Information Technology Reference
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While their names imply affective components, attitude and satisfaction, which have been
extensively studied within the last two decades, deserve further discussion. Borrowed mainly
from Theory of Reasoned Action, attitude is defined as “an individual's positive or negative feel-
ings (evaluative affect) about performing the target behavior” (Davis et al., 1989). The definition
of satisfaction in the IS field is very similar to those used in marketing and organizational behav-
ior research. Actually, researchers who study users' satisfaction directly refer to the definitions of
satisfaction. Both attitude and satisfaction are considered affect factors; satisfaction is conceptu-
ally distinct from attitude in that satisfaction is a transient and experience-specific affect, while
attitude is relatively more enduring. Thus, a user may have a positive attitude (with a pleasant
experience) but may still feel dissatisfied if his or her actual experience is below expectation
(Bhattacherjee, 2001 p. 607).
Table 14.3 lists the definitions, sources, and original measures of affective concepts studied in
IS research, along with their reinterpretations using the affective and cognitive reaction concepts
defined in the section “Theoretical Grounds and an Abstract Model.” For affective reactions, the
two dimensions (arousal and pleasure) are considered. Most of these original measuring items can
be reinterpreted by the two reaction concepts. It is noteworthy that researchers sometimes use
experiments to gain more accurate user descriptions of their affective reactions under the assump-
tion the users may not recall their spontaneous affective reactions. For example, Venkatesh and
Speier (2000) randomly assigned subjects to two different training interventions, game-based and
traditional interventions respectively, each of which had three 2-hour sessions. After the last ses-
sion, subjects were given a knowledge test.
Several interesting observations can be obtained from Table 14.3. First, there is little consis-
tency or agreement between the terms used and their measures: the same term may mean differ-
ent concepts or may be measured differently, and the same concept may be defined as different
terms. Second, the meanings of the affective concepts do not always fall within the affective reac-
tion dimensions. Some have to do with a mix of affective and cognitive reactions (Compeau and
Higgins, 1995; Moon and Kim, 2001). Third, the measures of some concepts of affective reaction
emphasize one dimension more than the other: Flow, perceived playfulness, and cognitive absorp-
tion have more measuring items for arousal than pleasure, while enjoyment (Igbaria et al., 1995)
has more items for pleasure than for arousal.
Cognitive Reactions
Compared to trait and affective reaction variables, cognitive reaction variables are well studied in lit-
erature. Several major concepts have been proposed and tested, among which we identify three major
concepts: perceived usefulness, perceived ease of use, and computer self-efficacy. Perceived useful-
ness (PU) and perceived ease of use (PEOU) are widely used in IS research when studying users'
adoption of IT. Perceived usefulness has been confirmed as an important, if not the most important,
factor that influences user technology acceptance and therefore has received a great deal of attention
from prior researchers (Sun and Zhang, 2006). There is almost no doubt that usefulness is the most
important issue in determining users' intentions. Because of its importance, almost all models or the-
ories that we are aware of include similar (if not totally the same) concepts, with perceived usefulness
such as outcome expectation in the computer self-efficacy model (Compeau and Higgins, 1995),
extrinsic motivation in the motivational model (Davis et al., 1992), and performance expectancy in
the united theory of acceptance and use of technology (UTAUT) (Venkatesh et al., 2003).
Another salient variable is perceived ease of use. Similar concepts are also found in several other
theories or models such as effort expectancy in UTAUT, and perceived complexity in Thompson
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