Adoption of mobile self-service retail banking technologies The role of technology, social, channel and personal factors

Purpose The purpose of this paper is to identify the factors influencing the adoption of mobile self-service retail banking technologies, and the degree of influence of each factors leading their usage. Having mobile banking (MB) as the reference service and drawing on previous studies in the field, an extended Uni?ed Theory of Acceptance and Use of Technology (UTAUT) model is proposed and empirically validated to investigate the impact of technology, social, channel and personal factors on potential customers' usage intentions. Design/methodology/approach On evidence drawn, through a dedicated research instrument, from 513 non-users in Greece, the effects of the extended UTAUT's drivers on MB adoption intentions are assessed using partial least squares path methodology. Findings The results indicated that technology-related factors, expressing innovation expected performance, and social influence are the leading determinants of MB adoption intentions, followed by the two channel-related factors, expressing perceived risk and trust toward MB usage, and potential users' inherent innovativeness. Furthermore, the consideration of service experience as a moderating variable has shown that there is a significant difference in the effects of social influence and perceived trust on adoption intention between potential users with high and limited service experience. Research limitations/implications - The sample is country specific and this may affect generalizability of findings. Also, the cross-sectional design adopted does not reflect the temporal changes. Practical implications - From a practical point of view, the findings suggest that banks should consider, except of the technology-related factors of MB, the way that potential users perceive the channel-related factors as well as the individual differences in order to improve the MB acceptance level. Originality/value Although there are a few studies that use UTAUT to predict MB adoption, the proposed model is the first that combines four groups of MB adoption driving factors into a causal model in order to explain MB adoption intentions in a country which is facing severe financial crisis for the last eight years, Greece.