Drawing on self-determination theory (SDT) and service-dominant logic (SDL), this study examines how stress-relief-oriented escape, self-fulfillment, and digital information environments are associated with emotion value co-creation among Generation Z cultural heritage tourists. Survey data from 457 adult Generation Z tourists who had visited cultural heritage destinations in Shanxi Province, China, were analyzed using partial least squares structural equation modeling. Stress-relief-oriented escape was negatively associated with both self-fulfillment and emotion value co-creation, while self-fulfillment was positively associated with emotion value co-creation and carried a significant indirect association between escape and emotion value co-creation. The moderation results revealed contrasting digital boundary conditions: higher media promotion progressively attenuated the negative escape relationships to statistical non-significance, whereas stronger GenAI personalization was associated with increasingly negative relationships. These findings extend tourism motivation research by positioning stress-relief-oriented escape as a recovery-oriented motivational starting condition whose implications depend on the experiential outcome considered. By integrating SDT and SDL, the study identifies self-fulfillment as a measured psychological pathway connecting motivational orientation with emotion value co-creation and shows that this relationship is conditioned differently by interpretive media and preference-adaptive GenAI environments. The findings offer implications for heritage communication and GenAI-enabled tourism design.

Artificial Intelligence generated content (AIGC) is rapidly reshaping higher education. Guided by the Technology Acceptance Model (TAM), this study examines how perceived ease of use (PEOU) and perceived usefulness (PU) predict Chinese faculty members’ AIGC use behaviour, with perceived self-efficacy (PSE) and institutional support (IS) modelled as external variables. Survey data from 295 faculty members was analysed and structural equation modelling was employed to test the hypothesized relationships. The results reveal that both PEOU and PU are critical predictors of AIGC adoption, while PSE and IS significantly enhance faculty perceptions of ease of use and usefulness, thereby facilitating actual usage behaviour. The model accounted for 55.2% of the variance in AIGC adoption. Furthermore, gender differences emerged as a significant moderating factor, where female faculty members were more strongly influenced by PEOU, whereas male faculty members with PU. These findings highlight the importance of strengthening faculty confidence and digital competence through differentiated training and institutional support mechanisms. The study extends TAM in an AIGC context and offers practical guidance for inclusive AIGC adoption strategies in higher education.