This study aims to predict whether university students will make efficient use of Artificial Intelligence (AI) in the coming years, using a statistical analysis that predicts the outcome of a binary dependent variable (in this case, the efficient use of AI). Several independent variables, such as digital skills management or the use of Chat GPT, are considered.The results obtained allow us to know that inefficient use is linked to the lack of digital skills or age, among other factors, whereas Social Sciences students have the least probability of using Chat GPT efficiently, and the youngest students are the ones who make the worst use of AI.

The purpose of this study is to identify the effects of multidimensional (fuzzy) inequalities and marginal changes on the Gini coefficients of various factors. This allows a range of social policies to be specifically targeted to reduce broader inequalities, but these policies are focused primarily on health, education, housing, sanitation, energy and drinking water. It is necessary to target policy areas that are unequally distributed, such as those with access to unevenly distributed drinking water policies. The data are from the Household and Consumption Survey of 6695 households in 2003 and 9259 households in 2011. This paper uses Lerman and Yitzhaki’s method. The results revealed that the main contributors to inequalities over the two periods were health and education. These sources have a potentially significant effect on total inequality. Health increases overall inequalities, but sources such as housing, sanitation and energy reduce them. This article provides resources to disadvantaged and vulnerable target groups. Multiple inequalities are analyzed for different subgroups of households, such as place of residence and the gender of the head of household. Analyzing fuzzy poverty inequalities makes it possible to develop targeted measures to combat poverty and inequality. This study is the first to investigate the sources of Gini’s fuzzy inequality in Chad via data analysis techniques, and in general, it is one of the few studies in Saharan Africa to be interested in this subject. Some development policies in sub-Saharan Africa should therefore focus on different sources (negative effect), sources (positive effect) and the equalization effect.

The nexus between foreign direct investment, natural resource endowment, and their impact on sustained economic growth, is contentious. This study investigates the resource curse hypothesis and the effects of FDI on economic growth in Kazakhstan. The study covers the period from 1990 to 2022 and employs the Autoregressive Distributed Lag (ARDL) model and Toda-Yamamoto causality methods. The Bounds cointegration results reveal the existence of long-term equilibria between per capita GDP and the predictors. The findings reveal a significant impact of oil rents on economic growth, contradicting the resource curse hypothesis and suggesting a resource boon instead. In stark contrast, the impact of FDI on Kazakhstan’s economic growth is found to be insignificant, despite the presence of a causal nexus. Furthermore, economic freedom and export diversification have a positive significant impact on economic growth, while inflation exhibits a negative but significant impact. Although governance has a direct impact on GDP per capita, it is deemed insignificant, as the negative average governance index implies poor governance. Expectedly, the result establishes a causal effect between export diversification, economic freedom, governance, oil rents, and economic growth. This underscores the fundamental role played by the interplay of diversification, economic freedom, governance, and oil rents in fostering sustainable economic growth. In addition, economic freedom stimulates gross fixed capital formation, indicating that it enhances domestic investment. Notably, the findings refute the crowding-out effect of FDI on domestic investment in Kazakhstan. Consequently, to escape the resource curse and the Dutch disease syndrome, the study advocates for enhancing good governance capabilities in Kazakhstan. Thus, we recommend that good governance could reconcile the twin goals of economic diversification and deriving benefits from oil resources, ultimately transforming oil wealth into a boon in Kazakhstan.

This study explores the determinants of political participation among Thai youth, focusing on the roles of political interest, knowledge, and efficacy. Employing stratified random sampling, data were collected from 191 university students in Bangkok. Structural Equation Modeling (SEM) via Smart PLS was utilized to test hypotheses regarding the direct and mediating effects of political interest and knowledge on participation, highlighting the mediating role of political efficacy. The findings indicate that political efficacy significantly enhances participation, while political interest boosts knowledge significantly but does not directly influence efficacy. Furthermore, political knowledge positively affects efficacy but not participation directly. Notably, the indirect effects of political interest on participation through efficacy alone are insignificant, but the pathways from interest to participation through both knowledge and efficacy, and from knowledge to participation through efficacy, are significant. These results elucidate the complex interactions between political interest, knowledge, and efficacy in shaping the political engagement of Thai youth.

In Urban development, diversity respect is needed to prioritize and balance the urban development design for sustainable eco-city development. As a result, this research aimed to investigate the causal factor pathways of social network factors influencing sustainable eco-city development in the northeastern region of Thailand through a quantitative research approach. With the aim to survey insightful information, the analysis unit was conducted at the individual level with three hundred and eighty-three (383) samplings in Khon Kaen and Udon Thani provinces, including univariate analysis and multivariate analysis, using path analysis and multiple linear regression. The study results indicated that two pathways of social network factors influencing sustainable eco-city development were indirect influence factors. The indirect influence factor consists of information exchange, benefits exchange in the network, and members’ role in the social network. Additionally, the study revealed that the pathway has influences through social network types and the economic and social dimensions of sustainable cities (R² = 0.330). Therefore, this study concluded that sustainable eco-city development should be implemented through community networks and economic and social network development for environmental development through social network types.