Roberta Barbieri (p), Benedetta Coluccia, Francesco Natale, Donatella Porrini

Persefoni Polychronidou

Government digitalization plays a crucial role in enhancing governance efficiency and facilitating public administration innovation. However, the uneven adoption of digital technologies across regions poses significant challenges, exacerbating economic and social inequalities. At the European level, cohesion policy serves as a fundamental tool for reducing territorial disparities by allocating financial resources to support regional development. Despite substantial EU funding efforts, regional gaps persist, raising questions about the effectiveness of fund distribution. While previous studies have examined the economic impact of EU cohesion policy, limited attention has been paid to the role of digitalization in shaping regional access to European funding. This study addresses this gap by investigating the extent to which government digitalization, in combination with institutional factors, influences the capacity of Italian regions to attract EU financial resources. A quantitative econometric approach is applied to analyze the distribution of EU funds across 20 Italian administrative regions during the 2014-2020 programming period. The analysis focuses on three key funding instruments: the Cohesion Fund (CF), the European Regional Development Fund (ERDF), and the European Social Fund (ESF). A Weighted Least Squares (WLS) model is employed to assess the impact of digitalization (digital infrastructure, literacy, and use) and institutional quality (governance index, corruption, GDP per capita, and inequality) on the amount of EU funds received. Preliminary findings indicate that both digitalization and institutional quality significantly affect regional fund absorption. Regions with advanced digital infrastructure, higher digital competence, and greater digital adoption secure more EU funds, suggesting that strong e-government systems enhance administrative efficiency and fund accessibility. Additionally, well-governed regions with lower corruption levels and better economic conditions attract higher allocations. Conversely, digitally lagging and weakly governed regions struggle to optimize funding opportunities, highlighting the risk of a widening digital divide.

Konstadina Kasabali, Persefoni Polychronidou (p)

Tuba Bircan

This paper explores the factors influencing the development of e-government in Greece, drawing insights from existing research on socio-demographic characteristics, economic growth, and technological advancements. E-government, which leverages internet technologies to enhance public administration and citizen engagement, varies significantly in adoption across different regions. By examining socio-demographic factors such as urban population, education levels, and age, as well as economic indicators like GDP growth and e-commerce development, this study aims to identify key determinants of e-government progress in Greece. Utilizing a regression model the research assesses data from various sources, to provide a comprehensive understanding of how information and computer technology, human capital, and economic conditions impact e-government development. The findings highlight the importance of these factors in shaping the effectiveness and reach of e-government initiatives, offering valuable insights for policymakers and stakeholders in Greece.

Tuba Bircan (p)

Roberta Barbieri

Artificial intelligence (AI) is increasingly integrated into public governance, influencing economic decision-making, urban planning, and public service delivery. While AI-driven policies promise enhanced efficiency, they also risk exacerbating regional inequalities due to disparities in digital infrastructure, institutional capacity, and AI investment. Some regions, particularly those with strong innovation ecosystems and advanced digital infrastructure, are better positioned to leverage AI for economic growth, while others may struggle to adopt AI-driven governance. This study examines whether AI governance fosters regional convergence or deepens territorial disparities, analyzing its spatial effects on economic inequalities across Europe.

Drawing on publicly available data from OECD, Eurostat, DESI, and the European Innovation Scoreboard, I construct a Regional AI Policy Index to assess the adoption and impact of AI-related governance strategies at the NUTS-2 level. The study employs a spatial analytical framework to detect patterns of regional AI adoption, assess policy spillovers, and examine the extent to which AI governance influences economic performance. This approach allows us to move beyond national-level comparisons and capture the uneven territorial dynamics of AI-driven policies.

I hypothesise that AI governance reinforces existing regional disparities, as wealthier regions with stronger digital infrastructure and institutional capacity attract more AI-related investment, widening the gap with less developed regions. By applying spatial econometric techniques, I identify whether AI-driven policies cluster in high-performing regions and assess whether they generate positive or negative externalities for neighbouring areas. This spatial perspective is crucial for understanding AI’s role in shaping regional economic trajectories and informing policy interventions that promote inclusive digital transformation.

Our findings contribute to the growing debate on AI’s impact on regional inequalities, offering empirical insights into how AI adoption in governance interacts with existing economic and spatial structures. The study also provides evidence-based recommendations for designing AI policies that ensure equitable digital development across regions. Addressing these disparities is essential to prevent further territorial polarisation and to leverage AI as a tool for regional cohesion rather than division.

This study advances the understanding of AI’s territorial effects and highlights the need for differentiated policy strategies that consider the uneven distribution of AI capabilities across regions, by integrating economic geography, digital governance, and spatial policy analysis. The findings are relevant for policymakers, researchers, and stakeholders aiming to foster a more balanced and inclusive AI-driven transition.