Communication competence factors as moderators to the relationship between user participation and information quality

PARTICIPATION AND INFORMATION QUALITY
Journal of Information Technology Management Volume XX, Number 4, 2009
10
Table 4: Factor Loadings
Component
Variables
Variable
Items
1
2
3
4
5
6
7
8
9
User
Participation
1
0.85
2
0.89
3
0.85
4
0.81
5
0.85
6
0.86
7
0.86
8
0.86
9
0.76
Information
Quality
1
0.78
2
0.88
3
0.90
4
0.86
5
0.84
6
0.88
7
0.88
8
0.88
9
0.91
1
0.64
User's
Experiences in
Current
Systems
2
0.82
5
0.64
1
0.83
2
0.89
User's
Experiences in
Current Job
3
-0.48
0.46

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COMMUNICATION COMPETENCE FACTORS AS MODERATORS TO THE RELATIONSHIP BETWEEN USER
PARTICIPATION AND INFORMATION QUALITY
Journal of Information Technology Management Volume XX, Number 4, 2009
11
Table 4 (continued)
Component
Variables
Variable
Items
1
2
3
4
5
6
7
8
9
Cognitive
Communication
1
0.49
Competence-
Planning
2
0.76
Cognition
4
0.44
1
0.78
2
0.67
3
0.72
Cognitive
Communication
Competence-
Modeling
Cognition
4
-0.5
0.43
1
0.60
2
0.64
Cognitive
Communication
Competence-
Presence
Cognition
3
0.53
1
0.76
2
0.86
3
0.91
4
0.89
Cognitive
Communication
Competence-
Reflection
Cognition
5
0.76
1
0.80
2
0.88
3
0.84
Cognitive
Communication
Competence-
Consequence
Cognition
4
0.78

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COMMUNICATION COMPETENCE FACTORS AS MODERATORS TO THE RELATIONSHIP BETWEEN USER
PARTICIPATION AND INFORMATION QUALITY
Journal of Information Technology Management Volume XX, Number 4, 2009
12
Table 4 (continued)
Component
Variables
Variable
Items
1
2
3
4
5
6
7
8
9
1
0.54
0.48
Communication
Apprehension
2
0.73
3
0.74
4
0.84
5
0.79
6
0.82
7
0.88
8
0.83
9
0.73
10
0.70
11
0.83
12
0.76
13
0.68
14
0.59
15
0.73
16
0.74
17
0.67
18
0.78
22
0.47
23
0.62
24
0.61
Variables
Percentage
of
Variance
22.76
13.42
11.80
6.99
4.98
3.76
3.16
2.58
2.16
Eigenvalue
16.39
9.66
8.50
5.03
3.59
2.71
2.28
1.86
1.56
Testing the Hypotheses
A Pearson correlation was performed to test the
first hypothesis (relationship between user participation
and information quality). Significant positive correlation
between user participation and information quality was
observed (r = 0.319; significance value = 0.027, p-value ≤
0.05), thus lending support for the first hypothesis.
Hypotheses 2 through 4 were tested by using
moderated regression analysis (following Aiken and West
[1]). All variables (except the dependent variable,
information quality) were centered to avoid problems
with multicollinearity [1]. Centering a variable is
accomplished by subtracting its mean off each value of
the variable. First, the predictor variables (user
participation and the moderating variables proposed in
Hypotheses 2 through 4) were entered in the regression
equation. Then, the interaction term between user
participation and a moderating variable was entered to the
regression equation. The hypotheses 2 through 4 will be
supported (i.e., the hypothesized variables significantly
moderate the relationship between user participation and
information quality), if the incremental R
2 
is significant.
Each of the changes in R
2
provided by adding an
interaction term to the equation and its significance are
shown in Table 5.

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COMMUNICATION COMPETENCE FACTORS AS MODERATORS TO THE RELATIONSHIP BETWEEN USER
PARTICIPATION AND INFORMATION QUALITY
Journal of Information Technology Management Volume XX, Number 4, 2009
13
Table 5: R-Squared Report
Hypothesis
N
R
2
Before
Adding
Interaction
Term
R
2
After
Adding
Interaction
Term
∆R
2
Significance F
Change
H2a: User's Experiences in Current System
48
0.149
0.177
0.028
0.226
H2b: User's Experiences in Current Job
48
0.102
0.178
0.076
0.05**
H3a: Planning Cognition
48
0.107
0.133
0.026
0.259
H3b: Modeling Cognition
48
0.112
0.178
0.066
0.067*
H3c: Presence Cognition
48
0.110
0.116
0.006
0.587
H3d: Reflection Cognition
48
0.104
0.104
0
0.973
H3e: Consequence Cognition
48
0.106
0.107
0.01
0.845
H4: Communication Apprehension
48
0.102
0.102
0
0.927
* p≤ 0.1 **p≤0.05
The results in Table 5 show that there are only
two variables that moderate the relationship between user