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regression analysis. In the following section, we
are going to test all study hypotheses in terms of
whether they are supported or not.
We tested the hypothesized relationship using
regression analysis. The first model to test is the
one representing H2, H3a, H4, and H5a. In which
we assume that INTEN is affected by P_USEF,
SN, PBC and SATISF. Regression results show
an R2 of 74%; which means that the predictor
variables are able to explain 74% of the changes in
the dependent variable. The ANOVA results show
that the model is significant at 0.00 meaning that
the changes in INTEN are not due to chance and
the entire model is significant. Finally, the coef-
ficients table shows the following equation where
all predictor variables are significant: INTEN =
-0.49+ 0.53 P_USEF+ 0.13 SN+ 0.23 PBC+ 0.27
SATISF. To summarize, the following hypotheses
are supported by the regression results:
coefficients table shows the following equation
where all predictor variables are significant:
P_USEF = 1.88+ 0.34 SN+ 025 CONF.
This shows
that SN and CONF are significant to P_USEF.
The following hypotheses are supported by the
regression results:
H1a:
In an ERP implementation environment
Confirmation of Expectation has a positive effect
on Perceived Usefulness (Supported).
H3b:
In an ERP implementation environment
Subjective Norm has a positive effect on Perceive
Usefulness (Supported).
The final model to test is the one testing
H1b and H5b in which we assume that CONF
and P_USEF affect SATISF. Regression results
show an R2 of 63% which means that CONF and
P_USEF are able to explain 63% of the changes
in SATISF. The ANOVA results show that the
model is significant at 0.00 which means that
changes in SATISF are not due to chance. The
entire model is significant. The model equation
is:
SATISF= -1.06+ 0.16 CONF+ 1.02 P_USEF
.
And as per the coefficients table both predictor
variables are significant which lead to the conclu-
sion that hypotheses tested are both supported by
the regression results:
H2:
In an ERP implementation environment Sat-
isfaction has a positive effect on Users' Intention
to continue using ERP system (Supported).
H3a:
In an ERP implementation environment
Subjective Norm has a positive effect on Users'
Intention to continue using ERP system (Sup-
ported).
H4:
In an ERP implementation environment
Perceived Behavior Control has a positive effect
on Users' Intention to continue using ERP system
(Supported).
H5a:
In an ERP implementation environment
Perceived Usefulness has a positive effect on
Users' Intention to continue using ERP system
(Supported).
H1b:
In an ERP implementation environment
Confirmation of Expectation has a positive effect
on Satisfaction (Supported).
H5b:
In an ERP implementation environment
Perceived Usefulness has a positive effect on
satisfaction of using ERP system (Supported).
In the second model we test H1a and H3b. The
model assumes that SN and CONF affect P_USEF.
Regression results show an R2 of 41%; meaning
that both SN and CONF are able to explain 41%
of the changes in P_USEF. According to the re-
sults of ANOVA the model is significant at 0.00
meaning that the changes in P_USEF are not due
to chance and the entire model is significant. The
future reseArch
Future research, with various sample (different
industry, type of ERP) and longitudinal studies
are required. In addition to, future research is
needed to investigate the success of the system
from the view point of IT managers and Users.
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