Purpose – This study provides a comprehensive analysis of the global uranium market and assesses the ability of future supplies to meet growing demand through 2050. The study aims to identify potential imbalances between projected uranium supply and demand, taking into account market and geopolitical factors.

Methodology – The study is based on a comprehensive approach that combines econometric analysis and uranium supply curve modeling. Econometric analysis uses a variety of methods to examine the correlation between prices and production volumes, ensuring the reliability of the results. Supply curve modeling shows how uranium availability will change with price changes, allowing for an assessment of market stability under different scenarios.

Originality / value – The study analyzes the International Atomic Energy Agency’s forecasts and shows that primary uranium production will remain the main resource, despite the contribution from secondary sources. The study also highlights the importance of reviewing production and export policies in uranium-rich countries and ensuring security of supply.

Findings – The main conclusion is that a significant imbalance between the projected uranium demand and supply, especially under medium and high demand scenarios, indicates that a potential shortage may arise by 2035. Kazakhstan is expected to take a leading position in the uranium export market by 2050. In addition, political and energy security issues may contribute to the growth of demand for nuclear energy, leading to the formation of new global partnerships and trade routes. The conclusions provide a deep understanding of market dynamics and contribute to the sustainable development of nuclear energy.

The purpose of the study is to evaluate the state policy aimed at increasing the competitiveness of socially significant products in Kazakhstan, analyze the main factors affecting the competitiveness of social products such as meat and dairy products, determine the dynamics of their development, as well as identify problems in the field of socially significant food products and propose solutions.

Methodology: comparative and statistical methods of analysis were used when writing the article.

The uniqueness of the study is the analysis of the main factors determining the competitiveness of such socially significant food products as meat and dairy products, the identification of problems and the definition of the main mechanisms of government regulation aimed at supporting the competitiveness of such products.

As a result of the research, problems in the field of socially significant products were identified and ways to solve them were considered to ensure the competitiveness of such products.

Purpose of the study. The study aims to identify the scale and specific features of external and regional educational migration of young people in Kazakhstan, and to justify policy measures aimed at transforming educational mobility into a driver of sustainable development.

Methodology. The research employs comparative and structural methods of analysis of migration statistics by region and field of study, as well as content analysis of government programs and regulatory documents governing migration, education, and youth policy in Kazakhstan.

Originality. This study is the first to compare external and regional youth migration in Kazakhstan within a unified analytical framework. The proposed approach reveals the relationship between territorial imbalances within the country and the scale of brain drain abroad. Its value lies in the integration of quantitative migration statistics and public policy analysis, which together provide a comprehensive understanding of migration processes.

Results. The largest outflow of young people is observed in technical, economic, and pedagogical specialties, particularly in the northern and eastern regions of Kazakhstan. In contrast, two southern and two western regions demonstrate a relative capacity to attract young people. A comparison of government programs indicates a gradual adaptation of youth policy to new challenges, although significant gaps remain in retaining specialists in strategically important fields.

Contemporary public administration reforms in Kazakhstan are oriented toward the principles of inclusiveness and human-centeredness; however, their theoretical conceptualization and practical implementation remain insufficiently studied and systematized. The research problem consists in the insufficient theoretical elaboration and systematization of the relationship between inclusiveness and human-centeredness in Kazakhstan's public administration and in the gap between the declared principles and their practical implementation. This article fills this gap by comparing the essential characteristics of the two approaches and clarifying their interaction based on the experience of Kazakhstan.

The aim of this study is to identify the interrelation between inclusive and human-centered approaches, assess their implementation in the context of Kazakhstan, and develop recommendations for their integration.

The methodological basis of the study includes qualitative analysis of secondary sources, comparative analysis of governance models, examination of Kazakhstan’s experience, and the development of the author's conceptual model.

The originality and scholarly value of the research lie in the exploration of the relationship between inclusive and human-centered approaches, their application to Kazakhstan’s governance practices, and the formulation of an original model of inclusive public administration.

The findings demonstrate that inclusive governance involves broad participation of all societal groups, while the human-centered approach focuses on prioritizing the needs of each individual citizen. These approaches are shown to be complementary. Practical examples, such as the «e-Otinish» and electronic petitions system, illustrate the potential of digitalization in implementing the principles of openness, accountability, and citizenoriented service delivery.

Purpose of the research is to identify key barriers and examine the mechanisms of public administration influencing the implementation of inclusive education in secondary schools in Kazakhstan, focusing on the case of the Almaty region.

Methodology. The study is based on a qualitative approach. Documentary analysis and online survey methods with elements of semi-structured interviews were used. Principals, inclusion coordinators and teachers from 40 schools in the Almaty region and Kaskelen took part in the study.

Originality / value of the research. The article focuses on the managerial and economic aspects of inclusive education, which remain understudied in the Kazakhstani context. The conducted empirical study for the first time systematizes the perception of barriers and conditions of inclusion by the participants in the educational process themselves.

Findings. Five key groups of barriers were identified: infrastructural limitations, staff shortages, insufficient funding, weak administrative support and low social preparedness. The findings confirm the need to modernize public administration mechanisms and sustainable budget planning to ensure equal access to quality education for all students.

The purpose of the study is to analyze the current state of development of the grain industry in Kazakhstan, identify the factors constraining their growth and substantiate recommendations for achieving high results in this industry.

Research methodology. The methodological basis of this study is a set of complementary scientific approaches that provide a comprehensive and objective analysis of the problems and prospects of the development of the grain industry in Kazakhstan. The choice of a systematic approach is conditioned by the need to take into account the multidimensional nature of the problem under consideration, since ignoring individual elements of the system can lead to ineffective solutions. The comparative analysis made it possible to set targets for the development of the industry and identify the most effective mechanisms of state support. The application of the dialectical approach made it possible to take into account the dynamics of industry development and predict possible changes in the future, as well as develop flexible strategies that can adapt to changing conditions.

The study used official statistical data obtained from the following sources: the Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan, the National Bank of the Republic of Kazakhstan, the Ministry of Agriculture of the Republic of Kazakhstan, the State Revenue Committee of the Ministry of Finance of the Republic of Kazakhstan, the World Bank, etc. Tools such as Microsoft Excel and IBM SPSS Statistics were used to process and analyze the collected data.

The time frame of the study covers the period from 2019 to 2024. The choice of this period is due to the availability of complete and reliable statistical data provided by official sources. The need to analyze the latest trends allows us to reflect current trends in the grain industry, changes in the global grain market and increased competition from Russian producers.

The originality/value. This research has a high degree of originality and value, as it offers a comprehensive and scientifically based approach to solving the problems of the grain industry in Kazakhstan, contributing to its sustainable development and increasing competitiveness in the global market.

Findings. This study provides a comprehensive analysis of the current state of the grain industry in the Republic of Kazakhstan, identifies key problems hindering its sustainable development, and develops scientifically sound recommendations for overcoming them. Special attention is paid to the issues of low yields, dependence on climatic conditions, inefficient water use, lack of financing and increased competition from imported grain.

The grain industry in Kazakhstan, despite its significant potential and strategic importance for ensuring food security, is characterized by a significant lag in yield from world leaders and high vulnerability to external factors. The lack of an integrated approach to solving systemic problems that hinder innovation, production modernization and market diversification hinders the development of the industry's potential and reduces its competitiveness.

The scientific novelty of the research consists in conducting a comprehensive analysis of the factors determining the sustainable development of the grain industry in Kazakhstan; substantiating the need to switch to targeted government support; developing a system of measures to diversify export markets and increase the competitiveness of Kazakhstani grain; proposing specific measures to implement long-term strategic goals for the development of the grain industry, including the allocation of responsibility.

This study explores the integration of the "quintuple helix" model and esg (environmental, social, and governance) framework for sustainable business development, both critical for improving business processes and fostering systematic analysis. The research aims to reassess these frameworks and propose an innovative n-model of management. Validity is confirmed through analysis of kazakhstani and international literature, practical testing, and implementation of findings in real-world contexts.

The purpose of the study is to review and rethink approaches to the formation of the “five helix” and esg with the development of prerequisites for the development of the n-model of management.

Research methodology. Qualitative methods were employed, including observation of processes in natural environments and focus group discussions to analyze the significance of the "quintuple helix" model and esg transformation. Theoretical generalization identified commonalities and differences between the frameworks, highlighting priority directions for further research.

Originality (value) of the research. The "quintuple helix" model emphasizes dynamic knowledge exchange within a nation for sustainable development. Esg focuses on environmental responsibility, social accountability, and robust corporate governance. Both concepts are essential for addressing issues like low management quality and insufficient decision-making systems in kazakhstan.

Results of the study. The significance of the results and conclusions of the study lies in clarifying the characteristics and conditions that complicate innovative interaction. The five spiral model and the existence of prerequisites for adapting the esg education model show the qualitative changes that the relationships between participants in kazakhstan's innovative development are undergoing. The study concludes that the integration of the two concepts contributes to the development of the n-model of management, improving interaction between participants in the innovation process.

Research aim. The aim of the research is to identify and evaluate the distinctive competitive advantages of ski tourism within Kazakhstan’s Almaty Aountain Aluster (AMC), and determine how these advantages can be strategically leveraged to enhance sustainable regional tourism development.

Research Methodology. The study employs a mixed-method approach, integrating Geographic Information Systems (GIS)-based spatial analysis, comparative benchmarking against established ski destinations (French Alps and Georgian ski clusters), and economic impact assessments based on secondary data from governmental and international sources. GIS methodologies included data extraction via Python from open-source geospatial databases (2GIS, OpenStreetMap), proximity analysis, and infrastructure density visualization.

Value of the study. This research is significant as it provides a comprehensive comparative spatial and economic analysis of AMC, a strategically crucial yet relatively understudied ski tourism destination. The combination of advanced GIS analytical tools and comparative benchmarking delivers practical insights and robust strategic recommendations, uniquely tailored to the sustainable tourism development needs of Kazakhstan.

Research findings. The study identified AMC’s core competitive strengths, including its accessibility, affordability, unique cultural and ecological assets, and governmental support. At the same time, the study reveals significant infrastructure scarcities in hospitality, gastronomic services, and complementary tourist facilities were evident. Comparative analysis with Georgian and French counterparts underscored AMC’s critical need to substantially expand its infrastructure, recommending the construction of 30-40 new accommodations, 60-70 restaurants, and approximately 20-30 complementary service facilities. Strategic infrastructure development aligned with sustainable tourism practices is projected to notably enhance AMC’s tourism capacity and its contribution to Kazakhstan’s GDP by an estimated 0.5%-1.5% annually by 2027.

The purpose of this study is to develop a methodology for assessing environmental risks and to test it using data on pollution across different regions of Kazakhstan.

Methodology. The study uses a literature review and deductive reasoning to find solutions to environmental pollution. Content analysis helps develop an integrated, weighted environmental risk through composite indexing. Economic and mathematical methods (including Moran’s I, spatial weights matrices), along with visualization techniques, are used to present the research results.

The uniqueness of this study lies in its focus on the influence of natural and climate features of a specific region, along with pollution from neighboring areas, rather than relying solely on national pollution indicators and their effects on the regional environment. Data collected and analyzed on emissions and waste in Kazakhstan's four largest regions allowed for the calculation and comparison of environmental risk levels. Regional environmental risk assessments were based on data of the end of 2024. The study revealed that Karaganda (1.26) and West Kazakhstan (1.78) regions experienced high environmental risk during this period, particularly due to the municipal waste index. Meanwhile, in East Kazakhstan, the index, at -0.0142, was considered quite low, and in Kyzylorda, it was closer to the boundary between moderate and high environmental risk (0.198).

The study highlights the importance of quick access to environmental data for guiding management decisions by regional governments. It also stresses the need to expand and sustain this research by developing a regional environmental database. Calculation of environmental risks helps to clarify measures for environmental management in regions adjusting decisions considering the weight of a particular index.

Research objective. To conduct a comparative analysis of logistics risks in Kazakhstan and the USA, identifying key vulnerabilities, assessing their impact on supply chains, and developing specialized risk management strategies.

Methodology. A mixed-method approach was used: quantitative analysis (World Bank LPI, trade statistics) and qualitative expert interviews. Applied SWOT analysis, risk mapping, and comparative assessment. Theoretical framework includes Sheffi (2022), ADB/WTO reports, state programs ("Nurly Zhol").

Originality/value. A comparative risk matrix for differently developed economies was created. Practical significance is evidenced by calculations: $2.1B rail gauge standardization reduces delays by 30%; NIST compliance cuts cyber incidents by 70%.

Results. Structural disparities were identified:

 - Kazakhstan: infrastructure gaps (22% roads meet standards), geopolitical risks (68% EU transit via Russia);

- USA: cyber threats ($4.3M damage/incident), climate risks ($18B annual losses).

Priority solutions: for KZ – developing "Middle Corridor", for USA – port cybersecurity.

This study contributes to the existing body of knowledge by providing a comparative analysis of logistical risk factors in different economic contexts (notably Kazakhstan and the USA) and proposing a novel integrated theoretical and methodological framework for risk assessment and management tailored for industrial enterprises.

The study aims. This study addresses severe environmental degradation in Ust-Kamenogorsk by developing the “MAZE Ecopark,” an innovative urban ecotourism model that integrates sustainable tourism, ecological restoration, and environmental education.

Methodology. A mixed-methods approach was applied, combining GIS-based spatial and environmental analysis, a pilot sociological survey (n≈80), cost-benefit and visitor-flow modeling, 3D visualization, and expert consultations. These tools allowed evaluation of environmental conditions, community demand, and preliminary economic viability.

Originality/value of the research. This is the first ecopark framework specifically designed for post-industrial cities in Central Asia. Unlike traditional urban parks, the model combines maze-design principles with ecological remediation and educational programming, linking recreation with sustainability and community engagement.

Key findings. Results confirm: (1) serious environmental degradation, with air quality indicators exceeding WHO standards and limited green infrastructure; (2) strong public support and willingness to engage in urban ecotourism; and (3) financial feasibility, with potential to attract substantial visitor flows and achieve mediumterm payback. The expected impact includes ecological improvements (air-quality mitigation, urban greening), social benefits (public health, environmental literacy, social cohesion), and economic contributions (tourism revenue, new jobs).

Purpose of the research - To examine modern methods of investment portfolio optimization with an emphasis on risk and volatility management, and to explore the integration of financial monitoring tools in ensuring regulatory compliance and operational resilience.

Methodology - The study is based on the modeling and analysis of a diversified hypothetical investment portfolio containing stocks, bonds, and ETFs. It combines classical optimization theories—such as the Markowitz model and Sharpe ratio—with advanced tools including Value-at-Risk (VaR), Conditional Valueat-Risk (CVaR), stress testing, and machine learning algorithms for volatility forecasting and asset allocation.

Originality/value - This research provides a synthesis of traditional financial models and modern datadriven techniques. A notable contribution is the applied use of financial monitoring systems—used by secondtier banks—to assess portfolio stability and regulatory risk under the frameworks of AML/CFT and Basel III.

Findings - The results show that implementing innovative risk management and optimization strategies significantly enhances portfolio performance and resilience. Empirical analysis demonstrates that financial monitoring, when combined with CVaR-based modeling and stress scenarios, contributes to better decisionmaking, reduced exposure to extreme losses, and improved compliance.

This article explores the challenges of managing financial flows at various stages of the startup lifecycle in Kazakhstan. Using empirical analysis methods, the study identifies key features and difficulties entrepreneurs face in financial management from the idea stage to scaling. Based on data collected from startups in Almaty, Astana, and other regions, the research offers recommendations aimed at optimizing financial strategies.

The paper examines financial flow management characteristics across different startup development stages. A review of domestic and international literature is provided, along with a classification of funding sources based on growth phases and an analysis of real-life cases from Kazakhstani startups. Particular attention is given to the limited financial literacy of founders and restricted access to venture capital.

The study concludes that tailored financial strategies are essential at each stage of development, and offers practical suggestions for improving the current ecosystem.

Research Objective: To identify the main features of financial flow management across different stages of Kazakhstani startups' lifecycle and provide recommendations for improvement.

Tasks:

1. To review theoretical models of startup lifecycles and financing.
2. To systematize funding sources by lifecycle stages.
3. To analyze practical case studies of Kazakhstani startups.
4. To identify financial management challenges and suggest improvements.

Methodology. The study is based on a comparative analysis of business lifecycle models, qualitative analysis of startup financial data, and five case studies of Kazakhstani companies. Interviews with startup founders, data from Astana Hub, and materials from accelerators and venture funds were also used.

Novelty. The research is the first to provide a comprehensive empirical analysis of financial management across the startup lifecycle in Kazakhstan. It adapts international theoretical models to the local context and categorizes domestic startup experiences by development stage.

Findings. The results show that startups suffer from a lack of financial planning at early stages and are heavily dependent on external funding. In the growth phase, the level of strategic financial management and control improves.

Research Objective. The purpose of this study is to analyze the experience of implementing ESG principles in developing countries and to examine the role of non-financial information in corporate reporting and its impact on investment attractiveness. ESG principles allow assessing not only the economic efficiency of companies but also their contribution to social responsibility and environmental safety. Nowadays, ESG requirements have become an important tool for ensuring transparency in accordance with international standards and for achieving the goals of sustainable development. Therefore, this research focuses on the disclosure of nonfinancial information by Kazakhstani public organizations.

Research Methodology. The study is based on content and comparative analysis. Bibliometric methods were applied within the content analysis, and the VOSviewer software was used to visualize relationships between keywords, authors, and publications. This made it possible to identify trends in publication activity, distinguish thematic clusters, and highlight authors contributing to the study of ESG practices and non-financial reporting in the context of developing countries. In addition, the non-financial reports of Kazakhstan Petrochemical Industries, Jusan Bank, KazMunayGas, Development Bank of Kazakhstan, and Eurasian Resources Group were analyzed.

Originality/Value of the Study. The scientific base has been enriched by a comprehensive assessment of the impact of ESG principles on the financial stability, investment attractiveness, and reputation of companies in developing countries. The study also contributes to the systematization of scientific publications by clusters and encourages the management of Kazakhstani organizations to pay greater attention to compliance with ESG requirements in their corporate reports.

Research Findings. The study found that the introduction of ESG principles enhances companies’ long-term competitiveness, facilitates international cooperation, and reduces reputational risks. The results emphasize the importance of non-financial information for the socio-economic development of developing countries and can serve as a foundation for designing effective corporate strategies.

Purpose: This article employs a regression-correlation approach to analyze indicators of Kazakhstan's economic digital transformation, utilizing statistical data to forecast changes in GDP per capita. The purpose of this analysis is to investigate the influence of digitalization on the economic development of the country, and to summarize the main factors driving the development of the digital economy

Methods: We use official statistics (2000–2023) and IBM SPSS Statistics software to estimate regression models and produce scenario forecasts.

Originality/Value: The primary value of this research lies in its analysis of key digital economy indicators and their impact on the country's GDP per cap.

Results: This study investigates the relationship between key innovation and technology indicators and economic growth, measured by Gross Domestic Product per capita in Kazakhstan. Using a stepwise multiple regression analysis on time-series data from 2000 to 2023, we identify the most significant predictors of GDP per capita. The final model, which includes internal R&D expenditures, internet users, R&D organizations (X1) and R&D personnel, demonstrates a strong explanatory power with an R2 of 0.995. The findings reveal that financial investment in R&D and digital infrastructure are the most powerful drivers of economic growth.

Limitations: The time-series analysis presented carries an inherent risk of spurious regression due to potential non-stationarity of the data.

Purpose: This study aims to analyze the impact of Open Government Data (OGD) on social trust formation in public administration in Kazakhstan, testing the OGD value creation theory in a highly digitalized environment that has not achieved the expected level of public trust.

Methodology: The research employs quantitative analysis of data from the Kazakhstan Digital Inclusiveness Survey using R software. Correlation and regression analyses were used to evaluate relationships between socio-demographic factors, platform usage, satisfaction, accessibility, and trust levels. Additionally, thematic content analysis of respondents' open-ended answers was applied.

Results: Contrary to expectations, socio-demographic factors minimally impact trust levels in OGD, while service quality and user satisfaction emerge as key determinants. Significant trust disparities were found across digital channels: official websites receive substantially lower ratings (3.448) compared to government social media (8.094) and news sources (9.745). Statistical analysis showed that platform accessibility moderates relationships between certain demographic factors and trust.

Originality: The study identifies a novel "circle of trust" mechanism connecting usage frequency, service satisfaction, and trust levels in a self-reinforcing cycle. This concept offers new perspectives on bridging the gap between formal digital platform implementation and public value creation. The findings indicate that for governments seeking to build public trust, merely creating digital platforms is insufficient; they must ensure data reliability and develop verification mechanisms that foster a comprehensive open data ecosystem.

Purpose – The research examines how artificial intelligence (AI) affects industrial project outcomes in Kazakhstan by studying cost reduction and time efficiency alongside risk management effectiveness.

Methodology – Based on the data collected from publicly accessible project databases, company reports as well as expert surveys, statistical methods including descriptive statistics, regression analysis, and comparative methods such as T-tests or ANOVA, were employed to evaluate the performance of 40 industrial projects in Kazakhstan, comprising 20 AI-enabled and 20 non-AI projects from the energy, manufacturing, and infrastructure sectors.

Originality / value – This research addresses the insufficient statistical analysis of AI’s impact on industrial projects in Kazakhstan, by providing quantitative evidence of its effects on key project outcomes like cost, timeline, and risk control. This study offers valuable insights for industry executives and government leaders in Kazakhstan regarding the benefits and effectiveness of AI integration in industrial projects for enhanced performance and sustainable economic expansion.

Findings – The study’s findings indicate that the adoption of AI in industrial projects in Kazakhstan leads to a reduction in project costs by 10% and an acceleration of project timeframes by 15%, when compared to traditional non-AI project efforts. Furthermore, AI implementation resulted in a 40% reduction in project risks and a higher project success rate of 92% for AI-enabled projects versus 85% for non-AI projects.

Purpose: This article employs a regression-correlation approach to analyze indicators of Kazakhstan's economic digital transformation, utilizing statistical data to forecast changes in GDP per capita. The purpose of this analysis is to investigate the influence of digitalization on the economic development of the country, and to summarize the main factors driving the development of the digital economy

Methods: We use official statistics (2000–2023) and IBM SPSS Statistics software to estimate regression models and produce scenario forecasts.

Originality/Value: The primary value of this research lies in its analysis of key digital economy indicators and their impact on the country's GDP per cap.

Results: This study investigates the relationship between key innovation and technology indicators and economic growth, measured by Gross Domestic Product per capita in Kazakhstan. Using a stepwise multiple regression analysis on time-series data from 2000 to 2023, we identify the most significant predictors of GDP per capita. The final model, which includes internal R&D expenditures, internet users, R&D organizations (X1) and R&D personnel, demonstrates a strong explanatory power with an R2 of 0.995. The findings reveal that financial investment in R&D and digital infrastructure are the most powerful drivers of economic growth.

Limitations: The time-series analysis presented carries an inherent risk of spurious regression due to potential non-stationarity of the data.