Cluster-driven innovation and management in healthcare under regional and socio-economic disparities

The effect of digitalization on inequality continues to spark discussions, with opinions divided on whether it alleviates or exacerbates the issue. This paper explores how digitalization has affected income inequality in Ukraine from 2017 to 2021. A pooled OLS model is used to investigate the relationship between mobile communication access and fixed Internet access and usage and their influence on disposable income levels. The findings reveal that mobile and Internet access significantly impact income distribution, with a notable disparity between high- and low-income regions. Specifically, wealthier regions benefit more from mobile access, while low-income regions lag due to insufficient broadband infrastructure. These results underscore the need for targeted management strategies to reduce regional income inequality via digitalization in Ukraine. The transition from desktop internet to mobile connectivity is clear, as 4G and 4G+ networks have enough speed to substitute fixed Internet and have become the primary means of internet access in Ukraine, reflecting a global trend. This highlights the increasing significance of mobile Internet, especially in lower-income regions, as a practical alternative to fixed broadband. Hence, mobile networks can boost economic participation and reduce regional disposable income inequality. The study suggests that targeted investments in digital infrastructure can significantly contribute to regional economic development.

Acknowledgment
This paper is funded as part of the project “Financial tools for reducing economic inequality in Ukraine” research project (No. 0124U002254), conducted at the State Organization “Institute for Economics and Forecasting of the National Academy of Sciences of Ukraine.”

Type of the article: Research Article

Abstract
This study aims to assess the impact of key components of quality of life, including human capital, social accessibility, and industrial development, on effective territorial development management in Kazakhstan. The study uses an index approach, cluster and correlation analysis, and Markov transition models. The empirical dataset covers 17 regions of Kazakhstan over the period 2013–2023 and is based on official annual statistics, including indicators of education (number of students and teaching staff), employment, income, digital infrastructure, and industrial development. The Quality of Life Index (QLI) was calculated using normalized variables, followed by regional grouping and dynamic modeling. Results indicate that the highest QLI values in 2023 were recorded in Astana city (0.837), Mangystau (0.790), and Shymkent city (0.771), where educational coverage and academic staffing are significantly higher than in other regions. Correlation analysis reveals that industrial development (r = 0.493, p = 0.052) and educational potential (ρ = 0.491, p = 0.045) are positively associated with regional upward transitions in quality of life. Cluster analysis identified three stable groups of regions: with active social transformation (e.g., Mangystau, Kyzylorda), balanced growth (Karaganda, Pavlodar), and limited dynamics (Turkistan, East-Kazakhstan). Thus, regions with strong educational infrastructure and dynamic labor markets, such as the Mangystau region, Astana and Shymkent cities, consistently outperform in QLI. In contrast, structurally lagging regions, such as Turkistan and East Kazakhstan, exhibit limited social mobility and weak institutional support. Consequently, investment in human capital is essential for reducing regional disparities and promoting sustainable territorial development.

Acknowledgments
This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (“Modernization of the quality assurance system of higher education in Kazakhstan based on digitalization: development of approaches, mechanisms and informationbase” No.BR24992974).