This study aims to study Kazakhstan’s regions and identify places with the best potential for developing smart cities based on cluster analysis. To analyze the differentiation by the level of development, 17 regions of Kazakhstan are grouped according to 2020 data from the statistical bulletin of the National Bureau of Statistics of the Republic of Kazakhstan. The formation of groups of regions with different values of indicators was carried out based on agglomerative clustering using the single linkage, complete linkage, and Ward’s clustering methods. In agglomerative clustering, the algorithm groups regions based on observations into clusters, and indicators determine each area’s innovative development level. The instrument to build clustering is the “RStudio” software package. As a result, regions with their essential characteristics were identified, and an assessment of their prospects was obtained with the most significant potential for developing and managing “smart cities” – Atyrau region, Almaty city, and Astana city. The remaining clusters include regions where favorable conditions for the development of innovations have not yet been formed, which require more resources and efforts to build “smart cities.” Therefore, they should not be the first to implement this concept. They need a more balanced, integrated approach, ideally supported by experience in implementing the idea in more promising regions. In a sense, clustering also allowed for identifying potential (or even existing) innovation clusters in regions of Kazakhstan. The study results can be used in developing government programs to form smart cities and further study the potential of smart cities.

Rapid urban growth and the spread of the concept of smart cities force an increasing need to understand how cities become “smart” and apply their experience where it will best take root. Understanding which experience will be most suitable is not a trivial task and requires labor-intensive analysis. This study aims to identify smart cities that are most similar to Almaty and Astana in terms of key indicators by applying quantitative methods. Using a sample of smart cities, this paper successively employs three methods—principal component analysis, hierarchical cluster analysis, and t-distributed stochastic neighbor embedding. The results showed that Denver and Ottawa are the closest to Almaty and Astana, followed by Ankara and Phoenix. The proposed methodology allowed us to assess the similarity of urban development conditions, with an assumption that similar development conditions determine approaches to the development of smart cities, and thus the relevance of experiences from other smart cities worldwide could be applied to Almaty and Astana. This approach is intended to contribute to the effectiveness of transferring advanced solutions of smart city development to the context of Kazakhstan. The obtained conclusions can be used to form recommendations for the development strategy of Almaty and Astana, as well as other cities facing similar challenges.

The authors of the article investigated the impact of corruption on the level of poverty in Kazakhstan. The aim of the study is to assess the impact of corruption on poverty in Kazakhstan, and compare with estimates from other countries, including Argentina, Germany and Denmark, to identify similarities and differences. In conducting the study, the authors use the Corruption Perceptions Index and other variables such as the unemployment rate and inflation. Corruption not only breeds poverty, but also undermines state power and threatens social stability. The results of the study show that corruption has a statistically significant impact on the level of poverty in all four countries, but with different intensity. As a result, it was revealed that the focus is on the context of Kazakhstan and the lack of quantitative research on the impact of corruption on poverty in this country. In particular, in Kazakhstan, the effect of corruption on the level of poverty was less pronounced after adding additional variables. The authors suggest that less obvious mechanisms of the relationship between corruption and poverty may operate for Kazakhstan, and suggest further research directions, such as the use of nonlinear models and a more accurate choice of variables. This study provides a better understanding of the impact of corruption on poverty and emphasizes the need for further research in this area.

Type of the article: Research ArticleAbstractDespite the growth of investments in higher education and innovative infrastructure in Kazakhstan, institutional and regional differences continue to shape heterogeneous outcomes in graduate employment. This study aims to assess the impact of higher education on the economic development and employment of graduates in Kazakhstan, while accounting for regional differences. The empirical research base is formed using official and publicly available statistical data from the Bureau of National Statistics and other government agencies of the Republic of Kazakhstan for the period 2000–2024. The study employs panel data econometric methods, including fixed-effects models and extended specifications. The results of the analysis show that investments in fixed assets per capita are positively and statistically significantly related to the level of gross regional product (β = 0.2855; p < 0.01), while average wages do not have a statistically significant effect (p = 0.941). The higher education index and the level of urbanization have negative and statistically significant coefficients (p < 0.05), and innovation activity shows a positive effect only in alternative model specifications. The results obtained emphasize the importance of considering the institutional and spatial characteristics of regions when forming management policies in the field of higher education, youth employment, and regional economic development.AcknowledgmentsThis paper has been funded by the Science Committee MSHE RK (Grant “Modernization of the quality assurance system of higher education in Kazakhstan based on digitalization: development of approaches, mechanisms and information base” BR24992974).

The problem domain of the research covers the consideration and analysis of the personal safety assurance of citizens of contemporary Kazakhstan society. The current work is aimed at revealing, studying and theoretical conceptualization of information on personal safety as an indicator of population living standards. To achieve the goal of the research the following common scientific methods were used: analysis and synthesis, methods of comparison, functional and logical analysis, and methods of applied researches. The work presents the retrospective analysis of the “personal safety” notion, systematizes the existing approaches to the investigation of the essence that allowed revealing its main components. The work considers personal safety as one of the basic needs of humans that affects the population living standards. Within this context, the existing methods of population living standards assessment considering the personal safety factors were analyzed. Basing on the considered methods and research results of the international organizations, the comparative analysis of indicators related to personal safety in Kazakhstan and OECD countries was conducted on different indexes. The conducted comparisons allowed providing some assessment of the personal safety state of Kazakhstan citizens. Also, using the method of the linear combination of particular indicators to the integrated indicator the authors have calculated the indicator of economic safety of the population for the Almaty region that covers the personal safety indicators. The authors show the advantages and disadvantages of the applied method and provide recommendations on its application at different levels. The conclusions of the research can be taken as a base for an in-depth study on measuring the indicators of population personal safety in the context of living standards assurance.

Although smart-city benchmarking has produced many indices and rankings, cities still lack a practical way to assess whether successful initiatives can be transferred across institutional contexts and converted into implementable urban roadmaps. In this study, we aimed to develop and empirically test a paired donor–recipient “problem–solution” methodology that bridges comparative city analysis with implementation readiness gap assessment, addressing the persistent disconnect between smart-city benchmarking and actionable transfer guidance. The smart-city ecosystem was decomposed into eight functional dimensions covering digital foundations, service platforms, finance and procurement, innovation capacity, governance, legal adaptability, and citizen participation. The method was applied to the Ottawa-Astana pair using a systematic desk-based analysis of publicly available strategic documents, legislation and policy frameworks, and implementation materials (e.g., roadmaps, program guidelines, departmental plans, and monitoring outputs). Data were analyzed using a structured gap analysis algorithm employing a three-level qualitative compliance scale (Full Compliance, Partial Compliance, and Non-compliance) to assess recipient city status against donor benchmarks across all eight functional dimensions. The results reveal Astana’s partial compliance with the Ottawa benchmark, with moderate readiness and pronounced “hard-soft” asymmetry; that is, greater progress in regard to infrastructure and platforms, but persistent gaps in adaptive regulation, experimentation-friendly legal instruments, and participatory governance. These findings suggest that progressing toward a Smart City 2.0 model requires prioritizing regulatory sandboxes, adaptive procurement pathways for pilots, and scalable civic-tech mechanisms alongside continued investment in talent and innovation ecosystems—understood here as interconnected networks of universities, technology parks, civic-tech communities, and incubation infrastructure that collectively sustain capacity for technology absorption and local adaptation. The proposed paired framework is replicable and supports phased, actionable transfer roadmaps for policymakers.