regulations. In collectivist societies, the relationships
between employers and employees are perceived to be
familial in moral terms. In such societies, technology is
adopted based primarily on social values. The literature
revealed that in the cultures with a greater IDV index, it
is easier to adopt new technologies (Van Everdingen &
Waarts, 2003) whereas the lack of individualism in any
society causes low adoptions of the technology.
(c) Femininity/Masculinity (MASC) as Moderator: At
the model level, the moderation test shows that there is
no moderating effect of a femininity/masculinity
dimension. The path-by-path moderation test also
revealed that the masculinity/femininity dimension does
not moderate any path of the model. Surprisingly, this
study is not consistent with other studies. For instance,
Yoon (2009) found that masculinity/femininity has a
moderating effect on perceived usefulness, ease of use,
and behavioral intention. Similarly, Im et al. (2011),
Sun and Zhang (2006), and Nistor et al. (2014) discovered that there is an influence of MASC on behavioral intention. Also, as shown in Fig. 4.2 that the score
of MASC for KSA is 60, whereas it is 66 for the UK
(Hofstede, 2010); meaning that the MASC value for
Saudi Arabia is inclined toward the high side. In a
masculine culture, people are more goal-oriented. The
individuals in such cultures are more concerned with
sticking with the absolute truth and are considered as
normative in their thinking. A MASC society is known
for recognition for improvement, competition, more
task-oriented, achievement, and success of the people;
and these characteristics of culture lead to the adoption
of new technology (Van Everdingen, & Waarts, 2003;
Hasan & Ditsa, 1999; Hofstede, 2011).
(d) Uncertainty avoidance (UA) as moderating variable:
The quantitative study indicated the existence of UA
that moderates the adoption of the LMS. The overall
moderation test shows that the presence of the UA
dimension moderates ‘behavioral intention’ of the users
to use LMS. The findings of this research study are
consistent with the other researchers. For instance,
Yoon (2009) found that a high uncertain culture may
decrease the intention of people for online shopping.
Similarly, Nistor et al. (2014) discovered that uncertainty avoidance influences the BI negatively. The
path-by-path moderation tests indicated the moderation
of two paths. First, the presence of UA influences the
relationship between EE and BI. Secondly, the presence
of UA influences the relationship between FC and UB.
This finding is supported by Nistor et al. (2014) and Im,
Kim, and Han (2008). This implies that the FC deals
with the facilitation and support issues and is given
importance by users. Hence, if more facilities support
the use of an LMS, then instructors would be more
likely to use the LMS. Hence, the existence of uncertainty in a society is the indication of low adoptions of
the technology (Van Everdingen & Waarts, 2003;
Hasan & Ditsa, 1999). As shown in Fig. 4.2, the score
of uncertainty avoidance for KSA is 80 (high), whereas
it is 35 (low) for the UK. A high UA culture reflects a
structured and a rule-oriented society having many
rules, regulations, and controls. The countries demonstrating such a high value of UA retain rigid codes of
behavior and belief. A culture with a greater UA index
will have resistance to adopting any new technology
because the society will not able to take the risks of
trying new technologies (Im et al., 2011) and will only
accept innovations that have already been used by
others. Consequently, it will not be easy to adopt new
technologies in a culture with greater values of UA
(Van Everdingen & Waarts, 2003; Hasan & Ditsa,
1999). Hence, the presence of high UA in the HEIs of
Arab societies could cause the lower adoption of LMS
technology because the innovations and adoptions of
technology are resisted in such societies.
Thus, the results of this study reveal that the Arab community appears to have more ‘power distance’ and less
‘uncertainty avoidance’. This might be one of the reasons for
less adoption of LMS.
8.6 Summary of the Empirical Evidence
We developed several research questions to explain and
assess the relationships between independent and dependent
variables of the UTAUT2 model. The key findings are
summarized in Table 8.1.
8.7 UTAUT2 Tested Model
Based on the above discussion, the following tested model
(Fig. 8.1) is proposed for the adoption of LMS in higher
educational institutions of the Middle East region:
Concerning the adoption of LMS, it appears that the
variables PE, EE, SI, FC, and HM directly influence the
78
8 Adoption of LMS: Evidence from the Middle East
between employers and employees are perceived to be
familial in moral terms. In such societies, technology is
adopted based primarily on social values. The literature
revealed that in the cultures with a greater IDV index, it
is easier to adopt new technologies (Van Everdingen &
Waarts, 2003) whereas the lack of individualism in any
society causes low adoptions of the technology.
(c) Femininity/Masculinity (MASC) as Moderator: At
the model level, the moderation test shows that there is
no moderating effect of a femininity/masculinity
dimension. The path-by-path moderation test also
revealed that the masculinity/femininity dimension does
not moderate any path of the model. Surprisingly, this
study is not consistent with other studies. For instance,
Yoon (2009) found that masculinity/femininity has a
moderating effect on perceived usefulness, ease of use,
and behavioral intention. Similarly, Im et al. (2011),
Sun and Zhang (2006), and Nistor et al. (2014) discovered that there is an influence of MASC on behavioral intention. Also, as shown in Fig. 4.2 that the score
of MASC for KSA is 60, whereas it is 66 for the UK
(Hofstede, 2010); meaning that the MASC value for
Saudi Arabia is inclined toward the high side. In a
masculine culture, people are more goal-oriented. The
individuals in such cultures are more concerned with
sticking with the absolute truth and are considered as
normative in their thinking. A MASC society is known
for recognition for improvement, competition, more
task-oriented, achievement, and success of the people;
and these characteristics of culture lead to the adoption
of new technology (Van Everdingen, & Waarts, 2003;
Hasan & Ditsa, 1999; Hofstede, 2011).
(d) Uncertainty avoidance (UA) as moderating variable:
The quantitative study indicated the existence of UA
that moderates the adoption of the LMS. The overall
moderation test shows that the presence of the UA
dimension moderates ‘behavioral intention’ of the users
to use LMS. The findings of this research study are
consistent with the other researchers. For instance,
Yoon (2009) found that a high uncertain culture may
decrease the intention of people for online shopping.
Similarly, Nistor et al. (2014) discovered that uncertainty avoidance influences the BI negatively. The
path-by-path moderation tests indicated the moderation
of two paths. First, the presence of UA influences the
relationship between EE and BI. Secondly, the presence
of UA influences the relationship between FC and UB.
This finding is supported by Nistor et al. (2014) and Im,
Kim, and Han (2008). This implies that the FC deals
with the facilitation and support issues and is given
importance by users. Hence, if more facilities support
the use of an LMS, then instructors would be more
likely to use the LMS. Hence, the existence of uncertainty in a society is the indication of low adoptions of
the technology (Van Everdingen & Waarts, 2003;
Hasan & Ditsa, 1999). As shown in Fig. 4.2, the score
of uncertainty avoidance for KSA is 80 (high), whereas
it is 35 (low) for the UK. A high UA culture reflects a
structured and a rule-oriented society having many
rules, regulations, and controls. The countries demonstrating such a high value of UA retain rigid codes of
behavior and belief. A culture with a greater UA index
will have resistance to adopting any new technology
because the society will not able to take the risks of
trying new technologies (Im et al., 2011) and will only
accept innovations that have already been used by
others. Consequently, it will not be easy to adopt new
technologies in a culture with greater values of UA
(Van Everdingen & Waarts, 2003; Hasan & Ditsa,
1999). Hence, the presence of high UA in the HEIs of
Arab societies could cause the lower adoption of LMS
technology because the innovations and adoptions of
technology are resisted in such societies.
Thus, the results of this study reveal that the Arab community appears to have more ‘power distance’ and less
‘uncertainty avoidance’. This might be one of the reasons for
less adoption of LMS.
8.6 Summary of the Empirical Evidence
We developed several research questions to explain and
assess the relationships between independent and dependent
variables of the UTAUT2 model. The key findings are
summarized in Table 8.1.
8.7 UTAUT2 Tested Model
Based on the above discussion, the following tested model
(Fig. 8.1) is proposed for the adoption of LMS in higher
educational institutions of the Middle East region:
Concerning the adoption of LMS, it appears that the
variables PE, EE, SI, FC, and HM directly influence the
78
8 Adoption of LMS: Evidence from the Middle East