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A multi-analytical approach to peer-to-peer mobile payment acceptance prediction

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  • Kalinic, Zoran
  • Marinkovic, Veljko
  • Molinillo, Sebastián
  • Liébana-Cabanillas, Francisco

Abstract

This research is a pioneering study into peer-to-peer mobile payment (P2PM-pay) systems' adoption. It proposes a behavioral model of the use of P2PM-pay systems and identifies the key antecedents of the customer's intention to use. Using a two-stage approach, the research model is assessed with data collected through an online survey from a sample of 701 respondents. In the first step, structural equation modeling (SEM) is used to determine P2P mobile payment acceptance predictors. In the second step, neural network models are used to rank the relative influence of significant predictors obtained from the SEM. The results show that consumers perceive the usefulness of P2PM-pay as the most important factor influencing their decision to adopt this innovative technology. The significant impact of social norms and perceived trust are also corroborated. The paper provides important strategic guidelines for the management of companies involved in the development and implementation of P2PM-pay systems.

Suggested Citation

  • Kalinic, Zoran & Marinkovic, Veljko & Molinillo, Sebastián & Liébana-Cabanillas, Francisco, 2019. "A multi-analytical approach to peer-to-peer mobile payment acceptance prediction," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 143-153.
    • Handle: RePEc:eee:joreco:v:49:y:2019:i:c:p:143-153
    DOI: 10.1016/j.jretconser.2019.03.016
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