An Empirical Investigation of Remote Mobile Payment Adoption

Despite being predicted to be one of the future’s most successful mobile services, mobile payments (MPs) have achieved limited acceptance in developed countries to date. Due to this limited success, examination of consumer adoption behavior is a key issue in order to provide important managerial information for the development and marketing of MP systems according to consumers’ needs. The imminent release of a central database for remote MP (RMP) in April 2014 by the UK Payments Council emphasizes the timeliness of this area. Currently MP research has largely ignored the variations between different MP solutions, has failed to compare factors affecting different user types, and no empirical research relating to MP adoption has been conducted in the context of the UK to date. This study applies the Unified Theory of Acceptance and Use of Technology (UTAUT) extended with perceived risk. The devised research model postulates that performance expectancy, effort expectancy, social influence, and perceived risk influence UK RMP users’ and non-users’ intentions to use, or continue using, the technology. In keeping with existing quantitative MP adoption research, a survey methodology employing a questionnaire as the data collection method was utilized. Confirmatory factor analysis was conducted by utilizing AMOS Version 20.0 to examine the measurement model which was then followed by examination of the structural relationships. In order to compare the factors affecting users and non-users of RMP, multi-group moderation was undertaken. The model fit indices and standardized factor loadings determined a good measurement model (CMIN/DF 1.829; GFI 0.904; CFI 0.981, RMSEA 0.046; PCLOSE 0.812; standardized factor loadings ≥0.76). Whilst the findings of the structural model analysis revealed that performance expectancy, effort expectancy, social influence, and perceived risk all significantly influenced non-users behavioral intention, only the effects of performance expectancy and perceived risk were significant for existing users of RMP. These findings support target market segmentation for RMP. Marketers should focus on emphasizing the utility and security of RMPs in communications with both current and potential users. Moreover, marketers should attempt to identify ‘opinion leaders’ in order to encourage positive word-of-mouth promotion, and emphasize the ease of using RMP, in communications with non-users of RMP.