TAM was formulated by Fred D. Davis to provide a valid measurement scale for assessing user acceptance of computers (Davis 1989, 1993). TAM is focused more on technology, and is claimed to be different from previous measurements as it provides a valid measurement scale to predict user acceptance of IT. These measurements were derived from TRA. To measure user acceptance, TAM uses two variables, “perceived usefulness” and “perceived ease” of use (Davis 1989, 1993). Perceived usefulness (PU) refers to the degree to which the user believes the new technology would enhance job performance (Davis 1989, 1993; Davis, Bagozzi & Warshaw 1989). Perceived ease of use (PEU) refers to the user’s belief that using the new technology would require minimum effort (Davis 1989, 1993; Davis, Bagozzi & Warshaw 1989). TAM suggested that the user’s intention to use new technology is jointly determined by attitudes toward using and perceived usefulness (Davis 1989, 1993; Davis, Bagozzi & Warshaw 1989) as shown in Figure 1:
Figure 1. Technology Acceptance Model (adopted from Davis 1989)
PEU may be influenced by two factors: the “availability of training and support” and “perceived accessibility” of the new technology (Karahanna & Straub 1999). PEU is also influenced by computer self-efficacy, objective usability, and direct experience (Venkatesh & Davis 1996). PU may be influenced by three factors: the availability of training and support; the social presence of the technology through communication channels; and the social influence to use the new technology (Karahanna & Straub 1999). However, in TAM the main focus to measure user acceptance is PU and PEU. TAM seems to ignore subjective norms found in both TRA and TPB. Probably TAM assumes that subjective norms are included within external variables.
As a model of measuring and predicting user acceptance of new technology, TAM has been tested in various contexts. It has been tested on IT adoption in North America, Switzerland, and Japan (Straub, Keil & Brenner 1997). It has also been tested with government employees (Roberts & Henderson 2000), web systems and e-commerce (Chen & Tan 2004; Lederer et al. 2000; Moon & Kim 2001; Yi & Hwang 2003), electronic supermarkets (Henderson & Divett 2003), and even in agricultural sectors (Flett et al. 2004). TAM is widely used and has been perceived as valid in different contexts.
Although TAM has been widely used, it has been found that it could not explain the IT adoption experience in Japan (Straub, Keil & Brenner 1997). Straub et.al. (1997) believe that this is due to cultural differences. Although it is not clear whether culture is the cause of differences in that study result and what the specific cultural characteristics are that cause the differences, TAM still could not explain the Japanese experience in IT adoption. Furthermore, TAM measurement tools (questionnaires for PEU and PU) could be biased if the researcher changes the order of questions asked. Changing the order or even the wording of questions is common practice when adapting TAM for investigations in different contexts (Davis & Venkatesh 1996). The order of questions and the translations of TAM’s questionnaire might be responsible for the Japanese result. Other research has found that although TAM is useful for predicting user acceptance of new technology, it is better in explaining technology adoption if the researcher takes into account human and social change processes and also the adoption of innovation model (Legris, Ingham & Collerette 2003). TAM’s focus on PU and PEU did not cover whether there is the need for applicability of a technology (IT) or whether it is “objectively” useful.
Finally, TAM has been extended and evolved into TAM2. TAM2 extends the original TAM to include factors such as subjective norms, image, job relevance, output quality, result demonstrability, experience, and voluntariness (Venkatesh & Davis 2000). TAM2 has also incorporated some aspects that are similar to the innovation adoption model: observability, triability, and compatibility (Rogers 1995) as suggested by Legris et.al (2003).
Even with the modification, TAM is used to explain behaviour based on specific stimuli given to individuals as is the case with TRA and TPB. It does not take into account the interactions between individuals within an organisation. TRA, TPB, and TAM usually predict the acceptance (or behaviour) of innovations as a statistical aggregate from respondents’ responses.
References
Chen, L.-D. & Tan, J. 2004, ‘Technology Adaptation in E-Commerce: Key Determinants of Virtual Stores Acceptance’, European Management Journal, vol. 22, no. 1, pp. 74-86.
Davis, F.D. 1989, ‘Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology’, MIS Quarterly, vol. 13, no. 3, pp. 319 – 340.
Davis, F.D. 1993, ‘User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts’, International Journal Man-Machine Studies, vol. 38, no. 3, pp. 475-487.
Davis, F.D., Bagozzi, R.P. & Warshaw, P.R. 1989, ‘User Acceptance of Computer Technology: A Comparison of Two Theoretical Models’, Management Science, vol. 35, no. 8, pp. 982-1003.
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Moon, J.-W. & Kim, Y.-G. 2001, ‘Extending The TAM for A World-Wide-Web Context’, Information & Management, vol. 38, no. 4, pp. 217-230.
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Rogers, E.M. 1995, Diffusion of Innovations, 4th edn, Free Press, New York.
Straub, D., Keil, M. & Brenner, W. 1997, ‘Testing the Technology Acceptance Model Across Culture: A Three Country Study’, Information & Management, vol. 33, no. 1, pp. 1-11.
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Yi, M.Y. & Hwang, Y. 2003, ‘Predicting the Use of Web-based Information Systems: Self-efficacy, Enjoyment, Learning Goal Orientation, and the Technology Acceptance Model’, International Journal Human-Computer Studies, vol. 59, no. 4, pp. 431-449.
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