Does Culture Matters in Intersection of Individual’s Personality and
Social Media Engagement?
Imran Khan
and Han Dongping
School of Management, Harbin Institute of Technology, Harbin, China
Department of Management Sciences, The Islamia University of Bahawalpur, Bahawalpur, Pakistan
Keywords: Internet, Social Media Marketing, Online Engagement, Personality, Facebook, Neo-Pi-R, Brand
Management, Consumer Behavior.
Abstract: Personality traits of consumers may be important elements in the increasingly user-generated web for the
engagement in this participatory media. Previous studies suggest three personality traits- extraversion,
neuroticism and openness to experience- are related to uses of social applications like Facebook. The aim of
current research is to evaluate the factors affecting consumer’s social media engagement in terms of liking,
commenting and sharing behavior on Facebook brand fan pages, and to evaluate the mediating role of
interaction modes and to analyze the moderating role of culture, on relationship between personality traits and
engagement behavior of consumers. Data was collected from 748 fans of 15 Facebook brand fan pages of five
fast food brands operating in three different countries. Structural equation modelling was used to test the
hypothesis. Results revealed that modes of interaction significantly mediate the relationship between
personality traits and social media engagement behaviors. While culture moderates this relationship. Results
showed the highest impact of personality traits on social media engagement in UK than Australia, while their
impact in lowest in USA. It is suggested that consumers of different countries having same personality traits
respond differently to Facebook brand page post, specifically when considering the Facebook functions of
The motivation of consumers to use social media is
not only to reach products or services, but they also
want to engage themselves with companies and other
consumers to attain valuable insight about products
and companies. Communications among consumers
and company’s own communications are the sources
of consumer reach. This novel system of social media
engagement enables organizations to extract value
from existing and potential consumers as an
opportunity. Social media engagement includes a
wide range of specific behaviors and activities such
as liking, commenting and sharing of brand pages on
social media that can be used as measure of social
media engagement (Coulter et al., 2012; Van Doorn
et al., 2010).
Facebook has been embraced by brands as a key
marketing determinant to drive engagement, brand
commitment, loyalty, recommendation and
awareness (Malhotra et al., 2013; Rohm et al., 2013).
Consumers are able to interact directly with brands
through these brand pages by liking, commenting and
sharing of brand page posts. Thus, Facebook users
post thousands of comments on brand post that
provide a platform of social media dialogue which
solicit information easily, better understand consumer
and gain feedback (Malhotra et al., 2013). Therefore,
organizations adopt social media marketing as
integral part of their marketing and public relation
Moreover, the relationship between Facebook
behavior and personality traits has yet to be tested
empirically. Past studies had highlighted that
personality can be a most relevant variable in
formulating social media and internet behavior
(Amichai-Hamburger, 2002). Previous studies have
established three personality traits (extroversion,
neuroticism and openness to experience) that affect
digital consumer behavior (Amichai-Hamburger,
2002; Ross et al., 2009; Zywica and Danowski,
2008). In addition, this study incorporates the shyness
into model as a personality trait and sharing behavior
as a Facebook fan engagement.
Khan, I. and Dongping, H.
Does Culture Matters in Intersection of Individual’s Personality and Social Media Engagement?.
In Proceedings of the 1st International Conference on Complex Information Systems (COMPLEXIS 2016), pages 167-176
ISBN: 978-989-758-181-6
2016 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
In this research, we investigate the relationship
between four personality traits and consumer’s liking,
commenting and sharing behaviors on Facebook.
Furthermore, we also investigate the relationship
between personality traits and number of Facebook
friends of respective consumers. Moreover, two
different interaction modes are also included in our
framework that consumer exhibit on Facebook
behavior. Furthermore, the present study incorporates
culture into the model as moderator that effect on the
relationship between personality traits and Facebook
fan engagement. We believe that the findings of our
research may highlight the understanding of
personality traits that enforce consumers to like,
comment or share on brand fan pages on Facebook,
thus guiding managers of social media fan pages to
enhance the effectiveness of their social media
strategies internationally related to brand
2.1 Consumer Engagement
It can be elaborated as “behaviors that go beyond
simple transactions, and may be specifically defined
as a customer’s behavioral manifestations that have a
brand focus, beyond purchase, resulting from
motivational drivers” (Van Doorn et al., 2010). It
involves all types of behaviors beyond loyalty
behaviors (Libai, 2011) and sometimes denoted as
uppermost form of loyalty (Roberts and Alpert,
2010). According to Brodie et al., (2011), consumer
engagement and marketing concept are consumer-
centric approaches as both of them focus on
consumers and their need to engage with them.
Consumer engagement and relationship
marketing concept are also sharing some common
grounds. Commitment and trust are the heart of
relationship marketing (Morgan and Hunt, 1994),
which are compulsory for conversion of any
interaction into relationship. Similarly, establishment
and maintenance of commitment and trust is
facilitated by consumer engagement that drives
consumer to be engaged with company or brand
(Sashi, 2012). Moreover, in addition to Brodie et al.
(2011) and Sashi (2012); (Van Doorn et al., 2010)
also concluded that consumer engagement can
contribute in formation of advanced levels of
commitment and trust between companies and
consumers and can be involved in structuring of
strong emotional links in relational exchange. Prior
research also suggests that consumer engagement
enhances the relationship quality between consumer
and brand by providing higher satisfaction in
relationship (Coulter et al., 2012). Therefore, it is
concluded that for the assurance of high-quality
enduring relationship with consumers, companies are
able to understand the factors of consumer
2.2 Modes of Interaction
Existing well-known connections can be reached by
using social networks that depend on user intention.
This intention can be elaborated via interaction mode
on social networking sites (SNSs) of the user.
Consumer behavior can be affected by these
interaction modes, holding important implications for
consumer engagement understanding on platforms of
social network (Zhao et al., 2008). Because of this we
include consumer’s mode of interaction as mediator
variables in our conceptual framework in relationship
between consumer engagement and personality traits.
Literature defines two interaction modes in which
users of social media operate, “broadcasting” (BO)
and “communicating” (CO) (Underwood et al.,
2011). BO is a “one-to-many” style of interaction
while CO is a “one-to few” or “one-to-one” type of
interaction. In the first mode, users pretend to indorse
themselves to the people of large networks (Pempek
et al., 2009). Impression management is the primary
concerns of people who use this mode (Walther,
1996). While, on the other hand, CO mode is more
private and produce high quality interaction with
already known individuals. They want to be less
visible and only interact with close-knit individuals.
They have quality interaction with online
communities of small size on regular bases (Skinstad,
2008). Thus, we postulate that:
H1. BO is positively related to (a) liking, (b)
commenting, (c) sharing behavior and (d) number of
friends on Facebook.
H2. CO is (a) positively related to liking behavior on
Facebook and negatively related to (b) commenting
and (c) sharing behavior, and (d) number of friends
on Facebook.
2.3 Personality Traits
In this growing popularity of internet usage, literature
shows that the Five-Factor Model is the most
commonly used model for examining personality
influence on internet usage (Ehrenberg et al., 2008;
John and Srivastava, 1999; Angela Hausman et al.,
COMPLEXIS 2016 - 1st International Conference on Complex Information Systems
2014). Former researchers have discussed three
personality traits and investigated the relation of two
modes of interaction with two Facebook behaviors
liking and commenting (Angela Hausman et al.,
2014). The present study incorporate shyness in
addition to NEO (Neuroticism-Extraversion-
Openness) Personality Inventory (NEO PI-R form S)
(Costa and McCrae, 1992) into the model as a
personality trait.
Extraversion (EX) describes a person’s ability to
experience positive emotions and his/her tendency to
be sociable (Butt and Phillips, 2008). According to
Amichai-Hamburger et al., (2002), extrovert is a
person who is friendly and seeks company, acts on
impulse and desires excitement, whereas introvert is
a reflective and quiet individual who does not feel
comfortable in large social events and prefer his/her
own company. Extroverted individuals have many
connections with others via Facebook groups (Ross et
al., 2009), social networking sites (Zywica and
Danowski, 2008), and take dominant and central
position in networks of friendship (Wehrli, 2008).
Facebook communication features that individuals
use are positively related to level of extraversion.
While, few features of Facebook are used by
introverts (Ryan and Xenos, 2011). Thus, introverts
might prefer one-to-one mode of interaction with
already known individuals to elude high levels of
social interaction and contact. Thus, we formulate
following hypothesis:
H3. Level of EX is (a) positively related to BO and
(b) negatively related to CO.
The neurotic (NE) individual is a worrisome, anxious
person who responds to every type of stimuli and
overly emotional (Ross et al., 2009). Research proved
that neurotic persons use internet for the reduction of
loneliness and have limited interaction to only known
persons (Butt and Phillips, 2008). High neurotic
persons have high control in information as they
prefer to control what type of information they have
to spread (Butt and Phillips, 2008). High neurotic
individuals are more nervous in social gathering, so
that they prefer small social network of known
individuals (Wehrli, 2008). Thus, it can be expected
that they would prefer communicating interaction
mode by interacting with only known individual (one-
to-one relationship) for the reduction of loneliness.
Based on the above discussion we postulate:
H4. Level of NE is (a) negatively related to BO and
(b) positively related to CO.
According to McCrae and Costa (1987) openness to
experience (OE) represents a person’s readiness to be
intellectually curious, to study alternative methods
and enjoy creative hobbies. They love extensive
diversity of interests and ready to follow them (Butt
and Phillips, 2008). Furthermore, these high OE trait
individuals like to use and share more features and
information with others (Amichai-Hamburger and
Vinitzky, 2010). They would show risk-taking social
behavior to satiate their curiosity with the large
unknown audience in social media (Ross et al., 2009).
These individuals are more prone to post on Facebook
wall of others (Ross et al., 2009) to enhance
interaction with large number of individuals
(Carpenter et al., 2011). Thus, we formulate the
following conjecture:
H5. Level of OE is (a) positively related to BO and
(b) negatively related to CO.
Shyness (SHY) is characterized by inhibition of
normal social behaviors and nervous responses (e.g.,
discomfort, tension, aversion of stare) in presence of
others (Buss, 1980). This type of anxiety and shyness
may also be obvious in online interaction. Previous
researches showed insignificant results for the
internet communication tool (e.g., chat rooms, e-mail
and instant messaging) usage by shy individuals
(Madell and Muncer, 2006). According to them,
shyness is neither a barrier nor boost high utilization
of online communication. The above discussion
support the notion that shyness may facilitate online
engagement. Therefore, we postulate:
H6. Level of SHY is (a) negatively related to BO and
(b) positively related to CO.
2.4 Moderating Effect of Culture
Prior researches had identified that culture impacts
consumer’s decision making process and information
seeking (Mangold and Smith, 2012; McGuinness et
al., 1991) but no research available in literature shows
the cultural difference impact on relationship between
personality traits and modes of communication, and
social media engagement and modes of interaction.
For the cultural differences variable of our model
we used Geert Hofstede theory. Based on the
Hofstede’s theory, we have selected three culturally
similar countries Australia (AUS), United Kingdom
(UK) and United States of America (USA) for
evaluation of cultural difference impact on consumer
engagement on social networks. These countries have
almost same scores in uncertainty avoidance and
power distance dimensions as Dawar et al., (1996)
proved that these dimensions of Hofstede’s
framework impact information exchange behavior of
Other dimensions also have matching scores in all
three countries. Research proves that using theoretical
aspects based similar countries, improve reliability
Does Culture Matters in Intersection of Individual’s Personality and Social Media Engagement?
and increase generalizability (Alden et al., 1993;
Sivakumar and Nakata, 2001). We propose that
Cultural differences (country/location) play a
moderating role among the relationship of personality
traits, modes of interactions, brand fan engagement
and number of Facebook friends (figure 1).
Based on the above discussion we postulate the
following hypothesis:
H7a: Culture moderates the relationship between EX
and (a1) BO and (a2) CO.
Figure 1: Theoretical Framework.
H7b: Culture moderates the relationship between NE
and (b1) BO and (b2) CO.
H7c: Culture moderates the relationship between OE
and (c1) BO and (c2) CO.
H7d: Culture moderates the relationship between
SHY and (d1) BO and (d2) CO.
H8a: Culture moderates the relationship between BO
and (a1) liking, (a2) commenting, (a3) sharing and
(a4) number of Facebook friends.
H8b: Culture moderates the relationship between CO
and (b1) liking, (b2) commenting, (b3) sharing and
(b4) number of Facebook friends.
3.1 Sampling and Procedure
To study the moderating and mediating effect of
mode of interaction and culture on the relationship
between personality traits and social media
engagement, an online survey was conducted among
AUS, USA and UK adults from May to July 2015.
Participants were selected from the 15 Facebook
brand fan pages of five companies operating in
aforementioned three countries. To assure more
accurate representation of brand based country
population, and to overcome the limitation of using
online surveys, this particular sample is based on two
census variables gender and age. This procedure is
authenticated by former researches (Bennett and
Iyengar, 2008; Vavreck, 2007; Gil de Zúñiga and
Valenzuela, 2009). We randomly matched 3000
respondents (200 from each Facebook fan page) to
these demographic characteristics. These selected
respondents were personally contacted on Facebook
and sent the survey’s URL. This invitation provides
estimated time to respondents for survey completion
and monetary incentive information that is given as
reward for participation. First invitation was sent on
May 18, 2015 and four reminders were sent in the
following eight weeks to improve response rate. The
last reminder was sent on July 13, 2015. A total 748
respondents filled the survey with the response rate of
24.9%, which fall within an acceptable response rate
for online survey (Batinic et al., 2002; Sax et al.,
2003). Fifty-eight percent were male and 42% were
female, having an average age of 24.68 years (SD=
3.2 Measure
The five-point Likert scales (5= “strongly agree” and
1= “strongly disagree”) were used from the former
studies for the measurement of personality traits,
interaction modes and engagement behaviors. This
study used three dimensions of revised NEO
Personality Inventory (NEO-PI-R from S) (Costa and
McCrae, 1992). Shyness was measured via the
Revised Cheek and Buss Shyness Scale (RCBS-
13)(Cheek and Buss, 1981). Score range from a
minimum of 13 (very non-shy) to a high of 65 (very
shy). Interaction modes were measured by using the
items based on the study of (Underwood et al., 2011).
Engagement behaviors (liking and commenting) were
measured by using the items based on (Angela
Hausman et al., 2014). Following the method of
(Angela Hausman et al., 2014), a three-item scale was
developed to ask participants about their Facebook
behavior in regard to sharing.
4.1 Analytical Approach, Data
Screening, and the Measurement
Data was analysed by sing SPSS and AMOS 7.0. At
first, measurement model was estimated using
confirmatory factor analysis (CFA) by following two-
COMPLEXIS 2016 - 1st International Conference on Complex Information Systems
step approach of (Anderson and Gerbing, 1988).
Structural equation modelling was applied after
accessing the adequacy of measurement model to
identify the model fitting and to study the causal
relationships. The structure of variables in the model
proposed by current research was assessed by
conducting CFA using maximum likelihood
estimation with 748 cases collected. After the model
was analysed for construct validity,
unidimensionality, and reliability, the results showed
that the model fit the data well (chi-sq= 1132.413, df=
953, p < 0.001, RMSEA = 0.02, CFI= 0.993, NFI=
0.955, IFI= 0.993). Cronbach’s alpha was used to test
the internal consistency reliability- how consistently
individuals responded to the items within a scale- of
each composite construct and its value ranged from
0.81 to 0.95 for all constructs, indicating the existence
of reliability.
The measurement model of current research
consisted of nine multiple-item latent variables
(extroversion, neuroticism, openness to experience,
shyness, broadcasting mode of interaction,
communicating mode of interaction, liking,
commenting and sharing brand fan page). Each of
them was then tested by CFA and showed a good
model-fit. Based on a good-fitted measurement
model, composite reliability (CR) - used to measure
consistency of individual’s response to the items
within a scale- supported the construct reliability as
CR values are greater than the value of 0.60 (CR
ranging from 0.82 to 0.93) (Fornell and Larcker,
1981) and (Bagozzi and Yi, 1988). Furthermore,
average variance extracted (AVE) values ranging
from 0.57 to 0.64, exceeded the threshold value of
0.50 recommended by (Fornell and Larcker, 1981).
Based on it discriminant validity have been achieved
because each construct’s AVE was greater than the
squared correlation among constructs. Therefore, it
can be concluded that the instrument had proper
discriminant and convergent validity.
4.2 Structural Model
There was a potential problem of the occurrence of
common method variance (CMV) as all the measures
were self-reported by the same respondents. CMV
was tested by utilizing CFA. According to (Podsakoff
et al., 2003), CMV does not appear to be a serious
threat if fit of the one-dimensional model is worse
than that of the measurement model. And results
prove the same, therefore, the issue of CMV is of less
concern in this study.
Unobserved characteristics of brand category and
difference in opinion of different gender might lead
to difference in explained variables across different
countries. Therefore we control for brand categories
and gender. It might be that high Facebook
experience fans of brand pages may respond
differently as compare to low experience users. So
that, we control for Facebook experience while
applying measurement model. Controlling these
variables may effectively reduce experimental errors
as they could have some unpredictable influences on
intention to use Facebook and fan pages. The results
gathered after using structural equation modelling
showed a good fit (χ2=1660.640, df= 148, p< 0.001,
RMSEA = 0.07, CFI= 0.914).
4.3 Mediating Effect
Table-1 show the results that provide support to all
the hypothesized relationships except H2a, H3a, H5a
and H5b. The results showed that broadcasting
interaction mode was positively related to all
engagement modes liking (β=0.367, p<0.001),
commenting (β=0.384, p<0.001) and sharing
(β=0.397, p<0.001), and number of friends on
Facebook (β=0.372, p<0.001). On the other hand
communicating interaction mode had a negative
relationship with all engagement modes liking (β=-
0.398, p<0.001), communicating (β= -0.385,
p<0.001), sharing (β= -0.349, p<0.001), and number
of friends on Facebook (β= -0.364, p<0.001).
Relationship between communicating mode of
interaction and liking was proposed positive (H2a)
and result oppose this hypothesis. Thus, H1a, H1b,
H1c, H1d, H2b, H2c and H2d were all supported.
Table 1: Structural Model Results of Mediation Analysis.
EX BO 0.058 1.468
EX CO -0.132** -3.177
NE BO -0.122** -3.169
NE CO 0.18*** 4.443
OE BO 0.066 1.695
OE CO -0.074 -1.805
SHY BO -0.648*** -19.346
SHY CO 0.507*** 14.43
BO LK 0.367*** 9.094
BO COMT 0.384*** 9.624
BO SH 0.397*** 9.625
BO NOF 0.372*** 8.942
CO LK -0.398*** -9.863
CO COMT -0.385*** -9.647
CO SH -0.349*** -8.474
CO NOF -0.364*** -8.757
*p<0.05, **p<0.01, ***p<0.001
Does Culture Matters in Intersection of Individual’s Personality and Social Media Engagement?
Results regarding personality traits and
interaction modes showed that neuroticism and
shyness were negatively related to broadcasting
interaction mode (β= -0.122, p<0.01; β= -0.648,
p<0.001). Moreover, extroversion was found to has
negative relationship with communicating interaction
mode (β= -0.132, p<0.01) while, neuroticism and
shyness were positively related (β= 0.18, p<0.001; β
=0.507, p<0.001) with communicating mode of
interaction. Therefore, these results provided support
for H3b, H4a, H4b, H6a, and H6b.
4.4 Moderating Effect
Invariance analysis of different groups was applied to
test the moderating effects of culture (Jurowski and
Gursoy, 2004), and used the procedure of (Han et al.,
2010, Han et al., 2013, Bell and Menguc, 2002).
Participants of three countries were divided into three
pairs (AUS-USA, AUS-UK and USA-UK) to
conduct pair wise invariance analysis of group
difference. Initially for every pair, the structural
models were estimated without across-group
constraints (i.e. unconstrained models). Then, cross-
group constraints (i.e. constrained model) where the
parameter estimates for each pair country groups
were constrained to be equal. Finally a χ2 test
comparing the unconstrained and constrained models
was used to detect moderating effects. A significant
χ2 difference between the unconstrained models
suggests that there are some differences between each
pair group countries in terms of Facebook fan page
engagement behavior. The findings show H8a2, H8a3
and H8a4 were supported fully for three pairs of
countries, while H7a1, H7b1, H7c1, H7c2, H7d1,
H7d2, H8a1, H8b2, H8b3 and H8b4 were reveal
partial support. Moreover, H7a2, H7b2 and H8b1
were not supported (Table 2). To be more specific,
this study’s proposed model varies in three countries
(AUS, USA and UK) with respect to personality traits
and Facebook brand fan page engagement. First,
culture partially moderates the relationship between
all personality traits and BO. Second, culture partially
moderates the relationship between OE and SHY, and
CO while, it did not moderates the relationship
between EX and NE, and CO. Third, culture fully
mediates the relationship between BO and Facebook
fan page engagement in terms of COMT and SH, and
NOF while, it partially moderates the relationship
between BO and LK. Forth, culture partially mediates
the relationship between CO and Facebook fan page
engagement in terms of COMT and SH, and NOF
while, it did not mediates the relationship between
CO and LK. Based on the presentation of the results
in this section, the next section discusses some of the
implications of the results and contributions of the
present study to the literature.
To narrow the gaps in the literature, this study
incorporates the shyness into model as personality
trait and sharing behavior as Facebook fan
engagement. Furthermore, the present study
incorporates culture into the model as moderator that
effect on the relationship between personality traits
and social media engagement. The results of the data
analysis generally support the present study’s
proposed framework. Modes of interactions mediate
the relationship between personality traits and
Facebook fan engagement. In addition, shyness is an
important personality trait that effect on online
engagement. Most important, the results of this study
confirm that culture significantly moderates the
relationship between personality traits and Facebook
fan engagement. This study findings are consistent
with previous research; nevertheless, there are some
issues worth further discussion.
For the main model before considering culture as
moderating variable, the results of this study show
that mode of interaction mediates the relationship
between personality traits and social media
engagement. Previous literature has consistently
supported this idea (Angela Hausman et al., 2014),
while (Correa et al., 2010, Ross et al., 2009)
investigated the direct relationship between
personality traits and individual’s behavior at social
Literature shows that extraversion has
inconsistent relationship with different uses of
internet (Hamburger and Ben-Artzi, 2000, Correa et
al., 2010). In addition, mediating role of modes of
interaction proved by (Angela Hausman et al., 2014)
that consumers pursue differential benefits on social
media (Facebook) depending on their interaction
mode. Our findings suggest that it is related to the fact
that consumers of the different countries may pursue
different benefits on social media (e.g., Facebook)
depending on their interaction mode. As far as the
social benefits are concerned (one-to-many
communication on brand’s fan page), broadcasters
might appreciate as they are more inclined to like,
comment and share but this might not work for
communicators at all. Therefore, managers of the
COMPLEXIS 2016 - 1st International Conference on Complex Information Systems
brands may need to study the interaction mode of
their consumers before formulating strategies about
social benefits for users on Facebook. But, ignoring
users with communicating interaction mode
completely is not a wise strategy.
Individual’s personality can be projected through
Facebook profile pages and postings (Ehrenberg,
2013). Managers of brands can utilize these methods
in identifying their user’s personality and categorize
them as communicators and broadcasters using the
significant relationships suggested by the present
study even in different cultures. Moreover,
information obtained from this kind of personality
assessment using behavior on Facebook could be
helpful for mangers of the brands those formulate
psychographics and demographics -based
segmentation strategy for Facebook (Shaer, 2013),
especially for different cultures.
Table 2: Culture Moderating Effects: Results of Multiple
Group Analysis.
0 0.45 0.46
0.19 ** 2.24 0.9 0.16
-0.01 -0.09
0.65 0.47
0.27 1 2.23
0.64 1.79
*p<0.10, **p<0.05, ***p<0.01
Based on the findings of the current research,
managers of the brands can formulate Facebook
brand fan page post strategy to generally invite and
boost broadcasters. More specifically, they can
design same Facebook posts for AUS and UK but
different for USA to invite and to encourages
broadcasters. For example, as self-promotion and
self-expression in more visible way are significant
aims for broadcasters (Underwood et al., 2011).
Moreover, managers of the brands may place more
interactive posts that ask for input from their users, or
that enforce them to spread their emotions and
opinions, which are significant for broadcaster’s need
of self-presentation. Managers of the brands must
have to keep in mind while formulating the
international Facebook fan page post strategy that
broadcasters have high engagement behavior in terms
of likes, comments and shares in UK followed by
AUS and USA. By offering opportunity of self-
promotion such as controversial discussion topics and
contests on Facebook fan page, so they can get
broadcaster’s attention and make them like, comment
and share their own posts. More vivid and interactive
posts can help brands to engage more broadcasters on
Facebook fan page. Managers of the brands should
keep in mind while formulating international brand
fan page post strategy that broadcasters love to
engage more in sharing behavior followed by
commenting and liking in all three countries. So that,
while segmenting their Facebook users based on their
valence and type of comments and using the insights
and information obtained from these comments, they
should have to keep in mind that the comments may
only reflect a group of consumers with specific
personality traits and interaction mode in all three
countries. Therefore, they should be aware of this
caution while formulating their segmentation
strategies, as they may exclude communicating
interaction mode individuals.
Success of social media strategies lies in
consumer engagement. The performance of the social
networking site to brands is limited without active
likers, commenters and sharers. Therefore, managers
of the brands should have to encourage and facilitate
such behavior for active engagement of their social
media users to maximize their benefits.
Although the findings of current research provide
meaningful implications for Facebook fan
Does Culture Matters in Intersection of Individual’s Personality and Social Media Engagement?
engagement, some limitations regarding the model’s
external validity are addressed here. First, the issue of
external validity is a concern in developing studies
with online samples. Although online samples were
considered as appropriate for the online engagement
study, a broader range from diverse groups of
respondents is suggested for future studies. Second,
only three personality factors are considered from Big
Five personality model as important determinants of
personality. Although this study include shyness in
addition to extroversion, neuroticism and openness to
experience, extended model including all
determinants of Big Five model and shyness is
suggested for future studies. Third, the present study
did not consider the real-world behavior of
consumers. However, this is less of a concern for
considerable empirical evidence for the fundamental
relationship between intention to behave and actual
behavior (Taylor and Todd, 1995; Venkatesh and
Morris, 2000). Fourth, the present study did not
consider the impact of age groups on explained
variables. However, future studies may test current
model with different age group respondents to see if
the results will hold. Finally, while we agree with
(Angela Hausman et al., 2014; Sashi, 2012) that more
studies are needed on social media engagement of
consumers, it is also important to understand the
financial impact of heavily discussed engagement
behaviors on brands fan pages. Therefore, it would be
useful and critical for the managers of the brands to
understand if such behaviors (liking, commenting and
sharing) results in high probability of sale of same
brand products of by the customers who liked,
commented or shared the brand posts on Facebook
fan page.
In conclusion, the present study strengthens our
views with empirical results and fills the gap in social
media fan engagement literature. The empirical
findings are supportive of the inclusion of shyness as
personality traits into the model. Moreover,
moderating role of culture incorporates a sound
contribution in the literature of social media fan
engagement. Overall, in spite of its limitation, this
research is an important step in understanding the
factors and motives affecting consumer’s Facebook
behavior and social media engagement in different
cultures, and it provides fruitful insights for managers
of the brands intending to utilize Facebook as part of
their promotion mix strategy.
Alden, D. L., Hoyer, W. D. & Lee, C. 1993. Identifying
global and culture-specific dimensions of humor in
advertising: A multinational analysis. The Journal of
Marketing, 64-75.
Amichai-Hamburger, Y. 2002. Internet and personality.
Computers in Human Behavior, 18, 1-10.
Amichai-Hamburger, Y. & Vinitzky, G. 2010. Social
network use and personality. Computers in human
behavior, 26, 1289-1295.
Amichai-Hamburger, Y., Wainapel, G. & Fox, S. 2002. "
On the Internet No One Knows I'm an Introvert":
Extroversion, Neuroticism, and Internet Interaction.
CyberPsychology & Behavior, 5, 125-128.
Anderson, J. C. & Gerbing, D. W. 1988. Structural equation
modeling in practice: A review and recommended two-
step approach. Psychological bulletin, 103, 411.
Angela Hausman, D., Kabadayi, S. & Price, K. 2014.
Consumer–brand engagement on Facebook: liking and
commenting behaviors. Journal of Research in
Interactive Marketing, 8, 203-223.
Bagozzi, R. P. & Yi, Y. 1988. On the evaluation of
structural equation models. Journal of the academy of
marketing science, 16, 74-94.
Batinic, B. E., Reips, U.-D. E. & Bosnjak, M. E. 2002.
Online social sciences, Hogrefe & Huber Publishers.
Bell, S. J. & Menguc, B. 2002. The employee-organization
relationship, organizational citizenship behaviors, and
superior service quality. Journal of retailing, 78, 131-
Bennett, W. L. & Iyengar, S. 2008. A new era of minimal
effects? The changing foundations of political
communication. Journal of Communication, 58, 707-
Brodie, R. J., Hollebeek, L. D., Juric, B. & Ilic, A. 2011.
Customer engagement: conceptual domain,
fundamental propositions, and implications for
research. Journal of Service Research,
Buss, A. H. 1980. Self-consciousness and social anxiety,
Butt, S. & Phillips, J. G. 2008. Personality and self reported
mobile phone use. Computers in Human Behavior, 24,
Carpenter, J. M., Green, M. C. & Laflam, J. 2011. People
or profiles: Individual differences in online social
networking use. Personality and individual differences,
50, 538-541.
Cheek, J. M. & Buss, A. H. 1981. Shyness and sociability.
Journal of personality and social psychology, 41, 330.
Correa, T., Hinsley, A. W. & De Zuniga, H. G. 2010. Who
interacts on the Web?: The intersection of users’
personality and social media use. Computers in Human
Behavior, 26, 247-253.
Costa, P. T. & Mccrae, R. R. 1992. Normal personality
assessment in clinical practice: The NEO Personality
Inventory. Psychological assessment, 4, 5.
Coulter, K. S., Gummerus, J., Liljander, V., Weman, E. &
Pihlström, M. 2012. Customer engagement in a
Facebook brand community. Management Research
Review, 35, 857-877.
Dawar, N., Parker, P. M. & Price, L. J. 1996. A cross-
COMPLEXIS 2016 - 1st International Conference on Complex Information Systems
cultural study of interpersonal information exchange.
Journal of International Business Studies, 497-516.
Ehrenberg, A., Juckes, S., White, K. M. & Walsh, S. P.
2008. Personality and self-esteem as predictors of
young people's technology use. CyberPsychology &
Behavior, 11, 739-741.
Ehrenberg, R. 2013. Science & society: What a Facebook
‘like’reveals: Researchers predict personal traits using
social media data. Science News, 183, 14-14.
Fornell, C. & Larcker, D. F. 1981. Evaluating structural
equation models with unobservable variables and
measurement error. Journal of marketing research, 39-
Gil De Zúñiga, H. & Valenzuela, S. 2009. Disentangling
facebookers: A snapshot of social network site users in
the United States. Facebook and philosophy. Open
Court Publishing.
Hamburger, Y. A. & Ben-Artzi, E. 2000. The relationship
between extraversion and neuroticism and the different
uses of the Internet. Computers in Human Behavior, 16,
Han, H., Hsu, L.-T. J. & Sheu, C. 2010. Application of the
theory of planned behavior to green hotel choice:
Testing the effect of environmental friendly activities.
Tourism Management, 31, 325-334.
Han, Y. J., Nunes, J. C. & Drèze, X. 2013. Signaling status
with luxury goods: The role of brand prominence.
International Retail and Marketing Review, 9, 1-22.
John, O. P. & Srivastava, S. 1999. The Big Five trait
taxonomy: History, measurement, and theoretical
perspectives. Handbook of personality: Theory and
research, 2, 102-138.
Jurowski, C. & Gursoy, D. 2004. DISTANCE EFFECTS
TOURISM. Annals of Tourism Research, 31, 296-312.
Libai, B. 2011. Comment: the perils of focusing on highly
engaged customers. Journal of Service Research, 14,
Madell, D. & Muncer, S. 2006. Internet communication: An
activity that appeals to shy and socially phobic people?
CyberPsychology & Behavior, 9, 618-622.
Malhotra, A., Malhotra, C. K. & See, A. 2013. How to
create brand engagement on Facebook. MIT Sloan
Management Review, 54, 18-20.
Mangold, W. G. & Smith, K. T. 2012. Selling to Millennials
with online reviews. Business Horizons, 55, 141-153.
Mccrae, R. R. & Costa, P. T. 1987. Validation of the five-
factor model of personality across instruments and
observers. Journal of personality and social
psychology, 52, 81.
Mcguinness, N., Campbell, N. & Leontiades, J. 1991.
Selling machinery to China: Chinese perceptions of
strategies and relationships. Journal of International
Business Studies, 187-207.
Morgan, R. M. & Hunt, S. D. 1994. The commitment-trust
theory of relationship marketing. the journal of
marketing, 20-38.
Pempek, T. A., Yermolayeva, Y. A. & Calvert, S. L. 2009.
College students' social networking experiences on
Facebook. Journal of Applied Developmental Psycho-
logy, 30, 227-238.
Podsakoff, P. M., Mackenzie, S. B., Lee, J.-Y. & Podsakoff,
N. P. 2003. Common method biases in behavioral
research: a critical review of the literature and
recommended remedies. Journal of applied
psychology, 88, 879.
Roberts, C. & Alpert, F. 2010. Total customer engagement:
designing and aligning key strategic elements to
achieve growth. Journal of Product & Brand
Management, 19, 198-209.
Rohm, A., D. Kaltcheva, V. & R. Milne, G. 2013. A mixed-
method approach to examining brand-consumer
interactions driven by social media. Journal of
Research in Interactive Marketing, 7, 295-311.
Ross, C., Orr, E. S., Sisic, M., Arseneault, J. M.,
Simmering, M. G. & Orr, R. R. 2009. Personality and
motivations associated with Facebook use. Computers
in human behavior, 25, 578-586.
Ryan, T. & Xenos, S. 2011. Who uses Facebook? An
investigation into the relationship between the Big Five,
shyness, narcissism, loneliness, and Facebook usage.
Computers in Human Behavior, 27, 1658-1664.
Sashi, C. 2012. Customer engagement, buyer-seller
relationships, and social media. Management decision,
50, 253-272.
Sax, L. J., Gilmartin, S. K. & Bryant, A. N. 2003. Assessing
response rates and nonresponse bias in web and paper
surveys. Research in higher education, 44, 409-432.
Shaer, M. 2013. Want to really know people? Take a look
at their Facebook 'likes.'. The Christian Science
Sivakumar, K. & Nakata, C. 2001. The stampede toward
Hofstede's framework: Avoiding the sample design pit
in cross-cultural research. Journal of international
business studies, 555-574.
Skinstad, M. Facebook: A digital network of friends. 24th
conference of the nordic sociological association, 2008.
Taylor, S. & Todd, P. A. 1995. Understanding information
technology usage: A test of competing models.
Information systems research, 6, 144-176.
Underwood, J. D., Kerlin, L. & Farrington-Flint, L. 2011.
The lies we tell and what they say about us: Using
behavioural characteristics to explain Facebook
activity. Computers in Human Behavior, 27, 1621-
Van Doorn, J., Lemon, K. N., Mittal, V., Nass, S., Pick, D.,
Pirner, P. & Verhoef, P. C. 2010. Customer engagement
behavior: theoretical foundations and research
directions. Journal of Service Research, 13, 253-266.
Vavreck, L. 2007. The exaggerated effects of advertising on
turnout: The dangers of self-reports. Quarterly Journal
of Political Science, 2, 325-343.
Venkatesh, V. & Morris, M. G. 2000. Why don't men ever
stop to ask for directions? Gender, social influence, and
their role in technology acceptance and usage behavior.
MIS quarterly, 115-139.
Walther, J. B. 1996. Computer-mediated communication
impersonal, interpersonal, and hyperpersonal
interaction. Communication research, 23, 3-43.
Does Culture Matters in Intersection of Individual’s Personality and Social Media Engagement?
Wehrli, S. 2008. Personality on social network sites: An
application of the five factor model. Zurich: ETH
Sociology (Working Paper No. 7).
Zhao, S., Grasmuck, S. & Martin, J. 2008. Identity
construction on Facebook: Digital empowerment in
anchored relationships. Computers in human behavior,
24, 1816-1836.
Zywica, J. & Danowski, J. 2008. The faces of Facebookers:
Investigating social enhancement and social
compensation hypotheses; predicting Facebook™ and
offline popularity from sociability and selfesteem, and
mapping the meanings of popularity with semantic
networks. Journal of Computer
Communication, 14, 1-34.
COMPLEXIS 2016 - 1st International Conference on Complex Information Systems