Search Results (54)

This study examines income convergence among EU NUTS-2 regions from 2000 to 2023 using a combination of Phillips-Sul (PS) club convergence methodology, $\beta$-convergence, and spatial econometric models. The results reveal that regional convergence in Europe is heterogeneous and nonlinear: four stable convergence clubs emerge, while overall convergence is rejected. Convergence was faster before 2012 and weakened afterward. A single income threshold and two structural breaks (2005 and 2012) mark shifts in growth dynamics. Spatial models reveal that neighboring regions affect each other’s growth, indicating that regional development in Europe depends on both local conditions and interactions across regions. Full article

In recent years, non-financial reporting has become a central regulatory instrument for integrating environmental considerations into corporate accountability frameworks in the European Union. This study examines regional variation in mandatory environmental disclosures contained in corporate sustainability reports prepared under the Non-Financial Reporting Directive (NFRD) and the Corporate Sustainability Reporting Directive (CSRD). The analysis adopts a regional perspective, assuming that more economically developed regions are associated with greater environmental pressures and therefore exhibit more comprehensive environmental reporting practices. Regions are classified at the NUTS 2 level using GDP per capita in purchasing power standards (PPSs), enabling a systematic comparison between more and less developed regions across the EU. The empirical analysis relies exclusively on publicly available corporate sustainability reports and is deliberately limited to legally mandated environmental disclosures. A structured qualitative content analysis is applied to 20 companies operating across multiple EU Member States, with firms assigned to regions based on the location of their registered headquarters. The results provide exploratory evidence of a positive association between regional economic development (GDP per capita at the NUTS 2 level) and the comprehensiveness of mandatory environmental disclosures. The results provide empirically grounded insights into the strengths and limitations of mandatory sustainability reporting as a governance mechanism and contribute to ongoing debates on the capacity of the CSRD to enhance sustainability-oriented corporate accountability across diverse regional contexts within the EU. Full article

The transformation of the labour market is a significant challenge for sustainable regional development, especially in countries with pronounced socioeconomic inequalities. This study aims to analyse the spatial disparities in the Bulgarian labour market at the regional level (NUTS 3, districts) for the period of 2021–2024, combining descriptive spatial analysis, multidimensional cluster analysis, and Local Indicator of Spatial Association (Local Moran’s I-LISA). The analysis is based on three key indicators: employment rates, unemployment rates, and the relative wage index, calculated against the national average. The results of the descriptive analysis reveal clear spatial imbalances, with low labour income persisting in many districts despite relatively high employment rates. The cluster analysis identifies four types of labour markets with specific socioeconomic profiles, confirming that the spatial disparities are a result of specific combinations of indicators and economic specialisation at the regional level. The LISA analysis further reveals the existence of spatially stable cores of vulnerability and local spatial anomalies that highlight the importance of regional context and spatial proximity. The results indicate the need for a spatially differentiated approach in regional policies in line with the objectives of SDG8, SDG10, the European Pillar of Social Rights, and the EU’s cohesion policy. Full article

Digital transformation is frequently argued to improve how agricultural businesses compete, coordinate, and capture value in markets, yet evidence remains limited of how regional innovation ecosystems shape farms’ digital readiness and how this readiness translates into accounting-relevant outcomes. This study addresses that gap by linking regional innovation capacity, observed farm digital readiness, and accounting performance within a single regional analytical framework. Using cross-sectional data for 180 EU NUTS2 regions (2023), we estimate a moderated mediation model with formative constructs based on harmonized secondary indicators. This study is original in shifting the analysis from the farm or firm level to the regional scale and in operationalizing digital readiness through observable uptake of precision technologies, robotics, livestock-management machinery, internet access, and management information systems. Regional innovation capacity is positively associated with farmers’ digital readiness, and digital readiness is positively associated with accounting performance in the baseline specification. The indirect pathway from innovation capacity to accounting performance via digital readiness is significant, consistent with digital readiness acting as a transmission channel through which ecosystems relate to measurable economic outcomes. Managerial composition conditions these relationships: the share of managers under 40 weakens both the ecosystem-to-digital link and the digital-to-performance link, while female managerial share shows only marginal moderation of the first stage and no significant moderation of the second. The findings provide a basis for future multilevel research and place-based policies and advisory actions aimed at strengthening digital uptake where regional innovation capacity is weaker. Full article

The European Union’s Just Transition Mechanism (JTM) is a public investment instrument aimed at supporting territorially differentiated pathways toward climate neutrality. The study aims to analyse territorial disparities in the implementation of the European Union’s JTM and to interpret these differences through the framework of multi-level public investment management. The study examines key dimensions of implementation, including territorial disparities, differences in instrument uptake, and temporal relationships between commitments and socio-economic outcomes. Methodologically, the research employs a comparative analytical approach based on the analysis of secondary EU data and programme sources. The empirical analysis focuses on NUTS3 transition regions under Territorial Just Transition Plans. The results indicate substantial cross-country variation in the territorial coverage of the mechanism and in the mobilisation of its three financial pillars. The implementation structure remains strongly dominated by grant-based financing, while the uptake of non-grant instruments remains uneven and relatively limited. The analysis also identifies time lags between commitments, payments, and socio-economic indicators. By linking public investment management with sustainability transitions and territorial resilience perspectives, the study contributes to understanding how sustainability objectives are translated into territorially embedded investment practices within the EU. Full article

Background: Food-related reactions can significantly impact children’s dietary choices, health, and nutritional status. This study evaluated adherence to the Mediterranean diet and explored its associations with regional and family socioeconomic status among Croatian children whose parents reported adverse food-related reactions. Methods: The cross-sectional study analyzed data on 193 children aged 2–9 years with parent-reported food-related reactions, collected from the Croatian National Food Consumption Survey, which included 1820 children aged 3 months to 9 years, based on the EU Menu methodology (OC/EFSA/DATA/2016/02 CT3). Parents completed standardized questionnaires on food-related reactions, lifestyle, dietary patterns, and socioeconomic indicators. Regional differences were assessed, and adherence to the Mediterranean diet was evaluated using the KIDMED index. Results: This survey found an 11% prevalence of parent-reported adverse food-related reactions among children aged 2 to 9 years. Milk, eggs, and tree nuts were the most commonly reported allergens. Adherence to the Mediterranean diet was moderate (36%) to low (41%; p = 0.011), with higher KIDMED scores associated with greater fruit, vegetable, legume, fish, and olive oil intake and lower adherence associated with more ultra-processed foods and obesity. Children from coastal and urban areas had better diet quality and socioeconomic indicators. Maternal education was strongly associated with Mediterranean diet adherence (OR = 1.88, p < 0.001), while maternal employment and household income showed no significant relationship. Conclusions: The findings highlight significant nutritional challenges among Croatian children with adverse food-related reactions, driven by regional and socioeconomic disparities. An adherence to a low Mediterranean diet indicates a need for a personalized approach to the diet management of children with food-related reactions. Addressing these through targeted, equitable public health strategies may improve outcomes for affected children. Full article

The European Union (EU) seeks to reduce regional disparities and foster economic growth through substantial financial support to its member states. However, the effectiveness of this support on regional convergence remains ambiguous. This study employs a Systematic Literature Review (SLR) of 33 articles (2012–2024) to evaluate the impact of EU funding on regional convergence and identify gaps in the literature. Findings indicate that convergence effects are often treated as spillovers or conflated with general economic growth. The review highlights the need for more nuanced analyses of specific instruments, such as the European Social Fund (ESF), particularly regarding their effects on unemployment, education, social inclusion, and public services. Research remains concentrated at the NUTS-2 level, neglecting smaller NUTS-3 regions. Future studies should disaggregate fund assessments, incorporate interaction terms between funds and target areas, and focus on specific regional outcomes to better understand the mechanisms driving convergence beyond aggregate spending effects. Full article

Hazelnut (Corylus avellana L.) is a major crop in the Caucasus region, but its safety is often threatened by Aspergillus flavus colonization and aflatoxin contamination. Although aflatoxins (AFs) are strictly regulated in the EU, the influence of post-harvest practices on fungal persistence and AF accumulation remains poorly defined. A three-year study was conducted to evaluate the effects of drying protocols, storage temperature, and conservation practices on fungal growth and AF occurrence in hazelnuts from three producing regions of Azerbaijan. Freshly harvested nuts were subjected to two drying regimes: good drying (sun-exposed, mixed, protected from rewetting) and bad drying (shaded, piled, rewetted). After drying, samples were stored at cold (8–10 °C) or room temperature (18–22 °C). Fungal prevalence was determined by CFU counts with morphological and qPCR identification of Aspergillus section Flavi. AFs were quantified by HPLC, and water activity (a_w) was monitored during storage. Drying emerged as the decisive factor: bad drying consistently resulted in markedly higher fungal loads for A. section Flavi, with mean counts up to 1.3 log10 (CFU/g), compared with 0.8 log10 (CFU/g) under good drying, representing a 7-fold increase. In contrast, storage temperature and shell condition had negligible effects when nuts were properly dried. Aflatoxins were consistently below the 5 µg/kg EU limit for AFB₁ in traced and well-dried samples, whereas market samples occasionally exhibited AFB₁ concentrations >450 µg/kg. These findings highlight drying efficiency as the key determinant of fungal persistence and AF risk in hazelnut post-harvest management. Full article

The beginning of the 21st century is associated with a significant technological leap on a global scale, which has had a substantial impact on production and economic processes at the national and regional levels. This radical technological change in the economy is linked to the emergence and development of artificial intelligence and effective knowledge management, which are the main drivers of economic growth. The use of AI today can be traced in many different areas of applied science—medicine, physics, mathematics, and engineering design, including modeling, planning, and management of territorial systems. The accumulation of large databases and other information necessary for AI to function is directly related to the spatial aspects of economic development, which is also based on local potential (a place-based approach). At the same time, local knowledge resources and innovation potential are not fully utilized in the context of technology diffusion and AI implementation in individual countries and regions. In this regard, this study aims to analyze the role of regional innovation systems, with a focus on AI development, and to track their impact across individual European regions, using NUTS2 spatial-level data to ensure objectivity. The authors consider AI innovation a modern tool for decision-making in the implementation of regional policy, with a specific impact on cohesion between EU regions. The results of the study show a direct link between the localization of regional innovation systems, R & D expenditure, AI implementation, and the economic development of European regions. Important factors influencing this process are the degree of Internet coverage, the capacity to generate innovation, the degree of AI implementation in the individual economic sectors of the countries, the growth of the ICT sector in relation to the overall development of GDP and the economy, and the result of the smart specialisation of regional innovation systems. Full article

The transition to renewable energy is crucial in order to attain sustainable development, lower greenhouse gas emissions, and secure long-term energy security. This study examines spatial–temporal trends in electricity generation (both renewable and non-renewable) across EU-28 countries using monthly Eurostat data (2008–2025) at the NUTS0 level. Two harmonized Space–Time Cubes (STCs) were constructed for renewable and non-renewable electricity covering the fully comparable 2017–2024 interval, while 2008–2016 data were used for descriptive validation, and 2025 data were used for one-step-ahead forecasting. In this paper, the authors present a novel multi-method approach to energy transition dynamics in Europe, integrating forecasting (ESF), hot-spot detection (EHSA), and clustering (TSC) with the help of a new spatial–temporal modeling framework. The methodology is a step forward in the development of methodological literature, since it regards predictive and exploratory GIS analytics as comparative energy transition evaluation. The paper uses Exponential Smoothing Forecast (ESF) and Emerging Hot Spot Analysis (EHSA) in a GIS-based analysis to uncover the dynamics in the region and the possible production pattern. The ESF also reported strong predictive performance in the form of the mean Root Mean Square Errors (RMSE) of renewable and non-renewable electricity generation of 422.5 GWh and 438.8 GWh, respectively. Of the EU-28 countries, seasonality was statistically significant in 78.6 per cent of locations that relied on hydropower, and 35.7 per cent of locations exhibited structural outliers associated with energy-transition asymmetries. EHSA identified short-lived localized spikes in renewable electricity production in a few Western and Northern European countries: Portugal, Spain, France, Denmark, and Sweden, termed as sporadic renewable hot spots. There were no cases of persistent or increase-based hot spots in any country; therefore, renewable growth is temporally and spatially inhomogeneous in the EU-28. In the case of non-renewable sources, a hot spot was evident in France, with an intermittent hot spot in Spain and sporadic increases over time, but otherwise, there was no statistically significant activity of hot or cold spots in the rest of Europe, indicating structural stagnation in the generation of fossil-based electricity. Time Series Clustering (TSC) determined 10 temporal clusters in the generation of renewable and non-renewable electricity. All renewable clusters were statistically significantly increasing (p < 0.001), with the most substantial increase in Cluster 4 (statistic = 9.95), observed in Poland, Finland, Portugal, and the Netherlands, indicating a transregional phase acceleration of renewable electricity production in northern, western, and eastern Europe. Conversely, all non-renewable clusters showed declining trends (p < 0.001), with Cluster 5 (statistic = −8.58) showing a concerted reduction in the use of fossil-based electricity, in line with EU decarbonization policies. The results contribute to an improved understanding of the spatial dynamics of the European energy transition and its potential to support energy security, reduce fossil fuel dependency, and foster balanced regional development. These insights are crucial to harmonize policy measures with the objectives of the European Green Deal and the United Nations Sustainable Development Goals (especially Goals 7, 11, and 13). Full article

Intersectoral labour mobility is a key driver of economic resilience and innovation in Europe. The redistribution of workers across sectors and regions enables economies to adapt to shocks, create flexibility and increase the rate of structural change. However, the dynamics of mobility have not been adequately investigated across varying scales of sectoral granularity and spatio-temporal dimensions. This paper applies the Intersectoral Mobility Index (MI) to all European NUTS-2 areas from 2008 to 2020, utilising Eurostat Structural Business Statistics. Two levels of sectoral aggregation (NACE Rev. 2, 1-digit and 2-digit) are employed to compute MI, capturing both broad and fine-grained reallocations. Classical indices of structural change (NAV, Krugman, Shorrocks) are combined with spatio-temporal modelling in ArcGIS Pro, employing Space–Time Cubes, time-series exponential smoothing forecasts, time-series clustering and emerging hot spot analysis. Results indicate that MI distributions are positively skewed and heavy-tailed, with peaks coinciding with systemic crises (2009–2011, 2020). At the 2-digit level, MI values are significantly higher, revealing intra-sectoral changes obscured in aggregated data. A statistically significant downward trend in mobility suggests an increasing structural rigidity following the global financial crisis. Regional clustering highlights heterogeneity: a small number of regions, such as Bremen, Madeira and the Southern Great Plain, have sustained high or unstable mobility, while most exhibit convergent mobility and low reallocation. This paper contributes to the conceptualisation of MI as a dual measure of resilience and innovation preparedness. It underscores the importance of multi-scalar and spatio-temporal methods in monitoring labour market flexibility. The findings have policy implications, including the design of targeted reskilling programmes, proactive labour market policies and just transition plans to maintain regional resilience during the EU’s green and digital transitions. Full article

Understanding the directionality of the relationship between artificial light at night (ALAN) and economic activity is crucial for evidence-based policymaking aimed at accelerating and sustaining development. In particular, this knowledge may help to ensure that ALAN does not serve just a proxy for economic activity, when information is unavailable, but may also become a meaningful development indicator on its own. However, the question remains about the directionality of the GDP–ALAN relationship: Does an increase in GDP simply leads to more nighttime light emissions, while the reverse link is negligible, or is this relationship two-directional, with ALAN affecting economic development as well. The present study attempts to answer this question by applying the Granger directionality test to time series panel data available for 1300+ EU NUTS-3 regions over the period of 2001–2021. The study aims to determine the directionality of the relationship between GDP and ALAN in European NUTS-3 regions, distinguishing between Western and Eastern Europe and between different measurement eras (DMSP-OLS vs. VIIRS). The analysis reveals a complex and bidirectional relationship that varies in strength. In particular, for the years 2001–2013, the analysis showed that GDP led to more ALAN emissions, while the reverse link was much weaker and negative. However, after 2013, this relationship has become unidirectional, with GDP continuing to lead to more ALAN emissions, but not vice versa. These findings highlight the importance of considering long-term trends when interpreting ALAN emissions as an indicator of economic development, which is widely used in empirical studies at present. Full article

This paper investigates the impact of demographic changes on regional disparities within the European Union. The analysis focuses on key demographic trends—population ageing, low fertility rates, and migration flows—and their long-term implications for labor markets, economic growth, and the sustainability of social systems across EU regions. Using Eurostat data for 169 NUTS2 regions for 2022 and 2023, the study applies descriptive statistics, correlation analysis, and multiple regression models to quantify the effects of life expectancy, fertility rates, and educational attainment on GDP growth and employment in knowledge-intensive and high-tech sectors. Findings indicate that regions with higher shares of highly educated labor and favorable demographic profiles tend to achieve greater economic resilience and competitiveness. In contrast, demographic decline and outmigration continue to deepen structural disparities, particularly in rural and less developed regions. The results underscore the importance of integrated EU policies aimed at addressing demographic challenges while promoting regional cohesion through investment in human capital, innovation, and infrastructure. By highlighting the critical role of demographic factors in shaping regional development, this study contributes to the discourse on designing effective policies to foster sustainable and inclusive growth within the European Union. Full article

Understanding the entrepreneurial profile is essential for developing effective regional policies that promote business growth. The path of an entrepreneur is shaped not only by individual decisions but also by the inherent risks of managing a business. This study aims to identify the characteristics of entrepreneurs at the regional level, specifically highlighting the impact of accumulated experience in their fields. Our central hypothesis asserts that entrepreneurial experience significantly influences how business owners perceive and respond to economic challenges. Utilizing survey data from 120 entrepreneurs in Romania’s Center Region (a NUTS 2 area), we reveal that entrepreneurial experience profoundly affects perceptions of key business challenges, such as legislative instability, taxation predictability, governmental support strategies, and access to SME financing. Importantly, our findings demonstrate that entrepreneurs with less than 10 years of experience express greater concerns about these challenges compared to their more seasoned peers. This novel insight highlights the need for tailored policy interventions aimed at enhancing regional economic resilience and fostering entrepreneurial sustainability. By addressing the specific needs of less experienced entrepreneurs, our study contributes to a deeper understanding of how experience shapes business dynamics in the region. Full article

This study investigates the role of innovation in shaping economic growth across the heterogeneous landscape of the European Union (EU). Through a detailed analysis at the NUTS-3 level, it identifies regions characterized by sustained and above-average growth, thereby providing new insights into the mechanisms through which innovation contributes to regional economic resilience and long-term prosperity. Our methodology employs panel data from the EU27 Member States and the United Kingdom (UK), spanning the period from 2002 to 2022, allowing a more comprehensive understanding of the determinants of regional growth, including Gross Value Added (GVA) across various industries, the unemployment rate, and inflation. Furthermore, the role of innovation as a pivotal force driving economic progress is underscored. The analysis reveals significant differentiation within the cluster, supporting the assumption that innovation plays a crucial role in driving robust and, most notably, sustainable economic growth in a region. The findings further highlight that regions with an industry structure closely resembling the sample average are significantly influenced by innovation. From this, it can be deduced that innovation is a key driver of sustainable growth, especially in regions with the necessary infrastructure, skilled labour, and industry diversification to effectively harness innovative activities. Full article