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Existing literature classifies technology acceptance theories based on their applicability to an individual or an organization. Main theories used to explain Information and Communication Technology (ICT) adoption at the individual level are Technology Acceptance Model (TAM, Davis, 1989; Davis, Bagozzi, & Warshaw, 1989), Theory of Planned Behaviour (TPB, Ajzen, 1985, 1991), Innovation Diffusion Theory (IDT, Rogers, 1995), and Unified Theory of Acceptance and Use of Technology (UTAUT, Venkatesh, Morris, Davis, & Davis, 2003). These theories have been extensively used to explain individuals’ acceptance and use of an ICT (Knudsen & Roman, 2015; Ramayah, Chiun, Rouibah, & May, 2014; Shih, 2013; Alwahaishi & Snášel, 2013; Abroud, Choong, & Muthaiyah, 2013; Ko & Lu, 2012; Islam, 2011).
TAM focuses on two theoretical constructs, perceived usefulness and perceived ease of use, which are theorized to be fundamental determinants of a system use. Davis (1989) developed his psychometric scales for both perceived usefulness and perceived ease of use in three stages; a pretesting stage with a sample of 15 computer users, an empirical field study with a sample of 120 computer users, and a laboratory experiment with a sample of 40 voluntary MBA students, each time he modified and refined the scales. Davis (1989) found that both perceived usefulness and perceived ease of use are significantly correlated with system use. However, perceived usefulness have a greater correlation with system use than that of perceived ease of use. Moreover, Davis (1989) suggested that perceived ease of use and perceived usefulness predict attitudes, which can be defined as users’ evaluation of the desirability of using a system. Attitude and usefulness influence individuals’ intention to use a system. In addition, actual use of a system is predicted by behavioral intentions.
TPB (Ajzen, 1988, 1991) is an extension of Theory of Reasoned Action (TRA, Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975). This theory suggests that behavior is determined by intentions to perform the behavior. Intention is predicted by three factors; attitudes toward the behavior, subjective norms, and perceived behavioral control. Attitudes, subjective norms, and perceived behavioral control are also related to appropriate sets of salient behavioral, normative, and control beliefs about the behavior.
Venkatesh et al. (2003) examined eight technology acceptance models and based on these examinations formulated a model that integrates and unifies the characteristics and elements of these models. First, they reviewed eight models to identify determinants of intention and use of information technology. Second, they empirically compared these models using longitudinal data from four organizations. Finally, the conceptual and empirical similarities across the eight models were used to formulate UTAUT. This theory posits that three direct determinants of intention to use are performance expectancy, effort expectancy, and social influence and two direct determinants of use behavior are behavioral intention and facilitating conditions. In addition, significant moderating influences of experience, voluntariness, gender, and age are confirmed.