Cultural heritage virtual tourism offers users a novel digital heritage experience, becoming an essential channel for cultural dissemination and preservation. However, how to stimulate users’ continuous behavioral intention remains unresolved. This study integrates the Stimulus–Organism–Response theory (SOR) and experience economy theories to construct a comprehensive model, exploring factors influencing users’ continuous intentions in cultural heritage virtual tourism. By analyzing data from 451 valid questionnaires through structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) methods, several key findings emerged. The SEM results show that (1) esthetics, entertainment, escapism, education, and connection experiences all positively affect perceived value and satisfaction; (2) except for escapism, other experiences positively influence cultural identity; and (3) perceived value, satisfaction, and cultural identity significantly impact continuous intention. The FsQCA results show that (1) in high continuous intention scenarios, perceived value, satisfaction, and cultural identity are core conditions, while esthetics, entertainment, escapism, education, and connection act as supporting conditions, enhancing users’ willingness to continue engaging under different configurations; (2) in low continuous intention cases, the absence of escapism, satisfaction, cultural identity, education, esthetics, and connection weakens users’ virtual tourism experiences, leading to a decline in continuous usage intentions. This study provides theoretical and practical insights for promoting users’ continuous intentions in cultural heritage virtual tourism.

With the acceleration of the aging process in China, chronic diseases have become one of the main health threats for older adults, creating significant pressure on society and the healthcare system. As information technology and artificial intelligence advance rapidly, smart health services have become readily accessible. However, utilization rates among the older adults, especially those with chronic illnesses, remain low, preventing them from fully benefiting from these advanced technologies. The value of mobile health (mHealth) services can only be realized through sustained use. Therefore, this study empirically investigates the continuous use intention of mHealth services from the perspective of older adults with chronic illnesses, integrating the Technology Acceptance Model (TAM) and Value-Based Adoption Model (VAM). A total of 372 questionnaires were collected from various cities in China, and data were analyzed using SPSS 24.0 and Partial Least Squares Structural Equation Modeling (PLS-SEM). Results indicate that perceived ease of use (β = 0.155, p = 0.004; β = 0.116, p = 0.027) and perceived usefulness (β = 0.175, p = 0.001; β = 0.151, p = 0.004) have a significant positive impact on attitude and perceived value. Perceived enjoyment significantly influences attitude (β = 0.147, p = 0.010), while perceived risk (β = −0.189, p < 0.001; β = −0.281, p < 0.001) and perceived cost (β = −0.155, p = 0.003; β = −0.130, p = 0.022) have a significant negative impact on attitude and perceived value. Both attitude (β = 0.357, p < 0.001) and perceived value (β = 0.314, p < 0.001) positively impact continuous intention. In total, only one of the twelve hypotheses was not supported. This study not only provides strong evidence for the effectiveness of the integrated TAM and VAM model in the mHealth field but also offers theoretical insights and practical recommendations for product optimization and promotion to mHealth service providers and designers.

Robotaxi services represent a major step in the commercialization of autonomous driving, offering efficiency, consistency, and safety benefits. However, despite technological advances, their large-scale adoption is far from guaranteed. Most urban users already rely on mature ride-hailing platforms such as Didi and Uber, making the real behavioral question not whether to adopt Robotaxi, but whether to migrate from existing services. Prior studies based on TAM, UTAUT, or trust models have primarily examined users’ initial adoption decisions, overlooking the substitution behavior that better captures how people shift between competing mobility services in real contexts. This study addresses this gap by applying the Push–Pull–Mooring (PPM) framework to examine users’ migration from ride-hailing to Robotaxi services, based on survey data collected from 1206 respondents across four Chinese cities (Beijing, Shanghai, Guangzhou, and Wuhan). The model was tested using structural equation modeling and multi-group analysis (SEM–MGA). Push factors reflect negative experiences with ride-hailing, including social anxiety and insecurity caused by drivers’ behaviors; pull factors emphasize Robotaxi’ autonomy and service reliability; while mooring factors capture habitual ride-hailing use and perceived Robotaxi risk. Findings indicate that push and pull factors significantly promote migration intentions, whereas mooring factors hinder them. Among all factors, perceived risk exerted the strongest negative effect (β = −0.36), underscoring its critical role as a barrier to Robotaxi migration. Gender differences are also evident, with women more sensitive to risks and men more influenced by reliability. By situating adoption within a migration context, this study enriches high-risk innovation theory and offers practical guidance for designing gender-sensitive and user-specific promotion strategies.