Abstract
Purpose
This study aims to examine the effects of green marketing tools on tourists’ behavioural intention to buy green products by measuring individuals’ subjective norms, attitudes and perceived behavioural control.
Design/methodology/approach
A total of 421 international tourists from several tourist attractions in Malaysia, selected through convenience sampling, participated in a survey.
Findings
The analysis results using partial least squares structural equation modelling suggest that behavioural intention of international tourists is firmly influenced by attitude, perceived behavioural control, subjective norms and green marketing tools. However, the subjective norm does not work as a mediator.
Practical implications
The relationships established in this study provide insight into hoteliers’ knowledge for further implementation of green marketing strategies (eco-label, eco-brand, environmental advertising), which can enhance green attitudes and behavioural intention of purchasing green products in the hospitality industry.
Originality/value
This study expands the theory of planned behaviour by including green marketing tools to measure international tourists’ green buying tendency in Malaysia.
Keywords
Citation
Patwary, A.K., Mohamed, M., Rabiul, M.K., Mehmood, W., Ashraf, M.U. and Adamu, A.A. (2022), "Green purchasing behaviour of international tourists in Malaysia using green marketing tools: theory of planned behaviour perspective", Nankai Business Review International, Vol. 13 No. 2, pp. 246-265. https://doi.org/10.1108/NBRI-06-2021-0044
Publisher
:Emerald Publishing Limited
Copyright © 2021, Emerald Publishing Limited
1. Introduction
The tourism sector is a vital contributor to the gross domestic product (GDP) of many countries (UNWTO, 2019). Mass tourism production has become a priority for most countries due to lucrative revenues produced by tourist activities (Comerio and Strozzi, 2019). The massive growth of the tourism industry, particularly climate change caused due to the use of non-renewable energy sources, particularly the non-renewable climate, has many adverse effects. It involves the degradation and deterioration of natural resources that cause climate change (Chekima et al., 2016; Handriana and Ambara, 2016).
The tourism industry, specifically the hotel industry in Malaysia, significantly contributes to the national GDP (UNWTO, 2019). The tourism industry of the country is highly dependent on the hotel business. Malaysia has taken some initiatives to develop hotel businesses in line with green practices due to the negative impacts of the hotel and tourism industry on the environment (Afthanorhan et al., 2017; Patwary et al., 2021). Similarly, Heung and Pun (2013) stated that the hotel industry contributes 1% of global greenhouse emissions worldwide. The Malaysian hotel industry consumes a vast amount of water and energy, and produces significant quantities of waste (Habibi, 2017; Yusof et al., 2017). Therefore, understanding tourists’ choices regarding green practices is of importance for further development of the sustainable hotel industry in Malaysia (Muniandy et al., 2019).
Therefore, researchers focus on consumers’ growing attention to environmental issues, which forces hoteliers to implement green practices in their operations. If consumers are willing to assume responsibility and choose green products, environmental issues can be effectively managed if not prevented (Patwary et al., 2020). Several companies have begun implementing green initiatives and using green marketing strategies to understand consumers’ preferences of green products to achieve long-term profits (Yusof et al., 2017). Green marketing is one aspect of the modern economy, and green marketing strategies are mostly applied in developed countries (Hasan et al., 2019).
While exploring green marketing in tourism and hospitality settings, researchers found that few studies considered all the prominent parameters of the theory of planned behaviour (TPB) and indicators of green marketing tools simultaneously. For example, Chin et al. (2018) implemented green marketing tools by underpinning TPB. However, the study ignored fundamental variables concerned with TPB, namely, attitude, subjective norm and perceived behavioural control. Ajzen (1991) pointed out that TPB’s central dependent variable is consumer intention, which indicates a person’s readiness to behave in a certain way. Similarly, Biswas and Roy (2015) measured the green consumption behaviour from the context of perception and value without taking into account consumers’ subjective norm and perceived behavioural control. However, considering the mediating effects of attitude, subjective norm and perceived behavioural control provide a more constructive picture towards particular behaviour (Roy et al., 2017).
Although considerable research has been conducted to examine consumers’ decision-making process, the findings on consumers’ behavioural intention are inconsistent (Yadav and Pathak, 2017). This indicates that the factors influencing the hotel industry’s behavioural intention vary in different contexts. For instance, in developed countries, perceived behavioural control has no significant influence on consumers’ intention to visit restaurants (Stoeva and Alriksson, 2017) or green hotels (Han and Yoon, 2015). In contrast, in developing countries, perceived behavioural control significantly impacts consumers’ behavioural intention for travelling abroad (Song et al., 2017). Earlier studies have attempted to explore the service-related factors, and how they influence the consumers’ decision and behavioural intention in the Asia Pacific region (Gursoy et al., 2019; Varkaris and Neuhofer, 2017).
Recent evidence suggests that the manner in which green marketing tools can shape consumers’ behavioural intentions have not yet been explored, and requires in-depth investigation (Prakash and Pathak, 2017). Previous studies in developing countries mostly focussed on the importance of green movements and the environmental awareness of consumers (Liu et al., 2018; Yang et al., 2019). A number of researchers have reported that factors related to the behavioural intention of the consumers, like the subjective norm, attitude and perceived behavioural control, are still unknown to the Malaysian hospitality industry (Uduji et al., 2020). Regarding theoretical applications in green marketing strategies, very limited studies empirically investigate the theoretical relationships in the Malaysian context, leading to a gap in the literature that needs to be addressed. This limited application of theory in green marketing strategies has led to insufficient explanations from academia and managers while using green marketing strategies. Moreover, previous studies have yet to investigate the effects of green marketing tools on behavioural intention through changing attitudes, perceived behavioural control and subjective norms to enhance green marketing strategy, especially in tourism and hospitality. Therefore, this study intends to address this gap by examining green marketing tools’ role on behavioural intention through attitude, perceived behavioural control and subjective norms.
2. Literature review
2.1 An overview of greening in the tourism industry
Green practices in the tourism and hospitality industry are a new edition that supports environmental and ecologically sustainable growth (Neto and Caldas, 2018). Green tourism is an alternative activity that encourages environmental protection (Handriana and Ambara, 2016; Song and Yu, 2018). Similarly, green marketing is described as creating and promoting goods or services with no adverse environmental consequences (Kilbourne, 1998). Green marketing strategies have proven to be important marketing techniques to improve green purchasing. Past studies show that green marketing tools (e.g. eco-label, eco-brand and environmental) significantly impact customers’ green buying behaviour (Widyastuti and Santoso, 2018). In particular, green marketing practices were developed to ensure the effectiveness of sustainable tourism tools in different industries, such as hoteliers, manufacturers and customers who opt for green procurement (Neto and Caldas, 2018).
Various ideas have been developed in the sequel to introducing the green marketing concept by Henion and Kinnear (1976). Marketing activities should consider environmental problems that ease environmental problems rather than exacerbate them (Rajapaksha and Tilakasiri, 2019). For example, Heath and McKechnie (2019) defined green marketing as “the holistic management process responsible for identifying, anticipating and satisfying the needs of customers and society, profitably and sustainably” (p. 141). Given the advantages of green marketing, many organisations have implemented this strategy to boost profits while reducing pollution. This green marketing strategy is an innovative way to develop a competitive edge and gain success (Sharma et al., 2021).
2.2 Green marketing tools
Although no single marketing tool is suitable for a particular organisation, many scholars have highlighted the following three dimensions of green marketing tools that influence consumers’ green purchasing behaviours: environmental advertisement, eco-label and eco-brand (Rizqiyana and Wahyono, 2020). Similar to earlier research, this study adopts the above three dimensions, making perception easier and increasing consumer awareness about green products. Implementing these green marketing policy tools plays an essential role in altering consumer purchasing behaviour in buying environment-friendly products, mitigating the negative environmental impact of synthetic products.
2.3 Eco-brand
Twedt (1960) defines a brand as:
[…] a name, term, sign, symbol, or design, or the combination of them, intended to identify the goods or services of one seller or group of sellers and to differentiate them from those of a competitor.
This definition of a brand can also be used for the eco brand. Hence, eco-brand is a name, symbol or design of products that indicates its minimal negative impact on the environment. Using eco-brand features on a green product or service help consumers differentiate them from non-green ones (Nekmahmud and Fekete-Farkas, 2020). It is believed that eco-brand is a modern expansion of green advertising instrument created to positively affect customer’s buying behaviour (Ihemezie et al., 2018). The eco-branded products have been economically profitable because of their positive public image, leading to an increase in consumer demand and brand loyalty advancement (Ferreira and Fernandes, 2021).
2.4 Eco-label
Eco-label is one of the underlying tools for green marketing that influences consumers to buy environmentally friendly products. Environmental labels ensure that products adhere to some rules and regulations with its ensure environment-friendly nature. Using eco-label, companies provide intangible information about products, including product quality related to environmental impacts. This enhances their image and creates value in the market (Rihn et al., 2019). The organisation provides a certified logo to the potential customers, while potential customers are encouraged to buy environment-friendly products. Eco-label is sometimes used to inform environmentally favourable information apart from locating and separating products. Advertisers broadly use environmental labels to promote green product characteristics (Chang et al., 2019). Eco-label is necessary to simplify decision-making on eco-friendly products, permitting consumers to gain knowledge of the manufacturing process of the product (Sun et al., 2021).
2.5 Environmental advertisement
Advertisement of environment is also regarded as green commercialising. Accordingly, Banerjee et al. (1995) demonstrated that commercial organisation should ensure apparent or implicit connection among service or a product and the natural environment. The growing interest for green commercials during the previous few decades has significantly raised awareness among the public on environmental issues, leading to expanding demand for products labelled as green (Matthes, 2019). Many organisations have selected environmental commercials by displaying media or printed newspapers as green strategies for attracting consumer interest (Ackerstein and Lemon, 2017; Soutter and Boag, 2019). Usually, green commercials appeal to the environmental preservation interest of the customers (Jermsittiparsert et al., 2019). Green publicity advertises the company based on the environment-friendly features of its products (Yoon et al., 2020). Green commercials include promotional messages that attract the demand and desires of customers (Dangelico and Vocalelli, 2017; Schmuck et al., 2018).
2.6 The theory of planned behaviour
TPB explains and predicts human behaviours in certain contexts (Ajzen, 1991). TPB consists of three basic elements: attitude, subjective norm and perceived behavioural control (Ajzen and Fishbein, 1988).
2.6.1 Attitude.
Attitude refers to a positive or negative belief that reinforces an intention towards a particular behaviour (Ajzen and Fishbein, 1988). The concept of attitude is derived from individual behavioural beliefs and outcome evaluations. Attitude towards the behaviour is based on how one evaluates situations (Ajzen, 1991). For instance, if a person positively evaluates the situation based on personal beliefs, he/she shows a positive attitude towards that particular behaviour and vice versa. Hence, an individual is more likely to show a positive attitude towards using environmental friendly products if he/she believes that using such products preserves the environment for the next generation while satisfying his/her needs. In turn, individual positive attitudes lead to an increase in usage of green marketing products. Several studies confirmed that individuals’ attitude has a positive and significant impact on intention to use the products.
2.6.2 Subjective norm.
Subjective norm describes the perceived social pressure about certain behaviours that can or cannot be performed (Ajzen and Fishbein, 1988). Subjective norms are strongly influenced by those the individual considers important in their life, such as colleagues, family members, friends and superiors (Ajzen, 1991). Subjective norm is a social pressure for an individual to behave in a certain manner. It is believed to be the outcome of normative belief and motivation. Normative behaviour, which decides how an individual behaves in a certain situation, is influenced by motivation. The motivation in such a situation would be to agree with others’ opinions. To adhere to the subjective norm created by social pressure (friends, colleagues, peers and society), an individual must comply with outsiders’ opinions and behave differently (La Barbera and Ajzen, 2020).
2.6.3 Perceived behavioural control.
Ajzen (2002) included perceived behavioural control as an independent variable in the TPB. This inclusion eased the measurement of behavioural intention when individuals perform an action. Perceived behavioural control is used to assess an individual’s ease of achieving a particular behaviour (Fellnhofer, 2017). The buyer should be convinced that resources are available and that the possibilities may facilitate or inhibit behaviour. Arli et al. (2018) suggest that resources and efficiency constitute two components that measure behaviour management, which directly impact behavioural intent and perceived behaviour control (Olya et al., 2019). The green product purchase intention can be used to assess an individual’s ease and is linked to the perceived lack of resources and opportunities for the behaviour (Choi and Johnson, 2019).
2.6.4 Behavioural intention.
Behavioural intention indicates a person’s preparation to conduct an expected behaviour. It is an immediate behavioural antecedent (Ajzen, 2002). The friendlier an attitude or behaviour, the friendlier the subjective value and the higher the realised control of the behaviour. Previous literature highlights that TPB has been used in a large number of environment-friendly goods and services, for instance, energy efficient products (Wang et al., 2018). Green restaurants and green hotels are also green labelled products (Liobikiene et al., 2016; Varah et al., 2021), which verified its toughness and anticipated ability for quantifying environment-friendly buying motive and behaviour. A number of studies have shown that TPB favours (i.e. whole TPB variables – manner, subjective standard and comprehended control of the behaviour – meaningfully affect customers “intention of buying green) customers” motive and conduct intended for environment-friendly goods and services.
Nevertheless, in some incidents, especially considering TPB variables, support exists for the buyers’ motive and attitude (Maichum et al., 2016). This exhibits that subjective standard realised control of the behaviour and attitude could be important in determining the customers’ green buying motive to buy environment-friendly goods.
Based on TPB assumptions and the above discussed literature, the following hypotheses and research framework (see Figure 1) are proposed:
Green marketing tools is positively related to the behavioural intention of international tourists in Malaysia.
Green marketing tools is positively related to the attitude of international tourists in Malaysia.
Green marketing tools is positively related to the perceived behavioural control of international tourists in Malaysia.
Green marketing tools is positively related to the subjective norm of international tourists in Malaysia.
Attitude is positively related to the behavioural intention of international tourists in Malaysia.
Perceived behavioural control is positively related to the behavioural intention of international tourists in Malaysia.
Subjective norm is positively related to the behavioural intention of international tourists in Malaysia.
Attitude mediates the relationship between green marketing tools and behavioural intention of international tourists in Malaysia.
Perceived behavioural control mediates the relationship between green marketing tools and behavioural intention of international tourists in Malaysia.
Subjective norm mediates the relationship between green marketing tools and behavioural intention of international tourists in Malaysia.
3. Research methodology
3.1 Data collection and samples
A convenience sampling technique was used to obtain the primary data. The convenience sampling technique is a non-probability sampling technique, which allows the researcher to reach out to respondents easily. Emerson (2015) stated that convenience sampling is suitable when the phenomena are little known to the audience, and the researchers want to develop new thoughts. Convenience sampling was used to obtain information from the selected population of the study – international tourists – from international tourists’ spots in Malaysia. 600 questionnaires were distributed to the respondents in several tourists’ attractions in Kuala Lumpur, Putrajaya, Langkawi and Penang between December 2019 and March 2020, out of which, 421 questionnaires were analysed. Table 1 shows the demographic distribution of the respondents.
3.2 Measurement
The measurements used in this study were adapted from previous studies. The green marketing tools consist of three dimensions – eco-label, eco-brand and environmental advertisement. To measure these three dimensions, 24 items were adapted from Rahbar and Wahid (2011), of which seven items were used for eco-label, seven for eco-brand and eight for environmental advertisement. To measure the attitude/environmental attitude and behavioural intention of international tourists, five items were adapted from Wu and Chen (2014) and six from Rahbar and Wahid (2011). Five items were adapted from Chan and Lau (2002) to measure subjective norms and six from Kim and Han (2010) to measure perceived behavioural control.
3.3 Demographic profile
No missing data was included for analysis. According to Krejcie and Morgan (1970) and G-power analysis, a sample size of 421 was enough to test the hypotheses. Therefore, any incomplete data considered invalid for testing the hypotheses was not chosen for analysis.
As shown in Table 1, 69.8% of respondents were female, and 30.2% were male. Most of the participants (31.6%) in the survey were from the age group of 30–39 years, followed by 17–20 years (29%) and then 21–29 years (21.9%). In terms of marital status, 56.1% of them were married and 38% were single. As for income, majority of respondents have income below US$1,000 (40.1%), followed by those in the range of US$2,001–3,000 (27.6%) and finally, US$1,001–2,000 (17.3%). As for education, respondents who mentioned primary school as the highest education were 29.7%, followed by master’s degree (27.1%) and secondary school education (17.6%). The different nationalities who participated in the survey belonged to Asia (39.4%), Middle East (37.3%), USA (11.4%), Europe (10.2%) and Africa (1.7%).
3.4 Data analysis
Various tests (normality, missing data) were performed through SPSS. Hypotheses testing were conducted through partial least square equation modelling (PLS-SEM) because PLS-SEM is popular in tourism research, especially for theory testing and predictive analysis (Kumar et al., 2018).
3.5 Missing data, data normality, common method bias and multicollinearity
Missing data were removed because performing analysis with such data could result in erroneous outcomes (Cheah et al., 2018). Hair et al. (2014) suggested checking for data normality as non-normal data results in underestimating the statistical significance of the structural path coefficient estimates. The skewness and kurtosis values were within the acceptable threshold of <2 and <7 (Hair et al., 2014). Thus, the data set was not highly non-normal. Since common method variance (CMV) is an issue in self-report surveys (Podsakoff and Organ, 1986), the study adopted various remedial procedures to lower the CMV effects (Podsakoff et al., 2012).
Statistical remedies were tested to ensure that CMV was not present in the data. Harman single factor test shows that a total of seven factors explained 62.70% and a single factor explained 24.59%, and therefore, no CMV exists in the data (Podsakoff et al., 2012).
According to Hair et al. (2019), all the latent variables have no multicollinearity issues as the Variance Inflation Factors (VIF) values are less than 3.0 and tolerance is greater than 0.2 (see Table 2).
4. Results
Table 3 shows the correlation among demographic factors and study variables, mean scores and standard deviation of the variables.
4.1 Measurement model
The measurement model in PLS-SEM must be evaluated before the actual hypothesis testing (Adamu and Mohamad, 2019; Ali et al., 2018). The measurement model consists of convergent validity and discriminant validity, such as item reliability, internal consistency and cross-loading (Cheah et al., 2018). Similar to Hair et al. (2014) benchmark, 39 items were retained as they were loaded within the range of 0.511 to 0.905. To delete the items, the following recommendation of Hair et al. (2014) was considered. Firstly, unsatisfactory loading for any items below 0.40 were discarded. Secondly, few items were deleted to keep the minimum average variance extracted (AVE) of 0.50 and maintain the minimum composite reliability of 0.70.
Table 4 displays that all items have Cronbach’s alpha more than 0.70, composite reliability above 0.70 and AVE greater than 0.50. Hence, the convergent validity of the latent variables was confirmed (Raza et al., 2020).
Discriminant validity for this study was confirmed through cross-loading and loading for individual items and heterotrait-monotrait (HTMT) ratio. Loading and cross-loading refer to indicator loading for primary constructs greater than the other constructs (Cheah et al., 2018). Table 5 indicates that the HTMT ratio is lower than 0.85. Moreover, loading for the primary construct was higher than the other secondary constructs. Therefore, as per Hair et al. (2019), all the latent variables were different and discriminant validity was confirmed.
4.2 Second-order establishment
Eco-brand (β = 0.590, P < 0.001), eco-label (β = 0.701, P < 0.001) and environmental marketing (β = 0.764, P < 0.001), were explained to represent green marketing. Thus, the second-order establishment was validated (see Table 6).
4.3 Quality of the model
Following Henseler et al. (2016) recommendation, blinding folding was applied to identify the predictive relevance (Q2). The results suggest that Q2 is greater than zero. Thus, the model has predictive power (Henseler et al., 2016). The coefficient of determination (R2) was 30.9% on attitude, 39.6% on behavioural intention, 18.7% on perceived behavioural control and 1.7% on subjective norm. Thus, the model has weak to moderate influence on endogenous variables (Hair et al., 2019).
4.4 Structural model or hypothesis testing
Age, sex, education level, earnings and nationality were controlled in the actual structural model, given their significant impact recorded in previous studies (Moon, 2021).
Bootstrapping results are presented in Table 7 with direct and indirect relationships between exogenous and endogenous variables. However, these control variables were excluded during bootstrapping following Becker’s (2005) suggestions. In Smart-PLS, bootstrapping with 6,000 samples was used following Chin et al.’s (2020) recommendation.
5. Discussion
Drawing on TPB theory, this study investigates the effect of green marketing on tourists’ behavioural intention to visit green hotels in Malaysia’s tourist places. All our hypotheses (except H10) supported the variable character of TPB in determining the behaviour and tendency of customers towards green products (see Table 7). This demonstrates TPB’s ability to determine the tendency and behaviour of the customers regarding buying green products when travelling abroad. The focus is on making conditions conducive to the customers’ green products’ purchasing decision (de Leeuw et al., 2015). The findings of the study highlight the uniqueness in terms of developing the hypotheses and findings. Results suggest that appropriate green marketing strategies are likely to increase green purchase intention and attitude of the consumers. The results are in line with Han and Cudjoe (2020) and Cui et al. (2021), where they found consumers, when concerned about energy and environmental issues, are more prone to engage in energy saving activities. The results also reveal that subjective norms influence the behavioural intention of the consumers, consistent with Cui et al. (2021), as they found that social influential factors lead to purchase motivation. However, the results indicate that subjective norms do not mediate the relationship between green marketing tools and behavioural intention.
5.1 Theoretical contribution
This study contributes to TPB by expanding and aligning the customers’ green buying tendency within the context of a developing country like Malaysia. The findings suggest that green marketing tools significantly influence attitude, perceived behavioural control and the subjective norm of international tourists in Malaysia. Besides, the study establishes a few new relationships: attitude, perceived behavioural control and subjective norms significantly influence the tourists’ behavioural intention; these variables also mediate the relationship between green marketing tools and behavioural intention. With this theoretical significance, this study can assist scholars by providing a more detailed view of the different constructs that may impact the customers’ green buying behaviour. The marketers’ perception and knowledge have also been augmented by the study about the customers’ tendency to purchase green products in the Malaysian context.
These imperative relationships will provide augment hoteliers’ knowledge for further implementation of green marketing strategies (eco-label, eco-brand and environmental advertising), which can drive green attitudes and behavioural intention of purchasing green products in the hospitality industry. Moreover, marketers’ focus on the customers’ attitude is necessary because it remarkably affects the customers’ green buying intention. Customers’ attitude regarding green buying may be increased by raising awareness within the society, which may successively build a friendly image about the green products among people. A person’s attitude can be altered by building a friendly image and creating awareness among people (Vafaei et al., 2019). It is equally important that marketers give information to the customers about how green products will benefit the environment and the customers. Appropriate communication regarding the benefit of green products should be the marketers’ supreme concern because communication is a crucial instrument for accomplishing green/environment-friendly goals (Haro, 2016; Wan et al., 2017). To encapsulate the theoretical contribution, this study was incorporated by bridging the gaps between the role of green marketing strategies and their influence on consumers’ buying intention and related indicators.
5.2 Practical contribution
Notably, the study offers several implications to establish strategies for marketers to promote green products for faster consumption among international tourists of Malaysia. Here, the term “marketers” is used for tour guide, transportation provider, owners of homestay and others who are associated with tourism activities, either directly or indirectly. However, the study’s findings deal with three-dimensional (3D) determinants of green marketing tools:
eco-labels;
eco-brands; and
environmental advertisement that impacts the overall green product purchasing behaviour of international tourists.
Hence, it is necessary for marketers to establish marketing plans related to the 3D green marketing tool constructs.
More importantly, Malaysian society, its corporate sector and the Malaysian Government must enhance tourists’ green consumption while focussing on environmental governance. The study’s findings carry implications for managers who are also marketers to formulate strategies with the perspective of environmental issues of society to promote green purchasing behaviour among international tourists. Furthermore, managers should also formulate strategies related to the green initiatives to develop a sustainability agenda in Malaysia for driving green purchasing behaviour. Likewise, managers should also consider identify the most acceptable green marketing strategy towards satisfying consumer needs and desires. Lastly, firm managers should prioritise the achievement of sustainability of their firms as well as for society. The results of this study can help enhance the green knowledge attitude that may augment purchasing decisions of international tourists in Malaysia.
5.3 Research limitation and future research suggestions
The research has some specific limitations that must be addressed in future research. Firstly, the self-reported data, instead of real behaviour, is used to analyse customers’ behaviour of green buying. The respondents’ own-choice biases may be another limitation of the study because a higher proportion of pro-environmental respondents may have participated in the investigation. However, self-reported data was found to be suitable for gathering information about behaviour and investigating such behaviours that may not be impossible in other circumstances. Future research might compare customer intention and attitude regarding several sections of green products. This may result in the excess representation of this kind of person within the sample that can bias the consequence. Convenience sampling was used in the study to collect data from the visitors to several tourist destinations in Malaysia. Future research may choose the random approach of sampling between populations to find a simplified reporting of customer’s behaviour in the context of green purpose.
Figures
Demographic profile of the respondents
| Factors | Categories | Frequency | (%) |
|---|---|---|---|
| Gender | Male | 127 | 30.2 |
| Female | 294 | 69.8 | |
| Age | 17–20 years old | 122 | 29.0 |
| 21–29 years old | 92 | 21.9 | |
| 30–39 years old | 133 | 31.6 | |
| 40–49 years old | 52 | 12.4 | |
| 50 years old and above | 22 | 5.2 | |
| Marital status | Single | 160 | 38.0 |
| Married | 236 | 56.1 | |
| Divorce/Widow | 25 | 5.9 | |
| Income (Monthly) | Less than US$1,000 | 169 | 40.1 |
| US$1,001–2,000 | 73 | 17.3 | |
| US$2,001–3,000 | 116 | 27.6 | |
| US$3,001–4,000 | 9 | 2.1 | |
| US$4,001–5,000 | 54 | 2.8 | |
| US$5,001 and above | 9 | 2.1 | |
| Education | Primary school | 125 | 29.7 |
| Secondary school | 74 | 17.6 | |
| Bachelor’s degree | 62 | 14.7 | |
| Master’s degree | 114 | 27.1 | |
| Doctoral degree | 46 | 10.9 | |
| Country of origin (Region) | Asia and the Pacific | 166 | 39.4 |
| Middle East | 157 | 37.3 | |
| USA | 48 | 11.4 | |
| Africa | 7 | 1.7 | |
| Europe | 43 | 10.2 | |
| Occupation | Professional/Managerial | 105 | 24.9 |
| Semi-skilled/clerical | 51 | 12.1 | |
| Self-employed | 127 | 30.2 | |
| Unemployed | 32 | 7.6 | |
| Retired | 106 | 25.2 | |
| Total | 421 | 100 |
Collinearity assessment
| Variables | Tolerance | Variance inflation factor (VIF) |
|---|---|---|
| Perceived behavioural control | 0.747 | 1.339 |
| Attitude | 0.574 | 1.741 |
| Eco-brand | 0.899 | 1.112 |
| Eco-label | 0.911 | 1.097 |
| Environmental marketing | 0.513 | 1.949 |
| Subjective norm | 0.976 | 1.025 |
Means (M), standard deviation (SD) and zero-order correlation of the latent variables
| Variables | M | SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Age | 1 | |||||||||||||
| 2 | Sex | 0.052 | 1 | ||||||||||||
| 3 | Education | −0.034 | −0.078 | 1 | |||||||||||
| 4 | Earning | 0.144** | −0.067 | 0.055 | 1 | ||||||||||
| 5 | Nationality | −0.161** | 0.034 | 0.053 | −0.036 | 1 | |||||||||
| 6 | Perceived behavioural control | 5.54 | 0.93 | 0.018 | −0.033 | 0.045 | 0.012 | −0.005 | 1 | ||||||
| 7 | Attitude | 5.21 | 0.964 | 0.035 | −0.024 | 0.071 | 0.040 | 0.033 | 0.355** | 1 | |||||
| 8 | Eco-brand | 4.86 | 1.264 | 0.113* | −0.073 | 0.087 | 0.027 | −0.021 | 0.271** | 0.198** | 1 | ||||
| 9 | Eco-label | 4.56 | 1.243 | −0.018 | −0.017 | 0.018 | 0.044 | −0.010 | 0.130* | 0.237** | 0.157** | 1 | |||
| 10 | Environmental marketing | 5.40 | 0.858 | 0.032 | 0.026 | 0.089 | 0.027 | −0.041 | 0.466** | 0.643** | 0.216** | 0.250** | 1 | ||
| 11 | Behavioural intention | 5.15 | 0.939 | 0.006 | 0.025 | 0.025 | −0.006 | −0.044 | 0.429** | 0.434** | 0.422** | 0.351** | 0.420** | 1 | |
| 12 | Subjective norm | 4.96 | 1.269 | −0.002 | 0.019 | −0.116* | 0.103* | 0.064 | 0.100 | 0.039 | 0.097 | 0.105* | 0.083 | 0.197** | 1 |
n = 421.
= significance level at 0.01 and
= significance level at 0.05 (two-tailed)
Convergent validity, Cronbach’s alpha (α), composite reliability (CR), average variance extracted (AVE) and R2
| Variables | Second-order constructs | Items | Loading | α > 0.70 | CR > 0.70 | AVE > 0.50 | R2 |
|---|---|---|---|---|---|---|---|
| Attitude | ATT1 | 0.786 | 0.841 | 0.887 | 0.611 | 0.309 | |
| ATT2 | 0.785 | ||||||
| ATT3 | 0.765 | ||||||
| ATT4 | 0.788 | ||||||
| ATT5 | 0.784 | ||||||
| Perceived behaviour control | PBC2 | 0.739 | 0.860 | 0.906 | 0.709 | 0.187 | |
| PBC4 | 0.791 | ||||||
| PBC5 | 0.930 | ||||||
| PBC6 | 0.892 | ||||||
| Eco-brand | BR1 | 0.732 | 0.883 | 0.911 | 0.632 | ||
| BR2 | 0.785 | ||||||
| BR3 | 0.837 | ||||||
| BR4 | 0.818 | ||||||
| BR5 | 0.783 | ||||||
| BR6 | 0.811 | ||||||
| Eco-label | ECO1 | 0.719 | 0.903 | 0.926 | 0.649 | ||
| ECO3 | 0.895 | ||||||
| ECO4 | 0.914 | ||||||
| ECO5 | 0.901 | ||||||
| ECO6 | 0.905 | ||||||
| ECO7 | 0.706 | ||||||
| ECO8 | 0.511 | ||||||
| Environment marketing | Environ1 | 0.756 | 0.865 | 0.897 | 0.554 | ||
| Environ2 | 0.752 | ||||||
| Environ3 | 0.750 | ||||||
| Environ4 | 0.730 | ||||||
| Environ5 | 0.769 | ||||||
| Environ6 | 0.770 | ||||||
| Environ7 | 0.677 | ||||||
| Behavioural intention | BINT1 | 0.734 | 0.827 | 0.874 | 0.538 | 0.396 | |
| BINT2 | 0.679 | ||||||
| BINT3 | 0.785 | ||||||
| BINT4 | 0.794 | ||||||
| BINT5 | 0.709 | ||||||
| BINT6 | 0.690 | ||||||
| Subjective norm | SUB2 | 0.728 | 0.836 | 0.890 | 0.670 | 0.017 | |
| SUB3 | 0.860 | ||||||
| SUB4 | 0.843 | ||||||
| SUB5 | 0.836 |
VIF = variance inflation factor and R2 = coefficient of determination
Heterotrait-monotrait ratio
| Constructs | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
|---|---|---|---|---|---|---|---|---|
| 1. Attitude | ||||||||
| 2. Perceived control | 0.416 | |||||||
| 3. Eco-brand | 0.230 | 0.312 | ||||||
| 4. Eco-label | 0.275 | 0.161 | 0.180 | |||||
| 5. Environmental marketing | 0.753 | 0.540 | 0.247 | 0.284 | ||||
| 6. Green marketing | 0.612 | 0.479 | 0.708 | 0.820 | 0.813 | |||
| 7. Intention | 0.520 | 0.506 | 0.498 | 0.413 | 0.496 | 0.685 | ||
| 8. Subjective norm | 0.073 | 0.119 | 0.115 | 0.126 | 0.101 | 0.168 | 0.237 |
Second-order reflective
| Second-order variable | Dimensions | Path coefficient | t-values | 95% confidence interval bias corrected | |
|---|---|---|---|---|---|
| 2.5% | 97.5% | ||||
| Green marketing (CR = 0.888; α = 0.867) | Eco-brand | 0.590 | 11.33 | 0.465 | 0.676 |
| Environmental marketing | 0.764 | 22.82 | 0.679 | 0.816 | |
| Eco-label | 0.701 | 15.00 | 0.587 | 0.775 | |
Direct and indirect relationships between variables
| 95% CIBC | |||||||
|---|---|---|---|---|---|---|---|
| No. | Hypothesis | (β) | t-values | Decision/supported | LL | UL | |
| H1 | Green marketing → Behavioural intention | 0.410 | 7.548* | Yes | 0.304 | 0.516 | |
| H2 | Green marketing →Attitude | 0.558 | 13.289* | Yes | 0.468 | 0.634 | |
| H3 | Green marketing → Perceived behavioural control | 0.436 | 8.947* | Yes | 0.332 | 0.523 | |
| H4 | Green marketing → Subjective norm | 0.139 | 2.884** | Yes | 0.041 | 0.230 | |
| H5 | Attitude → Behavioural intention | 0.134 | 2.295*** | Yes | 0.013 | 0.242 | |
| H6 | Perceived behavioural control → Behavioural intention | 0.190 | 3.410* | Yes | 0.077 | 0.296 | |
| H7 | Subjective norm → Behavioural intention | 0.119 | 2.913** | Yes | 0.032 | 0.195 | |
| H8 | Green marketing → Attitude→ Behavioural intention | 0.075 | 2.222*** | Yes | 0.008 | 0.140 | |
| H9 | Green marketing → Perceived behavioural control → Behavioural intention | 0.083 | 3.149** | Yes | 0.034 | 0.138 | |
| H10 | Green marketing → Subjective norm → Behavioural intention | 0.017 | 1.859 ns | No | 0.003 | 0.038 | |
n = 421.
p ≤ 0.001 or t ≥ 3.29;
p ≤ 0.01 or t ≥ 2.58;
p ≤ 0.05 or t ≥ 1.96;
β = path coefficient, CIBC = confidence interval bias corrected. ns = not significant
References
Ackerstein, D.S. and Lemon, K.A. (2017), “Greening the brand: environmental marketing strategies and the American consumer”, Greener Marketing, Routledge, London, pp. 233-254.
Adamu, A.A. and Mohamad, B. (2019), “A reliable and valid measurement scale for assessing internal crisis communication”, Journal of Communication Management, Vol. 23 No. 2, pp. 90-108.
Afthanorhan, A., Awang, Z. and Fazella, S. (2017), “Perception of tourism impact and support tourism development in Terengganu”, Social Sciences, Vol. 6 No. 3, p. 106.
Ajzen, I. (1991), “The theory of planned behavior”, Organizational Behavior and Human Decision Processes, Vol. 50 No. 2, pp. 179-211.
Ajzen, I. (2002), “Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior”, Journal of Applied Social Psychology, Vol. 32 No. 4, pp. 665-683.
Ajzen, I. and Fishbein, M. (1980), Understanding Attitudes and Predicting Social Behavior: Attitudes, Intentions, and Perceived Behavioral Control, Prentice Hall, Englewood Cliffs, NJ.
Ali, F., Rasoolimanesh, S.M., Sarstedt, M., Ringle, C.M. and Ryu, K. (2018), “An assessment of the use of partial least squares structural equation modelling (PLS-SEM) in hospitality research”, International Journal of Contemporary Hospitality Management, Vol. 30 No. 1, pp. 514-538.
Arli, D., Tan, L.P., Tjiptono, F. and Yang, L. (2018), “Exploring consumers’ purchase intention towards green products in an emerging market: the role of consumers’ perceived readiness”, International Journal of Consumer Studies, Vol. 42 No. 4, pp. 389-401.
Banerjee, S., Gulas, C.S. and Iyer, E. (1995), “Shades of green: a multidimensional analysis of environmental advertising”, Journal of Advertising, Vol. 24 No. 2, pp. 21-31.
Becker, T.E. (2005), “Potential problems in the statistical control of variables in organisational research: a qualitative analysis with recommendations”, Organizational Research Methods, Vol. 8 No. 3, pp. 274-289.
Biswas, A. and Roy, M. (2015), “Leveraging factors for sustained green consumption behavior based on consumption value perceptions: testing the structural model”, Journal of Cleaner Production, Vol. 95, pp. 332-340.
Chan, R.Y. and Lau, L.B. (2002), “Explaining green purchasing behavior: a cross-cultural study on American and Chinese consumers”, Journal of International Consumer Marketing, Vol. 14 Nos 2/3, pp. 9-40.
Chang, H.H., Tsai, S.H. and Huang, C.C. (2019), “Sustainable development: the effects of environmental policy disclosure in advertising”, Business Strategy and the Environment, Vol. 28 No. 8, pp. 1497-1506.
Cheah, J.H., Memon, M.A., Chuah, F. and Ting, H. (2018), “Assessing reflective models in marketing research: a comparison between PLS and PLSC estimates”, International Journal of Business and Society, Vol. 19 No. 1, pp. 139-160.
Chekima, B., Wafa, S.A.W.S.K., Igau, O.A., Chekima, S. and Sondoh, S.L. Jr (2016), “Examining green consumerism motivational drivers: does premium price and demographics matter to green purchasing?”, Journal of Cleaner Production, Vol. 112, pp. 3436-3450.
Chin, C.H., Chin, C.L. and Wong, W.P.M. (2018), “The implementation of green marketing tools in rural tourism: the readiness of tourists?”, Journal of Hospitality Marketing and Management, Vol. 27 No. 3, pp. 261-280.
Chin, W., Cheah, J.H., Liu, Y., Ting, H., Lim, X.J. and Cham, T.H. (2020), “Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research”, Industrial Management and Data Systems, Vol. 120 No. 12, pp. 2161-2209.
Choi, D. and Johnson, K.K. (2019), “Influences of environmental and hedonic motivations on intention to purchase green products: an extension of the theory of planned behavior”, Sustainable Production and Consumption, Vol. 18, pp. 145-155.
Comerio, N. and Strozzi, F. (2019), “Tourism and its economic impact: a literature review using bibliometric tools”, Tourism Economics, Vol. 25 No. 1, pp. 109-131, doi: 10.1177/1354816618793762.
Cui, L., Wang, Y., Chen, W., Wen, W. and Han, M.S. (2021), “Predicting determinants of consumers' purchase motivation for electric vehicles: an application of Maslow's hierarchy of needs model”, Energy Policy, Vol. 151, p. 112167.
Dangelico, R.M. and Vocalelli, D. (2017), “‘Green marketing’: an analysis of definitions, strategy steps, and tools through a systematic review of the literature”, Journal of Cleaner Production, Vol. 165, pp. 1263-1279.
De Leeuw, A., Valois, P., Ajzen, I. and Schmidt, P. (2015), “Using the theory of planned behavior to identify key beliefs underlying pro-environmental behavior in high-school students: implications for educational interventions”, Journal of Environmental Psychology, Vol. 42, pp. 128-138.
Fellnhofer, K. (2017), “Entrepreneurship education revisited: perceived entrepreneurial role models increase perceived behavioural control”, International Journal of Learning and Change, Vol. 9 No. 3, pp. 260-283.
Ferreira, G.A. and Fernandes, M.E. (2021), “Sustainable advertising or eco-labels: which is the best for your brand and for consumers' environmental consciousness?”, Journal of Marketing Theory and Practice, Ahead of print, pp. 1-17.
Gursoy, D., Ouyang, Z., Nunkoo, R. and Wei, W. (2019), “Residents' impact perceptions of and attitudes towards tourism development: a meta-analysis”, Journal of Hospitality Marketing and Management, Vol. 28 No. 3, pp. 306-333.
Habibi, S. (2017), “Micro-climatization and real-time digitalization effects on energy efficiency based on user behavior”, Building and Environment, Vol. 114, pp. 410-428.
Hair, J.F. Jr, Sarstedt, M., Hopkins, L. and Kuppelwieser, V.G. (2014), “Partial least squares structural equation modeling (PLS-SEM): an emerging tool in business research”, European Business Review, Vol. 26 No. 2, pp. 106-121.
Hair, J.F., Page, M. and Brunsveld, N. (2019), Essentials of Business Research Methods, Routledge, New York.
Han, H. and Yoon, H.J. (2015), “Hotel customers' environmentally responsible behavioral intention: impact of key constructs on decision in green consumerism”, International Journal of Hospitality Management, Vol. 45, pp. 22-33.
Han, M.S. and Cudjoe, D. (2020), “Determinants of energy-saving behavior of urban residents: evidence from Myanmar”, Energy Policy, Vol. 140, p. 111405.
Handriana, T. and Ambara, R. (2016), “Responsible environmental behavior intention of travelers on ecotourism sites”, Tourism and Hospitality Management, Vol. 22 No. 2, pp. 135-150, doi: 10.20867/thm.22.2.4.
Haro, A. (2016), “Understanding TPB model, availability, and information on consumer purchase intention for halal food”, International Journal of Business and Commerce, Vol. 5 No. 8, pp. 47-56.
Hasan, M.M., Nekmahmud, M., Yajuan, L. and Patwary, M.A. (2019), “Green business value chain: a systematic review”, Sustainable Production and Consumption, Vol. 20, pp. 326-339.
Heath, T. and McKechnie, S. (2019), “Sustainability in marketing”, Incorporating Sustainability in Management Education, Palgrave Macmillan, Cham, pp. 105-131.
Henion, K.E. and Kinnear, T.C. (1976), Ecological Marketing, American Marketing Association, Chicago.
Henseler, J., Hubona, G. and Ray, P.A. (2016), “Using PLS path modeling in new technology research: updated guidelines”, Industrial Management and Data Systems, Vol. 116 No. 1, pp. 2-20.
Heung, V.C. and Pun, P.S. (2013), “Dimensions of environmentalism: a study of policies and good practices in the Hong Kong hotel industry”, Journal of China Tourism Research, Vol. 9 No. 1, pp. 50-80.
Ihemezie, E.J., Ukwuaba, I.C. and Nnaji, A.P. (2018), “Impact of ‘Green’ product label standards on consumer behaviour: a systematic review analysis”, International Journal of Academic Research in Business and Social Sciences, Vol. 8 No. 9, pp. 666-684.
Jermsittiparsert, K., Siam, M., Issa, M., Ahmed, U. and Pahi, M. (2019), “Do consumers expect companies to be socially responsible? The impact of corporate social responsibility on buying behavior”, Uncertain Supply Chain Management, Vol. 7 No. 4, pp. 741-752.
Kilbourne, W.E. (1998), “Green marketing: a theoretical perspective”, Journal of Marketing Management, Vol. 14 No. 6, pp. 641-655.
Kim, Y. and Han, H. (2010), “Intention to pay conventional-hotel prices at a green hotel – a modification of the theory of planned behavior”, Journal of Sustainable Tourism, Vol. 18 No. 8, pp. 997-1014.
Krejcie, R.V. and Morgan, D.W. (1970), “Determining sample size for research activities”, Educational and Psychological Measurement, Vol. 30 No. 3, pp. 607-610.
Kumar, D.S., Purani, K. and Viswanathan, S.A. (2018), “Influences of ‘appscape’ on mobile app adoption and m-loyalty”, Journal of Retailing and Consumer Services, Vol. 45, pp. 132-141.
La Barbera, F. and Ajzen, I. (2020), “Control interactions in the theory of planned behavior: rethinking the role of subjective norm”, Europe’s Journal of Psychology, Vol. 16 No. 3, p. 401.
Liobikiene, G., Mandravickaitė, J. and Bernatonienė, J. (2016), “Theory of planned behavior approach to understand the green purchasing behavior in the EU: a cross-cultural study”, Ecological Economics, Vol. 125, pp. 38-46.
Liu, Y., Hong, Z., Zhu, J., Yan, J., Qi, J. and Liu, P. (2018), “Promoting green residential buildings: residents' environmental attitude, subjective knowledge, and social trust matter”, Energy Policy, Vol. 112, pp. 152-161.
Maichum, K., Parichatnon, S. and Peng, K.C. (2016), “Application of the extended theory of planned behavior model to investigate purchase intention of green products among Thai consumers”, Sustainability, Vol. 8 No. 10, p. 1077.
Matthes, J. (2019), “Uncharted territory in research on environmental advertising: toward an organising framework”, Journal of Advertising, Vol. 48 No. 1, pp. 91-101.
Moon, S.J. (2021), “Investigating beliefs, attitudes, and intentions regarding green restaurant patronage: an application of the extended theory of planned behavior with moderating effects of gender and age”, International Journal of Hospitality Management, Vol. 92, p. 102727.
Muniandy, K., Rahim, S.A., Ahmi, A. and Rahman, N.A.A. (2019), “Factors that influence customers' intention to visit green hotels in Malaysia”, International Journal of Supply Chain Management, Vol. 8 No. 3, pp. 994-1012.
Nekmahmud, M. and Fekete-Farkas, M. (2020), “Why not green marketing? Determinates of consumers’ intention to green purchase decision in a new developing nation”, Sustainability, Vol. 12 No. 19, p. 7880.
Neto, B. and Caldas, M.G. (2018), “The use of green criteria in the public procurement of food products and catering services: a review of EU schemes”, Environment, Development and Sustainability, Vol. 20 No. 5, pp. 1905-1933.
Olya, H.G., Bagheri, P. and Tümer, M. (2019), “Decoding behavioural responses of green hotel guests: a deeper insight into the application of the theory of planned behaviour”, International Journal of Contemporary Hospitality Management, Vol. 31 No. 6, pp. 2509-2525.
Patwary, A.K., Omar, H. and Tahir, S. (2020), “A conceptual model of what influences consumers when visiting green hotels in Malaysia”, International Journal of Innovation, Creativity and Change, Vol. 11 No. 11, pp. 11-25.
Patwary, A.K., Omar, H. and Tahir, S. (2021), “The impact of perceived environmental responsibility on tourists' intention to visit green hotel: the mediating role of attitude”, Geojournal of Tourism and Geosites, Vol. 34 No. 1, pp. 9-13.
Podsakoff, P.M. and Organ, D.W. (1986), “Self-reports in organizational research: Problems and prospects”, Academy of Management Proceedings, Vol. 12 No. 4, pp. 531-544.
Podsakoff, P.M., MacKenzie, S.B. and Podsakoff, N.P. (2012), “Sources of method bias in social science research and recommendations on how to control it”, Annual Review of Psychology, Vol. 63 No. 1, pp. 539-569.
Prakash, G. and Pathak, P. (2017), “Intention to buy eco-friendly packaged products among young consumers of India: a study on developing nation”, Journal of Cleaner Production, Vol. 141, pp. 385-393.
Rahbar, E. and Wahid, N.A. (2011), “Investigation of green marketing tools' effect on consumers' purchase behavior”, Business Strategy Series, Vol. 12 No. 2, pp. 73-83.
Rajapaksha, R.A.S. and Tilakasiri, K.K. (2019), “The impact of green marketing on consumer purchase intention: evidence from Sri Lanka”, International Postgraduate Research Conference 2019, Faculty of Graduate Studies, University of Kelaniya.
Raza, S.H., Adamu, A.A., Ogadimma, E.C. and Hasnain, A. (2020), “The influences of political values manifested in advertisements on political participation: moderating roles of self-transcendence and conservation”, Journal of Creative Communications, Vol. 15 No. 3, pp. 318-341.
Rihn, A., Wei, X. and Khachatryan, H. (2019), “Text vs logo: does eco-label format influence consumers’ visual attention and willingness-to-pay for fruit plants? An experimental auction approach”, Journal of Behavioral and Experimental Economics, Vol. 82, p. 101452.
Rizqiyana, I. and Wahyono, W. (2020), “The influence of eco-brand, eco-labelling and environmental advertisement on consumer purchasing behavior through Brand image”, Management Analysis Journal, Vol. 9 No. 2, pp. 211-220.
Roy, R., Akhtar, F. and Das, N. (2017), “Entrepreneurial intention among science and technology students in India: extending the theory of planned behavior”, International Entrepreneurship and Management Journal, Vol. 13 No. 4, pp. 1013-1041.
Schmuck, D., Matthes, J. and Naderer, B. (2018), “Misleading consumers with green advertising? An affect–reason–involvement account of greenwashing effects in environmental advertising”, Journal of Advertising, Vol. 47 No. 2, pp. 127-145.
Sharma, R.R., Kaur, T. and Syan, A.S. (2021), “Sustainability marketing–the environmental perspective”, Sustainability Marketing, Emerald Publishing.
Song, H., Lee, C.K., Reisinger, Y. and Xu, H.L. (2017), “The role of visa exemption in Chinese tourists' decision-making: a model of goal-directed behavior”, Journal of Travel and Tourism Marketing, Vol. 34 No. 5, pp. 666-679.
Song, W. and Yu, H. (2018), “Green innovation strategy and green innovation: the roles of green creativity and green organisational identity”, Corporate Social Responsibility and Environmental Management, Vol. 25 No. 2, pp. 135-150.
Soutter, A.R. and Boag, S. (2019), “Environmental advertising: the effect of imagery on pro-environmental attitudes and pro-environmental behaviour/publicidad medioambiental: el efecto de las imágenes sobre las actitudes proambientales y el comportamiento proambiental”, Psyecology, Vol. 10 No. 1, pp. 88-126.
Stoeva, K. and Alriksson, S. (2017), “Influence of recycling programmes on waste separation behaviour”, Waste Management, Vol. 68, pp. 732-741.
Sun, Y., Luo, B., Wang, S. and Fang, W. (2021), “What you see is meaningful: does green advertising change the intentions of consumers to purchase eco‐labeled products?”, Business Strategy and the Environment, Vol. 30 No. 1, pp. 694-704.
Twedt, D.W. (1960), “The American marketing association in 1960”, Journal of Marketing, Vol. 25 No. 1, pp. 57-61.
Uduji, J.I., Okolo‐Obasi, E.N. and Asongu, S.A. (2020), “Sustaining cultural tourism through higher female participation in Nigeria: the role of corporate social responsibility in oil host communities”, International Journal of Tourism Research, Vol. 22 No. 1, pp. 120-143.
UNWTO. (2019), “International accessible tourism destination distinction”, Madrid, available at: http://ethics.unwto.org/en/content/accessible-tourism
Vafaei, S.A., Azmoon, I. and Fekete-Farkas, M. (2019), “The impact of perceived sustainable marketing policies on green customer satisfaction”, Polish Journal of Management Studies, Vol. 19 No. 1.
Varah, F., Mahongnao, M., Pani, B. and Khamrang, S. (2021), “Exploring young consumers' intention toward green products: applying an extended theory of planned behavior”, Environment, Development and Sustainability, Vol. 23 No. 6, pp. 9181-9195.
Varkaris, E. and Neuhofer, B. (2017), “The influence of social media on the consumers' hotel decision journey”, Journal of Hospitality and Tourism Technology, Vol. 8 No. 1, pp. 101-118.
Wan, C., Shen, G.Q. and Choi, S. (2017), “Experiential and instrumental attitudes: interaction effect of attitude and subjective norm on recycling intention”, Journal of Environmental Psychology, Vol. 50, pp. 69-79.
Wang, B., Wang, X., Guo, D., Zhang, B. and Wang, Z. (2018), “Analysis of factors influencing residents’ habitual energy-saving behaviour based on NAM and TPB models: Egoism or altruism?”, Energy Policy, Vol. 116, pp. 68-77.
Widyastuti, S. and Santoso, B. (2018), “Green marketing: a study of the factors influencing the repurchase decision for javanony herbal products”, ASEAN Marketing Journal, Vol. 8 No. 2, p. 4.
Wu, S.I. and Chen, Y.J. (2014), “The impact of green marketing and perceived innovation on purchase intention for green products”, International Journal of Marketing Studies, Vol. 6 No. 5, p. 81.
Yadav, R. and Pathak, G.S. (2017), “Determinants of consumers’ green purchase behavior in a developing nation: applying and extending the theory of planned behavior”, Ecological Economics, Vol. 134, pp. 114-122.
Yang, D., Xiao, T. and Huang, J. (2019), “Dual-channel structure choice of an environmental responsibility supply chain with green investment”, Journal of Cleaner Production, Vol. 210, pp. 134-145.
Yoon, D., Kim, Y.K. and Fu, R.J. (2020), “How can hotels' green advertising be persuasive to consumers? An information-processing perspective”, Journal of Hospitality and Tourism Management, Vol. 45, pp. 511-519.
Yusof, Y., Awang, Z., Jusoff, K. and Ibrahim, Y. (2017), “The influence of green practices by non-green hotels on customer satisfaction and loyalty in the hotel and tourism industry”, International Journal of Green Economics, Vol. 11 No. 1, pp. 1-14.
Further reading
Aizen, I. (2009), “TPB bibliography”, available at: www.people.umass.edu/aizen/tpbrefs.html (accessed 9 April 2009).
Chan, E.S.W. (2014), “Green marketing: hotel customers' perspective”, Journal of Travel and Tourism Marketing, Vol. 31 No. 8, pp. 915-936.
Han, M.S. and Chen, W. (2021), “Determinants of eco-innovation adoption of small and medium enterprises: an empirical analysis in Myanmar”, Technological Forecasting and Social Change, Vol. 173, p. 121146.
Law, A., De Lacy, T., Lipman, G. and Jiang, M. (2016), “Transitioning to a green economy: the case of tourism in Bali, Indonesia”, Journal of Cleaner Production, Vol. 111, pp. 295-305.
Maziriri, E.T. (2020), “Green packaging and green advertising as precursors of competitive advantage and business performance among manufacturing small and medium enterprises in South Africa”, Cogent Business and Management, Vol. 7 No. 1, p. 1719586.
Sana, S.S. (2020), “Price competition between green and non green products under corporate social responsible firm”, Journal of Retailing and Consumer Services, Vol. 55, p. 102118.
Suki, N.M. (2016), “Consumer environmental concern and green product purchase in Malaysia: structural effects of consumption values”, Journal of Cleaner Production, Vol. 132, pp. 204-214.
Suki, N.M. and Suki, N.M. (2019), “Examination of peer influence as a moderator and predictor in explaining green purchase behaviour in a developing country”, Journal of Cleaner Production, Vol. 228, pp. 833-844.
Wan, C., Shen, G.Q. and Choi, S. (2018), “The moderating effect of subjective norm in predicting intention to use urban green spaces: a study of Hong Kong”, Sustainable Cities and Society, Vol. 37, pp. 288-297.
Acknowledgements
The authors want to thank the participants of the study for allowing us to interview them. Without their support, this research would not have been possible.
Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.
Funding: The authors received no financial support for the research, authorship and/or publication of this article.