This study is devoted to a comprehensive analysis of gender differences in access to information and communication technologies (hereinafter - ICT) in Kazakhstan from 2015 to 2024 and their impact on education and employment. The research methodology is based on descriptive statistical analysis, correlation methods, and the difference-by-difference (DiD) model. This approach allows us to compare the dynamics of gender inequality over time and determine how digitalization has affected the socio-economic differences between women and men. The results show a steady reduction in the gender digital gap. The difference in Internet access between men and women decreased from 2.8 percentage points in 2015 to 0.6 p.p. in 2024, and the use of mobile technologies saw an inverse shift in favor of women by 15.8 p.p. by 2024 (with a predominantly male dominance in 2016 by 1.6 p.p.). Correlation analysis revealed a strong positive relationship between Internet access and digital literacy (r > 0.9), as well as between digital skills and access to government employment platforms (r = 0.88 for men and r = 0.71 for women), which confirms the role of digitalization as a mechanism for increasing participation in the labor market. Women began to use smartphones and online platforms more actively, gaining wider access to electronic services and government resources, which facilitated their participation in the labor market and entry into formal employment systems. In addition, the study showed that gender inequality persists in higher education. As a result, the study highlights the dual nature of digitalization: on the one hand, it increases social inclusion, but on the other, it increases the persistence of structural inequality in society.

Rural poverty and labor migration are interrelated socio-economic phenomena that determine the specifics of spatial inequality between urban and rural areas. Their mutual influence manifests itself through the rural population's limited access to resources, infrastructure, labor markets, and social services, which stimulates migration flows and at the same time creates new forms of vulnerability. The purpose of this article is to conduct a comprehensive theoretical analysis of the concepts of rural poverty and labor migration, identify key stages in the evolution of scientific approaches to these phenomena, and determine analytical gaps that require further research. The methodological basis of the study consists of historical-logical, systemic, and comparative-historical approaches, as well as methods of analysis and synthesis, classification, and structural-functional analysis. Based on these methods, the theoretical concepts of classical, egalitarian, sociological, and multidisciplinary schools have been systematized. The results of the analysis made it possible to identify consistent patterns in the understanding of the phenomenon of rural poverty and its relationship with migration processes, as well as to show the multidimensionality of these phenomena through the categories of vulnerability, exclusion, and deprivation. Particular attention is paid to the gender aspect of rural poverty, reflecting structural inequality between men and women in access to resources and employment. In the future, comparative empirical studies are needed to assess the impact of different types of migration on the dynamics of household poverty, including vulnerable groups, as well as the development of methodological approaches to measuring multidimensional rural poverty, taking into account gender differences.

In the context of global digital transformation, the hospitality industry is undergoing rapid modernization, with innovations becoming a key factor in competitiveness and customer satisfaction. Kazakhstan, possessing significant tourism potential, is actively integrating digital tools such as online booking systems, artificial intelligence, and data analytics into its tourism infrastructure. The study addresses the relevance of digitalization for enhancing service quality and sustainable growth in Kazakhstan’s hospitality sector. The research is based on a mixedmethods approach combining statistical analysis, content review, and comparative methods. Data from the Bureau of National Statistics of the Republic of Kazakhstan, the Ministry of Tourism and Sports, and the World Tourism Organisation (UNWTO) reports were used. The study also includes case analyses of Kazakhstani hotels and platforms implementing digital solutions such as eQonaq and Smart Tourism. The results reveal a gradual increase in digital adoption across the hospitality sector, with large hotel chains showing high automation levels and small enterprises facing technological and human resource constraints. Between 2019 and 2024, the number of online bookings in Kazakhstan increased by 42%, while digital marketing expenditures grew by 35%. Despite these improvements, regional disparities and limited staff training remain significant barriers. The findings emphasize the importance of systematic digital transformation as a strategic priority for Kazakhstan’s tourism development. Effective integration of digital innovations can enhance operational efficiency, customer experience, and global competitiveness. The study concludes that state support, public-private partnerships, and professional training programs are critical for accelerating the digitalization of the hospitality industry.

In the context of accelerating digital transformation, environmental transition, and postpandemic recovery, employment research is increasingly shifting its focus from quantitative indicators to qualitative, stable, and sustainable aspects of work. The purpose of this study is to conduct a bibliometric analysis of publications devoted to issues of quality, stable, and sustainable employment using the Web of Science database for the period 2020–2024. The bibliometric network visualization was carried out using VOSviewer software, which enabled the identification of clusters of interrelated keywords. Two groups of keywords were applied for metadata selection. The first group included general terms related to employment: “employment,” “job,” “work,” “occupation,” “labour”. The second group consists of the terms “technological change”, “decent employment”, “commitment”, and “job satisfaction”. Cluster analysis helps to identify four main thematic groups reflecting the key areas of scientific research in this area. The results showed that the current research agenda is structured around clusters related to employee satisfaction, technological and globalization challenges, decent work and inequality, and education, gender, and employment quality. Key directions in employment research, as well as their structural interrelations, have been identified. Digitalization and the green transition influence the evolution of scientific approaches to decent, stable, and high-quality employment. The results of the study can be applied in policy-making and analytical research.

Today, business valuation is a key tool for making managerial and investment decisions, especially in restructuring, strategic planning, and capital raising. One of the most common approaches to valuation is the discounted cash flow method (hereinafter referred to as DDP), which allows you to bring future cash flows to their current value. The purpose of this study is to identify the potential risks of using the DDP model to assess the market value of a business, using the example of the Toyota Motor Corporation, and to propose approaches to minimise them. The work used Toyota Motor Corporation's open financial reports, including revenue, cost, EBITDA, net profit, and macroeconomic indicators of the Japanese economy. The research methodology combines theoretical literature analysis and practical modelling: a DDP model was built based on data from a public manufacturing company, using elements of risk management (sensitivity analysis, scenario analysis, and modelling of the post-forecast period). The results of the study showed that Toyota Motor Corporation's net profit increased (+103.4%), and the forecast of free cash flows increased from 426,564 to 513,563 million yen in the period 2025-2030. With a discount rate of 10.59% and a fixed growth rate of 1.06%, the high sensitivity of the final cost to changes in key parameters, especially the discount rate and macroeconomic assumptions, was revealed. The results of the study show the high sensitivity of the final assessment to changes in key parameters, particularly the discount rate and growth rates, as well as the model's vulnerability to macroeconomic volatility and production risks.