Predicting User Exit and Negative Word-of-Mouth in Buy Now Pay Later Apps: The EXIT Model from Bilingual App Store Reviews

The rapid growth of Buy Now, Pay Later (BNPL) services has expanded consumer access to credit, but it has also raised concerns about user satisfaction, trust, and long-term sustainability. This study develops and validates the Experience–Interaction–Trust model to explain and predict user disengagement in BNPL platforms. A multi-stage research design was employed to explore and test the experiential dimensions that shape consumer interactions with BNPL applications. In the exploratory phase, a bilingual corpus of approximately 39,000 authentic Arabic and English app reviews was analyzed. Text preprocessing, sentiment analysis, and topic modeling uncovered eleven core constructs: Harmony, Effortlessness, Favorability, Neglect, Breakdown, Automation, Boundedness, Disparity, Friction, Churn Risk, and NWOM. In the confirmatory phase, PLS regression and XGBoost were used to test and predict the relationships among constructs. The EXIT model demonstrates theoretical robustness and predictive utility, offering practical guidance for BNPL providers seeking to minimize churn, enhance user trust, and support sustainable digital financial innovation.