Public sector employees face the profound impact of digital work demands, especially with the advancement of China’s digital government construction. This study explores the dual-edged consequence of digital job demands on the work behaviors of public sector employees in China by constructing a dual-path model. Structural equation modeling (SEM) was used to validate the data of 873 public sector employees. This study found that digital job demands increase civil servants’ thriving at work, facilitating their job-crafting behaviors and increasing their workplace anxiety, leading to their work withdrawal behavior. Furthermore, this study validates the moderating effects of promotion and preventive focus. This study provides managers in the public sector with valuable insights to develop digital job demands managing strategies and for civil servants to adapt their perceptions and behaviors in the digital context.

Within the global sustainable development agenda, Sustainable Development Goal 4 (SDG 4) highlights improving the accessibility, quality, and learning experience of technical and vocational education and training (TVET). In China, students in vocational colleges often face greater disparities in academic preparation and access to educational resources than their peers in general higher education. Although artificial intelligence (AI) can provide additional learning support and help mitigate such inequalities, there is little empirical evidence on whether and how Gen-AI usage is associated with vocational students’ learning experiences and emotional outcomes, particularly academic anxiety. This study examines how Gen-AI usage is related to academic anxiety among Chinese vocational college students and explores the roles of class engagement and teacher support in this relationship. Drawing on Conservation of Resources (COR) theory, we analyse survey data from 511 students using structural equation modelling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA). The SEM results indicate that Gen-AI usage is associated with lower academic anxiety, with class engagement mediating this relationship. Teacher support for Gen-AI usage positively moderates the association between Gen-AI usage and class engagement. The fsQCA results further identify several configurations of conditions leading to low academic anxiety. These findings underscore AI’s potential to enhance learning quality and experiences in TVET and provide empirical support for advancing SDG 4 in vocational education contexts.

While the application of artificial intelligence (AI) in education has garnered growing scholarly attention, research specific to vocational education remains limited. In China, vocational education plays a critical role in cultivating skilled workers, yet students in this context often face distinctive academic anxiety and mental health challenges. This study, grounded in the conservation of resources theory, investigates how AI usage influences academic anxiety among Chinese vocational students. Drawing on data from 511 questionnaires, we employed structural equation modeling (SEM) and fuzzy set qualitative comparative analysis (fsQCA) to examine both linear and configurational relationships. The results reveal that AI usage significantly and negatively predicts academic anxiety, with class engagement serving as a key mediating variable. Moreover, teacher support for AI usage, as a conditional resource, positively moderates the link between AI usage and class engagement. The fsQCA further identifies three distinct configurational pathways leading to low academic anxiety. These findings contribute to the literature on AI in vocational education by uncovering its psychological impact and offering theoretical and practical insights for educational management in this domain.

Public sector employees face the profound impact of digital work demands, especially with the advancement of China's digital government construction. This study explores the dual-edged consequence of digital job demands on the work behaviors of public sector employees in China by constructing a dual-path model. Structural equation modeling (SEM) was used to validate the data of 873 public sector employees. This study found that digital job demands increase civil servants' thriving at work, facilitating their job crafting behaviors and increasing their workplace anxiety, leading to their work withdrawal behavior. Furthermore, this study validates the moderating effects of promotion and preventive focus. This study provides managers in the public sector with valuable insights to develop digital job demands managing strategies and for civil servants to adapt their perceptions and behaviors in the digital context.