Description
Mobile payments (m-payments) appear to have the potential to be among the more popular of mobile services, however, take-up has been lower than anticipated, and given associated levels of investment, the issue is of strategic organizational concern. This paper presents a study investigating consumer intentions toward m-payments, extending existing knowledge by developing and evaluating a model that incorporates factors relevant to the m-payment context, including a multi-dimensional treatment of perceived risk. Empirical data to test the model were captured in a region expected to exhibit strong mobile data traffic growth, and were analyzed using variance-based structural equation modeling. The empirical application of the model augments knowledge at the human level of the formation of consumer intentions to use m-payments. The authors also suggest a contribution from an organizational and managerial perspective through presenting information that has implications for development, management, and marketing of m-payment services.
Recommended Citation
Williams, Michael D.; Roderick, Sian; Davies, Gareth H.; and Clement, Marc, "Risk, Trust, and Compatibility as Antecedents of Mobile Payment Adoption" (2017). AMCIS 2017 Proceedings. 34.
https://aisel.aisnet.org/amcis2017/AdoptionIT/Presentations/34
Risk, Trust, and Compatibility as Antecedents of Mobile Payment Adoption
Mobile payments (m-payments) appear to have the potential to be among the more popular of mobile services, however, take-up has been lower than anticipated, and given associated levels of investment, the issue is of strategic organizational concern. This paper presents a study investigating consumer intentions toward m-payments, extending existing knowledge by developing and evaluating a model that incorporates factors relevant to the m-payment context, including a multi-dimensional treatment of perceived risk. Empirical data to test the model were captured in a region expected to exhibit strong mobile data traffic growth, and were analyzed using variance-based structural equation modeling. The empirical application of the model augments knowledge at the human level of the formation of consumer intentions to use m-payments. The authors also suggest a contribution from an organizational and managerial perspective through presenting information that has implications for development, management, and marketing of m-payment services.