The current issue and full text archive of this journal is available on Emerald Insight at:

https://www.emerald.com/insight/0309-0566.htm

Interplay of
Not all experiential consumers are customer
created equals: the interplay of equity drivers

customer equity drivers on

brand loyalty 2257
Pham Hung Cuong Received 3 April 2018
Revised 1 March 2019
Department of International Affairs and Scientific Management, 2 September 2019
Foreign Trade University, Ho Chi Minh City Campus, Ho Chi Minh, Vietnam 18 February 2020
29 May 2020
Accepted 9 June 2020
Oanh Dinh Yen Nguyen and Liem Viet Ngo
School of Marketing, University of New South Wales, Sydney, Australia, and
Nguyen Phong Nguyen
School of Accounting, University of Economics Ho Chi Minh City,
Ho Chi Minh City, Vietnam

Abstract
Purpose – This study aims to use social exchange theory and the principle of reciprocity in proposing a
theoretical model to examine the essential but unexplored unique roles of individual customer equity drivers
(CEDs) and their contribution to brand loyalty. This study identifies a reciprocity pathway in that brand equity,
which mediates the linkage between relationship equity and brand loyalty. This study further posits that the
linkage between relationship equity and brand equity is contingent on value equity. The authors then incorporate
value equity as a moderator upon which the interrelationships among CEDs and brand loyalty may vary.
Design/methodology/approach – A sample consisted of 2,268 shoppers in a metropolitan city in Vietnam.
Findings – Relationship equity significantly determines brand loyalty through the moderating effect of
value equity and the mediating effect of brand equity. Interestingly, these relationships are diverse across
different experiential types of consumers.
Research limitations/implications – This study contributes to a better understanding of why and
when value equity, brand equity and relationship equity trigger brand loyalty. Brand equity and value equity
are the two underlying mechanisms that establish a moderated mediation model between CEDs and brand
loyalty. The findings of this study show that experiential consumers are not created equals. The strength of
the relationships between CEDs and brand loyalty differ among the five clusters of experiential consumers.
Practical implications – This study reveals the critical relationships between the three components of
customer equity in the supermarket industry. The findings provide concrete direction for managers and
marketers to be more effective in allocating resources, tailoring their marketing strategies and, accordingly,
promoting brand loyalty of different types of consumers.
Originality/value – This study reveals the underlying modus operandi that explains the reciprocity
effects of CEDs and the contingency role of brand experience on the CEDs–loyalty link. This study shows that
brand equity fosters and sustains the reciprocity generated when consumers perceive a high level of
relationship equity, serving as a mediator between relationship equity and brand loyalty. Importantly, value
equity is an important moderator for strengthening this reciprocity effect. Furthermore, this study identifies a
typology of experience-focussed consumers and shows that the CEDs–loyalty link significantly varies by
these types of experiential appeal that characterise the consumers.
European Journal of Marketing
Keywords Brand loyalty, Brand experience, Customer equity, Relationship equity, Brand equity, Vol. 54 No. 9, 2020
pp. 2257-2286
Value equity © Emerald Publishing Limited
0309-0566
Paper type Research paper DOI 10.1108/EJM-04-2018-0228
EJM There is only one valid definition of business purpose: to create a customer.
54,9
Peter F. Drucker, The Practice of Management

Introduction
Practitioners and marketing scholars have acknowledged the importance of managing
2258 brand loyalty as an important determinant of profit (Bairrada et al., 2018; Watson et al.,
2015; Evanschitzky et al., 2012; Russell-Bennett et al., 2013). Recent industry research on
25,426 consumers in 33 countries reveals that 57% of consumers would spend more on
brands they are loyal to (Wollan et al., 2017). In parallel with this trend is a prominent
research stream in marketing that emphasises the linkage between relationship equity and
brand loyalty (Ou et al., 2017; Ou et al., 2014; Zhang et al., 2014; Dwivedi et al., 2012; Vogel
et al., 2008). Relationship equity refers to the overall evaluation of the interaction quality
between a brand and its consumers, representing all elements that contribute to the
consumer–brand relationship (Rust et al., 2001; Ou et al., 2017; Vogel et al., 2008). Premised
upon social exchange theory, advocates of this reciprocity-based literature of brand loyalty
claim that relationships evolve over time into loyalty on the basis of reciprocity (Cropanzano
and Mitchell, 2005). The principle of reciprocity is rooted in interdependent exchanges (e.g.
repayment in kind), social belief (e.g. one good turn deserves another) and moral norm (e.g.
obligations to behave reciprocally). Although the linkage between relationship equity and
brand loyalty has received ample support from recent literature (Ou et al., 2017; Ou and
Verhoef, 2017; Ou et al., 2014; Zhang et al., 2014; Dwivedi et al., 2012; Vogel et al., 2008),
questions still remain regarding how and under which boundary conditions relationship
equity contributes to brand loyalty.
First, relationship equity is necessary but not sufficient for creating and maintaining
better brand loyalty. Indeed, the simultaneous existence of relationship equity and other
customer equity drivers (i.e. CEDs: value equity and brand equity) is theoretically
recognised in the extant literature (Zeithaml et al., 2001). The three CEDs “work
independently and together” (Lemon et al., 2001, p. 1). However, prior empirical studies
exhibit variation in their findings regarding the significance and direction of the CEDs–
loyalty link. Some confirm the positive effects of the CEDs in fostering loyalty intention and
purchase intention (Ou et al., 2017; Ou et al., 2014; Zhang et al., 2014; Vogel et al., 2008).
Conversely, others find that value equity, relationship equity and brand equity are not
always positively related to brand loyalty (Dwivedi et al., 2012; Kim and Ko, 2012). These
divergent effects indicate that there might be potentially more complicated relationships
among the CEDs and brand loyalty, thus warranting further studies.
Second, a further phenomenal issue of interest is to create a strong experience for
customers and to examine how such experience influences key business outcomes such as
CEDs and loyalty (Lemon and Verhoef, 2016). The extant literature suggests that customers
are heterogeneous in their preferences for different dimensions of brand experience (Schmitt
et al., 2015; Zarantonello and Schmitt, 2010). However, little is known about how such
heterogeneity of experiential types of customers alters the CEDs–loyalty link. Thus, Brakus
et al. (2009, p. 66) urge researchers to examine “can brand experiences build customer equity,
and how should marketers manage brands to create experiences that build such equity?”
We address the above research gaps by developing a conceptual framework that
integrates CEDs, brand loyalty and brand experience. The conceptual framework builds on
social exchange theory and the principle of reciprocity that constitute an appropriate
paradigm for explaining how and why individuals engage in reciprocity decision-making
(Cialdini et al., 1975; Cropanzano and Mitchell, 2005; Montoya and Insko, 2008; Falk and Interplay of
Fischbacher, 2006). Based on the principle of reciprocity, we reveal the underlying modus customer
operandi that explains the reciprocity effects of CEDs and the contingency role of brand equity drivers
experience on the CEDs–loyalty link. Specifically, we develop and validate a model that
addresses the following questions:

Q1. What is the interplay among different drivers of customer equity (value equity,
brand equity and relationship equity) and brand loyalty? 2259
Q2. Do experiential types of consumers moderate the impacts of value equity, brand
equity and relationship equity on brand loyalty?
By answering these questions, we make two contributions to the marketing literature. First,
we decode the complexity of the CEDs–loyalty link by examining the highly essential but
unexplored unique roles of relationship equity, brand equity and value equity that delineate
a pathway through which the reciprocity effect occurs and the conditions under which this
effect is most effective. Based on the social exchange theory, we propose that there exists a
reciprocity effect and examine this reciprocity pathway from relationship equity through
brand equity to brand loyalty. We further incorporate value equity as an important
moderator strengthening or weakening this reciprocity effect. Our insights help answer
Swoboda et al.’s (2013, p. 447) question about how firms can “take reciprocal effects into
account when allocating resources,” especially in the retailing context.
Second, our study responds to the calls by Lemon and Verhoef (2016) and Brakus et al.
(2009) for further research on the contribution of brand experience to CEDs and brand
loyalty. We achieve this goal by proposing a typology of experience-focussed consumers
and examining whether these experiential types moderate the interrelationships among
CEDs and brand loyalty. Specifically, we build on prior work of Zarantonello and Schmitt
(2010) and propose that there exist different experiential types of consumers (i.e. holistic,
hedonistic, action oriented, sensorial and utilitarian consumers) for which the
interrelationships among CEDs and brand loyalty may vary.
The remainder of our article is organised as follows. We start with a discussion of
literature covering brand loyalty and its relationships with CEDs. Next, we propose a
moderated mediation model of the nexus between the three components of customer equity
and brand loyalty. We then address a pertinent review of experiential types of customers
and discuss how relationship equity, brand equity, value equity and brand loyalty vary
across different experiential appeals. With the use of a large-scale survey undertaken in a
metropolitan city, we test the hypotheses using partial least square structural equation
modelling (PLS-SEM), PROCESS model and multi-group analysis (MGA). Implications,
limitations and future research directions are finally discussed.

Literature review and theoretical model

Brand loyalty and customer equity drivers
Brand loyalty has been a significant factor that attracts remarkable attention of both
academia and practitioners for decades (Bairrada et al., 2018). Though there is a rich history
with a long debate of the loyalty definition in the literature, existing research basically
agrees that loyalty is a mix of attitudinal and behavioural aspects that benefit a brand over
its competitors (Watson et al., 2015; Chaudhuri and Holbrook, 2001; Dick and Basu, 1994).
Specifically, Oliver (1999, p. 34) defines brand loyalty and captures its elements as:
EJM a deeply held commitment to rebuy or repatronize a preferred product/service consistently in the
future, thereby causing repetitive same-brand or same brand-set purchasing, despite situational
54,9 influences and marketing efforts having the potential to cause switching behaviour.
This definition indicates that the behavioural aspect of loyalty relates to the consumers’
repeated purchases of the brand, while the attitudinal aspect of loyalty entails the
consumers’ dispositional commitment with the brand (e.g. the resistance of competitive
2260 offers). Achieving brand loyalty is a critical marketing goal because higher brand loyalty
would lead to greater marketing outcomes such as increased consumers’ repeat purchase
(Meyer-Waarden, 2007), higher market share (Chaudhuri and Holbrook, 2001), greater
premium prices (Evanschitzky et al., 2012), more effective cross-selling promotion (Liu-
Thompkins and Tam, 2013), higher share of wallet (Leenheer et al., 2007) and higher share of
visits (Evanschitzky et al., 2012).
Research on customer equity argues that brand loyalty can be strongly predicted by the
three CEDs (i.e. relationship equity, brand equity and value equity) (Ou et al., 2017; Rust
et al., 2004). The benefits of this approach are that brands can maximise its long-term loyalty
of consumers by allocating resources among the three major marketing areas (i.e.
relationship equity, brand equity and value equity) rather than spanning all expenses across
multitude areas (Dwivedi et al., 2012). In this research, we investigate the complex
relationships among the three CEDs and examine when and how these effects translate into
brand loyalty. Figure 1 presents our theoretical model. We next discuss our proposed effect
of relationship equity on brand loyalty, the mediating effect of brand loyalty, the moderating
effect of value equity and the moderating effect of experiential types in the following
sections.

Mediating effect of brand equity

Consumers tend to perceive high relationship quality when they receive advantages such as
special treatment benefits; social benefits (e.g. feel familiar with the brand, stores and its
employees); and trust or confidence benefits (e.g. feel confident with the quality of the
products that a brand offers) (Vogel et al., 2008; Hennig-Thurau et al., 2002; Menictas et al.,
2012). These benefits indicate the relational benefits that customers might receive as a
consequence of their long-term relationships with a brand (Gwinner et al., 1998). According
to the principle of reciprocity, relational benefits is central of reciprocity responses, which

Experiential
types

Relationship Brand Equity Brand Loyalty

Equity (RE) (BE) (LOYAL)

Controls
Value Equity • Gender
(VE) • Age
Figure 1. • Income
• Education
Theoretical model • Occupation
are the core contribution factors of a relationship marketing success (Bond et al., 2019; Interplay of
Swoboda et al., 2013). Indeed, a brand’s relationship marketing effort creates short-term customer
consumers’ gratitude that boosts long-term outcomes based on gratitude-related reciprocal
behaviours (Palmatier et al., 2009). Therefore, when a brand offers relational benefits,
equity drivers
consumers tend to reciprocate by building and maintaining a relationship with that brand
(Ku et al., 2018; Hennig-Thurau et al., 2002). For instance, passengers participating in the
frequent-flyer program are usually hesitant to switch entirely to another airline because they
will be unable to redeem the accumulated miles (i.e. increased customer switching costs) 2261
(Rust et al., 2001; Zeithaml et al., 2001). As such, higher relationship equity might increase
the consumers’ propensity to become more loyal to a brand (Han et al., 2018; Ou and Verhoef,
2017).
The preceding arguments explain why relationship equity is positively related to brand
loyalty. To further justify this linkage, we consider the mediating role of brand equity.
Brand equity specifies the subjective and intangible appraisal of a brand as strong, unique,
attractive and likeable (Vogel et al., 2008; Lemon et al., 2001; Christodoulides et al., 2015).
Reciprocity principle predicts that if consumers receive relational benefits, consumers
should respond in kind (Ku et al., 2018; Cropanzano and Mitchell, 2005). Relationship equity
which fosters reciprocity is thus critical in strengthening consumers’ subjective evaluation
towards that brand and enhancing brand equity (Aggarwal, 2004; Muniz and O’Guinn,
2001). Research in service branding has exemplified that to evaluate relationship quality
with a brand (i.e. whether the brand treats the customers well and cares for customers),
customers refer to prior incidents with that brand, which then helps them reduce uncertainty
and increase confidence in the credibility and quality of the brand, thereby positively affects
their evaluation of the brand’s performance (Nyffenegger et al., 2015; Aaker et al., 2004).
Moreover, research on the consumer–brand relationship has demonstrated that the
consumer–brand connection is reinforced if the brand has values and personality align with
the consumers’ self-concept (Malär et al., 2011; Dall’Olmo Riley and de Chernatony, 2000;
Fournier, 1998; Sirgy, 1982). As a result, a high unique self-concept connection, which is
regarded as a dimension of consumer–brand relationships, might not only promote the
resistance to counter attitudinal information but also assist selective memory that fosters
brand equity (Swaminathan et al., 2007; Pomerantz et al., 1995). For example, consumers
with higher relationship commitment tend to resist negative information and choose to focus
more on the positive information about a brand, whereas low-committed consumers are
more affected by the negative information and exhibit a greater attitude degradation
(Ahluwalia et al., 2000). These evidence jointly support that a harmonious consumer–brand
relationship helps build stronger brand equity (Dwivedi et al., 2012; Keller, 2001; Blackston,
2000), which subsequently results in higher brand loyalty (Hariharan et al., 2018; Ou et al.,
2017; Yoon and Oh, 2016; Zhang et al., 2014; Vogel et al., 2008). As such, brand equity might
be a critical mechanism that explains why a consumer with a good relationship with a brand
is more conducive to be loyal to that brand. We hypothesise the following [1]:

H1. Brand equity mediates the positive effect of relationship equity on brand loyalty.

Moderating effect of value equity

Value equity refers to the objective evaluation of consumers about what-is-given-up for
what-is-received (Ou et al., 2014; Vogel et al., 2008; Rust et al., 2004; Lemon et al., 2001). Value
is at the core of the consumer’s relationship with the firm; without it establishing sound
relationships with consumers will be insufficient (Lemon et al., 2001; Vogel et al., 2008).
Building on this assumption, we extend our previous hypothesis by suggesting that high
EJM (low) value equity strengthens (weakens) the linkage between relationship equity and brand
54,9 equity.
Economic models of consumer behaviours indicate that rational consumers will consider
the trade-offs between decision costs and the benefits of a particular decision (Jones et al.,
2000; Hauser and Wernerfelt, 1990). When perceived value increases, higher levels of
relationship equity should more readily translate into brand equity as a result of the
2262 reciprocal responses;, because the consumers interpret the increased value as a relationship-
building effort of the brand (Fazal-e-Hasan et al., 2018). For instance, granting initially
moderate discounts to new customers might, in return, activate the customers’ motive to
build long-term relationships with brands (del Rio Olivares et al., 2018), which subsequently
enhances consumers’ brand equity and accelerates their purchases (Dwivedi et al., 2012;
Inman et al., 1997). In the context of service branding, consumers perceiving that switching
costs outweigh switching benefits are more inclined to maintain the relationship with a
brand regardless of their satisfaction level with that brand (Lee and Cunningham, 2001;
Jones et al., 2000). Accordingly, the correlation between relationship equity and brand equity
should appear strongest when the customers perceived that the brand offers overall high
perceived values.
As value equity decreases, we expect that relationship equity should be less strongly
associated with brand equity. When the value received from brands is little, consumers
might be less likely grateful towards the brands and less concerned about the violation of
the reciprocity norm (Palmatier et al., 2009; Dahl et al., 2005). For instance, when a price
promotion is retracted, consumers could easily switch to competing brands as an attempt to
find a better value of price, thus leading to a decline in brand equity of the current brand (Ku
et al., 2018; Peinkofer et al., 2015; Chang et al., 2009; Jones et al., 2000). Even consumers who
have developed a relationship with a particular brand (i.e. they purchase a single brand
repeatedly) would be less likely to patronise that brand if they experience that the brand no
longer provides attractive benefits (Guha et al., 2018; Kahn and Louie, 1990). Therefore, the
positive effect of relationship equity on brand equity might diminish under low-value
equity.
Combining the above arguments, we expect the linkage between relationship equity and
brand equity are contingent on value equity. Higher value equity tends to reinforce the
nexus between relationship equity and brand equity as a result of reciprocal behaviours. By
contrast, consumers perceiving low-value equity may have less pressure to reciprocate and
might not necessarily pay much attention to the consumer–brand relationships and their
evaluation of a brand. Thus, we hypothesise the following:

H2. The positive effect of relationship equity on brand equity is stronger when value
equity is higher and weaker when value equity is lower.

Experiential types of consumers

Complementing and extending research on the customer-level moderators of the loyalty
effects of CEDs (Ou et al., 2014; Ou and Verhoef, 2017; Ou et al., 2017), we further propose
that our preceding hypothesised linkages vary across experiential types of consumers. We
focus on experiential types of consumers because in today’s changing retail landscape,
consumers are increasingly concerned about brand experiences that stem from consumer
interactions and impressions of a brand at various touchpoints along the consumer journey
(Brakus et al., 2009; Schmitt, 2013; Schmitt et al., 2015). Brand experience is defined as the
subjective, internal consumer responses (sensory, affective and intellectual) and behavioural
responses evoked by “brand-related stimuli that are part of a brand’s design and identity, Interplay of
packaging, communications and environments” (Brakus et al., 2009) [2]. customer
Depending on the intensity of the brand experience’s dimensions evoked, consumers
might be different from others (Schmitt et al., 2015; Zarantonello and Schmitt, 2010). Based
equity drivers
on the four dimensions of brand experience (i.e. sensory, affective, intellectual and
behavioural), Zarantonello and Schmitt (2010) identify five clusters of consumers that
preferring different experiential types: holistic consumers, hedonistic consumer, action-
oriented consumers, inner-directed consumers and utilitarian consumers. 2263
Despite its importance, existing studies have not fully explored the heterogeneity of
experiential types of customers and their impact on critical marketing outcomes (e.g. brand
loyalty). These experiential types might not contribute equally to the marketing outcomes
because of the essence “not all customers are created equal” (Hallberg, 1995). Within one
portfolio of consumers, there would be some profitable, some unprofitable and some break-
even consumers (Payne and Holt, 1999). In a similar vein, Zarantonello and Schmitt (2010)
pinpoint that experiential types may trigger impulsive behaviour; for instance, the effect of
brand attitude on purchase intention is strongest for the holistic consumers but weakest for
the utilitarian consumers. Consequently, further exploration of the effects of experiential
types on consumer perceptions and behaviours will provide critically important insights for
marketers and retailers to develop and tailor their experiential strategies.
In keeping with the aforementioned arguments, we propose that the impacts of
relationship equity, brand equity and value equity on brand loyalty vary across different
experiential types of consumers. Our core argument is that different experiential profiles
might trigger different levels of relationship equity, brand equity and value equity, which
result in differential levels of brand loyalty. Indeed, for experiential consumers, brand
experience has significant impacts on relationship equity, brand equity and value equity
across various touchpoints (i.e. communication contact, personnel contact and product
usage contact), whereas for utilitarian consumers, these effects only exist at the product
usage contact point (Chen et al., 2016). With respect to relationship equity, experiential
consumption might amplify or lessen relationship equity in such a way that higher (vs
lower) value derived from experiential consumption will positively increase the tendency to
maintain the long-term relationship between brand and its customers (Tsai, 2015).
With regard to brand equity, prior literature has highlighted that stronger experiential
values associating with pleasure, usability and social value of products will directly
magnify consumer-based brand equity (Datta et al., 2017; Mishra, 2016). Besides, research on
out-of-stock occurrence postulates that the hedonic level of products significantly moderates
the impact of brand equity on customer reactions. Such that consumers who encounter the
out-of-stock situation of high-equity brands of a hedonic (vs utilitarian) product are less (vs
more) conducive to postpone the purchase and tend to choose a substitute item of the same
brands (Sloot et al., 2005).
In relation to value equity, research on experiential consumption indicates that
consumers are inclined to make less (vs more) comparisons of experiential (vs material)
purchases (Carter and Gilovich, 2010). Comparing monetary values (e.g. cost vs benefits)
more likely occurred for material consumption than that for experiential consumption
(Mann and Gilovich, 2016). Consequently, value equity might be higher for a low
experiential profile (e.g. utilitarian) but lower for a high experiential profile (e.g. hedonic).
Taken together, different experiential profiles might trigger different levels of relationship
equity, brand equity and value equity.
Furthermore, ample research on consumer psychology shows that experiential pursuits
might foster customer satisfaction and happiness in comparison to the utilitarian purchases
EJM (Lee et al., 2018; Atulkar and Kesari, 2017; Gilovich et al., 2015; Carter and Gilovich, 2012,
54,9 2010; Nicolao et al., 2009; Van Boven and Gilovich, 2003). Higher customer satisfaction is a
key factor to predict stronger brand loyalty (Atulkar and Kesari, 2017; Brakus et al., 2009).
As such, different experiential types of consumers might associate with varying levels of
brand loyalty. Taken together, the preceding arguments suggest that different experiential
profiles might trigger different levels of relationship equity, brand equity, value equity and
2264 ultimately brand loyalty. Thus, we hypothesise the following:

H3. The effects of value equity, brand equity, relationship equity on brand loyalty vary
across experiential types of consumers.

Research methodology and data collection

Data collection and sampling
This study analysed the Vietnamese supermarket and hypermarket industry. Although
traditional retailers have dominated the retailing in Vietnam (especially for grocery
products), this channel has reached its maturity. In 2016, grocery sales of hypermarkets and
supermarkets recorded value growth of 15.7% and 8.3%, respectively, whereas traditional
retailers’ sales only reported a 6.7% increase (Euromonitor International, 2017). Sales are
predicted to remarkably shifting to modern retailing channels towards the end of 2021
(Euromonitor International, 2017). Indeed, the proliferation of supermarkets and
hypermarkets in Vietnam has well fitted to the emerging busier lifestyles in metropolitan
cities. The diversity of products and the comfortable, spacious modern shopping
environments have facilitated consumer shopping enjoyment. Consumers have also become
more familiar with weekly shopping trips to the supermarkets with their families instead of
traditional daily shopping.
The mall intercept method was used to survey shoppers in a metropolitan area of
Vietnam. This method is a relatively inexpensive approach that enabled us to obtain high
quality, accurate data in a face-to-face manner (Bush and Hair, 1985). The data collection
was conducted over six months by interviewing shoppers at different supermarkets and
hypermarkets in Ho Chi Minh city. We drew on the literature to build the scales used in this
study. The survey questionnaires contained questions regarding consumers’ shopping
behaviour, their demographics and rating of the measurement scales. A convenience sample
consisting of 2,268 participants was achieved after data cleaning. Table 1 presents the
demographics of the respondents. Female consumers accounted for 55.6% of the sample.
There were 81.3% of respondents belonged to the 18–30 years of age group, 13.2% to 31–40
years of age and 5.6% to 40þ years of age. A substantial proportion of the interviewed
shoppers (81.5%) earned less than 10 million VND monthly. Most of the respondents have
attained undergraduate education (63.8%). Around 43.5% of the respondents were students,
22.1% and 10.4% of the sample comprised clericals and tradespersons, respectively.

Measurement instruments
The participants were requested to report their agreement on a seven-point Likert scale,
ranging from 1 = strongly disagree to 7 = strongly agree. All scales in our study have
demonstrated a high psychometric validity in previous literature. Brand experience scale
developed and tested by Brakus et al. (2009) was used. Brand experience is a higher-order
construct, comprises 12 items that reflect 4 dimensions, namely sensory, affective,
intellectual and behavioural. Each dimension consists of three items. All three components
of customer equity in this study were consumer-based, which means that the measurement
 Frequency Frequency
Interplay of
Demographics (n = 2,268) (%) Demographics (n = 2,268) (%) customer
equity drivers
Gender Education
Male 1,008 44.4 High school 267 11.8
Female 1,260 55.6 Undergraduate 1,448 63.8
Age group Postgraduate 151 6.7
18–30 years 1,843 81.3 Others 402 17.7 2265
31–40 years 299 13.2 Occupation
41–50 years 86 3.8 Student 986 43.5
>50 years 40 1.8 Unemployed 87 3.8
Monthly income (EUR) Tradesperson 235 10.4
<113 598 26.4 Clerical 502 22.1
113 to <188 690 30.4 Technical 154 6.8
person
188 to <377 560 24.7 Self-employed 153 6.7
377 to <565 250 11.0 Professional 77 3.4 Table 1.
565 to <753 101 4.5 Retired 25 1.1 Demographics of the
>53 69 3.0 Others 49 2.2 respondents

of these constructs was at the consumer level through a consumer survey (Yoo and Donthu,
2001). A four-item scale to measure brand equity (BE) was adapted from Vogel et al. (2008),
capturing the invisible assessment of a brand. Value equity (VE) was measured using a six-
item scale adapted from Vogel et al. (2008), expressing the consumers’ perception of the
utility of a brand based on their objective evaluation. Relationship equity (RE) was measured
using a five-item scale developed by Vogel et al. (2008), expressing the propensity that the
consumers retain the relationship with the brand. Brand loyalty (LOYAL) was a five-item
scale adapted from Chaudhuri and Holbrook (2001), Groth et al. (2009), Ha et al. (2010) and
Vogel et al. (2008). This study incorporated the demographics (gender, age, income,
education, supermarket and occupation) to control for potentially confounding effect.

Clustering analysis
We used a cluster analysis to create the consumer typology preferring different experiential
appeals in the supermarket industry. Cluster analysis is a group of multivariate techniques
for classifying the respondents based on their characteristics (Hair et al., 2010) – in our case,
the consumers who have similar brand experiences. As the numbers of the clusters were
unknown in advance, we performed a hierarchical cluster with Ward’s method (rather than a
K-means cluster) to form the consumers into similar groups. The average ratings of the four
dimensions of brand experience (i.e. sensory dimension, affective dimension, intellectual
dimension and behavioural dimension) were treated as the clustering variables. The output
indicated the possibility of five or six clusters. Based on the dendrograms and
agglomeration outcome, we opted for the five clusters distribution as the most appropriate
solution.
Table 2 describes the mean and standard deviations of the four brand experience
dimensions and illustrates how the five clusters of consumers varied across the total
sample, the male sample and the female sample, whereas Figure 2 provides a more visual
illustration of different means among the five clusters of consumers. We discover five
experiential types of consumers based on their intensity of four dimensions of brand
experience. This result includes four groups of consumers that are proposed by
EJM Sample size Mean (SD)
54,9 Cluster N (%) Sensory Affective Intellectual Behavioural

Total sample (1) Holistic 448 19.8 5.65 (0.57) 5.75 (0.58) 5.68 (0.63) 5.66 (0.64)
(2) Hedonistic 188 8.3 5.11 (0.71) 5.17 (0.61) 3.59 (0.68) 4.27 (0.73)
(3) Action-oriented 927 40.9 4.27 (0.66) 4.57 (0.61) 4.71 (0.61) 4.61 (0.60)
(4) Sensorial 471 20.8 3.68 (0.78) 3.46 (0.71) 3.35 (0.75) 3.41 (0.59)
2266 (5) Utilitarian 234 10.3 2.71 (0.75) 2.49 (0.75) 2.02 (0.62) 2.12 (0.67)
Total 2,268 100.0 4.33 (1.10) 4.41 (1.18) 4.25 (1.28) 4.28 (1.20)
Male sample (1) Holistic 201 19.9 5.61 (0.56) 5.72 (0.60) 5.70 (0.62) 5.69 (0.63)
(2) Hedonistic 67 6.6 5.22 (0.61) 5.14 (0.55) 3.69 (0.69) 4.34 (0.69)
(3) Action-oriented 439 43.6 4.30 (0.65) 4.54 (0.64) 4.69 (0.61) 4.59 (0.57)
(4) Sensorial 200 19.8 3.70 (0.76) 3.51 (0.60) 3.40 (0.76) 3.42 (0.58)
Table 2. (5) Utilitarian 101 10.0 2.71 (0.63) 2.43 (0.70) 2.08 (0.65) 2.16 (0.61)
Mean and standard Total 1,008 100.0 4.35 (1.07) 4.40 (1.15) 4.31 (1.25) 4.32 (1.18)
Female sample (1) Holistic 247 19.6 5.68 (0.57) 5.77 (0.56) 5.67 (0.64) 5.63 (0.65)
deviations of
(2) Hedonistic 121 9.6 5.05 (0.75) 5.19 (0.64) 3.53 (0.67) 4.23 (0.76)
clustering variables (3) Action-oriented 488 38.7 4.25 (0.67) 4.59 (0.59) 4.72 (0.61) 4.63 (0.62)
of the total sample, (4) Sensorial 271 21.5 3.67 (0.79) 3.42 (0.79) 3.32 (0.75) 3.40 (0.59)
male sample and (5) Utilitarian 133 10.6 2.70 (0.84) 2.54 (0.78) 1.97 (0.60) 2.09 (0.70)
female sample Total 1,260 100.0 4.31 (1.13) 4.41 (1.20) 4.20 (1.30) 4.25 (1.22)

Zarantonello and Schmitt (2010) (e.g. holistic consumers, hedonistic consumers, action-
oriented consumers and utilitarian consumers). The inner-directed consumers were not
found from our analysis. However, we have explored one novel group that focusses
mostly on the sensorial experience (e.g. sensorial consumers):
 Holistic consumers: The first cluster comprised 19.8% of the total sample (mean =
5.686). This group included the consumers with similarly highest scores (above 5.65)
on all four experiential dimensions, although the affective dimension was slightly
higher than other dimensions (mean = 5.75). This segment of consumers reflects the
highest experiential profile that would be attracted by all four dimensions of brand

7.0

6.0 5.7 5.7 5.7 5.7

5.1 5.2
5.0 4.6 4.7 4.6
4.3 4.3
4.0 3.6 3.7
3.5 3.4 3.4

3.0 2.7
2.5
2.0 2.1
2.0

1.0

Figure 2. 0.0
Cluster means on the (1) Holisc (2) Hedonisc (3) Acon-oriented (4) Sensorial (5) Ulitarian
four brand consumers consumers consumers consumers consumers
experience’s
dimensions Sensory Affecve Intellectual Behavioral
 experience simultaneously (e.g. sensory, affective, intellectual and behavioural) Interplay of
(Zarantonello and Schmitt, 2010). customer
 Hedonistic consumers: The second cluster only made up 8.3% of the sample equity drivers
(mean = 4.535). Members of this cluster had considerable experience on the two
dimensions, sensory and affective (mean = 5.11 and 5.17, respectively), but less
experience on the behavioural (mean = 4.27) and intellectual (mean = 3.59). These
so-called hedonistic consumers preferred brands that attached strong sentiments 2267
and impression on their senses (Zarantonello and Schmitt, 2010).
 Action-oriented consumers: The third cluster constituted most of the sample (40.9%,
mean = 4.540). These consumers had above-average scores among the four
dimensions. They were especially interested in the intellectual dimension (mean =
4.71), behavioural dimension (mean = 4.61) and affective (mean = 4.57) but had less
concern about sensory (mean = 4.27). As such, these consumers could be possibly
attracted by brands that resulted in problem-solving encouragement, physical
actions and emotional appeals. Hence, our finding has pinpointed one more aspect of
the action-oriented consumers (i.e. affective dimension) as compared to previous
research (Zarantonello and Schmitt, 2010).
 Sensorial consumers: We found a new cluster that accounted for 20.8% consumers
in the sample (mean = 3.476). The members of this group seem to be opposite of the
action-oriented consumers: sensorial gratification played a remarkable role towards
this cluster (mean = 3.68), whereas affective, behavioural and intellectual
experiences scores were below the average value 3.5. This consumer-type looks for
the brands associated with sensory appeals and less compelling with physical
actions, bodily experiences and stimulation of thinking. Hence, we call this group as
sensorial consumers.
 Utilitarian consumers: This group composed 10.3% of the sample (mean = 2.334). In
contrast to holistic consumers, this cluster accounted for consumers that had the
lowest scores among the five clusters, ranging between 2.02 (intellectual) to 2.71
(sensory). Similar to the typology of Zarantonello and Schmitt (2010), this utilitarian
group is the low experiential profile that does not seem to attach much importance
to any brand experience dimension.

To validate our cluster analysis result, we adopted two of the most widely used methods
from the literature:
(1) performing a new cluster analysis on the subsamples; and
(2) conducting a discriminant analysis to establish membership of each individual
(Zarantonello and Schmitt, 2010).

Firstly, the cluster analysis conducted on the two subsamples (1,008 males and 1,260
females) revealed a highly consistent result with the total sample’s clusters outcome. Five
different clusters emerged in the two subgroups demonstrating analogous characteristics
with the five clusters segmented from the total sample. Details of the cases classification of
the total sample and two subsamples are represented in Table 2.
Secondly, the tests of equality of group means based on the discriminant analysis result
indicated strong group differences (i.e. Wilks’ Lambda for all four variables were much
lower than 1) and all were significant, such as Sensory (Wilks’ Lambda = 0.382, F(4, 2151) =
869.048, p < 0.001), Affective (Wilks’ Lambda = 0.278, F(4, 2151) = 1398.039, p < 0.001),
Intellectual (Wilks’ Lambda = 0.268, F(4, 2151) = 1467.082, p < 0.001) and Behavioural
EJM (Wilks’ Lambda = 0.323, F(4, 2151) = 1124.739, p < 0.001). Moreover, the result from the chi-
54,9 square statistic was highly significant (Wilks’ Lambda = 0.075, x 2 = 5561.511, df = 16, p <
0.001). There was 99.3% of original-grouped cases correctly classified into five clusters. This
result showed a highly similar distribution with the cluster analysis. Hence, the validation
for the five-cluster solution could be confirmed.

2268 Data analysis and findings

Measurement model
Table 3 depicts the strong psychometric properties of the measurement based on the criteria
of construct reliability, convergent validity and discriminant validity. Firstly, the construct
reliability was achieved because all-composite reliabilities (ranging between 0.87 and 0.91)
were considerably greater than the threshold of 0.7 (Nunnally and Bernstein, 1994).
Secondly, convergent validity was satisfactory as the average variance extracted (AVE)
of all constructs (ranging from 0.75 to 0.82) were well above 0.5 (Fornell and Larcker, 1981).

Constructs and manifest variables Loading

Relationship equity AVE = 0.57 composite reliability = 0.87 (adapted from Vogel et al., 2008; 7-point scale
1 = “strongly disagree” and 7 = “strongly agree”)
1. As a member of the loyalty program, they do services for me that they 0.78
don’t do for most customers 0.80
2. I am familiar with the employees that perform the service 0.66
3. I am glad to meet other customers in this supermarket 0.76
4. Employees in that supermarket know my name 0.75
5. I have trust in this supermarket
Brand equity AVE = 0.63 composite reliability = 0.87 (adapted from Vogel et al., 2008; 7-point scale 1 =
“strongly disagree” and 7 = “strongly agree”)
1. This brand is a strong brand 0.79
2. This brand is an attractive brand 0.80
3. This brand is a unique brand 0.79
4. This brand is a likeable brand 0.80
Value equity AVE = 0.61 composite reliability = 0.90 (adapted from Vogel et al., 2008; 7-point scale 1 =
“strongly disagree” and 7 = “strongly agree”)
1. The quality–price ratio with the dealer with respect to products is very good 0.77
2. The quality-price ratio with the dealer with respect to services is very good 0.79
3. The supermarket is very attractive 0.81
4. How would you rate your overall shopping experience at this supermarket (“extremely good 0.78
value/extremely poor value”)?
5. For the time spent at this supermarket, would you say shopping is (“highly reasonable/highly 0.80
unreasonable”)?
6. For the effort involved in shopping at this supermarket, would you say shopping is (“very 0.74
worthwhile/not at all worthwhile”)?
Brand loyalty AVE = 0.67 composite reliability = 0.91 (adapted from Ha et al., 2010; Chaudhuri and
Holbrook, 2001; Groth et al., 2009; Vogel et al., 2008; 7-point scale 1 = “strongly disagree” and 7 = “strongly
agree”)
1. This supermarket would be my first choice 0.81
2. I will not purchase from other supermarkets if the services and products are available at this 0.83
supermarket
Table 3. 3. I intend to keep shopping at this supermarket 0.83
Measurement model 4. I will recommend this supermarket to someone who seeks my advice 0.81
results 5. I would repurchase at this supermarket 0.82
Factor loadings of the focal constructs (ranging from 0.66 to 0.93) surpassed the required Interplay of
cut-off value of 0.5 (Hair et al., 2010) and all were significant. customer
Thirdly, discriminant validity was also obtained as the squared roots of AVE values
were consistently higher than the off-diagonal correlations, as shown in Table 4 (Fornell and
equity drivers
Larcker, 1981). Finally, a second method to evaluate the discriminant validity is the
employment of heterotrait–monotrait ratio (HTMT) recommended by Henseler et al. (2014)
which is demonstrated as a more powerful assessment of discriminant validity. The HTMT
for all reflective constructs in our model (ranging from 0.25 to 0.80) did not exceed the 2269
conservative value of 0.85 (Kline, 2011), thus guaranteed the constructs’ discriminant
validity. The highest upper confidence interval (CI) of all HTMT was 0.82, which
significantly differed from 1. Consequently, these results strongly supported that all
constructs achieved satisfactory construct validity.

Common method variance

The study investigated possible common method bias (CMV) effects that may cause
spurious relationship among variables (Podsakoff et al., 2003) by using Harman’s single-
factor test (Podsakoff and Organ, 1986), unmeasured latent method construct (ULMC)
technique in partial least square (PLS) (Liang et al., 2007) and marker-variable technique
(Lindell and Whitney, 2001; Malhotra et al., 2006). The result of Harman’s single factor
test indicated that the first factor only composed of 35% of the overall variance. Given
that a factor did not comprise most of the variance, the CMV effect is unlikely to bias our
analysis. We conducted an ULMC test as suggested by Liang et al. (2007), where a latent
method factor is included in our PLS model. The results showed that the method factor
loadings were either insignificant or the variance explained by the method factor was
smaller than the variance attributed to the substantive construct. The results showed
that the method factor loadings were either insignificant or that the variance explained
by the method factor was smaller than the variance attributed to the substantive
construct. The findings suggest that CMV is not a severe issue in our study.
Additionally, using the marker-variable technique (Lindell and Whitney, 2001; Malhotra
et al., 2006), we examined the correlations of a marker variable and the other variables to
obtain a more robust result for the CMV check. The proficiency in using Microsoft Word of
the respondents was used as the marker variable, as it represented the smallest positive
correlation with the dependent variable in the correlation matrix (r = 0.05, p = 0.03). The
average absolute correlation between the marker variable and the other factors of the model
was rm = 0.04 (p = 0.04). The average difference between the original and the CMV-adjusted
correlations was only 0.02. As such, none of the original correlations significantly differed
from their CMV-adjusted counterparts, proving that CMV was not existing.

Constructs Relationship equity Brand equity Value equity Brand loyalty

Relationship equity 0.75

Brand equity 0.46 0.79
Value equity 0.68 0.50 0.78
Brand loyalty 0.21 0.40 0.22 0.82
Table 4.
Notes: Sample size = 2,268; diagonal entries show the squared roots of AVE values; all correlation
coefficients are significant at the 0.01 level. The italic values (diagonal) are not correlation coefficients but Descriptive statistics
AVE. Thus, no significance level was attached. Besides, the off-diagonal elements are the correlations and correlations for
among the constructs and all were significant at p < 0.01. study variables
EJM Endogeneity check
54,9 The potential endogeneity in the model was controlled by using a two-stage least square
approach and education used as the instrumental variables. Education was chosen based on
the following two criteria:
(1) it correlated with relationship equity in the first stage; and
(2) it did not correlate with brand loyalty in the second stage.
2270
The ivendog command in STATA 14 was applied. The result from the endogeneity proved
that there was no endogeneity bias in our model (Durbin–Wu–Hausman chi-squared test:
x 2 = 0.04, p-value = 0.83; Wu–Hausman F-test: F(1, 2265) = 0.04, p-value = 0.83)
(Wooldridge, 2009).

Hypotheses testing
After segmenting the consumers by clustering analysis and discriminant analysis, we used
the PLS-SEM analysis with SmartPLS 3.0 to test the proposed hypotheses. PLS is a non-
parametric approach based on ordinary least squares (OLS) regression and is designed to
optimise the explained variance (Ringle et al., 2015; Sarstedt et al., 2019). We opted for PLS-
SEM instead of covariance-based structural equation modelling because of the following:
 our goal was to examine the primary driver constructs;
 formative constructs were part of our structural model; and
 the latent variable scores were used in our subsequent analyses (Hair et al., 2014).

After that, we confirmed the moderated mediation effect using approach (PROCESS Model
7), with a 95% CI and 5,000 bootstrap samples (Hayes et al., 2017; Hayes, 2013; Preacher and
Hayes, 2008). Finally, we used the MGA in PLS to test the potential differences of the
proposed model for different clusters.

Structural model
H1 predicted that brand equity would mediate the link between relationship equity and
brand loyalty. To test this hypothesis, we followed the approach suggested by Hair et al.
(2014) and developed Model 1 and Model 2. We firstly estimated the PLS path model without
brand equity as the potential mediator in Model 1. Then, we included the mediator variable
brand equity and tested the significance of the indirect effect of relationship equity on brand
loyalty via brand equity in Model 2. Finally, we evaluated the strength of this mediation
effect by measuring the variance accounted for (VAF) that represented the percentage of the
indirect effect out of the total effect. As suggested by Hair et al. (2014), if VAF is lower than
0.20 or higher than 0.20 but lower than 0.80, there is no mediation or partial mediation,
respectively. Full mediation can be affirmed if VAF is larger than 0.80.
As reported in Table 5, relationship equity positively influenced brand loyalty (Model 1,
b = 0.19, t-values = 10.71) and brand equity (Model 2, b = 0.47, t-values = 29.51), which
also positively affected brand loyalty (Model 2, b = 0.38, t-values = 19.61). Contrary to
Model 1, we found that the positive effect of relationship equity on brand loyalty converted
into insignificant in Model 2 ( b = 0.01, t-values = 0.59). The direct effect of relationship
equity on brand loyalty was 0.01, whereas the indirect effect via brand equity had a value of
0.18. We found that the size of the indirect effect in the total effect was 93.3% (>80%). As
such, brand equity fully mediated the link between relationship equity and brand loyalty.
Then, H1 was supported.
 Endogenous model
Interplay of
Model 1 Model 2 Full model customer
Exogenous variables Brand loyalty Brand equity Brand loyalty Brand equity Brand loyalty equity drivers
Direct effects
Relationship equity 0.19* (10.71) 0.47* (29.51) 0.01 (0.59) 0.23*(9.21) 0.01 (0.62)
Brand equity 0.38* (19.61) 0.38* (19.54)
Value equity 0.37* (14.29) 0.01 (0.30) 2271
RE  VE 0.08* (5.89)
Indirect effects
RE ! BE ! BL 0.18* (15.09) 0.09* (7.78)
Control variables
Gender 0.07* (3.87) 0.01 (0.58) 0.07* (3.79) 0.01 (0.56) 0.07* (3.79)
Age 0.07* (2.79) 0.01 (0.25) 0.07* (3.01) 0.01 (0.61) 0.07* (2.98)
Income 0.13* (5.60) 0.01 (0.67) 0.13* (6.02) 0.01 (0.29) 0.13* (5.79)
Education 0.01 (0.60) 0.02 (1.02) 0.02 (1.00) 0.02 (1.10) 0.02 (1.01)
Supermarket 0.07* (3.23) 0.10* (5.23) 0.03 (1.35) 0.03 (1.34) 0.03 (1.31)
Occupation 0.02 (0.73) 0.02 (0.77) 0.01 (0.54) 0.02 (0.92) 0.01 (0.55)
R2 0.09 0.22 0.20 0.29 0.20 Table 5.
Structural model
Note: *p < 0.01 results

H2 proposed that value equity would moderate the indirect effect of relationship equity on
brand loyalty through brand equity. We expected that the mediated relationship would be
stronger if value equity increased. The full model was developed to test this moderation
effect. As shown in the full model in Table 5, both relationship equity ( b = 0.23, t-values =
9.21) and value equity ( b = 0.37, t-values = 14.29) had positive impacts on brand equity.
More importantly, the interaction effect of relationship equity and value equity also
demonstrated a positive influence on brand equity ( b = 0.08, t-values = 5.89). Hence, the
linkage between relationship equity and brand loyalty via brand equity would increase
when value equity becomes higher, supporting H2.

Moderated mediation analysis

Moderated mediation effect was assured by using the bootstrapping bias-corrected CI
procedure of the SPSS Macro PROCESS Model 7 (Hayes, 2013). The OLS path analysis was
applied to estimate the model coefficients. The analysis confirmed that the moderation
model with brand equity as the outcome variable was significant, F (3, 2264) = 306.33, p <
0.001, R2 = 0.29. Also, the mediation model with brand loyalty as the outcome variable was
significant, F (2, 2265) = 215.19, p < 0.001, R2 = 0.16. Furthermore, the index of moderated
mediation was significant, b = 0.03, 95% CI = [0.02, 0.04], indicating that the indirect effect
of relationship equity on brand loyalty through brand equity differed significantly at
varying levels of value equity. This result was substantially identical to our PLS-SEM
result.
To ensure the robustness of our proposed model, we checked competing models for
potential interaction effects among the three CEDs: relationship equity (RE), brand equity
(BE) and value equity (VE) (e.g. VE moderates BE ! RE; BE moderates VE ! RE). We
further checked the potential mediating effects of brand equity and value equity on the link
between relationship equity and brand loyalty. We found neither significant moderating nor
mediating effects, suggesting the high level of robustness of our proposed model.
EJM Multigroup analysis
54,9 To test H3, we used multigroup analysis (PLS-MGA), the statistical procedure to explore
whether there are differences between path coefficients in the structural model. PLS-MGA is
a set of different techniques that can be used to compare the PLS models across subgroups
of data (Hair et al., 2010). To avoid ambiguity in the interpretation of the MGA results, before
testing and interpreting differences in the path coefficients, we followed Bagozzi and Yi
2272 (2012) to examine the factor-loading invariance across five clusters of consumers. We found
that for each of the main variables in our model, there was at least a factor loading per
variable was invariant (p > 0.05) across the five clusters. Therefore, the differences
discovered for the path coefficients could be interpreted unambiguously (Bagozzi and Yi,
2012).
As shown in Table 6, the MGA results indicated substantial differences among the five
clusters of consumers, supporting H3. As can be seen, the impact of relationship equity on
brand loyalty of sensorial consumers was significantly lowered than that of the holistic
consumers (|p(Ho) – p(Se)|= 0.225, p < 0.01), hedonistic consumers (|p(He) – p(Se)|= 0.187, p <
0.05) and action-oriented consumers (|p(Ac) – p(Se)|= 0.149, p < 0.1). Besides, the influence of
relationship equity on brand equity was stronger towards holistic consumers rather than
hedonistic consumers (|p(Ho) – p(He)|= 0.157, p < 0.05) and sensorial consumers (|p(Ho) –
p(Se)|= 0.230, p < 0.05). Regarding brand equity, the results indicated that the effect of brand
equity on brand loyalty was significantly stronger for holistic consumers and hedonistic
consumers than action-oriented consumers, sensorial consumers and utilitarian consumers
(p < 0.1).
Moreover, action-oriented consumers also experienced a significantly higher impact of
brand equity on brand loyalty than sensorial consumers (|p(Ac) – p(Se)|= 0.148, p < 0.1). In
terms of value equity, we found that the influence of value equity on brand equity towards
holistic consumers was stronger than the four other groups of consumers (p < 0.1). Overall,
the MGA result confirms that the strength of the relationship among three components of
customer equity (i.e. value equity, brand equity and relationship equity) and brand loyalty
would differ significantly among the five experiential types of consumer. Based on the
analysis results, all hypotheses in our research were strongly supported.

Conclusion and implications

Theoretical implications
Our study focusses on decoding the complexity of the CEDs–loyalty link and examining the
contingency role of brand experience on this link. In this connection, we use the principle of
reciprocity from social exchange theory (Cialdini et al., 1975; Cropanzano and Mitchell, 2005;
Montoya and Insko, 2008; Falk and Fischbacher, 2006) to delineate a reciprocity pathway in
that the unique roles of CEDs are identified towards creating the reciprocity effects.
Concerning the first question on the reciprocal relationships among CEDs and brand loyalty,
we propose that brand equity fosters and sustains the reciprocity generated when
consumers perceive a high level of relationship equity, serving as a mediator between
relationship equity and brand loyalty. We further posit that the linkage between
relationship equity brand equity is contingent on value equity. For the second research
question, we incorporate brand experience as a potential moderator upon which the
interrelationships among CEDs and brand loyalty may vary. The study findings provide
full support on the proposed hypotheses and make contributions to the growing body of
work on customer equity (Ou et al., 2017; Rust et al., 2004), brand loyalty (Chaudhuri and
Holbrook, 2001; Oliver, 1999) and brand experience (Brakus et al., 2009; Zarantonello and
Schmitt, 2010).
Relationships |p(Ho) – p(He)| |p(Ho) – p(Ac)| |p(Ho) – p(Se)| |p(Ho) – p(Ut)| |p(He) – p(Ac)| |p(He) – p(Se)| |p(He) – p(Ut)| |p(Ac) – p(Se)| |p(Ac) – p(Ut)| |p(Se) – p(Ut)|

RE ! LOYAL 0.037 0.076 0.225*** 0.096 0.038 0.187** 0.058 0.149* 0.020 0.129
RE ! BE 0.157** 0.074 0.230** 0.118 0.083 0.073 0.039 0.156 0.044 0.112
BE ! LOYAL 0.004 0.120** 0.269*** 0.169** 0.116** 0.265*** 0.165** 0.148* 0.048 0.100
VE ! BE 0.176*** 0.129* 0.157* 0.164* 0.047 0.019 0.012 0.028 0.036 0.008
VE*RE ! BE 0.026 0.029 0.036 0.024 0.003 0.010 0.002 0.007 0.005 0.012
Gender ! LOYAL 0.013 0.006 0.009 0.042 0.019 0.005 0.029 0.015 0.048 0.034
Age ! LOYAL 0.009 0.110* 0.079 0.095 0.101* 0.070 0.104 0.031 0.205** 0.174
Income ! LOYAL 0.006 0.085 0.245*** 0.080 0.078 0.238*** 0.073 0.160 0.005 0.165
Education ! LOYAL 0.042 0.062 0.027 0.095 0.105* 0.015 0.052 0.090 0.157* 0.067
Supermarket ! LOYAL 0.040 0.028 0.052 0.106 0.012 0.013 0.145** 0.025 0.133 0.158
Occupation ! LOYAL 0.004 0.031 0.154 0.141 0.035 0.158* 0.145* 0.123 0.110 0.013

Notes: p(Ho), p(He), p(Ac), p(So) and p(Ut) is the path coefficients of the holistic consumers, hedonistic consumers, action-oriented consumers, sensorial consumers and
utilitarian consumers, respectively. ***p < 0.01; **p < 0.05; *p < 0.1
customer

differences
results: path
Table 6.
2273

coefficients
equity drivers
Interplay of

Multi-group analysis
EJM Firstly, we introduce a reciprocity perspective to decode the complexity of the CEDs–loyalty
54,9 link. Previous studies emphasise the direct effects of CEDs in establishing consumer loyalty
(Ou et al., 2017; Vogel et al., 2008). However, firms still have little insights on how to make
effective resources allocation to value equity, brand equity and relationship equity. Such equal
investments in marketing efforts might turn out inefficienct if they miss their goals (Rust et al.,
2001). Current literature has limited knowledge of the interplay among value equity, brand
2274 equity and relationship equity. Understanding this interrelation is significant to clarify why
and when CEDs trigger loyalty. The principle of reciprocity may help us solve this puzzle.
Indeed, we find empirical evidence that reciprocity pathway exists between CEDs and brand
loyalty in which individual CED plays a unique role in creating reciprocity effect. Our findings
shed lights on brand equity and value equity as the two underlying mechanisms that establish
a moderated mediation model between CEDs and brand loyalty. Our study is a response to a
call by Swoboda et al.’s (2013, p. 447) on how firms can “take reciprocal effects into account
when allocating resources” especially in a retailing context. This study is among the first to
open the black box of the CEDs–brand loyalty linkage through the lens of reciprocity.
Second, we contribute to marketing literature by providing evidence of the moderating
effect of brand experience on the CEDs–loyalty link. There is a relative paucity of knowledge
about individual differences or consumer-based segmentation variables associated with brand
loyalty and other marketing-related variables (Chaudhuri and Holbrook, 2001). Our study
forges this missing gap and studies how the moderated mediation proposed model varies for
different types of experiential consumer. We reveal an important phenomenon: there exists a
typology of experience-focussed consumers and these experiential types moderate the
interrelationships among CEDs and brand loyalty. We discovered five emerging types of
experiential consumers comprising holistic consumers, hedonistic consumers, action-oriented
consumers, sensorial consumers and utilitarian consumers. The result of MGA indicates
substantial differences among the five clusters of consumers in enhancing the impact of
customer equity mechanisms on brand loyalty. Scholars have called for research to examine
the contribution of brand experience to CEDs and brand loyalty (Lemon and Verhoef, 2016;
Brakus et al., 2009). By positioning brand experience as an important moderator, we also
advance theory on the boundary conditions of the reciprocity effect.

Managerial implications
The retailing landscape is changing remarkably. For example, retailers such as Walmart have
thrived on beating the retail battle by refining their value equity. Its recently launched smart
pricing strategy has allowed the online consumers to share in the lower costs associated with
in-store collection instead of delivery (Weinswig, 2017). Thus, our theoretical viewpoint aims to
reflect fresh marketing insights for the dynamic retail settings. We demonstrate a rationale for
firms and suggest useful managerial solutions for marketers to manage and allocate resources
more efficiently, to better understand the diversity of consumers towards brand experience
dimensions and to ultimately boost the brand loyalty of the consumers.
The results offer valuable insights for managers that are responsible for building brands,
managing relationships and fostering brand loyalty of the consumers. Companies should
devote their attention to strengthening their brand equity because of its directly positive
mediating effect of the nexus between relationship equity and brand loyalty. If consumers
consider a brand as unique, strong and preferable, they experience higher brand equity
(Verhoef et al., 2009) and they would prefer choosing that brand than others (Vogel et al., 2008).
Firms can build their brand equity in several ways. For example, enhancing brand awareness
of the consumers by using marketing communications (Lemon et al., 2001; Yoo and Donthu,
2001), starting with quality products to build brand image and gain positive consumer
evaluation (Baalbaki and Guzman, 2016), creating positive brand attitude to leverage the Interplay of
consumer purchase decision (Lemon et al., 2001) and evolving a consistent brand image to form customer
a special relationship between the brand and its consumers (Keller, 1993).
Additionally, with a focus on relationship management, our findings suggest that any
equity drivers
attempt from the supermarkets to consolidate its relationship with consumers will
favourably stimulate positive influences on brand loyalty via brand equity. Savvy brands
should look for innovative ways to bring significantly greater benefits to their consumers
(Lemon et al., 2001). For example, through the launch of the loyalty program on mobile apps, 2275
supermarkets will be able to deliver more customised, relevant promotions to their shoppers.
Such apps will also make it more convenient for consumers to easily collect their rewards.
Though the idea of the loyalty program has been long recognised, a global study of Nielsen
on more than 29,000 in 58 nations in 2013 specifies that 84% surveyed consumers opt for
retailers that offer a loyalty program (Nielsen, 2013). Furthermore, literature has found that
the salespeople, who engage in a variety of selling behaviours for the long-term relationship,
will accordingly have a favourable impact on the consumer’s perception of relational quality
(Crosby et al., 1990). Thus, using well-trained in-store staffs is another approach for
managers and marketers to reinforce the relationships between brands and their consumers.
Furthermore, we also present significant implications for managers and marketers that
are responsible for improving value equity. Our study has exemplified how value equity can
strengthen the link between relationship equity and brand equity through its moderating
effect. It is noteworthy that 34% of the consumers would quit shopping if they are unaware
of enough benefits (Nielsen, 2013). Therefore, companies should highlight the visibility of
value that they provide to consumers. Such efforts should be implemented to leverage the
three fundamental levers that influence value equity, including quality, price and
convenience (Lemon et al., 2001). One way for managers is to continuously boost their
innovation and differentiate their products to meet consumer needs, reach prospective
consumer segments and prevent existing buyers from switching. Managers and marketers
should also track the operation of new launches and use that information to make sure that
they develop the right products at the right price. Firms could consider offering different
facets of value to consumers, such as convenience, engagement, quality products and
services, advertising campaigns and price promotions with a caution to the different
consumer types. Through these efforts, companies should be able to promote value equity
and, accordingly, facilitate the link between relationship equity and brand equity.
Finally, our study has also distinguished among holistic consumers, hedonistic consumers,
action-oriented consumers, sensorial consumers and utilitarian consumers. For instance,
holistic consumers prefer the entire aspects of brand experience, whereas utilitarian consumers
are unlikely to attach considerable concern to any brand dimension. More importantly, the
findings indicate that the moderated mediation effects of value equity, brand equity and
relationship equity on brand loyalty vary significantly depending on the types of experiential
appeal that characterise consumers. Consequently, managers and marketers can interpret our
results as support to set up a more effective resource allocation and tailored marketing
strategies that generate long-term effects on different experiential consumer appeals. For
example, understanding that value equity may be more dominant in fostering brand equity –
for those associated with holistic consumers rather than other types of consumer – suggests
different marketing strategies and themes for these consumer segments.

Limitations and future research directions

Our unique findings should be viewed in light of their limitations. Firstly, we particularly
examined the supermarket industry in Vietnam. Therefore, caution must be executed in
EJM determining if the effects still hold to other industries or other countries. Secondly, our study
54,9 highlighted a snapshot of the CEDs and brand loyalty across different segments of
consumers by using the data from one point in time. By doing so, we assumed that time lag
did not occur between the customer equity mechanisms and brand loyalty. Consequently,
we encourage future research to establish stronger inference and generalizability of our
findings by extending the impacts of the focal constructs in the model over time. Thirdly, we
2276 recognise that there exists the age bias among respondents. Although the age range of
respondents is from 18 to above 50 years, the 18–30 group accounts for a large portion of the
sample and is not representative of the general population. A positive aspect of this
limitation is that this group of consumers should receive more attention from the retailers.
Fourthly, our sample is limited to consumers of a metropolitan city in Vietnam, making it
difficult to generalise our findings across other geographies. Future studies could focus on
other geographies, such as country provinces.
Fifth, our study is also limited to the cross-sectional design. Future studies could use a
randomised experiment as another alternative. Sixth, because of a paucity of research in
discovering the moderating impact of experiential types, directional hypotheses would be
premature at this point in our study. In a recent study, Gao et al. (2020) examine the
moderating role of social influence in the linkages between the CEDs and customer
experience quality. Additional research might benefit from exploring the potential
moderating effects of customer experience quality on the linkages in our model.
Finally, our findings on segmented clusters and associated moderating effects might
be sample specific. Indeed, our findings confirmed four out of five segments from prior
work (Zarantonello and Schmitt, 2010). We probed into a typology of experience-focussed
consumers using the four dimensions of brand experience (i.e. sensory, affective,
intellectual and behavioural). Yet, we did not examine the stability of the segments,
which depends on the particular cluster solution from the sample (Wedel and Kamakura,
1998; Kim and Lee, 2011). Thus, the results on the moderating effects of experiential types
should be generalized with caution given the nature of the sample. Despite the preceding
limitations, this study provides a solid foundation for understanding the managerial
implications of the nexus among value equity, brand equity, relationship equity in
enhancing brand loyalty and how these mechanisms differ towards different brand
experience appeals of consumers.

Notes
1. It is worth noting that the reversal causation (e.g. brand equity fosters relationship equity) is not
likely occurred in this research. In fact, relationship equity measures the strength of the brand
relationship, beyond its objective and subjective values, whereas brand equity focuses on the
subjective perceptions of the brand only (Rust et al., 2001; Zeithaml et al., 2001). An increase of
brand equity does not necessarily associate with a rise in relationship equity (Dwivedi et al.,
2012). For example, a Scottish supermarket hired the robot assistant with the intention to boost
their business. While this initiative seemed to increase brand equity at the beginning, it did not
improve the relationship quality and turned out to be customers’ disappointment when the robot
failed to interact properly with customers (The Telegraph, 2018). Moreover, empirical
investigation from prior research directly emphasises that the mediating effect of relationship
equity on the link between brand equity and brand loyalty is not existing (Veloutsou, 2015;
Dwivedi et al., 2012). Hence, the causation should flow from relationship equity to brand equity
rather than from brand equity to relationship equity.
2. See Appendix for the brand experience scale.
References Interplay of
Aaker, J., Fournier, S. and Brasel, S.A. (2004), “When good brands do bad”, Journal of Consumer customer
Research, Vol. 31 No. 1, pp. 1-16.
equity drivers
Aggarwal, P. (2004), “The effects of brand relationship norms on consumer attitudes and behavior”,
Journal of Consumer Research, Vol. 31 No. 1, pp. 87-101.
Ahluwalia, R., Burnkrant, R.E. and Unnava, H.R. (2000), “Consumer response to negative publicity:
the moderating role of commitment”, Journal of Marketing Research, Vol. 37 No. 2, 2277
pp. 203-214.
Atulkar, S. and Kesari, B. (2017), “Satisfaction, loyalty and repatronage intentions: role of hedonic
shopping values”, Journal of Retailing and Consumer Services, Vol. 39, pp. 23-34.
Baalbaki, S. and Guzman, F. (2016), “A consumer–perceived consumer–based brand equity scale”,
Journal of Brand Management, Vol. 23 No. 3, pp. 229-251.
Bagozzi, R.P. and Yi, Y. (2012), “Specification, evaluation, and interpretation of structural equation
models”, Journal of the Academy of Marketing Science, Vol. 40 No. 1, pp. 8-34.
Bairrada, C.M., Coelho, F. and Coelho, A. (2018), “Antecedents and outcomes of brand love:
utilitarian and symbolic brand qualities”, European Journal of Marketing, Vol. 52 No. 3/4,
pp. 656-682.
Blackston, M. (2000), “Observations: building brand equity by managing the brand’s relationships”,
Journal of Advertising Research, Vol. 40 No. 6, pp. 101-105.
Bond, S.D., He, S.X. and Wen, W. (2019), “Speaking for ‘free’: word of mouth in free-and paid-product
settings”, Journal of Marketing Research, Vol. 56 No. 2, pp. 276-290.
Brakus, J.J., Schmitt, B.H. and Zarantonello, L. (2009), “Brand experience: what is it? How is it
measured? Does it affect loyalty?”, Journal of Marketing, Vol. 73 No. 3, pp. 52-68.
Bush, A.J. and Hair, J.F. Jr, (1985), “An assessment of the mall intercept as a data collection method”,
Journal of Marketing Research, Vol. 22 No. 2, pp. 158-167.
Carter, T.J. and Gilovich, T. (2010), “The relative relativity of material and experiential purchases”,
Journal of Personality and Social Psychology, Vol. 98 No. 1, pp. 146-159.
Carter, T.J. and Gilovich, T. (2012), “I am what I do, not what I have: the differential centrality of
experiential and material purchases to the self”, Journal of Personality and Social Psychology,
Vol. 102 No. 6, pp. 1304-1317.
Chang, H.H., Wang, Y.H. and Yang, W.Y. (2009), “The impact of e.service quality, customer satisfaction
and loyalty on e–marketing: moderating effect of perceived value”, Total Quality Management
and Business Excellence, Vol. 20 No. 4, pp. 423-443.
Chaudhuri, A. and Holbrook, M.B. (2001), “The chain of effects from brand trust and brand
affect to brand performance: the role of brand loyalty”, Journal of Marketing, Vol. 65
No. 2, pp. 81-93.
Chen, A.C.H., Chen, S.K. and Ma, C.L. (2016), “Brand experience and customer equity prediction”,
Advances in Business and Management Forecasting, Emerald Group Publishing, pp. 19-38.
Christodoulides, G., Cadogan, J.W. and Veloutsou, C. (2015), “Consumer-based brand equity
measurement: lessons learned from an international study”, International Marketing Review,
Vol. 32 No. 3/4, pp. 307-328.
Cialdini, R.B., Vincent, J.E., Lewis, S.K., Catalan, J., Wheeler, D. and Darby, B.L. (1975), “Reciprocal
concessions procedure for inducing compliance: the door-in-the-face technique”, Journal of
Personality and Social Psychology, Vol. 31 No. 2, pp. 206-215.
Cropanzano, R. and Mitchell, M.S. (2005), “Social exchange theory: an interdisciplinary review”, Journal
of Management, Vol. 31 No. 6, pp. 874-900.
Crosby, L.A., Evans, K.R. and Cowles, D. (1990), “Relationship quality in services selling: an
interpersonal influence perspective”, Journal of Marketing, Vol. 54 No. 3, pp. 68-81.
EJM Dahl, D.W., Honea, H. and Manchanda, R.V. (2005), “Three Rs of interpersonal consumer guilt:
relationship, reciprocity, reparation”, Journal of Consumer Psychology, Vol. 15 No. 4,
54,9 pp. 307-315.
Dall’Olmo Riley, F. and De Chernatony, L. (2000), “The service brand as relationships builder”, British
Journal of Management, Vol. 11 No. 2, pp. 137-150.
Datta, H., Ailawadi, K.L. and Van Heerde, H.J. (2017), “How well does consumer-based brand equity
2278 align with sales-based brand equity and marketing-mix response?”, Journal of Marketing,
Vol. 81 No. 3, pp. 1-20.
del Rio Olivares, M.J., Wittkowski, K., Aspara, J., Falk, T. and Mattila, P. (2018), “Relational price
discounts: consumers’ metacognitions and nonlinear effects of initial discounts on customer
retention”, Journal of Marketing, Vol. 82 No. 1, pp. 115-131.
Dick, A.S. and Basu, K. (1994), “Customer loyalty: toward an integrated conceptual framework”, Journal
of the Academy of Marketing Science, Vol. 22 No. 2, pp. 99-113.
Dwivedi, A., Merrilees, B., Miller, D. and Herington, C. (2012), “Brand, value and relationship equities
and loyalty–intentions in the Australian supermarket industry”, Journal of Retailing and
Consumer Services, Vol. 19 No. 5, pp. 526-536.
Euromonitor International (2017), “Grocery retailers in Vietnam”, available at: www.euromonitor.com/
grocery–retailers–in–vietnam/report (accessed 24 December 2017).
Evanschitzky, H., Ramaseshan, B., Woisetschläger, D.M., Richelsen, V., Blut, M. and Backhaus, C.
(2012), “Consequences of customer loyalty to the loyalty program and to the company”, Journal
of the Academy of Marketing Science, Vol. 40 No. 5, pp. 625-638.
Falk, A. and Fischbacher, U. (2006), “A theory of reciprocity”, Games and Economic Behavior, Vol. 54
No. 2, pp. 293-315.
Fazal-e-Hasan, S.M., Ahmadi, H., Mortimer, G., Grimmer, M. and Kelly, L. (2018), “Examining the role of
consumer hope in explaining the impact of perceived brand value on customer–brand
relationship outcomes in an online retailing environment”, Journal of Retailing and Consumer
Services, Vol. 41, pp. 101-111.
Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservable
variables and measurement error”, Journal of Marketing Research, Vol. 18 No. 1,
pp. 39-51.
Fournier, S. (1998), “Consumers and their brands: developing relationship theory in consumer
research”, Journal of Consumer Research, Vol. 24 No. 4, pp. 343-373.
Gao, L., Melero-Polo, I. and Sese, F.J. (2020), “Customer equity drivers, customer experience quality, and
customer profitability in banking services: the moderating role of social influence”, Journal of
Service Research, Vol. 23 No. 2, pp. 174-193.
Gilovich, T., Kumar, A. and Jampol, L. (2015), “A wonderful life: experiential consumption and
the pursuit of happiness”, Journal of Consumer Psychology, Vol. 25 No. 1, pp. 152-165.
Groth, M., Hennig–Thurau, T. and Walsh, G. (2009), “Customer reactions to emotional labor: the roles of
employee acting strategies and customer detection accuracy”, Academy of Management Journal,
Vol. 52 No. 5, pp. 958-974.
Guha, A., Biswas, A., Grewal, D., Verma, S., Banerjee, S. and Nordfält, J. (2018), “Reframing the discount
as a comparison against the sale price: does it make the discount more attractive?”, Journal of
Marketing Research, Vol. 55 No. 3, pp. 339-351.
Gwinner, K.P., Gremler, D.D. and Bitner, M.J. (1998), “Relational benefits in services industries: the
customer’s perspective”, Journal of the Academy of Marketing Science, Vol. 26 No. 2, pp. 101-114.
Ha, H.Y., Janda, S. and Muthaly, S. (2010), “Development of brand equity: evaluation of four alternative
models”, The Service Industries Journal, Vol. 30 No. 6, pp. 911-928.
Hair, J.F., Black, W.C., Babin, B.J. and Anderson, R.E. (2010), Multivariate Data Analysis, Vectors.
Hair, J.F., Jr, Hult, G.T.M., Ringle, C. and Sarstedt, M. (2014), A Primer on Partial Least Squares Interplay of
Structural Equation Modeling (PLS–SEM), SAGE Publications.
customer
Hallberg, G. (1995), All Consumers Are Not Created Equal: The Differential Marketing Strategy for
Brand Loyalty and Profits, John Wiley and Sons.
equity drivers
Han, H., Nguyen, H.N., Song, H., Chua, B.L., Lee, S. and Kim, W. (2018), “Drivers of brand loyalty in the
chain coffee shop industry”, International Journal of Hospitality Management, Vol. 72, pp. 86-97.
Hariharan, V.G., Desai, K.K., Talukdar, D. and Inman, J.J. (2018), “Shopper marketing moderators of
the brand equity-behavioral loyalty relationship”, Journal of Business Research, Vol. 85,
2279
pp. 91-104.
Hauser, J.R. and Wernerfelt, B. (1990), “An evaluation cost model of consideration sets”, Journal of
Consumer Research, Vol. 16 No. 4, pp. 393-408.
Hayes, A.F. (2013), Introduction, an Introduction to Mediation, Moderation, and Conditional Process
Analysis: A Regression–Based Approach, Guilford Press, New York, NY.
Hayes, A.F., Montoya, A.K. and Rockwood, N.J. (2017), “The analysis of mechanisms and their
contingencies: process versus structural equation modeling”, Australasian Marketing Journal
(AMJ), Vol. 25 No. 1, pp. 76-81.
Hennig-Thurau, T., Gwinner, K.P. and Gremler, D.D. (2002), “Understanding relationship marketing
outcomes: an integration of relational benefits and relationship quality”, Journal of Service
Research, Vol. 4 No. 3, pp. 230-247.
Henseler, J., Ringle, C. and Sarstedt, M. (2014), “A new criterion for assessing discriminant validity in
varianced–based structural equation modelling”, Journal of the Academy of Marketing Science,
Vol. 43 No. 1, pp. 115-135.
Inman, J.J., Peter, A.C. and Raghubir, P. (1997), “Framing the deal: the role of restrictions in
accentuating deal value”, Journal of Consumer Research, Vol. 24 No. 1, pp. 68-79.
Jones, M.A., Mothersbaugh, D.L. and Beatty, S.E. (2000), “Switching barriers and repurchase intentions
in services”, Journal of Retailing, Vol. 76 No. 2, pp. 259-274.
Kahn, B.E. and Louie, T.A. (1990), “Effects of retraction of price promotions on brand choice behavior
for variety-seeking and last-purchase-loyal consumers”, Journal of Marketing Research, Vol. 27
No. 3, pp. 279-289.
Keller, K.L. (1993), “Conceptualizing, measuring, managing customer–based brand equity”, Journal of
Marketing, Vol. 57 No. 1, pp. 1-22.
Keller, K.L. (2001), “Building customer–based brand equity: a blueprint for creating strong brands”,
Marketing Management, Vol. 10 No. 2, pp. 15-19.
Kim, A.J. and Ko, E. (2012), “Do social media marketing activities enhance customer equity? An empirical
study of luxury fashion brand”, Journal of Business Research, Vol. 65 No. 10, pp. 1480-1486.
Kim, T. and Lee, H.Y. (2011), “External validity of market segmentation methods”, European Journal of
Marketing, Vol. 45 Nos 1/2, pp. 153-169.
Kline, R.B. (2011), Principles and Practice of Structural Equation Modeling, Guilford Press,
New York, NY.
Ku, H.H., Yang, P.H. and Chang, C.L. (2018), “Reminding customers to be loyal: does message framing
matter?”, European Journal of Marketing, Vol. 52 Nos 3/4, pp. 783-810.
Lee, M. and Cunningham, L.F. (2001), “A cost/benefit approach to understanding service loyalty”,
Journal of Services Marketing, Vol. 15 No. 2, pp. 113-130.
Lee, J.C., Hall, D.L. and Wood, W. (2018), “Experiential or material purchases? Social class determines
purchase happiness”, Psychological Science, Vol. 29 No. 7, pp. 1031-1039.
Leenheer, J., van Heerde, H.J., Bijmolt, T.H.A. and Smidts, A. (2007), “Do loyalty programs really
enhance behavioral loyalty? An empirical analysis accounting for self-selected members”,
International Journal of Research in Marketing, Vol. 24 No. 1, pp. 31-47.
EJM Lemon, K.N. and Verhoef, P.C. (2016), “Understanding customer experience throughout the customer
journey”, Journal of marketing, Vol. 80 No. 6, pp. 69-96.
54,9
Lemon, K., Rust, R. and Zeithaml, V. (2001), “What drives customer equity”, Marketing Management,
Vol. 10 No. 1, pp. 20-25.
Liang, H., Saraf, N., Hu, Q. and Xue, Y. (2007), “Assimilation of enterprise systems: the effect of
institutional pressures and the mediating role of top management”, MIS Quarterly, Vol. 31 No. 1,
pp. 59-87.
2280
Lindell, M.K. and Whitney, D.J. (2001), “Accounting for common method variance in cross-
sectional research designs”, Journal of Applied Psychology, Vol. 86 No. 1, pp. 114-121.
Liu-Thompkins, Y. and Tam, L. (2013), “Not all repeat customers are the same: designing effective
cross-selling promotion on the basis of attitudinal loyalty and habit”, Journal of Marketing,
Vol. 77 No. 5, pp. 21-36.
Malär, L., Krohmer, H., Hoyer, W.D. and Nyffenegger, B. (2011), “Emotional brand attachment and
brand personality: the relative importance of the actual and the ideal self”, Journal of Marketing,
Vol. 75 No. 4, pp. 35-52.
Malhotra, N.K., Kim, S.S. and Patil, A. (2006), “Common method variance in is research: a comparison of
alternative approaches and a reanalysis of past research”, Management Science, Vol. 52 No. 12,
pp. 1865-1883.
Mann, T.C. and Gilovich, T. (2016), “The asymmetric connection between money and material
vs. experiential purchases”, The Journal of Positive Psychology, Vol. 11 No. 6, pp. 647-658.
Menictas, C., Wang, P.Z. and Louviere, J.J. (2012), “Assessing the validity of brand equity constructs”,
Australasian Marketing Journal (Amj), Vol. 20 No. 1, pp. 3-8.
Meyer-Waarden, L. (2007), “The effects of loyalty programs on customer lifetime duration and share of
wallet”, Journal of Retailing, Vol. 83 No. 2, pp. 223-236.
Mishra, A. (2016), “Attribute-based design perceptions and consumer-brand relationship: role of user
expertise”, Journal of Business Research, Vol. 69 No. 12, pp. 5983-5992.
Montoya, R.M. and Insko, C.A. (2008), “Toward a more complete understanding of the reciprocity of
liking effect”, European Journal of Social Psychology, Vol. 38 No. 3, pp. 477-498.
Muniz, A.M. and O’Guinn, T.C. (2001), “Brand community”, Journal of Consumer Research, Vol. 27
No. 4, pp. 412-432.
Nicolao, L., Irwin, J.R. and Goodman, J.K. (2009), “Happiness for sale: do experiential purchases make
consumers happier than material purchases?”, Journal of Consumer Research, Vol. 36 No. 2,
pp. 188-198.
Nielsen (2013), “How loyal are your customers? A view of loyalty sentiment around the world”,
available at: http://oaaa.org/Portals/0/pdf/research/Nielsen–Global–Report–of–Loyalty–
Sentiment–November–2013.pdf (accessed 29 December 2017).
Nunnally, J. and Bernstein, I. (1994), Psychological Theory, McGraw–Hill, New York, NY.
Nyffenegger, B., Krohmer, H., Hoyer, W.D. and Malaer, L. (2015), “Service brand relationship quality:
hot or cold?”, Journal of Service Research, Vol. 18 No. 1, pp. 90-106.
Oliver, R. (1999), “Whence consumer loyalty?”, Journal of Marketing, Vol. 63 No. 4_suppl1, pp. 33-44.
Ou, Y.C. and Verhoef, P.C. (2017), “The impact of positive and negative emotions on loyalty intentions
and their interactions with customer equity drivers”, Journal of Business Research, Vol. 80,
pp. 106-115.
Ou, Y.C., de Vries, L., Wiesel, T. and Verhoef, P.C. (2014), “The role of consumer confidence in creating
customer loyalty”, Journal of Service Research, Vol. 17 No. 3, pp. 339-354.
Ou, Y.C., Verhoef, P.C. and Wiesel, T. (2017), “The effects of customer equity drivers on loyalty across
services industries and firms”, Journal of the Academy of Marketing Science, Vol. 45 No. 3,
pp. 336-356.
Palmatier, R.W., Jarvis, C.B., Bechkoff, J.R. and Kardes, F.R. (2009), “The role of customer gratitude in Interplay of
relationship marketing”, Journal of Marketing, Vol. 73 No. 5, pp. 1-18.
customer
Payne, A. and Holt, S. (1999), “A review of the ‘value’ literature and implications for relationship
marketing”, Australasian Marketing Journal (AMJ), Vol. 7 No. 1, pp. 41-51.
equity drivers
Peinkofer, S.T., Esper, T.L., Smith, R.J. and Williams, B.D. (2015), “Assessing the impact of price
promotions on consumer response to online stockouts”, Journal of Business Logistics, Vol. 36
No. 3, pp. 260-272.
Podsakoff, P.M. and Organ, D.W. (1986), “Self–reports in organizational research problems and
2281
prospects”, Journal of Management Information Management, Vol. 12 No. 4, pp. 531-544.
Podsakoff, P.M., Mackenzie, S.B., Lee, J. and Podsakoff, N.P. (2003), “Common method biases in
behavioral research: a critical review of the literature and recommended remedies”, Journal of
Applied Psychology, Vol. 88 No. 5, pp. 879-903.
Pomerantz, E.M., Chaiken, S. and Tordesillas, R.S. (1995), “Attitude strength and resistance processes”,
Journal of Personality and Social Psychology, Vol. 69 No. 3, pp. 408-419.
Preacher, K. and Hayes, A. (2008), “Assessing mediation in communication research”, The Sage
Sourcebook of Advanced Data, SAGE Publications.
Ringle, C. Wende, S. and Becker, J. (2015), “SmartPLS 3”: SmartPLS GmbH”, available at: www.
Smartpls.Com.
Russell-Bennett, R., Härtel, C.E. and Worthington, S. (2013), “Exploring a functional approach to attitudinal
brand loyalty”, Australasian Marketing Journal (AMJ), Vol. 21 No. 1, pp. 43-51.
Rust, R., Lemon, K. and Zeithaml, V. (2001), “Where should the next marketing dollar go?”, Marketing
Management, Vol. 10 No. 3, pp. 24-29.
Rust, R., Lemon, K. and Zeithaml, V. (2004), “Return on marketing: using customer equity to focus
marketing strategy”, Journal of Marketing, Vol. 68 No. 1, pp. 109-127.
Sarstedt, M., Hair, J.F., Jr, Cheah, J.H., Becker, J.M. and Ringle, C.M. (2019), “How to specify, estimate,
and validate higher-order constructs in PLS-SEM”, Australasian Marketing Journal (AMJ),
Vol. 27 No. 3, pp. 197-211.
Schmitt, B. (2013), “The consumer psychology of customer–brand relationships: extending the AA
relationship model”, Journal of Consumer Psychology, Vol. 23 No. 2, pp. 249-252.
Schmitt, B., Joško Brakus, J. and Zarantonello, L. (2015), “From experiential psychology to consumer
experience”, Journal of Consumer Psychology, Vol. 25 No. 1, pp. 166-171.
Sirgy, M.J. (1982), “Self-concept in consumer behavior: a critical review”, Journal of Consumer Research,
Vol. 9 No. 3, pp. 287-300.
Sloot, L.M., Verhoef, P.C. and Franses, P.H. (2005), “The impact of brand equity and the hedonic level of
products on consumer stock-out reactions”, Journal of Retailing, Vol. 81 No. 1, pp. 15-34.
Swaminathan, V., Page, K.L. and Gürhan-Canli, Z. (2007), “My’ brand or ‘our’ brand: the effects of brand
relationship dimensions and self-construal on brand evaluations”, Journal of Consumer
Research, Vol. 34 No. 2, pp. 248-259.
Swoboda, B., Berg, B. and Schramm-Klein, H. (2013), “Reciprocal effects of the corporate reputation and
store equity of retailers”, Journal of Retailing, Vol. 89 No. 4, pp. 447-459.
The Telegraph (2018), “Fabio the robot sacked from supermarket after alarming customers”,
available at: www.telegraph.co.uk/science/2018/01/21/fabio-robot-sacked-supermarket-
alarming-customers/ (accessed 20 January 2019).
Tsai, C.F. (2015), “The relationships among theatrical components, experiential value, relationship
quality, and relationship marketing outcomes”, Asia Pacific Journal of Tourism Research, Vol. 20
No. 8, pp. 897-919.
Van Boven, L. and Gilovich, T. (2003), “To do or to have? That is the question”, Journal of Personality
and Social Psychology, Vol. 85 No. 6, pp. 1193-1202.
EJM Veloutsou, C. (2015), “Brand evaluation, satisfaction and trust as predictors of brand loyalty: the
mediator-moderator effect of brand relationships”, Journal of Consumer Marketing, Vol. 32
54,9 No. 6, pp. 405-421.
Verhoef, P.C., Lemon, K.N., Parasuraman, A., Roggeveen, A., Tsiros, M. and Schlesinger, L.A. (2009),
“Customer experience creation: determinants, dynamics and management strategies”, Journal of
Retailing, Vol. 85 No. 1, pp. 31-41.
Vogel, V., Evanschitzky, H. and Ramaseshan, B. (2008), “Customer equity drivers and future sales”,
2282 Journal of Marketing, Vol. 72 No. 6, pp. 98-108.
Watson, G.F., Beck, J.T., Henderson, C.M. and Palmatier, R.W. (2015), “Building, measuring, and
profiting from customer loyalty”, Journal of the Academy of Marketing Science, Vol. 43 No. 6,
pp. 790-825.
Wedel, M. and Kamakura, W. (1998), Market Segmentation Conceptual and Methodological
Foundations, Kluwer Academic Publishers, Norwell, MA.
Weinswig, D. (2017), “Walmart slashes prices with pickup discount: welcome to the new world
of pick–and–mix pricing”, Forbes, available at: www.forbes.com/sites/deborahweinswig/
2017/05/26/walmart–slashes–prices–with–pickup–discount–welcome–to–the–new–world–
of–pick–and–mix–pricing/#4c2a96176a88 (accessed 24 December 2017).
Wollan, R. Davis, P. De Angelis, F. and Quiring, K. (2017), “Seeing beyond the loyalty illusion: it’s time
you invest more wisely”, available at: www.accenture.com/t20170216T035010Z__w__/us–en/
_acnmedia/PDF–43/Accenture–Strategy–GCPR–Customer–Loyalty.pdf (accessed 29 December
2017).
Wooldridge, J.M. (2009), Introductory Econometrics a Modern Approach, 4th ed., South–Western
Cengage Learning, Mason, OH.
Yoo, B. and Donthu, N. (2001), “Developing and validating a multidimensional consumer–based brand
equity scale”, Journal of Business Research, Vol. 52 No. 1, pp. 1-14.
Yoon, S. and Oh, J.C. (2016), “A cross-national validation of a new retail customer equity model”,
International Journal of Consumer Studies, Vol. 40 No. 6, pp. 652-664.
Zarantonello, L. and Schmitt, B.H. (2010), “Using the brand experience scale to profile consumers and
predict consumer behaviour”, Journal of Brand Management, Vol. 17 No. 7, pp. 532-540.
Zeithaml, V.A., Lemon, K.N. and Rust, R.T. (2001), Driving Customer Equity: How Customer Lifetime
Value is Reshaping Corporate Strategy, Simon and Schuster.
Zhang, S.S., Van Doorn, J. and Leeflang, P.S.H. (2014), “Does the importance of value, brand and
relationship equity for customer loyalty differ between Eastern and Western cultures?”,
International Business Review, Vol. 23 No. 1, pp. 284-292.

Further reading
Addis, M. and Holbrook, M.B. (2001), “On the conceptual link between mass customisation and
experiential consumption: an explosion of subjectivity”, Journal of Consumer Behaviour, Vol. 1
No. 1, pp. 50-66.
Alvarez, C. and Fournier, S. (2016), “Consumers’ relationships with brands”, Current Opinion in
Psychology, Vol. 10, pp. 129-135.
Ambler, T., Bhattacharya, C.B., Edell, J., Keller, K.L., Lemon, K.N. and Mittal, V. (2002), “Relating brand
and customer perspectives on marketing management”, Journal of Service Research, Vol. 5 No. 1,
pp. 13-25.
Bagozzi, R.P. (1995), “Reflections on relationship marketing in consumer markets”, Journal of the
Academy of Marketing Science, Vol. 23 No. 4, pp. 272-277.
Buil, I., De Chernatony, L. and Martinez, E. (2013), “Examining the role of advertising and sales
promotions in brand equity creation”, Journal of Business Research, Vol. 66 No. 1,
pp. 115-122.
Das, G., Mukherjee, A. and Smith, R.J. (2018), “The perfect fit: the moderating role of selling cues on Interplay of
hedonic and utilitarian product types”, Journal of Retailing, Vol. 94 No. 2, pp. 203-216.
customer
Ding, C.G. and Tseng, T.H. (2015), “On the relationships among brand experience, hedonic emotions,
and Brand equity”, European Journal of Marketing, Vol. 49 No. 7/8, pp. 994-1015. equity drivers
Farquhar, P.H. (1989), “Managing Brand equity”, Marketing Research, Vol. 1 No. 3, pp. 24-33.
Fornell, C., Johnson, M.D., Anderson, E.W. and Bryant, B.E. (1996), “The American customer
satisfaction index: nature, purpose, and findings”, Journal of Marketing, Vol. 60 No. 4, pp. 7-18.
2283
Fournier, S. and Alvarez, C. (2012), “Brands as relationship partners: warmth, competence, and in-
between”, Journal of Consumer Psychology, Vol. 22 No. 2, pp. 177-185.
Hanssens, D.M., Thorpe, D. and Finkbeiner, C. (2008), “Marketing when customer equity matters”,
Harvard Business Review, Vol. 86 No. 5, pp. 117-124.
Hirschman, E.C. and Holbrook, M.B. (1982), “Hedonic consumption: emerging concepts, methods and
propositions”, Journal of Marketing, Vol. 46 No. 3, pp. 92-101.
Holbrook, M.B. and Hirschman, E.C. (1982), “The experiential aspects of consumption: consumer
fantasies, feelings, and fun”, Journal of Consumer Research, Vol. 9 No. 2, pp. 132-140.
Homburg, C., Koschate, N. and Hoyer, W.D. (2006), “The role of cognition and affect in the formation
of customer satisfaction: a dynamic perspective”, Journal of Marketing, Vol. 70 No. 3,
pp. 21-31.
Johnson, M.D., Herrmann, A. and Huber, F. (2006), “The evolution of loyalty intentions”, Journal of
Marketing, Vol. 70 No. 2, pp. 122-132.
Kelley, H.H. and Thibaut, J.W. (1978), Interpersonal Relationships: A Theory of Interdependence, John
Wiley and Sons, New York, NY.
Khan, I. and Fatma, M. (2017), “Antecedents and outcomes of brand experience: an empirical study”,
Journal of Brand Management, Vol. 24 No. 5, pp. 439-452.
Khan, I. and Rahman, Z. (2015), “A review and future directions of brand experience research”,
International Strategic Management Review, Vol. 3 Nos 1/2, pp. 1-14.
Kumar, R.S., Dash, S. and Malhotra, N.K. (2018), “The impact of marketing activities on service brand
equity: the mediating role of evoked experience”, European Journal of Marketing, Vol. 52 Nos 3/
4, pp. 596-618.
Kumar, R., Dash, S. and Purwar, P. (2013), “The nature and antecedents of brand equity and its
dimensions”, Marketing Intelligence and Planning, Vol. 31 No. 2, pp. 141-159.
Larson, A. (1992), “Network dyads in entrepreneurial settings: a study of the governance of exchange
relationships”, Administrative Science Quarterly, Vol. 37 No. 1, pp. 76-104.
McGrath, M. (2017), “Cheap drinks and fancier sandwiches boost McDonald’s sales above expectations”,
Forbes, available at: www.forbes.com/sites/maggiemcgrath/2017/07/25/cheap–drinks–and–fancier–
sandwiches–boost–mcdonalds–sales–above–expectations/#3235814f3894 (accessed 24 December
2017).
McKinsey and Company (2009), “McKinsey Global Survey Results: Measuring Marketing”, McKinsey
and Company.
Mittal, V. and Kamakura, W.A. (2001), “Satisfaction, repurchase intent, and repurchase behavior:
investigating the moderating effect of customer characteristics”, Journal of Marketing Research,
Vol. 38 No. 1, pp. 131-142.
Morgan–Thomas, A. and Veloutsou, C. (2013), “Beyond technology acceptance: brand relationships and
online brand experience”, Journal of Business Research, Vol. 66 No. 1, pp. 21-27.
Oliver, R. (1997), Satisfaction: A Behavioral Perspective on the Consumer, McGraw Hill, New York, NY.
Park, C.W., MacInnis, D.J., Priester, J., Eisingerich, A.B. and Iacobucci, D. (2010), “Brand attachment
and brand attitude strength: conceptual and empirical differentiation of two critical brand equity
drivers”, Journal of Marketing, Vol. 74 No. 6, pp. 1-17.
EJM Richardson, P.S., Dick, A.S. and Jain, A.K. (1994), “Extrinsic and intrinsic cue effects on perceptions of
store brand quality”, Journal of Marketing, Vol. 58 No. 4, pp. 28-36.
54,9
Roos, I., Edvardsson, B. and Gustafsson, A. (2004), “Customer switching patterns in competitive
and noncompetitive service industries”, Journal of Service Research, Vol. 6 No. 3,
pp. 256-271.
Roswinanto, W. and Strutton, D. (2014), “Investigating the advertising antecedents to and
consequences of brand experience”, Journal of Promotion Management, Vol. 20 No. 5,
2284 pp. 607-627.
Schmitt, B.H. (1999), Experiential Marketing: How to Get Customers to Sense, Feel, Think, Act, Relate,
Simon and Schuster.
Schmitt, B. and Zarantonello, L. (2013), “Consumer experience and experiential marketing: a
critical review”, Review of Marketing Research, Emerald Publishing Limited, Vol. 10,
pp. 25-61.
Shamim, A. and Butt, M.M. (2013), “A critical model of brand experience consequences”, Asia Pacific
Journal of Marketing and Logistics, Vol. 25 No. 1, pp. 102-117.
Tasci, A.D. (2016), “A critical review of consumer value and its complex relationships in the consumer-
based brand equity network”, Journal of Destination Marketing and Management, Vol. 5 No. 3,
pp. 171-191.
Taylor, S.A., Hunter, G.L. and Lindberg, D.L. (2007), “Understanding (customer-based) brand equity in
financial services”, Journal of Services Marketing, Vol. 21 No. 4, pp. 241-252.
Teas, R.K. and Agarwal, S. (2000), “The effects of extrinsic product cues on consumers’ perceptions of
quality, sacrifice, and value”, Journal of the Academy of Marketing Science, Vol. 28 No. 2,
pp. 278-290.
Valette-Florence, P., Guizani, H. and Merunka, D. (2011), “The impact of brand personality and
sales promotions on brand equity”, Journal of Business Research, Vol. 64 No. 1, pp. 24-28.
van Herpen, E., Pieters, R. and Zeelenberg, M. (2009), “When demand accelerates demand: trailing the
bandwagon”, Journal of Consumer Psychology, Vol. 19 No. 3, pp. 302-312.
Varki, S. and Colgate, M. (2001), “The role of price perceptions in an integrated model of behavioral
intentions”, Journal of Service Research, Vol. 3 No. 3, pp. 232-240.
Verhoef, P.C. (2003), “Understanding the effect of customer relationship management efforts on
customer retention and customer share development”, Journal of Marketing, Vol. 67 No. 4,
pp. 30-45.
Wang, Y., Po Lo, H., Chi, R. and Yang, Y. (2004), “An integrated framework for customer value
and customer-relationship-management performance: a customer-based perspective from
China”, Managing Service Quality: An International Journal, Vol. 14 Nos 2/3, pp. 169-182.
Wu, L. and Lee, C. (2016), “Limited edition for me and best seller for you: the impact of scarcity versus
popularity cues on self-versus other-purchase behavior”, Journal of Retailing, Vol. 92 No. 4,
pp. 486-499.
Zarantonello, L. and Schmitt, B.H. (2013), “The impact of event marketing on brand equity: the
mediating roles of brand experience and brand attitude”, International Journal of Advertising,
Vol. 32 No. 2, pp. 255-280.
Appendix Interplay of
customer
equity drivers
Dimensions Items Scale

sensory This brand makes a strong impression on my visual sense or 1 = Totally disagree
other senses 7 = Totally agree 2285
I find this brand interesting in a sensory way
This brand appeals to my senses
Affective This brand induces feelings and sentiments 1 = Totally disagree Table A1.
I have strong emotions for this brand 7 = Totally agree Brand experience
This brand is an emotional brand scale (Brakus et al.,
Intellectual I engage in a lot of thinking when I encounter this brand 1 = Totally disagree
2009) and different
This brand makes me think 7 = Totally agree
This brand stimulates my curiosity and problem solving experiential types of
Behavioral I engage in physical actions and behaviors when I use this brand 1 = Totally disagree consumers
This brand results in bodily experiences 7 = Totally agree (Zarantonello and
This brand is not action oriented Schmitt (2010)

 Sensory brand experience refers to the aesthetics and sensorial impressions that a brand
induces; affective brand experience reflects feelings, sentiments and emotions generated
by the brand; behavioral brand experience involves physical, bodily actions and
interactions with the brand; and intellectual brand experience is encouraged by the
ability of a brand to stimulate the consumers’ curiosity, thinking and problem-solving
(Brakus et al., 2009).
 Building on the four dimensions of brand experience proposed by Brakus et al. (2009)
and Zarantonello and Schmitt (2010) have identified five clusters of consumers that
prefer different experiential types: holistic consumers, hedonistic consumer, action-
oriented consumers, inner-directed consumers and utilitarian consumers. On one
extreme, holistic consumers are high-experiential shoppers that tend to attach
remarkable importance to all four dimensions of brand experiences. On the other
extreme, utilitarian consumers seem to be opposite (e.g. they are low-experiential
consumers that prefer a more rational, functional approach toward a brand). In between,
three different experiential types of consumers exist: hedonistic consumers who are
strongly affected by the sensorial gratification and emotional appeals, action-oriented
consumers driven by sentiments and behaviors and inner-directed consumers evoked by
brands with strong activation on the internal processes (i.e. sensations, emotions and
cognitions).

About the authors

Pham Hung Cuong is a Lecturer of Business Administration at Foreign Trade University, Ho Chi Minh
City (FTU – HCMC). He currently serves as Manager of the Department of International Affairs and
Scientific Management at Foreign Trade University, Ho Chi Minh City Campus. He has published in
Journal of Services Marketing, among others.
Oanh Dinh Yen Nguyen is currently PhD candidate in Marketing at University of New South
Wales, Australia. She received MSc in International Business at University College Dublin Smurfit
School of Business, University College Dublin, Ireland. Besides, Oanh is also Lecturer of the College
of Economics, Can Tho University, Vietnam. Her research interests include consumer behavior and
digital marketing.
EJM Liem Viet Ngo is Associate Professor of Marketing at School of Marketing, UNSW Sydney. He has
published in International Journal of Research in Marketing, Journal of Product Innovation
54,9 Management, Long Range Planning, British Journal of Management, Industrial Marketing
Management, European Journal of Marketing, Psychology and Marketing, Journal of Business
Research, among others. Liem Viet Ngo is the corresponding author and can be contacted at: liem.
ngo@unsw.edu.au
Nguyen Phong Nguyen is Lecturer at the School of Accounting, University of Economics Ho Chi
2286 Minh City, Vietnam. His studies have been published in Industrial Marketing Management, Journal of
Product and Public Management, Australasian Marketing Journal, Review, among others.

For instructions on how to order reprints of this article, please visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
Or contact us for further details: permissions@emeraldinsight.com