1. Introduction
The buying process is one of the main focuses of research in marketing, as it is of great interest to businesses, governments, and scientists. It is a dynamic, complex, and specific process that depends on multiple factors. One of the current social trends is the pursuit of a sustainable world [1]. This is something that has a direct impact on human consumption, and instigates questions for both companies and individuals about the direct and indirect effects of the production generated by the demand for goods and services [2].
As a consequence, research into green marketing has gained relevance in the past decade [3]. It encompasses various topics including ecologism, sustainability, pollution, and social impact. One interesting issue is the study of the purchasing process for products that are called “green”, meaning that they meet green criteria, whether through their raw materials, their manufacturing process, or their distribution process [4]. Consequently, marketing research has analysed the process of green marketing to understand precisely which factors lead a person to prefer or demand a green product.
Green consumption is related to ecological attitude, which is guided by a care for the environment and a wish to make the necessary effort to repair the environmental damage that has occurred [5]. According to various studies, ecological attitude is influenced by emotions such as fear, anger, and restlessness stimulated by an awareness of environmental issues, as well as other core values, the willingness to take action to address environmental problems, and ideas about the boundaries of personal responsibility for the benefit of the environment [6].
A positive ecological attitude leads to the individual being interested in seeking and acquiring knowledge and information about ecological products and events, and certainly in participating in activities that provide protection to the environment. Such an individual can take preventive and protective actions to protect nature and address environmental problems, and integrate this behaviour into their everyday life [7].
The new consumer trends show that consumers are becoming increasingly demanding of brands in relation to their impact on the environment and global sustainability. Companies that focus on offering green products have high possibilities of growth in the market, but green products present problems such as simple eco-labelling, falsehood in information, and poor manufacturing and marketing practices [8]. Even though brands are becoming more involved with the Sustainable Development Goals (SDGs), recent studies indicate that just over 60% of them link some of their involvement to a false belief in sustainability, known as “greenwashing” [8]. This leads to consumers feeling confused about the actual responsibility of brands towards the SDGs [9].
Numerous studies have scrutinized green products, analysing various elements such as health concerns, green lifestyle, environmental protection, social norms, and beliefs, and proposing that these play a significant role in the purchase of green products [10]. However, there are few studies that integrate the majority of the variables that have so far been tested.
This research seeks specific answers to the following question: What are the factors that influence the purchase of green products? To find these answers, the following general objectives are proposed:
To determine, based on previous empirical studies, the essential variables that the affect purchasing behaviour for green products.
To examine the cause-and-effect relationships between the variables that drive the purchasing behaviour for green products.
This study is explanatory in nature, as its objective is to specify the important characteristics of a particular phenomenon, and, in turn, to associate the variables with a predictable pattern for a population in order to explain why this phenomenon occurs [11]. Therefore, first, hypotheses will be proposed based on previous empirical studies found from a structured literature review. Subsequently, an empirical model of the cause–effect hypothesis relationships will be formed, and then a measurement scale will be adapted using a quantitative approach that allows the results to be generalized, gives control over the phenomena, and provides an analysis based on counts and magnitudes through psychographic scales that allow for complex phenomena to be measured [12]. For the data analysis, the method of structural equations will be used; this is recommended for analysing causal relationships between variables and thus verifying the relationships in a model. An analysis of the reliability and effectiveness of the measurement model and of the cause–effect relationships between the independent variables and the dependent ones will be carried out to validate the hypotheses [13], with the purpose of generating results and conclusions.
2. Framework and Hypotheses
A thorough literature review was conducted with the aim of constructing a comprehensive model for the variables explaining green buying behaviour. For this purpose, a search equation was formulated in the primary scientific databases, Scopus and Web of Science, containing the keywords “green”, “consumption”, and “attitude”. Subsequently, four filters were applied to the results, as detailed in Table 1.
The hypotheses and the empirical model to be analysed are presented below, and the results of the data collection and statistical analysis are then reported.
The literature review enables us to conclude that, in the first place, the classical theories of behaviour have been the starting point for the analysis of ecological purchasing behaviour, with several studies having utilized the theory of reasoned action [14] or the theory of planned behaviour [15,16]. The latter best predicts human behaviour by demonstrating that an individual acts based on the result of rational choice triggered by intention, under the influence of attitude or an evaluation of previous behaviour, the subjective norms that generate social influence from the environment, and perceived behavioural control, which refers to the individual’s ability to perform the behaviour. Other theories, such as the theory of consumer values and the theory of innovation adoption, have been integrated to explain the purchase of green products in a more complex manner [17].
The theory of planned behaviour is the most popular theory for the central model of analysis [2,18,19,20,21,22,23,24,25]. Studies applying this theory show that the purchase of green products is driven by the individual’s ecological attitude [2,20], which is similar to perceived behavioural control, and they add other important factors such as environmental ethical awareness and subjective norms related to the new environmental social consciousness. This is reinforced by the analysis of other behavioural theories such as the theory of organismic integration and the value–belief–norm theory [26], which demonstrates that the influence of peers, the perception of environmental responsibility, and matters related to the environment, translated into self-identity or green attitude, influence the purchase of green products [22,27].
Personality traits such as altruism and collectivism influence an individual in the purchase or consumption of green products and services [28]. Decision-making is also linked, in other studies, to the theory of reasoned behaviour, which can also explain the purchase of green products [29,30]. Religion even comes to influence care for the environment through its values and, consequently, influences the intention to purchase green products [31].
A personality profile oriented towards a collectivist personality is associated with a negative attitude towards non-green product consumption.
An altruistic personality profile is associated with a negative attitude towards non-green product consumption.
An altruistic personality profile influences environmental awareness.
The post-pandemic (COVID-19) context has also been assessed, with analyses of social concerns regarding future pandemics and their impact on consumption [27,32]. As regards the purchase of green products, the results have shown that, besides individual variables such as ecological attitude, new concerns about health also increase the intention to buy green products [21,32,33].
Environmental commitment is associated with a negative attitude towards non-green product consumption.
Environmental commitment is associated with a positive attitude towards consuming green products.
There has been perceived social pressure, and a newly found perceived autonomy in the context of a new life, due to COVID-19 [32]. Some studies have shown that an awareness of care for the environment among communities is significantly influencing the choice of green brands [22,23]. This includes the entire purchase decision process, information searches, and purchase intention [21,23,26].
The subjective norm for consuming green products influences the green product search time.
The subjective norm for consuming green products influences the intention to purchase green products.
Environmental ethics and beliefs significantly affect the intention to use environmentally friendly products [32,33]. In this line of research, it has also been found that information about products that are not green versus those that are green generates a preference in the consumer for green ones [34].
A negative attitude towards polluting products is associated with a positive attitude towards consuming green products.
A negative attitude towards polluting products influences the intention to purchase green products.
Previous studies have shown that prior attitudes towards green consumption lead to the purchase of green products [2,26,32,33,35].
The attitude towards consuming a green product influences the perceived behaviour control in relation to the purchase of green products.
On the other hand, consumers prefer to search for products with high quality standards, including products that do not pollute and that are environmentally friendly, even if this means paying a higher price [23]. The consumer of a green product will tend to seek detailed information about the product’s characteristics, place of origin, ingredients, environmental quality seals, and social or other green accreditations, will compare products, and will extensively research the green impact of these products [36].
Green product search time is associated with a positive attitude towards consuming green products.
Green product search time influences the intention to purchase green products.
Various studies that develop the theory of planned behaviour have validated the effect of perceived behaviour control on the intention to purchase and the actual purchase of green products [2,18,19,20,21,22,23,24,25]:
Perceived behaviour control influences the intention to purchase green products.
Perceived behaviour control influences the purchase of green products.
Some studies have found that perceived greenwashing in relation to products negatively affects the intention to purchase green products [9]:
The perception of greenwashing negatively influences the intention to purchase green products.
The perception of greenwashing negatively influences the purchase of green products.
To complete the model by taking a classic relationship from the behavioural purchase models, the hypothesis that purchase intention for green products is a predictor of their purchase will be tested [37]:
Intention to purchase green products influences the purchase of green products.
All the hypotheses are summarised in Figure 1.
Finally, some studies have examined whether there are differences between cultures regarding green purchasing and have uncovered discrepancies and variations but have been unable to make a conclusive determination of the impact of a country’s culture [38]. However, some findings indicate cultural differences [39]. On the other hand, socio-economic status has an effect on green consumption, with the middle and upper classes showing a greater intention to purchase than the lower classes [40].
With regard to age, it has been found that there are differences among age groups in terms of various factors relating to green consumption, with younger individuals being the most inclined to purchase these products [23,41]. Regarding differences between men and women in the consumption of green products, it has been found that women are more inclined to choose or to be influenced by green products and brands [42].
Since the moderating effect of demographic groups has not yet been thoroughly explored, no hypotheses are raised about the effect of these on the purchase of green products, but control analyses are applied which are presented in the Section 4.
3. Materials and Methods
3.1. Sample and Data Collection
In the fieldwork, the non-probabilistic quota sampling method was chosen to establish the sample, as the partial least squares methodology allows for a small sample [43]. However, the acceptable number of individuals to be reached was set at a minimum of one thousand people to ensure robustness in the results. The target population was university students in Spain and Colombia, and the questionnaire was disseminated digitally. The data collection was confidential, no personal information about the respondents was gathered, and participation was voluntary, all in accordance with established ethical standards. A total of 1219 surveys were collected from university students in Spain and Colombia, of whom 60.6% were females and 38.6% were males; this difference is possibly due to the questionnaire not asking about a particular green product or service. Similarly, 76% were young people aged 18 to 34, while the remaining 24% were older, and no differences were found within these age groups. It was found that 72% of the participants were single (Table 2). Once the multigroup and moderation tests had been carried out, no differences or effects moderated by any of the demographic variables of the sample were found.
3.2. Measures
The model was tested using partial least squares (PLS), a specific form of structural equation modelling (SEM). PLS relies on the variance in the dependent variables and aims to forecast unobserved variables through input data from observations. Its primary focus is on maximising the explained variance of the components, which are the latent variables used in this methodology [13,44].
The choice of PLS was made for various reasons. First, the study’s objective was to predict and elucidate the model’s dependent variables, rather than confirming the overall validity of the model using global model fit indices and global model verification. In this context, the study concentrated on explaining the dependent variables and enhancing their explained variance through the coefficient of determination, as well as the direction, magnitude, and significance of the path coefficients. It also aimed to establish precise predictions for the dependent variables [45].
Second, despite the sample’s substantial size, the model encompassed a significant number of latent and manifest variables. This, in turn, led to complexity in the model as it featured numerous direct and indirect pathways. In this regard, it has been demonstrated that PLS-SEM significantly mitigates the impact of measurement errors, thus enhancing the reliability of the construct scores, especially in complex models where multiple mediators are involved [46,47,48].
The questionnaire included 33 items that evaluated the following: altruistic personality and collectivist personality [4]; purchase of green products; negative attitude towards non-green products [22]; perception of greenwashing [33]; product search time; environmental commitment [20]; attitude towards green products [22]; intention to purchase green products; perceived behaviour control; and subjective norms [17] (Appendix A). To ensure accuracy in the translations, all measurement items were first rendered in Spanish and then back-translated into English. A 7-point Likert scale, ranging from 1 (strongly disagree) to 7 (strongly agree), was used to assess all items. The scales employed in this research were adapted from the prior literature and had demonstrated reliability and validity.
4. Results
4.1. Reliability and Validity of the Measurement Tool
The measurement model underwent an evaluation that involved the analysis of latent variable consistency, average variance extracted, and discriminant validity (Table 3). To assess the internal consistency of the constructs, the individual and composite reliability of these constructs were scrutinised. The results from the measurement model assessment are presented in Table 3. Following this, the model’s convergent validity was evaluated using the average variance extracted (AVE) metric. It is important to note that an AVE value above 0.5 is required to confirm the presence of this form of validity [13]. As depicted in Table 3, the latent variables exhibit both individual and composite reliability, as well as convergent validity. Discriminant validity among the constructs was established through two widely recognised methods: the well-established Fornell and Larcker criterion (Table 4) and the more recent and precise heterotrait–monotrait (HTMT) ratios criterion (Table 5) [47,48]. For conceptually similar constructs, HTMT values exceeding 0.9 indicate the presence of discriminant validity, whereas HTMT values below 0.85 are indicative of discriminant validity for conceptually dissimilar constructs [47,48]. The Fornell–Larcker criterion is satisfied when the square root of the AVE value for each construct exceeds the estimated correlation between each pair of constructs.
In addition, the collinearity among the exogenous factors related to a specific endogenous factor was assessed. It has been pointed out that interdependence issues could arise when VIF values surpass a threshold of 5, or 3.3 for a more stringent evaluation [43]. In the results of this study, all the VIF values remained below 2.883 (Table 3), clearly suggesting that collinearity is not an issue within the model.
4.2. Assessment of the Structural Model
To assess the importance of the structural parameters, a bootstrapping procedure was implemented at a significance level of 5%, utilising 10,000 subsamples [12,45]. As the hypotheses were formulated in a specific direction, a one-tailed test was conducted. Lastly, all the R2 values exceeded the 10% threshold, even for their adjusted values (Table 6), indicating that the model possesses sufficient capability to account for the dependent variables. However, this study is exploratory and does not aim to validate the predictability of this model. Advanced tests of predictive relevance and model fit were therefore not performed. The hypotheses were statistically tested with a reliability level of 95% and a t-Student probability of 5% confidence error (Table 7) (Figure 2).
5. Discussion
Hypothesis H1 was supported (β = 0.335 *), which reinforces previous studies that found that a collectivist personality is associated with a negative attitude towards the consumption of non-green products [19,49]. This result reinforces the personality approach towards green product buyers. Specifically, those with collectivist profiles seek the common good and the planet’s well-being, which is closely related to the new social trends of environmental awareness that are seen in individuals with this personality trait [19,49].
Hypothesis H2a (β = 0.046) was not validated: an altruistic personality profile is not associated with a negative attitude towards the consumption of non-green products. While this result is not what was expected, given that an altruistic person considers the common good and, therefore, the ecosystem, hypothesis H2b (β = 0.410 *) was validated, specifically demonstrating that the altruistic personality profile influences environmental awareness [10,19,22,49].
In accordance with previous findings [27,32], hypothesis H3a (β = 0.313 *) was validated, confirming that environmental commitment is associated with a negative attitude to non-green product consumption, and H3b (β = 0.123 *) was also validated, meaning that environmental commitment is associated with a positive attitude towards consuming green products. This demonstrates that customers with a higher environmental commitment are more likely to choose green products over environmentally harmful ones [27,32].
Hypothesis H4a was also confirmed (β = 0.462 *): the subjective norm for consuming a green product influences the green product search time. Hypothesis H4b, which posits that the subjective norm for consuming a green product influences the intention to purchase green products, was also validated (β = 0.317). These validations support previous studies [21,23,26] on how social and cultural pressure is growing regarding the search for and purchase of green products.
With regard to hypothesis H5a (β = 0.162 *), it was shown that a negative attitude towards polluting products is associated with a positive attitude towards consuming green products, and H5b (β = 0.153 *) was also validated—a negative attitude towards polluting products influences the intention to purchase green products [34]. This result is of great importance, given that consumers are comparing products, discarding those they consider harmful and polluting.
Hypothesis H6 (β = 0.343 *) was validated, indicating that the attitude towards consuming a green product influences the perceived behaviour control in relation to purchasing green products, suggesting that a more positive attitude towards green products leads to greater customer mastery of the purchasing process [2,26,32,33,35].
Hypothesis H7a (β = 0.296 *), which proposed that green product search time is associated with a positive attitude towards consuming green products, was supported. So too was hypothesis H7b (β = 0.398 *), which suggested that green product search time influences the intention to purchase green products. This result demonstrates the current trend of exhaustively evaluating product information, especially regarding its manufacturing, production, and environmental impact [8].
The two hypotheses about perceived behavioural control were both validated, confirming that, the more experience individuals have with respect to green products, the more positive their attitude will be and the more purchases they will make [2,26,32,33,35]. H8a (β = 0.154 *) proposed that perceived behaviour control influences the intention to purchase green products, and H8b (β = 0.290 *) that perceived behaviour control influences the purchase of green products, reinforcing the idea that the individual is the one who has control in decision-making and in the purchase of green products [2,18,19,20,21,22,23,24,25].
Hypothesis H9a (β = −0.063 *), which posits that the perception of greenwashing negatively influences the intention to purchase green products, and H9b (β = −0.085 *), which posits that the perception of greenwashing negatively influences the purchase of green products, were validated with respect to the negative attitude towards green products when the customer perceives its green attributes to be false [9,44].
Finally, hypothesis H10 (β = 0.445 *), according to which the intention to purchase green products influences the purchase of green products, was supported, demonstrating that attitude is a great predictor of the purchase of green products [2,26,32,33,35].
6. Conclusions
The objectives of this study were as follows: (1) to determine, based on previous empirical studies, the essential variables that affect the purchasing behaviour for green products, and (2) to examine the cause-and-effect relationships between the variables that drive the purchasing behaviour for green products.
The results of this study enabled the exploration of an empirical model that integrates different theories that—until now—have been examined separately, to understand the consumption of products referred to as “green”.
The contributions of this study in the research field of green product consumption first reinforce the value–belief–norm theory regarding the way in which both consumer personality traits, such as environmental consciousness, altruistic personality, and collectivist tendencies, and a positive attitude towards green products, linked to social influence, influence the purchase of green products. With regard to the search for information about green products, our study confirms that consumers are concerned with seeking detailed information about green products in terms of ingredients, production, packaging, and the environmental impact of product use and disposal, and this information influences whether or not they are motivated to make a purchase.
The findings also confirm that the theory of planned behaviour is applicable to the process of purchasing green products, as this study shows that, in addition to the individual and environmental factors, perceived behaviour control is a driver of green product purchases.
Regarding cultural differences, gender, and other demographic characteristics, no differences were observed in this study, demonstrating that it is not possible to conclude that there are significant distinctions, and also that the purchase of green products is possibly a global trend.
Connected to the above, this study found that, if a consumer believes that a green product exhibits greenwashing, they will be discouraged from making a purchase. This finding underscores the importance for brands to properly manage their green products, always striving to meet green standards throughout the value chain.
This study has important practical and managerial implications for producers and traders. Selling a green product offers a range of significant benefits for a brand. First, this study has revealed that adopting a green approach can solidify the brand’s leading position in its market. Additionally, the brand can leverage eco-conscious values and standards to attract consumers who value environmental awareness. Perceived behaviour control plays a pivotal role for green product buyers, providing companies with an opportunity to engage in information campaigns and co-creation in green product innovation.
Last but not least, the research highlights that consumers are sensitive to the authenticity of green products. If they perceive that a producer is engaging in “greenwashing”, that is, promoting its products as more environmentally friendly than they truly are, this can deter them from making a purchase. This underscores the importance of brands properly managing their green products and adhering to environmental standards throughout the value chain. In summary, adopting and promoting green products can not only enhance a brand’s image but also attract a diverse group of environmentally conscious consumers concerned with authenticity, potentially leading to increased sales and customer loyalty.
The key limitation of this research is that, despite the adoption of various variables from the literature review, not all the variables were included in the model. For instance, some personality variables were omitted. Second, this study considered green purchasing in general, rather than focusing on a specific green product or brand. Therefore, it is suggested that the model should be tested for a specific product to verify whether the same results are found as in this study.
Future studies should investigate the green product field, as this is expected to continue evolving rapidly. As a result, it is essential to keep studying the behavioural changes in consumers and in the products themselves that are labelled as “green”. New variables, such as digital ones, should be added to these models [50,51]. Finally, the mediating effect of the variables that have the most weight within the behavioural purchase models that are adjusted to green products must be analysed in detail [52,53,54,55].
Conceptualisation, E.J.D.O., J.A.S.-T., F.-J.A.-C., A.A.-I. and S.-M.P.-L.; methodology, E.J.D.O., J.A.S.-T., F.-J.A.-C., A.A.-I. and J.G.-L.F.; software, E.J.D.O. and J.G.-L.F.; validation, E.J.D.O., J.A.S.-T., F.-J.A.-C., A.A.-I. and S.-M.P.-L.; formal analysis, J.A.S.-T., F.-J.A.-C. and A.A.-I.; investigation, E.J.D.O., J.A.S.-T., F.-J.A.-C., A.A.-I., J.G.-L.F., S.-M.P.-L. and J.-P.A.-Z.; resources, E.J.D.O., J.A.S.-T., F.-J.A.-C., A.A.-I. and S.-M.P.-L.; data curation, J.A.S.-T., S.-M.P.-L. and J.-P.A.-Z.; writing—original draft preparation, J.A.S.-T., F.-J.A.-C., A.A.-I., S.-M.P.-L. and J.-P.A.-Z.; writing—review and editing, E.J.D.O., J.A.S.-T., F.-J.A.-C., A.A.-I., J.G.-L.F., S.-M.P.-L. and J.-P.A.-Z.; visualisation, J.A.S.-T., F.-J.A.-C., A.A.-I., S.-M.P.-L. and J.-P.A.-Z.; supervision, E.J.D.O., J.A.S.-T., F.-J.A.-C. and A.A.-I.; project administration, E.J.D.O., J.A.S.-T., F.-J.A.-C. and A.A.-I. All authors have read and agreed to the published version of the manuscript.
Not applicable.
Informed consent was obtained from all subjects involved in the study.
Data is unavailable due to privacy or ethical restrictions.
The authors declare no conflict of interest.
Footnotes
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Database search filters.
| Filter | Total Documents |
|---|---|
| Publication date: 1982–2022 | 626 |
| Publication date: 2013–2022 | 523 |
| Areas of knowledge: psychology, economics, and sociology | 189 |
| Buying behaviour topic | 32 |
Sample.
| Gender | Age | ||
| Female | 60.6% | 18–34 years | 76% |
| Male | 38.6% | 35 years and above | 24% |
| Other | 0.9% | ||
| Country | Marital status | ||
| Spain | 46% | Single | 72% |
| Colombia | 54% | Married–Free union | 25% |
| Divorced | 1% | ||
| Widowed | 1% | ||
| Religious | 1% |
Test reliability and validity of the measurement tool.
| Item | Loads * | t-Statistic | p Values | VIF Values | Construct | Cronbach’s Alpha | Composite Reliability | Composite Reliability | Average Variance Extracted |
|---|---|---|---|---|---|---|---|---|---|
| AV1 | 0.817 | 21.424 | 0.000 | 1.372 | Altruistic personality | 0.733 | 0.811 | 0.837 | 0.635 |
| AV2 | 0.844 | 23.095 | 0.000 | 1.676 | |||||
| AV3 | 0.823 | 7.773 | 0.000 | 1.458 | |||||
| BH1 | 0.866 | 46.324 | 0.000 | 2.347 | Purchase of green products | 0.876 | 0.879 | 0.924 | 0.802 |
| BH2 | 0.843 | 57.627 | 0.000 | 2.883 | |||||
| BH3 | 0.866 | 50.528 | 0.000 | 2.211 | |||||
| CV1 | 0.885 | 34.919 | 0.000 | 2.048 | Collectivist personality | 0.828 | 0.836 | 0.897 | 0.744 |
| CV2 | 0.828 | 26.352 | 0.000 | 1.757 | |||||
| CV3 | 0.872 | 32.921 | 0.000 | 1.922 | |||||
| EIA1 | 0.860 | 34.355 | 0.000 | 2.121 | Negative attitude towards non-green products | 0.846 | 0.847 | 0.907 | 0.765 |
| EIA2 | 0.910 | 44.204 | 0.000 | 2.633 | |||||
| EIA3 | 0.853 | 32.660 | 0.000 | 1.831 | |||||
| GW1 | 0.850 | 8.639 | 0.000 | 1.575 | Perception of greenwashing | 0.814 | 0.826 | 0.889 | 0.727 |
| GW2 | 0.854 | 8.372 | 0.000 | 2.058 | |||||
| GW3 | 0.854 | 9.041 | 0.000 | 1.972 | |||||
| IA1 | 0.822 | 38.726 | 0.000 | 1.260 | Product search time | 0.825 | 0.839 | 0.841 | 0.726 |
| IA2 | 0.881 | 43.218 | 0.000 | 1.260 | |||||
| IA3 | 0.838 | 33.702 | 0.000 | 2.567 | |||||
| INT1 | 0.867 | 47.748 | 0.000 | 2.090 | Intention to purchase green products | 0.869 | 0.873 | 0.920 | 0.793 |
| INT2 | 0.901 | 52.466 | 0.000 | 2.404 | |||||
| INT3 | 0.903 | 57.175 | 0.000 | 2.462 | |||||
| OK1 | 0.905 | 58.042 | 0.000 | 1.642 | Environmental commitment | 0.780 | 0.784 | 0.872 | 0.694 |
| OK2 | 0.871 | 31.440 | 0.000 | 1.568 | |||||
| OK3 | 0.912 | 29.956 | 0.000 | 1.642 | |||||
| PB1 | 0.854 | 34.317 | 0.000 | 2.054 | Attitude towards green products | 0.823 | 0.827 | 0.894 | 0.738 |
| PB2 | 0.843 | 37.908 | 0.000 | 1.608 | |||||
| PB3 | 0.881 | 38.843 | 0.000 | 2.213 | |||||
| PBC1 | 0.850 | 43.739 | 0.000 | 1.662 | Perceived behaviour control | 0.820 | 0.823 | 0.893 | 0.735 |
| PBC2 | 0.867 | 37.608 | 0.000 | 2.014 | |||||
| PBC3 | 0.854 | 40.948 | 0.000 | 1.933 | |||||
| SI1 | 0.867 | 40.278 | 0.000 | 2.061 | Subjective norm | 0.852 | 0.862 | 0.910 | 0.771 |
| SI2 | 0.879 | 36.630 | 0.000 | 2.254 | |||||
| SI3 | 0.887 | 36.858 | 0.000 | 2.006 |
Note: * Significant difference: p-value < 0.05.
Fornell–Larcker criteria.
| Altruistic personality | 0.797 | ||||||||||
| Purchase of green products | 0.296 | 0.895 | |||||||||
| Collectivist personality | 0.571 | 0.289 | 0.862 | ||||||||
| Negative attitude towards non-green products | 0.363 | 0.259 | 0.514 | 0.874 | |||||||
| Perception of greenwashing | 0.117 | 0.136 | 0.029 | 0.102 | 0.853 | ||||||
| Product search time | 0.314 | 0.604 | 0.369 | 0.299 | 0.153 | 0.852 | |||||
| Intention to purchase green products | 0.344 | 0.602 | 0.427 | 0.402 | 0.048 | 0.539 | 0.890 | ||||
| Environmental commitment | 0.410 | 0.250 | 0.614 | 0.556 | 0.078 | 0.316 | 0.399 | 0.833 | |||
| Attitude towards green products | 0.327 | 0.514 | 0.341 | 0.337 | 0.144 | 0.492 | 0.512 | 0.372 | 0.859 | ||
| Perceived behaviour control | 0.415 | 0.532 | 0.538 | 0.506 | 0.101 | 0.567 | 0.525 | 0.515 | 0.539 | 0.857 | |
| Subjective norm | 0.364 | 0.493 | 0.335 | 0.354 | 0.105 | 0.462 | 0.490 | 0.336 | 0.508 | 0.514 | 0.806 |
Heterotrait–monotrait ratio (HTMT).
| Altruistic personality | - | |||||||||
| Purchase of green products | 0.365 | |||||||||
| Collectivist personality | 0.691 | 0.340 | ||||||||
| Negative attitude towards non-green products | 0.411 | 0.300 | 0.608 | |||||||
| Perception of greenwashing | 0.182 | 0.159 | 0.063 | 0.127 | ||||||
| Product search time | 0.443 | 0.726 | 0.499 | 0.395 | 0.219 | |||||
| Intention to purchase green products | 0.395 | 0.685 | 0.505 | 0.471 | 0.058 | 0.719 | ||||
| Environmental commitment | 0.490 | 0.305 | 0.759 | 0.680 | 0.105 | 0.443 | 0.486 | |||
| Attitude towards green products | 0.405 | 0.606 | 0.407 | 0.394 | 0.178 | 0.684 | 0.600 | 0.458 | ||
| Perceived behaviour control | 0.502 | 0.624 | 0.653 | 0.607 | 0.125 | 0.786 | 0.621 | 0.647 | 0.651 | |
| Subjective norm | 0.450 | 0.567 | 0.396 | 0.414 | 0.127 | 0.624 | 0.564 | 0.409 | 0.601 | 0.609 |
| Construct | | |
|---|---|---|
| Purchase of green products | 0.434 | 0.432 |
| Negative attitude towards non-green products | 0.383 | 0.381 |
| Perception of greenwashing | 0.035 | 0.034 |
| Product search time | 0.214 | 0.213 |
| Intention to purchase green products | 0.424 | 0.422 |
| Attitude towards green products | 0.364 | 0.361 |
| Perceived behaviour control | 0.411 | 0.410 |
| Subjective norm | 0.113 | 0.112 |
Model test.
| Hypothesis | Validity | Original Sample (β) | T-Statistic * | p Values |
|---|---|---|---|---|
| H1 | Supported | 0.191 | 5.261 | 0.000 |
| H2a | Not supported | 0.046 | 1.522 | 0.128 |
| H2b | Supported | 0.410 | 15.113 | 0.000 |
| H3a | Supported | 0.313 | 9.330 | 0.000 |
| H3b | Supported | 0.123 | 4.095 | 0.000 |
| H4a | Supported | 0.462 | 16.908 | 0.000 |
| H4b | Supported | 0.317 | 10.549 | 0.000 |
| H5a | Supported | 0.162 | 5.321 | 0.000 |
| H5b | supported | 0.153 | 1.995 | 0.003 |
| H6 | Supported | 0.343 | 11.261 | 0.000 |
| H7a | Supported | 0.296 | 8.851 | 0.000 |
| H7b | Supported | 0.398 | 13.819 | 0.000 |
| H8a | Supported | 0.154 | 3.705 | 0.000 |
| H8b | Supported | 0.290 | 9.406 | 0.000 |
| H9a | Supported | −0.063 | 3.135 | 0.002 |
| H9b | Supported | −0.085 | 3.877 | 0.000 |
| H10 | Supported | 0.445 | 15.008 | 0.000 |
Note: * Significant difference: p-value < 0.05.
Appendix A. Questionnaire
| Item | Construct |
| AV1. I enjoy assisting strangers when they ask for help. | Altruistic personality [ |
| AV2. I enjoy making charitable donations. | |
| AV3. I enjoy making monetary donations to strangers in need. | |
| BH1. In the past month, I’ve purchased several “green” products/services. | Purchase of green products [ |
| BH2. I regularly purchase “green” products/services. | |
| BH3. On my last trip to the supermarket, I opted for ‘green’ products/services over non-green traditional brands. | |
| CV1. I enjoy working diligently towards achieving group objectives. | Collectivist personality [ |
| CV2. I enjoy helping others regardless of the time devoted to it. | |
| CV3. I like to maintain very good relationships with others. | |
| EIA1. When I become aware of the potential environmental harm caused by a product or service, I refrain from purchasing it. | Negative attitude towards non-green products [ |
| EIA2. I feel bad knowing about the animal, plant, and environmental harm caused by the manufacture of products or services. | |
| EIA3. I’m trying to persuade my friends and family not to purchase products or services that have a negative impact on the environment and the planet. | |
| GW1. I definitely think that green brands are only green on their labels. | Perception of greenwashing [ |
| GW2. In general, green brands tend to exaggerate the information about their manufacturing processes and the final product. | |
| GW3. Most green brands in some way deceive their consumers. | |
| IA1. I spend time researching information about products and brands before making a purchase. | Product search time [ |
| IA2. I’d like to have a great deal of time to research information about products and brands before making a purchase. | |
| IA3. I would like to have a great deal of time to research information about products and brands before making a purchase. | |
| INT1. I’m considering purchasing products that are less harmful to the environment. | Intention to purchase green products |
| INT2. I’m considering purchasing brands that I identify as eco-friendly or green. | |
| INT3. In my future purchases of a product, I will try to seek the most “green” version (non-polluting, ecological, sustainable, recyclable, etc.). | |
| OK1. I feel a personal obligation to prevent environmental harm. | Environmental commitment [ |
| OK2. I feel a moral obligation to use products that do not pollute. | |
| OK3. I feel a personal obligation to take care of the environment and the planet in everything I do daily. | |
| PB1. Green products/services have better quality than the rest. | Attitude towards green products [ |
| PB2. I believe that green products/services are healthier than others. | |
| PB3. I think that green products/services have higher quality than the rest. | |
| PBC1. I try to gather good information about the products/services to have control over my choice during the purchasing process. | Perceived behaviour control [ |
| PBC2. I try to maintain complete decision control throughout the purchasing process. | |
| PBC3. It’s important to me to have my own influence over the outcome of my purchasing choice. | |
| SI1. People who are significant in my life, such as my family and friends, advise me to purchase ‘green’ products/services. | Subjective norm [ |
| SI2. Other close acquaintances I know (such as colleagues or bosses) recommend that I purchase ‘green’ products/services. | |
| SI3. When my close friends recommend that I purchase “green” products/services, I do so. |
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Details
; Sánchez-Torres, Javier A 2
; Francisco-Javier Arroyo-Cañada 3
; Argila-Irurita, Ana 3 ; Gil-La Fuente, Jaime 3 ; Palacio-López, Sandra-Milena 2
; Juan-Pablo Arrubla-Zapata 2 1 School of Administration and Accounting, Universidad Nacional de Colombia, Bogotá 111321, Colombia;
2 Department of Marketing, University of Medellín, Medellín 050026, Colombia;
3 School of Business, University of Barcelona, 08001 Barcelona, Spain;