Determinants of User Continuance Intention toward AstraPay: An Integration of UTAUT, ITM, and TTF Models

Abstract

This study examines the determinants of continuance intention in using the AstraPay mobile payment application by integrating the Unified Theory of Acceptance and Use of Technology (UTAUT), Task Technology Fit (TTF), and the Initial Trust Model (ITM). Prior studies have mostly examined these models separately and focused on initial adoption rather than sustained, post-adoption usage, particularly in emerging markets such as Indonesia. A quantitative approach was applied using an online questionnaire distributed through purposive sampling; after screening for active account ownership and removing incomplete responses, 413 valid responses were retained. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS. The results show that all nine hypothesized paths are statistically significant: technology characteristic and task characteristic shape task-technology fit; task-technology fit and effort expectancy shape performance expectancy; performance expectancy, structural assurance, and trust propensity shape initial trust; and initial trust and social influence shape usage (continuance) intention. Initial trust is the strongest direct driver of continuance intention, followed by social influence and the indirect (mediated) effect of structural assurance. The findings highlight that trust and the fit between technology and user tasks are essential in sustaining mobile payment usage even after functional expectations have been met. This study contributes an integrated UTAUT–TTF–ITM framework tested on an already-active user base, and offers practical insights for AstraPay to strengthen trust, reliability, and task alignment to support digital financial inclusion in Indonesia.