How do technology and gamification influence continued usage intention of AI-based wearable devices? Evidence from SEM-ANN

Purpose In the last few years, AI-based wearable devices have increasingly played an important role in the leisure and personalized health management fields, but users’ intention to continue using these devices still faces numerous challenges. Design/methodology/approach This study proposes a novel theoretical model based on the attitude-behavior-context (ABC) theoretical framework to explore the effects of technological and gamification factors on the continued usage intention of AI-based wearable devices. Data were collected from 335 AI-based watch users in China to validate the model by employing a mixed analysis approach that combines structural equation modeling (SEM) and artificial neural network (ANN). Findings The results of the PLS-SEM analysis indicate that customization, personalization and interactivity among technological factors significantly enhance consumers’ perceived value. In the gamification factors, reward positively affects perceived value, whereas the effect of competition is insignificant. Moreover, both perceived value and emotional trust have significant positive effects on the user continuance intention, with perceived value also positively influencing user emotional trust. The ANN analysis further supplements these findings, showing that personalization, with 100% normalized relative importance (NRI), is the primary factor influencing consumer perceived value. Similarly, perceived value, with 100% NRI, significantly influences user continued usage intention. Originality/value This study provides practical insights for companies and developers of AI-based wearable devices to promote the long-term value for their users.