Impact of Households’ Future Orientation and Values on Their Willingness to Install Solar Photovoltaic Systems

Abstract

Solar energy is increasing in popularity as a renewable energy source, which reduces greenhouse gas emissions. Even though many governments promote solar energy by giving various incentives, its adoption rate in households is slow. Psychological factors have been relatively overlooked in solar adoption, despite the importance of social and economic factors. Therefore, the purpose of this study is to investigate how psychological determinants impact households’ willingness to install solar photovoltaic (PV) systems. This study focusses on the future orientation and personal values (biospheric, altruistic, and egoistic values) of households’ and their willingness to install solar PV systems. The research draws from three environmental psychology theories: values orientation theory, value beliefs and norms theory, and the theory of planned behaviour to construct an integrative theoretical model. A survey involving 179 respondents in Australia was conducted and analysed applying the PLS-SEM technique. Findings revealed that future orientation and values are significant predictors of household willingness to install solar PV systems. Further, findings showed that attitude and perceived behavioural control play a significant role in installing solar. The findings will assist policymakers and solar companies in developing lucrative policies and marketing strategies to promote solar PV systems among households.

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.

2. Literature Review

2.1. The Willingness to Install Solar PV Systems

Solar photovoltaic systems are defined as “a technology used to convert sunlight into electricity directly without any interface for conversion” [22]. Solar PV systems offer several advantages: they generate clean, renewable energy, reducing carbon emissions and dependence on fossil fuels [1]. They lower electricity bills and can provide energy independence, especially in remote areas [23]. Solar panels have low maintenance costs and can increase property value [24]. However, their high initial costs, dependence on the availability of sunlight, and requirements for energy storage during nighttime use are some of their disadvantages [16].

Numerous studies have delved into the factors influencing households’ willingness to adopt solar photovoltaic (PV) systems, reflecting a growing interest in renewable energy practices [23,25,26]. While the government’s primary focus for enhancing PV adoption has been on providing economic incentives, scholarly investigations suggest that a range of factors contribute to the adoption of residential solar energy systems. Consequently, this study seeks to delve into the impact of households’ environmental values, future-oriented behaviour, and purchase determinants such as attitude, subjective norms, and perceived behavioural control on their willingness to install solar PV systems.

2.2. Theory of Planned Behaviour

Solar is a relatively expensive, durable consumer product that requires high involvement from a purchaser. Therefore, some purchase determinant factors influence households’ willingness to invest in solar PV systems. Thus, TPB offers a useful framework to identify complexities in solar PV investment behaviour. The theory of planned behaviour was proposed by Ajzen in 1991 as a rational choice model in the psychological domain, which is a useful conceptual model to identify complexities in human social behaviour. The key assumption in this model is that behaviour is directly determined by the intention to perform the behaviour. The intention is shaped by the combination of three constructs: (1) the attitude towards the behaviour, (2) subjective norms, and (3) perceived behavioural control.

Attitudes are held with respect to some aspect of the individual’s world, such as another person, a physical object, a behaviour, or a policy [27]. Research indicates that a favourable attitude towards PV systems strongly predicts the intention to purchase [28,29,30]. Subjective norms are the perceived expectations of other people or the social pressure of which behavioural alternatives should be performed [31]. Subjective norms, which involve the social pressures or expectations from others, also play a significant role [32,33]. Studies suggest that recommendations from peers, neighbours, or community leaders encourage people to install PV systems, with significant peer effects observed in Sweden, Japan, and Australia [34,35,36]. However, a contradicting finding said that subjective norms had no effect on intention to install solar PV systems in Nordic countries [37]. Perceived behavioural control refers to people’s perception of the ease or difficulty of performing the behaviour. Solar PV installation involves factors like the knowledge of the consumer, a suitable roof and atmosphere, availability of sunlight, infrastructure, and financial capability. These factors are identified as the contextual factors to adopt solar PV systems [33]. Government policy support and financial incentives, such as feed-in tariff schemes, are identified as significant motivators for PV adoption [38,39,40,41]. However, the findings of [30] reveal that there is a weak relationship between perceived behavioural control and purchase intention.

2.3. Values Orientation Theory (VOT)

Solar PV systems are relatively expensive, and the return on investment is high as it reduces the electricity cost in the long term. In this regard, households’ solar PV intention should be measured through the long-term benefits households obtain by installing solar panels. Therefore, we use future orientation derived from VOT to explain this phenomenon.

The values orientation theory was introduced by Kluckhohn and Strodtbeck in 1961 to understand cultural variations in human values. This theory identifies five core value orientations: human-nature, time, activity, social, and modality, which guide individual and societal behaviour [42]. So far, the values orientation theory has been tested in many cultures across the world [43].

Future Orientation

This study focused on the temporal orientation, which is relating to the time orientation, as the study wants to measure households’ future-oriented investment behaviour. According to Kluckhohn and Strodtbeck [34], temporal orientation is divided into three: past, present, and future. This study only focused on the future orientation (FO), which is a time-based construct that belongs to the social–cultural and personal–psychological context [44]. In a social–cultural context, FO is defined as the extent to which individuals are involved in future-oriented behaviour such as delaying gratification, investing in the future and planning [42]. People who have FO may choose actions that have significant future benefits, even if it involves time, cost, and a willingness to sacrifice comfort to obtain favourable benefits in the future [45]. For example, choosing a long-term saving scheme or contracting bank loans or life insurance policies predicts better financial gains in the future. Therefore, studying FO is essential to having a better understanding of households’ behaviour.

There is an extensive use of FO in environmentally sustainable behaviour [46,47,48]. Enzler et al. [49] revealed that environmental concern and future orientation were positively and strongly related to household electricity use. Yorkovsky and Zysberg [47] examined how future orientation and attitude mediate the association between locus of control and pro-environment behaviour. The findings supported that both FO and attitude mediated the relationship between locus of control and pro-environment behaviour.

An interesting study on time perspective and values on environmental attitude indicated that environmental preservation was positively correlated with FO, biospheric, and altruistic values [50]. Therefore, considering the above empirical studies, it is evident that FO is a significant construct in determining pro-environmental behaviour. It is important to look at the household solar PV investment decision through FO as solar is an expensive product and the return on investment is high as the cost of electricity is reduced drastically in the long term. To date, FO has not been tested in solar PV research; thus, it is a unique contribution to the existing solar literature. Drawing on the above discussion, the following hypotheses have been formulated.

H_1a: 

A household’s future orientation has a positive influence on their attitude towards solar PV systems.

H_2a: 

A household’s future orientation has a positive influence on their subjective norms associated with willingness to install solar PV systems.

H_3a: 

A household’s future orientation has a positive influence on their perceived behavioural control associated with willingness to install solar PV systems.

H4: 

A household’s future orientation has a positive influence on their willingness to install solar PV systems.

2.4. The Value–Belief–Norm Theory

The study explores the role of pro-environmental behaviour theories in understanding consumer behaviour towards adopting solar energy, a renewable and green energy source that reduces greenhouse gas emissions. Specifically, the study employs the VBN theory to explain households’ pro-environmental behaviour and their willingness to install solar PV systems. As we use TPB constructs in the model, values are a better complement with TPB [51]. As [52] stated, in line with an expectancy–value framework, the assumption is that one’s attitude towards a behaviour is influenced by their beliefs regarding the outcomes of the behaviour. Each belief is given a weight based on the subjective value of the corresponding consequence.

The VBN theory, developed by Stern in 2000, integrates value theory, norm activation theory, and the New Environmental Paradigm (NEP) into a causal chain that links personal values, beliefs, and norms to pro-environmental behaviour [53]. This chain consists of five variables: personal values, ecological worldview, awareness of consequences, ascription of responsibility, and personal norms [53]. The study focuses on personal values within the VBN model, particularly how these values influence households’ intentions to adopt solar PV systems. The ecological worldview is connected to three general value orientations: biospheric, altruistic, and egoistic values [53]. Biospheric values are concerned with the well-being of nature and the biosphere; altruistic values focus on the welfare of other humans; and egoistic values emphasise personal outcomes [54].

VBN theory has been extensively applied in many environmental studies, including conservation behaviour [55], sustainable travel mode choice in urban areas [56], smart energy systems [57], and intention to use renewable energy sources [58]. However, according to the literature, very little attention has been paid to personal values to explain households’ willingness to install solar PV systems. Only one study used VBN to examine solar PV adoption [10], while some studies provide evidence of environmental motives and other environmental values in solar PV adoption [21,59]. Solar energy is recognised as an environmentally friendly source, prompting individuals to contemplate investment in solar technology due to its positive environmental effects. Consequently, it is crucial to explore the potential influence of households’ overall value orientation on their inclination to adopt solar PV systems, given the perception of solar as a green energy source. Consequently, investigating the relationship between personal values and the willingness to install solar PV systems will enhance the existing body of literature.

2.4.1. Biospheric Values and Purchase Determinant Factors

Individuals who strongly endorse biospheric values are significantly related to environmentally conscious behaviour, as people like to see themselves as morally right [53,60]. Hence, they are more likely to develop positive beliefs and norms relating to environmental behaviour. Several studies showed that biospheric values significantly influence pro-environmental attitudes [61,62]. A study by Nguyen et al. [63] revealed that biospheric values enhance the attitude towards environmental protection in pro-environmental purchase behaviour of energy-efficient household equipment. The literature suggests that biospheric values are more predictive of personal norms than altruistic and egoistic values [60]. A study revealed that personal values, organisational climate, and subjective norms have a positive and significant relationship to knowledge-sharing behaviour [64]. Further, they mentioned that personal values and organisational climate were positively related to subjective norms. A consumer’s purchase intention is dependent on the perceived behavioural control or the extent of resources and opportunities available to the person. If a person has fewer resources, such as money, time, or knowledge, the lower will be the perceived behavioural control of this person [30]. However, people with strong adherence to biospheric values engage in pro-environmental purchase behaviour irrespective of the perceived barriers [65]. Similarly, Perlaviciute and Steg [66] mentioned that stronger biospheric values showed a more positive evaluation of the personal consequences of energy alternatives. Based on the above discussion, the following hypotheses were derived.

H_1b: 

Household’s biospheric values have a positive influence on their attitude towards solar PV systems.

H_2b: 

Household’s biospheric values have a positive influence on their subjective norms associated with willingness to install solar PV systems.

H_3b: 

Household’s biospheric values have a positive influence on their perceived behavioural control associated with willingness to install solar PV systems.

2.4.2. Altruistic Values and Purchase Determinant Factors

Several studies found that altruistic values have a positive influence on environmental attitudes [67,68,69]. Kim and Stepchenkova [70] found that tourists’ altruistic values positively impact their attitude towards eco-travel. Another study conducted in Australia on environmentally responsible clothing revealed that altruistic values have a significant influence on consumer attitude [71]. Thøgersen and Grunert-Beckmann [72] suggests that consumers with strong adherence to social altruistic values demonstrate willingness to engage in recycling activities regardless of the perceived personal cost. Further, it has been found that people with altruistic values display an important role in energy conservation behaviour with regard to their purchasing power and the national economy [73]. Informed by the forgoing discussion, the following hypotheses were derived.

H_1c: 

A household’s altruistic values have a positive influence on their attitude towards solar PV systems.

H_2c: 

A household’s altruistic values have a positive influence on their subjective norms associated with willingness to install solar PV systems.

H_3c: 

A household’s altruistic values have a positive influence on their perceived behavioural control associated with willingness to install solar PV systems.

2.4.3. Egoistic Values and Purchase Determinant Factors

De Groot [68] states that people with stronger egoistic values are more likely to engage in pro-environmental behaviour because of extrinsic factors such as personal outcomes. Individuals with strong egoistic values predominantly consider the cost and benefits of their environmental actions and engage in pro-environmental behaviour when perceived benefits exceed the perceived cost [74]. Some studies have demonstrated that egoistic values are positively associated with environmental behaviour [66]. A similar finding derived from a study on eco-friendly hotel stays showed that environmental attitude partially mediated the relationship of eco-friendly behaviour with egoistic and altruistic values [75]. Othman et al. [64] mentioned that personal values and organisational climate were positively related to subjective norms. It was stated that values do not have a direct relationship with environmental behaviour, and it is rather an indirect relationship via behaviour-specific beliefs such as personal norms [60,74,76]. De Groot and Steg [77] highlighted egoistic values positively influence to external regulations and have less self-determined motivation to pro-environmental intention. In line with the above findings, Perlaviciute and Steg [78] claimed that consumers with stronger egoistic values consider the extra cost and inconvenience when selecting green energy sources. Therefore, considering the above discussion, the following hypotheses were derived.

H_1d: 

A household’s egoistic values have a positive influence on their attitude towards solar PV systems.

H_2d: 

A household’s egoistic values have a positive influence on their subjective norms associated with willingness to install solar PV systems.

H_3d: 

A household’s egoistic values have a positive influence on their perceived behavioural control associated with willingness to install solar PV systems.

2.5. Purchase Determinants and Willingness to Install Solar

According to the TPB, intention to perform a behaviour is determined by the attitude towards the behaviour, subjective norms, and perceived behavioural control. TPB is extensively applied in pro-environmental behaviour [79,80,81] and particularly in solar PV studies [23,28,37]. The study used the TPB variables to denote purchase determinants and try to examine its influence on household willingness to install solar PV systems. Therefore, by referring to the detailed discussion in Section 2.2 about the theory of planned behaviour, the following have been hypothesised.

H5: 

A household’s attitude towards solar PV systems has a positive influence on their willingness to install solar PV systems.

H6: 

A household’s subjective norms have a positive influence on their willingness to install solar PV systems.

H7: 

A household’s perceived behavioural control has a positive influence on their willingness to install solar PV systems.

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. Constructs and items in the model.

Variable	Items	Reliability (α Value)	Source
Future Orientation	FO1—I often think about the things I am going to do in the future.	0.924	[94]
	FO2—I consider how things might be in the future, and try to influence those things with my day to day behaviour.		[95]
	FO3—Often, I engage in a particular behaviour in order to achieve outcomes that may not achieve result for many years.
	FO4—I am willing to sacrifice my immediate happiness or wellbeing in order to achieve future outcomes.
	FO5—I think it is important to heed warnings about negative outcomes seriously even if the negative outcome will not occur for many years.
	FO6—I think it is more important to perform a behaviour with important distant consequences than a behaviour with less important immediate consequences.
	FO7—When I make a decision, I think about how it might affect me in the future.
	FO8—My behaviour is generally influenced by future consequences.
Egoistic values	EV1—Social power: Having control over others.	0.767	[60,96]
	EV2—Wealth: Possession of material or money.
	EV3—Authority: Possessing the right to lead or command.
	EV4—Influential: Having an impact on people and events.
	EV5—Ambitious: Being hard working and aspiring.
Altruistic values	AV1—Equality: Having equal opportunity for all.	0.873	[60,96]
	AV2—A world of peace: A world free of war and conflict.
	AV3—Social justice: Correcting injustice and caring for the weak.
	AV4—Helpful: Working for the welfare of others.
Biospheric values	BV1—Preventing pollution: Considering protecting natural resources.	0.963	[60,96]
	BV2—Respecting the earth: Being in harmony with other species.
	BV3—Unity with nature: Being in tune with nature.
	BV4—Protecting the environment: Willing to preserve nature.
Attitude towards solar PV systems	ATT1—I find PV system gives me a good feeling.	0.922	[30]
	ATT2—A PV system is very useful to me.
	ATT3—A PV system is a sensible decision for me.
Subjective norms	SN1—Many people who are important to me would find it good if I installed solar panels.	0.854	[30]
	SN2—Many people in my community would find it good if I installed solar panels.
	SN3—People expect me to install solar panels.
	SN4—I feel obligated to install solar panels.
	SN5—Many people who are important to me own solar panels.
	SN6—For people like me, it is common to install solar panels.
Perceived behavioural control	PBC1—My house is suitable for the installation of solar panels (not shaded by trees, chimneys, other buildings, etc.).	0.607	[30]
	PBC2—Financing for solar panels is possible for me.
	PBC3—Getting a permit to install solar panels is possible (no historic building).
	PBC4—The financial incentives (subsidies) provided by the state/federal government motivates me to install solar panels.		[97]
Willingness to install solar panels	WIS1—I plan to install solar panels within the next 3 years.	0.902	[30]
	WIS2—I will install solar panels on my rooftop.		[98]
	WIS3—It is worth to spend my money to install solar panels although it is expensive.		[99]

.

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].

5. Results

5.1. Demographic Factors

First, the study conducted a demographic analysis to examine respondents’ socio-demographic background. It includes their gender, age, annual income, education level, and average monthly electricity bill. These demographic factors were chosen because they play a significant role in decision-making for solar installations.

Table 2. Respondents’ sociodemographic background.

Variable		Percent (%)	Variable		Percent (%)
Gender	Male	52.5	Annual income	Less than 25,000	6.7
	Female	47.5		25,000–50,000	19
				50,000–75,000	18.4
Age	18–29	11.7		75,000–100,000	15.1
	30–39	20.1		100,000–125,000	11.2
	40–49	26.8		125,000–150,000	7.8
	50–59	22.3		150,000–175,000	5
	60 and above	19		175,000–200,000	5
				Above 200,000	6.7
Average monthly electricity bill	Less than AUD 60	2.2		Prefer not to say	5
	AUD 60 to AUD 90	14.5
	AUD 90 to AUD 120	21.2	Education level	Secondary school	10.6
	AUD 120 to AUD 150	17.3		Senior secondary school	24.6
	AUD 150 to AUD 180	16.2		Undergraduate	31.3
	AUD 180 to AUD 210	8.4		Postgraduate	15.6
	AUD 210 to AUD 240	6.1		Vocational education	17.9
	AUD 240 to AUD 270	10.1
	AUD 270 and more	3.9

provides a summary of the socio-demographic background of the study’s respondents.

Out of the total sample, 52.5% were male and 47.5% were female. The highest age category is the age between 40 and 49 which has 26.8% of the sample, while the second highest is between 50 and 59 (22.3%). An analysis of the participants’ annual income reported that 59.2% earn less than AUD 100,000, while 29% earn between AUD 100,000–200,000, and a small proportion of 6.7% enjoy more than AUD 200,000. Regarding the education level of participants, senior secondary school (24.6%) and university graduates (31.3%) made up the largest proportion of the sample, whereas postgraduate and vocational education accounted 15.6% and 17.9%, respectively. In terms of average monthly electricity bill, AUD 90 to AUD 120 is the highest average monthly electricity bill paid by the respondents (21.2%). The second highest is AUD 120 to AUD 150, which is 17.3%, and the third is AUD 150 to AUD 180, which is 16.2%.

5.2. The Assessment of the Measurement Model

In this study, all the constructs consisted of reflective indicators. Thus, the evaluation of the measurement model is based on reflective measurement model criteria. Accordingly, the measurement model assessment centred on internal consistency reliability, convergent validity, and discriminant validity.

Composite reliability (CR) was used to measure the internal consistency reliability. All the CR values of the constructs in the model were above the critical value of 0.7 [102]. The results confirmed the reliability of constructs in the proposed conceptual model.

Convergent validity was assessed to test the common variance among the model constructs and measured by the outer loadings and AVE (average variance extracted) values. The results indicated that most loadings of the constructs were greater than the threshold level of 0.7. However, a few item loadings were lower than the threshold level. They are EGO2 (0.645), EGO5 (0.619), FO5 (0.687), FO6 (0.659), SN4 (0.658), PBC1 (0.589), and PBC3 (0.609). Out of these items, only PBC1, PBC3, and SN4 were deleted, as this increased the CR and AVE of the perceived behavioural construct and subjective norms. Other items that had outer loadings above 0.6 were retained in the measurement model as they did not make significant changes to CR and AVE. Therefore, after removing three indicators from the measurement model, all other indicators had the acceptable level of outer loadings to meet the requirement of convergent validity. Another measure of convergent validity is AVE. An AVE value of 0.5 or higher indicates that the construct explains more than half of its indicators’ variance and is the threshold level to meet convergent validity. The AVE values of all constructs are above 0.5, ranging from 0.565 to 0.836. Therefore, the measures of all eight constructs met the requirements of convergent validity.

Table 3. Results of outer loadings, CR, and AVE after deleting the items.

Construct	Indicator	Loading	Composite Reliability (CR)	Average Variance Extracted (AVE)
Biospheric Values (BIO)	BIO_1	0.893
	BIO_2	0.920
	BIO_3	0.916
	BIO_4	0.883	0.947	0.816
Altruistic Values (ALT)	ALT_1	0.841
	ALT_2	0.799
	ALT_3	0.908
	ALT_4	0.899	0.921	0.745
Egoistic Values (EGO)	EGO_1	0.746
	EGO_2	0.642
	EGO_3	0.867
	EGO_4	0.875
	EGO_5	0.615	0.868	0.573
Future Orientation (FO)	FO_1	0.718
	FO_2	0.793
	FO_3	0.737
	FO_4	0.785
	FO_5	0.683
	FO_6	0.658
	FO_7	0.796
	FO_8	0.827	0.912	0.565
Attitude (ATT)	ATT_1	0.892
	ATT_2	0.905
	ATT_3	0.928	0.934	0.826
Subjective Norms (SN)	SN_1	0.822
	SN_2	0.818
	SN_3	0.760
	SN_5	0.784
	SN_6	0.794	0.896	0.633
Perceived Behavioural Control (PBC)	PBC_2	0.836
	PBC_4	0.853	0.833	0.713
Willingness to Install Solar (WIS)	WIS_1	0.919
	WIS_2	0.943
	WIS_3	0.880	0.939	0.836

shows the results of outer loadings, CR, and AVE values after deleting the three items.

The discriminant validity was measured based on the Fornell–Larcker criterion. According to the Fornell–Larcker criterion, the AVE of each construct should be higher than the construct’s highest squared correlation with any other construct [103]. The results were recorded in

Table 4. Fornell–Larcker criterion.

Indicator	ALT	ATT	BIO	EGO	FO	PBC	SN	WIS
ALT	0.863
ATT	0.283	0.909
BIO	0.763	0.289	0.903
EGO	0.317	0.22	0.277	0.757
FO	0.503	0.451	0.525	0.328	0.752
PBC	0.069	0.405	0.168	0.218	0.244	0.844
SN	0.337	0.542	0.26	0.394	0.484	0.388	0.796
WIS	0.213	0.529	0.308	0.228	0.415	0.568	0.377	0.914

Note: The bold diagonal elements are calculated by the square root of the AVEs, and non-bold off-diagonal elements are latent variable construct correlations.

and show that it satisfied the requirement. Therefore, discriminant validity of the constructs was established.

5.3. The Assessment of the Structural Model

5.3.1. Evaluating Direct Path Effect

The direct path effects were evaluated based on the path coefficients, and their significance was estimated based on the bootstrapping of 5000 samples suggested by [90]. Findings revealed that eleven out of sixteen hypotheses of direct relationships were statistically supported with 10%, 5%, and 1% significant levels. The results of the hypotheses testing are summarised in

Table 5. Result of path significance of the structural model.

Path Relation (Hypothesis)	Path Coefficient	t-Value	p-Value	Significance
H1a: Future orientation > Attitude towards solar PV systems	0.398	5.667	0.000 ***	Significant
H1b: Biospheric values > Attitude towards solar PV systems	0.038	0.367	0.714 *	Not significant
H1c: Altruistic values > Attitude towards solar PV systems	0.035	0.429	0.668 *	Not significant
H1d: Egoistic values > Attitude towards solar PV systems	0.077	1.202	0.230 *	Not significant
H2a: Future orientation > Subjective norms	0.398	4.866	0.000 ***	Significant
H2b: Biospheric values > Subjective norms	−0.147	1.537	0.124 *	Not significant
H2c: Altruistic values > Subjective norms	0.172	1.704	0.088 *	Significant
H2d: Egoistic values > Subjective norms	0.256	3.16	0.002 ***	Significant
H3a: Future orientation > Perceived behavioural control	0.218	2.238	0.025 **	Significant
H3b: Biospheric values > Perceived behavioural control	0.189	1.755	0.079 *	Significant
H3c: Altruistic values > Perceived behavioural control	−0.238	2.057	0.040 **	Significant
H3d: Egoistic values > Perceived behavioural control	0.176	2.53	0.011 **	Significant
H4: Future orientation > Willingness to install solar PV systems	0.199	2.283	0.022 **	Significant
H5: Attitude > Willingness to install solar PV systems	0.298	2.635	0.008 ***	Significant
H6: Subjective norms > Willingness to install solar PV systems	−0.041	0.568	0.570 *	Not significant
H7: Perceived behavioural control > Willingness to install solar PV systems	0.421	5.931	0.000 ***	Significant

Note: significance at * p < 0.1, ** p < 0.05, and *** p < 0.01.

, including the hypotheses with its path coefficients, t-value, p-value, and significance. Out of sixteen hypotheses, eleven hypotheses were supported by the findings of the study.

5.3.2. Coefficient of Determination (R² Value)

R² represents the combined effect of exogenous variables on the endogenous variable. In this study, the coefficient of determination of four endogenous latent variables (attitude towards solar PV systems, subjective norms, perceived behavioural control, and willingness to install solar PV systems) were assessed. The results of the R² values of four endogenous latent variables were presented in

Table 6. Results of Coefficient of determination R².

Endogenous Construct	R2 Value
Attitude towards solar PV systems (ATT)	0.240
Subjective norms (SNs)	0.336
Perceived behavioural control (PBC)	0.131
Willingness to install solar PV systems (WISs)	0.485

. According to the results, willingness to install solar PV systems shows the highest R² value of 0.485, indicating that 48.5% of variance in the endogenous variable is explained by the exogenous variables, suggesting a strong relationship.

5.3.3. Evaluating Indirect Effect

The proposed model for household willingness to install solar PV systems is developed based on three mediators: attitude towards solar PV systems, subjective norms, and perceived behavioural control. The bootstrapping method was performed to analyse the mediation effect suggested by [104]. To analyse the effect of mediators on the relationships, the p-value of specific indirect effects were investigated.

Table 7. Results of mediation—specific indirect effects.

Path Relationship	Path Coefficient	t-Value	p-Value
FO → ATT → WIS	0.119	2.278	0.023 **
FO → SN → WIS	−0.016	0.54	0.589 **
FO → PBC → WIS	0.092	2.008	0.045 **
BIO → ATT → WIS	0.014	0.31	0.757 **
BIO → SN → WIS	0.007	0.431	0.667 **
BIO → PBC → WIS	0.079	1.686	0.092 *
ALT → ATT → WIS	0.012	0.379	0.705 **
ALT → SN → WIS	−0.007	0.468	0.64 **
ALT → PBC → WIS	−0.099	1.975	0.048 *
EGO → ATT → WIS	0.022	0.998	0.318 **
EGO → SN → WIS	−0.011	0.515	0.606 **
EGO → PBC → WIS	0.075	2.223	0.026 **

Note: * p < 0.1, ** p < 0.05.

presents the specific indirect effects. The finding revealed that five out of twelve indirect relationships were significant. Accordingly, attitude towards solar PV systems mediated the relationship between future orientation and willingness to install solar PV systems at the 5% significance level. Moreover, perceived behavioural control mediated the relationships between biospheric, altruistic and egoistic values, future orientation, and the willingness to install solar PV systems at 5% and 10% significance levels.

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].

7. Implications of the Study

7.1. Theoretical Implication

First, the study presents a unique conceptual model by integrating future orientation, values, and purchase determinants of households. The study addressed the complexity of household PV investment from different perspectives, including the main three theories. The researchers examine households’ willingness to install solar as a consumer durable product, an environmentally friendly product, and households’ future-oriented behaviour relating to solar PV investment. Therefore, this integrative model gives a holistic picture of the household behaviour of solar PV investment.

Second, the study applied FO as a unique construct to explore whether households’ solar PV investment decisions are based on their return on investment in the long term. Even though FO was used in other pro-environmental behaviour studies [95,111], it has not been utilised in the solar PV domain. Hence, this study is the first of its kind that applied FO in the solar PV domain. Therefore, the integration of FO derived from values orientation theory provides a sound theoretical underpinning and unique contribution to the existing body of literature.

Third, the study employed personal values (altruistic, biospheric, and egoistic values) in the conceptual model to better predict household value orientation relating to the solar PV investment. Until now, only one study used VBN theory to examine household solar PV behaviour [10]. However, to the best of our knowledge, this is the first study that used all three-value orientations to determine household solar PV investment behaviour. Therefore, the inclusion of all three values from the VBN model provides a better prediction of households’ perceptions of solar as an environmentally friendly product.

7.2. Practical Implications

The findings of this study provide valuable insights for both policymakers and photovoltaic marketers, enabling them to better understand and influence households’ behaviour towards adopting solar energy. These managerial implications are crucial for shaping effective strategies to promote solar PV systems.

7.2.1. Practical Implications for Policymakers

Introducing Green Labels

The study found that households with a strong future orientation are more likely to invest in solar PV systems. As solar PV is a durable product, households invest significant time and effort in researching its quality, installation options, and available government incentives. To facilitate informed decision-making and reduce perceived risks, it is recommended that trusted information sources, such as government organisations, promote the introduction of green labels for solar PV systems and inverters. Currently, no such labels exist in Australia. Given the rising popularity of solar energy among Australian households, green labels would help consumers identify the best brands in the market, ensuring they make informed and confident purchases.

Promoting Solar Home Batteries

The study also highlighted that attitudes towards solar PV systems and perceived behavioural control are key predictors of households’ willingness to install these systems. Financial capability and government rebate systems are crucial factors in this decision-making process. To enhance both attitudes and perceived financial capability, it is suggested that PV systems be marketed in combination with energy storage devices, such as solar batteries. By storing excess electricity generated during the day, households can maximise their energy use during peak hours, reducing their reliance on the grid. While some Australian states offer rebates for solar home batteries, this is not a nationwide policy. Policymakers should consider extending these rebates to all states to encourage broader adoption of solar home batteries, thereby improving the efficiency of solar energy use.

Conducting a Nationwide Solar Campaign

The study found that subjective norms did not significantly influence households’ willingness to install solar PV systems. However, social norms can be strengthened through national solar campaigns that inform homeowners about the widespread adoption of solar PV and the associated benefits. For instance, in 2021, Australia achieved the highest per capita rooftop solar installation rate globally. Communicating this achievement through mass media could enhance social norms and encourage more households to invest in solar PV systems.

7.2.2. Practical Implications for PV Marketers

Marketing Communication Campaigns

The study suggests that households’ egoistic values—focused on personal benefits—are more prominent than altruistic or biospheric values in the context of solar PV investment. PV marketers should leverage this insight by highlighting the personal and financial benefits of installing solar PV systems, such as available incentive programmes, long-term economic savings, and environmental advantages. Effective marketing communication strategies should target these egoistic values to encourage homeowners to adopt solar energy.

Corporate Social Responsibility (CSR) Programmes

Engaging in CSR activities can significantly enhance a company’s reputation. Solar companies should consider partnering with social organisations or governments to launch initiatives that promote rural electrification, particularly in developing countries. Such CSR programmes not only build brand reputation but also contribute to global sustainability efforts.

Promote Solar Campaigns

Literature shows that social networks and peer effects strongly influence solar PV adoption. Seeing solar panels on neighbouring homes or hearing positive feedback from opinion leaders can create curiosity and prompt action. Solar companies can capitalise on this by launching solar campaigns, where households receive discounts when they sign up with others in their community. This sales promotion strategy can significantly increase solar PV adoption within specific postcodes, leveraging the power of community and word-of-mouth marketing.

8. Limitations of the Study

Despite the significant contribution of the current study, several limitations should be acknowledged in this study. First, the study was conducted in Australia and not concerned with other geographical locations. Therefore, it is important to examine the behaviour of households in other countries, including both developed and developing countries. The limited focus on an Australian population may limit the generalizability of the results. Second, the study focused only on solar PV systems and did not consider solar thermal, even though solar thermal is popular among some households. Third, the study considered only the impact of government/state incentives and households’ financial capability of investing in solar PV. The study did not consider the changes in the government/state solar rebate programme on household behaviour. Very little attention has been paid to the gradual decrease of government incentives and their impact on household willingness to install solar panels. Hence, it is imperative to investigate how the reduction of government rebates impacts installing solar PV systems. Finally, another key limitation of this study is the relatively small sample size of 179 respondents, which may limit the generalizability of the findings. A smaller sample can result in reduced statistical power, making it challenging to detect significant relationships between variables or to accurately represent the broader population. As a result, future research with a larger and more diverse sample is recommended to validate and extend these findings.

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.