A Socio-Technical Model of Knowledge Sharing and Discovery in Social Fitness Apps among Indonesian Users: A PLS-SEM Approach

Social fitness applications such as Strava, Nike Run Club, and Garmin Connect have turned exercise tracking into a community-based activity where users exchange tips, experiences, and performance data. However, little is known about what drives users to share and discover knowledge on these platforms. This study proposes and tests a socio-technical model that explains knowledge sharing and discovery behaviour in social fitness apps. The model integrates Social Capital Theory, the Technology Acceptance Model, and the Theory of Planned Behavior. Data was collected from 57 active users of social fitness applications and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that perceived usefulness, structural social capital, and perceived behavioural control significantly influence users’ intentions, while attitude and cognitive social capital do not play a major role. Intention, in turn, strongly predicts actual knowledge sharing and discovery behaviour. These findings suggest that knowledge-related actions in social fitness communities are driven mainly by functional benefits, connectedness within the community, and users’ sense of capability, rather than by evaluative attitudes alone. The study offers a clearer view of how socio-technical factors work together in digital fitness ecosystems and provides a basis for future research on knowledge behaviour in online communities