Search Results (478)

This study examines the association between tourism intensity, the free movement of people, and water quality outcomes across the European Union (EU-27) over the period 2012–2024. By integrating open-access datasets from Eurostat, the European Environment Agency (EEA), and the EXIOBASE input–output framework, the analysis estimates the direct (blue), indirect, and grey components of the tourism-related water footprint and explores their relationship with bathing water quality indicators using panel econometric models. The results indicate that tourism activity increased substantially during the study period, while the share of bathing waters classified as “excellent” also improved. The findings further show that the gray water footprint is strongly associated with variations in water quality, whereas higher wastewater treatment coverage is positively associated with improved environmental outcomes. These results highlight the importance of wastewater management and governance capacity in moderating the relationship between tourism and water quality across diverse European contexts. We find that tourism activity rose by approximately 28% during the study period; yet, through improvements in wastewater treatment infrastructure and governance, the share of bathing waters rated “excellent” also increased. Notably, the grey water footprint emerged as the strongest predictor of water quality deterioration, while wastewater treatment coverage significantly mitigated negative impacts. Comparative case studies of Spain, Greece, Croatia and Romania highlight how institutional and technological capacity are associated with differences in tourism–water relationships across diverse hydro-climatic contexts. Our findings underscore that sustainable tourism in Europe is less a matter of visitor numbers and more a question of effective water management systems. The study supports a policy shift towards integrated water-tourism planning and circular water-use strategies to support more sustainable management of tourism-related environmental pressures. Full article

Despite relatively low per capita rice consumption in the European Union (EU), averaging approximately 9 kg annually between 2010 and 2023, imports from Asian countries have shown a sustained upward trend since 2013. This study assessed hazards associated with rice available on the EU market. Data were obtained from Faostat, Eurostat, the Rapid Alert System for Food and Feed (RASFF), and the Web of Science. Pivot tables and a two-way joining cluster analysis were applied to examine temporal and geographical patterns in reported notifications. Notifications primarily concerned genetically modified rice (32%), pesticide residues (21%), and mycotoxins (17%). During 2006–2014, notifications mainly related to unauthorized genetic modifications in rice originating from China and the United States, whereas between 2017 and 2023, they predominantly involved excessive pesticide residues and mycotoxin contamination in rice from India and Pakistan. Most hazards were classified as border rejections (37%), reflecting the effectiveness and vigilance of EU food safety authorities. While rice is generally considered low risk for European consumers, rising cultural integration and the growing popularity of Asian cuisine may increase consumption in the future. Continuous monitoring, rigorous risk assessment, and collaboration with exporting countries are therefore essential to maintain high food safety standards and ensure consumer protection across the EU market. Full article

Monitoring progress toward Sustainable Development Goal 8 (SDG 8) requires analytical tools that enable flexible and transparent assessment of multiple indicators. However, existing monitoring approaches are usually based on predefined indicator sets and static analytical frameworks, which limit their adaptability. This study develops and demonstrates a computer-assisted system for monitoring SDG 8 achievement. The system integrates automatic data retrieval from Eurostat, flexible selection of indicators, countries, and years, procedures for handling missing data, and alternative options for constructing a synthetic index. The system was tested in an illustrative case study for European Union countries using Eurostat data for 2015–2023. The empirical application initially covered 19 indicators (11 core SDG 8 indicators and 8 supplementary indicators) for 27 EU countries, while the final analytical sample included 24 countries after data-based exclusions. The results showed substantial differences in SDG 8 achievement trajectories across countries: some countries maintained relatively stable high positions over time (e.g., Italy, Estonia, Germany, and Austria), whereas others recorded marked improvement (e.g., Ireland, Denmark, Cyprus, Lithuania, and Latvia). These findings confirm the practical usefulness of the proposed tool for data processing, comparative assessment, and evidence-informed monitoring of SDG 8 progress. Full article

This study aimed to estimate life expectancy at birth and survival patterns within a multigenerational family from Romania (102 individuals), whose members lived across the period 1900–2024. Life expectancy was estimated using abridged synthetic cohort life tables, and the results were interpreted through survival curve analysis. Life expectancy at birth was estimated at approximately 84 years for females and 80 years for males, while the overall life expectancy for the total family population was 81 years, representing a weighted estimate derived from sex-specific life tables, with weights corresponding to the proportion of females and males in the studied population, rather than a simple arithmetic mean, following standard demographic practice. The resulting survival curves exhibited a clear Type I survival pattern, characterized by low mortality at younger ages and an increasing concentration of deaths at older ages. When contextualized using recent Eurostat data, the life expectancy estimated for the analyzed family exceeds current national-level values reported for Romania and is close to the European Union average, particularly for females. These findings indicate a favorable survival profile at the familial level and illustrate the usefulness of life tables for investigating longevity patterns in small populations. Full article

In recent years, the escalation of international and internal conflicts in the Middle East and North Africa and Bulgaria’s geographical location, which places it on the route of those seeking protection from these regions in Europe, has led to a significant increase in the number of refugee children arriving in Bulgaria. According to Eurostat data, Bulgaria ranks fourth in terms of the number of unaccompanied refugee children in the European Union. In this article, the possibilities for achieving the welfare of refugee children and their successful integration into society are considered as a result of the intersection of two main trends—state legislation and public policies aimed at guaranteeing the best interests of refugee children, and public opinion about refugee children, which, in some cases, cause the failure of positive state measures and policies. The data on public attitudes towards refugee children used here are the result of an empirical study conducted in 2021 by the authors of this article. The results show that while state legislation and public policies are evolving towards ensuring the best interests of the child, the same cannot be said for public attitudes and the distance that the local population demonstrates towards refugee children. Full article

Growth in the elderly population will inevitably increase the demand for care and assistance, which must be matched by a sufficient number of individuals capable of providing the care and assistance required. This study aims to estimate the present and future caregiver support ratio (CSR) at the national level across Europe and at the Italian subnational level. Italy was selected due to its higher proportion of elderly citizens compared with other EU countries. The CSR is defined as the number of potential caregivers aged 45–64 years (the age range most commonly involved in caregiving) per citizen aged 80 and over (the most likely to require long-term caregiving). Data were obtained from Eurostat for the EU-level analysis, whereas those pertaining to Italy were sourced from the Italian National Institute of Statistics. CSR projections were made for the decades spanning 2030 to 2080. The findings show that the ratio of potential caregivers aged 45–64 to individuals aged 80 or over will steadily decline over the coming decades, implicating challenges for gerontological social policies. The results reveal variation in the CSR for the 27 European countries—with a decline from 5:1 in 2025 to 2:1 by 2050—and across the 20 Italian regions, as well as differences in the projected trends in CSR variations over the medium (until 2050) and long term (until 2080). Technology may offer possible solutions to address some of the challenges associated with the aging demographic. Full article

This paper examines whether broad enterprise AI adoption in Europe is best understood as an isolated technology decision or as the outcome of a wider bundle of digital capabilities. Using harmonized Eurostat data for European enterprises, the analysis builds a repeated cross-section at the country–size-class–year level and models high AI adoption with a combination of random forest and elastic-net estimation. The dependent variable captures enterprises using at least one AI technology, while the explanatory set focuses on cloud adoption, cloud CRM, cloud ERP, cloud database hosting, cloud security, cloud software use, e-sales intensity, and enterprise size. The findings reveal a stable predictive structure and consistent classification performance across specifications. Across models, cloud CRM and e-sales emerge as the strongest predictors of high AI adoption, followed by general cloud use and selected data-related cloud capabilities. This ordering remains largely stable in threshold-sensitivity checks based on alternative definitions of high adoption. The pattern also remains visible when country controls are removed, which suggests that the result is not merely a reflection of national heterogeneity. The paper contributes by shifting attention from broad claims about “digital readiness” to a narrower and more operational notion of capability complementarity: AI uptake tends to cluster where firms already possess customer-facing, cloud-based, and commercially digital infrastructures. In that sense, the paper offers a transparent, reproducible, and policy-relevant account of the digital foundations of enterprise AI adoption in Europe. Full article

Poland ranks among the world’s leading exporters of goose meat and edible offal, yet domestic consumption remains minimal, revealing a structural imbalance between production and internal demand. This study aims to provide a comprehensive economic assessment of Poland’s foreign trade in goose meat and offal during 2020–2024, examining export specialization, price dynamics, and market resilience. Using official data from the Central Statistical Office (GUS), Eurostat, UN Comtrade, and the National Bank of Poland (NBP), trade flows were disaggregated by CN product codes, destination countries, and unit prices to identify key structural patterns. Results indicate that export volumes remained largely limited by price responsiveness despite sharp price increases and exchange rate fluctuations, confirming stable foreign demand. Exports were heavily concentrated in Germany, which absorbed over 70% of the total trade value, while domestic consumption stayed below 0.5 kg per capita annually. These findings demonstrate both the competitiveness and the fragility of Poland’s export-oriented trade model, characterized by dependence on a single market and limited domestic integration. The study concludes that long-term food system resilience requires diversification of export destinations, stimulation of domestic demand, and stronger alignment with sustainability goals. A forthcoming second part will address environmental impacts and consumer awareness. Full article

Dynamic economic growth and climate change increase pressure on water resources, posing a challenge to achieving sustainable development goals, especially in regions with diverse hydrological conditions and development trajectories. This study aims to quantitatively assess the dynamic asymmetry between water management efficiency and the level of sustainable development in the European Union and the Three Seas Initiative (3SI) countries, with particular emphasis on cumulative mechanisms, regional divergence, and the potential low equilibrium trap. The values of the analysed indicators were calculated for 2015, 2021, and 2022, and subsequently their changes were determined for 2021/2015 and 2022/2021. This study was conducted using Eurostat data, applying the CRITIC method for objective weight determination, the TOPSIS technique for constructing synthetic measures, the Kruskal–Wallis and Mann–Whitney tests to assess inter-group differences, and linear regression to identify dependencies. Countries were grouped according to the dynamics of changes in the synthetic water management index. The results indicate a clear asymmetry: the water sector is characterised by a cumulative mechanism and strong divergence (particularly evident in the short period), whereas sustainable development remains significantly more stable, homogeneous, and weakly linearly correlated with previous water achievements. In 3SI countries, a higher rate of improvement in water indicators was observed compared to the rest of the EU; however, no significant synergy with progress in sustainable development was found. The negative impact of the Water Exploitation Index on sustainable development is statistically noticeable but does not confirm the existence of a clear “low equilibrium trap” across the entire 3SI region. This study highlights the need for regionally differentiated, asymmetrical water policies and the integration of water management with broader ecological transformation strategies. Full article

The main purpose of the research is to rank EU member states by the intensity of their efforts to implement the CE model. Understanding EU member states’ differences is crucial to formulating effective policy measures that foster sustainable development and enhance economic resilience across the EU. The degree of CE development was examined through three sub-indicators: (i) private investment related to CE sectors; (ii) persons employed in CE sectors; and (iii) gross value added as a percentage of GDP. Data from the Eurostat database for the last five available years were used. Hierarchical agglomerative cluster analysis is used to identify groups of structurally similar countries. Countries are ranked using the PROMETHEE II multi-criteria decision-making method with objectively derived CRITIC weights, complemented by GAIA visualisation. The analysis identifies five distinct clusters with a highly heterogeneous CE landscape across the EU. The PROMETHEE-GAIA research results reveal two different paths on which European countries are moving towards CE. The first, characterized by high structural maturity but limited dynamic flexibility, is evident in Sweden and Belgium. And the second path, illustrated by Estonia and Croatia, is distinguished by a rapid pace of transformation and lower historical structural capacities. Full article

Background: This study examines long-term trends in intra-EU trade among the Visegrad Group (V4) countries from 2004 to 2023, focusing on changes in export specialisation and comparative advantages in the context of trade resilience and sustainability. Methods: Trade performance is analysed at both the aggregate level and across SITC product groups, using Eurostat data. The analysis applies export and import dynamics, trade balance, export–import coverage ratio, trade balance index, and the symmetric revealed comparative advantage index. Results: The findings show significant heterogeneity in specialisation and competitiveness across the V4 countries. Poland reveals competitive advantages and trade stability in agri-food products. After European Union (EU) accession, comparative advantages and export specialisation emerged mainly in manufacturing and selected medium- and high-processed goods (SITC6–8), especially in Czechia and Hungary, and increasingly in Poland. Poland and Czechia shifted most clearly towards higher value-added products, Hungary followed a mixed pattern, while Slovakia remained narrowly focused on the automotive sector. Export competitiveness is closely linked to the business cycle, with upturns strengthening advantages and downturns causing only temporary weakening. Conclusions: The V4 intra-EU trade exhibits structural resilience, as key competitive positions persist and recover after economic shocks. Only Slovakia’s highly concentrated specialisation may entail risks for sustainable growth. Full article

The transition from a linear to a circular economy has intensified interest in environmentally friendly business models and policy instruments that support sustainable production and consumption. While prior research has largely examined green labels at the micro level, focusing on consumer perceptions and purchase intentions, limited evidence exists on their macro-level role in circular economic performance. This study tests the hypothesis that higher EU Ecolabel diffusion is positively associated with circular material use rates (CMUR) across European Union Member States over the period 2010–2024. This study does not directly measure business models but examines macro-level indicators associated with their development. Using panel data from Eurostat and the European Commission’s EU Ecolabel catalogue, ecolabel intensity is operationalized as the logarithm of total licenses per country. Pooled OLS models with year fixed effects and country-clustered standard errors are estimated, first in baseline specification and then with controls for GDP per capita, environmental tax revenues, manufacturing value added, and R&D intensity. Results reveal a positive and statistically significant relationship between ecolabel intensity and circular material use rates, remaining robust after including macroeconomic controls. These findings suggest that green labeling is associated with circular economy performance and may reflect an institutional dimension aligned with circular economy governance. The results are also consistent with patterns associated with environmentally friendly business models at the macro level. This study contributes by providing a macro-level, cross-country analysis of the relationship between EU Ecolabel diffusion and circular economy performance, incorporating key structural controls. Full article

Background/Objectives: Avoidable mortality—deaths before age 75 from preventable or treatable causes—is a key indicator of health system performance. In Mexico, nearly two-thirds of municipalities lack hospital beds, yet no study has examined the municipal-level association between healthcare infrastructure and avoidable mortality. This study assessed whether healthcare desert status is independently associated with avoidable mortality after adjusting for social deprivation. Methods: This ecological study analyzed 1891 Mexican municipalities (population ≥ 1000) over 2015–2024. Avoidable deaths were classified per OECD/Eurostat criteria (January 2022 revision). Healthcare desert status was defined by municipal hospital bed availability from 2019 facility data. Negative binomial mixed-effects regression estimated incidence-rate ratios (IRRs) adjusted for social deprivation, age structure, and state-level heterogeneity. Interrupted time-series analysis quantified pandemic disruption. Results: Of 4,960,244 deaths under 75 years, 81.2% were avoidable. Of 1891 municipalities, 1187 (62.8%) lacked hospital beds (healthcare deserts). Desert municipalities had 42.5% higher avoidable mortality (IRR = 1.425; 95% CI: 1.370–1.482; pre-pandemic 2015–2019), which attenuated to 1.353 after age-structure adjustment. Each standard-deviation increase in hospital beds (1 SD ≈ 2.2 beds per 1000) was associated with 7.9% lower mortality (IRR = 0.921). Avoidable mortality exhibited strong spatial clustering (Moran’s I = 0.382) in southern Mexico. By 2024, the desert–adequate mortality gap had widened by approximately five fold (from $\sim$12 to 69 per 100,000 population). Conclusions: Healthcare deserts are independently associated with substantially higher avoidable mortality in Mexico. The COVID-19 pandemic durably amplified pre-existing disparities associated with healthcare infrastructure deficits. Targeted hospital expansion in underserved municipalities is urgently needed, alongside investment in social determinants of health. Full article

Digital transformation reshapes firms into more digital, data-driven, and customer-centric organizations. Because it often supports innovation, firms are widely expected to benefit from higher performance and productivity. However, it remains unclear whether higher national levels of digital integration translate into higher aggregate enterprise productivity. This study adopts a socio-technical and ecosystem perspective to examine the relationship between digital technology integration and enterprise labor productivity across the 27 EU member states, while also considering the role of key ecosystem enablers. A balanced country-year panel of data (N = 162) was constructed from Eurostat Structural Business Statistics on the apparent labor productivity of total enterprises, together with Digital Economy and Society Index (DESI) indicators on the integration of digital technology, human capital, connectivity, and Gross Domestic Product (GDP) per capita, covering the period from 2017 to 2022. To this end, fixed-effects regression models were estimated using robust standard errors clustered by country and combined with correlated random effects (CRE/Mundlak) decomposition. This methodological approach was adopted to distinguish short-run within-country dynamics from persistent between-country differences. The study contributes to ecosystem-level DESI research by using this distinction to assess how country-level digital integration is associated with enterprise productivity. The fixed-effects results provide no evidence that year-to-year changes in digital technology integration, on their own, are associated with higher enterprise productivity. Additionally, no statistically significant interaction effect was observed with either human capital or digital connectivity. By contrast, GDP per capita was found to be a robust positive predictor of enterprise productivity. The CRE/Mundlak results indicate that the majority of between-country productivity differences are attributable to differences in economic development. Furthermore, there is evidence of a positive association between the average level of digital technology integration and human capital. Taken together, these findings suggest that national digital technology integration reflects business environment conditions at the ecosystem level. While it may create opportunities for enterprise business model innovation, its productivity implications are more likely to emerge gradually through stronger absorptive capacity and complementary capabilities. Consequently, the study suggests that enterprise digital transformation policies should be aligned with investments in digital skills and broadband infrastructure. These policies should also support process redesign, greater interoperability, and the implementation of AI-enabled technologies. Full article

The rapid transition to Industry 4.0/5.0 has widened the gap between graduates’ skill sets and labor market expectations; this study aimed to profile student competencies and align academic pathways with inclusive and adaptive AI-driven learning. A quantitative design was applied: an online survey of n = 126 students (engineering and economics, February–March 2025), expert evaluations from 5 faculty and 5 employers on a 5-point scale, framed by T-shaped competencies, 4C skills, and Bloom’s taxonomy. Analysis was performed in Python 3.11; future demand until 2035 was forecasted using ARIMA and Prophet models trained on publicly available labor market data (OECD, WEF, Eurostat 2015–2024); competency prioritization employed K-Means clustering and Random Forest models. Strengths included cooperation 4.2, critical thinking 3.9, communication 3.8, and creativity 3.6. Deficits were programming 2.8, project management 3.2, and solution development 3.2; employers rated programming at 2.5 (−0.7 compared to faculty). Forecast 2025–2035 showed growth in demand for programming +56% (3.2 → 5.0), data analytics +39% (3.6 → 5.0), project management +34% (3.2 → 4.3), digital literacy +30% (3.7 → 4.8), and critical thinking +15% (3.9 → 4.5). Clustering identified critical (programming, analytics, project management), supporting (creativity, communication, teamwork), and optional (narrow theoretical depth) competencies. Curriculum adjustment with practice-oriented modules, AI-enabled adaptive learning, and systematic university–employer feedback is essential; the proposed AI-supported profiling model is scalable and enhances inclusiveness. Full article