high experience this relationship (–0.259 at p<0.05) is
negatively significant, but for low-experience this
relationship is significant (0.187 at p<0.01).
• Path-by-path moderation of awareness: In the
path-by-path moderation test, the following moderating
effects were observed.
– EE ! BI: There is a moderating effect of awareness
between EE and BI (t = 2.04**, p<0.05). At high
awareness this relationship (0.035 at p = 0.703) is
insignificant. However, for low awareness this relationship is significant (0.272 at p = 0.000). This result
shows that the instructors having low awareness give
more importance to ease of use of the technology.
However, ease of use becomes irrelevant at high
awareness.
– SI ! BI: There is a moderating effect of awareness
between SI and BI (t = 2.774***, p<0.01). The result
shows that awareness interacts (moderates) the relationship between SI and BI differently. At high
awareness, this relationship (t = 0.330 at p = 0.000) is
significant. At low awareness, this relationship is
insignificant (t =0.008 at p = 0.8977).
– HM ! BI: There is a moderating effect of awareness
between HM and BI (t = 1.666*, p<0.10). At high
awareness this relationship (0.228 at p = 0.000) is significant. However, for low awareness, this relationship is
mildly significant (0.088 at p = 0.109). This result shows
that the instructors with high awareness have a stronger
relationship between HM and BI. In other words, high
awareness influences their motivational level of the
instructors to use LMS in their teaching.
• Path-by-Path tests for cultural dimensions (PD, UA,
IND, and MAS)
• Responses for power distance (PD) dimensions were collected on a five-point Likert scale. Then the statistical mean
was computed using SPSS and then the median was found.
Based on the median values, the entire responses were
categorized into two groups: high power distance (high PD)
and low power distance (low PD), as explained earlier.
A similar procedure was adopted to run the path-by-path
impact of other variables on an independent variable.
• Path-by-path moderation test for PD: The results of
the path-by-path of PD are shown here:
– Moderation between SI ! BI: PD moderates the
relationship between SI ! BI (t = 2.418**, p<0.01).
At low PD this relationship is insignificant (0.004 at p
= 0.945) and for high PD this relationship is significant (0.271 at p = 0.000).
– Moderation between M ! BI: PD moderates the
relationship between M and BI (t = 0.254*, p<0.1).
At low PD, this relationship is insignificant (0.077 at
p = 0.254) and for high PD, this relationship is significant (0.167 at p = 0.000).
– Moderation between FC ! BI: PD moderates the
relationship between FC and BI (t = 2.003**,
p<0.05). At low PD this relationship is significant
(0.434 at 0.000) and also for high PD this relationship
is significant (0.167 at p = 0.024).
• Path-by-path moderation test for UA: Path-by-path
moderation tests moderate two paths EE ! BI and
FC ! UB.
– Moderation between EE ! BI: There is a moderating effect of UA between EE and BI (as t =
2.757***, p<0.01 is observed) such that for high UA
(–0.049 at p = 0.610) this relationship is insignificant,
but for low UA this relationship is significant (0.292
at p<0.01). The results show that the UA moderates
the relationship between EE and BI.
– Moderation between FC ! UB: There is a moderating effect of UA between FC and UB (as t =
3.221***, p<0.01 is observed) such that for high UA
(0.294 at p<0.05) this relationship is significant but
for low UA this relationship is negatively significant
(–0.230 at p<0.05).
The results show that the UA moderates the relationship between FC and UB.
• Path-by-Path Moderation Test for IND: Path-by-path
shows that the IND dimension moderates only one path
from PE ! BI.
– Moderation between PE ! BI: There is a moderating
effect of IND between PE ! BI (t = 2.264**, p<0.05)
such that for high IND (0.144 at p<0.05) this relationship is significant and for low PD this relationship
is significant (0.392 at p<0.01). In other words, at the
high IND, the relationship between PE and BI is
positively moderated (increased) whereas at low IND
this relationship is stronger and almost triple.
– Path-by-Path Moderation Test for MAS: After
running the path-by-path test, it was found that MAS has
no moderating impact on any of the paths of the model.
7.6.3 Summary of Moderation Tests
Table 7.8 provides a summary of results for the tests performed for moderations at model-level and moderation at
the path-by-path level.
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7 Empirical Evidence of LMS Adoption in the Middle East
negatively significant, but for low-experience this
relationship is significant (0.187 at p<0.01).
• Path-by-path moderation of awareness: In the
path-by-path moderation test, the following moderating
effects were observed.
– EE ! BI: There is a moderating effect of awareness
between EE and BI (t = 2.04**, p<0.05). At high
awareness this relationship (0.035 at p = 0.703) is
insignificant. However, for low awareness this relationship is significant (0.272 at p = 0.000). This result
shows that the instructors having low awareness give
more importance to ease of use of the technology.
However, ease of use becomes irrelevant at high
awareness.
– SI ! BI: There is a moderating effect of awareness
between SI and BI (t = 2.774***, p<0.01). The result
shows that awareness interacts (moderates) the relationship between SI and BI differently. At high
awareness, this relationship (t = 0.330 at p = 0.000) is
significant. At low awareness, this relationship is
insignificant (t =0.008 at p = 0.8977).
– HM ! BI: There is a moderating effect of awareness
between HM and BI (t = 1.666*, p<0.10). At high
awareness this relationship (0.228 at p = 0.000) is significant. However, for low awareness, this relationship is
mildly significant (0.088 at p = 0.109). This result shows
that the instructors with high awareness have a stronger
relationship between HM and BI. In other words, high
awareness influences their motivational level of the
instructors to use LMS in their teaching.
• Path-by-Path tests for cultural dimensions (PD, UA,
IND, and MAS)
• Responses for power distance (PD) dimensions were collected on a five-point Likert scale. Then the statistical mean
was computed using SPSS and then the median was found.
Based on the median values, the entire responses were
categorized into two groups: high power distance (high PD)
and low power distance (low PD), as explained earlier.
A similar procedure was adopted to run the path-by-path
impact of other variables on an independent variable.
• Path-by-path moderation test for PD: The results of
the path-by-path of PD are shown here:
– Moderation between SI ! BI: PD moderates the
relationship between SI ! BI (t = 2.418**, p<0.01).
At low PD this relationship is insignificant (0.004 at p
= 0.945) and for high PD this relationship is significant (0.271 at p = 0.000).
– Moderation between M ! BI: PD moderates the
relationship between M and BI (t = 0.254*, p<0.1).
At low PD, this relationship is insignificant (0.077 at
p = 0.254) and for high PD, this relationship is significant (0.167 at p = 0.000).
– Moderation between FC ! BI: PD moderates the
relationship between FC and BI (t = 2.003**,
p<0.05). At low PD this relationship is significant
(0.434 at 0.000) and also for high PD this relationship
is significant (0.167 at p = 0.024).
• Path-by-path moderation test for UA: Path-by-path
moderation tests moderate two paths EE ! BI and
FC ! UB.
– Moderation between EE ! BI: There is a moderating effect of UA between EE and BI (as t =
2.757***, p<0.01 is observed) such that for high UA
(–0.049 at p = 0.610) this relationship is insignificant,
but for low UA this relationship is significant (0.292
at p<0.01). The results show that the UA moderates
the relationship between EE and BI.
– Moderation between FC ! UB: There is a moderating effect of UA between FC and UB (as t =
3.221***, p<0.01 is observed) such that for high UA
(0.294 at p<0.05) this relationship is significant but
for low UA this relationship is negatively significant
(–0.230 at p<0.05).
The results show that the UA moderates the relationship between FC and UB.
• Path-by-Path Moderation Test for IND: Path-by-path
shows that the IND dimension moderates only one path
from PE ! BI.
– Moderation between PE ! BI: There is a moderating
effect of IND between PE ! BI (t = 2.264**, p<0.05)
such that for high IND (0.144 at p<0.05) this relationship is significant and for low PD this relationship
is significant (0.392 at p<0.01). In other words, at the
high IND, the relationship between PE and BI is
positively moderated (increased) whereas at low IND
this relationship is stronger and almost triple.
– Path-by-Path Moderation Test for MAS: After
running the path-by-path test, it was found that MAS has
no moderating impact on any of the paths of the model.
7.6.3 Summary of Moderation Tests
Table 7.8 provides a summary of results for the tests performed for moderations at model-level and moderation at
the path-by-path level.
70
7 Empirical Evidence of LMS Adoption in the Middle East