University of International Business

The article examines current trends in internal and international migration in the Kyrgyz Republic and their relationship with state social policy. Particular attention is paid to the centripetal nature of migration flows from rural and economically less developed regions to major urban centers, primarily Bishkek and the Chui region. Based on a secondary analysis of data from international organizations, official statistics, and academic publications, the study identifies key socio-economic drivers of migration as well as major risks and vulnerabilities faced by migrants, including unemployment, informal employment, and limited access to social protection due to registration barriers. The findings demonstrate that despite migrants’ subjective perception of improved living conditions after relocation, a significant proportion of internal migrants remains socially vulnerable. The article concludes by emphasizing the need for deeper integration of migration issues into national social policy and sustainable development strategies in order to reduce inequality and enhance social inclusion.

Background: Artificial intelligence (AI) is increasingly integrated into everyday communication, extending beyond functional and academic uses to influence romantic relationships, particularly among university students who are deeply immersed in digital technologies. As AI systems become more emotionally responsive and easily accessible, they play an increasingly significant role in intimate interactions, raising important questions about their psychological and relational consequences. Purpose: This study aims to quantitatively examine the relationship between AI-assisted relationship communication and boundary confusion among university students, addressing a critical gap in the existing literature on artificial intelligence and intimate relationships. Methods: This quantitative cross-sectional study involved 420 university students (210 females, 210 males) currently engaged in romantic relationships. Participants completed standardized questionnaires measuring AI-Assisted Relationship Communication (AIRCS), Boundary Confusion in AI-Assisted Relationships (BCARS), and attachment anxiety and avoidance using the Experiences in Close Relationships–Revised (ECR-R). Data were analyzed using SPSS 29.0 and AMOS 29.0, applying correlation, regression, and structural equation modeling analyses. Results: AI-assisted relationship communication was strongly associated with boundary confusion and emerged as its strongest predictor. Attachment anxiety and avoidance also significantly predicted both AI-assisted communication and boundary confusion. Conclusion: The results show that students who frequently use AI for emotional support and relationship communication are more likely to experience confusion about boundaries in their romantic relationships, especially those with insecure attachment styles. While AI can help meet emotional needs, it can also blur the line between human relationships and technology. These findings highlight the importance of teaching students how to use AI responsibly in relationships, developing clear ethical guidelines, and providing targeted support through university counseling services.

Digital transformation in higher education represents a comprehensive strategic process that transcends technological modernization and embraces institutional, managerial, and pedagogical innovations. This paper explores the evolution of digital transformation in Kazakhstan – from informatization and digitalization to a fully integrated transformation – based on a systematic analysis of 44 academic publications. The study proposes a structural model of university digital transformation, integrating three key dimensions: strategic management and institutional processes, technological ecosystems and pedagogical innovations, and the development of human capital. The findings demonstrate that digital transformation serves as a crucial framework for bridging the digital divide, enhancing institutional efficiency, and ensuring the sustainable development of higher education. Moreover, the proposed model contributes to the alignment of national digital policies with university strategies, reinforcing competitiveness and adaptability in the global digital environment. The study provides theoretical and practical insights for universities navigating digital transition toward sustainable growth.

BackgroundThis study aimed to evaluate sociodemographic and health-related factors associated with quality of life (QoL) in older adults from Kazakhstan during the COVID-19 pandemic, as well as gender- and place-of-residence differences in these factors associated with QoL.MethodThis study included 445 individuals aged 60 years and above from both urban and rural areas in Kazakhstan, between June and July 2022. Sociodemographic and health-related variables were analyzed. QoL was evaluated by the Older People’s Quality of Life (OPQoL) Scale.ResultsThe multivariate regression analysis indicated that the entire study population belonging to an ethnic group other than Kazakh (p < 0.001) was associated with lower OPQoL scores. For men, being married (p = 0.001) was significantly associated with the higher OPQoL scores, while belonging to an ethnic group other than Kazakh (p = 0.040) was associated with the lower OPQoL scores. Regarding women, the presence of COPD (p < 0.001) and belonging to an ethnic group other than Kazakh (p < 0.001) were significantly associated with the lower OPQoL scores. For those living in urban areas, better self-reported overall health (p = 0.005) and the absence of chronic heart failure (p = 0.041) were significantly associated with higher OPQoL scores. In comparison, the presence of chronic diseases (p < 0.001) and belonging to an ethnic group other than Kazakh (p < 0.001) were associated with lower OPQoL scores. In the rural area, in univariate regression analysis, only diabetes (p = 0.012) was significantly associated with lower OPQoL scores. General linear model analysis indicated that age, in combination with various health and sociodemographic factors, significantly affected OPQoL scores. In men, significant associations involved age with diabetes (p = 0.024) and marital status (p < 0.001), and in women, age with COPD (p = 0.005), chronic diseases (p = 0.014), and ethnic background (p < 0.001). Among urban residents, age was significantly associated with chronic heart failure (p = 0.021), chronic disease (p = 0.005), and ethnic background (p < 0.001), while among rural residents, age was significantly associated with hypertension (p = 0.024) and chronic diseases (p = 0.043).ConclusionOur findings suggested that various sociodemographic and health-related factors influence QoL in older adults. Furthermore, this study showed gender- and place of residence-differentiated predictors of QoL. These results call for gender and place-of-residence-responsive healthcare provision and community support services.

This study is devoted to a comprehensive analysis of the determinants of youth unemployment in Kazakhstan and the specifics of the transition from education to sustainable employment for young people. The aim of the work is to identify key structural, institutional and socio-economic factors that affect youth employment, as well as to assess the dynamics of Not in Employment, Education or Training (hereinafter – NEET) and employment indicators from 2020 to 2044. The methodological basis includes descriptive statistics, comparative analysis and correlation analysis. Initial data were obtained from official sources such as the Bureau of National Statistics of Kazakhstan, International Labor Organization, and World Bank, disaggregated by gender, region, and level of education. Results showed that between 2019 and 2039, the youth unemployment rate decreased from 7% to 6%, NEET decreased from 6% to 4%, and the proportion of informal employment fell from 18% to 9%.. Young women have consistently higher NEET rates (6.7% in 2024) than men (4.9%). The regions with the highest unemployment rates are Turkestan Oblast and Shymkent, at 7.8% and 7.2% respectively. Educational differences remain significant: the employment rate for young people with a higher education is 78%, compared to only 38.9% for those with basic secondary education. These results confirm the structural nature of youth unemployment, resulting from a mismatch between graduates' skills and job market demand, as well as regional imbalances and limited entry-level positions. Future research paths involve the development of more sophisticated quantitative models to evaluate government programs and their impact on job creation.

В статье рассмотрено влияние динамики мировых цен на нефть на развитие нефтегазового сектора Казахстана и изменение структурных пропорций экономического роста в 2020-2024 гг. Проанализировано состояние нефтегазового и ненефтегазового секторов на основе официальных статистических данных, отражающих изменения валовой добавленной стоимости, индекса физического объема и долевых параметров в составе ВВП. Показано, что нефтегазовый сектор сохраняет значимую роль в экономике, однако выявлено устойчивое снижение его относительного вклада на фоне ускоренного роста ненефтегазового блока. Сопоставлены ключевые индикаторы отрасли с динамикой среднегодовой цены на нефть марки Brent. Определено, что реакция нефтегазового сектора обладает инерционностью и асимметрией, а чувствительность к внешним ценовым колебаниям постепенно изменяется. Установлено, что внутренняя структура экономики демонстрирует признаки адаптации, что выражается в изменении отраслевых пропорций и усилении роли несырьевых источников роста. На основе проведенного анализа сформулированы рекомендации, направленные на повышение устойчивости экономики Казахстана к нефтяным шокам, включающие меры макроэкономической стабилизации, усиление фискальных буферов и развитие инструментов диверсификации. Полученные результаты способны расширить аналитическую базу для дальнейших исследований и использования при разработке экономической политики. The article examines the impact of the dynamics of world oil prices on the development of the oil and gas sector in Kazakhstan and the change in the structural proportions of economic growth in 2020-2024. The state of the oil and gas and non-oil and gas sectors is analyzed on the basis of official statistical data reflecting changes in gross value added, volume index and share parameters in GDP. It is shown that the oil and gas sector retains a significant role in the economy, but a steady decrease in its relative contribution has been revealed against the background of accelerated growth of the non-oil and gas block. The key industry indicators are compared with the dynamics of the average annual price of Brent crude oil. It is determined that the reaction of the oil and gas sector has inertia and asymmetry, and sensitivity to external price fluctuations is gradually changing. It has been established that the internal structure of the economy shows signs of adaptation, which is reflected in a change in industry proportions and an increased role of non-resource sources of growth. Based on the analysis, recommendations have been formulated aimed at increasing the resilience of Kazakhstan's economy to oil shocks, including macroeconomic stabilization measures, strengthening fiscal buffers and developing diversification tools. The results obtained can expand the analytical base for further research and use in the development of economic policy.

Generative AI (GenAI) has been suggested as a promising approach to lowering R&D costs and enhancing drug efficacy, though its ultimate impact on therapeutic effectiveness remains uncertain. This paper investigates competition between an incumbent and a potential entrant, focusing on how the entrant leverages GenAI for market entry. The entrant’s entry-adoption decision depends on fixed cost thresholds, where low cost induces entry with GenAI, high cost precludes entry, and intermediate cost leads to entry without GenAI. The GenAI adoption incentive exhibits an inverted-U pattern in competition intensity. Specifically, with weak competition, outcome uncertainty dominates and the entrant forgoes GenAI. With moderate competition, GenAI is adopted to secure a quality advantage. In intense competition, aggressive price rivalry dissipates the returns to quality, and adoption again ceases. We further reveal that GenAI exerts a double-edged effect on both firms. It raises profits under mild competition, but may counterintuitively reduce them in relatively intense competition, creating a prisoner’s dilemma. Intriguingly, when fixed cost is relatively large but entry occurs, the incumbent may resort to defensive pricing to deter entry, sacrificing its own profit. Finally, we show that GenAI may diminish patient surplus when the entrant monopolises the market or when competition is weak, despite its quality benefits.

This research investigates models for ensuring the economic sustainability of potato production under the extreme continental climate conditions of Uzbekistan. The study provides an econometric analysis of how heat stress, water scarcity, and atmospheric humidity impact crop yields. Leveraging recent authoritative sources, the paper substantiates the influence of varietal diversification and advanced post-harvest storage technologies on overall economic efficiency. The findings suggest that integrating climate-resilient agrotechnology with optimized storage value chains is critical for mitigating environmental risks and enhancing the profitability of the agricultural sector in the region.