Tourism and Hospitality

Understanding destination image perceptions is critical for tourism destinations seeking to maintain competitive advantage and foster visitor loyalty. While the traditional literature suggests that first-time and repeat visitors differ significantly in their cognitive and affective destination image perceptions due to experiential differences, emerging evidence from destinations with established branding challenges these conventional assumptions. Thailand, as a globally prominent destination with sustained branding initiatives since 1998, provides an ideal context for examining whether visitor experience moderates destination image formation and loyalty outcomes. This study investigates differences in cognitive and affective destination image perceptions and destination loyalty between first-time and repeat international travellers to Thailand, applying the cognitive–affective–behavioural (CAB) model to examine how these constructs influence revisit and recommendation intentions across visitor segments. Data were collected from 392 international tourists visiting three major southern coastal destinations in Thailand (Phuket, Krabi, and Phang-Nga) through face-to-face surveys using purposive sampling. The sample comprised 185 first-time travellers and 207 repeat visitors. Partial least squares structural equation modeling (PLS-SEM) with multigroup analysis was employed to examine structural relationships and test for significant differences between visitor cohorts using parametric, Welch–Satterthwaite, and permutations tests. Contrary to theoretical expectations, multigroup analysis revealed no statistically significant differences between first-time and repeat travellers across all examined pathways (all permutation p-values > 0.05). Both groups demonstrated equivalent perceptions regarding how cognitive image influences affective image, and how these dimensions affect revisit and recommendation intentions. Affective image emerged as the dominant predictor of destination loyalty for both segments, while cognitive image primarily served as an enabler of emotional responses. These findings challenge traditional assumptions about experiential differences between visitor types suggesting that mature destinations with consistent long-term branding may achieve perceptual uniformity that transcends direct experience. Destination marketing organizations should implement unified rather than segmented strategies, prioritizing emotional engagement mechanisms over rational attribute promotion to cultivate destination loyalty across all visitor segments. However, these findings are specific to coastal leisure destination and may not fully generalize to other destination types. Full article

This article examines music’s potential to contribute to the co-creative development of sustainable place branding efforts. It highlights how music can brand a place with a specific music identity and provide places with foundations of their resilient futures. The authors explore the case study of Labyrinth Musical Workshop, which gathers musicians from all parts of the world to a small village in Crete called Houdetsi. The study builds on ethnography data (fieldnotes, photos/videos), interviews with musicians, local inhabitants and hotel owners and digital ethnography tools including thematic analysis of hashtags and comments on the official social media accounts of Labyrinth Musical Workshop and the Cultural Association of Houdetsi. Findings reveal the challenges of sustainable tourism development and how music and place branding through co-creation can lead destinations towards resilience. The co-created experiences on offer highlight notions of community and co-belonging that inspire repeat visits, whereas the support of cultural and economic networks prioritize social–cultural and environmental rather than merely economic sustainability pillars. Full article

This study examines the effects of trust in AI, willingness to accept AI, and perceptions of AI performance on brand loyalty in the hospitality industry. The study further posits that purchase intentions mediate the relationship between understudied independent variables and brand loyalty. Drawing on the Technology Acceptance Model, Unified Theory of Acceptance Use of Technology UTAUT, and Trust–Satisfaction theory as the theoretical foundation, the study posits seven hypotheses. Data were collected via an online platform; ultimately, 183 participants participated in the survey. The study tests the hypotheses using Hayes’s Macro PROCESS Model 4 mediation, where the direct and indirect effects were established. The study observes that the direct and indirect effects of trust in AI and the perceived performance of AI on brand loyalty were significant. However, only the indirect effect was significant for the willingness to accept AI on brand loyalty. These observations show that the use of AI-enabled services enhances a stronger intention to book, leading to an improved brand loyalty. The results extend the body of knowledge in this area by linking the unified framework of trust in AI, AI perceived performance, and willingness to accept AI to brand loyalty in the hospitality industry. For managers and hoteliers, this finding is clear, emphasising that the transparent and reliable use of AI enhances purchase intentions and improves brand loyalty. Full article

The rapid expansion of the tourism sector has raised concerns about how to provide satisfaction to visitors while preserving the environment, especially at tourism destinations that are trying to be sustainable. This study, based on Value-Belief-Norm (VBN) and Place attachment theory, investigates how tourism experience satisfaction predicts eco-tourism behaviour through destination bond while moderating the relationship between tourism experience satisfaction and eco-tourism behaviour via ecocentrism. A stratified random sampling technique was employed to capture a diverse representation of tourists visiting eco-heritage destinations. A total of 420 valid responses were retained after thorough screening for completeness and reliability. The final dataset was analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM) to evaluate both the measurement and structural relationships in the proposed model. The findings indicate that tourism experience satisfaction creates significant destination bonds, which lead to eco-tourism behaviour. Both destination attachment and dependence contribute significantly to eco-tourism behaviour, indicating they both play a mediation role. Furthermore, ecocentrism positively moderates the relationship between satisfaction and eco-behaviour, demonstrating that tourists with stronger ecological value orientations are more likely to translate satisfaction into responsible environmental action. Theoretically, the study contributes to the VBN and place attachment theory by acknowledging the role of attachment and dependence as important belief processes enabling the interacting of experiential fulfilment to moral engagement, and by finding ecocentrism to be a dynamic moderator. To the policy makers, destination managers and community stakeholders, the findings provide a behavioural model of enabling the process of stewardship using experiential design based on values and participative-based conservation initiatives. Full article

Tourism in active conflict zones constitutes a distinct and contentious form of dark tourism, wherein visitors engage with sites marked by death and tragedy that have significantly shaped public consciousness. This study investigates hot-war tourism as an emerging tourism product in places affected by ongoing conflict, highlighting its potential to foster resilience, support local communities, and enhance social awareness. Using Ukraine as a case study, the paper examines the underlying motivations that drive tourists to such destinations and explores how, under specific conditions, local stakeholders can design tourism offerings that represent both meaningful and responsible travel experiences. War-torn and conflict-affected destinations possess the capacity to transform adversity into opportunities for long-term recovery and sustainable development. The findings contribute to the broader discourse on reimagining tourism in the face of disruption, offering insights into how strategic planning and innovation can enable destinations to rebuild and adapt during times of crisis. Full article

Aviation accounts for a disproportionate share of tourism-related carbon emissions. Many travelers express environmental concern but continue to fly, reflecting the well-documented attitude–behavior gap. This study examines the concept of flight behavioral integrity (i.e., the alignment between professed avoidance of air travel for environmental reasons and actual flying behavior) to assess whether integrity profiles predict support for climate policy. Drawing on nationally representative survey data from Germany (N = 2410), respondents were classified into four groups based on flight avoidance attitudes and reported flight activity in the past 12 months. An elastic-net multinomial regression tested psychological predictors of group membership, and factorial ANCOVAs assessed differences in environmental and climate policy support. Results showed that flight avoidance attitudes, rather than recent flying behavior, were the primary predictors of both integrity profiles and policy support. Flight-avoidant respondents consistently reported stronger policy endorsement, regardless of whether they had flown. Contrary to expectations, recent fliers expressed marginally higher support than non-fliers, potentially reflecting compensatory mechanisms or sociodemographic factors. Findings suggest that there are opportunities for tourism operators and policymakers to engage travelers through value-based (vs. purely behavioral) sustainability initiatives. Full article

This study develops and empirically validates a theoretical model designed to assess the performance of tourism innovation ecosystems by integrating the dimensions of innovation, technology, and sustainability—dimensions that have typically been examined in isolation within the literature. The empirical investigation was conducted at two major tourism destinations: a pilot phase in Las Vegas, followed by the main study in Orlando, USA. Data collection was facilitated via the Amazon Mechanical Turk (MTurk) platform, and analysis was conducted using Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM), enabling the examination of eight hypotheses across seven constructs. The findings provided evidence of both convergent and discriminant validity and supported five of the eight proposed hypotheses. Specifically, the study confirmed significant relationships among technology acceptance and adoption, adoption and innovation generation, innovation and both sustainability and overall ecosystem performance, and adoption and sustainability. Conversely, collaboration and actor-integration barriers did not exhibit significant effects in Orlando, which is consistent with its mature institutional environment. Innovation emerged as a mediating variable linking technology and sustainability, exerting a substantial influence on overall ecosystem performance. This research advances the theoretical consolidation of the tourism innovation ecosystem concept and offers actionable insights for destination managers aiming to foster innovation, facilitate the adoption of connective technologies, and implement sustainable strategies. The proposed model demonstrates empirical robustness and practical relevance, providing a comprehensive framework for analyzing and enhancing smart, resilient tourism destinations. Full article

This study moves beyond the static view prevalent in hospitality loyalty research by developing and longitudinally testing a process-oriented model of loyalty formation. Recognizing that loyalty is a dynamic outcome, we employ a three-wave panel design with a three-month lag, surveying 562 customers of organic restaurants within green-certified hotels. Data are analyzed using a Cross-Lagged Panel Model (CLPM) to meticulously map the temporal interplay among key antecedents, controlling for autoregressive effects and covariates. The findings provide robust evidence for a specific cognitive-to-affective sequence: perceptions of food quality at one time point shape subsequent judgments of perceived value, which in turn drive customer satisfaction, ultimately fostering loyalty in a succeeding period. Crucially, the CLPM also reveals that food quality and price fairness exert significant, direct time-lagged effects on loyalty, suggesting the presence of dual psychological pathways. By establishing temporal precedence and mapping sequential mediation, this study offers a more causally robust and managerially actionable understanding of how customer loyalty evolves. Full article

As destinations featured in films and television programs attract growing numbers of tourists, exploring the factors that sustain film tourists’ loyalty and advocacy has become increasingly important. This study explores the determinants of post-visit behaviors through the lens of cognitive appraisal theory (CAT), investigating how perceived authenticity, perceived value, and satisfaction shape revisit and word-of-mouth (WOM) intentions among 436 Chinese film tourists visiting Thailand. Data were analyzed using structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to capture both symmetrical and configurational effects. The SEM results reveal that perceived authenticity, perceived value, and satisfaction significantly enhance WOM intentions. The complementary fsQCA findings reveal multiple causal pathways leading to high revisit and WOM intentions. The study advances theoretical understanding by demonstrating the applicability of CAT to film tourism and showing how tourists’ cognitive evaluations and emotional appraisals jointly shape their post-visit behavioral intentions. The findings also offer practical guidance for developing authenticity-based strategies to foster loyalty and positive destination advocacy. Full article

As inclusive and accessible tourism continues to expand, communication barriers remain a major obstacle for travelers with diverse needs. This study examines how infographics can function as a strategic communication tool to enhance accessibility, inclusivity and comprehension in tourism marketing. A quantitative survey with 187 tourism businesses in Kefalonia, Greece, assessed perceptions of infographic use through constructs adapted from the Technology Acceptance Model (TAM) & Usefulness, Satisfaction and Ease of use (USE) frameworks. Findings show that perceived usefulness and ease of learning directly influence intention to adopt infographics, while ease of use and perceived efficiency affect adoption indirectly through satisfaction. The study advances tourism and marketing literature by linking accessibility with visual communication strategies and offers practical guidance for Destination Management Organizations (DMOs), Small and Medium-sized Enterprises (SMEs) and policymakers on using infographics to promote clarity and equitable information access. Full article

This study examines the adoption of artificial intelligence (AI) among micro and small hospitality enterprises in Slovenia, a small EU economy where digital transformation remains limited. It explores how organisational characteristics and managers’ attitudes toward AI are related to its adoption and firms’ operating revenues. Data were collected from 286 accommodation and food-and-beverage enterprises through a structured questionnaire completed by managers or owner–managers, complemented by secondary official financial data. Using ordinary least squares regression, the analysis examined associations among organisational characteristics, managerial attitudes, AI use intention and adoption, and financial performance. The results indicate that firm size and structural features alone are not closely linked to digital transformation. AI adoption shows stronger associations with managers’ positive attitudes and with factors such as non-family ownership and smaller firm size. The overall General Attitudes toward AI Scale (GAAIS) score showed no direct relationship with revenue, but two specific items—enthusiasm for AI and recognition of business opportunities—were positively associated with higher revenues. Among AI tools, only smart text editors and CRM systems were statistically associated with revenues, suggesting that better-performing firms are more likely to use simpler, more affordable technologies. The study provides contextual evidence on behavioural and organisational dimensions of AI adoption in resource-constrained hospitality SMEs. Full article

Traditional foods (TFs) represent a key component of regional cultural identity and gastronomic heritage, particularly within the hospitality sector. The growing interest of tourists in authentic, locally sourced and sustainable food underscores the importance of understanding the perceptual and socio-demographic factors that shape their preferences and choices regarding TFs. The aim of this study is to identify and explain the factors that influence tourist attitudes toward dishes prepared with TFs in the hospitality sector, as well as to examine the extent to which socio-demographic characteristics predict tourists’ purchasing decisions. For this purpose, the Tourist Perception and Preferences Model in the Context of Traditional Foods (TPP-TF model) and the Perceptual Factors Scale for Traditional Food Consumption (PFS-TFC) were developed. The research was conducted on a sample of 507 respondents in the A.P. Vojvodina (Republic of Serbia), employing both exploratory and confirmatory factor analyses, which identified the following three key factors: socio-cultural, ecological, and economic. The results of the logistic regression analysisshowed that income level and place of residence significantly influenced the decision to purchase dishes based on traditional foods (TFs). Tourists with higher income levels were substantially more likely to purchase TFs, highlighting the role of economic affordability in shaping consumer choices. Conversely, individuals residing in urban areas showed a significantly lower likelihood of purchasing TFs compared to rural respondents, suggesting that traditional food consumption remains more rooted in rural environments and is closely associated with cultural proximity. Full article

The contemporary digital landscape overwhelms visitors with fragmented and dynamic information, complicating travel planning and often leading to decision paralysis. This paper presents a real-world case study on the design and deployment of an intelligent tourism assistant for Valencia, Spain, built upon a Retrieval-Augmented Generation (RAG) architecture. To address the complexity of integrating static attraction data, live events, and geospatial context, we implemented a multi-agent system orchestrated via the ReAct (Reason + Act) paradigm, comprising specialized Retrieval, Events, and Geospatial Agents. Powered by a large language model, the system unifies heterogeneous data sources—including official tourism repositories and OpenStreetMap—within a single conversational interface. Our contribution centers on practical insights and engineering lessons from developing RAG in an operational urban tourism environment. We outline data preprocessing strategies, such as coreference resolution, to improve contextual consistency and reduce hallucinations. System performance is evaluated using Retrieval Augmented Generation Assessment (RAGAS) metrics, yielding quantitative results that assess both retrieval efficiency and generation quality, with the Mistral Small 3.1 model achieving an Answer Relevancy score of 0.897. Overall, this work highlights both the challenges and advantages of using agent-based RAG to manage urban-scale information complexity, providing guidance for developers aiming to build trustworthy, context-aware AI systems for smart destination management. Full article

This study investigated how consumers’ food consumption needs and perceptions influence their attitudes and behavioral intentions toward food truck dining. Drawing on the stimulus–organism–response (SOR) framework, perceived risks and benefits were conceptualized as external stimuli; food consumption needs (necessity vs. enjoyment) and attitudes represented the organism; and behavioral intentions denoted the response. Data were collected via Amazon Mechanical Turk and analyzed using structural equation modeling and multigroup comparisons based on prior food truck experience. Perceived benefits and food enjoyment positively influenced attitudes, whereas perceived risks negatively influenced attitudes. Attitude significantly predicted future behavioral intentions, whereas food as a necessity did not. The multigroup analysis revealed that prior experience moderated these relationships; perceived benefits and risks primarily guided inexperienced consumers, whereas experienced consumers formed attitudes mainly through hedonic needs. These findings contribute to the literature by integrating the SOR and value–attitude–behavior hierarchies to explain cognitive and motivational mechanisms underlying food truck patronage. They also highlight the moderating role of prior experience, which reshapes the strength of the model’s key paths. The study offers practical implications for food truck operators seeking to balance risk mitigation with perceived benefits to encourage repeat patronage. Full article

Customer satisfaction (CS) is a cornerstone of competitiveness in the hospitality sector, particularly in restaurants, where service interactions are highly sensory and time-sensitive. Traditional measurement instruments, such as SERVQUAL, SERVPERF, and the American Customer Satisfaction Index, provide valuable diagnostic insights but remain limited by recall bias, social desirability, and delayed feedback. Advances in deep learning now enable non-intrusive, real-time monitoring of customer experience. This study evaluates the feasibility of using a convolutional neural network (CNN) to automatically classify customer satisfaction based on facial expressions captured at the point of payment in a restaurant. From an initial dataset of over 5000 images, 2969 were validated and labeled through a binary self-report mechanism. The CNN, implemented with transfer learning (MobileNetV2), achieved robust performance, with 93.5% accuracy, 92.8% recall, 91.0% F1-score, and an area under the ROC curve of 0.93. Comparative benchmarks with Support Vector Machine and Random Forest classifiers confirmed the superiority of the CNN across all metrics. The findings highlight CNNs as reliable and scalable tools for continuous CS monitoring, complementing rather than replacing classical survey-based approaches. By integrating implicit, real-time signals with traditional instruments, restaurants can strengthen decision-making, enhance service quality, and co-create personalized experiences while addressing challenges of explainability, external validity, and data ethics. Full article

The present paper deals with community participation in destination planning, using the small town of Koroni in Greece and the associated Maniatakeion Foundation as a case study. Benefiting from the author’s consulting experience and based on interviews with the foundation’s owner and the local community, on local press articles and a business plan on the development of Koroni, the paper aims at exploring the following: (A) how the participation of the local community in destination planning can lead to concrete plans and actions towards achieving sustainable development; and (B) the role of civil society organisations to this end. At first, the existing development model of Koroni is outlined. Then, the new development model of Koroni, based on the Mediterranean Diet, is analysed: how it was crafted; how it was implemented; what the role of the Maniatakeion Foundation was; and whether it was embraced by the local community groups. It is shown that (A) Koroni managed to shift from a mass tourism development model towards an alternate model that is rooted in sustainable development. Also, the fact that Koroni, which had no brand name (even on a local level), succeeded in acquiring an international brand name through the inscription of the Mediterranean Diet on the UNESCO Intangible Heritage List; (B) the destination planning process was initiated, coordinated, and operated by the local civil organisation Maniatakeion Foundation. The key lesson of broader application to be taken is that civil society organisations can build integrity and capacity and play a leading (and not only a supportive-supplementary) role in destination planning. Full article

This article analyzes the construction of the Digital Extended Self of digital influencers from the travel channel Travel Channel, drawing on R. W. Belk’s theory. The study employs a qualitative exploratory–descriptive approach, using a case study as its methodological strategy. Data collection involved analyzing five podcast interviews with the channel’s founders, along with videos published between 2022 and 2024. In addition, viewer comments on these videos were extracted and examined. All materials were analyzed using Bardin’s content analysis. The results reveal a strong presence of the Extended Self dimensions, co-construction, and sharing, showing that interaction with the audience actively shapes the influencers’ identity and content. The dimensions of dematerialization (e.g., cloud storage) and distributed memory (the use of digital records as extensions of memory) were also evident. Reincarnation (the use of avatars or personas) was the least observed dimension, a finding attributed to the influencers’ authentic style and focus on real-life experiences. Overall, the Digital Extended Self of the Travel Channel emerges as a genuine and organically constructed entity, resulting in an aggregated Self that reflects a strong connection with its audience. This research provides valuable insights into how Belk’s theory can be applied to the in-depth analysis of digital materials. Full article

Culinary culture shock (CCS)—the discomfort and ambivalence travelers feel when encountering unfamiliar foods—remains underexplored from a short-horizon, trip-bounded perspective. While prior work notes both attractions and impediments of food in tourism, a process-oriented account of how ordinary travelers experience and navigate CCS during brief trips is still limited. This study examines CCS in Guangzhou, China and delineates how it shapes travelers’ evaluations of place. We adopt a qualitative design, combining 30 semi-structured interviews with in situ ethnographic observations across markets, street-food settings, restaurants, and guided food tours, supplemented by document analysis (e.g., visitor materials and menus). Using reflexive thematic analysis, we identify three recurrent coping trajectories—avoidance, gradual adaptation, and immersion—that unfold nonlinearly as travelers recalibrate expectations, manage sensory dissonance, and renegotiate comfort boundaries. We integrate expectancy–disconfirmation theory (EDT) with an embodied view of tasting to develop the Palate Adaptation Spiral Model (PASM), which explains CCS as recursive cycles of appraisal, strategy enactment, and re-appraisal within the span of a trip. Social influence (peers, guides, and service staff) operates as a cross-cutting mechanism that can accelerate adaptation or entrench avoidance depending on cue valence and credibility. The study clarifies the scope of CCS as general travel encounters (not restricted to culinary-motivated tourists) and specifies contextual conditions under which negative reactions are reversible. Theoretically, we connect EDT to short-term culinary adaptation through PASM; practically, we outline design levers—pre-trip expectation management, pictorial/transparent menus, and guide-mediated tasting sequences—to reduce anxiety and support constructive exploration. Full article

This study examines the travel behaviour and motivations of tourists visiting heritage attractions in the Sekhukhune District Municipality (SDM) in South Africa, as part of the sustainable development of rural heritage tourism. A quantitative approach through a means of a questionnaire was used to collect data from a sample size of 208 respondents at major heritage attractions in the study area. The results indicate that the respondents are primarily motivated by cultural performances, historical stories and sites associated with mining and agricultural heritage. This study identified that tourists are more concerned about the level of crime and environmental degradation as inhibiting factors to their attitudes and behaviours of participation. This study also demonstrates the socio-economic and environmental barriers rural municipalities deal with. This study provides practical recommendations for enhancing cultural engagement, addressing safety concerns, and promoting local economic development, thereby fostering a more sustainable and inclusive approach to heritage tourism in the SDM. Full article