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potential for a better understanding of the role of affect in the IS field. The IIIT model is based on
a general model of the individuals interacting with objects (IIO) in the environment, and draws
upon solid research in three relevant disciplines: psychology, marketing and consumer research,
and organizational behavior. Both the IIO and IIIT models are theoretically sound and can explain
empirical evidence found in existing studies.
The proposed IIIT model draws on many prior studies, such as the technology acceptance model
(Davis, 1989; Davis et al., 1989), computer self-efficacy model (Compeau and Higgins, 1995), cog-
nitive absorption (Agarwal and Karahanna, 2000), and flow (Finneran and Zhang, 2003; Ghani
et al., 1991), to name a few, and it reassembles them in a novel way by positioning clear relation-
ships among the related concepts.
It is noteworthy that the IIIT model reflects only the key components and their relationships. In
a complex world, more factors may come into play. For example, many IS studies have shown that
social norms, facilitating factors, task natures, and user experience, among others, can influence
user behavior intention and usage of IT. In other words, the relationships depicted in the IIIT model
can be situational, and moderating factors could come into play. For example, Venkatesh (2000)
found that experience moderates the effect of trait variable (computer playfulness) on users' per-
ceptions of ease of use: trait influences PEOU only for inexperienced users. Experienced users'
affective reaction of “perceived enjoyment” has more influence on PEOU. It was argued that with
increasing experience, system use may become more routine, less challenging, and less discovery-
oriented, and, therefore, perceived enjoyment derived from actual interaction with the system
becomes more critical in forming users' perceptions of ease of use. A task's characteristics have
also been confirmed to have significant moderating effects. For example, Atkinson and Kydd
(1997) hypothesized and empirically confirmed the moderating effects of the task's purpose. Users
of work-related tasks are more driven by extrinsic motivation, measured as PU, while users of
entertainment-related tasks are more driven by intrinsic motivations, one of which is enjoyment.
Task complexity has shown to have moderating effects. According to the affect infusion model,
more complex tasks recruit more extensive processing strategies, increasing the scope of affect
infusion, which means more influence of affect on cognition (Forgas, 1995). Another related con-
cept is the task's novelty. The more complex a task, the more likely that individuals constantly
receive novel information and have to interpret and assimilate it into a pre-existing representational
system, a process in which affect is supposed to play an important role (Forgas, 1995). All these
findings suggest the importance of moderating effects.
This research calls for more attention to affect-related factors. In this study, we mentioned sev-
eral times that some of the deficiencies of existing theories and models in explaining users' behav-
ior may be due to their ignoring the role of affect. This study goes further and confirms that affect
does matter in determining users' behavioral intentions and actual usage behaviors. Affect also has
significant influence on cognitive factors. Future researchers can go in several directions. First, the
synthesis of the existing affect-related concepts may be helpful. As we can see in the IIIT model,
several affect-related concepts that are correlated have been named and conceptualized differently
in prior studies. Therefore, synthesis may be a good way to contribute to this stream of research.
Second, the interactions between affect and other groups of factors deserve more attention. Third,
as we suggested in a prior text, the distinctions between different types of affect (e.g., trait vs. state)
should be identified. Fourth, the dimensions of affect deserve more attention. Psychological
research could be a valuable reference source of affect dimensions. For example, Russell and col-
leagues produced the affect grid, which received lots of attention in psychology (Russell, 2003;
Russell and Barrett, 1999). It may be a good starting point to study the dimensions of affect as well
as their different relationships with other factors.
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