Introduction to Information Systems Models and Methodologies - High Level Models and Methodologies for Information Systems - page 13

1.7 Quality Evaluation Models

Technology acceptance has been a very active subject of research, not just for the

field of IS, but for marketing as well. For developers and managers alike, it is
crucial to evaluate by which processes will users or customers adopt and suc-
cessfully accept a given system or technology, or reject it altogether. In order to
determine this, the stage of implementation, as well as any other stages following
that, is fundamental. It is also of key importance to understand the constitution of
the user base, its contextual background, their needs, objectives, and obstacles.
Finally, researchers have also borrowed concepts from behavioral psychology,
going to the deeper level of human behavior to understand the processes by which
people make their choices to use or discard tools.
A pioneering approach on this issue was the theory of reasoned action (TRA),
developed by Fishbein and Ajzen ( 1975 ). It asserts that there are four different
variables that

uence behavioral action: beliefs, attitudes, intentions, and
behaviors. The model describes the relationships between these factors. Essentially,
beliefs and evaluations shape the user

in

' s attitude toward behavior; normative beliefs

and the user s motivation to comply with them shape the subjective norm. Beliefs

and subjective norm will then shape the user

'

s behavioral intention, leading to a
result of an actual behavior. This premise was later adjusted by Ajzen ( 1991 )inhis
theory of planned behavior (TPB), where the relationships and variables involved in
the process are analyzed in more depth. According to the TPB model, beside
behavioral and normative beliefs, there is a third factor that will in

'

uence the user ' s

intentions: control beliefs, related to the user s perception of whether he/she can

effectively use the new system. Both TRA and TPB models are essentially
behavioral theory models that can be adapted to the context of IS acceptance.
However, one of the most popular approaches on this

'

field was the technology
acceptance model (TAM), proposed by Davis ( 1986 ). It describes the means by
which subjective elements, such as a user

s usefulness,
will influence objective elements, such as system use. Once key design features are
implemented and also considering other external

' s perception of the system '

uences (such as personal
context, organizational structure, and socioeconomic background), users will form a
cognitive response based on their perception of the new system

in

s functionality and
usability (perceived usefulness). This will generate an affective response, translated
in their attitude toward use of the system, and eventually a behavioral response,
which is the actual use of the system (or its rejection). This model thus establishes a
causal relationship between user

'

' s perceptions of the system and their choice to use

it (see Fig. 1.5 ).
TAM is an exceedingly simple model, which has led it to be a very popular
option for researchers, because it can easily be adjusted to a variety of contexts. On
the other hand, it has also been the subject of frequent criticism, namely due to the
vague characterization of its core constructs and relationships. For this reason, there
have been attempts at building more consistent and complex models on this simple
premise. Venkatesh and Davis ( 2000 ) proposed the TAM 2, whose ultimate goal