Exploring the Mediating Effects of the Theory of Planned Behavior on the Relationships between Environmental Awareness, Green Advocacy, and Green Self-Efficacy on the Green Word-of-Mouth Intention

Abstract

The concept of green and sustainable has long been a global trend in consumerism. This study examines the mediating variables involved in the Theory of Planned Behavior (namely attitude, subjective norms, and perceived behavioral control) to explore their mediating relationship with green word-of-mouth intention and the impact on subsequent green product purchase behavior. The aim is to clarify the antecedents of green word-of-mouth intention and the establishment of mediating variables in order to construct a framework for understanding the influence of consumers green product purchase decisions using Google online surveys and traditional paper surveys and subsequently analyze them via statistical software SPSS 23.0. The results indicated significant relationships between environmental awareness, green advocacy, green self-efficacy, and green word-of-mouth intention. Furthermore, attitude, subjective norms, and perceived behavioral control were found to mediate a partial mediating relationship between the antecedent variables and green word-of-mouth intention. This study also demonstrated the significant impact of green word-of-mouth intention on consumers green product purchase behavior.

1. Introduction

The global environment is progressively deteriorating due to swift economic advancement and population growth, making ecological concerns a worldwide priority. Not only are natural resources being exhausted, but patterns of human consumption also play a considerable role in environmental damage. The production processes involved in creating marketable products consume energy and generate waste, affecting the environment at each stage. As such, consumer behavior becomes crucial in addressing environmental problems. Consequently, there has been a global uptick in environmental awareness and the emphasis on sustainability, garnering significant attention over time. This has given rise to the trend of buying eco-friendly products. Furthermore, various international environmental treaties and regulations have necessitated that industries adopt green and sustainable practices.

The ideals of green consumption and the notion of sustainable consumption mutually reinforce each other. The term ‘green’ widely symbolizes the idea of being eco-friendly and accountable to our planet [1]. Numerous studies have shown the growing intention and behavior of consumers towards purchasing environmentally friendly products [2,3]. Rizwan et al. [4] argue that the societal propensity for green purchasing can be leveraged as an accelerator for environmental conservation. The wave of green consumption is flourishing, and businesses adopting green marketing can alleviate the environmental concerns put forward by various stakeholders. Moreover, it has the potential to boost corporate image, gain a competitive advantage, and even increase product value. As a result, the application of green marketing strategies in businesses is no longer considered a simple cost but rather a stimulant for achieving sustainable growth, fostering innovation, and unveiling new market opportunities.

The Theory of Planned Behavior (TPB) is a development of the Theory of Reasoned Action and is globally acknowledged as the premier theoretical model for understanding how individuals adopt certain behaviors. It scrutinizes behavioral patterns through three stages. Initially, behavior impacts the human propensity to act. This propensity then molds the attitude, subjective norm, and perceived behavioral control linked to the behavior. Finally, external elements are significant in forecasting and interpreting individual actions. Besides boosting the model’s explanatory power, the TPB assists in grasping the relationship between beliefs and intentions to behave. It is extensively used in various domains, such as consumer behavior, technology acceptance, healthcare, knowledge management, social research, and educational behavior.

In addition to the aforementioned concepts, the notion of word-of-mouth (WOM) has seen considerable evolution over the years. With the emergence of online communities, WOM has transitioned from being merely a supplementary component of traditional marketing to a critical metric for product endorsements and the assessment of whether a product or service satisfies consumer needs. The most effective way to measure this is by evaluating the degree to which customers are eager to suggest it to their friends and family. The viral nature of WOM marketing demonstrates its marketing potency and its impact on future customer repurchase intentions and loyalty towards the brand. By stimulating WOM activities, businesses can connect with environmentally aware consumers, which can then sway their buying decisions. Spurred by their positive experiences with the product, these environmentally minded consumers spontaneously recommend a company brand or share environmentally friendly messages regarding their products or services with their social networks.

Additionally, WOM has an amplifying effect that can potentially trigger a bandwagon phenomenon, whereby consumers’ unplanned purchasing behaviors increase even as their actual evaluation of the product diminishes. WOM is defined as informal, one-on-one communication about a specific brand, product, company, or service. Given that WOM typically takes place by virtue of casual interactions among friends, family, or peer groups, it is widely accepted that such exchanges of information are not motivated by commercial interests. As a result, WOM is often perceived as more credible and convincing from a consumer perspective compared with conventional advertisements. It plays a substantial role in guiding consumers’ decisions regarding product purchases.

Many earlier studies have explored various aspects of green-related issues, including perceived value, satisfaction, trust, and loyalty. However, a comprehensive framework and a thorough understanding of green marketing have not yet been fully established within the academic field. Most research has focused on topics such as green marketing, green packaging, green brand image, and green equity. Still, there has been less focus on green advocacy, green self-efficacy, and the inclusion of green WOM intentions into TPB.

Even though Chen et al. [5] highlighted the significant role of green WOM influence in business growth in the era of green trends, where consumers can disseminate powerful environmental messages via WOM, leading businesses to modify their marketing strategies, most existing academic research mainly focuses on individual factors, product factors, or environmental factors when analyzing effects on consumers’ inclinations and behaviors towards green purchases. There is a research gap regarding the impact of green WOM intention on purchasing behavior and the examination of mediating factors. More analysis and exploration are needed to understand the connections between these variables.

Hence, besides studying the influence of environmental awareness, green advocacy, and green self-efficacy as independent variables on green WOM intention and green purchase behavior, another research aim is to investigate whether the three elements of the TPB (attitude, subjective norm, and perceived behavioral control) act as intermediary variables, bridging the gap between precursor variables affecting green WOM intention and green purchase behavior. The goal of this study is to fully comprehend how green WOM intentions sway consumers’ decision-making in the context of buying green products. These insights will provide useful references for businesses in shaping effective marketing strategies. The ambition is to establish a comprehensive framework that includes environmental awareness, green advocacy, and green self-efficacy concerning green WOM intention and subsequent green purchase behavior.

2. Literature Review and Hypotheses Development

2.1. Environmental Awareness (EA)

Environmental awareness can be understood as the personal convictions individuals harbor about certain subjects or entities, reflecting their interpretive thought processes. Beliefs significantly mold attitudes and other impactful elements. Altin [6] characterizes environmental awareness as the cognizance of environmental issues and active participation in environmental bodies. Thus, the assessment of environmental awareness involves accounting for apprehensions regarding environmental dilemmas, their origins, and their detrimental outcomes. Thompson and Tong [7] suggest that environmental awareness involves a holistic attitude that mirrors a sense of environmental concern. They propose that heightened environmental awareness demonstrates a more profound regard for the environment and a stronger obligation to it. This responsibility further amplifies the acknowledgment of the importance of participating in eco-friendly behaviors.

The research by Pagiaslis and Krontalis [8] emphasizes a clear relationship between the degree of public awareness about the environment and their propensity to engage in environmentally responsible activities, significantly affecting consumer attitudes. As a result, businesses that value environmental preservation and show a high degree of environmental awareness tend to adopt environmentally-advocated principles more readily, participate actively in recycling efforts, and create environmentally friendly goods. Sharma and Foropon [9] further underline that while aspects such as cost, quality, and branding play vital roles in choosing eco-friendly products, consumers possessing environmental awareness show a more pronounced tendency to purchase these products. In a similar vein, Li et al. [10] found that customers who had previously bought green products showed a positive relationship between their environmental awareness and their intention to buy green products. This relationship was determined to be shaped by three factors: altruism, environmental awareness, and communication of brand image.

Hence, we can deduce that consumers with heightened environmental awareness are more apt to proactively seek out information related to the environment, and they are more open and agreeable to environmentally friendly principles endorsed by society. Moreover, these consumers are more prone to ethical practices such as recycling or buying green products. Based on the literature reviewed thus far, this research proposes the following hypothesis:

Hypothesis (H1).

Environmental awareness has a positive and significant impact on attitudes.

2.2. Green Advocacy (GA)

As emphasized by Czarnecki et al. [11] and Cheng et al. [12], the promotion of green causes significantly impacts the adoption of eco-friendly behaviors. This advocacy includes active discourse on environmental sustainability and the voicing of various viewpoints to encourage or endorse sustainable practices, strategies, and actions. Green advocacy consists of proactive efforts focused on preserving natural resources, mitigating pollution, and undertaking other measures to maintain and safeguard the environment. It takes many forms, such as increasing public awareness about environmental matters, pushing for policy amendments to encourage sustainability, endorsing environmental activities, and carrying out educational campaigns to inspire individuals and organizations to adopt environmentally responsible behaviors. The primary aim of green advocacy, as highlighted by Wu [13], is to improve environmental practices and enhance their sustainability performance.

Luu [14] underscored that when corporations engage in eco-friendly endeavors, they disseminate the outcomes to their employees in a variety of ways. As a result, workers do not just receive information but also gain knowledge related to environmental preservation. Employees’ environmental awareness, developed through organic interactions, tends to yield better results than environmental regulations enforced through the organization’s code of conduct. Kim et al. [15] suggested that the environment fostered during staff interactions within a company is either directly or indirectly shaped by others. When it comes to environmental matters, people are often eager to demonstrate high respect and make recommendations for providers who offer environmentally friendly products or services. Within this context, advocates for green practices play a vital role, as their messages to the public are often delivered in an instructive or inspiring way, making them more easily accepted by people.

Afsar and Umrani [16] explain that peer green advocacy is the extent to which workmates actively engage in conversations and offer suggestions related to environmentally conscious topics. This includes disseminating pertinent knowledge, enlightening others about the importance of environmental matters, expressing views on problem-solving, and promoting involvement in related activities. When social circles demonstrate advocacy behaviors driven by their commitment to green and environmental values, these beliefs are aimed at persuading peers, ultimately leading to the impact of eco-friendly consumption [17]. Advocacy involves spreading messages to family and friends through positive WOM communications [18].

As a result, the natural dialogues emerging from social interactions cultivate an environmentally aware atmosphere that permeates the group. The propensity to convince others is an intrinsic part of human nature. When people articulate their advocacy, it can be seen as a sustainable way to wield influence. Drawing from the aforementioned scholarly discourse, this research develops the subsequent hypothesis:

Hypothesis (H2).

Green advocacy has a positive and significant impact on subjective norms.

2.3. Green Self-Efficacy (GSE)

Self-efficacy pertains to a person’s trust in their proficiency to execute a set of tasks effectively and accomplish the desired results. It includes conviction in one’s ability to attain certain performance standards. High self-efficacy makes people more likely to vigorously chase their objectives [19]. Sharma and Dayal [20] emphasized how self-efficacy boosts inherent motivation, which results in the formation of favorable environmental behaviors. Self-efficacy symbolizes faith in one’s potential to aid in mitigating environmental degradation within a business setting. It assists in comprehending the distinct skills tied to organizational tasks that navigate and steer environmental actions, eventually fostering positive environmental behaviors.

Green self-efficacy refers to a person’s faith in their ability to plan and execute required measures to fulfill environmental goals, with its activation reliant on their confidence in tackling and accomplishing environmental tasks [21]. Greater green self-efficacy motivates people to undertake eco-friendly actions in pursuit of environmental objectives [22]. Green self-efficacy has a substantial influence on environmental awareness and attitudes, inspiring corporations to adopt eco-responsible practices and promoting managerial responsibility for operational behaviors. As such, green self-efficacy can be characterized as a belief in the competence to adapt to the environmental context and achieve green goals. People generally exhibit behaviors that resonate with their personal beliefs, societal norms, and roles.

Green self-efficacy encourages people to focus on tasks related to environmental issues. Those with higher green self-efficacy harbor a conviction in their abilities and confidence to effectively carry out specific eco-friendly tasks. Earlier research has demonstrated the positive effect of green self-efficacy, a kind of self-perception, on environmentally friendly behavior [23]. By shaping attitudes and actions rooted in self-confidence, green self-efficacy inspires eco-friendly actions, thereby diminishing obstacles and enhancing environmental performance [24]. Consumer self-efficacy has been recognized as a potential predictor of consumer behavior [25,26]. As such, it is hypothesized that there’s a positive correlation between green self-efficacy, perceived behavioral control, and green purchase behavior. Drawing from the above literature, the subsequent research hypothesis is established:

Hypothesis (H3).

Green self-efficacy has a positive and significant impact on perceived behavioral control.

2.4. Theory of Planned Behavior (TPB)

The TPB is a psychological framework that investigates the basis of personal actions by exploring the connection between attitudes and behavior. TPB pinpoints three core factors—attitude, subjective norm, and perceived behavioral control—that contribute to the creation of behavioral intentions. Recognized as an all-encompassing model of behavioral intention, TPB has gained considerable acknowledgment in the academic realm and has been broadly employed in various sectors, including environmental conservation and consumer behavior.

The TPB suggests that behavioral intention mirrors an individual’s propensity and readiness to perform a certain behavior. It embodies the cognitive process involved in decision-making for behavior selection, signaling the psychological commitment to the action. Behavioral intention is a subjective likelihood that predicts the probability of a behavior and is a crucial influencer of actual behavior. It signifies the deliberate intent and planned action towards a specific behavior, and it serves as a potent instrument for elucidating and forecasting behavioral performance. The theory further emphasizes that positive attitudes, stronger perceived external pressures, and increased control and resources have more potent intentions to execute the behavior [27].

2.5. Attitude (ATT)

Since everyone’s perception of ecology and the environment differs, there are varied intentions, actions, and attitudes concerning the purchase of green products. An attitude encapsulates a positive or negative perspective and denotes a consistent stance or assessment of preference. Factors such as sex, financial situation, education, social background, lifestyle, environment, and societal norms influence attitudes [28]. However, attitude can be gauged by multiplying behavioral beliefs and outcome evaluations, thereby creating a functional link. The higher the precision and specificity of attitude and behavioral intention, the more noticeable the correlation and internal intention become. Essentially, behavioral attitudes can predict behavioral intentions. Greater levels of subjectively positive assessments increase the likelihood of both behavioral intention and actual conduct. Hence, the specificity and positivity of attitudes serve as predictors for the emergence of behavioral intention. Kumar and Ghodeswar [29] explored consumer purchase decisions regarding green environmental products and found that consumer attitudes towards environmental conservation and their commitment to environmental responsibility significantly influence their intention to purchase green products [30]. Building upon the literature mentioned above, this study derives the following research hypotheses:

Hypothesis (H4).

Attitude has a positive and significant impact on green WOM intention.

Hypothesis (H5).

Attitude has a mediating effect between environmental awareness and green WOM intention.

2.6. Subjective Norm (SN)

As inherently social beings, humans harbor a natural desire to belong within a community. A prevalent trait is to align with group behavior for integration and acceptance. Grasping the behaviors, values, and principles viewed as acceptable by the group is also significant for people. Subjective norms embody the views and impacts of key individuals or reference groups that shape behavior. Subjective norms also include the societal pressures and experiences encountered when deciding whether to participate in a specific action. This social pressure comes from significant individuals, such as family members, close friends, peers, teachers, and superiors. External factors, like social media or government policies, can also influence this. These factors fall under the category of subjective norms [31]. When evaluating subjective norms, it is essential to measure the degree of regard individuals hold for the opinions of influential figures regarding a certain behavior and their level of alignment with these views [32]. If subjective norms hold a strong positive impact, it is more likely to cultivate intentions for disseminating positive WOM about eco-friendly practices [33] and stimulate green consumption behavior [34]. Based on the above literature, this study puts forth the following research hypotheses:

Hypothesis (H6).

Subjective norms have a positive and significant impact on green WOM intention.

Hypothesis (H7).

Subjective norms have a mediating effect between green advocacy and green WOM intention.

2.7. Perceived Behavioral Control (PBC)

The TPB operates on the premise that individuals possess absolute volitional control, which restricts its effectiveness in explicating and forecasting behavior. However, the reality is that many behaviors necessitate certain skills, knowledge, resources, time, and cooperation from others. There are also various barriers and enablers that control their involvement in these behaviors, taking future expectations into account. In acknowledgment of these factors, the concept of perceived behavioral control was added as an extra component to the original model. Perceived behavioral control refers to individuals’ understanding of their ability to execute a specific behavior, and it serves as the third determinant of behavioral intention [32]. When people perceive a heightened level of control over their behavior, meaning they have ample opportunities, resources, and skills to conduct the behavior, or when they perceive fewer impediments to its execution, their cognitive control strengthens. This enhanced sense of control significantly influences their behavioral intentions, yielding a stronger effect on their intended actions and solidifying a more consistent relationship between intentions and actual behavior. Moreover, prior experiences and garnering support from others that aid in performing a behavior tend to show a stronger intention to engage in that behavior. Drawing from the existing literature, this study posits the following research hypotheses:

Hypothesis (H8).

Perceived behavioral control has a positive and significant impact on green WOM intention.

Hypothesis (H9).

Perceived behavioral control has a positive and significant impact on green purchase behavior.

Hypothesis (H10).

Perceived behavioral control has a mediating effect between green self-efficacy and green WOM intention.

2.8. Green Word-of-Mouth Intention (GWI)

WOM encompasses the aggregated opinions and discussions about a specific product or service. Incorporating sustainability and eco-friendly principles into this discourse gives rise to the notion of green WOM. Green WOM describes the process wherein consumers sway their friends, relatives, or colleagues by disseminating positive environmental insights about a product, thereby inspiring them to purchase green products [35]. The term green WOM intention denotes a propensity to share personal experiences or assessments of green products, either positively or negatively, through spoken or written communication with others. As highlighted by Kusumawati et al. [36], positive WOM promotion can bolster a company’s image and expand its popularity. The information shared by everyday consumers, who have firsthand experience with the product, is generally perceived as more reliable and influential than information from salespeople or vendors.

This study centers on green WOM intention as the dependent variable, marking it as a critical element in the overall research design. Green WOM is an essential factor, offering potential consumers unbiased and independent references for their purchasing decisions. It functions as a rich source of information, enabling real-time feedback and promoting interactive dialogue. Green WOM allows consumers to gain indirect experience, aiding them in reducing the risks and uncertainties associated with purchasing. Conversely, intention refers to subjective evaluations and their probability or intention to engage in a specific behavior. It symbolizes a conscious strategy or decision-making process. On the other hand, WOM intention pertains to a personal intention to participate in persuasive interpersonal communication. Chen et al. [5] had earlier characterized green WOM as the degree to which consumers convey positive environmental aspects about a product or brand to their friends, family, and coworkers. When environmental awareness is driven by their understanding of environmental conditions and green practices and their core values, it ultimately manifests in actions that advocate environmental conservation. They voluntarily and spontaneously spread impactful environmental messages about businesses or products. This fundamental value is where the power of green WOM marketing is most effectively exhibited [37].

Owing to the complexities of authenticating the validity and trustworthiness of product information sources in the contemporary market, consumers lean on WOM when they’re unfamiliar with a product or service. They sift through WOM information to lessen their cognitive risks before committing to a purchase. Green WOM encompasses the assessment of a product, where consumers share green-related information, either positive or negative, with others, including endorsements, recommendations, or cautionary advice. Positive green WOM impressions about a product can enhance consumer trust, thereby influencing their subsequent buying choices. When consumers are unsure about green products, they are more likely to trust and buy products with positive green WOM feedback [5,38]. Drawing on the existing literature, this study puts forward the following research hypothesis:

Hypothesis (H11).

Green WOM intention has a significant positive impact on green purchase behavior.

2.9. Green Purchase Behavior (GPB)

In the past three decades, a gradual surge in public cognizance and worry regarding environmental matters has led to an increase in the number of entities and institutions concentrating on the green product industry [39]. Green purchase behavior, also termed as buying environmentally friendly or sustainable items, entails the deliberate acquisition of recyclable goods that have environmental benefits, thus reducing adverse impacts on the social ecosystem. This form of consumer activity is commonly described as eco-conscious consumption behavior, where people make informed decisions and take steps to choose products and services that lessen environmental degradation, slow down resource exhaustion, and aid in ecosystem preservation [40,41].

In the context of green purchasing, consumer behavior is frequently gauged based on their readiness or intention to acquire eco-friendly goods. This mindful behavior or intention eventually materializes in their decision to truly buy these items, thereby aiding in the promotion of environmental sustainability [42]. The market for organic and eco-friendly food items has seen a notable spike, particularly among younger consumers who display a higher propensity to buy green products, partly due to their increased disposable income [43]. Joshi and Rahman [42] pinpoint environmental concern, awareness, and the ecological qualities and functionalities of green products as the main driving factors behind green purchase behavior.

Conversely, Chang et al. [44] characterize green purchase behavior as consumers’ decision-making process founded on their own experiences and understanding of green products, with a special focus on environmental factors. This could entail the purposeful buying of environmentally advantageous products or the avoidance of products that are detrimental to the environment.

3. Methods

This study explores the effects of environmental awareness (EA), green advocacy (GA), and green self-efficacy (GSE) as antecedent variables on green WOM intention (GWI) and green purchase behavior (GPB). This study also examines the mediating effects of three important constructs mentioned in the TPB, i.e., attitude (ATT), subjective norm (SN), and perceived behavioral control (PBC). Based on the research objectives and relevant theoretical literature, a research framework is established (as shown in Figure 1 below). The relationships between the variables to be examined are discussed, and the hypotheses to be tested are proposed. Consumers who have previously had experience purchasing green products are selected as the subjects for empirical research. Finally, the distribution of questionnaires, sample characteristics, and analysis methods for questionnaire content are described.

This study employed a questionnaire survey for data collection. All eight research variables were measured via Likert 7-point scale, with scores ranging from 1 (strongly disagree), 2 (disagree), 3 (slightly disagree), 4 (neutral), 5 (slightly agree), 6 (agree), to 7 (strongly agree), indicating the level of agreement of the consumer with each measurement item. Higher scores indicate a higher level of agreement with the measurement item. The questionnaire items were derived from relevant past literature, and appropriate scales were selected for each variable while maintaining the original intent of the items. Minor adjustments and modifications were made as necessary. The questionnaire content for all variables is consolidated in Appendix A.

4. Data Analysis and Results

This research utilized a convenience sampling method to distribute and collect surveys. The intended survey recipients were consumers familiar with buying green products. To counteract the common method variance, this study opted for a time-separated measurement strategy. Specifically, three private schools in Taipei City and Taoyuan City were chosen as distribution points between 20 and 26 May, 12 and 16 June, and 25 and 30 June 2023. Every student was assigned a number, and the recipients of the surveys were randomly chosen using Excel random function. The student populations at the three schools were 487, 369, and 296, respectively, leading to 1152 participants overall.

In three phases, a total of 580 surveys were handed out, and 385 were returned. Initially, 120 surveys were shared online and 100 were printed questionnaires, resulting in 76 online and 69 paper responses, totaling 145 responses with an overall response rate of 66% (63% online and 69% paper). In the second phase, 100 surveys were given out online and in paper form, resulting in 76 online and 60 paper responses, totaling 136 responses (76% online and 60% paper response rate). In the final phase, 80 surveys were shared online and in paper form, yielding 48 online and 56 paper responses, adding up to 104 responses (60% online and 70% paper response rate).

However, 57 of the returned surveys were incomplete and deemed invalid. These were removed from the overall count, leaving 328 valid surveys, equating to an effective response rate of 57%. The surveys were then coded and stored in an Excel database. SPSS 23.0 statistical software was chosen to conduct data analysis and processing.

4.1. Descriptive Statistics Analysis

Descriptive statistical analysis on each facet of the questionnaire items, as shown in

Table 1. Demographic characteristics of the respondents (n = 328).

Variables	Characteristics	Frequency	Percentage (%)
Sex	Male	148	45.1
	Female	180	54.9
Age	<20	12	11.9
	21–30	71	18.6
	31–40	103	31.4
	41–50	80	24.4
	51–60	31	9.5
	>61	31	9.5
Education	Middle school and below	11	3.4
	High school	62	18.9
	Associate or bachelor	173	52.7
	Master and above	82	25.0
Occupation	Students	17	5.2
	Civil servant	26	7.9
	Business	19	5.8
	Workers	17	5.2
	Manufacturing	56	17.1
	Agriculture, forestry, fishery and animal husbandry	7	2.1
	Service industry	118	36.0
	Freelancer	36	11.0
	Others	32	9.8
Average Monthly Income (TWD)	<30,000	64	19.5
	30,001–50,000	111	33.8
	50,001–70,000	81	24.7
	70,001–90,000	49	14.9
	>90,001	23	7.0

, to understand the background information of the research sample. This analysis focuses on the main demographic variables, including sex, age, education level, occupation, and personal average monthly income, as the basis for statistical analysis.

4.2. Factor Analysis and Reliability Analysis

This research carried out factor and reliability analyses to scrutinize the relationship and stability of each element and item. All items demonstrated communalities exceeding 0.45, showcasing their appropriateness for examination. The factor extraction process was carried out using the maximum variance method, and when Cronbach’s α values for all elements and items were above 0.76, it signified satisfactory consistency, as displayed in

Table 2. Factor analysis and reliability analysis of each variable.

Factors	Items	Communality	Kaiser-Meyer-Olkin	Explained Variation (%)	Cronbachs’s Alpha If Item Deleted	Cronbachs’s Alpha
EA	1	0.715	0.672	61.91	0.696	0.792
	2	0.666			0.721
	3	0.448			0.804
	4	0.647			0.732
GA	1	0.552	0.82	58.251	0.792	0.82
	2	0.65			0.767
	3	0.61			0.777
	4	0.549			0.79
	5	0.551			0.788
GSE	1	0.548	0.843	61.16	0.724	0.766
	2	0.66			0.739
	3	0.555			0.716
	4	0.66			0.708
	5	0.635			0.725
ATT	1	0.676	0.799	70.47	0.836	0.861
	2	0.539			0.877
	3	0.79			0.795
	4	0.834			0.776
SN	1	0.765	0.816	73.792	0.838	0.881
	2	0.771			0.835
	3	0.692			0.862
	4	0.723			0.853
PBC	1	0.594	0.799	65.832	0.804	0.826
	2	0.726			0.754
	3	0.734			0.751
	4	0.578			0.81
GWI	1	0.545	0.671	59.975	0.744	0.776
	2	0.706			0.671
	3	0.639			0.682
	4	0.51			0.757
GPB	1	0.552	0.785	65.275	0.808	0.82
	2	0.75			0.731
	3	0.741			0.733
	4	0.568			0.806

.

The research also aimed to gauge eight elements: environmental awareness, green advocacy, green self-efficacy, attitudes, subjective norms, perceived control over behavior, green WOM intention, and green purchase behavior. All these elements were addressed by the same survey participants. To prevent common method bias arising from a single participant’s responses, Harman’s single-factor test was used to assess the presence of any common method variance in the research structure. In this method, all concept items were fed into SPSS software. The result demonstrated that the first unrotated principal component accounted for 47.81% of the variance, which was below 50%. Consequently, it implied that there was no significant problem with common method variance [45].

4.3. Pearson Correlation Coefficient

This research uses the Pearson correlation coefficient method to investigate the relationship and significance of various factors. The primary goal is to assess the similarity between these factors and hypothesize whether the general population data mirrors the sample data, giving insights into the potency and course of the correlation among different aspects.

Additionally, Composite Reliability (CR) represents the internal coherence of constructs. In this investigation, the CR values for all factors exceed 0.69, which implies acceptable convergent validity for the scales used. Furthermore, the Average Variance Extracted (AVE) values fall within a satisfactory range, demonstrating convergent validity among latent factors and their corresponding indicators. Regarding discriminant validity, the square root of the AVE surpasses the correlation coefficients among different aspects; with a range from 0.34 to 0.55, representatives have moderate discriminant validity, as demonstrated in

Table 3. Pearson correlation analysis of each variable.

	EA	GA	GSE	ATT	SN	PBC	GWI	GPB	CR	AVE
EA	0.62	0.615 **	0.786 **	0.161 **	0.369 **	0.228 **	0.236 **	0.186 **	0.72	0.39
GA		0.58	0.896 **	0.265 **	0.374 **	0.453 **	0.295 **	0.255 **	0.72	0.34
GSE			0.61	0.267 **	0.343 **	0.424 **	0.344 **	0.292 **	0.75	0.37
ATT				0.72	0.357 **	0.393 **	0.518 **	0.48 **	0.81	0.52
SN					0.74	0.157 **	0.296 **	0.278 **	0.83	0.55
PBC						0.66	0.528 **	0.467 **	0.76	0.44
GWI							0.61	0.856 **	0.69	0.37
GPB								0.66	0.75	0.43

** The correlation is significant at the 0.01 level (two-tailed). The diagonal values are the square root of the AVE values, and the upper triangle is the Pearson correlation coefficient.

.

4.4. Variance Analysis

4.4.1. Independent Sample t-Test of Sex

A t-test was employed to scrutinize the connection between sex and diverse aspects, which is depicted in

Table 4. Independent sample t-test of sex variable.

Variables	Sex	Mean	Standard Deviation	t	Sig.
EA	Male	5.61	0.914	0.191	0.214
	Female	5.59	0.75
GA	Male	5.8	0.747	2.511	0.866
	Female	5.59	0.796
GSE	Male	5.82	0.712	2.452	0.89
	Female	5.62	0.713
ATT	Male	5.87	0.779	1.67	0.299
	Female	5.72	0.836
SN	Male	5.43	1.091	−0.281	0.056
	Female	5.47	0.919
PBC	Male	5.78	0.707	3.075	0.46
	Female	5.53	0.758
GWI	Male	5.87	0.681	1.092	0.805
	Female	5.79	0.679
GPB	Male	5.99	0.562	1.268	0.134
	Female	5.91	0.594

. The findings suggest that sex does not significantly influence the variables in this study.

4.4.2. ANOVA of Age

The analysis results are shown in

Table 5. One-way ANOVA table for age variable.

Variables	Age	Mean	Standard Deviation	F	p
EA	<20	5.48	1.1	0.994	0.421
	21–30	5.65	0.871
	31–40	5.58	0.703
	41–50	5.58	0.909
	51–60	5.4	0.844
	>61	5.83	0.746
GA	<20	5.92	0.711	0.622	0.683
	21–30	5.73	0.785
	31–40	5.68	0.718
	41–50	5.62	0.898
	51–60	5.55	0.766
	>61	5.77	0.704
GSE	<20	5.97	0.748	0.701	0.623
	21–30	5.76	0.713
	31–40	5.69	0.634
	41–50	5.69	0.838
	51–60	5.55	0.728
	>61	5.75	0.657
ATT	<20	5.88	0.758	1.656	0.145
	21–30	5.71	0.912
	31–40	5.78	0.743
	41–50	5.67	0.848
	51–60	5.96	0.806
	>61	6.09	0.666
SN	<20	5.06	1.31	1.705	0.133
	21–30	5.33	1.189
	31–40	5.56	0.825
	41–50	5.32	0.951
	51–60	5.73	0.97
	>61	5.56	1.016
PBC	<20	5.9	0.765	0.709	0.617
	21–30	5.68	0.829
	31–40	5.6	0.711
	41–50	5.57	0.72
	51–60	5.66	0.749
	>61	5.77	0.722
GWI	<20	5.96	0.706	1.629	0.152
	21–30	5.93	0.705
	31–40	5.76	0.652
	41–50	5.7	0.597
	51–60	5.9	0.848
	>61	5.99	0.688
GPB	<20	6.06	0.513	0.891	0.487
	21–30	5.98	0.629
	31–40	5.93	0.531
	41–50	5.85	0.527
	51–60	6.06	0.697
	>61	6.01	0.647

. Age had no significant impact on the variables in this study.

4.4.3. ANOVA of Education

The analysis results are shown in

Table 6. One-way ANOVA table for education level variable.

Variables	Education	Mean	Standard Deviation	F	p
EA	Middle school and below	5.57	0.881	0.122	0.947
	High school	5.55	0.848
	Associate or bachelor	5.62	0.842
	Master and above	5.58	0.785
GA	Middle school and below	5.89	0.647	1.224	0.301
	High school	5.53	0.821
	Associate or bachelor	5.69	0.795
	Master and above	5.75	0.73
GSE	Middle school and below	5.87	0.75	0.855	0.465
	High school	5.59	0.739
	Associate or bachelor	5.74	0.709
	Master and above	5.72	0.721
ATT	Middle school and below	5.75	0.791	0.088	0.967
	High school	5.81	0.729
	Associate or bachelor	5.8	0.857
	Master and above	5.75	0.792
SN	Middle school and below	5.16	0.957	0.657	0.579
	High school	5.57	0.84
	Associate or bachelor	5.42	1.02
	Master and above	5.45	1.072
PBC	Middle school and below	6.0	0.716	1.355	0.257
	High school	5.54	0.83
	Associate or bachelor	5.67	0.702
	Master and above	5.62	0.764
GWI	Middle school and below	5.91	0.683	1.773	0.152
	High school	5.68	0.606
	Associate or bachelor	5.82	0.709
	Master and above	5.94	0.659
GPB	Middle school and below	6.0	0.559	1.978	0.117
	High school	5.8	0.526
	Associate or bachelor	5.95	0.589
	Master and above	6.03	0.592

. Education level had no significant impact on the variables in this study.

4.4.4. ANOVA of Occupation

The analysis results are shown in

Table 7. One-way ANOVA table for occupation variable.

Variables	Occupation	Mean	Standard Deviation	F	p
EA	Students	5.31	1.168	1.053	0.396
	Civil servant	5.64	0.801
	Business	5.68	0.74
	Workers	5.81	0.798
	Manufacturing	5.58	0.671
	Agriculture, forestry, fishery and animal husbandry	5.96	0.994
	Service industry	5.65	0.793
	Freelancer	5.35	0.899
	Others	5.59	0.941
GA	Students	5.76	0.641	1.542	0.142
	Civil servant	5.84	0.757
	Business	5.67	0.716
	Workers	6.06	0.699
	Manufacturing	5.69	0.745
	Agriculture, forestry, fishery and animal husbandry	5.23	0.752
	Service industry	5.64	0.811
	Freelancer	5.47	0.786
	Others	5.57	0.831
GSE	Students	5.87	0.671	1.259	0.265
	Civil servant	5.82	0.711
	Business	5.73	0.749
	Workers	5.93	0.612
	Manufacturing	5.72	0.646
	Agriculture, forestry, fishery and animal husbandry	6.17	0.725
	Service industry	5.66	0.715
	Freelancer	5.48	0.788
	Others	5.72	0.803
ATT	Students	5.76	0.978	1.118	0.351
	Civil servant	6.08	0.783
	Business	5.79	0.678
	Workers	5.93	0.744
	Manufacturing	5.72	0.831
	Agriculture, forestry, fishery and animal husbandry	6.25	0.804
	Service industry	5.79	0.79
	Freelancer	5.61	0.716
	Others	5.66	0.977
SN	Students	4.91	1.732	2.399	0.016 *
	Civil servant	5.78	0.893
	Business	5.58	0.764
	Workers	5.75	0.713
	Manufacturing	5.68	0.746
	Agriculture, forestry, fishery and animal husbandry	6.07	1.018
	Service industry	5.31	1.126
	Freelancer	5.4	0.844
	Others	5.3	0.968
PBC	Students	5.6	0.977	0.515	0.845
	Civil servant	5.7	0.768
	Business	5.58	0.736
	Workers	5.63	0.751
	Manufacturing	5.59	0.724
	Agriculture, forestry, fishery and animal husbandry	6.07	0.921
	Service industry	5.67	0.751
	Freelancer	5.52	0.585
	Others	5.69	0.788
GWI	Students	5.94	0.721	0.906	0.511
	Civil servant	5.95	0.707
	Business	5.74	0.761
	Workers	5.72	0.483
	Manufacturing	5.77	0.615
	Agriculture, forestry, fishery and animal husbandry	6.29	0.847
	Service industry	5.86	0.72
	Freelancer	5.73	0.608
	Others	5.73	0.678
GPB	Students	6.06	0.504	0.739	0.657
	Civil servant	6.03	0.634
	Business	5.93	0.661
	Workers	5.85	0.307
	Manufacturing	5.9	0.561
	Agriculture, forestry, fishery and animal husbandry	6.21	0.871
	Service industry	5.99	0.591
	Freelancer	5.87	0.509
	Others	5.83	0.64

* p < 0.05

. Although occupational category had a significant impact on the subjective norm variable, post-hoc analysis using the Scheffe method revealed that the differences were too small to compare their distinctiveness.

4.4.5. ANOVA of Average Monthly Income

The analysis results are shown in

Table 8. One-way ANOVA table for average monthly income variable.

Variables	Average Monthly Income (NTD)	Mean	Standard Deviation	F	p
EA	<30,000	5.5	0.972	0.652	0.626
	30,001–50,000	5.69	0.883
	50,001–70,000	5.59	0.632
	70,001–90,000	5.58	0.823
	>90,000	5.49	0.74
GA	<30,000	5.69	0.754	0.612	0.654
	30,001–50,000	5.69	0.875
	50,001–70,000	5.75	0.675
	70,001–90,000	5.64	0.826
	>90,000	5.47	0.623
GSE	<30,000	5.74	0.712	0.529	0.714
	30,001–50,000	5.75	0.817
	50,001–70,000	5.7	0.592
	70,001–90,000	5.68	0.77
	>90,000	5.52	0.518
ATT	<30,000	5.75	0.824	0.432	0.786
	30,001–50,000	5.81	0.905
	50,001–70,000	5.83	0.715
	70,001–90,000	5.78	0.754
	>90,000	5.6	0.79
SN	<30,000	5.33	1.051	0.887	0.472
	30,001–50,000	5.47	1.068
	50,001–70,000	5.47	1.021
	70,001–90,000	5.63	0.845
	>90,000	5.24	0.676
PBC	<30,000	5.65	0.77	0.308	0.873
	30,001–50,000	5.62	0.774
	50,001–70,000	5.59	0.67
	70,001–90,000	5.73	0.775
	>90,000	5.7	0.757
GWI	<30,000	5.84	0.756	0.248	0.911
	30,001–50,000	5.85	0.644
	50,001–70,000	5.84	0.658
	70,001–90,000	5.77	0.723
	>90,000	5.73	0.652
GPB	<30,000	5.96	0.6	0.539	0.707
	30,001–50,000	5.95	0.608
	50,001–70,000	6.0	0.525
	70,001–90,000	5.88	0.606
	>90,000	5.84	0.52

. Average monthly income had no significant impact on the variables in this study.

4.5. Regression Analysis

A linear regression evaluation was performed to explore the interconnections among the study factors, such as the inclination towards green WOM intention and green purchase behavior. This examination was set to affirm research assumptions H₁ through H₈, the summarized outcomes of which are displayed in

Table 9. Regression analysis table of dependent variables.

Variable	ß	R2	Adj R2	t	F	p
EA → ATT	0.161	0.026	0.023	2.938	8.632	0.004 **
GA → SN	0.374	0.14	0.137	7.286	53.085	0.000 ***
GSE → PBC	0.424	0.18	0.177	8.451	71.413	0.000 ***
ATT → GWI	0.518	0.268	0.266	10.93	119.473	0.000 ***
SN → GWI	0.296	0.088	0.085	5.605	31.421	0.000 ***
PBC → GWI	0.528	0.279	0.277	11.238	126.296	0.000 ***
PBC → GPB	0.467	0.219	0.216	9.547	91.152	0.000 ***
GWI → GPB	0.856	0.732	0.732	29.868	892.08	0.000 ***

** p < 0.01; *** p < 0.001.

. Moreover, the potential for collinearity within the study variables was also investigated. The tolerance measures for each pathway variable oscillated between 0.76 and 0.97, and the variance inflation factor (VIF) measures for each pathway variable oscillated between 1.03 and 1.32. Consequently, this study did not suffer from any collinearity problems.

4.6. Hierarchical Regression Analysis

This study expands on previous analysis by delving deeper into the intermediary relationships of attitude, subjective norm, and perceived behavioral control variables as per the TPB, utilizing hierarchical regression analysis. It seeks to validate whether hypotheses H9 through H11 are substantiated. To scrutinize the mediating effects between variables, this study implements Baron and Kenny’s [46] approach. A mediating effect is established if it satisfies several prerequisites: initially, there should be a significant impact of the independent variable on the mediating variable; subsequently, both the independent variable and the mediating variable should have a significant influence on the dependent variable. Then, a multiple regression analysis is performed, including both the independent and the mediating variables on the dependent variable. If the impact of the independent variable on the dependent variable is lessened yet remains significant due to the mediating variable, there is partial mediation, and if the influence of the independent variable on the dependent variable becomes insignificant due to the presence of the mediating variable, it represents a complete mediating effect.

4.6.1. Mediating Effect of Attitude on the Relationship between Environmental Awareness and Green Word-of-Mouth Intention

As per the data presented in

Table 10. The mediating effect of attitude on the relationship between environmental awareness and green word-of-mouth intention.

Variable	Model 1		Model 2		Model 3		Model 4
	ATT		GWI		GWI		GWI
	ß	t	ß	t	ß	t	ß	t
EA	0.161 *	2.938	0.236 ***	4.382	-	-	0.154 **	3.314
ATT	-	-	-	-	0.518 ***	10.93	0.493 ***	10.42
F	8.632		19.2		119.473		67.057
R2	0.026		0.56		0.268		0.292
ΔR2	0.023		0.53		0.266		0.288

* p < 0.05, ** p < 0.01, *** p < 0.001.

, the standardized regression coefficient (ß) is noted as 0.161, signifying a significant level. This serves to illustrate that there is a substantial positive influence of environmental awareness on attitudes, thereby corroborating the first condition. The second model reveals a standardized regression coefficient of 0.236, which also hits a significant level, indicating that environmental awareness has a considerable positive effect on the green WOM intention, thus validating the second condition. The third model showcases a standardized regression coefficient of 0.518, reaching a significant level as well, signifying a substantial positive association between attitude and green WOM intention, which supports the third condition. Consequently, all preconditions for setting up the mediating impact of attitude are met.

Lastly, by juxtaposing the findings from Models 2 and 4, it becomes clear that the effect of environmental awareness on the green WOM intention, once the attitude variable is incorporated, displays a dip in the standardized regression coefficient from the initial value of 0.161 to 0.154 while still maintaining statistical significance (p = 0.000 < 0.05). As such, attitude plays a partial mediating role in the connection between environmental awareness and the green WOM intention, thereby endorsing Hypothesis H5.

4.6.2. Mediating Effect of Subjective Norm on the Relationship between Green Advocacy and Green Word-of-Mouth Intention

According to Model 1 displayed in

Table 11. The mediating effect of subjective norms on the relationship between green advocacy and green word-of-mouth intention.

Variable	Model 1		Model 2		Model 3		Model 4
	SN		GWI		GWI		GWI
	ß	t	ß	t	ß	t	ß	t
GA	0.374 ***	7.286	0.295 ***	5.58	-	-	0.214 ***	3.836
SN	-	-	-	-	0.296 ***	5.605	0.216 ***	3.871
F	53.085		31.137		31.421		23.729
R2	0.14		0.087		0.088		0.127
ΔR2	0.137		0.084		0.085		0.122

*** p < 0.001

, the significant standardized regression coefficient (ß) of 0.374 suggests a considerable positive effect of green advocacy on subjective norms, thereby fulfilling the first condition. Examining Model 2 reveals a standardized regression coefficient of 0.295, indicating that green advocacy notably enhances the propensity to participate in green WOM intentions, meeting the second condition. Model 3 shows a standardized regression coefficient of 0.296, signifying that subjective norms positively influence the green WOM intention, accomplishing the third condition. Thus, the basic prerequisites for subjective norms mediating effect are satisfied. Finally, the comparison of Models 2 and 4 results shows a decrease in the standardized regression coefficient for the impact of green advocacy on the green WOM intention from the original 0.295 to 0.214 after incorporating subjective norms. The decrease is statistically significant (p = 0.000 < 0.05), denoting that subjective norms partially mediate the connection between green advocacy and green WOM intention, thereby validating Hypothesis H7.

4.6.3. Mediating Effect of Perceived Behavioral Control on the Relationship between Green Self-Efficacy and Green Word-of-Mouth Intention

Examining Model 1 in

Table 12. The mediating effect of perceived behavioral control on the relationship between green self-efficacy and green word-of-mouth intention.

Variable	Model 1		Model 2		Model 3		Model 4
	PBC		GWI		GWI		GWI
	ß	t	ß	t	ß	t	ß	t
GSE	0.424 ***	8.451	0.344 ***	6.614	-	-	0.146 ***	2.847
PBC	-	-	-	-	0.528 ***	11.238	0.466 ***	9.082
F	71.413		43.741		126.296		68.577
R2	0.18		0.118		0.279		0.297
ΔR2	0.177		0.116		0.277		0.292

*** p < 0.001.

, we notice the significant standardized regression coefficient (ß) of 0.424, suggesting a substantial positive effect of green self-efficacy on perceived behavioral control, fulfilling the first condition. Model 2 also presents a significant standardized regression coefficient of 0.344, indicating green self-efficacy meaningfully influences green WOM intention, satisfying the second condition. The third model shows a significant standardized regression coefficient of 0.528, which signals a substantial positive impact of perceived behavioral control on green WOM intention, satisfying the third condition. Consequently, all the necessary preconditions for the mediation effect of perceived behavioral control are fulfilled. When comparing Models 2 and 4, it becomes clear that the impact of green self-efficacy on green WOM intention drops from a standardized regression coefficient of 0.344 to 0.146 upon inclusion of perceived behavioral control, achieving statistical significance (p = 0.000 < 0.05). Therefore, perceived behavioral control acts as a partially mediating factor between green self-efficacy and green WOM intention, backing up Hypothesis H10.

5. Conclusions and Discussion

The worldwide shift towards sustainable development has picked up speed. With a rise in environmental awareness among the public and an increase in sustainable practices in businesses, the notion of eco-friendly consumption has found a place in the mainstream market. This study recognizes and examines this growing trend. Green shopping is a way through which consumers can actively contribute to the protection of the environment. It involves the purchase of eco-friendly products, which can have a favorable effect on the environment. Eco-conscious consumers make a deliberate decision to buy products that are kind to the environment and take concrete steps in this direction. They adhere to principles of green consumption like waste reduction, material reuse, recycling, repairing instead of discarding, rejecting single-use items, and adopting lifestyle practices that are in sync with contemporary environmental movements.

Following the collection of responses from consumers who have previously bought eco-friendly products, the research carried out statistical evaluations to substantiate the findings. The data generated from standalone t-tests and one-way ANOVAs suggested that factors like sex, age, educational attainment, and average monthly income did not show a substantial effect on the variables studied. However, it was discovered that the category of occupation did play a significant role in affecting the variable related to subjective norms. The research found a significant and positive difference in the readiness to partake in green WOM amongst the three distinct variables studied. Examination of the β coefficient values showed that green self-efficacy had the strongest influence on the green WOM intention, closely trailed by green advocacy. In contrast, attitude had the least effect on readiness for green WOM. According to the regression analysis of the data collected from the questionnaire, it can be determined that the variables of environmental awareness, green advocacy, and green self-efficacy proposed in this study all have a significant positive impact on the dependent variable, green purchase intention.

In summary, this research scrutinized the mediating influences among the three primary variables in the TPB through hierarchical regression analysis. The results revealed critical understanding. First, it was found that attitude partially mediated the connection between environmental awareness and green WOM intention. Second, subjective norms were identified as having a partial mediating impact on the link between green advocacy and green WOM intention. Finally, this study established that perceived behavioral control also functioned as a partial mediator in the relationship between green self-efficacy and green WOM intention. Sustainable development has become a universally accepted concept today. Increased awareness and academic discussions on environmental issues have fueled a rise in scholarly research related to green marketing. Most of these investigations predominantly address different facets of consumer perceptions, contentment, trust, loyalty, and buying habits concerning eco-friendly products. However, there has been insufficient inquiry into the amalgamation of the readiness for green WOM and its effect within the structure of the TPB.

This research contributes to academia by confirming the framework and hypotheses, which illustrate that attitude, subjective norm, and perceived behavioral control serve as partial mediators. This outcome helps fill a research void in the study of green WOM. In addition, this study incorporates aspects of environmental awareness, green advocacy, and green self-efficacy into the TPB to statistically examine and verify the impact of green consumers on both green WOM intention and their behavior towards purchasing green products. Consequently, a thorough framework is constructed, encapsulating the intertwined relationships among these variables. From a practical perspective, the idea of eco-friendly consumption has achieved widespread acknowledgement and acceptance due to the endeavors of governmental bodies, industries, and the academic world. It has effortlessly become a part of contemporary products and services. Consumers are becoming cognizant of the considerable effects their consumer habits and buying behaviors exert on the environment and ecosystems. As a result, consumers have begun to alter their consumption behaviors, thus compelling businesses to embrace novel production techniques that diminish environmental pollution and damage. Green consumption spans various facets of everyday life, including diet, apparel, housing, travel, and leisure activities. The market is teeming with a plethora of visible and utilitarian items for daily use that underscore environmental attractiveness and the goal of a sustainable planet.

Consumers consciously opt for products that exert minimal harmful effects on both the planet’s ecology and human health, embodying a lifestyle of green consumption that emphasizes low pollution, recyclability, and conservation of resources. Throughout a product’s life cycle, it should be utilized efficiently, promoting the use of products that demand fewer resources while meeting consumer requirements without excessively draining ecological resources. It is also advisable for manufacturers to not only integrate environmentally friendly characteristics into their products but also to consider the materials used and the aesthetic appeal of eco-friendly products. This ensures that such eco-friendly goods maintain both high quality and an appealing design. Governments can help foster green consumption through mandatory regulations or incentives. Manufacturers can also highlight the importance of environmental protection in their advertisements, thereby encouraging consumers to choose green products.

By participating in green advocacy, we can jointly tackle environmental challenges. These actions can easily become part of daily routines, and while they might seem simple, they carry considerable weight. Schools or communities can regularly hold contests and events focused on green products, offering rewards to students or residents who actively buy and use eco-friendly products. This strategy aids in fostering the growth of personal environmental awareness. Additionally, to ensure the public is well-informed about environmental issues, develops a positive environmental value system, and actively engages in meaningful environmental practices, it is recommended that the education sector intensify its efforts to instill a positive and proactive environmental mindset among citizens. Such efforts will contribute to improving human well-being and promoting environmental sustainability.

6. Restriction and Further Research

During the course of the research, meticulous steps were undertaken to guarantee the accuracy and thoroughness of the investigation, all while maintaining impartiality and fairness. However, it is essential to recognize the constraints that may have affected the research outcomes, which necessitate their contemplation. With respect to the one-way analysis of variance, even though the occupational category showed a significant effect on the subjective norm variable, a post hoc analysis using Scheffe’s method disclosed that the detected differences were too minute to make substantial comparisons. This limitation underscores the requirement for future research to probe into this facet with more depth and careful examination. This study employed a structured questionnaire survey approach. Of the total 328 questionnaires gathered, 200 (61%) were filled out via online surveys. As a result, direct supervision of the respondents during the questionnaire completion process was not feasible. Several situational factors, such as unclear instructions leading to less thoughtful responses or environmental factors resulting in less precise answers, could have influenced the survey results and the overall credibility of the statistical data.

Furthermore, although the questionnaire design was based on previous similar studies and a custom-made structured questionnaire, it included a relatively smaller number of items, which might have affected the research results. Additionally, the subjects of green advocacy and green WOM intention are relatively nascent, and there is a scarce selection of scales available for reference. Therefore, it is recommended for future researchers to broaden their scale designs, perform repeated tests, and aim for questionnaires with enhanced reliability and validity, thereby ensuring a more robust construction of the dimensions being studied.

For upcoming researchers, it is suggested to expand the range of the study by incorporating various categories of eco-friendly products and executing comparative research in specific regions where green consumption is actively endorsed, given the feasibility regarding time, resources, and manpower. Moreover, while this study made use of a questionnaire design with indicator variables and quantitative statistical analysis, it would be beneficial for future research to consider alternative statistical analysis methods or introduce qualitative research techniques like focus group interviews. Such qualitative methods can offer extra insights that might not be fully grasped through solely quantitative analysis.

Ultimately, WOM serves as an informal channel of communication among friends and family, which bolsters its credibility in consumers’ eyes. As the propensity to share WOM escalates, it has a greater impact on customers’ immediate and long-term buying decisions [47]. WOM is regarded as an independent, reliable, and trustworthy source of information that is unaffected by commercial interests. It has a wider effect and a broader scope in terms of communication and influence as compared with other marketing strategies. The influence of WOM is considerably more potent, with positive WOM increasing the likelihood of consumers being inclined to make a purchase.

Finally, WOM encompasses casual conversations among friends and relatives, which bolsters the credibility perceived by consumers and escalates their propensity to disseminate such information, in turn influencing their immediate and future buying decisions [47]. WOM is recognized as an independent and dependable source of information, free from commercial biases, and is viewed as autonomous and trustworthy. Its impact and influence outshine those of other marketing approaches. The sway of WOM transcends that of other tactics, with positive WOM considerably increasing the probability of consumers purchase intentions. This study utilizes the TPB as its primary framework to explore the link between green consumers’ intent to share information and their purchasing behavior for environmentally friendly products, with an emphasis on their beliefs. To deepen the understanding of this relationship, upcoming research can consider adding other measurement metrics such as the experiences of green consumers, trust, loyalty, and the quality of green products to investigate their mediating roles. Furthermore, since this study did not delve into the moderating effects of variables, it could be beneficial to incorporate practical factors like consumer lifestyle, preferences, and expected psychological responses as potential moderating variables. By including these elements, a more holistic model can be developed to better clarify the manifestation of green purchasing intentions.