This study evaluates the health and sustainability of higher education systems in nine countries: the USA, UK, Australia, Germany, Canada, China, Brazil, India, and South Africa. Using a multi-level analysis model and principal component analysis (PCA), nine key factors—such as international student numbers, academic levels, and graduate employment rates—were identified, capturing over 90% of the cumulative impact on higher education systems. India, scoring 6.2036 initially, shows significant room for improvement. The study proposes policies to increase graduate employment, promote international faculty collaboration, and enhance India’s educational expenditure, which surpasses 9.8% of GDP. Post-policy simulations suggest India’s score could rise to 8.7432. The paper also addresses the impact of COVID-19 on global education, recommending a hybrid model and increased graduate enrollment in China to reduce unemployment by 5.4%. The research aims to guide sustainable development in higher education globally.

Purpose: This research aims to examine the influence of intellectual capital disclosure and the geographical location of universities on the sustainability of higher education institutions in Southeast Asia. Design/methodology/approach: This research is quantitative and uses secondary data obtained through the annual reports of universities that have the Universitas Indonesia Green Metric Rank. This research uses two stages of data analysis techniques, namely the content analysis stage to determine the number of Intellectual Capital disclosures and the hypothesis testing stage. The analysis tool uses the SPSS version 23 application. The population of this research includes all universities in Southeast Asia that are included in the UI Greenmetric World University Rankings. The sampling technique used was purposive sampling technique, which resulted in 86 analysis units of higher education institutions in Southeast Asia. Findings: The research results prove that the geographical location of universities has a negative and significant influence on Universitas Indonesia Green Metric’s performance in Southeast Asia and human capital has a positive influence on UIGM’s performance in Southeast Asia. However, the structural capital and relational capital components do not affect the UIGM performance of universities in Southeast Asia. Originality/value: The originality of the research is the use of higher education sustainability variables with UIGM proxies and modified IC indicators for universities and geographical areas that have not been widely used to see whether there are fundamental differences in the disclosure of intellectual capital for higher education institutions in Southeast Asia.

This research aims to determine and analyze the extent of the influence of community empowerment and sustainability-oriented innovation on sustainable performance through coworking spaces in the city of Bandung. To achieve the research objectives, a deductive approach is employed, intending to test a hypothesis to strengthen or reject existing hypotheses. Therefore, this research is also categorized as explanatory research. The research method used is the survey research method. The research sample is determined based on proportional stratified random sampling. This study focuses on business groups in coworking spaces in the 28 districts of Bandung City, with a total of 408 business operators. The sample selected consists of 208 business operators. Based on the research results, several conclusions are drawn, as follows: (1) Community empowerment has a significantly positive influence on sustainability performance, with a contribution of 84.5%; (2) Sustainability-oriented innovation has a significantly positive influence on sustainability performance, with a contribution of 69.2%; (3) Community empowerment has a significantly positive influence on Coworking Space, with a contribution of 93.6%; (4) Sustainability-oriented innovation has a significantly positive influence on Coworking Space, with a contribution of 36%; (5) Community empowerment has a significantly positive influence on sustainability-oriented innovation, with a contribution of 90.6%; (6) Coworking Space has a significantly positive influence on sustainability performance, with a contribution of 34%; (7) Community empowerment has a significantly positive influence on sustainability performance through Coworking Space, with a contribution of 20.7%; and (8) Sustainability oriented innovation has a significantly positive influence on sustainability performance through Coworking Space, with a contribution of 12.2%.

The rapid advancement of artificial intelligence (AI) technology is profoundly transforming the information ecosystem, reshaping the ways in which information is produced, distributed, and consumed. This study explores the impact of AI on the information environment, examining the challenges and opportunities for sustainable development in the age of AI. The research is motivated by the need to address the growing concerns about the reliability and sustainability of the information ecosystem in the face of AI-driven changes. Through a comprehensive analysis of the current AI landscape, including a review of existing literature and case studies, the study diagnoses the social implications of AI-driven changes in information ecosystems. The findings reveal a complex interplay between technological innovation and social responsibility, highlighting the need for collaborative governance strategies to navigate the tensions between the benefits and risks of AI. The study contributes to the growing discourse on AI governance by proposing a multi-stakeholder framework that emphasizes the importance of inclusive participation, transparency, and accountability in shaping the future of information. The research offers actionable insights for policymakers, industry leaders, and civil society organizations seeking to foster a trustworthy and inclusive information environment in the era of AI, while harnessing the potential of AI-driven innovations for sustainable development.

This study analyses the dynamic development of soybean (Glycine max (L.) Merr.) breeding in Russia, particularly examining its historical development, status, and future predictions. With the global demand for vegetable protein rising, understanding Russia’s potential contribution becomes crucial. This research provides valuable insights, offering precise data that may be unfamiliar to international researchers and the private sector. The authors trace the history of soybean selection in Russia, emphasizing its expansion from the Far East to other regions in Russia. The expansion is primarily attributed to the pioneering work of Soviet breeder V. A. Zolotnitsky and the development of the soybean variety in the Amur region in the 1930s. The study highlights the main areas of soybean variety originators, with approximately 40% of foreign varieties registered. The Krasnodar and Amur regions emerge as critical areas for breeding soybean varieties. In Russia, the highest yield potential of soybeans is in the Central Federal District. At the same time, the varieties registered in the Volga Federal District have higher oil content, and the Far Eastern Federal District has high protein content in the registered soybean varieties. The research outlines the state’s pivotal role in supporting soybean breeding and fostering a competitive market with foreign breeders. The study forecasts future soybean breeding development and the main factors that can influence the industry.

This comprehensive review examines recent innovations in green technology and their impact on environmental sustainability. The study analyzes advancements in renewable energy, sustainable transportation, waste management, and green building practices. To accomplish the specific objectives of the current study, the exploration was conducted using the PRISMA guidelines in major academic databases, such as Web of Science, Scopus, IEEE Xplore, and ScienceDirect. Through a systematic literature review with a research influence mapping technique, we identified key trends, challenges, and future directions in green technology. Our aggregate findings suggest that while significant progress has been made in reducing environmental impact, barriers such as high initial costs and technological limitations persist. Hence, for the well-being of societal communities, green technology innovations and practices should be adopted more widely. By investing in sustainable practices, communities can reduce environmental degradation, improve public health, and create resilient infrastructures that support both ecological and economic stability. Green technologies, such as renewable energy sources, eco-friendly construction, efficient waste management systems, and sustainable agriculture, not only mitigate pollution but also lower greenhouse gas emissions, thereby combating climate change. Finally, the paper concludes with recommendations for policymakers and industry leaders to foster the widespread adoption of green technologies.