLS-SEM) technique using Smart PLS version 3 software. PLS-SEM supports the small sample size compared with CB-SEM [
100]. Due to the complexity of accessing data, this study employed 179 respondents to evaluate the model. Therefore, PLS-SEM is selected as it facilitates the small sample size and has a higher level of statistical power to assess the structural model compared to CB-SEM [
101]. Further, the study used PLS-SEM, which is a nonparametric statistical method to analyse data, and it does not require satisfying the normal distribution of data to run the analysis [
100].
6. Discussion
This study investigated the drivers of household willingness to install solar PV systems, especially considering households’ personal values and future orientation. The study contributed to the body of research developing a new conceptual model integrating three prominent theories in the environmental psychology domain: values orientation theory, value–beliefs and norms theory, and theory of planned behaviour. The newly developed conceptual model provides a holistic view of household intention to invest in solar PV systems, and it was empirically tested using a survey of households in Australia. The PLS-SEM results suggested a well-fitted model explaining 48.5% of willingness to install solar PV systems and demonstrated that out of sixteen hypotheses, eleven hypotheses were supported with the findings.
The results of the data analysis indicated that FO is a significant construct that has a positive influence on purchase determinant variables and willingness to install solar PV systems. The findings revealed that FO with attitude towards solar PV systems, subjective norms, perceived behavioural control, and willingness to install solar PV systems were positive and significant. The above findings support the extant literature on future orientation and environmentally sustainable behaviour [
46,
47,
48]. Even though FO is a strong construct in pro-environmental studies, its appearance in the solar PV domain has been ignored. Considering the household decision-making practices, this study included FO to provide a better evaluation of household investment decisions on solar PV systems compared to the high installation cost versus the high return on investment. Hence, this study is among the first of its kind to apply FO in the solar PV domain and validate the relationships. Therefore, the study provides a novel academic and practical contribution to the solar PV research domain.
The results revealed that all three values were insignificant with attitude towards solar PV systems. It was indicated that biospheric values (β = 0.038, t = 0.367,
p < 0.1), altruistic values (β = 0.035, t = 0.429,
p < 0.1), and egoistic values (β = 0.077, t = 1.202,
p < 0.1) were not significant. However, the extisting research highlighted that biospheric and altruistic values are more likely to positively influence pro-environmental attitudes than egoistic values [
66,
105]. Individuals with stronger egoistic values engaged in pro-environmental behaviour when their perceived benefits exceeded the perceived cost [
74]. It is surprising that the findings of the study contradict the prevailing literature. One reason for this confusion is the nature of the product. Generally, solar PV systems are expensive, durable products that require a high initial investment to set up. Considering the high investment cost versus the more extended return on investment, most households in Australia might not have a favourable attitude towards solar PV installation. [
30] mentioned that perceived environmental benefits had a weaker contribution than the individual motives relating to the attitude to investing in solar PV systems. The authors further mentioned that homeowners’ attitude towards PV systems depends on their social status, energy independence, financial profits, and lesser cost of installing PV systems.
It is interesting to note that altruistic values (β = 0.172, t = 1.704,
p < 0.1) and egoistic values (β = 0.256, t = 3.160,
p < 0.01) have a positive and significant relationship with subjective norms. This suggests that households with stronger altruistic values and self-interest are more inclined to the social pressure from peers, neighbours, and other opinion leaders to install solar PV systems. Therefore, the finding of the study relates to the existing literature claiming that altruistic values are positively associated with pro-environmental behaviour [
106]. Steg et al. [
107] found that stronger egoistic values were less likely to have a positive evaluation of renewable energy sources as they are expensive and intermittent. Therefore, the findings supported the existing knowledge insisting that the installation of solar PV systems provides more financial benefits in the long term; thus, households tend to develop positive social norms relating to solar. Relating to the biospheric values, the findings have confirmed that it was not significant (β = −0.147, t = 1.537,
p < 0.1) and have a negative relationship with subjective norms relating to the willingness to install solar PV systems. Current research indicates that biospheric values are more predictive of subjective norms than altruistic and egoistic values [
60]. However, the findings of the study contradict the prevailing literature. One possible reason for this confusion may be that the respondents of the sample might not possess strong biospheric values and norms relating to solar PV systems.
In this study, perceived behavioural control consists of the financial incentives provided by the state/federal government and households’ financial capability. The findings of the study have demonstrated that biospheric values had a significant positive relationship with perceived behavioural control (β = 0.189, t = 1.755,
p < 0.01). This implies that households with stronger biospheric values are more likely to consider the financial incentives given by the government and their perceived ability to install solar PV systems. Several studies have suggested that people with strong adherence to biospheric values engage in pro-environmental purchase behaviour irrespective of perceived barriers [
13,
65]. In contrast, altruistic values showed a significant negative impact on perceived behavioural control (β = −0.238, t = 2.057,
p < 0.05). The results suggested that households concerned about the welfare of other people in the community neglect the perceived barriers of obtaining finance to install solar PV systems. In line with extant literature, studies have demonstrated that social altruistic values show a willingness to engage in pro-environmental behaviour regardless of the perceived barriers [
72]. The relationship between egoistic values and perceived behavioural control was significant and positive (β = 0.176, t = 2.530,
p < 0.05). It implies that households that focus on maximising personal benefits tend to rely on their financial capability, or the incentives given by the state/federal government. The findings are in line with the existing literature that claim that egoistic values positively influenced external regulations and pro-environmental behaviour [
78,
108].
The findings revealed that attitude towards solar PV systems had a significant and positive influence on the willingness to install solar PV systems (β = 0.298, t = 2.635,
p < 0.01). This denotes that households with a positive attitude towards solar PV systems demonstrate a strong willingness to install solar PV systems. The finding complies with the plethora of pro-environmental behaviour studies [
54,
67,
69,
81,
109].
The results have revealed that subjective norms had a negative and insignificant relationship with willingness to install solar PV systems (β = −0.041, t = 0.568,
p < 0.1). The finding implied that social pressure from friends, neighbours, and other opinion leaders does not influence households’ willingness to install solar PV systems. In line with the above finding, some studies demonstrated that subjective norms are insignificant in environmentally sustainable behaviour. For example, organic food purchasing behaviour [
110,
111], purchase of environmentally friendly products in Greece [
112], and plastic bag usage [
113]. However, the above finding contradicts most prior research on pro-environmental behaviour, highlighting a positive relationship between subjective norms and pro-environmental intention [
36,
54,
114,
115]. One possible reason for this ambiguity may be that in Australia, the social norms have not been developed yet regarding solar PV installation.
The results of the study indicated that perceived behavioural control (β = 0.421, t = 9.531,
p < 0.01) has a positive and significant influence on willingness to install solar PV systems. It suggests that households who are more concerned with government solar rebate programmes and their financial capability are positively influenced by their willingness to install solar PV systems. The finding of the study complies with the prevailing literature on the intention to install solar PV systems [
37,
39,
40,
116].
9. Conclusions
The study investigates households’ willingness to install solar photovoltaic systems, focusing on psychological determinants, particularly values and future orientation. Drawing on environmental psychology theories, the study develops a comprehensive model incorporating the theories of planned behaviour, value–beliefs, norms theory, and values orientation theory. Biospheric, altruistic, and egoistic values, along with FO, are identified as key factors influencing households’ decisions to invest in solar PV. The survey, conducted in Australia, employs structured questionnaires and the PLS-SEM technique for data analysis. Out of sixteen hypotheses, eleven are supported, revealing that 48% of the variance in households’ willingness to install solar PV is explained by the model’s variables. Notably, FO emerges as the most influential factor, while altruistic and egoistic values impact subjective norms and perceived behavioural control. Surprisingly, biospheric values exhibit no significant relationship with attitude or subjective norms. The study underscores the importance of psychological determinants in shaping households’ attitudes and behaviours towards solar PV adoption, offering practical insights for policymakers and marketers in the renewable energy sector.