Grounded in regulatory focus theory, this study investigates the double-edged sword effect of generative AI adoption on sustainable entrepreneurial intentions and its underlying mechanisms. A questionnaire-based survey was conducted among 357 business students from public universities in China. The results reveal that generative AI adoption exerts a double-edged effect: it enhances sustainable entrepreneurial intentions by strengthening sustainable entrepreneurial self-efficacy through a promotion-focused pathway, while simultaneously undermining such intentions by heightening sustainable entrepreneurial fear of failure via a prevention-focused pathway. Moreover, artificial intelligence literacy moderates these relationships, amplifying the positive influence of generative AI adoption on entrepreneurial self-efficacy and attenuating its negative effect on fear of failure. This study enhances understanding of sustainable entrepreneurship amid the rise in generative AI, extends regulatory focus theory, and informs the development of AI-integrated sustainability education in academic institutions.

Musculoskeletal diseases affect over 100 million people globally and are a leading cause of severe, prolonged pain, and disability. Recognized as a clinical emergency, prompt and accurate diagnosis of musculoskeletal disorders is crucial, as delayed identification poses the risk of amputation for patients, and in severe cases, can result in life-threatening conditions such as bone cancer. In this paper, a hybrid model HRD (Human-Resnet50-Densenet121) based on deep learning and human participation is proposed to efficiently identify disease features by classifying X-ray images. Feasibility testing of the model was conducted using the MURA dataset, with metrics such as accuracy, recall rate, F1-score, ROC curve, Cohen’s kappa, and AUC values employed for evaluation. Experimental results indicate that, in terms of model accuracy, the hybrid model constructed through a combination strategy surpassed the accuracy of any individual model by more than 4%. The model achieved a peak accuracy of 88.81%, a maximum recall rate of 94%, and the highest F1-score value of 87%, all surpassing those of any single model. The hybrid model demonstrates excellent generalization performance and classification accuracy.

In the contemporary entrepreneurial environment increasingly shaped by artificial intelligence, the Artificial intelligence (AI) literacy of entrepreneurs plays an essential role in enhancing entrepreneurial resilience. However, the underlying mechanisms that explain this relationship remain inadequately explored. Grounded in the Conservation of Resources (COR) theory, this study examines the effect of entrepreneurs’ AI literacy on entrepreneurial resilience, specifically assessing the mediating effect of AI anxiety and the moderating effect of social support. Data were obtained from 330 Chinese entrepreneurs using a two-wave survey design. The analysis revealed a significant positive association between AI literacy and entrepreneurial resilience. Furthermore, AI anxiety mediates this relationship, suggesting that AI literacy enhances entrepreneurial resilience by alleviating AI anxiety. Moreover, all three forms of social support were found to buffer the negative effect of AI anxiety on resilience. Notably, the moderating effects of subjective support and support utilization are significantly stronger than those of objective support, highlighting the distinct roles of different support types. These findings deepen theoretical insight into the psychological pathways linking AI literacy to resilience and offer practical guidance for entrepreneurs in the AI era.

As artificial intelligence (AI) rapidly permeates entrepreneurial ecosystems, understanding how technological literacy relates to entrepreneurial team well-being has become an urgent priority. Drawing on conservation of resources (COR) theory, this study examines the relationship between entrepreneurial teams’ AI literacy and team well-being (distinguishing between hedonic and eudaimonic well-being). Furthermore, it investigates the mediating roles of entrepreneurial team efficacy and collective AI anxiety. Data were collected from a survey of 271 entrepreneurial teams across four major economic zones in China. This study relies on team leaders as primary informants to report team-level perceptions. The results show that AI literacy is positively related to team hedonic well-being, but exhibits no significant direct relationship with team eudaimonic well-being. However, AI literacy is indirectly associated with entrepreneurial team well-being through two parallel pathways: entrepreneurial team efficacy and collective AI anxiety. The findings shed light on how technological literacy is linked to team mental health via the dual mechanisms of cognitive resource gain and emotional loss prevention. This study broadens our understanding of well-being at the entrepreneurial team level and offers insights into cultivating literacy, enhancing efficacy, and managing emotions to improve entrepreneurial team well-being.

The construction and enhancement of ecological niches are essential for small and medium-sized enterprises (SMEs), with digital platforms serving as key carriers for achieving niche improvement. However, SMEs encounter a “distinctiveness–conformity” paradox when leveraging digital platforms: they are expected to sustain differentiation to attract resource tilt while simultaneously integrating into the platform ecosystem to obtain a sense of belonging and complementary resources. Grounded in optimal distinctiveness theory, this study analyzes questionnaire data from 383 Chinese SMEs embedded in digital platforms. Results show that digital platform capabilities (integration and reconfiguration) enhance SMEs ecological niches through organizational agility and platform eco-embeddedness. Polynomial regression and response surface analyses reveal that balanced improvement in organizational agility and eco-embeddedness significantly strengthens niche enhancement, whereas imbalance between the two weakens it. This research clarifies how SMEs leverage digital platform capabilities to advance their ecological niches, offering theoretical and practical insights for achieving strategic balance between distinctiveness and conformity in digital platform ecosystems.