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Figure 6. Reliability of the constructs
Figure 7. Correlation between constructs
control, INTEN: intention to continue using ERP,
SATISF: satisfaction). (Figure 6) has the details.
relation coefficient does not explain the effect
of a variable on another but rather it measures
the strength and direction of the relationship.
So, regression analysis will be used to measure
the effect. Same logic applies to H1b (0.42), H2
(0.80), H3a (0.64), H3b (0.59), H4 (0.75), H5a
(0.79), H5b (0.79). (Figure 7) shows correlation
coefficients between survey constructs.
Here in this section, we have seen that the
variables included in a certain hypotheses retained
a significant positive relationship its strengths
ranges from 0.40 to 0.80.
Now the next step is to investigate the impact
of a variable on another, for which we will use
discussion And concLusion
Significant correlations found between all con-
structs. Significant correlation coefficient scores
support the study hypotheses because it tells
that there is a significant relationship between
the constructs. To explain, for H1a the correla-
tion between CONF and P_USEF is found to be
0.40 which indicates the significant relationship
between CONF and P_USEF. However, the cor-
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