Information Technology Reference
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(SCMS). Finally, enterprise systems were not that
popular as only 20 factories indicated using such
integrated type of systems (27%)
When trying to explain the results of the cor-
relations between the total number of systems (a
measure of usability in this study) and the number
of computers and employees and the total sales,
it seems obvious that the size of the firm is a
direct influencer (predictor) of the usability of
IT. The larger firms will have higher numbers of
employees and larger sales and thus they tend to
utilize technology to improve operations and gain
competitive advantage in the market. Also, it is
logical to conclude that the firm size is directly
correlated to complexity of operations and thus
firms adopt IT to better control operations and
improve flow of material and information. Finally,
we can conclude that firms with higher sales will
have larger tendency to invest in IT and thus buy
more computers and adopt more types of systems.
The second objective was to explore managers'
intention to adopt such systems. Results indicated
a high intention to adopt PIS because of two main
reasons: The first was the high mean values of
predictors, which indicates the high perceptions
of managers towards the adoption process. All
means were above 4.5 out of 7, which indicate a
high acceptance rates with respect to all variables
used. The second reason for this conclusion is
the high significant bivariate correlations with
the rate of adoption, and this indicates that the
method used and the large number of predictors
was a limitation. The only variable with none
significant correlation is ease of use and this
supports the limitation of the method used. The
highest correlation was between rate of adoption
and results demonstrability (0.440**).
On the other hand, when summed together,
the set of variables competed on the variance and
only two variables showed significant prediction
of rate of adoption. The two variables are: results
demonstrability; the ability to see tangible results
out of the system, and ease of use; where the com-
plexity of the system is a huge obstacle to using it.
The IDT model explained 27.6% of the variance
in the rate of adoption. Results might have some
limitations as the IDT have 8 predictors competing
on the variance in the rate of adoption and this
might limit the ability to explain the dependent
variable well. The regression method used was to
enter all variables forcefully and this might be the
reason behind this surprising result. As this study is
an exploratory one, we can conclude that a larger
sample size and a thorough conceptual analysis
of the predictors will lead to better utilization of
variables and better and accurate results.
concLusion
This paper aimed at exploring the status of using
IT and specifically PIS in the area of production
and manufacturing in Jordan. The study utilized
two samples for two separate studies; the first was
a sample of managers mainly related to IT in a
group of factories in Al-Hasan Industrial Zone and
other areas mainly in the Northern part of Jordan to
explore the usage of PIS and other types of systems
in the industrial area. The second study utilized
another sample (after four months and from a
different set of factories), from the same area and
from the Northern part of the country to test the
IDT using an instrument translated from Moore
and Benbasat work (1991). Results indicated that
systems like accounting information systems and
HR and payroll systems were the mostly used
among firms and distribution and manufacturing
aiding systems were the least used among the
sample used. The role of IS in production area
was highly appreciated and a major conclusion is
that the size of firm indicates the high computer
usage and the diversity of systems used.
The second study resulted in high and sig-
nificant indicators in predicting the adoption rate,
and most of the constructs used in the IDT were
significantly correlated to rate of adoption. But
when regressing all indicators on rate of adop-
tion, only two competed on the variance and
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