The potential for developing smart cities in Kazakhstan is evaluated using cluster analysis. Built on previous research focused on clustering the regions of Kazakhstan, this study applies the same method to the cities of the country. The analysis uses indicators related to human capital, infrastructure, education, information technology, production, and other factors to assess the potential of each city. The clustering is performed using Single Linkage, Complete Linkage, and Ward’s methods. The results show that Almaty and Astana are the cities with the highest potential for becoming smart cities. Aktobe is identified as a city with distinctive features that may help or hinder its development as a smart city. The remaining cities are clustered into two groups, with one group having the potential to catch up and maintain the trend of developing smart cities, while the other group is less suitable for starting smart city projects and may require more investment per capita. The study highlights the deep regional inequality affecting the potential to successfully develop and manage smart cities in Kazakhstan. The analysis also reveals some limitations and challenges in the data and variables used, including the lack of data for some variables and the difficulties in "translating" some factors and indicators into quantitative variables for clustering. The study concludes that future research should address these challenges and consider clustering inside certain regions to focus on their unique features. The study recommends launching pilot projects in small cities, with the most successful practices then scaled and implemented in the core smart cities and possibly Aktobe, if it manages to use its advantages to compensate for risks. Overall, this study provides insights into the potential of smart city development in Kazakhstan and can inform policymakers in their efforts to support smart city projects in the country.

In the last decade, ICT has significantly impacted economic growth in many developing countries, such as Kazakhstan. In addition, there is practically no analysis of the level of interconnections between the communication infrastructure and economic growth in the regional context. This article will consider the impact on GRP per capita of the following ICT factors: volume of communication services, number of fixed telephone lines, enterprises using computers, enterprises using the Internet, internal costs for R&D by regions, the number of organizations that have created and use new technologies and equipment. The data for the article were collected over ten years, from 2010 to 2020 as part of the dynamic panel data approach, which includes 14 regions and two cities. The initial data were taken from the statistical data of the Bureau of National Statistics of the Republic of Kazakhstan. The methodology used in the article includes the study of the proposed indicators and conducting correlation and regression analysis in the STATA program. The conclusions presented in our work showed that the ICT infrastructure has a significant positive impact on regional development, and the coefficient of elasticity of the ICT infrastructure to regional development is greater than the coefficient of elasticity of the degree of integration. The government can use the results of this study to develop programs to improve regional development.

The purpose of this study is to determine the socio-economic and demographic factors of intra-regional inequality in Kazakhstan and their implications for cluster-based innovation in healthcare. A hybrid approach has been used, consisting of a systematic review of 181 publications using the PRISMA 2020 protocol and econometric analysis of the 2001–2024 panel data for the districts of Kazakhstan, consisting of 3,842 observations. Fixed-effects, cluster-robust, and hierarchical mixed-effects models were employed using standardized variables of population size, fertility, mortality, migration, criminality, and investments. The results reveal that the strongest and most robust predictor of intra-regional inequality in Kazakhstan is investment in fixed capital (β = 0.466, p < 0.01; β = 0.399, p < 0.01). Population size has consistently negative effects on intra-regional inequality in Kazakhstan (β = –0.240 to –0.256, p < 0.05 and p < 0.01). In the multilevel model, fertility increases intra-regional inequality in Kazakhstan (β = 0.114, p < 0.01), whereas mortality and net migration decrease it (β = –0.150 and β = –0.037, p < 0.01). The model explained 37.1% of the variance in intra-regional inequality in Kazakhstan (R² = 0.371). The results suggest that without balanced investment and territorially differentiated policies, cluster-based innovation in healthcare can even reinforce rather than alleviate regional disparities.