Globally, universities play a key role in developing and commercializing new technologies through research and development (R&D) support. However, Kazakhstan faces several challenges, including financial constraints, outdated scientific infrastructure, and weak links between universities and industry. This study aims to provide a comprehensive analysis of the key factors affecting R&D support in Kazakhstan and to identify the main financial, infrastructural, and institutional challenges that hinder the efficient use of R&D resources. The study used bibliometric data analysis using VOSviewer and qualitative interview analysis using Atlas.ti software. Primary data were collected through interviews with experts from various higher education institutions in Kazakhstan. The analysis focused on aspects such as R&D financing, the state of scientific infrastructure, interaction with business, and barriers for young scientists. The results of the study show that financial constraints have a significant impact on infrastructure upgrades and project deadlines. Business integration correlates positively with R&D commercialization (r = 0.848) but remains weak due to structural barriers. Budgetary inflexibility hinders efforts to modernize infrastructure and digitize processes, while insufficient support for young scientists increases the problem of staff retention. Expert assessments demonstrate a negative perception of infrastructure accessibility (-0.421) and predictability of funding among most academic positions. Future research should focus on developing adaptive financing models and studying the international interaction experience between universities and industry to strengthen the innovation ecosystem of Kazakhstan.

This study examines the ongoing debate between Decentralized Finance (DeFi) and Centralized Finance (CeFi), analysing their unique advantages and challenges within the rapidly evolving financial landscape. The objective of this research is to argue for the convergence of DeFi and CeFi to create an innovative and secure financial ecosystem that balances accessibility with security, using Kazakhstan as a case study. The study employs comparative analysis and case-study methodology to explore Kazakhstan’s regulatory approach to digital assets. The focus is on understanding how licensing, anti-money laundering (AML) protocols, and consumer protection measures can support the integration of DeFi and CeFi. Primary data includes an analysis of Kazakhstan’s regulatory framework for digital assets, statistical data on AML implementation, and levels of consumer protection within the country. Findings indicate that a hybrid regulatory model effectively bridges the operational differences between DeFi and CeFi, fostering inclusivity and economic growth while safeguarding consumer interests. Kazakhstan’s regulatory focus on licensing and AML protocols illustrates that a balanced regulatory approach can accommodate both technological progress and necessary protections for financial participants. The study concludes that a convergence of DeFi and CeFi through a hybrid regulatory model can lay the foundation for a sustainable digital financial environment that is accessible, innovative, and secure. Future studies are encouraged to explore the role of emerging technologies, such as quantum computing, and examine the socio-economic impacts of DeFiCeFi integration on financial inclusivity for underserved populations.

Today, the quality of women’s employment is an urgent topic that attracts the attention of researchers and politicians in connection with the need to ensure equal opportunities in the labor market. The present study applied bibliometric analysis to examine the factors affecting quality employment for women based on the past literature over the past two decades, from 2000 to 2024. The study uses the Scopus database to identify the most cited journals, authors, countries, and keywords related to women’s employment. Different Booleans were applied with logical OR and AND operators to extract the data. PRISMA model was used with inclusion or exclusion criteria, and 238 papers were finalized based on the satisfactory requirement for the analysis. To analyze the data, bibliometric tools such as VOSviewer and R Studio were applied to generate a visualization of network diagrams, cluster analysis, and citation patterns regarding most cited journals, authors, countries, and keywords in the past literature on factors affecting the quality of employment for women. The analysis revealed vital trends, including the most cited sources, leading authors, and countries actively publishing works on this topic. The main thematic areas were highlighted, such as gender equality, mental health, employment conditions, and labor discrimination. Visualization using network diagrams made it possible to identify the relationships between authors, countries, and critical keywords, reflecting global scientific trends. This study provided a comprehensive science map to show a framework for future researchers and policymakers to understand the international trends and the factors affecting women’s employment quality.

This study presents a distributed system using RAY, K-means clustering, and Weka software to analyze clinical data from Almasara Hospital Group in Tripoli, Libya. The goal is to reduce patient risk and healthcare costs by providing daily feedback to hospital staff. The system utilizes a dataset containing information on 560 patients, including details like patient ID, gender, doctor ID, test IDs, medication, and a binary target variable. By implementing K-means clustering in Weka, the system categorizes patients and identifies patterns to reduce risks and costs for healthcare analytics. The study first reviews existing patient care and feedback practices and then details the implementation of the daily feedback system, which involves advanced data analysis for managing patient feedback and medical data continuously. The use of K-means clustering helps segment patient data, pinpointing specific risk factors and areas for improvement. Weka software aids in the in-depth analysis of these segments, leading to actionable insights. Results show significant improvements in patient outcomes, reduced hospital-acquired infections, and medication errors, and enhanced patient satisfaction scores. Moreover, the study notes a substantial decrease in overall healthcare costs due to more efficient resource allocation and lower hospital readmission rates. This integration of daily feedback with advanced data analysis tools like K-means and Weka emerges as an effective strategy for improving patient safety and operational efficiency in healthcare settings, demonstrating the value of data-driven decision-making and providing a scalable model for other hospitals aiming to enhance patient care and cost management.

The development of foreign economic cooperation with friendly countries is one of the key priorities of Russia’s economic and foreign policy. This study aims to determine the specific characteristics and promising directions for Russian-Vietnamese foreign economic cooperation in the context of regional integration. The research relies on foreign trade statistics provided by the Federal Customs Service of Russia and analytical data from the international trade platform Trade Map. Additionally, departmental reports and analytical materials concerning Russian-Vietnamese relations for the period from 2003 to 2021 are used. The study employs methods of comparison, interpretation, and identification of functional links. Specifically, the research follows a step-by-step algorithm comprising five stages: data collection and structuring, analysis of product groups, identification of critical Russian exporting regions, evaluation of regional export specifics, and developing recommendations for further cooperation. The analysis shows that foreign trade turnover between Russia and Vietnam increased fourteenfold from 2003 to 2021, despite Russia’s share in Vietnamese imports decreasing by 1.2%. Meanwhile, imports from Vietnam to Russia rose forty-ninefold. It was found that Russia’s exports to Vietnam consist primarily of low-processed goods, raw materials, and resources. Promising directions were identified based on Trade Map data for 2019–2021, focusing on increasing non-resource exports. Future research will assess the potential for cooperation between Russian and Vietnamese regions in the high-tech sector.

The article examines cross-border cooperation between Kazakhstan and Uzbekistan, focusing on developing logistics in border regions. Central Asian regions face significant barriers, such as logistical inefficiencies, legal and customs discrepancies, and weak coordination, which hinder their ability to meet the growing demand for freight transportation. The article aims to propose conceptual approaches for harmonizing regulations, simplifying customs procedures, and removing obstacles to the movement of goods and services across border regions. The research methodology includes case studies of transport corridors and content analysis of data from international organizations and national statistical agencies. The analysis of the Trans-Caspian Route and the Southern Corridor highlights challenges such as high transport costs, lack of institutional support, geopolitical influences, and investment risks. Special attention is given to crossborder industrial logistics zones (ILZs), which could serve as strategic tools for reducing transaction costs and expediting cargo processing. These zones should be integrated with international transport networks and automated customs systems. The research results show that sustainable development of crossborder cooperation requires not only infrastructure investments but also institutional reforms, including the establishment of joint regulatory bodies and harmonization of legislation to eliminate administrative barriers. The article provides recommendations for simplifying customs procedures, establishing industriallogistics centers, developing transport corridors, and forming a concept of cross-border interaction. Future research directions include assessing the economic impact of the proposed ILZs and exploring digital platforms for real-time coordination of freight transportation.

In today’s uncertain circumstances, issues related to sustainable economic growth have become more relevant. However, little attention has been paid to the impact of economic integration on the growth of member countries. The purpose of this research is to identify differences in the structure of the EAEU countries and assess their growth. Methods of induction and deduction, analysis, synthesis, time series and calculations based on economic and statistical units of account were used. Gatev, Salai, and Ryabtsev indices were used to measure structural changes. Data were collected from annual statistical reports of the Eurasian Economic Commission for 2015 to 2022, covering key economic activities in Russia, Kazakhstan, Belarus, Armenia, and Kyrgyzstan. As part of the study, it was found that Russia’s share in the gross domestic product (GDP) of the Eurasian Economic Union (EAEU) accounts for 83-86%, with Kazakhstan in second place at 8-10% and Belarus in third place at 3-4%. These results partially confirm the hypothesis that integration processes in the EAEU can have ambiguous effects on structural changes and economic growth, and further coordination of policies among member countries is needed to increase production capacity utilization and strengthen cooperation. These results can be applied to the analysis of sectoral structural changes and the development of government programs aimed at improving regional structural economic policies in the EAU, contributing to long-term economic development.

Currently, the issue of education for the development of a ‘green’ economy is among the most pressing global challenges. In this context, this study explores the relationship between CO2 emissions and education levels, represented by government spending on education as a share of GDP, alongside economic and social indicators such as GDP per capita, urbanization ratio, and inflation rate. The analysis focuses on the cases of Kazakhstan and Turkey. The study used a forecasting methodology involving a regression model to determine the relationships between changes in CO2 emissions, educational attainment, and economic and social parameters. A multiple linear regression model was constructed to assess education’s impact, and the ecological footprint and ecological deficit for the two countries studied were determined. The study uses information from the Footprint Data Foundation (Footprint Data Foundation). The research complements the existing theoretical framework on sustainable development, offering an interdisciplinary approach combining economic, environmental and educational aspects. The results show that education and GDP per capita significantly positively impact reducing CO2 emissions in Kazakhstan. The results can be used to justify the need to integrate environmental knowledge into educational programs and to develop more comprehensive models of the interaction of factors affecting the reduction of the carbon footprint. From a practical point of view, the study’s results will provide empirical data and analysis that can be useful for developing educational and economic strategies and more effective government programs aimed at reducing CO2 emissions, improving environmental quality and promoting green growth.

This bibliographic literature review investigates the state of risk management in the public sector, focusing on its evolution, current trends, and future directions. The study aims to systematically synthesize the literature, identifying critical areas such as risk governance, resilience, and emergency management as central themes. The methodology involved retrieving data from primary academic sources like Google Scholar, Web of Science, and Scopus. Data was curated using specific keywords, peer-reviewed filters, and a timeframe from 2001 to 2024, ensuring relevancy and high-quality outputs.  The review highlights the increasing significance of risk management in the public sector, particularly in response to global challenges such as financial crises and the COVID-19 pandemic. Results reveal an expanding focus on public sector risk management, driven by recent global challenges and the integration of digital technologies. However, notable research gaps persist, particularly in areas such as advanced technology adoption, longitudinal impact studies, and cross-regional comparative analyses. Despite extensive research, gaps remain in integrating advanced technologies, longitudinal studies, and comparative analyses across different regions. This study provides valuable insights for policymakers and practitioners, emphasizing the need for innovative and adaptive risk management strategies to enhance public sector resilience. Future research should address these gaps, promoting resilience in public sector organizations and contributing to a more robust understanding of risk management dynamics in an increasingly uncertain world.