Search Results (691)

Governments worldwide are mandating e-invoicing and real-time VAT reporting, yet many cash-intensive service SMEs continue to under-report VAT, eroding fiscal revenues. This study investigates whether financial technology (FinTech) adoption can reduce this under-reporting among tourism SMEs in Greece—an economy with high seasonal spending and a persistent shadow economy. This is the first micro-level empirical study to examine how FinTech tools affect VAT compliance in this sector, offering novel insights into how technology interacts with behavioral factors to influence fiscal behavior. Drawing on the Technology Acceptance Model, deterrence theory, and behavioral tax compliance frameworks, we surveyed 214 hotels, guesthouses, and tour operators across Greece’s main tourism regions. A structured questionnaire measured five constructs: FinTech adoption, VAT compliance behavior, tax morale, perceived audit probability, and financial performance. Using Partial Least Squares Structural Equation Modeling and bootstrapped moderation–mediation analysis, we find that FinTech adoption significantly improves declared VAT, with compliance fully mediating its impact on financial outcomes. The effect is especially strong among businesses led by owners with high tax morale or strong perceptions of audit risk. These findings suggest that FinTech tools function both as efficiency enablers and behavioral nudges. The results support targeted policy actions such as subsidies for e-invoicing, tax compliance training, and transparent audit communication. By integrating technological and psychological dimensions, the study contributes new evidence to the digital fiscal governance literature and offers a practical framework for narrowing the VAT gap in tourism-driven economies. Full article

This study employs a mixed method. In-depth interviews and observational studies are among the data collection approaches used in qualitative research. The quantitative method measures the weight of respondents’ answers to the distributed questionnaire. The questionnaire, containing 82 items, was distributed to 202 tourists to collect their perceptions based on the 4A tourist components. The results indicate that tourists’ perceptions of attractions, accessibility, and ancillary services are generally positive. In contrast, perceptions of amenity services are less favorable. Using the scores from IFAS, EFAS, and the I-E matrix, the total weighted scores for IFAS and EFAS are 2.68 and 2.83, respectively. The appropriate strategy for BTV is one of aggressive growth in a position of strengths and opportunities. The study highlights key techniques, including the application of information technology in service and promotion, the strengthening of community and government roles, the development of infrastructure and facilities, the utilization of external resources, sustainable innovation, and the encouragement of local governments to issue regulations for halal tourism villages. By identifying drivers and barriers from an economic, environmental, social, and cultural perspective, the SWOT analysis results help design strategies that can make positive contributions to the development of sustainable, community-based halal tourism and digital information in the future. Full article

Small towns in mountainous regions face significant challenges in formulating effective landscape zoning strategies due to pronounced landscape fragmentation, which is driven by both the dominance of large-scale forest resources and the lack of coordination between administrative planning departments. To tackle this problem, this study focused on Yuqian, a quintessential small mountainous town in Hangzhou, Zhejiang Province. The town’s layout was divided into a grid network measuring 70 m × 70 m. A two-step cluster process was employed using ArcGIS and SPSS software to analyze five landscape variables: altitude, slope, land use, heritage density, and visual visibility. Further, eCognition software’s semi-automated segmentation technique, complemented by manual adjustments, helped delineate landscape character types and areas. The overlay analysis integrated these areas with administrative village units, identifying four landscape character types across 35 character areas, which were recategorized into four planning and management zones: urban comprehensive service areas, agricultural and cultural tourism development areas, industrial development growth areas, and mountain forest ecological conservation areas. This result optimizes the current zoning types. These zones closely match governmental sustainable development zoning requirements. Based on these findings, we propose integrated landscape management and conservation strategies, including the cautious expansion of urban areas, leveraging agricultural and cultural tourism, ensuring industrial activities do not impact the natural and village environment adversely, and prioritizing ecological conservation in sensitive areas. This approach integrates spatial and administrative dimensions to enhance landscape connectivity and resource sustainability, providing key guidance for small town development in mountainous regions with unique environmental and cultural contexts. Full article

Dark skies, a vital natural and cultural resource, have been increasingly threatened by light pollution due to rapid urbanization, leading to ecological degradation and biodiversity loss. As a key strategy for sustainable regional development, dark sky parks (DSPs) not only preserve nocturnal environments but also enhance livability by balancing urban expansion and ecological conservation. This study develops a novel framework for evaluating DSP suitability, integrating ecological and socio-economic dimensions, including the resource base (e.g., nighttime light levels, meteorological conditions, and air quality) and development conditions (e.g., population density, transportation accessibility, and tourism infrastructure). Using the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as a case study, we employ Delphi expert consultation, GIS spatial analysis, and multi-criteria decision-making to identify optimal DSP locations and prioritize conservation zones. Our key findings reveal the following: (1) spatial heterogeneity in suitability, with high-potential zones being concentrated in the GBA’s northeastern, central–western, and southern regions; (2) ecosystem advantages of forests, wetlands, and high-elevation areas for minimizing light pollution; (3) coastal and island regions as ideal DSP sites due to the low light interference and high ecotourism potential. By bridging environmental assessments and spatial planning, this study provides a replicable model for DSP site selection, offering policymakers actionable insights to integrate dark sky preservation into sustainable urban–regional development strategies. Our results underscore the importance of DSPs in fostering ecological resilience, nighttime tourism, and regional livability, contributing to the broader discourse on sustainable landscape planning in high-urbanization contexts. Full article

While the explosive growth in e-commerce stresses urban logistics systems, city planners lack of fine-grained data in order to anticipate and manage the resulting freight flows. Using a three-stage analytical approach combining descriptive zonal statistics, hotspot analysis and different regression modeling from univariate to geographically weighted regression, this study integrates one year of parcel deliveries from a leading courier with open spatial layers of land-use zoning, census population, mobile-signal activity and household income to model last-mile demand across different land use types. A baseline linear regression shows that residential population alone accounts for roughly 30% of the variance in annual parcel volumes (2.5–3.0 deliveries per resident) while adding daytime workforce and income increases the prediction accuracy to 39%. In a similar approach where coefficients vary geographically with Geographically Weighted Regression to capture the local heterogeneity achieves a significant raise of the overall R² to 0.54 and surpassing 0.70 in residential and institutional districts. Hot-spot analysis reveals a highly fragmented pattern where fewer than 5% of blocks generate more than 8.5% of all deliveries with no apparent correlation to the broaden land-use classes. Commercial and administrative areas exhibit the greatest intensity (1149 deliveries per ha) yet remain the hardest to explain (global R² = 0.21) underscoring the importance of additional variables such as retail mix, street-network design and tourism flows. Through this approach, the calibrated models can be used to predict city-wide last-mile demand using only public inputs and offers a transferable, privacy-preserving template for evidence-based freight planning. By pinpointing the location and the land uses where demand concentrates, it supports targeted interventions such as micro-depots, locker allocation and dynamic curb-space management towards more sustainable and resilient urban-logistics networks. Full article

Online reviews increasingly shape experiential travel decisions. This study investigates how structural and linguistic features of user-generated content influence peer endorsement in wine tourism. While prior research has explored review valence and credibility, limited attention has been paid to how micro-level textual and identity cues affect social approval metrics such as likes. Grounded in the Elaboration Likelihood Model, the analysis draws on 7942 TripAdvisor reviews using automated web scraping, readability metrics, and multivariate regression. Results indicate that location disclosure significantly increases likes, while higher textual complexity reduces endorsement. Title length and reviewer contributions function as peripheral cues, with an interaction between complexity and title length compounding cognitive effort. Findings refine dual-process persuasion theory and offer practical insights for content optimization in post-pandemic tourism engagement. Full article

Growing awareness of sustainable development and green consumer concerns is driving the market expansion for green agriculture products. E-commerce live streaming gives rural enterprises a new channel through scenario-building and interaction, while agro-tourism integration combines resources to generate a variety of promotion scenarios. This study examines the effects of external stimuli, including social networks, resource endowment, infrastructure, and the characteristics of e-commerce streamers, on the perception, trust, perceived value, and purchase intention of green consumption. It is based on the SOR (Stimulus–Organism–Response) theoretical model and focuses on e-commerce live streaming in the agriculture-tourism integration scenario. According to a structural equation modeling (SEM) analysis of 350 consumer questionnaires, these external stimuli primarily influence purchase intention through perceived value, trust, and green consumption cognition, with resource endowment having the most significant impact. The effects of infrastructure on perceived value and streamer attractiveness on green consumption cognition are not statistically significant. This research not only broadens the use of the SOR model in the emerging field of agritourism integration but also offers rural businesses theoretical backing and useful guidance to maximize e-commerce live marketing and enhance agritourism integration. Full article

In the realm of recommender systems, the prediction of diverse customer preferences has emerged as a compelling research challenge, particularly for multi-state business organizations operating across various geographical regions. Collaborative filtering, a widely utilized recommendation technique, has demonstrated its efficacy in sectors such as e-commerce, tourism, hotel management, and entertainment-based customer services. In the item-based collaborative filtering approach, users’ evaluations of purchased items are considered uniformly, without assigning weight to the participatory data sources and users’ ratings. This approach results in the ‘relevance problem’ when assessing the generated recommendations. In such scenarios, filtering collaborative patterns based on regional and local characteristics, while emphasizing the significance of branches and user ratings, could enhance the accuracy of recommendations. This paper introduces a turnover-based weighting model utilizing a big data processing framework to mine multi-level collaborative filtering patterns. The proposed weighting model assigns weights to participatory data sources based on the turnover cost of the branches, where turnover refers to the revenue generated through total business transactions conducted by the branch. Furthermore, the proposed big data framework eliminates the forced integration of branch data into a centralized repository and avoids the complexities associated with data movement. To validate the proposed work, experimental studies were conducted using a benchmarking dataset, namely the ‘Movie Lens Dataset’. The proposed approach uncovers multi-level collaborative pattern bases, including global, sub-global, and local levels, with improved predicted ratings compared with results generated by traditional recommender systems. The findings of the proposed approach would be highly beneficial to the strategic management of an interstate business organization, enabling them to leverage regional implications from user preferences. Full article

This research analyzes the discourses and narratives surrounding the platform tourism economy in a highly touristified city, using Madrid as a case study. Rather than focusing on the socio-economic or spatial transformations themselves, the study examines how these processes are discussed, identifying the discursive strategies employed by different actors and ideologies, along with the power relations embedded in these narratives. A corpus of literature was compiled from twelve newspapers with varying ideological orientations and categorized according to political stance, access mode, and ideological radicalism. Using the LancsBox concordancer, a quantitative analysis was conducted to identify key discursive categories and preferred lexical items across ideological positions. These findings informed a subsequent in-depth qualitative analysis aimed at uncovering the rationalities behind each discourse: who speaks, how, and with what intent. The results reveal a dominant left-wing narrative that emphasizes institutional and economic mechanisms underlying platform tourism, highlighting associated social and urban harms. In contrast, conservative and liberal narratives are divided into two strands: a ‘heretic’ discourse that promotes and defends this new economic model, but also its urban results (e.g., gentrification), and a more institutional narrative framing platform tourism as inevitable and benign, thereby concealing the underlying structures of power. Full article

Microplastics (MPs) have emerged as a critical environmental challenge in China’s aquatic ecosystems, driven by rapid industrialization and population growth. This review synthesizes recent findings on the abundance, morphology, and polymer types of MPs in China’s freshwater systems (rivers, lakes, reservoirs) and coastal marine environments. Spatial analysis reveals significant variability in MP abundance, ranging from 0.1 items/L in Tibet’s Lalu Wetland to 30.8 items/L in Beijing’s Qinghe River, with polypropylene (PP) and polyethylene (PE) dominating polymer profiles. Coastal regions exhibit distinct contamination patterns, with the Yellow Sea (5.3 ± 2.0 items/L) and the South China Sea (180 ± 80 items/m³) showing the highest MP loads, primarily as fibers and fragments. Fluvial transport, atmospheric deposition, and coastal anthropogenic activities (e.g., fisheries, tourism) are identified as major pathways for marine MP influx. Secondary MPs from degraded plastics and primary MPs from industrial/domestic effluents pose synergistic risks through the adsorption of heavy metals and organic pollutants. Human exposure routes—ingestion, inhalation, and dermal contact—are linked to inflammatory, metabolic, and carcinogenic health outcomes. Policy interventions, including bans on microbeads and non-degradable plastics, demonstrate progress in pollution mitigation. This work underscores the urgency of integrated source control, advanced wastewater treatment, and transboundary monitoring to address MP contamination in aquatic ecosystems. Full article

Tourism is recognized as one of the key enabling industries driving Thailand’s strategic transition toward the Thailand 4.0 economic model. This paper presents the development of a national technology roadmap to support the transition toward sustainable tourism in Thailand, conducted between January and October 2024. The primary objective is to promote tourism growth that is environmentally responsible, economically viable, and socially inclusive. The roadmap was developed through a combination of a literature review, statistical data, and group discussions with tourism professionals. The roadmapping process focused on aligning external drivers, strategic goals, and the current capabilities of Thailand’s technological ecosystem. The key drivers identified include environmental concerns, the advancement of digital platforms, the growing trends of an aging population, diversity, and inclusion, political instability, and the emergence of middle-income nations. The resulting roadmap outlines a strategic vision for Thailand’s tourism sector from 2024 to beyond 2030. It emphasizes the transition linking sustainability and eco-design principles to smart tourism, metaverse applications, and personalized travel experiences. Priority areas include the adoption of green technologies, sustainable practices, and advanced digital platforms. This study further recommends research and development (R&D) initiatives in sustainability, biodiversity conservation, Data Analytics, Cybersecurity, and E-Tourism solutions. Ultimately, this roadmap provides actionable guidance for tourism stakeholders in defining their roles, responsibilities, and contributions toward achieving a sustainable tourism future in Thailand. Full article

Suyukou Gully, located on the eastern slope of the Helan Mountains in northwest China, is a typical debris-flow-prone catchment characterized by a steep terrain, fractured bedrock, and abundant loose colluvial material. The area is subject to intense short-duration convective rainfall events, which often trigger destructive debris flows that threaten the Suyukou Scenic Area. To investigate the dynamics and risks associated with such events, this study employed the FLO-2D two-dimensional numerical model to simulate debris flow propagation, deposition, and hazard distribution under four rainfall return periods (10-, 20-, 50-, and 100-year scenarios). The modeling framework integrated high-resolution digital elevation data (original 5 m DEM resampled to 20 m grid), land-use classification, rainfall design intensities derived from regional storm atlases, and detailed field-based sediment characterization. Rheological and hydraulic parameters, including Manning’s roughness coefficient, yield stress, dynamic viscosity, and volume concentration, were calibrated using post-event geomorphic surveys and empirical formulations. The model was validated against field-observed deposition limits and flow depths, achieving a spatial accuracy within 350 m. Results show that the debris flow mobility and hazard intensity increased significantly with rainfall magnitude. Under the 100-year scenario, the peak discharge reached 1195.88 m³/s, with a maximum flow depth of 20.15 m and velocities exceeding 8.85 m·s⁻¹, while the runout distance surpassed 5.1 km. Hazard zoning based on the depth–velocity (H × V) product indicated that over 76% of the affected area falls within the high-hazard zone. A vulnerability assessment incorporated exposure factors such as tourism infrastructure and population density, and a matrix-based risk classification revealed that 2.4% of the area is classified as high-risk, while 74.3% lies within the moderate-risk category. This study also proposed mitigation strategies, including structural measures (e.g., check dams and channel straightening) and non-structural approaches (e.g., early warning systems and land-use regulation). Overall, the research demonstrates the effectiveness of physically based modeling combined with field observations and a GIS analysis in understanding debris flow hazards and supports informed risk management and disaster preparedness in mountainous tourist regions. Full article

Trade fairs are not only commercial platforms but also catalysts for urban development, city branding, and international engagement. This longitudinal study analyzes data from trade fair exhibitors from China, the United Arab Emirates (UAE), and Germany to examine how cultural differences influence their experiences, satisfaction, and destination loyalty within the urban landscape of Thessaloniki. By adopting Social Exchange Theory (S.E.T.) as a framework, this research applies a mixed-methods approach, combining surveys and in-depth interviews conducted over multiple years (2017–2024) at the 82nd, 86th, and 88th Thessaloniki International Fair (T.I.F.). The empirical material consists of 226 survey responses (116 from China, 44 from the UAE, and 84 from Germany) and 52 semi-structured interviews, analyzed using descriptive and non-parametric statistics, alongside thematic interpretation of qualitative data. Findings reveal distinct exhibitor expectations. These cultural distinctions shape their perceptions of Thessaloniki’s infrastructure, services, and overall urban experience, influencing their likelihood to revisit or recommend the city. This study underscores the long-term role of trade fairs in shaping urban economies and offers insights into how cities can leverage international exhibitions for sustainable urban growth. Policy recommendations highlight the need for tailored infrastructural improvements, strategic city branding initiatives, and cultural adaptations to enhance exhibitor engagement and maximize the economic impact of global events. Full article

This study investigates the impact of web-based augmented reality (Web AR) on destination visit intention through the lens of a stimulus–organism–response (SOR) framework, a technology acceptance model (TAM) and flow theory into an integrated theoretical framework. This study aims to address gaps in the literature by providing insights about the relevance of augmented reality to tourism marketing effectiveness. Structural equation modeling was used to test this conceptual framework using AMOS23 on quantitative data collected from questionnaires distributed locally and internationally and applied to 384 participants after going through a Web AR destination experience. The findings confirmed that Web AR stimuli (i.e., interactivity and vividness) positively impact tourists’ destination visit intention through the tourist organism in terms of perceived ease of use, perceived usefulness, perceived certainty, perceived enjoyment and perceived immersion. Therefore, the promotion of destinations through augmented reality technology contributes to the development of sustainable tourism. The findings of this study will shed light on an alternative idea for destination marketing to inspire destination management organizations (DMOs) wishing to develop a competitive edge and win within the tourism industry. The results thus contribute to the Web AR and the tourism marketing literature by providing theoretical guidance through a framework for the AR tourism experience, as well as a reference for DMOs. Full article

The accessibility of nature trails for people with motor disabilities and impairments stands as a significant challenge for inclusive tourism. In the present study, we would like to present a review of research, approaches, and solutions to enable people with motor impairments to enjoy nature trails independently or with assistance. The study is conducted from the perspective of public bodies that aim to reduce the accessibility barriers for People with Disabilities (PwDs) by adapting and improving the conditions of the trails and by providing clear and comprehensive information about the difficulties that hikers may encounter on a trail while using a specific aid. The paper initially presents the wide variety of aids for outdoor mobility, including both those to be used independently (i.e., self-propelled wheelchairs that can be equipped with additional small wheels, off-road wheels and/or auxiliary drives) and those that require assistance (e.g., single-wheeled wheelchairs). Then, we shift focus onto the difficulty classification of trails for PwDs, analysing papers and guidelines that tried to define objective evaluation criteria such as the slope, the trail surface, and the length of the sloping sections. Starting from these studies, the paper proposes a synthesis of the different classifications that consider, for the first time, all the aids available on the market, thus filling the gaps of the single studies. In the last sections, we present some national and international guidelines with tailored and practical solutions to improve the accessibility of nature trails and some studies about the inclusive planning that directly involves PwDs, as well as on the need for a better training of tourism service providers. The present work aims to stimulate a debate on the barriers and opportunities related to the accessibility of hiking trails, contributing to making nature a truly accessible experience for all. Full article