The impacts of macro,meso,and micro antecedents on environmentally responsible behavior on tourism

Abstract

This study explored antecedents to tourist environmentally responsible behavior (ERB). An integrated model was constructed and tested using an analytical framework that categorized antecedents of ERB into macro (cultural factors: collectivism, biospheric value), meso (destination factors: environmental quality, environmental policy), and micro (personal factors: environmental knowledge, environmental awareness) levels with environmental attitude positioned as a mediating construct. Findings from Chinese tourists (n = 524) suggested that the investigated factors directly impact environmental attitude, which then act to strengthen ERB. Findings suggested that environmental attitude acts to partially (collectivism, environmental quality, environmental policy) or fully (biospheric values, environmental knowledge and awareness) mediate antecedent relationships with ERB.

Keywords

Collectivism biospheric value environmental quality environmental policy environmental knowledge environmental awareness environmental attitude environmentally responsible behavior

Introduction

The earth's environment continues to face severe challenges including air pollution, ecosystem degradation, and global warming (UN Environment Programme, 2022). These environmental issues pose serious risks to the health and well-being of humanity and the planet (Xu et al., 2023). Tourism, as a substantial leisure activity, has been identified as a key contributor to detrimental environmental impacts through practices such as the utilization of environmentally unfriendly modes of transportation (e.g., air travel, private vehicles), overuse of accommodation resources (e.g., water and energy wasting), increased pressure on natural resources from sightseeing activities (e.g., littering, noise pollution), and shopping (e.g., overconsumption, disposable products consumption) (He et al., 2022; Li et al., 2023a, 2023b; Qiu et al., 2023). Environmentally responsible behavior (ERB) among tourists, defined as actions “to minimize potentially adverse environmental effects and devote themselves to environmental protection during their tourism experience” (Su and Swanson, 2017: 311), can contribute to resource conservation, environmental protection, landscape preservation, sustainable tourism development, and enhanced tourist experiences (Gupta et al., 2022; Wang et al., 2022). Collectively, promoting ERB among tourists has the potential to significantly reduce the detrimental environmental impacts associated with the tourism industry (He et al., 2022). So, what leads to tourists adopting ERBs? This is a complex question that requires an understanding of the relationship of multiple dimensions.

Prior studies have examined drivers of tourist ERB, including tourist-related factors (e.g., values, awareness, emotions), host-related factors (e.g., service quality, sincerity), and tourist–host interaction factors (e.g., cocreation) (Chiu et al., 2014; Confente and Scarpi, 2021; Gupta et al., 2022; He et al., 2022; Kim and Thapa, 2018; Li et al., 2021; Qiu et al., 2023; Tu and Ma, 2022; Wang et al., 2022). Some researchers have looked at tourist ERB antecedents at the microlevel that pertain to individual characteristics and preferences (Akaka et al., 2022; Baumann et al., 2019; Li et al., 2023a; Winzar et al., 2022). Other studies have explored the influence of broader factors on tourist ERB, including meso- (e.g., environmental destination social responsibility, interpretation cues, destination image) and macrolevel factors (e.g., weather patterns, strengthening regulations, air pollution) (e.g., He et al., 2022; Li et al., 2023a; Liu et al., 2024). The present study investigates the collective impact of macro-, meso-, and microlevel factors on tourist ERB by developing and testing a model based on Li et al.'s (2023a) analytical framework. Macrolevel factors refer to the broad societal forces that shape individual behavior, such as culture (Akaka et al., 2022; Baumann et al., 2019; Leonidou et al., 2010) and values (Han, 2015). Mesolevel factors involve the intermediate levels that act to bridge the gap between individual (i.e., microlevel) and societal (i.e., macrolevel) factors (Cattani et al., 2017). Mesolevel factors would include the destination-based elements (He et al., 2018; Su and Swanson, 2017; Su et al., 2024), such as destination environmental quality and associated policies (Li et al., 2021; Liu et al., 2019).

Drawing on previous literature, two factors for each level are investigated: collectivism and biospheric value for the macrolevel, environmental quality and environmental policy for the mesolevel, and environmental knowledge and environmental awareness for the microlevel. In addition, the role of environmental attitude is examined as a mediator between the investigated antecedents and tourist ERB (Chaihanchanchai and Anantachart, 2023). Environmental attitude is defined as a favorable or unfavorable evaluation or feeling toward environmental protection (Chaihanchanchai and Anantachart, 2023; Lin and Lee, 2020).

The next section of the paper provides a brief literature review and presentation of the hypotheses which are used to construct a theoretical model. This is followed by the research methodology and results. The paper concludes with a discussion of the findings, including theoretical and managerial implications, finishing with study limitations and future research directions.

Literature review and hypotheses development

The macro–meso–micro analytical framework

The macro–meso–micro analytical framework is useful for the systematic exploration of the causes of a phenomenon (Cattani et al., 2017; Li et al., 2023a; Winzar et al., 2022). This framework facilitates a comprehensive understanding of complex behaviors as it considers how factors at various levels act to influence individual actions (Winzar et al., 2022). For instance, Winzar et al. (2022) used this framework to examine the process of practice diffusion, while Gao et al. (2022) employed it to better understand the underlying mechanisms of destination networks.

The macrolevel includes big picture considerations (Winzar et al., 2022) such as social, cultural, and institutional factors that shape consumption patterns (Cattani et al., 2017; Li et al., 2023a). The mesolevel involves investigating interactions and influences among consumers, marketers, and intermediaries in the marketplace at a corporate/organizational level (Cattani et al., 2017; Li et al., 2023a). The microlevel is more focused on the individual and seeks to understand the psychological, cognitive, and emotional processes that underlie behaviors (Cattani et al., 2017; Li et al., 2023a).

Macrolevel cultural factors

As previously noted, macrolevel factors are broad societal forces that influence individual behavior, culture being a key element thereof (Akaka et al., 2022; Baumann et al., 2019; Leonidou et al., 2010). Culture acts to shape the beliefs and values of a society and contributes to the dominant social paradigm (Kilbourne and Pickett, 2008; Kilbourne et al., 2002). As such, culture has been reported to directly affect the likelihood of an individual engaging in environmentally related behaviors (Khan and Fatma, 2021).

Although there are a number of cultural factors that could be investigated, two that have previously been identified as motivating people to engage in environmentally positive behaviors are collectivism (Jang et al., 2015) and biospheric value (Gupta et al., 2022; Lee et al., 2021; Lee and Jan, 2015). Collectivism emphasizes the strong connection between individuals and their extended family and society (Rojas-Méndez and Davies, 2024) and fosters interdependence, group success, and belonging (Hofstede, 2011). Biospheric value reflects the importance of the environment to one's life (Lee et al., 2021) and serves as a guiding principle for individuals’ beliefs about the well-being of the eco-system (Gupta et al., 2022). As such, this study focuses on the macrolevel cultural factors of collectivism and biospheric value. Collectivism is discussed in more detail next.

Collectivism

Collectivism is a cultural dimension that values group harmony and cohesion over individual distinction and autonomy (Rojas-Méndez and Davies, 2024). In contrast, individualism emphasizes personal achievements and goals that set one apart from others (Khan and Fatma, 2021). Collectivists are more likely to care for the welfare of their in-group members and to cooperate with them to achieve common objectives (Kim and Choi, 2005). They also tend to be more concerned about their social roles and obligations, as well as the impact of their actions on society at large (Laroche et al., 2001). For example, as argued by McCarty and Shrum (2001), a collectivistic orientation often leads individuals to forego personal motivations (e.g., the inconvenience of recycling) in favor of actions benefitting the collective good (e.g., keeping the shared environment clean). Therefore, collectivist cultures may appreciate ERB more because they understand how it benefits the collective welfare. It is predicted that more collectivistic individuals will view ERB as a way to protect and enhance the tourism environment, which will result in more favorable attitudes and behaviors toward the environment.

H1: Collectivism positively affects tourist environmental attitude.

H7: Collectivism positively affects tourist ERB.

Biospheric value

Values represent a culture's fundamental beliefs, which can act to direct attitudes and motivate actions (Stern, 2000; Zhang et al., 2014). A popular classification of values is that of De Groot and Steg (2007, 2008), which divides values into three dimensions: biospheric (i.e., the importance ascribed to the welfare of the ecosystem), egocentric (i.e., the importance ascribed to the welfare of the individual), and altruistic (i.e., the importance ascribed to the welfare of another). Biospheric value reflects the importance of nature and the environment to one's life and guides one's actions toward their well-being (Lee et al., 2021). Tourists with stronger biospheric values have been reported to be more attentive to the environment (Gupta et al., 2022) and more likely to adopt eco-friendly behaviors, such as recycling, using green transportation, and engaging in energy saving activities (Lee and Jan, 2015; Schultz et al., 2005). Tourists with strong biospheric values also tend to express more environmental concern (Stern, 2000; Zhang et al., 2014) and engage in proenvironmental actions (Han, 2015).

H2: Biospheric value positively affects tourist environmental attitude.

H8: Biospheric value positively affects tourist ERB.

Mesolevel destination factors

Mesolevel factors fall between macrosocietal and microindividual elements (Cattani et al., 2017). In a tourism setting, the destination constitutes a salient mesolevel context as it represents the place where tourists engage in activities divergent from home environments (He et al., 2018; Su and Swanson, 2017; Su et al., 2024). Relevant to this research, destination characteristics have been reported to impact tourist ERB (He et al., 2022; Kim and Thapa, 2018; Liu et al., 2019; Su and Swanson, 2017). While multiple destination attributes can shape tourist ERB, extant research has concentrated on the effects of destination social responsibility (He et al., 2022; Lee et al., 2021; Su and Swanson, 2017), service quality (He et al., 2022), tourist-destination relationship quality (He et al., 2018), tourist-destination interactions (Tu and Ma, 2022; Wang et al., 2022), and destination source credibility (Qiu et al., 2022). Destinations serve as the primary loci of tourist activities (Su et al., 2024), and it is suggested here that additional destination factors need to be investigated to improve our understanding of tourists performing environmentally responsible actions.

The broken windows theory (Wilson and Kelling, 1982) postulates that environmental cues convey normative expectations for behavior in a given setting (Lang et al., 2010). In a tourism context, destination environmental conditions largely hinge on two key factors: environmental quality and policy implementation (Birdir et al., 2013; Zhang et al., 2014). Environmental quality shapes tourists’ holistic perceptions of the destination's eco-friendliness, while policies signal the priority placed on environmental protection (Liu et al., 2019). The broken windows premise suggests that greater perceived environmental quality and strong policy signals will act to discourage tourist actions that result in environmental damage by conveying that such behaviors violate norms (Liu et al., 2019). Building on this theoretical rationale, the present study examines the influence of perceived destination environmental quality and policy on tourist ERB.

Environmental quality

The environmental conditions of a place will send contextual signals to visitors that indicate what are acceptable and normative behaviors (Lang et al., 2010). Thus, the quality of the environment may affect what an individual considers acceptable behavior. For example, Liu et al. (2019) reported that higher levels of environmental quality as perceived by tourists can act to generate a more positive attitude toward protecting the environment.

The environment can also act to enhance the value an individual perceives they are receiving at a destination, which leads them to engage with the destination in an environmentally friendly manner (Liu et al., 2019; Scannell and Gifford, 2010). Destinations perceived to be environmentally pleasant are more likely to be valued and safeguarded (Salnikova et al., 2022; Sokolova et al., 2023; Uzzell et al., 2002). Based on the provided discussion, the following hypotheses are proposed:

H3: Environmental quality positively affects tourist environmental attitude.

H9: Environmental quality positively affects tourist ERB.

Environmental policy

Environmental policy represents a strategic commitment to manage the relationship between the natural environment and human activity in a mutually beneficial manner (Schönherr et al., 2023; Sharma et al., 2021). Such policies encapsulate the environmental principles, rationales, and philosophies that guide a destination's sustainability agenda (Kathuria et al., 2020). For example, as an overarching framework for destination eco-practices, environmental policies can drive improvements in local energy usage and waste management (Parpairi, 2017) while also shaping individuals’ energy conservation behaviors (Yue et al., 2013).

Environmental policies can serve as motivational instruments that strengthen proenvironmental attitudes and ecological behavioral intentions among tourists (Wan et al., 2014). By signaling a destination's prioritization of sustainability, environmental policies are theorized to increase tourist motivation to act in accordance with the destination's green initiatives. Based on prior findings, it is suggested here that when tourists are aware of a destination's environmental policies, they will develop more positive environmental attitudes and greater intentions to engage in ERBs during their visit.

H4: Environmental policy positively affects tourist environmental attitude.

H10: Environmental policy positively affects tourist ERB.

Microlevel personal factors

In a tourism context, tourists’ personal (i.e., microlevel) characteristics help to determine their ERBs (He et al., 2022; Su and Swanson, 2017; Wu et al., 2022; Xiong et al., 2023). Existing literature has explored relationships between ERB and personal factors including environmental concern, norms, sensitivity, and place attachment (Cheng and Wu, 2015; Confente and Scarpi, 2021; Lin and Lee, 2020; Wu et al., 2022). In response to calls for additional investigation of microfactors (Xiong et al., 2023), the present study focuses specifically on environmental knowledge and awareness. Both have been reported to be increasing in China due to social media's coverage of ecological issues (Shah et al., 2021), and they have been previously identified as potential predictors of ERBs (Cheng and Wu, 2015). Theoretically, knowledge and awareness fundamentally shape individuals’ attitudes and behaviors toward an object (Shah et al., 2021). Building on this practical and theoretical rationale, the current study examines the influence of tourists’ environmental knowledge and awareness on their environmental attitudes and engagement in ERB.

Environmental knowledge

Environmental knowledge refers to a general understanding of facts, concepts, and associations related to ecosystems (Shah et al., 2021). Compared to less informed individuals, those possessing greater environmental knowledge tend to participate more actively in positive environmentally related behaviors (Cheng and Wu, 2015; Llewellyn, 2021; Shah et al., 2021). Persons with higher environmental knowledge feel more confident in and are more likely to value, protect, and express concern for the environment (Cheng and Wu, 2015). For instance, consumers more informed about eco-issues have shown a greater willingness to purchase green products (Chaihanchanchai and Anantachart, 2023). Similarly, tourists who possess greater environmental knowledge have been found to be more cognizant of the significance of sustainability, which is theorized to engender more positive feelings and thoughts toward environmental protection as well as higher engagement in ERBs during travel (Levine and Strube, 2012; Liu et al., 2020). Formally:

H5: Environmental knowledge positively affects tourist environmental attitude.

H11: Environmental knowledge positively affects tourist ERB.

Environmental awareness

Environmental awareness is the degree to which tourists understand and appreciate environmental issues and their implications for themselves and others (Blok et al., 2015). People who are more aware of environmental threats and the associated potentially negative personal consequences tend to care more about the environment and act more responsibly to preserve it (Blok et al., 2015; Darvishmotevali and Altinay, 2022). Consequently, greater environmental awareness leads to stronger proenvironmental commitment (Ahmad et al., 2020), resulting in increased purchase intentions toward, and willingness to pay for, green products (Xu et al., 2020). In a tourism context, it has been suggested that greater (lesser) environmental awareness can foster more (less) positive attitudes toward sustainability and increased (reduced) willingness to engage in ERBs (Confente and Scarpi, 2021; Shah et al., 2021). Thus, it is hypothesized that:

H6: Environmental awareness positively affects tourist environmental attitude.

H12: Environmental awareness positively affects tourist ERB.

The impact of environmental attitude on ERB

According to cognitive consistency theory, individuals are motivated to avoid inconsistencies (Chaxel and Han, 2018). Inconsistencies create tension, and individuals seek congruence between their attitudes and subsequent behaviors as a way to reduce or eliminate this tension (Joosten et al., 2014; Su et al., 2024). Therefore, when someone cares about the natural environment, they should be more likely to adopt behaviors that protect that environment. That is, a person with a positive environmental attitude would be more likely to act in accordance with that attitude to increase consistency and reduce inconsistency (Chaihanchanchai and Anantachart, 2023; Chen and Tung, 2014; Lin and Lee, 2020). Thus, a tourist with a proenvironmental attitude would have a higher propensity to purchase green products, look for recyclable goods, use public transport, and reduce waste (e.g., Chaihanchanchai and Anantachart, 2023; Chen and Tung, 2014; Han, 2015; Lin and Lee, 2020). More formally, we hypothesize:

H13: Environmental attitude positively affects tourist ERB.

Methodology

Participants

Visitors (n = 700) to Yuelu Mountain, Changsha, China, were approached when exiting multiple sites (Aiwan Pavilion, Yuelu Academy, Sightseeing Corridor, Southeast Gate, Ancient Lushan Temple, Qingfeng Gorge) at the destination and asked to take part in the study. A team of 15 undergraduate students, trained as survey investigators, were responsible for issuing and collecting questionnaires under the supervision of the primary investigators. The survey collectors were divided into three equal-sized teams with each team assigned to one of the identified sites on a rotating schedule at different times of the day, and days of the week, during a four-week period. All adult visitors were approached during the data collection periods so that every individual had an equal chance of participating. Potential participants were asked to verify their status as domestic adult Chinese tourists, and qualified individuals were provided with a verbal overview of the survey before being solicited to participate. Upon agreeing to complete the self-administered questionnaire, respondents were assured of their right to withdraw at any time and then provided with a hard copy by the field researchers. The survey collectors were trained to be friendly, while maintaining an objective and neutral stance throughout the recruitment process, refraining from persuasion or influence tactics. Notably, participants were informed that the questionnaire was anonymous and that the collected data would be used solely for an academic research project with no commercial sponsorship. The collection procedures were designed to collect data that was as unbiased and representative as possible to obtain accurate and generalizable results.

Yuelu Mountain was chosen as the data collection site for three key reasons. First, as a famous and heavily visited national tourist destination, Yuelu Mountain visitors provided access to a potentially geographically diverse national sample. Second, Yuelu Mountain is a renowned scenic area that maintains extensive environmental protection efforts through onsite regulations which are supported by strong promotional messaging. The location provided an apt setting that aligned with the study's focus on tourist ERB. Third, Yuelu Mountain encompasses a diverse array of natural landscapes and cultural heritage sites. These features are emblematic of many globally recognized tourist attractions, thereby providing a basis for the extrapolation of these findings to other tourist demographics across various destinations.

Of the 700 distributed questionnaires, 626 were retrieved (i.e., 74 were not returned by potential respondents), and 102 were incomplete and discarded. The remaining 524 questionnaires were used for subsequent analysis. The sample was equally distributed by gender and characterized by somewhat younger tourists (74.3% aged 18 to 44 years) with higher-level educations (65.8% with an undergraduate/associate degree). Table 1 provides additional details regarding the sample characteristics.

Table 1.

Characteristics of the sample.

	n	%		n	%
Age in years			Monthly Income
18 to 24	210	40.1	Less than 2000￥	134	25.6
25 to 44	179	34.2	2000 to 2999￥	72	13.7
45 to 64	105	20.0	3000 to 3999￥	67	12.8
65 or older	30	5.7	4000 to 4999￥	95	18.1
			5000￥ or more	156	29.8
Gender			Level of education
Male	262	50.0	Less than high school	24	4.6
Female	262	50.0	High school/technical school	83	15.8
			Undergraduate/associate degree	345	65.8
			Postgraduate degree	72	13.7

Measures

Collectivism was measured using four items adopted from Leonidou et al. (2010), biospheric value was assessed with four items from Han (2015), and the environmental quality scale utilized four items adopted from Su et al. (2019). The three-item environmental policy and four-item environmental attitude scales were adopted from Yu et al. (2015) and Song et al. (2012), respectively. Environmental knowledge was measured using three items (Cheng and Wu, 2015), environmental awareness with five items (Blok et al., 2015), and ERB used the six-item scale of Su et al. (2020). All scale items (see Table 2) included a seven-point Likert-type response option (1 = strongly disagree, 7 = strongly agree).

Table 2.

Measurement model results.

Constructs and scale items	Standard loading	t-statistic	CR	AVE	Cronbach's alpha
Collectivism
I work hard for the goals of a group, even if it does not result in personal recognition	.901	26.099	.914	.728	.913
I do what is good for most of the people in the group, even if it means that I will receive less	.899	25.996
I readily help others in need of help	.825	22.649
I am an active participant in group activities	.781	20.887
Biospheric value
I will prevent pollution	.865	24.613	.938	.792	.937
I will respect the earth	.933	27.952
I will be in unity with nature	.917	27.143
I will protect the environment	.843	23.616
Environmental quality
Overall, the natural environmental of this destination is comfortable	.832	22.824	.909	.713	.907
This destination has less garbage, is clean, and the sanitary conditions are good	.836	23.023
This destination has clear air and water, and high vegetation coverage	.893	25.556
The landscape layout, architecture of this destination is in harmony with the natural environment	.816	22.152
Environmental policy
This destination has established an effective environmental protection system and environmental interpretation system	.856	23.992	.924	.801	.923
The promotion of environmental education at this destination enables tourists to abide by environmental protection regulations	.921	26.959
This destination has developed environmental protection regulations to strictly manage tourists’ environmentally related behaviors	.908	26.321
Environmental knowledge
I know that the maintenance of ecological balance will enhance sustainable development	.889	25.459	.920	.794	.920
I know that for the next generation, we should protect the natural resources	.897	25.805
I know that the maintenance of diversity of species will balance the ecology	.887	25.338
Environmental awareness
Environmental pollution affects my health	.889	25.559	.918	.690	.917
Environmental problems are a risk for the future of my children	.904	26.289
I worry about environmental problems	.767	20.345
Environmental problems have consequences for my life	.817	22.351
People who do not take the environment into account try to escape their responsibility	.771	20.519
Environmental attitude
I think protecting the environment is a positive behavior	.872	24.950	.931	.772	.929
I think protecting the environment is a valuable behavior	.939	28.247
I think protecting the environment is a beneficial behavior	.886	25.595
I think protecting the environment is a necessary behavior	.814	22.360
Environmentally responsible behavior
I comply with the legal ways not to destroy the destination's environment	.782	20.954	.923	.666	.922
I report to the destination administration any environmental pollution or destruction	.824	22.680
When I see garbage and tree branches, I will make an effort to put them in the trash can	.845	23.600
If there are environmental clean-up activities, I am willing to attend	.870	24.728
I would convince my travel companions, if any, to protect the natural environment on the destination	.876	24.994
I try not to disrupt the fauna and flora (animals and plants) during my travel	.686	17.461

AVE: average variance extracted.

Goodness-of-fit: χ²/df = 2.775, RMSEA = .058, GFI = .864, AGFI = .837, NFI = .917, RFI = .906, IFI = .946, TLI = .938, CFI = .945.

To verify the suitability of the questionnaire items, three academics specializing in hospitality and tourism research and four tourist destination managers reviewed the questionnaire prior to distribution. The scales were also pretested with Chinese undergraduate hospitality majors (n = 40). Pretest results demonstrated acceptable reliability, convergent validity, and discriminant validity for all measurement scales. Cronbach's alpha values ranged from .923 to .966, exceeding the threshold for adequate internal consistency (Fornell and Larcker, 1981). Composite reliability varied from .926 to .972, also indicating good reliability. Item factor loadings were all above .626 and significant at p < .001, with average variance extracted (AVE) per construct surpassing .500 (range: .723 to .896), suggesting adequate convergent validity (Anderson and Gerbing, 1988; Fornell and Larcker, 1981; Hair et al., 1998). Moreover, the square root of AVEs (range: .850 to .930) exceeded the interconstruct correlations (range: .096 to .762), providing evidence of discriminant validity (Fornell and Larcker, 1981).

Analysis

Descriptive analysis was conducted using SPSS 21.0 with the latent constructs analyzed using structural equation modeling (SEM). Harmon's one factor test was utilized to test for common method variance (Podsakoff et al., 2003). Eight factors were extracted with eigenvalues greater than 1. The explained variance was 80.436%.

Measurement model

Based on the model evaluation criteria suggested by Hu and Bentler (1999), the fit indices of the measurement model were acceptable (χ²/df = 2.775; RMSEA = .058; NFI = .917; RFI = .906; IFI = .946; TLI = .938; CFI = .945; GFI = .864; AGFI = .837). Cronbach's alphas ranged from .907 to .937, and the composite reliabilities ranged from .909 to .938. See Table 2 for measurement model results. Convergent validity was satisfied with item factor loadings exceeding .686 and significant at .001, and AVE for all the constructs were above .500 (range: .666 to .801) (Anderson and Gerbing, 1988; Fornell and Larcker, 1981; Hair et al., 1998). Findings indicated a sizeable amount of the variance being explained by the constructs, suggesting convergent validity of the measures. As provided in Table 3, correlation coefficients ranged from .059 to .598, and the square root of the AVE ranged from .816 to .895. According to the criteria provided by Fornell and Larcker (1981), discriminant validity was satisfied.

Table 3.

Correlation coefficients and average variance extracted (AVE).

	1	2	3	4	5	6	7	8
1. Collectivism	.853
2. Biospheric value	.373^a	.891
3. Environmental quality	.529^a	.377^a	.845
4. Environmental policy	.358^a	.189^a	.480^a	.895
5. Environmental knowledge	.402^a	.535^a	.280^a	.059	.891
6. Environmental awareness	.465^a	.420^a	.397^a	.258^a	.490^a	.831
7. Environmental attitude	.522^a	.566^a	.511^a	.197^a	.598^a	.560^a	.879
8. Environmentally responsible behavior	.510^a	.330^a	.548^a	.400^a	.297^a	.357^a	.464^a	.816

Note: AVE values are provided on the diagonal; interconstruct correlations provided off the diagonal.

p = .001.

Structural model

The proposed model's overall fit to the data was satisfactory (χ²/df = 2.753, RMSEA = .058, GFI = .864, AGFI = .837, NFI = .917, RFI = .906, IFI = .946, TLI = .938, CFI = .945). The effect of collectivism (λ₇₁ = .195, p < .001), biospheric value (λ₇₂ = .207, p < .001), environmental quality (λ₇₃ = .222, p < .001), environmental policy (λ₇₄ = .083, p < .05), environmental knowledge (λ₇₅ = .259, p < .001), and environmental awareness (λ₇₆ = .188, p < .001) on environmental attitude were all statistically significant. H1–H6 were supported (see Table 4).

Table 4.

Structural model evaluation indices and hypothesis testing outcomes.

Hypothesis	Relationship	Label of path	Standard path loadings	T-value	Standard error	Hypothesis supported
H1	Collectivism → environmental attitude	λ₇₁	.195^b	4.458	.040	Yes
H2	Biospheric value → environmental attitude	λ₇₂	.207^b	5.003	.045	Yes
H3	Environmental quality → environmental attitude	λ₇₃	.222^b	4.953	.042	Yes
H4	Environmental policy → environmental attitude	λ₇₄	.083^a	2.150	.024	Yes
H5	Environmental knowledge → environmental attitude	λ₇₅	.259^b	5.856	.046	Yes
H6	Environmental awareness → environmental attitude	λ₇₆	.188^b	4.407	.044	Yes
H7	Collectivism → ERB	λ₈₁	.207^b	3.923	.051	Yes
H8	Biospheric value → ERB	λ₈₂	.020	0.396	.057	No
H9	Environmental quality → ERB	λ₈₃	.266^b	4.821	.055	Yes
H10	Environmental policy → ERB	λ₈₄	.161^b	3.502	.031	Yes
H11	Environmental knowledge → ERB	λ₈₅	.025	0.462	.059	No
H12	Environmental awareness → ERB	λ₈₆	.007	0.147	.055	No
H13	Environmental attitude → ERB	β₈₇	.153^a	2.481	.065	Yes

Note: ERB: environmentally responsible behavior.

p < .05.

p < .001.

Collectivism (λ₈₁ = .207, p < .001), environmental quality (λ₈₃ = .266, p < .001), and environmental policy (λ₈₄ = .161, p < .001) were found to positively impact tourist ERB, supporting H7, H9, and H10. The path coefficients of biospheric value (λ₈₂ = .020, p > .05), environmental knowledge (λ₈₅ = .025, p > .05), and environmental awareness (λ₈₆ = .007, p > .05) to tourist ERB were not significant. H8, H11, and H12 were not confirmed. Environmental attitude was found to significantly impact ERB (β₈₇ = .153, p < .05). H13 was supported.

The tested model (see Figure 1) explained 58.3% and 40.3% of the variance of environmental attitude and ERB, respectively. According to Cohen (1988), these findings indicate that the model demonstrated good explanatory power and that the investigated relationships were stable.

Direct, indirect, and total effects of variables in the model

The direct, indirect, and total effects are provided in Table 5. Findings suggest that environmental quality had the greatest direct effect on ERB, followed by collectivism and environmental policy. Environmental knowledge had the greatest indirect effect on ERB through environmental attitude. Generally, environmental attitude acted to partially, or fully, mediate the investigated antecedents on ERB.

Table 5.

The direct, indirect, and total effects for the relationships between variables.

Relationships between variables	Direct effects	Indirect effects	Total effects
Collectivism → environmental attitude	.195^b	–	.195^b
Collectivism → ERB	.207^b	.030^a	.237^b
Biospheric value → environmental attitude	.207^b	–	.207^b
Biospheric value → ERB	.020	.032^a	.051^a
Environmental quality → environmental attitude	.222^b	–	.222^b
Environmental quality → ERB	.266^b	.034^a	.300^b
Environmental policy → environmental attitude	.083^a	–	.083^a
Environmental policy → ERB	.161^b	.013^a	.174^b
Environmental knowledge → environmental attitude	.259^b	–	.259^b
Environmental knowledge → ERB	.025	.040^a	.064^a
Environmental awareness → environmental attitude	.188^b	–	.188^b
Environmental awareness → ERB	.007	.029^a	.036^a
Environmental attitude → ERB	.153^a	–	.153^a

Note: ERB: environmentally responsible behavior.

p < .05.

p < .01.

Discussion

Conclusions

The present study proposed an integrated model that investigated the collective impact of macro-, meso-, and microlevel factors on tourist ERB. A survey of Chinese visitors to a popular historically and environmentally important destination was conducted. Utilizing SEM analysis, the findings indicated that macrolevel cultural factors (collectivism, biospheric value), mesolevel destination factors (environmental quality, environmental policy), and microlevel personal factors (environmental knowledge, environmental awareness) can directly or indirectly enhance tourist ERB. Specifically, collectivism, environmental quality, and environmental policy directly fostered both environmental attitude and tourist ERB. Biospheric value, environmental knowledge, and environmental awareness were all found to indirectly improve tourist ERB through the mediation of environmental attitude. These findings contribute to a deeper understanding of the antecedents and underlying mechanisms influencing tourist ERB and provide valuable insights for developing targeted strategies to promote tourist ERB.

Theoretical contributions

This study makes three theoretical contributions to the literature on ERB. First, antecedents of tourist ERB at the macro (cultural), meso (destination), and micro (personal) levels were examined based on the analytical framework proposed by Li et al. (2023a). Prior studies have explored a variety of tourist ERB antecedents (e.g., Chiu et al., 2014; Confente and Scarpi, 2021; Gupta et al., 2022; He et al., 2022; Kim and Thapa, 2018; Li et al., 2021 , 2023a; Liu et al., 2024; Qiu et al., 2023; Tu and Ma, 2022; Wang et al., 2022). This research provides an integrated three-dimensional theoretical framework to holistically examine several potential micro-, meso-, and macrolevel antecedents of tourist ERB. Findings indicate that there are direct effects of collectivism and destination factors on tourist ERB, with indirect effects attributed to biospheric values and personal factors via environmental attitudes. By elucidating these macro, meso, and micropathways, a theoretical framework is provided that models cultural, destination, and personal antecedents that act to shape tourist ERB.

Second, this study examined the role of mesolevel destination factors (environmental quality and policy) in shaping tourist ERB. Prior research has suggested that environmental quality can prompt positive evaluations and behaviors toward sustainability practices, and policies might moderate awareness-behavior links (Liu et al., 2019; Scannell and Gifford, 2010). The current research demonstrated that destination factors can significantly influence tourists’ environmental attitudes and ERB. These findings complement existing research focused on tourist and host factors.

Finally, this research validates the mediating role of environmental attitude in transmitting macro, meso, and microlevel antecedents’ effects on tourist ERB. Findings from this study identified that biospheric values’ effect on ERB is mediated by attitude, but this indirect effect does not emerge for collectivism. Environmental attitude did not mediate destination attributes, yet fully mediated the impact of personal factors on ERB. These findings suggest that environmental attitude can act as a mediating mechanism for certain cultural and personal-level antecedents. The testing of environmental attitude's mediating role across macro, meso, and microfactors advances our understanding of how this variable transmits the effects of multidimensional influences on tourist ERB.

Managerial implications

Although destination operators likely already recognize the importance of environmental quality for attracting visitors, improving the environmental quality of a destination may also result in those visitors being more likely to adopt ERBs, thus further protecting the destination. One suggestion based on this finding is that destination managers might consider how planned improvements to infrastructure can be coordinated with the local natural environment to present a unified whole servicescape for visitors.

Second, the finding that environmental policy directly affected tourist ERB provides a potentially important insight for destination policymakers. In terms of policy formulation, establishing policies based on the special conditions of a destination, in conjunction with providing environmental education for tourists, could be important so that tourists understand the appropriate laws and regulations. As such, tourist destinations should consider establishing a policy release and ERB disclosure program so that the information is publicly available in formats easy for tourists to locate and digest. Through the formulation and disclosure of environmental policies, tourists might enhance their understanding of expectations for a destination, thereby prompting them (i.e., tourists) to act more environmentally responsibly. Likewise, destination managers might explore integrating sustainability into their branding strategies to convey the destination's dedication to preserving its natural and/or cultural resources to enhance visitor experiences.

Third, the association of environmental knowledge with environmental awareness and tourist ERB was supported. Taking a big picture approach, environmental issues could be integrated into the educational system to enhance the environmental awareness of young people. At the societal level, publicity efforts could be used to disseminate environmental knowledge, thus enabling people to act responsibly and wisely in dealing with environmental and environment-related issues.

Limitations and future research directions

While this study makes several meaningful contributions, there still remain limitations that present opportunities for future research. First, this research looked at the opinions of only Chinese tourists recruited from a Chinese destination. This approach raises concerns regarding the generalizability of the findings which need to be verified with tourists at other destinations across different cultures. While the focus was on the main effects in this study, examining potential moderating relationships between the cultural, destination, and personal factors could provide additional insights. Exploring the interaction effects between the multilevel antecedents represents a fruitful direction for future research that can build upon our findings to develop a more nuanced understanding of the pathways shaping tourists’ environmental attitudes and ERB. Moreover, while the present study employed a quantitative approach to verify the proposed theoretical model, the reliance on a single method may not capture the depth and richness of the investigated relationships. Future researchers could address this limitation by adopting a mixed-methods design, triangulating quantitative findings with qualitative insights using techniques such as in-depth interviews. Finally, Gifford and Nilsson (2014) have suggested that what influences ERB is so multifaceted as to resist practical integration and comprehension. Although this current study explored tourist ERB antecedents across three levels, there is still much work to do integrating additional factors pertaining to tourist behavior to better understand the potential drivers of tourists’ environmental attitudes and ERB.

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Youth Fund of Humanities and Social Sciences of the Ministry of Education, Key Project of Hunan Provincial Natural Science Foundation, and National Natural Science Foundation of China (Grant Nos. 22YJCZH050, 2024JJ3034, 72174213, and 72202061).

ORCID iD

Scott R. Swanson

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