Abstract
South Africa, like many other emerging economies, has witnessed a growing awareness of climate change in recent years, driven by school-based initiatives, media coverage, and non-governmental campaigns. However, evidence indicates that this awareness does not consistently translate into green purchasing behaviour. Drawing on quantitative data collected from 384 respondents residing in urban and semi-urban areas of the Eastern Cape Province, this study examines the impact of consumer attention to green communication, green attitudes, and awareness of climate change on green purchasing behaviour after controlling for demographic variable effects (gender, age, education and income level). Primary data were obtained through a survey and statistically analysed using SMART-PLS 4 software. The results of the structural equation modelling reveal that consumer attention and green attitude significantly influence green purchasing behaviour, consistent with the Theory of Planned Behaviour. In contrast, awareness of climate change exhibits a non-significant negative effect on green purchase behaviour, an outcome that diverges from existing empirical evidence, which generally reports positive associations between these variables in other emerging economies. This finding suggests that in contexts where poverty and income inequality persist, increasing awareness of climate change may paradoxically correspond with a reduction in green purchasing. The study recommends implementing strategies to enhance access to eco-friendly products and reduce their cost, thereby improving affordability in resource-constrained nations.
1. Introduction
Growing concerns over climate change, environmental degradation, and unsustainable consumption patterns have intensified global interest in green consumerism [1,2]. Green purchase behaviour, defined as the choice of environmentally friendly products, has become a pivotal component of sustainable development [3]. Despite global awareness campaigns and corporate efforts to provide eco-friendly alternatives, consumer adoption of green products remains inconsistent, particularly in emerging economies [4]. Dou et al. [5] lament that most consumers still do not prioritise eco-friendly products. This persistent “attitude–behaviour gap,” where expressed environmental concern does not consistently translate into green purchasing [6], raises an important question: what truly drives or hinders green purchase behaviour?
To answer the question, this research pays significant attention to three psychological factors that are central to answering this question: consumer attention to green communication, green attitude, and awareness of climate change. Consumer attention to green communication refers to the degree of focus and interest individuals allocate to environmental information and green products [7,8,9]. A green attitude reflects favourable or unfavourable evaluations of eco-friendly goods, while awareness of climate change encompasses knowledge and consciousness of environmental issues and individual responsibility [10,11]. These factors are believed to influence decision-making processes and, when combined, may offer deeper insights into the drivers of sustainable purchasing [12].
South Africa is an emerging economy [13], and like other emerging economies, consumer awareness of climate change has increased in recent years, driven by school-based initiatives, media, and non-governmental campaigns [14]. However, evidence suggests this awareness does not consistently translate into green purchasing [15]. For instance, youth and middle-income consumers express interest in eco-friendly products, yet their actual market share remains low [16]. Similar findings in emerging economies indicate that even environmentally conscious consumers may not follow through on green purchases due to limited product visibility or insufficient attention to green alternatives [17,18].
This highlights consumer attention as a neglected yet critical variable in green marketing literature. While attitudes and awareness are frequently studied [3,19], research rarely integrates these constructs with attention, particularly in the context of developing economies. Much of the existing literature also originates from developed countries [5,20,21] where consumer priorities and cultural contexts differ significantly from South Africa. This limits the generalisability of findings and underscores the need for locally grounded investigations.
Therefore, this study aims to examine how consumer attention to green communication, green attitude, and awareness of climate change collectively influence green purchase behaviour in South Africa. By integrating these constructs into a single model, the research addresses a critical gap in green consumer literature and provides context-specific insights into sustainable consumption. The findings will be valuable to policymakers, environmental organisations, and marketers in designing targeted strategies that not only raise awareness but also strengthen attention and attitudes, ultimately fostering meaningful behavioural change.
1.1. Research Objectives
The study sought:
- To investigate the impact of consumer attention to green communication on green purchase behaviour;
- To investigate the impact of green attitude on green purchase behaviour;
- To investigate the impact of awareness of climate change on green purchase behaviour;
- To investigate the impact of consumer attention, green attitude and awareness of climate change on green purchase behaviour after controlling for demographic variables (gender, age, income and education level).
1.2. Research Context
This study is situated within the broader discourse of sustainable consumption, which has gained increasing global attention due to the escalating environmental challenges caused by overconsumption, climate change, and resource depletion [19]. However, the low adoption rates of eco-friendly products are a major concern in developing nations [22]. This has prompted governments, businesses, and civil society to have intensified efforts to promote green products as an alternative to conventional goods, positioning consumer behaviour as a critical driver of sustainability transitions [23]. In the South African context, promoting green consumption is particularly important due to the country’s dual challenge of addressing developmental needs while ensuring environmental sustainability. South Africa faces significant environmental pressures, including energy-intensive production systems, waste management challenges, and high carbon emissions [24]. At the same time, consumers in regions such as the Eastern Cape Province are shaped by unique socio-economic and cultural conditions that influence their purchasing decisions. Factors such as income disparities, levels of environmental awareness, and exposure to sustainability campaigns may significantly impact consumer attention and attitudes toward green products. Despite these realities, existing research in South Africa remains limited, with most studies focusing on consumer attitudes in isolation or drawing heavily on evidence from developed economies.
Against this backdrop, the present study contributes to the growing body of knowledge by investigating the combined influence of consumer attention, green attitude, and environmental awareness on green purchase behaviour. This research context highlights the urgency and relevance of the study, offering insights that are both academically significant and practically useful for designing interventions to promote green consumption in South Africa.
2. Literature Review
2.1. Theoretical Framework
The Theory of Planned Behaviour (TPB) [25] builds on the earlier Theory of Reasoned Action (TRA) [26]. The TPB was designed to address the limitations of TRA by incorporating an additional construct, perceived behavioural control, to account for external factors that may constrain or facilitate the performance of [27,28].
The TPB rests on several key assumptions that shape its application in consumer research. First, it is grounded in the rational choice assumption, which suggests that consumers act as rational decision-makers who process available information before forming intentions and engaging in behaviour. In the context of green consumption, this implies that consumers are expected to weigh the benefits of eco-friendly products against those of conventional alternatives before making a purchasing decision. Second, the theory assumes that behavioural intention is the most immediate and reliable predictor of actual behaviour. Thus, a consumer’s intention to purchase green products strongly predicts whether the purchase will occur.
Furthermore, TPB posits that its core constructs, namely, attitude, subjective norms, and perceived behavioural control, are distinct yet interrelated, each contributing uniquely to intention formation while jointly shaping behaviour. Another assumption is that of volitional control, whereby consumers who intend to buy green products are generally able to do so, provided external barriers such as high prices or limited product availability are not prohibitive. Finally, the theory assumes that behavioural determinants remain relatively stable during the study period. However, in rapidly changing consumer environments, such as dynamic markets in South Africa, this stability may not always be present, which can affect the predictive power of the model.
In principle, the TPB comprises three core constructs, attitude, subjective norms, and perceived behavioural control, which jointly determine behavioural intention [25]. However, Ajzen, the developer of the model, explicitly acknowledges that additional predictors may be incorporated when they are theoretically justified, contextually relevant, or capable of significantly enhancing the model’s predictive power.
Aligned with this guidance, our study employs the TPB as a guiding framework rather than as a strict template requiring all original constructs. Testing subjective norms or perceived behavioural control is therefore not the primary intention of this study. Instead, the study seeks to extend the theory by examining the predictive power of attention to green communication, green attitude, and climate change awareness, factors that have recently emerged as salient determinants of green purchasing behaviour in contemporary sustainability literature.
Including all original TPB constructs would risk producing a basic replication of previous studies, many of which have already extensively validated the core TPB variables. Our aim, rather, is to advance the model’s applicability by integrating contextually meaningful predictors that better reflect the dynamics of consumer environmental behaviour in the present study setting.
2.2. Consumer Attention to Green Communication
Correia et al. [29] defined consumer attention to green communication as the extent to which individuals notice, focus on, and process marketing messages, product labels, or promotional content that emphasise environmental attributes or sustainability claims. Similarly, Jaiswal et al. [30] describe consumer attention as the degree to which consumers notice, concentrate on, and mentally process stimuli related to products, services, or marketing messages. In this context, consumer attention to green communication constitutes the first cognitive step in the decision-making process. Green communication tools, such as eco-labels, advertising messages, or packaging information, can only influence consumer attitudes and behaviours if they are able to capture attention [31].
High levels of attention increase the likelihood that consumers will recognise the environmental value of products, evaluate them positively, and incorporate them into their purchase considerations. Conversely, low levels of attention often result in eco-friendly alternatives being overlooked despite their availability. Attention thus serves as a critical gateway in the consumer decision-making process, determining whether a consumer even becomes aware of a product before considering a purchase [32]. In marketing and consumer behaviour research, attention is recognised as the initial stage in brand–consumer communication. Without it, the formation of attitudes and purchase intentions is unlikely to occur. Moreover, attention can be influenced by multiple factors, including advertisement design, product packaging, brand visibility, personal interests, environmental concerns, and the consumer’s situational needs or goals [30].
2.3. Green Attitude
Mehta and Chahal [33] defined green attitude as a consumer’s positive or negative evaluation of environmentally friendly products, practices, or behaviours, shaped by personal beliefs, values, and emotions related to environmental protection. Similarly, Nguyen [34] described it as an individual’s evaluation of eco-friendly products and practices, influenced by personal values, beliefs, and concern for the natural environment. Consumers with strong green attitudes are more likely to support eco-friendly initiatives, prefer sustainable products, and engage in behaviours that minimise environmental harm [18]. In marketing, a green attitude is particularly important because it influences whether consumers choose green products over conventional alternatives, even when cost or accessibility differ [35]. Shimul and Cheah [36] further emphasised that a green attitude reflects the degree to which individuals support sustainability initiatives and prioritise eco-friendly alternatives. Ultimately, consumers with strong green attitudes are more likely to perceive green products as desirable and align their purchase decisions with environmental protection goals, making this construct a key psychological driver of green purchase behaviour.
2.4. Awareness of Climate Change
Açıkalın et al. [37] defined awareness of climate change as the level of knowledge, understanding, and consciousness individuals possess regarding the causes, consequences, and potential solutions to climate-related issues such as global warming, rising sea levels, extreme weather, and biodiversity loss. This construct encompasses both cognitive dimensions (knowledge of scientific facts and environmental policies) and affective aspects (concern and perceived personal responsibility). Higher levels of awareness often foster pro-environmental attitudes and behaviours, as individuals who recognise the urgency of climate challenges are more likely to adopt sustainable practices and support green initiatives [38].
Within consumer behaviour, awareness of climate change reflects the degree to which environmental knowledge influences decision-making [39]. It includes understanding how products and companies contribute to, or mitigate, environmental problems such as pollution, waste, and climate change [40]. Awareness also extends to recognising eco-labels, certifications (e.g., organic or recyclable), and the long-term benefits of green products [41]. Consequently, higher environmental awareness can shape consumer perceptions, strengthen positive attitudes, and encourage environmentally responsible purchasing decisions.
2.5. Consumer Green Purchase Behaviour
Consumer green purchase behaviour refers to the decision-making processes and actions of consumers when selecting and buying products that are environmentally friendly, sustainable, and produced with minimal negative environmental impact [29]. It encompasses preferences for goods that are recyclable, biodegradable, energy-efficient, or certified as eco-friendly, thereby reflecting concern for environmental protection and sustainable development [42]. Green purchasing behaviour is shaped by psychological factors such as attitudes, awareness, and attention, alongside external influences including social norms, marketing communication, and product availability [3]. As a form of pro-environmental behaviour, it represents a critical pathway toward reducing ecological footprints and advancing sustainable consumption.
2.6. The Impact of Consumer Attention to Green Communication on Green Purchase Behaviour
Consumer attention plays a critical role in shaping purchasing decisions, particularly in the context of environmentally friendly products. When individuals focus on eco-labels, packaging cues, sustainability information, and green advertisements, they become more aware of the environmental benefits associated with such products. This heightened awareness increases the likelihood of translating environmental concern into actual purchasing behaviour [43].
First, consumer attention facilitates information processing, enabling individuals to notice and evaluate green product attributes such as recyclability, organic certification, or reduced carbon footprint. Correia et al. [29] argued that attentive consumers are more likely to process green messages deeply, which in turn strengthens positive attitudes and purchase intentions. Second, attention to environmental messages can activate pro-environmental values and norms, encouraging consumers to align their behaviour with sustainable choices. Studies by Wang et al. [44] and Yang et al. [45] show that consumers who actively attend to sustainability cues are more motivated to reduce their ecological footprint through purchasing decisions. Third, in contexts where greenwashing is prevalent, attention allows consumers to critically assess environmental claims, reducing scepticism and fostering trust in genuinely sustainable brands, thereby increasing green purchase behaviour [46].
In South Africa, where environmental education and sustainable marketing practices are still in development, consumer attention is particularly crucial. Attentive consumers in urban and semi-urban areas are not only more likely to recognise the long-term benefits of green products but also to influence peers, contributing to a cultural shift toward sustainable consumption [24].
Based on this empirical evidence, the study hypothesises that:
Hypothesis 1:
Consumer attention to green communication significantly impacts consumer green purchase behaviour.
2.7. Green Attitudes’ Impact on Green Purchase Behaviour
Green attitude refers to an individual’s positive or negative evaluation of performing environmentally friendly behaviours, such as purchasing eco-friendly products or supporting sustainable brands [47]. In consumer research, attitudes are regarded as one of the strongest predictors of behaviour, as suggested by the Theory of Planned Behaviour [25]. A positive green attitude reflects a consumer’s belief that buying environmentally friendly products contributes to sustainability, which can significantly influence actual purchasing decisions.
Empirical studies consistently demonstrate that a green attitude exerts a positive impact on green purchase behaviour. For example, Kumar et al. [48] found that Indian consumers with stronger pro-environmental attitudes were more inclined to purchase green products. Similarly, Joshi and Rahman [49] revealed that favourable attitudes toward environmental protection strongly predict the willingness to pay a premium for eco-friendly goods. These findings suggest that consumers who value sustainability are more likely to act on their beliefs through purchasing choices.
A green attitude also plays a role in shaping consumer loyalty and trust. Research by Majeed et al. [35] highlights that consumers with positive environmental attitudes tend to develop stronger loyalty toward green brands, further reinforcing sustainable purchasing habits. Moreover, attitudes influence how consumers interpret green marketing messages; a positive attitude increases receptivity to eco-labels, certifications, and advertising campaigns that emphasise sustainability [34].
In the South African context, pro-environmental attitudes are gradually emerging, but their impact on behaviour remains inconsistent. While research [24] reports increasing environmental concern among South African consumers, the translation of this concern into green purchase behaviour is still limited due to barriers such as higher prices, limited availability, and scepticism toward product claims. Nonetheless, positive green attitudes represent a critical psychological driver that can help narrow the attitude–behaviour gap if combined with awareness and attention.
Based on this empirical evidence, the study hypothesises that:
Hypothesis 2:
Green attitude significantly impacts consumer green purchase behaviour.
2.8. The Impact of Awareness of Climate Change on Green Purchase Behaviour
Awareness of climate change has a positive impact on green purchase behaviour because it enhances consumers’ understanding of the environmental consequences of their consumption choices, thereby motivating them to adopt more sustainable purchasing patterns [50]. When individuals are knowledgeable about the risks of global warming, carbon emissions, and environmental degradation, they are more likely to perceive green products as a means of contributing to climate change mitigation [34]. This heightened awareness shapes their values and strengthens their sense of environmental responsibility, often leading to a willingness to support eco-friendly alternatives, such as organic products, biodegradable packaging, or energy-efficient appliances. Furthermore, consumers who are aware of climate change issues are more inclined to align their purchasing behaviour with their moral and ethical beliefs, bridging the attitude–behaviour gap. Empirical studies confirm that climate change awareness significantly increases green purchase intentions and actual buying decisions by fostering environmental concern and social consciousness [51]. Thus, raising awareness of climate change plays a crucial role in promoting sustainable consumption practices and encouraging consumers to make more environmentally friendly purchasing choices.
Based on this empirical evidence, the study hypothesises that:
Hypothesis 3:
Awareness of climate change significantly impacts consumer green purchase behaviour.
3. Research Methodology
This study employed quantitative research methods. Quantitative research utilises statistical, logical, and mathematical methods to produce accurate information and facts [52]. Quantitative research methods are appropriate for this study because the aim is to examine the impact of consumer attention to green communication, green attitude, and awareness of climate change on green purchase behaviour among consumers. These constructs were measured using structured questionnaires and analysed statistically to test hypotheses formulated during the conceptualisation stage. The study employed positivist philosophy because positivism supports quantitative methods, which involve the use of numerical data and statistical techniques for analysis and, more importantly, objectivity [53,54].
3.1. Population and Sampling
This study targeted urban, semi-urban and rural areas of South African consumers aged 18 and above (adults likely to be independent) who are familiar with green products (through marketing messages and sustainability campaigns) or have access to them (e.g., eco-friendly household items, organic food, or sustainable clothing). The authors targeted residents in the second-largest city of the Eastern Cape Province, with a population of at least 470,000. These areas also provide a mix of socioeconomic and cultural diversity, which is essential for understanding varied consumer behaviours. Stratified random sampling was employed to ensure a representative sample of urban and semi-urban consumers in the Eastern Cape Province. Stratified sampling is appropriate because consumers differ in terms of age, income level, education, and exposure to green products, which may influence their green purchase behaviour. By dividing the population into distinct strata based on relevant characteristics (e.g., age group, education level, or income), and then randomly selecting respondents from each subgroup, the method ensures balanced representation. This approach guarantees that every consumer within the target population has a known and non-zero chance of being selected, enhancing the generalizability of the findings to the broader consumer base in the region. Residents from rural areas that surround the city participated in the study during grant payout days (usually the first week of the month). To receive their grant payout, most grant recipients travel to the city where they can access banks and major retail outlets to stock up on supplies. Given the stated population size, 384 respondents were selected for the study using the Raosoft sample size calculator [55]. The sample included consumers from both middle- and lower-income segments, ensuring representation across diverse socioeconomic contexts, including historically disadvantaged regions. Consumers frequenting well-known pro-green retail outlets were chosen, and they formed two strata. South Africa, as a country, has a larger female population in comparison to its male population. In that regard, two strata were created, one for females and one for males. Statistics South Africa [56] reports that for every 100 females, there are 94 males (1.07 females to 1 male). The study’s sample, however, showed a 68% female-to-32% male ratio, suggesting that women typically perform household shopping duties more frequently than men.
3.2. Measures, Data Collection and Ethical Considerations
The study adopted existing research instruments to measure the variables, which were later subjected to reliability and validity tests using structural equation modelling. The Consumer Attention to Green Communication Scale, the Green Attitude Scale, and the Consumer Green Purchase Behaviour scale, each with five items, were adopted from Correia et al. [29]. The awareness of climate change scale, also with five items, was adopted from Mishal et al. [57]. All the adopted scales were measured on a five-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree). Primary data was collected through a self-administered questionnaire. Owing to limited resources, twenty fieldworkers were employed to assist with the fieldwork processes after undergoing training. Data was gathered once over a period of 8 months, given the vast geographical space they had to cover, as more leads were being generated. Prior to primary data collection, the authors applied for an ethics clearance certificate to demonstrate their commitment to adhering to the principles of ethics when conducting studies involving humans, including the right to privacy, the right to withdraw without question, and the principle of anonymity, among other important ethical considerations. After a thorough review of the application, the Senate Research Ethics Committee granted the certificate with the protocol number: 069/2025/HBM/BME-7668.
3.3. Demographic Profile of the Respondents
The demographic characteristics of respondents were examined with respect to gender, age, education, monthly income, and place of residence. As shown in Table 1, female respondents constituted the majority at 68%, while males accounted for 32%. In terms of age, young adults between 30 and 39 years dominated the sample (51%), followed by those aged 18–29 (34%) and those aged 40–49 (15%). Regarding education, degree holders represented the largest group (45%), followed by postgraduate holders (25%). Diploma holders (19%) and matric holders (11%) were the least represented.
Table 1.
Demographic profile of the sample.
Income distribution presents a less favourable picture in terms of the affordability of green products. Most respondents (36%) reported earning less than R5000 per month (approximately US$288), followed by 29% who earned between R5001 and R10,000 per month (approximately US$576) and 29% who earned between R10,001 and R20,000 per month. A further 18% earned between R10,001 and R20,000, and R20,000 (approximately US$577–$1151), while only 17% reported incomes above R20,000 (US$1151 per month). With respect to place of residence, the majority (58%) lived in urban areas, followed by rural residents (28%) and a smaller proportion (14%) in semi-urban areas that combine both rural and urban characteristics.
3.4. Data Analysis and Software
Descriptive statistical analyses were conducted using the Statistical Package for the Social Sciences (SPSS) version 31. Structural equation modelling was performed using SmartPLS 4, selected for its robustness and user-friendly interface.
4. Results
Structural equation modelling (SEM) was performed using SMART-PLS 4 software. The two important steps associated with SEM, where the instrument used was assessed for reliability and validity, followed by assessment of the structural model, were undertaken.
4.1. The Reliability and Validity of the Measurement Instruments
Table 2 presents the reliability assessment of the measurement instruments used in this study. The reliability of the constructs was evaluated using Cronbach’s alpha and composite reliability (CR), which are standard measures for assessing internal consistency and overall measurement dependability [58]. The results show that all constructs achieved Cronbach’s alpha values above the recommended threshold of 0.5, indicating strong internal consistency. Specifically, Awareness of Climate Change (ACC) has a Cronbach’s alpha of 0.885, Consumer Attention to green communication (CA) has 0.891, Green Attitude (GA) has 0.877, and Green Purchase Behaviour (GPB) has the highest value of 0.960. These values demonstrate that the survey items used to measure each construct reliably capture the intended theoretical concept.
Table 2.
Measurement instruments’ reliability assessment.
Composite reliability values for all constructs also exceed the recommended minimum of 0.6, further confirming the reliability of the measurement instruments. ACC shows a CR of 0.912, CA of 0.920, GA of 0.910, and GPB of 0.969. The high CR values indicate that the latent variables have strong internal consistency, and the measurement model is dependable for further analysis. Overall, the reliability assessment confirms that the instruments used to measure the variables ACC, CA, GA, and GPB are statistically reliable and appropriate for the empirical investigation of their impact on green purchase behaviour. These findings provide a robust foundation for proceeding with the structural model testing in the subsequent analysis.
Convergent validity evaluates the extent to which multiple indicators of a construct converge or share a high proportion of variance, thereby confirming that they measure the same underlying concept [59]. In this study, convergent validity was assessed using outer loadings and average variance extracted (AVE). As recommended by Cheung et al. [59], outer loadings greater than 0.5 and AVE values exceeding 0.5 indicate acceptable convergent validity. Table 3 reveals that all indicators across the four constructs exhibit outer loadings above 0.735, demonstrating that each item strongly contributes to its respective construct. For ACC, outer loadings range from 0.735 to 0.883, with an AVE of 0.677, exceeding the 0.5 threshold. CA items range from 0.793 to 0.883, with an AVE of 0.697, while GA shows outer loadings between 0.774 and 0.855 and an AVE of 0.670. GPB demonstrates the highest convergence, with outer loadings ranging from 0.917 to 0.937 and an AVE of 0.863. These results confirm that the indicators of each construct are well-aligned and capture the intended latent variables. The AVE values above 0.5 further support the notion that a substantial portion of the variance in each construct is explained by its indicators, thereby establishing strong convergent validity. This indicates that the measurement model is robust and reliable for subsequent structural model analysis of the impact of ACC, CA, and GA on GPB.
Table 3.
Convergent validity.
To assess discriminant validity, the Fornell–Larcker Criterion was used. Discriminant validity ensures that a construct is truly distinct from other constructs by demonstrating that it shares more variance with its indicators than with other constructs in the model [60]. The Fornell–Larcker criterion is a widely used method to assess discriminant validity, where the square root of the AVE of each construct should be greater than its correlations with other constructs. Table 4 presents the Fornell–Larcker criterion results for the study constructs. The diagonal values represent the square root of the AVE for each construct, while the off-diagonal values show the correlations between constructs. The results indicate that the square root of the AVE for each construct is higher than the corresponding correlations with other constructs. Specifically, ACC has a square root AVE of 0.823, which is higher than its correlations with CA (0.251), GA (0.773), and GPB (0.295). Similarly, CA’s square root AVE is 0.835, exceeding its correlations with ACC (0.251), GA (0.241), and GPB (0.697). GA and GPB follow the same pattern, with diagonal values of 0.819 and 0.929, respectively, all higher than their respective correlations with the other constructs. These findings confirm that the constructs in the study exhibit adequate discriminant validity, indicating that each construct is distinct and measures unique aspects of the model. This ensures that the subsequent structural model analysis reliably reflects the relationships between ACC, CA, GA, and GPB without issues of multicollinearity or construct overlap.
Table 4.
Fornell–Larcker criterion.
The Heterotrait–Monotrait (HTMT) ratio is another robust method for assessing discriminant validity, particularly in partial least squares structural equation modelling (PLS-SEM). According to Cheung et al. [59], discriminant validity is confirmed when the correlation between constructs does not exceed 1.0, and HTMT values below 0.85 (or 0.90 in more lenient criteria) indicate that constructs are sufficiently distinct. Table 5 presents the HTMT values for the study constructs. The results show that all HTMT values fall below the conservative threshold of 0.85, except for the correlation between ACC and GA, which is 0.860. While slightly above 0.85, this value is still acceptable in many applied research contexts, indicating a high but tolerable relationship between ACC and GA. All other constructs demonstrate clear discriminant validity, with HTMT values of 0.255 (ACC to CA), 0.271 (CA to GA), 0.288 (ACC to GPB), 0.748 (CA to GPB), and 0.391 (GA to GPB). Overall, the HTMT analysis supports the discriminant validity of the measurement model, confirming that the constructs ACC, CA, GA, and GPB are conceptually distinct. This provides confidence that the subsequent structural model results will accurately capture the unique effects of each independent variable on green purchase behaviour.
Table 5.
Heterotrait–Monotrait ratio (HTMT)—Matrix.
Cross loadings provide an additional assessment of discriminant validity by examining the degree to which each indicator loads highest on its intended construct compared to other constructs. A valid measurement model requires that each indicator exhibits a stronger loading on its corresponding construct than on any other construct in the model. Table 6 presents the cross-loadings for the study constructs. The results demonstrate that all indicators load highest on their respective constructs. For example, ACC indicators range from 0.735 to 0.883 on the ACC construct, compared to lower cross-loadings on CA (0.101 to 0.306), GA (0.576 to 0.705), and GPB (0.157 to 0.328). Similarly, CA indicators load highest on CA (0.793 to 0.883), with lower cross-loadings on ACC (0.188 to 0.241), GA (0.163 to 0.251), and GPB (0.514 to 0.644). Green Attitude (GA) indicators load strongly on GA (0.774 to 0.855) and lower on other constructs, while GPB indicators load highest on GPB (0.917 to 0.937), with lower cross-loadings on ACC (0.247 to 0.303), CA (0.622 to 0.687), and GA (0.301 to 0.365). These results confirm that each indicator is most strongly associated with its intended latent variable, supporting the discriminant validity of the measurement model. Therefore, ACC, CA, GA, and GPB are distinct constructs, and the measurement model is reliable for testing the structural relationships in this study.
Table 6.
Cross loadings.
Data quality was further assessed by examining common method bias (CMB). Using factor analysis, Harman’s single-factor test was conducted, and the results showed that a single factor accounted for 41.86% of the total variance. This is below the recommended threshold of 50%, indicating that common method bias is not a concern in this study [61].
4.2. Structural Model Assessment
The adequacy of the data fit to the conceptual model was assessed using key fit indices, specifically the global goodness-of-fit (GoF) statistic and the normed fit index. These indicators provide evidence of whether the hypothesised structural model adequately represents the observed data. According to Wetzels et al. [62], the GoF statistic is a geometric mean of the average variance extracted (AVE) values and the average R2 values of the endogenous constructs. The GOF was derived as 0.450 for this study and is considered large, strong, and acceptable, as it exceeds the 0.36 threshold for a large effect. In addition to the global goodness-of-fit (GoF), the model fit was further evaluated using the Standardised Root Mean Square Residual (SRMR) and the Normed Fit Index (NFI). An NFI should ideally be greater than 0.90 to indicate a good fit, though values above 0.85 are considered marginally acceptable [63]. For SRMR, values below 0.10 are typically regarded as indicative of an acceptable fit. The results indicate that the SRMR value for both the saturated and estimated models is 0.060, which is well below the recommended threshold of 0.10, demonstrating an acceptable level of model fit. The NFI values for both models were 0.836, which falls slightly below the ideal threshold of 0.90 but remains within the marginally acceptable range of 0.85 or higher. Taken together, these results suggest that the structural model provides a reasonably good fit to the data, with SRMR confirming strong model adequacy and NFI indicating that, although the fit is slightly below the optimal benchmark, it remains acceptable for the purposes of this study.
4.3. Path Analysis
Path analysis was employed to investigate the causal relationships between latent variables after the suggested measurement and structural models had been assessed and refined [64]. As stated by Sarstedt et al. [65], to get estimated results that explain the relationships between these latent variables, SEM suggests that certain latent variables either directly or indirectly impact other latent variables within the model. The estimation findings resulting from hypothesis testing for the current investigation are shown in Table 7. The results reveal that two of the three proposed hypotheses (H1 and H2) were statistically significant, whereas H3 was not supported. Specifically, Consumer Awareness (CA) had a positive influence on Green Purchase Behaviour (GPB), β = 0.651, t = 12.568, p = 0.000, while Green Attitude (GA) also showed a significant positive effect on GPB, β = 0.266, t = 2.725, p = 0.006. In contrast, Awareness of climate change’s impact had an insignificant negative relationship with GPB (β = −0.074; t = 0.803; p = 0.422). These findings indicate that consumer awareness and a green attitude are key drivers of green purchasing behaviour, while awareness of climate change’s impact does not significantly influence consumers’ green purchasing decisions.
Table 7.
Predictors of green purchase behaviour.
The study further sought to examine the impact of CA, GA, and ACC on GPB after controlling for the effects of demographic variables, including gender, age, education, and income levels. After controlling demographic variables, including gender, age, education, and income levels, the impact of consumer attention on GPB decreased slightly but remained significant, B = 0.649, t = 12.381, p < 0.001. A similar phenomenon was observed in the impact of GA on GPB, which was slightly reduced but remained significant (B = 0.255, t = 2.786, p = 0.002). The impact of ACC on GPB marginally improved but remained insignificant after controlling for demographic variables, B = −0.073, t = 0.823, p = 0.442. Overall, the demographic variables do not add a significant contribution to the model with the respondents’ gender (B = 0.017, t = 0.287, p = 0.774), age (B = 0.051, t = 0.815, p = 0.416), education level (B = −0.006, t = −0.105, p = 0.916), and income level (B = −0.060, t = −0.932, p = 0.353) all yielding insignificant results.
5. Discussion
5.1. Theoretical Contribution
The study’s measures have been rigorously tested prior to their use in this study. To ensure their applicability in the South African context, we employed a similar testing approach, examining construct validity, reliability, and validity. The outcome suggests that the instrument is applicable in the South African context, making a significant contribution to theory and practice. The study examined the influence of consumer attention to green communication, green attitude, and climate change awareness on green purchase behaviour in South Africa’s Eastern Cape. The finding that consumer attention has a significant positive effect on green purchase behaviour reinforces existing literature underscoring its central role in shaping environmentally friendly consumption choices. For instance, Wang et al. [66] found that heightened attention to eco-labels and green certifications enhances consumer trust and strengthens purchase intentions. Similarly, Steenis et al. [67] demonstrated that close attention to sustainability claims in packaging increases alignment between purchasing behaviour and environmental values. Zhang et al. [38] further argued that consumer attention to environmental attributes serves as a cognitive trigger for sustainable consumption. The present study thus contributes to the literature by confirming that consumer attention to green communication is a vital driver of green purchase behaviour in developing contexts. This finding is consistent with the assumptions of the Theory of Planned Behaviour (TPB), which posits that consumers act as rational decision-makers and that repeated exposure to eco-friendly messages increases the likelihood of actual purchase behaviour.
The study also found that green attitude significantly and positively influences green purchase behaviour, a finding strongly supported by international evidence. For example, Kumar et al. [48] demonstrated that pro-environmental attitudes among Indian consumers foster green product adoption, while Joshi and Rahman [49] showed that favourable attitudes toward environmental protection predict willingness to pay a premium for eco-friendly goods. Similarly, Nguyen [34] found that positive attitudes enhance receptivity to eco-labels and sustainability campaigns in Vietnam, and Majeed et al. [35] revealed that green attitudes build loyalty and trust among Pakistani consumers. The present study reinforces these findings within the South African context, emphasising that green attitudes act as a key psychological driver of sustainable consumption. This aligns with TPB’s theoretical assertion that attitudes are a fundamental determinant of behavioural intention and subsequent action.
Interestingly, the study revealed a non-significant negative relationship between climate change awareness and green purchase behaviour. This finding contrasts with previous empirical evidence suggesting that higher awareness of climate issues is positively associated with pro-environmental behaviour [34,50]. The result makes an important theoretical contribution by highlighting the limitations of assuming a linear relationship between awareness and behaviour. The “attitude–behaviour gap” provides a useful lens to interpret this outcome, as awareness may not always translate into sustainable purchasing due to contextual barriers. In the South African context, key barriers include price sensitivity and limited accessibility to green products. Consequently, the scarcity of green products may significantly influence consumers’ purchasing decisions, affecting individuals across all income levels. This finding suggests that awareness alone is insufficient to drive behaviour in developing economies, extending TPB by showing that structural constraints may override cognitive drivers. This is supported by Ogiewonyi et al. [68], who provided evidence showing that although awareness is often positively related to green purchase behaviour, the presence of factors such as price sensitivity, distrust, and perceived ineffectiveness drastically reduces consumer pro-environmental behaviour. This reinforces the study’s assessment that, in the presence of contextual barriers, consumer behaviour can be compromised, leading to counterproductive sustainability outcomes.
Some studies have reported similar findings, namely a negative relationship between climate change awareness and green purchase behaviour. For example, Ref. [69] found that purchasing green products reduces the likelihood of engaging in subsequent sustainable behaviours, including policy support for green initiatives at a broader level. In other words, the increased awareness of climate change does not always translate to sustained cumulative green purchasing behaviour but can sometimes yield unexpected pro-environmental behaviours as a negative spillover effect. Additionally, Tucholska et al. [70] investigated whether emotions, particularly climate anxiety, fatalism, and personality profiles, lead to pro-environmental behaviour, that is, translate into actions. The study reports the existence of a complex relationship whereby higher awareness was not found to lead to pro-environmental behaviour but rather was associated with reduced planned action. The explanation for this phenomenon is that some pro-environmental behaviours are highly conditional, resulting in high awareness being associated with lower action due to emotional responses, such as eco-anxiety and fatalism. Furthermore, research also reports that heightened awareness of environmental claims, particularly misleading information (greenwash messages), increases consumers’ perceived risk, green confusion, which subsequently negatively affects green purchasing behaviour [71].
5.2. Managerial Implications
Given that consumer attention to green messages and green attitudes significantly influence green purchase behaviour, managers should prioritise strategies that both capture attention and reinforce pro-environmental attitudes. This can be achieved through clear labelling, credible and verifiable information, and the use of visible eco-certifications on product packaging, promotional materials, websites, and advertising platforms. Transparent communication of sustainability features, such as recyclability, reduced carbon footprint, and recognised certifications, is essential for building trust and encouraging the adoption of green products. In addition, green product managers should initiate sustainability campaigns and raise awareness by partnering with non-governmental organisations and environmental activists who advocate for stronger environmental policies. Leveraging platforms with high visibility, such as universities, national sports teams, and large public events, can further amplify awareness and foster long-term consumer engagement.
Equally important is ensuring the accessibility and affordability of green products. The negative relationship observed between awareness of climate change and green purchasing behaviour suggests that raising awareness alone is insufficient if consumers are unable to act on their intentions due to affordability barriers. In many developing countries, income inequality exacerbates this challenge, as green products are often perceived as premium-priced alternatives to conventional goods. Therefore, managers must strike a balance between enhancing awareness and facilitating action by adopting pricing strategies, distribution models, and promotional incentives that make green products more affordable and accessible to a wider audience.
6. Conclusions
This study examined the influence of consumer attention to green communication, green attitude, and climate change awareness on green purchase behaviour within a developing-country context, using the Theory of Planned Behaviour (TPB) as a guiding framework. Based on survey data from 384 respondents and structural equation modelling, the findings show that consumer attention to green communication and green attitude significantly and positively predict green purchasing behaviour. In contrast, awareness of climate change did not exhibit a significant positive effect. The demographic variables (gender, age, education, and income levels) did not make a significant contribution to the model after controlling for their effects.
These results contribute to the literature by extending the TPB to a developing-economy context and demonstrating that psychological predictors may function differently under varying socio-economic conditions. The study provides evidence that attention to environmental communication and environmentally positive attitudes remain crucial drivers of green purchasing, whereas awareness alone does not consistently lead to pro-environmental action.
The findings hold practical relevance for businesses and policymakers seeking to promote sustainable consumption in developing economies. Strengthening credible green communication, supporting positive consumer attitudes, and improving access to green products may help enhance green purchasing outcomes. Overall, the study advances theoretical and practical understanding by highlighting the need to consider both psychological and contextual factors when assessing green consumer behaviour in resource-constrained settings.
7. Limitations and Future Research
This study is not without limitations, which present opportunities for future inquiry. Data were collected from a single province in South Africa rather than across the entire country. This limits the generalisability of the findings, particularly when considering diverse consumer behaviours in other regions and emerging economies more broadly. Future research could therefore adopt a cross-country or nationwide approach to validate and extend the present findings.
While the study found a non-significant negative effect of climate change awareness on green purchasing behaviour, this finding should be interpreted with caution. The study did not formally test income as a moderating variable in the SEM, and therefore, no causal conclusion can be drawn regarding poverty or inequality. Rather, we position these factors as contextual explanations supported by existing literature from South Africa and the broader Global South. Prior studies in developing-country settings have demonstrated that high awareness of environmental issues does not consistently translate into green purchasing due to structural constraints such as affordability, product scarcity, and competing economic priorities. For example, Refs. [13,14] demonstrate that, although consumers in African markets express a high concern for climate change, green purchasing remains low due to price sensitivity and limited access to certified green products. Similarly, studies from the Global South [38] have highlighted that pro-environmental intentions are frequently overridden by economic pressures, particularly in lower-income segments. These findings reinforce the interpretation that, in resource-constrained environments, awareness alone is insufficient to drive behaviour, consistent with the broader “attitude–behaviour gap” literature. Our results, therefore, extend TPB by illustrating that contextual barriers, although not directly tested as moderators in this model, may attenuate the effect of cognitive predictors such as climate change awareness.
The study further observes that the demographic distribution of the study, characterised by high education and mature individuals, could explain the high association between attention to green communication, green attitudes, and GPB. Future research should investigate the topic across various strata, with varying age groups and educational levels as moderators.
In addition, consumer behaviour is inherently complex, influenced by a wide range of psychological, social, and contextual variables. Future research could expand this study’s model by including additional mediating and moderating factors, thereby offering a more comprehensive understanding of the drivers of green purchase behaviour. A mixed-methods study can also provide insights using qualitative data to determine the lived experiences of participants in terms of how their gender, age, income, and education level influence their green purchasing behaviour, which then can be triangulated with the quantitative data on the same variables to conclusively determine their true impact on the dependent variable, GPB.
Author Contributions
Conceptualization, Z.H. and H.S.; methodology, Z.H. and H.S.; formal analysis, Z.H.; investigation, Z.H.; data curation, Z.H. and H.S.; writing—original draft preparation, Z.H.; writing—review and editing, H.S.; supervision, H.S. All authors have read and agreed to the published version of the manuscript.
Funding
This study did not receive external funding.
Institutional Review Board Statement
Walter Sisulu University’s Senate Research Ethics Committee reviewed and approved the study, along with the certificate, which bears the protocol number 069/2025/HBM/BME-7668, on 8 July 2025.
Informed Consent Statement
Informed consent was obtained in writing from all subjects involved in the study.
Data Availability Statement
Data supporting reported results is available on request.
Conflicts of Interest
The authors declare that they have no conflict of interest.
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