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Article

The Impact Mechanism of Government Environmental Regulation and Green Consumer Orientation (GCO) on Green Purchase Intention: A Case Study of Zespri

Department of Global Business Graduate School, Kyonggi University, Suwon 16227, Republic of Korea
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Author to whom correspondence should be addressed.
Sustainability 2025, 17(6), 2575; https://doi.org/10.3390/su17062575
Submission received: 8 January 2025 / Revised: 7 March 2025 / Accepted: 13 March 2025 / Published: 14 March 2025

Abstract

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This study explores the impact mechanism of government environmental regulation on consumers’ green purchase intention through green consumer orientation (GCO) using Zespri as a case study. By integrating the Theory of Planned Behavior (TPB) and the Value–Belief–Norm (VBN) theory, a comprehensive framework was developed. A total of 857 valid questionnaires were collected, and Structural Equation Modeling (SEM) was applied for empirical analysis. The results indicate that government environmental regulation significantly enhances the three dimensions of GCO (identification, equilibrium, and interaction) and positively influences green purchase intention. Policy recommendations are proposed, including improving green certification systems and encouraging enterprises to adopt green marketing strategies. The findings provide theoretical and practical implications for policymakers and companies aiming to promote sustainable consumption and green supply chains.

1. Introduction

1.1. Research Background

Against the backdrop of global efforts to combat climate change and environmental degradation, government environmental regulations play a critical role in promoting sustainable development and green consumption behaviors. In recent years, with the increasing environmental awareness among consumers, green consumption has gradually become a focal point of market attention. Haws et al. [1] pointed out that consumers’ green values significantly influence their acceptance and purchase intention of eco-friendly products. Studies have shown that green market orientation can enhance firms’ green supply chain capabilities and positively impact their organizational performance [2]. This provides important theoretical support for exploring how government environmental regulations influence purchase intention through green consumer orientation (GCO). Moreover, Westjohn, S et al. [3] proposed that GCO, as an emerging behavioral theory, can reveal consumers’ attitudes, preferences, and behaviors toward green products.
The successful case of Zespri in New Zealand provides a solid practical foundation for studying this issue. By strictly adhering to government environmental regulation standards, Zespri has demonstrated a high level of environmental responsibility from green production to marketing strategies, establishing an outstanding green brand image globally. Hafezi and Zolfagharinia [4] pointed out that Zespri’s green transformation not only enhanced its market competitiveness but also achieved significant results in environmental protection.
This indicates that through effective government environmental regulations and corporate green strategies, a win-win situation for both economic and environmental benefits can be achieved. Therefore, using Zespri as an example to explore the mechanism by which government environmental regulations influence consumers’ green orientation and purchase intention can not only enrich theoretical research but also provide practical references for governments worldwide. The existing literature shows that government intervention in the market through tax incentives, subsidies, green certification, and promotion has positively influenced consumers’ awareness and acceptance of green products [5,6]. However, despite certain achievements of government policies in promoting green development, issues such as insufficient consumer awareness of green products and uneven regional effectiveness of policy implementation remain prominent [7]. Against this backdrop, Zespri has achieved above-average green development outcomes by coordinating government regulations with its own green strategies, offering valuable experience for other countries and enterprises to learn from.

1.2. Research Gaps and Objectives

Existing studies primarily focus on the impact of government regulation on corporate green behavior, while research on the consumer level remains limited. Previous research has mainly examined the role of green brand image and environmental beliefs in shaping green purchase intentions, while overlooking the mediating role of Green Consumer Orientation (GCO) between government policies and consumer purchasing behavior. Empirical studies on how government regulation influences consumers within the three-dimensional GCO framework (recognition, balance, and interaction) remain scarce, particularly in case analyses within the fresh cold chain industry. There is a lack of systematic research on the internal mechanism between government environmental regulations and green consumer orientation (GCO). Elhoushy and Lanzini [8] systematically reviewed multiple factors influencing sustainable consumption behavior, including social norms, information availability, and market accessibility. They emphasized the significant gap between consumers’ awareness of sustainable behavior and their actual decision-making. These factors are closely related to the three dimensions of green consumer orientation (GCO)—identification, balance, and interaction. However, existing research in this area remains insufficient, particularly lacking empirical analysis in specific policy intervention contexts. Current studies mainly focus on the external driving effect of government environmental regulations on corporate green behavior, with limited analysis on how government policies are internalized into consumers’ green behavior motivation through the three dimensions of green consumer orientation (identification, balance, and interaction). There is insufficient exploration of the mediating role of green consumer orientation (GCO) between policy intervention and green purchase intention. The existing literature emphasizes the mediating role of green brand image and environmental beliefs in green purchase intention but lacks research on the specific mechanisms of green consumer orientation as a behavioral tendency under policy intervention. For example, Majeed et al. [9] highlighted the role of green brand image but failed to delve into the process of forming consumer behavioral tendencies under policy guidance. There is a lack of empirical research on specific industries (e.g., fresh cold chain supply chains), as existing studies mainly focus on green behavior, in general, consumer markets, and rarely involve specific contexts such as fresh agricultural products. However, the fresh cold chain industry, due to its energy-intensive logistics and storage processes, has a significant environmental impact and thus requires green transformation under policy guidance. This study, through the case of Zespri, a leading enterprise in the fresh industry, aims to fill the empirical research gap in this context.
To fill the aforementioned gaps, the objectives of this study are as follows:
  • To explore the multidimensional impacts of government environmental regulations on the three dimensions of green consumer orientation (identification, balance, and interaction);
  • To analyze the mechanism of green consumer orientation in the relationship between government policies and green purchase intention;
  • To provide theoretical foundations and practical pathways for policy design and corporate green marketing strategies in the fresh cold chain industry, drawing on Zespri’s successful experience.

1.3. Research Contributions

1.3.1. Theoretical Innovations

This study integrates the Theory of Planned Behavior (TPB) with the Value–Belief–Norm (VBN) theory to construct a comprehensive theoretical framework, deeply exploring how government environmental regulations influence green purchase intention through the three dimensions of green consumer orientation: identification, balance, and interaction. Unlike existing studies that primarily focus on firms’ external green behaviors, this research emphasizes the intrinsic mechanism of consumer behavior and conducts empirical tests in a specific context (the fresh cold chain industry), offering a new perspective on green consumption behavior research [10,11].

1.3.2. Practical Significance

Zespri’s successful experience demonstrates that through effective government regulations and corporate green marketing strategies, widespread adoption of green consumption, and the coordinated development of the economy and the environment can be achieved. This study proposes specific policy recommendations, including improving the green certification system, optimizing tax incentive mechanisms, and enhancing green promotion and education, to help policymakers more effectively guide consumer behavior. Meanwhile, the research provides practical pathways for enterprises to design green marketing strategies, particularly offering highly actionable suggestions for the green transition in the fresh cold chain industry.

2. Literature Review

2.1. Green Purchase Intention

Green Purchase Intention (GPI) refers to consumers’ behavioral intention to purchase environmentally friendly green products, driven by their concern for environmental protection and sustainable development. Taufique et al. [12] developed a comprehensive scale for measuring consumers’ environmental responsibility, highlighting key constructs such as perceived consumer effectiveness and environmental concern. These constructs are closely related to the formation of green purchase intention, as they reflect consumers’ perceived ability to make a difference through their purchasing behavior. This suggests that enhancing consumers’ environmental responsibility could positively influence their intention to buy green products. Existing research indicates that consumers’ environmental values (altruism and biocentrism) play a crucial role in shaping their green purchase intentions, and this effect is moderated by green trust [13]. GPI is influenced by various factors:
Intrinsic factors: consumers’ environmental values and level of green awareness [14].
Extrinsic factors: including marketing, social opinion, and policy regulations [15].
Taking green purchase intention as the core dependent variable, this study focuses on how government environmental regulations influence it through green consumer orientation (GCO) [16]. This study aims to reveal the dynamic mechanism between policy intervention and consumer behavior, providing theoretical support and practical guidance for promoting green consumption behavior and achieving sustainable development goals.

2.2. Green Consumer Orientation (GCO) and Green Purchase Intention

Green Consumer Orientation (GCO) is an emerging theoretical framework for understanding consumers’ tendencies and behaviors when purchasing green products. The study by Souheila Ayoun and Serge Schmitz [17] conceptualized GCO into three main dimensions: Identification, Equilibrium, and Interaction, systematically revealing how consumers perceive and choose green products. Haws et al. [1] emphasized that green consumption values play a significant role in shaping consumers’ attitudes toward environmentally friendly products. Chen et al. [18] confirmed that consumers with strong environmental values are more likely to develop green trust and show higher purchase intentions towards environmentally friendly brands. This insight provides a theoretical basis for the inclusion of green values as a core dimension of GCO in this study.
Recent studies further enrich the theoretical framework of GCO. Yeğin and Ikram highlight that government environmental regulations, combined with consumers’ environmental concerns and green trust, significantly enhance green purchase intention, demonstrating how external regulations and internal green orientation interact to drive green consumption behavior [19]. Similarly, Ng et al. emphasize that consumers’ green purchase intention is jointly driven by perceived functional, social, and emotional values, indicating that GCO not only stems from environmental awareness but also from deeper personal and social motivations [20]. In addition, Sestino et al. reveal that consumers’ innovativeness and conspicuous consumption orientation positively predict their environmentalism and green purchase behavior, highlighting that GCO is not only a reflection of environmental responsibility but also a manifestation of social identity and personal value [21]. These findings collectively underscore the multifaceted drivers behind green consumer orientation and their linkage to green purchase intention.

2.2.1. Identification and Green Purchase Intention

Identification refers to consumers’ recognition and understanding of green product attributes and environmental information, which is the initial step in developing green consumer orientation. Research suggests that when consumers identify with green products, they are more likely to share their green experiences and engage in peer-to-peer recommendations, strengthening their green interaction [22]. Furthermore, strong identification fosters positive attitudes and purchase intentions, particularly when credible eco-labels are involved [1]. Consumers’ recognition and understanding of the environmental attributes and labels of green products are crucial in green purchasing decisions. Environmental knowledge not only directly influences consumers’ green purchase intentions but also indirectly affects their pro-environmental behavior through self-congruity [22]. When consumers perceive green consumption as consistent with their self-image, they are more likely to engage in green purchasing behavior. The study by Kim and Choi [23] indicated that social factors, information availability, and market accessibility significantly influence consumers’ purchasing decisions, promoting their identification and recognition of green products. This identification further strengthens consumers’ interaction with green products (H1) and their green purchase intention. The review by Elhoushy and Lanzini [24] highlighted that income level and trust in green products and their labels are important factors influencing consumers’ green behavior, further supporting the positive effect of identification on green purchase intention (H2). Therefore, it can be hypothesized that
H1. 
Recognition positively influences interaction.
H2. 
Recognition positively influences green purchase intention.

2.2.2. Interaction and Green Purchase Intention

The interaction dimension reflects consumers’ tendency to promote and showcase their green consumption behavior within their social circles. Research indicates that policy promotion and social recognition are important factors in enhancing consumers’ willingness to interact, effectively increasing their enthusiasm for sharing green consumption concepts in social circles [25]. By promoting green lifestyles, the government not only raises consumers’ awareness of environmental issues but also enhances their capacity for action, thereby encouraging positive interaction in social environments [26]. Interaction reflects consumers’ willingness to discuss, recommend, and promote green products within their social circles. Research has shown that active engagement in green conversations reinforces positive environmental attitudes and increases the likelihood of green purchasing [27]. Social proof and peer validation from these interactions play a significant role in converting environmental concern into actual green purchase decisions [8]. This positive interaction further reinforces consumers’ green purchase intention (H3). Therefore, interaction in the green consumption process not only has a dissemination effect but also exerts a direct positive influence on consumers’ purchasing intention. Therefore, it can be hypothesized that
H3. 
Interaction positively influences green purchase intention.

2.2.3. Equilibrium and Green Purchase Intention

The equilibrium dimension focuses on how consumers balance personal needs and environmental responsibilities, a process that is crucial for promoting green consumption behavior. The study by Li, Cheng, and Wang [28] confirmed the positive role of policy incentives in enhancing consumers’ balancing capability, indicating that policy measures can improve consumers’ ability to find a balance between environmental protection and personal needs, thereby promoting green consumption behavior. Additionally, the study by Panzone et al. [29] indicates that carbon tax policies significantly reduce the carbon footprint of shopping baskets. Similarly, prior research in the retail context has shown that when consumers are provided with clear information and incentives, they are more likely to adjust their purchasing behavior in favor of environmentally friendly options [30].
In this context, the equilibrium dimension can enhance consumers’ identification of green purchase intention and labels (H4), further promote their positive interaction regarding green behavior within social circles (H5), and ultimately foster the formation of green purchase intention (H6). Therefore, policy incentives and environmental taxation can effectively enhance consumers’ ability to balance personal needs with environmental responsibilities, thereby positively influencing their identification, interaction, and purchase intention.
Achieving equilibrium in green purchasing requires consumers to balance environmental responsibility with personal product preferences, including performance, price, and convenience. This balance process heavily relies on consumers’ ability to accurately identify green product attributes and certifications, fostering trust in product claims and environmental benefits. Previous studies also highlight the importance of green brand image and consumer environmental beliefs in shaping green purchase intention, as consumers’ trust in green products is not only built through direct product experience but also influenced by external marketing signals and broader environmental values [9]. Therefore, it can be hypothesized that
H4. 
Balance positively influences recognition.
When consumers successfully balance personal and environmental goals, they are also more likely to discuss and recommend these products within their social networks, contributing to a broader green communication network [31]. Therefore, it can be hypothesized that
H5. 
Balance positively influences interaction.
Furthermore, consumers who perceive a successful balance between individual and environmental interests tend to develop stable, long-term green purchasing habits, as the perceived trade-offs are minimized [32]. Therefore, it can be hypothesized that
H6. 
Balance positively influences green purchase intention.

2.3. Environmental Regulation and Green Purchase Intention

Environmental regulation is an important policy tool for promoting green consumption, mainly encompassing four aspects: legal regulations (e.g., emission limits and pollution control measures), tax incentives (e.g., tax reductions and subsidies for eco-friendly products), market mechanisms (e.g., carbon emission trading and green certificate trading), and public education (promoting behavior change by raising environmental awareness). Environmental regulations, particularly those involving mandatory eco-labeling and green certification, enhance consumers’ ability to identify environmentally friendly products [33]. Government environmental regulations, particularly those mandating credible eco-labeling and third-party certifications, play a critical role in enhancing consumers’ ability to distinguish truly green products from greenwashed products. This regulatory-induced identification process not only reduces consumer skepticism but also fosters trust in green product claims, thereby enhancing green purchase intention. This process aligns with the Value–Belief–Norm (VBN) theory, which posits that external signals and environmental information shape consumer environmental beliefs, strengthen personal norms, and ultimately drive environmentally significant behavior [11]. Studies have shown that environmental regulation plays a significant role in shaping consumers’ green behavior and driving corporate environmental actions. The recent literature further supports this view by illustrating the mediating role of consumer communication and social influence in the relationship between environmental regulation and green purchase intention. For example, Saqib, Ikram, and Qin highlight that corporate environmental responsibility (CSR) initiatives, aligned with environmental regulations, significantly enhance green purchase intention through the mediating role of electronic word-of-mouth (eWOM), demonstrating how regulatory actions indirectly shape consumer behavior by fostering public discourse and consumer trust [34]. These findings suggest that environmental regulations not only exert direct pressure on firms and consumers but also create a supportive social and informational environment that enhances green consumer orientation and purchase intention. Additionally, Le [35] found that ESG practices positively impact financial performance, supporting the argument that compliance with environmental regulations not only improves environmental outcomes but also enhances corporate profitability. Hamza et al. [36] introduced a sustainable consumption measurement scale, which includes dimensions such as social norms, environmental knowledge, and perceived behavioral control. These dimensions are critical in understanding how regulatory frameworks influence consumer behavior. By integrating these insights, this study proposes that environmental regulation enhances green purchase intention not only directly but also by influencing key mediating factors such as green consumer orientation.
Environmental regulations not only impose mandatory standards but also employ economic incentives such as subsidies and tax reductions to lower the financial barriers associated with purchasing green products. These economic measures play a crucial role in enhancing consumers’ perceived balance between environmental responsibility and personal economic interests, thereby promoting more rational and sustainable purchasing behavior. Previous research highlights that such incentives effectively reduce the cost burden of green product development and facilitate the market diffusion of environmentally friendly products, indirectly shaping consumers’ green purchase intention through improved affordability and perceived value [4].
Legal regulations can directly regulate corporate behavior. For example, research indicates that ownership structure and policy intervention methods significantly influence sustainable development practices. In urban waste management, diverse ownership structures and the involvement of private partners can enhance the effectiveness of policy implementation [37]. Dai [38] pointed out that environmental regulation not only promotes corporate green design but also indirectly enhances green recycling behavior through green design, generating positive impacts on both economic and environmental performance. Tax incentives reduce the cost of green products, helping consumers find a balance between economic concerns and green values, a mechanism empirically validated by Wei, Ang, and Jia [39]. Market mechanisms support green finance, as Zhang et al. [40] studied China’s green credit policy and found that it effectively promoted environmental governance and green economic development. In terms of public education, Gamlin J [33] emphasized that policy incentives and public education can enhance consumers’ perceived value of green consumption and their behavioral control, further promoting green purchase intention. Beyond influencing intermediate factors such as identification and interaction, environmental regulations can directly enhance green purchase intention by shaping social norms and consumers’ perceived behavioral control. When green purchasing is framed as both a regulatory expectation and a socially desirable behavior, consumers are more likely to translate environmental awareness into concrete purchasing decisions [10,15]. The influence of environmental regulation on consumers’ green purchase intention primarily unfolds through the three dimensions of Green Consumer Orientation (GCO): identification, equilibrium, and interaction. First, environmental regulation enhances consumers’ ability to identify green products through clear green certifications and standard labels (H7). Second, tax incentives and economic support help consumers achieve a balance between environmental responsibility and economic benefits (H8). Additionally, Lee [41] found that the government indirectly enhanced consumers’ trust in green products by shaping a green image, thereby increasing the level of interaction (H9). Ultimately, these mechanisms work together to significantly enhance consumers’ green purchase intention (H10).
H7. 
Environmental regulation positively influences recognition.
H8. 
Environmental regulation positively influences balance.
H9. 
Environmental regulation positively influences interaction.
H10. 
Environmental regulation positively influences green purchase intention.

3. Research Methodology

Drawing on the study by Naparin and Astuti [42], this research analyzes how the dimensions of identification, equilibrium, and interaction within Green Consumer Orientation influence consumers’ green purchase intention.
This study adopts the Green Consumer Orientation (GCO) theory and divides it into three core dimensions: identification, equilibrium, and interaction. These three dimensions are empirically analyzed through the Structural Equation Model (SEM) framework to explore the pathways through which environmental regulation affects GCO and green purchase intention. These dimensions form the foundation for understanding how regulatory interventions influence green purchasing behavior. They are integrated into the Structural Equation Model (SEM) framework for empirical analysis of the impact of regulation on GCO, thereby linking theoretical construction with observed consumer behavior (see Figure 1).

3.1. Case Typicality

This study selects Zespri as the case analysis subject, which demonstrates significant representativeness and research value. Zespri, as a globally renowned green fruit and vegetable brand, is known for its stringent environmental management standards and sustainable development practices. The selection of this company as a case is mainly based on the following considerations:

3.1.1. Typicality in Alignment with the Research Theme

Zespri, as a globally recognized green brand in the fresh agricultural product industry, has established itself as a leader in green supply chain management and environmental responsibility. The company has implemented strict environmental regulation policies, such as reducing carbon emissions, promoting sustainable cultivation practices, and adopting innovative green marketing strategies. This aligns directly with the research theme of exploring how government environmental regulation influences consumer green purchase intention through Green Consumer Orientation (GCO). Zespri’s emphasis on green production and transparent environmental practices makes it an ideal case study for understanding the interplay between policy interventions and consumer behavior [43,44].

3.1.2. Industry Benchmark for Sustainable Development

Zespri has long been regarded as an industry benchmark for its commitment to sustainable development. The company’s adherence to multiple green certification standards, including organic certification and carbon footprint labels, highlights its leadership in promoting green consumption values. By communicating these green values effectively to consumers through clear product labeling, Zespri demonstrates the practical application of the GCO dimensions of identification, equilibrium, and interaction. Its success serves as a model for other enterprises aiming to enhance their environmental and market performance [45].

3.1.3. Practical Application of Environmental Regulation

Zespri operates under stringent environmental regulations in New Zealand, which is known for its progressive environmental policies. For example, the government mandates reductions in agricultural greenhouse gas emissions and promotes carbon-neutral certifications. Zespri’s compliance with these regulations, coupled with its proactive innovations in green technology and supply chain management, not only ensures legal compliance but also enhances its competitiveness in the global market. This synergy between regulatory frameworks and corporate strategies offers valuable insights into the role of policy in shaping sustainable practices [46].

3.1.4. Representativeness of Consumers’ Perception of Green Products

Zespri’s products are widely recognized for their high quality and eco-friendly attributes, making them a preferred choice among environmentally conscious consumers. The company’s green branding strategies, including the use of carbon-neutral labels and sustainability certifications, enhance consumer trust and facilitate identification with green products. Additionally, Zespri has successfully balanced price and quality to meet consumer expectations, exemplifying the equilibrium dimension of GCO. Its ability to foster consumer interaction through marketing campaigns and social media engagement further amplifies the green consumption message, making it a representative case for studying consumer behavior in green markets [47].

3.1.5. International Market Impact

As a global brand, Zespri’s operations span diverse cultural and policy contexts, providing a robust foundation for examining the adaptability of environmental regulations across different markets. The company’s ability to navigate varying regulatory environments while maintaining consistent green practices demonstrates the scalability of its strategies. This global perspective adds depth to this study by highlighting how localized policy interventions can influence consumer behavior in an international context [48].

3.1.6. Economic and Social Benefits of Green Practices

Through its commitment to green supply chain management and sustainable development, Zespri has achieved significant economic and social benefits. The company has not only enhanced its profitability but also contributed to broader environmental goals, such as reducing carbon emissions and promoting biodiversity. This dual focus on economic and environmental performance provides a comprehensive framework for understanding the impact of green practices, reinforcing the practical significance of this study [49].
In summary, Zespri’s practices not only demonstrate the effectiveness of implementing government environmental regulations but also illustrate how green consumer orientation influences consumers’ purchase intention through the dimensions of identification, equilibrium, and interaction. The typicality of this case provides strong theoretical support and an empirical foundation for this study.

3.2. Source of Indicators (Questionnaire Design)

Variable Measurement: Based on the research hypotheses, the scales for measuring six core variables are as follows:

3.2.1. Identification (ID)

Identification (ID) refers to consumers’ ability to recognize the environmental attributes (including environmental and ethical attributes) of products. The scale developed by Sharma and Foropon [50] for green product attributes and green purchasing behavior was adopted, combined with items assessing consumers’ understanding of green certifications, labels, and environmental information, to verify the influence of identification on informed decision-making. This study drew on the aforementioned framework and designed items such as “I am well-informed about green fresh agricultural products” to reflect consumers’ level of recognition regarding environmental attributes.

3.2.2. Equilibrium (EQL)

Equilibrium (EQL) refers to consumers’ ability to balance personal needs with environmental responsibilities. This study references the measurement framework of subsidies and penalties on green technology investment and environmental responsibility proposed by Bian et al. [32], He et al. [51], and Bi et al. [52]. It aims to verify the incentive effect of subsidies or penalties on consumer behavior. Additionally, this study designs items linking external incentives with consumers’ internal decision-making, such as “Using green fresh agricultural products has reduced our impact on the environment”.

3.2.3. Interaction (INTRCT)

Interaction (INTRCT) captures the social and behavioral exchanges that promote green consumption, such as peer recommendations, marketing influences, and the reinforcement of social identity. This study references the measurement framework of social influence and green purchasing behavior proposed by Li et al. [53] and Muposhi et al. [2]. Furthermore, to verify the mediating role of social identity in consumer behavior, items such as “I feel proud when others know I use green fresh agricultural products” were designed to reflect the role of interaction in driving green consumption decisions.

3.2.4. Environmental Regulation (ER)

Government environmental regulation refers to the influence exerted on consumer behavior through policy measures (such as regulations, taxes, and subsidies). This study references the research framework by Li et al. [5] and proposes items such as “Government restrictions on environmentally unfriendly products affect my purchasing decisions”, with a focus on measuring the direct and indirect effects of policy regulations on consumer behavior.

3.2.5. Green Purchase Intention (GPI)

Green purchase intention refers to consumers’ tendency to choose eco-friendly products in their purchasing behavior. This study references the research framework by Tan and Huang [54] and proposes items such as “I am willing to purchase environmentally friendly products even if they are slightly more expensive”.

3.3. Survey Process

The survey questionnaire in this study is divided into three main sections, aiming to systematically collect data related to consumers’ green consumption behavior.

3.3.1. Screening Section

First, screening questions were used to determine whether the respondents had ever purchased Zespri’s green fresh agricultural products (kiwifruit), ensuring that the participants had relevant consumption experience. The screening questions aim to exclude consumers who have not encountered green fresh products, enhancing the relevance and effectiveness of subsequent data analysis.

3.3.2. Demographic Information Section

The second section collects basic information about the respondents, including gender, age, highest educational level, occupation, and average monthly expenditure. These demographic variables have been proven in previous studies to significantly influence green consumption behavior and were therefore given special consideration in the questionnaire design. This information helps in conducting subsequent group analysis to explore the similarities and differences in green purchase intention among different groups.

3.3.3. Core Variable Measurement Section

The third section uses a five-point Likert scale (1 = strongly disagree, 5 = strongly agree) to measure the three dimensions of green consumer orientation (identification, equilibrium, and interaction), government environmental regulation, and green purchase intention. Each dimension includes multiple items to ensure the comprehensiveness and validity of the measurement.
To ensure the breadth and representativeness of this study, general consumers were selected as the survey respondents. This design broadens the scope of this study and reduces the limitations of results caused by specific consumer groups. Moreover, considering the efficiency, convenience, and strong anonymity of electronic questionnaires, we used online questionnaires for data collection. This approach not only allows for random distribution of questionnaires, enhancing sample diversity, but also effectively protects the privacy of respondents, reducing their psychological concerns during the completion process.
During the questionnaire design process, we deliberately randomized the order of variable items to reduce the likelihood of respondents guessing answers based on the logical order of questions, thereby improving the authenticity and reliability of the data. Ultimately, 857 valid questionnaires were collected. These questionnaires provide a reliable data foundation for subsequent empirical analysis (see Appendix A).

4. Empirical Design

4.1. Description of Sample Characteristics Distribution

Descriptive statistics of the sample characteristics show that 55.7% of the respondents were male and 44.3% were female, indicating a relatively balanced gender distribution, ensuring the representativeness of gender in the analysis of green consumption behavior. Regarding age distribution, respondents aged 25 to 50 accounted for the highest proportion at 59.8%, with 42.3% specifically in the 25–50 age range. This age group generally has stronger purchasing power and environmental awareness, making them the core demographic for green consumption.
In terms of educational background, 48.2% of the respondents had a high school education or below, followed by 21.4% with a college diploma, 23.8% with a bachelor’s degree, and 6.7% with a master’s or doctoral degree. This result indicates that the sample primarily consists of low to medium-educated individuals, consistent with the general characteristics of consumers, and that differences in educational background may significantly influence green consumption behavior.
Regarding monthly expenditure, 86.2% of respondents reported spending below 10,000 yuan per month, with 38.2% spending less than 2000 yuan, 29.3% spending between 2001 and 4000 yuan, 18.7% spending between 4001 and 6000 yuan, 8.5% spending between 6001 and 8000 yuan, 3.4% spending between 8001 and 10,000 yuan, and only 2.0% spending more than 10,000 yuan. These data reflect that the sample mainly consists of low to medium-income groups, whose consumption behavior may be more price-sensitive. This is particularly important for the subsequent analysis of the acceptance of price premiums for green products.
In terms of occupational distribution, ordinary employees accounted for 19.3%, freelancers for 12.7%, ordinary workers for 15.1%, corporate managers for 8.9%, while students and retirees accounted for 7.5% and 8.4%, respectively. Additionally, individual business owners, homemakers, agricultural workers, government officials, and professionals also accounted for certain proportions. This diverse occupational distribution helps to comprehensively reflect the green consumption behavior of various occupational groups.
Regarding the purchase of green fresh agricultural products, 80.4% of respondents indicated that they had purchased green fresh agricultural products, while only 19.6% had not. This indicates that green products have gained a certain level of popularity and recognition in the market, providing a rich context for consumers’ “identification” behavior during the purchasing process.
In terms of purchase frequency, high-frequency buyers who purchase three or more times per week accounted for 36.5%, with 24.0% buying three times per week, 19.1% twice per week, and 12.5% daily. High-frequency purchasing behavior not only reflects the high demand for green fresh agricultural products but also provides a foundation for studying consumers’ “equilibrium” and “interaction” at different purchase frequencies.
For example, scholars have found that high-frequency buyers, due to prolonged exposure to green products, have stronger recognition of environmental labels and certifications, form a more stable sense of balance between price and quality, and are more likely to engage in interactive promotion through social networks or friend recommendations.
Regarding the awareness and purchase of Zespri kiwifruit, 36.3% of respondents indicated that they had purchased Zespri kiwifruit, 35.9% said they were aware of it but had not purchased it, and only 8.2% said they were unfamiliar with the brand. This indicates that Zespri kiwifruit has a high level of brand recognition in the green fresh agricultural product market [55].
Due to Zespri’s long-term investment in green certification, sustainable development, and product quality, its products can effectively stimulate consumers’ “identification” behavior regarding green attributes. Additionally, Zespri has enhanced the “interaction” between consumers and green products through brand promotion and social responsibility marketing, further promoting the dissemination of green consumption concepts.
These sample characteristic data provide a foundation for subsequent empirical analysis and strong support for exploring the impact of different demographic characteristics on green purchase intention. The broad coverage of the sample allows this study to comprehensively reflect the characteristics of consumers’ green consumption behavior in the market, which helps to further inform market positioning, pricing strategies, and promotional approaches for green products (see Table 1).

4.2. Reliability and Validity Analysis

In this study, the analysis was conducted using SPSS Statistics 25.0 and AMOS 23.0. Multiple methods were employed to test the reliability and validity of the scales to ensure the data quality of the measurement results and the effectiveness of subsequent analysis. First, Cronbach’s Alpha coefficient was used to test the internal consistency of each dimension. The value of Cronbach’s Alpha ranges from 0 to 1, with higher values indicating better internal consistency of the scale. Generally, a reliability coefficient below 0.6 indicates the need to redesign the questionnaire or recollect data; a coefficient between 0.6 and 0.7 is considered acceptable, 0.7 to 0.8 indicates high reliability, 0.8 to 0.9 denotes good reliability, and above 0.9 signifies excellent reliability. In this analysis, Cronbach’s Alpha coefficients for all core variables exceeded 0.9, indicating high internal consistency and excellent reliability of the scales.
Meanwhile, to further verify the construct validity of the scales, this study used the Kaiser–Meyer–Olkin (KMO) test and Bartlett’s test of sphericity to assess data suitability and factor structure. A KMO value greater than 0.8 indicates that the sample data are suitable for factor analysis, and Bartlett’s test reaching a significant level (p < 0.001) suggests good data aggregation properties (see Table 2).
Under the premise of good reliability statistics and satisfactory Bartlett’s test results, further model fit testing was conducted. According to the model fit indices in the table, the chi-square degrees of freedom ratio (CMIN/DF) is 2.077, which falls within the acceptable range of 1 to 3. The root mean square error of approximation (RMSEA) is 0.051, which is within the acceptable threshold of less than 0.08.
Additionally, the fit indices NFI, TLI, CFI, and GFI all exceed 0.9, indicating an excellent level of model fit. Therefore, based on the overall analysis, the CFA model demonstrates good model fit (see Table 3 and Figure 2).
The CFA results indicate that this study employs structural equation modeling (SEM) to validate the measurement model, with the results presented in Table 4. The standardized factor loadings of the measurement variables are all above 0.70, with only a few indicators slightly below 0.70 but still within the acceptable range.
Most of the variables have factor loadings ranging from 0.70 to 0.88, indicating that each measurement item effectively reflects its respective construct. Among them, the factor loading of GPI1 in green purchase intention (GPI) is the highest (0.879), indicating that this variable contributes the most to the construct.
Overall, the measurement model in this study demonstrates high convergent validity and measurement stability, making it suitable for subsequent structural model analysis.
Additionally, based on Bollen’s (1989) theoretical criteria, the composite reliability (CR) and average variance extracted (AVE) of each latent variable were calculated, and the results showed that all indicators met or exceeded the recommended thresholds, indicating good convergent and discriminant validity of the scales. Therefore, the scales used in this study meet the requirements for reliability and validity in academic research, providing a reliable data foundation for model analysis [56].
The formulas for calculating AVE and CR are as follows:
AVE = i = 1 n λ i 2 n
CR = i = 1 n λ i 2 i = 1 n λ i 2 + i = 1 n δ i
Table 4 presents the discriminant validity test results for each dimension in this study. According to the Fornell–Larcker criterion, the square root of the AVE value for each variable is greater than its correlation with other variables, indicating good discriminant validity among the constructs in this study [57].
Specifically, green purchase intention (GPI) shows a relatively high correlation with interaction (INTRCT) and balance (EQL), with values of 0.438 and 0.412, respectively, suggesting that these two factors play a significant role in predicting green purchase intention. In contrast, environmental regulation (ER) and identity recognition (ID) exhibit lower correlations with green purchase intention, at 0.397 and 0.363, respectively, indicating that these factors have a relatively weaker influence on green purchase intention.
Overall, the measurement model in this study demonstrates good discriminant validity, providing a solid foundation for subsequent structural equation modeling (SEM) analysis (see Table 5).
The table below presents the descriptive statistics and normality test results for each factor in this study. According to the descriptive statistics, the mean values of all variables range between 3 and 4 (based on a 1–5 positively scored scale), indicating that respondents generally have an above-average level of awareness and behavior regarding environmental regulation and green consumer orientation. In addition, the standard deviation values indicate a moderate degree of data dispersion, reflecting the variability of green consumption behavior among different respondents.
To test whether the data distribution meets normality, skewness and kurtosis were used as test indicators. According to Kline’s criteria [57], data can be considered approximately normally distributed if the absolute value of skewness is less than 3 and the absolute value of kurtosis is less than 8. Statistical analysis shows that the skewness and kurtosis of all measurement items meet the above criteria, indicating that the data in this study essentially satisfy the requirements for approximate normal distribution, which provides the statistical prerequisite for subsequent structural equation modeling (SEM) analysis (see Table 6).
In this analysis, Pearson correlation analysis was conducted to explore the relationships among the variables. The analysis results indicate that significant correlations exist among all variables, with all correlations being significant at the 99% confidence level. Based on the correlation coefficients, it is evident that the correlation coefficients r among all variables are greater than 0. Therefore, it can be concluded that all variables in this analysis exhibit significant positive correlations (see Table 7).

4.3. Comparison of Hypothesis Testing Results

In the quantitative analysis phase, this study used Structural Equation Modeling (SEM) to validate the path relationships between hypotheses. SEM, as a statistical method capable of simultaneously handling multiple latent variables and their interrelationships, is suitable for exploratory and confirmatory studies of complex models [58]. Based on the SEM and fit index evaluation criteria proposed by Hair et al. [59], this study conducted model estimation using AMOS 23.0 software, with a focus on the significance of path coefficients and overall model fit. Model fit evaluation indices include the chi-square to degrees of freedom ratio (CMIN/DF), root mean square error of approximation (RMSEA), and comparative fit index (CFI). All key fit indices met the recommended standards, indicating that the model achieved good fit. This analysis result provides strong statistical support for hypothesis validation (see Table 8).

SEM Model Path Relationship Hypothesis Testing Results

Path Relationship Hypothesis Testing Results for the Green Consumption Orientation-SEM Model
Recognition significantly and positively predicts interaction (β = 0.29, p < 0.001), thus supporting Hypothesis H1. Recognition significantly and positively predicts purchase intention (β = 0.104, p > 0.001, p = 0.004 < 0.05), thus supporting Hypothesis H2. Interaction significantly and positively predicts purchase intention (β = 0.143, p > 0.001, p = 0.004 < 0.05), thus supporting Hypothesis H3.
Balance significantly and positively predicts recognition (β = 0.275, p < 0.001), thus supporting Hypothesis H4. Balance significantly and positively predicts interaction (β = 0.278, p < 0.001), thus supporting Hypothesis H5. Balance significantly and positively predicts purchase intention (β = 0.115, p > 0.001, p = 0.004 < 0.05), thus supporting Hypothesis H6.
Environmental regulation significantly and positively predicts balance (β = 0.733, p < 0.001), thus supporting Hypothesis H7. Environmental regulation significantly and positively predicts recognition (β = 0.266, p < 0.001), thus supporting Hypothesis H8. Environmental regulation significantly and positively predicts interaction (β = 0.316, p < 0.001), thus supporting Hypothesis H9. Environmental regulation significantly and positively predicts purchase intention (β = 0.155, p > 0.001, p = 0.004 < 0.05), thus supporting Hypothesis H10 (see Table 9).

4.4. SEM Analysis Model Diagram

Figure 3 presents the SEM model, incorporating environmental regulation (ER) as an external factor. The model hypothesizes that ER directly influences green consumer orientation (identification, equilibrium, and interaction) and indirectly affects green purchase intention. The arrows represent direct and mediated paths tested through SEM analysis (see Figure 3).

5. Conclusions

This study successfully achieved the following research objectives:
Objective 1: To explore the multidimensional impacts of government environmental regulations on the three dimensions of green consumer orientation (identification, equilibrium, and interaction). Empirical results confirmed that environmental regulations significantly enhance all three dimensions (β = 0.266, β = 0.733, β = 0.316, all p < 0.001).
Objective 2: To analyze the mediating role of green consumer orientation between government policies and green purchase intention. The SEM results demonstrated that GCO mediates the relationship between environmental regulations and green purchase intention, with a total effect size of 0.373.
Objective 3: To provide theoretical foundations and practical strategies for green marketing and policy design in the fresh cold chain industry. The case of Zespri provided practical insights into the integration of policy interventions and corporate green strategies.

5.1. Conclusion and Discussion

A systematic analysis of the SEM model based on fit indices and path coefficient results clearly demonstrates that the SEM model performs better in terms of overall effectiveness and path significance. This result shows that introducing environmental regulation as an external influencing factor not only significantly enhances the explanatory power of the three core dimensions of green consumer orientation (identification, equilibrium, and interaction) but also further improves the predictive ability for green purchase intention.
In a complex green consumption environment, consumers’ purchase decisions are influenced by both policy guidance and the market environment. Therefore, the SEM model is more aligned with real-world contexts in revealing the driving mechanisms of green consumption behavior.
First, environmental regulation significantly enhances consumers’ ability to identify green products, making them more inclined to choose environmentally friendly products in their purchasing decisions. Peattie [60] pointed out that environmental regulation effectively promotes green consumption by altering social norms and consumer behavior.
This identification is not only based on consumers’ awareness of green labels and certifications but also reflects their personal commitment to environmental protection. The study by Antil et al. [61] showed that social factors, information availability, and market accessibility significantly influence consumers’ green purchase decisions, enhancing their identification and recognition of green products. Ajzen’s [10] Theory of Planned Behavior (TPB) provides a theoretical basis for understanding consumers’ behavioral intentions during the identification stage.
Secondly, environmental regulation helps consumers achieve better balance in green consumption decisions, finding the optimal trade-off among health, environmental protection, and economic benefits. Ambec and Lanoie [62] argued that environmentally friendly behavior not only improves a company’s environmental performance but also achieves a balance between economic benefits and environmental responsibility.
The study by Laari et al. [31] further validated the crucial role of green supply chain management in balancing corporate financial and environmental performance. At the consumer level, policy incentives and market guidance make it easier for consumers to balance economic costs and environmental value in green consumption, thereby enhancing green purchase intention.
Moreover, environmental regulation, through social promotion and policy incentives, significantly enhances consumer interaction with green products. Montoro-Rios et al. [63] pointed out that social promotion activities can effectively strengthen consumer interaction with green brands, thereby improving brand performance and consumer purchase motivation. Lin and Lin [26] also noted that promoting a green lifestyle can enhance consumers’ value recognition of environmentally friendly behavior and their social influence.
This study confirms that government environmental regulation significantly enhances green purchase intention by influencing the three dimensions of Green Consumer Orientation (GCO): identification, equilibrium, and interaction. These findings highlight that regulatory frameworks not only shape consumer perceptions but also provide practical guidance for enterprises to optimize their green strategies. This offers policymakers an evidence-based foundation for designing more effective green policies and incentives.
In summary, by introducing environmental regulation as a key variable, this study constructed a more explanatory green consumption behavior model and validated the significant role of environmental regulation in promoting green consumption. This result is consistent with the findings of Elhoushy and Lanzini [8], which indicated that the key role of policy in shaping consumers’ sustainable behavior lies in information provision and the formation of social norms.
Additionally, the findings of this study further support the viewpoint of Al-Swidi et al. that subjective norms, by shaping social expectations, can significantly enhance consumers’ recognition of green purchasing behavior [64].
Overall, this study provides important empirical references for governments and enterprises in formulating green policies and marketing strategies.

5.2. Theoretical Implications and Practical Implications

Compared with previous studies, which primarily focused on corporate green behavior under environmental regulations, this study highlights the consumer-side transformation mechanism. By introducing green consumer orientation (GCO) as a mediator, the study extends the policy–behavior linkage into the consumer decision-making domain. This shift from corporate to consumer perspective, especially within the fresh cold chain context, fills an important gap in the current green marketing literature.
This study offers the following theoretical contributions:
Theoretical Framework Innovation: By integrating the Theory of Planned Behavior (TPB) and the Value-Belief-Norm (VBN) framework, the study develops a comprehensive regulation-GCO-behavior model that explains how external policy signals transform into internal consumer motivation.
Conceptual Measurement Improvement: This study empirically validates the three-dimensional structure of GCO (identification, equilibrium, interaction), enriching the measurement system for green consumer orientation in the context of fresh agricultural products.
Contextual Contribution: By embedding the model into the fresh cold chain industry, this study expands the theoretical application of green consumer orientation into energy-intensive supply chains, which is rarely explored in the previous literature.

5.2.1. Theoretical Implications

This study offers several important theoretical contributions to the existing body of research on green purchase intention, government environmental regulation, and green consumer orientation (GCO).
First, this study enriches the theoretical understanding of how government environmental regulation influences green purchase intention by incorporating GCO as a mediating mechanism. While previous studies have separately explored the direct effects of environmental regulation on corporate environmental performance and consumer green behavior [4], the current research identifies the dynamic pathway through which regulation enhances green product identification, facilitates green consumer interaction, and promotes balanced decision-making. This contributes to the theoretical integration of policy signals and consumer psychological processes, forming a more comprehensive regulation–GCO–behavior framework [19].
Second, this study advances the conceptual application of GCO by empirically validating its three-dimensional structure (identification, equilibrium, and interaction) in the context of fresh produce consumption, which extends its applicability beyond general green product categories to the specific domain of perishable agricultural goods. This dimensional validation not only refines the operationalization of GCO but also enhances its explanatory power in contexts where product attributes (e.g., freshness and certification credibility) and perceived trade-offs (e.g., price vs. sustainability) are particularly salient [21].
Third, by embedding Zespri, a globally recognized green brand, into the empirical analysis, this study provides contextual insights into how brand credibility and environmental regulatory frameworks jointly shape consumer behavior. The integration of macro-level policy factors with micro-level brand positioning and consumer psychological processes offers a valuable extension to the green marketing and environmental policy literature, particularly in the domain of global agri-food supply chains [34].
Overall, this study bridges the gap between government environmental regulation research and green consumer behavior studies, demonstrating that regulatory actions are not isolated policy interventions but interactive forces shaping consumer values, social engagement, and purchasing norms [1].

5.2.2. Practical Implications

The findings of this study also provide several valuable practical implications for government policymakers, green product marketers, and supply chain managers, especially in the fresh produce and agri-food sectors.
First, for government policymakers are encouraged to adopt a combination of mandatory regulatory measures (e.g., eco-labeling and carbon footprint disclosure) and economic incentives (e.g., green subsidies, tax reductions) to lower the financial barriers consumers face when purchasing green products. Such policy combinations have been shown to not only enhance firms’ green supply chain management capabilities but also indirectly improve the market availability and affordability of green products, thereby fostering green consumerism [2]. Furthermore, public environmental campaigns should emphasize not only the environmental benefits of green products but also their alignment with consumers’ personal values and health concerns, thereby enhancing identification and interaction dimensions of GCO. This combination of regulatory enforcement, economic support, and public communication creates a holistic policy toolbox to drive green consumerism [7].
Second, for companies like Zespri and other agri-food brands, the findings emphasize the need to actively communicate their environmental compliance and green innovations to consumers. By ensuring transparency in supply chain carbon footprint, sustainability certifications, and eco-friendly farming practices, companies can strengthen consumer identification with their green brand attributes. Moreover, leveraging digital platforms and social media to foster consumer-to-consumer interaction can amplify positive green word-of-mouth (eWOM), thereby enhancing brand credibility and purchase intention [34].
Third, for supply chain managers and retailers, the results underscore the importance of balancing product quality, price, and environmental performance to achieve a consumer-perceived equilibrium. This means not only ensuring traceability and transparency throughout the supply chain but also actively engaging in value co-creation with consumers, allowing them to see how their personal preferences (e.g., freshness, taste, and price) align with environmental responsibility. Practical tools such as carbon footprint calculators at the point of sale, dynamic pricing for low-carbon products, and real-time supply chain visibility platforms can enhance this equilibrium perception, driving both consumer satisfaction and sustainable consumption [14].
In summary, government, businesses, and consumers form a synergistic ecosystem, where regulatory signals, corporate green practices, and consumer green orientation jointly shape the sustainable consumption landscape. This study offers actionable insights into how multi-stakeholder collaboration can foster both economic and environmental value, contributing to the global transition toward a greener and more sustainable economy [15].
Finally, Zespri’s case offers a replicable model for other global agricultural brands, demonstrating how proactive environmental compliance, transparent supply chain practices, and consumer-centric green communication can collectively foster brand differentiation and green purchase loyalty. For global agrifood companies aiming to balance profitability, product quality, and environmental responsibility, Zespri’s green strategy provides valuable strategic reference [20].

5.3. Policy Recommendations

The practical implications include the following:
For policymakers: Enhance eco-label credibility, expand green subsidies, and intensify environmental education to amplify consumers’ identification and equilibrium perceptions. For enterprises: Leverage green certifications and transparent carbon disclosure to strengthen brand credibility, while actively fostering consumer interaction through digital campaigns and green storytelling. For consumers: Enhance environmental literacy and participate in green consumption communities, strengthening peer influence and social identification with green lifestyles.
Based on the research results, this study proposes the following policy recommendations:

5.3.1. Strengthen the Role of Policy Guidance

The government should increase incentives for green consumption through green subsidies, tax incentives, and green financial support. At the same time, environmental awareness campaigns and green consumption education should be promoted to enhance public recognition and acceptance of green products. Hafezi and Zolfagharinia [4] showed that strict environmental policies and green subsidy measures by the government can effectively promote corporate investment and innovation in green product development.

5.3.2. Improve the Green Certification and Labeling System

Consumers’ green consumption behavior heavily depends on their ability to identify the environmental attributes of products; hence, the government should improve the green certification and labeling system, ensuring the authority and transparency of certification standards. Zespri’s successful experience in promoting carbon footprint labels also indicates that clear green labels and transparent information disclosure can significantly enhance consumers’ identification ability and purchase intention [45].

5.3.3. Encourage Enterprises to Adopt Green Marketing Strategies

Enterprises should actively respond to government environmental policies by adopting green production processes, improving product quality, and enhancing consumer trust in green products through transparent information disclosure. Dangelico and Vocalelli [47] pointed out that green marketing strategies play a crucial role in enhancing consumers’ awareness and trust in green products. Moreover, enterprises can use social media and online–offline promotional activities to stimulate consumer interest and participation in a green lifestyle, thereby enhancing the market competitiveness of green products.

5.4. Limitations and Future Outlook

Despite the valuable findings, this study has several limitations. First, the sample was drawn from consumers in a specific context, limiting the generalizability of the findings to other cultural and regulatory environments. Second, this study mainly focused on the cross-sectional relationship between government environmental regulations, green consumer orientation, and green purchase intention, without capturing the potential dynamic changes over time. Third, while this study considers environmental regulations as a whole, future studies could further differentiate between mandatory regulations, market-based mechanisms, and voluntary programs to evaluate their relative effectiveness. Future research could address these limitations through the following approaches:
Cross-Regional Comparative Studies: Expanding sample coverage to multiple countries or regions to explore how regulatory effectiveness varies under different institutional and cultural contexts.
Nurrochmat et al. [64] pointed out that the effectiveness of environmental regulation in a specific national context depends on the adaptability of policy design and the strength of implementation. Comparative studies could help uncover how these contextual factors shape the effectiveness of environmental policies and their impact on green consumer behavior.
Longitudinal Tracking: Conducting panel data analysis to capture the dynamic evolution of green consumer orientation and its response to changing environmental policies.
Policy Tool Effectiveness Comparison: Comparing the relative effectiveness of regulatory approaches (e.g., command-and-control vs. market-based) in shaping green consumer behavior across different product categories.
By addressing these areas, future research can contribute to a more comprehensive understanding of how environmental regulations influence sustainable consumption across diverse policy and cultural settings, ultimately enriching both academic knowledge and practical policy design.

Author Contributions

Conceptualization, Y.F. (Yi Feng); Methodology, Y.F. (Yi Feng); Software, Y.F. (Yi Feng); Validation, Y.F. (Yi Feng); Formal analysis, Y.F. (Yi Feng); Investigation, Y.F. (Yi Feng); Resources, Y.F. (Yi Feng); Data curation, Y.F. (Yu Feng); Writing—original draft, Y.F. (Yu Feng); Writing—review & editing, Y.F. (Yu Feng); Visualization, Y.F. (Yu Feng); Supervision, Y.F. (Yu Feng) and Z.L.; Project administration, Y.F. (Yu Feng); Funding acquisition, Y.F. (Yu Feng). All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

According to China’s regulations, ethical approval can be exempted since this research involves de-identified, anonymous data and poses minimal risk to participants, in accordance with the Ethical Review Methods for Life Sciences and Medical Research Involving Humans, issued by the National Health Commission in February 2023. The full text of the regulation can be accessed at: https://www.gov.cn/zhengce/2023-02/28/content_5743660.htm (accessed on 7 March 2025).

Informed Consent Statement

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

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

The following abbreviations are used in this manuscript:
SEMStructural Equation Modeling
SPSSStatistical Package for the Social Sciences
AMOSAnalysis of Moment Structures
GCOGreen Consumer Orientation
CRComposite Reliability
AVEAverage Variance Extracted
EREnvironmental regulation
IDIdentification
EQLEquilibrium
INTRCTInteraction
PIPurchase Intention

Appendix A

Table A1. Questionnaire.
Table A1. Questionnaire.
VariableCodeItemSource
Environmental regulationER1Government restrictions on environmentally unfriendly products will influence my purchasing decisions regarding Zespri kiwifruit.Li et al., 2024 [5]
ER2If subsidies are provided for purchasing Zespri kiwifruit, I would be more inclined to choose Zespri kiwifruit.
ER3Environmental policies implemented by the government can effectively promote green consumption behavior for Zespri kiwifruit.
ER4I believe that government regulations can enhance public awareness of the environmental benefits of Zespri kiwifruit.
IdentificationID1I am well-informed about Zespri kiwifruit and other green fresh agricultural products.Ayoun S, Schmitz S. 2024 [17]; Sharma and Foropon, 2019 [50]
ID2I always read the ingredient information of Zespri kiwifruit.
ID3Whenever I look for information on Zespri kiwifruit, I can easily find it because it is readily available.
ID4I trust the green label of Zespri kiwifruit.
ID5Zespri kiwifruit is environmentally friendly.
EquilibriumEQL1Consuming Zespri kiwifruit and other green fresh agricultural products is beneficial to my health.Bian et al., 2020 [32]; He et al., 2022 [51]; Bi et al., 2017 [52]
EQL2Purchasing Zespri kiwifruit and other green fresh agricultural products can reduce our environmental impact.
EQL3My income does not allow me to start consuming Zespri kiwifruit and other green fresh agricultural products.
EQL4I do not have time to look for Zespri kiwifruit and other green fresh agricultural products.
InteractionINTRCT1I like others to know that I consume Zespri kiwifruit and other green fresh agricultural products.Li et al., 2022 [53]; Muposhi et al., 2015 [27]
INTRCT2I feel proud when others know that I consume Zespri kiwifruit and other green fresh agricultural products.
INTRCT3Promotional information about Zespri kiwifruit and other green fresh agricultural products has attracted my interest.
INTRCT4A doctor’s recommendation would encourage me to switch to consuming Zespri kiwifruit and other green fresh agricultural products.
Green purchase IntentionGPI1I am willing to purchase Zespri kiwifruit and other environmentally friendly products, even if they are slightly more expensive.Tan et al., 2023 [54]
GPI2I prioritize the environmental attributes of Zespri kiwifruit when making a purchase.
GPI3I believe that choosing Zespri kiwifruit and other green products is crucial for environmental improvement.

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Figure 1. Pathway model. (ER = Environmental regulation; ID = identification; EQL = equilibrium; INTRCT = interaction; GPI = green purchase intention).
Figure 1. Pathway model. (ER = Environmental regulation; ID = identification; EQL = equilibrium; INTRCT = interaction; GPI = green purchase intention).
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Figure 2. Confirmatory factor analysis (CFA) model. (ER = environmental regulation; ID = identification; EQL = equilibrium; INTRCT = interaction; GPI = green purchase intention).
Figure 2. Confirmatory factor analysis (CFA) model. (ER = environmental regulation; ID = identification; EQL = equilibrium; INTRCT = interaction; GPI = green purchase intention).
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Figure 3. SEM analysis model diagram. (ER = environmental regulation; ID = identification; EQL = equilibrium; INTRCT = interaction; GPI = green purchase intention).
Figure 3. SEM analysis model diagram. (ER = environmental regulation; ID = identification; EQL = equilibrium; INTRCT = interaction; GPI = green purchase intention).
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Table 1. Descriptive statistics of the population sample.
Table 1. Descriptive statistics of the population sample.
CategoryDescriptionFrequencyPercentage
GenderMale47755.7
Female38044.3
Age18–24 years738.5
Under 18 years667.7
25–30 years15017.5
31–40 years18521.6
41–50 years17720.7
51–60 years12014.0
61 years and above8610.0
EducationBachelor’s degree20423.8
PhD172.0
High school and below41348.2
Master’s degree404.7
Associate degree18321.4
Monthly ExpenditureOver 10,001 RMB172.0
2000 RMB and below32738.2
2001–4000 RMB25129.3
4001–6000 RMB16018.7
6001–8000 RMB738.5
8001–10,000 RMB293.4
OccupationIndividual business owner/Contractor212.5
Housewife/Full-time homemaker424.9
Agricultural worker222.6
General laborer (e.g., factory worker)12915.1
Office worker16519.3
Other (Specify): Sanitation worker10.1
Business manager (includes mid- and high-level managers)768.9
Commercial service worker (e.g., sales staff, store clerk, and server)242.8
Retired728.4
Student647.5
Unemployed354.1
Government official/Civil servant516.0
Professional (e.g., doctor, lawyer, journalist, and teacher)465.4
Freelancer10912.7
Have you ever purchased green fresh agricultural products?No16819.6
Yes68980.4
Frequency of purchasing green fresh agricultural productsLess than once a year Once every six months364.2
Daily10712.5
Once a month627.2
Twice a week16419.1
Three times a week20624.0
Once a week11413.3
Are you aware of or have you purchased Zespri kiwifruit?No, unaware/never purchased708.2
Purchased31136.3
Aware, but never purchased30835.9
Total857100.0
Table 2. KMO and Bartlett’s Test and reliability.
Table 2. KMO and Bartlett’s Test and reliability.
ConstructCronbach’s AlphaNumber of Items
ER0.8614
ID0.8755
EQL0.8444
INTRCT0.8334
GPI0.8283
KMO Measure of Sampling Adequacy0.880
Bartlett’s Test of Sphericity
Approximate Chi-Square7514.705
Degrees of Freedom276
Significance0.000
ER = environmental regulation; ID = identification; EQL = equilibrium; INTRCT = interaction; GPI = green purchase intention.
Table 3. Fit test of the original green consumption orientation-SEM model.
Table 3. Fit test of the original green consumption orientation-SEM model.
ItemCMIN/DFNFITLICFIRMSEARFI
Excellent Value>1, <3>0.9>0.9>0.9<0.05>0.9
Good Value>3, <5>0.8>0.8>0.8<0.08>0.8
Result2.9570.9250.9390.9490.0570.911
Table 4. Convergent validity and composite reliability.
Table 4. Convergent validity and composite reliability.
Second-Order VariablesVariablesEstimateAVECR
ER1ER0.8650.61660.8646
ER2ER0.687
ER3ER0.812
ER4ER0.766
ID1ID0.8700.59240.8785
ID2ID0.705
ID3ID0.731
ID4ID0.777
ID5ID0.755
EQL1EQL0.8650.56780.8390
EQL2EQL0.714
EQL3EQL0.695
EQL4EQL0.728
INTRCT 1INTRCT0.8760.58770.8498
INTRCT 2INTRCT0.749
INTRCT 3INTRCT0.706
INTRCT 4INTRCT0.724
GPI1GPI0.8790.63280.9371
GPI2GPI0.769
GPI3GPI0.731
ER = environmental regulation; ID = identification; EQL = equilibrium; INTRCT = interaction; GPI = green purchase intention.
Table 5. Discriminant validity test results for each dimension of the scale.
Table 5. Discriminant validity test results for each dimension of the scale.
VariablesERIDEQLINTRCTGPI
ER0.617
ID0.3420.592
EQL0.5290.3810.568
INTRCT0.4980.4950.5350.588
GPI0.3970.3630.4120.4380.633
Square root of AVE values0.7850.7700.7540.7670.795
ER = environmental regulation; ID = identification; EQL = equilibrium; INTRCT = interaction; GPI = green purchase intention.
Table 6. Descriptive statistics and tests of normality for each dimension.
Table 6. Descriptive statistics and tests of normality for each dimension.
VariablesSecond-Order VariablesMeanStandard Deviation (SD)SkewnessKurtosisPopulation
Mean (M)
Population
SD
ERER13.341.337−0.407−0.9723.18790.97711
ER23.21.055−0.12−0.596
ER33.091.13−0.091−0.656
ER43.121.11−0.103−0.705
IDID13.361.337−0.449−0.9413.17820.93355
ID23.11.082−0.025−0.52
ID33.091.0760.009−0.612
ID43.21.114−0.114−0.705
ID53.141.085−0.084−0.538
EQLEQL13.191.344−0.163−1.1613.06330.95138
EQL23.031.091−0.025−0.559
EQL33.031.0690.016−0.481
EQL431.0820.071−0.573
INTRCTINTRCT 13.381.294−0.433−0.9393.15180.90830
INTRCT 23.11.048−0.155−0.476
INTRCT 33.071.049−0.035−0.576
INTRCT 43.061.04−0.047−0.435
GPIGPI13.361.372−0.358−1.0973.18011.04126
GPI23.091.111−0.105−0.636
GPI33.091.119−0.129−0.629
ER = environmental regulation; ID = identification; EQL = equilibrium; INTRCT = interaction; GPI = green purchase intention.
Table 7. Correlation matrix.
Table 7. Correlation matrix.
ERIDEQLINTRCTGPI
ER1
ID0.328 **1
EQL0.478 **0.368 **1
INTRCT0.451 **0.450 **0.474 **1
GPI0.370 **0.336 **0.383 **0.387 **1
** At the 0.01 level (two tailed), the correlation is significant. ER= environmental regulation; ID = identification; EQL = equilibrium; INTRCT = interaction; GPI = green purchase intention.
Table 8. SEM model fit test results.
Table 8. SEM model fit test results.
ItemCMIN/DFNFITLICFIRMSEAGFI
Excellent Value>1, <3>0.9>0.9>0.9<0.05>0.9
Good Value>3, <5>0.8>0.8>0.8<0.08>0.8
Result3.1150.9290.9510.9510.0650.859
Table 9. SEM path analysis results.
Table 9. SEM path analysis results.
Path RelationEstimateS.E.C.R.pOutcome
EQLER0.7330.06511.334***Supported
IDER0.2660.0733.621***Supported
IDEQL0.2750.0535.143***Supported
INTRCTER0.3160.0654.881***Supported
INTRCTEQL0.2780.0485.812***Supported
INTRCTID0.290.0426.882***Supported
GPIER0.1550.0532.920.004Supported
GPIEQL0.1150.042.8760.004Supported
GPIINTRCT0.1430.0443.2290.001Supported
GPIID0.1040.0362.9160.004Supported
ER = environmental regulation; ID = identification; EQL = equilibrium; INTRCT = interaction; GPI = green purchase intention; "***" indicates a statistically significant path coefficient, p < 0.05.
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MDPI and ACS Style

Feng, Y.; Feng, Y.; Liu, Z. The Impact Mechanism of Government Environmental Regulation and Green Consumer Orientation (GCO) on Green Purchase Intention: A Case Study of Zespri. Sustainability 2025, 17, 2575. https://doi.org/10.3390/su17062575

AMA Style

Feng Y, Feng Y, Liu Z. The Impact Mechanism of Government Environmental Regulation and Green Consumer Orientation (GCO) on Green Purchase Intention: A Case Study of Zespri. Sustainability. 2025; 17(6):2575. https://doi.org/10.3390/su17062575

Chicago/Turabian Style

Feng, Yi, Yu Feng, and Ziyang Liu. 2025. "The Impact Mechanism of Government Environmental Regulation and Green Consumer Orientation (GCO) on Green Purchase Intention: A Case Study of Zespri" Sustainability 17, no. 6: 2575. https://doi.org/10.3390/su17062575

APA Style

Feng, Y., Feng, Y., & Liu, Z. (2025). The Impact Mechanism of Government Environmental Regulation and Green Consumer Orientation (GCO) on Green Purchase Intention: A Case Study of Zespri. Sustainability, 17(6), 2575. https://doi.org/10.3390/su17062575

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