The technology acceptance model (TAM) is an information systems theory that models how users come to accept and use a technology.
The actual system use is the end-point where people use the technology. Behavioral intention is a factor that leads people to use the technology. The behavioral intention (BI) is influenced by the attitude (A) which is the general impression of the technology.
The model suggests that when users are presented with a new technology, a number of factors influence their decision about how and when they will use it, notably:
External variables such as social influence is an important factor to determine the attitude. When these things (TAM) are in place, people will have the attitude and intention to use the technology. However, the perception may change depending on age and gender because everyone is different.
The TAM has been continuously studied and expanded—the two major upgrades being the TAM 2 and the unified theory of acceptance and use of technology (or UTAUT). A TAM 3 has also been proposed in the context of e-commerce with an inclusion of the effects of trust and perceived risk on system use.
TAM is one of the most influential extensions of Ajzen and Fishbein's theory of reasoned action (TRA) in the literature. Davis's technology acceptance model (Davis, 1989; Davis, Bagozzi, & Warshaw, 1989)is the most widely applied model of users' acceptance and usage of technology(Venkatesh, 2000). It was developed by Fred Davis and Richard Bagozzi. [1] TAM replaces many of TRA's attitude measures with the two technology acceptance measures - ease of use, and usefulness. TRA and TAM, both of which have strong behavioural elements, assume that when someone forms an intention to act, that they will be free to act without limitation. In the real world there will be many constraints, such as limited freedom to act.
Bagozzi, Davis and Warshaw say:
Earlier research on the diffusion of innovations also suggested a prominent role for perceived ease of use. Tornatzky and Klein analysed the adoption, finding that compatibility, relative advantage, and complexity had the most significant relationships with adoption across a broad range of innovation types. Eason studied perceived usefulness in terms of a fit between systems, tasks and job profiles, using the terms "task fit" to describe the metric. Legris, Ingham and Collerette suggest that TAM must be extended to include variables that account for change processes and that this could be achieved through adoption of the innovation model into TAM.
Several researchers have replicated Davis's original study to provide empirical evidence on the relationships that exist between usefulness, ease of use and system use. Much attention has focused on testing the robustness and validity of the questionnaire instrument used by Davis. Adams et al. replicated the work of Davis to demonstrate the validity and reliability of his instrument and his measurement scales. They also extended it to different settings and, using two different samples, they demonstrated the internal consistency and replication reliability of the two scales. Hendrickson et al. found high reliability and good test-retest reliability. Szajna found that the instrument had predictive validity for intent to use, self-reported usage and attitude toward use. The sum of this research has confirmed the validity of the Davis instrument, and to support its use with different populations of users and different software choices.
Segars and Grover re-examined Adams et al.'s)replication of the Davis work. They were critical of the measurement model used, and postulated a different model based on three constructs: usefulness, effectiveness, and ease-of-use. These findings do not yet seem to have been replicated. However, some aspects of these findings were tested and supported by Workman by separating the dependent variable into information use versus technology use.
Mark Keil and his colleagues have developed (or, perhaps rendered more popularisable) Davis's model into what they call the Usefulness/EOU Grid, which is a 2×2 grid where each quadrant represents a different combination of the two attributes. In the context of software use, this provides a mechanism for discussing the current mix of usefulness and EOU for particular software packages, and for plotting a different course if a different mix is desired, such as the introduction of even more powerful software.The TAM model has been used in most technological and geographic contexts. One of these contexts is health care, which is growing rapidly[2]
Saravanos et al. [3] extended the TAM model to incorporate emotion and the effect that may play on the behavioral intention to accept a technology. Specifically, they looked at warm-glow.
Venkatesh and Davis extended the original TAM model to explain perceived usefulness and usage intentions in terms of social influence (subjective norms, voluntariness, image) and cognitive instrumental processes (job relevance, output quality, result demonstrability, perceived ease of use). The extended model, referred to as TAM2, was tested in both voluntary and mandatory settings. The results strongly supported TAM2.
In an attempt to integrate the main competing user acceptance models, Venkatesh et al. formulated the unified theory of acceptance and use of technology (UTAUT). This model was found to outperform each of the individual models (Adjusted R square of 69 percent). UTAUT has been adopted by some recent studies in healthcare.[5]
In addition, authors Jun et al. also think that the technology acceptance model is essential to analyze the factors affecting customers’ behavior towards online food delivery services. It is also a widely adopted theoretical model to demonstrate the acceptance of new technology fields. The foundation of TAM is a series of concepts that clarifies and predicts people’s behaviors with their beliefs, attitudes, and behavioral intention. In TAM, perceived ease of use and perceived usefulness, considered general beliefs, play a more vital role than salient beliefs in attitudes toward utilizing a particular technology.[6]
TAM has been widely criticised, despite its frequent use, leading the original proposers to attempt to redefine it several times. Criticisms of TAM as a "theory" include its questionable heuristic value, limited explanatory and predictive power, triviality, and lack of any practical value. Benbasat and Barki suggest that TAM "has diverted researchers' attention away from other important research issues and has created an illusion of progress in knowledge accumulation. Furthermore, the independent attempts by several researchers to expand TAM in order to adapt it to the constantly changing IT environments has lead to a state of theoretical chaos and confusion". In general, TAM focuses on the individual 'user' of a computer, with the concept of 'perceived usefulness', with extension to bring in more and more factors to explain how a user 'perceives' 'usefulness', and ignores the essentially social processes of IS development and implementation, without question where more technology is actually better, and the social consequences of IS use. Lunceford argues that the framework of perceived usefulness and ease of use overlooks other issues, such as cost and structural imperatives that force users into adopting the technology.[8] For a recent analysis and critique of TAM, see Bagozzi.
Legris et al.[9] claim that, together, TAM and TAM2 account for only 40% of a technological system's use.
Perceived ease of use is less likely to be a determinant of attitude and usage intention according to studies of telemedicine, mobile commerce,) and online banking.