The article examines the significance of digital platforms in the development of the agricultural products market of the Republic of Kazakhstan in the context of the digital transformation of the agro-industrial complex. The study analyzes the theoretical foundations of agricultural digitalization and identifies the role of digital platforms as an institutional and technological tool for improving market efficiency. Particular attention is paid to the functioning of state and sectoral digital platforms implemented in Kazakhstan, including systems for electronic subsidization, agricultural land monitoring, livestock identification, and digital services supporting agricultural producers. The economic effects of digital platform implementation are analyzed through the reduction of transaction costs, improvement of price transparency, optimization of supply chains, and enhancement of market accessibility for small and medium-sized agricultural producers. The article emphasizes that digital platforms contribute to reducing the number of intermediaries in the agricultural market, thereby increasing producers’ incomes and improving price formation mechanisms. Based on official statistical data and practical experience in the Republic of Kazakhstan, the study assesses the impact of digital platforms on the dynamics of average prices for key agricultural products. The analysis of price indicators is used as an indirect measure of the economic consequences of digitalization in the agricultural market. The findings demonstrate that the development of digital platforms creates favorable conditions for improving the competitiveness, sustainability, and economic stability of the agricultural sector. The results of the study may be useful for policymakers, researchers, and practitioners involved in the digital transformation of agriculture.

Currently, the Auyl–El Besigi (AEB) state program is primarily focused on financing infrastructure projects, but the sustainability and effectiveness of such investments largely depend on the quality of local governance and management capacity. The purpose – to develop a new theoretical and methodological framework for assessing the long-term effectiveness of the AEB aimed at integrated rural development in Kazakhstan. In the article, the general theory of economic development was used to analyze the program, based on the principle of economic discrimination and the model of the “triad of development”. The study showed to what extent the working mechanisms of the AEB correspond to the principle of economic development. The scientific novelty of the research lies in the introduction of a hybrid concept combining the principles of Kazakhstan’s macroeconomic development strategy and the Korean Trinity Model. The proposed hybrid model allows a comprehensive assessment of the synergetic effect of public investment and the potential of local government. The article provides a comparative analysis of the experiences of the Turkistan, Kyzylorda, and Zhambyl regions, which have applied different governance models in implementing the AEB. The findings demonstrate that the program’s effectiveness is determined not so much by the volume of funding as by its strategic orientation. In conclusion, the study proposes the use of a panel regression model based on annual panel data to empirically test the proposed hybrid framework. The results offer practical recommendations for subsequent stages of the AEB, focusing on strengthening local capacity and introducing digital governance mechanisms.

The profitability of agricultural production demonstrates how effectively land, labor, and financial resources are used to produce the final product. However, traditional methods of analyzing and forecasting economic efficiency often fail to account for the complexity and diversity of modern agricultural processes. Agriculture is characterized by a high level of uncertainty and dependence on many factors, such as weather conditions, market fluctuations, and technological changes. Therefore, there is a need to improve the methodology for assessing, analyzing, and forecasting the profitability of agricultural products. The purpose of this article is to study current issues in assessing and forecasting agricultural production efficiency based on the indicator of product profitability. In accordance with this goal, the following research objectives are addressed using abstract logical and comparative methods: generalizing theoretical approaches to interpreting the concept of “production efficiency” and the content of its indicators; and investigating forecasting methodology, particularly forecasting the efficiency of agricultural production. Based on the conducted factor analysis of profitability, a forecast of the production efficiency of certain types of agricultural products is substantiated, and the proposed measures are evaluated. The methodology for assessing the profitability of agricultural enterprises can be used as one of the criteria for providing them with state financial support.

In a market economy, financial security is constantly recognized as the economic security system’s key component. Its importance is increasing in today’s environment of economic instability, currency fluctuations, financial threats and counterparty insolvency, and internal financial resource management challenges, including capital shortages, low liquidity, solvency, and profitability. This study aim is to develop theoretical principles and formulate practical proposals for strengthening enterprise financial security in the face of high uncertainty and external instability. The key research areas include the analysis of external and internal threats to financial security, the substantiation of criteria and indicators for assessing it, and the improvement of financial resource management mechanisms. The key idea behind the study is the need to adapt existing scientific approaches to modern economic transformation processes. The value of the work lies in the development of author’s approaches to ensuring the financial security of an enterprise, focused on early detection and prevention of threats, as well as comprehensive management of financial resources, which contributes to the development of scientific ideas in the field of economic and financial security. The research results the can be used in the practical activities of the enterprise in the formation and improvement of the financial security system, increasing financial stability, investment attractiveness and ensuring long-term sustainable development.

In the context of the digital transformation of the financial sector and the increasing complexity of the regulatory environment, project management has become a key factor in ensuring the sustainability and competitiveness of financial organizations. In the Republic of Kazakhstan, this issue is particularly relevant due to large-scale digitalization initiatives, the introduction of new financial products and services, and increasing demands for operational efficiency and change management. This study provides a comprehensive assessment of the current state and maturity of project management in Kazakhstan’s financial sector and examines factors influencing its effectiveness. The research adopts a mixed-methods approach, combining quantitative and qualitative techniques. Empirical data were collected through a standardized survey of 137 employees from nine financial organizations, including banks, microfinance institutions, and insurance companies. Additionally, 15 expert interviews were conducted, and strategic documents and annual reports were analyzed. The results indicate that project management is mainly institutionalized at the level of basic structures and formal regulations, while maturity levels vary significantly across organizations. Hybrid use of waterfall and Agile approaches is common, whereas the adoption of project portfolio management (PPM) systems and business intelligence (BI) tools remains limited. Key challenges include regulatory pressure, a shortage of qualified professionals, weak project culture, and fragmented IT infrastructure, which hinder effective data integration and decision-making.

This article examines the development of the wage system in Kazakhstan. The aim of this study is to examine the differentiation of employee wages in the Republic of Kazakhstan and develop recommendations for optimizing its structure across regions and industries. A systems approach was used to analyze wages across industries and regions, employing economic and statistical methods, classification, structural analysis, historical and comparative analysis, and participant observation across various organizations across the country. It was determined that the implementation of a market mechanism for wage regulation largely depends on the optimization of individual structural elements of wages. An important approach to addressing this issue is the de facto recognition of wages as the price of labor, established through collective bargaining between representatives of employees and employers in the labor market. The amount of wages for hired workers should initially be determined through collective bargaining agreements at all levels: industry, regional, and national. Implementing this provision requires a radical revision of the entire legislative framework governing labor relations and the transformation of trade unions into a real force in the negotiating process.

This article develops a process-digital methodological model for accounting for trade transactions in electronic commerce. The digital transformation of trade changes the structure of business operations and accounting information formation, in which verified digital events generated within integrated information systems play a central role. In online trade, the accounting cycle begins with a digital order and includes payment processing, inventory movements and write-offs, return handling, recognition of marketplace commissions, and the recognition of tax liabilities. The study proposes a process-digital accounting model based on an event-driven approach to transaction recording and the formalization of the trigger for the transfer of control over goods. The model is presented as a structured register of digital order events and accounting procedures, with a key control-transfer trigger determining the timing of revenue recognition and related measurement estimates. The framework ensures consistent application of IFRS 15 to revenue recognition, IAS 2 to inventory measurement with consideration of net realizable value (NRV), and IFRS 9 to the recognition of expected credit loss allowances. The model also considers the regulatory impact of the mandatory application of the National Product Catalogue in Kazakhstan from 1 January 2026 in the issuance of online cash register receipts and electronic invoices, strengthening requirements for master data consistency within the digital accounting and tax environment. The methodological approach combines regulatory analysis and digital business process modeling. The practical significance lies in the applicability of the proposed model to accounting policy development and digital platform design for Kazakhstan’s e-commerce sector.

In the context of digitalization of the economy and increasing requirements for the efficiency of management of enterprises of the agro-industrial complex (AIC), the importance of improving the accounting and analytical support of business processes has increased. Proper formation of the budgeting information base allows you to increase the validity of management decisions, the efficiency of resource allocation, and reduce risks. The purpose of the study is to systematize and develop the theoretical and methodological foundations of the accounting and analytical support of business processes in the agro-industrial complex, taking into account modern digital tools and management accounting standards. In the course of the study, the methods of systematic and comparative analysis, structural and logical modeling, as well as economic and mathematical analysis were used to assess the impact of accounting and analytical tools on budgeting performance indicators. The methodological basis of the study is based on the concepts of management accounting, digitalization of financial processes, and analysis. The uniqueness of the study lies in defining the concept of accounting and analytical support for budgeting and making comprehensive recommendations for its development, taking into account the specifics of the agro-industrial complex of the Republic of Kazakhstan. The results of the study demonstrate the impact of integrating accounting and analytical data into the management budgeting system on increasing the transparency, efficiency and accuracy of management decisions. The developed model demonstrates that the connection between the strategic goals of the organization, financial indicators and operational plans increases the stability of agro-industrial enterprises and the efficiency of resource use.

Scientific approaches to determining value and place of investment potential as opportunity to carry out investment activities usingregional economic resources are explored in article. Object of study is Turkestan region which was formed in 2018 with regional center in Turkestan. Article provides economic analysis of Turkestan region’s economy for period of 2020–2024 is fulfilled in article, growth of gross regional product, industry, agriculture, trade, and tourism is determined, low indicators in the social sphere and wages of employees are identified. Analysis of indicators of population employment by types of economic activity is conducted, employment structure is calculated, private conclusion about predominant population employment in sphere of trade, agriculture, education is made. Analysis of indicators of investment to fixed capital by districts of Turkestan region, structure of investment led to conclusion of uneven development of investment potential in number of regional districts. Using information of Regional Project Pool of Turkestan Region for 2025–2028, investment matrix was calculated for first time. It was concluded that investment potential of region is mainly aimed at creating industrial production and energy sector. Taking into account agricultural orientation of region, analysis of investment projects for development of agroindustrial complex of Turkestan Region for 2022–2028 was carried out, significant projects involving Chinese and Russian investors were identified. Recommendations have been made about AI using in agriculture. Investment potential of tourism manifests itself in Turkestan, and conclusion about comprehensive approach to using investment potential of Turkestan region and its impact on regional economy has been made.

The study examines the contemporary patterns of economic cooperation between China and the countries of Central Asia under conditions of globalization and geopolitical transformation. Particular attention is paid to the impact of the Belt and Road Initiative on regional trade, infrastructure connectivity, energy cooperation, and transport integration. Methodologically, the research is based on comparative, systemic, and historical-logical approaches. The study analyzes macroeconomic trends, infrastructure projects, trade dynamics, and the influence of external geopolitical factors on regional economic interaction. The findings demonstrate that China – Central Asia cooperation has intensified in recent years due to the expansion of transport corridors, investment projects, and trade relations. Infrastructure connectivity and energy cooperation are identified as the principal drivers of regional economic integration. At the same time, the analysis indicates that the effects of cooperation are uneven across the region and depend on national economic policies, logistics capacity, and external market conditions. The study concludes that China – Central Asia economic interaction represents an important element of contemporary Eurasian economic development and contributes to the diversification of regional trade and infrastructure networks.

In the era of digitalization, business development is taking on a new form, where the involvement of artificial intelligence is inevitable. This article explores the relationship between artificial intelligence and business development. The purpose of the article is to conduct a bibliometric analysis of the interaction between artificial intelligence and business development. The research methodology is based on a bibliometric analysis of the Scopus database for the period from 2008 to January 2026 to identify trends in business development in artificial intelligence. The results show that the number of publications during the analyzed period increased from 8 to 1026, and the coverage by branches of science is multidisciplinary. In addition, it was shown that the popularity of the topic is characterized not only by an increase in the number of publications, but also by a high level of citations and the high activity of authors in the field of research. As a result of the analysis, four scientific trends were identified (AI and the industrial sector, Digital business platforms, chatbots and e-commerce, Strategic Business Management), which will serve as the basis for conceptualizing business development in the era of digitalization. The theoretical significance of the study lies in identifying major research trends and documenting the evolution of scientific interest in the relationship between artificial intelligence and business. The practical significance of this study lies in its conclusions and results, which can be helpful to business owners and government agencies developing programs to advance digitalization and business development.

The emergence and development of the concept of artificial intelligence is a logical consequence of the logic of scientific and technological progress in the context of the emergence of the digital economy. Artificial intelligence (AI) is currently becoming a key trend in the improvement of management technologies in many countries around the world. Kazakhstan is currently making certain efforts to join this community of countries with a developed AI concept. In this regard, the purpose of this scientific work is to study the issues of adapting the AI concept in the context of the modern development of the country, taking into account the existing experience in applying AI technologies to solving the problems of effective development of the digital economy. At the same time, an important task, in the author’s opinion, is to explore the potential for improving the quality of public management, bearing in mind the strengthening of consistency in justifying decisions at all levels and in all levels of public administration through the use of digital and AI technologies. In the course of the research, the author paid special attention to the establishment of relationships between IT technologies and AI, on the one hand, and the quality of human capital in public management, on the other hand. In the author’s opinion, this is especially important at the lower levels of the public administration system, where the economy in practice is directly and deeply tied to the tasks of social development.

Global shifts in commodity markets and growing supply chain transparency requirements are creating new institutional conditions for the extractive sector. In this context, internal control effectiveness is determined not only by procedural completeness but also by the level of digital transparency. The purpose of the study is to provide theoretical and methodological justification for the digital transformation of internal control systems in mining enterprises under conditions of mineral value concentration and supply chain transparency requirements. A quantitative-institutional approach was applied, encompassing analysis of physical output and world price dynamics, assessment of structural changes in value formation, and evaluation of internal control maturity using data from a major integrated mining company in Kazakhstan. It was established that after 2020, gold’s share in the aggregate value structure exceeded 50% without comparable growth in physical output. This reflects a value concentration phenomenon in which key supply chain risks shift from production control to provenance verification. The growth of internal control digital maturity in 2020–2024 coincides with intensifying value concentration, reflecting adaptation to changing risk structures and tightening provenance requirements. The scientific novelty lies in substantiating value concentration as an independent economic driver of internal control digital transformation, and in developing a five-level conceptual model with a feedback loop and a control architecture maturity index applicable for designing digital control mechanisms in responsible supply chains. The practical significance lies in the applicability of the proposed model to designing digital internal control mechanisms and improving provenance verification procedures in Kazakhstan’s extractive sector.

The article is devoted to a comprehensive analysis of the impact of migration processes in the Republic of Kazakhstan on the labor market, the quality of human capital and the structural development of the national economy. Тo comprehensively review the current state and dynamics of internal migration processes in the Republic of Kazakhstan. Analysis of the main trends in urbanization, the reasons for the concentration of the population from rural areas to large cities and economically active regions, and the differences in socioeconomic development levels between regions. The study identified the relationship between migration and socioeconomic and demographic factors, and conducted an analytical assessment based on official national and international statistical data for 2010–2025. Тhe study used methods of economic and statistical analysis.The results of the empirical analysis showed that internal migration is associated with a 25–30% increase in labor productivity in urbanized regions, and an increase in the share of highly qualified personnel in external migration from 31,8% to 38,8% increases the risk of a long-term negative impact on national innovation potential. The study results showed that migration contributes to increased territorial mobility of labor resources, partial improvement of the interregional balance, and acceleration of the urbanization process.In addition, there are risks such as the outflow of highly qualified personnel due to external migration, an increase in the infrastructure burden in large cities due to internal migration, and an increase in informal employment. The results obtained substantiate the importance of improving the mechanisms of effective management of internal migration, ensuring regional balanced development and comprehensive modernization of urban infrastructure. The results of the study will allow taking into account the migration factor in state and regional development policies, develop practical recommendations aimed at reducing the socio-economic gap between the regions and harmonizing the long-term economic development of the country.

The article examines the dynamics of life expectancy in the Republic of Kazakhstan and develops a scenariobased forecast of this indicator up to 2030. The relevance of the study is determined by the fact that life expectancy is an integral indicator reflecting the quality of socio-economic development, the state of public health, and the country’s resilience to external shocks. The purpose of the study is to forecast life expectancy in Kazakhstan, taking into account the influence of socio-economic, environmental, and shock-related factors. The methodological framework includes comparative analysis of indicator dynamics, Pearson correlation analysis, time-series modelling using the ARIMAX model, and scenario forecasting. The empirical base consists of annual data for 2014–2025 on life expectancy, GDP per capita, unemployment rate, and PM2.5 concentration. ACOVID dummy variable was introduced to account for the pandemic period. The results show that life expectancy in Kazakhstan is characterized by long-term growth, a sharp decline in 2020–2021, and subsequent recovery. The correlation analysis revealed a positive relationship between life expectancy and GDP, and a negative relationship with unemployment and PM2.5. The final ARIMAX(1,1,0) model showed a statistically significant negative relationship between unemployment and life expectancy, as well as a pronounced effect of the pandemic shock. The scenario forecast indicates that by 2030, life expectancy may reach 77.44 years under the baseline scenario, 79.18 years under the optimistic scenario, and 72.51 years under the pessimistic scenario. The findings highlight the importance of employment policy, reducing environmental risks, and strengthening the resilience of the public health system for Kazakhstan’s further demographic development.

Today, logistics is one of the main driving forces of the global economy and ensures the efficient functioning of global supply chains. In recent years, the concept of sustainable development, which emphasizes ecological balance and social responsibility, has become increasingly important in the logistics sector as well. Consequently, energy efficiency, waste reduction, minimizing environmental impact, and rational use of resources have become key priorities. To achieve these goals, modern technologies, particularly Artificial Intelligence (AI), are being widely implemented. AI enables the automation of logistics operations, real-time data analysis, and process optimization. This article explores ways to enhance the efficiency of logistics systems by integrating AI technologies with sustainable development principles. The main goal of the research is to identify the role of AI in improving the environmental, economic, and social performance of logistics systems. Key areas of analysis include route optimization, automation of warehousing and transportation operations, inventory management, demand forecasting, and supply chain digitalization. Research results show that AI-based solutions can increase logistics efficiency by an average of 20– 25%, reduce fuel consumption and carbon emissions, and shorten delivery time and costs. Furthermore, the experience of Kazakhstani logistics companies demonstrates the positive effects of AI implementation, such as faster operations, resource savings, and improved customer service quality. This study highlights the importance of AI technologies in achieving sustainable development in logistics and provides practical recommendations for their implementation.

The article provides an empirical and analytical assessment of Kazakhstan’s ability to transform its existing transport and logistics infrastructure into a competitive advantage within Central Asia. Based on a comparison of indicators for 2020–2024 and a case-study analysis, the authors demonstrate the country’s substantial infrastructural capacity-including an extensive railway network, port connectivity through the Caspian Sea, and key border crossings with China-which has supported a notable increase in transit volumes. The analysis of technological and institutional developments highlights progress in the digitalization of operations (electronic documentation and tracking platforms), partial railway electrification, and the expansion of renewable-energy initiatives. The authors show that the combination of digital traceability and technical modernization creates the foundations for the commercialization of low-carbon transport corridors; at the same time, several constraints are identified, including uneven electrification, the need for accurate verification of energy consumption and the share of renewables, as well as fragmented regional digital integration, which collectively limit the full realization of this potential. The results have practical significance for policy formation and investment strategies in the field of transit logistics.

This article investigates the barriers and prospects for integrating blockchain technology into supply chain management in the context of Eurasian trade. The relevance of the study stems from the high level of documentary burden and substantial transaction costs in cross-border logistics operations among EAEU member states, which constrains the region’s competitiveness in global markets. Based on a systematic review of 36 sources, content analysis of EAEU regulatory documents, and an expert survey (n=18), 24 barriers were identified and classified into four categories: technological, legal, institutional, and financial. Using the Analytic Hierarchy Process (AHP), technological barriers were found to be the most critical (weight 0.467), a finding attributed to the absence of standardized interoperability protocols among supply chain participants. Applying an original Total Transaction Cost (TTC) model, the potential effect of blockchain adoption was quantified: cost reduction amounts to 67.6% (from USD 1,700 to USD 550 per TEU), with the aggregate economic impact along the Almaty–Moscow corridor estimated at USD 977.5 million annually. An original Blockchain Compatibility and Readiness Index (BCR-Index) was developed to assess countries’ preparedness for blockchain adoption; Russia (71.8) and Kazakhstan (65.4) demonstrate the highest readiness among EAEU member states, with the Kazakhstan–Russia corridor identified as the priority site for pilot implementation. The findings provide concrete quantitative evidence supporting the economic rationale for integrating blockchain technologies into logistics systems and establish a scientific basis for strategic decision-making at both the corporate and governmental levels. The practical significance of the study lies in formulating evidencebased recommendations for regulators, logistics operators, and researchers engaged in the digital transformation of the EAEU transport and logistics complex.

The study is devoted to the analysis of problems and opportunities for diversifying the economy of Kazakhstan, with the aim of reducing its dependence on oil revenues. In the context of global economic changes and fluctuations in hydrocarbon prices, strategic diversification is a key aspect to ensure the sustainable development of the country. The research methodology covers quantitative and qualitative analysis of the current state of the economy, and also includes modeling of various development scenarios based on potential changes in the global economy and the oil market. The analysis shows that diversification can significantly increase the economic stability of Kazakhstan, reducing the risks associated with fluctuations in world oil prices. An important role in the diversification process is played by strengthening the institutional environment and developing a private sector capable of introducing innovations and improving the competitiveness of the economy. The results of the study offer concrete recommendations for the formation of policies that could promote greater inclusion of various sectors of the economy in the processes of innovative development and export activities, which, in turn, will reduce dependence on oil revenues and contribute to long-term economic growth.

In the context of increasing global economic instability, growing social inequality, and demographic challenges, the issue of state regulation of the population’s standard of living is gaining particular relevance. The effectiveness of social policy and quality of life are largely determined by the scale and efficiency of government intervention, as well as by the institutional capacity of the state to ensure socio-economic stability during periods of crisis. Historical experience of developed countries demonstrates that the role of the state in stabilizing incomes, employment, and access to basic social services intensifies during economic and social shocks. The purpose of this study is to analyze foreign models of state regulation of the population’s standard of living and to identify possibilities for adapting selected mechanisms to the conditions of the Republic of Kazakhstan. The study examines the evolution of theoretical approaches to social policy, compares liberal, continental, and social-democratic welfare models, and evaluates socio-economic indicators across countries with different institutional systems. The scientific significance of the study lies in its comprehensive comparative analysis of mechanisms for regulating living standards, taking into account institutional, fiscal, and social constraints characteristic of transition economies. The study substantiates the feasibility of developing a hybrid model for Kazakhstan that combines market-based incentives, elements of industrial and social policy, and targeted social support instruments. The practical significance of the research is reflected in the applicability of its results to improving socio-economic development programs6 strengthening social policy priorities, and enhancing mechanisms for regulating incomes, employment and healthcare.

In the context of global digitalization, the creative economy is becoming a significant driver of economic diversification and labor market transformation. This study aims to develop a scenario-based forecasting model for the development of Kazakhstan’s creative economy, taking into account technological changes up to 2030. The empirical basis includes data on the current state of the sector, which accounts for approximately 3.5% of total employment (around 310 thousand people) and 2.7% of gross domestic product, as well as the results of a quantitative assessment of digitalization effects, indicating that a 1% increase in ICT service exports leads to an approximately 1.541% growth in the gross value added of creative industries. The research methodology integrates foresight approaches, scenario analysis, and econometric time series modeling. Three alternative development scenarios are proposed: “Innovative Breakthrough,” “Moderate Adaptation,” and “Technological Lag,” reflecting different trajectories of sectoral evolution. The results demonstrate a wide range of possible outcomes: under the innovative scenario, the share of creative employment may reach 5.8–6.2% by 2030, whereas the pessimistic trajectory suggests stagnation at 3.2–3.5%. The study identifies key success factors, including the development of digital infrastructure, reduction of regional disparities, modernization of the education system, and effective public policy support for creative industries. The practical significance lies in the formulation of implementation mechanisms and policy recommendations aimed at fostering the development of the creative economy and labor market.

This research investigates the factors, obstacles, and approaches influencing the adoption of sustainable entrepreneurship within Kazakhstan’s hotel industry, utilizing data from Almaty, Astana, and Shymkent. This study used an explanatory sequential mixed-methods approach, integrating quantitative surveys from 158 hotel managers (utilizing SPSS 28.0 and SmartPLS 4) with 18 semi-structured interviews processed with NVivo 14. Multiple regression analysis (R² = 0.413, F = 21.67, p < 0.001) reveals operational cost savings (β = 0.38) and government regulations (β = 0.24) as the sole significant predictors of sustainability adoption, whereas competitive advantage, customer demand, and personal values are deemed non-significant. Primary obstacles encompass substantial initial capital expenditures, knowledge gaps, and restricted access to green financing. ANOVA analysis indicates significant stratification by hotel star rating, with five-star establishments markedly surpassing three-star hotels in energy efficiency, waste reduction, and local supplier participation. Research reveals that the adoption of sustainability in Kazakhstan is predominantly driven by economic rationality rather than ethical or environmental considerations, with institutional frameworks both facilitating and hindering advancement. The study introduces a Context-dependent Phased Transformation (CPT) model that conceptualizes sustainability transition as a non-linear, iterative process influenced by institutional readiness, financing conditions, and market maturity, providing both theoretical and practical insights for hotel entrepreneurs and policymakers in emerging economies.

The aim of the study is to analyze sustainable development indicators affecting the tourism industry of our country and determine their impact. The objectives of the article are to analyze publications of international organizations and works of world scientists, to provide the author’s definitions of the concepts of tourism and tourism resources, to identify and study indicators influencing the tourism industry, to obtain the results of the study, draw conclusions by calculating the ratio of the weight and absolute value of each indicator with the arithmetic mean of the selected indicators, and also conduct a review of the scientific literature devoted to the research of world scientists. An analysis of the indicators that have a dominant influence on the tourism industry, giving new impetus to economic growth, as well as the synergistic and multiplier effect of each of them increases the relevance of the article. When analyzing a scientific article, authors use several scientific methods to achieve the goals and objectives set in the article. An analysis and summary of scientific works by scientists from near and far countries, the weight of each indicator by the arithmetic mean value based on data from the Statistical Agency of the Republic of Kazakhstan and the Taldau Analytical Information System for 2020–2025. To sum up the article, it can be said that as a result of the intensive implementation of measures aimed at developing the country’s tourism industry, there is a positive trend in the development of tourism in our republic.

The study aims to examine the specifics of the development of digital tourism and excursion attractiveness in the Republic of Kazakhstan. The paper analyzes the main barriers to the digital transformation of tourism, examines political, economic, social, and technological factors, and suggests possible ways to overcome them, taking into account the national characteristics of the industry’s development. The study examines the theoretical aspects of the development of tourism and excursion activities in the context of the active digitalization of the urban environment of large megacities, and assesses the impact of the external environment on the formation of digital tourism infrastructure. Based on PEST analysis, key factors determining the attractiveness of digital infrastructure, the degree of integration of information systems, staffing, and institutional conditions are identified. Particular attention is paid to the problems of data fragmentation, digital inequality, and a shortage of specialists, which limit the implementation of modern digital solutions in the tourism sector. The article substantiates priority areas for increasing the attractiveness of digital tourism and excursion infrastructure related to the formation of a unified digital ecosystem, the development of big data analytics, the improvement of digital business competence, and the stimulation of the introduction of smart technologies in the urban tourism environment. The results obtained can be used in the development of tourism digitalization programs, as well as in the practical activities of management bodies and tourism industry entities in the megacities of Kazakhstan.

Organised travel for children and adolescents has long outgrown the boundaries of simple leisure: today it is perceived as an investment in human capital, a tool for civic education, and a driver of regional development. Despite this, the segment remains poorly studied in Kazakhstani scholarship from a quantitative perspective. This article addresses that gap: its aim is to identify and measure the socio-economic factors determining the scale and dynamics of children and youth tourism in Kazakhstan over 2020–2025. The study draws on official statistics from the Bureau of National Statistics of the Republic of Kazakhstan and combines correlation-regression analysis, regional comparative analysis, and SWOT methodology. The four-factor regression model explains 84.7% of the variation in tourist service volume; the key determinants are per capita GDP, the demographic potential of youth, state allocations for education, and tourist infrastructure. All predictors are significant at p<0.01, with no violations of OLS assumptions. By 2025, industry indicators had exceeded pre-pandemic levels by 74% in service volume and 29% in employment; however, a pronounced territorial concentration persists, with the two largest cities accounting for over 45% of the segment’s turnover. Regional analysis reveals the unrealised potential of East Kazakhstan and Almaty regions. The scientific novelty lies in developing the first verified econometric model for this segment. The practical outcome consists of recommendations on state regulation, subsidisation, and infrastructure development for sectoral programmes at national and regional levels.

This study empirically examines the effectiveness of agricultural subsidies in enhancing farm productivity in the Zhambyl region of Kazakhstan over the 2010–2025 period. Despite substantial public expenditure and the widespread use of subsidies as a core instrument of agricultural policy, their actual contribution to productivity growth remains contested. Using a quantitative research design, this study analyzes panel data from 34 farms (510 observations) obtained from the Ministry of Agriculture of the Republic of Kazakhstan. A two-way fixed effects regression model, validated through the Hausman test, is employed to estimate the relationship between subsidy amounts and farm productivity, controlling for land area and fixed assets. Diagnostic tests confirm the model’s compliance with key classical regression assumptions. The results reveal that agricultural subsidies have no statistically significant effect on farm productivity (β = 0.228, p > 0.05). This finding remains robust across sub-period analyses (2010–2015 and 2016–2025), indicating that increased subsidy volumes have not translated into measurable productivity gains. The study identifies structural inefficiencies in subsidy design, including disproportionate allocation to large farms, weak conditionality, and a focus on cost compensation rather than performance stimulation. These findings contribute to the growing body of evidence questioning the efficacy of untargeted financial support and underscore the urgent need for policy reform. The paper advocates for a transition toward “smart,” region-specific, and results-based subsidy mechanisms linked to technology adoption, sustainable practices, and robust monitoring frameworks. The study provides actionable recommendations for policymakers seeking to enhance the efficiency and sustainability of public spending in Kazakhstan’s agricultural sector.

As Kazakhstan’s fiscal space narrows, the sectoral structure of public capital allocation becomes critical. This study constructs and solves a network optimization model using Kazakhstan’s official data to allocate limited state capital across sectors, maximizing economic diversification under budget constraints. The methodology integrates input-output analysis, production network analysis, and constrained optimization. The empirical basis comprises Kazakhstan’s 2020–2023 symmetric input-output tables, used to calculate output multipliers, Rasmussen linkages, and centrality indicators for 68 product types aggregated into broad sectors. Diversification is operationalized via the Herfindahl-Hirschman Index of export concentration. The optimization model incorporates diminishing marginal returns, where sector shares in a fixed budget are decision variables, and sector contributions are determined by export-adjusted weights. Calculations show that trade, business services, and metallurgy possess the greatest network leverage, while transportation occupies a middle position; meanwhile, the high centrality of resource sectors does not imply a contribution to diversification. The model’s solution systematically diverges from the actual investment structure: the extractive sector is overinvested relative to its diversification impact, while several non-extractive sectors remain underfunded. The scientific novelty lies in deriving sectoral priorities not qualitatively, but as the solution to a formalized optimization model based on measurable, reproducible network parameters.

This research study is aimed at providing a comprehensive theoretical and practical analysis of the personal taxation system in the Republic of Kazakhstan. Particular emphasis is placed on the role of Personal Income Tax (PIT) in ensuring tax equity and fiscal sustainability. The study examines Kazakhstan’s taxation practices through a comparative perspective, juxtaposing them with the tax systems of developed countries (the United States, Germany, and France) and developing countries (Kyrgyzstan, Uzbekistan, Tajikistan, and Turkmenistan). Within this framework, the structural features of taxation, tax rates, administrative mechanisms, and tax incentives are systematically analyzed. Particular attention is devoted to personal income taxation in the country, with data collected and analyzed for the past five years, focusing specifically on regions that contribute substantial volumes of tax revenues to the state budget. In addition, the study examines more than ten countries that do not impose a personal income tax, providing an analytical overview of their principal sources of public revenue. As a result of the international comparative analysis, the institutional strengths and systemic weaknesses of Kazakhstan’s taxation system are identified and critically assessed. Furthermore, the study addresses pressing issues such as the shadow economy, tax filing compliance, tax evasion, and the potential introduction of a progressive taxation model. A progressive taxation system entails an increase in the tax rate as the level of income rises. In small member states of the European Union, such a model contributes not only to the stabilization of budget revenues but also to the reduction of social inequality and the strengthening of social justice within society.

Amidst global macroeconomic instability, tax policy is evolving from a mere fiscal tool into a critical mechanism for regulating household income and social equity in developing economies. This research presents a comparative analysis of tax reforms in the Republic of Kazakhstan and the Republic of Turkey during the 2024–2026 period, focusing on their divergent impacts on disposable household income. The primary objective is to evaluate the socioeconomic consequences of structural changes in Tax Codes, specifically scrutinizing Kazakhstan’s transition to a progressive Personal Income Tax scale and Turkey’s indexation policies under hyperinflation. The study’s main directions involve a quantitative assessment of “fiscal drag,” the “bracket creep” phenomenon, and a comparative calculation of the tax wedge in both jurisdictions. The scientific significance lies in uncovering the latent mechanisms by which nominal wage growth in high-inflation environments results in a hidden increase in the tax burden. Practically, the work assesses specific risks for the middle class and wage earners arising from the interplay of inflation and static tax thresholds. The value of this research consists of a novel comparative assessment of two distinct fiscal strategies: planned structural fiscal adjustments involving VAT hikes in Kazakhstan versus adaptive crisis management in Turkey. The empirical findings offer objective baseline guidelines for state authorities to dynamically adjust social tax parameters and indexation thresholds to mitigate adverse shocks on real household income.

In the context of heightened volatility of regional public revenues, policymakers increasingly need diagnostic tools that distinguish short-term fluctuations in receipts from a territory’s underlying ability to generate tax revenues given its economic base. This paper estimates the tax capacity of East Kazakhstan Region for 2020–2024 and quantifies the gap between actual tax collections and a representative (“normal”) revenue level under comparable economic fundamentals. The study aims (1) to compute tax capacity and the associated indicators of tax effort and tax gap, and (2) to identify which aggregated tax groups account for the largest deviations between actual and potential revenues. The empirical dataset combines open administrative information from the State Revenue Committee of the Ministry of Finance of the Republic of Kazakhstan (budget classification groups 1xx) with official regional socioeconomic indicators from the Bureau of National Statistics. Tax capacity is measured using two complementary approaches: a benchmark (quota-capacity) method based on a representative tax-to-GRP ratio, and a structural (base-linked) method that links major tax groups to macro proxies of tax bases (a payroll proxy, retail turnover, and GRP). The results reveal a pronounced divergence in 2024: despite growth in key macro proxies, actual tax revenues declined and tax effort dropped to 0.64–0.71, implying a tax gap of approximately KZT 132–180 billion. A decomposition shows that the gap is driven primarily by taxes on goods, works, and services (group 105) and, to a lesser extent, by personal income-related revenues (group 101). The paper’s contribution lies in a reproducible, open-data framework for subnational tax capacity assessment with structural gap decomposition. The findings can support fiscal sustainability monitoring and prioritize analytical attention to the most volatile revenue blocks, while acknowledging accounting and institutional limitations (e.g., netting effects for indirect taxes).

The article examines the development of the mortgage lending market in Kazakhstan and the impact of financial volatility factors on mortgage loans. The main objective of the study is to assess the influence of inflation, the policy interest rate, and the exchange rate on the volume of mortgage lending, as well as to identify directions for ensuring housing market stability. Official data from the National Bank of the Republic of Kazakhstan, the Bureau of National Statistics, and second-tier banks were used in the study. The study employed statistical, correlation, regression, vector autoregression (VAR), and cointegration methods of analysis. The econometric modeling results showed that increases in inflation and interest rates have a negative impact on mortgage lending volumes. It was found that a 1% increase in inflation reduces mortgage loan volumes by an average of 0.7–0.9%. In addition, exchange rate instability was proven to increase construction costs and contribute to rising housing prices. The study found that the Otbasy Bank housing savings system is a relatively stable model under conditions of financial volatility. Based on a deposit-based savings mechanism, this system helps maintain the stability of mortgage lending. Accordingly, practical recommendations were developed, including the introduction of an inflation-adjusted government premium system, differentiation of down payment requirements, and the development of a digital mortgage scoring system. The results show that financial volatility significantly affects the dynamics of mortgage lending. An increase in interest rates reduces demand for mortgage loans and slows activity in the housing market. Rising inflation decreases real household incomes and limits long-term borrowing capacity. Exchange rate fluctuations raise banks’ funding costs and increase credit risks. The cointegration analysis confirms the existence of a long-term equilibrium relationship between mortgage lending volumes and key macroeconomic indicators. Impulse response functions demonstrate that the effects of financial shocks persist for several quarters. Government support programs play an important role in stimulating the market; however, their effectiveness depends on macroeconomic stability and the quality of risk management in the banking sector. The study confirms the multiplicative effect of mortgage lending on economic growth. The findings of the study have practical significance for improving the mortgage lending market, increasing housing affordability, and shaping public policy aimed at reducing risks in the financial sector.

Investments in population health are considered a key factor of sustainable regional development. They are closely linked to human capital reproduction, demographic stability, and social resilience. Under conditions of territorial inequality, the effectiveness of such investments varies significantly across regions. This is especially typical for territories characterized by a pronounced core – periphery structure. In Kazakhstan, the regional dimension of health investment efficiency remains an important academic and policy issue. The purpose of this study is to assess the role of investments in population health in ensuring sustainable regional development. The research focuses on East Kazakhstan region. Special attention is paid to Ust-Kamenogorsk as the regional center as a concentration point of medical resources. The study analyzes investment dynamics, resource provision, and performance indicators of the healthcare system from the period 2019–2025. The empirical basis includes official statistical data from the Bureau of National Statistics and the Ministry of Health of the Republic of Kazakhstan. The research methodology combines dynamic, comparative, and structural analysis. It also, includes intraregional comparisons between the region as a whole and the regional center. The scientific contribution of the study lies in identifying the limited equalizing effect of healthcare investments at the regional level. The results show that increased funding contributes to the stabilization of healthcare system functioning and supports the recovery of selected performance indicators after the pandemic period. However, the territorial concentration of medical infrastructure and healthcare personnel reduces the social returns of investments in peripheral areas. The value of the study consists in substantiating institutional and territorial constraints that limit the effectiveness of social investments. The practical significance of the results is related to their potential use in designing targeted regional healthcare policies. These policies are aimed at improving access to medical services and reducing intraregional disparities.

Relevance: amid the transformation of public governance, the choice of optimal mechanisms for the budget financing of higher education institutions (HEIs) is gaining scholarly and practical importance, since the funding model directly shapes universities’ incentives to improve quality, research, and innovation. Purpose: to systematize the basic models and mechanisms of higher education financing used in global practice and to determine the position of the Kazakhstani system within this typology. Methodology: the study draws on comparative, structural, and institutional analysis. The theoretical framework distinguishes the institutional model (the HEI as the object of funding) and the demand-based model (the student as the object of funding), with three generations of mechanisms within the former: line-item, formula-based, and performance-based funding (PBF). Scientific significance: the study systematizes current global practice (2020–2026) of HE funding models and offers an original positioning of Kazakhstan’s state educational order within the international typology. Value: the research identifies specific systemic gaps between Kazakhstani practice and international standards across key parameters, namely the share of HE expenditure in GDP, the level of financial autonomy of HEIs, and the presence of performance-based funding mechanisms. Practical significance: the findings can be used in developing policy decisions to improve the financing of Kazakhstani HEIs in line with the 2023–2029 Concept, as well as in teaching the economics of education and public administration.

In the context of the transformation of the financial system of the Republic of Kazakhstan, the insurance market is gaining particular importance as an instrument for ensuring economic stability and social protection. The purpose of this study is to conduct a comprehensive analysis of the dynamics of the insurance market development in Kazakhstan for the period 2017–2025, to identify the key factors determining its efficiency, and to develop recommendations for enhancing the sustainability of the insurance sector. The study employs comparative, statistical, and coefficient analysis methods, as well as institutional and systemic approaches, which made it possible to examine the relationship between insurance premiums, claims, profitability, and macroeconomic indicators. The results of the analysis demonstrate the progressive development of the insurance market, reflected in the growth of insurance premiums and claims, an increase in insurance density and penetration, and the maintenance of positive industry profitability. The main drivers of growth include digitalization, regulatory reforms, and the expansion of insurance products, while the limiting factors are a low level of insurance culture and dependence on macroeconomic fluctuations. The scientific novelty of the study lies in a comprehensive assessment of the efficiency of the insurance sector through a system of analytical coefficients. The practical significance of the work lies in the possibility of applying the results to improve state policy and strategies for the development of Kazakhstan’s insurance market.

Artificial intelligence (AI) in today’s reality is no longer merely a technological tool – it is becoming the centerpiece of modern innovation management models. In Kazakhstan, 2026 has been officially declared the Year of Digitalization and Artificial Intelligence, lending the topic particular strategic significance. Meanwhile, existing theoretical models were developed for advanced markets and do not account for the specificities of transition economies. The purpose of this study is to conduct a systematic theoretical and methodological review of the international scholarly literature at the intersection of AI and enterprise innovation management, with a focus on the applicability of global approaches to the Kazakhstani context. The paper analyzes six theoretical lenses: the resource-based view, dynamic capabilities, diffusion of innovations theory, the TOE framework, the institutional perspective, and digital maturity models. The review covers publications from 1983 to 2026 retrieved from Scopus, Web of Science, and regional journals. A theoretical gap is identified between global models’ postulates about the decentralizing effect of AI and the phenomenon of “digital centralism” in Kazakhstan. Based on critical analysis, a research framework – “AI Resources – Dynamic Capabilities – Institutional Filter – Innovation Outcomes” – is proposed, which for the first time directly incorporates the institutional context of a transition economy. Six testable hypotheses are formulated for subsequent empirical research on a sample of Kazakhstani enterprises. The findings are of interest to innovation management researchers, digital transformation policymakers, and enterprise management in Kazakhstan.

In the context of digital marketing development, effective management of consumer attention is becoming a crucial task for small and medium-sized enterprises (SMEs). Traditional methods of marketing analysis do not fully reveal the mechanisms of unconscious consumer perception, which increases the relevance of applying neuromarketing approaches. The aim of this study is to evaluate the impact of video content structure (human presence and emotional dynamics) on the emotional and physiological responses of consumers. During the study, based on the iMotions platform and using FaceReading and GSR methods, a comparison of two types of videos was conducted: with and without human presence. The research results demonstrated that video content featuring a human increases emotional engagement, and that the change in emotions over time significantly affects consumer interest. The scientific novelty of the work lies in considering video content not as static, but as an emotional process evolving over time. The research results can be applied to improve digital marketing strategies, particularly to enhance the advertising effectiveness of small and medium-sized enterprises. The practical significance of the work consists in substantiating the role of emotional dynamics and anthropomorphic elements in the creation of video advertising.

The article investigates the phenomenon of emotional identification with a tourism destination brand, using Kazakhstan’s visual content as a case study. The main objective is to analyze participants’ emotional connection to the destination brand through neuromarketing methods, emphasizing the need to move beyond traditional subjective evaluations toward objective measurements of unconscious consumer responses. The research is grounded in an interdisciplinary methodological approach that combines theoretical analysis with an empirical neuromarketing experiment. Fifteen participants took part in the study and were shown an image-building promotional video aimed at presenting the tourism potential of the destination. During the viewing process, their emotional reactions were recorded in real time using Face Reading software supported by specialized hardware tools, which made it possible to capture both conscious and subconscious emotional responses to visual stimuli.The spectral analysis made it possible to identify the multidimensional nature of brand perception, illustrating how various visual elements generate different emotional reactions among viewers. The scientific and practical value of this research is connected with a deeper understanding of emotional identification in marketing communication processes and with improving destination branding strategies. The findings confirm that the use of visual codes with opposite emotional valence contributes to the creation of a more dynamic, memorable, and emotionally attractive brand image. The practical value includes improving the communicative power of advertising content, guiding the development of marketing campaigns, and promoting Kazakhstan’s tourism services internationally. By integrating neuromarketing insights with visual content analysis, the study provides actionable recommendations for creating emotionally compelling materials that strengthen brand loyalty and enhance the overall tourist experience.

In the context of accelerated digitalization and increasing fragmentation of the media environment, marketing communications are undergoing significant changes, which necessitates a revision of traditional approaches to

brand promotion. Modern consumers interact with brands through multiple online and offline channels, expecting consistency of messages and a holistic communication experience. The purpose of this study is to justify the need for integrating traditional and digital marketing communications and to identify the key mechanisms of their coordinated use. The paper examines the main theoretical approaches to integrated marketing communications, analyzes the functional differences between traditional and digital promotional tools, and systematizes the mechanisms of their integration. The scientific significance of the study lies in expanding the theoretical understanding of the role of communication integration in the context of digital transformation. The practical significance is determined by the possibility of applying the results in the development of brand communication strategies and media planning.

The article analyzes the relationship between citizens’ critical consciousness and support for state cultural policy aimed at the modernization of public consciousness in the Republic of Kazakhstan. The empirical basis is the data from an author-designed survey of the adult population (N = 188). Using regression analysis, the study evaluates the relationships between the cleaned index of critical consciousness (CC_clean), support for modernization projects in the cultural sphere, and the perception of cultural policy as a factor of modernization, while controlling for gender, age, educational level, type of place of residence, and type of employment. To test the robustness of the results and address the comment regarding possible substantive overlap between the predictor and the dependent variables, a cleaned index of critical consciousness was constructed, including only those items not related to the assessment of cultural policy itself. The results show that the relationship between critical consciousness, support for modernization initiatives, and a positive assessment of the modernization role of cultural policy remains significant in both linear and ordinal models and cannot be reduced to differences in socio-demographic composition. The article offers recommendations for improving cultural policy, focusing on the transition from a transmission-based to a dialogic model of engagement with the population, the development of formats for active citizen participation in cultural life, the integration of themes of social inequality and civic responsibility into cultural programs, as well as the institutionalization of measuring critical consciousness within the system for monitoring the effectiveness of cultural policy.

The digitalization of the social sphere is increasingly recognized as a key dimension of modern public administration, particularly within the framework of public value theory. The main objective of the research is twofold: first, to conduct a bibliometric analysis of the digitalization of the social sphere as a public value within public administration from 2012 to 2026; second, to test and refine the PRISMA methodology in combination with Big Data tools, including Scopus and OpenAlex databases. The study focuses on identifying publication dynamics, geographical and institutional structures, key thematic clusters, and dominant theoretical concepts shaping the research field. The scientific significance of the study lies in its systematic mapping of an emerging interdisciplinary domain that integrates public administration, digital governance, and social policy. The findings confirm the formation of a global, polycentric research landscape characterized by strong international collaboration and thematic diversity. The study also demonstrates the expansion of the public value concept into areas such as digital inclusion, digital public services, and sustainable development. The key contribution of this work is the development and validation of a universal methodological framework that combines PRISMA filtering, API-based data extraction, and bibliometric visualization. This approach enhances the transparency, reproducibility, and analytical depth of bibliographic reviews. Practically, the results can be used by researchers and policymakers to better understand global research trends, design evidence-based policies, and apply advanced bibliometric methods across various fields of study.

The Republic of Kazakhstan sets the goal of achieving carbon neutrality by 2060 and the transition to a green economy. The aim of this work is to study the impact of energy intensity, the use of renewable energy sources and the launch of an emissions trading system (ETS) on carbon intensity in the Republic of Kazakhstan for the period 1992– 2022. To achieve this goal, the method of autoregressive distribution lags was used. The research makes scientific contribution by considering carbon intensity as a target variable in econometric analyses. The practical importance lies in integrating in the model the ETS dummy variable as a determinant of the explained variable. The results of the study showed that there is a long-term relationship between the selected variables, and energy intensity is the main driver of carbon intensity in the long term. The impact of RES has not been statistically confirmed. Verification of the results by including GDP per capita variable, as controlling variable confirmed the correctness of the conclusions of the base model. The results of the work emphasize the importance of enhancing the design of the emissions trading system and improving energy intensity to increase its effectiveness in reducing the carbon intensity of the country’s economy.

Against the backdrop of a global climate agenda and the widespread adoption of sustainable development concepts, ESG (Environmental, Social, Governance) principles are becoming the central criteria of international investment decisions. The purpose of the study is to systematically analyse ESG regulatory models established in the EU, the USA and the Asia-Pacific region, identify criteria for their effectiveness, and propose a hybrid regulatory model for Kazakhstan. The main research directions include: comparative analysis of mandatory and voluntary disclosure standards; examination of the content and effectiveness of SFDR, CSRD, EU Taxonomy and ISSB S1/ S2 standards; case-study analysis of leading corporations’ ESG practices (Ørsted, DBS Bank); and assessment of Kazakhstan’s regulatory environment based on SWOT analysis. The scientific significance of the work lies in developing a new typology of ESG regulatory models through a ‘mandatory space – institutional capacity’ matrix that accounts for regional specifics. Regression analysis confirmed a positive relationship between the mandatory nature of ESG regulation and company performance (β=0.42, p<0.01); the level of institutional capacity acts as a moderating factor. The practical significance lies in proposing a phased roadmap for implementing a hybrid regulatory model for 2024–2031 for the AIFC, ARDFM and major companies. The results make a concrete contribution to improving public policy in the field of green finance development.

This article presents an analysis of the structure of imports of the Republic of Kazakhstan from the People’s Republic of China for the period 2019–2025. The aim of the study is to identify key structural changes in import flows and to assess the degree of their concentration. Particular attention is paid to the commodity and sectoral structure of imports, as well as to the formation of economic risks associated with increasing dependence on external supplies. The empirical basis of the study includes data from the Bureau of National Statistics of the Republic of Kazakhstan and the international UN Comtrade database. The research employs structural, comparative, and coefficient-based analytical methods. The Herfindahl–Hirschman Index (HHI) is used to quantitatively assess concentration, allowing for the evaluation of the extent to which import flows are concentrated within a limited number of commodity groups. The results show that Kazakhstan’s imports from China are characterized by steady growth alongside structural transformation. An increase in the share of machinery and equipment, transport vehicles, and other technologically significant categories has been identified. At the same time, the share of traditional consumer goods is decreasing. The scientific novelty of the study lies in substantiating the relationship between structural transformation of imports and the formation of economic risks. The practical significance of the study lies in the possibility of applying the results in the development of policies aimed at import diversification, reducing dependence on a single trading partner, and ensuring sustainable foreign economic policy.

Modern energy systems face the challenge of balancing tariff efficiency with social fairness. This study aims to identify the economic and behavioral factors influencing household adaptation to time-of-use (TOU) electricity tariffs in Almaty, Kazakhstan. The main objective is to empirically determine the key determinants of consumers’ willingness to adopt time-differentiated tariffs. The research is grounded in behavioral economics principles, and data analysis was conducted using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach. A survey of 388 respondents revealed that technological readiness, perceived fairness, and institutional trust are the primary drivers of behavioral intention to adopt TOU tariffs. Risk aversion negatively affects adaptation, reflecting consumer caution toward tariff changes. The environmental concern variable was statistically insignificant and excluded from the final model. The findings emphasize the importance of strengthening technological readiness, fairness, and trust to ensure the success of tariff reforms and contribute to advancing behavioral approaches in energy economics.

The study proposes an integrated analytical framework for assessing the competitiveness of service enterprises based on multi-criteria evaluation, inflation-adjusted price analysis, and time-series forecasting. To account for price dynamics, inflation data for 2012–2025 were used to calculate cumulative inflation coefficients and reconstruct historical price trends. Competitiveness was assessed using an integral indicator that aggregates price and non-price factors, including pricing policy, range and quality of services, discount systems, frequency of visits, and brand image, enabling an objective comparison of enterprises. Revenue forecasting for 2026–2030 was performed using the ARIMA model, allowing the identification of medium-term development trends under changing market conditions. The results demonstrate that low pricing represents only a short-term competitive advantage, while sustainable market leadership is achieved through the balanced development of multiple competitiveness parameters. Unlike traditional descriptive competitiveness assessments, the proposed approach includes a formalized optimization component that identifies the combination of managerial parameters maximizing the enterprise competitiveness index under economic and operational constraints. The study’s practical significance lies in developing a versatile competitiveness index, adaptable across industries, to guide strategic planning, optimize resources, strengthen market positions, and enhance investment attractiveness.

In the context of globalisation and digital transformation, human resource management (HRM) systems have become a strategic asset determining organisational competitiveness. This study provides a comprehensive analysis of transformational processes in HRM systems across organisations in the Republic of Kazakhstan. The research aim is to periodise the evolution of HR systems since independence, identify key challenges in the digital economy environment, and assess strategic opportunities for organisational HRM transformation. The scientific significance of the work lies in the absence of comprehensive theoretical research on HR transformation in a post-Soviet context. The scientific novelty consists in developing an original four-stage periodisation of HR system transformation in Kazakhstan and a Digital HR Maturity Index (DHRMI) methodology adapted to post-Soviet economies. A significant association between People Analytics adoption and staff retention was empirically confirmed (r=0.67; p<0.01) on a sample of 78 Kazakhstani organisations. The practical value consists in developing a set of indicators for assessing the level of HR system digitalisation, alongside a strategic recommendations package for medium and large enterprises. Specific implementation mechanisms are proposed: HR digitalisation roadmaps, People Analytics upskilling programmes for HR professionals, and government support tools for SMEs through tax incentives and digital platforms (eHRMS). The findings are applicable by public authorities, business associations, and corporate HR departments. Overall, the study contributes to defining the modernisation trajectory of HRM systems in Kazakhstani organisations and to the formulation of evidence-based practical recommendations.

The purpose of the study is to analyze the relationship between human capital and talent management in the context of the knowledge economy, as well as to identify factors influencing the effective use of labor potential. The research uses methods of economic and statistical analysis, comparative analysis of international practice and correlation modeling of labor market indicators. The scientific novelty of the research lies in the development and testing of the integral human capital index, which quantifies the state and dynamics of Kazakhstan’s human resource base in the knowledge economy. This approach considers talent management not only as a set of personnel practices, but also as an important element of state socio-economic policy that affects the sustainability of the national economy. The analysis showed that the processes of digitalization and the stabilization of the labor market contribute to the growth of human capital in the medium term. At the same time, insufficient spending on research and development remains the main obstacle to the transition to an innovation-based knowledge economy. Predictive modeling confirms the continuation of the positive dynamics of the integral indicator in the context of further development of digital competencies and institutional strengthening of talent management systems. The results obtained confirm that talent management is a strategic tool for the development of human capital in the knowledge economy. The integration of educational policy, labor market regulation and corporate personnel management practices is a prerequisite for sustainable economic growth and long-term competitiveness.

This study examines how small and medium-sized enterprise (SME) entrepreneurs in the Akmola region perceive government support measures and identifies systemic barriers that hinder business development, including within the social entrepreneurship sector. The methodological framework is based on two focus group discussions involving representatives of various business types, including social enterprises. The use of purposive sampling and semistructured discussions allowed for a thorough understanding of entrepreneurs’ subjective assessments, identification of key problem areas, and analysis of their interactions with government support instruments. The data were analyzed using thematic analysis following the approach of Braun and Clarke, which allowed the identification of nine major thematic problem areas, including administrative barriers, difficulties in accessing credit, grant financing constraints, infrastructure limitations, and challenges specific to social entrepreneurship. The findings suggest that official statistics on the number of SMEs do not always reflect their actual economic sustainability, while existing institutional support mechanisms are often perceived as formal, fragmented, and insufficiently accessible, particularly for microenterprises and rural businesses. Social entrepreneurs, in particular, emphasize the high value of obtaining official status but highlight excessive bureaucratic requirements and the limited applicability of current eligibility criteria. The scientific significance of the study lies in conducting a qualitative regional analysis of the development of SMEs and social entrepreneurship in the Akmola region, which allows us to supplement existing quantitative studies with empirical data on the practical experience of entrepreneurs. From a practical perspective, the results may inform policymakers and regional development institutions by highlighting critical gaps between formal support mechanisms and real business needs. The study offers targeted recommendations aimed at improving the transparency, accessibility, and adaptability of government support instruments, with particular attention to the needs of microbusinesses and rural areas, thereby contributing to more inclusive and sustainable regional economic development.

The increasing instability of the global economy and the growing impact of external shocks have intensified the importance of economic resilience at the regional level. This issue is particularly relevant for Kazakhstan due to the presence of single-industry towns, whose economies are characterized by high sectoral concentration, dependence on core enterprises, and sensitivity to external economic changes. This creates the need for a more accurate assessment of the factors influencing their stability. The aim of the study is to identify the key factors of economic resilience of single-industry towns in Kazakhstan based on a quantitative analysis of socio-economic indicators. The study is based on official statistical data for 2019–2025 for the towns of Zhezkazgan, Temirtau, and Ridder. Correlation and regression analysis methods are applied to assess the strength and direction of factor influence on investment activity. The results reveal a strong positive relationship between investment in fixed capital and wage levels, as well as a significant negative relationship with unemployment. The effect of employment is less pronounced. The findings also show that the strength of factor influence varies across towns, reflecting differences in their economic structure and adaptive capacity. The scientific contribution lies in the application of a quantitative approach to assess economic resilience at the city level. The practical significance of the study is related to the use of the results in regional policy aimed at increasing investment activity, reducing unemployment, and strengthening the resilience of single-industry towns in Kazakhstan.

The study of PPP as a factor in the sustainable development of Kazakhstan’s economy is a relevant task that helps identify effective mechanisms for the country’s growth. This article aims to substantiate the impact of PPP on sustainable development by establishing its link to achieving the SDGs, analyzing global PPP practices, identifying methods for evaluating PPP effectiveness, and presenting promising application areas in Kazakhstan. The scientific significance lies in identifying the main effects of PPP (economic, social, environmental, and institutional) and determining the most informative tools for assessing its effectiveness, such as key performance indicators (KPIs), benchmarking, expert surveys, and satisfaction analysis. The study outlines how PPPcontributes to national sustainable development by integrating public and private resources to solve key challenges. It also defines the potential of PPP to advance the UN Sustainable Development Goals in Kazakhstan. The practical value of the research is the applicability of the proposed assessment tools and strategies for engaging the private sector in addressing critical socio-economic issues. Examples provided in the article demonstrate how PPP increases efficiency and supports sustainability in areas such as infrastructure, education, healthcare, and ecology. It has been established that PPP holds significant potential for promoting Kazakhstan’s long-term growth. The article contributes to the theoretical understanding and practical application of PPP tools in the context of sustainable development, offering insights for improving national policy and fostering partnerships between the public and private sectors.

This article analyzes the theoretical evolution and contemporary conceptual models of project management mechanisms in public institutions in the context of sustainable development. The relevance of this study lies in the fact that public sector projects are characterized by multi-level stakeholder participation, high levels of accountability and institutional constraints, and growing demands for sustainable development. The aim of this study is to systematize classical and contemporary theoretical approaches to project management, identify their specific features in the public sector context, and present an integrated conceptual model that incorporates sustainable development principles. The study utilized a theoretical and analytical approach, including a systematic literature review, bibliometric analysis, comparative analysis, and conceptual synthesis. Based on publications in Scopus and Web of Science databases, the position of project management governance and sustainability topics in academic discourse was analyzed. The study identified stages in the evolution of project management mechanisms and proposed a typology of project management in the public sector from a sustainable development perspective. Furthermore, a conceptual model was developed that integrates project management principles, institutional theory, and the “triple bottom line” concept. The study’s findings demonstrate the theoretical and practical importance of considering project management in public institutions as a management system that ensures public value and long-term sustainable development. The findings emphasize that project management in public organizations should be considered not only as a tool for regulating internal processes but also as a comprehensive governance system that enhances public value and ensures long-term sustainable development. This provides opportunities for strategic project planning, effective resource allocation, and achieving sustainable development goals.

Modern universities in the context of globalisation and digital transformation of the educational environment face complex challenges that require updating strategic development concepts. Growing competition in the educational services market, expanding academic mobility and international cooperation, and the penetration of digital technologies into educational processes – all of these necessitate bringing university strategic management to a qualitatively new level. The purpose of the study is to identify the methodological foundations for forming university development strategies and to develop a comprehensive system for evaluating their effectiveness. The main directions of the work include: systematisation of the theoretical foundations of strategic planning from the perspectives of the Resource-Based View, stakeholder theory, and the “Triple Helix” concept; comparative analysis of the criteria of international rating systems QS, THE, and ARWU; development of an integral model for evaluating strategy effectiveness for higher education institutions. The scientific significance of the work lies in proposing a comprehensive model for evaluating strategy effectiveness that integrates academic, organisational, social and innovation dimensions. The proposed Integral Index of Strategic Effectiveness (IISE) is calculated as the weighted average of normalised indicators across four dimensions. Practical significance: the proposed system of criteria and indicators can be directly applied in planning the strategic development of universities. Practical results include a BSC adaptation model tested at 12 Kazakhstani universities and a three-level monitoring system.