Dana Kangalakova

This study aims to assess the relationship between R&D and economic growth in terms of their ability to understand R&D management. In the paper, the algorithm of actions was used, which allows ensuring interconnection, sequence of work, validity of the choice of the methods used, and defining key factors over a long period. The following methods of the empirical study were used: analysis of the provision of level development; regional analysis of the data; correlation analysis. Based on correlation analysis the impact of economic growth on R&D was investigated, which is expressed by such variables as the number of organizations engaged in R&D, internal expenditures in R&D, expenditures for technological innovations, number of employees in R&D. The data were obtained from the World Bank, the Eurasian Economic Union, and the statistical yearbook of Kazakhstan for 2009–2019. The results obtained show that all determinants correlate not only with the GDP but with each other as well. According to the findings, viewing the GDP level, there is a positive and negative correlation link between such two factors as ‘the number of research organizations’ and ‘R&D technological innovations’. These coefficients of correlation between GDP and independent factors selected for the analysis are significant, i.e. they can significantly affect the value of the GDP. The obtained results are useful in formulating the R&D development management strategy.

Acknowledgments
This study has been funded by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan (grant IRN AP08052800 “Intellectual potential of the regions of the Republic of Kazakhstan: assessment and development prospects”).

This study aims to determine the effectiveness of Kazakhstan’s public policy during the pandemic related to healthcare, education, and the financial situation of the population by assessing the population’s quality of life (QoL). The study proceeded from the assumption that the effectiveness of state measures can be assessed through the manifestation of citizens’ reaction to the ongoing public policy, i.e., satisfaction with its results. The source base was the Bureau of National Statistics and the Adilet information and legal base covering 2020–2021. During the pandemic, the population’s satisfaction with their material provision, health, education, and living conditions decreased but not critically. The population’s QoL in Kazakhstan is satisfactory. Satisfaction among rural residents with their life (70.7%) and conditions (63.7%) is higher than among urban residents (56.1% and 49.8%, respectively). One-third of the population reported improved well-being and only 6.5% reported a deterioration. The high number of citizens satisfied with their QoL indicates the effectiveness of Kazakhstani public policy. It is the result not only of the implementation of temporary anti-crisis measures of government through program, organizational, and economic mechanisms during the pandemic but systematic work on modernization of the social, medical, and educational systems from 2019. The practical value of the study is the development of recommendations for the development of public policy in the field of improving QoL and the development of anti-crisis management in Kazakhstan.

Acknowledgments
This study is supported by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan (targeted funding program BR10965247 “Study of factors, features and dynamics of demographic processes, migration, urbanization in Kazakhstan, development of digital maps and forecasts”).

Particular hopes have always been placed on the potential of scientists because they can act as a driving force for effective government. Understanding the importance of scientists ensured progress and prosperity for leading civilizations. This study aims to identify an evolutionary-chronological, geographical, and contextual scientific landscape of the development and management of the potential of scientists through a comprehensive bibliometric analysis. Initially, 5619 publications in the Scopus database were selected from 1957 to 2023. The evolution of knowledge about the importance of public administration of scientific personnel began in 1957 and reached its peak in 2019. Authors from the USA, Great Britain, and Australia have published more about the significance of managing the potential of scientific personnel, and strong schools of knowledge about scientific personnel are concentrated in the USA, France, Canada, and Australia. The analysis of the research’s conceptual orientation shows that publications in environmental and social sciences dominate this sphere. In addition, the bibliometric analysis results show that public management of scientific personnel will bring benefits such as effective government policy decisions, increased innovation activity, commercialization, and improvement of the population’s social life. The results of this study lay the foundation for future research that should improve the management of scientific personnel’s potential.

Acknowledgments
This study is supported by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (AP19579256 “Mechanisms for empowering women in scientific activity in the interests of the development of the innovative economy of Kazakhstan”, 2023–2025).

This study aims to identify challenges in the training of scientific personnel in the field of social sciences and humanities at the doctoral level in Kazakhstan. It proceeds from the assumption that successful completion of a Ph.D. program is conditioned by internal and external factors that influence the educational process and may lead to challenges in Ph.D. thesis defense. The study employs an explanatory-sequential approach within a mixed-methods design, incorporating economic-statistical, regression, and content analysis. Data were gathered through questionnaires from 61 current students and graduates of Ph.D. programs in the social sciences and humanities. Findings indicate that having a job made it more challenging for respondents to study and complete their Ph.D. programs, as employment requires time and effort; however, the additional monthly income besides scholarship helped reduce financial stress, thereby supporting their academic progress. Women found studying easier than men, while married respondents experienced fewer challenges than single ones. Although 36.1% of respondents expressed high satisfaction with Ph.D. training quality, the majority reported challenges, with 65.65% noting issues in the educational process, 52.5% identifying problems in scientific supervision, 33% raising concerns about teacher qualifications, and 25% highlighting infrastructure needs. Key factors influencing Ph.D. completion rates included an unstable study environment, characterized by frequent changes in regulations, and students’ difficulties in meeting government-imposed requirements, especially publication in a Scopus database journal. The study’s practical value is developing measures to enhance Ph.D. thesis defense rates by improving admission requirements, restricting external employment, increasing supervisor accountability, and adjusting publication standards.

Acknowledgments
This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (AP19680246 “Building up highly intelligent human resources in the conditions of digitalization of the economy of Kazakhstan: problems and prospects”, 2023–2025) and supported the Oxus Society for Central Asian Affairs (program “Advancing data-driven solutions by strengthening partnerships between the scientific, academic and civil sectors in Central Asia”, 2023–2024).

Business development contributes to the sustainable economic development of the country while also leading to significant environmental changes at the global level. The greening of businesses is becoming a priority area of strategic management for companies, considering the growing environmental challenges and the need to move toward sustainable business models. This study aims to identify the historical, evolutionary, spatial, and conceptually scientific landscape of greening businesses through bibliometric analysis. The study analyzed 660 sources in the Scopus database from 1992 to 2024. The use of VOS Viewer software and the Scopus analysis tool has shown that greening business research has been of interest among many authors and is a growing trend. The rapid growth of publications from 2019 to 2024 shows its significance to many government agencies, business people, investors, and researchers. The growing number of scientific studies in economics, management, and ecology indicates a growing scientific focus on the problems of greening businesses. The United States occupies a leading position in research volume, while the United Kingdom and China emphasize their significant contribution to developing this concept. A comprehensive analysis of scientific publications identified seven key clusters reflecting the directions of modernization of environmental business. These include green technologies, green finance, and an economy focused on the environmental transformation of businesses. The dynamics of publication activity in these fields of science confirm the relevance of the concept of eco-friendly business and its significant potential for further scientific research and practical implementation.

Acknowledgments
This study is supported by the Committee of Science Ministry of Science and Higher Education of the Republic of Kazakhstan [Grant BR21882122], Sustainable development of natural-industry and socio-economic systems in the West Kazakhstan region in the context of green growth: comprehensive analysis, concept, forecast assessments, and scenarios.

The Lima Declaration established the basis for inclusive and sustainable industrial development, emphasizing industry as a driver of progress. This study aims to analyze the sustainable industrial development of the regions of Western Kazakhstan. Using a comparative approach and Sustainable Development Goal framework, an economic-static analysis was performed on data from the Bureau of National Statistics and the National Bank of the Republic of Kazakhstan for 2010, 2015, and 2019–2022 to evaluate the state and trends of structural shifts in the sectors forming the gross regional product, as well as the development dynamics of the manufacturing industry. The study revealed that the technological structure of industry in Western Kazakhstan is dominated by the IV technological paradigm (76–82%). The manufacturing industry accounts for 11.79% of gross domestic product and is characterized by a low share of gross value added of medium- and high-tech industries in the gross regional product (0.24–1.45%). Despite the steady growth of manufacturing development indicators, only the Aktobe region demonstrates high potential for sustainable industrial development, while the West Kazakhstan and Mangystau regions have medium potential, and the Atyrau region has low potential. In these regions, sectors such as mechanical engineering, pharmaceutical and chemical production, electrical equipment, computers, and electronic and optical products have significant development potential. An important direction in sustainable industrial development in these regions could be establishing strict environmental standards, the digital transformation of mining enterprises, the transition to low-carbon sources, increasing intellectual potential, and human capital development.

Acknowledgments
This study is supported by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (BR21882122 “Sustainable development of natural-economic and socio-economic systems of the West Kazakhstan region in the context of green growth: comprehensive analysis, concept, forecast estimates and scenarios”).

Type of the article: Research Article

Abstract
Digital transformation is a key factor in the competitiveness of enterprises in the modern world. The study aims to analyze the readiness of enterprises in Kazakhstan for digital transformation at the regional and sectoral levels. The main research method was statistical analysis based on an index approach using data for 2023 from Kazakhstan’s Bureau of National Statistics, reflecting the digital readiness and digital maturity of enterprises. According to the findings, in Kazakhstan, the level of readiness of enterprises for digital transformation is heterogeneous both in regional and sectoral terms. Kazakhstani enterprises are characterized by a high level of basic digital readiness (81.4% of enterprises had computers, 79.5% – Internet access), an unsatisfactory level of advanced digital readiness (5.6% of enterprises had IT-specialists, 1.1% – own data centers, 3.1% – implemented business processes innovations in information and communication systems), and digital maturity (26.5% of enterprises had Internet resources, electronic invoices – 79.1%, automated internal business processes – 16.7%, cloud computing – 11.0%, big data technologies – 1.9%, and RFID technologies – 1.1%). A digital gap in the readiness of enterprises for digital transformation was revealed between the leading (Almaty and Astana cities, Atyrau, and Karaganda regions) and lagging (Mangystau, Turkestan, and Kyzylorda regions) regions, and between the sectors, where enterprises in industry, trade, information and communication, hospitality and healthcare are significantly ahead of enterprises in agriculture, construction, and real estate. It is advisable to make more active use of innovation infrastructure facilities to increase the digital potential of enterprises.

Acknowledgments
This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (IRN 19680544 “Innovation infrastructure of Kazakhstan in the context of digitalization: assessment of the state and development of an atlas”).

Type of the article: Research Article

Support for the education system is a strategic measure that ensures the long-term development and growth of a country’s economy. Increased funding in this area enables the training of qualified specialists who can adapt to the challenges of the modern economy. In this regard, the purpose of this study is to assess the impact of government spending on education to generate highly intelligent human capital on economic growth in Kazakhstan from 2009 to 2023 using the least squares method, which includes components of government spending on education, as well as the GLS random effects model, which is used to determine the reliability of results. The results show a strong relationship between economic growth and government spending on secondary technical education (0.2393), a moderate relationship between higher education spending (0.0423) and economic development, and a weak relationship between primary education (–0.0050) and economic growth. Thus, a 1-point increase in expenditures for secondary technical education may lead to a 0.2393% increase in GRP, and a 1-point increase in government spending on higher education will lead to a 0.0423% increase in GRP. However, a significant share of government spending is on basic primary education (58%). Based on this, the financing of the education system requires a shift in the financing vector, with a greater focus on higher and secondary technical education, to achieve a more significant impact on economic development.

Acknowledgments
This research is supported by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (AP19680246 “Building up highly intelligent human resources in the conditions of digitalization of the economy of Kazakhstan: problems and prospects”, 2023–2025).

Type of the article: Research Article

Abstract
Artificial intelligence (AI) has become the most eye-catching new technology in recent years, and its application is driving the transformation of enterprise management. In order to cope with the impact of new technological changes and address key issues affecting enterprise management development, it is necessary to research and clarify the basic relationship between the application of AI and the development of enterprise management. This study aims to analyze the current situation and future development direction of AI-driven enterprise management through bibliometric analysis. Scopus and Web of Science data from 2014 to July 2025 were analyzed to explore the evolutionary time, geography, and scientific landscape of this topic. The findings contribute to understanding AI’s driving role in enterprise management development. The analysis reveals exponential growth in research output on AI-driven management, accompanied by a decreasing growth rate of publications on AI-driven enterprise management since 2021. The important factors that affect research output are population and total GDP. China, the United States, and India were identified as the leading contributors, with significant research activity in this field. Keyword analysis indicates that the thematic focus is becoming more technical and universal. Thematic analysis highlights that human resource management, financial management, supply chain management, and operational decision-making are the main aspects of AI-driven enterprise management, accounting for 94% of the total number of publications. The study proposes a new direction for the development of AI-driven enterprise management, including department integration, cognitive convergence, and ethical and social responsibility.

Acknowledgments
This research has been supported by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (IRN 19680544 “Innovation infrastructure of Kazakhstan in the context of digitalization: assessment of the state and development of an atlas”).

Type of the article: Research Article

Abstract
The application of artificial intelligence (AI) in enterprises presents new opportunities for growth in their market value. This study aims to evaluate the impact of AI applications in enterprises on the growth of enterprise market value and the transmission mechanism of these impacts. Using an enterprise AI application level as the independent variable, a regression model is constructed to analyze the long-term and short-term market value of the enterprise. This study uses relevant data from Chinese listed companies from 2014 to 2023 for analysis. Findings show that for every 1% increase in AI application level, the enterprise market value increases by 0.03% and the enterprise value multiple increases by 0.44%. Increasing the level of AI application in enterprises will enhance their ability to implement low-carbon measures and investors’ expectations of corporate profits, thereby increasing the market value of enterprises. High-quality talent within the enterprise and market share can enhance the impact of these two mechanisms. The application of AI in enterprises has different impacts on different industries and companies of different sizes. This study provides new empirical evidence for enterprise market valuation.

Acknowledgments
This research has been funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (IRN BR28713593 “Sustainable development of Kazakhstan’s economy in the context of new сhallenges: foresight, strategies and scenarios of modernization, institutions”).