Journal of Research in Interactive Marketing
Consumer – brand engagement on Facebook: liking and commenting behaviors
Sertan Kabadayi Katherine Price
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Consumer – brand engagement
on Facebook: liking and
commenting behaviors
Sertan Kabadayi
Downloaded by Assumption University of Thailand At 04:01 28 September 2015 (PT)
Department of Marketing, Fordham University, New York,
New York, USA, and
Katherine Price
MediaCom, New York, New York, USA
Consumer –
brand
engagement on
Facebook
203
Received 9 December 2013
Revised 3 March 2014
22 April 2014
Accepted 24 May 2014
Abstract
Purpose – The purpose of this paper is to study factors affecting consumers’ liking and commenting
behavior on Facebook brand pages, and to analyze the mediating role of mode of interaction on
relationships between personality traits and liking/commenting behavior.
Design/methodology/approach – Data were collected using an online national survey from 269
respondents, ages between 18 and 32. The hypotheses were tested using structural equation modeling.
Findings – Results support nine of ten hypotheses with significant relationships between analyzed
constructs. It was found that two different modes of interaction acted as mediators between three
personality traits and liking/commenting behavior on Facebook.
Research limitations/implications – This study only included liking and commenting behavior
on Facebook. Future studies could extend the conceptual model by including sharing behavior and
other personality traits that were not included in this conceptual model.
Practical implications – The findings have several implications for brand managers with respect to
their social media strategies and give them guidance in achieving better customer engagement on
Facebook. This research is an important step in understanding the factors affecting consumers’
Facebook behavior and useful for practitioners intending to use Facebook as part of their marketing
strategy.
Originality/value – The study provides a comprehensive framework to understand consumer
engagement on Facebook by including specific types of Facebook behavior, three personality traits and
two modes of interaction that consumers have in social media.
Keywords Social media marketing, Facebook, Brand management, Consumer behavior, Internet,
Consumer psychology
Paper type Research paper
1. Introduction
Since its emergence, social media, especially social networking sites, have introduced
radically new means of interaction and engagement between consumers and brands.
Consumers increasingly use social media not only to research products and services, but
also to engage with the companies they purchase from, as well as other consumers who
may have valuable insights about these companies (Garretson, 2008). Brands are able to
reach consumers using both their own communications and the communications of
consumers. In this new environment, achieving consumer engagement is critical for
brands to fight against increasing consumer immunity from and skepticism toward
Journal of Research in Interactive
Marketing
Vol. 8 No. 3, 2014
pp. 203-223
© Emerald Group Publishing Limited
2040-7122
DOI 10.1108/JRIM-12-2013-0081
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traditional commercial media (Bagozzi and Dhlokia, 2006). Moreover, this new form of
engagement in social media opens up many new opportunities for brands to extract
value from existing and potential consumers. They can now receive feedback and
suggestions more easily from their consumers through these social networking sites,
allowing them to respond to their consumers, enhance their offerings, handle problems
and provide better service. While this new form of engagement includes a wide range of
activities, specific behaviors such as liking and commenting on brands’ social media
pages have become so popular among consumers that they are now used as measures of
consumer engagement in social media (Gummerus et al., 2012; van Doorn et al., 2010).
Over the past few years, brands have embraced one social networking site, i.e.
Facebook, as a key marketing channel to drive engagement and brand awareness
(Malhotra et al., 2013; Rohm et al., 2013). Facebook brand pages have become a major
channel through which consumers are able to interact with brands in a direct way by
liking and/or commenting on brands’ posts and messages. In fact, these liking and
commenting functions of Facebook enable anyone to respond to a brand post easily.
Thus, one brand post can receive thousands of comments from Facebook users
interacting with the brand and other commenters, providing a platform for dialogue on
social media from which it is easy to solicit information, gain feedback and better
understand the consumer (Malhotra et al., 2013). Therefore, it is not surprising that these
Facebook brand pages and the subsequent engagement they facilitate have become
integral parts of brands’ marketing and public relations campaigns.
Since consumer engagement was recognized as a key research priority of the
Marketing Science Institute (Bolton, 2011, p. 272), there has been an increasing interest
in understanding consumer activity and engagement in social media. However, these
studies have primarily examined the motivations for using or not using social media
(Lorenzo-Romero et al., 2011; Park et al., 2009; Raacke and Bonds-Raacke, 2008; Shao,
2009). While there is no doubt that their findings have been pivotal, such studies have
failed to provide deeper understanding of specific behaviors on social media platforms.
It has been suggested that instead of including overall use, measuring specific activities
and behaviors could be a more thorough way to understand social media use than the
previous research (Ross et al., 2009). Even though liking and commenting are two
common types of behavior on Facebook and are critical for brands’ overall social media
engagement strategies, academic research on this topic has been quite scarce. Given the
popularity of these behaviors, it is imperative to understand the factors that affect
consumers’ liking and commenting behaviors on Facebook, as it may have strategic
managerial implications for brands and their performance.
Although it was postulated that by liking or commenting on a post, consumers
express their own positive self-identity through the brand’s achievements (Malhotra
et al., 2013), the relationship between personality traits and those two types of Facebook
behavior has yet to be empirically tested. Previous studies have shown that personality
can be a highly relevant factor in determining behavior on the Internet and social media
(Amichai-Hamburger, 2002a), and have established three personality traits that affect
digital consumer behavior:
(1) extraversion;
(2) neuroticism; and
(3) openness to experience (Ross et al., 2009; Zywica and Danowski, 2008).
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In this study, we investigate the relationship between these three personality traits and
consumers’ liking and commenting behavior on Facebook. Specifically, we look into
how levels of extraversion, neuroticism and openness to new experiences lead
consumers to like or comment on a brand-related post on Facebook. Furthermore, we
also include in our model, two different modes of interaction that consumers exhibit in
social media as the mediating factors in the relationship between personality traits and
behavior on Facebook (Figure 1). An important component of a brand’s decision to use
social media should be a detailed analysis of how consumers behave on those social
networking sites. We believe that our findings may shed light on understanding the
personality factors that lead consumers to like and comment on Facebook brand pages,
thus helping companies improve the effectiveness of their brand engagement strategies
on social media.
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2. Theoretical development and hypotheses
2.1 Consumer engagement
Consumer engagement can be defined 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, p. 254). It involves consumers’ interactive experiences with brands and enhances
the overall brand value that consumers receive (Brodie et al., 2011). While consumer
engagement is sometimes used to denote the highest form of loyalty (Roberts and
Alpert, 2010), it includes all kinds of behaviors, beyond those that characterize high
levels of loyalty (Libai, 2011).
Some studies have emphasized consumer engagement’s ties back to some of the
major concepts of marketing literature such as the marketing concept and relationship
marketing (Sashi, 2012). For example, consumer engagement, similar to the marketing
concept, focuses on consumers and their needs to engage with them (Brodie et al., 2011).
Both are very consumer-centric approaches that emphasize the understanding of their
needs to create added value for those consumers. However, consumer engagement
Personality
Mode of
Facebook
Traits
Interaction
Behavior
Extraversion
H3a (+)
H3B (-)
H1a (+)
Broadcasting
H4a (-)
Liking
H1b (+)
Neuroticism
H2a (+)
H4b (+)
H5a(+)
Openness to
Experiences
H5b (-)
Communicating
H2b(-)
Commenting
Figure 1.
Conceptual model and
hypothesized
relationships
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expands the traditional role played by consumers, including them in the value-creation
process as co-creators. Consumers help to create value by helping companies
understand their needs, participating in product development and delivery, providing
feedback on products and becoming product advocates (Sashi, 2012). Consumer
engagement also shares some common ground with the relationship marketing concept.
At the heart of relationship marketing lies the establishment of trust and commitment
(Morgan and Hunt, 1994), which are required for any interaction to turn into a
relationship. In the absence of these two components, the relationship is unlikely to
become durable in the long run. Similarly, consumer engagement facilitates the
establishment and maintenance of trust and commitment which drives the consumer to
stay engaged with a brand or company (Sashi, 2012). However, more than that,
consumer engagement itself can be instrumental in building stronger emotional bonds
in relational exchanges and can contribute to the creation of higher levels of trust and
commitment between consumers and companies (Brodie et al., 2011; Sashi, 2012; van
Doorn et al., 2010). Previous empirical findings also suggest that engagement’s presence
improves the quality of consumer – brand relationships by providing higher levels of
relationship satisfaction (Gummerus et al., 2012). Therefore, it is imperative that
companies understand the factors that enable consumer engagement to ensure
high-quality long-term relationships with consumers.
2.2 Social media behavior on Facebook
Brands constantly seek ways to leverage social media as a channel of communication to
reach a large network of consumers. Approximately 83 per cent of Fortune 500
companies use some form of social media to connect and engage with consumers in the
marketplace (Naylor et al., 2012). In fact, consumer engagement has recently emerged as
a topic of great interest to managers in diverse industries and markets that aim to
improve their company performance (Gummerus et al., 2012; Sashi, 2012).
Out of the various social networking sites that enable consumer engagement tactics,
the most heavily used by brands is undoubtedly Facebook. In less than a decade,
Facebook has very much shaped the social media landscape with more than one billion
users, and has become an integral part of the lives of many consumers. From a brand
management perspective, its attraction comes from the fact that Facebook allows
companies to create their own brand page where they can post pictures, links and make
comments to engage their visitors, including current and potential consumers
(Gummerus et al., 2012). In return, consumers respond to these efforts by liking and/or
commenting on those posts and messages. These activities strengthen the bonds that
consumers have with companies by turning them into engaged fans (Wallace et al.,
2012). It is vital for brands to understand this engagement to successfully develop their
social media strategies, and thus achieve their desired outcomes.
Facebook brand pages can engage consumers in various ways, two of which have
been quite popular with the public: liking and commenting. If a company can get
consumers to like its posts, then the brand’s posts will appear on consumers’ profile
pages, ensuring that whatever that brand posts is seen by consumers and their friends
(Wallace et al., 2012). The Like button feature for brands enabled by Facebook has
gained traction among brands from various industries that have seen spikes in Internet
traffic and improve their performance after implementation. For example, IMDB, the
film database, has seen traffic from Facebook double since it installed the Like button
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throughout the site (Gelles, 2010). It has also been suggested that “likes” on Facebook
help companies increase brand awareness and engagement, and thus positively
contributes to their return on investment (Barnard and Knapp, 2011). Moreover, the
value of each consumer that likes a brand on Facebook has increased an average of 28
per cent over past couple of years (PR Newswire, 2013). Those engaged consumers are
not only more likely to research products of the brands that they like, but also more
likely to be satisfied with the brand and to continue using it in the future (Smith, 2013;
Wallace et al., 2012).
Another type of engagement involves getting the consumers to comment on a
brand’s Facebook page. When a consumer comments on a brand’s Facebook post, in
addition to his/her friends on his/her own profile, anyone who views the brand’s post can
also see the comment, even though the consumer does not know those viewers
personally. Commenting behavior allows consumers to share their opinions about or
agreement/disagreement with the content on the brand’s Facebook page, created either
by the brand itself or other visitors.
These two behaviors, liking and commenting, let Facebook users casually signal
their affinity for a brand, item or product and share that with their own personal
network on Facebook (Wallace et al., 2012). Through this functionality, users can lend
their support to a brand and influence their peers solely by liking and/or commenting on
the posts of that brand, without any purposeful influencing activity (Naylor et al., 2012).
While both behaviors take place in a public space, liking can be less visible and
less-exposing to the general public than other types of engagement, as it does not
explicitly state users’ feelings, opinions, thoughts, etc. (Lipsman et al., 2012). When a
consumer likes a brand, his or her name is noted beneath the post, and it appears in the
list of those who also like the same brand, which does not give any other detailed
information about the consumer’s profile or his/her thoughts and feelings about the
brand (Facebook Developers, 2012). It is more about building that personal relationship
between the brand and the consumer, which does not have to be very revealing to the
public, especially to those who are not friends with the consumer on Facebook (Wallace
et al., 2012). On the other hand, commenting is more visible to the public not only by
showing the user’s name and picture next to his/her comment (Facebook Developers,
2012), but also by exposing the consumer’s thoughts about a brand or its posts on a
public display (Gummerus et al., 2012). These comments do not only appear on the
consumer’s friends’ Facebook news feed and sidebars where friends of friends can see
them even though the consumer does not know them directly, but also appear on the
brands’ own profile pages where anyone, including total strangers, can see and read
them (Facebook Developers, 2012). It is no secret that users can change their privacy
settings to prevent total strangers from seeing their comments and profiles. However,
that feature is ignored by millions of Facebook users, as they do not change their privacy
settings often (Palis, 2012). Therefore, those commenting consumers’ feelings, opinions
and emotions toward the brand are easily accessible to anyone who visits that brand’s
page on Facebook. Furthermore, while the users can change their privacy setting to
ensure that the general public will not have access to their comments, that setting only
applies to search engines indexing a preview of users’ own Facebook Timeline. It does
not apply to comments users have made in brand Groups or Pages that are open to
everyone (Facebook Developers, 2012). Therefore, those comments can be seen by
anyone using those search engines, unless they are deleted by the user.
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2.3 Modes of interaction
Social networks can be used to reach well-known existing connections as well as loose
acquaintances or total strangers, depending on the user’s intent. This intent can be
determined through the mode in which the user chooses to interact with others on social
networking sites. The identification of these interaction modes can affect how
consumers behave in social media, holding important implications for our
understanding of consumer engagement on social networking platforms (Zhao et al.,
2008). For that reason, we include consumers’ interaction modes in our conceptual model
as mediator variables in the relationship between personality traits and Facebook
behavior.
Underwood et al. (2011) define two modes of interaction in which social media users
operate. The first is the “broadcasting” mode, which entails a “one-to-many” style of
interaction. In this mode, the users seek to promote themselves to a large network of
people. Broadcasting can be perceived as a more active form of public interaction and
communication style characterized by the individual’s self-projection (Pempek et al.,
2009). People who use this mode are generally concerned with impression management
and engage in interaction for public consumption (Walther, 1996).
The second mode is the “communicating” mode, characterized by a “one-to-one” or
“one-to-few” type of interaction (Underwood et al., 2011). This mode is more private and
generally produces more high-quality interactions with individuals the user already
knows. The communicators are more likely to have anchored relationships. They
interact with individuals who are close to them and prefer to be less visible. They focus
on the maintenance of a strong, close-knit social friend group and have regular
high-quality interactions with smaller online communities (Singla and Richardson,
2008; Skinstad, 2008).
Individuals operating in the broadcasting mode of interaction tend to use every
opportunity in social media to increase their presence and visibility. They prefer to
engage in activities aimed at public consumption to enhance their self-presence and
self-promotion in the public domain (Underwood et al., 2011). This is why they may
engage in both liking and commenting behaviors as opportunities for public
communication and consumption. Given that Facebook can provide them with almost
full control over their behavior and the amount of information that they disclose,
broadcasters can be more strategic in managing their self-presentation using liking and
commenting (Bibby, 2008; Kramer and Winter, 2008). For example, they may like
brands to show their support and affinity for them and share this on their own personal
Facebook pages. Also, they may make comments on these brands’ pages that project
their identity as part of their self-promotion, knowing that their comments will be visible
to the entire brand page and other users (Amiel and Sargent, 2004). They do not mind the
amount of information that they share even with total strangers. In most cases, they are
willing to share personal information, opinions and feelings with others as long as it
contributes to their self-presentation (Kolek and Saunders, 2008; Stutzman, 2006). In
short, both types of Facebook behavior would be ideal for broadcasters to satisfy their
need for self-promotion and one-to-many interaction (Buffardi and Campbell, 2008).
On the other hand, communicators are not very interested in sharing information or
giving their opinions in a public way (Pederson and Macafee, 2007). In fact, they avoid
any form of interaction indicative of self-promotion (Dahlberg, 2001). They focus on
maintenance of a small, strong close-knit social group and engage in one-to-one or
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one-to-few interactions aimed at specific individuals that are known to them
(Underwood et al., 2011). They try to maintain their membership of a group without
being very visible. They emphasize group identity over their personal identity without
sharing too much about what they think or how they feel about things (Zhao et al., 2008).
Communicators avoid commenting behavior that would put their feelings, emotions and
thoughts on public display (Underwood et al., 2011). They know that when they
comment, not only do their comments, accompanied by their names and pictures, appear
in the brands’ Facebook page, but they will also be visible to anyone who visits that
page. This would be too much of a public presence for communicators who prefer more
private and less visible form of interaction with one-to-one or small-group interactions
(Pempek et al., 2009; Underwood et al., 2011). This is why they would feel at ease with
liking behavior, which would give them much less visibility than commenting, as the
former does not post their names and picture on brands’ pages. Thus, we hypothesize
that:
H1. Broadcasting mode is (a) positively related to liking behavior on Facebook, and
(b) positively related to commenting behavior on Facebook.
H2. Communicating mode is (a) positively related to liking behavior on Facebook,
and (b) negatively related to commenting behavior on Facebook.
2.4 Personality traits
As the popularity of the Internet has grown, several scholars have examined the
influence of personality on Internet usage by utilizing the Five-Factor Model, a model
that contains five factors representing personality traits at a broad level (Ehrenberg
et al., 2008; John and Srivastava, 1999). Earlier studies demonstrated the link between
personality and the Internet, providing support for the initial suggestion that the
variance in use of the Internet depended on personality traits. This line of research
determined that various personality traits were significantly related to online activities
in general (Amichai-Hamburger, 2002a; Amichai-Hamburger and Ben-Artzi, 2000).
Following in the footsteps of this research, personality traits were also examined as
potential predictors of the use of social networking sites. In these studies, three of the
five traits turned out to be significant factors: extraversion, neuroticism and openness to
experience (Correa et al., 2010; Ross et al., 2009; Zywica and Danowski, 2008). In this
study, we discuss these three personality traits and investigate how they are related to
the two modes of interaction, which then affect individuals’ liking and commenting
behavior on Facebook.
2.4.1 Extraversion. Extraversion describes a person’s tendency to be sociable and
his/her ability to experience positive emotions (Butt and Phillips, 2008). The extrovert is
a friendly person who seeks company, desires excitement and acts on impulse, whereas
the introvert is a quiet, reflective person who prefers his or her own company and does
not enjoy large social events; he or she does not crave excitement (Amichai-Hamburger
et al., 2002b). The level of extraversion has been found to play a significant role in online
communication experiences (Butt and Phillips, 2008; Kraut et al., 2002). Extraverted
individuals were found to have many connections with others via social networking
sites (Zywica and Danowski, 2008), to belong to more Facebook groups (Ross et al., 2009)
and to take the central and dominant position in friendship networks (Wehrli, 2008).
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The earlier research suggests that while extroverts do not use Facebook as an
alternative to social activities, they still utilize it as a social tool (Ross et al., 2009). This
is consistent with other research which found that extraverts do not use the Internet as
a substitute for real-world interactions (Butt and Phillips, 2008). Instead, they are more
likely to use forms of computer-mediated communications to voice their own opinions,
conduct research and share information with others (Amiel and Sargent, 2004). In terms
of social media use, extroverts generally have more Facebook friends (AmichaiHamburger and Vinitzky, 2010) and belong to more Facebook groups than introverts
(Ross et al., 2009). As many extroverts have a large amount of acquaintances and a large
size of social networks (Ryan and Xenos, 2011), this increases the likelihood that they
will interact with a large audience that would enable their one-to-many interaction mode
on- and off-line. They benefit from any possible Facebook interaction, as Facebook
provides another platform for them to communicate with friends and contacts made
offline (Ong et al., 2011). As extroverts are not afraid of social interaction, they would not
shy away from interacting with people who they do not know personally, and they may
seek the excitement of attention from a larger group of people with whom they are not
close to.
Extraversion can also be linked to self-presentational behavior (Amichai-Hamburger
and Ben-Artzi, 2000) and social identity expressiveness in social media (Pagani et al.,
2013), which are likely to cause their Facebook behavior to be more public. Correa et al.
(2010) found that extraverts were more likely to publicize their activities on Facebook by
making all types of possible contacts. They enjoy the attention that they receive in
one-to-many communication. One-to-one communication would not be enough for their
desire for social interaction. Therefore, high levels of extraversion match
self-presentational motives of broadcasters, and their need for interaction with a large
audience.
On the other hand, level of extraversion was shown to be positively related to the
number of Facebook communication features that they use. Introverts use only a few
features as they fit their needs (Ryan and Xenos, 2011). Furthermore, they prefer to stay
private in their interactions without giving away too much about themselves (Costa and
McCrae, 1992) and generally refraining from sharing their opinions and emotions with
others in the case of an interaction (Pempek et al., 2009). Consequently, introverts may
prefer the mode, which would offer them one-to-one interaction to avoid high levels of
social contact and interaction. They would feel safe knowing that they have limited
amount of social interaction with only those who they personally know and stay away
from large groups of unknown individuals (Wehrli, 2008). Thus, our subsequent
hypotheses are:
H3. Level of extraversion is (a) positively related to the broadcasting mode of
interaction, and (b) negatively related to the communicating mode of interaction.
2.4.2 Neuroticism. Neuroticism reflects a person’s tendency to experience psychological
distress and a high level of sensitivity to threat. The neurotic person is an anxious,
worrisome individual who is overly emotional and reacts to all types of stimuli (Ross
et al., 2009). One of the central measures of neuroticism is lack of emotional stability. It
has been found that those who are high in this trait are likely to use the Internet to avoid
loneliness, limiting their interaction to only those who they personally know (Butt and
Phillips, 2008). Those who are high in neuroticism demonstrate a strong interest in using
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the Internet for communication and interaction, but it is not specified what specific mode
of interaction they prefer (Wolfradt and Doll, 2001). However, the hypothesis that
individuals who scored higher in the trait of neuroticism would be more willing to share
personally identifying information and spend more time on Facebook was not
supported (Ross et al., 2009).
Previous research suggests that neuroticism also plays a role in information control,
such that those high in the trait of neuroticism are more likely to control what
information is shared (Butt and Philips, 2008). People with greater neurotic tendencies
are drawn to certain aspects of social media, especially text-based elements that allow
contemplation before acting (Ehrenberg et al., 2008; Ross et al., 2009). They may not even
like to post their photos in case they inadvertently convey information about their
emotional states or geographical location (Ross et al., 2009). Individuals with high levels
of neuroticism are generally more anxious in social situations, thus they try to keep their
social circles small, mostly composed of people who they know and feel close to (Wehrli,
2008). They usually shy away from communicating with others in large groups, in the
presence of others who they do not know well, especially when this activity would be in
public spaces such as Facebook (Butt and Philips, 2008). Similarly, neurotic individuals
tend to use social media for information-seeking purposes (Seidman, 2013), as opposed
to reaching out to others, so they should be less likely to interact with those people who
they do not know personally. Their high level of public self-consciousness would stop
them from being very visible in public settings (Trapnell and Campbell, 1999). On the
other hand, those high in neuroticism would feel less nervous and less sensitive when
they interact with a small group of people in a more private manner (Costa and McCrae,
1992). Facebook offers a range of privacy settings that users can change based on their
needs and choose the individuals who they want to communicate with (Facebook
Developers, 2012). However, given the ever-changing nature of these control settings
(Hill, 2013), highly neurotic individuals may feel uneasy about interacting with large
groups regardless of how well they know them. This is why one would expect them to be
more likely to demonstrate communicating mode in which they interact only with those
who they know in a one-to-one relationship to avoid loneliness and socialize in small,
more personal circles. Our next hypotheses are:
H4. The level of neuroticism is (a) negatively related to the broadcasting mode of
interaction, and (b) positively related to the communicating mode of interaction.
2.4.3 Openness to experience. Openness to experience represents an individual’s
willingness to consider alternative approaches, be intellectually curious and enjoy
artistic pursuits (McCrae and Costa, 1987). Those who are high on the trait of openness
to experience are more likely to have a wide variety of interests and a willingness to
pursue those interests through unusual means (Butt and Phillips, 2008). This is the
personality factor most likely to be associated with trying out new methods of
communication, or using a social networking site to seek out new and novel experiences
(Ross et al., 2009). Consumers who rank high on this trait also do not mind using more
features from their personal information section with others (Amichai-Hamburger and
Vinetsky, 2010).
In social media, individuals who are open to new experiences would exhibit more
risk-taking social behavior by interacting with a large audience of unknown individuals
to satiate their curiosity (Ross et al., 2009). In fact, higher levels of this trait have been
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shown to be related to online sociability with large groups of individuals, and especially
through Facebook groups (Butt and Phillips, 2008). They report posting more on others’
Facebook walls (Ross et al., 2009) to supplement real-life interactions with many people
by learning more about them and their activities (Carpenter et al., 2011). Individuals with
high openness to experience prefer visibility and popularity over familiarity and
convention (McCrae and Costa, 1987). Therefore, they may choose the one-to-many
interaction mode, as it could introduce them to a diverse group of users whose interests
and stories would provide opportunities for new experiences. As they seek satisfaction
from trying new experiences created by interaction with many people (Ross et al., 2009),
individuals with high levels of this trait would benefit more from broadcasting mode.
Additionally, those who are open to new experiences tend to be more self-disclosing and
enjoy sharing information with others, hoping to stimulate new experiences (Guadagno
et al., 2003). Therefore, familiarity provided by interacting with a small group of known
individuals would not be satisfactory for them (McCrae and Costa, 1997). The limited
excitement of one-to-one interaction with a small group of already known individuals
would not suit those individuals who seek new experiences. Thus, our final hypotheses
are:
H5. The level of openness to experience is (a) positively related to the broadcasting
mode of interaction, and (b) negatively related to the communicating mode of
interaction.
4. Method
4.1 Participants
A total of 269 participants completed our questionnaire distributed through an online
survey tool. The sample was 53 per cent male and 47 per cent female. The participants
were aged between 18 and 32, with an average age of 25.8. This age range is a good fit for
our study, as the individuals in this age cohort, i.e. Generation Y, grew up with the
Internet and have mastered its use for many aspects of their lives, particularly
communication. Ninety per cent of online young adults between ages 18 and 24 use
social networks on a regular basis, and Facebook in particular (Williams et al., 2012).
The individuals in this cohort have a greater tendency to value others’ opinions in social
media and to feel important when they provide feedback about the brands or products
they use.
While social media usage is very common among individuals between ages 18 and
32, we still used a filter to make sure that we reached the right respondents in our
sample. The key factor for inclusion of the participants in this study was having an
active Facebook account and accessing Facebook at least once a week. The respondents
in our sample all had an active Facebook account, and 87 per cent of them either agreed
or strongly agreed that Facebook was a part of their everyday activity. They estimated
that they, on average, checked Facebook 18.3 times per week, and 88.3 per cent of the
respondents used their mobile devices to access Facebook.
4.2 Measures
The 5-point Likert scales anchored by “strongly disagree” and “strongly agree” were
adopted from the previous studies to measure personality traits and modes of
interaction. We measured three personality traits using items based on the
self-administered version of the revised NEO (Neuroticism-Extraversion-Openness)
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Personality Inventory (NEO PI-R form S) (Costa and McCrae, 1992; McCrae, 1992). While
it was designed to measure the five personality dimensions as described by the
Five-Factor Model, we only used the items specific to the three personality dimensions
included in this study, as they most closely relate to social media behavior. Two modes
of interaction were measured by using the items based on Underwood et al. (2011). The
specific scale items for the variables are listed in Table I along with item loadings and
reliabilities.
Two different three-item scales were developed to ask participants about their
Facebook behavior with regard to liking and commenting. The liking items included:
(1) “I enjoy liking brands on Facebook”.
(2) “I regularly like brands on Facebook”.
(3) “Liking brands is something that I do often while on Facebook”.
The commenting items included “I enjoy commenting on brands’ Facebook pages”, “I
regularly comment on brands’ Facebook pages” and “Commenting on brands’ pages is
something that I do often while on Facebook”. The participants were explicitly asked
about brands, not just individuals like celebrities, when they refer to their liking and
commenting behavior. In addition to these measures, we also asked the participants to
report on the number of times they had liked and commented on various brands’
Facebook pages (Pempek et al., 2009; Ross et al., 2009). They had to go back and check
their own Facebook accounts history, and then reported how many brands they had
liked and commented on in past 15 days prior to completing the survey. The average
number of liking was 13.4, ranging from 1 to 25, and the average number of comments
on brands’ Facebook pages was 7.9, ranging from 0 to 18. The high and significantly
positive correlations between self-reported numbers and our measures for both
behaviors (0.92 for liking and 0.90 for commenting, both significant at ⬍ 0.001 level)
gave us confidence about the quality of our measures. Then, as those two behaviors
were central to our model, we also included two 5-point Likert scales (from very
infrequently to very frequently) that measure the frequency of subjects’ liking and
commenting behavior (Gummerus et al., 2012) to further check for the validity of the
other two measures. The results showed high and significant positive correlations
between frequency measures and the other two measures used for liking (0.90 with
three-item Likert scale, p ⬍ 0.001, and 0.92 with self-counting measure, p ⬍ 0.001) and
commenting (0.94 with three-item Likert scale, and 0.91 with self-counting measure, p ⬍
0.001). These results assured us of the quality of our Facebook behavior measures.
We also asked subjects about their perception of liking and commenting behaviors
on Facebook in terms of the visibility and privacy of each behavior. Two semantic
differential scales were used for each behavior, i.e. not visible – highly visible and
private – public as being the anchors. The results indicated that the subjects perceived
commenting behavior as much more visible (Mv ⫽ 4.43) and public (Mp ⫽ 4.29) in
comparison to liking behavior (Mv ⫽ 2.78 and Mp ⫽ 2.36). All differences between
means of both behaviors in terms of both visibility and privacy were significant at 0.001
levels.
We then evaluated the measurement properties of the constructs in a confirmatory
factor analysis using LISREL 8.80 (Joreskog and Sorbom, 2006). The results showed that
all indexes met or exceeded the critical values for acceptable fit (␹2 ⫽ 418.34, df ⫽ 232,
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Table I.
Scale items, reliabilities
and item loadings
Loadings
Extraversion (Cronbach’s ␣ ⫽ 0.88, CR ⫽ 0.89, AVE ⫽ 0.63)
I see myself as someone who is talkative
I see myself as someone who generates a lot of enthusiasm
I see myself as someone who is sometimes shy/inhibited (R)
I see myself as someone who tends to be quiet (R)
I see myself as someone who is reserved (R)
I see myself as someone who has an assertive personality
0.87
0.88
0.79
0.81
0.80
0.89
Neuroticism (Cronbach’s ␣ ⫽ 0.86, CR ⫽ 0.87, AVE ⫽ 0.60)
I see myself as someone who is relaxed/handles stress well
I see myself as someone who is unhappy
I see myself as someone who can be tense
I see myself as someone who worries a lot
I see myself as someone who is emotionally stable/not easily upset (R)
I see myself as someone who remains calm in tense situations (R)
0.85
0.80
0.81
0.88
0.76
0.74
Openness to Experience (Cronbach’s ␣ ⫽ 0.79, CR ⫽ 0.79, AVE ⫽ 0.57)
I see myself as someone who is curious about many different things
I see myself as someone who has an active imagination
I see myself as someone who likes to reflect/play with ideas
I see myself as someone who is inventive
I see myself as someone who has few artistic interests
I see myself as someone who prefers work that is routine
0.77
0.79
0.81
0.82
0.73
0.75
Broadcasting (Cronbach’s ␣ ⫽ 0.76, CR ⫽ 0.78, AVE ⫽ 0.54)
My Facebook activities are aimed at everyone
I do not mind interacting with new people and making new friends on Facebook
When I post something on my Facebook page, I prefer it to be seen by the public
0.73
0.79
0.75
Communicating (Cronbach’s ␣ ⫽ 0.80, CR ⫽ 0.81, AVE ⫽ 0.59)
On Facebook, I only communicate with my friends
I do not like my Facebook activities to be very visible
I use Facebook to strengthen my personal relationships
0.81
0.76
0.79
Liking (Cronbach’s ␣ ⫽ 0.79, CR ⫽ 0.80, AVE ⫽ 0.57)
I enjoy liking brands on Facebook
I regularly like brands on Facebook
Liking brands is something that I do often while on Facebook
0.81
0.78
0.72
Commenting (Cronbach’s ␣ ⫽ 0.77, CR ⫽ 0.78, AVE ⫽ 0.55)
I enjoy commenting on brands’ Facebook pages
I regularly comment on brands Facebook pages
Commenting on brands’ pages is something that I do often while on Facebook
0.77
0.78
0.74
p ⬍ 0.01, comparative fit index [CFI] ⫽ 0.92, goodness-of-fit index [GFI] ⫽ 0.95, root
mean square error of approximation [RMSEA] ⫽ 0.05), suggesting a satisfactory fit for
the measurement model tested. We assessed the convergent validity of the measures by
examining the path coefficients (loadings) for each latent factor to their manifest
indicators. The analysis indicated that all items loaded significantly on their
corresponding latent factors and were higher than 0.5 (Steenkamp and Geykens, 2006).
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Then, we assessed discriminant validity by examining the shared variance between all
possible pairs of constructs in relation to the average variance extracted (AVE) for each
individual construct (Bagozzi and Yi, 1988). As expected, the former was much lower
than the latter. A reliability test was performed for each construct to see if all the
measures demonstrated satisfactory coefficient reliability. All Cronbach alpha scores of
the constructs were above 0.70. Additionally, we calculated composite reliability (CR)
values for each construct; all CR values were above the desirable value of 0.6. Thus, we
concluded that our measures demonstrated adequate convergent validity and reliability
(Table I).
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5. Analysis and results
We tested our hypotheses using a structural equation model with LISREL 8.80 (Joreskog
and Sorbom, 2006). The overall model indices (␹2 ⫽ 502.94, df ⫽ 257, p ⬍ 0.01, CFI ⫽
0.97, GFI ⫽ 0.94, NFI⫽ 0.95, RMSEA ⫽ 0.04) indicated that the proposed model had a
good fit. As seen in Table II, the results provide support to all the hypothesized
relationships, with the exception of H4b.
The results showed that broadcasting mode of interaction was positively related to
both liking (␤ ⫽ 0.397, p ⬍ 0.01) and commenting (␤ ⫽ 0.451, p ⬍ 0.01) behaviors. On the
other hand, the communicating mode of interaction had a positive relationship with
liking behavior (␤ ⫽ 0.329, p ⬍ 0.01) and a negative relationship with commenting
behavior (␤ ⫽ ⫺0.254, p ⬍ 0.05). Thus, H1a, H1b, H2a and H2b were all supported.
Regarding the relationships between personality traits and two modes of interaction,
the results were as follows. Both extraversion and openness to experience were
positively related to broadcasting (␤ ⫽ 0.296, p ⬍ 0.01 for extraversion, and ␤ ⫽ 0.251,
p ⬍ 0.01 for openness to experience). Similarly, both personality traits were found to
have significant negative relationships with communicating mode of interaction (␤ ⫽
⫺0.223, p ⬍ 0.05 for extraversion, and ␤ ⫽ ⫺0.204, p ⬍ 0.05 for openness to experience).
Therefore, these results provided support for H3a, H3b, H5a and H5b. Finally,
neuroticism was found to have a negative relationship with broadcasting (␤ ⫽ ⫺0.237,
p ⬍ 0.05). However, the relationship between neuroticism and communicating turned
out to be positive, yet non-significant (␤ ⫽ 0.108, n.s.). Therefore, while H4a was
supported, there was no support for H4b.
Hypothesis
Path
H1a (⫹)
H1b (⫹)
H2a (⫹)
H2b (⫺)
H3a (⫹)
H3b (⫺)
H4a (⫺)
H4b (⫹)
H5a (⫹)
H5b (⫺)
Broadcasting ¡ liking
Broadcasting ¡ commenting
Communicating ¡ liking
Communicating ¡ commenting
Extraversion ¡ broadcasting
Extraversion ¡ communicating
Neuroticism ¡ broadcasting
Neuroticism ¡ communicating
Openness to experience ¡ broadcasting
Openness to experience ¡ communicating
Standardized path coefficients
t-value
0.397**
0.451**
0.329**
⫺0.254*
0.296**
⫺0.223*
⫺0.237*
0.108n.s.
0.251**
⫺0.204*
5.874
7.358
5.127
⫺4.309
4.672
⫺3.814
⫺3.971
1.342
4.287
3.425
Notes: ** p ⬍ 0.01; * p ⬍ 0.05; n.s. ⫽ Not significant; overall model fit: ␹2 ⫽ 502.94; df ⫽ 257; p ⬍ 0.01;
CFI ⫽ 0.97; GFI ⫽ 0.94; NFI ⫽ 0.95; RMSEA ⫽ 0.04
Table II.
Structural model results
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6. Comparison with an alternative model
To ensure confidence in our theoretical model and results, we followed Bagozzi and Yi
(1988) and tested an alternative model to compare model performance. As previous
studies investigated the direct relationships between personality traits and social media
behavior (Correa et al., 2010; Ross et al., 2009), in the alternative model, we allowed three
personality traits to influence liking and commenting behavior directly. We then
compared our proposed conceptual model with this alternative model using two criteria:
overall fit and percentage of the model’s statistically significant paths (Sultan et al.,
2009). The results showed that added paths in the alternative model did not result in
improvements over our original conceptual model in either of the criteria. First of all,
compared to the original model, the overall fit of the alternative model weakened by
including the additional paths (␹2 ⫽ 502.94, df ⫽ 257 in the original model, ␹2 ⫽ 458.89,
df ⫽ 251 in the alternative model, p ⫽ 0.07, CFI ⫽ 0.83, GFI ⫽ 0.81, NFI⫽ 0.80,
RMSEA ⫽ 0.09). The ␹2 difference, 44.05 (df ⫽ 6), was significant (p ⬍ 0.05), implying
that the structural equivalence between two models was not confirmed. Furthermore,
the alternative model scored a lower percentage of supported hypotheses, 9 of 16 (56 per
cent), as compared to 9 of 10 (90 per cent) for the original conceptual model. Out of the
newly added direct paths between personality traits and two behaviors, only
extraversion to commenting path turned out to be significant (␤ ⫽ 0.226, p ⬍ 0.05). None
of the additional paths was significant. Taken collectively, these results provided
additional support for our conceptual model.
7. Discussion and implications
Customer engagement is essential for the success of brands’ social media strategies.
While previous studies (Gummerus et al., 2012) discussed the effects of engagement in a
Facebook brand community for brand performance in terms of satisfaction and loyalty,
our study focuses on the factors that enable such engagement with consumers. This
article contributes to the literature by shedding light on the relationship between
personality traits and two specific types of consumer engagement with brands on
Facebook, i.e. liking and commenting behavior. Furthermore, this study introduces two
modes of interaction that consumers may have, i.e. broadcasting and communicating, as
the mediating variables in the relationship aforementioned.
The findings in the literature regarding the relationship between personality traits,
the Internet and social media use have been mixed. For example, studies that explored
the relationship between extraversion and different uses of the Internet produced
inconsistent results (Amichai-Hamburger and Ben-Artzi, 2000; Correa et al., 2010). Even
though the same personality traits are used in our study, we hope that by expanding our
conceptual model to include modes of interaction as the mediator variables, our results
provide further clarification of consumers’ engagement behavior on Facebook. For
example, Gummerus et al. (2012) found that social benefits did not act as mediators
between community engagement behavior and loyalty. Based on our findings, we
suggest that this could be related to the fact that consumers may seek different benefits
on Facebook depending on their mode of interaction. Broadcasters might appreciate
social benefits created by the opportunities for one-to-many interaction on brand’s
Facebook page. However, this might not work for communicators at all. Therefore,
brands may need to consider the mode of interaction that their consumers have before
they design the social benefits that they wish to provide to users on social media.
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Our findings suggest that personality traits affect individuals’ mode of interaction
which in turn determines if they like and/or comment on a post in a brand’s Facebook
page. While being aware of the personality traits of Facebook users is important, their
present mode of interaction could be pivotal to get specific consumer engagement with
brands on Facebook as well. Such understanding may have several implications for
brand managers with respect to their social media strategies and help them achieve
better consumer engagement on Facebook. Regarding the mode of interaction –
Facebook behavior relationship, it seems that broadcasters offer better engagement
opportunities for brands, as they are more inclined to like and comment, but
communicators could probably be better targets only to get them to like the content on
brands’ Facebook pages. This implies that managers seeking to improve consumer
engagement for their brands on Facebook would benefit from targeting consumers with
broadcasting mode of interaction, as they are more likely to engage in both liking and
commenting. The brand managers need to remember that they can still get
communicators to like their brands, but those communicators’ commenting behavior
would be limited, if any. However, this does not suggest that they should ignore users
with communicating mode of interaction completely. As the number of likes can be used
by some brands as a metric to assess effectiveness and reach of their posts (Chen, 2012;
Lipsman et al., 2012), increasing that number can be critical. Therefore, in such cases,
targeting those communicators could prove beneficial for those brands’ social media
efforts.
As Facebook profile pages and postings can now be used to predict the personality of
individuals (Ehrenberg, 2013), it is possible to reveal users’ personalities without them
even taking a personality test (Bower, 2010). In fact, it has been suggested that a
Facebook profile can be a more robust method to assess personality than a self-rated test
(see Dobson, 2012 for reporting on various studies). Therefore, these new methods can
enable brands to identify their visitors’ personality traits and categorize them as
broadcasters and communicators using the significant relationships as suggested by
this study. Also, this kind of information obtained from personality assessment using
Facebook behavior could be helpful for brands that plan to use demographics and
psychographics-based segmentation on social media (Shaer, 2013).
Our results indicate that the broadcasters tend to be extraverted, be less neurotic and
have high levels of the openness to experience trait, while the communicators tend to be
introverted and do not seek new experiences. Given the increased likelihood of
broadcasters to engage with brands on Facebook by both liking and commenting
behaviors, brands can design their Facebook posts strategically in a way that invites
and encourages broadcasters. For example, as self-expression and self-promotion in a
very visible and public way are two important motives for broadcasters (Underwood
et al., 2011), brands may consider posting content that would stimulate such motives.
Similarly, brands may choose to have postings that ask for input from their visitors, or
that encourage them to share their opinions and emotions, which are important for
self-presentation needs of broadcasters. Brands may also want to encourage and reward
broadcasters by acknowledging their comments visibly and publicly, which would help
their self-promotion motives. An example would be offering self-promotion
opportunities like contests or having controversial discussion topics on their Facebook
pages, so they can get broadcasters’ attention and make them like and comment on their
own posts. By giving them opportunities to share their opinions on controversial topics
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and posts, brands could satisfy the high level of self-promotional needs of extravert
broadcasters. In a similar way, brands may want to repost some of the individuals’
comments as entries in their main Facebook pages, as it could be an effective way to
publicly praise those individuals and satisfy their self-promotion needs. The importance
of openness to experience for broadcasters may imply changing and updating their
Facebook posts, visuals and messages can help brands get more broadcasters engage on
Facebook as well. Brands also need to be aware of the fact that broadcasters tend to
engage more heavily in commenting than liking behavior, and they exhibit specific
personality traits. Therefore, when they segment their Facebook visitors based on their
comments and use the information and insights obtained from those comments, they
need to remember that the comments may only reflect a group of consumers with a
specific interaction mode and personality traits. Therefore, they should use such
segmentation with caution when they develop their strategies, as they may exclude
individuals operating in the communicating mode of interaction.
Consumer engagement is essential for the success of brands’ social media strategies.
Without active commenters and likers, the success and contribution of social
networking sites to brands’ overall performance would be limited. Therefore, brands
need to find ways to facilitate and encourage such behavior, so their consumers become
more active and engaged to maximize the benefits of social media.
8. Limitations and future research directions
In this study, we only included liking and commenting behaviors as part of consumer
engagement with brands on Facebook. However, the recently introduced “share”
function, which gives the users the opportunity to share posts on their timeline has also
become quite popular among consumers. In fact, now whenever there is a new post on
Facebook, there are three buttons below each post for consumers to choose from: like,
comment and share. Future studies should extend our conceptual model by including
“share” in addition to liking and commenting behaviors and test the relationships
between personality traits, modes of interaction and sharing in the way we tested our
conceptual model. The profile of our respondents fits the overall profile of heavy social
media users. However, given the increasing use of social media by different age cohorts,
future studies may want to test our model with respondents from different age groups to
see if the results will hold. Finally, while we agree with Sashi (2012) that there is a need
for more studies on the nature of consumer engagement in social media, it is also
necessary to understand the effects of heavily discussed engagement behaviors on
brands’ financial performance. For example, in this study, we investigated liking and
commenting behaviors as examples of consumer engagement and presented a model
that included the factors that affect those two types of behaviors. However, it would be
critical and useful for brands to understand if such behavior results in higher likelihood
of purchase of the same brand by the consumers who liked or commented on the brand’s
Facebook page.
Overall, we believe that despite its limitations, this research is an important step in
understanding the motives and factors affecting consumers’ Facebook behavior and
engagement in social media, and it offers useful insights for practitioners intending to
use Facebook as part of their marketing strategy.
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Further reading
Eysenck, S.B.G., Eysenck, H.J. and Barrett, P.A. (1985), “Revised version of the psychoticism
scale”, Personality and Individual Differences, Vol. 6 No. 1, pp. 21-29.
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Consumer –
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Facebook
About the authors
Sertan Kabadayi is an Associate Professor of Marketing at Fordham University’s Schools of
Business. He received his PhD from Baruch College, CUNY. His primary research interests include
multiple distribution channel strategies, Web site loyalty and social media behavior. His work has
been published in journals including Journal of Marketing, Journal of Business Research,
Psychology and Marketing and others. Sertan Kabadayi is the corresponding author and can be
contacted at: Kabadayi@fordham.edu
Katherine Price currently works for MediaCom as an Assistant Media Planner in New York
City. She graduated from Gabelli School of Business at Fordham University in May 2012 with
Honors degree.
223
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