Saltanat Tamenova

The article examines the institutional environment for the implementation of the strategy of sustainable development of agriculture in the Republic of Kazakhstan. The degree of integration of economic, environmental and social priorities in key strategic documents of agrarian policy for 2015-2024 has been assessed. Based on comparative institutional and statistical analysis, the specifics of the industry's transformation have been identified, reflected in the dynamics of key macroeconomic indicators and the results of cross-country comparisons with the EU, China and Russia. The predominance of the economic block in the system of state support has been established with limited development of environmental and social areas. It is shown that the agricultural sector of Kazakhstan is developing along the trajectory of modernization, accompanied by institutional asymmetry. The conclusion is made about the transitional nature of the sustainable development model and the need for a more balanced strategic management.

The United Nations recognized creative economy as one of the fastest growing sectors. The sector not only employs 30 million people worldwide, but also provides more jobs for young people than any other area of employment. The study was conducted within the 5-year “Creative Spark” program funded by the British Council and implemented in the countries of Central Asia (Kazakhstan, Uzbekistan, Kyrgyzstan), South Caucasus (Azerbaijan, Armenia, Georgia) and Ukraine. The program aimed at strengthening partnerships between universities and creative institutions in the UK and participating countries, developing entrepreneurial skills among young people and increasing their English level proficiency. Kazakhstan places a special importance on development of creative industries and approved the “Concept for the Development of Creative Industries for 2021–2025” [1]. In order to keep pace with the government’s initiatives and international trends, higher education institutions in Kazakhstan need to provide educational programmes to prepare future leaders for creative industries. The first step in this process is to identify current situation and demand for educational programmes in creative economy. This is the aim of the study. The methods employed in the study are in-depth interviews with experts and surveying applicants to Kazakh American Free University located in Ust-Kamenogorsk, Eastern Kazakhstan. The results of the study show that the demand for creative industries is not completely formed and strong promotion is needed in order to popularize this sector. Some recommendations for higher education institutions in Kazakhstan include the development of double degree programs with the US and the UK universities in web design, brand management and advertising.

The digital transformation of the economy is marked by a fundamental shift in the logic of modern socioeconomic development. This process requires the accelerated creation of adaptation mechanisms at the micro, meso, and macro levels. The widespread adoption of digital technologies calls for new approaches to business organization and leads to the revision of traditional processes. Accordingly, the relevance of research aimed at introducing innovative technologies into various sectors of the economy, modernizing business processes, and enhancing entrepreneurial efficiency is increasing. The study is driven by the need to develop adaptive management approaches through the formation of business ecosystems. Their advantage lies in creating optimal value chains based on participants’ interaction and strengthening the capacity to adapt to dynamic external changes. The hypothesis suggests that business ecosystems, under conditions of digital transformation, enhance the efficiency of all participants. The purpose of the study is to develop and substantiate a methodological framework for building a management model of interaction among ecosystem participants aimed at improving entrepreneurial activity. The scientific significance is determined by clarifying methodological foundations for ecosystem formation and offering theoretical and practical recommendations to improve interaction management. The novelty lies in adaptive approaches to ecosystem management and a cluster-based model tailored to Kazakhstan’s real sector. The author’s contribution is reflected in advancing methods for assessing dynamic ecosystem development using time lags and quantitative indicators

Artificial intelligence is being actively introduced into academic research, increasing its efficiency and scale. However, its use raises questions of academic integrity, intellectual property protection and the use of an open resource. This is a very important aspect for PhD students who combine training with the creation of new knowledge. Modern scientific research uses various artificial intelligence tools, covering all stages of the scientific process. The aim of the study is to analyze the use of artificial intelligence technologies in research activities, identify key areas of their application, and review tools that help improve the efficiency of scientific research while taking into account ethical standards. Based on a literature review and content analysis, the main areas of AI application were identified: from hypothesis formulation to support for publication activity. This study offers practical recommendations for doctoral students, supervisors and heads of doctoral educational programs.

For further improvement of strategies and programs for the development of agriculture in the Republic of Kazakhstan, it is necessary to determine ways to adapt to the UN Global concept of sustainable development for the period up to 2030. The purpose of the study is to identify national priorities in the field of sustainable agricultural development, taking into account the 2030 Sustainable Development Concept (SDGs). The scientific significance of the study is the adaptation of the SDG 2030 goals to the national conditions of Kazakhstan and the development of a mechanism for achieving them in the agri-food sector. The work systematized the relationship of the agrifood sector with 12 SDGs goals, as well as identified 78 urgent tasks for Kazakhstan (46%) within the framework of the Global Sustainable Development Goals. The use of a systematic approach made it possible to identify and clarify the social, economic and environmental indicators necessary for the development of national indicators of sustainable development of the agro-industrial sector of Kazakhstan. The results of the study show the importance of the relationship of the agro-food sector of Kazakhstan with the target tasks and indicators of the SDG 2030. These results can serve as the basis for creating a concept for the sustainable development of the industry. The proposed approach should include not only monitoring and reporting mechanisms, but also a set of incentive measures aimed at developing and implementing sustainable development strategies. These strategies should be aimed at technological transformation of the agri-food sector, increasing its sustainability, efficiency and ability to adapt to external challenges and global shocks.

Having a university degree provides only a slight advantage over those without higher education, making other factors crucial in determining a graduate’s employment prospects. This study aims to analyze the factors that affect the employment of university graduates and define opportunities for public administration and university management in Kazakhstan. A logistic regression model based on primary data was used to examine the impact of the availability of practical experience and jobs in their specialty, social connections, technology development, and entrepreneurship on the likelihood of employment. The survey was conducted in 2022 and involved 300 graduates of the 2020–2021 academic year from all regions of Kazakhstan. Findings show that personal connections (F3) and technology and entrepreneurship (F4) positively impact graduates’ job prospects. However, lack of experience (F1) and the limited number of job offers (F2) reduce employment likelihood. If a graduate responds with 3 points for F1, 7 for F2, 7 for F3, and 1 for F4, they are less likely to secure a job in their specialty within a year of graduation. The main practical value of this study is that university career centers can use this model to predict the likelihood of graduates being employed. Providing a sophisticated online platform and different analytics-driven career services, open access to administrative data on the labor market, and new programs for students’ job experience and entrepreneurship will prepare university graduates for a dynamic labor market and reduce the mismatch between education and employment needs.

University graduates are part of the country's intellectual potential and their employment contributes to the socio-economic development of the country. This study aims to analyze the possible economic effect of employment of university graduates in Kazakhstan and define opportunities for Triple Helix Model implementation. To achieve the research aim, an autoregressive distributed lag model of the effect of the number of graduates on GDP per capita was used. Information base of the study was a secondary data of Kazakhstan’s Bureau of national statistics from 2000 to 2021. According to the results of the study, an increase in the number of university graduates has influence on the economic progress of Kazakhstan. So, a 1,000-person increase in graduates improved GDP per capita by $55 in the current year, while a 1,000-person increase in graduates three years ago increased the GDP per capita by $58 in the current year. The practical value of the study is to justify the need to apply the Triple Helix approach in managing the employment of university graduates in Kazakhstan.

The goal is to identify the possibilities of applying the SDG (Sustainable Development Goals) system for agro-industrial complex based on the analysis of its current state and adaptation to the concept of socio-economic and environmental sustainability (ESG). The methods - general scientific: comparative, statistical analysis, as well as logical and generalization, which were used as theoretical and methodological basis based on the fundamental principles of the ESG-concept, presented in the works of various foreign economic schools. Results - main problems of AIC are identified and systematized according to the UN methodology. The authors note that the proposed grouping of SDG parameters, focused on agricultural sector of Kazakhstan and connections established between them, will make it possible to create an effective, efficient model for the growth of the country’s economy and its agro-industrial production. Conclusions - the research conducted by the authors of the article shows that there is significant resource for achieving the effectiveness of the Sustainable Development Goals based on the implementation of integrated approach that ensures unity and balance of social, economic and environmental goals and their integration into corporate strategies that set out the mission and objectives of the enterprise, as well as means and methods for their implementation. The importance and advantages of the ESG-concept for overcoming the environmental crisis, reducing the anthropogenic impact on the environment, creating conditions for improving the well-being of the rural population and the level of competitiveness of agricultural producers are justified. The implementation of ESG-standards plays important role in ensuring the sustainable development of the industry, helping to improve financial performance of enterprises, providing optimal conditions for attracting investors and strengthening reputation on domestic and international markets, preserving biological and natural diversity.

The purpose of the article is to study the models for creating innovative “milk processing cooperative”, created on the basis of cooperative relations with dairy-producing personal subsidiary farms, to give recommendations. Based on the creation of dairy processing cooperatives in private subsidiary farms for processing and selling milk within the country, their great potential is being used and dependence on dairy products is being reduced. The models and options for creating dairy processing cooperatives based on the cooperation of private subsidiary farms in the dairy industry of the country are presented: 1) the creation of a “dairy processing innovation cooperative” based on a cooperative relationship with personal subsidiary farms; 2) under a cooperative agreement with personal subsidiary farms of the Turkistan region, the activities of the innovative dairy processing company FoodMaster-Shymkent LLP were considered; 3) the creation of a “dairy production cooperative” with a commercial dairy farm in the settlements of the district is suggested, based on the cooperation process. This is due to the fact that dairy processing and marketing cooperatives, along with the collection, processing, and sale of milk from personal subsidiary farms, of which they were members, assume responsibilities for processing land plots, foraging, providing breeding young animals, providing production and technical services, and state support for personal subsidiary farms. State support (subsidies, tax and credit benefits) through “milk-producing cooperatives”, in which personal subsidiary farms are created, support for personal subsidiary farms is provided through milk-producing cooperatives and milk-processing cooperatives.

The effective functioning of a smart university management system significantly improves higher education institutions’ competitiveness. This study aims to assess the implementation of a smart university management system on the example of Kazakh Ablai khan International Relations and World Languages University. The paper considers elements of a smart university system (smart learning technology infrastructure, smart faculty staff, and smart students) from the university managers’ and students’ viewpoints using the stepwise algorithm to raise the university’s competitiveness. During the study, 2700 students were surveyed to assess the implementation and operation of smart systems at the university, and ten experts (the expert team consists of deans and head of departments) were interviewed to identify the weights of each element. The survey results showed that the technology infrastructure for smart learning at the university is at a lower level (50%) than the competence of the teaching staff (60%) and students (89%). Furthermore, based on standardized factor scores and the weighted average, the implementation level of a smart university management system is low – C (0.498), where the weighted assessment of smart learning technology infrastructure is 0.2, smart teaching faculty – 0.19, and smart students – 0.108. According to the results, the university management needs to develop the smart learning technology infrastructure (free Wi-Fi, smart education environment, and smart classrooms) and improve the qualifications of its teaching staff (knowledge and skills, content of the courses, and educational process).