influences, and task technology. Similar findings have been reached by Chiu et al. (2010) who demonstrated that performance expectancy, facilitating conditions, social influences, and effort expectancy were all significant determinates of the customers’ inclination to use Mobile banking. Indeed, adopters are more likely to be different in their awareness of these predictors in comparison to non-adopters (Chiu et al., 2010). Yu (2012) also confirmed a strong and positive correlation between customers’ intentions and actual usage of Mobile banking. In addition, social influences, performance expectancy, and perceived credibility have been acknowledged by Yu (2012) as positive indicators of customers’ intention to use Mobile banking. However, effort expectancy as stated by Yu (2012) does not present any concern for customers when formulating their intention to adopt Mobile banking. Zhou et al. (2010) observed that the role of effort expectancy on behavioural intention was restricted by the indirect influence of performance expectancy. Püschel et al. (2010) debated that even though perceived behavioural control was strongly affected by both self-efficacy and facilitating conditions, perceived behavioural control does not have a statistical association with customer willingness to adopt Mobile banking.
Banking customers in Finland were found to be highly dependent on interpersonal information sources to formulate their decisions to adopt Mobile banking, rather than information received from the mass media (Suoranta and Mattila 2003). Nevertheless, a negative but non-significant relationship between social influences and perceived usefulness was noticed by Gu et al. (2009) regarding Mobile banking. Suoranta and Mattila (2003) noted that there were significant differences between non-users, occasional users, and regular users based on their income and age. Further, Laukkanen and Pasanen (2008) examined the impact of customer profiles on their adoption of Mobile banking. Their findings indicated that customer adoption of Mobile banking was exclusively predicted by the customers’ age and gender, but was not predicted by education level, career, family size and income. Riquelme and Rios (2010) revealed that the males’ intention to adopt Mobile banking was strongly affected by the role of perceived usefulness, while females paid particular attention to aspects related to ease of use. Chiu et al. (2010) indicated that there were no statistical differences in the role of these factors on customer intention. This could be attributed to the technology readiness dimensions.