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perceived usefulness and ease of use and the development and validation of measurement scales,
and Davis, Bagozzi, and Warshaw (1989), which developed the underlying theoretical rationale for
the causal model, and showed that TAM outperformed the generic version of the theory of reasoned
action from which it was largely adapted. After that, two journal articles reported that TAM compared
favorably to the theory of planned behavior, which is an extension of the theory of reasoned action
from social psychology (Mathieson, 1991; Taylor and Todd, 1994). Moore and Benbasat (1991)
introduced an instrument to measure the various perceptions of an IT innovation based on diffusion
of innovations theory, and adapted the TAM measures of perceived usefulness and ease of use to oper-
ationalize relative advantage and complexity, respectively. In the 1990s, numerous published studies
replicated and extended TAM and applied it to a wide range of systems and user populations. In 2000,
two major extensions to TAM were published: Venkatesh and Davis (2000) published TAM2, which
included various antecedents of perceived usefulness, and Venkatesh (2000) published a paper
investigating various antecedents of perceived ease of use.
Lee et al. (2003) published a critical meta-analytic review that “traces TAM's history, investigates
its findings, and cautiously predict its future trajectory” (p. 752). Lee et al. (2003, p. 752) state that
TAM “continues to be the most widely applied theoretical model in the IS field.” Although TAM's
original focus was on evaluating the effects of system design features on usage behavior through
perceived usefulness, ease of use and usage intentions, most TAM research has not examined
the role of system design features. This gives rise to the somewhat ironic criticism that
“TAM's narrow focus reduced attention on the role of technology and design” (Lee et al., 2003,
p. 766). In many conference discussions lamenting the IS field's over-reliance on reference field
theories, TAM is often mentioned as an example of a true IS-specific theory, which is ironic given
the extent to which TAM was derived from reference field theory such as the theory of reasoned
action. TAM's appeal is driven by its parsimony and robust generality across a broad range of sys-
tem and user types. Its success has also had the effect of overly constraining research attention to the
constructs within TAM, to the exclusion of other potentially important constructs. Lee et al. (2003)
identify several directions for future TAM research. Venkatesh et al. (2003) theoretically and empir-
ically compared TAM to seven other intention models of user acceptance that had been reported in
the literature, and developed a model that unifies the key intention determinants across the eight
models as well as several moderating variables (UTAUT—unified theory of acceptance and use of
technology). Davis and Venkatesh (2004) provided guidelines for embedding early (preprototype)
user acceptance testing within overall software project management practices.
CONCLUSION: THE RELATIONSHIP BETWEEN HCI AND TECHNOLOGY
ADOPTION RESEARCH
In the early to mid 1980s, when TAM was originally being formulated, early human factors and HCI
research played an influential role. This was a time when ideas surrounding “user-centered design”
were first emerging (e.g., Gould and Lewis, 1985). At the time, I regarded TAM as a contribution to
the practice of user-centered design, and expected rapid convergence of user-oriented MIS research
and HCI research. Some convergence has indeed taken place, but at a much slower pace than I
expected. The role for HCI research within the MIS literature is now well established. There is much
that HCI and MIS can learn from each other. However, I think it is unlikely and undesirable for HCI
and MIS research to converge to the point of unification. Both HCI and MIS have unique strengths
and specializations, as well as distinct disciplinary foundations. HCI tends to be more micro in its
focus, drawing extensively upon cognitive psychology, whereas user-oriented MIS tends to be more
macro, drawing from social and organizational psychology (Zhang et al., 2002).
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