ABSTRACT
The COVID-19 and associated lockdown in the country emerged as an opportunity for the digital payment providers and Unified Payment Interface (UPI) is the frontrunner among them. UPI is way ahead of other digital payment modes and recorded more than 22 billion transactions which account for over trillion during the 2020-21 financial year. Even though UPI is the most used digital payment mode in India, currently there is no well-established research model for measuring the user adoption towards UPI. So, this paper portrays the in-depth review of current works of literature on digital and mobile payment adoption intention of consumers and developed a new model exclusively for identifying the factors of adoption of 'Unified Payment Interface (UPI)'. The study introduced the model by extending the existing UTAUT2 model by incorporating 'Relative Advantage', 'Add-on Services' and 'Promotional Benefits' as additional constructs apart from the existing UTAUT2 constructs. The proposed model can be empirically tested further to derive meaningful findings and conclusions that can guide the payment service providers in taking appropriate decisions for the development of their user base. © 2022 IEEE.
ABSTRACT
Due to the emergence of the COVID-19 pandemic, governments have implemented several urgent steps to minimize the disease’s effect and transmission. Supportive measures to trace contacts and warn people infected with COVID-19 were also implemented such as the COVID-19 contact tracing application. This study investigated the effects of variables influencing the intention to use the COVID-19 tracker. The extended Unified Theory of Acceptance and Use of Technology model was used to investigate user behavior using the COVID-19 tracker application. Google Form was used to construct and distribute the online survey to participants. Experiment results from 224 individuals revealed that performance expectations, trust, and privacy all have an impact on app usage intention. However, social impact, effort expectation, and facilitating conditions were not shown to be statistically significant. The conceptual model explained 60.07% of the amount of variation, suggesting that software developers, service providers, and policymakers should consider performance expectations, trust, and privacy as viable factors to encourage citizens to use the app. This study work’s recommendations and limitations are thoroughly discussed. © 2022. Vinh T. Nguyen and Chuyen T. H. Nguyen. This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.