Year: 2026
Type: article
Abstract: Mobile payment applications have become an important channel for everyday financial transactions, particularly in rapidly digitalizing economies such as Vietnam. Prior mobile payment research has relied largely on predefined theoretical constructs to explain adoption and continuance and offers less insight into the service aspects that users raise spontaneously from their own experience. This study applies Latent Dirichlet Allocation (LDA) to 2,938 Google Play reviews of MoMo and VNPAY in Vietnam. The analysis identifies 12 service-related topics spanning financial transactions, application functionality, authentication and access, technical performance, promotional mechanisms, and customer support. App interface and feature functionality was the most prevalent topic overall, followed by bank account and fund transfer issues and by customer support and complaint resolution. Topic prevalence differed significantly between the two applications: VNPAY reviews placed greater emphasis on app interface and feature functionality, whereas MoMo reviews placed greater emphasis on customer support and complaint resolution, app speed and stability, device access and connectivity, recurring-payment deductions, and purchase and login problems. Google Play star ratings were combined with review-level topic probabilities to give a star-weighted prominence score for each topic. Bootstrap comparisons showed significantly higher scores for VNPAY on app interface and feature functionality and on bank account and fund transfer issues, and for MoMo on device access and connectivity, app speed and stability, and customer support and complaint resolution. The findings show that post-adoption experiences of mobile payment users are multidimensional and vary across competing providers, and they offer practical evidence for identifying platform-specific service priorities.
Authors: Thanh Tuong Vo, Thi My Linh Cao, Hsi-Hua Chen
Institutions: Dong A University, National Taipei University of Technology
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7225002598