Search Results (203)

Architectural heritage plays a central role in shaping visitors’ emotional experiences within cultural tourism contexts. However, empirical research examining how specific architectural styles evoke emotional responses remains limited, particularly when using objective measurement techniques. This study investigates emotional reactions to architectural heritage by applying the Stimulus–Organism–Response (SOR) theoretical framework. In this model, architectural styles act as environmental stimuli, emotional processing represents the organismic state, and the resulting emotional activation constitutes the response. An experimental protocol was conducted with a sample of 645 participants exposed to a series of standardized architectural heritage images representing different architectural styles and infrastructure types. Emotional reactions were captured in real time through facial emotion recognition technology, enabling the objective measurement of eight basic emotions: neutral, happiness, sadness, surprise, fear, disgust, anger, and contempt. The collected emotional data were statistically analyzed using Analysis of Variance (ANOVA) to identify significant differences in emotional responses across architectural styles, heritage typologies, and gender. When significant differences were detected, Tukey’s HSD post hoc tests were applied to determine specific group contrasts. The findings reveal that different architectural styles generate distinct emotional patterns, highlighting the role of architectural aesthetics as a powerful mediator of affective engagement with heritage environments. From a theoretical perspective, this research contributes to heritage tourism and environmental psychology by integrating the SOR framework with real-time emotion detection technologies, providing a novel methodological approach for analyzing emotional responses to architectural heritage. Full article

Nature-based tourism in protected areas brings economic benefits but can also lead to negative environmental impacts, such as trail degradation. This study aimed to quantify hiking-induced degradation on the Mvubu and Nkonkoni trails in Enseleni Nature Reserve, South Africa. Data were collected through systematic sampling at 20 points along each trail, with 50-m intervals between sampling locations. Several trail degradation indicators were recorded, including: trail grade (TG), landform grade (LG), cross-sectional area (CSA), soil compaction, surface composition, soil texture, and soil moisture. Maximum incision depth (MID) and trail width (WID) were treated as response variables. Statistical relationships between degradation indicators and response variables were analysed using linear regression and partial least squares regression (PLSR). The results indicated significant differences (p < 0.05) between the two trails for several degradation indicators, including surface composition (specifically soil cover), soil compaction, soil texture, and soil moisture. PLSR models explained 19–20% of the variance in MID and 12–55% of the variance in WID. Such weak model performance suggests that trail degradation may be influenced by additional factors not measured in this study. In particular, human behavioural factors, such as hiker avoidance of muddy sections, may play an important role in shaping patterns of trail degradation beyond the measured environmental variables. Early signs of rill erosion were observed on the Mvubu Trail, while informal trail formation was evident on the Nkonkoni Trail. Consequently, the study recommends a dual-track strategy involving revegetation along with the installation of water bars and check dams on the Mvubu Trail to prevent rilling, and “Leave-No-Trace” visitor education for the Nkonkoni Trail to reduce informal path formation. Full article

Numerous metrics, such as visitor numbers, tourism net profit, and hotel occupancy rates, are included in the dataset presented in this study, which covers 77 provinces. A baseline-based concept of shock recovery is introduced to measure impact and recovery paths in different regions. Recurrent neural networks incorporate engineered elements that capture seasonality, trend dynamics, shock strength, volatility, and recovery timing. Importantly, latent spatial heterogeneity and cross-regional dependencies are learned within a single architecture by integrating province-level spatiotemporal embeddings. To jointly forecast tourism demand and net profit, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models are created. Using a time-preserving evaluation technique, model performance is assessed against statistical time-series baselines and XGBoost. In early 2020, the results show a structural break that exceeded the 95% decline, along with significantly unequal recovery patterns. The suggested deep learning models surpass baselines by roughly 22–28% in RMSE and 14–16% in MAPE, exhibiting superior ability in capturing spatial heterogeneity and nonlinear recovery dynamics. Full article

Understanding and managing tourism event experiences requires insight into how emotions unfold across space. Drawing on constructed emotion theory, this study advanced both theoretical and methodological knowledge by comparing three spatial emotion mapping approaches. Namely, we applied experience reconstruction maps, emotion physiology maps, and emotion effectiveness maps to visitor experiences of two events at nature-based fort settings in the Netherlands. Using intercept sampling (N = 98), we combined questionnaires with GPS tracking and skin conductance measurement to collect location-resolved emotional data. The resulting maps revealed markedly different spatial emotion patterns, reflecting distinct emotional components: physiological arousal and recalled or reconstructed emotional arousal and valence. Studies which map emotions have usually not accounted for within-individual autocorrelation. Our multilevel statistical models, in contrast, did account for this. The difference in emotion ranking of AOI raised questions about the validity of previous emotion mapping efforts. We extended constructed emotion theory to spatial analysis, demonstrated the limits of current mapping methods, and argued in favor of controlling for autocorrelation for robust spatial emotion research. Our findings can provide methodological guidance for researchers and event managers, and can lay the groundwork for future innovations that integrate physiological, self-reported, and spatial data for sustainable tourism event management. Full article

Dispersed archaeological landscapes are often rich in heritage value but weakly integrated into regional tourism systems. This creates difficulties in visitor orientation, interpretive continuity, and conservation-sensitive tourism planning. In response to this problem, this study examines the Adana–Kozan–Anavarza axis in southern Türkiye and proposes a spatial corridor framework for organising tourism development within a dispersed archaeological landscape. The research integrates spatial accessibility assessment, service-capacity evaluation, field observation, and sequential route design in order to establish a hierarchical gateway–transition–anchor configuration. Anavarza, one of the largest archaeological complexes of Cilicia, represents a monumental urban heritage site and a biocultural landscape situated within a Mediterranean ecological zone historically associated with Pedanius Dioscorides. Although current visitor volumes remain moderate, official statistics indicate a substantial increase in annual entries between 2022 and 2024, reflecting rising destination visibility. This emerging growth trajectory underscores the need for proactive spatial governance mechanisms prior to the onset of congestion and environmental degradation pressures. The findings suggest that Adana can function as a metropolitan gateway, Kozan as an intermediate staging node, and Anavarza as the archaeological anchor within a realistic multi-day visitor sequence. In this configuration, visitor functions are distributed across multiple nodes, while the ecological and archaeological sensitivity of the anchor landscape is more cautiously managed through spatial sequencing. Rather than proposing a predictive model, the study develops and assesses a context-responsive spatial planning framework grounded in accessibility, infrastructural feasibility, and conservation-sensitive visitor distribution. Beyond the local case, the study offers a transferable hierarchical staging logic for corridor-based heritage planning. Full article

Background: Frequent and short-term repeat visits place significant pressure on primary care-centered health systems, particularly in large metropolitan areas. Istanbul, with its high population density and heterogeneous sociodemographic profile, presents a unique context for understanding short-interval healthcare utilization dynamics. Objective: To examine short-term repeat healthcare utilization following an index primary care visit and to explore how district-level population and socioeconomic characteristics shape early post-visit care-seeking dynamics in a large metropolitan setting. Methods: This retrospective cohort study analyzed protocol records from 225 randomly selected FMUs across Istanbul. A total of 11,101 individuals who presented on 7 July 2025 were followed for 21 days, during which 26,743 healthcare contacts (index family medicine unit visits, recurrent FMU visits, and secondary/tertiary care visits) were captured. FMU repeat visits, higher-level utilization, district-level population density, and socioeconomic development level (SEGE-2022) were analyzed using descriptive statistics and district-level comparative analyses. Results: During the 21-day follow-up period, participants generated a total of 26,743 healthcare contacts. Across the full cohort, the median number of recurrent FMU visits was 0 (IQR 0–1), and the median number of secondary/tertiary visits was 0 (IQR 0–1). Among individuals who had repeat contacts, the median number of recurrent FMU visits was 1 (IQR 1–2), and the median number of secondary/tertiary visits was 1 (IQR 1–2). Repeat visits clustered in the first 7 days, whereas higher-level visits increased between days 10–21. Districts with lower SEGE status and high population density (e.g., Esenyurt, Bağcılar, Pendik, Küçükçekmece, Ümraniye) exhibited markedly higher repeat visit intensity. Spatial patterns indicated substantial clustering in western and socioeconomically disadvantaged districts. Multivariable regression analysis showed that visitor patient status was associated with higher secondary/tertiary care utilization (OR = 1.14, 95% CI 1.04–1.24), while higher SEGE scores were modestly associated with increased repeat FMU visits. Conclusions: Short-term repeat visits in Istanbul appear to be influenced not only by clinical needs but also by broader contextual factors such as socioeconomic disadvantage, population density, and health system organization. These findings suggest potential structural pressures within Türkiye’s primary care-centered system and highlight the potential value of district-specific interventions. Full article

Forest recreation sites provide accessible settings for everyday leisure while accommodating multiple, and often competing, uses, making zoning both a central planning challenge and solution. This study advances micro-zoning as a novel, site-scale extension of established recreation zoning concepts, examining how zoning principles can be operationalized within intensively used forest recreation areas. Data were collected from 302 visitors using a structured questionnaire on visit patterns, valued forest attributes, disturbances, and socio-demographic characteristics. Descriptive statistics and tests of association were used to identify needs, disturbances, and recurring combinations of use. The results show that these forests function as everyday recreation spaces for diverse group visits, with high importance placed on peacefulness, shade, cleanliness, natural scenery, and basic infrastructure, alongside frequent reports of disturbance from music, crowding, and litter. Building on these patterns, the study develops a micro-zoning framework that delineates three interpretive planning micro-areas: Drive-in Forest Recreation, representing high-intensity, infrastructure-oriented social use; Low-Intensity Recreation, a moderate-use, low-noise nature-oriented area prioritizing separation from disturbance; and Active Recreation Use, comprising movement-focused routes for walking, running, and cycling. The study illustrates how visitor survey data can guide evidence-based micro-zoning and adapt zoning frameworks to the fine spatial grain of intensively used forest recreation sites. Full article

This study presents a comprehensive regional analysis of the COVID-19 pandemic’s impact on tourism in Slovakia during 2018–2024, employing rigorous statistical methods to quantify sectoral transformations. Based on extensive data on visitor arrivals, revenues, and accommodation facility utilisation across eight NUTS III regions, the analysis identifies four distinct regional tourism clusters characterised by differentiated recovery trajectories. Paired t-tests confirmed statistically significant changes in international tourist arrival indices across seven regions (p < 0.05), validating fundamental structural reorientation in tourism demand. The findings reveal pronounced heterogeneity in recovery patterns: while the Bratislava Region and the Žilina Region achieved substantial revenue growth (46.04% and 146.54%, respectively), domestically oriented regions (Banská Bystrica, Košice, Nitra, Prešov, and Trenčín) demonstrated minimal recovery (8.19% aggregate growth). Critical findings include the persistence of passive tourism dominance (94.09% of national revenues), declining international competitiveness from traditional Western European source markets, and compensatory expansion from emerging markets (USA +398.73%, Oman +234.68%, and Poland +226.55%). The ANOVA analysis revealed no statistically significant differences between regional indices in 2024 (p = 0.362), indicating market stabilisation despite differentiated trajectories. The study emphasises the necessity of regionally calibrated sustainable strategic interventions to diversify experiential tourism, activate the domestic market, and enhance technological infrastructure to build sectoral resilience against future exogenous shocks. Full article

Wellness tourism represents a significant growth sector within the global tourism industry; however, empirical research examining development determinants in resource-constrained, emerging African destinations remains limited. This study investigates the structural relationships among infrastructure development, community involvement, marketing and promotion, and visitor expectations/service quality in advancing wellness tourism at Allelobad Hot Spring in Ethiopia’s Afar Region. Using a quantitative methodology, structured questionnaires were administered to 210 respondents (visitors, local community members, and tourism stakeholders), resulting in 186 valid responses. Data were analyzed through Confirmatory Factor Analysis (CFA) and Partial Least Squares Structural Equation Modeling (PLS-SEM). Results demonstrate that all four determinants exert statistically significant positive effects on wellness tourism development (p < 0.001), with visitor expectations and service quality emerging as the strongest predictor (β = 0.35), followed by infrastructure development (β = 0.32), marketing and promotion (β = 0.30), and community involvement (β = 0.27). The structural model explains 68% of the variance in wellness tourism development, indicating substantial explanatory power. These findings underscore that sustainable wellness tourism growth in emerging destinations necessitates integrated, multidimensional strategies that simultaneously address physical infrastructure, stakeholder engagement, strategic positioning, and experiential excellence, rather than isolated sector-specific interventions. Full article

Public green spaces play a critical role in fostering social cohesion in rapidly industrializing cities. However, empirical research on how urban residents in non-Western contexts perceive, evaluate and use these spaces remains limited, particularly in Islamic industrial cities with distinct cultural practices and urban development patterns. This study examines determinants of visitor satisfaction in Coastal Park, Asaluyeh, a rapidly industrializing Persian Gulf city. The city’s industrial character, marked by acute green space scarcity and demographic imbalances due to workforce migration, provides a distinctive context for examining urban park dynamics in Iran’s petrochemical industrial zones. Using structured questionnaires and systematic field observations, we assess factors influencing park satisfaction and the role of the park in facilitating community bonds. Results reveal that vegetation quality shows the strongest association with visitor satisfaction (r = 0.45, p < 0.001), surpassing demographic characteristics in explanatory power. The park predominantly serves group-based activities, with family gatherings representing the dominant form of social interaction, reflecting cultural preferences for communal recreation. Significant disparities emerge across men and women in satisfaction levels and usage patterns. Temporal concentration during weekend evenings is driven by extreme daytime heat, while transportation barriers limit equitable access. Statistical analyses indicate weak correlations between demographic variables and satisfaction, underscoring the primacy of experiential factors in shaping visitor perceptions. The findings provide evidence-based recommendations for culturally sensitive park design in industrial Islamic cities, emphasizing the need for infrastructure, amenities, and improved public transport connectivity to ensure equitable access across diverse demographic groups. Full article

Biosecurity plays a central role in preventing disease transmission in dairy production systems and animal welfare. However, quantitative data on biosecurity implementation in smallholder and medium-scale dairy farms remains inconsistent, especially in developing countries. This study provides a structured assessment of on-farm biosecurity practices in northern Kosovo using a standardized, risk-based scoring approach. A cross-sectional survey was conducted on 55 dairy farms using the unmodified Biocheck.UGent™ dairy questionnaire. External and internal biosecurity scores were calculated through predefined, weighted algorithms and analyzed using non-parametric descriptive statistics. Farm-level results were subsequently compared with international reference values derived from the Biocheck.UGent™ global database. The median biosecurity scores for Kosovo farms were 47.8% for external biosecurity and 29.0% for internal biosecurity, indicating uneven implementation with pronounced weaknesses in measures designed to limit within-herd transmission. The lowest-scoring domains were purchase and reproduction and feed and water within external biosecurity, and working organization and equipment, calf management, and calving management within internal biosecurity. In contrast, visitors and farmworkers, control of vermin and other animals among external measures, and adult cattle management among internal measures, showed relatively higher scores, although all remained below international reference levels. When compared with the global overall biosecurity reference median of 76.7% derived from the Biocheck.UGent™ database, the biosecurity performance of the surveyed dairy farms in Kosovo was substantially lower. This gap does not indicate a complete absence of biosecurity measures but rather an uneven application, with the most pronounced deficiency observed in routine practices that govern within-herd disease transmission. The use of a risk-based scoring system allowed these weaknesses to be identified in a structured manner and placed the Kosovo results within an international benchmarking framework. In this context, the approach functions as a practical diagnostic tool, enabling farmers and veterinarians to prioritize feasible, epidemiological-relevant improvements within small- and medium-scale dairy production settings. Full article

The Venice lagoon is the largest in the Mediterranean Sea. The historic city of Venice, located on a cluster of islands in the centre of this lagoon, is an enchanting and iconic destination for national and international tourists. The historical centre of Venice and the other islands of the lagoon, such as Burano, Murano and Torcello, attract crowds of tourists every year. Transportation is provided by boats navigating the lagoon along a network of canals. The lagoon itself attracts visitors who enjoy various outdoor recreational activities in the open air, such as fishing and sunbathing. While statistics are available for the activities targeting the islands, no information is currently available on the spatio-temporal distribution of recreational activities across the lagoon waters. This study explores the feasibility of using Sentinel-2 satellite images to assess and map the spatio-temporal distribution of boats in the Venice Lagoon. Cloud-free Level-2A images have been selected to study seasonal (summer vs. winter) and weekly (weekends vs. weekdays) variabilities in 2023, 2024, and 2025. The RGB threshold filtering and the U-Net Semantic Segmentation were applied to the Sentinel-2 images to ensure reliable results. Two spatial indices were produced: (i) a Water Recreation Index (WRI), identifying standing boats in areas attractive for recreation; and (ii) a Water Transportation Index (WTI), mapping moving boats along the canals. Multi-temporal WRI maps allow areas with recurring recreational activities—that are significantly higher in the summer compared to winter, and on weekends compared to other weekdays—to be identified. The WTI identifies canal paths with higher traffic intensity with seasonal and weekly variations. The latter should be targeted by measures for traffic control to limit wave induced erosion, while the first could be subject to protection or development strategies. Full article

In the era of digital intelligence, cultural heritage is undergoing a profound transformation. This study investigates how digital technologies facilitate the inheritance and innovation of traditional culture in China, focusing on the case of Huangyan’s Song Rhyme Culture in Zhejiang Province. Drawing on the framework of “glocalized intelligent heritage,” the research explores how global technological systems interact with local cultural practices to produce new forms of cultural continuity. Methodologically, the study employs a qualitative case study approach supported by empirical data. It combines policy analysis, semi-structured interviews with twenty-six stakeholders, field observations, and quantitative indicators such as visitor statistics, online engagement, and project investment. This mixed design provides both contextual depth and measurable evidence of digital transformation. The findings show that digital intelligence has reshaped cultural representation, platform-based public engagement, and local sustainability. In Huangyan, technologies such as AI-based monitoring, 3D modeling, and VR exhibitions have transformed heritage display into an interactive and educational experience. Digital media have enhanced public engagement, with more than 1.2 million virtual visits and over 20 million online interactions recorded in 2024. At the same time, the project has stimulated cultural tourism and creative industries, contributing to a 28.6% increase in cultural revenue between 2020 and 2024. The study concludes that digital intelligence can function as a cultural bridge by strengthening heritage mediation, widening access, and enabling platform- and institution-based participation, while noting that embodied intergenerational cultural transmission lies beyond the direct measurement of this research design. Full article

The growing integration of immersive technologies in the tourism sector raises questions about their real impact on the visitor experience. This study investigates whether mixed reality effectively influences the tourism experience, seeking to understand the mechanisms through which tourism content and emerging technologies shape tourists’ perceptions. A quantitative approach was adopted through the application of a questionnaire. The data were analyzed using the PLS-SEM (Partial Least Squares Structural Equation Modeling) method, allowing us to test direct and indirect relationships between the constructs Tourism Content, Adoption of Mixed Reality, and Tourist Experience. The analysis revealed positive and statistically significant direct effects. Tourism content strongly influences the adoption of mixed reality (β = 0.725; p < 0.001). Moderate impacts of the adoption of mixed reality (β = 0.375; p < 0.001) and tourism content (β = 0.392; p = 0.001) on the tourist experience were found. The indirect effect mediated by the adoption of mixed reality proved to be significant (β = 0.272; p = 0.001), with a VAF (Variance Accounted For) of 41%. Mixed reality plays a complementary partial mediating role in the relationship between tourism content and visitor experience, confirming its relevance in the contemporary tourism experience. Full article

Historic religious cities are living examples of cultural landscapes where spiritual traditions, heritage, and visitor experiences combine to demonstrate a timeless experience. It is very challenging to achieve balance among the demands of mass pilgrimage, heritage preservation, and urbanization. Govardhan, India is a Hindu religious town with historical significance. Millions of pilgrims travel to Govardhan every year to perform parikrama and take a holy dip in kunds. The quality of the visitor experience, spatial coherence, and heritage conservation are all at risk due to increasing urbanization and tourism. The study intends to create a paradigm for the sustainable management of religious heritage towns by evaluating the factors involving visitor perception, historical significance, and spatial visibility, employing a combination of computational methods and cognitive assessments. The study employed space syntax tools (visibility graph analysis and isovist area analysis) to quantify spatial significance (SS) and identify patterns of openness, congestion, and visibility along the parikrama route of Govardhan. By examining pilgrims’ cognitive surveys for openness, orientation, congestion, and spiritual impression, a cognitive index (CI) and heritage importance scores (HIS) have been developed. The computed spatial significance (SS) has been correlated with cognitive index (CI) and heritage importance (HIS) scores to create an experiential priority index (EPI). The study employs a mixed-method approach that incorporates heritage significance scoring, cognitive surveys, and spatial analytics, including methods such as the isovist area analysis and visibility graph analysis. In order to assess how spatial arrangement and intangible perceptions together influence visitor experience, these statistics are further combined using a composite experiential priority index (EPI). The findings show a strong correlation between spiritual orientation, visual connectivity, and spatial openness; locations such as ‘punchari ka lota temple’ and ‘kusum sarovar’ are high-priority nodes. In accordance with United Nation Sustainable Development Goals (SDGs) (11, 9, 12, 4.7, and 8.9), this research proposes a heritage impact assessment (HIA) framework that provides workable solutions for ecological restoration, heritage-sensitive zoning, sustainable pilgrimage management, and enhanced tourism. Full article