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.

This study investigates the impact of perceived innovative leadership on team innovation performance, with innovation climate acting as a mediating variable. A quantitative research approach, including a survey of team members across various industries, was used to collect data. Analysis through Structural Equation Modeling (SEM) reveals that perceived innovative leadership significantly positively influences team innovation performance, with innovation climate partially mediating this relationship. The findings emphasize the critical role of innovative leadership and a positive innovation climate in fostering organizational innovation, offering valuable insights for management practices. This paper also discusses the study’s limitations and provides directions for future research.

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.

Sustainability has become a generalized concern for society, specifically businesses, governments, and academia. In the specific case of universities, sustainability has been approached from different perspectives, some viewing it from environmental practices, management initiatives, operational criteria, green buildings, and even education for sustainable development. This research focuses on sustainability as a managerial practice and investigates how it affects the performance of five private universities in Medellin, Colombia. For this purpose, a literature review using a mixed sequential approach, including bibliometric and content analysis, was initially conducted. In the s second phase, more than 5000 responses from students, professors, and employees of the five mentioned private universities were collected. A previously validated instrument for both sustainability and performance was applied in the quantitative phase, and a novel dimensionality of the constructs was proposed by conducting an exploratory factor analysis using the SPSS software. Results were then processed through a structural equation analysis with the Smart PLS software. The impact of sustainability on university performance is verified, making some managerial recommendations.

Protecting the environment and the Earth's natural resources is one of the most important tasks for modern societies, economies, and countries. Changes in the environment have made climate protection a key task of state policy implemented at the local, national, and international. They also have caused such negative social manifestations as environmental radicalism and terrorism. The purpose of this paper was to analyze the capacity of state institutions to prevent environmental terrorism and radicalism, particularly in the Russian context, by identifying and prioritizing key challenges and countermeasures. A mixed-methods approach was adopted, involving both qualitative and quantitative analyses. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a total of 35 articles and reviews were selected to provide a foundation for understanding eco-terrorism trends. Additionally, an expert survey was conducted with 44 qualified participants to rank problems and recommended actions. The Kendall concordance coefficient was used to assess the consistency of expert opinions. The authors conclude that low environmental awareness and insufficient cooperation between state institutions and environmental organizations are the most significant challenges in preventing eco-terrorism. To adequately and competently prevent environmental terrorism and radicalism in society, the prevention system must be based on clear and thoughtful actions by state institutions.