Explanatory and predictive model of the adoptionof P2P payment systems

Abstract

The purpose of this paper is to identify the factors affecting the intention to use peer-to-peer (P2P)mobile payment. Although mobile technology has become part of everyday life, certain actions andservices, such as mobile payments, are still used relatively infrequently. In this paper, we analyseconsumers’adoption of P2P mobile payment services. Following a review of previous literaturein thisfield, we identify the main factors that determine the adoption of mobile payments, andthen perform a logistic regression (LR) analysis and propose a neural network to predict thisadoption. From the logistic regression results obtained we conclude that six variablessignificantly influence intentions to use P2P payment: ease of use, perceived risk, personalinnovativeness, perceived usefulness, subjective norms and perceived enjoyment. With respectto the nonparametric technique, wefind that the multilayer perceptrons (MLP) prediction modelfor the use of P2P payment obtains higher AUC values, and thus is more accurate, than the LRmodel. This paper is a pioneer study of intention to use with mobile payment using thesemethodologies. The outcome of this research has important implications for the theory andpractice of the adoption of P2P mobile payment services.