Olena Pakhnenko

Type of the article: Research Article

Abstract
Digital technologies have become a key driver of economic growth, competitiveness, and social inclusion, while significant disparities in digital development persist across national economies. The aim of this study is to map and interpret the trajectories of digital transformation in 30 selected European countries (EU member states, associated economies, and Ukraine) during 2011–2022. The study employs the self-organizing map (SOM) with Ward hierarchical clustering to uncover latent structures of digital development, using a balanced panel of 20 indicators across three domains: ICT sector development, digital infrastructure, and digital technology adoption and skills. Cluster validity was assessed via the Elbow Method, Silhouette Coefficient, Calinski-Harabasz, and Davies-Bouldin indices. Results indicate that the two-cluster solution is statistically robust, while the three-cluster solution provides additional insight into transitional patterns of digital transformation. The two-cluster solution revealed a clear distinction between digital leaders and less advanced economies, with the greatest disparities observed in online banking (71% vs. 29%), online purchases (68% vs. 32%), and e-government use (68% vs. 34%). The three-cluster solution provided further nuance, showing that in 2011 most European economies were concentrated in the weakest cluster, while only Northern Europe achieved high levels of digitalization. By 2020, all European countries had reached at least the middle cluster, reflecting a shift from strong polarization toward a more balanced distribution of digital development. Despite progress, structural gaps remain, emphasizing the need for policies that advance digital skills, encourage inclusive adoption, and build trust in online services to sustain digital transformation.

Acknowledgment
The authors acknowledge with gratitude the financial support provided by the Ministry of Education and Science of Ukraine for the research project “Cybersecurity and digital transformations of the country’s wartime economy: the fight against cybercrime, corruption and the shadow sector”, state registration number 0124U000544).

Type of the article: Research Article

Abstract
The study develops a framework for forecasting conflict-related socio-economic vulnerabilities in a cross-country sample using indicators of armed conflict risk, forced displacement, and illicit practices. The analysis uses panel data covering 135 countries over 2012–2024. The Conflict Risk Index, Refugee Load Index, and Cyber Vulnerability Index were constructed using standardized indicators and Principal Component Analysis. The Cyber Vulnerability Index is a proxy for digital exposure to cyber-related disruptions. First-difference panel regressions identified associations between conflict- and migration-related risks and socio-economic indicators. Separately, GRU neural networks were applied to forecast these indicators, while comparative quartile-based ablation and scenario-based perturbation analyses assessed the contribution and sensitivity of corruption, AML-related risk, and cyber vulnerability across country groups. Regression analysis showed that the Conflict Risk Index was statistically associated with deterioration in GDP, GDP per capita, GDP per capita growth, political stability, life expectancy, labor force dynamics, and migration balance. The Refugee Load Index was associated with positive net migration alongside weaker economic growth and lower political stability in host countries. Forecasting results were heterogeneous: adding corruption, AML-related risk, and cyber vulnerability indicators improved accuracy for several targets, but deteriorated performance for some variables and showed evidence of overfitting for GDP per capita in the conflict-risk specification. In high-conflict-risk countries, the largest forecast improvements were for life expectancy (61.02%), GDP per capita (43.96%), and net migration (10.75%); in high-refugee-load countries, they were observed for life expectancy (60.30%), political stability (38.41%), and net migration (16.20%). The framework can support early warning, resilience assessment, and crisis response.

Acknowledgment
We acknowledge with gratitude the financial support provided by the Ministry of Education and Science of Ukraine for the research project “Cybersecurity and digital transformations of the country’s wartime economy: the fight against cybercrime, corruption and the shadow sector,” state registration number 0124U000544.