Sustainable Tourism Development: An Empirical Analysis of Tourists’ Emotional Drivers for Environmentally Responsible Behavior ()
1. Introduction
Amid China’s transition to high-quality economic and social development, the tourism sector is witnessing a fundamental shift in consumption patterns—from traditional “scenic consumption” to more meaningful “emotional resonance.” This transformation is most pronounced among Generation Z travelers, who actively shape their tourism experiences through social media participation while demonstrating consumption behaviors increasingly influenced by cultural identity and ceremonial significance (Kelauri, 2023). Guided by the people-centered development philosophy and the principle that “lucid waters and lush mountains are invaluable assets,” tourists’ environmental awareness has been steadily growing. This dual trend of “emotional value enhancement” and “awakening of responsible consumption” presents new imperatives for sustainable tourism development.
Existing research has revealed complex relationships between affective factors and environmentally responsible behavior (ERB). For instance, aesthetic experiences can activate tourists’ intrinsic motivation for ecological conservation, while place attachment enhances environmental willingness (Liang et al., 2025; Li & Ye, 2023; Chen, 2022). However, excessive commercialization and standardized services in tourism management may disrupt tourists’ emotional connections (Yu, 2020), and an overemphasis on technical indicators (e.g., carbon footprint metrics) could trigger psychological resistance (Wang et al., 2011).
2. Literature Review
2.1. Theoretical Foundations: The Role of Emotions in Behavioral
Decision-Making
Arnold’s Excitatory Theory of Emotion establishes that individuals interpret external stimuli through cognitive appraisal systems (evaluating event relevance and goal congruence), while simultaneously activating physiological arousal (e.g., heart rate, skin conductance) through the autonomic nervous system, with the dynamic interaction of these systems generating differentiated emotional states. These affect-laden responses serve critical motivational functions by (1) driving reactive behaviors, (2) providing decision-making impetus, and (3) predisposing affect-congruent choices (Ma & Xie, 2019). Complementing this view, the Theory of Planned Behavior (TPB) demonstrates how behavioral intentions emerge from attitudinal, normative, and control perceptions (Zhang et al., 2017), while contemporary research identifies dual affect-influence pathways (Liu & Jin, 2015): directly through valence-based approach/avoidance tendencies (e.g., destination loyalty versus disengagement), and indirectly via attitude-mediated behavioral intentions in sustainable tourism contexts.
2.2. Multidimensional Drivers of Tourist Emotion Generation
Tourist emotions emerge through an “environmental stimulus-cognitive appraisal-emotional response” pathway, driven by both external and internal factors (Ma & Xie, 2019). External drivers encompass destination attributes (e.g., resource endowments, landscape features), designed atmospherics, and social interactions, while internal drivers include travel motivations, cultural identification, and other subjective cognitive elements.
In cultural heritage settings, authenticity perception constitutes a core affective stimulus dimension (Kolar & Zabkar, 2010). proposed the dichotomy of “objective authenticity” (emphasizing historical attributes) versus “constructed authenticity” (focusing on tourists’ cultural identification). In the Chinese context, tourists predominantly pursue “symbolic authenticity” (Li, 2025)—establishing emotional connections through embodied practices with cultural symbols (e.g., reciting classical poetry, traditional craft workshops).
The mobile internet era has transformed tourists from passive consumers to experience co-creators through platforms like Xiaohongshu and Douyin (Li & Shi, 2022). By proactively searching information, deeply engaging, and sharing content, tourists become both experience leaders and value co-producers. This participatory ecosystem enhances emotional investment while creating a positive feedback loop: participation—emotional engagement—social sharing—reinforced affect. Crucially, participation intensity correlates with a destination’s physical environment, atmosphere, and social interactions, collectively forming key sources of emotional responses (Li & Ye, 2023; Li & Shi, 2022; Zhou et al., 2024). Empirical evidence reveals dual pathways of affective influence on decision-making: positive emotions broaden-and-build behavioral intentions, serving as both drivers and triggers (Santos et al., 2017). When destinations satisfy cognitive (meaning-making), affective (belongingness), and functional (facility convenience) needs, they foster “people-place emotional bonds” that significantly predict pro-conservation behaviors (Xin & Cui, 2017).
In summary, contemporary environmental stimuli and affective qualities demonstrate mutual adaptability, where participation amplifies emotional intensity, and such emotional energy transforms into responsible behaviors.
3. Research Design
3.1. Measurement of Research Variables
This study conceptualizes authenticity through tourists’ dual perceptions of objective authenticity (their evaluations of tangible elements including architecture, site facilities, layouts, landscapes, physical artifacts, and cultural manifestations like customs and atmospheric qualities) and existential authenticity (subjective experiential dimensions encompassing historical connections and perceptions of genuineness). Grounded in the specific context of historical-cultural tourism destinations, the measurement employs a 9-item scale adapted from Guan and Luo’s (2017) foundational work.
Tourist participation is defined as the process through which visitors enhance their travel experiences by engaging in information exchange, active interactions, and innovative behaviors during tourism consumption. This study employs a 9-item scale adapted from the works of Taheri, Jafari, et al. (2014) and Liu et al. (2020) to measure participatory behaviors.
Considering the unique characteristics of emotional expression in Chinese cultural contexts, we conceptualize tourists’ positive emotions at historical-cultural destinations through three distinct dimensions: (1) general positive emotions (e.g., interest, happiness, satisfaction); (2) nostalgic sentiment; and (3) awe and related emotional experiences.
Place attachment encompasses multiple components: functional dependence on the destination’s physical attributes (activities, services, and authenticity of attractions); cultural preferences and value congruence with the site; and social connections to historical events associated with the location.
Environmentally responsible behavior (ERB) refers to tourists’ behavioral intentions regarding environmental protection, resource conservation, and civilized conduct monitoring.
All variables were measured using five-point Likert scales.
3.2. Sampling Methodology
This study targeted historical and cultural tourism sites within China’s inaugural cohort of 24 nationally designated historical cities, selected for their exceptional preservation of cultural relics, architectural heritage, and urban fabric, along with their multidimensional historical significance. These historical and cultural scenic areas invest more in cultural displays and interactive experiences, facilitating the study of the impact mechanisms of “perceived authenticity” and “tourist engagement” on emotions and environmentally responsible behavior. We employed a hybrid sampling strategy combining convenience and judgmental approaches, following other scholars’s methodologies (Cheng et al., 2023; Bao, Yin, & Duan, 2022). Using Baidu Index analytics, we analyzed provincial-level search trends across the mainland China from January 2019 to May 2023, ultimately identifying six high-search-volume cities (Xi’an, Guilin, Chengdu, Beijing, Hangzhou, and Nanjing) as primary research sites.
To ensure data quality, respondents were required to recall their most recent cultural tourism experience within a three-year window and evaluate one specific attraction. The survey employed multi-channel distribution including targeted invitations, social media snowball sampling, regional penetration techniques, and key informant networks to capture diverse visitor perspectives while maintaining methodological rigor. This approach balanced representativeness with practical feasibility in accessing hard-to-reach tourist populations.
4. Data Analysis
The study initially collected 430 completed questionnaires. After excluding responses with completion times under 120 seconds (which might indicate insufficient comprehension of the survey content), a total of 405 valid questionnaires were retained, yielding an effective response rate of 94.1%.
4.1. Descriptive Analysis
The sample exhibited a slightly higher proportion of female respondents (58.8%) compared to males (41.2%). The majority of participants (79.7%) fell within the 20 - 39 age range, with 41.7% aged 20 - 29 and 38% aged 30 - 39, indicating younger demographics as the primary survey population. Educational attainment was notably high, with nearly 90% holding bachelor’s degrees or higher (58.8% undergraduates and 30% master’s degree holders or above). Occupation distribution showed enterprise employees as the largest group (33.5%), followed by students (28.5%) and government/institutional staff (24.3%), collectively representing the core respondent categories. Income levels reflected that over 70% earned monthly incomes below ¥10,000 (39.2% ≤ ¥5,000; 38% at ¥5,001 - 10,000), consistent with the substantial student representation. These demographic characteristics in gender, age, education, occupation, and income aligned with the patterns observed in online sampling studies by Feng and Yang (2024) and Wang, Wang, and Yu (2016).
4.2. Travel Behavior Characteristics
Leisure-oriented motivations dominated tourists’ purposes, with “pursuit of pleasure” being the most prevalent (37.7%), followed by “family companionship” (33.3%). Regarding travel companionship patterns, traveling with friends/colleagues was most common (39.1%), while family trips constituted 32.9% of cases.
In terms of travel experience, 70% of respondents had visited five or more domestic cities, contrasting with relatively limited international exposure—53.1% reported no overseas travel experience. These patterns collectively indicate respondents’ substantial domestic travel experience coupled with comparatively lower participation in outbound tourism.
4.3. Validity Analysis
The study assessed the reliability of the variables using Cronbach’s α coefficients. The α coefficient for positive emotions (comprising three dimensions: general mood, nostalgic mood, and awe mood) was 0.88, indicating high internal consistency of the scale. To simplify the model and focus on the overall impact of emotions on environmentally responsible behavior (ERB), while avoiding multicollinearity issues, the study consolidated the three dimensions into a single variable, “positive emotions,” for analysis. Additionally, the reliability test results for other key variables were as follows: authenticity (α = 0.935), place attachment (α = 0.917), and sustainable behavior (α = 0.886), all demonstrating good internal consistency. The correlation coefficients between the variables ranged from 0.366 to 0.602, indicating moderate to strong correlations, meeting the requirements for further analysis.
4.4. Regression Analysis
The regression analysis incorporated eight demographic and behavioral variables as controls: gender, age, education level, occupation, monthly income, travel companionship, domestic travel experience, and international travel experience. Two distinct models were examined to assess the predictive relationships between key constructs, with all analyses conducted using SPSS 26.0.
(1) Regression Analysis of Authenticity and Participation on Positive Emotions and Place Attachment
The first model evaluated how authenticity and participation influenced positive emotions, while the second model tested their effects on place attachment. As detailed in Table 1, both regression analyses revealed significant predictive relationships, demonstrating the importance of these experiential factors in shaping tourists’ emotional responses and destination connections.
Table 1. Regression analysis of authenticity and participation on positive emotions and place attachment.
Variables |
Positive Emotions |
Place Attachment |
|
M1 |
M2 |
M3 |
M4 |
M’1 |
M’2 |
M’3 |
M’4 |
|
β |
β |
β |
β |
β |
β |
β |
β |
Gender |
0.173** |
0.085 |
0.138 |
0.079 |
0.180** |
0.113* |
0.127** |
0.097 |
Age |
0.002 |
0.023 |
0.064 |
0.055 |
0.073 |
0.089 |
0.165** |
0.161 |
Education |
0.020 |
0.024 |
0.036 |
0.032 |
0.008 |
0.011 |
0.031 |
0.030 |
Occupation |
0.002 |
0.021 |
0.020 |
0.028 |
0.025 |
0.039 |
0.052 |
0.056 |
Monthly Income |
0.080 |
0.050 |
0.054 |
0.040 |
0.076 |
0.053 |
0.036 |
0.029 |
Travel Companion |
−0.024 |
0.005 |
−0.032 |
−0.004 |
−0.099 |
−0.077 |
−0.111* |
−0.097 |
Domestic Travel Exp. |
−0.012 |
−0.049 |
−0.015 |
−0.045 |
0.031 |
0.003 |
0.027 |
0.012 |
Overseas Travel Exp. |
0.019 |
0.025 |
0.003 |
0.015 |
−0.042 |
−0.037 |
−0.065 |
−0.059 |
Authenticity |
|
0.496*** |
|
0.421*** |
|
0.381*** |
|
0.212*** |
Participation |
|
|
0.357*** |
0.201*** |
|
|
0.534*** |
0.456*** |
R² |
0.035 |
0.269 |
0.157 |
0.303 |
0.044 |
0.183 |
0.318 |
0.355 |
ΔR² |
|
0.234 |
0.122 |
0.268 |
|
0.139 |
0.274 |
0.311 |
F-value |
1.776 |
16.078*** |
8.139*** |
17.025*** |
2.261* |
9.754*** |
20.356*** |
21.566*** |
Note: *p < 0.05; **p < 0.01; ***p < 0.001.
Regarding positive emotions, Table 1 demonstrates that when the independent variables “authenticity” and “participation” were not included, Model M1 had an R2 of 0.035, indicating that the control variables had limited explanatory power for positive emotions, accounting for only 3.5% of the variance, with the model being statistically non-significant.
When authenticity was added to M1 to create M2, R2 increased to 0.269, representing a 23.4% improvement in explained variance (ΔR2 = 0.234, F = 16.078*). This suggests authenticity had a significant positive effect on positive emotions (β = 0.496, p < 0.001). Similarly, adding participation to M1 (M3) increased R2 to 0.157 (ΔR2 = 0.122, F = 8.139*), indicating participation’s significant positive influence (β = 0.357, p < 0.001).
The full model (M4) incorporating both authenticity and participation showed no multicollinearity issues (all VIFs < 5), with ΔR2 = 0.268 (F = 17.025***), confirming model stability. These results collectively demonstrate that both authenticity and participation significantly enhance positive emotions, with authenticity showing relatively stronger predictive power.
The initial model M’1 containing only control variables explained a modest proportion of variance in place attachment (R2 = 0.044), indicating limited predictive power. The incorporation of authenticity as an independent variable in model M’2 significantly improved model fit, with R² increasing by 0.139 (F = 9.754, p < 0.001), accounting for an additional 13.9% of variance. The strong positive coefficient (β = 0.381, p < 0.001) confirms authenticity’s substantial influence on place attachment. Model M’3, which added participation to the baseline, demonstrated even greater explanatory power, with R² increasing by 0.274 (F = 20.356, p < 0.001)—a 27.4% improvement. The notably higher beta coefficient (β = 0.534, p < 0.001) suggests participation is an exceptionally robust predictor of place attachment. The comprehensive model (M’4) including both predictors maintained statistical reliability, with all variance inflation factors (VIFs) below 5 (indicating acceptable multicollinearity) and a total R2 increase of 0.311 (F = 21.566, p < 0.001).
2) Regression Analysis of Authenticity, Participation, Positive Emotions, and Place Attachment on Sustainable Tourism Behavior
A regression analysis was conducted using SPSS 26.0 with positive emotions, participation, authenticity, and place attachment as independent variables and environmentally responsible behavior as the dependent variable. The results are presented in the following Table 2.
Table 2. Regression analysis of authenticity, participation, positive emotions, and place attachment on environmentally responsible behavior.
Variables |
Sustainable Tourism Behavior |
|
M5 |
M6 |
|
β |
β |
Gender |
0.207*** |
0.045 |
Age |
−0.022 |
0.003 |
Education Level |
0.033 |
0.035 |
Occupation |
−0.075 |
−0.064 |
Monthly Income |
0.034 |
−0.041 |
Travel Companion |
−0.006 |
0.036 |
Domestic Travel Exp. |
−0.023 |
−0.044 |
Overseas Travel Exp. |
0.034 |
0.033 |
Authenticity |
|
0.192*** |
Participation |
|
0.227*** |
Positive Emotions |
|
0.306*** |
Place Attachment |
|
0.295*** |
R2 |
0.051 |
0.611 |
ΔR2 |
0.051 |
0.559 |
F-value |
2.657** |
50.944*** |
Note: *p < 0.05; **p < 0.01; ***p < 0.001.
As shown in Table 2, Model M5 (without the independent variables of authenticity, participation, positive emotions, and place attachment) demonstrated a significant positive effect of gender (β = 0.207*), indicating that female tourists were more likely to engage in environmentally responsible behaviors. Other demographic variables including age, education level, and occupation showed non-significant effects, suggesting limited independent explanatory power of these sociodemographic characteristics. After incorporating the key independent variables, all variance inflation factors (VIFs) ranged between 1.4 and 1.5, confirming the absence of multicollinearity. The analysis revealed that authenticity (β = 0.192*) significantly promoted environmentally responsible behaviors, while higher levels of tourist participation (β = 0.227*) were associated with increased pro-environmental actions. Positive emotions (β = 0.306*) exerted a strong positive influence on sustainable behaviors, and place attachment (β = 0.295***) emerged as another key driver of environmental responsibility. Notably, the initially significant gender effect became non-significant after including these independent variables, suggesting its influence may be mediated through the affective and experiential factors.
4.5. Mediation Effect Test
This study employed the Bootstrap sampling method (with 5,000 repetitions) to test the mediation effects. As shown in Table 3, all p-values were less than 0.001, and the 95% confidence intervals for all mediation paths did not include zero. This indicates that both positive emotions (PE) and place attachment (PA) play significant mediating roles between the independent variables and environmentally responsible behavior (ERB). These results suggest that the perceived authenticity and engagement in tourism experiences not only directly promote ERB but also indirectly influence it by eliciting positive emotions and strengthening place identity. Notably, the mediation effect of place attachment was generally stronger than that of positive emotion, implying that emotional bonds to a place may exert a more enduring influence on driving ERB compared to immediate emotional responses.
Table 3. Mediation effect test.
IndependentVariable |
MediatingVariable |
DependentVariable |
Effect Quantity (Unstd.) |
BootSE |
Percentile |
95%CI |
Lower |
Upper |
A |
PE |
ERB |
0.2424 |
0.0569 |
0.1401 |
0.3598 |
A |
PA |
ERB |
0.2029 |
0.0502 |
0.1173 |
0.3129 |
P |
PE |
ERB |
0.1615 |
0.0355 |
0.0943 |
0.2352 |
P |
PA |
ERB |
0.2212 |
0.0432 |
0.1400 |
0.3098 |
Note: A: Authenticity; P: Participation; PE: Positive Emotions; PA: Place Attachment; Environmentally Responsible Behavior: ERB.
5. Conclusions and Discussion
5.1. Research Findings
Grounding our investigation in the “Stimulus-Affect-Environmentally Responsible Behavior” framework, this study elucidates the emotional generation pathways of tourists at historical-cultural sites and their subsequent impact on pro-environmental actions. Empirical analysis of 405 visitors across six destinations (Xi’an, Guilin, et al.) yields three pivotal insights: First, destination authenticity and participatory engagement jointly drive 30.3% of positive emotional variance (authenticity β = 0.421) and 35.5% of place attachment variance (participation β = 0.456), revealing differentiated affective mechanisms—where authentic encounters directly spark awe and pleasure, while hands-on participation cultivates deeper place bonding. Second, these affective responses collectively demonstrate stronger predictive power for environmental behaviors than demographic factors alone. Third, the identified mediation effects underscore an emotion-driven transformation process from experiential stimuli to sustainable actions. These findings advance theoretical integration of affective psychology with sustainable tourism models.
Positive emotions and place attachment were found to play significant mediating roles between authenticity/participation and environmentally responsible behavior (ERB). Together, these four factors explained 61.1% of the variance in ERB, highlighting emotions as a critical bridge linking tourist experiences with pro-environmental actions. Specifically, both positive emotions (β = 0.306) and place attachment (β = 0.295) demonstrated particularly strong positive emotions on ERB, confirming the pathway through which emotional energy transforms into responsible behavior.
In this study, demographic characteristics such as age, income, and education level showed limited direct influence on ERB—a finding that diverges from some existing research. This discrepancy may stem from low variability in the sample’s education and age distribution (e.g., 98% held higher education degrees, 79.7% were aged 20 - 39). However, the results align with gender role theory, as women exhibited stronger pro-environmental behavioral tendencies than men (β = 0.207), consistent with their greater propensity for prosocial behavior (Liu, 2010).
5.2. Implications
This study substantiates the pivotal role of emotions in tourism behavior research, advancing the application of the “emotionst-behavior” chain in sustainable tourism and providing empirical support for an emotion-oriented model of environmentally responsible behavior. By revealing the dual-pathway driving mechanism of authenticity and participation, it expands the theoretical framework of emotional generation in cultural heritage tourism, particularly highlighting the unique value of active tourist participation in fostering place attachment.
Developing immersive cultural experiences to enhance authenticity perception. To strengthen tourists’ perception of authenticity, destination managers should design diversified experiential activities, including traditional craft workshops, historical reenactments, and interactive cultural symbol participation. These initiatives enable visitors to deeply participate in local historical narratives and cultural practices, thereby:
Enhancing social interaction and co-creation participation. Destination managers should strengthen social interactions and co-creation participation by incorporating viral check-in elements into community cultural projects and eco-volunteer programs, aligning with tourists’ preference for online sharing. These activities should be designed as distinctive “memory anchors”—such as the tangible experience of “hand-repaired brick walls” from heritage restoration or “community-planted trees” from ecological activities—which transform into highly evocative emotional memories. When recalled, these memories reinforce positive cognitive evaluations and emotional imprints, fostering destination familiarity while generating anticipation for repeat participation. This dual mechanism of “memory recall” and “future expectation” ultimately elevates transient positive emotions into lasting place attachment.
Emotional storytelling and policy integration. Strategic initiatives like “Preserve Villages, Sustain Nostalgia” campaigns can effectively link environmental responsibility with visitors’ emotional drivers. This approach involves: (1) employing documentary films and cultural products to associate conservation behaviors with nostalgic sentiments; (2) developing emotionally compelling guided narratives told from first-person perspectives to evoke protective instincts; and (3) incorporating emotional indicators (e.g., visitor delight and attachment indices) into sustainability assessments, complemented by behavioral incentive systems. Such integrated measures ensure environmental responsibility becomes intrinsically motivated through emotional connections rather than externally imposed obligations.
5.3. Recommendations for Future Research
Building upon the authors’ previous tourism emotion research (Lei & Zheng, 2025) that focused on highly-educated young adults, this study suggests future research should expand demographic diversity to validate findings’ generalizability, incorporate theoretical constructs from the Theory of Planned Behavior (e.g., values, attitudes) and Value-Belief-Norm Theory to examine affective-cognitive interactions, include negative emotion measures, and employ mixed-methods combining quantitative and qualitative approaches (e.g., interviews) to comprehensively understand how emotional experiences influence environmentally responsible behaviors, thereby advancing both theoretical frameworks and practical applications for sustainable cultural tourism development.
Acknowledgements
This work was supported by the Guangxi College of Sports Education Research Project: “Research on Educational Travel Activities Based on Embodied Theory” (Project No. tzky2022007) and the Special Project for Study Practice Education of the Guangxi Education Science “14th Five-Year Plan” 2022 Annual Program (Project No. 2022ZJY1790).