Search Results (89)

Tourism seasonality remains one of the most persistent structural challenges of Mediterranean destinations, intensifying environmental, economic and social pressures during peak months while leaving tourism capacity underused in the remainder of the year. This paper examines the level, spatial distribution and structural determinants of tourism seasonality in 61 Mediterranean EU NUTS–2 regions from Croatia, Spain, Greece, Portugal and Italy over the period 2020–2024. Using harmonised Eurostat data, annual Gini coefficients are calculated from monthly overnight stays and analysed within a balanced panel of 305 region-year observations, testing whether seasonality is associated with international tourism dependency, hotel accommodation share and island geography, while controlling for regional GDP per capita, tourism intensity and the COVID-19 disruption period. Fixed and random effects models are estimated, with model choice guided by the Hausman test and cluster-robust standard errors applied at the regional level, complemented by a correlated random effects (Mundlak) specification. The results show substantial regional heterogeneity: Greece and Italy record the highest average seasonal concentration, while Spain and Portugal display more balanced patterns, partly due to regions with year-round demand, and Jadranska Hrvatska emerges as the most seasonally concentrated non-island region in the sample. A higher hotel accommodation share is significantly associated with lower seasonality, while the COVID-19 years significantly increased seasonal concentration, with concentration levels returning to recovery-phase values from 2022 onwards; as the panel does not include pre-pandemic baseline years, the findings compare the pandemic phase (2020–2021) with the recovery phase (2022–2024) and do not directly test a return to pre-pandemic equilibrium. The study contributes to comparative destination research by operationalising the Gini coefficient as a dependent variable in a multi-country regional panel framework and provides policy-relevant evidence for supply-side deseasonalisation strategies embedded in integrated destination management. Full article

Tourism is an activity that contributes positively to economic growth. Although tourism should be supported because of its benefits for a region’s development, it can place a strain on the environment. Integrating the principles of sustainable development into tourism is essential to ensuring its long-term viability while protecting natural and cultural resources. The purpose of this study is to determine the extent of tourism pressure, its trends, and its impact on sustainable development in three major rural tourist regions of Romania, namely Humor, Câmpulung Moldovenesc, and Dorna, located in the historical province of Bucovina, Suceava County. An analysis of the trends in the three evaluation indicators (density, duration, and pressure level) at the rural region level (Humor Region, Câmpulung Moldovenesc Region, and Dorna Region) is warranted, as these regions are the main centers of attraction and development for rural tourism in Suceava County. Between 2001 and 2023, the density indicator (arrivals/km²) showed significant increases in all three rural regions analyzed—over 6000% in Humor, 2200% in Dorna, and 2000% in Câmpulung Moldovenesc, significantly amplifying the pressure on these three areas; the duration indicator (overnight stays/km²) recorded considerable increases of over 7400% in Humor, 2400% in Dorna, and 2250% in Câmpulung Moldovenesc, proving to be a much more severe pressure indicator than the density indicator; and the pressure level indicator (arrivals/resident population) increased substantially, by over 8000% in Humor, 2100% in Dorna, and 2000% in Câmpulung Moldovenesc, indicating profound sociocultural pressure on the rural communities analyzed. The importance of this research and the originality of this study are closely linked to an understanding of the evolution and intensity of tourism pressure in the three regions analyzed, with a view to informing future strategies for sustainable rural development. An analysis of the environmental pressure caused by tourism in the three regions of Bucovina for the period 2001–2023 reflects a shift from a localized and negligible impact to an increasingly significant pressure. Currently, the regions face the challenge of balancing rapid economic development with the critical need to preserve their unique heritage. Identifying increases in tourist pressure can facilitate the implementation of effective mitigation measures, which are essential for ensuring the sustainability of tourism-related activities in the most popular tourist regions of Bucovina. Full article

Commodity prices are notoriously hard to forecast, and whether the returns of commodity exchange-traded funds (ETFs) can be predicted remains an open question. We compare three deep learning models, Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Transformer, for forecasting the returns of six Deutsche Bank commodity ETFs covering agriculture (DBA), base metals (DBB), broad commodities (DBC), energy (DBE), oil (DBO), and precious metals (DBP). Using daily price data from January 2007 to December 2025, we predict daytime returns (open to close) and overnight returns (previous close to open) separately, over five horizons of 1, 5, 30, 60, and 180 trading days. Each model sees a 20-day window of price-based features, returns, rolling averages and volatilities, momentum, and recent lags, built from all six ETFs. All models are trained on a strict chronological split and judged by two simple, decision-oriented measures: how often they call the direction correctly, and the risk-adjusted return (annualized Sharpe ratio) of a stylized long–short strategy that ignores transaction costs. Formal significance tests with HAC corrections for overlapping targets, bootstrap confidence intervals, and comparisons with ARIMA, random forest, and simpler benchmarks corroborate strong predictability in overnight DBP and daytime DBB at medium horizons. Predictability turns out to be highly specific to the asset, the trading session, and the horizon. Overnight returns of the precious metals ETF (DBP) are by far the most predictable: the correct direction is called 71.6% of the time at 60 days and 76.7% at 180 days, with Sharpe ratios reaching about 15. Base metals (DBB) daytime returns are predictable at 30 days and oil (DBO) daytime returns at 180 days, whereas one-day-ahead forecasts and agricultural returns (DBA) stay essentially unpredictable. The Transformer has a slight edge at longer horizons and the GRU at shorter ones. Key directional accuracy and Sharpe ratio results are confirmed by Newey–West HAC significance tests and Diebold–Mariano forecast comparison tests with the Harvey–Leybourne–Newbold small-sample correction; HAC standard errors at the 180-day horizon exceed naïve OLS errors by a factor of approximately 7.4, and we explicitly flag results that do not survive this correction. A three-fold expanding walk-forward validation scheme corroborates the main findings, with DBP overnight and DBO daytime predictability persisting across all evaluation windows. Deep learning architectures statistically and economically outperform logistic regression, ridge regression, and momentum baselines on the most predictable configurations. An anomalous failure of all models on DBA daytime returns at the 180-day horizon is diagnosed as a regime-driven artefact associated with post-2021 commodity inflation, not a general feature of agricultural return dynamics. The broader lesson is that splitting returns into daytime and overnight components exposes predictable structure that conventional close-to-close returns hide. Full article

The growth in the number of half-marathon participants reflects a transformation from performance-centred participation towards sporting experiences of a social and hybrid nature, with a great capacity to generate tourism flows. This study examines the social motivational structure of participants in the Bidasoa Half Marathon and identifies distinct profiles based on their social motivations. In this event, with a strong tourism appeal, 59.15% of respondents reside outside the Bidasoa region, a characteristic already recognised by the organisers, who promote parallel social activities aimed at enhancing the participant experience and encouraging overnight stays. A self-administered questionnaire was distributed to all runners registered for the 2025 edition (N = 1496), yielding 284 valid responses (an 18.98% response rate). The instrument measured three specific dimensions: event inclusivity, face-to-face socialisation, and digital interaction/validation. Exploratory and Confirmatory Factor Analyses validated a robust three-dimensional model explaining 85.04% of the total variance, with adequate reliability and convergent and discriminant validity indices. Inclusivity emerged as the primary motivational driver, followed by digital interaction and physical socialisation. Furthermore, cluster analysis identified three segments: the Inclusive Runner (38.03%), characterised by a high valuation of inclusivity and low digital interest; the Connected Runner (31.34%), with high and balanced scores across the three dimensions and a peak score in digital interaction; and the Autonomous Runner (30.63%), displaying low levels across all social dimensions. Significant associations with age, gender, and educational attainment evidence the inherent heterogeneity of the participants. Consequently, the findings extend traditional models by integrating social and digital dimensions, thereby providing strategic implications for the contemporary management of sporting events. Full article

Exposure to high-altitude hypoxia leads to complex physiological and molecular adaptations, particularly in skeletal muscle. MicroRNAs (miRNAs), including muscle-enriched (myomiRNAs) and hypoxia-responsive (hypoxamiRNAs), play critical roles in regulating these responses. We investigated miRNA expression changes in the skeletal muscle of healthy, non-smoking Italian adults (mean age 36.7 ± 12.4 years) participating in the Himalayan expedition “Lobuche Peak—Pyramid Exploration & Physiology” conducted in the Sagaramāthā (Mount Everest) National Park, Nepal. The peak overnight stay altitude was ≈5000 m at the Pyramid International Laboratory—Observatory. Muscle biopsies were taken before and after the expedition from Vastus lateralis, at one-third of the distance from the upper margin of the rotula to the anterior superior iliac spine. Small RNA sequencing was used to profile differentially expressed miRNAs. Several miRNAs were differentially expressed (exploratory analysis), suggesting potential involvement in hypoxia-related adaptation. These encompass both canonical myomiRNAs (e.g., miR-206, miR-486-5p) and hypoxamiRNAs (e.g., miR-378a-5p, miR-199a-3p, let-7b-5p). In enrichment analysis, we found several connections between miRNAs and pathways that may play a role in physiological regeneration or differentiation in muscle cells. Among functions, focal adhesion (p-value = 0.001), regulation of actin cytoskeleton (p-value = 0.026), Rap-1 (p-value = 0.007), cAMP (p-value = 0.017), MAPK (p-value = 0.019), and Hippo (p-value = <0.001) signaling pathways were predicted to be the most targeted. These findings provide preliminary insights into physiological adaptation, requiring confirmation in larger and controlled cohorts. 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

Background: Esophagectomy is an invasive treatment for esophageal cancer associated with postoperative complications and mortality. Herein, to prevent postoperative complications, early extubation (EE) in the operating room without overnight mechanical ventilation (MV) was introduced. Methods: We compared overnight MV and EE to evaluate the impact on short-term outcomes post-esophagectomy. In total, 91 patients with thoracic esophageal cancer who underwent subtotal esophagectomy were included. In total, 26 patients were extubated in the operating room postoperatively (EE group), and 65 were extubated the following morning (MV group). Propensity score matching was used to assemble a well-balanced cohort. The clinical and postoperative outcomes were investigated; the postoperative fluid balance in the intensive care unit was compared between groups. Results: Propensity score matching produced 21 paired cases from the cohort; the groups were comparable. The EE group had a lower operative time and fluid-in/out balance in the intensive care unit than the MV group. Regarding postoperative outcomes, the EE group had shorter postoperative hospital and intensive care unit stays. In addition, the EE group had significantly fewer incidences of pulmonary complication and surgical site infection. Conclusions: EE was associated with shorter postoperative hospital and intensive care unit stays and reduced incidence of pulmonary complications and surgical site infections by preventing volume overload in the intensive care unit. Full article

This study conducts a meta-analysis to assess the impact of tourism on employment, synthesizing 401 partial correlation coefficients extracted from 39 empirical studies. Employing partial correlation coefficients (PACs) as the effect size measure, the results indicate a modest but statistically significant positive association between tourism and employment, with an average effect size ranging from 0.095 to 0.113. The meta-regression results indicate that the estimated effect varies systematically with the type of tourism indicator, employment definition, use of fixed effects, panel data and macroeconomic controls. Evidence of publication bias and small-study effects is detected, yet robust estimation techniques confirm the presence of a genuine effect. The findings imply that tourism should be considered a complementary and context-dependent instrument for employment policy, with stronger effects associated with tourism intensity measures such as overnight stays and with weaker effects in studies employing more rigorous empirical designs. Full article

Rapid eye movement sleep (REM) is a critical sleep stage associated with several sleep disorders, including sleep apnea and rapid eye movement sleep behavior disorder. Polysomnography (PSG) is the gold standard for identifying REM periods and diagnosing sleep disorders. However, PSG is typically conducted in sleep medicine centers using specialized equipment, where sleep experts assess sleep conditions through measurements such as brain activity, respiration, heart activity, and eye movements. An overnight stay in a sleep laboratory can adversely affect a patient’s natural sleep quality, introducing the risk of iatrogenic sleep disturbances. Recent studies have explored sleep stage detection using lightweight wearable devices, such as smartwatches, which offer lower cost but rely on a limited set of psychological signals. In this study, we propose a machine learning approach for REM sleep staging based solely on breathing rate (BR) and heart rate (HR), without relying on PSG recordings. Experimental evaluations conducted on the Dreamt dataset demonstrate the feasibility of the proposed approach and its potential to provide meaningful information for sleep staging. Future work will focus on developing a fully non-contact REM detection framework by integrating video-based estimation of HR and BR. Full article

The rise in seasonal lifestyle tourism, characterized by winter-escape health and wellness stays and long-term leisure residence, has intensified peak–off-peak imbalances and pressures on the allocation of tourism service supply in tropical island destinations. However, existing research lacks a systematic comparison of seasonal fluctuations and long-term evolution for this subgroup at the city/county level. Therefore, this study aims to characterize the seasonal pattern, long-term trend features, and typological differentiation of seasonal lifestyle tourism at the county level, and to compare differences across types. Using monthly data on seasonal lifestyle tourism for 18 cities/counties in Hainan from 2021 to 2024, we apply TRAMO/SEATS decomposition to identify seasonal structures and measure seasonal amplitude and employ the Hodrick–Prescott (HP) filter to extract trend components and determine their directions of change. We further construct five development types by integrating trend categories and changes in seasonal amplitude and test between-type differences using one-way analysis of variance (ANOVA). Results show that Hainan exhibits a stable “winter–spring peak and summer–autumn trough” pattern (peaks concentrated in January–March and December, with the off-season typically spanning May–October), with strong seasonality and pronounced spatial heterogeneity. The four-year mean seasonal range at the county level is 215.01, with high values clustered in southern Hainan; Haikou remains relatively low, while Wenchang shows an upward trend. Long-term trends are clearly differentiated: 13 counties show sustained growth, 2 show decline, and 3 display a U-shaped recovery (decline followed by rebound). Growth rates also vary substantially, with Qionghai increasing at roughly 27 times the rate of Qiongzhong. Integrating seasonal and trend characteristics yields five types, of which the Robust Development type accounts for the largest share (50%). Between-type differences are mainly reflected in tourism service supply capacity: the number of star-rated hotels (p = 0.033, η² = 0.530) and overnight visitors (p = 0.004, η² = 0.676) differ significantly across types, whereas differences in natural-environment conditions are not significant. This study provides a scientific basis for zoning management and optimizing low-season strategies in Hainan. Full article

Road running tourism events continue to grow worldwide and are increasingly leveraged by destinations seeking diversification and seasonality reduction. This study examines the motivational structure of participants in the 2025 Half Marathon Magaluf (Mallorca, Spain)—a mature Mediterranean resort undergoing tourism repositioning—and analyses how motivation-based segments relate to socio-demographic, sporting and tourism behaviours. Data were collected through a self-administered online survey (N = 306). An Exploratory Factor Analysis (EFA), followed by a Confirmatory Factor Analysis (CFA), validated a five-factor motivational structure: sport-related hedonism, socialisation, personal challenge, inclusiveness and digital interaction. A k-means cluster analysis identified five distinct segments—Digital Enthusiasts, Inclusive Enjoyers, Socializers, Hedonic Achievers and Inclusivists—each exhibiting differentiated patterns in Experience-Use History (EUH), origin, gender, and running-club membership. Notably, Socializers recorded the longest stays, Inclusive Enjoyers were overrepresented among first-time visitors, and Digital Enthusiasts and Hedonic Achievers included a higher share of international runners. These findings expand traditional motivational models by incorporating inclusiveness and digital interaction as emerging drivers and offer actionable recommendations for event organisers and destination managers seeking to enhance overnight stays and support destination repositioning strategies. Full article

Platform-enabled governance is reshaping destination management, yet subnational destinations still lack replicable dashboards that combine key performance indicators (KPIs) with efficiency analysis. This study examines whether a compact KPI stack coupled with longitudinal Data Envelopment Analysis (DEA) can provide actionable targets for destination development management and marketing organizations (DDMMOs). Using 2020–2024 administrative data for five regional units of the Peloponnese, an output-oriented CRS DEA model is specified with one input (room capacity) and two outputs (tourism revenue and overnight stays), complemented by a VRS specification that decomposes Overall Technical Efficiency into Pure Technical and Scale Efficiency. The results show a clear differentiation in trajectories: one regional unit remains consistently on the efficiency frontier, and others exhibit gradual convergence towards best practice, while at least one unit displays persistent underperformance that is driven primarily by scale rather than managerial inefficiency. These distances to frontier are transformed into proportional, output-specific targets and dynamically updated peer sets, which are integrated into a KPI dashboard to support a continuous measure–act–learn loop on pricing, promotion, and capacity allocation. Overall, the article proposes a transparent, reproducible template that links destination competitiveness frameworks with a multi-input, multi-output efficiency lens and embeds KPIs and dynamic DEA insights in a continuous governance loop for destination management. Full article

Rural destinations face a difficult challenge in balancing economic vitality with the environmental and infrastructural pressures, including congestion of car-dependent destinations. Despite growing calls for more sustainable mobility, destination management organisations (DMOs) can assume that private vehicles are vital for rural access, fearing that alternatives such as soft mobility or public transport may have an adverse effect on visitor satisfaction and spending. Yet, empirical evidence to support or challenge these assumptions remains limited. This study addresses this gap by analysing visitor survey data (N = 512) from international and domestic tourists to a rural destination in County Clare, Ireland. Using one-way and two-way ANOVA, along with chi-square and logistic regression analyses, we examine how transport mode relates to visitor satisfaction, daily expenditure, and overnight stay behaviour. Results revealed that visitor satisfaction does not significantly differ across transport modes, suggesting that sustainable mobility options (e.g., walking, cycling, public transport) do not impact the visitor experience. While transport mode had a minimal impact on spending overall, overnight visitors, regardless of how they travelled, spent significantly more than day-trippers (p < 0.001), identifying length of stay as the key economic driver. Moreover, soft mobility users (walking and cycling) had a higher likelihood of staying overnight than car users, while tour bus users were significantly less likely to do so. However, among those who did stay overnight, tour bus users reported the highest daily spending, revealing a complex relationship between mobility type and economic impact. Overall, the results question long-held assumptions linking car use with rural tourism success. Low-impact transport options, such as soft mobility and public transport, were found to sustain visitor satisfaction and spending outcomes comparable to car travel, suggesting their integration could contribute to more balanced, sustainable mobility planning. Full article

Approximately 27.6% of Italian beaches are currently affected by erosion, despite the widespread implementation of coastal defence structures. Around 10,500 installations—mainly groins and detached breakwaters—occupy nearly 24.6% of the national shoreline. Although primarily designed to protect tourist beaches, these hard-engineered structures often degrade coastal landscapes, alter nearshore circulation, and pose risks to swimmers. Nevertheless, beaches remain a fundamental asset for the “3S” (Sun, Sea, Sand) tourism sector, which contributes approximately 2.2% to Italy’s GDP, accounting for over 175 million tourists’ overnight stays in 2024, frequently concentrated near protected coastal zones. In this study, drowning incidents along the Italian coastline were analyzed using press reports complemented by official statistics. Between 2016 and 2021, an average of 145 fatalities occurred per bathing season. Sudden drownings following medical emergencies accounted for 41% of cases, non-swimmers for 18%, accidental falls into the water for 3%, and water sports activities for an additional 3%. Rip currents on natural beaches were responsible for 22% of drownings, whereas those generated by coastal defence structures accounted for 12%. A further 12% of non-swimmer fatalities are suspected to have resulted from falls into depressions or channels formed in proximity to these structures. Evidence from previous studies and seabed morphology analyses indicates that coastal defence structures can generate rip currents through two main mechanisms: (1) hydraulic pressure exerted against groins, which drives offshore flow, and (2) water outflow between pairs of breakwaters resulting from wave setup behind them. Both processes, though often less intense, are also observed near submerged structures. The erosional channels formed by these currents may persist well beyond storm events, maintaining dangerous conditions for bathers. As Italy continues to rely predominantly on hard coastal protection measures, improving the understanding of drowning dynamics associated with these structures is crucial. This should be accompanied by regulatory updates requiring designers and coastal managers to systematically assess related hazards and to propose effective mitigation and safety strategies. Full article

The chorematic method represents an innovative and contemporary approach for organizing tourist space, supporting the sustainable regional development of the future UNESCO Geopark, and guiding research, evaluation, and tourism monitoring activities in the area. This study applies Geographic Information System (GIS) techniques to develop a chorematic model illustrating the influence of county capitals, using Oltenia de sub Munte—an aspiring UNESCO Geopark in Romania—as a case study. The area’s complex geographical characteristics make it an ideal context for demonstrating the capabilities of GIS-based spatial analysis, including the use of the Reilly–Converse gravity model, which posits that a city’s influence increases with its population size and decreases with distance. The theoretical and methodological framework integrates spatial analysis and statistical visualization through the use of thematic maps and diagrams to explore the chorematic model and to assess tourism supply and demand. Accordingly, spatial representations based on chorematic modeling are presented, and the dynamics of tourism demand and supply from 2015 to 2024 are analyzed, focusing on the number of tourist arrivals, overnight stays, and the overall tourism offer within the Oltenia de sub Munte Geopark. Full article