4.7 Article

Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology

Journal

COMPUTERS IN HUMAN BEHAVIOR
Volume 61, Issue -, Pages 404-414

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chb.2016.03.030

Keywords

Mobile; Payment; UTAUT2; DOI; Adoption; Intention to recommend

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Mobile payment is receiving growing attention globally, from consumers to merchants, as an alternative to using cash, check, or credit cards. The potential of this technology is enormous. This study aims to identify the main determinants of mobile payment adoption and the intention to recommend this technology. We advance the body of knowledge on this subject by proposing an innovative research model that combines the strengths of two well-known theories; the extended unified theory of acceptance and use of technology (UTAUT2) with the innovation characteristics of the diffusion of innovations (DOI), with perceived security and intention to recommend the technology constructs. The research model was empirically tested using 301 responses from an online survey conducted in a European country, Portugal. Data was analyzed using the structured equation modeling (SEM). We found compatibility, perceived technology security, performance expectations, innovativeness, and social influence to have significant direct and indirect effects over the adoption of mobile payment and the intention to recommend this technology. The relevance of customer's intention to recommend mobile payment technology in social networks and other means of communication was also confirmed, supporting the recommendation to include it in social marketing campaigns and in future technology adoption studies. For researchers this study provides a basis for further refinement of individual models of acceptance. For practitioners, understanding the key constructs is crucial to design, refine, and implement mobile payment services, applications, and products that achieve high consumer acceptance, value, and high rates of positive recommendations in social networks. (C) 2016 Elsevier Ltd. All rights reserved.

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