Technology Acceptance Model and Extended Models

a. Technology Acceptance Model

Davis' (1989) technology acceptance model (TAM), refined from the TRA, was developed to predict the determinants of user acceptance of a wide range of IT.

While the aforementioned TRA and TPB are general theories of human behavior, this model was formulated specifically for the use of IT system (Mathieson et al., 2001). That is, the goal of this model is "to provide an explanation of the determinants of computer usage that is generally capable of explaining user behavior across a broad range of end-user computing technologies and user population, while at the same time being both parsimonious and theoretically justified" (Davis et al., 1989, p. 985).

Davis identified two predictors out of cognitive and affective variables, and took two as a departure point, which are 'perceived ease of use' (PEOU) and 'perceived usefulness' (PU). According to him, actual use of new IT is a product of rational insight into desirable outcomes, and users adopt IT when their perceptions on ease of use and usefulness are positive. Davis (1989) defined perceived ease of use as “the degree to which a person believes that using a particular system would be free of effort” (p. 320); i.e., the level of difficulty in integrating it into routine, whether physically or mentally; and the measure of system quality, as said by some researchers (Petter, Delone, & McLean, 2008).

Davis also defined perceived usefulness as “the degree to which a person believes that using a particular system would enhance his or her job performance” (p. 320). It is assumed not only that the system application would be useful but that he can perceive the usefulness.

In the model, actual system use is determined by behavioral intention, and the intention are jointly determined by attitude toward using and perceived usefulness. See Figure 4.

[Figure 4] Technology Acceptance Model (TAM) (Davis, 1989, p. 320)

The perceived usefulness has a direct effect on the intention over and above the attitude; and yet, the perceived ease of use does only via the perceived usefulness. In other words, the perceived usefulness is confirmed as a major determinant of individual intention to use, whereas the perceived usefulness is a significant but secondary indirect variable of intention. TAM also proposes that external variables affect behavioral intention and actual use through mediated effects on perceived ease of use and perceived usefulness.

Davis conducted numerous experiments to testify validity of perceived ease of use and perceived usefulness. In 1989, he developed scales for two concepts, and validated six highly reliable items for each construct. Because of the parsimony and robustness, TAM is suitable for dealing with various phenomena of IT acceptance, facilitating transformation and extension. At the same time, it also has the modularity meaning its independence enough to delete and exchange specific factors (Park, 2004). Although a stream of prolific researches on the use of IT have held their foundations on many theoretical models, TAM is considered the most influential and widely applied theory.

b. Extensions of Technology Acceptance Model

Ever since originally proposed, TAM has evolved over time. There have been tons of empirical studies replicating or extending TAM since its inception. A

growing body of information technology acceptance studies have modified or extended it to examine a variety of systems in different contexts (Chin & Todd, 1995; Davis et al., 1989; Igbaria et al., 1995; Szajna, 1996; Taylor & Todd, 1995; Venkatesh, 1999, 2000; Venkatesh & Bala, 2008; Venkatesh & Davis, 2000;

Venkatesh & Morris, 2000; Venkatesh et al., 2003).

To name a few, Taylor and Todd combined TAM and TPB (C-TAM-TPB) into a model in 1995, focusing on the role of prior experience. In this alternative version taking variables from the two, the authors submitted that behavioral intention is influenced by attitude, subjective norm, perceived behavioral control, and perceived usefulness.

And Venkatesh (2000) tested dominants of perceived ease of use and presented a theoretical model on an anchor and adjustment base. He integrated three variables (control, intrinsic motivation, and emotion) as dominant factors that determine early perceptions of a new system.

Furthermore, Venkatesh and Davis (2000) developed technology acceptance model 2 (TAM 2), and added theoretical constructs spanning two processes:

"social influence processes (subjective norm, voluntariness, and image) and cognitive instrumental processes (job relevance, output quality, result demonstrability, and perceived ease of use)” (p. 187).

Similarly, technology acceptance model 3 (TAM 3) developed by Venkatesh and Bala (2008) presents an integrated model of the determinants of individual levels of IT adoption and use. This extension is based on a theoretical framework consisting of four categories: individual differences (computer self efficacy, computer anxiety, and computer playfulness); system characteristics (job relevance, output quality, result demonstrability, perceived enjoyment, and objective usability); social influence (subjective norm and image), and facilitating conditions (perceptions of external control).

On top of this, in 2003, unified theory of acceptance and use of technology (UTAUT) was developed by Venkatesh and his associates. On the basis of TAM, the authors reviewed eight models toward a unified view, and included four key constructs (e.g. performance expectancy, effort expectancy, social influence, and

facilitating conditions), attitude toward IT, computer self-efficacy, and anxiety that influence behavioral intention to use and technology use. 'Performance expectancy', similar to the concept of perceived usefulness, is defined as the perceptions of benefits resulting from a behavior, which is viewed as extrinsic motivation as well. And the notion of 'effort expectancy', corresponding to the perceived ease of use, means the expected degree of ease or difficulty involved with the behavior.