This study examines the relationship between migration (M), economic activity (EA), and the labour market (LM) in the Republic of Kazakhstan from 2000 to 2022. The research comprises three stages, namely indicator selection, data analysis, and correlation-regression analysis. The study hypotheses propose that migration has a notably adverse influence on both the labor market and economic activity. Secondary data from the World Bank and the National Bureau of Statistics of the Republic of Kazakhstan were employed, covering the years 2000 to 2022. The chosen variables encompass migration growth, GDP, labor productivity, investment in fixed assets, real wages, and unemployment rates. The research includes three latent variables: migration (M), economic activity (EA), and the labor market (LM). The measurement models for these variables show acceptable to high reliability, suggesting a sufficient association between the included variables. Regression analysis reveals a significant negative impact of migration on both economic activity and the labour market. Migration can significantly influence economic activity, unemployment rate, and real wages. The findings support the hypotheses, indicating positive economic indicators and the country's socio-economic development trends. These results are valuable for understanding population dynamics and the potential impact of migration on the economy and social processes in Kazakhstan. Overall, the study provides insights into the relationships between migration, economic activity, and the labour market, highlighting the importance of these factors in shaping the country's development.

Understanding structural dynamics and workforce segmentation has become essential for sustainable economic policy and employment regulation in the context of global economic transformation, technological change, and labour market volatility. The goal of the current study is to identify key worker groups with varying levels of employment stability, staff turnover, and personnel cost distribution. The fuzzy clustering algorithm (Fuzzy C-Means) is used as the primary method, which makes it possible to assign objects to several clusters with varying degrees of affiliation. The analysis was based on official statistics of the labor market in the Republic of Kazakhstan for the period 2013-2023. The analysis revealed three stable clusters: stable workforce flow cluster with low staff turnover (0.172) and balanced replacement (0.152); adaptive cluster with moderate instability, turnover of 0.355 and demand for labor up to 30 020 people; unbalanced cluster with high-cost variability (up to 19 billion tenge), compensation (coefficient of variation of 0.386) and maximum admission of graduates (up to 86,227 people). Kazakhstan's labor market is characterized by stability in traditional sectors, moderate adaptation in cyclical industries, and high volatility in technologically advanced and competitive segments. These results suggest the need for a differentiated employment policy that considers industry-specific characteristics and the digital transformation of the economy. Future research should investigate sector-specific models of human resource transformation and explore how employment dynamics can be integrated into strategies for sustainable and innovation-driven development.

This article examines the relationship between innovation, education and economic growth in the Republic of Kazakhstan. Many empirical studies have proved a positive relationship between innovation and economic growth, that innovation has become a major component of global economic growth. Despite the acceleration of economic growth in various countries, including Kazakhstan, the relationship between economic growth and innovation in the country remains unclear. This study examined the impact of three factors: R&D, academic staff and innovation spending on economic growth in the Republic of Kazakhstan. The identified groups of indicators of economic development consist of sub-indicators. A regression analysis was done based on statistical data from 2009 to 2021. SPSS software was used for data processing. Three pairs of hypotheses were developed. The results of the first and third groups of hypotheses are similar only in those indicators that represent the total number of participants in innovative development, whose influence on economic development becomes strong. Thus, we can conclude that there is a strong relationship between GDP and indicators of educational and innovation factors. There is a relationship between the indicators of the academic staff in R&D and all enterprises that are involved in the process of development and implementation of innovations in Kazakhstan. The proposed hypotheses were accepted. Government agencies can use the results of this study in the development of innovation policy in the country.

The object of the study is the digitalization of enterprises in the field of crop production to increase production efficiency. The problem of assessing the level of digitalization of enterprises in the crop industry and the effectiveness of implementing an industry-specific regional digital platform has been solved. The results of the study were obtained: – the analysis showed the absence of companies with an active level of digitalization, while a third (29%) have a stagnant level; – the implementation of the digital platform provides a return on investment of 25.2%; – a positive dependence of the revenue growth potential on the ADA integral score (β1 = 0.327, p = 0.002) was revealed; – the analysis showed a payback period of 0.80 years in a realistic scenario; – in the cost structure for the implementation of the digital platform, the majority (43.2%) is allocated to the technical infrastructure. The results of the study are explained by the use of the ADA model, which allows a comprehensive assessment of the level of digitalization of crop production enterprises, taking into account industry and regional specifics. The specifics of the results obtained are that this paper offers not only an assessment of the current state of digitalization, but also practical recommendations for the implementation of a digital platform adapted to the needs of the region. The practical significance of the study lies in the proposal of a specific methodology for assessing the level of digitalization of crop production enterprises. In addition, the implementation of the digital platform will create a unified information environment for all market participants, reduce costs, optimize production processes and improve interaction between stakeholders. The results of the study can be used by government agencies, agricultural enterprises and developers of digital solutions for agriculture