Determinants of Use Intensity in Social Networking Sites
A Cross-cultural Study of Korea and USA
Cheol Park
, Jongkun Jun
and Thaemin Lee
Division of Business Administration, Korea University, 2511, Sejong-Ro, Sejong City 339-700, South Korea
Department of International Business, Hankuk University of Foreign Studies,
81, Oedae-ro, Cheoin-gu, Yongin-si, Gyeonggi-do 449-791, South Korea
Department of Business Administration, Chungbuk National University Gaeshing-Dong,
Heungduk-Gu, Cheongju, Chungbuk 361-763, South Korea
Keywords: Social Networking Sites, Cross-culture, Innovativeness, Propensity to Share Information, Privacy Concern,
Korea, USA.
Abstract: This study examined the antecedents and consequences of intensity of SNS use in a cross-cultural context.
A survey of 977 SNS users was performed in Korea and USA, and the causal relationship was tested using
structural equation modelling. Consumer innovativeness, propensity to share information, and privacy
concern affected intensity of SNS use and the usage of SNS enabled social capital. In addition, the effects of
innovativeness and privacy concern on intensity of SNS use were greater in the U.S. sample than in the
Korean sample. This moderation effects come from the differences of collectivism and individualism and
the implications and further researches were suggested.
Recently, social networking sites are gaining
popularity throughout the world. The number of
Facebook user is estimated over one billion in the
world, 8 million in Korea, and 160 million in US
People can bridge and bond their relationships in the
social networking sites, and they are perceived to be
a good and easy tool of accumulating social capital
(Ellison et al., 2007). The differences in online
social networking may cause another type of digital
divide (Pfeil et al., 2009). Age difference is said to a
main source of digital divide (Prensky, 2001), but
there might be other personal or personality related
factors influencing social networking sites use and
social capital from the use.
There are studies on the use of social networking
sites and social capital (Ellison et al., 2007);
(Valenzuela et al., 2009). We attempt to extend
previous research in two ways. First, we examine the
impacts of three personality related variables -
privacy concern, consumer innovativeness, and
propensity to share information– on the use of social
networking sites. Second, we examine if there are
cross-cultural differences in the relationships
between personality-related variables and social
networking sites (SNS) use.
The findings from this research will provide
empirical evidence to the practitioners and
academics in the SNS related field, especially who
are interested in cross-cultural variations. We
established hypothesis after literature review and
presented results of an empirical study in the
remainder of this paper.
Ever since Ellison et al. (2007) examined the
relationship between Facebook intensity and social
capital, the dynamics of social capital in social
network sites have been widely tested (Valenzuela et
al., 2009); (Steinfield et al., 2008). Besides the topic
of social capital, a stream of study on the factors of
consumer behavior in online social networks is
gaining popularity recently. There were studies on
adoption of SNS (Cheung and Lee, 2010); (Joinson,
2008), electronic word-of-mouth (eWOM) on SNSs
(Jansen et al., 2009); (Chu and Kim, 2011),
Park C., Jun J. and Lee T..
Determinants of Use Intensity in Social Networking Sites - A Cross-cultural Study of Korea and USA.
DOI: 10.5220/0004497501190126
In Proceedings of the 4th International Conference on Data Communication Networking, 10th International Conference on e-Business and 4th
International Conference on Optical Communication Systems (ICE-B-2013), pages 119-126
ISBN: 978-989-8565-72-3
2013 SCITEPRESS (Science and Technology Publications, Lda.)
personality and SNS use (Correa et al., 2010);
(Pagani et al., 2011). Another group of research is
focused on examining how cultural contexts
influence the uses of SNS (Kim et al., 2011); (Chu
and Choi, 2011). Yet very few researches are
addressing the relationship between consumer
characteristics and SNS use in cultural contexts.
Most previous studies considered positive
determinants of SNS adoption or use (Pagani et al.,
2011); (Thorbjørnsen et al., 2007), but there are few
studies that considered both positive and negative
determinants of SNS use.
This research examines the impacts of consumer
innovativeness, propensity to share information, and
privacy concern on SNS use and SNS-enabled social
capital in a cross-cultural context.
2.1 Consumer Innovativeness
The concept of innovativeness is a personality trait
defined as the degree to which an individual makes
innovative decisions independently of the
communicated experience of others (Midgley and
Dowling, 1978). Especially, domain specific
innovativeness (DSI) reflecting the tendency to
adopt innovations within a specific product domain
has been a good predictor for consumer behavior on
the Internet (Goldsmith, 2001); (Park and Jun, 2003).
Consumer DSI was positively associated with
both creating new content (active use) and
consuming the contents of others (passive use) on
the social networking sites (Pagani et al., 2011).
Since social networks are still in the growth stage,
we propose that a person with high innovativeness in
the technology domain will spend more time using
SNS. Furthermore, as innovators are the first group
of consumers to adopt new features or functions of
products, they will likely use them more than others.
H1: High innovativeness in technology domain
will be positively associated with intensity of SNS
2.2 Propensity to Share Information
Identity expressiveness has been regarded as a good
determinant of intention and behavior for symbolic
goods or in public settings of consumption
(Hirschman and Holbrook, 1981); (Richins, 1994).
Expressiveness was found to be a strong driver of
using mobile communication services (Thorbjørnsen
et al., 2007). Similarly, Pagani et al. (2011) showed
both self-identity expressiveness and social-identity
expressiveness are positively related to active use of
social networking sites. Although identity
expressiveness is a good motive for using SNS,
sharing content or information is another motive.
Many social network sites such as Facebook and
Myspace support users in sharing content, especially
LinkedIn is most commonly used for information
providing and gathering, not on socializing
(DiMicco et al., 2008). Social networks are based on
information sharing and revealing enough
information is one of the strongest motivator of SNS
use (Acquisti and Gross, 2006). Travel blogs have
been perceived as useful sources of information for
those who are planning trips, and the bloggers may
have high propensity to share information.
According to Constant et al. (1994), sharing tangible
information depends on pro-social attitudes and
norms whereas sharing expertise depends on
people's own self-expressive needs. Propensity to
share information is regarded as part of pro-social
transformation behaviors as well as a personal norm
reflecting the costs and benefits of sharing and is
significantly related with the use of collaborative
electronic media (Jarvenpaa and Staples, 2000).
H2: Propensity to share information will be
positively associated with intensity of SNS use.
2.3 Privacy Concern
Social networking sites may raise privacy concerns
since they allow users to search for profiles of other
members. Users are concerned about their privacy
when their personal information is used without their
permissions or knowledge (Phelps et al., 2000).
While most SNS users are aware of the visibility of
their profiles, they seem to believe their ability to
control the information revelation (Acquisti and
Gross, 2006). Some possible reasons for revealing
one’s information at the risk of privacy invasion
include cost benefit approach (Donath and Boyd,
2004), peer pressure and herding behavior, relaxed
attitudes towards (or lack of interest in) personal
privacy, incomplete information, faith in the
networking service or trust in its members(Gross and
Acquisti, 2005).
Another reaction to the privacy concern on SNS
may be staying away from it. Privacy concern was
associated with negative attitudes toward SNS
(Boyd, 2008), but not with the behavioral intention
(Tan et al., 2012). A survey on college students
showed that privacy concern was higher for non-
members of Facebook than for members, and non-
members showed stronger sensitivity towards
privacy than members (Acquisti and Gross, 2006).
Although the results of previous researches are
mixed, individuals with high privacy concern will
have lower intensity of SNS use due to either not
using them or using them passively.
H3: Privacy concern will be negatively
associated with intensity of SNS use.
2.4 Intensity of SNS use and Social
The relationship between Facebook use and social
capital has been positively significant in most
previous researches (Papacharissi and Mendelson,
2008); (Burke et al., 2010). While Facebook use was
associated with social capital in general, the
relationship was moderated by the ability and
inclination of the users (Burke et al., 2010).
Although the impact of Facebook use on social
capital has been investigated in previous studies,
fewer studies have tested the relationship between
SNS use overall and social capital.
H4: Intensity of SNS use will be positively
associated with SNS-enabled Social Capital.
2.5 Cross-cultural Variations
Facebook has been allowing users to track the
actions, beliefs and interests of the larger groups to
which they belong, which may serve a social
searching or a surveillance function (Joinson, 2008).
The desire to meet new people on Facebook was a
primary motivation for opening their profile. Many
Facebook users may expect reciprocity in social
surveillance when they leave their privacy settings
relatively open (Gross and Acquisti, 2005). In
general, collectivism culture has stronger peer
pressure to adhere to societal norms than
individualism culture (Hofstede, 2001), which is
also related with herding behavior. Innovators tend
to perceive less risk in their adoption process
(Alda´s-Manzano et al, 2009), and once they started
to adopt SNS by leaving their privacy open, the
majority in collectivism culture will more likely
follow the same practice as a herding behavior than
those in individualism culture. In addition, people in
the culture of high peer pressure and herding
behavior will expect more reciprocity in social
surveillance, especially among in-group members
since they are interested in tracking others in the
group. This tendency might alleviate the negative
impact of privacy concern on intensity of SNS use.
A recent study on mobile phone adoption
showed that the innovation factor of Bass diffusion
model had higher impact on adoption in
individualism culture than in collectivism culture
(Lee et al., 2013). In contrast, in collectivism culture
imitation factor was more effective on adoption than
it was in individualism culture. These findings imply
that innovativeness may be less effective in
explaining adoption behavior in collectivism culture
than in individualism culture. Another recent study
reports that the relationship between consumer
innovativeness and adoption of innovation varies
across cultural norms and values (Truong, 2013).
Based on the discussion above, we propose the
following hypotheses.
H5a: The relationship between privacy concern
and intensity of SNS use will be moderated by cross-
cultural variations.
H5b: The relationship between innovativeness
and intensity of SNS use will be moderated by cross-
cultural variations.
3.1 Samples
A total of 977 responses were collected through an
online survey in South Korea and the U.S. The
subjects for this study were confined to smartphone
users. Responses consist of 50.4% men and 49.6%
women. In the sample, 39.9% were in their twenties,
39.8% were in their thirties and20.3% were in their
forties. The sample consisted of white-collars
(30.2%), professionals (15.3%), (under)graduate
students (14.3%), housewives (12.2%), sales/service
(8.7%), government employees (3.6%), production
(2.7%), and etc. (13.1%).
3.2 Measures
All measurement items used seven-point scales
(1=very strongly disagree, 7=very strongly agree).
Consumer innovativeness was measured using five
items based from Keller and Holland (1978),
Goldsmith(2001): (1) “I can understand the latest
products or service without any help of others”, (2)
“I know about the new technology trend in my
interest area”, (3) “Compared to others, I am the first
person to accept the new technology”, (4) “In
general, others ask me advice of the new
technology”, (5) “I purchase new product before
most other people do”. Propensity to share
information was measured by the agreement with the
following five statements based from Davenport and
Prusak (2000), Hsu et al. (2007) : (1) “I frequently
share new information and my knowledge with
others”, (2) “I frequently talk about the information,
knowledge and know-how with others”, (3) “I
exchange information and data with others
regularly”, (4) “I share purchase information or
knowledge with others”, (5) “I share my knowledge
and experiences with others voluntarily”. Privacy
concern was measured using three items based from
Xin et al. (2012): (1) “I am concerned about the
negative consequences of unknown parties accessing
my private information on this mobile social
network”, (2) “I am concerned that my private
information on the mobile social network may be
misused”, (3) “I am concerned that unknown parties
have access to my private information on this mobile
social network”. Intensity of SNS use was
measured by the agreement with the following six
statements based from Ellison et al. (2007): (1)
“SNS is part of my everyday activity”, (2) “I am
proud to tell people I’m on SNS”, (3) SNS has
become part of my daily routine”, (4) “I feel out of
touch when I haven’t logged onto SNS for a while”,
(5) “I feel I am part of the SNS community”, (6) “I
would be sorry if SNS shut down”. The
measurement of intensity of SNS use was not
confined to a specific SNS; rather it was SNS use in
the aggregate. We did not measure the use of a
separate SNS since the types and popularity of SNS
between Korea and USA are different. Social capital
was measured using three items based from Ellison
et al. (2007): (1) “If I needed an emergency loan of
$100, I know someone at SNS I can turn to”, (2)
“There is someone at SNS I can turn to for advice
about making very important decisions”, (3) “The
people I interact with at SNS would be good job
references for me”.
4.1 Validity of Measurements
Following Anderson and Gerbing (1998), we
conducted the confirmatory factor analysis in order
to establish the reliability and discriminant validity
of the multi-item scales.
Although the chi-square value for this model was
significant (727.325, with 192 degrees of freedom
[df], p = .00), these statistics are sensitive to the
sample size and model complexity; as such, the
goodness-of-fit index (GFI), Tucker–Lewis index
(TLI), and comparative fit index (CFI) are more
appropriate for assessing the model fit here (Bagozzi
and Yi, 1988); (Bearden et al., 1982).
GFI (0.932), AGFI (0.911), TLI (0.965), CFI
(0.971), SRMR (0.039), and RMSEA (0.053)
Table 1: Confirmatory factor analysis results.
Innovativeness 0.920
INNO1 0.749* 26.801
INNO2 0.832* 31.433
INNO3 0.911* 36.390
INNO4 0.889* 34.951
INNO5 0.788* 28.928
Propensity to share
PROP1 0.743* 26.297
PROP2 0.735* 25.695
PROP3 0.835* 31.706
PROP4 0.829* 30.895
PROP5 0.870* 33.275
Privacy concern 0.906
PRIV1 0.759* 27.386
PRIV2 0.960* 38.742
PRIV3 0.892* 34.433
Intensity of SNS use 0.943
INT1 0.847* 32.620
INT2 0.846* 32.438
INT3 0.830* 31.460
INT4 0.815* 30.557
INT5 0.938* 38.574
INT6 0.855* 32.965
Social Capital 0.888
SC1 0.787* 28.589
SC2 0.900* 35.054
SC3 0.864* 33.312
* Parameter estimates are significant at the .001 level.
** AVE = average variance extracted
indicate a satisfactory model fit. Furthermore, all the
individual scales exceed the recommended standards
proposed by Baggozi and Yi (1988) in terms of
construct reliability (greater than 0.60) and average
variance extracted (AVE) by the latent construct
(greater than 0.50). Further, all item loadings
indicate significant t-values, suggesting that
convergent validity was achieved.
The squared correlation between the two
constructs is less than all the AVE for each construct
(See table 1 and 2), suggesting discriminant validity
was achieved (Fornell and Larcker, 1981). In
addition, as shown in table 2, the confidence interval
for each pair-wise correlation estimate does not
include the value of 1. This result also suggested that
discriminant validity was achieved (Anderson and
Gerbing, 1988).
Table 2: Correlation Matrix.
INNO 0.498 0.000 0.160 0.162
0.007 0.187 0.218
0.008 0.006
INNO: Innovativeness, PROP: Propensity to share information,
PRIV: Privacy concern, INT: Intensity of SNS use, SC: Social
Construct correlations (and standard errors) appear below the
diagonal. Squared correlations appear above the diagonal.
4.2 Hypotheses Test
AMOS 20.0 was used to test the model and
hypotheses. The covariance structure testing of the
research model resulted in a chi-square statistic of
766.420 (df = 195, p = 0.00). Although this chi-
square value was significant, this statistic is sensitive
to the sample size and model complexity; as such,
the goodness-of-fit index (GFI), non-normed fit
index (NNFI), and comparative fit index (CFI) are
more appropriate for assessing the model fit here
(Bagozzi and Yi, 1988; Bearden, Sharma and Teel,
1982). GFI (0.928), AGFI (0.907), NNFI (0.963),
CFI (0.969), SRMR (0.048), RMSEA (0.055)
indicate a satisfactory model fit.
The results of the hypotheses test are
summarized in Table3, which show that all proposed
relationships received strong support.
Table 3: Hypotheses Test Results.
H Path
t-value Results
H1 INNOINT 0.201 3.759
H2 PROPINT 0.378 6.773
H3 PRIVINT -0.135 -3.948
H4 INTSC 0.768 24.144
INNO: Innovativeness, PROP: Propensity to share information,
PRIV: Privacy concern, INT: Intensity of SNS use, SC: Social
* p< 0.01
4.3 Cultural Effect
In order to investigate the moderating effect of
national culture in explaining Intensity of SNS use
and social capital, we performed a multi-group
analysis for Korean sample and the U.S. sample. We
performed a multi-group analysis to test for
statistical differences in the structural relationships
across the two groups. The initial baseline model
(unconstrained model) was estimated by allowing all
the model parameters to be free estimates. Then we
constrained one path to be equal across the two
samples. A significant difference would imply that
the path coefficient is statistically different across
the two groups. An insignificant difference in-
between the constrained and unconstrained models
with respect to the degree of freedom would suggest
an equal path coefficient across the two groups. The
results of the multi-group comparison are
summarized in Table 4.
Table 4: Multi-group comparison results.
Path Korea U.S
Results of
d(1) =
Korea <
d(1) =
Korea =
d(1) =
Korea <
d(1) =
Korea =
**p< 0.01, * p<0.05
INNO: Innovativeness, PROP: Propensity to share information,
PRIV: Privacy concern, INT: Intensity of SNS use, SC: Social
The coefficients are non-standardized values. t-values are in
As shown in Table 4, the effect of innovativeness
and privacy concern on intensity of SNS use was
greater for U.S sample than for Korean sample.
However, there is no significant difference in the
two paths (propensity to share information
intensity of SNS use, intensity of SNS use social
capital) between Korean sample and U.S. sample.
This study developed a causal model consisting the
antecedents and consequences of intensity of SNS
use and examined the model using survey data from
USA and South Korea. Among the antecedents of
intensity of SNS use, consumer innovativeness and
propensity to share information were positively
related to intensity of SNS use, whereas privacy
concern was the opposite. Since intensity of SNS use
determines social capital, the results imply that
social capital may be influenced by consumer
characteristics other than the age-related differences
although it is indirect. The study reports that
innovative users spend more time using SNS let
alone they adopt it earlier than others. The results of
this study also show that propensity to share
information affects intensity of SNS use. It implies
that social networking sites need to promote
information sharing beyond the mere expression of
user identity. Social networking sites may raise
privacy concerns since they allow users to search for
profiles of other members. Consumers who had high
privacy concern had lower intensity of SNS use due
to either not using them or using them passively.
Social networking sites need to understand that users
with high privacy concern can leave the sites and try
to reduce the concern on privacy by adding the opt-
in type of networking.
Culture was found to moderate the relationships
between the antecedents (privacy concern and
consumer innovativeness) and intensity of SNS use.
The negative impact of privacy concern on intensity
of SNS use was alleviated in the collectivism culture.
People in the culture of high peer pressure and
herding behavior tend to expect more reciprocity in
social surveillance, especially among in-group
members since they are interested in tracking others
in the group. This tendency might alleviate the
negative impact of privacy concern on intensity of
SNS use.
The positive impact of innovativeness on
intensity of SNS use was alleviated in the
collectivism culture. This is maybe because the
imitation factor predicts adoption behavior better
than the innovation factor in the collectivism culture.
This finding implies that social networking sites
should focus more on group behavior than individual
behavior in order to promote SNS use.
Despite several notable contributions, there are a
few limitations to this study, which may be
overcome by further research. First, this study only
considered consumer innovativeness and privacy
concern as antecedents of intensity of SNS use.
Various personal variables (i.e. demographics,
perception, attitudes, and etc.) will be considered in
the further research.
Second, most measurements were retrospective,
depending on the respondents’ memory of past
shopping behavior, so there were the errors of
measurements. More accurate measurement scale
will be developed in a further study.
Third, an experimental research will be needed to
obtain more accurate effects of antecedents on
intensity of SNS use in the next stage.
This research was supported by SSK 2011 of Korea
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