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Article

Modelling Gen Z’s Photovoltaic Purchase Intentions: A Mediator–Moderator Model

by
Xiaoxiao Li
1,
Ming Li
2,*,
Pick-Soon Ling
3 and
Chee-Hua Chin
3
1
School of International Education, North China University of Water Resources and Electric Power, 136 Jinshui East Road, Zhengzhou 450046, China
2
School of Management and Economics, North China University of Water Resources and Electric Power, 136 Jinshui East Road, Zhengzhou 450046, China
3
School of Business and Management, University of Technology Sarawak, Sibu 96000, Malaysia
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(18), 8409; https://doi.org/10.3390/su17188409
Submission received: 14 August 2025 / Revised: 12 September 2025 / Accepted: 17 September 2025 / Published: 19 September 2025
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Abstract

This study aims to explore the significant factors that predicted the purchase intention (PI) of Generation Z (Gen Z) in China on photovoltaics (PV) products. The Theory of Planned Behaviour (TPB) is extended with two exogenous variables (environmental responsibility (ER) and environmental consciousness (EC)) and government support (GS) as a moderator. In the proposed model, three TPB dimensions also serve as mediators. A total of 675 valid responses from Generation Z in China were gathered via purposive sampling and analysed using partial least squares–structural equation modelling (PLS-SEM). The findings revealed that subjective norms (SN), perceived behavioural control (PBC), and EC exerted a substantial influence on PI towards PV products. In accordance with the findings, EC has an indirect effect on PI via SN and PBC. In addition, the moderation analysis revealed that GS significantly enhances the relationship between EC and PI. Several important practical implications derived from the findings of the study were discussed, and it could be a useful reference for stakeholders in framing strategies to promote the PI of PV products. This study extends the TPB model by including two possible exogenous variables and examining the moderator and mediator propositions that significantly influence the PI of PV products, based on a comprehensive literature review. The proposed model is envisaged to provide additional evidence on the topic.

1. Introduction

Sustainability is a critical global objective, and green energy, particularly photovoltaic (PV) technology, plays a pivotal role in achieving it [1]. While the literature provides a comprehensive understanding of the factors influencing PV product purchase intentions, to fully achieve sustainability goals, it is essential to consider the potential of integrating environmental, social, and economic dimensions [2,3,4]. In brief, green energy is generated from renewable resources and is naturally replenished, resulting in minimal environmental impact [5]. Among the possible alternatives to generate green energy, solar photovoltaic is recognised as one of the most prevalent and least expensive forms of renewable energy because it does not require an existing public infrastructure [5]. Technically, PV systems convert sunlight into electricity, offering a renewable and clean energy source that can significantly reduce reliance on fossil fuels and decrease greenhouse gas emissions [6]. The use of PV products is a promising approach to reducing energy waste and promoting sustainability [7]. Due to technological advancements, PVs promise higher efficiency and lower material consumption, which further enhances the sustainability of solar energy systems [8]. This transition to solar energy is essential for sustainable development, as it provides a reliable and nearly limitless power source.
Utilising these photovoltaic products is perceived as one of the efforts in contributing to the 12th Sustainable Development Goal (SDG): Responsible Consumption and Production. As consumers become more environmentally conscious, they are more likely to switch to eco-friendly purchases. Ref. [9] noted that Generation Z in emerging markets such as China are more aware of environmental issues and tend to purchase more sustainable products. In addition, approximately 40 per cent of the Asian population in 2035 will be Generation Z [10], and they are expected to dominate the consumer market over the next decade. Given their uniqueness in this context, it is essential to study pro-environmental behaviour, such as PV product PI, among Chinese Gen Z. Due to the vast potential of this generation, this study aimed to reveal the purchase intent (PI) of Chinese Gen Z on PV products in China, as they tend to demonstrate their environmental consciousness by purchasing environmentally friendly products [11].
Empirically, numerous studies have been conducted to investigate the determining factors of consumers’ pro-environmental behaviour in different contexts [12,13]. However, the study that particularly focused on PV products is relatively scarce. For instance, Ref. [14] focused on sustainable products, Ref. [15] studied organic products, and Ref. [16] investigated green products. Therefore, there is an urge to examine the determining factor that significantly influences the PI of PV products, especially for Chinese Gen Z. In fact, past studies have integrated environmental factors into the TPB to provide a more comprehensive understanding of Gen Z’s intentions and behaviours, especially in areas like green tourism [17] and waste management [18]. However, there is a lack of studies that incorporate environmental responsibility and consciousness into the TPB to reveal the purchase intentions of PV products through the lens of Gen Z. This study is deemed to fulfil the underlying gaps, and most importantly, this demographic is increasingly recognised for its potential to drive sustainable practices due to its unique values and behaviours [19].
Theoretically, consumers’ behavioural intention (BI) could be explained by utilising the Theory of Planned Behaviour (TPB) as has been conducted previously [20]. However, the literature has not yet reached a consistent result regarding the effect of the three dimensions in the TPB on behavioural intention. For instance, Ref. [15] found an insignificant effect of attitudes (ATT) towards BI, while Ref. [14] found otherwise. Similarly, inconclusive findings were also found in subjective norms (SN), in which Refs. [16,20] found a significant effect of SN, but an insignificant effect was also documented [12,21]. Moreover, although the significant influence of perceived behavioural control (PBC) is dominant in the literature [22], an insignificant role of PBC is still found in a few studies [15].
In addition, as the TPB was introduced to predict general behaviour, therefore, it has to be extended by other constructs to better explain pro-environmental behaviours such as PV product purchase intention. In addition to that, the TPB emphasises more on self-interest and social approval, while overlooking other influences such as personal norms [23], even though an individual’s behaviour could be influenced by an individual’s green motivations and obligated morality [12]. Therefore, extending the TPB model with two exogenous variables to reflect the influence of personal norms (environmental responsibility (ER) and environmental consciousness (EC)) could address the paradoxical strain and comprehensively predict Gen Z PI towards PV products. ER and EC are chosen as their substantial effect in influencing the sustainable behaviour has been widely recognised in past studies [22,24,25,26]. Therefore, this study further postulates that both ER and EC have a direct and indirect impact on PI on PV products as well.
Overall, three research questions have been raised in the study, including (1) what are the factors that significantly determine Gen Z to purchase PV products? (2) Do three dimensions of the TPB (i.e., ATT, SN, and PBC) significantly mediate the relationships between ER and EC on PI? and (3) does government support (GS) strengthen the effect on the direct relationships between proposed antecedents and the PI of PV products? Therefore, based on these research questions, this study aims to examine the determinant factors of Gen Z in purchasing PV products by extending the TPB with two exogenous variables that reflect personal norms (ER and EC) and by examining the mediating effect of the three dimensions in the TPB in the relationship between the two exogenous variables and PI on PV products. This study examines the moderating effect of GS on the direct relationship between the antecedents and the PI of PV products, recognising the government’s crucial role in promoting environmentally friendly behaviours. The contribution of this study is fourfold: Firstly, contextually, this study examines the factors that determine the PI of PV products. Secondly, a novel framework is proposed in this study by extending the TPB with two exogenous variables that reflect the influence of personal norms in explaining the PI of Generation Z towards PV products. Thirdly, the research demonstrated that SN and PBC can significantly mediate the associations between exogenous variables and PI on PV products. Lastly, the study details the significant moderating effect of GS on the association between EC and PV product PI.

2. Literature Review and Hypotheses Development

2.1. Theory of Planned Behaviour

The TPB is an extension model of the Theory of Reasoned Action (TRA) developed by Ref. [27]. Three dimensions have been proposed in the TPB that could be used to predict an individual’s behaviour, namely ATT, SN, and PBC. The degree to which an individual has a positive or negative assessment of a specific behaviour is referred to as attitude [28]. Subjective norms are defined as the perceived perception of the important people in the surroundings towards a certain behaviour [28]. Lastly, perceived behavioural control refers to the level of difficulty in performing the behaviour [28]. Since its inception, the TPB has been extensively used in social science to explain human behaviours, for instance, investment intention [29], pro-environmental behaviour [20,30], organic food consumption [15], and others. Thus, the TPB is appropriate to investigate any behaviour if planning is required for the behaviour [31]. However, additional variables are required to be integrated with the initial TPB to improve the predictive ability of the model [28] and also capture the special and unique characteristics that have not been considered in the TPB. The importance of the personal norms of ER and EC has been widely remarked on in different sustainable products. In this study, the PV products are also considered as sustainable products, and thus, it might suggest that both ER and EC are also vital factors that influence Gen Z in purchasing PV products. Therefore, the TPB has been extended with two additional exogenous variables (ER and EC), together with GS as a moderator in this study. In addition, the three dimensions of the TPB are also utilised as mediators to examine the indirect relationships between the two exogenous variables and PI of PV products.

2.2. Hypotheses Development

2.2.1. Attitudes

ATT is defined as the degree to which an individual shows her/his favourable or unfavourable responses towards a BI [28]. An individual has a positive attitude towards a particular behaviour if they have favourable responses to that behaviour. For instance, consumers will likely buy sustainable products like PV products if they have favourable attitudes towards the outcome of such behaviour. The BI to perform such environmentally friendly behaviour was found to be significantly influenced by attitudes [20,32]. For instance, Ref. [14] revealed that consumers’ intention on sustainable food consumption behaviour is significantly affected by attitudes. Ref. [22] found that attitudes have a significant relationship with environmentally friendly products’ PI. Therefore, the following hypothesis is proposed.
H1. 
ATT has a positive relationship with the PI of PV products.

2.2.2. Subjective Norms

Ref. [28] defined SN as the perceived social power of the surrounding people that may affect an individual’s behaviour. SN is also defined as the level of pressure from the people in his/her social context [33]. Ref. [31] further defined SN as the individual’s perception of whether the people who are important to them encourage them to perform a certain behaviour. This indicates that if the people who are important to individuals encourage them to buy sustainable products like PV products, then the students are likely to do so. SN has been discovered to significantly influence BI in several contexts [16,20,22]. For instance, Ref. [15] found that SN significantly influenced organic rice PI. With that, the following hypothesis is formulated.
H2. 
SN has a positive relationship with the PI of PV products.

2.2.3. Perceived Behavioural Control

PBC refers to the individual’s perception of the level of perceived ease in performing certain behaviour [28]. If individuals expect that it does not require additional effort or cost to perform a particular behaviour, then they are likely to do so. Specifically, individuals tend to purchase sustainable products like PV products if they perceive that it is easy to do so. Studies in different research contexts, such as Ref. [32], discovered that PBC is a vital factor influencing an individual’s BI. Specifically, Ref. [12] revealed that PBC significantly affects green PI. Ref. [16] found that PBC has a significant positive association with green product PI. Thus, the hypothesis below is suggested.
H3. 
PBC has a positive relationship with the PI of PV products.

2.2.4. Environmental Responsibility

ER is known as a symbol of socially responsible behaviour [34], and it is one of the variables that may affect the sustainable products’ PI. With the increasing awareness of environmental problems, individuals are becoming more aware of their role in protecting the ecosystem [21]. Specifically, an individual will perform environmentally friendly behaviour if they feel they have an obligation to protect the environment. With this, it could be postulated that individuals will purchase sustainable products like PV products if they feel it is their responsibility to protect the ecosystem. Empirically, a significant influence of ER on BI has been found [24]. For instance, Ref. [21] found that perceived ER has a significant influence on the consumer’s green PI, while a similar effect was also documented by Ref. [25] on the green consumption intention in China. Hence, the following hypothesis is formulated.
H4. 
ER has a positive relationship with the PI of PV products.
This study further postulated that ER can significantly affect the dimensions of the TPB. As suggested by Ref. [34], individuals will have a favourable ATT if they have a higher level of ER. Ref. [12] further remarked that consumers will have a favourable ATT if they have a high perception of ER. ER will create environmental awareness in individuals and further nurture their positive ATT if they have such information or knowledge about environmental issues. Ref. [31] reported a positive relationship between environmental corporate responsibility and SN. In other words, if individuals are becoming more aware of their responsibilities to protect the environment, they will more likely perceive that their significant others will approve of their intentions to purchase sustainable products such as PV products. Ref. [12], in their study to investigate the role of environmental responsibility in shaping green PI, indicated that ER positively influences PBC. In addition, Ref. [33] argued that a higher level of environmental awareness will increase an individual’s PBC. It can be argued that if individuals have a strong sense of ER, they will more likely perceive that it is easy to purchase PV products in the context of this study. Thus, individuals are expected to have stronger PBC if they have a high level of ER. The following hypotheses were hypothesised to examine their associations.
H4a. 
ER has a positive relationship with ATT.
H4b. 
ER has a positive relationship with SN.
H4c. 
ER has a positive relationship with PBC.

2.2.5. Environmental Consciousness

Ref. [26] suggests that individuals will react either positively or negatively towards ecological issues. Individuals will boycott a certain product if it brings negative consequences to the environment. In a similar tone, Ref. [22] also suggests that when an individual is more environmentally concerned, they are more willing to engage in environmental protection behaviour. Ref. [5] remarked that the level of environmental concern positively affects the likelihood of practising environmentally friendly behaviour. Therefore, this study hypothesises that consumers are likely to purchase PV products if they are more conscious of environmental issues. This is supported by previous studies that also found the same effect [22,35]. For example, Ref. [26] revealed that EC significantly influences consumers’ PI of organic drinking products. Thus, the following hypothesis is proposed.
H5. 
EC has a positive relationship with the PI of PV products.
From the theoretical and empirical perspectives, EC could behave as antecedents for the three dimensions in the TPB. For instance, Ref. [12] remarked that individuals that are conscious of environmental issues are more likely to buy pro-ecological products as they tend to have a positive ATT, PBC, and intention to do so. Ref. [36] also suggests that EC significantly influences individuals’ ATT. Similarly, Ref. [37] found that environmental concerns are positively significant with ATT and SN. Thus, this postulates that when individuals are highly concerned with environmental problems, they tend to have a favourable ATT towards sustainable products and also favourable perceptions about how their significant others encourage them to purchase sustainable products. Moreover, when individuals are more conscious of environmental issues, they will have a stronger PBC, as found by Ref. [38]. The hypotheses below were proposed for examination in this study.
H5a. 
EC has a positive relationship with ATT.
H5b. 
EC has a positive relationship with SN.
H5c. 
EC has a positive relationship with PBC.

2.2.6. Mediating Effects of TPB’s Dimensions

This study further proposed the three dimensions in the TPB as mediators of the relationship between the two exogenous variables and BI, to enrich the evidence in the subject matter. This assumption is supported by theoretical and empirical reasons. Empirically, the TPB is widely applied in consumer behaviour studies [15,17], and a significant association of both exogenous variables with the dimensions in the TPB is also remarked upon [36,37,38]. Furthermore, the mediator effects of the TPB’s dimensions are widely investigated in different contexts, such as pro-environmental behaviour [30] and entrepreneur intentions [37]. These studies found that the dimensions of the TPB could significantly mediate the relationship between exogenous variables and BI. For instance, Ref. [12] found the mediated role of ATT and PBC on the relationship between perceived ER and environmental concern with green PI. Ref. [39] also remarked on the significant mediation role of PBC on the relationship between environmental concern and intention to adopt green concepts. Theoretically, Ref. [40] remarked that some other exogenous variables or background factors may indirectly influence BI via the dimensions in the TPB; thereby, these exogenous variables indirectly influence BI through the TPB’s dimensions. In other words, ER and EC were postulated to indirectly influence the PI of PV products through ATT, SN, and PBC. Therefore, the following hypotheses were proposed.
H6a and H6b. 
ATT mediates the relationship between exogenous variables (ER and EC) and PI of PV products.
H7a and H7b. 
SN mediates the relationship between exogenous variables (ER and EC) and PI of PV products.
H8a and H8b. 
PBC mediates the relationship between exogenous variables (ER and EC) and PI of PV products.

2.2.7. Government Support as Moderator

GS is defined as the assistance provided by government-related entities in encouraging citizens to perform a certain behaviour. Various supports could be provided by governments, such as laws and regulations, infrastructures, and policies. The government played a vital role in encouraging pro-environmental behaviour [41]. As found by Ref. [41], practising pro-environmental behaviour is not the sole responsibility of consumers, and the government is also responsible for promoting such behaviour. The government should take the lead in promoting the use of green products with necessary incentives and regulations. Ref. [38] also remarked on the similar idea that strict environmental rules should be formulated by the government to dampen certain behaviour that could affect the environment. Empirically, several government-related factors have been investigated and found to significantly influence consumer behaviours. The significant influence of GS on BI is also documented in other contexts [42,43].
Empirically, the strong moderating role of government-related factors has been established in the literature, but in other contexts. For instance, Ref. [44] discovered that GS has a significant moderating effect on the SME’s innovative performance. Ref. [45] also found that the relationships between subjective norms and social media influence on green consumption behaviour are significantly moderated by government support. The association between attitudes and intention to use is also significantly moderated by GS [46]. The significant moderating role of perceived demonetisation regulation was also remarked on by [47]. Therefore, this study proposed that GS could significantly moderate the association with sustainable products’ PI. Hence, the following hypotheses were proposed:
H9. 
GS moderates the relationship between ATT and PI, where the relationship becomes stronger when GS is high.
H10. 
GS moderates the relationship between SN and PI, where the relationship becomes stronger when GS is high.
H11. 
GS moderates the relationship between PBC and PI, where the relationship becomes stronger when GS is high.
H12. 
GS moderates the relationship between ER and PI, where the relationship becomes stronger when GS is high.
H13. 
GS moderates the relationship between EC and PI, where the relationship becomes stronger when GS is high.
From the discussion above, the proposed research model is provided in Figure 1.

3. Methodology

3.1. Sample

In this study, the Chinese Gen Z were the targeted population, and they are greatly affected by technology products [48]. Moreover, this population is generally highly literate and educated and uses the internet a lot. This generation is defined as those who were born between 1995 and 2010, accounting for 149 million people in China [48]. As they were born during the implementation of China’s one-child policy, this population is expected to show impressive consumption power, although they are financially supported by their parents. Therefore, to study the PI of the Chinese Gen Z, this study focused on those university students who are aged 18–25 years old, as they are consumers who can make their purchasing decisions autonomously.
Purposive sampling was employed to select the eligible respondents who fulfilled the selection criteria of (1) registered university students in China, and (2) must have an age range between 18 and 25 years old. As mentioned by Ref. [49], Chinese college students are appropriate for purposive sampling to improve the generalizability of the results that could accurately represent the Chinese Gen Z consumers to a large extent. The online survey was utilised to collect the responses from the target population, where the invitation link was shared with university students in China through several social media platforms such as WeChat, Weibo, QQ, and others between February 2022 and March 2022. A total of 675 valid responses were collected, and this sample is considered sufficient for the study as the number was greater than the recommended minimum sample size of 178 obtained using G Power with an effect size of 0.15, a power level of 0.95, and a significance level of 0.05.

3.2. Data Collection and Instruments

Before the data collection, the researchers obtained ethical clearance from the ethics review committee of the North China University of Water Resources and Electric Power. In addition, the respondents’ participation in the survey was entirely voluntary, and they were allowed to withdraw from the study at any time if they felt uncomfortable. The rights of the respondents were also explained clearly in the description of the survey, and the respondents only had to continue to provide their responses if they agreed to participate in this study. In addition, the study also guaranteed confidentiality, and their identities remained anonymous. To collect the responses, a Chinese online survey platform, Wenjuan Xing (www.wjx.cn), was used, as it is a reliable and appropriate platform in China. Moreover, this online survey platform is free to use, and it can connect with several local messaging platforms like WeChat. To better measure the constructs proposed in the model, 30 measurement items from prior studies were adopted and adapted in this study (Refer to Appendix A). For instance, four items of ATT and SN were modified from Ref. [14] and [50], respectively. The measurement of PBC includes five items borrowed from Ref. [51]. ER was measured by four items from Ref. [25], while four items from [22,26] were adapted to measure EC. To measure the moderation effect of GS, five items were adapted from Ref. [43]. Lastly, four items of PI were adapted from Ref. [16]. These items were first prepared in English and further translated into Chinese using back-to-back translation to increase the level of understanding of the respondents. The questionnaire was checked by three experts to ensure its validity. The 7-point Likert scale that ranged from 1 to 7 was used to measure the level of agreement on the items, in which 1 represents strongly disagree and 7 represents strongly agree.

3.3. Analytic Approach

The primary responses were first measured by the multivariate normality test through Mardia’s coefficient procedure. Mardia’s coefficient procedure was chosen due to its superiority in examining multivariate normality, especially in studies that utilise multivariate analysis like partial least squares–structural equation modelling (PLS-SEM). The result showed that the responses were not normally distributed, as shown by the p-Value of skewness (β = 7.541, p < 0.01) and kurtosis (β = 99.035, p < 0.01). Thus, PLS-SEM was appropriate to be used to test the proposed model [52]. In addition, PLS-SEM is also adequate for the study as the study aims to validate the proposed research model. Moreover, as the proposed research model involved a more complex relationship, PLS is estimated to be appropriate for this study. The estimation of PLS-SEM was performed using SmartPLS software (Version 4.1.1.2) with a 5000-resampling procedure.
The characteristics of the respondents are provided in Table 1 and show that the majority of respondents are female (53.78%) and are dominated by the Han nationality (94.07%). For the age distribution, approximately half of the respondents were between 18 and 19 years old, followed by one-fourth of the respondents aged between 20 and 21 years old. In addition to that, 89% of the respondents received financial assistance from their parents, and this showed their remarkable purchasing power, as most of them do not need to worry about the financial burden during their studies, compared to only 3% of respondents who have to work part-time to earn money for their expenses.

4. Findings

4.1. Common Method Bias

As the responses were gathered using the same questionnaire, therefore, common method bias (CMB) issues may be present in the collected responses. To prevent any CMB issues, Harman’s single-factor test in SPSS (Version 27) was performed, and the result showed that there is no single factor dominating the variances in responses, as the dominant factor only explains 45.44% of the total variances, which is less than the 50% level [53]. This indicates that CMB does not exist in this study. In addition, the variance inflation factors (VIFs) in Table 2 also show a similar result, whereas CMB is absent in the study, as the values are less than 3.3 [54].

4.2. Assessment of the Measurement Model

The study continued with the reliability and validity assessments, and the results are presented in Table 2. The outer loading and average variance extracted (AVE) could be used to assess the convergent validity [55]. As shown in Table 2, all items have an outer loading value that is greater than 0.7080 [52], while the AVE values for each construct are also greater than the threshold level of 0.5000 [56]. This finding indicates that the convergent validity was established at both the item and construct levels. Composite Reliability (CR) has been used to measure internal consistency, and the result also confirmed that internal consistency is achieved as the CR value is higher than the standard level of 0.7000 [57]. To assess the discriminant validity, the Heterotrait–Monotrait (HTMT) ratio of correlation is employed, and the result is provided in Table 3. As all the HTMT values are less than the most conservative criterion level of 0.85, thus, the discriminant validity was also established [58]. Through these reliability and validity assessments, the measurement model is considered sufficiently reliable, convergent, and discriminant valid.

4.3. Assessment of the Structural Model

The study then followed with the structural model assessment to confirm the inner model and test the proposed hypotheses. Firstly, the R-Squared (R2) values showed that around 65.90% of the PI variance is explained by ATT, SN, PBC, ER, and EC. Meanwhile, ER and EC explained around 30.60%, 32.10%, and 29.40% of the variance in ATT, SN, and PBC, respectively. The Q2 values of 0.567, 0.297, 0.314, and 0.286 also confirmed the predictive validity of the proposed model, as the Q2 values are greater than zero [55].
The summarised results of the hypotheses testing are provided in Table 4 and Figure 2. The findings showed that only 3 of the 11 proposed direct hypotheses were not supported (H1, H4, and H4b), while the remaining 8 direct hypotheses were accepted. Among the five hypotheses towards PI, EC (H5, β = 0.381) has the greatest effect, followed by PBC (H3, β = 0.233) and SN (H2, β = 0.118). Although ER has no significant influence on SN (H4b, β = 0.0657), the proposed hypotheses between ER with ATT (H4a, β = 0.220) and PBC (H4c, β = 0.109) are accepted. Meanwhile, EC has a significant effect on all three dimensions in the TPB and supports H5a, H5b, and H5c.
In addition to that, the indirect relationship between the two exogenous variables and PI through the three TPB dimensions has also been estimated, and the results are presented in Table 5. The result showed ER cannot indirectly impact PI via the TPB’s dimensions and thus, H6a, H7a, and H8a are not supported. Moreover, H7b and H8b were supported as EC is positively associated with PI via both SN (β = 0.062) and PBC (β = 0.108), but not through ATT.
Furthermore, the results of the moderating effect of GS presented in Table 6 proved that GS played a significant role in moderating the relationship between EC and PI (H13), while the remaining four moderating effects of GS were not supported; thus, H9, H10, H11, and H12 were rejected. The interaction plot in Figure 3 further shows that when GS is high, the stronger the positive relationship between EC and PI is.

5. Discussion

The factors that significantly influenced the younger generation in China to purchase PV products were examined in this study. Surprisingly, ATT has no significant influence on PI, and this contradicts Refs. [14,20,32]. This implies that the PI of PV products is not influenced by ATT, and thus, the personal evaluation of sustainability is not a decisive factor for their sustainable behaviour. As remarked by Ref. [45], the sustainable behaviour of Gen Z is influenced by factors other than ATT, such as the influence from the social circle, as well as the feasibility of the behaviour, as proven in the study. This further signified that the younger generation in China are more collectivist, whereas their behaviour tends to be affected by others. In addition, the respondents might have limited knowledge and experience with PV products, and this could be the reason for the lack of significant results, as the term PV is more technical or jargon for them, compared to other sustainable products.
As hypothesised, both SN and PBC have a significant relationship with PI. These findings validate the results of Refs. [16,22], which emphasised the significant influence of SN and PBC on the PI. Gen Z in China are likely to purchase PV products if the people who are important to them and surrounding them feel that purchasing these PV products is good and protects the environment. Moreover, if consumers perceive that purchasing these products is easy to perform and does not require any additional effort or cost, then they will buy them.
In addition, inconsistent findings were reported for the two exogenous variables that reflect personal norms. The results revealed that ER has a significant negative influence on PI, and this finding is in disagreement with Refs. [21,24,25]. This indicates that even though the younger generation feel they are aware of environmental problems and obligated to protect the environment, it will reduce their PI on PV products. One of the possible reasons is that Gen Z might not be familiar with the benefits of PV products, as they might have limited involvement with PV products. With that, they may not understand how PV products can mitigate environmental issues, although they feel responsible for them. In addition, the study further found that EC has a significant positive effect on PI, which coincides with prior studies [22,26,35]. This showed that Chinese consumers are willing to purchase PV products if they are conscious of environmental issues.
Moreover, ER only significantly affects two of the three dimensions in the TPB, except SN. The significant influence of ER on ATT is similar to Refs. [12,31], which means consumers will have favourable and positive attitudes if they feel responsible for protecting the environment. The significant relationship between ER and PBC is in line with Ref. [31] but contradicts Ref. [12]. This result proved that a higher level of ER will increase the ability of the younger generation to purchase PV products, and thus make it easier to purchase them. However, the insignificant connection between ER and SN refutes the works of Ref. [31] and shows that individual responsibility does not influence SN. Although Gen Z feel that they are responsible for environmental problems, their responsibility does not necessarily become an external influence that will eventually affect their behaviour. With that, no significant effect of ER on SN is found.
Additionally, as hypothesised, the three dimensions of the TPB are significantly influenced by EC. Similar findings were also revealed in previous studies such as Refs. [12,22,37]. The findings indicated that Gen Z have favourable ATT, greater social pressure, and strong PBC if they are more conscious of environmental issues. Furthermore, two of the three dimensions in the TPB were proven to significantly mediate the association between EC and PI. Specifically, SN and PBC significantly mediated the relationship between EC and PI. As suggested by Ref. [39], a stronger PBC would be established with high environmental concern and thus influence the green concept adoption intention. With that, the study proved that SN and PBC could play a mediating role in influencing PV products’ PI. However, the three dimensions of the TPB are found to have an insignificant mediating effect on the relationships between ER and PI. This is consistent with the direct effect of ER on PI. The sense of environmental responsibility still does not affect the PI on PV products, although the three dimensions of the TPB’s presence act as mediators. As explained earlier, the limited understanding of PV products of the younger generation could be the main reason. As this generation have insufficient understanding of PV products, the personal evaluation of PV products, influence from others in the social circle, as well as the feasibility of purchasing PV products, did not mediate the influence of ER on PI.
Lastly, the significant moderating role of GS is also found in this study, especially in the relationship between EC and PI. The finding is similar to Refs. [44,46], and showed that the association between EC and PI could be further strengthened with the presence of support from the government. This signified that the Chinese Gen Z perceived that GS is important to reinforce the relationship of EC towards PI in purchasing PV products.

6. Implications

6.1. Theoretical Implications

This study provides substantial contributions to the existing literature from a different research context that focuses on PV products. Firstly, two exogenous variables were added to the proposed model to reflect the influence of personal norms, and it was discovered that one of these variables has a significant direct influence on the PI of PV products. In addition, the results demonstrated that two exogenous variables had a significant impact on the three dimensions of the TPB. This indicates that the two exogenous variables not only have a direct effect on PI, but also have a direct correlation with the three dimensions of the TPB. As the initial model only explained the general behaviour, the TPB model should be expanded with additional variables that can capture the specific and unique characteristics of the research context. Moreover, the three dimensions of the TPB were used as mediators in the relationship between two exogenous variables and PI, and the results demonstrated that SN and PBC could significantly mediate the relationship between EC and PI. Finally, GS was proposed as a moderator to examine its moderating effect on the relationship between direct relationships and PI. The results indicated that GS significantly moderates the relationship between EC and PI to purchase PV products. Therefore, the moderating role of GS should not be overlooked, as it may influence the BI of consumers to engage in specific pro-environmental actions.

6.2. Practical Implications

In terms of practical perspectives, this study also offers several practical implications for stakeholders to increase the PI of Chinese Gen Z on PV products. Firstly, the results showed that SN, PBC, and EC have a significant effect on PI. Therefore, to achieve SDG 12, stakeholders such as government agencies, PV product manufacturers, and marketers have to focus on these three variables to increase the PI of consumers on PV products. For example, government agencies have to disseminate information regarding ecological problems to the public, as this could increase their awareness and consciousness. As found in this study, EC is important in influencing all three dimensions of the TPB and also the PI to purchase PV products. Therefore, increasing consciousness could bring a favourable ATT, greater social pressure, and also stronger PBC for them to purchase PV products. In addition, when consumers receive more information and are aware of ecological issues, they will feel more responsible and become more obligated to protect the environment by purchasing environmentally friendly products.
The influences of people surrounding Gen Z are also important, as they could put social pressure on them to purchase PV products. As Gen Z are youth consumers, therefore, they are likely to seek an opinion from those who are important to them. For instance, the marketers of PV products have to spread and share the benefit of purchasing PV products with people who are important to the younger generation, such as families and friends. Consumers are likely to purchase PV products if people surrounding them encourage them to purchase or have a favourable perception of those products as the findings indicated that the younger generation are more towards collectivism rather than individualism. Moreover, the marketers and sellers of PV products have to reduce the difficulty of purchasing PV products. For example, PV products have to be labelled with a special label or packaging for consumers to easily identify them. Shops may also allocate a designated place to market all the products that are produced through this concept. In addition, special discounts or promotions or marketing events to promote these PV products may be implemented by the businesses to attract greater PI.
In addition, PV manufacturers have to reform the PV products to make them more user-friendly. As explained earlier, this younger generation may have limited exposure and experience with PV products, and this has led them to be unaware of the benefits of PV products. With that, PV manufacturers are required to redesign the PV products so that they can be used more easily. The way of installation and the instructions of operation also have to be clearly provided so that they will reduce the difficulty level of Gen Z when they want to use it.
Furthermore, to increase the PI of PV products, policymakers have to play their role. For instance, government and their agencies have to articulate some policies and strategies to increase consumers’ willingness to purchase these PV products. Governments may provide certain incentives or rewards to consumers who purchase PV products, as well as give publicity support regarding the benefits of PV products, as this is important to enhance the awareness and consciousness of the younger generation and result in increasing their PI. Therefore, to increase the PI of the Chinese Gen Z, all stakeholders, including governments and businesses, have to play their role, as this is not the sole responsibility of consumers.

7. Conclusions, Limitations, and Future Recommendations

This study aims to investigate the significant factors that determine Gen Z in China to purchase PV products. Two exogenous variables have been integrated with the TPB to reflect the personal norms to examine their influence on PI on PV products. In addition to that, the three dimensions of the TPB were also utilised as mediators to examine the indirect influence of two exogenous variables on PI. Moreover, this study further included GS as a moderator to examine its moderating effect on the relationships. With the responses gathered from 675 Gen Z in China, the study revealed that PI is significantly influenced by SN, PBC, and EC. Moreover, ER significantly affects ATT and PBC, while the three dimensions of the TPB are significantly impacted by EC. The mediating test further found that SN and PBC significantly mediated the relationships between EC and PI. Additionally, the moderating analysis revealed that the association between EC and PI is significantly strengthened by GS.
Although several contributions were provided, several other limitations appear in this study. Firstly, this study only focused on general PV products and was not specific enough on which type of PV products. Therefore, future study is encouraged to narrow down the context of the study to focus on more specific PV products, as they may have different results. In addition to that, this study solely focused on Gen Z. Thus, it would be interesting if future studies could include other consumer groups, such as working adults and older generations, as different behaviour may be found. In addition, this study assumed all respondents were homogeneous, but different subcultures may exist. This would open an opportunity for future studies to consider the heterogeneity of the respondents, such as male vs. female, younger vs. older, and parent-subsidised vs. self-earning respondents. Moreover, the future study also suggested utilising other theories to examine the subject matter, such as social cognitive theory or the norm activation model, as this study employed the most commonly used theory (TPB) to understand the BI of Gen Z in purchasing PV products.

Author Contributions

Conceptualization, X.L. and P.-S.L.; methodology, P.-S.L. and C.-H.C.; software, P.-S.L. and C.-H.C.; validation, X.L. and M.L.; formal analysis, P.-S.L.; investigation, X.L.; resources, M.L. and X.L.; data curation, X.L.; writing—original draft preparation, X.L., P.-S.L. and M.L.; writing—review and editing, P.-S.L., C.-H.C. and M.L.; visualization, P.-S.L. supervision, P.-S.L.; project administration, X.L.; funding acquisition, X.L. and M.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by Ethics Committee of North China University of Water Resources and Electric Power Science and Technology of 364002 on 1 March 2022.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Acknowledgments

The authors wish to express their gratitude to the University of Technology Sarawak for its invaluable support throughout the duration of this research.

Conflicts of Interest

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Appendix A

ConstructItemsSources
Attitudes
  • I like to consume photovoltaic products because it will balance nature.
  • Consuming photovoltaic products is good because it is an advantage to me.
  • I like the consumption of photovoltaic products because mankind is severely abusing the natural environment.
  • I would consume photovoltaic products because human needs to adapt to the natural environment.
[14]
Subjective Norms
  • Most people who are important to me think I should purchase photovoltaic products.
  • Most people who are important to me would want me to purchase photovoltaic products.
  • People whose opinions I value would prefer that I purchase photovoltaic products.
  • My friend’s positive opinion influences me to purchase photovoltaic products.
[50]
Perceived Behavioural Control
  • I have the ability to choose whether or not to purchase photovoltaic products.
  • Purchase of photovoltaic products is doable for me.
  • I am able to purchase photovoltaic products.
  • I have the ability to purchase photovoltaic products.
  • I believe that my decision to consume photovoltaic products has a direct influence on the environment as a whole.
[51]
Environmental Responsibility
  • My actions impact the health of the environment.
  • I have the power to protect the environment.
  • I can learn how to improve the environment.
  • I will work to make my surroundings environment a better place.
[25]
Environmental Consciousness
  • I am willing to make some exceptional attempts, like purchasing photovoltaic products to protect the environment.
  • The balance of nature is very delicate and can be easily upset.
  • I have switched to photovoltaic products for ecological reasons.
  • When I have a choice between two equal products, I purchase the one less harmful to other people and the environment.
[22,26]
Government Support
  • The government is actively promoting the purchase of photovoltaic products by issuing guidelines and policies.
  • For me, the government supporting photovoltaic products is important.
  • The government encourages purchasing photovoltaic products.
  • The government has good laws and regulations in place to encourage purchasing photovoltaic products.
  • For me, the government’s promotion of photovoltaic products is important.
[43]
Purchase Intention
  • I plan to purchase photovoltaic products in the future.
  • I am willing to purchase photovoltaic products.
  • From now on, I plan to purchase photovoltaic products.
  • I intend to pay more for photovoltaic products.
[16]

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Sustainability 17 08409 g001
Figure 1. Proposed research model.
Figure 1. Proposed research model.
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Figure 2. Research model with path coefficient and p-Values.
Figure 2. Research model with path coefficient and p-Values.
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Figure 3. GS moderates the relationship between EC and BI.
Figure 3. GS moderates the relationship between EC and BI.
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Table 1. Respondent profile.
Table 1. Respondent profile.
CharacteristicsFrequencyPercentage
Gender
Male31246.22
Female36353.78
Ethnicity
Han Nationality63594.07
Minor Nationality405.93
Age
18–19-Year-Old34350.81
20–21-Year-Old17325.63
22–23-Year-Old10014.81
24–25-Year-Old598.74
Source of Income
Parents60289.19
Grant and Scholarship314.59
National Education Loan223.26
Part-time Job202.96
Table 2. Construct reliability and convergent validity.
Table 2. Construct reliability and convergent validity.
ConstructItemsLoadingAVECRVIF
Attitude (ATT)ATT10.8110.7230.9132.524
ATT20.85
ATT30.857
ATT40.883
Subjective Norms (SN)SN10.910.80.9413.065
SN20.923
SN30.929
SN40.811
Perceived Behavioural Control (PBC)PBC10.820.690.9172.076
PBC20.884
PBC30.882
PBC40.823
PBC50.735
Environmental Responsibility (ER)ER10.7320.6690.891.889
ER20.833
ER30.856
ER40.846
Environmental Consciousness (EC)EC10.8440.6270.872.946
EC20.768
EC30.772
EC40.78
Government Support (GS)GS10.8730.7910.952.315
GS20.881
GS30.915
GS40.881
GS50.896
Purchase Intention (PI)PI10.9050.7850.9362.855
PI20.891
PI30.889
PI40.859
Table 3. Discriminant validity using HTMT.
Table 3. Discriminant validity using HTMT.
ATTSNPBCERECGSPI
ATT
SN0.835
PBC0.6060.723
ER0.5360.4520.450
EC0.6190.6520.6150.787
GS0.5510.5370.4960.6480.784
PI0.5980.6710.6840.5170.8280.721
Table 4. Path coefficients and hypotheses testing.
Table 4. Path coefficients and hypotheses testing.
Hypo.RelationshipBetat-Valuep-ValueBCI-LLBCI-ULf2Decision
H1ATT → PI0.0390.8470.198−0.0360.1130.039Not Supported
H2SN → PI0.1182.3660.0090.0420.2060.118Supported
H3PBC → PI0.2335.1610.0000.1560.3050.233Supported
H4ER → PI−0.1012.5690.005−0.168−0.038−0.059Not Supported
H4aER → ATT0.2204.0100.0000.1300.3100.220Supported
H4bER → SN0.0661.1840.118−0.0220.1580.066Not Supported
H4cER → PBC0.1091.8760.0300.0130.2020.109Supported
H5EC → PI0.3817.1760.0000.2950.4690.567Supported
H5aEC → ATT0.3866.4160.0000.2850.4840.386Supported
H5bEC → SN0.5238.7920.0000.4210.6140.523Supported
H5cEC → PBC0.4667.6650.0000.3600.5610.466Supported
Table 5. Hypotheses testing for the indirect relationship.
Table 5. Hypotheses testing for the indirect relationship.
Hypo.RelationshipBetat-Valuep-ValueBCI-LLBCI-ULf2Decision
H6aER → ATT → PI0.0080.0820.211−0.0070.029NoneNot Supported
H7aER → SN → PI0.0081.0310.1510.0000.026NoneNot Supported
H8aER → PBC → PI0.0251.6360.0510.0030.053NoneNot Supported
H6bEC → ATT → PI0.0150.8320.203−0.0130.046NoneNot Supported
H7bEC → SN → PI0.0622.2060.0140.0210.115NoneSupported
H8bEC → PBC → PI0.1084.4320.0000.0710.150SmallSupported
Table 6. Hypotheses testing for moderating effect.
Table 6. Hypotheses testing for moderating effect.
Hypo.RelationshipBetat-Valuep-ValueBCI-LLBCI-ULf2Decision
H9ATT*GS → PI−0.0751.6730.047−0.148−0.005−0.075Not Supported
H10SN*GS → PI0.0571.2190.111−0.0210.1320.057Not Supported
H11PBC*GS → PI0.0090.1860.426−0.0620.0870.009Not Supported
H12ER*GS → PI−0.0381.1380.128−0.0920.015−0.038Not Supported
H13EC*GS → PI0.0711.7660.0390.0040.1360.071Supported
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MDPI and ACS Style

Li, X.; Li, M.; Ling, P.-S.; Chin, C.-H. Modelling Gen Z’s Photovoltaic Purchase Intentions: A Mediator–Moderator Model. Sustainability 2025, 17, 8409. https://doi.org/10.3390/su17188409

AMA Style

Li X, Li M, Ling P-S, Chin C-H. Modelling Gen Z’s Photovoltaic Purchase Intentions: A Mediator–Moderator Model. Sustainability. 2025; 17(18):8409. https://doi.org/10.3390/su17188409

Chicago/Turabian Style

Li, Xiaoxiao, Ming Li, Pick-Soon Ling, and Chee-Hua Chin. 2025. "Modelling Gen Z’s Photovoltaic Purchase Intentions: A Mediator–Moderator Model" Sustainability 17, no. 18: 8409. https://doi.org/10.3390/su17188409

APA Style

Li, X., Li, M., Ling, P.-S., & Chin, C.-H. (2025). Modelling Gen Z’s Photovoltaic Purchase Intentions: A Mediator–Moderator Model. Sustainability, 17(18), 8409. https://doi.org/10.3390/su17188409

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