Journal of Research in Interactive Marketing
Antecedents and consequences of customer engagement on Facebook: An
attachment theory perspective
Robert Hinson, Henry Boateng, Anne Renner, John Paul Basewe Kosiba,
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Robert Hinson, Henry Boateng, Anne Renner, John Paul Basewe Kosiba, (2019) "Antecedents
and consequences of customer engagement on Facebook: An attachment theory perspective",
Journal of Research in Interactive Marketing, Vol. 13 Issue: 2, pp.204-226, https://doi.org/10.1108/
JRIM-04-2018-0059
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JRIM
13,2 Antecedents and consequences
of customer engagement
on Facebook
204 An attachment theory perspective
Received 21April 2018 Robert Hinson
Revised 13 November 2018 Department of Marketing and Entrepreneurship,
Accepted 9 December 2018
University of Ghana Business School, Accra, Ghana
Henry Boateng
Business School, University of Technology Sydney,
Faculty of Business, Haymarket, Australia
Anne Renner
Department of Marketing and Entrepreneurship,
University of Ghana Business School, Accra, Ghana, and
John Paul Basewe Kosiba
Department of Marketing, University of Professional Studies, Accra, Ghana
Abstract
Purpose –Marketing researchers have usually studied consumers’ attachment to brands from an emotional
bonding perspective. However, the purpose of this study is to show that attachment to objects is not only
limited to bonding. Thus, the authors conceptualised the attachment theory from two perspectives: bonding-
based and identity-based attachment. In addition, the study further seeks to identify the elements of each
component and examine how these elements drive customer engagement on a brand’s Facebook page while
assessing some consumer-related outcomes of customer engagement on Facebook.
Design/methodology/approach – Using an online survey, the authors examined antecedents of
customer engagement on Facebook and the outcomes of engagement behaviours among 649 respondents.
Structural equation modelling was used in analysing the data.
Findings – The results of the study show that consumers’ attachment to a brand drives them to engage the
brand on the brand’s Facebook page. The results also show that the consumer engagement of brands on
Facebook results in positive user-generated contents and consumer involvement.
Practical implications – Managerially, the attachment theory provides value for marketers in terms of
evaluating customer–brand relationships and how such a relationship can yield positive results.
Originality/value – This study expands how the attachment theory has been conceptualised and applied
in the marketing literature. The study shows that consumer attachment to brands is identity-based in
addition to being bonding-based.
Keywords Facebook, Social media advertising, Brand
Paper type Research paper
Journal of Research in Interactive
Marketing
Vol. 13 No. 2, 2019 Introduction
pp. 204-226
© EmeraldPublishingLimited The concept of engagement has received much attention from many scholars. For instance,
2040-7122
DOI 10.1108/JRIM-04-2018-0059 many researchers have studied the concept of engagement in sociology, political science,
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educational psychology, organisational behaviour and, in recent times, in the marketing Attachment
discipline (Barger et al., 2016; Chahal and Rani, 2017; Triantafillidou and Siomkos, 2018; theory
Kosiba, et al., 2018a; Hollebeek et al., 2018). The emergence and the exponential growth of
social technologies like Facebook, Twitter, and LinkedIn has made it possible to understand perspective
this concept through the electronic ties that individuals choose to have with brands (Noë
et al., 2016), as it presents an opportunity for many firms and marketers to engage their
customers. Amongst the social technological platforms, Facebook in particular has
transformed the media landscape (Chester et al., 2010; Ángeles Oviedo-García et al., 2014). 205
Facebook is the most widely used social network site worldwide, with about 2 billion active
users globally (Facebook Newsroom, 2017). Many firms have therefore created brand fan
pages on Facebook where they engage with their customers. For example, 85 per cent of
Fortune 500 companies use Facebook (Barnes and Pavao, 2018). Research has shown that as
of 2017, there were more than 65 million firms that were active on Facebook, and over 2.5
billion comments were made every month on the Facebook Pages of these firms (Kaplan,
2017). For consumer brands, the main purposes of utilising Facebook are to engage with
customers, advertise special offers, and/or deliver an opportunity for consumers to have
social interactions with other consumers and friends (Ng, 2013; Kabadayi and Price, 2014).).
These activities have catapulted researchers’ interest in consumers’ customer engagement
on Facebook (Triantafillidou and Siomkos, 2018).
According to Putnam (1995), individuals’ need for bonding drives them to engage in
community activities. This has implications for digital engagement as many consumers look
for opportunities to connect emotionally with their favourite brands (Dessart et al., 2015),
leading to the formation of online brand communities. Some studies have found a
relationship between Facebook users’ level of usage and formation of identity, and
engagement in civil society activities (Ji et al., 2010; Valenzuela et al., 2009). Following from
these, we argue that consumers’ engagement with brands on Facebook can be explained
with the attachment theory. That is, for a consumer to engage a brand on Facebook, that
consumer should have a sense of attachment to the brand. In the marketing literature, the
attachment theory has been used to understand consumers’ attachment to an object of
interest (Wallendorf and Arnould, 1988). It has also been used partially to understand how
consumers bond with some brands (Malär et al., 2011; Frasquet et al., 2017). However,
Harper et al. (2007) posited that people’s attachment to an online community is not limited to
bonding but includes identity attachment. In this case, we argue that two forms of
attachment – bonding-based attachment and identity-based attachment – drive consumers’
engagement with brands on their Facebook fan pages.
The outcome of customer engagement has received much attention from researchers in
the marketing discipline. Previous studies have identified enhanced customer experience,
customer satisfaction, brand loyalty, customer participation, superior expected bottom-line
performance results and electronic word-of-mouth as outcomes of customer engagement
(Brodie et al., 2013; Hollebeek et al., 2018; Kosiba et al., 2018b). In this study, we identified
customer participation in brand building and consumer generated advertising as some of
the outcomes of customer engagement on a brand’s Facebook fan page. Our argument is
premised on the idea that customer engagement on social media constitutes a “moment of
truth” and this moment of truth informs the customer’s disposition towards the brand and
their “degree of activeness” (Demangeot and Broderick, 2016). Furthermore, the interactive
features of social media platforms like Facebook enable customers’ interactions with firms
and create contents that are vital for value creation (Lomborg and Bechmann, 2012).
Facebook also enables customers to often suggest how these brands can be improved and
take part in decision-making, thus empowering consumers to be active participants in brand
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JRIM building. The aim of this study is therefore to examine the relationship between attachment
13,2 (identity and bonding) and customer engagement on Facebook. We ascertain the elements of
identity-based and bonding-based attachment that facilitate customer engagement on
Facebook. This study also seeks to ascertain the outcome of this engagement with respect to
consumers’ actions.
Our study contributes to the application of the attachment theory in marketing,
206 identifying the elements of identity and bonding base-attachment that drives customer
engagement on Facebook. This study also examines the mediating role of the elements of
customer engagement in affecting customer participation and consumer generated
advertising on Facebook. Practically, this study proposes the need for brands managers to
interact, recognise, and build an enduring relationship with their customers on their
Facebook page. The rest of the paper is divided as follows: the first part offers the theoretical
and conceptual background of this study while the second part focuses of conceptual
framework and hypotheses development. Part three contains the methodology and part four
presents the findings of the study. Discussions of the findings are contained in part five. The
theoretical and practical implications of the study are captured in part six and seven,
respectively. Part eight focuses on the limitations and directions for future study.
Literature review
Attachment theory
The attachment theory assesses a person’s sense of the finest “balance between closeness to
and distance from key people in his or her life” (Ainsworth, 1967 cited in Miles, 2012, p. 49).
It has been defined via the emotional bond between people (Ainsworth, 1969). People’s
attachment experiences affect their thoughts and their actions and inactions towards others.
Ainsworth et al. (1978) noted three forms of attachment that infants create with their
mothers: secure, resistant and avoidant. Riger and Lavrakas (1981) studied attachment from
three perspectives; social structure, bonding, and social identity. In other words, there is
social structure-based attachment, bonding-based attachment, and identity-based
attachment. Social structure-based attachment relates to physical structures that bind an
individual to a place or an object. Bonding-based attachment relates to long-enduring ties,
and identity-based attachment relates to the inclusion of an object to an individual’s self-
concept. For the purposes of this study, attachment is conceptualised as having bonding and
identity components. That is, consumers’ attachment to a brand may be expressed in
continual emotional bonding with the brand, and by identifying with the brand. We did not
include structure-based attachment because Facebook features do not automatically bind a
user to a particular brand’s page. In a relatable theorisation, the brand attachment theory
also delineates – homophily – which spells out that people with similar traits may be more
likely to attach to each other than dissimilar ones (Lazarsfeld and Merton, 1954; Kim and
Altmann, 2017). Homophily, which is a widely occurring human disposition (McPherson
et al., 2001), seems to be more popular with the advent of social media (Noë et al., 2016;
Ahmed et al., 2018). Recent studies (Orben and Dunbar, 2017) have found this behaviour
among Facebook users. Therefore we argue that the manifestation of homophily could also
be seen in customers who associate themselves with brands on Facebook. These
associations may create attachment between the customers and the brand on Facebook
(Dessart et al., 2015; Malär et al., 2011), which results in engagement with these brands.
Customer engagement
Customer engagement has its theoretical roots in the expanded/transcending view of
relationship marketing (Brodie et al., 2013; Pansari and Kumar, 2017). According to
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Vargo (2009), this transcending view sees consumer behaviour as being focussed on Attachment
customers’ “interactive experiences taking place in complex, co-creative environments” theory
(Brodie et al., 2013, p. 106). Customer engagement is regarded as a multi-dimensional
concept, comprising either two or three elements which are clearly seen in the diverse, yet perspective
sparse, definitions scholars have given. Mollen and Wilson (2010, p. 5 in Brodie et al., 2013),
for instance, state that customer engagement is “the 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”. Bowden (2009 in Brodie et al., 207
2013) views the concept as a psychological process comprising cognitive and emotional
aspects. Van Doorn et al. (2010 in Hollebeek and Chen, 2014), on the contrary, perceive
customer engagement as comprising cognitive, emotional, and behavioural dimensions.
Hollebeek (2011, p. 790) also views customer engagement as “the level of a customer’s
motivational, brand-related, and context-dependent state of mind characterised by specific
levels of cognitive, emotional, and behavioural activity in brand interactions”.
We concur with the latter two perceptions as the former fails to capture behavioural
dimensions, which we contend result from cognitive and affective responses. This view
seems to have gained wide acceptance in the literature on customer engagement (Hollebeek
et al., 2014; Dessart et al., 2015; Leckie et al., 2016; Kunz et al., 2017). Consequently, we view
customer engagement as comprising cognitive, emotional, and behavioural dimensions.
Hence, we adopt Hollebeek and Chen’s (2014, p. 154) definition of customer engagement as “a
consumer’s positively valenced brand-related cognitive, emotional and behavioural activity
during or related to focal consumer/brand interaction”. The cognitive dimension refers to an
individual’s level of engrossment in a brand, thus, the extent to which he/she is mentally
focussed on the brand during interaction; emotional engagement refers to the customer’s
level of pride or positive feelings whilst interacting with the brand (Schaufeli et al., 2002;
Leckie et al., 2016); and the behavioural dimension refers to the customer’s interest in
spending energy, time and effort on an activity related to the brand (Patterson et al., 2006;
Leckie et al., 2016). Incorporating these diverse perspectives, we expose cognitive, emotional,
and behavioural dimensions as the three core conceptual dimensions of engagement.
Therefore, following the extant literature, we also conceptualise customer engagement as
a multi-dimensional construct consisting of behavioural, cognitive and affective engagement.
Our conceptualisation of customer engagement as a multi-dimensional construct composed
of the aforementioned dimensions stems from the increasing manner in which customers and
brands interact. Subsequently, the construct is highly interactive in nature, as espoused by
early work (Hollebeek, 2011). It is evident that in their interactions with brands, customers
are more likely to invest effort (behaviour) to maintain interaction, be mentally engrossed
(cognitive) in the interaction, and enthusiastically inspired (affective) in the process of
interaction (Dwivedi, 2015). Dwivedi (2015) has also used these elements to measure customer
engagement, but with a different conceptualisation. We find support from the existing
literature that demonstrate positive correlations among behavioural, cognitive and affective
engagement (Habibi et al., 2014; Brodie et al., 2013; Patterson et al., 2006; Leckie et al., 2016).
For example, a consumer’s affective engagement with a brand can influence the consumer to
engage in behavioural engagement activity such as spreading positive word-of-mouth
(Patterson et al., 2006). Jarvis et al. (2003) refer to this kind of measurement approach as
reflective first-order and reflective second-order. Thus, we argue that customer engagement
is a reflective second-order construct, with its first-order dimension as behavioural, cognitive,
and affective engagement since these three dimensions of customer engagement are
positively correlated. In line with these, we hypothesise that:
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JRIM H1. Customer engagement is a second-order construct manifested in the first-order
13,2 dimensions of cognitive, affective, and behavioural engagement.
Hypothesised model
Using the attachment theory, the study is anchored on the conceptual framework presented
208 in Figure 1. The framework assumes that the antecedents of customer engagement arebonding-based attachment and identity-based attachment. In addition, the framework
presents the consumer-related outcomes of customer engagement as customer participation
and consumer generated advertising. The rest of this section is used to discuss the
relationships among the elements of the framework. A possible hypothesis is formulated to
guide the empirical investigation.
Bonding-based attachment
We define bonding-based attachment via social interaction ties and brand trust. This is
consistent with Riger and Lavrakas (1981) “bondedness” which entails social ties. Wright
and Perrone (2008), also noted that individuals form bonds with individuals they can trust.
Social interaction ties. Social interaction is the interpersonal relationship between a
person and others (Wang and Wang, 2013). It was, for a while, limited to the offline context.
However, with the surge in the use of the internet, in particular, social media, social
interaction seems to have taken on another dimension, where people interact with others
they probably have never physically met (Park and Chung, 2011). Thus, social interaction
ties are now viewed as the transfer of social capital from offline to online (Zhang et al., 2017).
These interactions, we maintain, create ties between an individual and others they may be
interacting with, which we opine strengthen over time with the frequency of the interaction.
It is these ties and their strength (or otherwise) that may or may not influence an individual’s
actions (Riger and Lavrakas, 1981; Wang and Wang, 2013). In this study, therefore, we
define social interaction ties as the strength of the relationships/bonds, amount of time spent
and communication frequency between consumers and brands (Chiu et al., 2006). As
consumers interact with their favourite brands, strong ties are developed (Dessart et al.,
2015). Scholars (Chu and Kim, 2011; Shan and King, 2015; Phua et al., 2017) have found that
users’ perceived tie strength positively influences engagement with brand communities.
Consequently, it is these strong ties that propel them to engage with the brands. Thus, we
Identity-based attachment  
Self-image expression
Customer engagement 
Consequences 
H4
Brand identification H1
Customer participation
H5 H6
Emotional 
Figure 1. Cognitive 
A conceptual model H7
H2 Behavioural Consumer generated 
of antecedents and Bonding-based attachment  advertising
consequences of H3
customer Social interaction ties
engagement on
Facebook
Brand trust
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argue that consumers who have strong ties with their favourite brands will engage the Attachment
brand on Facebook via affective, cognitive and behavioural means. Against this backdrop, theory
therefore, we hypothesise that: perspective
H2. Social interaction ties are positively associated with customer engagement.
Brand trust. Trust in the general sense of the word is the belief that something or someone
will perform to expectations and not disappoint. The concept of trust brings with it the idea 209
of relationships among people or brands. According to Delgado-Ballester et al. (2003), brand
trust is the confident expectations of the brand’s reliability and intentions. When a consumer
trusts a brand, he/she will recommend it (Eggers et al., 2013), consider it when making
product purchase decisions (Luk and Yip, 2008; Bhandari and Rodgers, 2018), and use more
of its products and services (Eggers et al., 2013). Consequently, if a customer does not trust a
brand, it stands the risk of not being recommended, not being considered during purchasing
decisions, etc. According to Eggers et al. (2013), if customers trust a brand, they will use
more of its products and services and recommend it to others. Some studies argue that
customer engagement outcomes may include brand trust (Hollebeek, 2011; Brodie et al.,
2013). Nonetheless, Laroche et al. (2012) found that social media based brand community
engagement does not significantly predict brand trust. On the other hand, Kosiba et al.
(2018b) found out that trustworthiness informs how customers engage with service brands.
Similarly, Kosiba et al. (2018a) indicated that customer engagement within the banking
sector is influenced by trust in the service provider and economy-based trust. Following this
line of argument, we argue that brand trust will positively affect consumers to cognitively,
affectively and behaviourally engage their favourite brands on Facebook. For example,
consumers who trust a brand will fully support the brand by defending it and displaying a
positive attitude on its Facebook fan page. Thus, we hypothesise that:
H3. Brand trust is positively associated with customer engagement.
Identity-based attachment
We define identity-based attachment via self-image expression and brand identification.
This view is in line with existing literature that notes that identity attachment is symbolic
(Low and Altman, 1992), and it relates to the inclusion of an object in a person’s self-concept
(Clayton, 2003). Our position is also supported by Tajfel’s (1974) definition of social identity.
According to Tajfel, social identity refers to an individual’s knowledge of being part of a
group. Sharing of common identity makes people attached to each other. Therefore, identity-
based attachment works through self-image expression and identification (Chiu et al., 2006;
Chung et al., 2016).
Self-image expression. According to Khoo-Lattimore and Prayag (2016), a consumer’s
self-image can be upheld, expressed, and augmented through the products they purchase
and use. Contemporary consumers make choices based on whether a product fits their
lifestyle or whether it represents an exciting new concept or a desirable experience (Schmitt
and Simonson, 1997 in Murphy et al., 2007). Additionally, Caldwell and Freire (2004) in
Murphy et al. (2007) aver that a brand must fulfil self-expression needs, not just functional
ones. The congruence between self-image and product image is also positively related to
consumers’ product evaluations (Graeff, 1996 in Jamal and Goode, 2001). The self-image
congruity facilitates positive behaviour and attitudes (Sirgy et al., 1997). For instance, Kahn
(1990) in his study involving psychological conditions of personal engagement and
disengagement at work, found that personal engagement is the “expression of a person’s
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JRIM “preferred self” in task behaviours that promote connections to work and to others, personal
13,2 presence (physical, cognitive, and emotional), and active, full role performances” (p. 700).
Social-image expression is also a central social value in online communities (Kim et al., 2011)
and, according to Park and Chung (2011), some individuals interact and chat with others on
social network sites to satisfy self-image expression desires. Unsurprisingly, Islam et al.
(2018) found that an individual’s self-brand image congruity positively influences their
210 online brand engagement. That is, consumers who seek to satisfy this desire will engage
their favourite brands online. Therefore, we hypothesise that:
H4. Self-image expression is positively associated with customer engagement.
Brand identification. The concept of identification originates from social identity theory (So
et al., 2013). Mael and Ashforth (1992) explain that individuals develop a social identity by
grouping themselves and others into diverse social categories. An individual will identify
with a social category when it (and its associated social identity) enhances their self-esteem,
and is based on how psychologically intertwined the individual is with the characteristics of
the category (Bhattacharya and Sen, 2003). Extending this to brands, Kuenzel and Vaux
Halliday (2008) maintain that brands are pertinent to creating and communicating consumer
identity, and can be meaningful categories with which to identify (Bhattacharya and Sen,
2003). This is because brands enable consumers to express their unique attributes and
identity (McEwen, 2005). Brand identification, therefore, is the oneness a consumer perceives
between a brand and himself (Stokburger-Sauer et al., 2012). The stronger the perception of
the overlap between the characteristics of the brand and the consumer, the stronger the
identification and vice versa. Some of the ways that consumers may identify themselves
with their favourite brands on Facebook are commenting on, liking, and sharing the brands’
pages (Cvijikj and Michahelles, 2013). Algesheimer et al. (2005) found that brand
identification has a positive influence on brand communities’ engagement in the European
car clubs context. As a result, Wirtz et al. (2013) in their study conceptualise a positive
association between brand identification and customer engagement in brand communities.
The findings of another study by Stephenson and Yerger (2014) show that brand
identification can be used as a mechanism to increase the engagement of alumni and
potential donors. Following this, the hypothesis below is proposed:
H5. Brand identification is positively associated with customer engagement.
Consumer-related outcomes of customer engagement
Customer participation. Customer participation is the degree to which customers contribute
their effort, preference, knowledge, or other resources into the process of production and
delivery (Chan et al., 2010), hence taking an active part in consumption and production
(Nysveen and Pedersen, 2014). It comprises the physical and mental inputs required for
co-production (Flores and Vasquez-Parraga, 2015) and may be demonstrated in an active
role through the application of knowledge and sharing of information with the firm (Ranjan
and Read, 2016). Although it is unclear if a relationship exists between customer
participation and customer engagement, the former is seen to be an antecedent of the latter
(Ramaswamy and Gouillart, 2010; Vivek et al., 2012; Nysveen and Pedersen, 2014), whereby
engagement arises from the customers’ application of efforts and resources in production
and consumption (Solem and Pedersen, 2016). Alternatively, customer participation is
argued to be a subset of customer engagement (Sawhney et al., 2005).
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Contrary to these, we view the relationship between the two as that in which customer Attachment
engagement and the degree thereof influences customer participation. In other words, we theory
posit that customer engagement is an antecedent of customer participation, the two being perspective
distinct from each other. Taking cognisance of our earlier stance on the multidimensional
nature of customer engagement (cognitive, affective and behavioural), and premised on the
fact that the intensity of customer engagement is based on brand stimuli (brand activities on
the social media platform) (Solem and Pedersen, 2016), we contend that the greater the 211
stimuli, the greater the affective, emotional, behavioural engagement and, consequently, the
greater the engagement, the greater the participation. Thus, customer engagement creates
deep connections with customers that drive participation over time. This is in line with
Wirtz et al. (2013) who state that online brand customer engagement results in interactive
participation in virtual communities. Pagani and Malacarne (2017) also found that personal
engagement significantly influences active usage in mobile location-based social networks,
which results in critics (react to the online content shared by other users giving feedback,
ratings and reviewing products or services), a form of participation. Therefore, we
operationalise participation not as a passive act (e.g. information seeking, reading
comments), but as posting comments, which is regarded as active participation (Shang et al.,
2006). In other words, as the consumer engages with the brand on the social media platform,
they are predisposed to exert their energies and contribute their preference, knowledge and
other resources in consumption and production. Thus, we hypothesise that:
H6. Customer engagement is positively associated with customer participation.
Consumer generated advertising. Marketers for decades have employed consumers’
feedback in the process of developing ads by way of communication ideas, slogan contests,
testimonials, etc.(Lawrence et al., 2013). However, there is an emerging phenomenon whereby
consumers individually, either of their own volition or under some level of enticement by
firms, create advertisements, known as consumer-generated advertising. This phenomenon
is set apart from the traditional forms of advertising, in that access to multimedia software,
the internet, and social media platforms now permit consumers to create, produce and
disseminate adverts (Lawrence et al., 2013). Hence, the outcomes of social media advertising
rest on not only simply the fundamental advertising message but also co-created consumer-
generated advertising in the background of the particular message (e.g. Facebook comments
or likes associated to an advert) (Knoll and Proksch, 2017). These consumer-generated efforts,
we opine, also tend to create greater perceptions of credibility than traditional advertising,
being that they come from consumers and not the company. Social media platforms such as
Twitter and Facebook have given consumers the opportunity to actively engage with brands
and create a huge amount of data about their experiences with brands and products (Liu
et al., 2017). Satisfied customers write blogs to praise their favourite brands, offer positive
word-of-mouth online, and recommend the brand to others (Kietzmann et al., 2011).
Accordingly, Wei et al. (2013) in their study view customer engagement behaviours with a
brand as the manifestation of user-generated hotel reviews as perceived by potential
customers. Pagani and Malacarne (2017) found that personal engagement on mobile location-
based social networks affect active content creation behaviour. From this, it can be inferred
that customer engagement on Facebook may result in consumer generated advertising.
Therefore, we hypothesise that:
H7. Customer engagement is positively associated with consumer generated advertising.
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JRIM Method
13,2 Measures
The measuring scales used in this study were adapted from established measures (Table I).
To ensure that there were higher response rates and the prevention of respondent fatigue
and confusion, a pre-test as suggested by Malhotra et al. (2017) was carried out using 25
working professionals who are also students enrolled in the Executive Masters Programme
212 in a leading Business School in Ghana to reduce ambiguity. Some items were revised
according to their suggestions. All the final items were measured on a five-point Likert
Scale, ranging from strongly disagree (1) to strongly agree (5).
Sample and data collection
The present study engaged an online survey directed to Facebook users using LimeSurvey.
LimeSurvey is an open source online survey tool that allows for the development,
publishing, and collection of responses to surveys. The use of an online survey has become
increasingly more popular since it decreases the expenses involved in locating suitable
Variable Frequency (N = 649) (%)
Gender
Male 325 50.1
Female 324 49.9
Age
Under 30 years 331 51.0
30-39 years 243 37.4
40-49 years 63 9.7
50-59 years 9 1.4
60 years 3 0.5
Educational level
Vocational/high school 34 5.2
HND 22 3.4
University degree 379 58.4
Postgraduate degree 194 29.9
Other 20 3.1
Number of brands followed
1-4 213 32.8
5-9 195 30.0
10-14 116 17.9
15-19 42 6.5
over 19 83 12.8
Total 649 100.0
Country
Canada 3 0.5
China 4 0.6
France 9 1.4
Ghana 489 75.3
Namibia 9 1.4
Nigeria 9 1.4
Table I. South Africa 110 16.9
Characteristics of the UK 4 0.6
samples USA 12 1.8
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respondents, boosts the response pace, and guarantees the instant readiness of the Attachment
respondents. Admittedly, its popularity is not an indication that the method is inerrantly theory
valid and dependable, as evidenced by some drawbacks that are linked to this sampling perspective
method (e.g. control and representativeness issues) (De Gregorio and Sung, 2010).
Irrespective of these, this method was adopted for the study as the aim was to acquire a
large sample containing a variety of demographic and socialisation features, such as norms,
beliefs, and ideologies from across nations (De Gregorio and Sung, 2010). The link for the 213
questionnaire was generated using LimeSurvey and was posted on various brands’
Facebook fan pages and the researchers’ Facebook walls to allow public participation. This
was also to target Facebook users and allow participants to have a real feel of the
environment while filling out the questionnaire. Respondents were asked to think of any
brand (product) they have liked and still follow on Facebook in answering the question.
Subject profile
In all, 2,382 individuals clicked on the link; 986 respondents completed the item survey
yielding a 41.39 per cent response rate after a 3 months period (23 January to 23 March 2017).
From this sample, we analysed respondents who follow brands on Facebook and eliminated
non-respondent engagement (thus responses with standard deviation equal to zero for the
construct). A total of 649 responses, which represents 27.24 per cent of the sample, fit the
criteria. Among the 649 respondents, 325 (50.1 per cent) were males and 324 (49.9 per cent)
were females. The majority (51 per cent) of the respondents were under 30 years, followed by
ages 30-39 (37.4 per cent), 40-49 (9.7 per cent), 50-59 (1.4 per cent) and 60 and over (0.5
per cent). Approximately 33 per cent follow 1-4 brand(s) on Facebook, followed by those who
follow 5-9 brands (30 per cent), 10-14 brands (17.9 per cent), over 19 brands (12.8 per cent) and
15-19 brands (6.5). Ghanaians comprised 75.3 per cent of the sample, followed by South
Africans (16.9 per cent), Americans (1.8 per cent), French, Namibians and Nigerians (1.4
per cent each), British and Chinese (0.6 per cent each) and Canadians (0.5 per cent).
Common method variance (CMV) is the most frequently cited methodological problem in
quantitative studies and any self-report survey (Malhotra et al., 2017), as it threatens the
validity of the findings on the relationship between constructs (Campbell and Fiske, 1959;
Reio Jr, 2010). Concerns of CMV were examined using Harman’s one-test factor for this
study (Podsakoff et al., 2003). All the substantive variables were then entered into an
exploratory factor analysis (EFA). Results showed that a single factor did not emerge from a
factor analysis. Moreover, when all items were forced to load onto a single factor, it
accounted for 35.72 per cent of the variance. This was an indication that there were no
serious concerns of CMV.
Control variables
In this study, we controlled for a number of constructs that were not of direct theoretical
interest, but could have an effect on the relationship among our variables (see in Tröster and
Van Knippenberg, 2012). Frist, we controlled for demographics such as age and gender, as
previous research has found an important effect between these variables and technology
use. For examples, Pfeil et al.’s (2009) study shows that teenagers tend to make more use of
different social network sites. Also, a study by Thelwall et al. (2010) shows that females are
more successful social network site users partly because of their greater ability to textually
harness positive affect. We also controlled for number of brands followed since we perceived
that the number of brands an individual follows will affect the probability of participation
and engagement with the brands’ fan page.
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JRIM Results
13,2 Measurement model analysis
Structural equation modelling using IBM Analysis of Moments of Structures (AMOS)
software package (Version 22) was used for data analysis. We estimated our hypothesised
measurement model using maximum likelihood estimation for confirmatory factor analysis
(CFA). The initial measurement model provided a good fit to the data; chi-square (i.e.
x 2214 (524) = 1180.477, p< 0.00). Other fit indices suggest an acceptable fit to data (i.e. Normed
x 2 = 2.25; Goodness of Fit Index, GFI = 0.90; Adjusted Goodness of Fit Index, AGFI = 0.88;
Comparative Fit Index, CFI = 0.94, Tucker–Lewis Index, TLI = 0.93; Root Mean Square
Error of Approximation, RMSEA = 0.044). Also, all the items had standardised indicator
loadings greater than 0.5. Nevertheless, following Hair et al.’s (2017) suggestion, we
eliminated items for the standardised indicator loadings
 0.70. Thus, BI1, BI2, SIT2, SIT4,
BT4, BT 5, EE3, CI4 and UG4 were dropped (Table I). Yet, BI3 When I post on the Facebook
pages of these brands, I usually say ‘we’ rather than ‘they’, which had a loading 0.695, was
retained since it was above the acceptable level suggested by Kline (2005). In addition, its
deletion meant the construct brand identification would have to be eliminated. The adjusted
measurement model provided a good fit to the data with chi-square x 2 (288) = 563.215, p <
0.00, Normed x 2 = 1.95; GFI = 0.94; AGFI = 0.92; CFI = 0.97, TLI = 0.96; RMSEA= 0.038.
Themeasurement model results appear in Table II.
Construct reliability was evident as the Cronbach’s alpha (CA) and composite reliability
(CR) scores were above the 
0.70 rules of thumb, the average variance extracted (AVE) for
establishing convergent validity for each construct exceeded the suggested cut-off point of
0.5 (Hair et al., 2017) as presented in Table III. We assessed discriminant validity using two
approaches: first, we assessed whether the AVE for each construct was greater than the
highest shared correlation, shown as maximum shared variance (MSV) in Table III, between
the focal constructs (Fornell and Larcker, 1981); and second, whether the AVE of a latent
construct was higher than the construct’s highest squared correlation with any other latent
construct (Hair et al., 2017).
Test of hypotheses
The strong interrelationships among the three engagement dimensions (average r # 0.64)
suggested a commonality indicative of a higher-order factor (Kline, 2005; Law et al., 1998).
Consequently, we specified an additional model in which we examined the second-order
path loadings of customer engagement as in previous studies (see in Rich et al., 2010;
Dwivedi, 2015). After examining the fit of our measurement model (chi-square x 2 (300) =
642.019, p < 0.01, Normed x 2 = 2.14; GFI = 0.93; AGFI = 0.91; CFI = 0.96, TLI = 0.96;
RMSEA = 0.04), we observed that customer engagement significantly explained the first-
order dimensions: emotional (standardised beta coefficient, b = 0.81, t-values = 16.82, p <
0.01), cognitive (b = 0.77, t-values = 16.47, p < 0.01) and behavioural (b = 0.84, t-values =
18.09, p< 0.01). This result supportsH1.
Main-effects only: Our remaining hypotheses were tested using the structural model
maximum likelihood method (Hair et al., 2017). The overall fit of the structural model 1 was
good, with Chi-square x 2 (21) = 69.568, p < 0.000, Normed x 2 = 3.31; GFI = 0.97; AGFI =
0.94; CFI = 0.98; TLI = 0.97; RMSEA= 0.06. The results also suggest that the structural
model has substantial explanatory power, as the R2 was 0.85 for customer engagement, 0.54
for customer participation and 0.46 for consumer generated advertising. The coefficients,
t-values and p-values for the structural paths are presented in Table IV (Model 1).
As we hypothesised, social interaction ties (b = 0.38, p < 0.001) and brand trust (b =
0.31, p < 0.001) exert significant positive effects on customer engagement, in support of H2
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Attachment
Item Measures Mean (SD) Loading theory
SIE Self-image expression (Kim et al., 2011) perspective
SIE1 Commenting about these brands on Facebook enhances my self-image 3.07 (1.10) 0.82
expression
SIE2 Posting a brand-related contents improves my self-image expression 3.09 (1.10) 0.866
SIE3 A ‘like’ on these brands Facebook fan pages boosts my self-image 3.09 (1.17) 0.865
expression 215
SIE4 Overall, interacting with these brands on their Facebook pages improves 3.03 (1.13) 0.849
my self-image expression
BI Brand Identification (Mael and Ashforth, 1992)
BI1 I am very interested in what others say about these brands on Facebook (D) 3.69 (1.01) –
BI2 I feel very proud when people ‘like’my post on the Facebook pages of these 3.87 (1.04) –
brands (D)
BI3 When I post on the Facebook pages of these brands, I usually say ‘we’ 3.07 (1.12) 0.695
rather than ‘they’
BI4 These brands’ successes are my successes 3.18 (1.18) 0.865
SIT Social interaction ties (Chiu et al., 2006)
SIT1 I feel very close to these brands via my interactions with them on Facebook 3.35 (1.05) 0.718
SIT2 These brands interact with me regularly on Facebook (D) 2.90 (1.07) –
SIT3 Interacting with these brands on Facebook helps me maintain social 3.37 (1.05) 0.787
relationships with them
SIT4 Interacting with these brands on Facebook makes me emotionally attached 2.8 (1.11) –
to them (D)
SIT5 Interacting with these brands on Facebook enhances my social 3.26 (1.08) 0.825
relationships with them
BT Brand Trust (Gurviez and Korchia, 2003)
BT1 Interacting with these brands on Facebook helps me trust them 3.34 (1.02) 0.763
BT2 Interacting with these brands on Facebook makes me see them to be 3.31 (1.02) 0.849
transparent
BT3 Interacting with these brands on Facebook makes me perceive them as 3.4 (1.03) 0.812
reliable
BT4 Interacting with these brands on Facebook makes me perceive them as 3.67 (0.92) –
innovative (D)
BT5 I feel comfortable when interacting with these brands on their Facebook 3.57 (0.90) –
pages (D)
EE Emotional engagement (Solem and Pedersen, 2016)
EE1 I am enthusiastic in relation to these brands on their Facebook pages 3.23 (0.90) 0.78
EE2 I feel energetic when in contact with these brands on their Facebook pages 3.09 (0.94) 0.758
EE3 I feel positive about these brands on their Facebook pages (D) 3.48 (0.89) –
CE Cognitive engagement (Solem and Pedersen, 2016)
CE1 On these brands’ Facebook pages, my mind is very focussed on these brand 3.25 (0.97) 0.765
CE2 On these brands’ Facebook pages, I focus a great deal of attention to these 3.25 (0.98) 0.837
brands
CE3 On these brands’ Facebook pages, I become absorbed by these brands 2.94 (1.01) 0.719
BE Behavioural engagement (Solem and Pedersen, 2016) Table II.
BE1 I exert my full effort in supporting these brands on their Facebook pages 2.95 (1.01) 0.763 Operational
BE2 I am very active in relation to these brands on their Facebook pages 2.91 (0.99) 0.835 measures, descriptive
BE3 I try my hardest to perform well on behalf of these brands on their 2.84 (1.01) 0.768 statistics and
Facebook pages standardised factor
(continued ) loadings
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JRIM
13,2 Item Measures Mean (SD) Loading
CP Customer Participation (Nysveen and Pedersen, 2014; Chan et al., 2010)
CP1 I often express my personal needs to these brands on Facebook 2.76 (1.09) 0.694
CP2 I often suggest how these brands can be improved on Facebook 2.90 (1.15) 0.784
CP3 I participate in decisions about how these brands offer their services/ 2.73 (1.09) 0.779
216 products on Facebook
CP4 I often find solutions of my problems together with these brands on 2.84 (1.03) –
Facebook (D)
UG Consumer generated advertising (Moon et al., 2014)
UG1 I post comments, videos, photos, to inform my Facebook friends about these 3.02 (1.20) 0.839
brands I follow on Facebook
UG2 I post comments, videos, photos, to persuade my Facebook friends to use 2.91 (1.19) 0.87
these brands I follow on Facebook
UG3 I post comments, videos, photos, to create awareness about these brands I 3.12 (1.18) 0.864
follow on Facebook
UG4 I ‘like’ advertisements that these brands I follow on Facebook post on their 3.51 (1.06) –
fan pages (D)
UG5 Overall, I post brand-related contents (e.g. Product review, experience with 2.94 (1.11) 0.751
the brand, etc.) on Facebook
Notes: Normed x2 = 1.95; GFI = 0.94; AGFI = 0.92; CFI = 0.97, TLI = 0.96; RMSEA = 0.038; (D) indicates
Table II. that the item was dropped as a result of scale purification
Construct Mean SD CA CR AVE MSV SIE BI SIT BT EE CE BE CI UG
SIE 2.889 0.869 0.912 0.913 0.723 0.508 0.850
BI 2.452 0.711 0.750 0.760 0.616 0.508 0.713 0.785
SIT 2.862 0.694 0.815 0.821 0.605 0.418 0.609 0.574 0.778
BT 2.889 0.723 0.848 0.850 0.654 0.320 0.380 0.288 0.505 0.809
Table III. EE 2.830 0.630 0.743 0.743 0.591 0.472 0.566 0.553 0.647 0.566 0.769
Construct descriptive CE 2.874 0.684 0.812 0.818 0.601 0.472 0.544 0.490 0.602 0.529 0.687 0.775
statistics, reliability BE 2.880 0.727 0.831 0.832 0.623 0.436 0.541 0.593 0.631 0.424 0.661 0.648 0.789CI 2.394 0.686 0.794 0.797 0.567 0.424 0.403 0.376 0.521 0.351 0.442 0.482 0.651 0.753
and validity UG 3.024 0.966 0.898 0.900 0.693 0.399 0.390 0.448 0.477 0.311 0.444 0.411 0.632 0.58 0.832
measures and
correlations Note: Diagonal numbers are average variance explained by each construct (AVE)
and H3, respectively, an indication that bonding-based attachment is significantly associated
with customer engagement. In addition, as expected, identity-based attachment is positively
associated with customer engagement. Thus, self-image expression exerted a significant effect
on customer engagement (b = 0.09, p < 0.001) supporting H4; likewise brand identification
exerted a significant effect on customer engagement (b = 0.32, p < 0.001) supporting H5.
Furthermore, customer engagement exerted significant influences on customer participation
(b = 0.64, p < 0.001) and consumer generated advertising (b = 0.60, p < 0.001) in support of
H6 andH7, respectively.
We controlled for age, gender and number of brands followed on Facebook on customer
participation and consumer generated advertising. This was done by treating the controls as
independent variables, thus, having them regress on the endogenous variables (customer
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Attachment
theory
perspective
217
Table IV.
Hypotheses and
standardised
structural paths
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Path Standardized direct effects Standard error Critical ratios p-value Result
Direction effect
Social interaction ties! customer engagement (H2) 0.383 0.016 17.922 *** Supported
Brand trust! customer engagement (H3) 0.313 0.012 18.79 *** Supported
Self-image expression! customer engagement (H4) 0.099 0.014 4.218 *** Supported
Brand identification! customer engagement (H5) 0.321 0.017 13.809 *** Supported
Customer engagement! Customer participation (H6) 0.645 0.037 22.586 *** Supported
Customer engagement! Consumer generated advertising (H7) 0.606 0.056 19.599 *** Supported
Controls
Number of brands followed on Facebook! Customer participation 0.014 0.020 0.561 0.575
Number of brands followed on Facebook! Consumer generated advertising 0.021 0.013 0.766 0.444
Age! Customer participation 0.025 0.022 1.010 0.313
Age! Consumer generated advertising 0.005 0.035 0.190 0.846
Gender! Customer participation 0.023 0.033 0.948 0.343
Gender! Consumer generated advertising 0.009 0.053 0.319 0.750
Notes: Adjustment measures – Normed x 2 = 3.31; GFI = 0.97; AGFI = 0.94; CFI = 0.98; TLI = 0.97; RMSEA= 0.06; *p< 0.05, **p< 0.01, ***p< 0.01
JRIM participation and consumer generated advertising) and co-vary with other non-endogenous
13,2 variables (social interaction ties, brand trust, self-image expression and brand identification)
in AMOS, following the suggestion by Gaskin (2016). However, the control variables did not
significantly influence the consequences of customer engagement.
Discussion of findings
218 Brand attachment and customer engagement are normally studied in isolation. To bridge
this gap in the literature, we examined the relationship between brand attachment and
customer participation and consumer generated advertising on a brand’s Facebook page.
We also ascertain the mediating role of customer engagement in this relationship.
Drawing on the attachment theory (Ainsworth, 1967, 1969), we conceptualised brand
attachment from two perspectives; bonding-based attachment and identity-based
attachment. Identifying the elements of these two dimensions of brand attachment, we
tested how these elements drive customer engagement on a brand’s Facebook page. Our
first hypothesis proposed customer engagement as a higher-order concept consisting of
cognitive engagement, emotional engagement and behavioural engagement as some
existing studies have defined customer engagement (Dwivedi, 2015; Hollebeek and Chen,
2014; Brodie et al., 2011). In support of this argument, we found statistically significant
relationships supporting our higher-order concept. An indication of this was that
customers in our study who were engaged with brands on Facebook not only spend their
energy, time and effort on activities such as supporting these brands on their Facebook
pages, writing comments and liking post, but were enthused and felt positive about these
brands. The findings showed that they had the brand in mind and concentrate on the
ongoing discussions about the brands they engage with on their Facebook fan page.
We ascertained whether consumers’ attachment to brands has impact on their
engagement with these brands on Facebook. Our findings show that customer engagement
on a brand’s Facebook page is driven by bonding-based attachment to the brands and
identity-based attachment. The bond between consumers and their favourite brands, which
is manifested in strong ties and the trust consumers have in the brands, had a significant
impact on customer engagement. Our findings suggest that having strong ties and frequent
interactions with consumers drive them to become enthused, attentive and active
contributors to positive discussion about the brand on the brand’s Facebook page.
Additionally, as shown in our H3, which is supported, consumers’ trust in a brand is
necessary for them to engage the brand on its Facebook page. This trust is built through
consistent interactions with the consumers on the brand’s Facebook page. Such interactions
on Facebook make consumers see the brand as transparent and innovative. These results
are parallel with Putnam (1995) who argues that trust and emotional connection drive people
to engage each other in community activities.
The findings from H4 and H5 show that identity-based attachment drives customer
engagement on Facebook. That is, brand identification and self-image expression were
positively related to customer engagement. What this means is that consumers who are
proud of some brands and show interest in what people say about the brand engage the
brand on the brand’s Facebook page. As the existing literature has shown, consumers
identify themselves with brands and use brands to improve their self-image (Khoo-
Lattimore and Prayag, 2016; Jamal and Goode, 2001), and this is a good basis to drive such
consumers to engage the brands on Facebook as our study has shown.
In our study, we also examined the consequences of customer engagement on Facebook.
The results show that customer engagement on Facebook results in customer participation
in brand building and consumer generated advertising. Customers who engage their
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favourite brands on Facebook express their needs and offer suggestions to the brands as to Attachment
how the brand can be improved. These consumers also take active part in finding solutions theory
to the problems they are facing with regard to using the brand. These results are consistent
with Kietzmann et al. (2011) who argue that consumers who are satisfied with some brands perspective
sometimes create contents online to promote their brands. In our case, the consumers
participate in solving their problems relating to the brand, and generate contents to create
awareness about the brand and recommend the brand to others on the Facebook platform. 219
Theoretical contributions
Our primary theoretical contribution is that we extended the attachment theory and its
application in the marketing discipline. This study seem to be the first in offering a useful
model that explains customer engagement in brand building on Facebook by applying
elements of bonding-based attachment and identity-based attachment. Our study shows
that consumers’ feeling of “bondedness” to a brand, and its inclusion into their ‘self’
facilitates customer participation, and encourages consumer generated advertising via
customer engagement. In other words, consumers’ participation and creation of contents on
a brand’s Facebook page, which help in brand building, is driven by two dimensions of
attachment, bonding and identity, when facilitated by engagement. Furthermore, our study
indicates that customer engagement accounts for the relationship that exists between
attachment (bonding and identity) and customer participation and encourages consumer-
generated advertising.
Likewise, it identifies various elements that constitute bonding-based attachment and
identity-based attachment that facilitate customer participation and consumer generated
advertising on Facebook. For example, we identified self-image expression and brand
identification as elements of identity-based attachment while social interactions, ties, and
brand trust were identified as elements of bonding-based attachment that drive customer
participation and consumer generated advertising on a brand’s Facebook page through
customer engagement.
Finally, our research supports previous conceptualisation of customer engagement as a
higher-order construct even within the digital environment. We hypothesised customer
engagement as a multi-dimensional model defined as a customer interactive experience
taking place within an environment and characterised by cognitive, physical and emotional
attachment. The results supported our arguments based on a three-dimensional factor
structure.
Practical implication
We argued that the attachment theory provides for a more complete representation of a
person’s sense of the finest balance between closeness to and distance from brands on digital
platforms such as Facebook, to affect digital engagement resulting in customer participation
and consumer generated advertising. In support of this argument, we found statistically
significant, direct relationships between each of the attachment theory antecedents and
customer engagement. In addition, we found that customer engagement’s statistical
significance is directly associated with customer participation and consumer generated
advertising. Therefore, when examining customer–brand relationship building, marketers
should consider the ties consumers have with the brand and how consumers trust the brand.
Additionally, marketers should consider and project the elements of a brand that
enhances the self-image of the target consumers. Again, what is worth considering in this
relationship is the commonalities that consumers share with the brand. Our research
suggests that the creation of bonding-based attachment and identity-based attachment on
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JRIM digital platforms can enhance customer engagement, which results in customer participation
13,2 and consumer generated advertising. This conceptual model provides managers with
strategies for increasing customer participation and consumer generated advertising, which
is key to online sales and business performance (Ye et al., 2009).
Important managerial decisions therefore revolve around getting to know customers,
interacting with them, and building a unique and enduring relationship with them. It also
220 means that brands managers utilising Facebook to promote their brands must have closer
relationships with targeted customers based on trust, social bonds, image, and identity on
digital platforms. To develop the trust route of customer engagement, marketers can focus on
innovation and be reliable. The advent of social technologies is an opportunity for marketers
to show how innovative they are in terms of creating more touch points for their consumers.
Marketers must also fulfil their promises to consumers; in this way, they instil trust and
confidence in the consumers, which drive them to engage even more on the brand’s Facebook
page.
Instilling trust in consumers is a way of creating a strong tie with the consumers, which
also drives them to engage the brand on its Facebook page. Furthermore, to drive and engage
consumers on a brand’s Facebook page, brand managers and marketers in general should
create and communicate a brand image that is consistent with the self-image of their target
market or the image their target aspires to attain. With this, brands will be able to drive their
consumers to their Facebook pages for fruitful interactions. Similarly, communicating a
brand’s resemblance with the target market or consumers has the potential of driving
consumers to engage brands on Facebook. Consumers have a need for association and
identification and they seek such from brands.
Limitations and areas for further research
Although our study makes a substantial contribution to literature, there are some limitations
that serve as an avenue for future research. We recognise that there is the possibility of
limiting external validity, as the majority of our respondents are from Ghana. This might
affect generalisation of the findings. Therefore, we recommend that future studies may
consider other approaches such as the intercept approach, which can yield a higher response
rate and capture responses from different geographical locations to improve generalisation.
Again, our study was limited to only brands’ Facebook fan pages; however, there are
numerous social media platforms on which brands interact with their consumers. Therefore,
we recommend that future studies should consider examining the impact of brand
attachment on customer engagement on other platforms such as in brand communities.
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Corresponding author
John Paul Basewe Kosiba can be contacted at: john.kosiba@upsamail.edu.gh
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