Search Results (788)

Digital transformation has become an essential component of sustainable rural development, yet substantial inequalities persist in how communities access, adopt, and benefit from digital technologies. Understanding these disparities requires not only information about technological resources but also knowledge of the relational structures through which information, support, and opportunities circulate. This article presents a reproducible synthetic socio-digital network dataset designed to support the analysis of digital gaps in community-based tourism (CBT) environments. Rather than containing original respondent-level observations, the repository was computationally reconstructed from aggregate statistics derived from field studies conducted in three rural communities in the province of Guayas, Ecuador: Bucay (5 de Septiembre), Manglares Churute, and Ruta de los Chirijos. All node-level records, survey variables, and support relationships included in the repository were synthetically generated to preserve aggregate community characteristics while protecting participant confidentiality and preventing individual re-identification. The repository contains synthetic actor metadata, reconstructed socio-digital variables, directed support networks, graph representations in interoperable formats, and precomputed Social Network Analysis (SNA) indicators. The dataset includes 90 synthetic actors, more than one thousand generated support interactions distributed across multiple socio-digital dimensions, machine-readable metadata, and reusable scripts for preprocessing, validation, graph construction, and metric computation. The represented dimensions include financial assistance, training support, information exchange, technological support, social media promotion, institutional collaboration, trust, and emotional closeness. To facilitate reuse, all resources are distributed in standardized formats compatible with NetworkX, Gephi, Neo4j, and graph-learning frameworks. The repository follows FAIR principles and includes documentation intended to support transparency, reproducibility, and methodological benchmarking. Potential applications include social network analysis, graph mining, graph neural networks, digital inequality research, computational social science, community resilience studies, and educational activities. By providing an openly documented synthetic dataset and reproducible computational workflow, the repository contributes to the study of socio-digital systems, privacy-preserving data sharing, and community-level digital transformation processes. Full article

Tourism digitalization is widely viewed as a tool for sustainable local development, yet whether policy-led digital transformation generates measurable improvements in tourism-economy quality remains insufficiently tested. Treating the staggered establishment of China’s National Big Data Comprehensive Pilot Zones as a quasi-natural experiment, a sustainability-oriented index of high-quality tourism-economy development was constructed using 2011–2019 provincial panel data, and the policy effect was estimated with difference-in-differences and propensity-score-matched difference-in-differences models. The results show that the pilot zones significantly improve the sustainability-oriented quality of the tourism economy, a finding supported by parallel-trends tests, placebo tests, and multiple robustness checks. Heterogeneity analyses indicate positive effects across regional contexts and relatively larger estimated responses in the innovation, green, and shared development dimensions. For pilot-zone type, a more precisely estimated positive effect is shown for regional pilot zones within the current sample. Mechanism-oriented analyses show empirical patterns consistent with improvements in digital infrastructure, digital industry development, and regional innovation capacity as plausible explanatory channels. Quasi-natural experimental evidence is thus provided on how digital policy supports sustainable tourism and local development, with implications for destination governance, tourism service quality, and responsible digital transformation. Full article

Aquatic recreation significantly enhances well-being; however, individuals experiencing functional limitations remain frequently marginalized from this form of tourism due to infrastructural and environmental barriers. This study investigates the perceived operational risks and apprehensions encountered by users with specific accessibility needs during yacht sailing, aiming to inform inclusive vessel design aligned with the social dimension of sustainable development. A survey of 277 participants with diverse, officially certified functional limitations was conducted to evaluate their maritime experiences and safety concerns. Participants identified a mean of 11 pre-voyage apprehensions out of 19 distinct risk categories. The most prevalent concerns included stumbling, slipping, or falling on board (79%), the risk of falling overboard (73%), and seasickness (70%), with an overall moderate severity ($\overline{X}$ = 2.2 on a 4-point scale). Crucially, severe safety concerns (e.g., vessel sinking or falling overboard) were significantly mitigated following practical sailing experience. Conversely, everyday functional and ergonomic challenges—such as moving between the deck and crew quarters ($\overline{X}$ = 2.6), operating rigging ($\overline{X}$ = 2.7), embarkation ($\overline{X}$ = 2.6), and utilizing sanitary facilities ($\overline{X}$ = 2.1)—persisted irrespective of experience level. Statistical analysis revealed that gender and age had negligible effects on concern levels. Extensive maritime experience reduced apprehensions regarding balance and swimming competencies, while concurrently increasing awareness of communication and comfort-related operational challenges. This study highlights a distinct divergence between initial psychological anxiety—which is largely mitigated by experience—and persistent architectural barriers inherent in standard yacht design. The results underscore that achieving meaningful inclusivity in water tourism requires prioritizing interior spatial layouts, accessible sanitary facilities, and barrier-free vertical circulation in naval architecture, rather than focusing exclusively on emergency safety systems. These insights directly support the advancement of Sustainable Development Goal 10 and the integration of universal and human-centered design principles within the maritime recreation sector. Full article

Environmental degradation has intensified alongside rising carbon emissions driven by economic expansion, energy consumption, and transport activities. In recent decades, Middle Eastern economies have experienced substantial growth in tourism, trade openness, and energy use, raising concerns about their environmental consequences. This study investigates the impact of tourism activity, energy consumption, and trade openness on transport-related CO₂ emissions in ten Middle Eastern countries over the period 2000–2020. Data were obtained from the World Development Indicators (WDI) database of the World Bank. Using a panel autoregressive distributed lag (ARDL) framework, the analysis captures both short-run dynamics and long-run equilibrium relationships. To improve measurement robustness, tourism activity is proxied using two alternative indicators: international tourism expenditures (TEs) and international tourism receipts (TRs). The empirical results indicate that tourism activity and energy consumption significantly increase transport-related CO₂ emissions in both the short and long run, while trade openness does not exert a statistically significant long-run effect. These findings suggest that tourism expansion and energy-intensive transport systems are key contributors to environmental pressure In the region, whereas the environmental impact of trade may be indirect or conditional. The study highlights the importance of integrating sustainable tourism policies and improving energy efficiency. In addition, it underscores the need to develop low-carbon transport strategies to support environmentally sustainable economic development in Middle Eastern economies. Full article

Walking tourism is an important form of thematic and sustainable tourism, especially in rural and naturally attractive destinations. It contributes to diversifying the tourist environments and improving destination management. This paper analyses the role of walking tourism in destination management and uses an integrated machine-learning model to predict tourist preferences. A key focus of this study is identifying the key factors influencing walking tourism preferences, including demographic, socioeconomic, behavioural, and activity-related variables. The methodology of this study is based on an integrated Machine Learning (ML) approach. CatBoostClassifier was used as the primary predictive model, and hyperparameter optimization was performed using Particle Swarm Optimization (PSO). Model interpretability was ensured through SHapley Additive exPlanations (SHAP) analysis, supported by CatBoost feature importance evaluation. This combination enables both high prediction accuracy and transparent explanation of variable influence. The research is based on 467 responses collected through an anonymous online survey. Results confirm that walking tourism is predominantly linked to natural and mountain experiences, which have strong implications for destination planning and tourism product development. The proposed model provides reliable predictions of tourist preferences under class imbalance conditions, achieving a macro-F1 score of 0.5114. Additionally, key factors influencing the choice of walking tours were identified, supporting destination managers in tourist segmentation, tourism product development, and sustainable allocation of destination resources. Full article

Protected areas (PAs) are increasingly challenged by the need to reconcile biodiversity conservation with sustainable human use, particularly in landscapes containing underutilized or resting area (RA). This study evaluated the potential of resting forest and agricultural lands to enhance biodiversity and support sustainable land use within protected areas of Cesme, Türkiye. A Geographic Information System (GIS)-based multi-criteria evaluation approach was employed, integrating land cover data, soil group maps, topographic parameters, and protected area classifications to generate Plant Suitability Maps (PSMs). Eight thematic layers were developed, incorporating soil depth, slope, erosion risk, and land capability classes to identify suitable plant species and land-use options. The results indicate that the strategic use of resting agricultural lands could contribute up to 35.5% to ecological enhancement, while resting forest lands could contribute an additional 18%. The proposed plant assemblages include medicinal and aromatic species, erosion-control plants, and economically valuable perennial species that support ecosystem services such as pollination, beekeeping, and agro-tourism. Overall, the findings demonstrate that integrating RA management into conservation planning can simultaneously strengthen biodiversity, improve ecosystem services, and generate socio-economic benefits for local communities. The proposed GIS-based framework offered a transferable and scalable methodology for sustainable land management in Mediterranean landscapes and other protected regions worldwide. Also, in this research, the aim was to determine plant species using GIS-based suitability analyses of multi-spatial datato guide vegetation decisions in multi-criteria PA. Full article

This study addresses the fragmented understanding of tourist responses to AI-generated content (AIGC) in tourism and hospitality by developing a process-oriented systematic review. While prior studies have examined AIGC-related trust, authenticity, credibility, and adoption, these constructs have often been treated separately, limiting theoretical understanding of how tourists evaluate and rely on AI-generated tourism content. Based on a systematic review of 98 peer-reviewed journal articles retrieved from Scopus and the Web of Science Core Collection and published between January 2023 and March 2026, this study synthesizes the literature around four connected stages: perceived AIGC attributes, evaluative judgments, trust calibration, and behavioral responses. The findings show that tourist responses to AIGC are not direct reactions to technological exposure, but emerge through a layered process in which tourists assess content quality, credibility, authenticity, and contextual appropriateness before deciding whether and how far to rely on AI-generated outputs. The review contributes by reconceptualizing trust as a dynamic calibration mechanism, distinguishing authenticity from credibility and trust, and identifying reliance as a key bridge between evaluation and behavior. The study offers a process-oriented framework and a future research agenda for advancing more theoretically integrated and context-sensitive research on AIGC in sustainable digital tourism. By clarifying how tourists evaluate, trust, verify, and rely on AI-generated tourism content, the review contributes to sustainable tourism development by highlighting the conditions under which AIGC can support more responsible, transparent, and human-centered tourism communication. These insights are relevant to destination sustainability because trustworthy and context-sensitive AIGC can improve information quality, reduce misleading representations, and support more informed tourist decision-making. Full article

Underground heritage represents a hidden urban resource for cultural regeneration and sustainable tourism, preserving historical layers, wartime memory, and local identity. Positioning the shelters as a form of Underground Built Heritage (UBH), this study examines how concealed civil-defense spaces can be reinterpreted as local cultural heritage resources before systematic reuse. However, enclosed and unfamiliar spaces are often perceived as risky, making adaptive reuse socially sensitive. This study investigates Jingdezhen’s underground air-raid shelters through a scenario-based survey and partial least squares structural equation modeling (PLS-SEM). Using an extended Value-Attitude-Behavior (VAB) framework incorporating perceived authenticity, anticipated affective identification, safety assurance, and perceived risk, this study identifies factors influencing pre-development public acceptance. Results show that public acceptance is shaped by cognitive evaluation of value and anticipated affective identification, while perceived risk constrains behavioral intentions. Perceived authenticity enhances value perception and anticipated affective identification; perceived value strengthens attitudes; safety assurance shows a small but statistically significant negative association with perceived risk, although most variance in perceived risk remains unexplained; and an exploratory moderation analysis further suggested that perceived risk may weaken the attitude–visit intention relationship. Although the estimated model showed a relatively high SRMR, the results are interpreted as prediction-oriented ex ante evidence rather than as a covariance-based model with strong global fit. These findings provide prediction-oriented ex ante evidence for the sustainable reuse of underground heritage, supporting heritage interpretation, risk management, and urban regeneration aligned with SDG 11. 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

The development of sustainable tourism requires the use of planning methods that combine environmental protection with inclusive access to nature-based destinations. This article presents a macro-level spatial decision-support framework for planning service infrastructure for specialized off-road electric wheelchairs in mountain destinations. The proposed framework combines predefined static vehicle-related constraints, Geographic Information System (GIS) analysis using QGIS and OpenStreetMap data, and Multi-Criteria Decision Analysis (MCDA). The spatial filtering stage evaluates terrain feasibility using an adopted maximum longitudinal slope threshold and minimum path-width requirement. The location–allocation stage combines Simple Additive Weighting (SAW) with a spatial-dispersion procedure to identify service hubs that are both suitable and regionally distributed. The method is not a dynamic engineering model of vehicle performance, but a GIS-MCDA planning tool for preliminary regional infrastructure siting under predefined operational constraints. Full article

Digital platforms are increasingly presented as instruments for sustainable tourism governance, yet destinations often remain data-rich and governance-poor: digital traces are dispersed across actors, indicators are weakly standardised and communities frequently lack meaningful access to the information that shapes destination decisions. This article addresses this problem through the conceptual design and preliminary formative evaluation of ORVE (Optimisation of Resources and Valorisation of Experiences), a destination-level platform designed to connect tourists and residents, companies and institutions and Destination Management Organisations (DMOs) through a circular data ecosystem, understood as feedback loops across stakeholder levels. Methodologically, the study adopts Design Science Research (DSR). It operationalises problem identification, definition of solution objectives, artefact design and development, preliminary demonstration and formative evaluation, while recognising that full-scale causal evaluation remains a future research stage. The empirical component draws on a real-world pre-test with 12 tourism companies mediated by Biosphere Portugal, two Biosphere-administered pilot-company surveys involving 58 and 52 companies and scenario-based testing by 14 student groups involving more than 60 final-year students from Tourism and Tourism and Hospitality Management programmes. These sources are interpreted as exploratory and formative evidence rather than as a representative adoption study or a causal impact evaluation. The results suggest perceived usefulness for structuring sustainability information, supporting indicator monitoring and informing decision making, while also revealing operational constraints related to usability, data-entry flexibility, privacy communication, validation mechanisms, data availability in micro and small enterprises and the need for close onboarding support. The article contributes a refined platform architecture, a governance requirements matrix, design principles, an operationalisation roadmap and an evaluation protocol for sustainable tourism platform governance. 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

Ecologically fragile hilly areas are key regions for safeguarding national ecological security and advancing ecological civilization construction. Accurate assessment of ecosystem service value (ESV) and future scenario simulations in these regions is crucial for improving regional land use and attaining sustainable development. Based on high-resolution remote sensing data of the Longji Mountain area in Guangxi, China, from 2013 to 2023, this study systematically assesses the spatiotemporal evolution characteristics of ESV using the equivalent factor method with localized corrections. This study adopts spatial autocorrelation analysis, geographic modeling, and scenario simulation. It predicts the spatial patterns of ESV for 2028 and 2033 under three scenarios: ecological protection, natural development, and tourism development. The results reveal that: (1) from 2013 to 2023, the total ESV in the Longji Mountain area showed an overall fluctuating trend. It increased first, then declined and recovered slightly, with an average annual growth rate of −0.15%. Spatially, the ESV presented a heterogeneous pattern, characterized by “high-value agglomeration in forest land, medium-value transition in terraced fields, and low-value interpolation in constructed areas”, with distinct clustering features; (2) regional ecological functions are mainly dominated by regulating and supporting services. Climate regulation contributes the highest value. Water supply is the only service with negative value, indicating a persistent water ecological deficit that remains unaddressed; (3) scenario simulations reveal that the total ESV is highest and spatial connectivity is strongest under the ecological protection scenario. Furthermore, a consistent trend is observed across all three scenarios: high-value ESV areas tend to become dominant, while spatial connectivity shows progressive enhancement. The human–land system coupling framework for the ecologically fragile hilly region suggests that ecologically oriented decision-making is the core pathway to sustainably improve ecosystem services and realize regional sustainable development. This study offers scientific support for regional ecological conservation and sustainable advancement. Full article

Railway transport is increasingly recognized as a key pillar of sustainable mobility, offering a low-carbon and energy-efficient alternative to road and air transport and playing a critical role in achieving climate objectives, regional connectivity, and sustainable tourism development. Despite extensive research on service quality, sustainability, and tourism, their interrelationship within the railway sector remains insufficiently explored. This study aims to systematically analyze the intersection of quality management systems (QMS), sustainability, and tourism in passenger railway transport and to identify structural gaps that hinder their integration. A systematic literature review was conducted following the PRISMA methodology, resulting in a final sample of 37 studies. The findings reveal a significant research gap, particularly the absence of integrated and empirically supported QMS frameworks linking passenger satisfaction with sustainability and tourism objectives. Quality-management-oriented constructs appear in 48.6% of the analyzed studies, sustainability in 32.4%, and tourism in 24.3%, while none demonstrate full integration of all three dimensions. The study contributes by providing a conceptual basis for future research on the integration of operational quality management, environmental performance, and passenger-oriented service quality in railway systems. Full article

This study investigates the development and current status of agritourism in Croatia, with a specific focus on Istria County, a region characterized by favorable Mediterranean climatic conditions and a long-standing tourism culture. The research aims to assess the structure and success factors of agritourism enterprises within the broader Croatian tourism market. An empirical field survey was conducted on a sample of 58 agritourism businesses operating in Istria County. The collected data were analyzed using descriptive statistical methods, and enterprises were segmented into three groups according to their length of business operation. The results reveal significant differences among the identified groups in terms of demographic and professional characteristics, including age, educational attainment, prior tourism experience, years in business, and annual tourist visits. The analysis further identifies three key dimensions influencing agritourism: future development (1), consisting of economic and social variables enhancing the business; limitations (2) of land, capital, and laws that can hinder their future; and state interventions (3), such as incentives and taxes created by state authorities. The findings suggest that the sustainable development of agritourism in Istria depends on coordinated policy support, effective utilization of farm, local nature, and heritage resources, as well as continuous improvement in service provision. This study contributes to a better understanding of agritourism dynamics in emerging rural tourism markets and provides a basis for future research and policy development. Full article