In the context of accelerating digital transformation of the economy, the analysis of intersectoral differentiation of digitalization processes becomes increasingly relevant. The aim of the study is to analyze the intersectoral differentiation of digitalization processes within the socioeconomic system of Kazakhstan and to identify structural constraints hindering the digital transformation of the real sector. The methodological framework of the research is based on comparative economic analysis, structural assessment, and the calculation of relative digitalization indicators. The study relies on official statistical data from the Bureau of National Statistics of the Republic of Kazakhstan for 2022–2024, covering 172,335 organizations across various types of economic activity. The results demonstrate a positive trend in the diffusion of digital technologies: the number of organizations using cloud computing increased by 45%, while those applying big data analytics grew by 39%. The share of large and medium-sized manufacturing enterprises implementing digital technologies rose from 12.9% to 19.2%. At the same time, only 5.45% of organizations employ in-house ICT specialists, with an average of 4.6 specialists per organization. Specialists in information security account for 33% of total ICT personnel, though their presence remains extremely limited in system-forming industries. The findings indicate a high level of sectoral differentiation in digital development and structural constraints within the real sector of the economy. Priority directions include strengthening infrastructural support for industries, expanding public-private partnership mechanisms for financing digital projects, developing corporate data centers, and modernizing ICT workforce training systems.

Women's participation in the information and communication technology (hereinafter - ICT) sector It is increasingly seen as an essential element of inclusive digital transformation. This study examines the impact of digitalization and gender-related indicators on regional economic growth and evaluates whether women’s participation in ICT contributes to more inclusive development patterns. The analysis is based on a balanced panel dataset of 16 regions for the period 2010–2024. A pooled OLS model, a two-way fixed effects specification, and robustness checks with clustered heteroskedasticity-robust standard errors are employed. Estimates of the two-factor model of fixed effects show that the wage level is the most stable determinant of regional economic growth (β = 1.330; p < 0.001), while investments in fixed assets retain marginal statistical significance (β = 0.126; p = 0.060). The human capital index shows a statistically significant negative internal effect (p < 0.001), while indicators of digitalization and gender variables turn out to be statistically insignificant. The results show that digitalization indicators and gender variables do not have a statistically significant intraregional impact on the gross regional product after taking into account regional and temporary fixed effects. At the same time, investments in fixed assets and wages are the most stable determinants of regional growth. Cluster analysis revealed four models of regional development — digital-service, industrial, agricultural and resource, which confirms the structural heterogeneity. The results show that digitalization by itself does not guarantee inclusive growth, and its economic effects are mediated by structural factors.

In the context of the increasing spatial differentiation of agricultural development and the need to switch to a growth model with higher added value, the task of scientific substantiation of the territorial location of agricultural farms in the regions of Kazakhstan is being actualized. The purpose of the study is to analyze the dynamics of the development of the regions of Kazakhstan and determine the prerequisites for the formation of agrohabs based on industrial, infrastructural and social determinants. The methodological framework includes descriptive statistical analysis, normalization of indicators using the min-max method, and calculation of an integral index. The typologization of the regions was carried out using the quartile method, and a socially oriented SWOT diagnosis was additionally carried out for regions with high and medium potential levels. The information base was the official data of the Bureau of National Statistics and the National Bank for the period 2010-2024. The results showed that during the analyzed period, gross agricultural output increased from 1.82 trillion tenge to 8.31 trillion tenge (an increase of 4.56 times; average annual rate of 11.5%), while employment decreased from 2.29 million to 1.03 million people and labor productivity increased from 0.79 to 8.09 million tenge per employee. The integral index revealed a pronounced regional differentiation: the highest values were recorded in Turkestan (0.80), Almaty (0.69), Akmola (0.66) and North Kazakhstan (0.65) regions, the lowest in Mangystau (0.37) and Ulytau (0.10) regions. The results obtained confirm the need for a differentiated regional policy and the use of integrated assessment as a tool for strategic planning of agrohabs.

In the context of the institutionalization of the sustainable development agenda and the strengthening of corporate social responsibility requirements, the analysis of social and gender differences in ESG (Environmental, Social, Governance) attitudes is of particular importance. The aim of the study is to identify gender differences in ESG socio-value attitudes and to determine the role of the national context in moderating these differences at the crosscountry level. Principal component analysis (PCA) methods were used to isolate the latent structure of ESG attitudes and multiple linear regression analysis (OLS) to assess the impact of gender, institutional trust, social equality, environmental attitudes, and demographic factors. The empirical base was formed on the basis of a cross-national survey (N = 8,291) in the UK, USA, Russia and Kazakhstan. As a result of the PCA, four latent components were identified that explain about 60% of the total variance: traditional gender attitudes, institutional trust, social equality, and environmental orientation. Regression analysis showed a statistically significant influence of gender on attitudes towards traditional gender roles (B = -0.188; p < 0.001), which indicates a more pronounced egalitarian position of women. The greatest contribution to the variation of attitudes was made by institutional trust (β = 0.128; p < 0.001), followed by environmental orientation (β = 0.054; p < 0.001) and support for social equality (β = 0.025; p = 0.020). The gender gap was more pronounced in Kazakhstan and Russia than in the UK and the USA. The results obtained confirm that gender differences in ESG attitudes are stable, but contextually depend on the socio-institutional environment.

The problem of territorial socio-economic imbalances remains one of the key issues in Kazakhstan's regional policy, as differences between the economic potential of regions and the achieved social results persist even with sustained economic growth. The purpose of the study is to evaluate the effectiveness of the transformation of economic and infrastructural resources of the regions of Kazakhstan into social results, primarily in reducing poverty and unemployment. The methodological basis of the study is the nonparametric method of Data Envelope Analysis (DEA), which makes it possible to assess the relative effectiveness of regions as decision-making units in converting resources into social outcomes. The results of the DEA analysis showed that 13 of the 20 regions achieved full efficiency, while 7 regions demonstrated relative inefficiency, including Almaty с. (0.8087), Mangystau (0.8840) and Pavlodar (0.9327) regions. At the same time, a territorial differentiation of social indicators was revealed: the depth of poverty varies from 0.3 to 1.6, and the proportion of the population with incomes below the subsistence level ranges from less than 3% to more than 8%. The results showed that a high level of economic development in the region does not guarantee proportionately high social efficiency, and territorial imbalances are associated with differences in management efficiency and resource use. A promising area of further research is to expand the time coverage of the analysis through the use of panel data, which will allow us to assess the dynamics of the relative effectiveness of regions and identify trends in the transformation of economic resources into social outcomes.

In Central Asian countries, women's entrepreneurial activity is gradually increasing, but its development is accompanied by a number of institutional, economic and socio-cultural constraints. The purpose of this study is to assess the level of influence of social, economic and institutional variables on the level of entrepreneurial activity of women in Central Asian countries. The empirical database covers data for Kazakhstan, Kyrgyzstan, Uzbekistan and Tajikistan for 2015-2024, based on information from the World Bank, reports from the Global Entrepreneurship Monitor, the Global Gender Gap Index of the World Economic Forum and national statistical agencies. The results of the study showed a steady increase in the proportion of women among entrepreneurs in all the countries under consideration: in Kazakhstan, the indicator increased from 40.1% in 2015 to 46.5% in 2024, in Kyrgyzstan — from 37.2% to 43.1%, in Uzbekistan — from 28.7% to 38.2%, in Tajikistan — from 22.5% to 29.3%.. The results of the panel regression showed a statistically significant positive impact of women's labor force participation (β = 0.38; p = 0.002), Internet penetration (β = 0.29; p = 0.005), access to credit (β = 0.34; p = 0.009) and GDP per capita (β = 0.21; p = 0.017) for the development of women's entrepreneurship; the explanatory power of the model was R2 = 0.64. The results show that Kazakhstan and Kyrgyzstan demonstrate the highest level of women's involvement in entrepreneurial activity, while Uzbekistan and Tajikistan maintain a more pronounced gender gap in entrepreneurial activity. The results of the study can be used in the development of programs to support small and medium-sized businesses and gender equality policies in Central Asian countries.

In the context of increasing regional differentiation and the digital transformation of the economy, there is a growing need to quantify the factors driving regional economic growth. The purpose of the study is to quantify the impact of human capital, innovation activity, social conditions, and the dynamics of world oil prices on the economic growth of Kazakhstan's regions. The methodological basis of the study is a panel model with fixed effects within the catch-up growth framework, along with spatial econometric methods to account for interregional spillovers. The assessment results show that the most significant growth factors are oil prices and innovation activity. The simulation results show that a 1% increase in world oil prices raises the GRP growth rate by an average of 0.48%, with an effect of 0.54% for oil-producing regions and 0.44% for other regions. Expenditures on technological innovations have a positive and statistically significant impact of β = 2.15 (p < 0.01), with interregional innovation spillovers of β = 11.8 (p < 0.01). The contribution of healthcare is also significant ((β = 5.66, p < 0.05), whereas expenditures on R&D, education and investments in fixed assets did not show a statistically significant shortterm effect. A high correlation has been established between the dynamics of world oil prices and the average growth of regional GRP (r = 0.87). At the same time, expenditures on R&D, education, and fixed capital investments do not show a statistically significant shortterm effect. The results obtained confirm the dominant role of the oil factor and the importance of innovative spillovers as key drivers of regional economic growth.

In the context of the accelerating digital transformation of the economy, the importance of quantifying the impact of digital factors on the effectiveness of the higher education system is increasing. The purpose of the study is to analyze the impact of digitalization on the effectiveness of the educational process in higher education institutions in Kazakhstan. The methodological basis of the work consists of quantitative analysis methods, including the calculation of relative indicators of digitalization and educational effectiveness, as well as econometric modeling using the least squares method (OLS). The empirical base of the study was made up of statistical data from the Bureau of National Statistics of the Republic of Kazakhstan, including indicators of the number of students, graduates, teachers, as well as the provision of universities with computer technology and Internet access. The results of the study show that during the analyzed period, the availability of Internet computers increased from 11.64 to 13.28 units per 100 students (+14.1%), while the graduation rate increased from 23.57% to 26.51% (+2.94 p.p.). The econometric analysis revealed a positive relationship between the level of digitalization and the effectiveness of the educational process: an increase in the availability of Internet computers by 1 unit per 100 students is accompanied by an increase in the graduation rate by an average of 2.09 percentage points (R2 = 0.874). The results show that digitalization is a significant factor in improving the effectiveness of higher education, but its impact is primarily quantitative and does not fully reflect qualitative changes in graduate training.

Today, the impact of climate change on agriculture is increasing and there is a need to rethink the role of rural infrastructure as a key factor in the sustainability and adaptive potential of the agricultural sector. The aim of the study is to assess the impact of rural infrastructure development on the sustainability of agriculture in Kazakhstan, taking into account regional differentiation and climatic factors. The methodological basis of the research includes methods of descriptive statistics, comparative analysis and econometric modeling. Panel data from the Bureau of National Statistics of the Republic of Kazakhstan on five macro-regions of Kazakhstan for 2010-2025 were used. The results showed that there is a stable positive relationship between infrastructure development and agricultural sustainability. In the basic model, an increase in the infrastructure index by 1 unit leads to an increase in the sustainability index by 0.58 (β = 0.58; R2 = 0.81). The extended model has a higher explanatory power and shows that the greatest impact is exerted by water infrastructure (β = 0.34), followed by digital (β = 0.29) and transport (β = 0.17) components. The regional analysis revealed a significant differentiation: the maximum values of sustainability are observed in the Northern macroregion, while the Western macroregion remains the most vulnerable. The results obtained confirm that rural infrastructure acts as a systemic mechanism for adaptation to climate change, but its effectiveness is determined by its structural balance and regional conditions. The greatest effect is achieved with the integrated development of water, digital and transport infrastructure.