Antecedents of unified payment interface (UPI) adoption: a PLS-SEM and artificial neural network approach (ANN)

Purpose This study aims to investigate the antecedents of attitude, namely, hedonic motivation (HM), social influence (SI), perceived benefits (PB) and perceived security (PS) that shape up attitude (ATT) towards unified payment interface (UPI) which further influences consumers’ intention to use UPI (UI) in an emerging economy. Furthermore, it examines whether consumers age moderates the relationship of HM and SI with their attitude towards UPI. Similarly, it tests whether consumer’s perceived trust (PT) moderates the relationship of PB and PS with their attitude towards UPI. Design/methodology/approach A structured questionnaire developed in Google Forms was administered through email and WhatsApp to collect data from a sample of 439 Indian consumers. Subsequently, the collected data was analysed using a multi-analytic approach that blended partial least squares structural equation modelling (PLS-SEM) and artificial neural network (ANN) analysis. Findings The findings reveal that HM, SI and PS have a direct and significant positive impact on ATT, however, interestingly the effect of PB on ATT was not found to be statistically significant. In addition to this, consumers’ attitudes towards UPI had direct effect on their intentions to use UPI. Both the proposed moderation effects were found to be statistically insignificant. Furthermore, validating the PLS-SEM results, the outputs of ANN analysis suggest that HM is the strongest predictor of UI followed by PS, ATT, SI and PB. Research limitations/implications Theoretically, this research establishes how selected antecedents shape up consumers’ attitude towards UPI and determine their usage intentions in emerging economies. Practically, this research suggests that consumers age as well as PT do not moderate the proposed relationships. Single cross-sectional research design, non-probability sampling approach, limited sample size and selected antecedents mark the key limitations of this research. Originality/value This research contributes to the Fintech literature by bridging the knowledge gap about proposed associations among HM, SI, PB, PS, Age, PT, ATT that eventually determine UI via stimulus-organism-response framework.