Does Culture Matters in Intersection of Individual’s Personality and

Social Media Engagement?

Imran Khan

1,2

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

individual.

1 INTRODUCTION

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

campaigns.

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

167

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

engagement.

2 LITERATURE REVIEW AND

HYPOTHESIS DEVELOPMENT

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

engagement.

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.,

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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

consumers.

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?

169

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 METHOD

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=

8.6).

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 DATA ANALYSIS

4.1 Analytical Approach, Data

Screening, and the Measurement

Model

Data was analysed by sing SPSS and AMOS 7.0. At

first, measurement model was estimated using

confirmatory factor analysis (CFA) by following two-

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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.

Standardized

estimates

t-value

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?

171

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.

5 DISCUSSION AND

IMPLICATION FOR

MANAGERS

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

media.

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

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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.

AUS USA U

Std.

Esti

mate

Std.

Esti

mate

Std.

Estimat

∆χ2

AUS

USA

∆χ2

AUS

-UK

∆χ2

UK-

USA

→BO

0.20

***

-0.05

0.19

***

7.15

***

0.01

6.67

***

EX →

0.13

***

-0.13

-0.19

0 0.45 0.46

NE →

0.32

***

-0.07

-0.14

6.05

3.9

0.49

NE →

0.29

***

0.14

0.19 ** 2.24 0.9 0.16

OE →

0.14

-0.03

0.25

***

3.01

1.49

7.33

***

OE →

-0.17

-0.01 -0.09

2.75

0.65 0.47

SHY

→ BO

-0.29

***

-0.85

***

-0.36

***

60.3

0***

0.65

37.6

6***

SHY

→ CO

0.35

***

0.63

***

0.36

***

13.5

0***

0.02

6.26

BO →

0.36

***

0.19

0.58

***

2.42

7.6

***

18.2

3***

BO →

COMT

0.49

***

0.15

0.65

***

10.7

2***

4.93

30.0

4***

BO →

SHR

0.46

***

0.19

0.63

***

7.34

***

5.75

25.1

7***

BO →

NOF

0.48

***

0.1

0.60

***

10.0

6***

2.73

20.2

5***

CO →

0.43

***

-0.47

***

-0.32

***

0.27 1 2.23

CO →

COMT

0.33

***

-0.55

***

-0.25

***

5.90

0.8

11.6

4***

CO →

SHR

-0.36

***

-0.46

***

-0.23

***

0.64 1.79

4.22

CO →

NOF

-0.35

***

-0.51

***

-0.24

***

4.60

1.21

9.17

***

*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.

6 LIMITATIONS AND FUTURE

GUIDELINES

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?

173

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.

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