Economic series of the Bulletin of L.N. Gumilyov ENU

A bibliometric analysis of the social, behavioral, and potential economic consequences of gambling among youth and Generation Z

A. Samambayeva — 2026-09-30

Objective – to conduct a bibliometric analysis of scientific publications on gambling among Generation Z indexed in Scopus during 2012–2025 and identify key research areas and factors influencing gambling addiction. Methods – bibliometric, comparative, cluster, and visualization methods, as well as systematization and synthesis of scientific literature. Results – an analysis of the dynamics of publication activity on the topic under study was conducted, identifying the main areas of scientific research related to gambling addiction in Generation Z, including risky behavior, pathological gambling, decision-making characteristics, and cultural aspects. As digital natives, Generation Z integrate gambling into digital entertainment, combining video games, eSports, and social interaction. A clear pattern emerges: this generation prefers fast-paced and interactive gambling games. A cluster analysis was conducted on the selected database, revealing four distinct clusters comprising key factors influencing gambling addiction in the socioeconomic context. Conclusions –research on gambling among Generation Z in the socioeconomic context is growing. Effective prevention methodology considers the digital environment and behavioral characteristics of young people. The findings contribute to the existing literature, identify directions for future research, and offer recommendations for policies and prevention programs to prevent gambling addiction among youth. Limitations are also identified.

Analysis of the Institutional Environment and Factors of Social Entrepreneurship Development in the Republic of Kazakhstan

Botakoz Tusupbaeva — 2026-09-30

The article is devoted to a comprehensive analysis of the institutional environment and factors influencing the development of social entrepreneurship in the Republic of Kazakhstan. The aim of the study is to identify the key institutional conditions affecting the formation and sustainable development of social entrepreneurship, as well as to determine the barriers and drivers of its growth. Special attention is paid to the regulatory framework, mechanisms of state support, the role of the quasi-public sector and development institutions, as well as the interaction between business, the state, and civil society.

Methods include institutional, systemic, and comparative analysis, evaluation of existing support programs, and analysis of international experience in the development of social entrepreneurship. Legislative initiatives, including the formal recognition of the status of a social entrepreneur, were reviewed, and the effectiveness of implemented support measures was assessed.

Results reveal the key factors driving the development of social entrepreneurship: the presence of state support, the development of infrastructure (business incubators, accelerators), access to financing, and the growth of corporate social responsibility. At the same time, the main challenges were identified, including insufficient institutional maturity, limited access to financial resources, low awareness, and regional disparities.

Based on the analysis, recommendations were formulated to improve the institutional environment, including the development of public-private partnership mechanisms, expansion of financing instruments, implementation of ESG approaches, and strengthening the role of digital platforms in supporting social entrepreneurs.

Conclusions indicate that social entrepreneurship is an important tool for addressing social problems, increasing employment, and fostering an inclusive economy. The effective development of this sector requires systematic improvement of the institutional environment, stronger state support, and integration into the international socio-economic space.

Determinants of Income Inequality in Kazakhstan: Econometric Modeling of the Effects of Educational Coverage, Entrepreneurship, and Digital Transformation

G. Dauliyeva — 2026-09-30

Income inequality remains one of the key socio-economic challenges in Kazakhstan. The aim of this study is to assess, using econometric methods, the relationship between entrepreneurial activity, higher education enrollment, real wages, digital infrastructure, and income inequality. Methods – the analysis is based on official statistical data for 2004–2025. The Gini coefficient is used as the dependent variable, while the independent variables include the number of active SMEs per 1,000 population, higher education enrollment, real average monthly wages expressed in constant 2025 prices, and the share of internet users. Linear, semi-logarithmic, and log-log models are estimated, while the stationarity of the time series and the diagnostic properties of the models are also examined. The results show that higher education enrollment has a positive and statistically significant relationship with the Gini coefficient in all model specifications. Real wages demonstrate a negative relationship in the linear and semi-logarithmic models, whereas the share of internet users shows a positive and statistically significant relationship in these specifications. Conclusion – a statistically significant relationship for entrepreneurial activity is observed in the log-log model. Overall, the findings indicate that the relationship between the examined indicators and income inequality varies depending on the model specification.

Territorial and sectoral structure of the economy of Kazakhstan: production concentration and regional disparities

G. Taikulakova — 2026-09-30

The article examines the territorial and sectoral structure of Kazakhstan’s economy through the relationship between production concentration, regional specialization and spatial disparities. The relevance of the topic is determined by the fact that uneven industrial development affects regional resilience, employment, labour productivity, value-added depth and the ability of territories to build interregional production chains. The aim of the study is to identify industries in which Kazakhstan’s regions have pronounced production advantages and to determine which forms of concentration can become growth points and which indicate structural constraints. The methodological basis is the PCR/ECR diagnostic model, where PCR reflects the relative production performance of a sector and ECR reflects labour-force concentration. Based on 2025 data, industries are classified into four quadrants: priority, highly efficient, socially significant and sectors requiring productivity upgrading. The results show that Kazakhstan has a heterogeneous industrial space: western regions retain a resource-processing profile, central and eastern regions have industrial and technological potential, northern and southern regions develop agro-industrial specialization, while large cities concentrate service-industrial and consumer-oriented production. The practical significance lies in justifying differentiated regional industrial policy instruments.

Regional Prioritization of Digital Irrigation Management in Southern Kazakhstan: A Multi-Level Decision-Support Framework

B. Kair — 2026-09-30

The purpose: Irrigated agriculture in Southern Kazakhstan faces water scarcity, climatic stress, and uneven adoption of water-saving irrigation technologies, creating a need for transparent regional prioritization of digital irrigation management. Methods: This study develops a multi-level, non-causal decision-support framework for Turkestan, Kyzylorda, and Zhambyl. The framework combines three analytically separate evidence blocks: a descriptive field-level water-balance comparison, contextual treatment-level economic evidence, and regional indicators of technology adoption, relative climate stress, land suitability, and observable implementation readiness. Results: The first two blocks provide contextual evidence and do not measure digitalization or enter the composite index. Only regional indicators are integrated through the Digital Irrigation Management Priority Index (DIMPI). In the source-reported grain-maize trial, seasonal total water consumption was 3,282 m³/ha under drip irrigation versus 3,996 m³/ha under discrete irrigation, a descriptive difference of 17.87%. Conclusions: Under all prespecified DIMPI weighting scenarios, Turkestan ranked first, while Kyzylorda and Zhambyl exhibited contrasting need–readiness profiles. The results support the use of DIMPI as a preliminary screening tool for identifying where more detailed digital-irrigation feasibility assessment may be warranted, rather than as an estimate of digitalization effects or project-level investment returns.

Economic returns to higher education in Kazakhstan: assessing wage differentiation by education level based on the Mincer model

R. Bernazarova — 2026-09-30

Objective – to provide a quantitative assessment of the economic returns to higher education in the Republic of Kazakhstan based on an analysis of wage differentiation by education level for 2018-2025, applying the Mincer equation adapted to aggregated official statistics. Methods – aggregate adaptation of the Mincer equation to panel data (, calculation of wage differentiation coefficients, the education premium, and the gender wage gap coefficient, descriptive statistics. Results – the empirical base comprises data from the annual Bureau of National Statistics (BNS RK) survey under Form 2-T "Report on the Structure and Distribution of Wages" for 2018-2025 (8 observations, April of each year). A panel regression with year fixed effects (N=24) yielded an education premium coefficient of ρ = 0.161 (standard error 0.009; p < 0.001; 95% confidence interval 0.142-0.181), corresponding to a 17.5% increase in earnings per additional year of schooling. A model with an education × year interaction showed a statistically significant decline in this return over the period (interaction coefficient -0.012; p = 0.001). The premium for higher education relative to secondary, which fell from 110.4% in 2018 to 67.0% in 2024, rose to 71.8% in 2025. Gender analysis revealed a persistent wage gap across all education groups: the gender gap coefficient in 2025 ranged from 1.345 for higher education to 1.503 for postgraduate education. Conclusions – the authors note the statistically confirmed significance of the economic returns to education in Kazakhstan alongside its compression over 2018-2024 and reversal in 2025, pointing to the sensitivity of the premium to income policy; confirm the applicability of human capital theory to a transition economy, and point to the need for further monitoring of the identified trend.

Artificial Intelligence and the Transformation of Youth Employment in Kazakhstan: Conceptual Risks and Opportunities for NEET Youth

D. Kazbekova — 2026-09-30

Aim – to form a conceptual understanding of the mechanisms of youth employment transformation in Kazakhstan under the influence of artificial intelligence technologies and to determine the specific risks of digital exclusion for NEET youth. Relevance – AI changes the structure of demand for competencies, raising entry barriers to the labor market for socially vulnerable categories. Methods – conceptual modeling, structural-logical analysis, and dynamic analysis of official data from the Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan for the comparable period of 2023–2025. Results – it was established that despite an overall decline in the youth unemployment rate in Kazakhstan, regional, gender, and institutional imbalances persist. An author's conceptual model of youth labor market structural polarization under the influence of AI is proposed. Conclusions – the impact of AI on youth employment is indirect, manifesting through a shift in demand toward complex digital and adaptive skills. NEET youth are characterized by heightened vulnerability to digital exclusion, requiring specialized institutional integration mechanisms.

Methodology for assessing the readiness of innovation systems

D. Baxultanov — 2026-09-30

Purpose – to examine existing approaches to assessing the level of development of scientific, technological, and innovation potential of regions and clusters, as well as to develop an original methodology for evaluating the readiness level of innovation systems. Methods – comparative analysis, abstract-logical, and systems approaches to the study of innovation assessment methodologies.
Results – the study identifies the key advantages and specific features of existing methodologies, along with their limitations that hinder practical application. It is established that there is currently no universal methodology for assessing the level of development of innovation systems. Approaches based on composite indices fail to provide a comprehensive assessment of system maturity. The paper proposes an original methodology for evaluating the readiness level of innovation systems, integrating the Technology Readiness Level (TRL) tool and taking into account the specifics of interactions among participants in the innovation ecosystem. The proposed approach enables a comprehensive analysis of innovation environment maturity, identification of bottlenecks in technology commercialization processes, and improved justification of managerial decisions in the field of innovation development.
Conclusions – the developed methodology makes it possible to assess the state of innovation systems at both national and regional (local) levels and can be adapted to sector-specific features in the context of cluster development.

Conceptual model of building a supply chain management system based on artificial intelligence tools

S. Muratov — 2026-09-30

This article presents a conceptual model for developing a supply chain management system (SCMS) based on artificial intelligence tools. The relevance of this research lies in the fact that artificial intelligence is often used in supply chains for specific tasks, such as demand forecasting, route optimization, or improving warehouse operations, while the principles for integrating these into a single end-to-end system at the corporate level are insufficiently systematized.

The objective of this study is to substantiate the architecture of an AI-based SCMS that integrates planning, execution, and management modules, includes a data layer, an analytical (modeling) layer, a decision-making cycle, and a feedback mechanism, and to propose a system of key performance indicators that simultaneously measure model quality and business impact for performance evaluation.

The methodological framework utilizes methods of system analysis, literature review and synthesis, conceptual modeling, and comparative logical analysis. Results - the study structured the SCMS architecture at the "data-model-decision-feedback" levels, describing the main types of models in the analytical layer (forecasting, optimization, risk and anomaly detection, scenario modeling) and their lifecycle in a production environment.

Within the decision support mechanism, human-system interaction modes were defined: consultation, collaborative decision-making, and independent execution. Furthermore, a system of key performance indicators was proposed in two dimensions: assessing model quality and measuring its impact on business results. Conclusions - the proposed model provides organizations with a methodological basis for the phased implementation of artificial intelligence in supply chain management systems and a substantiated assessment of its effectiveness.

Family Business Identification and Managerial Maturity Assessment: A Diagnostic Model for Kazakhstan

I. — 2026-09-30

Objective – This study aims to substantiate the criteria for identifying family businesses in Kazakhstan and to distinguish the characteristics of family control from indicators of corporate governance maturity. The study is relevant because the absence of an official statistical classification of family enterprises limits the assessment of their needs, risks, and the effectiveness of government support. Methods – The theoretical framework integrates the behavioral approach, the F-PEC scale, the familiness concept, and institutional theory. The empirical evidence comprises a survey of 85 representatives of enterprises exhibiting family involvement, conducted from January to May 2026 in Shymkent, Turkestan, and the Turkestan Region, as well as eight semi-structured expert interviews. Comparative, content, and descriptive analysis methods were employed. Results – a business’s family nature is determined by family control, relatives’ continuous involvement, the perception of the business as a shared family asset, and the intention to transfer it to subsequent generations. Separating family and corporate finances, clearly allocating responsibilities, planning succession, and engaging external professionals indicate governance maturity. Among respondents, 76.5% lacked a formally documented succession plan, 72.9% reported mixing family and business finances, and 53.0% identified distrust of hired managers and insufficient managerial competencies. These associations should not be interpreted as causal relationships. Conclusions – a voluntary diagnostic model adapted to Kazakhstan’s institutional context is proposed. It can identify the needs of family enterprises and guide targeted advisory and educational support without introducing an additional administrative status or regulatory burden.

From waste to capital: Circular marketing in Central Asia (Kazakhstan, Uzbekistan) - a comparative institutional analysis with the experience of Turkey

G. Tuleshova — 2026-09-30

The purpose of the study is to conduct a comparative analysis of circular marketing practices in Central Asia (Kazakhstan and Uzbekistan) and Türkiye’s institutional and technological experience. The article is intended for researchers in economics, marketing, and environmental policy, as well as public authorities and business practitioners developing green branding strategies. The theoretical foundation of the study draws on institutional economics (Acemoglu & Robinson, 2012), innovation-based growth theory (Aghion & Howitt, 1992), and the concepts of the circular economy and green marketing (Kirchherr, Reike & Hekkert, 2017; Peattie & Crane, 2005).

Methods include the synthesis and systematization of data from reports published by the World Bank, GreenEdge, KPMG, and the OECD, as well as comparative institutional analysis.

Results demonstrate that the regulatory mechanisms established under Kazakhstan’s new Environmental Code are compatible with the communication and technological experience accumulated by Türkiye through its Zero Waste Programme. Türkiye’s experience is of practical relevance for promoting circular consumption, supporting environmentally responsible brands, and integrating waste management principles into marketing strategies. In addition, the study identifies promising areas for marketing technology transfer and institutional cooperation among Kazakhstan, Uzbekistan, and Türkiye.

Conclusions – circular marketing is one of the key drivers of the sustainable development of Central Asian markets. The study provides specific recommendations for developing regional eco-retail, strengthening green communications, and adapting Türkiye’s experience.

Institutional research in higher education: Historical Context and Implications for Economic Development

G. Manarbek — 2026-09-30

Purpose – this paper examines the historical development of institutional research (IR) practices and explores its relevance for strengthening data-driven quality management in Kazakhstani higher education. Methods - a conceptual framework combined with a systematic literature review, organizational models, and practices in IR and higher education analytics, with a focus on adapting these approaches to the Kazakhstan context. Findings – a bibliometric comparison of publications from the USA, Europe, England, and Central Asia shows substantial differences in scholarly attention to IR. The USA accounts for 4,750 publications (40.9% of the reviewed total), followed by Europe with 4,554 (39.2%), while England accounts for 18.9%. Central Asia contributes only 115 publications (1.0%), covering Kazakhstan, Kyrgyzstan, and Uzbekistan. These results suggest that IR remains at an early stage of development in the region. More detailed normalization, such as publications per institution or researcher, is proposed for future research. Drawing on the U.S. “combo office” model and existing practices at Nazarbayev University and KIMEP, the paper proposes pillars for developing IR capacity in Kazakhstan. Conclusions – developing institutional research capacity can strengthen evidence-based decision-making and data-driven culture, support continuous quality improvement, and help universities respond more effectively to a rapidly changing labour market.

Problems of the Impact of Financial Instruments on Supporting the Real Sector of the Economy

A. Zeinelgabdin — 2026-09-30

The article presents a comprehensive analysis of the impact of financial instruments on the development and support of the real sector of the economy of the Republic of Kazakhstan.

Purpose of the study – to analyze the impact of financial instruments on supporting the real sector of the economy and to identify the key challenges to its development.

Methods – statistical and analytical methods were used to assess the impact of financial instruments on the development of Kazakhstan’s real sector of the economy during 2020-2025.

Results – it was established that the share of tax revenues in GDP remained within the range of 14,2-15,8% in 2022-2025, while certain budget execution indicators demonstrated pronounced unevenness. During the period under review, December receipts of advance corporate income tax (CIT) payments exceeded the average monthly level of the preceding 11 months by approximately 2,7-4,0 times. At the same time, accounts payable of the state budget increased from KZT 178,5 billion in 2022 to KZT 1025,4 billion in 2025, while budget fund balances reached significant levels during the financial year. The findings indicate the need to coordinate fiscal decisions with monetary conditions and to improve the uniformity of the use of public financial resources. On this basis, proposals were formulated to improve the instruments for supporting the real sector of the economy.

Conclusions – the results of the study confirm the importance of financial instruments for the development and support of the real sector of the country’s economy. The findings may be used to improve the regulatory framework for mechanisms of state support for the economy and to enhance the effectiveness of the economic policy of the Republic of Kazakhstan.

Financial Support for Agriculture in the Republic of Kazakhstan: From Subsidies to Digitalization and Green Technologies

A. Zeinolla — 2026-09-30

Objective − to trace the evolution of state support for agriculture in Kazakhstan in 2020–2025 in terms of the transition from the predominance of direct subsidies toward the expansion of digital and "green" development instruments, and to assess the implications of this transformation for the sustainability and efficiency of the sector, including compliance with Kazakhstan's obligations under the WTO and the EAEU. Methods − economic-statistical analysis of the dynamics of gross output, profitability of agricultural enterprises and the structure of fixed-capital investment in the sector; comparative analysis of the structure of state financial support instruments; structural classification; calculation of growth rates, compound annual growth rate (CAGR), and an original indicator relating investment to the increment in gross output. Results −The sector's share in the country's total fixed-capital investment fell from 5.4% in 2023 to 4.7% in 2024. A shift in the structure of state financing of the agro-industrial complex was identified toward preferential lending for seasonal work (about 53% of funds allocated in 2024), machinery leasing (28%) and investment projects (18%), together with the expansion of electronic subsidy systems and elements of green finance. Conclusions − the growth in gross output has been accompanied by declining producer profitability and a shrinking share of the sector in the country's investment portfolio, indicating the exhaustion of extensive growth reserves and increasing the importance of a qualitative transformation of support.

Foundations of budgetary and law policy in the Kyrgyz Republic

N. Temirov — 2026-09-30

Purpose. The study aims to examine the theoretical and legal foundations of budgetary and legal policy in the Kyrgyz Republic under contemporary socio-economic conditions and to identify priority areas for improving public financial management. Methods. The research employs legal and documentary analysis, comparative analysis, statistical analysis, and methods of synthesis and generalization. The empirical basis comprises official indicators of gross domestic product (GDP), government budget revenues and expenditures for 2017–2025, and the ratios of budget revenues and expenditures to GDP. Results. The study systematizes the essence, objectives, principles, and principal implementation areas of budgetary and legal policy. The findings show that in 2025 government budget revenues reached KGS 673.2 billion, while expenditures amounted to KGS 623.0 billion, resulting in a cash surplus of KGS 50.2 billion. The analysis identifies digitalization of the budget process, performance-based budgeting, fiscal transparency, and stronger public financial control as the principal areas of institutional development. Conclusions. Improving the effectiveness of budgetary and legal policy requires further development of budget legislation, greater transparency and accountability in the allocation and use of public funds, wider adoption of digital technologies, and stronger performance-oriented public financial management mechanisms.

Digital and Econometric Forecasting Tools Based on Financial Reporting Indicators

К. Saduakassova — 2026-09-30

Aim. To develop an integrated methodology for forecasting a company's financial performance by enhancing the informational potential of financial reporting indicators and to systematize modern digital and econometric tools used in financial forecasting.

Methods. The study employed the methods of scientific abstraction, comparative and systems analysis, economic and statistical analysis, regression analysis, time-series models, and multivariate econometric techniques. In addition, econometric model parameters were estimated, their statistical significance and forecasting accuracy were evaluated, and automated data processing and analytics systems, business intelligence platforms, and machine learning techniques were applied as digital analytical tools.

Results. The qualitative characteristics of financial reporting information, including reliability, completeness, and comparability, were evaluated, and their role in managerial decision-making and performance assessment was determined. A methodological approach based on the transformation and integration of financial reporting data was proposed to improve the accuracy of financial performance forecasting. The findings demonstrate that integrating financial and management accounting information reduces information asymmetry and enhances the reliability of forecasting results. Furthermore, the application of modern digital analytical tools expands the capabilities for assessing financial sustainability, managing risks, and improving the quality of strategic managerial decisions.

Conclusions. The proposed methodological approach enhances both the scientific validity and practical effectiveness of corporate financial performance forecasting. The research findings provide a methodological foundation for expanding the informational capacity of financial reporting, strengthening the analytical capabilities of enterprises under digital transformation, and developing a data-driven management system.

The impact of an integrated management accounting and controlling system on the profitability of sales of construction materials

N. Zhiyenbay — 2026-09-30

The study aims to determine how management accounting, cost analysis, and budgeting contribute to cost control, sound pricing decisions, and improved profitability in the construction materials market. Methods – The methodology combines the analysis of selling expense structure, cost classification by responsibility centers and sales channels, and the assessment of commercial efficiency. Full costing and direct costing are applied alongside break-even analysis, activity-based costing (ABC), and activity-based budgeting (ABB). The empirical basis comprises official construction statistics for Kazakhstan for 2023–2025 and a company case study incorporating a six-month operating budget and a three-month cash flow forecast. Results – The analysis identifies the principal cost drivers and reveals differences in the contribution margins generated by individual product groups and sales channels. The findings demonstrate that integrating management accounting with budgeting improves the transparency of selling expenses, strengthens control over deviations, and provides a more reliable basis for pricing and product-mix decisions. Conclusions – The study concludes that an integrated accounting and analytical system can enhance cost management, optimize cash flows, and improve the profitability and financial stability of construction-sector trading enterprises. Its effectiveness can be further strengthened through digital visualization, advanced analytics, and forecasting based on interconnected financial and operational indicators.

Analysis of Sustainable Development Factors in the Tourism Industry Using Correlation and Regression Modeling

Т. Rakhimzhanova — 2026-09-30

The aim of this study is to identify and evaluate the factors influencing the sustainable development of the tourism industry in the Republic of Kazakhstan, based on an analysis of statistical indicators characterizing the state and dynamics of tourism infrastructure development.

Methods: econometric research methods, including correlation and regression analysis of statistical data. The empirical basis of this study is based on official data from the National Statistics Bureau of the Republic of Kazakhstan for 2014–2024. The volume of services provided by accommodation facilities is used as the outcome variable, while the explanatory variables include indicators of tourist flows, accommodation capacity, investment activity in the accommodation and food service sectors, and the wage level of industry employees. Results: A correlation analysis of the relationships between key indicators of tourism industry development was conducted, and a reduced regression model was constructed to characterize the influence of key factors on the dynamics of the accommodation services market. The model was found to have high explanatory power (R² = 0.94), and the statistical significance of the model as a whole and of the coefficient for the tourist flow variable was established. Conclusions: In the short term, the main factor driving the growth in the volume of accommodation services is the dynamics of tourist flow, which reflects the level of tourist demand.

Investment activity shapes the conditions for the sector’s long-term development; however, the model developed does not statistically confirm its independent short-term effect. The results obtained can be used in the development of government policies for tourism infrastructure development and in enhancing the investment attractiveness of Kazakhstan’s tourism sector.