This article uses a bibliometric approach to identify the roles of women in leadership and the various challenges they face in corporate management. The study's goal is to determine the leading countries, commonly used keywords, research trends and the dynamics of the growth of scientific papers on this subject over the previous fifteen years (2010–2025). To process and analyse data from the Scopus database, programs like VOSviewer and Bibliometrix (R Studio) were used. As a result of the analysis of 1,036 scientific publications, key research trends, the most productive countries and frequently used keywords were identified. It was found that despite the growing representation of women in leadership, structural barriers, gender inequality, and cultural and social constraints remain. The geographical and thematic differentiation of publications indicates the global importance of the topic under consideration and the interdisciplinary nature of the research. The bibliometric approach enabled the identification of the main research clusters: gender stereotypes and discrimination, institutional barriers, and the phenomenon of the “glass ceiling”. The findings highlight a growing interdisciplinary interest linking gender economics, corporate governance, and organizational psychology. Additionally, using the bibliometric technique, the study identifies scientific focus, research gaps, and prospects. Future research should focus on in-depth analysis of under-researched topics such as intersectionality and mentoring, as well as on developing practical tools to overcome structural and cultural barriers in women's leadership.

In the context of accelerated digitalization of education and national initiatives for the introduction of artificial intelligence (hereinafter – AI) in Kazakhstan, the study aims to identify the factors determining the adoption of AI by teachers. This study examines the determinants of teachers’ adoption of AI in Kazakhstan, a context where empirical evidence remains limited despite growing national emphasis on AI integration in education. Drawing on survey data from 662 teachers across diverse regions, the study investigated how demographic factors, professional qualifications, ICT training, self-efficacy, and resource availability influence AI use in classrooms. Results indicate that younger teachers are significantly more likely to use AI, whereas qualification level did not affect use. Formal ICT training during university education emerged as a strong positive predictor of adoption, and initial confidence with ICT was modestly associated with AI use. Age was a statistically significant predictor (F = 3.72, p = 0.0054): teachers aged 20-39 are more likely to use AI (M = 2.18) than teachers in older age groups (M = 1.82). On the contrary, the presence of ICT education in higher education significantly increased AI use (U = 48,209.5, p = 0.0015). By contrast, gender, subject specialisation, school location, and language of instruction did not yield meaningful differences. The findings highlight that while AI adoption among Kazakhstani teachers is growing, its use remains selective rather than routine. The study concludes that embedding structured ICT preparation in teacher education and providing sustained professional.

Kazakhstan’s ecotourism marketing is currently fragmented and weakly aligned with sustainability governance (e.g., no national eco certification), unlike leading destinations that integrate environmental values into their branding and communications. This study benchmarks Kazakhstan against four international ecotourism leaders to identify strategic gaps and adaptation opportunities. The methodology is based on comparative and systematic approaches, including the development of a composite index of marketing-resistant architecture (CMSI), analysis of the PESO model (Paid, Earned, Shared, Owned), and panel regression based on 2019-2024 data. International best-practice destinations embed sustainability certification into national brands and maintain an Owned/Shared-media–heavy outreach, whereas Kazakhstan relies mainly on advertising, with limited data transparency or visitorflow management. As a result, Kazakhstan’s composite marketing sustainability score is barely 0.32 (on a 0-1 scale), about half that of peers, correlating with weaker visitation outcomes. Regression analysis showed that an increase in CMSI by 1 point is associated with an increase in attendance by +12.4 p.p. and the introduction of internationally recognized certification by +3.2 p.p. The results confirm the importance of integrating a certification system, a balanced PESO media mix, and open data to enhance ecotourism's competitiveness. Future research is advisable to model stress indices for parks through 2030 and assess the impact of the transition to owned or shared dominant communication channels on demand sustainability and ecosystem conservation.

Cities are the main centres of economic growth and spatial development in Kazakhstan; therefore, studying their formation and dynamics is of particular relevance. The purpose of the study is to identify regional differences and patterns in urbanisation processes by analysing social, economic, and geographical factors that determine the dynamics of urban growth. The methodological framework includes comparative, statistical, and GIS analysis, as well as correlation and regression methods, aimed at studying the interrelationships among urbanisation levels, demographic changes, infrastructure development, and the quality of education. The empirical database is based on official data from the Bureau of National Statistics, the UNFPA, and the World Bank for 2014-2024. The results showed that the share of the urban population in Kazakhstan increased from 54% in 2014 to 60% in 2024, with the most significant increases observed in Almaty (+200 thousand) and Astana (+150 thousand). Large agglomerations concentrate economic activity and human capital, while small, single-industry cities face depopulation and a lack of infrastructure. A stable relationship has been established between the level of socio-economic development of the region and the quality of education: the integral indicators of educational achievement are 76-78% in Astana, 73-75% in Almaty and 68-70% in Shymkent. The practical significance of the results is determined by their applicability in shaping regional policies, spatial planning strategies, and sustainable urban development programs.

The participation of women in the information and communication technology (hereinafter – ICT) sector remains one of the key challenges for the digital transformation and inclusive economic development of Kazakhstan. The purpose of this study is to identify the structural, institutional and innovative factors influencing the involvement of women in entrepreneurship and management in the field of ICT. The methodological framework is based on quantitative analysis and binary logistic regression. Empirical data from the World Bank's Enterprise Survey (2024) were used, which included 1,013 companies, of which 26.9% were female-owned (≥50% female ownership or presence of a female top manager). Descriptive statistics show that most women are involved in small- and medium-sized businesses: the average company size with a female manager is 53 people versus 100 or more male employees. The econometric assessment revealed that the size of the firm is the most significant factor: an increase in the number of employees per person reduces the likelihood of female participation by 0.05 percentage points (β = - 0.0026; p < 0.01). The remaining variables demonstrated statistically insignificant but significant negative effects. connections, which indicates the presence of hidden structural obstacles. The results confirm that the key barriers remain limited access to financial resources, weak scaling opportunities for women's businesses, and the structural concentration of women in smaller and younger ICT companies. Strengthening women's participation requires targeted support measures, including loan guarantees, scaling programs, and institutional mechanisms for the development of a gender-sensitive digital ecosystem. 

Food security among the elderly population is a pressing issue with multifaceted implications for health and well-being. The study aims to systematically map the global research landscape on food security among the elderly population and identify dominant thematic clusters, influential publications, and structural research gaps. A scientometric methodology was applied, combining descriptive statistics and network analysis using Scopus data for 1996-2024.  Descriptive statistics and network analysis methods were employed using VOS viewer software for data processing and visualization. Descriptive statistics revealed a sharp acceleration in research output after 2011, with publication dynamics well captured by a 4th-degree polynomial model (R² = 0.9288). The research is highly interdisciplinary, spanning agricultural and biological sciences, medicine, and social Sciences. The United States, China, and the United Kingdom lead in publication output, while the Chinese Academy of Sciences (55 publications) and the National Natural Science Foundation of China (92 funded studies) are the key institutional and financial contributors. The analysis confirms the field's complexity and interdisciplinary nature and reveals critical gaps, particularly the lack of longitudinal and qualitative studies. A critical structural gap was identified between biological research and socio-policy studies, indicating limited integration across disciplinary boundaries. The systematized knowledge and identified research structure serve as a robust basis for policymakers and researchers to develop targeted interventions and define new, high-priority research directions.

Digital transformation is fundamentally reshaping the landscape of Kazakhstan’s hospitality industry, creating new opportunities and challenges for market participants. This study examines the influence of digitalization and innovation on the development trajectory of the national hotel sector, identifying key transformation drivers and assessing their impact on operational performance. The empirical dataset includes information from 127 hotels for the period 2014–2024, covering indicators of digital maturity, innovation activity, and financial outcomes. The methodology integrates correlation analysis, regression modeling, and cluster analysis to provide a comprehensive evaluation of transformation processes. The results reveal a strong positive relationship between the digitalization index and core operational metrics: hotels with high digital maturity demonstrate revenue per room 58% above the market average and occupancy rates 28 percentage points higher. Significant heterogeneity of digital development is observed: only 27% of hotels qualify as digital leaders, whereas 31% remain technologically lagging. A pronounced regional gap persists, with capital cities outperforming peripheral regions by a factor of three in the digitalization index. The COVID-19 pandemic accelerated the adoption of contactless technologies by 3.7 times, establishing digital services as a baseline expectation among guests. The study confirms that successful digital transformation requires an integrated approach that combines technological innovation, organizational change, and the development of digital competencies. The findings hold substantial relevance for shaping digital development strategies of hospitality enterprises and informing innovation-supporting sectoral policies.

Tourism is one of Kazakhstan's most promising sectors, capable of making a significant contribution to economic diversification, employment, and regional development. The purpose of the study is to assess the effectiveness of management in Kazakhstan's tourism sector and analyze its impact on sectoral and regional development. The research methodology is a mixed approach that combines quantitative and qualitative methods, as well as correlation and regression analyses. The empirical base consisted of data from a survey of 47 tourism enterprises in the Almaty, Akmola, and Mangystau regions for 2015-2024, as well as the results of 23 semi-structured interviews with managers and industry experts. The results of the study showed that the level of managerial efficiency varies significantly: the average TMEI value was 54.2 points, while the gap between large and small enterprises reached 33.2 points. A strong positive relationship was found between TMEI and industry development indicators: the growth of international tourist arrivals (r = 0.78; p < 0.001), tourist spending (r = 0.72), the contribution of tourism to regional GDP (r = 0.65), and the online reputation of destinations (r = 0.81). Regression analysis confirmed that managerial efficiency is a statistically significant factor in enterprises' financial performance (β = 0.34; p = 0.015). The prospects for further research include expanding the sample, conducting panel and longitudinal studies, and adapting the TMEI index to monitor the effectiveness of tourism policy and conducting comparative analyses across countries with economies in transition.

Given the high dependence of Kazakhstan's economy on capital-intensive industries, the importance of analyzing income distribution and the factors that determine the strengthening or weakening of economic inequality is increasing. The purpose of this study is to analyze the dynamics of income distribution in Kazakhstan by comparing the rates of return on capital and economic growth. The research methodology is based on Piketty's conceptual framework and includes constructing integral indicators of return on capital (r-index) and economic growth (g-index) from normalized macroeconomic and industry indicators. The empirical base of the study comprises official statistical data from the Bureau of National Statistics of the Republic of Kazakhstan for the period 2010-2024. The results showed that in 11 of the 15 analyzed years, economic growth outpaced the return on capital (g > r), indicating a more balanced income distribution. During 2010-2016, the gap between the g-index and the r-index remained positive, peaking at +0.42, reflecting the dominance of economic growth over capital incomes. In 2017-2018 and in 2020. The return on capital exceeded economic growth, with the difference reaching -0.08, indicating an increase in income inequality and income concentration in capital-intensive sectors. The directions of future research relate to the possibility of using the r–g approach to monitor the distributional effects of macroeconomic policy, as well as to expanding the analysis at the regional level and including institutional factors of income redistribution.