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Predictive and explanatory modeling regarding adoption of mobile payment systems

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  • Liébana-Cabanillas, F.
  • Lara-Rubio, J.

Abstract

Commercial activities have evolved during the past decade from a single-channel focus and perspective on business opportunities to a multiple-channel approach, with mobile phones playing a major role in the most recent and latest business opportunities. Even if mobile payment systems are still under development and steadily becoming available worldwide, many experts have already pointed to them as the potential payment system of choice taking into account its high penetration level within our society, its accessibility and ease of use. This paper explores the adoption of mobile payment systems from the point of view and perspective of the merchants. In order to provide a comprehensive analysis, this research extensively reviewed existing literature and determined the main factors influencing the adoption of mobile payment systems approaching a methodology involving both a logistic regression modeling and a neural network analysis. Results of these different analyses show that the neural network analysis is the most precise tool in this research when predicting the use of mobile payment systems in certain business. According to these results, some suggestions are proposed to incentive and encourage the intention to use of these mobile payment systems regarding each participant in the adoption process. Finally, this paper discusses some factors regarding future research opportunities.

Suggested Citation

  • Liébana-Cabanillas, F. & Lara-Rubio, J., 2017. "Predictive and explanatory modeling regarding adoption of mobile payment systems," Technological Forecasting and Social Change, Elsevier, vol. 120(C), pages 32-40.
    • Handle: RePEc:eee:tefoso:v:120:y:2017:i:c:p:32-40
    DOI: 10.1016/j.techfore.2017.04.002
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