Gamified metacognitive support in smart health wearable platforms: A SEM-ANN study of subscription renewal intention

Achieving sustainable subscription revenue remains a critical challenge for the smart health e-commerce sector. This study investigates the drivers of subscription renewal intention by examining the interplay between gamification mechanics and metacognitive support. Adopting a dual-stage analytical approach, this study utilizes structural equation modeling (SEM) to examine hypothesized relationships among constructs and artificial neural network (ANN) analysis to identify model-dependent predictive contributions and rank the relative importance of predictors. Results indicate that reward and feedback transparency and metacognitive monitoring support are the most prominent predictors associated with subscription renewal intention in this dataset, whereas social gamification mechanics and challenge-skill fit show limited direct associations with renewal decisions. Reward and feedback transparency also exhibit strong associations with metacognitive support dimensions, suggesting that clear reward rules and progress feedback can enable self-regulatory monitoring that supports continued payment. The predictive ranking from the ANN underscores the prominence of transparency and monitoring features for explaining reuse, pointing to a retention logic centered on value communication rather than engagement alone. This study contributes to the theoretical development of the smart health field by proposing that, within health wearable platforms, transparent data interpretation may play a more prominent role than entertainment-oriented features in supporting recurring subscription decisions.