Journal of Marketing Management

ISSN: 0267-257X (Print) 1472-1376 (Online) Journal homepage: http://www.tandfonline.com/loi/rjmm20

Social media engagement: a model of antecedents

and relational outcomes

Laurence Dessart

To cite this article: Laurence Dessart (2017): Social media engagement: a model
of antecedents and relational outcomes, Journal of Marketing Management, DOI:
10.1080/0267257X.2017.1302975

To link to this article: http://dx.doi.org/10.1080/0267257X.2017.1302975

Published online: 27 Mar 2017.

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Download by: [University of Newcastle, Australia] Date: 27 March 2017, At: 04:46
JOURNAL OF MARKETING MANAGEMENT, 2017
http://dx.doi.org/10.1080/0267257X.2017.1302975

Social media engagement: a model of antecedents and

relational outcomes
Laurence Dessart
Marketing Department, KEDGE Business School, Talence, France

ABSTRACT ARTICLE HISTORY

This article investigates individual-level antecedents and rela- Received 16 September 2016
tional outcomes of social media engagement. Social media Accepted 16 February 2017
engagement approached in this study is a three-dimensional KEYWORDS
construct composed of affective, cognitive and behavioural Social media; consumer
dimensions. Surveying more than 48 Facebook pages, span- engagement; online
ning nine product categories and 448 consumers, the results community; brand
show that product involvement, attitude towards the commu- relationship
nity and online interaction propensity all impact social media
engagement. The study also reveals that high social media
engagement increases brand relationships significantly, parti-
cularly affecting brand trust, commitment and loyalty.
Additionally, community engagement appears as a precursor
of brand engagement. These findings provide insight into
antecedents and outcomes of engagement for academic
research and bring value to online brand and community
management.

Introduction
At a time in which companies are increasingly competing for consumer attention,
social media afford unique opportunities to engage consumers on deep and
meaningful levels. Consumers partake in interactive experiences with brands or
community members beyond a simple purchase (Brodie, Ilic, Juric, & Hollebeek,
2013), creating more enduring and intimate relationships with brands (Sashi, 2012).
Given that the global social media user population comprises 2.2 billion people in
2016 and is expected to grow to 3 billion by 2020 (Statista, 2016), strategic
consumer insight focusing on social media is essential for brands. This study uses
the concept of social media engagement, a potent construct that captures the
complexity of social media participation (Dessart, Veloutsou, & Morgan-Thomas,
2015) to provide such insight.
The role of social media engagement in a nomological network of relationships
with other consumer- and brand-related constructs (Hollebeek, Glynn, & Brodie,
2014) is of interest here. For this reason, the study focuses on understanding
specific drivers and outcomes of social media engagement. Understanding the

CONTACT Laurence Dessart laurence.dessart@kedgebs.com KEDGE Business School, 680 Cours de la

Libération, 33405 Talence Cedex, France
© 2017 Westburn Publishers Ltd.
2 L. DESSART

reasons why people engage and the results of engagement affects the way
companies manage brands and communities online in important ways. Given the
paucity of studies investigating on a large scale and in a generalisable manner
these relationships (Hollebeek, Conduit, & Brodie, 2016), this study endeavours to
determine some of the key drivers and outcomes of social media engagement.
To date, research into the antecedents and outcomes of social media engagement is
high on the agenda of engagement practice and scholarship. This goal is evidenced in
recent special issues (e.g. Journal of Marketing Management, 2016) and by the call for
dedicated research on how ‘social media and other marketing activities create
engagement’ (MSI, 2014, p. 4). Hollebeek et al. (2016) prove the lack of research in
this domain and the existing research’s limited scope for generalisability. Specifically,
existing studies have restricted contextual scopes (e.g. Vivek, Beatty, & Morgan, 2012),
focus on a small set of variables (e.g. Malthouse Calder, Kim, & Vandenbosch, 2016), or
include too few brands or products (e.g. Hollebeek et al., 2014), calling for an extension
of the generalisability of this stream of research (Hollebeek et al., 2016).
Studies exploring the antecedents and outcomes of engagement on social media
from the last few years have opened avenues. Theories of regulatory fit, for instance, can
help determine engagement types and levels on Facebook (Solem & Pedersen, 2016),
and personality traits of consumers also affect engagement formation (Marbach, Lages,
& Nunan, 2016). Other exploratory work also suggests that consumers engage in online
community settings to reduce information search and perceived risk (Brodie et al., 2013).
In terms of outcomes, social media engagement is a trigger for buying intentions and
decisions (Brodie et al., 2013; Malthouse et al., 2016).
Despite these interesting advances, knowledge is still lacking, specifically on the
role of consumer engagement on brand relationship development across contexts
(Hollebeek et al., 2016). Much conceptual and exploratory work exists on the role of
consumer engagement in brand-relationship formation (Brodie et al., 2013;
Hollebeek, 2011b; Van Doorn et al., 2010; Vivek et al., 2012), but this work is still
to be validated in social media environments. Understanding the ways in which
engagement can transform individual consumer predispositions into beneficial
brand outcomes is at the heart of this study.
The purpose of the present study is thus to provide an account of some of the key
individual-level antecedents and relational outcomes of social media engagement.
Conceptualising social media engagement as a multifocal, multidimensional and
context-specific phenomenon, the study proposes individual-level antecedents and
anticipates social media engagement to lead to a series of positive brand-relationship
outcomes, including brand trust, commitment and loyalty.
This article starts with a literature review conceptualising social media
engagement; its dimensions, actors and focus and then reviews existing insights
and gaps concerning its antecedents and outcomes. The next section presents the
hypotheses, leading to a conceptual model of social media engagement. The
methodology covers the practical aspects of data collection and analysis, followed
by results and discussions. The last section deals with the practical and theoretical
implications of the study.
 JOURNAL OF MARKETING MANAGEMENT 3

Literature review and hypothesis formulation

Social media engagement
Consumer or customer engagement scholarship has grown significantly in the last
7 years (Dessart, Veloutsou, & Morgan-Thomas, 2016; Sprott, Czellar, & Spangenberg,
2009; Van Doorn et al., 2010). The overall agreement resulting from recent customer
engagement research pictures it as a ‘psychologically based willingness to invest in the
undertaking of focal interactions with particular engagement objects’ (Hollebeek et al.,
2016, p. 2). Three dimensions constitute engagement: cognitive, affective and
behavioural (Calder, Malthouse, & Schaedel, 2009; Dessart et al., 2015; Hollebeek,
2011a, 2011b). Specifically, Dessart et al. (2015, 2016) conceptualise cognitive
engagement similar to the overall mental activity focused on something, involving
attention and absorption. Affective engagement is composed of enthusiasm and
enjoyment with regard to an engagement object. Last, behavioural engagement
represents the active manifestations of the concept, including sharing, learning and
endorsing behaviours.
Social media engagement is a context-specific occurrence of consumer engagement
(Brodie et al., 2013) worth considering since engagement varies across online media
(Geissinger & Laurell, 2016). Social media are vast ecosystems with intricate networks of
relationships and a multiplicity of social nets and levels of interactions. Scholars define
them as ‘a group of Internet-based applications that build on the ideological and
technological foundations of Web 2.0, and allow the creation and exchange of User
Generated Content’ (Kaplan & Haenlein, 2010, p. 61). Social media include social
networking sites such as Facebook or Instagram, but also other media like YouTube,
Flickr or blogs. The important feature of social media when it comes to consumer
engagement is that they allow consumer–brand interactions. Specifically, when a
brand is present on social media and uses it to connect with its consumers, an online
brand community is formed (Zaglia, 2013). Given the consumer–brand interactions that
social media allow, this study focuses on online brand communities embedded on social
media as the context of engagement (Brodie et al., 2013; Zaglia, 2013).
This focus follows work by Breidbach, Brodie, and Hollebeek (2014), which pinpoints
the importance to model and study engagement with respect to specific consumer
touchpoints. Furthermore, social media enable ‘more frequent, faster and richer
interactions among large groups of people’ (Sashi, 2012, p. 269). One way of fostering
these rich interactions on social media is the use of online brand communities, which are
powerful tools in consumer relationship strategies and are at the forefront of academic
and industry studies (Forrester Research, 2014).
In this context of online brand communities embedded on social media, this study
defines social media engagement as the state that reflects consumers’ positive individual
dispositions towards the community and the focal brand as expressed through varying
levels of affective, cognitive and behavioural manifestations that go beyond exchange
situations. This study focuses on the positive facet of engagement experiences.
Although acknowledging the existence and importance of negatively valenced
engagement (Hollebeek & Chen, 2014), this article focuses on positive engagement
and its positive outcomes to extend existing work in this domain (Brodie et al., 2013).
4 L. DESSART

A focus on positive engagement is adopted in this article for several reasons. First, the
treatment of negative engagement would necessitate a different method based on the
status of extant research negative engagement research. Indeed, the field still embryonic
and mostly restricted to conceptualisation and exploratory work (Hollebeek & Chen,
2014), whereas positive engagement research already benefits from stronger empirical
ground, allowing to contribute to the development of existing frames and models (e.g.
Dessart et al., 2015, 2016; Marbach et al., 2016) in a confirmatory manner. Further,
negative engagement seems driven by other antecedents than positive engagement
(Dolan, Conduit, Fahy, & Goodman, 2016). Specifically, brand-related motives are
prominent in the development of negative engagement (Hollebeek & Chen, 2014)
whereas individual predispositions are not recognised as relevant to study. The article
also uses the term ‘consumers’, rather than ‘customers’, considering that social media
users are ‘consumers’ of the platform, without having to be ‘customers’ of any brand to
engage on the platform.
An important aspect of this definition is the duality of engagement objects: the
community and the brand. On social media, engagement can emerge with respect
to different objects (Wirtz et al., 2013). Algesheimer, Dholakia, and Herrmann (2005)
are precursors of this idea with their study on community engagement in offline
brand communities. In online and social media ecosystems, many recent studies
parallel this notion of community engagement (Wirtz et al., 2013). Brand
engagement, on the other hand, is probably the most studied engagement focus
(Van Doorn et al., 2010; Verhoef, Reinartz, & Krafft, 2010), including in social media
contexts (Malthouse et al., 2016; Marbach et al., 2016). In this study, the view is
that, in online brand communities embedded on social media, the two key
engagement objects are the community, representing the other consumers in the
group, and the focal brand (Brodie et al., 2013; Dessart et al., 2015, 2016). In order
to clarify the concept of social media engagement, Table 1 provides examples of
manifestations of consumer engagement on social media for each of its dimensions
and foci.
Social media engagement comprises community engagement and brand
engagement, and therefore understanding how these two focuses of engagement
coexist becomes important (Brodie et al., 2013). Their specific dynamic might in fact
contribute to the creation, sustenance and vitality of the communities and affect
customer relationships and brand management strategies (Hennig-Thurau et al.,
2010). Despite a lack of research on the interplay between community engagement

Table 1. Example of social media engagement manifestations.

Dimension
of engagement Brand focus Community focus
Affective A consumer feeling happy that a brand has A consumer enjoying interacting with other fans
replied to his question on social media of a brand on social media
Cognitive A consumer who is so absorbed in the content A consumer paying a lot of attention to the
posted by the brand on social media that he comments and replies of other consumers
spends a lot of time browsing it about the brand on social media
Behavioural A consumer sharing his opinion about a product A consumer seeking information about the
with the brand on social media brand and asking other members of the
community for their help or advice on social
media
 JOURNAL OF MARKETING MANAGEMENT 5

and brand engagement (Dessart et al., 2015, 2016), conceptual studies suggest that
community engagement leads to increased levels of brand engagement (Wirtz
et al., 2013). This observation is in line with other community studies that prove
the positive impact of community practices on brand engagement (Schau, Muñiz, &
Arnould, 2009), supporting the development of the first hypothesis:

Hypothesis 1: Community engagement positively influences brand engagement.

Antecedents and outcomes

Appendix 1 gives an account of all consumer engagement research that has
investigated its antecedents and outcomes. The table shows that until 2013, most
studies have been conceptual (e.g. Bowden, 2009; Van Doorn et al., 2010) and none
has a specific social media or online focus. This stream of research, however, shows
a vast interest in the impact of consumer engagement on brand relationship
constructs, such as trust, commitment, satisfaction or loyalty (Bowden, 2009;
Brodie, Hollebeek, Juric, & Ilic, 2011; Hollebeek, 2011a, 2011b), or brand recall and
attention (Sprott et al., 2009). Other conceptual antecedents of engagement
include several individual variables, such as identity or consumption goals (Van
Doorn et al., 2010) or interactivity and involvement (Hollebeek, 2011b; Sprott et al.,
2009), for instance.
Since 2013, scholars have tackled the scarcity of empirical research on the
drivers and outcomes of engagement, particularly in Brodie et al. (2013), who
propose antecedents and outcomes of online brand community engagement on
the basis of qualitative data. More recent studies advance this research by finding
empirical evidence on social media that engagement leads to brand love or word
of mouth (WOM) and that this engagement is driven by specific personality traits
(Marbach et al., 2016). Apart from Brodie et al. (2013), studies focusing on
consumer engagement on social media and its drivers and outcomes are scarce,
to say the least. This lack of interest in social media engagement represents an
important oversight of the engagement literature, also leading to a limited account
of the potential community engagement outcomes and antecedents (Brodie et al.,
2013). However, existing studies provide a guidance to develop hypotheses.
In line with past studies highlighting the importance of individual factors in driving
engagement (France, Merrilees, & Miller, 2016; Marbach et al., 2016; Solem & Pedersen,
2016; Vivek et al., 2012), this article focuses on three variables that capture individual
predispositions: online interaction propensity (OIP), attitude towards community
participation and product involvement. These variables were chosen because they
align with the notion that engagement results from intrinsic motivational triggers
(Brodie et al., 2011).
In communication and psychology disciplines, OIP means the willingness to
communicate with others, and people can exhibit different levels of propensities to
interact (Wiertz & De Ruyter, 2007). OIP is a fairly under-researched individual trait in the
formation of online brand community participation. Blazevic, Wiertz, Cotte, De Ruyter,
and Keeling (2014) determine that general online social interaction propensity is an
explanatory factor for consumer engagement and online interaction behaviours,
6 L. DESSART

confirming its anticipated impact on social media engagement, thus leading to the
second hypothesis:

Hypothesis 2: Online interaction propensity is positively related to social media engage-

ment as defined by a composition of (a) community engagement and (b) brand
engagement.

Despite a lack of focus on attitude in existing consumer engagement

frameworks, past scholarship on online consumer behaviours shows the
importance of the attitudes, particularly using the theory of planned behaviour
(TPB) (e.g. Bagozzi & Dholakia, 2006). Following Wu and Chen (2005), the attitude
towards online community participation reflects in this study the favourable or
unfavourable assessment a consumer makes of participating in the community. In
an extended version of the TPB, Bagozzi and Dholakia (2006) find that attitude
towards brand community participation is a driver of the desire, intention and
behaviour of community participation. Similarly, Casaló, Flavián, and Guinalíu
(2010) show that member attitude towards participation in a firm-hosted online
travel community is a potent driver of the actual intention to participate. These
findings find further conceptual validation in Hennig-Thurau et al. (2010), who
assert that consumers with high positive attitudes towards new media are more
likely to exhibit high levels of new media brand engagement. The following
hypothesis reflects this expected contribution of attitude towards engagement:

Hypothesis 3: Attitude towards community participation is positively related to social

media engagement as defined by a composition of (a) community engagement and (b)
brand engagement.

A last important potential antecedent of social media engagement is

involvement (Hollebeek, 2011b; Sprott et al., 2009; Vivek et al., 2012), but this
relationship has received little empirical attention (Hollebeek et al., 2014).
Studying involvement is important because whether a product generates high or
low involvement could significantly affect consumer engagement with the product
(Hollebeek, 2011a). Although involvement and engagement might seem similar,
involvement does not have a behavioural aspect. In fact, Hollebeek et al. (2014)
prove the empirical distinctiveness of engagement and involvement, further
validating the mediating role of engagement in the relationship between
involvement and self-brand connection. Product involvement overall seems to be
a powerful antecedent of social media engagement, leading to the fourth
hypothesis:

Hypothesis 4: Product involvement is positively related to social media engagement

as defined by a composition of (a) community engagement and (b) brand
engagement.

The potential outcomes of social media engagement fall under the brand relationship
framework. Indeed, consumer engagement frames the next generation of brand
 JOURNAL OF MARKETING MANAGEMENT 7

relationships and offers an extended version of previous relational models (Vivek, Beatty,
Dalela & Morgan, 2014). Appendix 1 proves in particular the strong appetency of
engagement scholarship for relational metrics. Additionally, online community-based
research also stresses the role of online communities in sustaining consumer-brand
relationships (e.g. Matzler, Pichler, Füller, & Mooradian, 2011).
Brand trust and brand commitment are two closely related constructs in
foundational brand relationship research (Chaudhuri & Holbrook, 2002) and in
recent consumer engagement studies (Hollebeek, 2011b). In this study, brand
trust is the willingness of the consumer to rely on the ability of the brand to
perform its stated function (Moorman, Zaltman, & Deshpande, 1992), and brand
commitment is the enduring desire to maintain a valued relationship with a brand
in the long term (Morgan & Hunt, 1994). Brand commitment is based on the
emotional or psychological attachment to and preference for a brand within a
product category (Lastovicka & Gardner, 1979). According to Gambetti and
Graffigna (2010), engagement, in the relational sense of the term, is a way to
build trust and commitment with the brand. More recently, Hollebeek et al.
(2014) showed the impact of engaging with social media brands (such as
Facebook or LinkedIn) on self-brand connection and brand usage intent.
Combined with the conceptual work positing brand trust and brand commitment
as outcomes of brand engagement in social media contexts (Brodie et al., 2013),
the fifth hypothesis reads as follows.

Hypothesis 5: Brand engagement is positively related to (a) brand trust and (b) brand
commitment.

In social media and online community studies, behavioural brand loyalty is a

common dependent variable and success factor of the community (e.g.
Algesheimer et al., 2005; Bagozzi & Dholakia, 2006), thus requiring further
attention in an engagement framework. Similarly, in traditional relationship
marketing, the impact of brand commitment and brand trust on brand loyalty is
well verified (e.g. Garbarino & Johnson, 1999), as well as in brand community
contexts (Marzocchi, Morandin, & Bergami, 2013; Porter & Donthu, 2008).
Conceptually, trust and commitment also have a mediating role in driving loyalty
from engagement (Hollebeek, 2011b), supporting the need for empirical validation
of this relationship. Aligning early relationship marketing studies with community
and consumer engagement research enables positing that, with the precedence of
consumer engagement over brand trust and commitment, the following
hypotheses hold for social media engagement:

Hypothesis 6: Brand trust is positively related to brand loyalty.

Hypothesis 7: Brand commitment is positively related to brand loyalty.

Figure 1 summarises the hypotheses.

8 L. DESSART

INDIVIDUAL-RELATED SOCIAL MEDIA BRAND RELATIONSHIP

ANTECEDENTS ENGAGEMENT OUTCOMES

Online
interaction H2a
propensity
Community Brand trust
H2b H6
engagement
H3a Brand
Attitude H1 H5a
toward loyalty
participation H3b
Brand Brand H5
H4a
engagement commitment
H5b
Product
involvement H4b

Figure 1. The conceptual model.

Method
Official brand pages on Facebook serve as the context of this study for several reasons.
Facebook is the biggest global social media in terms of usage, with more than 1 billion
registered users and 1.59 billion monthly active users (Statista, 2016). Additionally,
Facebook is a powerful tool for brand relationships creation: users can share their
enthusiasm about the brand and are united by their common interest in the brand
(Malhotra, Malhotra, & See, 2012). Facebook pages are also sources of information and
social benefits to the members (De Vries, Gensler, & Leeflang, 2012). Recent focus on
Facebook in the context of consumer engagement further supports the adequacy of
Facebook as an engagement medium (Solem & Pedersen, 2016). Additionally, Facebook
is a rich platform for brands and supports a large variety of brand pages, depending on
the type of product and business.
A first level of purposive sampling is applied in the selection of Facebook pages (30
million Facebook pages exist at the time of the study) to categorise the type of pages
under investigation. The aim of this categorisation is to make sure each type of
Facebook page is represented, thus using Facebook’s own classification criteria, as
well as Social Bakers (2014) to come up with a selection of nine brand page
categories: (1) food and beverage, (2) travel, (3) fashion and beauty, (4) entertainment,
(5) durable goods, (6) services, (7) technology, (8) retail and (9) others. The research does
not attempt statistical representativeness of the number of existing Facebook pages.
Rather, a good span of all pages in terms of product types seeks to extend the validity of
previous engagement studies, which often focus on service brands (e.g. Jaakkola &
Alexander, 2014).
The questionnaire displays multiple-choice, 7-point Likert scale questions,
capturing constructs of interest with existing scales. Bagozzi and Dholakia’s (2006)
scale measures attitude towards community participation; Laurent and Kapferer’s
(1985) research measures product involvement; Wiertz and de Ruyter’s (2007) scale
 JOURNAL OF MARKETING MANAGEMENT 9

measures OIP; Chaudhuri and Holbrook’s (2001) research measures brand trust; El-
Manstrly and Harrison’s (2013) research operationalises brand commitment; Odin,
Odin, and Valette-Florence’s (2001) research measures brand loyalty and Dessart
et al.’s (2016) scale determines social media engagement, composed of community
and brand engagement. This latter scale was chosen as a measure of social media
engagement in opposition to other recent engagement scales (e.g. Hollebeek et al.,
2014; Vivek et al., 2014) because it is the one that best allows capturing the dual
engagement focus on the brand and the community, and reflects the conceptual
position on dimensionality. Furthermore, it allows measuring the enduring and
ongoing nature of engagement, in contrast to Hollebeek et al. (2014), which is
interaction-bound. Dessart et al. (2016) also provides a better operationalisation of
the social media engagement concept and its dimensionality than Vivek et al.
(2014), who pool together the emotional and participative dimensions into one.
The detail of the items used in this study is provided in Appendix 2.
Prior to full-scale collection, the survey is pretested on a sample of 101 undergraduate
and postgraduate business students, enabling the research to validate the good
understanding of the questions, the appropriateness of their wording and sequencing,
and offer a first check of the internal consistency, means, variances, inter-item
correlations and factor structure.
Data are collected by contacting brand page administrators and asking them to
post the link to the survey on their page. This approach ensures that the study is
done with respect to the chosen brands and brand categories and that respondents
to the survey are indeed members of these communities. This match would not
have been possible by contacting people through other channels. Prior brand page
experience is a prerequisite to having the required level of knowledge and memory
to answer the questionnaire. Additionally, the fact that the post is written by the
administrator increases the source credibility of the survey and builds trust for
respondents, which is important in the study of community members who are hard
to reach. Over a period of 5 months, researchers contacted a total of 326 page
administrators, with 48 of them posting the survey on their page, resulting in a
posting rate of 15%. When clicking on the link, respondents are redirected to the
web-based questionnaire.
A total sample size of 448 respondents constitutes the final sample. The
respondents’ age ranges between 18 and 82 years old with a median of 29, and
the study consists of 51% female. Respondents come from a total of 75 different
countries, out of which the United Kingdom and the United States are most
represented. In terms of brand categories, food and beverage achieve the highest
overall score (33%), followed by travel (21%), fashion and beauty (14%), and
entertainment (12%). These brand categories match Facebook’s current best-
performing categories. Roughly 83% of the respondents are purchasing clients of
the brand they follow, evidencing that online brand use and membership does not
imply prior buying behaviour. Respondents exhibit relatively high levels of Facebook
activity because close to 30% of them spend 60 min or more on Facebook every day.
The complete detail of sample characteristics and brand pages surveyed can be found
in Appendices 3 and 4.
10 L. DESSART

Results
The analysis uses a two-phase structural equation modelling (SEM) process, focusing first
on the measurement model to assess the factor structure and then looking at the
structural model to test the hypothesised links between the variables and assess the
fit of the full structural model with the data (Anderson & Gerbing, 1988).

Reliability and validity

Establishing the reliability and validity of the scales is essential before testing the model.
The constructs are internally consistent with all Cronbach’s alpha values above 0.86
(Bagozzi & Yi, 1988). The convergent validity indicators are also satisfactory, with average
variance extracted (AVE) values all above 0.61, supporting the measurement model’s
convergent validity. The coefficient of reliability (CR) indicators are equal to or above
0.83 for all constructs, which further indicate reliability, as Hair, Bush, and Ortinau (2006)
suggest. Correlations among latent variables are all significant (CR ≥ 1.96). All AVEs are
superior to the square of their related pairwise correlations, which also indicates that the
measurement model achieves discriminant validity, as shown in Table 2. As expected
due to their conceptual similarity, community engagement and brand engagement
show a high pairwise correlation (0.89). This figure is, however, not problematic since
it shows good construct validity (Bagozzi, Yi, & Phillips, 1991), and supports the fact that
they measure the same construct, albeit for a different engagement focus. Further, a full
Fornell–Larcker test was computed, and the maximum shared variances and average
shared variances for all variables are smaller than their AVEs, thus ensuring complete
discriminant validity.

Model analysis
The measurement model exhibits a chi-square of 1741.34 (p = 0.00) with 1535 degrees
of freedom, comparative fit index (CFI) = 0.84, Tucker Lewis Index (TLI) = 0.83 and an
root mean square residuals (RMSEA) = 0.06. All standardised loadings are above or close
to 0.50 and t-values are all significant (p < 0.01). The reasons for CFI and TLI measures
below the advocated guidelines are largely because of the nature of the engagement
scales included in the model, because lengthy and complex scales are more difficult to

Table 2. Reliability and validity.

Constructs 1 2 3 4 5 6 7 8
1. Brand engagement 0.84 0.79 0.32 0.47 0.43 0.25 0.33 0.15
2. Community engagement 0.89 0.86 0.21 0.24 0.20 0.13 0.29 0.22
3. Brand loyalty 0.56 0.46 0.61 0.30 0.43 0.17 0.17 0.05
4. Brand trust 0.69 0.49 0.55 0.74 0.67 0.16 0.28 0.11
5. Brand commitment 0.66 0.44 0.66 0.82 0.75 0.12 0.16 0.07
6. Product involvement 0.50 0.36 0.42 0.40 0.34 0.89 0.22 0.02
7. Attitude 0.58 0.54 0.41 0.53 0.40 0.46 0.74 0.05
8. OIP 0.39 0.47 0.22 0.33 0.26 0.14 0.23 0.78
CR 0.94 0.95 0.86 0.86 0.90 0.94 0.92 0.93
Alpha 0.90 0.93 0.86 0.91 0.90 0.94 0.91 0.93
Note: The diagonal (values given in bold) represents the AVEs of each construct; below the diagonal are the pairwise
correlations between constructs and above are the squared pairwise correlations.
 JOURNAL OF MARKETING MANAGEMENT 11

use in models with many variables and may result in redundancy between closely
related items (Ruvio, Shoham, & Brencic, 2008). It is the case here because
engagement is measured for two different engagement objects. However, the
constructs perform perfectly at their higher-order levels, showing no evidence of
multicollinearity, and the engagement scale is valid (Dessart et al., 2016).

Hypothesis testing
Hypothesis testing uses SEM with maximum likelihood estimation. In the causal path
model, the statistics support that the data fit the model at adequate levels with a
significant chi-square = 3441.881 (p = 0.00) with 1066 degrees of freedom. The CFI is
0.89, TLI is 0.90 and RMSEA equals 0.06. The study discusses the acceptable support for
model fit prior to the SEM measurement model results.
Most of the hypothesised relationships hold according to the path analysis, with
different yet largely consistent estimates for each sample. More specifically, H1 and H2b
fail to account for the impact of OIP and attitude towards community engagement on
online brand engagement. Additionally, the data fail to support H7, evidencing rejection
of the impact of brand trust on brand loyalty.
The significance of the model’s path coefficient shows that online brand engagement
is positively influenced by product involvement (β = 0.20, sig = 0.00) and community
engagement (β = 0.75, sig = 0.00), showing support for H1 and H4b. H2b (β = − 0.20,
sig = 0.69) and H3b (β = 0.09 sig = 0.07), however, are not supported. OIP and attitude
towards community participation therefore have no effect on online brand engagement.
The results also show that the most powerful predictor of brand engagement is by far
community engagement (β = 0.75), with an overall R2 of 0.73 for brand engagement.
All the hypotheses related to the drivers of community engagement exhibit
significant values. Support is therefore granted to H2a (β = 0.39, sig = 0.00), H3a
(β = 0.47, sig = 0.00) and H4a (β = 0.18, sig = 0.00). This result shows that community
engagement is significantly and positively influenced by consumer’s OIP, attitude
towards community participation and product involvement. Data show that the
strongest influence of community engagement derives from consumer’s general
attitude towards online participation (β = 0.47, sig = 0.00), directly followed by OIP
(β = 0.39, sig = 0.00), with an R2 of 0.40.
Brand trust is positively influenced by brand engagement, supporting H5a (β = 0.72,
sig = 0.00), and H5b is also validated, as evidenced by the significant beta values
(β = 0.69, sig = 0.00). Brand engagement therefore affects brand trust and brand
commitment, with a stronger influence on brand trust. Last, the impact of brand trust
and brand commitment on brand loyalty is hypothesised, respectively, with H6 and H7.
The data show rejection of H6 (β = 0.09, sig = 0.19). The impact of brand commitment on
brand loyalty is supported, denoting acceptance of H7 (β = 0.60, sig = 0.00), with an R2
for brand loyalty of 0.42. Table 3 summarises the hypotheses’ support.

Alternative model
An alternative model whereby brand commitment and brand trust are hypothesised to
be antecedents of consumer engagement rather than outcomes is thus run, since the
12 L. DESSART

Table 3. Hypothesis testing.

Hypothesis Path β CR Hypothesis support
H1 Community engagement -> brand engagement 0.75** 9.75 Supported
H2b Online interaction propensity -> brand engagement −0.2 −0.39 Not supported
H3b Attitude towards community -> brand engagement 0.09 1.78 Not supported
H4b Product involvement -> brand engagement 0.20** 4.19 Supported
H2a Online interaction propensity -> community engagement 0.39** 6.41 Supported
H3a Attitude towards community -> community engagement 0.47** 7.49 Supported
H4a Product involvement -> community engagement 0.18* 3.03 Supported
H5a Brand engagement -> brand trust 0.72** 10.50 Supported
H5b Brand engagement -> brand commitment 0.69** 9.39 Supported
H6 Brand trust -> brand loyalty 0.09 1.28 Not supported
H7 Brand commitment -> brand loyalty 0.60** 6.80 Supported
*Significant at the 0.05 level.
**Significant at the 0.01 level.

direction of the relationship, as we hypothesise it, has been conceptually challenged

(Hollebeek, 2011a) The same statistical techniques as previously detailed are used. In this
alternative model, social media engagement is not significantly impacted by brand trust
and brand commitment (β are all below 0.14 and significance levels above 0.05). Brand
relational variables can therefore not be modelled as antecedents of online brand
community (OBC) engagement. Goodness of fit values of the alternative model
support this assertion with: chi-square = 2705.92 (p = 0.00) with 685 degrees of
freedom. The CFI is 0.74, TLI is 0.76 and RMSEA equals 0.11. The testing of the
alternative model shows that brand trust and commitment should definitely not be
modelled as antecedents of OBC engagement, and that trust and commitment are also
better modelled as outcomes of online brand engagement. In other words, the testing
of the alternative model further validates the adequacy of this study’s model.

Discussion
The results of the hypothesis testing provide important insights into the antecedents
and outcomes of social media engagement, as well as the link between engagements
with two focal objects in social media settings. Importantly, the interplay between the
two aspects of social media engagement addressed in H1 is interesting because it shows
that community engagement is the strongest predictor of brand engagement,
highlighting the vital explanatory power of community participation over brand
engagement (Wirtz et al., 2013). This realisation echoes research in online brand
communities whereby interactions with a community of consumers foster stronger
and more frequent brand-related behaviours and attitudes (e.g. Algesheimer et al.,
2005), also suggesting that the community has a central role in providing brand-
related information, thus increasing brand-related experiences and practice (Calder
et al., 2009; Schau et al., 2009). Through community engagement, one’s level of brand
engagement is triggered and enhanced.
Brand engagement, however, is not directly affected by individual dispositions, other
than product involvement. There may be multiple reasons why OIP and attitude towards
community participation do not impact brand engagement. Despite being used to
online interactions and having a general positive attitude towards it, OBC users might
feel that engaging with the brand in public setting is inadequate, preferring to keep
 JOURNAL OF MARKETING MANAGEMENT 13

direct brand interactions in the private sphere. Indeed, consumers are often conscious of
what others will think if they interact with brands too closely (Patterson, 2012), thus
relating to issues of self-presentation (Hollenbeck & Kaikati, 2012). This could also be due
to online privacy concerns (Murphy, Hill, & Dean, 2014) such as fear of the brand using
these interactions for commercial purposes in the future. Research also shows that when
a community becomes too big, people feel hindered in their interactions with brands
(Dholakia, Bagozzi, & Pearo, 2004). This factor was not accounted for in this study but
could be a moderator of the relationships in H2b and H3b. On the other hand,
involvement with a product is in multiple conceptual and exploratory settings an
important driver of brand engagement offline (Dwivedi, 2015; France et al., 2016), and
this study proves that this observation is also valid in online social media settings.
Interestingly, although brand engagement on social media cannot be rely heavily on
individual predispositions, it can emerge if social stimuli exist in the form of community
engagement. The support of H1 in this study is a reminder of the crucial role of the
community of users on social media in generating consumer–brand interactions (Ashley
& Tuten, 2015). Specifically, consumers might not want to interact with brands directly
without the intermediation of the community (Fournier & Avery, 2011). This study
suggests that if consumers are involved emotionally, cognitively and behaviourally
with other consumers, identical forms of engagement with the brand are more likely
to ensue. This echoes existing brand community research showing that by being more
exposed to brand-related information and gaining increased brand-related experiences
and practice through community engagement (Calder et al., 2009; Schau et al., 2009),
one’s level of brand engagement is triggered and enhanced. Overall, the findings
support that social media represent unique contexts of engagement with unique
features (Brodie et al., 2013) and thus necessitate dedicated treatment (Dessart et al.,
2015, 2016).
Regarding the drivers of community engagement, this study advances the
understanding that individuals on social media exhibit different engagement levels
based on their own internal predispositions (France et al., 2016). Specifically, individual
factors of attitude, involvement and interaction propensity influence engagement with
the community (Blazevic et al., 2014). These variables not only affect consumers’
behavioural participation on social media but also the whole engagement
manifestations of affect, cognition and behaviours towards other community
members. The findings grant further support to the work of De Villiers (2015) and also
imply that community engagement on social media is a function of individual traits and
predispositions, a postulate that so far has been only conceptual (Wirtz et al., 2013). The
findings also support the relevance of considering consumer individual profiles and
identity traits in community engagement strategies (Solem & Pedersen, 2016).
Considering the outcomes, brand engagement affects trust and commitment to the
brand. Trust is likely to be increased by engagement because, in the interactive process
of engagement, consumers give brands the opportunity to ensure themselves of their
quality as a relationship partner (Hollebeek, 2011b). Similar to trust, engagement grows
over the long term and repeat occurrences, and if a brand behaves in a way to enable
consumers to satisfactorily engage with them, trust is likely to occur. Echoing the recent
brand community and social media literature, if the brands provide compelling content
to share and learn from, they entertain and keep consumer’s attention through their
14 L. DESSART

actions on social media (Malhotra et al., 2012), enabling consumers to be engaged with
them, and if they do so consistently over time, consumers are more likely to trust them
(Marzocchi et al., 2013). Similarly, consumers are more likely to develop high
commitment, that is to say, a desire to maintain the relationship with the brand (Jang,
Olfman, Ko, Koh, & Kim, 2008). The findings of this study thus suggest that brand
engagement is conducive towards brand trust and brand commitment, which are two
core aspects of brand relationship quality. So far, these relationships have been only
conceptualised (Brodie et al., 2011; Hollebeek, 2011b; Van Doorn et al., 2010).
Finally, the impact of trust and commitment on loyalty is explored in this context.
Supporting extensive brand relationship literature (Garbarino & Johnson, 1999) and
brand community literature (Algesheimer et al., 2005; Jang et al., 2008), the findings
expand the view that commitment is driving brand loyalty outcomes in social media
engagement contexts. However, the relationship between brand trust and brand loyalty
is not supported. This interesting finding might be because of the concept of
uncertainty avoidance (Hofstede, 2014), which is akin to trust. Indeed, uncertainty
avoidance is low in Anglo-Saxon cultures, which represent most of the respondents of
the study and can explain why trust is not an important antecedent of loyalty (El-
Manstrly & Harrisson, 2013). Additionally, there might be lower trust levels in social
media environments, where brands still sometimes tend to be considered as
manipulative intruders (Fournier & Avery, 2011).

Conclusion
Theoretical contribution
This study significantly contributes to the identification and validation of antecedents
and outcomes of social media engagement. It develops and tests a causal model
explaining the role of individual traits and predispositions driving social media
engagement and its impact on consumer-brand relationships, answering the call for
empirical research into the drivers and outcomes of consumer engagement (Hollebeek
et al., 2016). Specifically, the findings bring clarity to the individual traits and
predispositions that trigger consumer engagement in social media and proves its
benefits for brand relationship building (Vivek et al., 2012).
The consideration of social media engagement as a multifocal phenomenon and the
focus on community and brand engagement brings a unique particularity to the study.
The article shows that in a given context, when different engagement foci are isolated, the
sequence in which they develop is crucial for the overall vitality of engagement. There is
evidence that individual consumer traits and characteristics will likely lead to increased
levels of community engagement, which then acts as the leading antecedent of brand
engagement. Eventually, it is the brand engagement and not community engagement
that bring benefits to the brand, though. Engagement with different entities thus
responds to different norms, conditions and motivations. They develop in a sequence in
social media environments and they are all essential for brands.
Further, this article extends the generalisability of past studies, first by focusing on online
environments for the study of antecedents and outcomes, which to date mainly have been
considered in offline settings. Second, the study includes nine different product categories
 JOURNAL OF MARKETING MANAGEMENT 15

of data, which goes much further than most studies that usually investigate one or a few
brands at most (e.g. Hollebeek et al., 2014). These findings have potent implications for the
management of social media online communities and suggest that researchers can
replicate broadly similar consumer engagement strategies across brand categories.

Managerial implications
From a managerial standpoint, the findings shed light on recent advances regarding social
media branding strategies and Facebook page management in particular. Malhotra et al.
(2012) suggest that in order to increase levels of behavioural engagement on Facebook,
brands should not hesitate to heavily promote the brand and its products and directly engage
with consumers with calls to action. Although these strategies should prove very powerful in
creating brand engagement, this study brings a nuance to their analysis by suggesting that a
sequence or progression from community engaging content should create movement to
more brand-focused content. In this spirit, researchers should consider the suggestion to post
topical content that is not related to the brand during the early stages of community building.
Additionally, the study demonstrates the importance of individual traits in
segmenting consumers for effective engagement. For instance, highly informational
and educational content is likely to suit more very involved consumers, whereas
playful and socially stimulating content would better suit consumers with high online
interactivity propensity. Given the multidimensionality of social media engagement,
community managers would do well to adopt a very complete engagement strategy,
triggering emotional, cognitive and behavioural aspects of engagement to maximise
return on social media investment.

Limitations and suggestions for future research

Despite the valuable contributions that this study brings to the consumer engagement
and social media literature, the current examination is not without limitations. First, the
cross-sectional nature of the data does not enable understanding the evolution of
engagement through time. Several authors suggest that engagement is an ongoing
process of cyclical nature (e.g. Bowden, 2009), and measuring engagement at several
points in time should enhance the understanding of this enduring phenomenon.
Additionally, qualitative or organic netnographic data could be useful in furthering the
understanding of the motivations for engaging on social media. This type of data could
also shed light on the under-researched construct of negative engagement on social
media (Dolan et al., 2016) and advance the understanding of the whole spectrum of
engagement valence. While a die-hard brand fan is unlikely to ever engage negatively,
most consumers can move on the continuum of positive–negative engagement in
official brand outlets (Hollebeek & Chen, 2014) and some even join anti-brand
movements characterised by strong levels of negative engagement (Dolan et al., 2016).
One of the most interesting findings of this study lie in the unique link between
community and brand engagement, and it opens avenue to further investigation of
multifocal engagement situations. For instance, it would be worth testing whether this
relationship holds in other environments and conditions (other consumer-brand
touchpoints or media) or if the direction of the relationship is ever reversed or impacted
16 L. DESSART

by media-specific functionalities. Further, since engagement with each focus is

multidimensional, it would be interesting to test the interplay of cognitive, affective and
behavioural dimensions of community and brand engagement. It might be the case that
behavioural brand engagement depends mainly on affective community engagement, for
instance, as recent studies suggest that behavioural engagement can follows a hierarchical
sequence (Schivinski, Christodoulides, & Dabrowski, 2016). Future work on the interplay
and interdependence of the dimensions of community and brand engagement is required.
Researchers should also investigate other antecedents and outcomes of engagement.
This study includes some of the most relevant and cited variables related to engagement,
but many are left to explore (Mollen & Wilson, 2010). Antecedents could include perceived
costs and benefits of engaging (Van Doorn et al., 2010) while outcomes could focus on
brand recall and attention (Sprott et al., 2009) or brand experiences (Hollebeek, 2011a).
Further, social media engagement is by nature bound to social media environments and
touchpoints, which only represent one portion of all omni-channel consumer–brand
interactions, and only one facet of the vast engagement ecosystem (Breidbach et al.,
2014). As consumers interact with brands through ever increasing amounts of
touchpoints (Lemon & Verhoef, 2016), social media engagement is limited in scope and
might be impacted by engagement through other channels. Further, our sample is highly
educated, with almost 50% of the sample having a postgraduate degree, and education
level might not be foreign to the causal effect tested in this study, particularly when it comes
to cognitive engagement. The role of such confounding engagement variables should be
included in further research to expand on the tested model. Last, researchers should
undertake additional efforts to enhance the generalisability of the findings: social media
are continuously evolving and expanding, and engagement research on other platforms
could lead to other results. New developments in the attention economy have seen the rise
of social media such as Snapchat, which capitalise on content ephemerality to create brand
relationships (Sashittal, DeMar, & Jassawalla, 2016), and thus provide exciting opportunities
to test levels of cognitive engagement and attention. Further research is warranted to
explore the fascinating realm of consumer engagement in social media.

Disclosure statement
No potential conflict of interest was reported by the author.

Notes on contributor
Laurence Dessart is assistant professor in marketing at KEDGE Business School in France.

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Appendix 1. Overview of antecedents and outcomes of consumer

engagement

Engagement Antecedent/
Authors Paper type object Context Construct outcome
Bowden (2009) Conceptual Brand Offline Loyalty O
Sprott et al. Empirical Brand Offline Involvement A
(2009) Self-brand memory links O
Brand recall O
Brand attention O
Product preference O
Van Doorn et al. Conceptual Brand Offline Identity A
(2010) Consumption goals A
Resources A
Perceived costs/benefits A
Trust A
Commitment A
Satisfaction A
Mollen and Conceptual Brand Online Flow A
Wilson (2010) Interactivity A
Telepresence A
Optimal consumer O
attitudes and
behaviours
Brodie et al. Conceptual Brand Offline and Trust A
(2011) online Commitment A
(service Satisfaction A&O
brands)
Hollebeek Conceptual Brand Offline Flow A
(2011a)
Hollebeek Conceptual Brand Offline Involvement A
(2011b) Interactivity A
Rapport A
Trust A& O
Commitment A& O
Satisfaction A& O
Loyalty A& O
Co-created value O
Experience O
Vivek et al. Conceptual Organisational Offline Involvement A
(2012) offering or Participation A
activities WOM O
Brodie et al. Empirical Brand and/or Online brand Trust O
(2013) (qualitative) community community Commitment O
members (blog) Satisfaction O
Empowerment O
Connection and O
emotional bond
Loyalty O
Need to reduce A
information search
and perceived risk
Hollebeek et al. Empirical Brand Social media Involvement A
(2014) brands Self-brand connection O
Brand usage intent O
Dwivedi (2015) Empirical Brand Offline Involvement with A
category
Loyalty intentions O
(Continued )
22 L. DESSART

(Continued).
Engagement Antecedent/
Authors Paper type object Context Construct outcome
France et al. Empirical Brand Offline Brand interactivity A
(2016) Brand quality A
Brand-self congruity A
Brand involvement A
Brand value O
Brand loyalty O
Solem and Empirical Brand Social media – Regulatory fit A
Pedersen Facebook
(2016)
Malthouse et al. Empirical Brand Social media Buying decisions O
(2016)
Marbach et al. Empirical, Brand Social media Personality traits A
(2016) qualitative
Yang, Lin, Empirical Brand Online Search engine O
Carlson, and advertising
Ross (2016) effectiveness
Leckie, Empirical Brand Offline Involvement A
Nyadzayo, and Participation A
Johnson Self-expressive brand A
(2016)

Appendix 2. Items
Online interaction propensity (Wiertz & De Ruyter, 2007)
In general, I like to get involved in online discussions
I am someone who enjoys interacting with like-minded people online
I am someone who likes actively participating in online discussions
In general, I thoroughly enjoy exchanging ideas with others online
Attitude toward community participation (Bagozzi & Dholakia, 2006)
On the following scales, please express your attitude toward participating in the group
(semantic differential)

● Foolish/Wise
● Harmful/Beneficial
● Bad/Good
● Punishing/Rewarding

Product involvement (Laurent & Kapferer, 1985)

This type of product is very important to me
This type of product matters to me
When you buy this type of product, it’s a big deal if you make a mistake
I particularly like this type of product
You can really tell a lot about a person by the type of product he/she picks out
Social media engagement (Dessart et al., 2016)
The items below were administered twice, one with respect to the brand, and once to the community
as evidenced by the (brand/community) placeholder.
Affective engagement
I feel enthusiastic about (brand/community)
I am interested in anything about (brand/community)
I find (brand/community) interesting
When interacting with (brand/community), I feel happy
I get pleasure from interacting with (brand/community)
 JOURNAL OF MARKETING MANAGEMENT 23

Interacting with (brand/community) is like a treat for me

Cognitive engagement
I spend a lot of time thinking about (brand/community)
I make time to think about (brand/community)
When interacting with (brand/community), I forget everything else around me
Time flies when I am interacting with (brand/community)
When I am interacting with (brand/community), I get carried away
When interacting with (brand/community), it is difficult to detach myself
Behavioural engagement
I share my ideas with (brand/community)
I share interesting content with (brand/community)
I help (brand/community)
I ask (brand/community) questions
I seek ideas or information from (brand/community)
I seek help from (brand/community)
I promote (brand/community)
I try to get other interested in (brand/community)
I actively defend (brand/community) from its critics
I say positive things about (brand/community) to other people
Brand trust (Chaudhuri and Holbrook, 2001)
I trust this brand
I rely on this brand
This is an honest brand
This brand is safe
Brand commitment (El-Manstrly & Harrison, 2013)
I have grown to like this brand more than others offering the same product/service
I like the product/services offered by this brand
To me, this brand is the one whose product/services I enjoy using most
Brand loyalty (Odin et al., 2001)
I am loyal to only one brand (the one I follow), when I buy this type of product
For my next purchase, I will buy this brand again
I always buy this brand
I usually buy this brand
 24

Appendix 3. Sample characteristics

Variables Count Percent Variables Count Percent

Age (years) Year of joining Facebook
L. DESSART

18–24 80 18 2004 13 3
25–34 193 43 2005 18 4
35–44 104 23 2006 45 10
45–54 52 12 2007 89 20
55+ 19 4 2008 103 23
Gender 2009 74 17
Male 252 56 2010 50 11
Female 196 44 2011 25 6
Education 2012 19 4
Primary school 2 0 2013 9 2
Secondary school 56 13 2014 3 1
Undergraduate degree 174 39 Daily time on Facebook
Postgraduate degree 216 48 Less than 10 min 37 8
Nationality 10–30 min 129 29
United Kingdom 76 17 31–60 min 143 32
Greece 42 9 60 min + 139 31
Belgium 35 8 Daily Facebook log-ons
United States 34 8 All the time 151 34
Ireland 33 7 1–3 116 26
Others 228 51 4–6 88 20
Brand category 6+ 70 16
Travel 148 33 I don’t log on every day 23 5
Food and beverage 87 19 Page membership duration
Durable goods 66 15 Less than a year 150 33
Entertainment 52 12 1–5 years 282 63
Fashion and beauty 50 11 5–10 years 16 4
Services 23 5 Active page visits
Others 11 2 Never 43 10
Retail 6 1 Less than once a month 123 27
Technology 5 1 About once a month 99 22
About once a week 114 25
More than once a week 69 15
Note: number of respondents = 448.
Appendix 4. Brand pages detail

Member count at time of Study answer Product Member count at time of Study answer
Product category Facebook Pages study count category Facebook Pages study count
Food and The Huggy’s Bar 6 Entertainment Fit Body Bootcamp 3156 26
beverage Kate’s Kitchen 4536 38 Runner’s World 1,134,000 7
Agora Greek 1128 20 TEDx University of 4123 11
Delicacies Glasgow
Jupiler 2679 8 Snooze Pure FM 52
MaBelle 773 7 Borrowed Space 354 3
Edward & Irwyn 458 5 Playstation 28,345,000 1
The Belgian Owl 1484 4 ESN 657 1
Red Bull 38,456,000 3 Citizen Mule 173 2
Nutella 218 1 Scottish Rugby 118,978 1
Nespresso 300 1 Durable Porsche 630 54
Travel Star Alliance 152 135 goods Audi 7,690,545 12
Delta Airlines 130 4 Services Santander UK 187 16
Lufthansa 150 3 Creative Wallonia 4456 3
US Airways 128 3 Betacowork 1879 2
United Airlines 685 1 University of Glasgow 87 2
Swiss 534 2 Others Hot Dog Fashion 1,039 5
International
Air Lines
Fashion and ASOS 3,100,000 23 L’Echo 8979 3
beauty Made&More 817 3 The Guardian 3,987,000 3
Zara 18,567,000 11 Technology Go Pro 7,678,000 3
Smalltwongirl 1456 6 Plug&Go 188 1
Too Belgista 281 2 Samsung Mobile 31,000,000 1
Scotts Guard 567 1 Retail Amazon 22,000,000 5
Watches
J&Joy 36 2 TESCO 1,300,000 1
Suit Supply 14,567,000 1 Total 181,543,713 285
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Skin Clinics 786 1

Note: number of brand pages = 48.
25