As a pivotal carrier of emerging human–computer interaction technologies, artificial intelligence (AI) conversational agents (CAs) hold critical significance for research on the mechanisms of users’ continuance usage behaviour, which is essential for technological optimization and commercial transformation. However, the differential impact pathways of multidimensional perceived interactivity on continuance usage intention, particularly the synergistic mechanisms between technical and affective dual-path dimensions, remain unclear. This study investigates the personalized AI-based CAs project “Dialogue with Great Souls,” launched on a Chinese social platform, using survey data from 305 users. A hybrid approach combining partial least squares structural equation modelling (PLS-SEM) and artificial neural networks (ANN) was employed for empirical analysis. The results indicate that technical dimensions, such as control and responsiveness, are key factors influencing trust, while affective interactive dimensions, including communication, personalization, and playfulness, significantly affect social presence, thereby shaping users’ continuance usage intention. ANN results corroborated most PLS-SEM findings but revealed inconsistencies in the predictive importance of personalization and communication on social presence, highlighting the complementary nature of linear and nonlinear interaction mechanisms. By expanding the interactivity model and adopting a hybrid methodology, this study constructs a novel framework for AI CAs. The empirical findings suggest that developers should strengthen socio-emotional bonds in anthropomorphic interactions while ensuring technical credibility to enhance users’ continuance usage intention. This research not only advances theoretical perspectives on the integration of technical and affective dimensions in agent systems but also provides practical recommendations for optimizing the design and development of AI CAs.

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.

With the development of Information and Communication Technology (ICT), cultural heritage has adopted new forms of display by integrating digital and physical realms. Interaction methods have expanded from traditional touchscreen input to touchless input, enriching user engagement. However, the differences between touch and touchless interaction modes -and their impact on experience remain insufficiently explored. This paper presents a virtual museum themed around blue-and-white porcelain. We systematically designed gestures, interfaces, and tasks for user to experience and evaluate. Participants were assigned three tasks-translation, rotation, and scaling. Both objective performance data and subjective feedback were collected. Results show that touchless interaction outperformed touch interaction in depth-related tasks, while touch interaction was superior in lateral tasks. Subjective feedback indicated that touchless input scored higher in attractiveness, stimulation, and novelty. These findings provide guidance for selecting appropriate interaction modes in virtual museums and digital heritage.