South Korea has experienced rapid economic development since the 1960s. However, pronounced regional disparities have concurrently emerged. Amid the escalating regional inequalities and persistent demographic challenges characterized by low fertility rates, regional decline has become a pressing issue. Therefore, the feasibility of expanding transportation networks as a countermeasure to regional decline has been proposed. This study utilizes the synthetic control method and spatial difference-in-differences methodologies to assess the impact of the 2017 opening of Seoul–Yangyang Expressway on economic development and population inflow within Hongcheon-gun, Inje-gun, and Yangyang-gun. The purpose of this study is to evaluate the effectiveness of highway development as a policy instrument to mitigate regional decline. Findings from the synthetic control method analysis suggest a positive impact of the opening of the expressway on Hongcheon-gun’s Gross Regional Domestic Product (GRDP) in 2018, as well as Yangyang-gun’s net migration rates from 2017 to 2019. Conversely, the spatial difference-in-differences analysis, designed to identify spillover effects, reveals negative impacts of the highway on the GRDP and net migration rates of adjacent regions. Consequently, although targeted transportation infrastructure development in key non Seoul Metropolitan cities may contribute to ameliorating regional imbalances, results indicate that such measures alone are unlikely to suffice in attracting population to small- and medium-sized cities outside the Seoul Metropolitan Area.

This study employs the Standard Error Estimation technique to investigate the connections between the digitalization of economy, population, trade openness, financial development, and sustainable development across 127 countries from 1990 to 2019. The findings revealed associations between financial development, population growth, trade openness, economic growth, Digitalization development, foreign direct investment (FDI), and sustainable development. Financial development negatively impacts sustainable development, suggesting that countries with advanced financial systems may struggle to maintain sustainability. Trade openness exhibits a negative association with sustainable development, implying that countries with open trade policies may face challenges in maintaining sustainability, possibly due to heightened competition or resource exploitation. These findings highlight the multifaceted relationship between economic factors and sustainable development, underscoring the importance of comprehensive policies and governance mechanisms in fostering sustainability amidst global economic dynamics.

One of the most frequently debated subjects in international forums is economic growth, which is regarded as a global priority. Consequently, researchers have turned their attention from conventional economic growth at a single average coefficient to divisible economic growth at levels of its value. Although the existing literature has discussed several determinants of economic growth, our article contributes to examining the sources of economic growth in African countries during the generations of reforms from 1990 to 2019 and in the context of economic vulnerability. The variables used in the analysis are gross domestic product, trade openness, financial development, and economic vulnerability. The study uses a quantile regression econometric model to examine these variables at different stages of reform. Quantile regression (QR) estimates for quantiles 0.05 to 0.95 showed mixed results: financial development is favorable to African economic growth at all quantile levels. However, economic vulnerability is a major impediment to economic growth at all quantile levels. In addition, it was found that a high degree of trade openness has a detrimental effect on African economic growth from quantile 0.5 of the dependent variable. Finally, another important result proves that financial development is a remedy for decision-makers against economic vulnerability.

Credit policies for clean and renewable energy businesses play a crucial role in supporting carbon neutrality efforts to combat climate change. Clustering the credit capacity of these companies to prioritize lending is essential given the limited capital available. Support Vector Machine (SVM) and Artificial Neural Network (ANN) are two robust machine learning algorithms for addressing complex clustering problems. Additionally, hyperparameter selection within these models is effectively enhanced through the support of a robust heuristic optimization algorithm, Particle Swarm Optimization (PSO). To leverage the strength of these advanced machine learning techniques, this paper aims to develop SVM and ANN models, optimized with the PSO, for the clustering problem of green credit capacity in the renewable energy industry. The results show low Mean Square Error (MSE) values for both models, indicating high clustering accuracy. The credit capabilities of wind energy, clean fuel, and biomass pellet companies are illustrated in quadrant charts, providing stakeholders with a clear view to adjust their credit strategies. This helps ensure the efficient operation of banking green credit policies.

This research aims to develop a Synergy Learning Model in the context of science learning.  This research was conducted at Islamic Junior High School, Madrasah Tsanawiyah Negeri 2 Medan, involving 64 students of Grade 7 as the research subject. The method used in this research refers to the development research approach (R&D). In collecting the data, the research employed test and non-test techniques. The results prove that the Synergy learning model developed is effective in improving student learning outcomes. This is evident through the t-test statistical test where the t-count of 4.26 is higher than the t-table of 1.99. In addition, the level of practicality with a score of 3.39 is categorized as practical. This learning model emphasizes the learning process that supports the development of science skills and develops students' competencies in planning, collaborating, and critically reflecting. The findings of this study contribute to pedagogical practices and literature in the field of science learning.