The effects of gender and age onnew technology implementatio.docx

The effects of gender and age on
new technology implementation
in a developing country
Testing the theory of planned behavior (TPB)
Elizabeth White Baker
Virginia Military Institute, Lexington, Virginia, USA
Said S. Al-Gahtani
King Khalid University, Abha, Saudi Arabia, and
Geoffrey S. Hubona
Georgia State University, Atlanta, Georgia, USA
Abstract
Purpose – This paper aims to investigate the effects of gender,
age and education on new technology
implementation in Saudi Arabia, a technologically developing
country, using the Theory of Planned
Behavior (TPB).
Design/methodology/approach – The research was an empirical
investigation based on surveys
completed by 1,088 Saudi knowledge workers.
Findings – The TPB model performs well in Saudi Arabia. This
validation accounts for 37 percent of
the variance in behavioral intention among Saudi knowledge
workers. For the moderator variables,
there were no statistically significant interactions, with the

exception of the moderation of perceived
behavioral control on behavioral intention by level of education.
Research limitations/implications – Saudi Arabia is an exemplar
for many developing nations
characterized by distinct intellectual and cultural traditions that
differ from Western cultures.
Demographic variables (e.g. gender and age) that have been
reported to be significant moderators of
the influences of attitude, subjective norm and perceived
behavioral control on behavioral intention in
other cultural samples were found to be non-significant in this
Saudi Arabian sample.
Practical implications – System developers using user-centered
design approaches have different
design criteria for the successful workforce adoption of
information technology (IT) systems in a
technologically developing nation, as compared to the
workforce of a technologically developed nation.
Originality/value – This paper validates TPB as a multi-cultural
model for investigating the impact
of attitudes, beliefs, and subjective norms on technology
adoption, and, in contrast to previous studies,
indicates the (non)effects of select demographic moderators on
the model using a non-Western sample.
Keywords Demographics, Developing countries, Communication
technologies, Culture, Behaviour,
Saudi Arabia
Paper type Research paper
Introduction
The adoption and use of technology in organizational settings is

a topic of intense
interest germane to developing countries. Whereas the
implementation and use of
organizational information technologies (ITs) have been widely
researched in
developed nations, these findings are not necessarily applicable
to less developed
regions of the world. With the increasing trend towards the
transnational globalization
The current issue and full text archive of this journal is
available at
www.emeraldinsight.com/0959-3845.htm
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Information Technology & People
Vol. 20 No. 4, 2007
pp. 352-375
q Emerald Group Publishing Limited
0959-3845
DOI 10.1108/09593840710839798
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of industries, it becomes necessary to better understand those
factors that promote the
successful deployment and adoption of technology in
organizations that are located in

these regions. Specifically, there is the need to understand those
social and cultural
factors that affect technology adoption and use. Such an
understanding will assist the
growing number of organizations in those regions that are
implementing and using
new information technologies. Among the social and cultural
factors that affect the use
of IT in organizations, gender, social norms, education and age
(among others) have
been shown to impact the transfer and use of technology in
organizations (Hubona
et al., 2006).
The social and cultural characteristics of Arab and Muslim
societies differ from
those of industrialized Western nations, and these
characteristics are reflected in the
overall demographics of the workforce. Using a specific
example of an Arab nation,
Saudi Arabia, women constitute a much smaller percentage of
the Saudi workforce,
and the median age of a professional worker is much younger in
Saudi Arabia than in
more technologically developed countries (Al-Gahtani, 2004).
With a workforce that is
predominantly young and male, the effects of age and gender on
the adoption and use
of technology might have a different impact on Saudi
organizations, compared to
organizations in industrialized Western nations, such as the US
and Europe.
Using the theory of planned behavior (TPB) (Ajzen, 1991), this
study investigates
the effects of gender, age and education on IT implementation

in Saudi Arabia. The
primary contribution of this research is to utilize TPB to predict
intention to use
computer technology in Saudi Arabia, while also examining the
influences of potential
moderating variables in the model. The next section relates the
theoretical background
of TPB for investigating IT implementation in a developing
country, and discusses the
primary TPB constructs, as well as the moderating variables of
gender, age and
education within the context of the Saudi culture. The third
section details the research
methodology and explains the survey sample characteristics and
measures. The fourth
section describes the data analysis procedure and presents the
results of the study. The
fifth section considers the implications of the findings for both
researchers and
practitioners. Finally, the last section presents and discusses the
conclusions of the
study.
Background and theory
Adoption and use of organizational technology in developing
countries
Information technology can play an important role in leveraging
productivity and
efficiency in both public and private organizations.
Organizations that successfully
adopt and implement IT processes can realize significant
performance gains (Cash
et al., 1992; Nickerson, 1981; Swanson, 1988). Surveying
previous studies of
productivity enhancements resulting from IT implementation,
Hirschheim (1986)

reported productivity gains ranging from 15 percent to 340
percent.
Potential gains in productivity can offset the high investment
cost in IT. According
to the latest Organization for Economic Cooperation and
Development Information
Technology Outlook (2000), the world IT market (hardware,
software, and services)
grew at an annual rate of 8 percent between 1990 and 1997. By
2000, the worldwide
revenues of IT producers exceeded $735 billion. The
information and communications
technology (ICT) sector contributed close to 10 percent of
OECD business GDP in 2001,
up from 8 percent in 1995. The statistics reported by OECD
show that developing
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countries are far behind developed countries in spending on IT
acquisition, and that
ICT adoption is affected by income, educational attainment,
children in the family, age
and gender across different cultures.
The IT literature on developing countries has proliferated to
include a wide range of
forces driving IT adoption (Odedra and Kluzer, 1988). Initially,
studies indicated
significant resistance to adopting and using computer resources
in developing
countries, based on social and cultural factors (Abdul-Gader,
1999). Developing
countries, generally speaking, are facing many barriers that can
hinder the adoption
and diffusion of IT. Malek and Al-Shoaibi (1998) report some
of these barriers as
related to the lack of:
. sufficient IT infrastructure;
. IT expertise;
. government support;
. conceiving of information as an important asset; and
. effective national policies pertaining to information
technology.
However, today, with the accelerating forces of globalization,
and the increasing
deployment of IT in developing countries, there exist
compelling incentives to better
understand the unique drivers of IT adoption in non-Western

countries (Al-Gahtani,
2004; Anandarajan et al., 2002). The parameters for successful
IT adoption vary across
the spectrum of national technological development from the
least developed countries
to the most developed. These are largely due to differing social
and cultural contexts
(Abdul-Gader, 1999; Straub et al., 2001), in addition to
differential economic
development. In the case of Saudi Arabia, detailed and
supportive national IT policies
have been explicitly developed by the Saudi government. These
policies address
political, social, economic and environmental aspects for
promoting the adoption of IT
(Malek and Al-Shoaibi, 1998). The success of these policies
will depend on how well the
individual factors of IT adoption have been incorporated.
Understanding how social and cultural factors, such as gender,
age and level of
education can influence the adoption of IT is useful in
promoting the organizational
diffusion of IT in non-Western cultures. Many studies show how
gender, age and
level of education affect IT adoption and usage, although most
were conducted
within developed nations (Ahuja, 2002; Ford et al., 1996;
Rhodes, 1983; Woodfield,
2002). In a study simultaneously conducted in three nations
characterized by
differing cultural beliefs and norms, Gefen and Straub (1997)
demonstrated that
gender roles represent an important social factor influencing
perceptions and
behaviors with respect to IT adoption. Their results indicate that

gender does have
an effect on the IT adoption process and provides a rationale to
investigate whether
gender moderates the effects of predictor variables in existing
models of IT adoption
and usage.
Approaching cross-cultural research
There are many theoretical frameworks of the factors promoting
of IT in organizational settings, but few have been validated in
non-Western cultures.
The lack of frameworks that have been demonstrated to be
robust across cultures can
limit the development of theoretical extensions in this area
(Maheswaran and Shavitt,
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2000). The choice of emic research, indigenous and conducted
on the basis of
culture-specific frameworks, versus etic research, which
examines cultural differences
using previously established universal frameworks as
benchmarks, can confuse the
issue about the most appropriate orientation of cross-cultural
research (Maheswaran
and Shavitt, 2000; Morris et al., 1999; Peng et al., 1991).
In conducting this research, we follow Berry’s (1989) five-step
process as a basis for

an integrated etic/emic approach to studying IT adoption
differences among cultures.
The first step is to examine the research problem in one’s own
culture, developing a
conceptual framework and a relevant instrument. The study
conducted by Mathieson
(1991) provides the foundation for an initial emic study of the
adoption of IT among
professional workers. The second step Berry recommends is to
transport this
measurement model so as to examine the same issue in another
culture, as an imposed
etic study. Accordingly, an objective of our study is to report
the findings of an
imposed etic study of predicted IT use in the Saudi workforce.
According to Berry
(1989), the third step is to enrich the imposed etic framework
with unique aspects of the
second culture, and to then examine the two, culturally diverse
sets of findings for
comparability. Accordingly, the findings from this study can be
leveraged in future
TPB studies to continue to investigate predicted IT use in
culturally diverse settings.
Saudi Arabia and the importance of IT adoption
Saudi Arabia is a developing country where IT adoption is being
influenced by explicit
government policy in the attempt to enhance national
organizational productivity.
Saudi Arabia encompasses 2.25 million square kilometers with a
population of 24.6
million in 2005 (World Bank Group, 2006), including
approximately 5.6 million foreign
residents. By 2002, the ratio of PCs per 1,000 persons was only
63.8, which makes up 60

percent of the Arab PC market, a consortium of 22 Arab
nations. Furthermore, Saudi
internet users were estimated to number 4.5 million in 2005. In
total IT market
penetration, Saudi Arabia ranks third among the 22 Arab
Nations. Unlike many
developing countries, the Saudis do not suffer from financial
resource limitations,
although despite these abundant fiscal resources, Saudi Arabia
has historically been
characterized by the underutilization of available computing
capacity (Atiyyah, 1989;
Yavas et al., 1992) (Table I).
Saudi Arabia has many valid reasons to encourage IT adoption
as a leverage to
achieve organizational productivity gains. The contribution of
information and
communication technologies to economic development overall
is an important new
focus. A key objective of promoting the implementation of new
technology is to bridge
the digital gap between Arab countries and the developed world.
According to the
United Nations Development Program’s Arab Human
Development Report (Fergany
Size (sq.km.) 2,250,000
Population (2005) 24.6 million
Foreign residents (2005) 5.6 million
Ration of PCs per 1,000 (2002) 63.8
Internet users (2005) 4.5 million
Total IT market penetration among Arab nations 3rd of 22
Table I.
Saudi Arabia –

technological and
demographic facts
Theory of
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355
et al., 2002), this gap has widened, due to the nature of the Arab
ICT industry, which is
highly susceptible to:
. monopoly and consolidation;
. the high costs of infrastructure; and
. Arab “brain drain” away from native countries toward
developed nations.
Moreover, there are information disparities among Arab states,
where the primary
language is not English. A societal focus on more Arabic-
language-specific software
and internet content would foster an improved internal
infrastructure dedicated to the
dissemination of this information.
For Saudi Arabia specifically, IT plays a pivotal role in limiting
the demand for
foreign labor, semi-skilled labor in particular (Abdul-Gader and
Al-Angari, 1995), by

providing the capability for organizations to be more productive
with fewer foreign
employees. In Saudi Arabia, Saudization is a development
strategy that seeks to
replace foreign workers with Saudi nationals (Looney, 2004),
part of a growing trend in
policy for the Arab Gulf Cooperation Council (GCC) countries
to control the flow of
foreign labor (Winckler, 1997). Foreign labor is being restricted
as a result of reputed
negative economic and social ramifications of a large foreign
resident population on
Saudi nationals. Guidelines of the Shura council (a Saudi
consultative body on
government policy to the Saudi ministers’ council) dictate that
by 2007, 70 percent of
the workforce will have to be Saudi (Smith, 2002). A major
objective of the Saudi
Development Plans of the 1990s has been to develop general
education to deal with
technological changes and with the rapidly changing social and
economic conditions.
The ultimate goal is to supplant a large portion of Saudi
Arabia’s significant foreign
labor force with indigenous workers, who comprised only 79
percent of the total Saudi
labor force in 1989 (Metz, 1992), through a three-prong
strategy:
(1) increase employment for saudi nationals across all sectors of
the domestic
economy;
(2) reduce and reverse over-reliance on foreign workers; and
(3) recapture and reinvest income which otherwise would have

flowed overseas as
remittances to foreign worker home countries (Looney, 2004).
Leading private sector Saudi-based companies, such as Saudi
ARAMCO (Arabian
American Oil Company) played a significant role in the initial
adoption of IT within
Saudi organizations. Currently, large Saudi companies,
including Saudi ARAMCO,
SABIC (Saudi Basic Industries Corp), and Saudi Arabian
airlines and banks use
state-of-the-art application technologies with more than 80
percent of industrial
companies using computer systems. The continued increase of
internet usage and
e-commerce is an important catalyst for individuals and
organizations to adopt IT for
their competitive advantage, with the anticipation of significant
continued growth in
the near-future Saudi IT market.
Following the lead of the private sector, the Saudi public sector
has also developed
initiatives to accelerate the adoption of IT throughout the
country. In 2004, the Saudi
Crown Prince issued a decree to the Saudi Computer Society to
provide a National IT
Plan (NITP) for Saudi Arabia. The Saudi NITP project, almost
complete and in the final
revision stage, utilizes information and other technologies to
promote knowledge and
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to support economic development throughout the Kingdom. The
plan asserts that
scientific and technological innovation is an essential feature
for economic
development, such that support for the development of science
and technology is
seen as a measure of development. The plan stresses the
importance of disseminating
information services and of enhancing the awareness of IT
throughout Saudi society.
Two specific initiatives to foster IT adoption include:
(1) an incentive policy that offers a 25 percent bonus of basic
salary to Saudi
nationals who specialize in computers or pursue an IT career;
and
(2) a new initiative from the Saudi ICT commission to provide
one personal
computer per Saudi household to leverage IT assimilation and
diffusion.
In May 2007, the Saudi government approved a national plan
for the development of its
telecom and IT sector with the objective of transforming the
Kingdom into a
knowledge-based society and a digital economy. This plan
includes continuing work
on Saudi Arabia’s first Knowledge Economic City (KEC) in
Madinah, a technological
and economic information center designed to attract investment
and create nearly
25,000 new jobs (Arab News, 2007).

With systemic policy support from the Saudi government, IT
adoption should be
promoted throughout Saudi Arabia. However, Arab workers are
also heavily
influenced by the existing social structure, and by the
associated norms, values and
expectations of the populace (Bjerke and Al-Meer, 1993).
Atiyyah (1989) found that
information technology transfer (ITT) is often hampered by
technical, organizational,
and human problems in Saudi Arabia. Cultural conflicts arise
from the clash of
management styles characteristic of Western and Arabic
institutional leaders. These
conflicts have affected workers and have impacted the system
development process,
fostering unsuccessful approaches to computer use and policy
(Ali, 1990; Atiyyah,
1989; Goodman and Green, 1992). A deeper understanding of
how the Saudi worker
interacts with computing environments could facilitate the
adoption of IT throughout
the Kingdom.
Social and cultural characteristics of Arab and Muslim societies
differ from those of
the West. Saudi Arabia in particular is a conservative country
where Islamic teachings
and Arabian cultural values are dominant. The country falls
along a spectrum of
cultural characteristics of GCC countries, distinctly tribal,
conservative in its adherence
to Islam and influenced by significant exposure to the West
(Dadfar et al., 2003; H.
Dadfar, 1990). Each country also has different policies with

respect to IT, ranging from
positive and supportive of IT to not so distinctly so (Abdul-
Gader, 1999). Most IT
policies are part of larger economic policies aimed at spurring
development.
Specifically, we speculate that there are social and cultural
characteristics that impact
work-related aspects of IT adoption. Particularly, we are
concerned with the following
question: Do social and cultural characteristics, particularly
those related to beliefs,
attitudes, and social norms, affect the intention to use IT among
Saudi Arabian
professional workers? Our methodology to test this question
probes whether specific
characteristics of the Saudi people influence the success of IT
adoption and whether
these characteristics have differential ramifications for existing
IT acceptance models
tested in developed countries (Ein-Dor et al., 1992).
Hill et al. (1998) explored the characteristics of Arab
individuals that affect IT
adoption. They reported that social factors, including class and
education, were key
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variables impacting the success of IT adoption. Additionally,

the factor of age was
important in influencing differences in IT adoption. Saudi
Arabia’s population is
relatively young, with a median age of 21.28 in 2005, with 39.3
percent of the
population under the age of 15 and with only 2.6 percent of the
population aged 65 or
above (Global Virtual University, 2006). The Hill et al. (1998)
study found that
technological changes are often brought into Arabic
organizations by younger people
who have been previously exposed to these technologies in
other, more developed
countries.
Education is also an important factor that influences
organizational behavior,
particularly with respect to the acceptance of new information
technologies. The
participants in the Hill et al. (1998) study believed education to
be the most important
avenue to improve social standing in Arab society. Increasingly,
more and more Saudis
achieve higher levels of education (Vassiliev, 1998). In 1991,
over 19 percent of female
Saudi students leaving high school entered a university, as did
7.1 percent of male
students. By 2004, 28 percent of Saudi students who were
eligible, including 33 percent
of the women and 22 percent of the men, participated in
university-level education
(UNESCO Institute for Statistics, 2004). The rapid increase in
the number of students
who complete programs of higher education has lead to a better
educated and to a more
technologically savvy workforce. Thus, a better educated

workforce could promote the
use of computers and other IT. Additionally, Saudi Arabians
have become quite
technology-savvy in their daily lifestyle. Saudi Arabia is the
biggest Gulf Arab telecom
market, and there is a boom in third generation (3G) mobile
phone technology
(including wide-area wireless voice telephony and broadband
wireless data) being
deployed throughout the Kingdom, as Saudis increasingly use
mobile phones to
counter the low internet penetration rate (Reuters, 2007).
In Saudi Arabia, as in other Arab states, there is a sharp
division of labor between
men and women, and there exists a widely practiced segregation
of the genders in
many public roles. To date, there have been few in-depth
studies to show the impact of
gender on IT adoption in Saudi Arabian culture. The growing
number of women in the
Saudi workforce, albeit slowly increasing, could potentially
affect the adoption of IT in
that country. Traditionally, women have not adequately
participated in the Saudi
workforce (Esposito and Haddad, 1998). In the early 1990s,
fewer than 10 percent of all
employees in Saudi Arabia were women (Vassiliev, 1998), and
this proportion remains
about 5 percent today (Kinninmont, 2006), reflecting small
increases in participation
each year. The prevailing Islamic culture within Saudi Arabia
posits that women are
not supposed to work outside of the home, or if they do, work in
an exclusively female
environment (for example, as directors of their own businesses,

teachers, doctors or
nurses.) Achieving gender integration in the Saudi workplace is
made even more
difficult in practice, as women are not allowed to be out in
public, save in the company
of a male relative. In fact, the vast majority of Saudi workplaces
employ a strict
maintenance of separate working areas for men and women to
conform to widely
accepted cultural practices (Al-Munajjed, 1997; Field, 1994). In
these ways, Saudi
Arabia is representative of the conservative end of a continuum
that stretches across
toward much less formal and traditional practices in other
Muslim cultures.
However, a changing economy and the increasing cost of living,
coupled with the
rising number of dual-income households, has resulted in
greater numbers of Saudi
women working for income outside of the home (Esposito and
Haddad, 1998).
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Moreover, the Saudi government encourages more participation
of women in the Saudi
workforce in socially and culturally accepted fields that suit
women. Accordingly, they
might also condone the participation of women in other fields
that are not socially or

culturally accepted, as highly educated Saudi women (women
constituted 55 percent of
Saudi graduates in 2006) represent a precious major pool of
indigenous Saudi labor.
Women could help displace the large numbers of foreign
workers who are perceived to
threaten the delicate balance of traditional Saudi life (Facey,
1993). This is part of the
practice of Saudization and is thought to require a higher level
of participation of both
genders in the workforce (Al-Munajjed, 1997). If one
responsibility of higher education
is to replace foreign workers with qualified Saudi men and
women (Mose, 2000), then
the education system should focus on IT skills needed in the
private sector, since this is
where many new jobs will be created (Baki, 2004, June 17).
The theory of planned behavior
The theory of planned behavior (TPB), presented as Figure 1,
predicts human behavior
based on putative relationships among attitudes, norms, beliefs
(i.e. perceived
behavioral control), behavioral intentions and usage behavior.
According to TPB, one’s
attitude towards a behavior, coupled with prevailing subjective
norms, and with
perceptions of behavioral control factors, all serve to influence
an individual’s intention
to perform a given behavior (Ajzen, 1991). Applying TPB in an
IT adoption context,
intention to use IT is posited to influence an individual’s
subsequent IT usage, while
fully mediating the influences of attitudes and subjective norms
on subsequent IT
usage. Moreover, perceived behavioral control also directly

influences the intention to
use IT, as well as ultimate IT usage.
Recent meta-analyses suggest that TPB explains about 41-50
percent of variance in
intention, and 28-34 percent of the variance in behavior with
non-IT applications
(Albarracin et al., 2001; Godin and Kok, 1996). However,
despite its substantial
predictive power, there is a large proportion of the variance in
intention and usage that
is not accounted for by the model. As a result, contemporary
applications of TPB with
Figure 1.
Theory of planned
behavior (TPB)
(technology-specific)
Theory of
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behavior
359
respect to organizational technology adoption investigate the
influence of additional,
relevant moderator variables to explain additional variance in
the model (Morris et al.,
2005). There have been a number of studies investigating the
adoption and use of
technology through the application of TPB (Mathieson, 1991;

Taylor and Todd,
1995a, 1995b). Al-Gahtani (2003) investigated technological
factors promoting IT
adoption in Saudi Arabia, but he did not investigate the
individual human factors’
influence on technology adoption. This study investigates
whether gender, age and
level of education have any effect on the TPB relationships as
they exist in a
developing nation, where the workforce demographics differ
significantly from those
of Western nations.
Whereas the TPB model is depicted as Figure 1, the research
model, derived from
TPB, is depicted as Figure 2. The research model excludes
technology usage, focusing on
intention to use technology as the dependent variable.
Additionally, the research model
includes the moderating influences (or interactions) of gender,
age, and education with
attitude, subjective norm, and perceived behavioral control, all
on intention to use
technology. TPB asserts that behavior, in this case, technology
usage, is a direct function
of intention to use that technology and perceived behavioral
control, and that the intention
to use the technology is jointly influenced by one’s attitude,
subjective norm, and
perceived behavioral control. Other studies have demonstrated
strong empirical support
for TPB, explaining technology adoption behavior in both
individual and organizational
settings (Mathieson, 1991; Taylor and Todd, 1995b). While
detailed studies of
technologically developing countries using TPB have not been

performed, there is reason
to expect that the TPB model would provide significant
explanatory power for intentions
to adopt technology in Saudi Arabia. TPB explains technology
usage behavior in settings
where individuals do not have complete control over their
behavior, such as in an
organizational setting where workers are required to use a
variety of information
technologies in the performance of their work duties (Rawstorne
et al., 2000).
Figure 2.
Research model
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Attitude toward using technology
TPB postulates three conceptually independent determinants of
behavioral intention,
which in this instantiation of the model is intention to use
technology. These
determinants of intention include attitude toward the behavior,
subjective norm, and
perceived behavioral control (Ajzen, 1991). TPB defines
attitude toward a behavior as
“the degree to which a person has a favorable or unfavorable
evaluation or appraisal of

the behavior in question” (Ajzen, 1991, p. 188). Attitude toward
the behavior relates to
the extent to which an individual has a favorable or unfavorable
evaluation, or
appraisal, of the target behavior. In general, the more favorable
the attitude toward the
behavior, then the stronger will be an individual’s intention to
perform the behavior
(Ajzen, 1991). Mathieson (1991, p. 175) defines attitude toward
using technology as:
“the user’s evaluation of the desirability of his or her using the
system,” a function of
the subjective probability that the usage behavior will lead to a
particular outcome and
a rating of the desirability of the outcome. When investigating
technology adoption in
organizations, attitude toward using technology is an
employee’s evaluation of the
costs and benefits of using the new technology. Attitude is
determined by an
employee’s subjective evaluation of the consequences of using
the technology, and the
individual’s affective evaluation of the importance of those
consequences. In our case,
the target behavior is the intention to use IT, and the attitude is
that toward using IT.
Attitude toward using technology reflects feelings that
performing a behavior would
lead to a particular, and desirable, outcome, as a result of
performing that behavior.
Subjective norm
TPB postulates a second determinant of intention, subjective
norm. Within TPB,
subjective norm is defined as “the perceived social pressure to
perform or not to

perform the behavior” by the individual (Ajzen, 1991, p. 188).
TPB views the role of
social pressure to be more important when the motivation to
comply with that pressure
is greater. Motivation to comply is the extent to which the
person wants to comply with
the wishes of the other party (Mathieson, 1991). A component
of subjective norm is
normative belief, or the individual’s perception of a significant
referent other’s opinion
about the individual’s performance of the behavior. When
applying TPB in the
technology adoption context, subjective norm has been divided
into two types of
normative influence:
(1) the influence of one’s peers (e.g. peer influence); and
(2) the influence of one’s superiors (e.g. superior influence).
Although the opinions of these two distinct normative groups
might differ from each
other, they are still both expected to have a significant
influence on an individual’s
intention to use the technology (Mathieson, 1991; Taylor and
Todd, 1995b).
The role of subjective norm as a determinant of intention to use
IT is well
documented in situations where the actual behavior entails
tangible, and beneficial,
consequences for the user (Taylor and Todd, 1995b). Indeed,
organizational studies
have found subjective norm to be an important determinant of
behavioral intention to
use IT (Hartwick and Barki, 1994; Moore and Benbasat, 1993).

Moreover, the relative
importance of subjective norm on the intention to use
technology has also been
reported to be a function of the phase of implementation of the
technology. Specifically,
it has been found to be more important in the early stages of
implementation, when
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users have only limited direct experience from which to develop
attitudes (Hartwick
and Barki, 1994).

Perceived behavioral control
Finally, TPB postulates a third determinant of behavioral
intention: perceived
behavioral control. Perceived behavioral control refers to
(Ajzen, 1991, p. 188): “the
perceived ease or difficulty of performing the behavior”.
Moreover, perceived
behavioral control (p. 122): “is assumed to reflect past
experience as well as anticipated
impediments and consequences.” According to TPB, it is the
perception of behavioral
control, as opposed to the degree of actual behavioral control,
that directly impacts
both intentions to perform a behavior, as well as the actual
performance of that
behavior. Ajzen’s view of perceived behavioral control is
similar to Bandura’s (1977,
1982) notion of perceived self-efficacy, which is “concerned
with judgments of how well
one can execute courses of action required to deal with
prospective situations”
(Bandura, 1982, p. 122). Bandura’s research has demonstrated
that people’s behavior is
strongly affected by their confidence in their ability (i.e.
perceive behavioral control) to
perform that behavior.
Perceived behavioral control is comprised of two factors:
(1) control beliefs, which relate to the sense of the self-
availability of skills,
resources and opportunities; and
(2) perceived facilitation, which relates to an individual’s
assessment of the
importance of those skills, resources and opportunities for the

achievement of
desired outcomes.
Control beliefs can be situational as well as personal
(Mathieson, 1991). Within the
context of technology adoption, perceived behavioral control
relates to the individual’s
perception of the accessibility of IT and to the opportunities for
its usage, and to an
individual’s self-confidence in his or her ability to use IT
effectively.
Perceived behavioral control has been shown to be an important
determinant of
usage intention. In a direct test, Mathieson (1991) found that
perceived behavioral
control did have a significant effect of behavioral intention.
Additional studies provide
indirect evidence of the effect of perceived behavioral control
on intention to use
technology and on technology usage, such as the effect of
computer self-efficacy, user
involvement and mandatory use of IT (Compeau and Higgins,
1995; Hartwick and
Barki, 1994; Moore and Benbasat, 1993).
Behavioral intention to use technology
According to TPB, perceived behavioral control, together with
behavioral intention,
can be used to directly predict behavioral achievement, or
actual behavior. However,
the predictive power of perceived behavioral control on actual
behavior can be
significantly muted, and rendered unrealistic, when, as
examples, a person has little
information about the behavior, when available resources and/or

requirements have
changed, or when emergent, new, and unfamiliar elements
impinge on the situation.
Furthermore, the influence of perceived behavioral control on
behavior is more
important as the behavior becomes less volitional. When the
person has complete
control over the behavior in question, that is, when the behavior
is completely
voluntary, intentions alone should adequately predict behavior
(Ajzen and Fishbein,
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1980). In these cases, it is the existing behavioral intention to
perform the behavior that
can significantly predict actual future behavior. Behavioral
intention has long been
recognized as an important mediator in the relationship between

behavior and other
factors, such as attitude, subjective norm, and perceived
behavioral control (Ajzen,
1991; Ajzen and Fishbein, 1980).
Our research model (see Figure 2) differs from TPB (see Figure
1) in two key
respects. First, we exclude the TPB measure of technology
usage from our research
model. In our study, a large multi-organizational survey, data
on the model constructs
were collected at a single point in time (see Research
Methodology section that follows).
Our focus is on how well attitude, subjective norm, and
perceived behavioral control
predict intention to use technology in the future. We did collect
data on existing
technology usage behavior, but these measures reflect current
and past technology
usage behavior. Additionally, in the research model, the
constructs for attitude,
subjective norm and perceived behavior control are modeled as
moderated by gender,
age and level of education. That is, we explore the interactions
of attitude, subjective
norm, and perceived behavioral control with gender, age and
level of education,
assessing the effect of each of the nine interactions on
behavioral intention, as similarly
studied by Morris et al. (2005).
Interaction of attitude with gender, age, and level of education
In Saudi Arabia, where the majority of the workforce is under
the age of 40, prior
research suggests that attitudes toward male and female
stereotypes disappear in

younger respondents (M. G. Morris et al., 2005; Nosek et al.,
2002). Furthermore, women
constitute a very small percentage of the Saudi workforce, and,
as stated earlier, the
typical professional worker in Saudi Arabia is under the age of
40 (Al-Gahtani, 2004)
and is well educated. Accordingly, there is no reason to expect
that the moderation of
attitude with gender, with age, or with level of education, upon
the intention to use
technology, to be significant in Saudi Arabia.
Interaction of subjective norm with gender, age and level of
education
Peer influence on women has been shown to be high in gender
studies (Eagly, 1987;
Miller, 1986). Therefore, there is reason to expect that gender
will moderate the
influence of subjective norm on behavioral intention. In a
traditional Islamic society,
such as Saudi Arabia, where expectations for behavior are rigid
and generally
accepted, workers would be subject to social pressure to
conform to appropriate
behavior in the workplace. This might hold true for female
participants in the
workforce in particular. However, we are not aware of research
suggesting that
subjective norm should interact with either age or level of
education on intentions to
use technology in the Saudi workforce. Indeed, the homogeneity
of the professional
Saudi workforce as predominantly young and well educated
would not suggest any
likely moderating effects of age or education with subjective
norm on intention to use

IT.
Interaction of perceived behavioral control with gender, age and
level of education
Previous research has shown that situational constraints are
more important
determinants of the intention to use technology for women than
for men (Venkatesh
et al., 2000). For women participants in the Saudi workforce,
who are often less trained
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in IT skills because of less opportunity to pursue technical
subjects, this effect might be
more pronounced. Consequently, we do expect that gender will
moderate the influence
of perceived behavioral control on one’s intention to use
technology. However, the
Saudi population is youthful in age, and well educated, so we do

not expect for the
influence of perceived behavioral control on intention to be
moderated by age or by
level of education.
Research methodology
A survey questionnaire was designed to measure the research
model variable constructs.
Appendix A presents the survey measurement items for each
construct. Each variable
construct (e.g. attitude, subjective norm, perceived behavioral
control, and intention to use
technology) was measured using multiple items. The survey
instrument also captured
values for the three moderating demographic variables, gender,
age and level of
education. Gender was measured by the respondents indicating
that they were either male
or female. Age was measured with a five category ordinal scale:
(1) less than 20 years;
(2) 20-30 years;
(3) 31-40 years;
(4) 41-50 years; and
(5) (5) over 50 years.
Level of education was measured using a five category ordinal
scale:
(1) less than high school;
(2) high school;

(3) diploma;
(4) graduate; and
(5) higher studies.
These categories conform to typical levels of education attained
by Saudi nationals
within their country.
The items comprising the constructs of attitude, subjective
norm, perceived
behavioral control, and intention to use technology were
adapted from Mathieson
(1991). All survey items, originally published in English, were
adapted for this study in
Arabic using Brislin’s (1986) back translation method. The
items were translated back
and forth between English and Arabic by several bilingual
professors, and this process
was repeated until both versions converged.
Participants in the study were knowledge workers within 56
private and public
sector organizations in Saudi Arabia, including banking,
merchandising,
manufacturing, and petroleum industries, engaged in the use of
desktop “computers
for the purpose of their work”. Originally, 136 public and
private organizations were
contacted. Eventually, 56 organizations participated in the
study. The returned usable
responses from participants numbered 1088, with a response
rate of slightly over 62
percent. All survey participants were Saudi nationals. Foreign

(e.g. non-Saudi) workers
were excluded from the sample. Of the 1088 participants, 310
respondents were from
the private sector (28.5 percent) and 778 (71.5 percent) were
from the public sector.
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Overall, 78.1 percent of the respondents were men, while 21.9
percent were women.
There is an imbalance of male gender representation in our
sample. However, due to
the cultural preponderance of working males in Saudi Arabia,
there was nothing that
could be done to correct this imbalance. Respondents ranged in
age from 18 to 58. In

terms of levels of education:
. 59 respondents (5.4 percent) had less than a high school
education;
. 184 respondents (16.9 percent) graduated from high school;
. 294 (27.0 percent) had earned a diploma;
. 473 (43.5 percent) were a graduate of higher education; and
. 78 (7.2 percent) had engaged in higher studies.
The demographic characteristics of the survey sample are
summarized in Table II.
Data analysis and results
The research model depicted as Figure 2 was analyzed using
PLS-Graph (build 1126), a
Partial Least Squares (PLS) Structural Equation Modeling
(SEM) tool. PLS-Graph
simultaneously assesses the psychometric properties of the
measurement model (i.e.
the reliability and validity of the scales used to measure each
variable), and estimates
the parameters of the structural model (i.e. the strength of the
path relationships among
the model variables).
Reliability results from testing the measurement model are
reported in Table III.
The data indicates that the measures are robust in terms of their
internal consistency
Demographics No. (%)

Public vs. private sector:
Public 778 (71.5)
Private 310 (28.5)
Gender:
Men 850 (78.1)
Women 238 (21.9)
Level of education:
Less than high school 59 (5.4)
High School 184 (16.9)
Diploma 294 (27.0)
Graduate 473 (43.5)
Engaged in higher studies 78 (7.2)
Table II.
Demographics of survey
sample – 1,088
respondents
Variable constructs
Composite reliability
(internal consistency reliability) Average variance
extracted/explained
ATT 0.95 0.796
SN 0.95 0.868
PBC 0.80 0.574
BI 0.81 0.587
Table III.
Reliability assessment of
the measurement model
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reliabilities as indexed by their composite reliabilities. The
composite reliabilities of the
different measures in the model range from 0.80 to 0.95, which
exceed the
recommended threshold value of 0.70 (Nunnally, 1978). In
addition, consistent with the
recommendation of Fornell and Larcker (1981), the average
variance extracted (AVE)
for each measure exceeds 0.50. Table IV reports the results of
testing the discriminant
validity of the measure scales. The bolded elements in the
matrix diagonals,
representing the square roots of the AVEs, are greater in all
cases than the off-diagonal
elements in their corresponding row and column, supporting the
discriminant validity
of the scales.

We tested convergent validity with PLS-Graph by extracting the
factor loadings
(and cross loadings) of all indicator items to their respective
latent constructs. These
results, presented in Table V, indicate that all items loaded:
. on their respective construct (i.e. the bolded factor loadings)
from a lower bound
of 0.70 to an upper bound of 0.94; and
. more highly on their respective construct than on any other
construct (i.e. the
non-bolded factor loadings in any one row).
A common rule of thumb to indicate convergent validity is that
all items should load
greater than 0.7 on their own construct (Yoo and Alavi, 2001),
and should load more
highly on their respective construct than on the other constructs.
Furthermore, each
item’s factor loading on its respective construct was highly
significant ( p , 0.001). The
Latent variables 1 2 3 4 5
1. Attitude 0.89
2. Subjective norm 0.13 0.93
3. Perceived behavioral control 0.31 0.29 0.76
4. Behavioral intention 0.37 0.39 0.50 0.77
Table IV.
Discriminant validity
(intercorrelations) of
variable constructs

ATT SN PBC BI
ATT1 0.90 0.15 0.28 0.36
ATT2 0.91 0.12 0.32 0.35
ATT3 0.90 0.13 0.28 0.34
ATT4 0.88 0.11 0.26 0.31
ATT5 0.88 0.08 0.24 0.28
SN1 0.13 0.94 0.28 0.36
SN2 0.11 0.94 0.28 0.35
SN3 0.13 0.91 0.27 0.38
PBC1 0.21 0.23 0.76 0.34
PBC2 0.27 0.18 0.76 0.41
PBC3 0.21 0.26 0.75 0.39
BI1 0.32 0.28 0.38 0.82
BI2 0.28 0.30 0.42 0.70
BI3 0.25 0.31 0.34 0.79
Table V.
Factor loadings
(italicised) and cross
loadings
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loadings presented in Table V confirm the convergent validity
of the measures for
these latent constructs.
Figure 3 presents the results of the structural model, where the
beta values of the
path coefficients indicate the direct influences of the predictor
upon the predicted latent
constructs. Attitude toward technology exhibited a strong
positive influence (b ¼ 0.23,
p , 0.001) on behavioral intention, as did subjective norm (b ¼
0.25, p , 0.001) and
perceived behavioral control (b ¼ 0.39, p , 0.001).
For the moderator (interacting) variables, there were no
statistically significant
interactions, with the exception of the moderation of perceived
behavioral control on
intention to use technology by level of education. Specifically,
higher levels of
education had a negative moderating effect (b ¼ 2 0.07, p ,
0.01) on the positive
influence of perceived behavioral control on intention to use
technology. The remaining
eight non-significant moderating paths are omitted from the
results presented in
Figure 3. The direct influences of attitude, subjective norm and
perceived behavioral
control account for approximately 36.7 percent of the variance
in behavioral intention
(R 2 ¼ 0.367) (Cohen et al., 2003; Everitt and Dunn, 1991;

Loehlin, 1991).
Discussion
The results of this survey validate the predictive constructs as
determinants of
behavioral intention in the theory of planned behavior. Attitude
toward technology,
subjective norm, and perceived behavioral control are all found
to be significant,
positive determinants of the intention to use technology within
this cultural group.
In a technologically developing nation, regardless of prior
experience with IT, the
workers’ attitude toward IT is a strong indicator of intended use
of IT within the
Figure 3.
The structural model
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organization. This study also confirms that subjective norm is a
significant, positive

determinant of intention to use technology. This finding
supports Hartwick and
Barki’s (1994) assertion that the relative influence of subjective
norm on behavioral
intention is significant even when users have only limited direct
experience from
which to develop attitudes about IT adoption and usage. This
limited direct
experience is evident in Saudi Arabia, where the PC penetration
rate in 2002 was
6.38 percent of the population (Madar Research Group, 2002).
This study also
provides further direct evidence that perceived behavioral
control has a significant,
positive effect on behavioral intention. TPB was validated in
this study, explaining
approximately 37 percent of the variance in behavioral
intention. The magnitude of
this variance is similar to that reported in previous studies of
technology adoption
modeled by TPB.
Perhaps the most salient finding of this study is the non-
significance of age and
gender as moderating variables on attitude, subjective norm,
and perceived behavioral
control as they affect behavioral intention to use technology.
This finding with respect
to age was not unexpected. With the overwhelming majority of
the Saudi workforce
being relatively young and homogeneous in this respect,
specifically in the 31-40 age
range, across both the public and private sector, the effect of
age as a moderating
demographic variable was expected to be minimal.

However, from the perspective of gender, the lack of any
moderating influence was
a bit surprising. The proportional representation of women in
this study is small,
approximately 21.9 percent, although this proportion of women
is larger than that
present in the Saudi workforce in general, which is
approximately 5 percent (Esposito
and Haddad, 1998). Should women represent a larger proportion
of the Saudi workforce
in the future, which is possible given the policy of Saudization
and the increasing
educational attainments of Saudi women, it is possible that
gender might have a
significant moderating influence in the future. Furthermore, the
significant moderating
influence of gender with subjective norm has been reported in
previous TPB
technology adoption studies using a Western (i.e. the USA)
survey sample (M.G. Morris
et al., 2005).
With a Saudi workforce that is predominantly young in age and
highly educated,
we expected to find little or no effect of age or level of
education on the importance of
attitude, subjective norm, and perceived behavioral control as
influencing behavioral
intention. However, there was a significant, negative (b ¼ 2
0.07, p , 0.01)
moderating effect of level of education with perceived
behavioral control on intention
to use technology. This negative moderating effect suggests
that, with increasing
levels of education, the influence of perceived behavioral
control on intention to use

technology is muted. Why might this be true? Perceived
behavioral control is a
measure of the perceived ease or difficulty of performing the
behavior, that is, of using
IT. It is possible that the more highly educated Saudis have
benefited from more
training and a greater exposure to IT as part of their education.
That is, they are more
adept at using IT and are therefore better able to use computer
regardless of job-related
“knowledge, opportunities, and abilities” to use computers.
Again, the results indicate
that the homogeneity of the Saudi workforce is a significant
influence on perceived
behavioral control. However, to our knowledge, this negative
moderating influence of
education on intention to use IT has not been validated in other
TPB studies, in
Western or in non-Western cultural contexts.
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Our results indicate the strong influence of subjective norm (b
¼ 0.25, p , 0.001)
and perceived behavioral control (b ¼ 0.39, p , 0.001) on
behavioral intention in this
Saudi sample. We argue that the influences of subjective norm
and perceived
behavioral control on behavioral intention would be stronger in
a culture with strong
group identification among its people and strict religious

adherence as is characteristic
of Saudi Arabia. In adhering to a strict social code throughout
their daily lives, Saudis
try to minimize the possibility of feeling either uncomfortable
or uncertain in
unstructured situations. Uncertainty is mitigated by strict laws
and rules, and by the
philosophical and religious beliefs inherent in the Islamic
fundamentals and genuine
teachings (Salafism, a fundamentalist movement within Islam)
which accompanied the
Saudi movement milieu in its first state-owned government
(Vassiliev, 1998). In the
workplace, greater levels of perceived behavioral control would
promote, and would be
associated with decreasing levels of uncertainty when
computers are used. That is, the
extent to which there is greater self-efficacy to use a computer,
as well as enhanced
resources, knowledge, and opportunities to use a computer, then
the levels of
uncertainty in using computers should be reduced. In fact, our
findings do indicate a
strong association between perceived behavioral control and
behavioral intention
(b ¼ 0.39, p , 0.001), consistent with the expectation that the
Saudi cultural
characteristic of avoiding uncertain situations would drive
strong associations
between these two variables.
Additionally, we argue that the influence of subjective norm on
behavioral
intention would be strong in a culture that maintains strict
adherence to a
well-defined hierarchy and values group identity over individual

achievement. In
the Saudi culture we argue that individuals are more inclined to
show deference to
authority and to conform to the expectations of others
occupying superior social
roles. There are typically more rigid structures of authority
between managers
and subordinates in Arabic cultures. Saudi Arabia has a culture
that values
collective achievements and interpersonal relationships. In such
a culture, the
de-emphasis of individual achievement, and the greater
importance attached to
collective achievement and group success provides additional
rationale to
anticipate a strong relationship between subjective norm and
behavioral
intention. Indeed, our findings do indicate a strong association
between
subjective norm and behavioral intention (b ¼ 0.25, p , 0.001).
These findings
are consistent with the expectation that the strong deference to
authority and the
desire for social conformity present in the Saudi culture would
drive strong
associations between these two variables.
Conclusion
As a model investigating the influences of attitudes, subjective
norms, and beliefs on
technology adoption, TPB performs well, and is largely
validated in our Saudi
Arabia survey sample. This validation of TPB accounts for
approximately 37
percent of the variance in intention to use computers among
Saudi knowledge

workers. Additionally, demographic variables (e.g. gender and
age) that have been
reported to be significant moderators of the influences of
attitude, subjective norm,
and perceived behavioral control on behavioral intention in
other cultural samples
(M.G. Morris et al., 2005; Venkatesh et al., 2000) were found to
be non-significant in
Theory of
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369
this Saudi Arabian sample. We speculate that our results are due
to the more
homogeneous (young, male, educated) workforce that exists in
Saudi Arabia.
Saudi Arabia is an example for many technologically
developing nations
differ from Western
cultures. In many such developing countries, there is a
fundamental challenge to
synthesizing existing pre-technological, socio-cultural systems
with ready-made
imported technological products from other cultures (Tibi,
1990). In a somewhat
rigid, hierarchical society such as Saudi Arabia, it is less likely
that “rank and file”
individuals adopting technology will have much influence on

the society overall.
Instead, it is more likely that the adoption beliefs and actions of
the elites of this
society will influence the attitudes and subjective norms with
respect to using
technology. If the elites of Saudi Arabia are able to plan a road
map built from the
perspective of “progress” for the country to cope culturally with
the advent of
widespread technological adoption, it will be impressed upon
the people of Saudi
Arabia that IT adoption is a positive outcome. This perspective
is preferable to the
perception that IT adoption is “forced” from other cultures, like
external reformation
programs, that might be seen as a danger to spiritual authority
and national and
cultural independence. By analogy, although less sensitive than
reform, IT adoption
can be cultivated culturally with a higher probability of success
using Saudi elites
with an internal “progress” perspective within Saudi Arabia’s
beliefs and traditions
than using external entities to force IT adoption.
Future studies of the influence of individual cognitive, social,
demographic and
cultural factors on technology adoption in developing nations
would provide
researchers and practitioners alike with an advanced
understanding of those unique
individual and societal factors that predict technology adoption
in developing nations.
With the continuing globalization and proliferation of IT, this
advanced understanding
will contribute significantly to successful technology adoption

and implementation
throughout various, diverse cultures.
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Appendix
Corresponding author
Elizabeth White Baker can be contacted at: [email protected]
Figure A1.
Survey instrument
Theory of
planned
behavior

375
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Reproduced with permission of the copyright owner. Further
reproduction prohibited without permission.
The effects of gender and age on
new technology implementation
in a developing country
Testing the theory of planned behavior (TPB)
Elizabeth White Baker
Virginia Military Institute, Lexington, Virginia, USA
Said S. Al-Gahtani
King Khalid University, Abha, Saudi Arabia, and
Geoffrey S. Hubona
Georgia State University, Atlanta, Georgia, USA
Abstract
Purpose – This paper aims to investigate the effects of gender,

age and education on new technology
implementation in Saudi Arabia, a technologically developing
country, using the Theory of Planned
Behavior (TPB).
Design/methodology/approach – The research was an empirical
investigation based on surveys
completed by 1,088 Saudi knowledge workers.
Findings – The TPB model performs well in Saudi Arabia. This
validation accounts for 37 percent of
the variance in behavioral intention among Saudi knowledge
workers. For the moderator variables,
there were no statistically significant interactions, with the
exception of the moderation of perceived
behavioral control on behavioral intention by level of education.
Research limitations/implications – Saudi Arabia is an exemplar
for many developing nations
differ from Western cultures.
Demographic variables (e.g. gender and age) that have been
reported to be significant moderators of
the influences of attitude, subjective norm and perceived
behavioral control on behavioral intention in
other cultural samples were found to be non-significant in this
Saudi Arabian sample.
Practical implications – System developers using user-centered
design approaches have different
design criteria for the successful workforce adoption of
information technology (IT) systems in a
technologically developing nation, as compared to the
workforce of a technologically developed nation.
Originality/value – This paper validates TPB as a multi-cultural

model for investigating the impact
of attitudes, beliefs, and subjective norms on technology
adoption, and, in contrast to previous studies,
indicates the (non)effects of select demographic moderators on
the model using a non-Western sample.
Keywords Demographics, Developing countries, Communication
technologies, Culture, Behaviour,
Saudi Arabia
Paper type Research paper
Introduction
The adoption and use of technology in organizational settings is
a topic of intense
interest germane to developing countries. Whereas the
implementation and use of
organizational information technologies (ITs) have been widely
researched in
developed nations, these findings are not necessarily applicable
to less developed
regions of the world. With the increasing trend towards the
transnational globalization
The current issue and full text archive of this journal is
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Vol. 20 No. 4, 2007

pp. 352-375
q Emerald Group Publishing Limited
0959-3845
DOI 10.1108/09593840710839798
Jose Angeles
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of industries, it becomes necessary to better understand those
factors that promote the
successful deployment and adoption of technology in
organizations that are located in
these regions. Specifically, there is the need to understand those
social and cultural
factors that affect technology adoption and use. Such an
understanding will assist the
growing number of organizations in those regions that are
implementing and using
new information technologies. Among the social and cultural
factors that affect the use
of IT in organizations, gender, social norms, education and age
(among others) have
been shown to impact the transfer and use of technology in
organizations (Hubona
et al., 2006).
The social and cultural characteristics of Arab and Muslim
societies differ from
those of industrialized Western nations, and these
characteristics are reflected in the
overall demographics of the workforce. Using a specific
example of an Arab nation,
Saudi Arabia, women constitute a much smaller percentage of
the Saudi workforce,

and the median age of a professional worker is much younger in
Saudi Arabia than in
more technologically developed countries (Al-Gahtani, 2004).
With a workforce that is
predominantly young and male, the effects of age and gender on
of technology might have a different impact on Saudi
organizations, compared to
organizations in industrialized Western nations, such as the US
and Europe.
Using the theory of planned behavior (TPB) (Ajzen, 1991), this
study investigates
the effects of gender, age and education on IT implementation
in Saudi Arabia. The
primary contribution of this research is to utilize TPB to predict
intention to use
computer technology in Saudi Arabia, while also examining the
influences of potential
moderating variables in the model. The next section relates the
theoretical background
of TPB for investigating IT implementation in a developing
country, and discusses the
primary TPB constructs, as well as the moderating variables of
gender, age and
education within the context of the Saudi culture. The third
section details the research
methodology and explains the survey sample characteristics and
measures. The fourth
section describes the data analysis procedure and presents the
results of the study. The
fifth section considers the implications of the findings for both
researchers and
practitioners. Finally, the last section presents and discusses the
conclusions of the
study.

Background and theory
Adoption and use of organizational technology in developing
countries
Information technology can play an important role in leveraging
productivity and
efficiency in both public and private organizations.
Organizations that successfully
adopt and implement IT processes can realize significant
performance gains (Cash
et al., 1992; Nickerson, 1981; Swanson, 1988). Surveying
previous studies of
productivity enhancements resulting from IT implementation,
Hirschheim (1986)
reported productivity gains ranging from 15 percent to 340
percent.
Potential gains in productivity can offset the high investment
cost in IT. According
to the latest Organization for Economic Cooperation and
Development Information
Technology Outlook (2000), the world IT market (hardware,
software, and services)
grew at an annual rate of 8 percent between 1990 and 1997. By
2000, the worldwide
revenues of IT producers exceeded $735 billion. The
information and communications
technology (ICT) sector contributed close to 10 percent of
OECD business GDP in 2001,
up from 8 percent in 1995. The statistics reported by OECD
show that developing
Theory of
planned
behavior

353
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countries are far behind developed countries in spending on IT
acquisition, and that
ICT adoption is affected by income, educational attainment,
children in the family, age
and gender across different cultures.
The IT literature on developing countries has proliferated to
include a wide range of
forces driving IT adoption (Odedra and Kluzer, 1988). Initially,
studies indicated
significant resistance to adopting and using computer resources
in developing
countries, based on social and cultural factors (Abdul-Gader,
1999). Developing
countries, generally speaking, are facing many barriers that can
hinder the adoption
and diffusion of IT. Malek and Al-Shoaibi (1998) report some
of these barriers as
related to the lack of:
. sufficient IT infrastructure;

. IT expertise;
. government support;
. conceiving of information as an important asset; and
. effective national policies pertaining to information
technology.
However, today, with the accelerating forces of globalization,
and the increasing
deployment of IT in developing countries, there exist
compelling incentives to better
understand the unique drivers of IT adoption in non-Western
countries (Al-Gahtani,
2004; Anandarajan et al., 2002). The parameters for successful
IT adoption vary across
the spectrum of national technological development from the
least developed countries
to the most developed. These are largely due to differing social
and cultural contexts
(Abdul-Gader, 1999; Straub et al., 2001), in addition to
differential economic
development. In the case of Saudi Arabia, detailed and
supportive national IT policies
have been explicitly developed by the Saudi government. These
policies address
political, social, economic and environmental aspects for
promoting the adoption of IT
(Malek and Al-Shoaibi, 1998). The success of these policies
will depend on how well the
individual factors of IT adoption have been incorporated.
Understanding how social and cultural factors, such as gender,
age and level of
education can influence the adoption of IT is useful in

promoting the organizational
diffusion of IT in non-Western cultures. Many studies show how
gender, age and
level of education affect IT adoption and usage, although most
were conducted
within developed nations (Ahuja, 2002; Ford et al., 1996;
Rhodes, 1983; Woodfield,
2002). In a study simultaneously conducted in three nations
characterized by
differing cultural beliefs and norms, Gefen and Straub (1997)
demonstrated that
gender roles represent an important social factor influencing
perceptions and
behaviors with respect to IT adoption. Their results indicate that
gender does have
an effect on the IT adoption process and provides a rationale to
investigate whether
gender moderates the effects of predictor variables in existing
models of IT adoption
and usage.
Approaching cross-cultural research
There are many theoretical frameworks of the factors promoting
of IT in organizational settings, but few have been validated in
non-Western cultures.
The lack of frameworks that have been demonstrated to be
robust across cultures can
limit the development of theoretical extensions in this area
(Maheswaran and Shavitt,
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2000). The choice of emic research, indigenous and conducted
on the basis of
culture-specific frameworks, versus etic research, which
examines cultural differences
using previously established universal frameworks as
benchmarks, can confuse the
issue about the most appropriate orientation of cross-cultural
research (Maheswaran
and Shavitt, 2000; Morris et al., 1999; Peng et al., 1991).
In conducting this research, we follow Berry’s (1989) five-step
process as a basis for
an integrated etic/emic approach to studying IT adoption
differences among cultures.
The first step is to examine the research problem in one’s own
culture, developing a
conceptual framework and a relevant instrument. The study
conducted by Mathieson
(1991) provides the foundation for an initial emic study of the
adoption of IT among
professional workers. The second step Berry recommends is to
transport this
measurement model so as to examine the same issue in another
culture, as an imposed
etic study. Accordingly, an objective of our study is to report
the findings of an
imposed etic study of predicted IT use in the Saudi workforce.
According to Berry
(1989), the third step is to enrich the imposed etic framework
with unique aspects of the
second culture, and to then examine the two, culturally diverse
sets of findings for
comparability. Accordingly, the findings from this study can be
leveraged in future

TPB studies to continue to investigate predicted IT use in
culturally diverse settings.
Saudi Arabia and the importance of IT adoption
Saudi Arabia is a developing country where IT adoption is being
influenced by explicit
government policy in the attempt to enhance national
organizational productivity.
Saudi Arabia encompasses 2.25 million square kilometers with a
population of 24.6
million in 2005 (World Bank Group, 2006), including
approximately 5.6 million foreign
residents. By 2002, the ratio of PCs per 1,000 persons was only
63.8, which makes up 60
percent of the Arab PC market, a consortium of 22 Arab
nations. Furthermore, Saudi
internet users were estimated to number 4.5 million in 2005. In
total IT market
penetration, Saudi Arabia ranks third among the 22 Arab
Nations. Unlike many
developing countries, the Saudis do not suffer from financial
resource limitations,
although despite these abundant fiscal resources, Saudi Arabia
has historically been
characterized by the underutilization of available computing
capacity (Atiyyah, 1989;
Yavas et al., 1992) (Table I).
Saudi Arabia has many valid reasons to encourage IT adoption
as a leverage to
achieve organizational productivity gains. The contribution of
information and
communication technologies to economic development overall
is an important new
focus. A key objective of promoting the implementation of new
technology is to bridge

the digital gap between Arab countries and the developed world.
According to the
United Nations Development Program’s Arab Human
Development Report (Fergany
Size (sq.km.) 2,250,000
Population (2005) 24.6 million
Foreign residents (2005) 5.6 million
Ration of PCs per 1,000 (2002) 63.8
Internet users (2005) 4.5 million
Total IT market penetration among Arab nations 3rd of 22
Table I.
Saudi Arabia –
technological and
demographic facts
Theory of
planned
behavior
355
et al., 2002), this gap has widened, due to the nature of the Arab
ICT industry, which is
highly susceptible to:
. monopoly and consolidation;
. the high costs of infrastructure; and
. Arab “brain drain” away from native countries toward

developed nations.
Moreover, there are information disparities among Arab states,
where the primary
language is not English. A societal focus on more Arabic-
language-specific software
and internet content would foster an improved internal
infrastructure dedicated to the
dissemination of this information.
For Saudi Arabia specifically, IT plays a pivotal role in limiting
the demand for
foreign labor, semi-skilled labor in particular (Abdul-Gader and
Al-Angari, 1995), by
providing the capability for organizations to be more productive
with fewer foreign
employees. In Saudi Arabia, Saudization is a development
strategy that seeks to
replace foreign workers with Saudi nationals (Looney, 2004),
part of a growing trend in
policy for the Arab Gulf Cooperation Council (GCC) countries
to control the flow of
foreign labor (Winckler, 1997). Foreign labor is being restricted
as a result of reputed
negative economic and social ramifications of a large foreign
resident population on
Saudi nationals. Guidelines of the Shura council (a Saudi
consultative body on
government policy to the Saudi ministers’ council) dictate that
by 2007, 70 percent of
the workforce will have to be Saudi (Smith, 2002). A major
objective of the Saudi
Development Plans of the 1990s has been to develop general
education to deal with
technological changes and with the rapidly changing social and
economic conditions.

The ultimate goal is to supplant a large portion of Saudi
Arabia’s significant foreign
labor force with indigenous workers, who comprised only 79
percent of the total Saudi
labor force in 1989 (Metz, 1992), through a three-prong
strategy:
(1) increase employment for saudi nationals across all sectors of
the domestic
economy;
(2) reduce and reverse over-reliance on foreign workers; and
(3) recapture and reinvest income which otherwise would have
flowed overseas as
remittances to foreign worker home countries (Looney, 2004).
Leading private sector Saudi-based companies, such as Saudi
ARAMCO (Arabian
American Oil Company) played a significant role in the initial
adoption of IT within
Saudi organizations. Currently, large Saudi companies,
including Saudi ARAMCO,
SABIC (Saudi Basic Industries Corp), and Saudi Arabian
airlines and banks use
state-of-the-art application technologies with more than 80
percent of industrial
companies using computer systems. The continued increase of
internet usage and
e-commerce is an important catalyst for individuals and
organizations to adopt IT for
their competitive advantage, with the anticipation of significant
continued growth in
the near-future Saudi IT market.
Following the lead of the private sector, the Saudi public sector

has also developed
initiatives to accelerate the adoption of IT throughout the
country. In 2004, the Saudi
Crown Prince issued a decree to the Saudi Computer Society to
provide a National IT
Plan (NITP) for Saudi Arabia. The Saudi NITP project, almost
complete and in the final
revision stage, utilizes information and other technologies to
promote knowledge and
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to support economic development throughout the Kingdom. The
plan asserts that
scientific and technological innovation is an essential feature
for economic
development, such that support for the development of science
and technology is
seen as a measure of development. The plan stresses the
importance of disseminating
information services and of enhancing the awareness of IT
throughout Saudi society.
Two specific initiatives to foster IT adoption include:
(1) an incentive policy that offers a 25 percent bonus of basic
salary to Saudi
nationals who specialize in computers or pursue an IT career;
and
(2) a new initiative from the Saudi ICT commission to provide
one personal

computer per Saudi household to leverage IT assimilation and
diffusion.
In May 2007, the Saudi government approved a national plan
for the development of its
telecom and IT sector with the objective of transforming the
Kingdom into a
knowledge-based society and a digital economy. This plan
includes continuing work
on Saudi Arabia’s first Knowledge Economic City (KEC) in
Madinah, a technological
and economic information center designed to attract investment
and create nearly
25,000 new jobs (Arab News, 2007).
With systemic policy support from the Saudi government, IT
adoption should be
promoted throughout Saudi Arabia. However, Arab workers are
also heavily
influenced by the existing social structure, and by the
associated norms, values and
expectations of the populace (Bjerke and Al-Meer, 1993).
Atiyyah (1989) found that
information technology transfer (ITT) is often hampered by
technical, organizational,
and human problems in Saudi Arabia. Cultural conflicts arise
from the clash of
management styles characteristic of Western and Arabic
institutional leaders. These
conflicts have affected workers and have impacted the system
development process,
fostering unsuccessful approaches to computer use and policy
(Ali, 1990; Atiyyah,
1989; Goodman and Green, 1992). A deeper understanding of
how the Saudi worker
interacts with computing environments could facilitate the

adoption of IT throughout
the Kingdom.
Social and cultural characteristics of Arab and Muslim societies
differ from those of
the West. Saudi Arabia in particular is a conservative country
where Islamic teachings
and Arabian cultural values are dominant. The country falls
along a spectrum of
cultural characteristics of GCC countries, distinctly tribal,
conservative in its adherence
to Islam and influenced by significant exposure to the West
(Dadfar et al., 2003; H.
Dadfar, 1990). Each country also has different policies with
respect to IT, ranging from
positive and supportive of IT to not so distinctly so (Abdul-
Gader, 1999). Most IT
policies are part of larger economic policies aimed at spurring
development.
Specifically, we speculate that there are social and cultural
characteristics that impact
work-related aspects of IT adoption. Particularly, we are
concerned with the following
question: Do social and cultural characteristics, particularly
those related to beliefs,
attitudes, and social norms, affect the intention to use IT among
Saudi Arabian
professional workers? Our methodology to test this question
probes whether specific
characteristics of the Saudi people influence the success of IT
adoption and whether
these characteristics have differential ramifications for existing
IT acceptance models
tested in developed countries (Ein-Dor et al., 1992).
Hill et al. (1998) explored the characteristics of Arab

individuals that affect IT
adoption. They reported that social factors, including class and
education, were key
Theory of
planned
behavior
357
variables impacting the success of IT adoption. Additionally,
the factor of age was
important in influencing differences in IT adoption. Saudi
Arabia’s population is
relatively young, with a median age of 21.28 in 2005, with 39.3
percent of the
population under the age of 15 and with only 2.6 percent of the
population aged 65 or
above (Global Virtual University, 2006). The Hill et al. (1998)
study found that
technological changes are often brought into Arabic
organizations by younger people
who have been previously exposed to these technologies in
other, more developed
countries.
Education is also an important factor that influences
organizational behavior,
particularly with respect to the acceptance of new information
technologies. The
participants in the Hill et al. (1998) study believed education to
be the most important
avenue to improve social standing in Arab society. Increasingly,

more and more Saudis
achieve higher levels of education (Vassiliev, 1998). In 1991,
over 19 percent of female
Saudi students leaving high school entered a university, as did
7.1 percent of male
students. By 2004, 28 percent of Saudi students who were
eligible, including 33 percent
of the women and 22 percent of the men, participated in
university-level education
(UNESCO Institute for Statistics, 2004). The rapid increase in
the number of students
who complete programs of higher education has lead to a better
educated and to a more
technologically savvy workforce. Thus, a better educated
workforce could promote the
use of computers and other IT. Additionally, Saudi Arabians
have become quite
technology-savvy in their daily lifestyle. Saudi Arabia is the
biggest Gulf Arab telecom
market, and there is a boom in third generation (3G) mobile
phone technology
(including wide-area wireless voice telephony and broadband
wireless data) being
deployed throughout the Kingdom, as Saudis increasingly use
mobile phones to
counter the low internet penetration rate (Reuters, 2007).
In Saudi Arabia, as in other Arab states, there is a sharp
division of labor between
men and women, and there exists a widely practiced segregation
of the genders in
many public roles. To date, there have been few in-depth
studies to show the impact of
gender on IT adoption in Saudi Arabian culture. The growing
number of women in the
Saudi workforce, albeit slowly increasing, could potentially

affect the adoption of IT in
that country. Traditionally, women have not adequately
participated in the Saudi
workforce (Esposito and Haddad, 1998). In the early 1990s,
fewer than 10 percent of all
employees in Saudi Arabia were women (Vassiliev, 1998), and
this proportion remains
about 5 percent today (Kinninmont, 2006), reflecting small
increases in participation
each year. The prevailing Islamic culture within Saudi Arabia
posits that women are
not supposed to work outside of the home, or if they do, work in
an exclusively female
environment (for example, as directors of their own businesses,
teachers, doctors or
nurses.) Achieving gender integration in the Saudi workplace is
made even more
difficult in practice, as women are not allowed to be out in
public, save in the company
of a male relative. In fact, the vast majority of Saudi workplaces
employ a strict
maintenance of separate working areas for men and women to
conform to widely
accepted cultural practices (Al-Munajjed, 1997; Field, 1994). In
these ways, Saudi
Arabia is representative of the conservative end of a continuum
that stretches across
toward much less formal and traditional practices in other
Muslim cultures.
However, a changing economy and the increasing cost of living,
coupled with the
rising number of dual-income households, has resulted in
greater numbers of Saudi
women working for income outside of the home (Esposito and
Haddad, 1998).

ITP
20,4
358
Moreover, the Saudi government encourages more participation
of women in the Saudi
workforce in socially and culturally accepted fields that suit
women. Accordingly, they
might also condone the participation of women in other fields
that are not socially or
culturally accepted, as highly educated Saudi women (women
constituted 55 percent of
Saudi graduates in 2006) represent a precious major pool of
indigenous Saudi labor.
Women could help displace the large numbers of foreign
workers who are perceived to
threaten the delicate balance of traditional Saudi life (Facey,
1993). This is part of the
practice of Saudization and is thought to require a higher level
of participation of both
genders in the workforce (Al-Munajjed, 1997). If one
responsibility of higher education
is to replace foreign workers with qualified Saudi men and
women (Mose, 2000), then
the education system should focus on IT skills needed in the
private sector, since this is
where many new jobs will be created (Baki, 2004, June 17).
The theory of planned behavior
The theory of planned behavior (TPB), presented as Figure 1,
predicts human behavior
based on putative relationships among attitudes, norms, beliefs

(i.e. perceived
behavioral control), behavioral intentions and usage behavior.
According to TPB, one’s
attitude towards a behavior, coupled with prevailing subjective
norms, and with
perceptions of behavioral control factors, all serve to influence
an individual’s intention
to perform a given behavior (Ajzen, 1991). Applying TPB in an
IT adoption context,
intention to use IT is posited to influence an individual’s
subsequent IT usage, while
fully mediating the influences of attitudes and subjective norms
on subsequent IT
usage. Moreover, perceived behavioral control also directly
influences the intention to
use IT, as well as ultimate IT usage.
Recent meta-analyses suggest that TPB explains about 41-50
percent of variance in
intention, and 28-34 percent of the variance in behavior with
non-IT applications
(Albarracin et al., 2001; Godin and Kok, 1996). However,
despite its substantial
predictive power, there is a large proportion of the variance in
intention and usage that
is not accounted for by the model. As a result, contemporary
applications of TPB with
Figure 1.
Theory of planned
behavior (TPB)
(technology-specific)
Theory of
planned

behavior
359
respect to organizational technology adoption investigate the
influence of additional,
relevant moderator variables to explain additional variance in
the model (Morris et al.,
2005). There have been a number of studies investigating the
adoption and use of
technology through the application of TPB (Mathieson, 1991;
Taylor and Todd,
1995a, 1995b). Al-Gahtani (2003) investigated technological
factors promoting IT
adoption in Saudi Arabia, but he did not investigate the
individual human factors’
influence on technology adoption. This study investigates
whether gender, age and
level of education have any effect on the TPB relationships as
they exist in a
developing nation, where the workforce demographics differ
significantly from those
of Western nations.
Whereas the TPB model is depicted as Figure 1, the research
model, derived from
TPB, is depicted as Figure 2. The research model excludes
technology usage, focusing on
intention to use technology as the dependent variable.
Additionally, the research model
includes the moderating influences (or interactions) of gender,
age, and education with
attitude, subjective norm, and perceived behavioral control, all

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