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Influences of customer participation and customer brand engagement on brand loyalty:

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Purpose Value co-creation assumes that customers take active roles and create value together with firms. This paper aims to investigate the short- and long-term effects of customer participation on brand loyalty, through brand satisfaction. Participation effects were also examined among social media-using customers with the additional explanatory factor of brand engagement. Design/methodology/approach Two studies were conducted among insurance customers: a cross-sectional study using a nationwide sample ( N = 954) and a subsample of social media users ( N = 145) to examine short-term effects, and a longitudinal study using data from three assessment timepoints ( N = 376) to enable empirical long-term testing. Findings The cross-sectional study showed positive short-term effects of customer participation on brand loyalty, mediated by satisfaction. Among customers using social media, positive participation effects gained from brand engagement strengthened brand satisfaction. The longitudinal study did not show similar positive long-term effects of customer participation. Practical implications These findings help deepen service marketers’ understanding of the possible short-term effects of customer participation and customer brand engagement, and caution them to not expect that customer participation will have long-term positive satisfaction and loyalty effects. Originality/value This research provides interesting short- and long-term findings, due to the complementary cross-sectional and longitudinal study designs.
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Journal of Consumer Marketing
Influences of customer participation and customer brand engagement on brand loyalty
Birgit Andrine Apenes Solem
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Birgit Andrine Apenes Solem , (2016),"Influences of customer participation and customer brand engagement on brand loyalty ",
Journal of Consumer Marketing, Vol. 33 Iss 5 pp. 332 - 342
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Influences of customer participation and
customer brand engagement on brand loyalty
Birgit Andrine Apenes Solem
Department of Business and Management, Institute of Business and Social Sciences,
University College of Southeast-Norway, Borre, Norway and Department of Strategy and Management,
Norwegian School of Economics, Bergen, Norway
Abstract
Purpose Value co-creation assumes that customers take active roles and create value together with firms. This paper aims to investigate the short-
and long-term effects of customer participation on brand loyalty, through brand satisfaction. Participation effects were also examined among social
media-using customers with the additional explanatory factor of brand engagement.
Design/methodology/approach – Two studies were conducted among insurance customers: a cross-sectional study using a nationwide sample
(
N
954) and a subsample of social media users (
N
145) to examine short-term effects, and a longitudinal study using data from three
assessment timepoints (
N
376) to enable empirical long-term testing.
Findings The cross-sectional study showed positive short-term effects of customer participation on brand loyalty, mediated by satisfaction. Among
customers using social media, positive participation effects gained from brand engagement strengthened brand satisfaction. The longitudinal study
did not show similar positive long-term effects of customer participation.
Practical implications – These findings help deepen service marketers’ understanding of the possible short-term effects of customer participation
and customer brand engagement, and caution them to not expect that customer participation will have long-term positive satisfaction and loyalty
effects.
Originality/value – This research provides interesting short- and long-term findings, due to the complementary cross-sectional and longitudinal
study designs.
Keywords Brand satisfaction, Customer participation, Brand loyalty, Customer brand engagement
Paper type Research paper
Service firms continually strive to maintain long-term
relationships with customers and to understand the factors
that build and sustain brand loyalty. From a value co-creation
perspective, which recognizes customers’ active participatory
roles in value creation (Ranjan and Read, 2014;Pralahad and
Ramaswamy, 2004;Jaakkola and Alexander, 2014),
customers’ participation (Nysveen and Pedersen, 2014) and
engagement (Brodie et al., 2011b;Hollebeek, 2011a) can be
prioritized to ensure their loyalty. Firms considering customers
as value co-creators view them as partners or co-producers,
instead of “external elements” (Fuat Firat et al., 1995), as they
engage and participate in specific interactions and activities.
Thus, interaction manifests through participation (Grönroos and
Ravald, 2011) and engagement (Zhu, 2006).
Modern technology plays a crucial role in supporting the
manner in which firms and customers interact (Flores and
Vasquez-Parraga, 2015). Social media comprise a major arena
in which customers participate in co-production, and which
supports the development of collaborative customer
relationships (Maklan and Klaus, 2011). Engagement is
considered to be a particularly important phenomenon in
social media (e.g. chats, blogs, videos and brand
communities) (Brodie et al., 2011a;Fournier and Avery,
2011;Jahn and Kunz, 2012;Dessart et al., 2014). The
interactive nature of social media gives service firms the
opportunity to become more customer-centric, thereby
encouraging customer participation (Kaplan and Haenlein,
2010;Hoffman and Novak, 2012) and engagement in certain
brand activities (Schamari and Schaefers, 2015). Thus, social
media complement brands’ physical-world counterparts and
serve as platforms for customers’ sharing of feelings, thoughts
and content (Schau et al., 2009). An increasing number of
service brands invests time and marketing resources in the
organization of social media-based brand communities and
Facebook brand pages (McAlexander et al., 2002;Shankar
and Batra, 2009;Laroche et al., 2012;Vries et al., 2012),
positively encouraging engagement (Algesheimer et al., 2005;
Brodie et al., 2011b;Hollebeek, 2011a,2011b), in the hope
that customers will participate. Previous studies have
investigated customer preferences for online versus offline
interaction (Frambach et al., 2007), customer satisfaction and
loyalty in online versus offline contexts (Shankar et al., 2003),
and customer participation in virtual brand communities
(Casaló et al., 2008) and service recovery using online
The current issue and full text archive of this journal is available on
Emerald Insight at: www.emeraldinsight.com/0736-3761.htm
Journal of Consumer Marketing
33/5 (2016) 332–342
© Emerald Group Publishing Limited [ISSN 0736-3761]
[DOI 10.1108/JCM-04-2015-1390]
Received 7 April 2015
Revised 15 October 2015
18 April 2016
Accepted 23 April 2016
332
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platforms (Dong et al., 2008). However, empirical research on
brand loyalty effects of the participation of customers using
and not using social media, and that incorporating the effects
of customer brand engagement (CBE) in social media, is
lacking. Thus, in relation to insurance firms’ Facebook brand
pages, this research explored short- and long-term effects of
customer participation on brand loyalty through the bridging
element of brand satisfaction; it also investigated whether
CBE among social media users explained customer
participation, further enhancing brand satisfaction and brand
loyalty.
Given the high cost of attracting new customers, service
firms must increasingly reinforce established customer ties
(Casaló et al., 2007). The insurance sector is known to have
low switching barriers; 17 per cent of the customer base
switches insurance providers each year (Lavik and Schjøll,
2012), which makes it imperative for insurance firms to gain
knowledge about factors that build and sustain brand loyalty.
Brand loyalty denotes an intended behavior in relation to the
brand and/or its services. If real alternatives exist or switching
barriers are low, a service brand will discover its inability to
satisfy customers via two feedback mechanisms: exit and voice
(Hirschman, 1970). This paper considers brand loyalty as the
expression of individual preferences – an attitudinal concept
(e.g. intentions to stay loyal, recommend the brand, and
choose the brand again) (Jacoby and Chestnut, 1978;
Andreassen and Lindestad, 1998).
Previous studies of the loyalty effects of customer participation
have used cross-sectional data (Casaló et al., 2007;Nysveen and
Pedersen, 2014). Although marketing scholars frequently
conduct cross-sectional studies, several researchers have argued
that longitudinal studies are more trustworthy, as they more
precisely characterize long-term effects (Brodie et al., 2011b;
Hollebeek, 2011a,2011b). Longitudinal studies enable
consideration of auto-correlational (i.e. historical) effects, which
is expected to weaken between-variable effects in comparison
with cross-sectional studies (Rindfleisch et al., 2008). In the
present empirical research, cross-sectional and longitudinal
studies were conducted to investigate observed effect patterns
over short- and long-term periods. The hypotheses were that
customers’ willingness to participate over time would affect their
brand satisfaction positively, thereby affecting their subsequent
loyalty, in the short and long terms.
This paper proceeds as follows. First, it presents a
theoretical framework, describing the concepts of customer
participation and CBE, and the study hypotheses. Next, the
methodological approaches and results of the cross-sectional
and longitudinal studies are described. In the discussion
section, findings from the two studies are compared and
interpreted, with consideration of their implications and
limitations, and suggestions for future research are made.
Conceptual background
Customer participation
Customer participation specifies the degree to which a
customer puts effort and resources into the process of
production (Dabholkar, 1990), thus taking an active part in
consuming and producing value (Nysveen and Pedersen,
2014). It includes the physical and mental inputs required
for co-production (Flores and Vasquez-Parraga, 2015).
Co-production consists of direct and indirect co-working
between a firm and its customers, or customers’ participation
in product design (Lemke et al., 2011). Customer
participation might be evidenced in a facilitatory role at the
periphery of a firm’s processes (Auh et al., 2007)orinan
active role through the application of knowledge and sharing
of information with the firm (Ranjan and Read, 2014).
Following Ranjan and Read (2014), customer participation
should be considered a component of co-production. In
co-production, the firm is the predominant locus of process
control (Vargo and Lusch, 2004,2008). Etgar (2008) defined
co-production as customers’ participation in one or more
activities in a firm’s network chain (design, production,
delivery, executing use) and referred to the co-production
phase of value co-creation as the activation stage. This stage,
which is the focus of this research, is where customer
participation via co-production occurs and results in the
production of the core offering. Similarly, Auh et al. (2007)
defined co-production as customers’ cooperative participation
in service creation and delivery, and Chen et al. (2011) defined
it as constructive participation in the service process.
Customer brand engagement
The concept of engagement has received considerable
attention in several academic disciplines (e.g. educational
psychology and organizational behavior), but only recently in
the field of marketing (Gambetti and Graffigna, 2010;
Hollebeek, 2011a,2011b). In recent marketing and service
research, CBE was found to be a core explanatory element in
online brand communities (Brodie et al., 2011a), the
emergence of social media networking sites (Jahn and Kunz,
2012) and, particularly, social media (e.g. Facebook)-based
brand communities (Gummerus et al., 2012;Laroche et al.,
2012;Habibi et al., 2014). As social media use has been added
to firms’ marketing and brand-building activities (Kaplan and
Haenlein, 2010), attracted by the large number of users, firms
have begun to create Facebook brand pages (Gummerus et al.,
2012) to encourage CBE. Following Brodie et al. (2011b) and
Hollebeek et al. (2014), CBE is considered in this study to be
a context-dependent, psychological construct, reflected by
emotional, cognitive and intentional states generated by
interactive experiences underlying behavioral interactions (e.g.
in social media). After Hollebeek et al. (2014), emotional CBE
is considered to be a customer’s degree of positive brand
activity-related affect, and cognitive CBE is conserved to be
his/her level of brand activity-related thought processing and
elaboration. Intentional CBE refers to a customer’s interest in
spending energy, effort and time on a brand activity. Brodie
et al. (2011a) highlighted the fluctuating nature of CBE state
dimensions. Intensity levels of cognitive, emotional and
intentional states can change rapidly, from one moment or
situation to another, in engagement processes (Hollebeek,
2011a).
Hypotheses
The disconfirmation-of-expectation paradigm (Oliver, 1980)
holds that customer loyalty (e.g. intention to stay loyal,
willingness to recommend a brand to others) is a function of
customer satisfaction. Thus, when customers realize that their
patronage has been a good choice and that the brand offers
Customer participation and customer brand engagement
Birgit Andrine Apenes Solem
Journal of Consumer Marketing
Volume 33 · Number 5 · 2016 · 332–342
333
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good solutions, they likely intend to stay loyal to the brand in
the future. They are also more willing to recommend the
brand to other people. From a value co-creation perspective
(Ranjan and Read, 2014), customers’ participation in
co-production is argued to help to build brand loyalty in this
study. To encourage customer participation, a firm creates
platforms for value creation that suit customers’ unique
interests, thereby enhancing brand satisfaction personally and
subjectively and affecting brand loyalty positively.
Co-production has been found to be a positive predictor of
attitudinal loyalty (Auh et al., 2007;Hosseini, 2013) and
satisfaction (Ranjan and Read, 2014;Flores and
Vasquez-Parraga, 2015). When customers participate in
co-production activities, they tend to share their new ideas,
suggestions and problems with a service firm (Chen et al.,
2011), and thus are expected to become more satisfied due to
their personal investment (Cermak et al. 1994). Ranjan and
Read (2014) argued that co-production is a cooperative act of
satisfaction, as customers outlay resources in this process. In
this paper, customers who obtain more customized services
through brand activity participation are argued to be more
satisfied (Bendapudi and Leone, 2003), with competitors
facing more difficulty in attracting them. The short- and
long-term effects of this process were tested using the
following hypothesis:
H1. Through brand satisfaction, customer participation
positively affects brand loyalty.
Chan et al.’s (2010) findings provide empirical support for the
argument that customers’ involvement beyond good/service
consumption can add value for them. Similarly, Van Doorn
et al. (2010) argued that customer engagement goes beyond
transactions, with positive brand/firm and customer
consequences. Little research has investigated relationships of
CBE to other concepts, but CBE appears to positively affect
brand satisfaction (Van Doorn et al., 2010;Hollebeek, 2011a)
and brand loyalty (Brodie et al., 2011a;Hollebeek, 2011a,
2011b). The relationship between CBE and customer
participation remains unclear. Sawhney et al. (2005) argued
that customer engagement in virtual communities comprised
customer participation in innovation, and Sashi (2012)
proposed an engagement cycle in social media, in which
customer connection and interaction are outcomes of
engagement. Other researchers have suggested that customer
participation is an antecedent of CBE (Nysveen and Pedersen,
2014;Ramaswamy and Gouillart, 2010;Vivek, 2009), with
engagement resulting from customers’ efforts and resource
integration in co-production processes. Wirtz et al. (2013)
argued that customer expertise is a moderator between
brand-related social and functional drivers and online brand
community engagement.
Leaning toward the view of Brodie et al. (2011a) by
considering CBE to reflect inherent motivational, emotional,
cognitive and intentional states, with CBE intensity based on
brand stimuli (e.g. activities), CBE investment in social
media-based brand activities is argued here to generate
participation (willingness to consume and produce value, e.g.
sharing ideas, participating in valuable discussions). For
example, customers with greater emotional attachment to a
brand will be more motivated to participate in brand activities
(Auh et al., 2007). However, customers’ engagement with an
object (e.g. a brand) is assumed to fluctuate frequently (Brodie
et al., 2011a), thus evoking short-term positive effects. In the
short term, customers who engage and participate in brand
activities will be satisfied (Chan et al., 2010;Flores and
Vasquez-Parraga, 2015) and loyal (Hollebeek, 2011b). In
interactive social media, customers who enter positively
valenced engagement states are assumed to participate
willingly in joint activities, leading to brand satisfaction and
loyalty. In this paper, customers’ participation is argued to
generate satisfaction with their own performance (individual
value) and with the engagement object (e.g. brand or brand
activity; relational value), with the positive outcome of
strengthened brand loyalty. This extensive affect chain is
expressed in the following hypothesis, tested in the
cross-sectional study:
H2. In social media, CBE will positively affect customer
participation, generating positive brand satisfaction and
loyalty effects.
Study 1
Design, sample and measurement
This cross-sectional study was conducted in April 2012 in
partnership with Norstat (the largest online panel data
provider in Norway) using a nationwide online panel survey of
insurance customers aged 15 years. Respondents were
rewarded through the Norstat system. To make the sample
representative, Norstat controlled recruitment according to
age, gender, education, income and non-disclosed
customer-related variables. Participating customers of seven
insurance brands filled out questionnaires with reference to
the brand with which each had a relationship, and those
reporting use of Facebook as a customer channel answered
questions regarding their relationships with the brands in that
context. Included insurance brands had used Facebook brand
pages as customer channels since 2011. Customers had been
invited to express their preference for the brands by “liking”
them; content on the firms’ Facebook brand pages was then
posted automatically to these customers’ Facebook news
feeds, where they were expected to engage emotionally,
cognitively and through behavioral intentions.
Self-reported questionnaire items measured latent constructs
using modifications of previously used scales (Appendix).
Customers rated their willingness to participate with the brand
[four items reflecting customer participation in creating value
together with a service brand (Nysveen and Pedersen, 2014;
Chan et al., 2010)]. CBE in social media was measured using a
three-dimensional scale reflecting states of emotional, cognitive
and intentional CBE [Solem and Pedersen (2016), based on the
work engagement scale of Rich et al. (2010)]. Item wording was
amended slightly for the Facebook brand page (reflecting brand–
customer interactivity), following Reitz (2012) and Casaló et al.
(2010). The questionnaire also assessed brand satisfaction [five
items reflecting overall satisfaction, meeting of expectations
(Fornell, 1992), and acceptability of brand choice (Oliver, 1980;
Gottlieb et al., 1994)] and brand loyalty [four items reflecting
future loyalty and continued patronage (Selnes, 1993;Brakus
et al., 2009;Wagner et al., 2009), recommendation to others
(Brakus et al., 2009) and repeat selection (Selnes, 1993)].
Customer participation and customer brand engagement
Birgit Andrine Apenes Solem
Journal of Consumer Marketing
Volume 33 · Number 5 · 2016 · 332–342
334
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Responses were structured by a seven-point scale ranging from
“totally disagree” to “totally agree”.
A total of 964 invited panel members completed the
questionnaire. Ten “outliers” showing no variance in CBE
were excluded, resulting in a final sample of 954 respondents,
145 (15 per cent) of whom reported using Facebook in
relation to the insurance brands. Gender was distributed
evenly in the sample, 59 per cent of respondents were aged
45 years, 66 per cent were well educated and 47 per cent had
household incomes 600,000 NOK (Table I).
Reliability and validity testing
The data were examined through confirmatory factor analysis
with maximum likelihood estimation (Bollen, 1989) using
IBM SPSS AMOS 21. To assess nomological validity,
concept positions were tested using a measurement model for
the total sample of respondents. Convergent and divergent
validity were assessed following Fornell and Larcker (1981a,
1981b).
The estimated measurement model for the total sample (N
954) showed a reasonably good fit [
2
/df 4.90, comparative fit
index (CFI) 0.98, root mean square error of approximation
(RMSEA) 0.064]. All constructs showed acceptable reliability
(Cronbach’s á0.7). Brand satisfaction and brand loyalty
showed acceptable convergent validity, whereas customer
participation did not [Cronbach’s áaverage variance extracted
(AVE) 0.5], indicating that the items did not optimally reflect
the concept. No discriminant validity issue was observed, except
for brand loyalty (maximum shared variance AVE; Table II).
The square root of AVE for brand loyalty was lower than its
correlation with brand satisfaction.
As the strong correlation between brand satisfaction and
brand loyalty may have been due to common method bias, the
marker variable technique (Lindell and Whitney, 2001;
Malhotra et al., 2006) was applied. A theoretically unrelated
two-item variable (“Facebook can be used to read what other
people are writing”, “Facebook can be used to achieve
personal gains”), structured by a seven-point Likert scale
anchored by “totally disagree” and “totally agree”, served as a
marker. The two lowest correlations with the marker (r0.15
and r0.12) fell below the suggested 0.20 threshold for
problematic method variance (Malhotra et al., 2006). All
correlations in the model remained significant, with signs
unchanged. These results indicated that method bias was not
a significant risk in this data set.
Hypothesis testing
The hypotheses were tested using structural equation modeling
(SEM; IBM SPSS AMOS 21), following the procedure of Bollen
and Long (1993).H1 was tested using data from the 809
respondents who did not use Facebook in relation to the brands.
This model showed acceptable fit (
2
/df 4.70, CFI 0.98,
RMSEA 0.068; Figure 1). Customer participation affected
brand satisfaction positively (
0.27), and brand satisfaction
affected brand loyalty positively (
0.85). Customer
participation had no significant direct effect on brand loyalty.
These results supported H1.
Possible different effects of customer participation were
controlled by introducing brand as a control variable
(covariate) in the analysis to test direct effects on brand
satisfaction and loyalty. All models yielded insignificant
results, except the model for one brand (
2
/df 4.37, CFI
0.98, RMSEA 0.065), which showed that brand negatively
affected brand satisfaction (
⫽⫺0.11). Comparison of
results from this model and the original model showed that the
effect of customer participation on brand satisfaction
remained positive, although marginally lower (
0.26), and
the effects of customer participation and brand satisfaction on
brand loyalty were unchanged.
Table I Sample demographics from the cross-sectional study
Sample demographics (
N
954) (%)
Gender
Male 54.4
Female 45.6
Age
15-24 9.7
25-34 14.0
35-44 17.2
45-54 17.9
55-64 19.2
64- 21.9
Education
Primary 5.2
Secondary 28.6
University/College <3 years 30.8
University/College >3 years 35.3
Household income (in NOK)
<200,000 4.9
200,000-399,000 15.7
400,000-599,000 23.4
600,000-799,000 18.1
>800,000 28.9
No response 8.9
Using social media
Using Facebook in relation to brand 15.2
Table II Reliability, validity and the correlation matrix for the total sample (
N
954)
Constructs
AVE MSV ASV Customer participation Brand satisfaction Brand loyalty
Customer participation 1.01 1.04 0.06 0.06 1.02
Brand satisfaction 0.95 0.78 0.77 0.41 0.24
ⴱⴱⴱ
0.88
Brand loyalty 0.90 0.69 0.77 0.41 0.23
ⴱⴱⴱ
0.88
ⴱⴱⴱ
0.83
Notes:
Cronbach’s alpha; AVE average variance extracted; MSV maximum shared squared variance; ASV average shared squared
variance; the bold values on the diagonal of the matrix represent the square root values for each AVE; significant covariances:
p
0.1;
ⴱⴱ
p
0.05;
ⴱⴱⴱ
p
0.01;
N
954
Customer participation and customer brand engagement
Birgit Andrine Apenes Solem
Journal of Consumer Marketing
Volume 33 · Number 5 · 2016 · 332–342
335
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Testing for a mediating effect
The assumed mediating effect of brand satisfaction on the
relationship between customer participation and brand loyalty
was further examined using a bootstrap resampling method.
Bootstrapping is not bound by the assumptions of normal
theoretical approaches (e.g. the Sobel test), and thus
characterizes indirect effects more accurately (Hayes and
Preacher, 2013). An indirect effect is considered to be
significant when the bootstrap confidence interval (CI)
excludes zero. In the present study, a 95 per cent CI for the
indirect effect was obtained using 5,000 bootstrap re-samples.
The results confirmed that brand satisfaction significantly
mediated the relationship between customer participation and
brand loyalty (95 per cent CI 0.15-0.25).
Incorporation of customer brand engagement in
social media
To test H2 with data from customers who engaged with the
brands in social media, CBE was incorporated as a predictor
variable. Composite (aggregated average) scores were used for
the multidimensional CBE concept, following Brakus et al.
(2009). Total, rather than individual dimensional, effects of
these variables were thus examined. The SEM model showed
acceptable fit (
2
/df 1.63, CFI 0.98, RMSEA 0.066;
Figure 2).
In this subsample, CBE positively affected customer
participation (
0.60), which positively affected brand
satisfaction (
0.49). These effects were substantially
greater than observed for customers with no social media
brand interaction. The effect of brand satisfaction on brand
loyalty (
0.85) was similar. These results support H2.To
clarify the theorized relationship between CBE and customer
participation, an alternative model with customer participation
serving as the predictor variable and CBE as the proximal
mediator was tested. Although this model showed acceptable fit
(
2
/df 2.05, CFI 0.98, RMSEA 0.085) and a significant
effect of customer participation on CBE (
0.52), it was not as
strong as the original model used to test H2.
Study 2
This longitudinal study was conducted to test H1.
Longitudinal analysis allows one to account for potential
common-method variance (Bijleveld et al., 1998;Griffith
et al., 2006;Rindfleisch et al., 2008;Ployhart and
Vandenberg, 2011). It also shows auto-correlation effects,
reducing between-variable effects while strengthening the
validity of effect patterns (Menard, 1991). Thus, Study 2 was
expected to provide similar, but weaker, support for H1
compared with Study 1. The effect of customer participation
subsequent to brand satisfaction was assessed, with brand
loyalty serving as the outcome (Jap and Anderson, 2004) and
with the incorporation of historical (auto-correlational)
effects.
Design and sample
Norstat collected data from the same insurance customers
over an 18-month period in autumn 2011 (T
0
), spring 2012
(T
1
, data set used in Study 1), and spring 2013 (T
2
) using
the methodology and measures described for Study 1. The
three-wave structure was selected according to the
recommended minimum number of repeated measures
(Chan, 1998 in Ployhart and Vandenberg, 2011), and to
ensure validity and avoid variance (Vandenberg, 2002). The
unequal intervals between surveys were planned, together with
the insurance firms’ marketing managers, to ensure that they
would appropriately reflect changes (Gollob and Reichardt,
1991) and to capture the predictive effects of customer
participation and brand satisfaction on loyalty, as described
for mediational models (Cole and Maxwell, 2003).
Respondents to the first survey were asked by email to
complete additional surveys at T
1
and T
2
. To account for a
dropout rate of up to 75 per cent between T
0
and T
2
, a much
Figure 1
H1
test results from the cross-sectional study
Brand
Loyalty
Customer
Participation
0.27***
0.05(ns)
0.85***
N=809
χ2/df =4.70
CFI= 0.98
RMSEA= 0.068
Brand
Satisfaction
Notes: All coefficient values are standardized. Significance level:
***p < 0.001, **p < 0.01, * p < 0.05; N = 809; x2/df = 4.70;
CFI = 0.98; RMSEA = 0.068
Figure 2
H2
test results from the cross-sectional study
0.04 (ns)
Brand
Loyalty
Customer
Participation
0.83
0.95 0.49***
0.85***
0.94
Emotional Cognitive Intentional
Brand
Satisfaction
CBE
0.60***
Notes: All coefficient values are standardized; the concept of CBE is presented by
dimensions. Significance level: ***p < 0.001; **p < 0.01; *p < 0.05; N = 145;
x
2/df = 1.63; CFI = 0.98; RMSEA = 0.066
Customer participation and customer brand engagement
Birgit Andrine Apenes Solem
Journal of Consumer Marketing
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larger sample than required was recruited at T
0
(Ployhart and
Vandenberg, 2011). The numbers of participants at T
0
,T
1
and T
2
were 1,389, 964 and 1,172, respectively. The study
sample comprised 376 respondents who completed surveys at
all timepoints.
Following Cole and Maxwell (2003), the effects of the
independent variable (customer participation) at T
0
were
considered to predict the mediating variable (brand
satisfaction) at T
1
. In turn, the mediating variable was thought
to predict the dependent variable (brand loyalty) at T
2
. The
potentially confounding auto-correlational effects of all
variables were controlled to avoid spuriously inflated estimates
of the causal path of interest (Figure 3)(Cole and Maxwell,
2003;Orth et al., 2009). For example, Chandler and Lusch
(2014) characterize temporal connections as current
connections stemming from past customer participation and
giving rise to future participation.
In contrast to cross-sectional research, in which construct
residuals are assumed to be uncorrelated and normally
distributed, residual correlation was allowed (Ployhart and
Vandenberg, 2011). The causal structure (the degree to which
one set of variables produces change in another set) was assumed
to remain unchanged over time (Bijleveld et al., 1998). The
observed invariance (equality of standardized factor loadings of
like items across timepoints; Appendix) indicated that the items
retained the same meanings for participants throughout the study
period (Ployhart and Vandenberg, 2011).
Analysis and results
Mplus 7.11 software was used to perform SEM of
between-variable auto-correlational effects (Muthén and
Muthén, 2007), with maximum likelihood estimation. The
model showed a good fit (CFI 0.94, Tucker–Lewis index
0.93, RMSEA 0.065, Bayesian information criterion
39,295.219). Customer participation at T
0
had a non-significant
negative effect on brand satisfaction at T
1
and T
2
(
⫽⫺0.009)
and a non-significant positive effect on brand loyalty at T
2
(
0.03). Brand satisfaction at T
0
and T
1
had a significant positive
effect on brand loyalty at T
1
and T
2
(
0.17). All
auto-correlational relationships were significantly positive
(customer participation,
0.56; brand satisfaction,
0.70;
brand loyalty,
0.50; Table III). These results do not support
H1 or the short-term results from Study 1.
Discussion, implications and directions for
future research
This paper contributes to the marketing literature by shedding
light on the short- and long-term effects of customer
participation on brand loyalty (through brand satisfaction) from
a value co-creation perspective. It documents the short-term
effects of CBE on these variables in a social media context. The
findings support the disconfirmation-of-expectation theory,
which predicts that satisfaction is the primary route to loyalty
(Anderson and Sullivan, 1993;Bloemer and Kasper, 1995;
Oliver, 1999), in the short and long terms.
Study 1 documented substantial positive effects of customer
participation on brand loyalty through brand satisfaction.
CBE was an important driver of customer participation and
enhanced the positive effects of customer participation on
brand satisfaction, although these results were derived from a
limited subsample and survey data leaned toward correlation.
When customers engage emotionally, cognitively and/or
intentionally in certain brand activities and content on a
brand’s Facebook page, they show more interest in
participating with the brand. The alternative model tested in
Study 1 supported this positive effect of CBE on customer
Figure 3 An illustrative path diagram of a longitudinal model of
mediation
X0Customer
Participation
X1Customer
Participation
X2Customer
Participation
M1Brand
Satisfaction
Y2Brand
Loyalty
Y1Brand
Loyalty
M2Brand
Satisfaction
Y0Brand
Loyalty
M0Brand
Satisfaction
Table III
H1
test results from the longitudinal study (
N
376)
SEM analysis in Mplus Results Acceptance level
Model results
Acceptable fit
CFI 0.94 0.95
TLI 0.93 0.95
RMSEA 0.065 0.080
BIC 39,295.219 As low as possible
Test results
Customer participation on brand satisfaction 0.009 (ns)
Customer participation on brand loyalty 0.032 (ns)
Brand satisfaction on brand loyalty 0.17
ⴱⴱⴱ
Autocorrelation effects
Customer participation on customer participation 0.56
ⴱⴱⴱ
Brand satisfaction on brand satisfaction 0.70
ⴱⴱⴱ
Brand loyalty on brand loyalty 0.50
ⴱⴱⴱ
Notes: CFI comparative fit index; TLI Tucker–Lewis Index; RMSEA root-mean-square-error of approximation; BIC Bayesian information
criterion;
p
0.10 (two-sided);
ⴱⴱ
p
0.05 (two-sided);
ⴱⴱⴱ
p
0.01 (two-sided)
Customer participation and customer brand engagement
Birgit Andrine Apenes Solem
Journal of Consumer Marketing
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participation, suggesting reciprocal effects between these
variables in social media contexts. The greater effect of
customer participation on brand satisfaction among customers
engaging with brands in social media is a promising result for
service firms that are using social media strategically as a
marketing and service channel.
In contradiction of cross-sectional findings (Auh et al., 2007;
Hosseini, 2013;Flores and Vasquez-Parraga, 2015), the effects
of customer participation were not significant in Study 2. These
results provide a useful contribution to the marketing literature,
although customer participation produces positive short-term
outcomes, it does not appear to result in long-term brand
satisfaction or loyalty. Observed auto-correlational effects
showed that participating customers are likely to participate again
later, which is promising for service firms.
These findings may be explained by the fluctuating nature of
customer participation with brands and in brand activities (as
with CBE); co-producing customers may forget such
participation soon after completing it. Another explanation could
be that service firms do not plan the foundation for customer
participation well, consequently providing random and
unsystemized handling of feedback over time. If customers see no
service improvement based on their input, then their satisfaction
and loyalty will probably remain unchanged.
Other explanations may be plausible. For example, the effects
of customer participation on satisfaction may depend on
customers’ expectations of outcomes. Bendapudi and Leone
(2003) found that customers who participated in production
with a firm were less satisfied with the firm than were those who
chose not to participate when outcomes were better than
expected and more satisfied when outcomes were worse than
expected. Thus, the “outcome as expected” condition may be an
“invisible” factor that should be incorporated in future empirical
studies of customer participation effects on brand satisfaction.
Customers allocate credit for positive outcomes or blame for
negative outcomes to themselves and the firm, which may affect
satisfaction. The absence of a longitudinal effect of customer
participation may also be due to the lack of moderating (e.g.
“easy” versus “difficult” design example) and/or mediating (e.g.
self-congruity) variables (Chang et al., 2009).
Managerial implications
For service marketers, these study findings have important
implications with regard to brand-building strategies. Brand
satisfaction remains key to brand loyalty in the short and long
terms. Service firm customers’ co-creative activities, such as
innovation and service improvement initiatives, provide service
marketers with positive short-term brand satisfaction and brand
loyalty effects. Service firms can encourage CBE by using social
media platforms, such as Facebook brand pages, which will
positively affect customer participation, with subsequent positive
short-term effects on brand satisfaction. Thus, for short-term
purposes, customer participation should be encouraged through
CBE in social media contexts, in relation to activities beyond
exchange.
Service marketers should not have overly high expectations for
long-lasting effects of customer participation. Customers willing
to participate in brand relationships (e.g. expressing their needs,
suggesting service improvements) will not necessarily become
more satisfied and/or loyal over the long term. An interesting
practical insight gained from Study 2 is that managerial creativity
might be necessary for engagement and participation effects to
stand the test of time.
Marketers must take the consequences of customer
participation seriously, strategically developing systems and
(online and offline) network platforms that recognize customers’
concerns and interests, and facilitate their engagement and
participation. They must systemize changes based on customer
input so that customers can benefit personally. These measures
may enhance short- and long-term brand satisfaction and loyalty.
The study results are particularly promising for insurance firms
wishing to use social media for CBE and customer participation
purposes. However, for insurance firms struggling with high
annual turnover rates and failing loyalty, the absence of
long-term effects is not promising. Like other service firms,
insurance firms must form strategies for the development of
platforms and networks that facilitate customer participation, in
the hope that brand loyalty will become a positive long-term
effect.
Limitations and future research possibilities
The use of correlational survey data in Study 1 precluded
causality prediction; future studies should examine customer
participation effects using small-scale experiments in an online
panel context. Given the small subsample of customers who used
social media to relate to the brands, the findings cannot be
considered to provide definitive evidence of CBE effects. Larger
and more diverse samples are needed in future studies. The
convergent validity of the customer participation concept should
also be addressed by improving relevant survey items.
CBE effects were examined holistically in this research.
Dimension effects should be examined separately in future to
gain more detailed and sophisticated knowledge. Following
research tradition, CBE was measured using positively valenced
scales (Brakus et al., 2009;Hollebeek et al., 2014). In practice,
however, customers can become negatively engaged (e.g. in
social media) (Laroche et al., 2012;Hollebeek and Chen, 2014).
Thus, researchers should seek to assess valence more accurately
(e.g. by evaluating positively and negatively worded versions of
scales), as recommended by Brakus et al. (2009).
In this research, brand loyalty was operationalized as
customers’ brand-related intended behavior (i.e. an attitudinal
concept). It was not defined based on repeat purchase patterns.
By considering brand loyalty as a behavioral construct, panel data
on registered repeat-purchase behavior could have been used to
assess repeat-purchase loyalty (e.g. penetration, purchase
frequency, market share, repeat buying) and analyzed using
Dirichlet models/negative binominal distribution (Ehrenberg
et al., 2004;Sharp et al., 2012). Future studies could benefit from
the conceptualization of brand loyalty as a hybrid attitudinal/
behavioral construct, enabling the analysis of attitudinal and
repeat-purchase loyalty.
In assessments of relationship variables, including the present
longitudinal study, optimal timepoints for data collection are
difficult to determine. The 18-month period may have been
insufficient for insurance brand loyalty analysis. However, with
17 per cent of customers switching insurance providers annually,
much can happen in this period. Regardless, longitudinal data
collection is probably more valuable in situations involving daily
observation and data recording, rather than the administration of
Customer participation and customer brand engagement
Birgit Andrine Apenes Solem
Journal of Consumer Marketing
Volume 33 · Number 5 · 2016 · 332–342
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self-reported questionnaires at one-year intervals. These
limitations make it difficult to favor the Study 2 results over those
of Study 1; rather, they should be considered as supplementary.
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Customer participation and customer brand engagement
Birgit Andrine Apenes Solem
Journal of Consumer Marketing
Volume 33 · Number 5 · 2016 · 332–342
341
Downloaded by OSLO AND AKERSHUS UNIVERSITY COLLEGE OF APPLIED SCIENCES At 05:34 01 February 2017 (PT)
Appendix
Corresponding author
Birgit Andrine Apenes Solem can be contacted at: Birgit.A.
Solem@hbv.no
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Table AI Concepts and measures
Concepts Dimensions and measures
Item
loading T
0
Item
loading T
1
Item
loading T
2
Customer
participation
I often express my personal needs to (brand) 0.84 0.85 0.85
I often suggest how (brand) can improve their services 0.90 0.92 0.92
I participate in decisions about how (brand) offer its services 0.90 0.91 0.90
I often find solutions of my problems together with (brand) 0.83 0.81 0.85
CBE
Emotional engagement
I am enthusiastic in relation to (brand) at (brand)’s Facebook page 0.93
I feel energetic in contact with (brand) at its Facebook page 0.94
I feel positive about (brand) at its Facebook page 0.86
Cognitive engagement
At (brand)’s Facebook page, my mind is very focused on (brand) 0.78
At (brand)’s Facebook page, I focus a great deal of attention to (brand) 0.80
At (brand)’s Facebook page, I become absorbed by (brand) 0.91
Intentional engagement
I exert my full effort in supporting (brand) at its Facebook page 0.78
I am very active in relation to (brand) at its Facebook page 0.92
I try my hardest to perform well on behalf of (brand) at its Facebook page 0.92
Brand satisfaction Overall, I am satisfied with (brand) 0.91 0.90 0.92
Being a customer of (brand) has been a good choice for me 0.92 0.91 0.91
(brand) has lived up to my expectations 0.91 0.92 0.94
(brand) is concerned with what solutions that is the best for me 0.87 0.80 0.79
(brand) offers me good solutions 0.93 0.91 0.92
Brand loyalty I intend to stay loyal to (brand) in the future 0.90 0.89 0.89
I intend to stay on as a customer of (brand) for the next three years 0.87 0.84 0.88
I intend to recommend (brand) to other people 0.87 0.84 0.82
If I had to choose again I would still choose (brand) 0.92 0.89 0.89
Notes: Item wording and standardized coefficients from the confirmatory factor analysis (CFA); loadings are based on the customer sample in the
longitudinal study (
N
376) for customer participation, brand satisfaction and brand loyalty; for CBE, the factor loadings are based on the
cross-sectional study conducted at T
1
(
N
145)
Customer participation and customer brand engagement
Birgit Andrine Apenes Solem
Journal of Consumer Marketing
Volume 33 · Number 5 · 2016 · 332–342
342
Downloaded by OSLO AND AKERSHUS UNIVERSITY COLLEGE OF APPLIED SCIENCES At 05:34 01 February 2017 (PT)
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