Tourism livestreaming allows global audiences to encounter destinations in real time, yet how livestreamers’ expressive behaviors shape audiences’ destination evaluations across cultures remains unclear. Drawing on a performative perspective, this research conceptualizes expressed destination image formation as a temporally situated process generated through live narrative enactment. Using multimodal cross-cultural livestream data, the study shows that emotional expression is positively associated with expressed affective destination image, explicit self-disclosure is positively associated with expressed cognitive image, and interactive engagement shows partial evidence of an inverted U-shaped relationship with expressed cognitive destination image. Cross-cultural proximity further operates unevenly: cultural distance reshapes the interaction–cognition pathway, whereas linguistic accessibility improves destination image expression but does not consistently amplify performative cues. Finally, post-livestream destination image expression attenuates over time, with affective impressions fading faster. Overall, this research clarifies how destination image expression is performatively activated, cross-culturally conditioned, and temporally attenuated in tourism livestreaming.
Destinations evolve through lifecycles, with a very real risk of entering long-term decline in the post-maturity phase. Decline is not inevitable, though, for it depends on whether destination stakeholders recognise early symptoms and respond appropriately. Unfortunately, the literature suggests that timely, anticipatory responses are rare. Instead, most destinations fail to detect or act on early warning signals and only respond reactively after decline has set in. This paper develops a conceptual model that identifies and contrasts reactive and proactive responses to post-maturity decline. The model is derived from a systematic synthesis of case-study evidence of 50 case studies examining destination decline and attempts at rejuvenation.
Marketing unpredictable tourism experiences like aurora or wildlife viewing poses distinct challenges due to their inherent uncertainty, yet research on effective strategies remains limited. In Stage I of this Registered Report, we proposed that cause-related marketing (CRM) would boost purchase intention for unpredictable tourism products more effectively than traditional discounts by activating a karmic investment mechanism (i.e., self-luck expectancy), especially under consumer-focused framing. Through an eye-tracking experiment, a quasi-experimental field study, and three scenario-based experiments, we found no conclusive evidence that CRM outperforms discounts in increasing purchase intention, nor support for the mediating role of self-luck expectancy. Although a moderating influence of protagonist focus was observed, its effect contradicted our hypothesis. However, an unexpected finding emerged: luck primes significantly elevate self-luck expectancy and enhance purchase intention. These results suggest that practitioners should either exercise caution in deploying standard CRM from a cost-benefit perspective or enhance its utility by fostering deeper consumer moral engagement.
Tourism studies have largely examined cultural identification through encounters with difference, while paying less attention to culturally proximate travel contexts. Drawing on schema theory, this study examines how latent cultural identification (LCI) emerges when sedimented cultural meanings become perceptible and interpretable during travel. Based on interviews with 41 Vietnamese tourists traveling in China, the findings indicate that material, social, and mediated cues make routinized meanings noticeable, while internalized cultural schemata help tourists interpret them in relation to their cultural self-understanding. Affective resonance amplifies this process by intensifying the salience and self-relevance of interpreted meanings. Behavioural responses vary across compliance, inquiry, reinterpretation, and co-creation, reflecting different degrees of self-reflection and social embeddedness. By highlighting the role of cultural schemata in LCI, this study extends tourism identity research and shows how LCI can help tourists locate their own culture within the wider world-cultural landscape, enrich personal meaning-making, and foster intercultural exchange.
Although mindfulness interventions have been found to play a critical role in improving employee well-being and job performance, empirical evidence from the hospitality industry remains scarce. Grounded in workplace mindfulness theory, this study explores how daily mindfulness interventions coupled with human coaching guidance influence psychological states (self-acceptance and serenity) and work behaviors (job crafting and helping behavior) among hospitality employees. Specifically, with the support of a human coach, employees participated in 10 consecutive days of systematic mindfulness intervention sessions, and the experience sampling method (ESM) was employed to assess the effects on psychological and behavioral outcomes. The multilevel modeling revealed that the intervention significantly enhanced participants’ psychological and behavioral functioning, with effects varying as a function of baseline levels. Based on these findings, hospitality managers are encouraged to adopt evidence-based mindfulness intervention programs to foster employees’ psychological well-being and proactive work behaviors.
Generative AI (GAI) is increasingly mediating tourism service encounters, reshaping GAI failure recovery within a broader tourist–employee–GAI service configuration, in which GAI serves as the failure source, employees act as recovery agents, and tourists are the end recipients. Drawing on Mind Perception Theory, we theorize and test a post-failure recovery tactic in which employees intentionally foreground anthropomorphic aspects of the failing GAI during recovery interactions. Across six scenario-based experiments and two on-site simulation studies (N = 2061), results provide convergent evidence that employee-led disclosure of GAI anthropomorphism (vs. control) improves recovery outcomes for both tourists and employees through mirrored mechanisms. Specifically, it increases tourist forgiveness by elevating perceived GAI experience and increases state employee satisfaction by elevating perceived GAI agency. These benefits weaken under high tourist anger or employees' perceptions of tourist anger and are further contingent on tourists' AI expertise and employees’ competitive versus collaborative mindset. The findings advance tourism research by offering parallel dyadic evidence on GAI failure recovery beyond a tourist-centric lens, extending Mind Perception Theory through stakeholder-contingent effects of perceived experience and perceived agency, and repositioning anthropomorphism in recovery as a co-produced mechanism jointly enacted through employee framing and available GAI interface affordances.
Stablecoins are increasingly discussed as an emerging form of digital tourism payment infrastructure. This study examines whether instability in stablecoins creates vulnerabilities in emerging tourism payment ecosystems by analysing the UST and USDC depeg events. Drawing on tourism systems theory, tourism resilience theory, and financial economics, the analysis combines high-frequency market data, on-chain transaction activity, and tourism payment indicators. The results show that depeg events degrade market quality by widening bid–ask spreads, reducing market depth, and increasing transaction costs. Large market participants also reduce risk-bearing and withdraw liquidity during periods of stress. In addition, depeg events strengthen dynamic correlations among closely linked stablecoins. Evidence from tourism payment activity suggests that severe depeg events may reduce the use of stablecoin-based payments within crypto-native tourism ecosystems. The findings suggest that instability in stablecoins may introduce settlement uncertainty and payment frictions within tourism ecosystems experimenting with blockchain-based payment infrastructure.
Influencers exert significant promotional effects in tourism marketing; however, few empirical studies have examined how different types of tourism activities can strategically leverage these effects through influencer narrative style. To address this gap, this study draws on Heuristic-Analytic Theory to investigate how personal and professional narrative styles align with relaxing and challenging tourism activities to maximize influencers’ persuasiveness. The study analyzes secondary data from 1187 social media posts and conducts three scenario-based experiments with 1438 participants. Results show that personal narrative style is more persuasive for relaxing activities, whereas professional narrative style works better for challenging activities. Moreover, experience resonance and knowledge acquisition are identified as key underlying mechanisms. Notably, the study introduces temporal distance in travel decision as a moderator, highlighting the importance of dynamic temporal cues in influencer recommendations. The findings provide valuable theoretical contributions and practical implications for optimizing influencer marketing strategies in the tourism context.
Research on mega sport events and tourism demand has largely overlooked domestic tourism and relied on aggregated data that mask individual behavioural adjustments. Using Paris 2024 as a case study, we propose a methodology to estimate the direct impact of mega sport events on domestic tourism at the individual level. A retrospective paired-sample survey is used to construct a two-period panel dataset (2023–2024). Individuals are classified as positively affected, negatively affected, or unaffected using self-reported motivations validated by counterfactual behaviour absent the event to mitigate ex-post rationalisation bias. Tourism demand remains unchanged based on the full sample due to offsetting behavioural responses: travel versus stay-at-home attraction among positively affected, and substitution versus crowding-out among negatively affected. However, focusing on actual travellers, affected individuals exhibit a larger increase in overnight stays than unaffected residents, without increasing visit frequency. Micro-level approaches are critical to capture how mega events reshape tourism demand.
Fashion tourism is increasingly positioned as a driver of destination development, yet its governance remains poorly theorized with respect to power concentration, digital visibility, and sustainability. Drawing on Actor–Network Theory and in-depth interviews with 23 international stakeholders, this study examines how collaborative governance is assembled, contested, and maintained across fashion tourism destinations. The analysis identifies three interconnected dynamics: governance asymmetries, digital ecosystem reconfiguration, and emergent sustainability logics. The study employs Actor–Network Theory to show how unequal actor positions, platform-mediated visibility, and resource dependencies shape who is enrolled, who gains influence, and whose sustainability priorities count. It further traces how actor-networks are assembled through brand hierarchies, event infrastructures, and platform algorithms that mediate access to resources and visibility. The findings challenge assumptions of collaborative governance as inherently inclusive and reconceptualize fashion tourism destinations as asymmetrical, digitally mediated governance networks that shape power relations, value distribution, and adaptive capacity.
This conceptual and methodological research note addresses event industry dynamics during armed conflicts, proposing an urgent anthropology approach to document transformations in real time. Using Ukraine as an example, we illustrate how event organizations have adapted to existential threats since the 2022 Russian invasion, demonstrating resilience through cultural initiatives, charitable events, and creative repurposing of resources. We argue that these practices have the potential to sustain cultural identity and to contribute to economic development, social cohesion and morale in conflict settings. To overcome the methodological and ethical challenges of traditional ethnography in war zones, we propose a novel citizen science framework within the urgent anthropology paradigm, leveraging digital technologies, social media, and participatory methods. This approach can decentralize knowledge production, mitigate researcher risk, and create longitudinal archives of industry adaptations. Our proposal supports SDG 16 by suggesting ways to link events and tourism research to peace, justice, and institutional resilience.
This research introduces Tourism Deceleration as a theoretically grounded framework for understanding temporal recalibration in tourism. Building on social acceleration theory and consumer deceleration framework, we conceptualize tourism deceleration as a situated temporal negotiation through which travelers recalibrate pace, attention, mobility, digital connectivity, and presence. Using hybrid deductive-inductive qualitative content analysis supported by LLM-assisted coding and human validation, we analyze 367 unique Reddit posts and 21,554 comments related to slow travel and long-term travel. The findings show that decelerated travel is often negotiated through practical, social, and personal constraints rather than simply chosen as a preferred travel style. Episodic deceleration remains the most explicit form of decelerated travel, while extended duration often intersects with embodied practices, reduced mobility pressure, and selective negotiation of digital technologies. The research note contributes by distinguishing tourism deceleration from slow tourism and explaining how travelers manage time under conditions of choice, context, and constraint.
This study examines event tourism competitiveness by integrating stakeholder-constructed competitiveness attributes with visitor valuation. Using Hong Kong as the primary empirical context and London as a validation context, the study combines thematic analysis, confirmatory composite analysis (CCA), and a discrete choice experiment (DCE). The thematic analysis identifies six competitiveness dimensions, including Resource Synergies, a novel dimension capturing cross-sector and cross-boundary integration. The DCE results show that Resource Synergies functions as a direct destination selection criterion for MICE participants, whereas its direct effect is not significant among leisure-event visitors. Professionalism and Facilities emerges as a universal competitiveness driver for both groups, while leisure-event visitors prioritise experiential distinctiveness and international content. These findings advance event tourism competitiveness research by explaining how competitiveness attributes are constructed by stakeholders and differentially valued in the event tourism context.
Empirical evidence on how air quality shapes tourist responses remains inconsistent. Drawing on a meta-analytical framework and cognitive-relational theory, this study synthesizes the effects of air pollution on demand- and experience-related outcomes across the travel process. The analysis pools 974 estimates from 58 demand studies and 92 estimates from 8 experience studies on destination-side pollution, as well as 483 estimates from 17 demand studies on origin-side pollution. After correcting for publication bias, air pollution has a mild, partly remediable adverse effect on tourism demand, while evidence for tourist experience is less consistent. The demand effect remains robust across destination-only and origin-destination settings, whereas origin-side air pollution has a negligible, statistically insignificant positive effect. Meta-regression results indicate that between-study heterogeneity is mainly driven by international tourism contexts, online word-of-mouth measures, PM2.5 or air quality index measures, and long-run effects. This meta-analysis provides actionable implications for scenario-based planning, forecasting and econometric practice.
