Search Results (143)

This study examines the transformation of environmental governance processes in recreational tourism in Turkey and Lithuania through artificial intelligence (AI)-supported waste management applications. The research focuses on the contributions of AI-based applications to sustainable destination management, environmental sustainability, and data-driven governance processes. A case study design was used within the framework of qualitative research methods. The dataset was obtained through semi-structured interviews with a total of 40 experts from Turkey and Lithuania. The data were analyzed using content analysis with the NVivo 14 program. The research findings reveal significant differences between the two countries in terms of digital infrastructure, institutional coordination, governance structures, and AI integration capacity. In Turkey, AI-supported waste management applications are still in their development phase; processes are largely shaped by managerial initiative, project-based approaches, financial constraints, and lack of institutional coordination. In contrast, Lithuania exhibits a more systematic and institutionalized digital governance structure thanks to EU-supported environmental and digitalization policies. However, data security, system sustainability, and high technology costs in small-scale recreation areas stand out as significant problem areas for Lithuania. This study addresses an underexplored intersection between artificial intelligence applications and environmental governance within recreational tourism contexts, contributing to the emerging literature on digital transformation in sustainable destination management. The findings reveal that AI-supported environmental management systems have significant potential to strengthen sustainable tourism management, increase operational efficiency, and support data-driven sustainable destination strategies. These findings offer practical implications for destination managers and policy makers by highlighting how AI-enabled environmental governance systems can enhance sustainability-oriented decision-making and improve operational efficiency in recreational tourism areas. Full article

Circular economy principles are increasingly influencing tourism development strategies, particularly in rural destinations characterized by strong linkages between agriculture, gastronomy, and local economic systems. This study develops and empirically examines a conceptual model investigating the relationship between circular economy practices, gastronomy integration, perceived authenticity, and destination competitiveness within rural tourism economies. The research focuses on the role of gastronomy as a circular tourism resource capable of connecting local sourcing, sustainability, and experiential value creation. Data were collected through a stakeholder-based survey targeting tourism enterprises, local producers, destination management organizations, and hospitality providers operating in rural tourism destinations. The proposed relationships were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) implemented in SmartPLS 4 and bootstrapped mediation analysis. The findings indicate that circular economy practices positively influence gastronomy integration, while gastronomy integration significantly enhances perceived authenticity. Furthermore, authenticity demonstrates a strong positive effect on destination competitiveness. The mediation analysis confirms that gastronomy integration and perceived authenticity function as intermediary mechanisms through which circular economy practices contribute to competitiveness outcomes. The study contributes to tourism economics and destination competitiveness literature by developing and empirically testing a mediation-based framework linking circular gastronomy, authenticity, and rural tourism competitiveness. The findings provide theoretical and practical implications for destination managers and policymakers seeking to strengthen sustainability, local value creation, and competitiveness through circular gastronomy strategies. Full article

This study addresses the fragmented integration of smart technologies into sustainable tourism management, where digital tools are often implemented without sufficient coordination, interoperability, or clear links to sustainability objectives. Such a situation limits the potential of smart solutions to improve destination governance, visitor experience, and the long-term competitiveness of tourism destinations. The aim of the study is to evaluate how the Smart Region concept can be operationalized at the urban level by analysing the city of České Budějovice (Czech Republic)—the primary regional tourism and administrative hub—as a critical case study. The research first analysed relevant municipal and regional strategic documents, then examined secondary data and publicly available digital services and technological solutions, and finally conducted a structured observation of selected tools relevant to tourism management. The findings show that the city has already introduced several elements of smart tourism management, especially in digital information services, transport management, and sustainable mobility. However, the analysis also reveals important shortcomings in data sharing, cross-sector coordination, and the integration of tourism-oriented digital tools. The study concludes that deeper institutional cooperation and more coherent smart governance are necessary to strengthen sustainability, improve efficiency, and support the long-term competitiveness of the destination. Full article

This study aims to explore and evaluate the factors influencing Gen Z’s intention to choose green tourism destinations in Hanoi, Vietnam. The paper proposes a comprehensive analytical framework by integrating the Stimulus-Organism-Response (S-O-R) model and the Theory of Planned Behavior (TPB). A mixed-method approach was employed, in which quantitative data were collected from 269 Gen Z respondents in Hanoi and analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique through SmartPLS. The findings reveal that external environmental stimuli, including green destination image (GDI) and social media influence (SMI), positively affect individuals’ internal psychological states, namely environmental awareness (EA), attitude toward green tourism (ATT), and subjective norms (SM). These psychological states, in turn, exert positive effects and strongly promote Gen Z’s intention to choose green tourism destinations in Hanoi. This study not only contributes to filling the theoretical gap in sustainable tourism consumption behavior in the digital era but also provides practical managerial implications for policymakers and tourism businesses in developing communication strategies and tourism products that align with the preferences and expectations of younger generations. Full article

Smart tourism destinations, embedded by the internet and information and communication technologies, have been improving tourists’ experiences and connectivity. However, Destination Management Organisations (DMOs) still lack knowledge of how digital technologies can enhance their role and bring greater competitive advantage to destinations. In this sense, this study aims to develop an integrated smart tourism destination management ecosystem model that clarifies the relationships between digital technologies, managerial functions, benefits and implementation barriers within the broader smart city context. The study adopts a mixed-review design, combining bibliometric analysis and a systematic literature review. Bibliometric mapping was conducted using VOSviewer to analyse co-occurrence networks, thematic clusters and research trends. At the same time, the systematic review, with a systems thinking approach, enabled an in-depth qualitative examination of technological applications, managerial roles and governance implications. Data was gathered from 29 Scopus-indexed articles. The analysis identifies key benefits, including enhanced visitor experiences, improved decision-making and increased destination competitiveness, alongside persistent barriers related to governance, digital literacy, interoperability and cybersecurity. Based on these findings, the study proposes a conceptual ecosystem model that illustrates how DMOs can orchestrate digital technologies to support smart, sustainable and adaptive destination management. This research contributes to the smart tourism and smart cities literature by integrating bibliometric insights with a systems thinking perspective to develop a holistic destination management ecosystem model. Unlike prior reviews that address technologies or outcomes in isolation, this study offers a structured and actionable framework that advances theoretical understanding of smart tourism destinations while providing practical guidance for DMOs engaged in digital transformation. Full article

As China experiences rapid population aging, promoting high-quality tourism for older adults has become essential for enhancing elderly well-being, improving inclusive and age-friendly tourism services, supporting culture–tourism integration, and fostering sustainable destination development. Drawing on the global literature on smart tourism, digital inclusion for older adults, and service quality in aging societies, this study investigates how digital empowerment (DE) influences the high-quality development of silver tourism (HDST) in Hubei Province, China. Partial least squares structural equation modeling (PLS-SEM) was applied to survey data from 702 elderly respondents, incorporating cultural tourism integration (CTI), age-friendly service adaptation (ASA), and perception of silver tourists (PST), with family support (FS) and policy support (PS) as key moderating variables. The results indicate that DE significantly promotes HDST through ASA and PST, while FS and PS play important moderating roles. These findings provide practical guidance for tourism practitioners and policymakers seeking to enhance age-friendly digital services, improve the tourism experience for older adults, and support the sustainable development of silver tourism. Full article

This research focuses on the effects of online destination brand experience on destination brand authenticity, destination brand engagement, and external search behavior and behavioral intention. It also investigates the mediating effect of destination brand authenticity on the relationship between online destination brand experience and destination brand engagement. The research population consisted of visitors who had experienced the Zeugma and Gaziantep cultural tourism destinations. The Smart PLS (Partial Least Squares) statistical program was used for data analysis. The analysis results showed that online destination brand experience positively affected destination brand authenticity and destination brand engagement. Destination brand engagement influenced external search behavior and behavioral intention positively. However, the findings revealed that the social engagement dimension of destination brand engagement did not have a significant effect on external search behavior. Furthermore, the effect of the cognitive engagement dimension on behavioral intention was also insignificant. Finally, it was found that destination brand authenticity partially mediated the relationship between online destination brand experience and destination brand engagement. Full article

Artificial intelligence (AI) is increasingly embedded in tourism platforms and services, yet continued participation often coexists with residual privacy concerns, accountability uncertainty, and uneven governance visibility. This study examines multi-actor trust in AI-enabled smart tourism governance as a problem of governance adequacy rather than trust maximization. Using the Three-Line Heuristic Framework (TLHF) and Satisficing Equilibrium (SE) as descriptive organizing tools, it asks whether trust-related outcomes can be organized around a mid-to-high adequacy region when visibility, accountability, usability, and platform choice conditions are perceived as sufficiently acceptable. TLHF organizes government-related visibility, firm-side operational adequacy, and user-side familiarity, while SE provides a descriptive governance heuristic for interpreting adequacy-oriented concentration under bounded concern. Empirically, the study uses a multi-context but unevenly distributed adult online survey sample of 1568 respondents, together with 35 semi-structured interviews as contextual qualitative material. Kernel density estimation, LOESS diagnostics, internal visual checks, and binary logit with Average Marginal Effects are used to summarize concentration patterns and marginal associations with safe platform preference. The results show that platform benefit evaluation and higher residual privacy concern after reverse scoring have the clearest positive associations with safe platform preference, while AI use breadth shows a more modest positive association and travel frequency is negatively associated. The density profiles show a recognizable mid-to-upper concentration zone, with similar visual patterns under limited resampling and split half comparisons. Within the retained adult sample, the findings highlight the relevance of visible transparency, maintainable service conditions, residual privacy concern, and low-friction usability for sustainable AI tourism governance and destination management. Full article

Digital Twins (DTs) are increasingly explored in tourism and hospitality as enabling technologies for smart destinations, service optimization, and data-driven decision-making. Yet these environments are inherently human-centered. Existing DT implementations, however, are largely technology-driven and focus mostly on infrastructures and operational processes. This study presents a systematic literature review of DT applications in tourism and hospitality. It combines a comparative taxonomy with a technological and data-oriented analysis to examine how these systems are currently conceptualized, implemented, and integrated. The review analyzes 42 studies, classifying them by application level, twin focus, architectural approach, and human integration. The results show a strong dominance of destination- and facility-level DTs, limited human-centered models, and a prevalent use of varied sensing technologies. There is limited attention to interoperability and semantic integration. Governance, socio-technical aspects, and real-time synchronization mechanisms are also mostly underexplored. Based on these findings, this study identifies key research gaps and calls for a shift towards Social Digital Twins (SDTs). SDTs integrate human actors, social interactions, and governance within unified modelling frameworks. This transition will require advances in semantic and ontology-driven architectures. Greater attention to privacy, trust, and user acceptance in data-intensive service environments is also needed. Full article

This study aims to analyse the influence of sustainability knowledge on sustainable lifestyles with attitudes toward sustainability as a mediating variable, within the framework of Stimulus–Organism–Response (SOR). The study respondents were 311 tourism managers in Yogyakarta with various destinations who were selected using non-probability sampling techniques due to limited population access and the specific needs of subjects relevant to sustainability issues. The data analysis uses Structural Equation Modelling–Partial Least Squares (SEM-PLS) with Smart PLS. The results of the study show that sustainability knowledge directly affects sustainable lifestyles; in addition, attitudes towards sustainability partially mediate the influence of sustainability knowledge on sustainable lifestyles. Sustainability knowledge is seen as an external stimulus that influences positive attitudes towards sustainability, which then drives a response in the form of adopting a sustainable lifestyle. Although knowledge is often assumed to directly influence behaviour, theoretical and empirical findings suggest that attitudes play an important role as mediators that bridge knowledge with real behaviour. Other results show that sustainable awareness does not directly affect a sustainable lifestyle. Attitude toward sustainability plays a mediating role in the influence of sustainable awareness on sustainable lifestyles. Individuals or tourism managers who have a deep awareness of environmental, social, and economic issues tend to internalise sustainability values, form positive attitudes, and ultimately adopt sustainable lifestyles. This research is expected to make a theoretical contribution by strengthening the application of the SOR framework in sustainable tourism, as well as a practical contribution through educational programme recommendations that emphasise the importance of forming positive attitudes in behaviour transformation. Full article

The digitization of tourism has made numerous platforms available, but there remains a significant shortage of tools capable of promoting local events and activities. This study hypothesizes that a decentralized digital interface can mitigate over-tourism. We conducted an experiment by deploying a digital platform to assess the synergy between local providers and visitors through the Tourism Open-ended Experimentation Platform (TOEP), a multi-interface solution designed to directly connect tourism activity providers with residents and visitors. The platform integrates a web portal for providers and a mobile app for users, supported by a recommendation system based on individual profiles and preferences. TOEP stands out for its focus on local and sustainable tourism, facilitating the promotion of smaller events and helping to reduce the concentration of tourist flows in already saturated destinations. Initial validation, conducted with a panel of industry experts, highlighted the ease of use and good organization of the interfaces, with scores above average. Preliminary results confirm the relevance of TOEP as a tool for the sustainable and digitized promotion of local tourism, opening prospects for development towards a smart, participatory tourism ecosystem that can be replicated in different territorial contexts. Full article

Tourism’s digital transformation has reshaped how travelers search for and evaluate destinations. However, relatively little empirical work has examined how user engagement translates into booking intent, especially under the emergent discovery channels mediated by artificial intelligence (AI). This study tests an engagement-driven referral framework using longitudinal behavioral data from a Mediterranean destination portal (April 2022–January 2026; 1.6 million sessions). Engagement depth, measured as average session time, significantly predicts booking intent click rate. Mobile drives 83% of sessions, but desktop users convert at nearly twice the rate (5.69% vs. 3.37%). High traffic, as it turns out, does not equal high commercial intent. Lower-volume international markets routinely outperform the dominant domestic market. The most striking result concerns AI referrals. Traffic arriving from AI assistants converts at 8.26%, more than double the organic search rate of 3.88%, despite shorter sessions, a pattern consistent with compressed decision-making under generative AI. These findings, grounded in real travel portal data, extend engagement theory beyond transactional settings and shed early light on how referrals from AI assistants like ChatGPT or Gemini differ behaviorally from organic search, with practical implications for portal managers, destination marketing organizations (DMOs), and sustainable demand management. Full article

Digital transformation is increasingly reshaping how tourism destinations enhance service quality and strengthen competitive positioning, particularly in developing economies characterized by heterogeneous digital maturity and structural constraints. This study develops and empirically tests a conceptual model examining the relationship between destination digital transformation, tourism supply quality, and destination competitiveness, with a specific focus on the mediating role of quality-oriented tourism supply. Survey data were collected from 242 tourism stakeholders and analyzed using hierarchical regression and bootstrapped mediation analysis (PROCESS Model 4, 5000 samples). The results show that digital transformation has a significant positive total effect on destination competitiveness (β = 0.48, p < 0.001), explaining 56% of the variance in competitiveness (R² = 0.56). However, a substantial portion of this effect is transmitted indirectly through tourism supply quality. The mediation analysis confirms a statistically significant partial mediation effect, with approximately 41% of the total effect operating through quality-oriented mechanisms. The findings demonstrate that digital transformation enhances competitiveness primarily when embedded within structured quality management, online reputation management, and smart governance practices, rather than through technological adoption alone. The study contributes to the literature by integrating digital transformation and tourism supply quality into a unified competitiveness framework tailored to developing economy contexts and provides practical guidance for policymakers and destination managers seeking inclusive and sustainable growth through quality-oriented digital strategies. Full article

The rapid growth of digital tourism platforms has intensified information overload and decision complexity for both locals and travelers, while operators struggle to differentiate their offerings and sustain profitable, data-driven e-commerce models. This paper presents Doroob, a big data and artificial intelligence (AI)-driven, context-aware recommendation system that integrates traditional recommender techniques with real-time facial emotion recognition (FER) to enable intelligent tourism commerce. Doroob combines three AI-based recommendation strategies: smart adaptive recommendation (SAR) collaborative filtering, a Vowpal Wabbit-based context-aware model, and a LightFM hybrid model. It trained on datasets built from the Google Places API and enriched with ratings adapted from MovieLens. FER, implemented with DeepFace and OpenCV, analyzes short video segments as users browse destination details, converts emotion scores into 1–5 satisfaction ratings, and stores this implicit feedback alongside explicit ratings to support adaptive, emotion-aware personalization. Experimental results show that the context-aware model achieves the strongest top-K ranking performance, the hybrid LightFM model yields the highest AUC of 0.95, and the SAR model provides the most accurate rating predictions, demonstrating that combining contextual modeling and FER-based implicit feedback can enhance personalization, mitigate cold-start, and support data-driven promotion of local tourist services in intelligent e-commerce ecosystems. Full article

This study investigates the impact of sustainable destination marketing on enhancing tourists’ intention for responsible visitation in Saudi Arabia by fostering destination trust through two manageable digital levers: the quality of sustainability storytelling and the interactivity of smart tourism. Based on a trust-based S-O-R framework and supplemented by signaling and uncertainty reduction theories, the research posits that high-quality, credible sustainability narratives and responsive, two-way smart touchpoints serve as trust indicators that lead to enhanced responsibility-oriented intentions. An online survey of digitally engaged tourists and potential tourists (N = 420) was used to gather the data. We used SmartPLS, version 4.1.1.7 (SmartPLS GmbH, Monheim am Rhein, Germany), with bootstrapping (5000 resamples) to assess the measurement and structural models. The findings demonstrate that the quality of sustainability storytelling significantly predicts destination trust (β = 0.418, p < 0.001), as does smart tourism interactivity (β = 0.347, p < 0.001). Destination trust positively affects responsible visit intention (β = 0.318, p < 0.001) and partially mediates the impacts of storytelling quality (β = 0.133, p < 0.001) and interactivity (β = 0.110, p < 0.001) on responsible visit intention. The model elucidates 40.9% of the variance in destination trust and 40.6% in responsible visit intention, underscoring trust as a pivotal mechanism by which credible sustainability storytelling and efficient smart interactivity can promote more responsible visitation. Full article