This paper examines the relationship between renewable energy (RE) generation, economic factors, infrastructure, and governance quality in ASEAN countries. Based on the Fixed Effects regression model on panel data spanning the years 2002–2021, results demonstrate that domestic capital investment, foreign direct investment, governance effectiveness, and crude oil price exhibit an inverse yet significant relationship with RE generation. An increase in those factors will lead to a decline in RE generation. Meanwhile, economic growth and infrastructure have a positive relationship, which implies that these factors act as stimulants for RE generation in the region. Hence, it is advisable to prioritise policies that foster economic growth, including offering tax breaks specifically for RE projects. Additionally, it’s crucial to streamline governance processes to facilitate infrastructure conducive to RE generation, along with investing in RE infrastructure. This could be achieved by establishing one-stop centres for consolidating permitting processes, which would streamline the often-bureaucratic process. However, given the extensive time period covered, future research should examine the short-term relationship between the variables to address any potential temporal trends between the factors and RE generation.

Developing “New Quality Productive Forces” (NQPFs) has been accepted as a new theory to accelerate the high-quality development in China. In current, China’s high-quality development mainly relies on the traction of the digital economy. In view of this, developing NQPFs in China’s digital economy sector requires locate and remove some obstacles, such as the insufficient utilization of data, inadequate algorithm regulation, the mismatched supply and demand of regional computing power and the immature market environment. As a solution, it is necessary to allocating data property rights in a market-oriented way, establishing a user-centered algorithm governance system, accelerating the establishment of the national integrated computing network, and maintaining fair competition to optimize the market environment.

Introduction: Chatbots are increasingly utilized in education, offering real-time, personalized communication. While research has explored technical aspects of chatbots, user experience remains under-investigated. This study examines a model for evaluating user experience and satisfaction with chatbots in higher education. Methodology: A four-factor model (information quality, system quality, chatbot experience, user satisfaction) was proposed based on prior research. An alternative two-factor model emerged through exploratory factor analysis, focusing on “Chatbot Response Quality” and “User Experience and Satisfaction with the Chatbot.” Surveys were distributed to students and faculty at a university in Ecuador to collect data. Confirmatory factor analysis validated both models. Results: The two-factor model explained a significantly greater proportion of the data’s variance (55.2%) compared to the four-factor model (46.4%). Conclusion: This study suggests that a simpler model focusing on chatbot response quality and user experience is more effective for evaluating chatbots in education. Future research can explore methods to optimize these factors and improve the learning experience for students.

This article investigates the income and expenditure patterns of individuals, with a specific focus on investments in luxury items, real estate, and expensive modes of transportation. Using global databases such as “Luxury Goods—Worldwide/Statista Market Forecast” and “Data—WID—World Inequality Database”, the authors explore the correlation between high demand for luxury items and economic inequality. The study emphasizes the role of luxury tax as essential for implementing a progressive personal income tax system in Russia. By examining country-specific factors, particularly in China and Russia, and conducting a comparative analysis of progressive tax systems globally, the research highlights the potential of luxury tax to enhance the efficacy of income tax in reducing inequality.

China’s graduate quality management system is designed to ensure that students possess the necessary skills, knowledge, and competencies for future success. This system is rooted in China’s ambitious educational reforms aimed at cultivating a highly skilled workforce to drive economic growth and innovation. Effective graduate quality management significantly impacts employment levels, training models, and national policy formulation. This study investigates the quality management approaches of 56 vocational institutions in Yunnan Province using a 5-level questionnaire and a quantitative research methodology. A sample of 556 individuals was selected through stratified random sampling. Exploratory factor analysis identified five primary components of the quality management model: College graduate quality (mean = 4.56, SD = 0.49), teaching quality (mean = 4.39, SD = 0.42), hardware environment (mean = 4.38, SD = 0.44), social support (mean = 4.37, SD = 0.42), and job satisfaction (mean = 4.38, SD = 0.42). College graduate quality and teaching quality were the most influential factors, while hardware environment, social support, and job satisfaction had lesser impacts.