E- Retail Payment Perception: User Satisfaction and Behavioural Intentions User Satisfaction and Behavioural Intentions

N Manju; B Sudha; S Sasikala

doi:10.34293/commerce.v14i2.9940

N Manju Ph.D Scholar (Part time), Department of Commerce, Alagappa University, Karaikudi https://orcid.org/0000-0003-4051-6346
B Sudha Professor, Department of Bank Management, Alagappa University, Karaikudi https://orcid.org/0000-0002-0785-4020
S Sasikala Teaching Assistant, Department of Bank Management, Alagappa University, Karaikudi https://orcid.org/0000-0003-3121-9411

DOI: https://doi.org/10.34293/commerce.v14i2.9940

Keywords: NPCI, E-Retail Payments, User Satisfaction, Behavioural Intention and Adoption, Perceived Security, Technology Acceptance Model

Abstract

The transition from cash-based transactions to cashless payments has become inevitable in the developing digital-empowered society to support a technology-driven economy. The National Payments Corporation of India (NPCI) has strengthened the digital payment ecosystem through platforms such as RuPay, Bharat QR, and the Unified Payments Interface (UPI), enhancing user convenience in e-retailing transactions. This study aimed to examine the factors influencing user satisfaction and behavioural intention toward NPCI-facilitated e-retail payment systems. A conceptual framework grounded in the Technology Acceptance Model (TAM) and Theory of Planned Behaviour (TPB) was developed and empirically tested using structural equation modelling (SEM). Primary data were collected using convenience sampling from users of digital payment systems through a structured questionnaire. Self-efficacy and user happiness are the predictors that support system quality and impact customer behaviour to adopt and continue NPCI-powered payment solutions. The importance of enhancing user satisfaction strengthens the usage intention, where fintech professionals and service providers must focus on improving security, simplifying transaction processes, and ensuring accessibility. Future research should extend this study by employing larger and more diverse samples, incorporating additional behavioural variables, and conducting longitudinal analyses to improve generalisability.