Using generative artificial intelligence systems in the classroom for law case analysis teaching can enhance the efficiency and accuracy of knowledge delivery. They can create interactive learning environments that are appropriate, immersive, integrated, and evocative, guiding students to conduct case analysis from interdisciplinary and cross-cultural perspectives. This teaching method not only increases students’ interest and participation in learning but also helps cultivate their interdisciplinary thinking and global vision. However, the application of generative artificial intelligence systems in legal education also faces some challenges and issues. If students excessively rely on these systems, their ability to think independently, make judgments, and innovate may be weakened, leading to over-trust in machines and reinforcement of value biases. To address these challenges and issues, legal education should focus more on cultivating students’ questioning skills, self-analysis abilities, critical thinking, basic legal literacy, digital skills, and humanistic spirit. This will enable students to respond to the challenges brought by generative artificial intelligence and ensure their comprehensive development in the new era.

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.

The R3A Route represents a collaborative initiative involving the governments of Thailand, Laos, and China aimed at bolstering connectivity along the North-South Economic Corridor, as a vital component of the Greater Mekong Subregion Economic Cooperation Program (GMS). Since its inception in 2008, this endeavor has substantially enhanced the logistical framework between Thailand, Laos, and China. However, it has also revealed an imbalance in the benefit distribution of value chains within the tourism industry. One of the fact that, local stakeholders in each country often leverage their home country’s advantages, leading to the exploitation of counterparts with lower capacity in other nations. This unfair utilization goes against the initial intentions of fostering collaboration among these countries. Given China and its development as a starting point for tourism and its popularity among tourists traveling this route, this study provides a comprehensive analysis of China’s policy and insights of its influences on R3A tourism development in Laos and Thailand. The study constructs a content analysis with an umbrella of stakeholder analysis based on reliable data and is cross-verified through data triangulation. The findings lead to recommendations aimed at making Thai-Lao-Chinese tourism cooperation more sustainable and effective.

Although the problems created by exceeding Earth’s carrying capacity are real, a too-small population also creates problems. The convergence of a nation’s population into small areas (i.e., cities) via processes such as urbanization can accelerate the evolution of a more advanced economy by promoting new divisions of labor and the evolution of new industries. The degree to which population density contributes to this evolution remains unclear. To provide insights into whether an optimal “threshold” population exists, we quantified the relationships between population density and economic development using threshold regression model based on the panel data for 295 Chinese cities from 2007 to 2019. We found that when the population density of the whole city (urban and rural areas combined) exceeded 866 km⁻², the impact of industrial upgrading on the economy decreased; however, when the population density exceeded 15,131 km⁻² in the urban part of the cities, the impact of industrial upgrading increased. Moreover, it appears that different regions in China may have different population density thresholds. Our results provide important insights into urban economic evolution, while also supporting the development of more effective population policies.

This article examines the overseas corporate social responsibility (CSR) patterns of Chinese international contractors (CICs). Adopting an institutional and political economy approach, a unique dataset is constructed with country-specific contents drawn from CSR-related reports and website information of 50 top CICs. This dataset provides a foundation for systematic content analysis of CICs’ overseas CSR practices, revealing that both political legitimacy-seeking and strategic competitiveness-seeking motivations drive CICs’ CSR activities abroad, characterized by the prioritization of customer and community engagement. The findings highlight the coexistence of the exogenous pressures for the national image-building purpose and the endogenous awareness of CSR strategic importance for corporate internationalization. The hybridization of political and economic rationales is presented as the defining feature of CICs’ current overseas CSR patterns, with the balance between them being determined by stakeholder type and internal business needs influenced by corporate internationalization experience.

With the continuous development of network has also greatly developed, exploring the role of social network relationships and attachment emotions on consumer intention helps community managers to promote community purchases for more consumer. As another core component of social e-commerce, social media influencer also has a significant influence on consumer intention. This study systematically analyzed the effects of social network relationships and social media influencer characteristics on consumer purchase intentions. Introduced consumer attachment and perceived value as mediating variables to construct the research framework of this study. This article adopts quantitative analysis methods to test the research hypotheses proposed. This article collected 600 first-hand data in the form of a survey questionnaire and analyzed the data using AMOS and SPSS statistical software. The empirical analysis in this article confirms that social network relationships has a significant impact on consumer purchase intentions; social media influencer characteristics has a significant impact on consumer purchase intentions; consumer attachment has a significant impact on perceived value;  consumer attachment plays a mediating role in the effect of social network relationships on consumers purchase intentions; perceived value plays no mediating role in the effect of social media influencer characteristics on consumer purchase intentions; perceived value plays a mediating role in the effect of consumer attachment on consumer purchase intentions; consumer attachment and perceived value have a chain mediating role between social network relationships and consumer purchase intentions.