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The moderating effect of experience in the adoption of mobile payment tools in Virtual Social Networks: The m-Payment Acceptance Model in Virtual Social Networks (MPAM-VSN)

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  • Liébana-Cabanillas, Francisco
  • Sánchez-Fernández, Juan
  • Muñoz-Leiva, Francisco

Abstract

Although mobile-related technologies are widely accepted in today's society, mobile payment in Virtual Social Networks (VSN) is not among the most widely used mobile services. This paper analyzes users’ acceptance of mobile payment in VSN. In order to analyze the level of acceptance of this technology, as well as the factors that determine its use by consumers, we have introduced a modification of the classical technological acceptance models (TRA and TAM). Thus, the study proposes and tests an integrated theoretical model, which establishes the relative importance of the key factors (external influences, ease of use, usefulness, attitude, trust and risk) in terms of the acceptance of the mobile payment system in VSN. It also analyzes the eventual moderating effect of users’ experience with similar tools. The empirical results show that the proposed behavioral model (named MPAM-VSN) is accordingly adjusted, thus showing that previous experience increases intention of use. Finally, the results obtained in this study reveal interesting implications for the diffusion of mobile payment systems in VSN.

Suggested Citation

  • Liébana-Cabanillas, Francisco & Sánchez-Fernández, Juan & Muñoz-Leiva, Francisco, 2014. "The moderating effect of experience in the adoption of mobile payment tools in Virtual Social Networks: The m-Payment Acceptance Model in Virtual Social Networks (MPAM-VSN)," International Journal of Information Management, Elsevier, vol. 34(2), pages 151-166.
    • Handle: RePEc:eee:ininma:v:34:y:2014:i:2:p:151-166
    DOI: 10.1016/j.ijinfomgt.2013.12.006
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    1. Liébana-Cabanillas, Francisco & Marinković, Veljko & Kalinić, Zoran, 2017. "A SEM-neural network approach for predicting antecedents of m-commerce acceptance," International Journal of Information Management, Elsevier, vol. 37(2), pages 14-24.

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