Quality Evaluation Models - High Level Models and Methodologies for Information Systems - page 108

Thus, the fourth premise is that the intention to continue using an IS derives
from perceived usefulness of IS use. It is important to note that while users might
have an initial perception of low usefulness, that perception can be adjusted during
the con

rmation stage, if users realize that their initial expectations were unrealistic.
They will adjust their perception of usefulness (Bhattacherjee 2001 ).
In a study developed by Halilovic and Cicic ( 2013 ), the authors assessed the
level of in uence that supporting conditions could have on the intention of

continuing to use IS. The ECM was extended to incorporate conditions of support
as a determinant element of IS usage continuance. The conclusions of the empirical
validation of the extension of this model demonstrated that, by including the ele-
ment of supporting conditions, the extended model gained a more accurate pre-
diction rate, than the traditional ECM. The results allowed for a new premise to be
established: Users

' belief in a supporting structure had a signi cant impact on their

perception of the system s usefulness (Halilovic and Cicic 2013 ).

As with other models, the ECM has been adopted by researchers using other
theories or models. This happens when the model is able to explain certain parts of
the process of usage continuance, but is insuf

'

cient to understand the entirety of the
steps that lead to IS continuance. Kim ( 2010 ) investigated the continuance of
mobile data service, by allying the TPB with the ECM. The author argued that
despite the fact that the ECM of IS continuance was a thorough model for the
calculation of the core elements behind continuance intention, it neglected the effect
of social norm and perceived behavior control. To understand the impact that these
two aspects had on IS continuance of use remained an intricate task, which justifies
the choice of combining the TPB and the ECM (Kim 2010 ).

6.11 The Social Influence Model

Vannoy and Palvia ( 2010 ) argued that in the literature regarding technology

adoption there was not suf cient research on adoption in a broader context, at the

level of society, community, or lifestyle. Speci cally, they argued that the prevalent

models of technology adoption were not appropriate for the study of social com-
puting, which made it urgent to de ne a model that had that ability, considering the

growing role of social technologies in the present day. They suggested that certain
constructs of social computing were determinant for this purpose and had direct
impact over perceptions of usefulness and ease of use, making the process of
technology adoption a twofold construct based on adoption by individuals and
embedment in society (Vannoy and Palvia 2010 ). They named their framework the
social in uence model (SIM).

SIM is essentially based on the premise that a person will adopt a certain
technology or product when there is a considerable amount of people in his/her
group that have done so (Young 2009 ). Therefore, it regards social in

uence as the
element that precedes the adoption of a certain technology. Although the TRA
already accounts for a social component of technology adoption, in the concept of