customer brand engagement on online social media
DESCRIPTION
Customer Brand Engagement on online social mediaTRANSCRIPT
Department of Business Administration
Master of Science in Marketing
CUSTOMER BRAND ENGAGEMENT ON ONLINE
SOCIAL MEDIA PLATFORMS
A Conceptual Model and Empirical Analysis
Master Thesis
Author: Justina Malciute
Advisor: Polymeros Chrysochou
Total number of characters: 104,269
Aarhus University
Business and Social Sciences
August 2012
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Abstract
A great interest in the concept of customer engagement has emerged along with the rise of
online social media during the past few years. Marketing practitioners were the first ones
attempting to define and understand the potential outcomes of customer engagement.
However, due to a lack of scholarly interest and empirical support, the nature of customer
engagement has remained rather vague and its presupposed capability to enhance customer
relationships still uncertain. The aim of this study is to bridge this gap by proposing a
conceptual model of customer brand engagement in the context of online social media
platforms and conducting an empirical analysis. Drawing on the overview of academic
literature and the results of a quantitative online consumer study, the paper delivers a
thorough investigation of the concept and offers empirical evidence of its impact on the
ultimate business performance. The most important findings of this study suggest that both
customer brand relationship related factors and online social media platform related factors
can influence the level of customer engagement, which in turn will influence the level of
behavioral loyalty and the spread of word-of-mouth communication. Thus, this paper is an
important contribution to academic marketing literature in the field of customer
engagement, which still remains mostly conceptual or qualitative, and provides useful
managerial insights for marketing practitioners.
Keywords: customer engagement, brands, social media, customer relationships, brand
loyalty, word-of-mouth.
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Table of contents
1. Introduction .................................................................................................................. 1
2. Literature review .......................................................................................................... 3
2.1 Conceptual foundations ....................................................................................... 3
2.2 Engagement conceptualizations in social science and management literature ... 5
2.3 Engagement conceptualizations in the marketing literature ............................... 6
2.4 Conceptual relationships ................................................................................... 10
2.5 Engagement in the online social media context ................................................ 14
2.6 Problem statement ............................................................................................. 16
2.7 A conceptual model of customer brand engagement on online social media
platforms ................................................................................................................. 17
3. Methodology ............................................................................................................... 20
3.1 Data collection .................................................................................................. 20
3.2 Measurement of constructs ............................................................................... 23
3.3 Statistical analysis ............................................................................................. 28
4. Results ........................................................................................................................ 30
4.1 Descriptive analysis .......................................................................................... 30
4.2 Measurement reliability and validity ................................................................ 33
4.3 Model estimation results ................................................................................... 37
4.4 Moderation effects ............................................................................................ 38
5. Discussion and implications ....................................................................................... 41
5.1 Implications for marketing theory ..................................................................... 42
5.2 Managerial implications .................................................................................... 43
5.3 Limitations and future research ......................................................................... 45
6. Conclusion .................................................................................................................. 46
References ...................................................................................................................... 48
Appendix 1: Online Questionnaire ................................................................................. 52
Appendix 2: Top Facebook Pages, Worldwide, Food & Drink Brands ......................... 62
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List of figures
Figure 1. Conceptual model of customer engagement behavior .................................... 14
Figure 2. Conceptual model of customer brand engagement on online social media
platforms ......................................................................................................................... 19
Figure 3: Fan distribution based on engagement level (N1=112) .................................. 31
List of tables
Table 1: Characteristics of the respondents (N1=112, N2=307) .................................... 23
Table 2: Construct measurement items, sources and scale reliabilities .......................... 26
Table 3: Means, standard deviations and results of t-test for equality of means (N1=112,
N2=307) .......................................................................................................................... 31
Table 4: Means, standard deviations and results of t-test for equality of means in
behavioral brand loyalty of high and low engaged fans (N1a=56, N1b=56) ................. 32
Table 5: Reliability and validity measures for first-order latent constructs (N1=112) .. 33
Table 6: Average variance extracted and squared correlations between first-order latent
constructs (N1=112) ....................................................................................................... 35
Table 7: Reliability and validity measures for second-order latent construct of customer
brand relationship related antecedents (N1=112) ........................................................... 36
Table 8: Estimated weights and variance inflation factors for formative dimensions of
second-order latent construct of online social media platform related antecedents
(N1=112) ........................................................................................................................ 36
Table 9: Results and direct effects of the structural path model (N1=112) .................... 37
Table 10: Results of the two-stage PLS approach for estimating moderating effects
(N1=112) ........................................................................................................................ 40
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1. Introduction
“Engage or die” is the new marketing catchphrase, which emerged as a result of the rise of
social media in the past few years (Nelson-Field & Taylor, 2012). The practitioners from
various industries caught on to it and the topic quickly became of great interest. Numerous
business conferences, seminars, discussion forums, blogs, commentaries and white papers
were suddenly talking about the concept of customer engagement, which did not really
exist in the marketing literature before (Brodie, Hollebeek, Jurić, & Ilić, 2011a).
The rules of engagement are new to the marketers and require some major changes in
the conventional marketing thinking. It is no longer a monologue dictated by the firm
through a commercial, print ad or a corporate website. The emergence of new media
provides businesses with an opportunity to start a two-way digital conversation with the
audiences and makes it almost effortless for an individual customer to talk back and also
talk to each other (Deighton & Kornfeld, 2009). The new media channels such as YouTube,
Wikipedia, Facebook, Twitter or MySpace gave a voice to the customers and made it
possible for them to create and easily share their own web content. In other words, each
individual has now the opportunity to become a media producer, an author, a reviewer, or
engage in many other kinds of behaviors that can be consumed by others on the Internet.
Thus, instead of generally being the ones to talk brands have now become the ones mostly
talked about.
The businesses gradually came to realization that they have to change their way of
looking at the customer, and the concept of engagement appeared to be the key to success.
The rationale behind this assertion is the prevailing conception of customer engagement as
a way to create deeper and more lasting customer brand relationships (Kumar et al., 2010).
And even though the traditional media still plays the major role in reaching the customer,
the companies are increasingly using the new social media channels for managing their
customer relationships. Research showed, that social media has emerged as a valuable tool
widely employed by businesses and even 54% of executives of consumer goods companies
participating in a recently conducted survey said that social media was central to their effort
to engage consumers in 2011(WARC, 2012a). Hence, even though no single theory exists
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on how customer engagement on social media works, marketers have been actively
pioneering the field. Almost every brand today has an established profile on the mainstream
social media platforms such as Facebook, Twitter or Google+. Others have also turned to
more novel platforms such as Instagram, Pinterest or Foursquare. There are multiple
different ways and tools that businesses can use in order to engage their customers.
However, despite all the effort the levels of customer engagement resulting on the
platforms of social media suggest that the conventional marketing knowledge lacks the
ability to explain and guide the marketers throughout the process. One recent practitioner
study of the most popular brands on Facebook has discovered that less than 5% of brands
were able to attract repeated fan visits to their page within a 30 day period, meaning that
under one in 20 fans in a month chose to return to the brand page more than once (WARC,
2012b). On the other hand, the proportion of Facebook fans who not only visit the fan page
but also engage with it was found to be even lower. Only 1% of customers observed in
another study were found to actually engage with the brand after initially becoming a fan
on Facebook (Creamer, 2012). Hence, given the entire struggle that businesses are going
through trying to engage their customers, the inevitable question arises – is it worth it?
Some of the biggest brand owners such as Coca-Cola, Unilever and Ford who already
managed to establish a large fan base are still attempting to define the potential return on
investment from using Facebook and expect that it will take at least a couple more years
until the value of fans is established (WARC, 2012c). Thus, the brands are willing to take a
leap of faith building on the core premise of social media paradigm, which suggests that
brands need to engage their customers in order to sustain growth. Yet, the link between the
effects of engagement and business performance remains tenuous and fails to explain the
return in real terms (Nelson-Field & Taylor, 2012). Not surprisingly, the concept of
engagement on social media platforms has also received criticism and is sometimes even
referred to as an air of the early-dot-com hype (Baker, 2009), given that its effectiveness
and consequences to the brand are still largely uncertain.
The buzz of social media along with the dilemma of the newly emerged concept of
customer engagement among the practitioners has also started attracting the interest of
marketing scholars. The Marketing Science Institute has listed customer engagement as one
of the research priorities for the period of 2010-2012 recognizing the lack of conceptual
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frameworks and methods for understanding this concept (MSI, 2010). Hence, making use
of the new media opportunities requires a deeper knowledge of how customers engage with
the different types of media and what it ultimately means for the brand. This study attempts
to develop a conceptual model of customer brand engagement on online social media
platforms by reviewing the existing marketing literature concerning the concept and
subsequently refining it through empirical analysis in order to help marketers better
understand how the process of customer engagement works in this increasingly complex
landscape of social media.
2. Literature review
While the notion of engagement is not new in the literature of various academic disciplines,
it has only emerged in the field of academic marketing relatively recently. Before 2005
there were very few academic articles in the field of marketing which have mentioned the
term “engagement” (Brodie et al., 2011a). Since then the term has gained popularity.
However, despite the significant practitioner interest evolved during the last decade, there
have only been a few systematic scholarly attempts to define the concept, its distinctiveness
from the more traditional relational concepts like participation or involvement, and, finally,
the conceptual roots of customer engagement.
2.1 Conceptual foundations
A few underlying logic perspectives were identified in the academic literature exploring the
conceptual foundations of customer engagement. First of all, Brodie et al. (2011a) suggest
that the theoretical roots of customer engagement can be examined by drawing on the
service-dominant (S-D) logic and the relationship marketing theory. The S-D logic is a
framework that conceptualizes business exchange by addressing service as the main
purpose, and explains how the different network actors (firms, customers and other
stakeholders) can co-create value while interacting with each other (Karpen, Bove, &
Lukas, 2012). The term “service” here is referring to “the process of using one‟s resources
for the benefit of another entity” (Vargo & Lusch, 2008). The logic implies that the co-
creation of superior value is replacing the more traditional notion of value provision,
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meaning that creating superior value in cooperation with the customer becomes a source of
competitive advantage for the firms. To date, a set of 10 foundational S-D logic premises
have been established building on marketing relationships characterized by customers‟
interactive service experience (Vargo & Lusch, 2008):
1. Service is the fundamental basis of exchange.
2. Indirect exchange masks the fundamental basis of exchange.
3. Goods are a distribution mechanism for service provision.
4. Operant resources are the fundamental source of competitive advantage.
5. All economics are service economics.
6. The customer is always a co-creator of value.
7. The enterprise cannot deliver value, but only offer value propositions.
8. A service-centered view is inherently customer oriented and relational.
9. All social and economic actors are resource integrators.
10. Value is always uniquely and phenomenologically determined by the beneficiary.
Four of these underlying S-D logic premises (numbers 6, 8, 9 and 10) have been found
as of particular relevance in explaining the conceptual roots of customer engagement
(Brodie et al., 2011a). Together the four premises imply that value is not something
embedded in the product, but the benefit that the customer gets out of using the product
instead. Thus, the nature of value is highly contextual and subject to experiences (Karpen et
al., 2012). Moreover, value that is realized through market exchange always involves a
combination of resources and, therefore, cannot be created unilaterally, which makes the
customer a co-creator of value (Vargo & Lusch, 2008). Naturally, the interactive nature of
the co-creation process leads to viewing the firm and the customer in a relational context
and, since the benefit is always determined by the customer, it is inherently customer
oriented. Finally, the value is created within the networks where the firms and individuals
are motivated to interact in order to integrate their specialized resources and create more
complex services (Vargo & Lusch, 2008). These four S-D logic premises build a solid
conceptual foundation for the concept of customer engagement. In particular, it is also
suggested that the customer experiences of the co-creative and interactive nature taking
place in complex relational environments may actually be viewed as the act of “engaging”
(Brodie et al., 2011a).
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Another perspective of exploring the conceptual foundations of customer engagement
draws on the so called broadened relationship marketing domain (Brodie et al., 2011a;
Brodie et al., 2011b; Hollebeek, 2011a). Relationship marketing refers to “all marketing
activities directed toward establishing, developing, and maintaining successful relational
exchange” (Morgan & Hunt, 1994), which are critical to the firms in order to build value-
driven interactive long-term relationships with their existing as well as potential customers
and organizational networks and facilitate the processes of value co-creation (Brodie, Ilic,
Juric, & Hollebeek, 2011b).
While the S-D logic and relationship marketing perspectives introduce the notion of the
customer behavior being focused on interactive and co-creative experiences in the complex
relational networks, Hollebeek (2011a) also draws on the social exchange theory to explain
the rationale behind the customers‟ motivation of contributing to the superior value
creation. The social exchange theory functions under the premise that one party will do a
favor to another party because of being motivated by expected future return. Therefore, it
would also suggest that a customer experiencing a benefit from a brand relationship is
expected to respond with positive thoughts, feelings and behaviors (L. Hollebeek, 2011a).
As a result, all three foundational perspectives of customer engagement build on the
interactive nature of exchange between the value creating network actors.
2.2 Engagement conceptualizations in social science and management
literature
The concept of engagement has been used in various disciplines including organizational
behavior, psychology, sociology and political science. Different studies have been
exploring various sub-forms of engagement (e.g. civic engagement, social engagement,
student engagement, engagement of nation states, employee engagement, stakeholder
engagement), which led to a variety of approaches to interpreting the concept (Brodie et al.,
2011a). Literature within organizational behavior describes engagement as physically,
emotionally or cognitively expressed “task behaviors that promote connections to work and
others”, which motivate the employees and encourage personal development (Bowden,
2009). The concept of social engagement in the field of social psychology has been defined
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as “a sense of initiative, involvement and adequate response to social stimuli, participating
in social activities and interacting with others”, whereas student engagement in the field of
educational psychology has been conceptualized as “students‟ academic investment,
motivation and commitment to their institution, their perceived psychological connection,
comfort and sense of belonging towards their institution” (L. D. Hollebeek, 2011b).
An overview of the diversity of engagement conceptualizations across the different
academic disciplines reveals few important observations. First of all, engagement can be
viewed as a process that can be characterized by “specific interactions and/or experiences
between a focal engagement subject (e.g., student; customer) and object (e.g.
course/module; brand, product, or organization, respectively)” (Brodie et al., 2011b).
Second, most of the reviewed conceptualizations present engagement as a multidimensional
concept comprising behavioral (actions), cognitive (thoughts) and emotional (feelings)
dimensions (L. Hollebeek, 2011a). Even though there is still a relatively large number of
researchers, who view engagement from the unidimensional perspective, the focus remains
on the three mentioned dimensions with the behavioral focus being the dominant one
(Brodie et al., 2011a). According to the Oxford Dictionary the verb “to engage” means to
employ or hire, to bind by a contract, to hold fast, and to take part in something (van Doorn
et al., 2010). All these meanings point to the behavioral aspect of engagement, however, the
unidimensional perspective lags behind in expressing the wider scope of the concept
(Brodie et al., 2011a). Furthermore, Hollebeek (2011a) also points out that despite of
looking into engagement from a wide range of disciplines, all the different definitions of
the term reveal favorable expressions towards the concept and its highly interactive nature.
The next section will explore engagement research in the practitioner and academic
marketing literature.
2.3 Engagement conceptualizations in the marketing literature
The exploration of available marketing literature reveals the emergence of several
engagement sub-forms, such as “customer engagement”, “customer engagement
behaviors”, “consumer engagement”, “customer brand engagement” as well as the more
general conceptualizations of simply the “engagement” itself (L. Hollebeek, 2011a).
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Bowden (2009) presents customer engagement as a sequential psychological process
that customers move through to become loyal towards a brand. This process is suggested to
model the mechanisms by which loyalty may be developed and maintained for two
different types of customers – new and existing. Bowden (2009) is also discussing the
distinction between customer engagement and the more traditional marketing constructs
such as involvement, commitment and loyalty. It is in fact suggested that customer
engagement process helps to examine the dynamic relationships between these constructs
and further the understanding of how they drive the development of customer loyalty.
Customer engagement has also been explored as a new perspective in the field of
customer management (Verhoef, Reinartz, & Krafft, 2010). It has been highlighted that the
emerging concept of customer engagement is highly important in the increasingly
networked society. Building on the research of van Doorn et al. (2010), Verhoef et al.
(2010) consider customer engagement as behavioral manifestations towards a focal object
(e.g. a brand or a firm), other than purchase, resulting from motivational drivers. The
concept of customer engagement behaviors implies that van Doorn et al. (2010) are
focusing on the behavioral aspects of the relationship between the customer and the firm.
Some other authors have also suggested that customer engagement includes a continuum of
behaviors ranging from pure voice (complaining, recommendation, word-of-mouth) to pure
exit (reduced or discontinued consumption) (Hirschman, 1970). All the customer
engagement behaviors are proposed to comprise five dimensions: valence (positive or
negative), form and modality, scope (temporal and geographic), nature of impact and,
finally, customer goals. Moreover, van Doorn et al. (2010) establish a conceptual model
suggesting that customer engagement behaviors are affected by customer characteristics,
firm initiatives and the contextual environment. In addition, they also present a number of
consequences that customer engagement behaviors bring to the firm, the society and the
customer itself. Despite the customer management research mostly being focused on the
transactional side of the customer-firm relationship, the non-transactional forms of behavior
have also gained their share of attention recently. Verhoef et al. (2010) acknowledge the
importance of the impact of word-of-mouth and co-creation in particular. It has been
recognized that ignoring the non-transactional behavior manifestations may have
detrimental effects to the firm because of potentially wrong valuation of the customers
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(Kumar et al., 2010). The paper of Kumar et al. (2010) introduces a new metric for
customer valuation, where they include both the value from transactional and the non-
transactional behaviors and, therefore, disagree with the view of van Doorn et al. (2010).
Hollebeek (2011b) presents the concept of customer brand engagement and defines it as
“the level of an individual customer‟s motivational, brand-related and context-dependent
state of mind characterized by specific levels of cognitive, emotional and behavioral
activity in direct brand interactions”, where the focus lies on the interactions between a
specific subject (the customer) and the focal object (brand). The cognitive activity refers to
the level of engrossment or concentration towards a brand, whereas the emotional and
behavioral activities reflect the level of an individual‟s pride or inspiration and the level of
energy expressed while interacting with the brand, respectively (L. D. Hollebeek, 2011b).
Just like Bowden (2009), Hollebeek (2011b) also suggests that customer brand engagement
contributes to developing customer loyalty by focusing on conceptualizing the positively
valenced expressions of customer brand engagement. In her other works Hollebeek (2011a)
further explores the concept of customer brand engagement and, by utilizing qualitative
research methods, identifies the key themes of customer engagement behavior: immersion,
passion and activation. This implies that the level of customer‟s brand-related concentration
(immersion), positive affect (passion) and the level of energy put in particular brand
interactions (activation) together represent just how much the customer is prepared to exert
cognitive, emotional and behavioral investments while interacting with the focal brand (L.
Hollebeek, 2011a).
Mollen and Wilson (2010) elaborate on the concept of engagement from the perspective
of online consumer experience. Building on the findings from e-learning and online
marketing literature, the authors suggest that a consumer‟s experiential response to a
website or some other computer-mediated entity comprises three experiential states
including perceived interactivity, telepresence and engagement. In particular, engagement
is defined as “a cognitive and affective commitment to an active relationship with the brand
as personified by the website or other computer-mediated entities designed to communicate
brand value” and is suggested to comprise the dimensions of active, sustained, cognitive
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processing, attainment of instrumental value (relevance and utility), and experiential value
(emotional congruence) (Mollen & Wilson, 2010).
Another conceptualization addressed in the literature is the “brand engagement in self-
concept” (Sprott, Czellar, & Spangenberg, 2009). The construct suggests that consumers
vary in their tendency to possess brand related schemas, meaning that differences exist in
consumers‟ tendency to engage brands in their self-concepts and, therefore, also in their
brand-related behaviors. Sprott et al. (2009) develop a scale to measure the self-brand
connections in individuals. However, the concept has been criticized for failing to fully
capture the interactive nature of customer engagement (Brodie et al., 2011a).
Engagement has also been conceptualized as a state of sustained attention, which can be
characterized by full absorption and involvement as well as being fully occupied or
engrossed in something (Higgins & Scholer, 2009). Higgins & Scholer (2009) also
recognize that individuals can be engaged on different levels of intensity and suggest that
the more a person is engaged, the more intense will be the experience of the motivational
force. This means that a more engaged individual will experience the positive target more
positively and the negative target more negatively in the pursuit of his goal. Thus, the
authors express considerations towards both positive (e.g. attraction) and negative (e.g.
repulsion) expressions of engagement.
Brodie et al. (2011a) have derived the main themes prominent in the literature
concerning customer engagement and developed a set of five fundamental propositions,
which consequently provide the basis for the suggested general definition:
“Customer engagement (CE) is (1) a psychological state that occurs by virtue of
interactive, co-creative customer experiences with a focal agent/object (e.g. brand) in
focal service relationships. It occurs (2) under a specific set of context-dependent
conditions generating differing CE levels; and (3) exists as a dynamic, iterative process
within service relationships that co-create value. CE plays (4) a central role in a
nomological network governing service relationships in which other relational concepts
(e.g. involvement, loyalty) are antecedents and/or consequences in iterative CE
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processes. It is (5) a multidimensional concept subject to a context- and/or stakeholder-
specific expression of relevant cognitive, emotional and/or behavioral dimensions.”
Unlike most other reviewed conceptualizations, Brodie et al. (2011a) suggested a
definition that can be applicable in a wide range of contexts. Furthermore, a generic
expression of the dimensions (cognitive, emotional and behavioral) comprising the
engagement concept allows for it to encompass any context-specific expressions of the
customer engagement. However, this particular conceptualization has also received
criticism for being too broad and exposing to the danger of confounding the behaviors,
which are potentially caused by engagement, and all other behavioral indications
(Malthouse & Calder, 2011). A comment on Brodie‟s et al. (2011a) conceptualization also
suggests that the interactive and co-creative nature of experiences should not imply that
engagement requires a high level of overt activity. Malthouse & Calder (2011) point out
that engagement can arise not only from active behaviors such as e.g. blogging, but simply
receiving communication can also be viewed as interactive and co-creative, as long as these
experiences are immersive. Finally, Brodie‟s et al. (2011a) definition also addresses the
issue of differentiating customer engagement from other relational concepts and suggests
that they represent the potential antecedents and/or consequences embedded in the iterative
process of service relationships.
2.4 Conceptual relationships
Exploring the newly emerged concept of customer engagement may also lead to a question
whether it could simply be the case of “the old wine in a new bottle” (Bowden, 2009).
However, all the authors researching different sub-forms of engagement (Brodie et al.,
2011a; Hollebeek, 2011a; Mollen & Wilson, 2010; Bowden, 2009) argue that this is not the
case and that there is a clear distinction between engagement and other more familiar
relational concepts.
Mollen & Wilson (2010) suggest that involvement is an important dimension of
engagement and therefore an important relational concept to discuss. Involvement has been
defined as an internal state of arousal, which can be used to reflect an ongoing concern by
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the customer towards a product based on the perceived importance and/or general interest
in the purchase process (Bowden, 2009). Mollen & Wilson (2010) identify three major
differences between engagement and involvement. First of all, the definition of
involvement indicates that it requires a consumption object (e.g. product category). Second,
involvement refers to a more passive allocation of mental resources and unlike engagement
does not encompass an active relationship with the consumption object. Finally,
engagement not only requires the attainment of instrumental value through relevance and
utility, but also a certain degree of emotional bonding, which can be achieved through
pleasant and satisfying experiences.
Besides involvement, Bowden (2009) also compares the customer engagement process
with and delineates the distinction from the concepts of commitment and loyalty.
Commitment often encompasses some sort of psychological attachment, where a customer
views a specific commitment object as the only acceptable choice alternative. Thus,
commitment generally means that unlike in the case of involvement, a customer is not
simply interested in an issue, but rather holds an actual attitudinal position. Loyalty is also
known to comprise an attitudinal element. However, it is most often evaluated in the
behavioral manner, e.g. the intention to repeat a purchase. Commitment and loyalty are
often considered as highly related concepts. Nevertheless, the effects of the two may yield
different behavioral outcomes. It has been discovered that due to attitudinal attachment
brand-committed customers are actually less likely to switch brands than the brand-loyal
customers (Bowden, 2009).
Mollen & Wilson (2010) also discuss the constructs of interactivity, flow and
telepresence in relation to the online brand engagement. However, these are depicted as a
process, where interactivity is assumed to be an antecedent of telepresence, which
consequently is an antecedent of engagement. There is no consensus about the definition of
interactivity in the literature, so the authors propose their own definition, which suggests
that interactivity is an “experiential phenomenon”, which describes to what degree
customers perceive the communication as “two-way, controllable and responsive to their
actions”. The construct of flow is viewed as a cognitive state, which asserts when
individuals are so involved in an activity, that it makes them forget everything else.
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Telepresence is related to flow, however, it extends to a psychological state of being
present in a computer-mediated environment. The process of telepresence is expected to
positively affect both the instrumental and the experiential value and, thus, suggested to be
an antecedent of engagement.
Brodie et al. (2011a) building on one of their fundamental propositions to the concept
of customer engagement also suggest that it is only a part of a broader relationship
structure, where the other concepts play the roles of antecedents and/or consequences.
Apart from some of the constructs mentioned already, Brodie et al. (2011a) also consider
and justify a number of other potential antecedents and/or consequences of customer
engagement, such as participation, rapport, customer satisfaction, trust, self-brand
connection, and emotional attachment. The authors have found some relational constructs
such as involvement and participation to be prerequisite to drive engagement, whereas the
others could act as both potential antecedents and consequences within particular dynamic
service relationships. This point of view is in line with the argument of Bowden (2009)
saying that new and existing brand customers will follow a different engagement process in
developing loyalty.
The iterative nature of the service relationships implies that different concepts will play
different roles in different contexts. For instance, an exploratory analysis investigating
consumer engagement in a virtual brand community has revealed that the consequences of
consumer engagement in that particular case included loyalty, satisfaction, empowerment,
connection, emotional bonding, trust and commitment (Brodie et al., 2011b). Furthermore,
Hollebeek (2011b) has pursued defining the conceptual relationships of customer brand
engagement and identified involvement and interactivity to be the antecedents required
prior to the expression of a relevant customer‟s brand engagement level. Flow has also been
determined to be an antecedent state, whereas the concepts of co-created value, brand
experience, perceived quality, customer value and brand loyalty are suggested to represent
the potential consequences of customer brand engagement. Finally, rapport, customer
satisfaction, trust and commitment could act as both antecedents and/or consequences
depending on whether the customer is new or existing. The concepts of interactivity,
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rapport and value co-creation in particular have been noted as of high relevance in service
contexts and Web 2.01 settings, which can be characterized by human interactive forms.
Van Doorn et al. (2010) introducing the concept of customer engagement behaviors
offer a somewhat different perspective of the potential antecedents and consequences, and
present a useful theoretical framework for research in this area (see Figure 1). As already
mentioned in the previous section, the authors suggest a conceptual model, which examines
different types of motivational drivers and outcomes of customer engagement behaviors.
The antecedents are divided into three major groups and include not only customer-based,
but also firm-based and context-based factors. The model implies that not only customer
related factors, such as attitudes, goals, resources and perceptions, but also the
characteristics of the brand and the firm together with the different aspects of contextual
environment can have just as much impact on customer engagement behaviors. Though,
some of these factors may not necessarily elicit a direct effect. The model also indicates
that the factors can interact with each other and moderate the effect of other particular
factors on customer engagement behaviors. The consequences considered in the model
include the effects on the customer, the firm and other constituents (e.g. the customers of
other products and brands).
To sum up, the literature reviewed explores different sub-forms of engagement and
offers a variety of conceptualizations. Yet, even though the topic has received considerable
attention among the practitioners (Cheung, Lee, & Jin, 2011), the lack of consensus in the
academic literature suggests that the concept of customer engagement is still understood in
a rather unsystematic way.
1 “Web 2.0 is a collection of open-source, interactive and user controlled online applications expanding the
experiences, knowledge and market power of the users as participants in business and social processes.”
(Constantinides & Fountain, 2008)
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2.5 Engagement in the online social media context
Internet is an open, highly cost-effective and far reaching global network, which helps
reducing or even eliminating the barriers of geography and distance (Sawhney, Verona, &
Prandelli, 2005). In the physical world, businesses often face the trade-off between the
Figure 1. Conceptual model of customer engagement behavior
CUSTOMER ENGAGEMENT
BEHAVIOR
Satisfaction
Trust/commitment
Identity
Consumption goals
Resources
Perceived costs/benefits
Competitive factors
P.E.S.T. o Political o Economic/
environmental o Social o Technological
Valence
Form/modality
Scope
Nature of impact
Customer goals
Customer-Based
Context-Based
ANTECEDENTS
Cognitive
Attitudinal
Emotional
Physical/Time
Identity
Financial
Reputational
Regulatory
Competitive
Employee
Product
Consumer welfare
Economic surplus
Social surplus
Regulation
Cross-brand
Cross-customer
CONSEQUENCES
Customer
Firm
Others
Firm-Based
Source: van Doorn et al. (2010)
Brand characteristics
Firm reputation
Firm size/diversification
Firm information usage and processes
Industry
15
richness and the reach of their communication. That is, a rich dialogue with a customer
requires personal interaction and physical proximity, which means that there is only a
limited number of customers that the firm can communicate with in the most effective
manner. Internet, however, allows the firms to overcome these constraints and reach a
much larger number of customers without having to lose on the richness of the
communication too much.
The emergence and rise of new social media channels in the recent years enabled the
customers to increasingly participate in the new forms of customer/firm interaction
processes. Discussion forums, chat rooms, email, bulletin boards, blogs and social networks
are just some of the tools facilitating interactive customer experiences, that may eventually
also foster the development of customer engagement with the specific brands (Brodie et al.,
2011b). Hollebeek (2011b) also recognizes the importance of customer engagement in the
so called Web 2.0 applications, which are designed in a way that enables them to aggregate
the information from their user base in order to expand their content as well as value
(Wilkins, 2007). Some practitioners even refer to customer engagement as the Holy Grail in
the context of online marketing (Mollen & Wilson, 2010). One of the main reasons behind
the suggested importance of the concept lies in the definition of Web 2.0 and the fact that
this kind of setting would not persist without the user-generated content, which in turn
requires users to be engaged in the new media. Not surprisingly, this specific sub-form of
engagement has also gained attention among the researchers. For instance, Cheung et al.
(2011) have initiated a study exploring customer engagement in online social platforms.
The authors of the research-in-progress paper have defined it as “the level of a customer‟s
physical, cognitive, and emotional presence in connections with a particular online social
platform”. The conceptual model developed suggests that customer engagement in an
online social platform is a construct comprising vigor (level of energy and mental
resilience), absorption (level of concentration and engrossment) and dedication (sense of
significance, enthusiasm, inspiration, pride and challenge) towards the online social
platform, which are driven by involvement and social interaction. The consequences
reflected in the model exhibit the authors‟ belief that customer engagement will have a
positive effect on online social platform participation and word-of-mouth communication
about the platform (Cheung et al., 2011). The study by Cheung et al. (2011) is expected to
16
contribute highly to the existing knowledge about social media engagement by providing a
validated measurement scale for customer engagement in online social platforms. However,
the research is still in progress and no results have been published to date. Thus, even
though the new media present a number of significant opportunities and challenges for both
researchers and practitioners (Hennig-Thurau et al., 2010), most of the existing research is
primarily conceptual or qualitative (Cheung et al., 2011).
2.6 Problem statement
Academic literature highlights the importance of approaching the concept of engagement
with consideration to its highly contextual nature, because “engagement, separated from its
(…) context, is a contradiction that ignores deeply embedded understandings about the
purpose and nature of engagement itself” (Vibert & Shields, 2003). Moreover, Brodie et al.
(2011a) suggest that under different circumstances the importance of the cognitive,
emotional, and behavioral customer engagement dimensions may vary. Therefore, it is
likely that customer engagement in different contexts, such as online versus offline
environments, would manifest in different expressions.
The context of online social media has become of great interest to marketing
practitioners as the new social media platforms quickly emerged as valuable tools central to
their effort of customer engagement (WARC, 2012a). Despite the vast popularity of the
concept among businesses, the push of engagement still misses the mark and fails to
explain what it ultimately means to the brand. The behavioral measures of engagement
currently available on online social media platforms such as number of fans, repeated visits
or interactions with the brand page provide little information about the returns to be
expected (Nelson-Field & Taylor, 2012). Hence, the lack of theory-guided empirical studies
in order to better understand customer engagement with brands in the context of online
social media points to a fault line between the practitioners who increasingly pursue the
quest for their “Holy Grail”, and the scholars who yet mostly choose to focus their
empirical research elsewhere.
17
Hence, the main objective of this study is to bridge this gap by conceptualizing
customer brand engagement on online social media platforms and answering two important
research questions:
1. What drives the customer to engage with brands on online social media
platforms?
2. What are the outcomes of such engagement?
Identifying and validating the antecedents and consequences of customer brand
engagement in this particular context is crucial in order to further advance the knowledge in
the area. According to Hollebeek (2011b), the rising practitioner interest in the concept of
customer brand engagement is mostly driven by the expected benefits and its explanatory
and predictive power in customer relationship outcomes, such as loyalty in particular. Since
it is more cost-effective to retain the existing as opposed to winning new customers,
insights into customer brand engagement on online social media platforms may help
businesses to capitalize on enhancing customer relationships, retention and loyalty through
the use of social media.
2.7 A conceptual model of customer brand engagement on online social
media platforms
The five fundamental propositions underlying the general concept of customer engagement
suggested by Brodie et al. (2011a) provide suitable guidelines for framing the investigation
of the nature and role of customer brand engagement on online social media platforms.
These five themes were therefore applied in developing the working definition and building
the conceptual model. The proposed working definition in this study is the following:
The concept of customer brand engagement on online social media platforms is
characterized by interactive customer experiences with the brand. It is a process of
dynamic and iterative nature, which stems from the domains of S-D logic, relationship
marketing and social exchange theory. Customer brand engagement on online social
media platforms is the central element embedded in a broader network of other
relational constructs serving as the antecedents and the consequences. The concept of
18
engagement is multidimensional and comprises the expressions of emotional,
behavioral and cognitive engagement specific to this particular context.
Based on this definition and the findings from the literature review, a conceptual model
of customer brand engagement on online social media platforms was developed (see Figure
2). The framework portrays customer brand engagement on online social media platforms
as the central element embedded in the network of other constructs, which are divided into
two groups of potential antecedents and consequences. In principle, the structure of the
framework relates to van Doorn‟s et al. (2010) conceptual model of customer engagement
behavior. However, instead of considering three types of factors that can affect
engagement, the current model is focused on customer-based antecedents and consequences
only. The customer-based perspective has been chosen, since not only it represents the
inevitable focus of the business, but the consequences of engagement to the customer are
also suggested to have an inherent effect on the ultimate business performance (Kumar et
al., 2010). Furthermore, as suggested in the working definition, the conceptual framework
does not only comprise the behavioral aspect of engagement, but addresses the concept in a
broader sense by including the cognitive and emotional aspects as well.
The group of potential antecedents portrayed in the model includes factors related to
customer brand relationship quality and online social media platforms. The customer brand
relationship quality related factors are further specified as involvement, satisfaction,
commitment and trust. Brodie et al. (2011a) suggest involvement to be a required
antecedent of customer engagement, whereas customer satisfaction, commitment and trust
in relation to the brand represent the potential attitudinal antecedents also proposed by
Bowden (2009) and Hollebeek (2011b). Because of the iterative nature of customer
engagement, all three attitudinal factors have been found to have the potential of acting as
both antecedents and consequences. The role of the factor will vary depending on whether
the customer is new or existing (L. D. Hollebeek, 2011b). The structure of the conceptual
model given in Figure 2, however, implies that it was chosen and built on the premise of
existing customers in particular.
19
Another sub-group of antecedents comprises online social media platform related
factors, such as involvement, participation, telepresence and ease of use. Even though
involvement has already been included to the relationship quality related factors, the latter
case addresses the concept in terms of personal interest and relevance towards online social
media platforms. Participation, according to Brodie et al. (2011a), is another prerequisite
for customer engagement, as it determines customers‟ propensity to participate on online
social media platforms. Furthermore, the concept of telepresence is included in the model,
since Mollen and Wilson (2010) suggest it to be a direct antecedent of online engagement.
Hollebeek (2011b) and Brodie et al. (2011a) also suggested the concept of flow, which is
related to telepresence and could also be considered relevant in this specific context.
However, as no commonly accepted conceptualization or consensus regarding the
operationalization of flow exists in the academic literature (Mollen & Wilson, 2010), it has
been decided to leave the concept out of the model. Finally, ease of use has also been added
BEHAVIORAL
EMOTIONAL
COGNITIVE
CUSTOMER BRAND RELATIONSHIP RELATED
ONLINE SOCIAL MEDIA PLATFORM RELATED
INVOLVEMENT
SATISFACTION
COMMITMENT
TRUST
INVOLVEMENT
PARTICIPATION
TELEPRESENCE
EASE OF USE
CUSTOMER BRAND
ENGAGEMENT ON
ONLINE SOCIAL
MEDIA PLATFORMS
BRAND LOYALTY
WORD-OF-MOUTH
CONSEQUENCES
ANTECEDENTS
Figure 2. Conceptual model of customer brand engagement on online social
media platforms
20
to the model as a potential contextual antecedent referring to the degree to which a
customer perceives using online social media platforms to be free of effort (Davis, 1989).
As for the consequences, two customer-based items were selected – brand loyalty and
word-of-mouth, which here refers to the intention to recommend the brand. Bowden (2009)
addresses customer engagement as the superior predictor of customer loyalty as compared
to other more traditional marketing constructs. On the other hand, Cheung et al. (2011)
suggest that a customer willing to invest physical, cognitive and emotional effort into an
online platform will also have a higher propensity to spread word-of-mouth communication
about it. A customer valuation framework introduced by Kumar et al. (2010) suggests that
the value of customer engagement is comprised of four dimensions: customer purchasing
behavior, customer referral behavior, customer influencer behavior through customers‟
influence on other existing or prospect customers, and finally, customer knowledge
behavior via feedback provided to the firm. Thus, both customer loyalty and word-of-
mouth have established grounds as potential engagement consequences in the literature.
3. Methodology
3.1 Data collection
In order to collect the data and test the proposed model of customer brand engagement
on online social media platforms an online survey was conducted using a convenience
sample of Facebook2 account holders. With 901 million active monthly users Facebook is
currently world‟s largest online social network (Facebook, 2012) and a highly relevant
platform for this study. Among many various online services offered by Facebook, there is
also something called Facebook Pages. Facebook Pages are public profiles meant to
promote brands, products, artists, web sites or organizations. Once registered Facebook
users visit a Page, they are able to 'become fans' by clicking on the 'Like' button. The
owners of the Page can then post informational content, which consequently will appear in
the news feed of their fans. The fans can choose to react to the posts in few different ways
such as „liking‟, commenting or sharing it with their own networks. In other words,
2 www.facebook.com
21
Facebook is a medium that can give any brand a voice and allows it to establish an active
conversation with Facebook users. It has therefore been largely employed by various
brands and used as a tool for customer engagement. According to the statistics, some of the
largest Facebook brands in terms of number of fans belong to food and drinks‟ product
category (FanPageList, 2012), which has also been chosen to be the focus of this study.
Even though one recent paper about Facebook has showed that the degree of fan
engagement with brands from any given category is highly similar (Nelson-Field & Taylor,
2012), it is still important to narrow it down to a single category as to assure that the
antecedents and the consequences of engaging with the brands are more or less
homogeneous.
The data collection procedure comprised two stages - a pilot study to pretest the survey
instrument and a full-scale field study. During the pretest a self-administrated online
questionnaire was created on an online survey tool Qualtrics3 and distributed to a number of
selected web forums. A total of 57 responses were collected. The results of the pilot test
have been used for reviewing and refining the questions. The full-scale questionnaire has
also been launched online and distributed using various web tools such as email, social
networking platforms (e.g. Facebook) as well as various international forums. The
questionnaire comprised a few basic parts. It started out with an introduction to the survey
and a screening question, to make sure that only those, who have a Facebook account,
participate in the survey. Further questions were related to the usage of and perceptions
about Facebook, such as involvement, participation, ease of use and telepresence as well as
three control variables (customer goals, resources and perceived cost/benefit). In order to
get to the next part of the questionnaire the participants had to state whether they are fans of
any of food or drink brands on Facebook, which then allowed to divide the total sample (N)
into two major groups – 1) respondents who are fans of at least one food or drink brands on
Facebook (N1); 2) respondents who are not fans of any food or drink brand on Facebook
(N2). The respondents in the first group were then asked about their engagement with a
certain brand of their choice on Facebook as well as the ongoing relationship with that
brand and future intentions related to loyalty and recommending the brand to others. A list
3 www.qualtrics.com
22
of 15 most popular food and drink product brands at that very moment was provided to the
respondents to choose from. The brand popularity ranks were retrieved from a social media
counter application previously called Famecount4 (see Appendix 2).The respondents also
had an option to enter a brand name of their own liking, in case it was not provided on the
list. Since the respondents in the second group were not fans of any food or drink brands,
they were simply asked to pick a brand from the same list that they liked most (also with
the option of entering a brand name of their own). They were then directed straight to the
questions relating to the customer brand relationship and its outcomes. The final part of the
questionnaire included socio-demographic questions, such as age, gender, country of origin
as well as the usage of other online social media platforms.
The final survey sample (N) contained a total of 419 internet users from all over the
world, who also had an account on Facebook. Almost 27% of those Facebook users have
identified themselves as fans of at least a single Facebook page dedicated to a brand in the
food and drinks‟ product category, meaning that N1=112 and N2=307. The total sample
included respondents from various age groups ranging from teenagers to seniors, with the
largest group consisting of 20-29 year olds (70% of all respondents). A chi-square test was
performed on age and other demographic variables to investigate whether there are
statistically significant differences between the two groups of N1 and N2. Table 1 below
reports demographic characteristics of the two sub-samples along with the results of the
chi-square test.
The findings of the test suggest that there were no statistically significant differences
between the two groups of fans and non-fans with respect to age and gender of the
respondents. However, the use of other online social media platforms and the time spent on
it per day were found to be related to the group of the respondent. In particular, those
respondents who indicated themselves as fans of at least one food and drink brand on
Facebook showed a tendency of using a higher number of various online social media
platforms and were to spend more time on Facebook and other platforms per day.
4 From the 1
st of May 2012 Famecount has changed its name to Starcount. For more information visit
http://www.starcount.com/pages/starcount.
23
Table 1: Characteristics of the respondents (N1=112, N2=307)
Fans
(N1) %
Non-fans
(N2) %
Age X2(7) = 4.43, ρ = 0.729
Younger than 20
20 – 24
25 – 29
30 – 34
35 – 39
40 – 44
45 – 49
50 and older
7
37
33
11
4
4
2
3
4
33
38
15
4
2
1
3
Gender X2(1) = 0.70, ρ = 0.401
Male
Female
58
42
53
47
Use of other online social media platforms X2(4) = 10.51, ρ = 0.033
No other
1-2 others
3-5 others
6-9 others
10 and more others
8
32
35
23
2
9
43
35
12
1
Time spent on online social media platforms per day X2(4) = 15.92, ρ = 0.003
Less than 30 mins
30 mins – 1 hour
1 hour – 2 hours
2 hours – 3 hours
More than 3 hours
12
22
33
16
17
26
25
26
14
8
Time spent on Facebook per day X2(4) = 13.97, ρ = 0.007
Less than 30 mins
30 mins – 1 hour
1 hour – 2 hours
2 hours – 3 hours
More than 3 hours
19
29
27
14
11
36
27
23
9
6
3.2 Measurement of constructs
The survey instrument comprised of 62 items measuring the constructs mentioned in the
model – the antecedents, the consequences, and the customer brand engagement on online
social media platforms itself.
There were two groups of constructs representing the potential antecedents – customer
brand relationship quality related and online social media platform related. The customer
24
brand relationship quality related constructs (involvement, satisfaction, commitment and
trust) have been widely discussed in academic marketing literature and the choice of scales
for these constructs has therefore been based on the findings of previously published
research. Brand involvement has been operationalized via five items measuring an
individual‟s level of interest, importance and personal relevance in relation to the brand
(Beatty & Talpade, 1994). Commitment has been measured with a six item scale valuing an
ongoing relationship between the customer and the brand as well as willingness to make
efforts in order to maintain it (Aaker, Fournier, & Brasel, 2008). The satisfaction scale
included three items focusing on the general performance of the brand (Gustafsson,
Johnson, & Roos, 2005). Finally, the construct of trust has been measured with four items
relating to an individual‟s perceptions and beliefs regarding the safety and security of
interacting with the brand (Chaudhuri & Holbrook, 2001).
The suggested antecedents related to online social media platform were involvement,
participation, ease of use and telepresence. Involvement in online social media platform has
been measured with the same five item scale adapted from the paper by Beatty & Talpade
(1994). The construct of participation in an online social media platform has been
approached as the frequency and the intensity of participation as suggested by van Doorn et
al. (2010), and measured with three self-constructed items. The ease of use scale has been
adapted from a research paper by Davis (1989) and included six items. Even though
telepresence has been discussed in the literature and defined as the psychological state of
“being there” in the computed-mediated environment (Mollen & Wilson, 2010), there is no
actual measuring instrument developed for telepresence in the online social media platform
context yet. Therefore, a set of four relevant items from an originally eight item scale by
Kim & Biocca (1997) meant to measure telepresence in the context of television has been
adapted and used in this survey.
Customer brand engagement on online social media platforms has been split into three
dimensions – behavioral, emotional and cognitive. The emotional and cognitive
engagement scales have been used as suggested by Cheung et al. (2011), where both
constructs are measured with six items each. The behavioral dimension, however, only
included two relevant items of those suggested by Cheung et al. (2011) and has been
25
supplemented with seven other self-constructed items referring to the frequency of the
different forms of behavioral engagement. Nelson-Field & Taylor (2012) suggest that in
social media, and particularly on Facebook, engagement takes the form of all kinds of
direct interaction with the fan page. The inclusion of seven additional Facebook specific
items was also based on this premise. Thus, the self-constructed items refer to the
frequency of various interactions with a particular fan page, such as visiting the page,
noticing, reading, „liking‟, commenting and sharing its contents as well as creating and
posting contents on the fan page yourself. The response format chosen for these seven
items has been a seven point frequency scale (1=”Never”, 2=”Almost never”, 3=”Rarely”,
4=”Sometimes”, 5=”Often”, 6=”Almost all the time”, 7=”All the time”). The response
format used for the rest of the items in the questionnaire was a seven point Likert scale
anchored by 1=”Strongly disagree”, 7=”Strongly agree”.
The consequences of customer brand engagement on online social media platforms
have been measured in terms of behavioral brand loyalty and word-of-mouth. The scale for
behavioral brand loyalty contained two items relating to future purchase intentions
(Chaudhuri & Holbrook, 2001). Word-of-mouth, which can also be defined as the intention
to recommend the brand to others, has been measured with three items suggested by
Zeithaml, Berry & Parasuraman (1996).
In addition to the 62 mentioned items, there were also three control variables included
in the questionnaire and measured by two self-constructed items each. These were goals,
resources, and the perceived cost/benefit of interacting with the brand pages on Facebook
specifically. These control variables have been included in the survey as the literature
suggests that they can also be expected to influence how customers engage with brands
(van Doorn et al., 2010). The two specific goals accounted for in the questionnaire were: 1)
maximizing the consumption benefits (e.g. interacting with the brand on Facebook out of
interest); 2) maximizing the relational benefits (e.g. becoming a member of a brand
community). The resource items referred to the time available for browsing on Facebook
fan pages and the effort that it takes. Finally, the perceived cost/benefit items were focusing
on the respondents‟ perceived levels of enjoyment while browsing on Facebook fan pages
and its value in comparison to the time and effort spent on it. A summary of all the
26
mentioned questionnaire items including the sources of reference and the resulting
Cronbach‟s alpha for each scales are displayed in Table 2 below.
Table 2: Construct measurement items, sources and scale reliabilities
Measure/Source Items Reliability
Antecedents
Customer brand relationship quality related
Involvement
(Beatty & Talpade,
1994)
1.In general I have a strong interest in [BN]5
2.[BN] is very important to me
3.[BN] matters a lot to me
4.I get bored when other people talk to me about [BN]*6
5.[BN] is relevant to me
0.80
Satisfaction
(Gustafsson et al.,
2005)
6.Overall I am satisfied with [BN]
7.[BN] exceeds my expectations
8.The performance of [BN] is very close to the ideal brand
in the product category
0.75
Commitment
(Aaker, Fournier,
& Brasel, 2008)
9.I am very loyal to [BN]
10.I am willing to make small sacrifices in order to keep
using the products of [BN]
11.I would be willing to postpone my purchase if the
products of [BN] were temporarily unavailable
12.I would stick with [BN] even if it would let me down
once or twice
13.I am so happy with [BN] that I no longer feel the need
to watch out for other alternatives
14.I am likely to be using [BN] one year from now
0.84
Trust
(Chaudhuri &
Holbrook,
2001)
15.I trust [BN]
16.I rely on [BN]
17.[BN] is an honest brand
18.[BN] is safe to use
0.81
Online social media platform related
Involvement
(Beatty & Talpade,
1994)
19.In general, I have a strong interest in Facebook
20.Facebook is very important to me
21.Facebook matters a lot to me
22.I get bored when other people talk to me about
Facebook*
23.Facebook is relevant to me
0.83
Participation
(Self-constructed)
24.I consider myself an active user of Facebook
25.I log on to Facebook everyday
26.I spend long periods of time on Facebook
0.82
5 The abbreviation BN stands for brand name, as different respondents have answered the questions with
a different brand name in mind. 6 The items marked with “*” were reverse scored.
27
Ease of use
(Davis, 1989)
27.Learning to use Facebook is/was easy for me
28.It is easy to get Facebook to do what I want it to do
29.It is clear and understandable how to use Facebook
30.Facebook is flexible to interact with
31.It is easy to become skillful at using Facebook
32.In general, I find Facebook easy to use
0.90
Telepresence
(Kim & Biocca,
1997)
While browsing on Facebook..
33… I feel like my mind is in a different world created
by Facebook
34… I forget about the “real world” around me
35… I feel like my mind is more present in the
“Facebook world” than the “real world”
36.After I am done browsing on Facebook, I feel like my
mind comes back to the “real world”
0.89
Customer brand engagement on online social media platforms
Behavioral
(Self-constructed)
(Cheung, Lee, &
Jin, 2011)
How often do you...
37.…visit the Facebook FP7 of [BN]?
38…notice the posts by [BN] in your news feed?
39…read posts by [BN]?
40…‟like‟ posts by [BN]?
41…comment on posts by [BN]?
42…share posts by [BN] with your friends?
43…post on the Facebook FP of [BN] yourself?
0.89
44.I can continue browsing on the Facebook FP of [BN]
for long periods at a time
45.I devote a lot of energy to the Facebook FP of [BN]
Emotional
(Cheung, Lee, &
Jin, 2011)
46.I am enthusiastic about the Facebook FP of [BN]
47.The Facebook FP of [BN] inspires me
48.I find the Facebook FP of [BN] full of meaning and
purpose
49.I am excited when browsing on and interacting with
the Facebook FP of [BN]
50.I am interested in the Facebook FP of [BN]
51.I am proud of being a fan of [BN]
0.89
Cognitive
(Cheung, Lee, &
Jin, 2011)
52.Time flies when I am browsing on the Facebook FP of
[BN]
53.Browsing on the Facebook FP of [BN] is so absorbing
that I forget about everything else
54.I am rarely distracted when browsing on the Facebook
FP of [BN]
55.I am immersed in browsing on and interacting with the
Facebook FP of [BN]
56.My mind is focused when browsing on the Facebook
FP of [BN]
57.I pay a lot of attention to the Facebook FP of [BN]
0.90
7 The abbreviation FP stands for fan page.
28
Consequences
Behavioral brand
loyalty
(Chaudhuri &
Holbrook, 2001)
58.I will buy [BN] the next time I buy food/drinks
59.I intend to keep purchasing [BN]
0.61
Word-of-mouth
(Zeithaml, Berry,
& Parasuraman,
1996)
60.I say positive things about [BN] to other people
61.I often recommend [BN] to others
62.I encourage friends to buy [BN]
0.89
Control variables
Goals
(Self-constructed)
63.I browse on Facebook FPs because I am interested in
the brands
64.I browse on Facebook FPs because I am interested in
being a part of a brand community
0.59
Resources
(Self-constructed)
65.I have enough time to browse on Facebook FPs
66.Browsing on Facebook FPs does not take too much
effort
0.53
Perceived
cost/benefit
(Self-constructed)
67.I enjoy browsing on Facebook FPs
68.I think that browsing on Facebook FPs is not worth the
time and effort*
0.56
The coefficient reliability analysis revealed that all the scales consisting of more than
two items exceeded the recommended Cronbach‟s alpha benchmark of 0.70 (Nunnally,
1978). However, the construct of behavioral brand loyalty measured by two items only has
performed an internal consistency of 0.61, which is considered to be questionable (George
& Mallery, 1999). In addition, the same happened to be the case with the three control
variables that were also operationalized by two items each and did not meet the 0.70
benchmark. However, the nature of the Cronbach‟s alpha dictates that its value is
determined not only by the mean of inter-item correlations, but also depends on the number
of the items in the scale, which implies that the scales with fewer items will generally be
expected to yield lower reliability coefficients. Therefore, the four underperforming two
item scales were not eliminated and used further in the analysis.
3.3 Statistical analysis
The approach applied in the data analysis of this study is called structural equation
modeling, which is a powerful framework for estimating causal models and systems of
simultaneous equations with measurement error. The structural model was established of
seven key constructs: customer brand relationship related antecedents (CBRR), online
29
social media platform related antecedents (OSMPR), behavioral engagement (BEH),
emotional engagement (EMO), cognitive engagement (COG), behavioral brand loyalty
(BBL), and word-of-mouth (WOM).The construct of customer brand engagement on online
social media platforms was split into three dimensions (behavioral, emotional and
cognitive) in order to observe the effects of the two groups of antecedents on each of the
engagement dimensions individually. Also, it was necessary to define which of the
dimensions drive the selected customer consequences – behavioral brand loyalty and word-
of-mouth. Thus, the three facets of behavioral, emotional and cognitive engagement, and
the two potential consequences were modeled as first-order constructs and measured
directly by multiple indicators. On the other hand, the suspected customer brand
relationship related antecedents and the online social media platform related antecedents
were modeled as second-order constructs, which were operationalized by four first-order
dimensions each. That is, involvement (in the brand), trust, commitment and satisfaction
served as indicators of the higher order construct referring to the customer brand
relationship related antecedents, whereas participation, involvement, ease of use and
telepresence were conceptualized as the dimensions of online social media platform related
antecedents.
Based on theoretical considerations and the types of indicators used each construct can
be measured with either a reflective or a formative model. The reflective mode implies that
changes in a construct are expected to be manifested in changes in all of its indicators,
whereas in the formative mode a change in value of an indicator would translate into a
change in the construct, regardless of the value of the other indicators (Henseler, Ringle, &
Sinkovics, 2009). In this model all the first-order constructs as well as the response
constructs relating to customer brand engagement and its consequences were measured
with reflective items. In case of second-order constructs the second level of relationships
from the individual first-order dimensions to the combined construct has to be considered
as well. It was therefore decided that the dimensions of the customer brand relationship
related antecedents would serve as indicators of a reflective measurement model, whereas
in case of the second-order construct of online social media platform related antecedents a
formative model was more adequate.
30
There are two types of statistical techniques for estimating structural equation models –
covariance-based (e.g. LISREL) and variance-based (e.g. PLS) (Henseler et al., 2009). The
method used in this study is PLS (partial least squares) path modeling, which can be viewed
as a combination of principal component and multiple regression analysis. The main
reasons behind choosing PLS relate to the highly favorable features of this technique
(Henseler et al., 2009). PLS allows analyzing highly complex models without making the
estimation problematic even when both formative and reflective measurement models are
employed. Moreover, it can be used with a relatively small sample size and there are no
distributional requirements. In this study only the data collected from respondents who
belonged to the group of fans of at least one food or drink brand on Facebook could be used
for testing the full model, which implies that the sample size equaled N1=112. Given that
the model contained a total of 15 latent constructs (13 first-order constructs and 2 second-
order constructs), a sample of N1=112 was considered to be relatively small. In addition,
some of the observations turned out to be skewed. Therefore, PLS was the more appropriate
technique to apply in this study. Because of its flexible nature PLS path modeling is also
generally suggested to be more adequate for causal modeling applications with no prior
theoretical background. Thus, it goes well with the purposes of this study – developing and
testing a conceptual model of customer brand engagement on online social media
platforms. All data analysis were performed using a predictive analysis software SPSS and
a path modeling software application SmartPLS (Ringle, Wende, & Will, 2005).
4. Results
4.1 Descriptive analysis
Means and standard deviations were calculated for each of the constructs in order to
compare the differences between the two groups of fans and non-fans (Table 3). The
independent samples t-test revealed that the two groups showed significant differences in
several aspects. With regards to customer brand relationship related antecedents, the group
of fans was found to be more involved and expressed more trust in the brands than the non-
fans. On the other hand, no significant differences were discovered in the levels of
31
satisfaction or commitment to the brands. Furthermore, the fans also showed a higher
tendency of involvement, participation and telepresence in Facebook than the non-fans.
Table 3: Means, standard deviations and results of t-test for equality of means
(N1=112, N2=307)
Construct
Fans (N1) Non-fans (N2)
t-value Mean SD Mean SD
Dimensions of customer brand relationship related antecedents
1. Involvement 3.85 1.38 3.09 1.48 4.77***
2. Satisfaction 4.76 1.41 4.75 1.24 0.09
3. Commitment 4.09 1.42 3.94 1.36 1.02
4. Trust 4.66 1.31 4.20 1.35 3.11**
Dimensions of online social media platform related antecedents
5. Involvement 4.05 1.38 3.71 1.48 2.11*
6. Participation 5.31 1.41 4.98 1.62 2.06*
7. Ease of use 5.49 1.04 5.33 1.07 1.37
8. Telepresence 3.06 1.50 2.67 1.42 2.48*
9. Emotional engagement 2.90 1.30 n.a. n.a. n.a.
10. Behavioral engagement 2.54 1.04 n.a. n.a. n.a.
11. Cognitive engagement 2.33 1.19 n.a. n.a. n.a.
12. Behavioral brand loyalty 4.50 1.31 4.22 1.47 1.75
13. Word-of-mouth 4.63 1.55 3.92 1.67 3.93*** Note: n.a. = not applicable; SD = standard deviation; t-values were obtained by performing the
independent samples t-test; *significant at <0.05 level, **significant at <0.01 level, ***significant at
<0.001 level.
Figure 3: Fan distribution based on engagement level (N1=112)
0%
10%
20%
30%
40%
50%
1 2 3 4 5 6 7
Behavioral engagement
Emotional engagement
Cognitive engagement
32
As the non-fans did not have to answer the questions about emotional, behavioral or
cognitive engagement, the data is only available for the group of fans. Inspecting the means
of fan engagement showed that it is mainly concentrated in the lower part of the scale and
ranges from 2.33 to 2.90 on average, with emotional engagement scoring the highest.
Hence, the engagement level with the brand pages on Facebook can be considered
relatively low. Figure 3 illustrates fan distribution in percentage based on engagement level
(on a scale from 1 to 7) for all three dimensions.
Finally, the group of fans showed a significantly higher intention to recommend their
favorite brand than the non-fans. On the other hand, the observed levels of behavioral brand
loyalty were found to be similar for both groups, which would suggest that the fans are no
more likely to be loyal to their brands than the non-fans. However, it must also be taken
into consideration that low levels of engagement will also influence the levels of customer
outcomes to be lower. Hence, the sample of 112 fans was split at the median (2.47) into two
equal sub-groups of low engaged and highly engaged fans, and another t-test was
performed in order to determine whether the two types of fans differ in their behavioral
loyalty to the brand. The test results portrayed in Table 4 reveal that the highly engaged
fans show a significantly higher level of behavioral brand loyalty than those of low
engagement. Thus, it can be concluded that a certain level of engagement has to be
achieved before the level of behavioral brand loyalty increases notably.
Table 4: Means, standard deviations and results of t-test for equality of means in
behavioral brand loyalty of high and low engaged fans (N1a=56, N1b=56)
Construct
Low engaged
(N1a)
Highly engaged
(N1b)
t-value Mean SD Mean SD
Behavioral brand
loyalty 4.23 1.43 4.78 1.13 2.232*
Note: SD = standard deviation; t-values were obtained by performing the independent samples t-
test; *significant at <0.05 level.
33
4.2 Measurement reliability and validity
Before estimating the structural model each construct was assessed for validity and
reliability. As the assessment criteria for reflective and formative measurement models are
different, the analysis of the reflective constructs is presented first (Table 5).
Cronbach‟s alpha is one of the more traditional criteria for determining internal
consistency. However, since this measure has already been introduced and accounted for
previously (Table 2), the analysis proceeds with the coefficient of composite reliability.
Composite reliability is another measure of internal consistency like the previously
mentioned Cronbach‟s alpha. However, unlike Cronbach‟s alpha it takes into account the
differences in the loadings of indicators and is therefore considered to be a better indicator
of the unidimensionality of a block (Henseler et al., 2009). Table 5 reports that, without
exception, all latent variable composite reliabilities exceed the commonly accepted
threshold of 0.7 (Jarvis, MacKenzie, & Podsakoff, 2003) and are higher than 0.8, which
indicates a high internal consistency of the constructs.
Table 5: Reliability and validity measures for first-order latent constructs (N1=112)
Construct No. of
indicators
Item loading
range
Composite
reliability AVE
Dimensions of customer brand relationship related antecedents
1. Involvement 4 0.72 0.92 0.91 0.71
2. Satisfaction 3 0.83 0.88 0.90 0.74
3. Commitment 5 0.77 0.81 0.89 0.63
4. Trust 4 0.70 0.91 0.88 0.66
Dimensions of online social media platform related antecedents
5. Involvement 4 0.85 0.92 0.93 0.77
6. Participation 3 0.82 0.92 0.89 0.74
7. Ease of use 6 0.79 0.88 0.93 0.68
8. Telepresence 4 0.81 0.88 0.92 0.74
9. Emotional engagement 6 0.73 0.88 0.92 0.66
10. Behavioral engagement 8 0.64 0.81 0.91 0.57
11. Cognitive engagement 6 0.73 0.88 0.93 0.69
12. Behavioral brand loyalty 2 0.75 0.92 0.83 0.71
13. Word-of-mouth 3 0.86 0.93 0.93 0.81
34
Item loadings were inspected next. Literature suggests that item loadings on their
respective latent variables should be at least 0.6 and ideally above 0.7 (Chin, 1998a), which
implies that the construct should share more variance with the item than the error term. The
analysis revealed that most of item loadings exceeded the more stringent threshold of 0.7.
One of the items measuring involvement in both online social media and the brand (INV4 –
I get bored when other people talk to me about Facebook/[brand name], reverse scored) had
a construct loading of 0.30 and -0.30 respectively. As the loading values were way below
the accepted threshold and expressed low item reliability, INV4 has been eliminated from
each of the involvement constructs. Other two constructs (commitment and behavioral
engagement) each had an item loading just below 0.6 (COMM6 – I am likely to be using
[brand name] one year from now; BEH2 – I devote a lot of energy to the Facebook fan page
of [brand name]). Even though the loading values of these two items (COMM6 – 0.59 and
BEH2 – 0.58) were rather close to passing the threshold, they were still discarded as it
consequently helped increase the reliability and validity of the two respective constructs.
Table 5 reports the reliability and validity measures after removing the four items.
In order to assess the validity of the constructs two measures were used. Average
variance extracted (AVE) is usually employed as the criterion for convergent validity,
which signifies that a block of indicators is unidimentional and represents the exact same
construct. The requirements for the convergent validity of the constructs were met as all
AVE values exceeded the suggested cut-off threshold of 0.5 (Henseler et al., 2009). The
discriminant validity was inspected by using the Fornell-Larcker criterion (Fornell &
Larcker, 1981), which requires the AVE of each latent construct to be higher than its
highest squared correlation with any other latent construct. This means, that a latent
construct should share more variance with its own measurement indicators, than any other
latent construct. Table 6 below illustrates that the squares of absolute correlation
coefficients between constructs are mostly higher than the respective AVEs. However, the
construct of emotional engagement seems to share slightly more variance with the construct
of cognitive engagement than its own set of indicators. It is therefore inherent that the same
tendency also appears when assessing the discriminant validity on the indicator level, i.e.
inspecting the cross-loadings. However, as the difference between the AVE of emotional
35
engagement and its squared correlation with cognitive engagement is only 0.02 (see Table
6), the discriminant validity of the construct was still deemed acceptable.
Validation of the second-order constructs should follow the exact same assessment
process (Chin, 1998a). The first second-order construct CBRR (customer brand relationship
related antecedents) is modeled in the reflective mode. Therefore, both the reliability and
the validity of the construct have to be evaluated. The construct of CBRR was deemed
satisfactory by the previously discussed conventional standards. Table 7 below reports the
parameters of the composite reliability and AVE as well as the loadings of the first-order
latent constructs on the CBRR construct. The thresholds for reliability and validity are met
as the composite reliability is equal to 0.95, the AVE exceeds 0.5 and the component
loadings range from 0.85 to 0.93 (all significant).
Table 6: Average variance extracted and squared correlations between first-order
latent constructs (N1=112)
1 2 3 4 5 6 7 8 9 10 11 12 13
Dimensions of customer brand relationship related antecedents
1. Involvement 0,71
2. Satisfaction 0,39 0,74
3. Commitment 0,58 0,54 0,63
4. Trust 0,39 0,70 0,46 0,66
Dimensions of online social media platform related antecedents
5. Involvement 0,00 0,01 0,01 0,01 0,77
6. Participation 0,00 0,00 0,00 0,00 0,33 0,74
7. Ease of use 0,00 0,03 0,00 0,01 0,17 0,32 0,67
8. Telepresence 0,02 0,00 0,01 0,00 0,14 0,03 0,02 0,74
9. Emotional
engagement 0,20 0,11 0,12 0,15 0,05 0,01 0,00 0,06 0,66
10. Behavioral
engagement 0,17 0,08 0,13 0,07 0,06 0,02 0,01 0,07 0,58 0,57
11. Cognitive
engagement 0,17 0,04 0,12 0,06 0,05 0,00 0,00 0,09 0,68 0,53 0,69
12. Behavioral
brand loyalty 0,42 0,26 0,44 0,28 0,00 0,00 0,01 0,01 0,08 0,13 0,06 0,71
13. Word-of-
mouth 0,45 0,49 0,48 0,37 0,01 0,02 0,02 0,00 0,06 0,04 0,02 0,28 0,81
Note: Numbers in bold denote the values of average variance extracted
36
Table 7: Reliability and validity measures for second-order latent construct of
customer brand relationship related antecedents (N1=112)
Construct Indicators Indicator
loadings
Composite
reliability AVE
Customer brand relationship
related antecedents
Commitment
Involvement
Satisfaction
Trust
0.90*
0.86*
0.87*
0.88*
0.95 0.52
Note: * Significant at <0.001level.
When assessing the formative measurement models, the same concepts of validation no
longer apply as the assumption of error-free measures eliminates the issue of reliability all
together (Henseler et al., 2009). The criteria used for the formative indicators are therefore
focused on validity (Diamantopoulos, Riefler, & Roth, 2008).
At the indicator level, each of the four OSMPR (online social media platform related
antecedents) dimensions was checked for the weight and significance of the delivered
contributions to the formative index. Table 8 presents the indicator weights and their
significance estimated by means of bootstrapping. All indicators were found to have a
significant impact on the OSMPR construct.
Table 8: Estimated weights and variance inflation factors for formative dimensions of
second-order latent construct of online social media platform related antecedents
(N1=112)
Construct Indicators Weight t-value VIF range
Online social media platform
related antecedents
Ease of use
Involvement
Participation
Telepresence
0.43**
0.41**
0.25**
0.26*
4.76
8.13
7.95
2.56
1.11 1.57
1.02 1.45
1.11 1.28
1.45 1.98 Note: *Significant at <0.05 level, **significant at <0.001 level. The VIF values were calculated by
regressing each of the indicators on the other three.
The next step in validating the formative indicators is to assess the degree of
multicollinearity by calculating the variance inflation factor (VIF) (Henseler et al., 2009). A
rule of thumb is that any VIF greater than one shows a presence of multicollinearity.
However, only a VIF value above ten indicates a critical level of multicollinearity, which is
already harmful. In the case of OSMPR indicators all VIF values ranged from 1.02 to 1.98
37
(Table 8), meaning that the information of the indicators was not redundant and, therefore,
each of them contributes to the formative index. Finally, as the outer model was assessed to
be valid and reliable, the estimation of the inner path model was performed next.
4.3 Model estimation results
In PLS path modeling the main criteria used to assess the structural model‟s fit are the
estimates of path coefficients, the determination coefficients (R2) of endogenous latent
variables and the evaluation of predictor effects. The following analysis will therefore be
focused on these three criteria.
Table 9: Results and direct effects of the structural path model (N1=112)
Criterion Predictors Path t-value f2 R
2
Behavioral
engagement
Customer brand relationship
related antecedents
0.38 4.81*** 0.17 0.20
Online social media
platform related antecedents
0.21 1.83 0.05
Cognitive
engagement
Customer brand relationship
related antecedents
0.35 4.11*** 0.14 0.14
Online social media
platform related antecedents
0.11 0.77 0.01
Emotional
engagement
Customer brand relationship
related antecedents
0.43 5.76*** 0.23 0.22
Online social media
platform related antecedents
0.15 1.40 0.04
Behavioral
brand loyalty
Behavioral engagement 0.40 3.20** 0.07 0.14
Cognitive engagement -0.08 0.38 0.00
Emotional engagement 0.04 0.20 0.00
Word-of-
mouth
Behavioral engagement 0.12 0.59 0.01 0.09
Cognitive engagement -0.26 1.41 0.03
Emotional engagement 0.38 2.24* 0.04
Note: *Significant at <0.05 level, **significant at <0.01 level, ***significant at <0.001 level; the effect size f2
is calculated as the relationship of the determination coefficients when including or excluding each of the
predictors from the structural model, i.e. f2= (R
2included-R
2excluded)/(1-R
2included).
The relationships between the latent exogenous and endogenous variables were
assessed first. The t-values and the significance of the structural coefficients were
computed for each path by means of a bootstrapping procedure using 500 subsamples as
recommended by Chin (1998b). Inspection of the paths revealed that not all the
relationships in the inner model turned out statistically significant (see Table 9). Online
38
social media platform related antecedents have shown no significant direct effect on either
of the three engagement dimensions. However, customer brand relationship related
antecedents were found to have a strong effect on each of the three dimensions – behavioral
engagement (0.38), cognitive engagement (0.35) and emotional engagement (0.43). Yet,
only two of the paths connecting the behavioral, cognitive and emotional engagement with
their expected outcomes turned out to be significant. That is, a strong and positive
relationship was found between the behavioral engagement and the behavioral brand
loyalty (0.40), and between the emotional engagement and word-of-mouth (0.38).
The size of the predictor effect (f2) was also assessed for each of the paths. The effect
size determines the relevance of each predictor in a latent endogenous variable. The f2
values of 0.02, 0.15 and 0.35 can be classified as weak, medium and large, respectively
(Cohen, 1988). The values provided in Table 9 above show that all of the insignificant
predictors were found to have a weak effect on their latent endogenous variables. Customer
brand relationship related antecedents turned out to have a medium influence on the
behavioral and cognitive engagement. However, it had a more prominent effect on
emotional engagement. On the other hand, the significant predictor effects on behavioral
brand loyalty and word-of-mouth were found to be relatively weak.
Table 9 also provides the R2 values for endogenous latent variables, which determine
the explanatory power of the underlying models. The suggested classification for the R2
values of 0.67, 0.33 and 0.19 is substantial, moderate and weak, respectively (Chin, 1998b).
When referring to the endogenous latent variables in this model, the low R2 values ranging
from 0.09 to 0.22 would seem to suggest that the model is relatively weak in explaining the
constructs. However, given the early stage of research in this field, where little is known
about the variables observed, this result provides some useful insights and is, therefore,
considered acceptable.
4.4 Moderation effects
In addition to the direct effects assessed in the structural model, an analysis of potential
moderating effects was performed. The measurement instrument included three control
39
variables relating to the usage of and attitudinal perceptions about Facebook fan pages:
goals, resources and perceived cost/benefit. According to van Doorn et al. (2010), these
three factors are potential antecedents of customer engagement behaviors. However, as no
further support was found in alternative sources of academic literature, the three factors
were not included in the main model. Yet, it is possible, that the goals of browsing on
Facebook fan pages along with the time available, the effort that it takes, and the perceived
cost and benefit could moderate the effect of the online social media platform related
antecedents. That is, the effect of telepresence, involvement, ease of use and participation
in the online social media platform on customer engagement may vary with the level of
perceived cost/benefit, existing resources or goals. Therefore, the tests for the potential
moderating effects between the online social media platform related antecedents and the
three control variables were performed on each of the engagement dimensions.
Since the construct of online social media platform related antecedents was formative,
a two-stage PLS procedure recommended by Henseler et al. (2009) for estimating
moderating effects was applied. In the first stage, the main effects PLS model including a
predictor, a moderator and a latent endogenous variable was run in order to obtain the
estimates for latent variable scores. The latent variables scores were then saved and
subsequently used in the second stage. In the second stage an interaction term was created
between the predictor and the moderator using the latent variable scores, and used in a
linear multiple regression as the independent variable together with the latent variable
scores of the predictor and the moderator alone on the endogenous latent variable scores as
the dependent variable. The existence of a moderation effect is determined by a significant
path coefficient (or regression coefficient in this case) of the interaction term regardless of
the values of path coefficients between the predictor or the moderator and the dependent
variable. After identifying the significant moderation effects, the next step in the analysis is
to assess their strength (Henseler & Fassott, 2010).
A total of nine moderation effects were tested between each of the three control
variables and the online social media platform related antecedents on behavioral, cognitive
and emotional engagement dimensions. Out of nine potential moderation effects, five
interaction terms turned out to be significant (see Table 10). The perceived cost/benefit
40
(AVE = 0.68, composite reliability = 0.80, item loadings of 0.96 and 0.66) was found to
moderate the effect of online social media platform related antecedents on cognitive
engagement. The goals (AVE = 0.69, composite reliability = 0.82, item loadings of 0.79
and 0.87) turned out to have a moderating effect regarding the behavioral engagement.
And, finally, resources (AVE = 0.67, composite reliability = 0.80, item loadings of 0.77 and
0.86) were found to moderate the effect of online social media platform related antecedents
on all three engagement dimensions.
Table 10: Results of the two-stage PLS approach for estimating moderating effects
(N1=112)
DV IVs β t-value R2
f2 of the interaction
term
Behavioral
engagement
OSMPR 0.14 1.41 0.15
0.02
BEN 0.31 3.21**
OSMPR x BEN 0.14 1.60
OSMPR 0.14 1.47 0.19
0.05
GOAL 0.33 3.49**
OSMPR x GOAL 0.17 2.02*
OSMPR 0.20 2.21* 0.19
0.12
RES 0.21 2.38*
OSMPR x RES 0.28 3.53**
Cognitive
engagement
OSMPR 0.03 0.29 0.16
0.06
BEN 0.35 3.58**
OSMPR x BEN 0.21 2.30*
OSMPR 0.03 0.31 0.11
0.01
GOAL 0.30 3.06**
OSMPR x GOAL 0.11 1.33
OSMPR 0.08 0.86 0.10
0.07
RES 0.19 1.98*
OSMPR x RES 0.23 2.67**
Emotional
engagement
OSMPR 0.07 0.76 0.15
0.02
BEN 0.34 3.54**
OSMPR x BEN 0.15 1.68
OSMPR 0.04 0.47 0.16
0.00
GOAL 0.38 4.00***
OSMPR x GOAL -0.01 -0.01
OSMPR 0.14 1.53 0.17
0.08 RES 0.27 3.01**
OSMPR x RES 0.23 2.92**
Note: DV = dependent variable, IV = independent variable, OSMPR = Online social media platform related
antecedents, BEN = Perceived cost/benefit, GOAL = Goals, RES = Resources; *significant at <0.05 level,
**significant at <0.01 level, ***significant at <0.001 level.
41
These results imply that the positive effect of online social media platform related
antecedents on behavioral, cognitive and emotional engagement increases as the level of
resources available to browse on Facebook fan pages increases. Moreover, an increase in
perceived benefit of browsing on Facebook fan pages will increase the effect of online
social media platform related antecedents on cognitive engagement. Whereas an increase in
levels of interest in the brand or the desire to become a part of a brand community when
browsing on Facebook fan pages will result in increased effect of the online social media
platform related antecedents on behavioral engagement. Yet, the inspection of R2
values
and, especially, the effect size of the interaction terms on the engagement dimensions
reveals that most of the moderations are weak in explaining the latent endogenous variable
and have a rather small effect size, except for the interaction term between online social
media platform related antecedents and resources on behavioral engagement, which is
closer to being classified as a medium effect.
Hence, even though the online social media platform related antecedents did not have a
significant direct effect on customer brand engagement in this particular context, their
effect was found to be moderated by attitudinal customer perceptions towards the Facebook
fan pages in terms of goals and benefits of using them as well as availability of time and
necessary effort.
5. Discussion and implications
The main purpose of this study was to fill a widening gap between the practitioner and
academic interests in the newly emerged concept of customer engagement. Due to a lack of
agreement in conceptualization and the support of empirical evidence in the academic
literature, the nature of customer engagement has remained rather vague and its
presupposed effectiveness on customer outcomes uncertain. This paper contributes to the
field of customer engagement by presenting a conceptual model of customer brand
engagement on online social media platforms and confirming it through empirical analysis.
Hence, the findings of the study demonstrate how customer engagement is formed in this
particular context and what outcomes are to be expected, which present important
implications for both marketing theory and practice.
42
5.1 Implications for marketing theory
The potential consequences mentioned in the academic literature mostly suggest that
customer engagement should lead to an improved customer brand relationship and,
therefore, increased brand loyalty and intention to recommend (Brodie et al., 2011a). The
results of this research provide empirical support for this claim and show that there is in
fact a relationship between customer brand engagement on online social media platforms
and the two selected consequences – behavioral brand loyalty and word-of-mouth. In
particular, behavioral engagement referring to the frequency and span of various forms of
interactions with the Facebook fan page of a brand will lead to the development of
behavioral brand loyalty, whereas the level and valence of emotional engagement will
influence the intention to recommend the brand. However, it must be noted that, as Table 4
revealed, the fans were no more likely to be loyal to their brands than the non-fans, unless a
certain engagement level is achieved. These findings imply that even though there is a
connection between behavioral engagement and behavioral brand loyalty, low levels of fan
engagement will not have a visible effect on the loyalty of fans. Nevertheless, the analysis
has also showed that even rare customer interactions with the brand on an online social
media platform can already be expected to influence a significant increase in behavioral
brand loyalty. Even though the fans and non-fans were found to differ significantly in their
propensity to spread word-of-mouth communication about the brand, the same requirement
of minimum level of emotional engagement is also expected to apply. The fact that it did
not show up in the analysis could be attributed to the difference in the observed levels of
the two engagement facets. That is, on average the level of emotional engagement (2.90)
turned out to be higher than the average level behavioral engagement (2.54).
The available sources of literature mainly refer to customer brand relationship related
constructs as the potential antecedents and even consequences embedded in the broader
nomological network of customer engagement (Brodie et al., 2011a; Hollebeek, 2011b;
Bowden 2009). Yet, van Doorn et al. (2010) suggested that there is a wider array of factors
involved in the formation of customer engagement behaviors. The results of this research
concur with van Doorn‟s et al. (2010) point of view and add to it by providing empirical
evidence. Customer brand relationship related antecedents (commitment, involvement,
43
satisfaction and trust) were all together found to have significant direct effects on all three
engagement dimensions, which imply that they all are valid predictors of customer brand
engagement on online social media platforms. However, the results given in Table 9
suggest that the larger portion of variance in the engagement levels will remain unexplained
if measured by customer brand relationship related constructs only. This outcome can be
explained by the highly contextual nature of customer engagement (Vibert & Shields,
2003), which implies that the context specific factors will influence the engagement itself.
Thus, it is merely inherent that online social media platform related antecedents would play
an important role in the formation of customer brand engagement in this specific context.
Even though the suggested online social media platform related antecedents such as ease of
use, involvement, telepresence and participation were not significant in affecting customer
brand engagement directly, their effect was found to be moderated by three contextual
factors concerning the goals, resources and perceived cost/benefit of browsing on Facebook
fan pages specifically. As a result, variation in available resources such as time and effort to
engage with brands on Facebook influences the effect of online social media platform
related antecedents on all three facets of engagement, whereas the level of perceived
cost/benefit and the prevailing goals moderate the effects on cognitive and behavioral
engagement, respectively.
Finally, the above mentioned findings helped refining and validating the
multidimensional concept of customer brand engagement in the context of online social
media platforms. Both customer brand relationship related and online social media platform
related factors were found to influence all three dimensions of customer engagement.
However, only two of them - behavioral and emotional engagement - turned out to be
critical in order to achieve the desired customer outcomes such as behavioral brand loyalty
and intention to recommend.
5.2 Managerial implications
Even without a sound theoretical foundation the concept of customer engagement is already
being considered an important component of a successful social media marketing strategy
among the practitioners with a common belief that it leads to an increased business
44
performance (Nelson-Field & Taylor, 2012). However, the low levels of engagement
observed in this study show that businesses still lack the knowledge and skill to achieve a
substantial level of customer engagement. The conceptualization of customer brand
engagement on online social media platforms presented in this paper provides the managers
with a better understanding of the newly emerged concept and delivers empirical evidence
of the potential returns.
First of all, the findings of this research allow drawing a line and defining the main
differences between the two groups of customers - fans and non-fans. The knowledge of the
fan base on social media platforms will allow marketers setting more realistic goals and
targeting the communication better. Facebook users who engage with fan pages dedicated
to brands are more trusting and involved in the relationship with a brand. They are also
more involved, telepresent and participate on Facebook and other online social media
platforms more actively. Second, even if they are heavy users of online social media, the
final decision to engage with Facebook fan pages will depend on the perceived level of
benefit, available resources and goals. Thus, the managers need to realize that a Facebook
user who decides to become a fan of a brand is driven by certain goals and expectations.
The task of the marketers is therefore to fulfill these expectations and respond accordingly.
Based on the findings of this research, businesses should especially focus on engaging the
customer emotionally and behaviorally, which means that the communication transmitted
through online social media platforms should excel in emotional appeal and encourage
various forms of interaction with the brand. Yet, it will be more effective if the
communication can be perceived purposeful, valuable and not too complicated to respond
to. Even though this study was focused on Facebook fan pages, the group of fans was
found to use and spend time on other online social media platforms as well. The managers
should therefore consider integrating their social media effort on different platforms as it
will provide the brand with increased exposure and, therefore, even more ways to interact
with and engage the customer.
Finally, literature suggests that engaged customers can lead businesses to their ultimate
objective – increased sales (Kumar et al., 2010). The rationale behind this assertion is that
engaged customers are highly important for successful viral marketing as they are more
45
likely to influence other existing and prospect customers by providing referrals and
recommendations, which in turn will help businesses to acquire new and retain existing
customers. The results of this study support this statement and present empirical evidence
that customer engagement will lead to an enhanced business performance. Even if it may
not be visible at first, increasing the levels of customer engagement will also gradually lead
to a significant increase in behavioral brand loyalty and the intention to recommend the
brand.
5.3 Limitations and future research
There are also some limitations that have to be considered in relation to this study. First of
all, because of the early stage of research in this area, the conclusions should be made with
cautiousness. The empirical model cannot be generalized and requires further testing in
alternative settings. Although it has been found that overall engagement levels are not
affected by popularity, category or type of the brand (Nelson-Field & Taylor, 2012), some
differences with regards to the antecedents, the consequences or the importance of the three
engagement dimensions could be expected. Second, the conceptual model only included
two potential consequences, assuming that it concerned existing customers only. The
iterative nature of the customer engagement process makes it too difficult to test all
suggested outcomes. However, future studies could consider applying this model and
defining the antecedents and the consequences of engagement for the segment of new
customers as well. Furthermore, even though the coefficients of determination yielded by
the analysis were rather weak, given the nature of this research they were still considered
acceptable. Nevertheless, the findings imply that the model is not capable of explaining a
large portion of variance in the levels of engagement and the consequences. Future studies
should therefore attempt to capture the missing parts of the model and identify what other
factors are also involved in the process of customer brand engagement in the context of
online social media platforms. Finally, most of the available customer engagement studies
take the case of Facebook and, as a result, little is known whether the results can be
generalized and applied to other online social media platforms. Thus, future research should
also consider applying the model in alternative social media contexts.
46
6. Conclusion
This study was an attempt to introduce and investigate the newly emerged concept of
customer brand engagement in the context of online social media platforms. With the
diminishing role of traditional media and the evolution of Internet technologies the rules of
the marketing game have changed. As a result, customer engagement was brought to the
attention of the marketers as a way to improve customer brand relationships and therefore
gain competitive advantage in the new era of social media.
The concept and its roots were introduced by reviewing the existing academic literature.
While the notion of engagement was not new in other disciplines, it has only emerged in
the field of marketing in the past few years. Building on various conceptualizations adapted
from other academic disciplines, it has been concluded that the concept of customer brand
engagement on online social media platforms is characterized by interactive customer
experiences with the brand. It is a process of dynamic and iterative nature, which stems
from S-D logic and the relationship marketing domain, which imply that creating superior
value in cooperation with the customer is becoming the source of competitive advantage
and it is therefore important for businesses to put their focus on building and maintaining
long-term interactive value-driven relationships with their customers. Customer brand
engagement on online social media platforms is the central element embedded in a broader
network of other relational constructs serving as the antecedents and the consequences. The
concept of engagement is multidimensional and comprises the expressions of emotional,
behavioral and cognitive engagement specific to this particular context.
Furthermore, the conceptual model of customer brand engagement on online social
media platforms was established by identifying the potential drivers and outcomes, and
consequently tested in a quantitative online consumer study. Two groups of antecedents
were found to influence the overall level of customer engagement: customer brand
relationship related factors such as commitment, involvement, satisfaction and trust, and
online social media platform related factors such as ease of use, involvement, participation
and telepresence. While the brand relationship related factors had a direct effect on
customer brand engagement, the effect of online social media platform related factors was
47
moderated by the perceived level of cost/benefit, available resources and goals when
interacting with the brand. The concepts of behavioral brand loyalty and word-of-mouth
were identified to be the consequences of engagement, driven by the dimensions of
behavioral engagement and emotional engagement, respectively.
In conclusion, the findings of this study have important implications for both academic
marketing literature and practice. As the scholarly inquiries into the notion customer
engagement have mostly remained conceptual to date, this research is one of the first few
attempts to test the concept in an empirical setting. On the other hand, the managers will
also find some useful implications that are relevant and can be applied in designing the
strategies for engaging the customers. Yet, further testing and refinement of the model is
necessary in order to fully leverage the potential of customer brand engagement in the
context of online social media platforms.
48
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52
Appendix 1: Online Questionnaire
Introduction
Dear participant,
I am a marketing student at the Aarhus School of Business & Social Sciences
(Denmark) and the following survey is a part of my master thesis focusing on brands in the
context of social media. The questionnaire should take no more than 10 minutes to
complete. The survey is anonymous and your responses will be used for the purposes of
this research only. If you do not manage to complete the entire questionnaire at once, you
may come back to it later and continue from where you previously left off by using the
exact same link. The program keeps the record of your progress in the questionnaire for a
few days. However, please note that you cannot use the back button on your browser to go
back to the previous page while answering the questionnaire.
Thank you in advance.
Kind regards,
Justina Malciute
Screening question
1. Do you have a Facebook account?
○ Yes
○ No
53
The use of Facebook
2. How much do you agree with the following statements?
Strongly
Disagree 2 3 4 5 6
Strongly
Agree
In general, I find Facebook easy to
use ○ ○ ○ ○ ○ ○ ○
I log on to Facebook everyday ○ ○ ○ ○ ○ ○ ○
It is easy to get Facebook to do
what I want it to do ○ ○ ○ ○ ○ ○ ○
Learning to use Facebook is/was
easy for me ○ ○ ○ ○ ○ ○ ○
I consider myself an active
Facebook user ○ ○ ○ ○ ○ ○ ○
I spend long periods of time on
Facebook ○ ○ ○ ○ ○ ○ ○
It is clear and understandable how
to use Facebook ○ ○ ○ ○ ○ ○ ○
It is easy to become skillful at
using Facebook ○ ○ ○ ○ ○ ○ ○
Facebook is flexible to interact
with ○ ○ ○ ○ ○ ○ ○
While browsing on Facebook, I
feel like my mind is in a different
world created by Facebook
○ ○ ○ ○ ○ ○ ○
While browsing on Facebook, I
forget about the “real world”
around me
○ ○ ○ ○ ○ ○ ○
While browsing on Facebook, I
feel like my mind is more present
in the “Facebook world” than the
“real world”
○ ○ ○ ○ ○ ○ ○
Facebook is very important to me ○ ○ ○ ○ ○ ○ ○
After I am done browsing on
Facebook, I feel like my mind
comes back to the “real world”
○ ○ ○ ○ ○ ○ ○
Facebook is relevant to me ○ ○ ○ ○ ○ ○ ○
I get bored when other people talk
to me about Facebook ○ ○ ○ ○ ○ ○ ○
Facebook matters a lot to me ○ ○ ○ ○ ○ ○ ○
In general I have a strong interest
in Facebook ○ ○ ○ ○ ○ ○ ○
54
Interaction with Facebook fan pages screening question
3. Have you ever joined/ liked/ participated in any Facebook fan pages dedicated to brands?
Note: Facebook fan pages are special public profiles meant to promote brands, products, artists,
web sites or organizations. Once the Facebook users visit the page, they are able to 'become fans' by
clicking on the 'Like' button. The owners of the fan page post informational content, which
consequently appears in the news feed of their fans.
○ Yes
○ No
If ‘no’, jump to question 9.
Control variables
4. How much do you agree with the following statements?
Strongly
Disagree 2 3 4 5 6
Strongly
Agree
I browse on Facebook fan pages
because I am interested in being a
part of a brand community
○ ○ ○ ○ ○ ○ ○
I have enough time to browse on
Facebook fan pages ○ ○ ○ ○ ○ ○ ○
I think that browsing on Facebook
fan pages is not worth the time and
effort
○ ○ ○ ○ ○ ○ ○
Browsing on Facebook fan pages
does not take too much effort ○ ○ ○ ○ ○ ○ ○
I enjoy browsing on Facebook fan
pages ○ ○ ○ ○ ○ ○ ○
I browse on Facebook fan pages
because I am interested in the
brands they are dedicated to
○ ○ ○ ○ ○ ○ ○
55
5. Which of the following food and drink brands are you a fan of on Facebook, if any?
You may select more than one answers.
Coca
Red Bull
Oreo
Skittles
Pringles
Monster Energy
Ferrero Rocher
Nutella
Dr Pepper
Starburst
Reese‟s
Starbucks Frappuccino
Sprite
Pepsi
Mountain Dew
Other food or drink brand (please name one only): _____
None
If one brand name selected, jump to question 7.
If ‘none’, jump to question 9.
6. Which one of these Facebook brand pages have you interacted the most with?
○ Coca
○ Red Bull
○ Oreo
○ Skittles
○ Pringles
○ Monster Energy
○ Ferrero Rocher
○ Nutella
○ Dr Pepper
○ Starburst
○ Reese‟s
○ Starbucks Frappuccino
Cont.on the next page
56
Cont. from the previous page
○ Sprite
○ Pepsi
○ Mountain Dew
○ [Other food or drink brand, if selected and entered in the previous question]
Engagement with the Facebook fan page
The following questions concern your engagement with the Facebook fan page of
[selected brand].
7. How often do you..
Never Almost
never Rarely Sometimes Often
Almost
all the
time
All the
time
…visit the Facebook fan page
of [selected brand] ○ ○ ○ ○ ○ ○ ○
…notice posts by [selected
brand] in your news feed? ○ ○ ○ ○ ○ ○ ○
…read posts by [selected
brand]? ○ ○ ○ ○ ○ ○ ○
…‟like‟ posts by [selected
brand]? ○ ○ ○ ○ ○ ○ ○
…comment on Facebook wall
posts by [selected brand]? ○ ○ ○ ○ ○ ○ ○
…share posts by [selected
brand] with your friends? ○ ○ ○ ○ ○ ○ ○
…post on the Facebook fan
page of [selected brand]
yourself?
○ ○ ○ ○ ○ ○ ○
57
8. How much do you agree with the following statements?
Strongly
Disagree 2 3 4 5 6
Strongly
Agree
.I can continue browsing on the
Facebook FP8 of [selected brand]
for long periods at a time
○ ○ ○ ○ ○ ○ ○
.I devote a lot of energy to the
Facebook FP of [selected brand] ○ ○ ○ ○ ○ ○ ○
I am enthusiastic about the
Facebook FP of [selected brand] ○ ○ ○ ○ ○ ○ ○
The Facebook FP of [selected
brand] inspires me ○ ○ ○ ○ ○ ○ ○
.I find the Facebook FP of
[selected brand] full of meaning
and purpose
○ ○ ○ ○ ○ ○ ○
.I am excited when browsing on
and interacting with the Facebook
FP of [selected brand]
○ ○ ○ ○ ○ ○ ○
I am interested in the Facebook FP
of [selected brand] ○ ○ ○ ○ ○ ○ ○
.I am proud of being a fan of
[selected brand] ○ ○ ○ ○ ○ ○ ○
Time flies when I am browsing on
the Facebook FP of [selected
brand]
○ ○ ○ ○ ○ ○ ○
Browsing on the Facebook FP of
[selected brand] is so absorbing
that I forget about everything else
○ ○ ○ ○ ○ ○ ○
I am rarely distracted when
browsing on the Facebook FP of
[selected brand]
○ ○ ○ ○ ○ ○ ○
I am immersed in browsing on and
interacting with the Facebook FP
of [selected brand]
○ ○ ○ ○ ○ ○ ○
.My mind is focused when
browsing on the Facebook FP of
[selected brand]
○ ○ ○ ○ ○ ○ ○
I pay a lot of attention to the
Facebook FP of [selected brand] ○ ○ ○ ○ ○ ○ ○
Jump to question 10 and continue answering the remaining questions with the same brand in
mind.
8 FP = Fan page
58
Customer brand relationship quality
9. Which of the following food and drink brands is your favorite?
○ Coca
○ Red Bull
○ Oreo
○ Skittles
○ Pringles
○ Monster Energy
○ Ferrero Rocher
○ Nutella
○ Dr Pepper
○ Starburst
○ Reese‟s
○ Starbucks Frappuccino
○ Sprite
○ Pepsi
○ Mountain Dew
○ Other food or drink brand (please name one only):______
59
The following questions concern your attitude towards [selected brand].
10. How much do you agree with the following statements?
Strongly
Disagree 2 3 4 5 6
Strongly
Agree
In general I have a strong interest in
[selected brand] ○ ○ ○ ○ ○ ○ ○
[Selected brand] is very important to me ○ ○ ○ ○ ○ ○ ○
[Selected brand] matters a lot to me ○ ○ ○ ○ ○ ○ ○
I get bored when other people talk to me
about [selected brand] ○ ○ ○ ○ ○ ○ ○
[Selected brand] is relevant to me ○ ○ ○ ○ ○ ○ ○
Overall I am satisfied with [selected
brand] ○ ○ ○ ○ ○ ○ ○
[Selected brand] exceeds my
expectations ○ ○ ○ ○ ○ ○ ○
The performance of [selected brand] is
very close to the ideal brand in the
product category
○ ○ ○ ○ ○ ○ ○
I am very loyal to [selected brand] ○ ○ ○ ○ ○ ○ ○
I am willing to make small sacrifices in
order to keep using the products of
[selected brand]
○ ○ ○ ○ ○ ○ ○
I would be willing to postpone my
purchase if the products of [selected
brand] were temporarily unavailable
○ ○ ○ ○ ○ ○ ○
I would stick with [selected brand] even
if it would let me down once or twice ○ ○ ○ ○ ○ ○ ○
I am so happy with [selected brand] that
I no longer feel the need to watch out for
other alternatives
○ ○ ○ ○ ○ ○ ○
I am likely to be using [selected brand]
one year from now ○ ○ ○ ○ ○ ○ ○
I trust [selected brand] ○ ○ ○ ○ ○ ○ ○
.I rely on [selected brand] ○ ○ ○ ○ ○ ○ ○
[Selected brand] is an honest brand ○ ○ ○ ○ ○ ○ ○
[Selected brand] is safe to use ○ ○ ○ ○ ○ ○ ○
60
Consequences
11. How much do you agree with the following statements?
Strongly
Disagree 2 3 4 5 6
Strongly
Agree
I will buy [selected brand] the next
time I buy food/drinks ○ ○ ○ ○ ○ ○ ○
I intend to keep purchasing
[selected brand] ○ ○ ○ ○ ○ ○ ○
I say positive things about
[selected brand] to other people ○ ○ ○ ○ ○ ○ ○
I often recommend [selected
brand] to others ○ ○ ○ ○ ○ ○ ○
I encourage friends to buy
[selected brand] ○ ○ ○ ○ ○ ○ ○
Socio-demographic
12. What other online social media platforms do you have an account on, if any? You
may select more than one answer.
MySpace
Google+
Bebo
Badoo
Tagged
Orkut
Friendster
hi5
Netlog
YouTube
Flickr
Foursquare
Tumblr
Other (please specify): _______
None
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13. How much time do you spend on online social media platforms on average every day?
○ Less than 30 mins
○ 30 mins – 1 hour
○ 1 hour – 2 hours
○ 2 hours – 3 hours
○ More than 3 hours
14. How much of that time do you spend on Facebook?
○ Less than 30 mins
○ 30 mins – 1 hour
○ 1 hour – 2 hours
○ 2 hours – 3 hours
○ More than 3 hours
15. How old are you?
___________
16. What is your gender?
○ Male
○ Female
17. What is your country of origin?
___________
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Appendix 2: Top Facebook Pages, Worldwide, Food & Drink Brands