The territorial planning approach to allocating productive forces is based on the fact that territories have competitive advantages in producing specific products. However, in agriculture, the advantages principle cannot be used to shape the allocation patterns, due to a variety of intervening factors, such as the climatic and environmental conditions for agricultural production and the quality of land and availability of water. In the case of Russia, one of the most diverse countries in terms of the territorial disparities in agricultural production, this study examines the location and development patterns of the agricultural sector. The study identifies the competitive advantages of territories by comparing localization of agricultural production, production costs, performance, and profitability of agricultural producers, as well as prices of agricultural products in 78 different administrative regions in Russia. The study reveals which regions have more advantageous conditions for over-concentrating energy capacities, labor resources, fixed capital, and investments. However, at a certain point, over-concentrated production forces can lead to a deterioration in the performance of farmers due to an increase in capital intensity. Therefore, countries with significant regional differences in agricultural production should adjust their spatial development patterns according to the parameters of territories’ comparative advantages.

The rapid advancement of information and communication technology has greatly facilitated access to information across various sectors, including healthcare services. This digital transformation demands enhanced knowledge and skills among healthcare providers, particularly in comprehensive midwifery care. However, midwives in rural areas face numerous challenges such as limited resources, cultural factors, knowledge disparities, geographic conditions, and technological adoption. This research aims to evaluate the impact of AI utilization on midwives’ knowledge and behavior to optimize the implementation of healthcare services in accordance with Delima Midwife Service standards in rural settings. The analysis encompasses competencies, characteristics, information systems, learning processes, and health examinations conducted by midwives in adopting AI. The research methodology employs a cross-sectional approach involving 413 rural midwives selected proportionally. Results from Partial Least Squares Structural Equation Modeling indicate that all reflective evaluation variables meet the required criteria. Fornell-Larcker criterion demonstrates that the square root of AVE is greater than other variables. The primary findings reveal that information systems (0.029) and midwives’ competencies (0.033) significantly influence AI utilization. Furthermore, midwives’ competencies (0.002), characteristics (0.031), and AI utilization (0.011) also significantly impact midwives’ knowledge and behavior. Midwives’ characteristics also significantly affect their competencies (0.000), while midwives’ learning influences health examinations (0.000). Midwives’ knowledge and behavior affect the transformation of healthcare services in rural midwifery (0.022). The model fit results in a value of 0.097, empirically supporting the explanation of relationships among variables in the model and meeting the established linearity test.

Artificial intelligence has transformed teachers’ teaching models. This article explores the application of artificial intelligence in basic education in Macao middle schools. This study adopts case analysis in qualitative research, using a total of eight cases from the innovative technology education platform of the Macau education and Youth Development Bureau. These data illustrate how Macao’s artificial intelligence technology promotes teaching innovation in basic education. These eight cases are closely related to the application of artificial intelligence in basic education in Macao. The survey results show that Macao’s education policy has a positive effect on teaching innovation in artificial intelligence education. In teaching practice, the school also cooperates with the government’s policy. The application of AI technology in teaching, students’ learning styles, changes in teachers’ roles, and new needs for teacher training are all influential.

This study aimed to examine the impact of Environmental, Social, and Corporate Governance (ESG) scores and Country Governance Indicators (CGI) on companies’ value. The study procedures were carried out by creating a linear empirical model where the dependent variable was companies’ value. In addition, the variables of interest in the model were ESG scores and CGI. Analysis was carried out on annual data from 278 non-financial Asian companies spanning 11 years from 2011–2021. The feasible generalized least squares (FGLS) method was used for estimation due to the presence of serial correlation and heteroscedasticity in the data obtained. The results showed the presence of a positive relationship and correlation between ESG scores and companies’ value. Meanwhile, CGI had a negative impact, revealing the potential difficulties caused by country governance framework. This study also found a positive correlation between CGI and ESG on company value. These findings have important practical contributions emphasizing the significance of ESG factors in improving companies’ value and the complex relationship between country governance and corporate valuation.

This article presents a comprehensive analysis and strategic framework for enhancing social welfare in Kazakhstan through the adoption of international social security standards. This article aims to formulate scientific and practical recommendations for enhancing the legal framework governing Kazakhstan’s social security system. It posits that integrating international social protection standards is pivotal for refining national legislation and charting future developmental courses. Employing a novel methodology, this study analyzes key documents from the International Labour Organization (ILO), the United Nations, the Commonwealth of Independent States (CIS), and the Eurasian Economic Union (EAEU). It also examines efforts to assimilate these international norms into Kazakhstan’s social security laws. The investigation reveals a stagnation in the evolution of the nation’s social sector, marked by a dearth of innovative ideas and initiatives to elevate the subpar social security standards. The adoption of international social standards emerges as a catalyst for rejuvenating the national social sphere, aiming to elevate the Kazakhstani social protection system to meet global benchmarks. This research outlines the pathways for Kazakhstan’s ratification of and accession to key social protection instruments and offers expert recommendations to support this endeavor. The conclusions and recommendations developed are poised for application in legislative reforms, aiming to amend and enhance existing laws to foster a more robust and inclusive social security framework. The findings suggest that the adoption of international social security standards not only contributes to the improvement of individual lives but also fosters social cohesion and economic stability. The article concludes with tailored recommendations for Kazakhstan, highlighting the role of stakeholder engagement, phased implementation, and continuous evaluation in the successful integration of global social security norms. This research contributes to the ongoing discourse on social security reform, offering a valuable perspective for scholars, policymakers, and practitioners involved in social welfare enhancement efforts in Kazakhstan and similar contexts.

The impact of crude oil price fluctuations on the real effective exchange rate (REER) has been widely debated, but specific evidence, particularly for developing countries in Southeast Asia, is scarce and inconclusive. This issue, especially concerning both short- and long-term relationships, remains inadequately addressed, affecting these countries for risk management related to oil price fluctuations. This study aims to fill this gap by examining these relationships in Thailand context to provide more evidence on how the REER in Southeast Asia responds to changes in crude oil prices. Monthly data of crude oil prices in Dubai market and the Thai baht REER from 2000 to 2019 were employed. Johansen co-integration test and Vector Error Correction Model (VECM) were used for analyzing long-term and short-term relationships, respectively. The results indicate a significant negative long-term relationship between crude oil prices and the REER, with a 0.31% reduction in the REER for every 1% increase in the real price of oil. However, in the short term, VECM analysis reveals significant movements in the REER in response to external shocks. On average from 2000–2019, the significant fluctuations in the REER are quickly alleviated and adjusted to its long-run equilibrium, typically by 2% in the following month following external shocks such as crude oil price fluctuations. Given these findings, which highlight the long-term relationship between the REER and crude oil prices and its short-term adjustment, it is suggested that when there is a shock from the crude oil prices, the government can strengthen short-term oil price controls or monetary subsidies to mitigate the extensive repercussions of energy market fluctuations, as such interventions would have a lesser impact on the long-term equilibrium of the REER.