Citation

Rahman, Ashikur and Al Farid, Fahmid and Bashar, Mohammad Abul and Uddin, Jia and Mahmud, Arif and Abdul Karim, Hezerul (2026) Examining the influence of deterrent and enhancement factors on QR-code mobile payment continuance intention: insights from PLS-SEM and IPMA analysis. Frontiers in Big Data, 8. ISSN 2624-909X

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Abstract

Introduction: The rise of contactless payment has made quick response (QR) code-mobile payment (QR-MP) platform increasingly popular among mobile financial service (MFS) users, especially in emerging economies. It has been demonstrated that the ongoing use of QR payments can significantly drive the growth of emerging economies. However, despite its importance, the continued use of this technology has not been satisfactory. Thus, this study seeks to explore the modified Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model, including four additional constructs: amotivation (AM), alternative attractiveness (AA), QR transaction anxiety (QTA), and transaction convenience (TC) to examine the MFS users' sustained usage of QR payment.Methods: Data were collected from 247 MFS users in Bangladesh using an online survey and analyzed through SEM-PLS and non-linear analysis of IPMA.Results: The research findings reveal that effort expectancy is the most influential factor, and that both moderator factors, QTA and TC, are significant. However, social influence and hedonic motivation were found to be insignificant. Furthermore, our extended research model explains 76.5% of the variance in CINT without the moderation effect.Discussion: The IPMA findings help to find the best-performing variables and provide practical insights for this study. Theoretical and managerial implications are provided to enrich the existing literature on the study of information technology, indicating how MFS providers in developing countries can retain their existing users.

Item Type:	Article
Uncontrolled Keywords:	continuance intention, mobile financial service, PLS-SEM, QR-code mobile payment, UTAUT2, emerging economies
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28-70 Management. Industrial Management > HD30.2 Electronic data processing. Information technology. Including artificial intelligence and knowledge management
Divisions:	Faculty of Artificial Intelligence & Engineering (FAIE)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	02 Mar 2026 02:14
Last Modified:	02 Mar 2026 02:14
URII:	http://shdl.mmu.edu.my/id/eprint/15404

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