How Does the Pandemic Facilitate Mobile Payment? An Investigation on Users' Perspective under the COVID-19 Pandemic

Int J Environ Res Public Health. 2021 Jan 24;18(3):1016. doi: 10.3390/ijerph18031016.

Abstract

Owing to the convenience, reliability and contact-free feature of Mobile payment (M-payment), it has been diffusely adopted in China during the COVID-19 pandemic to reduce the direct and indirect contacts in transactions, allowing social distancing to be maintained and facilitating stabilization of the social economy. This paper aims to comprehensively investigate the technological and mental factors affecting users' adoption intentions of M-payment under the COVID-19 pandemic, to expand the domain of technology adoption under the emergency situation. This study integrated Unified Theory of Acceptance and Use of Technology (UTAUT) with perceived benefits from Mental Accounting Theory (MAT), and two additional variables (perceived security and trust) to investigate 739 smartphone users' adoption intentions of M-payment during the COVID-19 pandemic in China. The empirical results showed that users' technological and mental perceptions conjointly influence their adoption intentions of M-payment during the COVID-19 pandemic, wherein perceived benefits are significantly determined by social influence and trust, corresponding with the situation of pandemic. This study initially integrated UTAUT with MAT to develop the theoretical framework for investigating users' adoption intentions. Meanwhile, this study originally investigated the antecedents of M-payment adoption under the pandemic situation and indicated that users' perceptions will be positively influenced when technology's specific characteristics can benefit a particular situation.

Keywords: COVID-2019; adoption intention; mental accounting theory (MAT); mobile payment; unified theory of acceptance and use of technology (UTAUT).

MeSH terms

  • COVID-19*
  • China / epidemiology
  • Commerce / trends*
  • Humans
  • Mobile Applications / statistics & numerical data*
  • Pandemics / economics*
  • Reproducibility of Results