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Data · dataset · 2025

From Tap to Track: Technology-Oriented Predictors of Continuance Intention in Running Applications

Listed in Teesside University Research Data Repository

The rapid adoption of mobile running applications (running apps) in Indonesia has transformed fitness management, yet sustaining long-term user engagement remains a critical challenge.

Description

This study aims to analyze how technology-oriented factors, specifically Perceived Ease of Use (PEOU), Gamification (GAM), and Social Relatedness (SR), influence users' Continuance Intention (CI) in running applications. Utilizing a quantitative approach, data were collected through an online survey of 400 active running app users in Indonesia, followed by analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM).

The findings indicate that all three hypothesized relationships are statistically supported at P = 0.000. PEOU significantly affects CI (T = 3.558), and both GAM (T = 5.240) and SR (T = 5.446) demonstrate exceptionally strong influences. Crucially, the combination of GAM and SR emerges as the dominant predictor of continued use, suggesting that integrating motivational rewards with a strong community element is key to user retention.

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These results reinforce the necessity of extending the Technology Acceptance Model (TAM) with social and intrinsic motivation factors in the digital fitness context. The study offers vital practical implications for developers seeking to design applications that ensure sustained user commitment in trend-sensitive markets.

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