Social Networking Sites: An Exploration of the Effect of National
Cultural Dimensions on Country Adoption Rates
Rodney L. Stump
1
and Wen Gong
2
1
Towson University, Towson, MD, U.S.A.
2
Howard University, Washington, D.C., U.S.A.
Keywords: Social Networking Sites, National Adoption Rates, Culture.
Abstract: This study investigates the impact of the several dimensions of Hofstede’s cultural framework on the
adoption rates of social networking sites (SNS) across 30 countries, while controlling for a country’s
median age, its urban population level and mobile internet penetration. Hierarchical regressions are
conducted. Our findings reveal that three cultural dimensions, i.e., masculinity/femininity, uncertainty
avoidance and long-term orientation, significantly impact nations’ adoption levels of SNS above and
beyond the effects of median age and urban population level. While there is a growing body of literature
that examines the influence of national culture on the adoption and use of a variety of high-tech innovations
and services mediated by these technologies, our study is among the first to specifically relate cultural
perspectives to country adoption levels of social networking sites using an array of cultural dimensions. We
provide a theoretical framework and supporting empirical evidence to underscore the importance of
understanding how culture impacts consumers’ SNS adoption behavior across countries. Implications from
our findings, limitations and directions for future research are provided.
1 INTRODUCTION
It is estimated that in 2014 global social media users
have now surpassed the 2 billion mark, more than
doubling from where it was just four years ago
(Kemp, 2014; Statista.com, 2015). Social media
plays an increasingly important role in people’s lives.
The digitization of content, proliferation of access
through mobile devices, growing availability of
online retailing and interactive marketing
communication strategies have all contributed to the
phenomenal evolution of the social media landscape.
Firms are responding to these trends by engaging in
strategic marketing initiatives, such as utilizing
multichannel marketing, developing apps, or using
novel ways to make their brands more accessible,
engaging and shoppable via SNS. A recent study
conducted by Van Belleghem (2011) revealed that
more than half of users were following brands on
social media and preferred to share their positive
brand experiences on this media. Both of these
activities have been shown to strongly influence
brand perceptions and buying intentions.
SNS provide virtual online contexts where
individuals can communicate, interact, share and
exchange content with others, overcoming the
temporal and geographic boundaries that may
separate them (Sawyer, 2011). Chen and Zhang
(2010) have noted that new media and globalization
have converged to compress time and space, thereby
transforming the world into a smaller interactive
field.
Despite the apparent appeal of SNS, country
adoption rates and the manner by which the
populace engages with SNS vary considerably. For
example, Van Belleghem (2011) found that the
population of countries in emerging markets like
Brazil, China and India had higher awareness,
participated in more networks and had higher daily
usage rates than those from many countries in
Western Europe. Even though the overall Internet
penetration in emerging markets is still somewhat
lower than in developed nations, the consumers from
these countries who are online ostensibly have a
higher level of social media engagement. A recent
report from Forrester (Nielsen, 2012) revealed that
social media users in the West prefer to consume
content more than create it. Despite having the
longest access to social media, online users in North
America and Western Europe appear to have much
more passive attitudes toward it. In addition to the
apparent differences across global regions, there is
233
L. Stump R. and Gong W..
Social Networking Sites: An Exploration of the Effect of National Cultural Dimensions on Country Adoption Rates.
DOI: 10.5220/0005509002330245
In Proceedings of the 12th International Conference on e-Business (ICE-B-2015), pages 233-245
ISBN: 978-989-758-113-7
Copyright
c
2015 SCITEPRESS (Science and Technology Publications, Lda.)
also considerable variation within regions
themselves. In Asia, Japan has a 35 percent SNS
penetration rate, while Indonesia, China, and India
all boast rates above 60 percent (eMarketer.com,
2012). Nielsen (2012) suggests that Japan may not
follow the emerging Asian social media patterns
because aspects of Japanese culture carry through to
social media preferences, i.e., Japanese consumers
have a greater preference for online anonymity.
Such unevenness in SNS country penetration
rates and usage patterns implies that we still need to
develop a better understanding the potential impact
of culture on the adoption and use of SNS. From
both macro-marketing and micro-marketing
perspectives there are additional reasons for
focusing research attention on this phenomenon.
One consideration is the reciprocal relationship
between technology and quality of life (United
Nations Development Programme 2008; Hill and
Dhanda 2004). Another is marketing’s influence on
consumer satisfaction and well-being (Pan et al.,
Sheng 2007). Consequently, marketers are
increasingly seeking new ways in which consumer-
brand engagement can be formed, nurtured and
sustained across multiple potential touch points,
especially via virtual interactions (Schultz and
Peltier, 2013). Building on past investments in
websites and e-commerce, new investments in social
media platforms, mobile apps, payment systems and
other emerging technologies have the potential to
facilitate consumers sharing and exchanging of
knowledge; to create or enhance functional, time,
place and information utilities; and thus enhance
customer satisfaction and perceived quality of life
for people around the globe.
With the advent of social media comes the
growing interest in conducting research on it by both
academics and practitioners (Schultz and Peltier,
2013; Tsai and Men, 2012). This growing literature
spans a wide range of affiliated topics, including
users’ experiences and gratifications (Dunne et al.,
2010; Palmer and Koenig-Lewis, 2009; Raacke and
Bonds-Raacke, 2008), perceived ease of use and
perceived usefulness of SNS (Pinho and Soares,
2011), branding impact of user-generated content
(UGC) and eWOM on SNS (e.g., Christodoulides et
al., 2012; Goodricha and De Mooij, 2013, Jansen et
al., 2009; Lin et al., 2012), evaluation and
measurement of consumer-brand engagement of
SNS (e.g., Dix, 2012; Gambetti and Graffigna, 2010;
Keller, 2010; LaPointe, 2012; Quinton and
Harridge-March, 2010; Schultz and Block, 2012;
Singh and Sonnenburg, 2012, Trueman et al., 2012;
Valette-Florence et al., 2011), perceived risk and
privacy disclosure behavior on SNS (Xu et al., 2013),
cultural distinctive appeals on SNS (Tsai and Men,
2012), etc. As this inventory suggests, studies
exploring the relationship between culture and
online networking behavior have not been featured
prominently in the extant research literature.
Reflecting the several calls by researchers (e.g.,
Goodricha and De Mooij, 2013; Ribiere et al., 2010;
Rosen et al., 2010; Steers et al., 2008) to address this
gap, we explore cultural explanations for why the
populations of many countries are lagging behind
others with regard to the adoption and use of SNS.
Thus, the intent of the present study is to determine
whether and how cultural factors influence the
country adoption rates of SNS and the usage patterns
of populations, specifically average time spent on
social media.
In the following sections, we first elaborate on
the theoretical background upon which our research
hypotheses are formulated. Specifically, both the
diffusion of innovations literature and Hofstede’s
national culture framework (2001) frame our
investigation into the adoption and use of SNS. Next,
methodological procedures are outlined, along with
and empirical test of our hypotheses using secondary
data for 30 countries that have been drawn from
several reputable sources, including We Are Social
Inc. (wearesocial.com), The Hofstede Centre (geert-
hofstede.com) and CIA World Fact Book. After a
discussion of the results, we conclude with
implications and directions for future research.
2 LITERATURE REVIEW AND
HYPOTHESES
2.1 Social Networking Sites (SNS)
The explosive growth of online social media use
worldwide is indicative that SNS have become one
of the most prominent social computing applications
in the Web 2.0 era (European Commission, Joint
Research Centre, Institute for Prospective
Technological Studies, 2009). Kaplan and Haenlein
(2010, p. 60) define social media as “a group of
Internet-based applications and technological
foundations of Web 2.0, and that allow the creation
and exchange of User Generated Content.” SNS are
web-based services that allow individuals to (1)
construct a public or semi-public profile within a
bounded system, (2) articulate a list of other users
with whom they share a connection, and (3) view
and traverse their list of connections and those made
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234
by others within the system. Consequently, SNS
enable users to build personal profiles, publish
information, promote dialogues, and share networks,
experiences and knowledge within a defined system
(Boyd and Ellison, 2008; Constantinides and
Fountain, 2007). Many users of SNS are active
content generators and critics, rather than merely
being passive content consumers. SNS have shown
great potential to influence the way people socialize,
entertain, shop, acquire and consume information
and make decisions. Marketers, in turn, have
increasingly turned to marketing strategies that
allows them to monitor and shape users’ online
communications on SNS while also engaging
consumers with their brands in a more active,
voluntary and interactive fashion.
2.2 Adoption of Technological
Innovations
Diffusion of innovations (DOI) theory explains how
adoption takes place over time within a social
system. The adoption rate of an innovation is
influenced by (1) characteristics of the innovation
itself, (2) the communication channels through
which the benefits of the innovation are
communicated, (3) the time elapsed since the
introduction of the innovation and (4) the social
system in which the innovation is to diffuse (Rogers,
1983). While it has been common to use individuals
as the unit of analysis in adoption studies, the system
level can also be used. Studies embracing the system
level, consider the nature of a social system and the
relative extent to which an innovation is adopted
within communities, countries, or other social units
having different macroenvironmental characteristics
(e.g., economic, demographic, technological and
cultural factors). These factors can be used to
compare the adoption rates of different innovations
as well as the relative extent to which particular
innovations are adopted across social units with
varying macroenvironmental conditions. Culture can
play an implicit or explicit role in such comparisons
(Maitland and Bauer, 2001) and the diffusion of
innovations can be envisioned as a prolonged
process through which the new culture element(s) is
(are) presented to the society, then accepted by its
people and further integrated into a preexisting
culture (Dearing, 2009).
2.3 Culture
Culture has been described and defined in many
ways. Geertz (1973) labels it as the fabric of
meaning through which people interpret events
around them. Trompenaars and Hampden-Turner
(1998) depict it as the manner in which a group of
people solves problems and reconciles dilemmas.
Hofstede (2001) describes it as the collective mental
programming of a people that distinguishes them
from others. Common to all of these definitions is
the notion that while culture may be abstract it is
characterized by shared values and norms and
mutually reinforcing patterns of behavior (Steers et
al. 2008). Culture is learned and evolves over time
(Hofstede and Bond, 1988; McCort and Malhotra,
1993; Ward et al., 1987). However, culture does
have definite characteristics that are observable and
amenable to empirical description (Strauss and
Quinn, 1992; Rohner, 1984).
One may conceive of culture in terms of its parts,
components, functional segments or institutions,
such as the economic system, the family, education,
religion, government and social control, language
and communication, and transformation and
technology (Baligh, 1994; Chanlat and Bedard, 1991;
Culpan, 1991; Ferraro, 1990; Hall and Hall, 1987
and 1990). To the individual consumer, these social,
economic, and institutional structures and related
macroenvironmental influences determine the
overall context, or “objective reality,” in which he or
she makes a purchasing decision. Beliefs, values,
logic and decision rules are also basic components
of a culture. They are internalized and constitute the
“subjective reality” of the individual consumer, i.e.,
personal values are heavily influenced by cultural
values since individuals are expected to abide by the
values that are promoted in their society as being
important and useful (Clawson and Vinson, 1978;
Patwardhan, 2013). Hence, culture can be seen as
being an underlying framework, consisting both of
the objective reality, as manifested in societal
institutions, and the subjective reality, which
comprise socialized predispositions and beliefs that
guides individuals’ perceptions of observed events
and personal interactions, and the selection of
appropriate responses in social situations (Johansson,
1997). In sum, an individual’s behavior is both a
component and a reflection of the culture in which
they are embedded (Baligh, 1994).
As noted by Cheng and Wong (1996), culture
influences the social construction of phenomena,
such as meanings and practices. Learning, too, is a
fundamentally cultural endeavor, i.e., humans learn
norms through imitation or by observing the process
of reward and punishment in a society of members
who adhere to or deviate from the group's norms
(Engel et al., 1995). Furthermore, meanings, values,
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ideas and beliefs of a social group are articulated
through various cultural artifacts, such as products,
information and communication technologies
(Hasan and Ditsa, 1999).
2.4 Hypotheses of National Culture and
Adoption of Technological
Innovations
Hofstede (1991) argues that people share a collective
national character that represents their cultural
mental programming, which in turn shapes
individuals values, beliefs, assumptions,
expectations, attitudes and behaviors. Hofstede
initially identified four dimensions along which
national cultures vary: power distance, uncertainty
avoidance, individualism vs. collectivism, and
femininity vs. masculinity (Hofstede, 1980 and
2001). More recently Hofstede has expanded his
taxonomy to include long-term vs. short-term
orientation and indulgence vs. restraint and provides
ratings on these dimensions for many countries
(Hofstede, 2015-a & b).
In recent years numerous studies have employed
Hofstede’s framework (e.g., Dwyer et al., 2005;
Ganesh et al., 1997; Kumar and Krishnan, 2002; La
Ferle et al., 2002; Tellis et al., 2003; Van
Everdingen and Waarts, 2003; Yeniyurt and
Townsend, 2003). For example, the study done by
La Ferle and colleagues (2002) examined the
adoption of the Internet in Japan versus the United
States and found that differences on cultural
dimensions explained some of the variance in
Internet penetration and patterns of adoption, even
though Japan and the U.S. share similar
characteristics in terms of economic conditions,
literacy rates and technological infrastructure.
Yeniyurt and Townsend (2003) found a strong
association between the cultural dimensions and the
penetration rates of new high-tech products (i.e., the
Internet, Cellular phones and PCs) and that this
relationship was moderated by social-economic
variables.
Rather than restricting our attention to
individualism vs. collectivism and femininity vs.
masculinity, the two cultural dimensions that past
research has indicated to be relevant to users’ online
communication behaviors (e.g., Goodricha and De
Mooij, 2013; Rosen et al., 2010) the current study
encompasses all six. Drawing on the extant
literature, we posit a rationale for each below.
Individualism-Collectivism is one of the most
widely studied dimensions in cross-cultural research
(Gudykunst, 1998; Kim et al., 1994; Triandis, 1989;
Triandis et al,. 1988; Zhang and Gelb, 1996). This
dimension describes the relation between the group
and the individual. Individualist cultures are
characterized by a loosely knit social framework in
which individuals focus on taking care of themselves
and their immediate family. Personal freedom is
valued and individual decision-making is
encouraged in societies found toward the
individualistic end of the spectrum (Singh et al.,
2003). In contrast, members from collectivistic
societies are apt to be integrated into stronger, more
cohesive groups. Relatives and others in this
extended social group are expected to look after
individuals within them in exchange for obedience
and loyalty. Obligations and group harmony come
before individual aspirations or goals in collectivist
cultures (De Mooij, 1998).
Members of individualist cultures tend to exhibit
more favorable attitudes toward differentiation and
uniqueness (Aaker and Maheswaran, 1997). An
individual’s identity is largely defined by one’s role
in various social relationships. Social networking
can be used to heighten one’s identity, especially
social identity, via self-expression and extra self-
awareness. (Rosen et al. (2010) found a propensity
to engage in more attention-seeking behaviors via
SNS in individualistic cultures. They also reported
that social media users from more individualistic
cultural backgrounds (1) have larger networks of
friends on SNS, (2) whose networks include a
greater proportion of friends who have not been met
face-to-face, and (3) share more photos online, as
opposed to users who identify with more collectivist
cultural backgrounds.
It is important to note that while people in
individualist cultures seem to have more freedom to
try new things than those in collectivistic societies,
members from collectivistic societies may be more
inclined to join and participate in SNS to gain a
sense of belonging, fulfill group obligations and
achieve group harmony. Gangadharbatla (2008)
provided evidence that the need to belong has a
positive effect on a person’s attitude toward SNS
and willingness to join them. Kim and Yun (2007)
found that most Koreans who participated in the
SNS were doing so to keep close ties with a small
number of friends instead of befriending new people.
This juxtaposition is in line with the extant research
that distinguishes between two processes that
explain diffusion, i.e., innovation and imitation.
Populations from individualistic countries appear to
be quicker to adopt in the early stages, whereas
collectivistic countries have adoption rates that are
greater in the later stages, which may be indicative
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of when enough of a critical mass of adopters exist
(Lee et al., 2013; Peng and Mu 2011).
Based on the above discussion, plausible
theoretical arguments can be made for both
individualism and collectivism. Given the lack of a
preponderance of evidence to substantiate one
perspective, we pose the following competing
hypotheses:
H1: Nations whose cultures represent
higher levels of individualism (IDV) will
show higher adoption rates of SNS.
H2: Nations whose cultures represent
higher levels of collectivism will show
higher adoption rates of SNS.
Masculinity-Femininity addresses the extent to
which a society is characterized by assertiveness
versus nurturance and is closely related to societal
expectations of gender roles. Masculine cultures
value achievement and material success more and
also tend to have clear role distinctions between
males and females. In contrast, feminine cultures
value relationships, caring, and are not apt to have
such rigid gender roles (Hofstede, 1980 and 2001).
Although SNS can serve a utilitarian purpose and
foster commercial pursuits, which is likely to be
aligned with masculine cultures where material
things and career advancement are highly valued,
the social aspects of SNS can be expected to be
more germane in feminine cultures where the
nurturing of personal relationships is more cherished
(Ribiere et al., 2010; Singh 2006). Pew Internet &
American Life Project (Pewinternet.org, 2012)
reports that women have been significantly more
likely to use SNS than men since 2009 (Brenner,
2012). Hargittai (2007) found that women were not
only more likely to use SNS than men but also more
likely to embrace different services such as
Facebook, MySpace, and Friendster. Sveningsson
Elm (2007) reported more women than men
emphasized their relationships and expressed
stronger feelings about them in an online meeting
place. Joinson (2008) found women used SNS more
to explicitly foster social connections. Jones and his
colleagues (2008) reported significant differences on
blog usage between genders, with female users
being more likely to use the blog feature available
on MySpace and write about their family, romantic
relationships and health than male users. In a series
of studies of the social networking website MySpace,
Thelwall (2008 and 2009) and his colleagues (2010)
reported that females were likely to give and receive
more positive comments than were males, which
suggests females have a greater ability to textually
harness positive affect. Together, the research above
suggests that systematic differences based on gender
persist in users’ online networking behavior.
Again, given the conflicting theoretical
arguments, we pose competing hypotheses:
H3: Nations whose cultures represent higher
levels of masculinity (MAS) will show higher
adoption rates of SNS.
H4: Nations whose cultures represent higher
levels of femininity will show higher
adoption rates of SNS.
Power distance is the extent to which the less
powerful individuals of a society (and less powerful
members of organizations and institutions within
that society) accept and expect that power will be
distributed unequally. This view of a society's level
of inequality is embraced by followers as well as by
leaders (Hofstede, 1980 and 2001). Singh (2006)
notes that the dimension of power distance has been
found to be inversely related with individualism,
which suggests the following:
H5: Nations whose cultures represent
higher levels of power distance (PDI) will
show lower adoption rates of SNS.
Uncertainty avoidance represents a society's
tolerance for uncertainty and ambiguity (House et al.
2004). It can be shown by the degree of comfort or
discomfort in novel, unknown, surprising, or unusual
situations. Uncertainty avoidant societies tend to be
distrustful of new ideas and stick to historically
tested patterns of behavior. They are more prone to
have strict laws and rules, safety and security
measures, and philosophical and religious beliefs
that tend toward absolute “truth”. Conversely,
uncertainty accepting cultures are more tolerant of
different behaviors and opinions, are likely to have
fewer rules, and tend to be more relativist from
philosophical and religious perspectives (Hofstede,
1980 and 2001; Singh, 2006).
House et al. (2004) contend that uncertainty
avoidance is the cultural dimension that most
strongly correlates with technology adoption. While
uncertainty-avoiding cultures may tend to resist
change, this does not necessarily imply that they are
averse to adopting new technologies (Barron and
Schneckenberg, 2012), but it does appear to
influence timing, i.e., when and how long the
adoption process takes before a significant
penetration level is achieved. For example,
Sundqvist et al. (2005) reported that uncertainty-
avoiding cultures needed more time than
uncertainty-accepting cultures to adopt new
technologies and concluded that the majority
preferred to observe the experiences of early
adopters before they made their technology-
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237
implementation decisions. Other researchers (e.g.,
Garfield and Watson, 1998; Hasan and Ditsa, 1999;
Veiga et al, 2001) have found that uncertainty-
avoiding cultures tend to adopt new technologies
later than uncertainty-accepting ones. Taken
together, these findings suggest that imitation may
be the dominant process influencing diffusion in
uncertainty-avoiding cultures. Thus we propose:
H6: Nations whose cultures represent higher
levels of uncertainty avoidance (UAI) will
show lower adoption rates of SNS
Long-term vs. short-term orientation captures
whether a society is oriented towards future rewards,
and thus lauds saving, persistence, and adaptation,
versus those that focus on the past and present,
where national pride, respect for tradition and
traditional values, preservation of face, and fulfilling
social obligations are dominant sentiments (Franke
et al., 1991; Hofstede, 2001; Hofstede and Minkov,
2010; Minkov and Hofstede 2012). Long-term
oriented cultures are more open to new ideas; in
such countries the rate of adoption of new
technologies is expected to be higher than in
countries with cultures that are more short-term
oriented (Erumban and de Jong, 2006; Van
Everdingen and Waarts, 2003). Accordingly, we
hypothesize:
H7: Nations whose cultures represent
long-term orientations (LTO) will show
higher adoption rates of SNS.
Indulgence vs. restraint is the most recently
added dimension to Hofstede’s typology. This
dimension represents whether a society tends to
allow relatively free gratification of basic and
natural human drives, i.e., are oriented toward
enjoying life and having fun. Conversely, a
restrained society constrains gratification of needs
through means of strict social norms (Franke et al.,
1991; Hofstede, 2001; Hofstede, 2015-a; Minkov,
2011). In indulgent cultures people tend to focus
more on individual happiness and well-being.,
Furthermore, time is more important and individuals
perceive themselves to have greater freedom and
personal control. Conversely, in restrained cultures
positive emotions are less freely expressed and
happiness, freedom and leisure are not given the
same importance (MacClachlan, 2013). We thus
propose:
H8: Nations whose cultures represent
higher levels of indulgence (IND) will show
higher adoption rates of SNS.
Control Variables. The diffusion literature
shows that adoption and diffusion process is
influenced by variety of socioeconomic factors and
the economic and technological infrastructure of a
country may have a concrete and direct
manifestation of a culture’s impact on consumer
behavior (Yeniyurt and Townsend, 2003). Thus we
also include other country-level variables in our
model to empirically account for extraneous factors
that may influence adoptions levels. These include:
a nation’s mobile Internet penetration, urban
population and the median age of the nation.
Dutta and Bilbao-Osorio (2012) argue that the
world is becoming hyperconnected, fueled by the
exponential growth of mobile devices, big data and
social media. Mobile broadband has become the
primary method of access for people around the
world (Bold and Davidson, 2012). Therefore, the
penetration rate for mobile Internet is included to
account for its impact on access to and use of SNS.
Drawing on urban density theory, SNS may
benefit from easier and cheaper access to ICT
(information and communications technologies)
infrastructure because adoption costs are likely to
decrease when population size and density increase
(Forman, 2005; Billon et al., 2009). Reino, Frew
and Albacete-Saez (2010) have reported that rural
businesses tend to have weaker technology adoption
than those located in urban settings, which suggests
that access, scale economies and associated cost
structures may be the underlying reasons. Hence, a
nation’s urban population is included to account for
the potential influence derived from the inherently
greater market potential, deployment and marketing
efforts on the part of mobile providers.
The literature also suggests that young people are
more favorably disposed toward change (Schiffman
and Kanuk 2003) and have been found to be more
receptive to new ICT innovations such as the mobile
phone and ICT-mediated services such as ATMs and
Internet banking (Eastin 2002). Teens and young
adults have been consistently reported to have
highest wireless and SNS usage rates
(pewinternet.org, 2013). We posit that nations with a
relatively young population should be more
receptive to adoption since country-level penetration
rates are effectively an aggregation of individual
consumption decisions. Thus we include the median
age of a nation as our final control variable.
3 METHODOLOGY AND
FINDINGS
This study examines culture’s impact on global
adoption and use of SNS. Since it is a challenge to
collect data for a multivariate analysis on a global
scale, we utilize secondary data from reputable
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238
sources, namely Hofstede’s (2001) cultural
dimension scores, We Are Social’s Digital, Social
and Mobile in 2015 Report’ for global social media
penetration rates and mobile Internet penetration
data (Kemp, 2015), and the CIA World Factbook for
a nation’s median age and urban population data
(CIA, 2014). Altogether, data are available for 30
countries. The list of countries in this study is
available from the authors.
The hypotheses regarding the effects of the six
cultural dimensions were tested in a hierarchical
fashion using ordinary least squares (OLS)
regression. In the Baseline Model, the main effects
of the three control variables were assessed. In the
Full Model, the main effects of the six cultural
dimensions were then added and the model was re-
estimated. The significant overall F values in all
models are indicative that interpretation of the
individual regression models and parameter
estimates for the independent variables are
warranted. Regression results are displayed in Table
1.
Table 1: Regression Results (Standardized Coefficients &
t-Values Shown).
1
DV: Adoption Rate of
SNS
Baseline (Control
Variables Only)
Urban Population 2014 .03 0.15 ns
Median Age 2014 .08 0.42 ns
Mobile Internet
Penetration 2014
.46 2.26 **
F-value
(df1,df2)
F
(3,26)
= 4.90*
R
2
(Adjusted R
2
) .36 (.29)
DV: Adoption Rate of
SNS
Full (Control &
Substantive
Predictors)
Urban Population 2014 .56 3.19 *
Median Age 2014 .90 3.50 *
Mobile Internet
Penetration 2014
-.16 -0.91 ns
IDV (H 1-a & H 2-a) -.25 -1.19 ns
MAS (H 3-a & H 4-a) -.31 -2.42 **
PDI (H 5-a) .27 1.30 ns
UAI (H 6-a) -.44 -3.49 *
LTO (H 7-a) -.69 -3.54 *
IND (H 8-a) .23 1.45 ***
F-value
(df1,df2)
F
(9,19)
= 5.98*
R
2
(Adjusted R
2
) .74 (.62)
F-value
F
(6,19)
= 4.59 *
R
2
R
2
= .38
As we can see from Table I, the coefficients of three
of the cultural variables, i.e., masculinity/femininity
1
Significance levels (one-tailed test) * = p < .01; ** = p < .05;
*** = p < .10; ns = not significant
(MAS), uncertainty avoidance (UAI) and long-term
orientation (LTO) were significant and another,
indulgence (IND), was marginally significant in the
Full Model. Moreover, the addition of the main
effect terms relating to the cultural dimensions
resulted in a significant improvement in the
explanatory power of the model, i.e., R
2
showed a
significant improvement by increasing from .36 to
.74. Based on these results, we conclude:
Neither hypotheses 1 or 2 were supported;
individualism/collectivism (IDV) was found to
be non-significant.
Hypothesis 4 was supported, while hypothesis
3 was refuted. Masculinity/femininity (MAS)
was found to be significant, but negative,
which is consistent with the social rationale for
SNS rates to be higher in feminine cultures.
Hypothesis 5 was not supported; power
distance (PDI) was found to be non-significant.
Hypothesis 6 was supported; uncertainty
avoidance (UAI) was found to be significant
and negative, which means that lower SNS
adoption rates were found in nations that were
more uncertainty avoidant.
Hypothesis 7 was not supported; although
long-term orientation (LTO) was found to be
significant it was negative, which is contrary to
our expectation. This result suggests that short-
term oriented cultures had higher SNS
adoption rates.
Hypothesis 8 was marginally supported; as
expected, indulgence (IND) was found to be
positive although only significant at the p <
.10, which suggests that higher SNS adoption
rates are found in more indulgent cultures.
Two of the control variables, median age and
urbanization, were found to be significant and
positive.
4 DISCUSSION
Overall, the results of our hierarchical regressions support
the general premise that culture does influence the
county adoption rates of SNS and that inclusion of
cultural dimensions provide a significant increase in
the explanatory power of the model beyond merely
considering nations’ social (demographic) and
technical contexts.
Unlike the study by Rosen et al. (2010), this
study revealed no significant impact of
individualism (IDV) on SNS adoption, thus failing
to support either of the competing hypotheses we
posed (H 1 and H 2). One possible explanation,
SocialNetworkingSites:AnExplorationoftheEffectofNationalCulturalDimensionsonCountryAdoptionRates
239
given the small sample size of countries, is that this
effect may be relatively weak and we simply did not
have enough power for the apparent negative effect
to achieve significance. Another potential reason
could be that both innovation and imitation
processes are taking place and cancelling out one
another.
Finding support for Hypothesis 4 over 3 is
indicative that more feminine cultures appear be
more conducive to adopting SNS than those that are
more masculine (MAS). This is in line with other
studies that have reported that women typically
outnumber men on SNS and tend to use SNS more
than men and for different and more social purposes
(Hampton et al., 2011; Koetsier, 2012; Joinson, 2008;
Van Belleghem, 2011).
We found no significant impact of power
distance (PDI) on SNS adoption, thus failing to
support Hypothesis 5. Consequently the role of this
cultural dimension on the adoption of SNS remains
equivocal.
Empirical support for Hypothesis 6, i.e.,
uncertainty avoidance (UAI) was found to be
significant and negative, is consistent with the
premise the adoption of SNS is apt to be higher in
uncertainty accepting cultures where different
behaviors and opinions are more likely to be
tolerated (Hofstede, 1980 and 2001; Singh, 2006).
SNS, with the ability to create and share content,
provides a platform for self-expression with less risk
to the originator.
Our lack of support for Hypothesis 7, which
related to long-term orientation (LTO) (i.e., the
significant but negative coefficient), was unexpected
given an abundance of empirical research supporting
the proposition that the rate of adoption of new
technologies is expected to be higher in long-term
oriented nations than in countries with cultures that
are more short-term oriented (e.g., Erumban and de
Jong, 2006; Van Everdingen and Waarts, 2003).
While long-term oriented cultures are thought to be
more open to new ideas and more adaptive, the
emphasis on fulfilling social obligations in short-
term oriented societies (Hofstede, 2001; Minkov,
2010) may foster the adoption of SNS since this is a
medium that enables the conveyance of richer, more
nuanced messages beyond the verbal or written word.
Thus, further conceptual development appears to be
warranted.
Although the coefficient for indulgence (IND)
was in the expected positive direction (Hypothesis 8),
it was only marginally significant (p < .10), thus
providing weak support for the premise that more
indulgent cultures will have higher SNS adoption
rates.
5 IMPLICATIONS,
LIMITATIONS AND FUTURE
RESEARCH
Culture influences people’s beliefs and values,
which in turn, shape their behaviors. The effect of
the cultural environment is important in the sense
that it determines the unique social values of the
population of a particular country (Fields, 1983),
which may foster or retard the adoption of
technological innovations, including SNS. Hence,
marketing activities related to the commercial
introduction of these innovations need also be
culturally nuanced (Takada and Jain, 1991). As
Schultz and Peltier (2013) have observed, research is
still at an embryonic stage despite the growing
attention to social media marketing. Our results
underscore the need to further explore how cultural
factors influence people’s adoption and SNS.
Individuals can and do use SNS to present
themselves and interact with others, including
businesses.
This study constitutes a novel contribution to the
literature and further enhances our understanding of
the importance of cultural influences on consumers’
adoption of SNS. Overall, our results are intriguing
since they do provide evidence of culture’s role in
influencing country adoption rates of SNS.
Moreover, this study is one of the few to take a
comprehensive approach and include all six of the
cultural dimensions that are prominent in the
conceptualizations of Hofstede (1980 and 2001),
House et al. (2004) and. Minkov (2010) as
predictors.
Our results suggest that international marketers,
nongovernmental organizations (NGO) and/or
government bodies should use culturally-sensitive
criteria when determining which social media
platforms to employ to communicate with particular
country or regional markets and in the design of
messages used to interact with targeted segments.
Communication materials are key carriers of cultural
values (Cheong et al., 2010), which implies that the
degree to which social marketing strategies and
tactics align with a culture may be an important
determinant of the relative success or failure of those
efforts in a particular country. Promotional messages
on SNS can play an essential role in communicating
with targeted audiences and heightening their
engagement with a brand, an entity or an initiative.
ICE-B2015-InternationalConferenceone-Business
240
Cultural characteristics can also be used as screening
criteria for selecting countries where marketers
might more heavily employ social media strategies
versus using more traditional media, not only to
promote products, but also to support learning,
social inclusion, health and governance (European
Commission, Joint Research Centre, Institute for
Prospective Technological Studies, 2009).
We would be remiss if we did not acknowledge
the limitations to this study. One is to recognize our
reliance on secondary data obtained from different
sources, which has been criticized for being
inconsistent and unreliable (Yeniyurt and Townsend,
2003). Another is the limited sample size and cross-
sectional design. Due to the limited availability of
the data, only one year adoption rates for a limited
number of countries were included. To enhance the
generalizability of the results of this research, time-
series data for a larger sample of nations
representing greater diversity are required in order to
form more conclusive ideas about the adoption and
diffusion of SNS across countries.
Another limitation is that we only employed a
main effects model. Thus we are not able to address
whether these cultural dimensions operate
independently of one another or in a contingent
fashion to enhance or retard the adoption of SNS in
particular countries. Furthermore, we implicitly
assume that the effect of these cultural dimensions is
linear, rather than curvilinear. Thus additional
conceptual development and empirical research is
warranted.
Despite these limitations, our study has provided
new insights about how cultural differences
influence the country-level adoption rates of social
networks. We hope further research in cross-cultural
comparisons about the role and effects of cultural
factors on the adoption and use of SNS will follow.
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