Technology acceptance is posited to be influenced by a variety of factors, including individual differences, social influences, beliefs, attitudes and situational influences (Agarwal, 2000; Teo, 2009a). A majority of the conceptualisations of technology acceptance have drawn on theories and models from social psychology, notably the theory of reasoned action (TRA) (Fishbein & Ajzen,1975), theory of planned behaviour (TPB) (Ajzen, 1991), technology acceptance model (TAM) (Davis, 1989), and unified theory of acceptance and use of technology (UTAUT) (Venkatesh, Morris, Davis & Davis, 2003). In these theories, the dependent variable of interest is an observable manifestation of the focal behaviour in question. Furthermore, these theories posit that one's behaviour is influenced by an intention to perform the behaviour. In other words, the performance of actual behaviour is preceded by a person's behavioural intention to engage in the activity. The intention construct in the TRA is determined by the individual's attitude towards the behaviour and the subjective norm. Subjective norm reflects an individual's assessment of the extent which people who are important to him/her would desire the performance or non-performance of the focal behaviour, while attitude shows the affective response (positive or negative) towards the behaviour. In the TPB, another construct, perceived behavioural control reflects an individual's perceptions of the extent to which personal and situational factors act as influences to the performance of the behaviour. The TAM posits that intention is determined by attitude which in turn is influenced by perceived usefulness and perceived ease of use. Perceived usefulness refers to an individual's perception of the extent to which using technology would enhance one's productivity and perceived ease of use captures one's belief of the extent to which using technology would be free from effort. The UTAUT holds that four key constructs (performance expectancy, effort expectancy, social influence and facilitating conditions) are direct determinants of usage intention. Among acceptance studies (eg, Teo, 2011), performance expectancy, effort expectancy and social influence are operationalised as perceived usefulness, perceived ease of use and social norm, respectively. Facilitating conditions refers to the degree to which an individual believes that an organisational and technical infrastructure exists to support use of technology. Despite the popularity and empirical support, researchers have called for greater empirical comparisons of these models to establish their explanatory and predictive power, with a view to generate more meaningful insights on technology acceptance. (Contains 1 table and 1 figure.)