Social media and place based attachment as pathways to environmentally responsible coastal tourism

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C., Harisha G. Joshi, Rithika Jeethu Suvarna This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8495787/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Coastal tourism provides important economic benefits while also placing environmental pressures on fragile beach and marine ecosystems. Therefore, encouraging tourists' environmentally responsible behaviour (TERB) is essential for promoting sustainable coastal tourism and achieving the Sustainable Development Goals (SDGs). This study uses the stimulus-organism-response (SOR) framework to develop and test an integrated model that connects sustainability-oriented social media user-generated content (SMUGC), environmental dispositions, and place-based attachments to TERB. Data were collected from 432 tourists visiting nine beaches along the Karnataka coast of India and analysed using partial least squares structural equation modelling (PLS-SEM). The results show that both cognitive (informativeness and credibility) and affective (emotional and aesthetic) triggers of SMUGC strongly improve tourists' environmental concern and environmental attitude. These environmental dispositions, in turn, positively influence TERB. Furthermore, place attachment and cultural attachment exert strong direct effects on environmentally responsible behaviour. The proposed model accounts for 57.7% of the variance in TERB, showing strong explanatory power. By integrating digital media stimuli with environmental psychology and place-based attachments, this study advances sustainability-oriented tourism research and provides valuable insights for destination managers and policymakers. The results highlight the importance of combining sustainability-focused social media communication with attachment-building tourism experiences to promote responsible tourist behaviour and enhance the resilience of coastal socio-ecological systems. environmentally responsible behaviour social media user generated content place attachment cultural attachment coastal tourism SOR Figures Figure 1 Figure 2 Figure 3 Introduction Coastal tourism provides important economic benefits for local communities, but also produces serious environmental impacts, including litter and plastic leakage, habitat degradation and overuse of water and energy resources [ 1 – 3 ]. Along the Karnataka coast of India, beaches have become popular destinations for domestic and international tourists. While tourism development generates new livelihood opportunities, it simultaneously raises concerns about beach cleanliness, marine pollution and long-term ecosystem integrity. Tourists’ environmentally responsible behaviour (TERB), such as proper waste disposal, recycling, conserving water and energy, complying with regulations and supporting conservation initiatives plays a central role in determining environmental outcomes in coastal destinations [ 1 , 4 – 6 ]. Previous studies link TERB to environmental concern, pro-environmental attitudes, personal values and norms, emotional responses and bonds with places and cultures [ 4 , 5 , 7 , 8 ]. However, many studies consider these determinants in isolation, either emphasising social media influences on behaviour or focusing on place attachment and stewardship, rather than integrating digital stimuli, environmental dispositions and place-based bonds into a single behavioural framework. These dynamics align closely with the Sustainable Development Goals (SDGs). SDG 11 (Sustainable Cities and Communities) calls for inclusive, safe, resilient and sustainable human settlements, including coastal towns that depend heavily on tourism. SDG 14 (Life Below Water) stresses the conservation and sustainable use of oceans, seas and marine resources. Coastal Karnataka is exposed to climate-related risks such as sea level rise, coastal erosion and extreme weather events, making the sustainability of tourism and the resilience of local communities particularly critical. Encouraging TERB among tourists is therefore part of a broader strategy to enhance the resilience and sustainability of coastal socio-ecological systems [ 1 , 5 , 9 – 11 ]. Tourists’ encounters with destinations are increasingly mediated by social media. Social Media User Generated Content (SMUGC) on platforms such as Instagram, Facebook and YouTube influences destination image, perceived authenticity, visit intentions, loyalty and even overtourism [ 12 – 16 ]. Previous work has examined how social media attributes, opinion leaders and group dynamics shape travel decisions, impulsive travel, loyalty and sustainable tourism development, often drawing on the stimulus-organism-response (SOR) framework [ 2 , 13 , 17 , 18 ]. Sustainability-oriented SMUGC can encourage pro-environmental behaviour by providing information, shaping norms and eliciting emotional responses such as empathy and eco-guilt [ 1 , 19 – 22 ]. Parallel literature emphasises the importance of tourist experience, place attachment and cultural attachment for environmentally responsible behaviour and stewardship. Studies in cultural heritage sites, industrial heritage and cultural tourism destinations show that attachment to places and cultures predicts TERB, psychological ownership, environmental conservation and citizenship behaviours [ 4 , 5 , 8 , 23 – 26 ]. Systematic reviews underscore the central role of place attachment in environment-related behaviour and call for integrated models that connect cognitive appraisals, emotional bonds and behavioural outcomes [ 27 , 28 ]. Despite growing scholarly interest in tourists’ environmentally responsible behaviour (TERB), existing studies tend to examine its determinants in a fragmented manner [ 5 – 7 ]. Prior research has either focused on the influence of social media user-generated content (SMUGC) on destination image, attitudes and behavioural intentions [ 12 , 13 , 19 , 29 ], or on the role of place attachment and stewardship in shaping pro-environmental behaviour [ 4 , 8 , 23 , 24 ]. Only limited empirical work has integrated digital stimuli, environmental dispositions and place-based attachments within a single behavioural framework, particularly in real-world coastal tourism settings in the Global South [ 1 , 2 , 21 ]. Moreover, most SMUGC-based tourism studies treat social media exposure as a homogeneous construct, without distinguishing between its cognitive (informational and credibility-related) and affective (emotional and aesthetic) properties that may differentially influence environmental concern and attitudes [ 2 , 30 , 31 ]. At the same time, while place attachment has been widely recognised as a driver of environmentally responsible behaviour [ 5 , 23 ],the role of cultural attachment, especially in culturally embedded coastal destinations, remains underexplored in sustainability-oriented tourism research [ 4 , 25 , 32 ]. Drawing on the SOR framework, this study addresses these gaps by conceptualising sustainability-oriented SMUGC as the stimulus (S), operationalised through cognitive and affective triggers; environmental concern, environmental attitude, place attachment and cultural attachment as organismic states (O); and TERB as the behavioural response (R). Using survey data from 432 tourists across nine beaches along the Karnataka coast of India, the study aims to: 1. Develop and test an integrated SOR-based model linking SMUGC, environmental dispositions, place attachment and cultural attachment to TERB in a coastal tourism context. 2. Empirically examine the distinct effects of cognitive and affective SMUGC triggers on environmental concern and environmental attitude. 3. Derive practical implications for destination managers and policymakers seeking to promote sustainable coastal tourism and advance SDGs 11 and 14. 2. Literature Review and Hypotheses 2.1 Social Media UGC as Cognitive and Affective Stimulus Social media has become a dominant information source for tourists, shaping destination image, perceived authenticity, visit intentions and loyalty [ 12 , 13 ]. SMUGC on platforms such as Instagram and YouTube allows travellers to access peer experiences, visual impressions and evaluations of destinations in real time [ 14 , 33 ]. Empirical studies show that SMUGC influences destination imagery and visit intentions [ 12 , 29 ] and loyalty behaviour in heritage contexts [ 13 ]. Beyond marketing outcomes, there is growing interest in the role of SMUGC in supporting sustainable tourism [ 1 , 16 , 19 ]. Within the SOR framework, platform attributes such as vividness, interactivity and credibility are conceptualised as stimuli that shape internal psychological states (organism), including emotions, attitudes and perceived value, which then influence behavioural responses such as impulsive travel or purchase intentions [ 2 , 17 , 34 ]. This conceptual framework has been applied to the context of social media within the tourism sector, displaying that specific attributes can elicit organismic reactions, which subsequently lead to behavioural outcomes [ 15 ]. In sustainability contexts, digital media can provide both cognitive and affective triggers. Environmentally oriented SMUGC and short videos can convey information about environmental problems and low-impact options (cognitive triggers), while immersive or aesthetic digital experiences can evoke emotional responses such as awe, eco guilt and empathy [ 1 , 19 , 21 , 22 ]. For instance, virtual experiences can enhance environmental responsibility through aesthetic engagement; environment friendly short videos can increase low-carbon tourism intentions [ 21 ]; and digital content that induces eco guilt and empathy with nature can foster pro-environmental behaviour in tourists [ 22 ]. Social media can also create conformity pressures: seeing peers engage in pro-environmental actions can encourage users to imitate similar behaviours [ 31 ]. Drawing on this literature, this study conceptualises SMUGC through two dimensions: Cognitive triggers: perceived informativeness, credibility and clarity of environmental and destination-related information [ 1 , 12 , 19 ]. Affective triggers: emotional arousal, aesthetic appreciation and empathy elicited by coastal and community-related content [ 1 , 19 , 21 , 22 , 35 ]. Within the SOR framework, these cognitive and affective triggers represent the stimuli (S) that shape tourists’ internal environmental dispositions. Accordingly, we hypothesise: H1a. Cognitive triggers in SMUGC positively influence tourists’ environmental concern. H1b. Affective triggers in SMUGC positively influence tourists’ environmental concern. H2a. Cognitive triggers in SMUGC positively influence tourists’ environmental attitude. H2b. Affective triggers in SMUGC positively influence tourists’ environmental attitude. 2.2 Environmental Concern, Environmental Attitude and TERB Environmental concern and environmental attitude are widely recognised as key antecedents of pro-environmental behaviour [ 6 , 36 , 37 ]. In tourism, environmentally responsible behaviour has been examined in nature-based tourism, cultural heritage sites and coastal destinations [ 3 , 4 , 6 , 7 ]. Conceptual work on nature-based tourists highlights the importance of clarifying related concepts and measurement approaches for environmentally responsible behaviour [ 6 ]. Empirical studies show that tourists with stronger environmental concern and more positive environmental attitudes are more likely to engage in behaviours such as proper waste disposal, resource conservation and support for conservation initiatives [ 4 , 7 ]. The value-belief-norm (VBN) framework and related models provide theoretical support for the role of concern and attitudes. For example, research on food festival attendees demonstrates that environmental values and beliefs shape pro-environmental intentions through norm activation and attitudes [ 36 ]. Similar mechanisms have been observed in other tourism and leisure contexts where concern, values and attitudes contribute to environmentally responsible behaviour [ 7 , 37 , 38 ]. In coastal destinations specifically, environmental attitudes and perceptions of responsibility have been linked to tourists’ responsible behaviour, including waste management and compliance with regulations [ 2 , 3 ]. In this study, environmental concern is defined as awareness of environmental issues and willingness to address them, whereas environmental attitude captures relatively stable evaluations of environmental protection and related behaviours. Both are treated as organism (O) that mediate the influence of social media stimuli on TERB. We therefore propose: H3. Environmental concern positively influences tourists’ environmentally responsible behaviour. H4. Environmental attitude positively influences tourists’ environmentally responsible behaviour. 2.3 Place Attachment, Cultural Attachment and TERB Place attachment refers to the emotional and cognitive bonds individuals form with specific places, often operationalised through place identity and place dependence [ 5 , 27 , 28 ]. Early work by Vaske and Kobrin [ 5 ] showed that place attachment predicts environmentally responsible behaviour among recreationists, providing a foundation for numerous subsequent studies. Systematic reviews confirm that place attachment plays a central role in environment-related behaviour, acting as a motivational basis for stewardship and conservation [ 27 ]. In tourism, place attachment has been integrated into models explaining environmentally responsible behaviour and related outcomes. Research at cultural heritage sites and other destinations indicates that place attachment can mediate the relationship between destination attractiveness and tourists’ environmentally responsible behaviour [ 8 ], and that psychological ownership can serve as a mechanism linking attachment and pro-environmental behaviour [ 23 ]. Conceptual overviews further highlight the importance of place attachment in tourism research and its connection to sustainability outcomes [ 24 , 28 , 39 ]. Cultural attachment, referring to emotional ties to the cultural meanings and heritage of a destination, has also been shown to influence environmentally responsible behaviour. At cultural heritage sites, tourism experiences can foster cultural attachment, which then promotes tourists’ environmentally responsible behaviour and citizenship behaviours [ 4 ]. Studies in industrial heritage settings indicate that perceived authenticity and place attachment are associated with tourists’ environmental behaviour [ 25 , 40 ]. Work on cultural tourism destinations suggests that fascination with a place, combined with attachment, can support environmental stewardship [ 24 ]. Place identity and attachment to local communities are also linked to conservation intentions in rural heritage villages [ 26 , 41 ]. In this study, place attachment and cultural attachment are conceptualised as additional organism (O), reflecting emotional and cognitive bonds formed through repeated or meaningful interactions with coastal places and cultures. Rather than being purely structural characteristics of destinations, they represent internalised connections that can motivate stewardship behaviour. Based on prior evidence, we hypothesise: H5. Place attachment positively influences tourists’ environmentally responsible behaviour. H6. Cultural attachment positively influences tourists’ environmentally responsible behaviour. 2.4 Conceptual Model Bringing these strands together, the proposed SOR based model positions SMUGC, represented by its cognitive and affective triggers, as the stimulus (S). Environmental concern, environmental attitude, place attachment and cultural attachment represent distinct but related organism (O) that capture tourists’ cognitive evaluations and emotional bonds. Tourists’ environmentally responsible behaviour (TERB) constitutes the response (R), expressed through waste management, resource conservation and compliance with rules in the beach context. This configuration extends prior SOR applications in tourism in two ways. First, it moves beyond models that focus solely on environmental concern and attitude by incorporating place attachment and cultural attachment as additional organism that directly shape TERB [ 4 , 5 , 8 , 24 ]. Second, it treats SMUGC explicitly in terms of cognitive and affective triggers, allowing a more nuanced assessment of how different qualities of social media content influence environmental dispositions. Accordingly, the model specifies paths from cognitive and affective triggers of SMUGC to environmental concern and environmental attitude (H1a, H1b, H2a, H2b), from environmental concern and environmental attitude to TERB (H3,H4), and from place attachment and cultural attachment to TERB (H5,H6). The conceptual model is presented in Fig. 1 , where the S, O and R components are explicitly indicated. Methodology 3.1 Study Area The empirical study was conducted at nine beaches along the Karnataka coast of India. Malpe, Kapu, Padubidri, Panambur, Thannirbavi, NITK, Karwar, Gokarna and Murdeshwara. These sites are important tourism nodes combining recreational, religious and cultural functions and are frequently featured in SMUGC posts. The beaches are representative of rapidly developing coastal destinations where tourism growth, cultural activities and environmental pressures intersect [ 1 ]. 3.2 Research Design and Instrument A cross-sectional survey design was adopted. A structured questionnaire contained two sections. Section A captured socio-demographic and trip characteristics, including gender, age, education, place of residence, frequency of coastal visits, main purpose of visit, primary social media platforms used and survey location. Section B consisted of multi-item five-point Likert scales (1 = strongly disagree, 5 = strongly agree). Measurement items were adapted from established scales. The measurement items for the constructs CT, AT, EA, EC, PA, CA and TERB are included from the previous research that was reliable and valid. The questionnaire consisted of a total of 33 items. The CT was measured using four items [ 1 ], AT using four items [ 1 ], EC using eight items [ 1 , 42 ], EA using four items [ 1 ], PA using four items [ 7 ], CA using three items [ 4 ] and TERB using six items [ 11 ]. Items were reworded to fit the coastal tourism context to refer specifically to beaches and related environment. 3.3 Sampling and Data Collection Because a sampling frame for tourists at the study sites was unavailable, a convenience sampling approach was used. Trained surveyors approached tourists at each beach during morning and evening periods, briefly explained the study and invited participation. The Inclusion criteria required respondents to be at least 18 years old, visiting for leisure or tourism and having at least one active social media account (Instagram, Facebook or YouTube). Participation was voluntary and anonymous. Informed consent was obtained, and no personally identifiable information was collected. Out of the 453 questionnaires distributed, 432 valid responses were retained after excluding those that were incomplete or inconsistent, resulting in a usable response rate of approximately 95%. This sample size is consistent with the recommendations for PLS-SEM, considering the number of constructs, indicators, and the complexity of the model [ 43 ]. 3.4 Data Analysis The study used the Partial Least Squares Structural Equation Modelling (PLS-SEM) approach for both the specification and evaluation of the research model. All constructs in the study were modelled as reflective, as done in earlier sustainable tourism and environmental behaviour research. PLS-SEM was used due to the study’s predictive orientation, the complexity of the proposed model. Through this approach, the measurement model was assessed to determine the reliability and validity of the constructs, while the structural model was evaluated to examine the proposed relationships among the variables, while ensuring that the model met the required psychometric and predictive standards [ 43 ]. Results 4.1 Sample Profile Valid responses to this study were received from 432 beach tourists who visited designated beaches on the Karnataka Coastline. All respondents were recreational travellers using at least one social media platform (Instagram, Facebook, YouTube). The sample included a diverse mix of genders, age groups, and educational levels, with domestic tourists constituting the majority and a smaller group of international visitors. Detailed sociodemographic data are presented in Table 1 . Table 1 Demographical data Variable Category n % Gender Male 242 56.0 Female 186 43.1 Non-binary 4 0.9 Age group ≤ 20 years 13 3.0 > 20-≤ 30 years 158 36.6 > 30-≤ 40 years 120 27.8 > 40-≤ 50 years 49 11.3 > 50-≤ 60 years 50 11.6 > 60 years 42 9.7 Educational qualification High school or below 85 19.7 11th -12th 95 22.0 Bachelor’s degree 90 20.8 Master’s degree 70 16.2 Above Master’s degree 92 21.3 Employment status Student 85 19.7 Self-employed 88 20.4 Employee 76 17.6 Homemaker 95 22.0 Unemployed 88 20.4 Annual income level No income 84 19.4 ≤ ₹3,00,000 91 21.1 > ₹3,00,000-≤ ₹5,00,000 69 16.0 > ₹5,00,000-≤ ₹8,00,000 94 21.8 > ₹8,00,000 94 21.8 Nationality Indian Tourist 395 91.4 International Tourist 37 8.6 Local resident status Local resident 189 43.8 Non local resident 243 56.2 Social media platforms used Instagram 229 53.0 Facebook 219 50.7 YouTube 222 51.4 Other 215 49.8 4.2 Construct Reliability and Validity As noted by [ 44 ], composite reliability is employed to assess internal consistency and individual indicator reliability, while average variance extracted (AVE) is utilized to evaluate convergent validity within the reflective measurement model. Table 2 presents the values for Cronbach’s Alpha, Composite Reliability, and Average Variance Extracted (AVE). The composite reliability exceeds 0.8, Cronbach’s Alpha is greater than 0.7, and the average variance extracted is greater than 0.5 for all constructs. Hence, these results suggest that the constructs utilized in the study demonstrate good validity and reliability [ 43 , 44 ]. Table 2 Results of construct reliability and validity analysis Cronbach’s alpha Composite Reliability AVE AT 0.904 0.933 0.776 CA 0.838 0.902 0.754 CT 0.907 0.935 0.782 EA 0.860 0.905 0.704 EC 0.940 0.950 0.706 PA 0.903 0.932 0.775 TERB 0.918 0.936 0.710 AT: Affective Trigger, CA: Cultural Attachment, CT: Cognitive Trigger, EA: Environmental Attitude, EC: Environmental Concern, PA: Place Attachment, TERB: Tourists Environmentally Responsible Behaviour. 4.3 HTMT values of the constructs Table 3 provides an analysis of discriminant validity through the heterotrait-monotrait ratio (HTMT). According to [ 45 ], an HTMT value must be below 0.90 to be deemed significant. Therefore, Table 3 verifies that all HTMT values fall below this threshold, confirming the discriminant validity of the construct. Once the construct's reliability and validity are established, the subsequent step involves evaluating the structural model. Table 3 HTMT Value AT CA CT EA EC PA TERB HTMT confidence interval does not include 1 AT Yes CA 0.070 Yes CT 0.039 0.037 Yes EA 0.768 0.099 0.343 Yes EC 0.455 0.077 0.694 0.540 Yes PA 0.043 0.565 0.030 0.060 0.051 Yes TERB 0.396 0.477 0.311 0.483 0.459 0.546 Yes 4.4 Results of Structural Model The conceptual model illustrated in Fig. 2 describes the path coefficient, indicating the strength of the relationships between the variables, outer loading and R 2 values of EC, EA, and TERB. As seen in Fig. 2 , the path coefficient values among all constructs indicate stronger relationships, as these values are above 0.10 [ 59 ]. In addition, Fig. 2 demonstrates that the outer loadings of all constructs surpass the threshold value of 0.7, indicating satisfactory levels of indicator reliability. The R 2 value of TERB accounts for 57.7% of the variance. According to [ 44 ], an R 2 value of 0.25 is considered weak, 0.50 moderate, and 0.75 high for endogenous variables. The R 2 value for TERB is reasonably moderate, which suggests that the structural model has predictive validity. However, the R 2 values for EC and EA account for 58% and 54.3%, respectively, indicating moderate variance. Table 4 presents a summary of the hypothesis testing outcomes derived from the bootstrapping procedure in PLS-SEM, detailing standardized path coefficients, t-values, and corresponding significance levels. The results show that all hypothesized relationships are statistically significant as P values are less than 0.001 level, thereby offering robust empirical support for the proposed model [ 46 ]. Both cognitive and affective triggers of SMUGC have strong positive effects on environmental concern and environmental attitude (H1a, H1b, H2a, H2b), confirming the role of sustainability-oriented digital stimuli as key antecedents of tourists’ environmentally responsible behaviour. Moreover, environmental concern and environmental attitude are shown to positively influence TERB (H3 and H4). Also, place attachment and cultural attachment exhibit significant direct effects on environmentally responsible behaviour (H5 and H6), suggesting that emotional bonds with places and local culture act as important motivational bases for responsible tourist behaviour in coastal destinations. Table 4 Hypotheses testing results of the structural model. Hypothesis Path coefficient T values P values Conclusion H1a: CT -> EC 0.634 23.195 0.000*** Supported H1b: AT -> EC 0.409 13.013 0.000*** Supported H2a: CT -> EA 0.290 8.412 0.000*** Supported H2b: AT -> EA 0.671 26.075 0.000*** Supported H3: EC -> TERB 0.291 7.470 0.000*** Supported H4: EA -> TERB 0.330 8.914 0.000*** Supported H5: PA -> TERB 0.375 10.410 0.000*** Supported H6: CA -> TERB 0.284 7.881 0.000*** Supported *** p < 0.001; **p < 0.01; p < 0.05 4.5 Structural Model Estimates Table 5 illustrates the model fit, reporting an SRMR of 0.039 for the saturated model and an NFI of 0.912. As per [ 43 ], an NFI value close to 1 and an SRMR value below 0.08 signify a good model fit. The structural model values for SRMR and NFI, as detailed in Table 4 , align with these criteria, thereby confirming the model's adequacy in terms of fit. Table 5 Model Fit Saturated Model Estimated Model SRMR 0.039 0.041 D_ULS 0.849 0.964 D_G 0.370 0.381 Chi-square 911.355 941.758 NFI 0.912 0.909 Discussion This research makes a notable contribution to the field of sustainability-oriented tourism by bringing together social media stimuli, environmental dispositions and place-based attachments within a SOR framework. This approach illustrates TERB in coastal destinations. The study's findings not only support existing evidence on the impact of environmental concern, attitudes, and place attachment on responsible behaviour but also expand the current literature by showing how sustainability-oriented SMUGC, divided into cognitive and affective triggers, indirectly influences TERB through cognitive and emotional routes. Consequently, the research enhances the understanding of the combined role of digital communication and on-site emotional connections in influencing pro-environmental behaviour within coastal tourism contexts in the Global South. 5.1 Social Media UGC as a Driver of Environmental Dispositions The significanstrong influence of cognitive and affective SMUGC triggers on environmental concern and environmental attitude highlights the critical role of social media as a medium for sustainability communication in coastal tourism [ 1 , 12 , 19 ]. From a SOR theory perspective, SMUGC serves as a multidimensional stimulus that enhances both information-based and emotion-based organismic states. The strong correlation between affective triggers and environmental attitude suggests that emotionally engaging and aesthetically appealing content is particularly effective in shaping positive evaluations of environmental protection, consistent with evidence from environment friendly short videos [ 21 ]. By explicitly distinguishing cognitive and affective triggers within SMUGC, this study extends previous work that treated social media exposure more generically [ 1 , 17 , 19 ]. Identifying which aspects of digital communication, such as informative messages, credibility cues, emotional storytelling or aesthetic imagery, are most closely associated with shifts in environmental concern and attitudes provides practical guidance for destination communication strategies. 5.2 Environmental Concern and Attitude as Predictors of TERB Environmental concern and environmental attitude both exerted significant positive effects on TERB, underscoring their role as key organism in the SOR model and aligning with value-belief-norm and related frameworks [ 4 , 6 , 8 , 36 ]. The relatively stronger effect of environmental attitude indicates that context-specific evaluations of behaviours such as not littering, conserving water and following local rules are particularly influential [ 47 ]. This is consistent with studies showing that attitudes towards concrete behaviours are central in predicting intentions and actions in festival and youth tourism contexts [ 7 , 30 , 36 , 38 ]. The findings also align with research on risk perception and norm activation in tourism [ 37 , 47 , 48 ], suggesting that strengthening positive environmental attitudes in specific destinations may be an effective way to translate general concern into concrete action. 5.3 Place and Cultural Attachment as Motivational Bases for TERB Place attachment and cultural attachment also emerged as important organisms that directly motivate TERB. Place attachment displayed the largest direct effect on TERB among all predictors, reinforcing extensive evidence that emotional bonds with destinations foster stewardship and conservation behaviour [ 5 , 8 , 24 , 27 ]. Cultural attachment further contributed to TERB, supporting findings from heritage and cultural tourism settings where attachment to local culture encourages environmentally responsible and citizenship behaviours [ 4 , 23 , 25 , 26 , 32 , 49 ]. In the coastal Karnataka context, beaches are intertwined with temples, religious activities, festivals and fishing communities. Experiences that foster emotional connections with these cultural landscapes appear to motivate tourists to care for and protect them. This highlights the need to treat attachment building not as a byproduct of tourism development but as a deliberate component of sustainable coastal destination strategies. 5.4 Theoretical Contributions This study makes three main theoretical contributions. It integrates digital media stimuli, environmental dispositions and place-based attachments into a single SOR framework for explaining tourists’ environmentally responsible behaviour (TERB) in coastal tourism. Existing SOR applications in tourism and hospitality have predominantly focused on social media influences on intentions and loyalty or on environmentally responsible behaviour, without simultaneously considering place-based bonds [ 2 , 17 , 18 , 50 ]. By treating SMUGC through its cognitive and affective triggers as the stimulus and environmental concern, environmental attitude, place attachment and cultural attachment as the organism, the model connects digital communication, psychological processes and behavioural responses in a unified structure. The study advances SMUGC research by explicitly distinguishing between cognitive and affective triggers as separate but related dimensions of the digital stimulus rather than relying on hierarchical terminology. Prior work often measures social media exposure in aggregate terms or focuses primarily on informational qualities [ 1 , 12 , 19 ]. Distinguishing perceived informativeness and credibility (cognitive triggers) from emotional arousal, empathy and aesthetic appreciation (affective triggers) clarifies how different qualities of SMUGC influence environmental concern and attitudes. This responds to recent calls to better understand how digital communication and nudging strategies shape sustainability-related behaviour in a rapidly evolving media landscape [ 51 ]. The study positions place attachment and cultural attachment as organismic states that directly motivate TERB, alongside environmental concern and attitude. While reviews of place attachment and environment-related behaviour emphasise the importance of emotional bonds for stewardship [ 5 , 27 , 28 ], and recent sustainable tourism research highlights links between tourism, local communities and SDGs, the micro-level behavioural role of place and culture-based attachment in coastal destinations remains underexplored [ 52 – 54 ]. By demonstrating that place attachment has the strongest direct effect on TERB and that cultural attachment is also a significant predictor, this study shows that digital stimuli and on-site attachment-building processes are complementary rather than competing pathways for promoting responsible behaviour in coastal socio-ecological systems. In combination, these contributions position the SOR-based TERB model within emerging sustainable tourism scholarship that maps SDG-related themes and calls for more behaviourally grounded evidence, particularly in the Global South [ 52 , 55 , 56 ]. Managerial Implications The findings suggest several implications for destination managers, tourism businesses and local authorities in coastal regions. Destination managers can co-create sustainability-oriented SMUGC campaigns with influencers, local creators, residents and visitors. Campaigns that portray both the beauty and vulnerability of coastal environments are likely to activate both the cognitive and affective triggers identified in this study. Communication strategies should deliberately blend factual information with emotional storytelling. Clear messages about rules, available facilities and environmental impacts can be combined with narratives, photographs and short videos featuring local community members, lifeguards, conservation volunteers and tourists who demonstrate responsible behaviour. Such content can strengthen environmental concern and attitudes while also building empathy with local people and ecosystems.[ 21 , 51 , 57 , 58 ] Tourist service providers should emphasise on experiences that foster place and cultural attachment. Examples include heritage trails linking beaches with nearby temples and fishing hamlets, community-led tours, homestay programmes and opportunities to participate in local festivals and conservation activities such as beach clean-ups or mangrove planting. These immersive experiences deepen emotional bonds with the destination and can motivate tourists to act as stewards. On-site infrastructure and behavioural cues must support responsible choices. Adequate bins, recycling facilities, water refill points and signage are basic prerequisites. Behavioural “nudges” at entrances, food stalls and scenic viewpoints such as reminders about plastic use, prompts to sort waste, or messages highlighting the responsible behaviour of other visitors can make environmentally responsible choices easier and more salient [ 5 , 59 ]. Destination managers can use social media data for monitoring and adaptive management. Tracking hashtags, geotags, sentiment and content themes can help identify hotspots of crowding or environmental stress and reveal how tourists represent the destination online. These insights can inform targeted communication, visitor dispersion strategies and collaborations with residents to co-create more sustainable tourism pathways. In this way, digital and on-site interventions can jointly contribute to SDGs 11 and 14 by enhancing the resilience of coastal socio-ecological systems [ 51 ]. 6.1 Implications for the Sustainable Development Goals (SDGs) The findings have direct implications for the achievement of several Sustainable Development Goals (SDGs) in tourism-dependent coastal regions. At the macro level, recent reviews of tourism research show that integrating the SDGs into tourism practices is essential for moving towards a more sustainable and responsible sector, yet empirical studies connecting micro-level tourist behaviour with SDG outcomes remain comparatively scarce [ 52 , 55 ]. By focusing on tourists’ environmentally responsible behaviour (TERB) in coastal Karnataka, this study provides behaviourally grounded evidence that complements system-level analyses of sustainable tourism development and carrying capacity in coastal destinations [ 60 ]. Specifically, strengthening TERB through sustainability-oriented SMUGC and attachment-building experiences can support SDG 11 (Sustainable Cities and Communities) by helping coastal towns manage tourism-related pressures on public spaces and infrastructure, and SDG 14 (Life Below Water) by reducing littering, plastic leakage and other forms of marine pollution. Improvements in waste management, resource conservation and compliance with local rules also contribute to SDG 12 (Responsible Consumption and Production) and SDG 13 (Climate Action) by promoting low-impact tourism practices and fostering pro-environmental norms. These results align with recent work in Discover Sustainability that links sustainable tourism, local well-being and green spaces to broader SDG agendas and highlights the need for nuanced behavioural interventions in tourism policy [ 53 , 54 ]. By showing how SMUGC and place-based attachments jointly motivate TERB, the study illustrates actionable levers communication campaigns, attachment-focused experiences and behavioural nudges that policymakers and destination managers can use to operationalise SDG targets in coastal socio-ecological systems rather than treating the goals as abstract aspirations. Limitations and Future Scope This study has several limitations that offer directions for future research. The use of convenience sampling at nine beaches limits the statistical generalisability of the findings. Future work could adopt probability sampling strategies or multi-site comparisons across different coastal regions and countries to test the robustness and transferability of the model. The cross-sectional design captures perceptions and behaviours at a single point in time. Longitudinal studies could examine how repeated exposure to sustainability-oriented SMUGC, shifting social norms and repeat visits influence attachment and TERB over time. Although the model integrates several key organismic states, it does not include other potentially important factors such as social norms, perceived behavioural control, risk perceptions, mindfulness and perceptions of greenwashing [ 37 , 48 , 61 ]. Future work could extend the SOR framework to incorporate these variables or compare alternative explanations such as the theory of planned behaviour and the value-belief-norm model. This study treated social media largely in aggregate terms. Subsequent research could differentiate between platforms (e.g., Instagram, short video apps, YouTube), content types (official destination accounts vs. peer SMUGC) and algorithmic features to explore how different digital ecologies influence environmental concern, attitudes, attachment and behaviour. Furthermore, this study does not account for potential algorithmic biases and unequal exposure to sustainability-oriented content across social media platforms. Differences in platform algorithms, influencer visibility and commercial content may shape what types of environmental messages tourists encounter, as well as their perceived credibility. Future research could explicitly examine how algorithmic curation, greenwashing concerns and trust in digital sustainability communication moderate the relationship between SMUGC and environmentally responsible behaviour. Conclusion This study developed and empirically tested an SOR-based model explaining tourists’ environmentally responsible behaviour (TERB) in nine coastal destinations along the Karnataka coast of India. By integrating SMUGC operationalised through its cognitive and affective triggers environmental concern and environmental attitude, and place and cultural attachment, the model offers a comprehensive explanation of TERB in a coastal tourism context in the Global South. The results show that informative and emotionally engaging SMUGC can enhance environmental concern and positive attitudes towards environmental protection, which in turn support responsible behaviour. At the same time, strong bonds with places and local culture, cultivated through immersive and meaningful experiences, provide a powerful motivational basis for tourists to protect the destinations they visit. Conceptually, the study contributes to sustainability science by integrating digital stimuli, psychological dispositions and place-based attachments into a single behavioural framework for coastal tourism. For practitioners, the findings highlight concrete levers for promoting more sustainable tourist behaviour in coastal regions: designing sustainability-oriented SMUGC campaigns, creating attachment-building experiences, improving on-site infrastructure and using social media analytics to support adaptive management. Indirectly, such efforts can contribute to broader sustainability objectives related to responsible consumption, climate action, marine conservation and the resilience of coastal communities, thereby advancing SDGs 11 and 14. Declarations Ethics approval and consent to participate The Institutional Ethics Committee (IEC) at Kasturba Medical College and Kasturba Hospital in Manipal, Karnataka, India, waived the requirement for formal ethical approval, suggesting that “the study appears to fall under pure marketing, economic, social, and management research. If there are no health-related concerns, you may proceed without IEC approval”. The study was conducted in accordance with the ethical guidelines and regulations of the Institutional Ethics Committee. Written informed consent was obtained from all participants prior to data collection, and anonymity and confidentiality were strictly maintained. Clinical trial number Not applicable Consent for publication Not applicable. Competing interests The authors declare no competing interests Funding Open-access funding provided by Manipal Academy of Higher Education, Manipal. This research received no external funding. Author Contribution M.S.P., K.T.C., and H.G.J. conceptualised the study and designed the research framework. M.S.P. conducted the data collection. M.S.P., K.T.C., and R.J.S. performed the data analysis and methodology implementation. M.S.P. prepared the original draft of the manuscript. K.T.C. and H.G.J. supervised the study and contributed to validation and critical revision. R.J.S. contributed to the literature review and manuscript editing. All authors reviewed and approved the final manuscript. Data Availability The data used for this research is available and will be made available upon request. References Sultan MT, Sharmin F, Badulescu A, Stiubea E, Xue K. Travelers’ Responsible Environmental Behaviour towards Sustainable Coastal Tourism: An Empirical Investigation on Social Media User-Generated Content. Sustainability. 2020;13:56. 10.3390/su13010056 . Qiu H, Wang X, Wu M-Y, Wei W, Morrison AM, Kelly C. 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Singapore: Springer Nature Singapore; 2024. pp. 1031–48. 10.1007/978-981-97-4318-6_67 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8495787","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":580200381,"identity":"62e801ae-1d60-4bfd-8d13-683efd07d18b","order_by":0,"name":"Mahesh Shekar Poojary","email":"","orcid":"","institution":"Manipal Academy of Higher Education","correspondingAuthor":false,"prefix":"","firstName":"Mahesh","middleName":"Shekar","lastName":"Poojary","suffix":""},{"id":580200385,"identity":"1ead23f3-e280-4d03-a356-7ae1b278d5b4","order_by":1,"name":"Kavitha T. 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Along the Karnataka coast of India, beaches have become popular destinations for domestic and international tourists. While tourism development generates new livelihood opportunities, it simultaneously raises concerns about beach cleanliness, marine pollution and long-term ecosystem integrity.\u003c/p\u003e \u003cp\u003eTourists\u0026rsquo; environmentally responsible behaviour (TERB), such as proper waste disposal, recycling, conserving water and energy, complying with regulations and supporting conservation initiatives plays a central role in determining environmental outcomes in coastal destinations [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Previous studies link TERB to environmental concern, pro-environmental attitudes, personal values and norms, emotional responses and bonds with places and cultures [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, many studies consider these determinants in isolation, either emphasising social media influences on behaviour or focusing on place attachment and stewardship, rather than integrating digital stimuli, environmental dispositions and place-based bonds into a single behavioural framework. These dynamics align closely with the Sustainable Development Goals (SDGs). SDG 11 (Sustainable Cities and Communities) calls for inclusive, safe, resilient and sustainable human settlements, including coastal towns that depend heavily on tourism. SDG 14 (Life Below Water) stresses the conservation and sustainable use of oceans, seas and marine resources. Coastal Karnataka is exposed to climate-related risks such as sea level rise, coastal erosion and extreme weather events, making the sustainability of tourism and the resilience of local communities particularly critical. Encouraging TERB among tourists is therefore part of a broader strategy to enhance the resilience and sustainability of coastal socio-ecological systems [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTourists\u0026rsquo; encounters with destinations are increasingly mediated by social media. Social Media User Generated Content (SMUGC) on platforms such as Instagram, Facebook and YouTube influences destination image, perceived authenticity, visit intentions, loyalty and even overtourism [\u003cspan additionalcitationids=\"CR13 CR14 CR15\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Previous work has examined how social media attributes, opinion leaders and group dynamics shape travel decisions, impulsive travel, loyalty and sustainable tourism development, often drawing on the stimulus-organism-response (SOR) framework [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Sustainability-oriented SMUGC can encourage pro-environmental behaviour by providing information, shaping norms and eliciting emotional responses such as empathy and eco-guilt [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20 CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eParallel literature emphasises the importance of tourist experience, place attachment and cultural attachment for environmentally responsible behaviour and stewardship. Studies in cultural heritage sites, industrial heritage and cultural tourism destinations show that attachment to places and cultures predicts TERB, psychological ownership, environmental conservation and citizenship behaviours [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Systematic reviews underscore the central role of place attachment in environment-related behaviour and call for integrated models that connect cognitive appraisals, emotional bonds and behavioural outcomes [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite growing scholarly interest in tourists\u0026rsquo; environmentally responsible behaviour (TERB), existing studies tend to examine its determinants in a fragmented manner [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Prior research has either focused on the influence of social media user-generated content (SMUGC) on destination image, attitudes and behavioural intentions [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], or on the role of place attachment and stewardship in shaping pro-environmental behaviour [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Only limited empirical work has integrated digital stimuli, environmental dispositions and place-based attachments within a single behavioural framework, particularly in real-world coastal tourism settings in the Global South [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, most SMUGC-based tourism studies treat social media exposure as a homogeneous construct, without distinguishing between its cognitive (informational and credibility-related) and affective (emotional and aesthetic) properties that may differentially influence environmental concern and attitudes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. At the same time, while place attachment has been widely recognised as a driver of environmentally responsible behaviour [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e],the role of cultural attachment, especially in culturally embedded coastal destinations, remains underexplored in sustainability-oriented tourism research [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDrawing on the SOR framework, this study addresses these gaps by conceptualising sustainability-oriented SMUGC as the stimulus (S), operationalised through cognitive and affective triggers; environmental concern, environmental attitude, place attachment and cultural attachment as organismic states (O); and TERB as the behavioural response (R). Using survey data from 432 tourists across nine beaches along the Karnataka coast of India, the study aims to:\u003c/p\u003e \u003cp\u003e1. Develop and test an integrated SOR-based model linking SMUGC, environmental dispositions, place attachment and cultural attachment to TERB in a coastal tourism context.\u003c/p\u003e \u003cp\u003e2. Empirically examine the distinct effects of cognitive and affective SMUGC triggers on environmental concern and environmental attitude.\u003c/p\u003e \u003cp\u003e3. Derive practical implications for destination managers and policymakers seeking to promote sustainable coastal tourism and advance SDGs 11 and 14.\u003c/p\u003e \u003ch2\u003e2. Literature Review and Hypotheses\u003c/h2\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Social Media UGC as Cognitive and Affective Stimulus\u003c/h2\u003e \u003cp\u003eSocial media has become a dominant information source for tourists, shaping destination image, perceived authenticity, visit intentions and loyalty [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. SMUGC on platforms such as Instagram and YouTube allows travellers to access peer experiences, visual impressions and evaluations of destinations in real time [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Empirical studies show that SMUGC influences destination imagery and visit intentions [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and loyalty behaviour in heritage contexts [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Beyond marketing outcomes, there is growing interest in the role of SMUGC in supporting sustainable tourism [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWithin the SOR framework, platform attributes such as vividness, interactivity and credibility are conceptualised as stimuli that shape internal psychological states (organism), including emotions, attitudes and perceived value, which then influence behavioural responses such as impulsive travel or purchase intentions [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This conceptual framework has been applied to the context of social media within the tourism sector, displaying that specific attributes can elicit organismic reactions, which subsequently lead to behavioural outcomes [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn sustainability contexts, digital media can provide both cognitive and affective triggers. Environmentally oriented SMUGC and short videos can convey information about environmental problems and low-impact options (cognitive triggers), while immersive or aesthetic digital experiences can evoke emotional responses such as awe, eco guilt and empathy [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. For instance, virtual experiences can enhance environmental responsibility through aesthetic engagement; environment friendly short videos can increase low-carbon tourism intentions [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]; and digital content that induces eco guilt and empathy with nature can foster pro-environmental behaviour in tourists [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Social media can also create conformity pressures: seeing peers engage in pro-environmental actions can encourage users to imitate similar behaviours [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDrawing on this literature, this study conceptualises SMUGC through two dimensions:\u003c/p\u003e \u003cp\u003eCognitive triggers: perceived informativeness, credibility and clarity of environmental and destination-related information [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAffective triggers: emotional arousal, aesthetic appreciation and empathy elicited by coastal and community-related content [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWithin the SOR framework, these cognitive and affective triggers represent the stimuli (S) that shape tourists\u0026rsquo; internal environmental dispositions. Accordingly, we hypothesise:\u003c/p\u003e \u003cp\u003eH1a. Cognitive triggers in SMUGC positively influence tourists\u0026rsquo; environmental concern.\u003c/p\u003e \u003cp\u003eH1b. Affective triggers in SMUGC positively influence tourists\u0026rsquo; environmental concern.\u003c/p\u003e \u003cp\u003eH2a. Cognitive triggers in SMUGC positively influence tourists\u0026rsquo; environmental attitude.\u003c/p\u003e \u003cp\u003eH2b. Affective triggers in SMUGC positively influence tourists\u0026rsquo; environmental attitude.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Environmental Concern, Environmental Attitude and TERB\u003c/h2\u003e \u003cp\u003eEnvironmental concern and environmental attitude are widely recognised as key antecedents of pro-environmental behaviour [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In tourism, environmentally responsible behaviour has been examined in nature-based tourism, cultural heritage sites and coastal destinations [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Conceptual work on nature-based tourists highlights the importance of clarifying related concepts and measurement approaches for environmentally responsible behaviour [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Empirical studies show that tourists with stronger environmental concern and more positive environmental attitudes are more likely to engage in behaviours such as proper waste disposal, resource conservation and support for conservation initiatives [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe value-belief-norm (VBN) framework and related models provide theoretical support for the role of concern and attitudes. For example, research on food festival attendees demonstrates that environmental values and beliefs shape pro-environmental intentions through norm activation and attitudes [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Similar mechanisms have been observed in other tourism and leisure contexts where concern, values and attitudes contribute to environmentally responsible behaviour [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In coastal destinations specifically, environmental attitudes and perceptions of responsibility have been linked to tourists\u0026rsquo; responsible behaviour, including waste management and compliance with regulations [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, environmental concern is defined as awareness of environmental issues and willingness to address them, whereas environmental attitude captures relatively stable evaluations of environmental protection and related behaviours. Both are treated as organism (O) that mediate the influence of social media stimuli on TERB. We therefore propose:\u003c/p\u003e \u003cp\u003eH3. Environmental concern positively influences tourists\u0026rsquo; environmentally responsible behaviour.\u003c/p\u003e \u003cp\u003eH4. Environmental attitude positively influences tourists\u0026rsquo; environmentally responsible behaviour.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Place Attachment, Cultural Attachment and TERB\u003c/h2\u003e \u003cp\u003ePlace attachment refers to the emotional and cognitive bonds individuals form with specific places, often operationalised through place identity and place dependence [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Early work by Vaske and Kobrin [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] showed that place attachment predicts environmentally responsible behaviour among recreationists, providing a foundation for numerous subsequent studies. Systematic reviews confirm that place attachment plays a central role in environment-related behaviour, acting as a motivational basis for stewardship and conservation [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn tourism, place attachment has been integrated into models explaining environmentally responsible behaviour and related outcomes. Research at cultural heritage sites and other destinations indicates that place attachment can mediate the relationship between destination attractiveness and tourists\u0026rsquo; environmentally responsible behaviour [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], and that psychological ownership can serve as a mechanism linking attachment and pro-environmental behaviour [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Conceptual overviews further highlight the importance of place attachment in tourism research and its connection to sustainability outcomes [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCultural attachment, referring to emotional ties to the cultural meanings and heritage of a destination, has also been shown to influence environmentally responsible behaviour. At cultural heritage sites, tourism experiences can foster cultural attachment, which then promotes tourists\u0026rsquo; environmentally responsible behaviour and citizenship behaviours [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Studies in industrial heritage settings indicate that perceived authenticity and place attachment are associated with tourists\u0026rsquo; environmental behaviour [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Work on cultural tourism destinations suggests that fascination with a place, combined with attachment, can support environmental stewardship [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Place identity and attachment to local communities are also linked to conservation intentions in rural heritage villages [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, place attachment and cultural attachment are conceptualised as additional organism (O), reflecting emotional and cognitive bonds formed through repeated or meaningful interactions with coastal places and cultures. Rather than being purely structural characteristics of destinations, they represent internalised connections that can motivate stewardship behaviour. Based on prior evidence, we hypothesise:\u003c/p\u003e \u003cp\u003eH5. Place attachment positively influences tourists\u0026rsquo; environmentally responsible behaviour.\u003c/p\u003e \u003cp\u003eH6. Cultural attachment positively influences tourists\u0026rsquo; environmentally responsible behaviour.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Conceptual Model\u003c/h2\u003e \u003cp\u003eBringing these strands together, the proposed SOR based model positions SMUGC, represented by its cognitive and affective triggers, as the stimulus (S). Environmental concern, environmental attitude, place attachment and cultural attachment represent distinct but related organism (O) that capture tourists\u0026rsquo; cognitive evaluations and emotional bonds. Tourists\u0026rsquo; environmentally responsible behaviour (TERB) constitutes the response (R), expressed through waste management, resource conservation and compliance with rules in the beach context.\u003c/p\u003e \u003cp\u003eThis configuration extends prior SOR applications in tourism in two ways. First, it moves beyond models that focus solely on environmental concern and attitude by incorporating place attachment and cultural attachment as additional organism that directly shape TERB [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Second, it treats SMUGC explicitly in terms of cognitive and affective triggers, allowing a more nuanced assessment of how different qualities of social media content influence environmental dispositions.\u003c/p\u003e \u003cp\u003eAccordingly, the model specifies paths from cognitive and affective triggers of SMUGC to environmental concern and environmental attitude (H1a, H1b, H2a, H2b), from environmental concern and environmental attitude to TERB (H3,H4), and from place attachment and cultural attachment to TERB (H5,H6). The conceptual model is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, where the S, O and R components are explicitly indicated.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Study Area\u003c/h2\u003e \u003cp\u003eThe empirical study was conducted at nine beaches along the Karnataka coast of India. Malpe, Kapu, Padubidri, Panambur, Thannirbavi, NITK, Karwar, Gokarna and Murdeshwara. These sites are important tourism nodes combining recreational, religious and cultural functions and are frequently featured in SMUGC posts. The beaches are representative of rapidly developing coastal destinations where tourism growth, cultural activities and environmental pressures intersect [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Research Design and Instrument\u003c/h2\u003e \u003cp\u003eA cross-sectional survey design was adopted. A structured questionnaire contained two sections. Section A captured socio-demographic and trip characteristics, including gender, age, education, place of residence, frequency of coastal visits, main purpose of visit, primary social media platforms used and survey location. Section B consisted of multi-item five-point Likert scales (1\u0026thinsp;=\u0026thinsp;strongly disagree, 5\u0026thinsp;=\u0026thinsp;strongly agree). Measurement items were adapted from established scales. The measurement items for the constructs CT, AT, EA, EC, PA, CA and TERB are included from the previous research that was reliable and valid. The questionnaire consisted of a total of 33 items. The CT was measured using four items [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], AT using four items [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], EC using eight items [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], EA using four items [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], PA using four items [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], CA using three items [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and TERB using six items [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Items were reworded to fit the coastal tourism context to refer specifically to beaches and related environment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Sampling and Data Collection\u003c/h2\u003e \u003cp\u003eBecause a sampling frame for tourists at the study sites was unavailable, a convenience sampling approach was used. Trained surveyors approached tourists at each beach during morning and evening periods, briefly explained the study and invited participation. The Inclusion criteria required respondents to be at least 18 years old, visiting for leisure or tourism and having at least one active social media account (Instagram, Facebook or YouTube). Participation was voluntary and anonymous. Informed consent was obtained, and no personally identifiable information was collected.\u003c/p\u003e \u003cp\u003eOut of the 453 questionnaires distributed, 432 valid responses were retained after excluding those that were incomplete or inconsistent, resulting in a usable response rate of approximately 95%. This sample size is consistent with the recommendations for PLS-SEM, considering the number of constructs, indicators, and the complexity of the model [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Data Analysis\u003c/h2\u003e \u003cp\u003eThe study used the Partial Least Squares Structural Equation Modelling (PLS-SEM) approach for both the specification and evaluation of the research model. All constructs in the study were modelled as reflective, as done in earlier sustainable tourism and environmental behaviour research. PLS-SEM was used due to the study\u0026rsquo;s predictive orientation, the complexity of the proposed model. Through this approach, the measurement model was assessed to determine the reliability and validity of the constructs, while the structural model was evaluated to examine the proposed relationships among the variables, while ensuring that the model met the required psychometric and predictive standards [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Sample Profile\u003c/h2\u003e \u003cp\u003eValid responses to this study were received from 432 beach tourists who visited designated beaches on the Karnataka Coastline. All respondents were recreational travellers using at least one social media platform (Instagram, Facebook, YouTube). The sample included a diverse mix of genders, age groups, and educational levels, with domestic tourists constituting the majority and a smaller group of international visitors. Detailed sociodemographic data are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographical data\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-binary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;20 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;20-\u0026le; 30 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e36.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30-\u0026le; 40 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;40-\u0026le; 50 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;50-\u0026le; 60 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational qualification\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh school or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11th -12th\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBachelor\u0026rsquo;s degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMaster\u0026rsquo;s degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbove Master\u0026rsquo;s degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSelf-employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmployee\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHomemaker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnnual income level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le; ₹3,00,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt; ₹3,00,000-\u0026le; ₹5,00,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt; ₹5,00,000-\u0026le; ₹8,00,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt; ₹8,00,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNationality\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndian Tourist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e91.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInternational Tourist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLocal resident status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLocal resident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e43.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon local resident\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e56.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocial media platforms used\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInstagram\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFacebook\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e50.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYouTube\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e51.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e215\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Construct Reliability and Validity\u003c/h2\u003e \u003cp\u003eAs noted by [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], composite reliability is employed to assess internal consistency and individual indicator reliability, while average variance extracted (AVE) is utilized to evaluate convergent validity within the reflective measurement model. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the values for Cronbach\u0026rsquo;s Alpha, Composite Reliability, and Average Variance Extracted (AVE). The composite reliability exceeds 0.8, Cronbach\u0026rsquo;s Alpha is greater than 0.7, and the average variance extracted is greater than 0.5 for all constructs. Hence, these results suggest that the constructs utilized in the study demonstrate good validity and reliability [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults of construct reliability and validity analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCronbach\u0026rsquo;s alpha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eComposite Reliability\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAVE\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.904\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.776\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.838\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.754\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.782\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.860\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.704\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.940\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.706\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.903\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTERB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.918\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAT: Affective Trigger, CA: Cultural Attachment, CT: Cognitive Trigger, EA: Environmental Attitude, EC: Environmental Concern, PA: Place Attachment, TERB: Tourists Environmentally Responsible Behaviour.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.3 HTMT values of the constructs\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e provides an analysis of discriminant validity through the heterotrait-monotrait ratio (HTMT). According to [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], an HTMT value must be below 0.90 to be deemed significant. Therefore, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e verifies that all HTMT values fall below this threshold, confirming the discriminant validity of the construct. Once the construct's reliability and validity are established, the subsequent step involves evaluating the structural model.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHTMT Value\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTERB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eHTMT confidence interval does not include 1\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTERB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.546\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Results of Structural Model\u003c/h2\u003e \u003cp\u003eThe conceptual model illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e describes the path coefficient, indicating the strength of the relationships between the variables, outer loading and R\u003csup\u003e2\u003c/sup\u003e values of EC, EA, and TERB. As seen in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the path coefficient values among all constructs indicate stronger relationships, as these values are above 0.10 [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. In addition, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e demonstrates that the outer loadings of all constructs surpass the threshold value of 0.7, indicating satisfactory levels of indicator reliability. The R\u003csup\u003e2\u003c/sup\u003e value of TERB accounts for 57.7% of the variance. According to [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], an R\u003csup\u003e2\u003c/sup\u003e value of 0.25 is considered weak, 0.50 moderate, and 0.75 high for endogenous variables. The R\u003csup\u003e2\u003c/sup\u003e value for TERB is reasonably moderate, which suggests that the structural model has predictive validity. However, the R\u003csup\u003e2\u003c/sup\u003e values for EC and EA account for 58% and 54.3%, respectively, indicating moderate variance.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents a summary of the hypothesis testing outcomes derived from the bootstrapping procedure in PLS-SEM, detailing standardized path coefficients, t-values, and corresponding significance levels. The results show that all hypothesized relationships are statistically significant as P values are less than 0.001 level, thereby offering robust empirical support for the proposed model [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Both cognitive and affective triggers of SMUGC have strong positive effects on environmental concern and environmental attitude (H1a, H1b, H2a, H2b), confirming the role of sustainability-oriented digital stimuli as key antecedents of tourists\u0026rsquo; environmentally responsible behaviour. Moreover, environmental concern and environmental attitude are shown to positively influence TERB (H3 and H4). Also, place attachment and cultural attachment exhibit significant direct effects on environmentally responsible behaviour (H5 and H6), suggesting that emotional bonds with places and local culture act as important motivational bases for responsible tourist behaviour in coastal destinations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHypotheses testing results of the structural model.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypothesis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePath coefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eT values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP values\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eConclusion\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH1a: CT -\u0026gt; EC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.634\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH1b: AT -\u0026gt; EC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH2a: CT -\u0026gt; EA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.290\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH2b: AT -\u0026gt; EA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH3: EC -\u0026gt; TERB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.291\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH4: EA -\u0026gt; TERB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.914\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH5: PA -\u0026gt; TERB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH6: CA -\u0026gt; TERB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.284\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.881\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSupported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*** p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Structural Model Estimates\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrates the model fit, reporting an SRMR of 0.039 for the saturated model and an NFI of 0.912. As per [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], an NFI value close to 1 and an SRMR value below 0.08 signify a good model fit. The structural model values for SRMR and NFI, as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, align with these criteria, thereby confirming the model's adequacy in terms of fit.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModel Fit\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSaturated Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEstimated Model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSRMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD_ULS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.964\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD_G\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.381\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChi-square\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e911.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e941.758\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNFI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis research makes a notable contribution to the field of sustainability-oriented tourism by bringing together social media stimuli, environmental dispositions and place-based attachments within a SOR framework. This approach illustrates TERB in coastal destinations. The study's findings not only support existing evidence on the impact of environmental concern, attitudes, and place attachment on responsible behaviour but also expand the current literature by showing how sustainability-oriented SMUGC, divided into cognitive and affective triggers, indirectly influences TERB through cognitive and emotional routes. Consequently, the research enhances the understanding of the combined role of digital communication and on-site emotional connections in influencing pro-environmental behaviour within coastal tourism contexts in the Global South.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Social Media UGC as a Driver of Environmental Dispositions\u003c/h2\u003e \u003cp\u003eThe significanstrong influence of cognitive and affective SMUGC triggers on environmental concern and environmental attitude highlights the critical role of social media as a medium for sustainability communication in coastal tourism [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. From a SOR theory perspective, SMUGC serves as a multidimensional stimulus that enhances both information-based and emotion-based organismic states. The strong correlation between affective triggers and environmental attitude suggests that emotionally engaging and aesthetically appealing content is particularly effective in shaping positive evaluations of environmental protection, consistent with evidence from environment friendly short videos [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBy explicitly distinguishing cognitive and affective triggers within SMUGC, this study extends previous work that treated social media exposure more generically [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Identifying which aspects of digital communication, such as informative messages, credibility cues, emotional storytelling or aesthetic imagery, are most closely associated with shifts in environmental concern and attitudes provides practical guidance for destination communication strategies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Environmental Concern and Attitude as Predictors of TERB\u003c/h2\u003e \u003cp\u003eEnvironmental concern and environmental attitude both exerted significant positive effects on TERB, underscoring their role as key organism in the SOR model and aligning with value-belief-norm and related frameworks [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The relatively stronger effect of environmental attitude indicates that context-specific evaluations of behaviours such as not littering, conserving water and following local rules are particularly influential [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. This is consistent with studies showing that attitudes towards concrete behaviours are central in predicting intentions and actions in festival and youth tourism contexts [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe findings also align with research on risk perception and norm activation in tourism [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], suggesting that strengthening positive environmental attitudes in specific destinations may be an effective way to translate general concern into concrete action.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e5.3 Place and Cultural Attachment as Motivational Bases for TERB\u003c/h2\u003e \u003cp\u003ePlace attachment and cultural attachment also emerged as important organisms that directly motivate TERB. Place attachment displayed the largest direct effect on TERB among all predictors, reinforcing extensive evidence that emotional bonds with destinations foster stewardship and conservation behaviour [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Cultural attachment further contributed to TERB, supporting findings from heritage and cultural tourism settings where attachment to local culture encourages environmentally responsible and citizenship behaviours [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the coastal Karnataka context, beaches are intertwined with temples, religious activities, festivals and fishing communities. Experiences that foster emotional connections with these cultural landscapes appear to motivate tourists to care for and protect them. This highlights the need to treat attachment building not as a byproduct of tourism development but as a deliberate component of sustainable coastal destination strategies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e5.4 Theoretical Contributions\u003c/h2\u003e \u003cp\u003eThis study makes three main theoretical contributions. It integrates digital media stimuli, environmental dispositions and place-based attachments into a single SOR framework for explaining tourists\u0026rsquo; environmentally responsible behaviour (TERB) in coastal tourism. Existing SOR applications in tourism and hospitality have predominantly focused on social media influences on intentions and loyalty or on environmentally responsible behaviour, without simultaneously considering place-based bonds [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. By treating SMUGC through its cognitive and affective triggers as the stimulus and environmental concern, environmental attitude, place attachment and cultural attachment as the organism, the model connects digital communication, psychological processes and behavioural responses in a unified structure.\u003c/p\u003e \u003cp\u003eThe study advances SMUGC research by explicitly distinguishing between cognitive and affective triggers as separate but related dimensions of the digital stimulus rather than relying on hierarchical terminology. Prior work often measures social media exposure in aggregate terms or focuses primarily on informational qualities [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Distinguishing perceived informativeness and credibility (cognitive triggers) from emotional arousal, empathy and aesthetic appreciation (affective triggers) clarifies how different qualities of SMUGC influence environmental concern and attitudes. This responds to recent calls to better understand how digital communication and nudging strategies shape sustainability-related behaviour in a rapidly evolving media landscape [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe study positions place attachment and cultural attachment as organismic states that directly motivate TERB, alongside environmental concern and attitude. While reviews of place attachment and environment-related behaviour emphasise the importance of emotional bonds for stewardship [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], and recent sustainable tourism research highlights links between tourism, local communities and SDGs, the micro-level behavioural role of place and culture-based attachment in coastal destinations remains underexplored [\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. By demonstrating that place attachment has the strongest direct effect on TERB and that cultural attachment is also a significant predictor, this study shows that digital stimuli and on-site attachment-building processes are complementary rather than competing pathways for promoting responsible behaviour in coastal socio-ecological systems.\u003c/p\u003e \u003cp\u003eIn combination, these contributions position the SOR-based TERB model within emerging sustainable tourism scholarship that maps SDG-related themes and calls for more behaviourally grounded evidence, particularly in the Global South [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eManagerial Implications\u003c/h3\u003e\n\u003cp\u003eThe findings suggest several implications for destination managers, tourism businesses and local authorities in coastal regions.\u003c/p\u003e \u003cp\u003eDestination managers can co-create sustainability-oriented SMUGC campaigns with influencers, local creators, residents and visitors. Campaigns that portray both the beauty and vulnerability of coastal environments are likely to activate both the cognitive and affective triggers identified in this study. Communication strategies should deliberately blend factual information with emotional storytelling. Clear messages about rules, available facilities and environmental impacts can be combined with narratives, photographs and short videos featuring local community members, lifeguards, conservation volunteers and tourists who demonstrate responsible behaviour. Such content can strengthen environmental concern and attitudes while also building empathy with local people and ecosystems.[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eTourist service providers should emphasise on experiences that foster place and cultural attachment. Examples include heritage trails linking beaches with nearby temples and fishing hamlets, community-led tours, homestay programmes and opportunities to participate in local festivals and conservation activities such as beach clean-ups or mangrove planting. These immersive experiences deepen emotional bonds with the destination and can motivate tourists to act as stewards. On-site infrastructure and behavioural cues must support responsible choices. Adequate bins, recycling facilities, water refill points and signage are basic prerequisites. Behavioural \u0026ldquo;nudges\u0026rdquo; at entrances, food stalls and scenic viewpoints such as reminders about plastic use, prompts to sort waste, or messages highlighting the responsible behaviour of other visitors can make environmentally responsible choices easier and more salient [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDestination managers can use social media data for monitoring and adaptive management. Tracking hashtags, geotags, sentiment and content themes can help identify hotspots of crowding or environmental stress and reveal how tourists represent the destination online. These insights can inform targeted communication, visitor dispersion strategies and collaborations with residents to co-create more sustainable tourism pathways. In this way, digital and on-site interventions can jointly contribute to SDGs 11 and 14 by enhancing the resilience of coastal socio-ecological systems [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e6.1 Implications for the Sustainable Development Goals (SDGs)\u003c/h2\u003e \u003cp\u003eThe findings have direct implications for the achievement of several Sustainable Development Goals (SDGs) in tourism-dependent coastal regions. At the macro level, recent reviews of tourism research show that integrating the SDGs into tourism practices is essential for moving towards a more sustainable and responsible sector, yet empirical studies connecting micro-level tourist behaviour with SDG outcomes remain comparatively scarce [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. By focusing on tourists\u0026rsquo; environmentally responsible behaviour (TERB) in coastal Karnataka, this study provides behaviourally grounded evidence that complements system-level analyses of sustainable tourism development and carrying capacity in coastal destinations [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSpecifically, strengthening TERB through sustainability-oriented SMUGC and attachment-building experiences can support SDG 11 (Sustainable Cities and Communities) by helping coastal towns manage tourism-related pressures on public spaces and infrastructure, and SDG 14 (Life Below Water) by reducing littering, plastic leakage and other forms of marine pollution. Improvements in waste management, resource conservation and compliance with local rules also contribute to SDG 12 (Responsible Consumption and Production) and SDG 13 (Climate Action) by promoting low-impact tourism practices and fostering pro-environmental norms. These results align with recent work in \u003cem\u003eDiscover Sustainability\u003c/em\u003e that links sustainable tourism, local well-being and green spaces to broader SDG agendas and highlights the need for nuanced behavioural interventions in tourism policy [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. By showing how SMUGC and place-based attachments jointly motivate TERB, the study illustrates actionable levers communication campaigns, attachment-focused experiences and behavioural nudges that policymakers and destination managers can use to operationalise SDG targets in coastal socio-ecological systems rather than treating the goals as abstract aspirations.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eLimitations and Future Scope\u003c/h3\u003e\n\u003cp\u003eThis study has several limitations that offer directions for future research. The use of convenience sampling at nine beaches limits the statistical generalisability of the findings. Future work could adopt probability sampling strategies or multi-site comparisons across different coastal regions and countries to test the robustness and transferability of the model.\u003c/p\u003e \u003cp\u003eThe cross-sectional design captures perceptions and behaviours at a single point in time. Longitudinal studies could examine how repeated exposure to sustainability-oriented SMUGC, shifting social norms and repeat visits influence attachment and TERB over time.\u003c/p\u003e \u003cp\u003eAlthough the model integrates several key organismic states, it does not include other potentially important factors such as social norms, perceived behavioural control, risk perceptions, mindfulness and perceptions of greenwashing [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Future work could extend the SOR framework to incorporate these variables or compare alternative explanations such as the theory of planned behaviour and the value-belief-norm model.\u003c/p\u003e \u003cp\u003eThis study treated social media largely in aggregate terms. Subsequent research could differentiate between platforms (e.g., Instagram, short video apps, YouTube), content types (official destination accounts vs. peer SMUGC) and algorithmic features to explore how different digital ecologies influence environmental concern, attitudes, attachment and behaviour. Furthermore, this study does not account for potential algorithmic biases and unequal exposure to sustainability-oriented content across social media platforms. Differences in platform algorithms, influencer visibility and commercial content may shape what types of environmental messages tourists encounter, as well as their perceived credibility. Future research could explicitly examine how algorithmic curation, greenwashing concerns and trust in digital sustainability communication moderate the relationship between SMUGC and environmentally responsible behaviour.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study developed and empirically tested an SOR-based model explaining tourists\u0026rsquo; environmentally responsible behaviour (TERB) in nine coastal destinations along the Karnataka coast of India. By integrating SMUGC operationalised through its cognitive and affective triggers environmental concern and environmental attitude, and place and cultural attachment, the model offers a comprehensive explanation of TERB in a coastal tourism context in the Global South.\u003c/p\u003e \u003cp\u003eThe results show that informative and emotionally engaging SMUGC can enhance environmental concern and positive attitudes towards environmental protection, which in turn support responsible behaviour. At the same time, strong bonds with places and local culture, cultivated through immersive and meaningful experiences, provide a powerful motivational basis for tourists to protect the destinations they visit. Conceptually, the study contributes to sustainability science by integrating digital stimuli, psychological dispositions and place-based attachments into a single behavioural framework for coastal tourism.\u003c/p\u003e \u003cp\u003eFor practitioners, the findings highlight concrete levers for promoting more sustainable tourist behaviour in coastal regions: designing sustainability-oriented SMUGC campaigns, creating attachment-building experiences, improving on-site infrastructure and using social media analytics to support adaptive management. Indirectly, such efforts can contribute to broader sustainability objectives related to responsible consumption, climate action, marine conservation and the resilience of coastal communities, thereby advancing SDGs 11 and 14.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eThe Institutional Ethics Committee (IEC) at Kasturba Medical College and Kasturba Hospital in Manipal, Karnataka, India, waived the requirement for formal ethical approval, suggesting that \u0026ldquo;the study appears to fall under pure marketing, economic, social, and management research. If there are no health-related concerns, you may proceed without IEC approval\u0026rdquo;. The study was conducted in accordance with the ethical guidelines and regulations of the Institutional Ethics Committee. Written informed consent was obtained from all participants prior to data collection, and anonymity and confidentiality were strictly maintained.\u003c/p\u003e \u003ch2\u003eClinical trial number\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003ch2\u003eConsent for publication\u003c/h2\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eOpen-access funding provided by Manipal Academy of Higher Education, Manipal. This research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eM.S.P., K.T.C., and H.G.J. conceptualised the study and designed the research framework. M.S.P. conducted the data collection. M.S.P., K.T.C., and R.J.S. performed the data analysis and methodology implementation. M.S.P. prepared the original draft of the manuscript. K.T.C. and H.G.J. supervised the study and contributed to validation and critical revision. R.J.S. contributed to the literature review and manuscript editing. All authors reviewed and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data used for this research is available and will be made available upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSultan MT, Sharmin F, Badulescu A, Stiubea E, Xue K. Travelers\u0026rsquo; Responsible Environmental Behaviour towards Sustainable Coastal Tourism: An Empirical Investigation on Social Media User-Generated Content. 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Singapore: Springer Nature Singapore; 2024. pp. 1031\u0026ndash;48. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-981-97-4318-6_67\u003c/span\u003e\u003cspan address=\"10.1007/978-981-97-4318-6_67\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"environmentally responsible behaviour, social media, user generated content, place attachment, cultural attachment, coastal tourism, SOR","lastPublishedDoi":"10.21203/rs.3.rs-8495787/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8495787/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCoastal tourism provides important economic benefits while also placing environmental pressures on fragile beach and marine ecosystems. Therefore, encouraging tourists' environmentally responsible behaviour (TERB) is essential for promoting sustainable coastal tourism and achieving the Sustainable Development Goals (SDGs). This study uses the stimulus-organism-response (SOR) framework to develop and test an integrated model that connects sustainability-oriented social media user-generated content (SMUGC), environmental dispositions, and place-based attachments to TERB. Data were collected from 432 tourists visiting nine beaches along the Karnataka coast of India and analysed using partial least squares structural equation modelling (PLS-SEM). The results show that both cognitive (informativeness and credibility) and affective (emotional and aesthetic) triggers of SMUGC strongly improve tourists' environmental concern and environmental attitude. These environmental dispositions, in turn, positively influence TERB. Furthermore, place attachment and cultural attachment exert strong direct effects on environmentally responsible behaviour. The proposed model accounts for 57.7% of the variance in TERB, showing strong explanatory power. By integrating digital media stimuli with environmental psychology and place-based attachments, this study advances sustainability-oriented tourism research and provides valuable insights for destination managers and policymakers. The results highlight the importance of combining sustainability-focused social media communication with attachment-building tourism experiences to promote responsible tourist behaviour and enhance the resilience of coastal socio-ecological systems.\u003c/p\u003e","manuscriptTitle":"Social media and place based attachment as pathways to environmentally responsible coastal tourism","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-28 13:57:35","doi":"10.21203/rs.3.rs-8495787/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4dcabb4d-5762-4852-b8dd-e8de920591eb","owner":[],"postedDate":"January 28th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-10T10:40:38+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-28 13:57:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8495787","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8495787","identity":"rs-8495787","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}