Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model

•M-Banking is one of the most promising technologies that could prove to have considerable value to both banks and customers.•This study investigates factors that could predict the use of M-Banking, customer satisfaction and customer loyalty.•This study proposes a comprehensive conceptual model that clarifies the use of M-Banking from the perspective of Saudi users.•A questionnaire survey was conducted to collect the required data from convenience sampling of Saudi bank customers.•This study would consider the adoption of numeric data in order to inferentially analyse them using SEM. Mobile banking is one of the most promising technologies that has emerged in recent years and could prove to have considerable value to both banks and customers. Thus, this study recognises the need to test the main factors that could predict the use of mobile banking as well as how using such a system could contribute to both customer satisfaction and customer loyalty. The conceptual model of this study combines two models (i.e. UTAUT2 and the D&M IS Success Model). A questionnaire survey was conducted to collect the required data from convenience sampling of Saudi bank customers. The main factors – performance expectancy, price value, facilitating conditions, hedonic motivation, habit, system quality and service quality – were found to have a significant impact on actual use behaviour. This study was cross-sectional, therefore future studies should implement longitudinal studies in order to re-collect the findings. Further, this study adopted convenience sampling of Saudi M-Banking users. This may adversely impact the issue of generalisability to the whole population. The gap in the M-Banking literature in Saudi Arabia would be bridged by proposing a comprehensive conceptual model that scrupulously clarifies the use of M-Banking from the perspective of Saudi users. Furthermore, this study would consider the adoption of numeric data in order to inferentially analyse them using SEM. This in turn would assist in generalising the findings to the whole Saudi population.