This study aims to develop and test a model for predicting guests’ intention to visit green hotels by extending the theory of planned behaviour (TPB) to include spirituality, moral norms and habit.
Data were collected from green hotel patrons using in-person, paper-based surveys. The proposed model was evaluated and tested using structural equation modelling in SPSS AMOS 28.
The results reveal that spirituality and moral norms have a significant, positive effect on attitude. They also indicate that while spirituality has a positive effect on subjective norms, moral norms do not. The findings also reveal that the TPB variables (attitude, subjective norms and perceived behavioural control), together with habit, positively affect behavioural intentions.
The study found that adding spirituality, moral norms and habitual green behaviour to the TPB enhances the prediction of consumers’ intention to visit green hotels. The results suggest that green hotel marketing should incorporate spiritual values, social influences and habitual behaviours to effectively promote sustainability and attract environmentally conscious consumers.
This study provides novel insights into green hotel visit intention by integrating spirituality, moral norms and habit. To the best of the authors’ knowledge this is the first study from an emerging African economy to investigate these factors within this context.
1. Introduction
Over the past few decades, the tourism industry has rapidly expanded into a substantial contributor to many national economies (Leal Filho et al., 2023). As a significant economic and social industry, tourism accounts for 9.5% of the global GDP (World Travel & Tourism Council, 2024), is the world’s third largest export industry (Rasool et al., 2021) and accounts for 10% of global employment (Haq et al., 2023). However, despite its numerous economic benefits, the tourism industry accounts for about 8% of greenhouse gas emissions (Pilgreen et al., 2024; Rasheed and Balakrishnan, 2024; Wu et al., 2024). Consequently, tourism has received substantial criticism owing to its negative impact on the environment and climate change (Leal Filho et al., 2023; Rasool et al., 2021). In addition, growing environmental concerns and a shift towards sustainable tourism (Rasheed and Balakrishnan, 2024) have led to an increase in consumer interest in green consumption, as well as scholarly interest in sustainable tourism practices (Kamboj et al., 2022; Wu et al., 2024). However, consumer behaviour research in the pro-environmental hospitality domain is limited (Nimri et al., 2022). Furthermore, extant literature on green hotel visit intention indicates that there is limited research relating to some of the cultural, personal and social factors influencing pro-environmental behaviour (Eid et al., 2021; Patwary et al., 2023; Piramanayagam et al., 2023; Wang et al., 2018).
To better understand the green behaviours of consumers, researchers in the hospitality industry have turned to behavioural theories such as the theory of planned behaviour (TPB) and the theory of reasoned action (Agag and Colmekcioglu, 2020; Eid et al., 2021; Hasan, 2023a). Originally developed in the field of psychology, the TPB – useful for predicting and understanding human behaviour – has been used in a variety of fields, including hospitality (Fauzi et al., 2022; Ferreira et al., 2023; Yeh et al., 2021). Researchers have attempted to improve the explanatory power of the TPB by either combining it with other theoretical models or including additional predictors (Canova et al., 2023) and found that the combination of the TPB with other behavioural, psychosocial and economic theories can provide robust theoretical support for understanding and predicting green consumer behaviour (Nimri et al., 2020; Wu et al., 2024).
Despite the proliferation of studies investigating pro-environmental behaviours, very few of these studies have investigated the role of culture-specific factors such as spirituality (Lestar and Böhm, 2020; Saleem et al., 2018; Saxena and Sharma, 2023). In this emerging field of research, scholars have examined the role of spirituality and pro-environmental behaviour in the areas such as education, religion, consumer goods and personal vehicles (Chavan and Sharma, 2024; Leal Filho et al., 2023; Saleem et al., 2018; Saxena and Sharma, 2023). However, in the green hotel industry, the role of spirituality has been overlooked. The current study assumes that this may be due to the complexity in measuring and defining spirituality as well as the limited integration of cultural aspects in sustainability research. Similarly, despite evidence of the positive association between moral norms and sustainable consumption intentions (Canova et al., 2023; Talwar et al., 2022), few studies have considered moral norms in the context of green hotels (Han et al., 2019; Pan et al., 2022; Shehawy et al., 2024). Against this backdrop, this study aims to fill this important gap by examining the role of spirituality, moral norms as well as the influence of TPB variables on green hotel visit intention. To achieve this, the study seeks to answer the following research questions: how do spirituality and moral norms influence consumers’ attitudes and subjective norms towards green hotels and to what extent do the TPB variables (including habitual green hotel behaviour) predict consumers’ intention to visit green hotels? Investigating the role of spirituality and moral norms may shed light on the personal and socio-cultural factors influencing pro-environmental behaviour.
2. Theoretical framework and hypothesis development
2.1 Green hotels
The hospitality industry consumes enormous resources and, if unchecked, can be responsible for environmental degradation (Ferreira et al., 2023; Rasheed and Balakrishnan, 2024). Thus, as part of efforts to reduce the negative impact of tourism, green hotels have expanded rapidly. The Green Hotels Association (2024) defines “green hotels” as “environmentally-friendly properties whose managers are eager to institute programs that save water, save energy and reduce solid waste – while saving money – to help protect our one and only earth”. Green hotels implement green measures such as waste management practices, conservation projects and solar power systems (Mohammed et al., 2024). Past research has shown that consumers are more willing to patronise green hotels when they want to engage in consumption that has a minimal carbon footprint (Kamboj et al., 2022).
2.3 The theory of planned behaviour
The TPB is a social psychology theory that attempts to explain human behaviour by examining the relationships between beliefs, attitudes, intentions and actual behaviour (Ajzen, 1991). The TPB posits that three variables, namely perceived behavioural control (PBC), subjective norms and attitude, are key drivers of behavioural intentions, which, in turn, predict actual behaviour (Meng et al., 2022; Patwary et al., 2023). Over the years, this theory has evolved to become one of the most used social psychology models to predict behavioural intentions. In addition, owing to its highly adaptable nature, the TPB allows researchers to enhance its explanatory power by including elements from other models/theories, allowing it to be used in other research fields (Wu et al., 2024). The TBP has been adopted as a theoretical framework by researchers to predict pro-environmental behaviour and to investigate consumers’ willingness to engage in environmentally friendly activities (Agrawal and Pradhan, 2023; Kamboj et al., 2022). The TPB has also been used in the hospitality industry where it has been shown to be useful in predicting hotel customers’ behaviour (Patwary et al., 2023; Sharma et al., 2023; Yeh et al., 2021).
2.3.1 TPB and Green Hotels.
Studies on green hotels have adopted TPB as a theoretical framework to understand hotel patrons’ behaviour concerning green hotels. The first group of studies are concerned with consumer’s attitudes towards green hotels. Attitude is the degree to which a person views a behaviour favourably or unfavourably (Ajzen, 1991). In TPB research, attitude has been identified as the most significant predictor of behaviour (Piramanayagam et al., 2023). The relationship between attitudes and behavioural intention has been posed as a direct and positive one, with various studies finding a positive relationship between attitudes towards green hotels and guests’ intention to visit (Ferreira et al., 2023; Mohammed et al., 2024; Pan et al., 2022). In addition to attitude, studies have investigated the influence of social pressure on green hotel patronage. “Subjective norms” are defined as an individual’s perception of the social expectation to engage in or adopt a particular behaviour (Ham et al., 2015) and whether that behaviour will be acceptable or not acceptable to others. Research has shown that subjective norms have a significantly positive effect on individuals’ attitudes towards green hotel intention (Fauzi et al., 2022; Ham et al., 2015; Pan et al., 2022; Shehawy et al., 2024; Wu et al., 2024). Finally, studies have shown that PBC, which indicates a person’s perception of how easy or difficult it would be to perform a certain task (Piramanayagam et al., 2023; Yeh et al., 2021) is an important factor in the establishment of green hotel visit intention and behaviour (Fauzi et al., 2022; Ham et al., 2015; Pan et al., 2022). The current study thus proposes the following hypotheses:
Attitude towards green hotels positively influences consumers’ intention to visit green hotels.
Subjective norms positively influence intention to visit green hotels.
Perceived behavioural control positively influences intention to visit green hotels.
2.3.2 Spirituality and green behaviour.
“Spirituality” is defined as “a belief in the spiritual interconnectedness and essential oneness of all phenomena, both living and non-living; and the belief that happiness depends on living in accord with this understanding” (Saleem et al., 2018). As a self-reflective construct, spiritualty is often aligned with social justice, environmental sustainability and economic equity (Leal Filho et al., 2023). In recent years, spirituality – as a personal/cultural trait – has become a concern for marketers in understanding its association with sustainable/green consumption behaviour (Chavan and Sharma, 2024; Lestar and Böhm, 2020; Saxena and Sharma, 2023). Research has indicated that spirituality significantly influences attitudes towards sustainable consumption (Rasanjalee, 2021; Saxena and Sharma, 2023). Given these findings, the researchers propose the following hypotheses:
Spirituality positively influences attitude towards green hotels.
Spirituality positively influences subjective norms.
2.3.3 Moral norms.
Moral norms are defined as an individual’s perception of the moral correctness or incorrectness of engaging in a certain behaviour (Canova et al., 2023) or the feelings of moral obligation to engage in that behaviour (Pan et al., 2022). Evidence from previous research indicates that moral norms significantly influence consumers’ pro-environmental behaviours (Shehawy et al., 2024; Talwar et al., 2022) including their intention to visit green hotels (Han et al., 2019; Pan et al., 2022). Other studies have adopted moral norms as an additional predictor in the TPB for studying pro-environmental behaviour. For instance, Pan et al. (2022) extended the TPB to include personal moral norms and environmental concern to study Gen Z tourists’ green hotel visit intention and found personal moral norms to influence intention positively and significantly. Given these results, the researchers in the current study propose the following hypotheses:
Moral norms positively influence attitude towards green hotels.
Moral norms positively influence subjective norms.
2.3.4 Habit.
“Habit” is defined as the “extent to which people tend to perform behaviours automatically because of learning” (Venkatesh et al., 2012). Limited studies have investigated the influence of habit on sustainable consumption behaviour in the hospitality sector. For instance, Dharmesti et al. (2020) investigated habitual behaviour as an antecedent of pro-environmental behaviour in hotels and found that individuals’ green habits at home predict hotel guests’ pro-environmental behaviour. More recently, Hasan (2023b) applied the theory of repeat purchase behaviour to green hotel visitors and found that habitual attachment positively relates to green hotel revisit intentions. Thus, the researchers in the current study seek to integrate habit into the TBP to ascertain if it will increase the predictive power of the TPB in the context of green hotels:
Green hotel habit has a significant positive influence on green hotel visit intention.
Figure 1 presents the conceptual model adopted for this study.
3. Methodology
3.1 Measurement development
This study’s constructs were measured using multi-item scales, selected and adapted to the study from previously validated instruments. Seven multi-item constructs were designed, based on an in-depth examination of existing literature to meet the current study’s objectives. Spirituality was measured using four items, adapted from the Daily Spiritual Experience Scale (Underwood, 2011). Only four items were adapted from this scale as the rest of the items leaned more on religious values rather than spirituality. Moral norms were measured using four items adapted from Botetzagias et al. (2015), edited for the context of the study. While the original scale validated two items, the current scale added two more items to make the construct more robust. Attitude was measured using five items, while subjective norms and PBC were measured with three items each (Haq et al., 2023; Wang et al., 2018). In line with the seminal works of (Venkatesh et al., 2012) habit was measured using four items, adapted for the green hotel context. Finally, green hotel visit intention was measured using four items adapted from Rahman and Reynolds (2016). All the scale items were measured using a seven-point Likert scale (1 = strongly disagree, 2 = disagree, 3 = disagree somewhat; 4 = neutral, 5 = agree somewhat, 6 = agree, 7 = strongly agree). Constructs and their measurements are presented in Appendix.
3.2 Data collection and sample characteristics
To test the proposed hypotheses, a survey was conducted among green hotels in Gauteng, South Africa. The study’s statistical population consisted of green hotel patrons, aged 18 and over. Data were collected using an English language, self-administered questionnaire. The questionnaire was hand-delivered to 315 hotel patrons of hotels designated as green hotels on Trip Advisor. A consent form, with a definition of green hotels, was given to the responds to advise them of the objective of the study and the confidential nature of the study. Data were collected from 10 August 2023 to 13 August 2023. After the survey was terminated, 250 questionnaires were returned. The smaller sample size was influenced by the fact that not many hotels are designated as green hotels. After performing the completeness checks and removing responses with a substantial amount of missing data, 240 questionnaires were retained for the analysis, representing a 76% response rate. The demographic characteristics of the sample are depicted in Table 1 below. The female participants were slightly more at 52.5% compared to 47.5% males. The 18–25-year-olds represented the largest percentage of respondents at 48.3%. The researchers also considered the number of nights stayed and found that short stays (1–5 days) had the most patrons at 88.3%. The results of the various demographic variables indicate that there was a measure of diversity in the sample.
Demographics
| Demographic characteristics | Frequency | % |
|---|---|---|
| Gender | ||
| Male | 114 | 47.5 |
| Female | 126 | 52.4 |
| Age | ||
| 18–25 yrs | 115 | 48.3 |
| 26–30 yrs | 49 | 20.4 |
| 31–35 yrs | 29 | 12.1 |
| 36–40 yrs | 27 | 11.3 |
| Over 40 yrs | 19 | 7.9 |
| Racial group | ||
| Black | 211 | 87.9 |
| White | 5 | 2.1 |
| Indian | 6 | 2.5 |
| Coloured | 18 | 7.5 |
| Number of nights stayed | ||
| 1–5 days | 212 | 88.3 |
| 6–10 days | 20 | 8.3 |
| 11–15 days | 2 | 0.9 |
| 16–20 days | 6 | 2.5 |
| Demographic characteristics | Frequency | % |
|---|---|---|
| Gender | ||
| Male | 114 | 47.5 |
| Female | 126 | 52.4 |
| Age | ||
| 18–25 yrs | 115 | 48.3 |
| 26–30 yrs | 49 | 20.4 |
| 31–35 yrs | 29 | 12.1 |
| 36–40 yrs | 27 | 11.3 |
| Over 40 yrs | 19 | 7.9 |
| Racial group | ||
| Black | 211 | 87.9 |
| White | 5 | 2.1 |
| Indian | 6 | 2.5 |
| Coloured | 18 | 7.5 |
| Number of nights stayed | ||
| 1–5 days | 212 | 88.3 |
| 6–10 days | 20 | 8.3 |
| 11–15 days | 2 | 0.9 |
| 16–20 days | 6 | 2.5 |
3.3 Common method bias
Several steps were taken in this study, both during and after data collection, to reduce bias in the results. Several procedural remedies recommended by Podsakoff et al. (2003) were adopted. Firstly, previously validated items were used to measure the predictor and criterion variables to ensure that the constructs were reliably measured. Secondly, the questionnaire was pretested to ensure the validity of the instrument and to identify any challenges that the respondents might face in answering the questions. Finally, following the data collection process, Harman’s single-factor test was applied as a statistical remedy to the common method bias. The results indicated that the single factor accounted for 36.217% of the variance, which is less than the recommended 40% (Babin et al., 2016). The procedural remedies used, and the results of Harman’s single-factor test, suggest that common method bias was not a concern in this study.
4. Data analysis and results
Data for the study were analysed using SPSS version 28, while SPSS AMOS version 28 was used to carry out structural equation modelling (SEM), with a confirmatory factor analysis (CFA) being conducted before the SEM. In conducting the analyses, the validity of the measurement model was first confirmed, then the structural model was analysed to test the hypotheses. To validate the measurement model, CFA was used to analyse and explore the relationships between the constructs and the indicators, while path analysis was used to connect the dependent and independent variables in the structural model.
4.1 Measurement model validation
In validating the measurement model, three sequential steps were carried out. Firstly, the reliability measures of the constructs were assessed using Cronbach’s alpha. Table 2 presents the results of the validation. The coding for items were adopted from the original scales and extended where necessary. The results indicate that Alpha values ranged from 0.740 for PBC to 0.920 for moral norms. These values were above the recommended 0.7 (Cheung et al., 2024) threshold for internal consistency, confirming that the measures were internally consistent and reliable. Secondly, to measure the validity of the model, CFA was applied and then goodness-of-fit indices, convergent validity and discriminant validity were assessed. Parameter estimates are depicted in Table 2 and Figure 2. For the model fit indices, the chi-square index/degree of freedom (χ2/df) must be < 3.0, while the goodness-of-fit index (GFI), normed-fit index (NFI), incremental-fit index (IFI), Tucker–Lewis index (TLI) and comparative-fit index (CFI) must all be > 0.90 and the root means square error of approximation (RMSEA) must be lower than 0.08 (Kamboj et al., 2022). The results of the goodness of fit (χ2 = 411,260, df = 231, χ2/df = 1.780, p = 0.000, NFI = 0.900, IFI = 0.954, TLI = 0.944, CFI = 0.953 and RMSEA = 0.057) revealed that the measurement model provided a reasonable fit with the data.
Measurement reliability and convergent validity
| Construct | Indicator loadings | Cronbach’s α | Composite reliability | Average variance extracted | Maximum shared variance |
|---|---|---|---|---|---|
| Spirituality | 0.791 | 0.799 | 0.501 | 0.227 | |
| SP1 | 0.738 | ||||
| SP2 | 0.672 | ||||
| SP3 | 0.792 | ||||
| SP4 | 0.617 | ||||
| Moral norms | 0.920 | 0.922 | 0.747 | 0.248 | |
| MN1 | 0.812 | ||||
| MN2 | 0.885 | ||||
| MN3 | 0.916 | ||||
| MN4 | 0.804 | ||||
| Attitude | 0.862 | 0.863 | 0.679 | 0.677 | |
| ATT1 | 0.895 | ||||
| ATT2 | 0.850 | ||||
| ATT4 | 0.715 | ||||
| Subjective norms | 0.898 | 0.898 | 0.746 | 0.385 | |
| SN1 | 0.853 | ||||
| SN2 | 0.862 | ||||
| SN3 | 0.876 | ||||
| Perceived behavioural control | 0.740 | 0.746 | 0.597 | 0.280 | |
| PBC1 | 0.703 | ||||
| PBC2 | 0.836 | ||||
| Habit | 0.904 | 0.908 | 0.713 | 0.385 | |
| HB1 | 0.838 | ||||
| HB2 | 0.896 | ||||
| HB3 | 0.746 | ||||
| HB4 | 0.888 | ||||
| Visit intention | 0.898 | 0.900 | 0.693 | 0.677 | |
| VI1 | 0.770 | ||||
| VI2 | 0.890 | ||||
| VI3 | 0.820 | ||||
| VI4 | 0.850 | ||||
| Construct | Indicator loadings | Cronbach’s α | Composite reliability | Average variance extracted | Maximum shared variance |
|---|---|---|---|---|---|
| Spirituality | 0.791 | 0.799 | 0.501 | 0.227 | |
| SP1 | 0.738 | ||||
| SP2 | 0.672 | ||||
| SP3 | 0.792 | ||||
| SP4 | 0.617 | ||||
| Moral norms | 0.920 | 0.922 | 0.747 | 0.248 | |
| MN1 | 0.812 | ||||
| MN2 | 0.885 | ||||
| MN3 | 0.916 | ||||
| MN4 | 0.804 | ||||
| Attitude | 0.862 | 0.863 | 0.679 | 0.677 | |
| ATT1 | 0.895 | ||||
| ATT2 | 0.850 | ||||
| ATT4 | 0.715 | ||||
| Subjective norms | 0.898 | 0.898 | 0.746 | 0.385 | |
| SN1 | 0.853 | ||||
| SN2 | 0.862 | ||||
| SN3 | 0.876 | ||||
| Perceived behavioural control | 0.740 | 0.746 | 0.597 | 0.280 | |
| PBC1 | 0.703 | ||||
| PBC2 | 0.836 | ||||
| Habit | 0.904 | 0.908 | 0.713 | 0.385 | |
| HB1 | 0.838 | ||||
| HB2 | 0.896 | ||||
| HB3 | 0.746 | ||||
| HB4 | 0.888 | ||||
| Visit intention | 0.898 | 0.900 | 0.693 | 0.677 | |
| VI1 | 0.770 | ||||
| VI2 | 0.890 | ||||
| VI3 | 0.820 | ||||
| VI4 | 0.850 | ||||
Note(s):
MN = moral norms, ATT = attitude, PBC = perceived behavioural control, HB = habit, VI = visit intention, SP = spirituality, SN = subjective norms
Research model with path coefficients and R2 estimates
Source(s): Authors’ own creation
Research model with path coefficients and R2 estimates
Source(s): Authors’ own creation
Convergent validity was established using the standardised factor loadings, composite reliability (CR) and average variance extracted (AVE) (Cheung et al., 2024). For convergent validity to be confirmed, the factor loadings should be significant and greater than 0.7, the CR should be greater than 0.7 and the AVE should be greater than 0.5 (Maduku, 2024). In the initial estimation of the measurement model, two items for attitude (ATT3 and ATT5) and one item for perceived behavioural control (PBC3) had weak loadings and were subsequently removed from further analyses. The remaining factor loadings were all greater than 0.7. The CR and AVE values for each of the constructs were all above the threshold. The CR values presented in Table 2 ranged from 0.746 (PBC) to 0.922 (moral norms). The estimated AVE values exceeded the 0.5 threshold, with the lowest being 0.501 (spirituality) and the highest being 0.747 (moral norms). In addition, the AVE values were greater than the maximum shared variance (MSV). All these results, taken together, provide support for the convergent validity of the measurement model.
After confirming the reliability and convergent validity, discriminant validity was assessed using the Fornell and Larcker (1981) criterion. This validity method measures the extent to which constructs are empirically different from other constructs (Ab Hamid et al., 2017). Discriminant validity is achieved when the square root of the AVE of a construct exceeds its correlation with other constructs (Cheung et al., 2024). The results of the discriminant validity presented in Table 3 revealed that the square root of AVE for each construct was greater than its correlation with other constructs, thus confirming the discriminant validity of the measurement model.
Discriminant validity
| Construct | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
|---|---|---|---|---|---|---|---|
| 1. MN | 0.864 | ||||||
| 2. ATT | 0.384 | 0.824 | |||||
| 3. PBC | 0.498 | 0.529 | 0.772 | ||||
| 4. HB | 0.002 | 0.391 | 0.065 | 0.44 | |||
| 5. VI | 0.382 | 0.823 | 0.489 | 0.524 | 0.833 | ||
| 6. SP | 0.427 | 0.476 | 0.454 | 0.436 | 0.477 | 0.708 | |
| 7. SN | 0.073 | 0.500 | 0.207 | 0.621 | 0.591 | 0.347 | 0.864 |
| Construct | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
|---|---|---|---|---|---|---|---|
| 1. MN | 0.864 | ||||||
| 2. ATT | 0.384 | 0.824 | |||||
| 3. PBC | 0.498 | 0.529 | 0.772 | ||||
| 4. HB | 0.002 | 0.391 | 0.065 | 0.44 | |||
| 5. VI | 0.382 | 0.823 | 0.489 | 0.524 | 0.833 | ||
| 6. SP | 0.427 | 0.476 | 0.454 | 0.436 | 0.477 | 0.708 | |
| 7. SN | 0.073 | 0.500 | 0.207 | 0.621 | 0.591 | 0.347 | 0.864 |
Note(s):
MN = moral norms, ATT = attitude, PBC = perceived behavioural control, HB = habit, VI = visit intention, SP = spirituality, SN = subjective norms
An additional measure of discriminant validity, the heterotrait-monotrait (HTMT) ratio of correlations was considered (Henseler et al., 2015). This method, based on the multitrait-multimethod matrix, aids in overcoming the weakness of reliability in the Fornell-Larcker criterion (Ab Hamid et al., 2017). HTMT values must be less than 0.85, with values closer to 1 indicating a lack of discriminant validity (Henseler et al., 2015). The values tabulated in Table 4 below indicate that all the values for the constructs were below the recommended threshold, thus confirming discriminant validity.
HTMT analysis
| Construct | MN | ATT | PBC | HB | VI | SP | SN |
|---|---|---|---|---|---|---|---|
| MN | |||||||
| ATT | 0.338 | ||||||
| PBC | 0.416 | 0.430 | |||||
| HB | 0.026 | 0.380 | 0.071 | ||||
| VI | 0.352 | 0.717 | 0.394 | 0.511 | |||
| SP | 0.388 | 0.391 | 0.364 | 0.395 | 0.406 | ||
| SN | 0.069 | 0.439 | 0.151 | 0.582 | 0.526 | 0.285 |
| Construct | MN | ATT | PBC | HB | VI | SP | SN |
|---|---|---|---|---|---|---|---|
| MN | |||||||
| ATT | 0.338 | ||||||
| PBC | 0.416 | 0.430 | |||||
| HB | 0.026 | 0.380 | 0.071 | ||||
| VI | 0.352 | 0.717 | 0.394 | 0.511 | |||
| SP | 0.388 | 0.391 | 0.364 | 0.395 | 0.406 | ||
| SN | 0.069 | 0.439 | 0.151 | 0.582 | 0.526 | 0.285 |
Note(s):
MN = moral norms, ATT = attitude, PBC = perceived behavioural control, HB = habit, VI = visit intention, SP = spirituality, SN = subjective norms
Once the measurement model was confirmed, a structural model generated through AMOS was used to test the study’s hypotheses and the relationships between the constructs. The model fit indices (χ2 = 519.9930, df = 238, χ2/df = 2.185, p = 0.000, IFI = 0.928, TLI = 0.915, CFI = 0.927 and RMSEA = 0.070) for the structural model were satisfactory. The structural model accounted for 73.8% of the variance in green hotel visit intention, while spirituality and moral norms accounted for 39.2% of the variance in attitude and 29.5% of the variance in subjective norms. The results of the model testing are presented in Table 5 and Figure 2.
Hypothesis testing results
| Hypothesis | Path | β | t | p | Decision |
|---|---|---|---|---|---|
| H1 | Attitude ← spirituality | 0.545 | 5.971 | *** | Accepted |
| H2 | Subjective norm ← spirituality | 0.604 | 6.514 | *** | Accepted |
| H3 | Attitude ← moral norms | 0.141 | 1.970 | 0.049 | Accepted |
| H4 | Subjective norm ← moral norms | −0.211 | −2.742 | 0.006 | Rejected |
| H5 | Visit intention ← attitude | 0.632 | 8.757 | *** | Accepted |
| H6 | Visit intention ← subjective norms | 0.181 | 3.545 | *** | Accepted |
| H7 | Visit intention ← PBC | 0.147 | 2.622 | 0.009 | Accepted |
| H8 | Visit intention ← habit | 0.190 | 3.755 | *** | Accepted |
| Hypothesis | Path | β | t | p | Decision |
|---|---|---|---|---|---|
| H1 | Attitude ← spirituality | 0.545 | 5.971 | *** | Accepted |
| H2 | Subjective norm ← spirituality | 0.604 | 6.514 | *** | Accepted |
| H3 | Attitude ← moral norms | 0.141 | 1.970 | 0.049 | Accepted |
| H4 | Subjective norm ← moral norms | −0.211 | −2.742 | 0.006 | Rejected |
| H5 | Visit intention ← attitude | 0.632 | 8.757 | *** | Accepted |
| H6 | Visit intention ← subjective norms | 0.181 | 3.545 | *** | Accepted |
| H7 | Visit intention ← PBC | 0.147 | 2.622 | 0.009 | Accepted |
| H8 | Visit intention ← habit | 0.190 | 3.755 | *** | Accepted |
Note(s):
***p < 0.001, β = beta, t = t-values, p = p-value, PBC = perceived behavioural control
The hypothesis tests revealed a positive significant effect of spirituality on attitude (β = 0.545, t = 5.971, p = 0.000), spirituality on subjective norms (β = 0.604, t = 6.514, p = 0.000), moral norms on attitude (β = 0.141, t = 1.970, p = 0.049) attitude on visit intention (β = 0.632, t = 8.757, p = 0.000), subjective norms on visit intention (β = 0.181, t = 3.545, p = 0.000), PBC on visit intention (β = 0.147, t = 2.622, p = 0.009) and habit on visit intention (β = 0.190, t = 3.755, p = 0.000). The only negative but significant effect was of moral norms on subjective norms (β = −0.211, t = −2.742, p = 0.006). These results provided support for H1, H2, H3, H5, H6, H7 and H8. However, H4 was rejected. This negative relationship suggests that consumers’ moral obligations do not have an impact on their subjective norms regarding green hotel intentions. The results showed that consumers’ attitudes, subjective norms, PBC and habitual green behaviour provided a significant and positive explanation for their green hotel visit intention. Figure 2 below illustrates the research model with path coefficient and R2 estimates.
5. Discussion
This paper explored the link between spirituality, moral norms and habit with the TPB to explain green hotel visit intention. Drawing insights from the TPB, the study proposed a conceptual model that hypothesised that spirituality and moral norms have a significant influence on attitudes and consumers’ subjective norms in relation to green hotels. The study provides empirical support for a green hotel visit intention model that incorporates spirituality, moral norms and habit. The results provide an important contribution to the development of marketing programmes for the hospitality industry.
The findings of the study revealed that both spirituality and moral norms have a significant and positive effect on consumers’ attitudes towards green hotels. Together, these two constructs accounted for 39.2% of the variance in attitude towards green hotels. It must be noted, however, that although the results were positive and significant, the low variance implies that other factors may need to be incorporated into the model to increase its predictive ability. The findings on the significant positive effect of these two factors are supported by previous research (Pan et al., 2022; Rasanjalee, 2021; Saxena and Sharma, 2023). Between the two constructs, spirituality contributed a larger portion of the variance, suggesting that people’s faith-based beliefs are more significant in explaining attitudes than are their feelings of moral obligation. The findings that these two constructs, simultaneously contribute to attitudes, are unique to the current study; hence, they offer different perspectives from those in the existing literature in that they indicate the significance of these two factors in the development of attitudes.
Regarding subjective norms, the findings revealed that spirituality had a significant positive influence, while moral norms did not. The confirmation of H3 provides evidence of the importance of spirituality in informing subjective norms around green hotel intention. The two constructs together accounted for 29.5% of the variance in subjective norms. The findings revealed a negative relationship between moral norms and subjective norms. This finding was not anticipated, given that moral norms are often assumed to positively influence both attitudes and subjective norms. The relationships between spirituality and subjective norms, as well as between moral norms and subjective norms, have not been tested in the literature. Hence, the current study makes a novel contribution to the discussion on the influence of personal and socio-cultural factors influencing green hotel visit intention. The findings revealed that moral norms have a negative influence on subjective norms. The lack of literature to support the relationship between spirituality, moral norms and subjective norms indicates that research still needs to be conducted to provide empirical evidence for the proposed relationships. Studies on green hotels have incorporated the role of moral norms in shaping consumer behaviour, but most of these studies have considered it an immediate antecedent of intention rather than an antecedent of subjective norms.
The study’s findings revealed that all three TPB variables (attitudes, PBC and subjective norms), as well as habit, had a significant positive impact on intention to visit green hotels, explaining 73.8% of the variance in green hotel visit intention. The findings indicated that attitude accounted for the largest portion of the variance, followed by habit. The study’s findings on the impact of attitude on green hotel visit intention are consistent with the literature’s adopting the TPB to study green hotel visit intention (Agag and Colmekcioglu, 2020; Nimri et al., 2020; Pan et al., 2022; Wu et al., 2024). These findings support the literature on the importance of attitudes in shaping green behavioural intention. Empirical support for H6 and H7 provided by the study indicates that PBC and subjective norms also have a significant and positive effect on intention. These findings are also consistent with the literature on green hotel visit intention (Agag and Colmekcioglu, 2020; Eid et al., 2021; Fauzi et al., 2022; Mohammed et al., 2024; Shehawy et al., 2024). To enhance the explanatory power of the TPB variables on intention, the study also proposed H7, which posited that habitual green hotel behaviour is an additional predictor of intention. The study found empirical support for the hypothesis, which was consistent with the literature (Ghazali et al., 2018; Hasan, 2023b).
6. Theoretical contributions
Over the last two decades, scholars have shown interest in understanding the personal and socio-cultural factors influencing consumers’ pro-environmental behaviour (Maduku, 2024; Van Tonder et al., 2023; Xiao et al., 2023). In the hospitality industry, this interest has been particularly focused on green consumer behaviour in the lodging/accommodation sector (Haq et al., 2023; Legrand et al., 2024; Sharma et al., 2023). The current study set out to contribute to the discussion by offering a conceptual model integrating the TPB with spirituality, moral norms and habit. Even though the TPB has been widely adopted to study sustainable consumption intentions, the spirituality construct is still under-researched (Saleem et al., 2018; Saxena and Sharma, 2023).
The findings of the study indicated that the addition of spirituality, moral norms and habit to the TPB provided a superior rationalisation of consumers’ intention to stay in green hotels, beyond the variance explained by the standard TPB constructs. This extension provides a novel theoretical foundation for understanding how personal belief systems and ethical obligations influence environmentally conscious consumer behaviour. In addition, the findings highlighted the greater influence of spirituality over moral norms on attitudes and subjective norms. This finding suggests that consumers’ faith-based beliefs may serve as a stronger motivator for green hotel behaviour than moral obligations. The study also revealed a negative relationship between moral norms and subjective norms. This unexpected result challenges existing assumptions in the literature and opens up new lines of inquiry into the complexities of how moral obligations interact with social pressures to influence behaviour. Finally, the validated model explains a high variance in green hotel visit intention, which is more than the predictive power of the proposed research model for other studies (Agag and Colmekcioglu, 2020; Fauzi et al., 2022; Yeh et al., 2021). This indicates that the proposed model of the study is appropriate for the current context.
7. Practical contributions
The study set out to examine whether the TPB can be enhanced by adding spirituality, moral norms and habitual green behaviour as predictors of consumers’ intention to visit green hotels. The results indicated that consumers who are more spiritual are more likely to exhibit green hotel visit intention, which demonstrates the importance of spiritual values. The results revealed that consumers’ attitudes and subjective norms towards green hotels are strongly driven by their spirituality. Green hotels can therefore target spirituality in their green marketing strategies by creating campaigns that resonate with consumers’ spiritual and faith-based values. Green hotels can emphasise their establishments’ respect, promotion and support for individual differences in spirituality. Green establishments can promote environmental stewardship by framing sustainability as a moral responsibility which is tied to spiritual beliefs. In addition, marketers involved in green marketing can avoid messaging that may be offensive to people who are spiritually inclined. For example, advertisements should avoid using offensive language and rooms should not have any texts or symbols that may be offensive.
The findings of the study indicated that the three TPB constructs are all positively related to green hotel visit intention. In this regard, marketers can develop effective marketing programmes that influence green consumption intention by emphasising certain benefits. For instance, given the role of subjective norms in influencing green hotel visit intention, marketers can tailor their programmes to emphasise how the patronage of green hotels will enhance the customers’ image in their reference groups. In addition to the study’s confirming the role of the three TPB variables in influencing green hotel visit intention, the study’s findings also revealed that the addition of habit as an additional construct to the three TPB variables led to a relatively high predictive power of the proposed model. This highlights the importance of habit in green hotel visit intention. Given the findings that indicated the importance of habit, green hotel marketing strategies should focus not only on attitudes and social influences but also on fostering habitual green behaviours. Through offering loyalty programs, incentives for repeat bookings and providing eco-friendly amenities, hotels can foster habitual sustainable behaviour. Research has shown that habits are better than intention in predicting behaviour (Ghazali et al., 2018) therefore, marketers in the hospitality industry can intensify marketing campaigns that promote green habits within their establishments.
8. Limitations of the study
This study encountered several limitations, which also present opportunities for future research. The primary limitation was the sample size. Although a larger sample was initially intended, the final sample of 240 participants was constrained by the difficulty in accessing patrons of eco-friendly hotels. Secondly, the study measured intention rather than actual behaviour, which may limit the insights into real-world actions. Thirdly, the focus was on the South African market, which, while potentially limiting, offers valuable avenues for cross-cultural exploration in future research. Finally, the proposed research framework did not consider emotional and affective processes, which are key components of green consumption behaviour and warrant further investigation.
9. Avenues for future research
Given the study’s limited sample size, future research could benefit from expanding the population to enhance the generalisability of the findings. Including patrons of green, eco-friendly and nature-focused hotels could broaden the study’s scope and increase the sample size. Secondly, since scholars have acknowledged the intention–behaviour gap and questioned whether intention is a reliable predictor of behaviour (Pilgreen et al., 2024; Sousa et al., 2025), future studies should explore actual green hotel visitation behaviour to offer a more comprehensive understanding of the factors influencing sustainable tourism practices. Thirdly, the extended TPB model could be applied to other markets that are socio-culturally distinct from South Africa, with potential cross-cultural implications for promoting green hotels. Our extended TPB provides a robust framework for exploring other aspects of human behaviour in different contexts such as different research domains and across various industries. Finally, as the current study did not consider affective or emotional factors, future research could extend the TPB model by incorporating these constructs.
10. Conclusions
This study aimed to identify the key social and cultural factors influencing the intention to visit green hotels, providing deeper insight into the motivations driving green consumer behaviour. A structural model was developed to explore the theoretical and empirical relationships between the constructs of the TPB and socio-cultural elements, such as spirituality and moral norms. The findings contribute to the ongoing discussion about the personal and social determinants of pro-environmental behaviour, particularly in relation to consumers’ behavioural intentions towards green services. From a personal standpoint, the study demonstrates that spirituality impacts attitudes and subjective norms, ultimately shaping the intention to stay at green hotels. Likewise, from a socio-cultural perspective, the results show that moral norms influence attitudes, with green hotel visitation intentions as the outcome. Furthermore, the study suggests that habitual green behaviour positively affects consumers’ intentions to visit green hotels. In summary, the findings highlight that individuals’ belief in a higher power, coupled with their personal sense of moral obligation, significantly shapes their green attitudes, while the habitual use of green services strengthens their intention to choose green hotels.
References
Further reading
Appendix
Construct measurement items
| Spirituality | |
| SP1 | I feel god’s presence |
| SP2 | I experience a connection to all life |
| SP3 | I feel a sense of selflessness towards others |
| SP4 | I feel deep inner peace and harmony |
| Moral norms | |
| MN1 | I believe I have a moral obligation to protect the environment |
| MN2 | It is in line with my principles to protect the environment |
| MN3 | I have a responsibility to protect the environment |
| MN4 | My personal values encourage me to protect the environment |
| Attitude | |
| ATT1 | For me, staying at a green hotel while travelling is a good idea |
| ATT2 | For me, staying at a green hotel while travelling is desirable |
| ATT3 | For me, staying at a green hotel while travelling is unpleasant |
| ATT4 | For me, staying at a green hotel while travelling is wise |
| ATT5 | For me, staying at a green hotel while travelling is unfavourable |
| Subjective norms | |
| SN1 | People important to me think that I should stay at a green hotel |
| SN2 | Most people who are important to me would want me to choose green hotels while travelling |
| SN3 | People whose opinions I value would want me to stay at green hotels |
| Perceived behavioural control | |
| PBC1 | To stay or not to stay at a green hotel while travelling is completely up to me |
| PBC2 | I am confident that I can stay at green hotels if I want to do so |
| PBC3 | I don’t have the resources, time and opportunity to stay at green hotels while travelling |
| Habit | |
| HB1 | Staying at a green hotel has become a habit for me |
| HB2 | I am addicted to staying at green hotels |
| HB3 | I must use green hotels during my holidays |
| HB4 | Using green hotels has become natural for me |
| Visit intention | |
| VI1 | I am willing to stay at a green hotel while travelling |
| VI2 | I will make an effort to stay at a green hotel when travelling |
| VI3 | I plan to stay at a green hotel for my next vacation |
| VI4 | I intend to use green hotels whenever I travel |
| Spirituality | |
| SP1 | I feel god’s presence |
| SP2 | I experience a connection to all life |
| SP3 | I feel a sense of selflessness towards others |
| SP4 | I feel deep inner peace and harmony |
| Moral norms | |
| MN1 | I believe I have a moral obligation to protect the environment |
| MN2 | It is in line with my principles to protect the environment |
| MN3 | I have a responsibility to protect the environment |
| MN4 | My personal values encourage me to protect the environment |
| Attitude | |
| ATT1 | For me, staying at a green hotel while travelling is a good idea |
| ATT2 | For me, staying at a green hotel while travelling is desirable |
| ATT3 | For me, staying at a green hotel while travelling is unpleasant |
| ATT4 | For me, staying at a green hotel while travelling is wise |
| ATT5 | For me, staying at a green hotel while travelling is unfavourable |
| Subjective norms | |
| SN1 | People important to me think that I should stay at a green hotel |
| SN2 | Most people who are important to me would want me to choose green hotels while travelling |
| SN3 | People whose opinions I value would want me to stay at green hotels |
| Perceived behavioural control | |
| PBC1 | To stay or not to stay at a green hotel while travelling is completely up to me |
| PBC2 | I am confident that I can stay at green hotels if I want to do so |
| PBC3 | I don’t have the resources, time and opportunity to stay at green hotels while travelling |
| Habit | |
| HB1 | Staying at a green hotel has become a habit for me |
| HB2 | I am addicted to staying at green hotels |
| HB3 | I must use green hotels during my holidays |
| HB4 | Using green hotels has become natural for me |
| Visit intention | |
| VI1 | I am willing to stay at a green hotel while travelling |
| VI2 | I will make an effort to stay at a green hotel when travelling |
| VI3 | I plan to stay at a green hotel for my next vacation |
| VI4 | I intend to use green hotels whenever I travel |


