Human capital development is considered as one of the key factors of sustainable economic growth, however, for Nigeria, the issue of the comparative impact of government spending on health and education in terms of current and capital expenditures remains poorly understood. The purpose of this study is to assess the impact of human capital development on economic growth in Nigeria. The methodological basis is the distributed lag autoregression model (ARDL), which makes it possible to evaluate the short- and long-term effects between variables with a mixed order of their integration. The empirical base covers annual data for Nigeria from 1970-2024 on GDP growth rate, government current health expenditure, Government capital expenditure on health, Government current education expenditure and Government capital expenditure on education. The results showed that the economic growth variable is stationary at the level, while the other variables are stationary in the first differences, which confirms the applicability of the ARDL approach. ARDL's long-term estimates showed that current education expenditures have a positive and statistically significant impact on economic growth (β = 0.039955; p = 0.0067), as do capital expenditures on education (β = 0.072462; p = 0.0030), while the impact of healthcare costs turned out to be statistically insignificant: for capital expenditures β = -0.03087 (p = 0.6185), for current expenditures β = -0.06336 (p = 0.1414). The results show that educational expenditures, especially capital investments in educational infrastructure, make the greatest contribution to Nigeria's economic growth. 

Given the high external volatility and structural vulnerability of the Kazakh economy, there is an increasing need to assess the macroeconomic and social effects of monetary policy. The purpose of this study is to study the relationship between monetary policy, consumer demand, poverty and income inequality in Kazakhstan during the crisis and post-crisis periods. The empirical analysis is based on quarterly macroeconomic data for 2006-2023 and annual social indicators for 2001-2023. Time series models with lag structures and multiple linear regression were used to evaluate transmission mechanisms. The results show that an increase in the base rate has a statistically significant disinflationary effect with a lag of two quarters (coefficient -0.059; p < 0.01) and reduces economic growth with a lag of three quarters (coefficient -0.030; p < 0.01). Economic growth has a positive effect on consumption (coefficient 1,093; p < 0.05), while inflation has a restraining effect (coefficient -0.871; p < 0.10). The results obtained indicate that the influence of monetary policy on social indicators is mainly indirect and is implemented through the channels of inflation, economic growth and income dynamics, which justifies the need for coordination of monetary and fiscal instruments to achieve the goals of inclusive development. The findings of this study provide policy makers with valuable information for developing a balanced monetary policy that simultaneously ensures macroeconomic stability and promotes inclusive social development. 

This study investigates how integrated strategic communication influences the process of consensus building and organizational readiness during digital innovation in the retail banking industry. Although many institutions adopt digital technologies, innovation performance often remains limited due to weak employee alignment and ineffective communication systems that fail to bridge the gap between strategy and execution. A multiple case study design was employed, comparing a public retail banking organization (Company A) and a private retail banking organization (Company B) that both implemented large-scale digital innovation projects. Data was collected through document analysis, semi-structured interviews, and surveys structured around Lancefield’s (2022) five principles of strategic communication: comprehensiveness, personalization, timeliness, transparency, and consistency. Findings indicate that although Company A recognized the importance of digital transformation, significant gaps were observed between the perceived importance and the actual implementation of strategic communication mechanisms. Employees rated the importance of communication dimensions highly (means ranging from 5.70 to 5.98 on a seven-point scale), while the current level of implementation was evaluated considerably lower (means between 4.08 and 4.38), revealing gaps of approximately 1.5-1.9 points. The largest gap was found in terms of timeliness and transparency, which indicates a lack of efficiency and openness of communication processes. Strategic communication functions as a critical mechanism linking technological innovation with cultural and psychological alignment within organizations. The study provides valuable theoretical and practical implications by presenting a communication-based framework for optimizing and successfully improving digital transformation outcomes in financial institutions. 

With the increasing frequency and depth of crisis shocks, the analysis of factors that determine the recovery of tourism industry enterprises across various institutional contexts is becoming particularly relevant. The purpose of the study is to assess the impact of geographical location and marketing activities on anti-crisis adaptation and revenue dynamics of tourism organizations, and to analyze the relationship between operational changes and marketing strategies during the crisis. The research methodology is based on structural equation modeling (hereinafter – SEM), which enables simultaneous assessment of direct, indirect, and moderating effects among key variables. The empirical base of the study includes data from a survey of 342 tourism organizations from 40 countries, including 187 companies registered in Kazakhstan (54.7%) and 155 companies from other countries (45.3%). The data were collected in 2025 using a questionnaire and cover marketing activities, operational changes, crisis challenges, geographical location, and a subjective assessment of the crisis's impact on revenue. The results of the study showed that geographical location is the only statistically significant predictor of revenue changes (β = -0.157; p = 0.004): companies operating in Kazakhstan, on average, demonstrated higher revenue indicators compared with organizations from other countries. Marketing activities proved to be the strongest factor influencing the implementation of operational changes (β = 0.385; p < 0.001). The results indicate the need to develop context-specific anti-crisis strategies and confirm the role of marketing activities as a key driver of organizational adaptability, rather than as a direct source of financial recovery. 

In the context of increasing macroeconomic instability and increasing credit risks, the analysis of the factors of formation of problem mortgage loans in the banking system is becoming particularly relevant. This study aims to develop and propose a conceptual project-based framework, the NPL Project Approach that conceptualizes the management of non-performing mortgage loans as an integrated project cycle. The methodological basis of the research consists of methods of descriptive statistics, correlation analysis and multiple regression modeling. The empirical basis of the study consists of data collected from the Bureau of National Statistics and the National Bank of the Republic of Kazakhstan for the period 2020-2024, including indicators of household income, gross domestic product, inflation, interest rates, deposits and overdue debt. The analysis results show that the average level of problem loans in the European Union decreased from 2.6% in 2020 to 1.9% in 2024, reflecting an increase in the effectiveness of credit risk management systems. In Central Asian countries, the level of problem loans in Kazakhstan decreased from 6.9% in 2020 to 3.1% in 2024, indicating a partial improvement in the quality of the loan portfolio, but sensitivity to the growth of mortgage lending remains. The prospects for further research include empirical verification of the model based on case studies of emerging market banks, quantification of its impact on loan portfolio performance, as well as adaptation of the approach to other non-mortgage lending segments.

This study investigates how integrated strategic communication influences the process of consensus building and organizational readiness during digital innovation in the retail banking industry. This study examined how the technological attributes of AI-based short-form content recency, reliability, and shareability effect cognitive attributes, specifically convenience and usefulness, and how these cognitive responses subsequently influence satisfaction and repurchase intention. Analyzed differences based on consumers’ levels of functional and economic value. A survey was conducted with 400 consumers who had viewed AI-based short-form content and purchased the recommended product, and the research model was validated using exploratory factor analysis, confirmatory factor analysis, structural equation modeling, and multi-group analysis. The results showed that relevance and the possibility of distribution significantly increase perceived convenience (β = 0.366 and β = 0.600; p < 0.001), while reliability has a positive effect on usefulness (β = 0.266; p < 0.001), which, in turn, significantly increases the intention of repeat purchase (β = 0.921; p < 0.001). The practical significance of the study lies in substantiating the priority of increasing the perceived usefulness and trust in AI content in order to increase loyalty and repeat demand. The prospects for further research are related to expanding the sample to different age and gender groups, comparative analysis of various types of AI algorithms, as well as studying the long-term effects of personalization in the context of digital transformation of consumer markets. 

Digitalization of agriculture is one of the key factors in the structural transformation of the agricultural sector in the context of global challenges to food security and sustainable development. The purpose of this study is a comprehensive systematization and in-depth analysis of scientific publications on the digitalization of agriculture for the period 2001-2024 based on data from the international bibliographic database Scopus using bibliometric methods. The research methods include bibliometric analysis of publications indexed in the Scopus database using the TITLE-ABS-KEY protocol and VOSviewer software. The initial data covers 1,326 scientific articles for the period 2001-2024. The results showed that until 2017, only 28 publications were registered in the database, whereas in 2018-2019 their number increased from 7 to 62 (almost 10 times), and in 2020-2024 it reached the range of 129-318 articles annually. The leading positions are occupied by Russia (400 publications, about 30%), India (118), China (113), Germany (107) and Italy (90). Kazakhstan is represented by 22 publications (approximately 2%), which indicates the formation of a national research direction. The cluster analysis identified four key thematic blocks: economic and institutional, data and IoT management, sustainable development and climate, and digital platforms for the agricultural industry. The results obtained confirm that the digitalization of the agricultural sector is evolving from a technological focus to a comprehensive economic and institutional transformation and forms the basis for further empirical research on the effectiveness of digital solutions in agriculture. 

In the context of accelerating digital transformation, quantification of the impact of artificial intelligence (AI) on the structural dynamics of resource–dependent economies is becoming particularly relevant. The purpose of the study is to develop and test an integrated dynamic model to quantify the impact of AI on Kazakhstan's structural transformation and diversification. The methodological framework includes the integration of the Bass model of innovation diffusion, an expanded production function with endogenous technological progress and the task-oriented Acemoglu–Restrepo approach, as well as a multi-criteria system of industry prioritisation. The empirical basis was based on industry data from the Bureau of National Statistics of the Republic of Kazakhstan for 2020-2024. The simulation results show that for the period 2025-2035. The cumulative increase in gross value added in the analysed industries will amount to 35.3 p.p., of which 16.8 percentage points are attributable to AI. The level of AI adoption in priority sectors reaches 86.8–93.8 p.p by 2035, which exceeds the indicators of non-priority industries by 13-32 p.p. The share of priority industries in the GDP structure increases by 6.3 p.p, while total employment increases by 22.4 p.p (+1.3 million jobs). At the same time, across all sectors, there is a steady excess of the effect of creating new tasks over the effect of automation, reflecting the specifics of a resource-dependent economy with a shortage of qualified personnel. The results confirm the expediency of concentrating government support on a limited number of industries with the greatest potential for structural transformation. 

The digital transformation of the agricultural sector strengthens the role of digital infrastructure and financial inclusion as factors of productivity growth in agriculture in the context of structural modernization of the economy. The aim of the study is to assess the impact of digital infrastructure on agricultural productivity and to identify the cross—country heterogeneity of effects in economies with different levels of digitalization and institutional development. A balanced panel for 2011-2023 (26 observations) based on data from the World Bank and the International Labour Organisation was used. In the combined model, digital infrastructure demonstrates a positive and statistically significant relationship with performance (β = 0.7626; p < 0.01), with a high quality of fit (r2 = 0.946). The exclusion of pandemic years confirms the stability of the effect (β = 0.744; p < 0.01; r2 = 0.937). The cross-country analysis revealed heterogeneity: in China, the effect of digital infrastructure is positive and significant (β = 0.421; p < 0.01), while in Kazakhstan the coefficient is negative and weakly significant at the level of 10% (β = -0.483; p = 0.092), indicating differences in institutional readiness and the level of digital maturity. The results obtained confirm the importance of digital infrastructure in improving the efficiency of the agricultural sector, but demonstrate that the institutional and structural environment determines the scale and direction of this impact.