The informal economy remains a stable and multidimensional phenomenon, especially in developing regions, where its dynamics are determined by a combination of institutional constraints and external shocks. The aim of the study is to develop a predictive model for assessing informal economy factors in Central African and Mediterranean countries based on machine learning methods. The methodological basis of the research includes the use of modern machine learning algorithms such as Random Forest, XGBoost, Support Vector Regression (SVR) and Elastic Net, using nested cross-validation (5-fold) and Bayesian hyperparameter optimization. The empirical base consisted of panel data for 28 countries (12 Central African countries and 16 Mediterranean countries) for the period 2005-2023. The share of employment in the informal sector was used as a dependent variable, while institutional indicators (quality of regulation, social spending, education) and external determinants (foreign direct investment, remittances, trade openness, and geopolitical risk) were used as factors. An analysis of the importance of the attributes shows that the quality of institutions and the coverage of social protection are the dominant internal predictors, while trade volatility and the influx of remittances act as critical external variables. Random Forest (R2 = 0.983; MAPE = 2.57%) and SVR (R2 = 0.982; MAPE = 2.17%) also confirmed the high accuracy of forecasting. It was found that among the factors, the geopolitical risk index has the greatest influence (up to 0.86 in correlation), as well as institutional indicators the quality of regulation (up to -0.96) and social spending (up to -0.93). The results show that external shocks can have a comparable or stronger impact on the level of informality compared to internal institutional factors.

The transition to a low-carbon economy is increasing pressure on industrial companies, especially in resource-dependent countries where a significant share of production, exports, and investment is tied to carbon-intensive sectors. The purpose of the article is to assess the risks of the carbon transition in Kazakhstan's industrial economy and to identify the main factors influencing enterprises' carbon risk levels. The methodological basis of the study includes the calculation of the composite carbon risk index (CRI), correlation analysis, panel regression with fixed effects, and the construction of a matrix of carbon transition risks and opportunities. The empirical base of the study covers the period 2011-2025 and includes data from the Bureau of National Statistics of the Republic of Kazakhstan, the Ministry of Energy of the Republic of Kazakhstan, reports from international organizations, as well as annual and ESG reports from 12 large industrial companies in Kazakhstan. The results show that for 2011-2025. The CRI index decreased from 0.72 to 0.53, and the industry's carbon intensity decreased by 18.4%. Panel regression showed that the main factors of carbon risk are carbon intensity of production (β=0.614; p<0.001), outdated equipment (β=0.441; p<0.01), and green financing (β=-0.383; p<0.01). The model explains 71.2% of the intra-company variation in CRI. The greatest reduction in risk was noted in the electric power industry (-31.8%), the lowest in the mining sector (-8.8%). The results confirm the need for technological modernization, expansion of green financing, and the development of industry-specific mechanisms to manage carbon transition risks.

In the context of administrative transformations and the enlargement of territorial units in Vietnam, the problem of uncertainty of the origin of products is increasing, which affects the stability of local markets and consumer behavior. The aim of the study is to assess the impact of regional brand perception on loyalty to local brands, as well as to analyze the moderating role of uncertainty of origin in the context of provincial unification. The paper uses a quantitative approach using the PLS-SEM method. The empirical base consisted of data from a survey of 628 households in North Vietnam. The results showed that the perception of a regional brand has a positive and statistically significant effect on loyalty (β = 0.257; p < 0.001), while uncertainty of origin has a negative effect (β = -0.306; p < 0.001) and weakens this dependence (moderating effect β = -0.200; p = 0.007). The model explains 28.7% of the loyalty variation (R² = 0.287), which indicates a significant but vulnerable role of regional branding in the context of institutional changes. The results obtained emphasize the need to increase the transparency of information about the origin of products and the consistency of regional branding strategies in order to maintain the economic stability of local markets. By providing empirical evidence from an evolving administrative context, the study contributes to regional marketing literature and offers practical insights for policymakers, cooperatives, and producers aiming to safeguard local economic value amid structural reforms.

In the context of the transformation of consumer behavior and the growing importance of intangible assets, the study of factors determining recommendation behavior in the art market is becoming particularly relevant. The purpose of this study is to identify the influence of consumer values on the recommendation behavior of consumers in the art market, taking into account the mediating role of hedonic and eudaimonic happiness. An online survey was conducted with 342 MZ generation respondents. Five consumption values (functional, emotional, social, epistemic, and ethical) were measured along with two types of happiness and word-of-mouth (hereinafter WOM). Structural equation modeling and bootstrapping were used to test the hypothesized relationships and mediating effects. The analysis results show that social (β = 0.284; p < 0.001), epistemic (β = 0.205; p < 0.001) and ethical (β = 0.229; p < 0.001) values have a significant impact on eudaimonic happiness, while emotional (β = 0.240; p < 0.001) and social (β = 0.289; p < 0.001) values significantly affect hedonic happiness. The study identifies dual hedonic and eudaimonic pathways through which consumption values shape WOM in the arts retail context. The results obtained confirm that consumer happiness is a key behavioral mechanism for the transformation of consumer values into recommendatory behavior, which is important for developing strategies for the development of the art market and improving the effectiveness of marketing communications.

In the context of digital transformation and accelerated technological development, employees' competitiveness is increasingly determined not only by professional knowledge but also by the ability to master new technologies, adapt to change, and continuously develop their competencies. This study aimed to explore how technological competencies, openness to learning, adaptability, and willingness to retrain are interrelated and how these factors influence employees’ organizational commitment. The methodological basis of the study was exploratory factor analysis, evaluation of scale reliability using Cronbach's alpha, Pearson correlation analysis, and linear regression analysis. The empirical basis of the study was an online survey of 281 employees of small and medium-sized enterprises in Hungary conducted in January 2026. The results empirically supported the hypothesis that technological competence, learning orientation, adaptability, and willingness to retrain are integrated into a single adaptive technological human capital (hereinafter ATHC) index (Cronbach’s alpha = 0.837). ATHC showed a strong, positive relationship with affective organizational commitment (r = 0.758; p < 0.001) and explained 57.4% of its variance. However, a weak but significant positive relationship was found for continuance organizational commitment (r = 0.220; p < 0.001), which did not support the theoretically hypothesized negative relationship. The results indicate that developing adaptive technological human capital can not only enhance employees’ employability and adaptability but also contribute to organizational competitiveness by increasing organizational commitment. Thus, in the digital economy, adaptive technological human capital is an important resource for enhancing employee resilience, strengthening organizational commitment, and ensuring long-term organizational competitiveness.

Increased competition between territories highlights the need for a deeper understanding of the relationship between competitiveness and the brand of the territory as factors of sustainable regional development. The purpose of this study is to determine the relationship between the categories “competitiveness of the territory” and “brand of the territory” through a comparative analysis of their content. The study uses a systematic review of the literature based on the PRISMA method in combination with retrospective, comparative and spatial analysis methods. The data was processed and systematized using Python programming language tools. The empirical basis of the study was 1972 scientific publications, including 690 articles by Russian authors selected from the database. eLibrary.ru and 1,282 foreign publications identified through Google Scholar, covering the entire research period without time limits. The results showed that scientific interest in territorial competitiveness began to form in the late 1970s, while research on the brand of the territory intensified only since 1998Comparative analysis identified eight groups of characteristics shaping the conceptual content of the studied categories, including socio-demographic, financial-economic, natural-recreational, administrative-political, cultural, infrastructural, innovative, and informational dimensions. The findings reveal that territorial competitiveness and place branding are largely based on an overlapping set of characteristics, however, place branding additionally incorporates associative attributes such as symbols, images, and identity. It was also found that, by 2020–2024, domestic and international studies had converged toward similar conceptual approaches to the interpretation of these categories.

Migration is an important factor of socio-economic development, influencing labor markets, demographic structure, human capital, and regional development. This study aims to analyze the dynamics and spatial disparities of external migration in Kazakhstan for 2001–2024 and to assess the role of socio-economic factors, particularly real household income, in shaping migration inflows. The study applies comparative cross-country analysis, regional spatio-temporal analysis, Pearson correlation analysis, OLS regression with Newey–West standard errors, the Augmented Dickey–Fuller test, residual-based cointegration analysis, and a first-difference model. The results show that the highest positive migration balances were recorded in Almaty city, Almaty region, Mangystau region, and Astana city, while negative values remained in North Kazakhstan, East Kazakhstan, Karaganda, Abay, Zhambyl, and Ulytau regions. Correlation analysis revealed strong positive associations between migration and GDP (r = 0.92), investment (r = 0.91), construction volume (r = 0.90), and real household income (r = 0.89), while poverty showed a negative correlation (r = -0.81). The results of the OLS regression showed a statistically significant positive relationship between real incomes and migration inflows. However, the cointegration test did not confirm a stable long-term relationship (p = 0.144), and the first-differences model did not reveal a statistically significant short-term relationship (p = 0.3454). The results show that migration processes in Kazakhstan are related to the income level of the population, but at the same time depend on a broader set of factors, including the state of the labor market, regional differences, infrastructure and institutional conditions.

The wage inequality remains one of the key problems of the Kazakh labor market, as wage differences are formed not only by individual characteristics of employees, but also by regional, sectoral, and gender employment patterns. The aim of the study is to quantify the relative contribution of the region of employment and the type of economic activity to the intergroup wage differentiation in Kazakhstan, as well as to determine the dominant factor based on the decomposition of the explained variance. The research methods include a semi-logarithmic regression model with dummy variables of the region and industry, employee weighting, robust standard errors, and Shapley decomposition. The results showed that the selected factors explain 75% of the wage variation between the analyzed groups. In 15 of the 20 regions, wages are statistically significantly lower than in Almaty. The largest industry premium relative to education was found in the mining industry (+111%) and financial activities (+101%), while the negative discount ranges from 11% to 18%. After accounting for the region and industry, the gender pay gap is estimated at about 12%. Shapley's decomposition showed that the regional factor explains 21% of the variance of the logarithm of wages, and the industry factor explains 45%. The results of the study can be used by government agencies to adjust employment promotion, retraining, and regional development programs.

In the context of increasing global risks, pandemics, urbanization and socio-economic polarization, the problem of mortality inequality is becoming one of the key problems of modern distributive and social science. The purpose of this study is to analyze the long-term evolution of life expectancy inequality and assess the impact of modern socio-economic imbalances and global risks on changing trends towards equalization of mortality. The article uses a mixed approach combining historical and comparative interpretation, life table-based distribution analysis, and qualitative institutional analysis. The study uses data from WHO, the OECD, and the results of international research in the 19th, 20th, and early 21st centuries. The results of the study showed that during the 20th century, the coefficient of life expectancy inequality in developed countries decreased significantly: in the USA from 0.476 in 1852 to 0.099 in 2002, in England and Wales from 0.443 to 0.094, in France from 0.446 to 0.083. At the same time, in the 21st century, there is a slowdown in the processes of equalization of life expectancy and an increase in socio-economic stratification of survival rates. During the COVID-19 pandemic, global life expectancy decreased by 1.8 years, while excess mortality reached about 14.9 million people. The study showed that mortality inequality is formed through the mechanisms of unequal exposure to risks, vulnerability, institutional protection and access to medical technologies. Furthermore, the study shows that the distribution of medical resources and access to them directly influence differences in survival outcomes between countries and social groups.

Дәрілік заттарға жұмсалатын жоғары жеке шығындар үй шаруашылықтарының қаржылық осалдығын күшейтіп, медициналық көмекке қолжетімділікті төмендетуі мүмкін, әсіресе денсаулық сақтау саласындағы өңірлік және әлеуметтік теңсіздік жағдайында. Осы зерттеудің мақсаты Қазақстандағы дәрілік сақтандыру полисі үшін төлеуге дайындықтың әлеуметтік-экономикалық, медициналық және лингвистикалық факторлармен байланысын бағалау, сондай-ақ қазақтілді және орыстілді респонденттер арасындағы айырмашылықтардың сипатын анықтау. Зерттеудің эмпирикалық базасын Қазақстанның әртүрлі өңірлерінде жүргізілген онлайн-сауалнама деректері құрады. Қорытынды аналитикалық іріктеме өз табыс көзі бар 2695 респондентті қамтыды, оның ішінде 2044 қазақтілді және 651 орыстілді респондент болды. Зерттеуде сипаттамалық статистика, салыстырмалы талдау, t-тесттер, permutation tests және OLS-регрессия әдістері қолданылды. Нәтижелер қазақтілді респонденттер арасында дәрілік сақтандыру үшін төлеуге дайындықтың орташа деңгейі шамамен 65,4 АҚШ долларын, ал орыстілді респонденттер арасында шамамен 46,4 АҚШ долларын құрағанын көрсетті; айырмашылықтар 5% деңгейінде статистикалық мәнді болып табылады (t-test = 2,26; p < 0,024). Регрессиялық талдау төлеуге дайындықтың дәрілік заттарға ағымдағы шығындармен, денсаулық жағдайын өзін-өзі бағалаумен, тұрғылықты өңірмен, елді мекен түрімен және үй шаруашылығындағы қарым-қатынас тілімен байланысты екенін көрсетті. Зерттеу нәтижелері медициналық көмектің қолжетімділігін арттыру, емделуге байланысты қаржылық кедергілерді төмендету және Қазақстандағы денсаулық сақтау экономикасының орнықты дамуын қамтамасыз ету мақсатында дәрілік сақтандыру тетіктері мен коммуникациялық саясатты сараланған тәсіл негізінде әзірлеудің маңыздылығын айқындайды.