Esmira Ahmadova

Type of the article: Research Article

Abstract
This study examines the association between multidimensional digital transformation and national startup ecosystem performance across 23 European Union economies, comparing EU11 with 12 selected EU15 economies from 2017 to 2024. The balanced panel contains 184 country-year observations. Principal component analysis is used to construct three composite indicators: the Digital Services Index, Digital Connectivity Index, and Digital Human Capital Index. The indices demonstrate satisfactory factorial adequacy, internal consistency, and one-component structures supported by parallel analysis. Their associations with startup ecosystem performance are estimated using two-way fixed-effects models. Because the panel contains only 23 country clusters, the principal inference uses CR2 bias-reduced country-clustered standard errors with Satterthwaite-adjusted degrees of freedom. In the full-sample specification, DSI has a positive but only marginally significant association with startup ecosystem performance (β = 0.0834, p = 0.082), while DCI, DHCI, and e-government are statistically insignificant. R&D intensity has a negative contemporaneous coefficient that is also marginally significant (β = −0.0145, p = 0.053). Regional heterogeneity is jointly significant and is concentrated primarily in digital connectivity: DCI is negatively associated with startup ecosystem performance in the EU11 group, whereas its total slope is approximately zero in the selected EU15 group. DHCI has a positive total slope within the selected EU15 group, although the difference between the EU15 and EU11 slopes is not statistically significant. A one-year-lagged specification produces a positive but marginal DSI coefficient and does not identify statistically significant associations for the remaining predictors. These estimates should be interpreted as conditional associations rather than causal effects.

Type of the article: Research Article

Abstract
The digital transformation of banking is entering a new phase, shifting from mobile applications toward AI-driven, personalized services, yet the readiness of national environments for this shift remains largely unexamined. The study aims to assess the cross-country readiness of banking systems for this shift by integrating demand-side digital financial inclusion with supply-side government AI readiness in a single composite measure. To this end, an AI-Banking Readiness Index (ABRI) is constructed by two-stage principal-component analysis from the World Bank Global Findex (2011–2024) and the Oxford Insights Government AI Readiness Index 2025 for 97 economies; it is complemented by k-means clustering, a demand–supply positioning matrix, and cross-sectional and two-way fixed-effects panel regressions. Three findings follow. First, at the index level, the two sides of readiness are only moderately aligned (r = 0.655), and 28 of the 97 economies lead on one side only – a mismatch that supply-only rankings conceal. Second, across countries, government AI readiness is positively associated with deeper household digital-finance adoption once income is controlled (β = 0.451, p = 0.017). Third, within countries over time, e-government capacity is related to account ownership in a pattern consistent with an infrastructure-mediated channel; this constitutes suggestive channel evidence rather than a formal mediation test. Practically, the index locates each economy’s binding constraint: supply-led economies need demand-side activation through connectivity, interoperable payments, and digital literacy, whereas demand-led economies need AI governance and supervisory capacity before personalized, AI-driven services can scale safely.

Acknowledgment
This article was prepared based on the results of a study funded by the Ministry of Education and Science of Ukraine entitled “GovTech for Ukraine: A Digital, Secure, Transparent, and Equitable State in Times of War and Post-War Reconstruction” (registration number: 0126U000544)