Green Marketing: Drivers in the Process of Buying Green Products—The Role of Green Satisfaction, Green Trust, Green WOM and Green Perceived Value

Abstract

Green marketing is currently one of the most powerful strategies in the corporate world as it responds to a growing demand for green products. Therefore, this study aims to analyse the influence of green perceived value on green trust and green satisfaction, study how both variables impact green word of mouth in turn and, at the same time, how the three variables influence green purchase intention. Data collection was carried out through a digital survey of buyers of green products. The hypotheses posed were solved with a PLS-SEM model through the Smart-PLS software. The results showed that green perceived value positively affects green trust and green satisfaction. Furthermore, green satisfaction was found to influence green trust and green WOM. Green trust also influences green WOM. Regarding the antecedents of green purchase intention, only green satisfaction and green trust showed a positive relationship. In contrast, green WOM did not show a relationship with green purchase intention. The article shows the importance of green satisfaction for green companies in achieving green purchase intention, green WOM and green trust. Green perceived value is also an important variable, as it is the trigger for the process that leads to green purchase intention.

1. Introduction

The market for green products, understood as ecological, natural, organic and healthy goods, has grown significantly in recent years thanks to the corporate world’s efforts to offer better environmental protection and wellness schemes [1] under the concept of green marketing [2], which includes a wide range of activities related to production, sales, brand image creation and communication with the consumer [3]. According to Garvey et al. [4], these green marketing strategies have increased green awareness among mainstream consumers, thus generating a highly profitable segment in which brands are constantly investing [5]. As a result of these strategies, green consumption at a global level is booming due to the concern for health and the environment that both companies and consumers are generating [6]. In this regard, previous research found that 92% of companies had made changes to their products to be seen as green in order to respond to the environmental concerns of the market [3].

From a theoretical point of view, it is known that green marketing strategies have a high impact on businesses, as they allow the generation of commitment to the brand due to the trust generated by green products [7], which in turn can be transformed into green word of mouth, and which can ultimately lead to the intention to purchase green products or services [8]. However, despite the fact that green products have gained a market presence and manufacturers are tailoring their products to the public’s preference for these types of goods, their purchase is not as frequent or high as one might expect, mainly due to the reluctance to substitute the purchase of mainstream products with those that are labelled as green [8,9]. In this sense, the present study aims to examine the reasons that influence the purchase intention process of green products, evaluating green perceived value, green trust, green satisfaction and green WOM [10,11,12]. More specifically, the present study aims to analyse and understand the impact of green perceived value on green trust and green satisfaction, as well as the specific relationship between green satisfaction and green trust. In addition, the influence of green trust and green satisfaction on green WOM and green purchase intention is also explored, in addition to an analysis of the impact of green WOM on green purchase intention.

Regarding the variables included in this research proposal, it is known that green perceived value is a variable that reduces the perceived risk of green products, thus improving purchase intention, competitive market advantage [10] and brand positioning [13]. In addition, it is known to have the ability to influence green satisfaction, green trust, green WOM [14] and green purchase intention [10,15]. On the other hand, according to Wang et al. [16], green trust is a variable in green marketing that provides credibility, generates loyalty and can influence purchase intention and green WOM [10]. In the case of green satisfaction, this variable has been extensively studied in green marketing due to its strong influence on green trust, loyalty [16] and purchase intention for green products [12], and due to its relationship with consumer environmental awareness [17]. It is also worth noting that the literature has corroborated that green purchase intention is related to customer satisfaction [12], green trust [8,18] and green perceived value [12,17].

Finally, green WOM, according to Wang et al. [16], can be related to the perceived value, satisfaction or purchase intention of green products [17]. However, despite its importance in green marketing [3,19], the number of research studies that study green WOM as a relevant link within the purchase process [11] have been limited thus far; undoubtedly, the results of the present research can contribute significantly to this knowledge from a theoretical and practical point of view.

Moreover, this research aims to extend the knowledge of the theory of planned behaviour (TPB) [20] and the stakeholder theory [21]. The TPB argues that consumer decision processes often are conditioned by motivational factors that influence consumer attitudes and behavioural intentions [22] to purchase green products and services [23,24,25,26]. According to the stakeholder theory, companies should use strategies to satisfy and win the trust of their stakeholders [21]; green marketing is one of the main strategies used to be socially responsible [10,27] since green marketing focuses on long-term sustainability [28] by studying consumer’s green attitudes and behaviours and by developing marketing programs [29].

1.1. Green Perceived Value (GPV)

The literature on marketing suggests that perceived value is an essential factor for companies and customers, as it has a direct impact on economic profitability and price/value for money [14,30]. Initially, it was measured in a unidimensional way, but it faced multiple criticisms [15,31]; thus, it is now studied by taking into account emotional, social, economic and quality dimensions [32,33].

Regarding its conceptualization, perceived value is defined as the overall evaluation that customers develop towards a product, based on what is delivered and what is received [15,34,35,36]. In the case of the green market, it is known as green perceived value and is associated with the benefits obtained by the consumer that serve to satisfy their environmental concerns and sustainable expectations [37,38] which, according to Chen et al. [10], can contribute to the generation of green WOM or intention to purchase a green product.

1.2. Green Trust (GT)

The creation of various forms of relationships has turned trust into a fundamental variable in the exchange [39] or purchases made between individuals and companies, where brands show their ability to watch out for the interests of their customers [12,40,41,42] by guaranteeing the reliability of the exchange [43,44] thanks to the trustworthiness, credibility and benevolence on the part of the supplier [41,45]. In the case of green trust, this comprises the buyer’s willingness to trust a green product based on beliefs or expectations about the environmental and health performance capacity of the green product [10,12], which conditions the green purchase intention [16,38].

1.3. Green Satisfaction (GS)

The first studies on satisfaction in the context of marketing were limited because academic research focused on variables that conditioned consumption, such as perceived value, leaving aside other relevant variables such as satisfaction, purchase intention and WOM [46,47]. Currently, satisfaction is defined as a consumer’s feeling about a product after having bought and used it [48,49]; it has become one of the most important variables for marketing, due to its importance in ensuring the success of a brand and guaranteeing long-term relationships with consumers [50,51,52] in virtually any context or sector. In this sense, one of the sectors where the study of the variable has aroused the most interest is in green products, which has allowed green satisfaction to be defined as the level of pleasurable fulfilment related to consumption in order to satisfy the environmental and health desires or expectations of a customer [12,53,54], which can lead to the generation of green perceived value, green trust and green WOM [8].

1.4. Green Word of Mouth (WOM)

The study of the word-of-mouth variable dates back to the first research studies in which the positive relationship between customer satisfaction and the generation of recommendations about a product or service by buyers was studied [55]. Currently, WOM is considered one of the variables which is used most by users when they need to obtain information about products and/or services [56], as they perceive that WOM is tailored to them and is reliable, as there are people involved who do not have a direct relationship with the product [57,58]. Conceptually, word of mouth was initially defined as communication about a brand, product or service between a receiver and a communicator [59,60]. Over time, the green trend began to be incorporated into the study of WOM, resulting in green word of mouth (green WOM), defined as the extent to which a customer influences friends, family or associates by spreading positive environmental messages about a product [17], eventually leading them to often buy a green product [11,16].

1.5. Green Purchase Intention (GPI)

The purchase intention variable is based on the theories of planned behaviour (TPB) [20] and reasoned action (TRA) [61], where the relationship between a person’s attitude is influenced by their intentions and the amount of effort they are willing to make to behave in a certain way is explained [62]. In this sense, purchase intention can be defined as a consumer’s predisposition to buy a brand or product [63] based on the motivations they have [64]. As with the other variables that are a part of this study, it should be noted that purchase intention has also been studied from a green perspective, which has allowed us to conceptualise green purchase intention as the interest, desire and probability that a consumer will purchase environmentally friendly products [11,65], whereas its relationship with green satisfaction, green trust and green perceived value has also been proven [10,11].

1.6. Hypotheses and Research Model

Green perceived value is not only a determinant of purchase intentions, but also of long-term customer relationships which are built on green trust [10], especially since consumers initially tend not to trust green products [38] due to the fact that companies sometimes exaggerate green perceived value through their communication strategies [42] and the implementation of green marketing strategies. Furthermore, previous research has shown that in the eco-friendly product category, green perceived value has a strong influence on green purchase intention and green trust [9,66,67,68]. Based on the above, it can be assumed that such a relationship also occurs in the green product category, and therefore, the following hypothesis is proposed:

Hypothesis 1 (H1).

Green perceived value has a positive influence on green trust regarding green products.

On the other hand, previous studies have shown that green perceived value and green satisfaction are good predictors of customer behaviour; therefore, there is a positive relationship between the two [15,34,38], where the green satisfaction is determined by the green perceived value [17]. This relationship was proven, for example, in the research of Issock Isssock et al. [8] on eco-friendly products, or Wu et al. [69] and Pahlevi et al. [9] on green products and green services [9,27,70]. Based on the above, the following hypothesis is proposed:

Hypothesis 2 (H2).

Green perceived value has a positive influence on green satisfaction regarding green products.

Green satisfaction with a product tends to increase green trust, as satisfactory experiences are related to the degree of consumer trust [16] in believing that the green product is safe and protects the planet and the stakeholders. Han et al. [71] described in their study of customers of green medical services how green satisfaction significantly affects green trust. Similarly, other authors have mentioned that green satisfaction positively influences green trust, as it generates certainty in the customer’s purchase intentions [8,9,27,72,73]. Based on the above, the following hypothesis is proposed:

Hypothesis 3 (H3).

Green satisfaction has a positive influence on green trust regarding green products.

Previous studies have corroborated the importance of green trust when generating green WOM, as high levels of trust in the customer generate not only intentions to buy, but also intentions to recommend the product or service to other potential consumers [16]. Likewise, authors such as Han et al. [71] and Wang et al. [74] mention in their studies that green trust generates the necessary security and credibility in customers for them to be able to recommend products, and thus, generate green WOM since, when a consumer trusts a green brand, the consumer is more disposed to generate WOM [75]. The literature on green marketing further indicates that green trust has a positive and significant effect on green WOM, since when customers have confidence in the environmental capability of a product, they talk about it positively to other potential customers [8,73,76]. In this regard, the following hypothesis is proposed:

Hypothesis 4 (H4).

Green trust has a positive influence on green WOM regarding green products.

Studies in the green product category have demonstrated the positive relationship between green trust and green purchase intention [9,10,11,26,77] since customers prefer to purchase trusted green products [75]. Furthermore, Lam et al. [28], Suhartanto et al. [73], and Guerreiro and Pacheco [75] mentioned that a critical element of green marketing is green trust, as it has the ability to influence the green purchase intention of targeted consumers since green trust is key in influencing green behaviour [67] based on the theory of planned behaviour [20,42]. In view of this, the following hypothesis is proposed:

Hypothesis 5 (H5).

Green trust has a positive influence on green purchase intention regarding green products.

It has been known for a long time how important satisfaction is in the construction of green WOM in environmentally conscious consumers [78]. In this respect, Wang et al. [16] argued that green satisfaction acts as a relevant determining factor for the generation of green WOM. Furthermore, Issock Issock et al. [8] mentioned that if customers have satisfactory experiences with green products, they will recommend the product positively, which will generate not only green trust, but also positive green WOM for the product [8] or services [76]. Therefore, the following hypothesis is proposed:

Hypothesis 6 (H6).

Green satisfaction has a positive influence on green WOM regarding green products.

Previous studies have shown that there is a positive relationship between green satisfaction, green brand image and green trust with green purchase intention among consumers of a green brand [12] or simply between green satisfaction and green purchase intention [26,79]. In this sense, the following hypothesis is proposed:

Hypothesis 7 (H7).

Green satisfaction has a positive influence on green purchase intention regarding green products.

Finally, it is known that green WOM can be of great use to companies by allowing them to reduce their marketing expenditures and increase profits [11,80] since consumers can share information about green products and influence other consumers to purchase green products [1]. In this sense, Wang et al. [16], Guerreiro and Pacheco [75], and Ahmad and Zhang [11] argued that green purchase intention is directly influenced by green WOM, as the information that green consumers obtain online through other consumers can be key in deciding to purchase a green product as customers search for trusted online information about green products to reduce the perceived risk [75]. Based on the above, the following hypothesis is proposed.

Hypothesis 8 (H8).

Green WOM has a positive influence on green purchase intention regarding green products.

2. Materials and Methods

This study is of a definitive nature, based on the causes and effects of the relationship between the proposed concepts [81]. The research population was consumers of green products in Lima, Peru. The sample consisted of 404 people, from whom 208 valid responses were obtained (see

Table 1. Demographic profile of the respondents.

Demographic Profile	Frequency	%
Gender
Female	189	64%
Male	108	36%
Age
Under 18	9	3%
18 to 25 years old	147	49%
26 to 35 years old	95	32%
36 to 45 years old	40	13%
46 and over	6	2%
Occupation
Student	102	34%
Employee	126	42%
Self-employed	59	20%
Unemployed or retired	10	3%
Place of purchase
Eco-fair	58	20%
Specialised shops	95	32%
Online websites of specialised shops or supermarkets	54	18%
Supermarkets	90	30%
Products
Dairy	102	15%
Snacks (cereal bars, biscuits)	175	26%
Health drinks	84	12%
Oils and vinegars	96	14%
Granola and corn flakes	154	23%
Other	62	9%
Frequency of purchase
Weekly	52	18%
More than once a month	59	20%
Monthly	134	45%
Infrequently	52	18%

) since the other 198 responses were incomplete. A convenience sample by quotas was used, based on responders’ ages and gender (non-probabilistic sampling procedure). Data were collected through a self-administered online questionnaire for one month in the second half of 2021. Data collection was carried out through rigorous ethical protocols to guarantee the respondents’ anonymity and the answers’ reliability. The data collection instrument was divided into two sections. Furthermore, there was a filter question regarding the purchase intention of green products. Only consumers of green products answered the online questionnaire. The first section consisted of questions associated with the demographic profile of the respondents, such as gender, age, occupation, place of purchase, range of green products bought and frequency of purchase (See Table 1).

The second section of the questionnaire included the scales for measuring the variables proposed in the study model: green perceived value (GPV), green trust (GT), green satisfaction (GS), green WOM (GW) and green purchase intention (GPI).

Table 2. Scales and descriptive results.

Scales	Median	DE
Green Perceived Value (GPV)—Pahlevi, M.R., Suhartanto, D. (2020) [9]
GPV1—Organic products provide more benefits than the cost of obtaining them. They are worth it.	4.16	0.72
GPV2—Organic products are more environmentally sound and health-conscious than more conventional products.	4.39	0.67
GPV3—Organic products are more beneficial to my health and the environment than more conventional ones.	4.43	0.66
Green Trust (GT)—Pahlevi, M.R., Suhartanto, D. (2020) [9]
GT1—I believe organic products have a good reputation because they help our health and the environment.	4.26	0.75
GT2—I believe that organic products are reliable.	4.15	0.72
GT3—I believe in the brands that sell organic and eco-friendly products.	3.91	0.90
GT4—I believe that organic products live up to their promises to care for our health and the environment.	4.05	0.84
Green Satisfaction (GS)—Pahlevi, M.R., Suhartanto, D. (2020) [9]
GS1—Using organic products makes me feel good and satisfied.	4.28	0.62
GS2—I think it is a wise decision to buy organic products.	4.25	0.61
GS3—Overall, I am satisfied with organic products.	4.12	0.80
Green Word of Mouth (GW)—Ahmad, W., Zhang, Q. (2020) [11]
GW1—Due to their eco-friendly and healthy image, organic products are recommended by other people.	4.12	0.76
GW2—Due to their environmental and health benefits, organic products are positively recommended by other people.	4.22	0.62
GW3—Due to being environmentally friendly and healthy, organic products have a good reputation.	4.25	0.69
GW4—Due to their environmental and health benefits, organic products receive positive feedback from people.	4.21	0.68
Green Purchase Intention (GPI)—Ahmad, W., Zhang, Q. (2020) [11]
GPI1—Because of my concerns about the environment and health, I will try to buy organic products.	4.26	0.62
GPI2—I intend to buy organic products due to their ecological and health performance.	4.10	0.74
GPI3—I intend to buy organic products because of their environmental impact and health benefits.	4.21	0.68
GPI4—I am happy to buy organic products because of their respect for the environment and health.	4.34	0.64
GPI5- I will keep myself updated about the benefits of using organic products.	4.22	0.76
GPI6—I will buy organic products when I need to buy healthy things.	4.26	0.72

shows the scales and descriptive results. All the scales used in the research were previously used in other investigations. The questionnaire was pretested on ten samples.

It is worth mentioning that Likert scales (1—strongly disagree to 5—strongly agree) were used to evaluate the indicators of the variables. Since these scales were originally written in English, they were translated into Spanish so that they could be applied to the population under study. In addition, a validity analysis was carried out through a pilot test in order to ensure the rigour and quality of the study in the proposed context [82]. Likewise, the validation test allowed us to check that there was no ambiguity of terms, meanings and other problems that could arise among consumers of green products covered in this study.

To answer the hypotheses stated above, a PLS-SEM model was developed, this being the most appropriate method of estimating complex models due to its high probability of revealing substantial effects in an exploratory research environment [83]. The model (See Figure 1) was developed based on previous investigations about green marketing [10,84]. The statistical programme used to solve the PLS-SEM model was Smart-PLS 3.3.3 [85].

3. Results

The analysis is based on the structural theory and the measure of latent variables in a reflective model [85]. In order to answer the hypotheses posed, the results of the study were evaluated through a two-stage PLS-SEM model [86,87,88]. In the first stage, the reflective model was examined, and in the second stage, the structural theory was evaluated to validate the proposed relationships between variables [85,89].

Since the present study contained reflexively specified constructs, we started with an analysis of the indicator loadings. The results showed that all items had values above 0.7 (see

Table 3. Results of the measurements of the reflective model.

Latent Variable	Indicators	Loadings	Cronbach’s Alpha	rho_A	Composite Reliability	Average Variance Extracted (AVE)
GPI	GPI2	0.84	0.844	0.849	0.889	0.617
	GPI3	0.83
	GPI4	0.77
	GPI5	0.73
	GPI6	0.75
GPV	GPV1	0.70	0.718	0.747	0.841	0.640
	GPV2	0.83
	GPV3	0.86
GS	GS1	0.78	0.726	0.728	0.845	0.646
	GS2	0.85
	GS3	0.78
GT	GT1	0.78	0.843	0.844	0.895	0.681
	GT2	0.80
	GT3	0.86
	GT4	0.87
GW	GW1	0.71	0.818	0.833	0.880	0.648
	GW2	0.81
	GW3	0.86
	GW4	0.83

) [83].

The next step involved an analysis of the composite reliability [90], using Cronbach’s alpha as a complementary measure of reliability for internal consistency, and using Rho A. The values of all three indicators were above 0.7, which allowed for the verification that the constructs meet the internal consistency reliability [83,85,91]. Furthermore, convergent validity was calculated using the average variance extracted (AVE). The results indicated that the constructs met convergent validity by being above 0.5 in all cases [83,87,92].

Finally, in the first phase, the discriminant validity of the model was assessed through the heterotrait-monotrait ratio (HTMT) and the Fornell–Larcker criterion [92]. The results allowed for the verification of the discriminant validity since all the values calculated, both under the Fornell–Larcker criterion and HTMT, were within the ranges considered optimal (see

Table 4. Fornell–Larcker Criterion.

	GPI	GPV	GS	GT	GW
GPI	0.785
GPV	0.439	0.800
GS	0.714	0.525	0.803
GT	0.653	0.629	0.670	0.825
GW	0.598	0.514	0.637	0.600	0.805

and

Table 5. HTMT Values.

	GPI	GPV	GS	GT	GW
GPI
GPV	0.557
GS	0.899	0.728
GT	0.774	0.797	0.845
GW	0.707	0.656	0.812	0.711

).

After verifying that the measurement model met all the necessary criteria, the evaluation of the structural model proceeded [85]. First, possible collinearity problems between variables were checked through the VIF, and then the evaluation focused on the predictive model. For this, different criteria such as R², Q², Q²predict, f² and path coefficients were used (see Table 5).

First, VIF was assessed, taking into consideration that values greater than 5 indicate collinearity between constructs [83]. Regarding the results, GPI was 1.738; GPI2, 2.188; and GPI3, 2.063. GPV had a value of 1.269 for GPV1; 1.526 for GPV2; and 1.599 for GPV3. In the case of GS, GS1 showed a value of 1.587; GS2, 1.779; and GS3, 1.279. In GT, GT1 had a value of 1.606 and GT2, 1.709. Finally, GW obtained 1.422 for GW1 and 2.001 for GW2. From the results, it could be concluded that the constructs do not have collinearity problems as they are below 5. Next, the results of R² were analysed in order to find out the coefficient of determination (See Figure 2). For this evaluation, it was considered that there is greater predictive accuracy as the value is higher [85]. The results of the research showed results of 0.579 for GPI, 0.275 for GS, 0.555 for GT and 0.460 for GW; thus, it could be affirmed that the values of the endogenous latent variables of the inner model are moderate [93].

Bootstrapping was then performed with 5000 samples for p < 0.05 and p < 0.01 in order to determine the relationship between the variables [66]. In this regard, it could be verified by the proposed analysis that all hypotheses were accepted for a p < 0.05, but not for a p < 0.01, where hypothesis H8 was rejected. The results showed that for hypothesis H8, which evaluated the relationship of GW → GPI, the path coefficient was 0.16. For H2, GPV → GS, a β of 0.52 was obtained. For H3, GS → GT, the β data was 0.47. For H1, which measured the relationship of GPV → GT, its β was 0.63, whereas for H4, GT → GW, its β was 0.31.

Finally, H6, which assessed the relationship of GS → GW, had a β of 0.57, the relationship of GT → GPI, H5, showed a β of 0.32, and H7, GS → GPI, yielded a result of 0.65 (see

Table 6. Structural model path coefficients and hypothesis testing.

	β	T-Value	p-Values Sig < 0.05	Supported	p-Values Sig < 0.01	Supported	f2
H1—GPV → GT	0.63	12.81	0.000	Yes	0.000	Yes	0.24
H2—GPV → GS	0.52	9.22	0.000	Yes	0.000	Yes	0.38
H3—GS →GT	0.47	7.84	0.000	Yes	0.000	Yes	0.36
H4—GT → GW	0.31	4.66	0.000	Yes	0.000	Yes	0.10
H5—GT → GPI	0.32	5.18	0.000	Yes	0.000	Yes	0.08
H6—GS → GW	0.57	10.41	0.000	Yes	0.000	Yes	0.19
H7—GS → GPI	0.65	15.90	0.000	Yes	0.000	Yes	0.21
H8—GW → GPI	0.16	2.48	0.013	Yes	0.013	No	0.03

).

Subsequently, the f² results were evaluated in order to assess the effect of exogenous latent variables [94]. The results obtained from f² for the relationship between GS and GPI were 0.21; for GT and GPI, it was 0.08. In the case of GW and GPI, a value of 0.03 was obtained. For GPV and GS, the result was 0.38; for GPV and GT, 0.24; for GS and GT, the result was 0.3; for GT and GW, the result was 0.10; and, finally, GS and GW achieved an f² of 0.19. From the results, it could be concluded that the effects are small in the cases of GT-GPI, GW-GPI, and GT-GW. For GPV-GT and GS-GW, the effects were medium, whereas in the case of GPV-GS and GS-GT the effects were high [93,94].

The Q² results were also evaluated by blindfolding with an omission distance of 7 [95]. In this regard, the present study showed that the Q² of GPI was 0.35; that of GS, 0.18; GT, 0.37; and GW, 0.29. The results indicated that the predictive ability of the model is acceptable [83,85,93].

Finally, predictive ability was also assessed with the PLS predict algorithm by using ten folds and ten repetitions and estimating the Q²predict [96,97]. The first step was to check that all Q²predict values were greater than 0 and then compare the RMSE values with the naïve LM for each indicator. It should be noted that RMSE was used because visual analysis of the graphs of the prediction errors showed that the distribution is not highly non-symmetric. The results indicated that all but three PLS-SEM indicators have an RMSE lower than the LM (see

Table 7. PLS predict assessment of manifest variables (original model).

	PLS-SEM		LM	PLS-SEM − LM
	RMSE	Q2predict	RMSE	RMSE
GPI3	0.636	0.141	0.645	−0.009
GPI6	0.705	0.093	0.701	0.005
GPI4	0.620	0.114	0.630	−0.009
GPI2	0.728	0.111	0.738	−0.010
GPI5	0.743	0.108	0.754	−0.011
GS3	0.775	0.130	0.780	−0.006
GS2	0.541	0.186	0.541	0.000
GS1	0.549	0.204	0.554	−0.005
GT3	0.854	0.186	0.859	−0.005
GT1	0.664	0.280	0.657	0.007
GT4	0.741	0.256	0.738	0.003
GT2	0.603	0.325	0.607	−0.004
GW4	0.618	0.212	0.619	−0.001
GW3	0.633	0.203	0.639	−0.006
GW1	0.735	0.120	0.742	−0.007
GW2	0.619	0.102	0.629	−0.010

); therefore, it could be concluded that the predictive ability was average [97].

4. Discussion and Implications

This study presents a series of significant contributions to understanding how different variables associated with green marketing, such as green perceived value, green trust, green satisfaction and green word of mouth, influence consumers of green products when they intend to buy a green product. In this sense, it is worth emphasising the incorporation of the model of green word of mouth as a central variable for the generation of green purchase intention, which represents a significant theoretical contribution compared to the recent research by Issock Issock et al. [8], Wang et al. [16], Zhang et al. [2], Lam et al. [38] and McDougall et al. [34].

In this sense, the first contribution of this research is the incorporation of green WOM as a variable that conditions green purchase intention, which undoubtedly complements the findings of Yang et al. [36], Chen [12], Guenzi et al. [43] and Ahmad et al. [11], who in their respective studies had identified variables such as green satisfaction or green trust as decisive for the generation of green purchase intention. However, it should be noted that, contrary to what might be expected, the results of the influence of green WOM on green purchase intention are limited, which contradicts the findings of Wang et al. [16] in the green hospitality sector. Although these results are initially striking, they may be due to the category on which this research was based, green products, as the low involvement and risk taken when buying these products may mean that the search for consumer recommendations is limited. In this sense, these results are consistent with those of Pandey et al. [98], who confirmed that WOM has little importance in the purchase of organic products in an emerging country, or those of Hamzah et al. [99], who came to the same results in the case of halal products.

The second contribution is also related to green WOM, since, although its importance in influencing green purchase intention is limited, the same is not true when analysing its importance within the model in general. In this sense, it is worth noting that there is a strong relationship between green WOM and green trust and green satisfaction. As can be seen in the results, especially in the case of green satisfaction, but also with green trust, the two variables are fundamental for the generation of green word of mouth, which reinforces the findings of Chen et al. [10] and Pahlevi et al. [9] in the case of green trust, and those of Wang et al. [16], Issock Issock et al. [8,17,100] and Martenson [101] in the case of green satisfaction.

On the other hand, this research has also been able to corroborate the importance of green perceived value as the beginning of the process that a consumer initiates when they intend to buy a green product. As the results show, green perceived value is key to generating green satisfaction and, to a slightly lesser extent, green trust. It should be noted that these results are consistent with previous studies by Chen et al. [15], McDougall et al. [34] and Lam et al. [38]. It should also be noted that the fundamental role played by green satisfaction within the proposed model has also been confirmed. In this sense, the results have shown that green satisfaction is decisive for the generation of green trust, green WOM and green purchase intention; thus, it could be concluded that green satisfaction is the key variable in the whole evaluation process for a consumer of green products. It should be noted that these findings are also consistent with those presented in previous studies. For example, in the case of the influence of green satisfaction on green trust, this relationship had been proven by [9], whereas in the case of the influence of green satisfaction on green WOM, it was Wang et al. [16] and Issock Issock et al. [8] who analysed it.

The relationship between green satisfaction and green purchase intention deserves a separate mention. The results have allowed us to confirm, as have previous studies related to the green products sector [12,100,101], that green satisfaction influences green purchase intention, but also, in light of the findings of this study, it has become clear that green satisfaction is the most important variable for consumers of green products when they assess buying such products. It should also be noted that the results corroborated the findings of Chen et al. [10] and Lam et al. [38], who had confirmed the influence of green trust on green purchase intention, although it is worth clarifying that, as can be seen from the results of this research, green trust is less decisive than green satisfaction for the generation of green purchase intention.

From an application point of view, this research’s findings also contribute to the knowledge about companies producing and marketing green products, since it is known that increasing green purchase intention is critical for generating higher revenues for companies [17,38]. As explained in the previous paragraphs, green purchase intention is produced through green satisfaction and, to a lesser extent, through green trust. This implies that for the organisations involved in the sector, the generation of green satisfaction is fundamental, since without this variable, the generation of green WOM, green trust and above all, green purchase intention, is very complicated. Likewise, the results show companies that the starting point of the whole purchase intention process is when the value of the green product is perceived. In other words, if a product does not generate value for the consumer, it is very unlikely to obtain green trust or green satisfaction. This is why organisations associated with the marketing of green products need to strengthen their product development strategies by incorporating attributes relevant to consumers of green products that, at the same time, are useful for creating a relevant brand positioning.

Finally, although green WOM was not found to be an important variable in itself for generating green purchase intention, this does not mean that companies that produce or sell green products should ignore this variable. As reflected in the results, green satisfaction and green trust have the capacity to generate green WOM, and it is likely to influence other variables that have not been considered in this study. In this sense, taking into account that green WOM is undoubtedly one of the most important marketing variables today [102], and considering that green WOM is conditioned by green satisfaction and green trust, it is worthwhile for companies to focus on its generation since the economic cost of its development may be limited, whereas the benefits generated by green WOM for green corporations may be significant.

5. Limitations and Future Research

This study has a number of limitations which could be addressed in future research. Firstly, from the theoretical point of view, it is worth mentioning that the data collection was carried out only in Peru, which could limit the extrapolation of the findings to other realities. Secondly, from the practical point of view, the development of the study focused on analysing variables within the context of the consumption of green food products such as dairy products, oils and vinegars, snacks, and health drinks, among others. In this sense, extending the research to other categories of green products or services is suggested, in order to test whether the relationships studied can be applied to any green context. In addition, such future research could corroborate whether green WOM is related differently to green purchase intention depending on the category of green products studied. It is also suggested that other variables associated with green marketing may be related to green WOM. Among the variables that could be incorporated are green brand equity, green perceived benefits or customer engagement [102].