Information Technology Reference
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(Taylor & Todd, 1995a). The third influence on
affect is self-efficacy. Perceived usefulness is
hypothesized to be influenced by perceived ease
of use, computer self-efficacy, and social factors,
while perceived ease of use is hypothesized to
be influenced by self-efficacy, social factors,
perceived behavioral control, and personal inno-
vativeness with IT. Perceived behavioral control is
influenced by self-efficacy as well. Finally, self-
efficacy is influenced by personal innovativeness
with IT and social factors.
Our model builds on previous literature in
several ways. First, we have opened up the paths
across the avenues of behavioral, normative, and
control beliefs. In earlier models (e.g., TAM,
DTPB), these antecedents were viewed as separate
and distinct influences, with no linkages among
them. As we discuss in detail in the following
section, however, there are theoretical reasons
and empirical support for the existence of link-
ages across these influences.
Second, we have incorporated the personality
trait of personal innovativeness with information
technology as an attempt to begin the reintegra-
tion of general tendencies into our understanding
of individual behavior with respect to IT. An
explicit aim of TRA and TPB, when they were
developed, was to move away from trying to as-
sociate general personality traits with behaviors.
At the time, it was felt that such predictors were
not as good as beliefs and attitudes (Ajzen, 1991).
Yet now that we have begun to understand these
specific beliefs and attitudes, there is a benefit to
re-examining the role of personality variables in
our models.
In addition, we consider the model at two time
periods to examine the influence of experience
in changing the model parameters. Other specific
differences between our model and previous ones
(e.g., TAM, DTPB) are discussed in later sections.
The primary goal of the study is not to try and
increase the amount of variance explained in
intentions or use of an IT, but rather to obtain a
clearer picture of the antecedent factors that influ-
ence attitudes, subjective norms, and perceived
behavioral control, as well as the inter-relations
among them.
ConstruCts and hypotheses
For space reasons, we do not provide detailed defi-
nitions of the constructs employed in the model.
Interested readers can refer to previous sources for
intentions to use a specific information technol-
ogy in the future (Davis et al., 1989; Venkatesh
et al., 2003), affect (Compeau & Higgins, 1995a;
Thompson, Higgins, & Howell, 1991), perceived
usefulness (Davis et al., 1989), perceived ease
of use (Davis et al., 1989), perceived behavioral
control (Ajzen, 1991; Taylor & Todd, 1995a), com-
puter self-efficacy (Compeau & Higgins, 1995a;
Taylor & Todd, 1995a), social factors (Compeau
& Higgins, 1995a), and personal innovativeness
in the domain of information technology (Agar-
wal & Prasad, 1998). Explanations and working
definitions for all constructs are also available
from the authors upon request.
To avoid unnecessarily repeating the rationale
for hypotheses and relationships that have been
well established by previous research, we simply
list relationships that are not considered contro-
versial and then focus on those that are extensions
to DTPB and TAM. Relationships that have been
previously established (and represented with dot-
ted lines on Figure 2) include:
•
Affect toward using an information technol-
ogy will have a positive influence on intentions
to use the technology (DTPB, TAM).
The perceived usefulness of an information
technology will exert a positive influence on
affect toward using the technology (DTPB,
TAM).
Perceived usefulness of an information
technology will exert a positive influence on
intentions to use the information technology
(TAM).
•
•
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