The Service Industries Journal

ISSN: 0264-2069 (Print) 1743-9507 (Online) Journal homepage: http://www.tandfonline.com/loi/fsij20

Impact of customer experience on loyalty: a

multichannel examination

Isabelle Brun, Lova Rajaobelina, Line Ricard & Bilitis Berthiaume

To cite this article: Isabelle Brun, Lova Rajaobelina, Line Ricard & Bilitis Berthiaume (2017):
Impact of customer experience on loyalty: a multichannel examination, The Service Industries
Journal, DOI: 10.1080/02642069.2017.1322959

To link to this article: http://dx.doi.org/10.1080/02642069.2017.1322959

Published online: 09 May 2017.

Submit your article to this journal

View related articles

View Crossmark data

Full Terms & Conditions of access and use can be found at

http://www.tandfonline.com/action/journalInformation?journalCode=fsij20

Download by: [The UC San Diego Library] Date: 11 May 2017, At: 01:08
THE SERVICE INDUSTRIES JOURNAL, 2017
https://doi.org/10.1080/02642069.2017.1322959

Impact of customer experience on loyalty: a multichannel

examination
Isabelle Bruna, Lova Rajaobelina b
, Line Ricard b
and Bilitis Berthiaumeb
a
Faculty of Business Administration, University of Moncton, Moncton, Canada; bSchool of Business and
Management, ESG – University of Quebec in Montreal, Montreal, Canada

ABSTRACT ARTICLE HISTORY

This article examines the relation between the five dimensions of Received 12 July 2016
customer experience advocated by Schmitt [1999a. Experiential Accepted 21 April 2017
Marketing. Journal of Marketing Management, 15, 53–67]
KEYWORDS
(cognitive, affective, sensory, behavioural and social) and service Marketing; loyalty; service
provider loyalty. The examination focuses on two different industry; multichannel;
channels, namely branch/agency (physical) and online (Web- customer experience
based). A total of 484 panellists of a large Canadian polling firm
self-administered a Web-based questionnaire regarding banking
experience. The exercise was subsequently replicated in the
tourism sector. Findings demonstrate that the main dimension
impacting loyalty is the affective dimension (negative), thereby
contributing handsomely to experiential marketing literature since
negative emotions are rarely investigated. Findings also reveal
that choice of channel exerts a moderating effect on the different
dimensions influencing loyalty and that results vary from one
sector to another. The multidimensional, multichannel, multisector
approach selected for this study substantiates customer
experience as complex and context specific. The authors also
suggest practical implications and set out avenues of future
research.

Introduction
For years now, large numbers of service providers have endeavoured to develop consumer
loyalty for a variety of reasons such as to trim costs, enhance word of mouth and increase
revenue per purchase (Cielle, 2014; Reichheld, 1996). Marketing researchers have also
manifested an interest in loyalty (e.g. Guest, 1964; Jacoby & Kyner, 1973; Oliver, 1999),
electing to focus mainly on the impact of antecedents such as satisfaction, perceived
quality, reputation (Pan, Sheng, & Xie, 2012) and website characteristics (Hsu, Wang, &
Chih, 2013). Despite these ongoing efforts by academics and practitioners, loyalty
remains an enduring challenge.
At a point in time when it is increasingly difficult for companies to distinguish them-
selves by service alone, some believe that the route to differentiation lies in customer
experience. Indeed, since the introduction of an experiential view of consumption (Hol-
brook & Hirschman, 1982), the traditional economic theory whereby consumers are

CONTACT Isabelle Brun Isabelle.brun@umoncton.ca

© 2017 Informa UK Limited, trading as Taylor & Francis Group
2 I. BRUN ET AL.

deemed logical thinkers has been revisited. Today, the emotional aspect of customer
experience is now considered of equal importance (Gentile, Spiller, & Noci, 2007). Some
academics (e.g. Hosany & Witham, 2010; Mathwick, Malhotra, & Rigdon, 2001; Pine II &
Gilmore, 1998) even point to the emergence of an experiential economy. For these
authors, the focus in marketing has shifted, first from product to service and then from
service to customer experience (Chang & Horng, 2010; Maklan & Klaus, 2011). One of
the chief buzzwords in marketing today, customer experience will doubtless prove a
major priority in research going forward (Lemon & Verhoef, 2016). Schmitt (1999a) proffers
a widely accepted conceptualization of the notion and considers five dimensions as repre-
sentative of customer experience: cognitive (think), affective (feel), social or relational
(relate), behavioural (act) and sensory (sense). These dimensions come replete with their
own particularities and are distinguishable by their holistic conceptualization of customer
experience.
In light of ever-increasing competition and the ever-broadening scope of purchasing
possibilities, could it be that service companies would be better advised to focus on the
creation of positive customer experiences to more properly differentiate themselves
from rivals and enhance customer loyalty? If so, appreciating that customer experience
is a multidimensional concept, would it not follow that some dimensions are more impor-
tant than others and should be prioritized in an effort to foster customer loyalty? Hence,
the relevance of examining in detail the impact of each of these dimensions to bring differ-
ences to the fore and better grasp the factors that truly impact customer loyalty and help
develop more targeted strategies. Although several authors have examined existing links
between customer experience and loyalty (e.g. Brakus, Schmitt, & Zarantonello, 2009; Sri-
vastava & Kaul, 2016), a more comprehensive treatment of customer experience and more
in-depth analyses of the specific impact of each different dimension are lacking in aca-
demic literature. An investigation of this nature would address a knowledge gap relating
to customer experience as a means of building a loyal customer base (Srivastava & Kaul,
2016).
From another standpoint, Maklan and Klaus (2011, p. 785) postulate as follows: ‘It is
likely that practising researchers will need to model customer experience for their
unique context; current generic conceptualizations of experience may be too broad to
be actionable and relevant in any one context.’ Indeed, key variables could differ based
on the context (Lemke, Clark, & Wilson, 2011; Voss, Roth, & Chase, 2008), just as recent
technologies spawn new kinds of experiences (Pine II & Gilmore, 1998). Nowadays, mul-
tiple touch points in a diversity of channels and media enable customers to interact
with firms, rendering customer experience increasingly more complex and varied
(Lemon & Verhoef, 2016). Consider the example of a Web-based environment (versus a
physical setting) where consumers are exposed to different factors such as website inter-
face, broader availability of information, round-the-clock accessibility from any location
and absence of physical human presence. Differences such as these encountered in a
virtual environment can stir emotions and elicit cognitive responses which, in turn, can
cause individuals to adopt various behaviours. Hence the need for new studies to
better comprehend customer experience in a multichannel environment (Klaus &
Nguyen, 2013; Lemon & Verhoef, 2016). More precisely, it is relevant to investigate
whether or not the impact of the dimensions of customer experience on customer
loyalty differs based on the channel used (e.g. physical branch/agency versus Web-
 THE SERVICE INDUSTRIES JOURNAL 3

based environment). If so, then service providers will be poised to tailor their strategies to
the channel or channels of choice.
Today’s well-informed consumers are demanding, use multiple channels and seek out
rewarding, emotion-rich experiences. It is therefore important to better seize the notion of
customer experience in all its magnitude and complexity, and investigate how it can be
used to develop a loyal customer base. Accordingly, this article seeks to answer the follow-
ing research questions:

. What is the impact of customer experience on customer loyalty? Which dimensions of cus-
tomer experience contribute most to customer loyalty?
. What is the nature of the moderating effect of the channel used (physical versus Web-
based) on the impact of the dimensions of customer experience on loyalty?

To answer these research questions, this study advocates a multidimensional, multichannel

and multisector examination to better understand the subtleties of the different experien-
tial contexts, identify the key dimensions of customer experience and develop better
adapted strategies.
In the upcoming section, we provide an overview of literature on customer experience
and the links between this concept and loyalty. Subsequently, we develop our research
hypotheses and detail both the methodology employed and results obtained. In the dis-
cussion section, we substantiate the practical implications, limits and conclusions of the
research conducted.

Theoretical background
In this section, we define customer experience and expose the links between the concept
and loyalty. We then examine the dimensions of customer experience with a view to for-
mulating our research hypotheses.

Customer experience
In 1982, Holbrook and Hirschman demonstrated that consumer behaviour was not solely
rational. Rather, the senses, imagination, feelings and even consumer involvement enter
into the decision making equation. Customers are drawn not only to products but also
to product sense and meaning (Carù & Cova, 2006). Since Holbrook and Hirschman’s
(1982) paper, a number of researchers have manifested an interest in experiential market-
ing. They have attempted to better grasp the concept of customer experience, the dimen-
sions of the latter, their impact on behaviour and their potential for aiding in the
development of successful marketing strategies.
More specifically, customer experience has been defined as a multidimensional, holistic
evaluation (e.g. Gentile et al., 2007; Hosany & Witham, 2010; Schmitt, 1999b) involving a cus-
tomer’s cognitive, affective, emotional, social and physical responses to a company (Verhoef
et al., 2009) throughout the entirety of a purchase journey (Lemon & Verhoef, 2016). This
experience represents the customer’s personal, internal and subjective response, a
response shaped by all points of contact and interaction direct or indirect (Meyer & Schwa-
ger, 2007) with a product, company or part of an organization (Gentile et al., 2007):
4 I. BRUN ET AL.

This experience is created not only by those elements which the retailer can control (e.g.,
service interface, retail atmosphere, assortment, price), but also by elements that are
outside of the retailer’s control (e.g. influence of others, purpose of shopping). … the customer
experience encompasses the total experience, including the search, purchase, consumption
and after-sale phases of the experience, and may involve multiple retail channels (Verhoef
et al., 2009, p. 32).

Since customer experience manifests at various levels for consumers, different dimensions
must be examined to substantiate the breadth of the concept. As the dimensions ident-
ified by Schmitt (1999a) – cognitive, affective, behavioural, sensory and social – offer a
broad, holistic and comprehensive vision of customer experience, they have been privi-
leged as the basis for research in the field (e.g. Brakus et al., 2009; Gentile et al., 2007;
Tsaur, Chiu, & Wang, 2006; Verhoef et al., 2009) and have become widely accepted
(Lemon & Verhoef, 2016). These dimensions are discussed in greater detail in the following
sections.
The trend to an experiential approach in marketing coincides with one of the weightiest
challenges ever to impact the manner in which companies and consumers interact,
namely the advent of the Internet (Maklan & Klaus, 2011). Novak, Hoffman, and Yung
(2000) figure among the first to examine online customer experience based on a generally
cognitive approach through the notion of flow, a state of total immersion in which the indi-
vidual in an electronic environment is completely absorbed by the task at hand. An affec-
tive approach has since been added (Rose, Clark, Samouel, & Hair, 2012), characterized by
the presence of emotions during the online experience. Ensuring quality online customer
experience can indeed be key to commercial success in a fiercely competitive environ-
ment where customer retention is crucial. It is therefore interesting to identify which of
the dimensions advocated by Schmitt (1999a) (cognitive, affective, social, behavioural
and sensory) are deemed to be of the greatest importance in an online environment,
the object being to create memorable, positive experiences with customers increasingly
open unto the world.
Lastly, despite services being highly experiential by nature, research into customer
experience in this particular industry is scant or lacking according to Khan and Rahman
(2015) who examined 73 studies on brand experience. Customer experience is, however,
extremely important in the service industry by reason of the inherent intangibility of ser-
vices and co-creation among players (Jaakkola, Helkkula, & Aarikka-Stenroos, 2015). ‘Con-
ventional wisdom holds that the customer contact model of service implies that any
contact or “moment of truth” is a customer experience’ (Voss et al., 2008, p. 248). For
some, customer experience lies at the heart of the service offer (Shobeiri, Mazaheri, &
Laroche, 2014; Zomerdijk & Voss, 2010), further supporting a need for investigating this
important topic in service literature.

Links between customer experience and loyalty

Constituting a pool of loyal customers represents a leading goal for many service compa-
nies. Loyalty is often associated with a favourable attitude and repetitive behaviour,
thereby evidencing the conceptualization advocated by Jacoby and Kyner (1973)
(1) the biased (i.e. non-random) (2) behavioural response (i.e. purchase) (3) expressed over
time (4) by some decision making unit (5) with respect to one or more alternative brands
 THE SERVICE INDUSTRIES JOURNAL 5

out of a set of such brands (6) is a function of psychological (decision making, evaluative) pro-
cesses. (p. 2)

The study of the impact of customer experience on the latter is therefore consequential.
Lemon and Verhoef (2016) indeed identify the consequences of customer experience as
one of the critical areas for research in this field and call for further investigation respecting
loyalty.
An examination of previous literature has identified authors having investigated the
links between customer experience and loyalty (research summarized in Table 1). From
this table, it is plain to see that few researchers have broached Web-based environments,
none has touched upon both channels and most tend to base their research on the
hedonic (e.g. tourism). The studies appearing in the table nonetheless provide a theoreti-
cal framework for the research at hand.
Basing ourselves on Table 1, we can confirm that the dimensions advocated by Schmitt
(1999a) (sensory, affective, cognitive, behavioural and social) occur more frequently in
experiential marketing research (e.g. Brakus et al., 2009; Iglesias, Singh, & Batista-Foguet,
2011; Sahin, Zehir, & Kitapçı, 2011; Tsaur et al., 2006), with few researchers having exam-
ined other dimensions of customer experience (e.g. dimensions of entertainment, edu-
cation, aesthetics and escape pointed up by Pine II & Gilmore, 2011). This having been
said, Brakus et al. (2009) eliminate the social dimension from Schmitt’s conceptualization,
as do Iglesias et al. (2011) and Sahin et al. (2011) who stray from the scale developed by
Brakus given correlation to the affective dimension (loading on the same factor). They con-
clude that ‘the socially worded items include strong emotional aspects’ (Brakus et al., 2009,
p. 58). For the purpose of this study, the social dimension will be considered since multi-
channel differences could come to light, especially given that a physical branch/agency
has a more tangible social component than the Web-based alternative. Customer experi-
ences are more social than ever before (Lemon & Verhoef, 2016). Hence, the social dimen-
sion cannot be ignored. Lastly, the table evidences that no previous study has examined
the direct and distinct impact of the different dimensions of customer experience advo-
cated by Schmitt (1999a) on loyalty. Some investigate an indirect relation (e.g. Tsaur
et al. 2006) and view the link to loyalty as emotion-based or focus on the integrative
impact of the various dimensions (e.g. Brakus et al., 2009; Sahin et al., 2011), thereby ren-
dering the contributions made by this research all the more important.
In the next section, we explain the different dimensions of customer experience,
present hypotheses relating to loyalty and expose the conceptual framework used.

Impact of the dimensions of customer experience on customer loyalty

As mentioned, those researchers having examined customer experience based on the
dimensions advocated by Schmitt (1999a) view it above all as an integrative concept
(e.g. Brakus et al., 2009; Iglesias et al., 2011; Sahin et al., 2011). They indeed test ‘global’
or ‘integrated’ customer experience to ascertain the impact on loyalty. Since the dimen-
sions are deemed to be separate and have their own individual idiosyncrasies, we
believe it relevant to investigate the direct impact of each separately. Accordingly, this
study nuances the importance of each of the dimensions and sheds light on the facets
of customer experience that service companies would be well advised to prioritize to
enhance customer loyalty.
Table 1. Studies on customer experience (CE) and loyalty.

6
Sector/
Authors context Objective Dimensions of experience Methodology Findings (impact on loyalty)
Terblanche and Retail Develop an instrument to measure Value of goods, store Questionnaire Only one dimension of experience found not to

I. BRUN ET AL.
Boshoff (2006) business consumer satisfaction based on shopping environment, social administered by e-mail, impact loyalty (environment). The five others
experience interaction, assortment of 3153 customers indirectly impact loyalty through satisfaction
goods, complaints
management (Terblanche &
Boshoff, 2006 )
Tsaur et al. (2006) Tourism Examine the effects of CE on consumer Sensory, affective, cognitive, Self-administered The five dimensions of experience positively impact
behaviour physical/behavioural, social questionnaire, 405 emotions which subsequently impact satisfaction
(Schmitt, 1999a) visitors and loyalty
Brakus et al. (2009) Brand Determine whether CE can predict Sensory, affective, intellectual, Final face-to-face survey, Experience (integrated) directly impacts loyalty and
consumer behaviour behavioural (adapted from 209 students indirectly through brand personality
Schmitt, 1999a)
Slåtten, Tourism Describe and explain the relations between Social interaction, design, Self-administered Social interaction and design directly impact loyalty
Mehmetoglu, atmosphere, joy and loyalty ambience questionnaire, 162 through a sense of joy
Svensson, and visitors
Sværi, (2009)
Iglesias et al. (2011) Brand Study the relation between CE and brand Sensory, affective, intellectual, Online and paper Experience (integrated) does not directly impact
loyalty behavioural (Brakus et al., questionnaire, 195 loyalty but does so indirectly through affective
2009) students commitment
Luo et al. (2011) Web Study the relation between virtual Senses, interaction, pleasure, Online questionnaire, 976 Experience indirectly impacts loyalty through site
experiential marketing, site browsing flow, relations with buyers browsing and purchasing intentions
intentions, purchasing and loyalty community (e.g. Mathwick
et al., 2001; Pine II & Gilmore,
1998; Schmitt, 1999a)
Sahin et al. (2011) Brand Identify the relations between CE, Sensory, affective, intellectual, Self-administered Experience (integrated) directly impacts loyalty and
satisfaction, trust and loyalty behavioural (Brakus et al., questionnaire, 258 indirectly through trust and satisfaction
2009) consumers
Zhou and Lu (2011) Mobile Identify mobile experience factors Network: size and perceived Questionnaire All dimensions of experience indirectly impact loyalty
messaging impacting loyalty complementarity (Lin & administered: 223 mobile through perceived usefulness
Bhattacherjee, 2008)/Flow: Internet users
perceived amusement and
concentration (Koufaris, 2002)
Mhaya, Najjar, and Web Study the relational consequences of Emotional reactions, social Online questionnaire, 226 No dimension of experience directly impacts loyalty.
Jannet (2013) browsing experience on a non- interaction respondents Dimensions indirectly impact loyalty through
transactional website satisfaction
Ali, Hussain, and Tourism Examine the impact of CE on memory and Education, entertainment, Self-administered Each dimension of experience positively impacts
Ragavan (2014) loyalty aesthetics, escape (Pine II & questionnaire, 450 loyalty (intention)
Gilmore, 2011) respondents
Srivastava and Kaul Retail Study the impact of CE on attitudinal Feel, relate, sense, think (Brakus Self-administered Experience (integrated) directly impacts attitudinal
(2016) and behavioral loyalty et al., 2009) questionnaire, 840 retail and behavioral loyalty which in turn leads to greater
customers share of wallet
 THE SERVICE INDUSTRIES JOURNAL 7

In this segment, we present the five dimensions of customer experience and identify
the potential impact of each on customer loyalty. Given the scarcity of work having exam-
ined the impact of each dimension on loyalty, for some hypotheses we present additional
academic findings regarding derived consumer behaviour (e.g. word of mouth, purchase
intentions, etc.).
The cognitive dimension concerns the consumer’s cognitive processes. It seeks to lead
consumers to think and engage their creativity by surprising, intriguing and provoking
them (Fornerino, Helme-guizon, & De Gaudemaris, 2005; Schmitt, 1999b). In other
words, the experience must be enriching, enhance teaching and discovery, and hone con-
sumer skills (Holbrook, 2000; Pine II & Gilmore, 2011). In some cases, the cognitive experi-
ence can even empower customers to resolve certain issues (Gentile et al., 2007). Lastly,
the cognitive experience provides a means of engaging consumers and developing
loyalty to a company (Schmitt, 1999b).
Donovan, Rossiter, Marcoolyn, and Nesdale (1994) demonstrate that awareness
achieved by dint of the cognitive experience impacts the time spent in a store and pur-
chases made. Moreover, a study by Swinyard (1993) reveals that when consumers are
directly involved, they are more attentive to product quality and available information,
two factors which influence purchase intentions. In a Web-based environment, flow
impacts both consumer engagement and loyalty (Fuglsang & Sundbo, 2006). Hence, we
hypothesize as follows:
H1: The cognitive dimension of customer experience positively impacts loyalty.

‘The distinctive characteristics of services suggest that it is particularly apt that consumer
emotional responses are now also being considered’ (Mudie, Cottam, & Raeside, 2003,
p. 85). In eliciting consumer emotions, the affective dimension spawns a mental state
accompanied by physical and physiological processes which can lead to concrete action
(Bagozzi, Gopinath, & Nyer, 1999). For example, interest, joy, surprise, sadness, anger
and disgust are all emotions which can be felt by consumers. The first three rank as posi-
tive, while the latter three qualify as negative. Researchers such as Schmitt (1999a), Brakus
et al. (2009) and Tsaur et al. (2006) do not generally include negative emotions in their
studies. The affective dimension is nonetheless enriched by taking into account both posi-
tive and negative emotions (Fornerino, Helme-Guizon, & Gotteland, 2006). Accordingly, we
include and make allowance for each in this study.
Eliciting positive emotions from consumers is a good means of enhancing word of
mouth, enticing consumers to pay more and boosting repeat business (Barsky & Nash,
2002; Yu & Dean, 2001). Others have demonstrated the inverse impact of negative
emotions on consumer behaviour, including decreased consumer loyalty (Roos, Friman,
& Edvardsson, 2009). Chebat and Slusarczyk (2005) find that positive and negative
emotions both impact consumer loyalty in the banking sector (bank branch environment),
especially in instances of service recovery. We therefore hypothesize as follows:
H2: The affective (+) dimension of customer experience positively impacts loyalty.

H3: The affective (−) dimension of customer experience negatively impacts loyalty.

The sensory dimension relates to the perception of experience through the senses. Each of
the five senses, namely sight, hearing, touch, taste and smell, can be solicited (Fornerino
8 I. BRUN ET AL.

et al., 2005; Schmitt, 1999b). The experience can transform an environment (e.g. physical
branch/agency) and render it more pleasurable for the consumer (Filser, 2002; Parasura-
man, Zeithaml, & Berry, 1988; Pine II & Gilmore, 2011). Lastly, the sensory aspect can be
experienced through different points of contact such as advertisements, the Web and
points of sale (Filser, 2003).
According to Babin and Attaway (2000), environment and atmosphere can enhance
consumer retention by developing a lasting consumption relation with the customer.
From a sports marketing perspective and in trying to understand how consumers experi-
ence the stadium through their senses, Lee, Heere, and Chung (2013) found that sight,
touch and smell positively affected the team loyalty. We therefore hypothesize as follows:
H4: The sensory dimension of customer experience positively impacts loyalty.

The behavioural dimension supposes that customer experience affects consumers phys-
ically by modifying action taken, habits and lifestyles (Carù & Cova, 2006; Fornerino
et al., 2005; Schmitt, 1999b). This dimension, more than any of the others, begets confusion
in existing literature, if only because it is not consistently defined or measured in the same
manner by the different authors. For example, in topical literature, there are authors who
refer to the amount of money disbursed (Bakini Driss, Jerbi, & Ben Lallouna Hafsia, 2009),
time spent in the store or time devoted to unplanned purchases (Donovan et al., 1994).
According to us, these forms of action could be confused with loyalty-associated behav-
iour or the consequences of customer experience (e.g. time allotted or dollar amount
spent) and not the experiential act itself. Furthermore, ‘behavior analysis should move
beyond choice processes that lead to purchase decisions and include experiences that
customers have as a result of using a product or service’ (Payne, Storbacka, & Frow,
2008, p. 87); for example, engaging in physical actions and behaviours when using a
brand (Brakus et al., 2009). Therefore, we are of the opinion that the behavioural dimen-
sion of customer experience must seek to point up behaviour linked to the act of con-
sumption (e.g. take part in the co-creation of a product or service, share in its discovery,
etc.). Such is the perspective retained for the purpose of this study.
While literature regarding the distinct impact of the behavioural dimension of customer
experience is rare, research conducted by Reniou (2009) demonstrates that customer par-
ticipation in proposed activities generates word of mouth with consumers. Hence, the fol-
lowing assumption:
H5: The behavioural dimension of customer experience positively impacts loyalty.

Customer experiences today are more social than ever before given the myriad channels,
media and touch points that customers enjoy with companies and diversity of interaction
involved (Lemon & Verhoef, 2016). The social dimension can be defined as ‘interaction or
communion with other individuals’ (Fornerino et al., 2006, p. 10). An experience, albeit
individual by nature, forms part of a social context where individuals interrelate with
one another (e.g. employees and other consumers) (Yi & Gong, 2009). Accordingly, the
social dimension broached in this research focuses on consumer interaction (Helme-
Guizon, 2001), the sense of belonging (Nasermoadeli, Ling, & Maghnati, 2013), socialization
and sustainment or perpetuation of links between companies and consumers (Nambisan,
2005), and identification.
 THE SERVICE INDUSTRIES JOURNAL 9

Both customer-to-customer and customer-to-employee relationships contribute to the

development of customer loyalty (Genzi & Pelloni, 2004). Regarding the presence of other
consumers, Pareigis, Edvardsson, and Enquist (2011) demonstrate that this dimension
cannot be neglected in a service context. Lemke et al. (2011) support the conceptualiz-
ation of the influence of the role of other consumers on purchase behaviour, retention
and word of mouth despite the indirect nature of the impact. Moreover, customers
having entertained sound relations with employees tend to come back and recommend
the company to their friends (Sivadas & Baker-Prewitt, 2000). We therefore hypothesize
as follows:
H6: The social dimension of customer experience positively impacts loyalty.

Moderating effect of channel

Owing to the distinct differences between physical branch/agency settings and alternate
online environments, we believe that the impact of the dimensions of customer experi-
ence on loyalty varies based on the channel used. However, given the dearth of studies
having examined the experience-based differences between these contexts, academic
support remains sparse. Accordingly, in this segment of our research, we have adopted
an exploratory approach to the predicted moderating effect of the channel used (physical
versus Web-based) on the impact of the dimensions of customer experience on loyalty.
The hypothesis therefore remains general, hence the following assumption:
H7: The impact of the dimensions of customer experience on loyalty will differ based on the
channel used (physical versus Web-based).

In the following paragraphs, we discuss several predicted impacts in different contexts

based on our examination of existing literature which we present in Table 2.
To begin with, research substantiates the importance of the cognitive dimension of
customer experience in an electronic context. More precisely, Novak, Hoffman, and
Yung (2000), in their conceptualization of online experience flow, explain that it is a cog-
nitive state determined by such factors as levels of focused attention, skill, challenge,
arousal, etc. ‘Flow makes the user feel that he has solved a problem or obtained
more knowledge’ (Fuglsang & Sundbo, 2006, p. 631). These authors, who examined
Web-based travel booking, add that flow can help foster online consumer engagement
and loyalty, especially when the service is complex. Engaging the customer’s cognitive
responses appears to be extremely important in a Web-based setting. Hence, it can be
predicted that this dimension exerts a greater impact on loyalty in a virtual
environment.

Table 2. Predicted moderating impact of channel used (physical versus Web-based).

Predicted impact of channel
Dimensions Physical (branch) Web-based
Cognitive +
Affective (−) +
Affective (+) +
Sensory +
Behavioural +
Social +
10 I. BRUN ET AL.

Regarding the affective dimension, Leelakulthanit and Hongcharu (2011) demonstrate

that positive emotions impact online but not offline repurchase intentions in the
banking sector. It therefore follows that the impact of positive emotions should be
greater online than in an offline physical branch/agency location. The same likely
applies to negative emotions such as in an online environment where consumers are
oftentime left to their own devices. Frustrations can be addressed quickly and easily in
a physical location given ready access to onsite personnel. Online, however, companies
cannot pick up on negative consumer emotion until such time as it is actually expressed.
As for the sensory dimension, the latter is more accessible in a physical commercial
context (such as a branch/agency location) given potential solicitation of all five senses
whereas touch, taste and smell are absent in a virtual environment (Eroglu, Machleit, &
Davis, 2003). This dimension is therefore likely to have a greater impact on loyalty in a
branch or agency setting.
Subsequently, the behavioural dimension should also reveal differences. For example, in
a physical setting, it is generally more difficult to draw comparisons with the service offers
of rival companies. In a Web-based environment, however, consumer involvement is
greater given that it is the consumers themselves who engage in browsing, information
searches, etc. Accordingly, the impact of the behavioural dimension should be greater
online than offline.
Lastly, the impact of the social dimension could vary in accordance with the channel used.
Compared with the branch/agency setting where employees and other customers are
present, the Web-based context means that the consumer is alone in front of his or her com-
puter screen. In their exploratory research, Pareigis et al. (2011) reveal that frontline staff and
other consumers play an extremely important role in delivering a positive service experience
in a traditional, non-electronic context. The social dimension would therefore appear to
exert a greater impact in a branch or agency setting than in an online context.
Study findings enable us to understand more fully the impact of the channel used on
customer experience and loyalty. Figure 1 illustrates the conceptual framework of the
study and the research hypotheses.
The following section presents the methodology used to test the proposed model and
related hypotheses.

Methodology
In this section, we present the research sector, data collection process and questionnaire
measurements.

Research sector
The object of this research is to understand the impact of customer experience and the
dimensions of the latter on customer loyalty in the service sector, and to ascertain
whether there exist any differences based on the channel used (moderating impact of
physical location versus virtual environment). Khan and Rahman (2015), who deplore
the lack of experiential marketing research in the service industry, suggest that sectors
such as hospitality, tourism, banking and airlines be examined. We therefore selected
the banking industry to test hypotheses H1–H7. Since findings from a single sector are
 THE SERVICE INDUSTRIES JOURNAL 11

Figure 1. Conceptual framework.

not particularly conducive to generalization, we deemed it appropriate to validate results

by replicating our analyses in the tourism industry. With banking considered more utilitar-
ian and tourism more hedonic, the investigation of these two industries should also shed
light on contrasting settings. The choices made further reflect the importance of these
service sectors for consumers in both offline and online offline contexts. For example, in
Canada, 55% consider the Internet as their primary means of banking (Canadian
Bankers Association, 2015). In tourism, when planning a trip, online platforms represent
one of the principal sources of information for 65% of travellers (Google, 2014).
That said, even though the banking and tourism industries are fairly well represented in
topical marketing literature and journals (e.g. International Journal of Bank Marketing,
Journal of Travel and Tourism Marketing), no study on the impact of customer experience
on customer loyalty has been conducted in a multichannel context despite the ever-
increasing presence and use of the Internet in these sectors.

Data collection
An electronic survey was used as this method makes it possible to reach a large number of
respondents in short order. For the purpose of this study, customers were required to have
made use of both channels (physical and virtual).
12 I. BRUN ET AL.

Data collection took place in two stages, with banking customers targeted in the first
phase and tourism customers targeted in the second phase. Data were collected in
cooperation with one of the largest research firms in Canada, composed of more than
450,000 panelists at the time. They randomly dispatching invitations to panelists urging
them to take part in the survey. For the banking sector, while 502 individuals answered
the survey, the final number of useable Web-based, self-administered questionnaires rep-
resented a sample of 484 adult Canadians having one or more bank accounts or other pro-
ducts with a financial institution, and having visited their institution’s website and physical
branch facilities during the past year. Although the final sample comprised 484 individuals,
the total number of responses used in our analyses (n = 968) reflects our inclusion of both
physical (n = 484) and virtual (n = 484) customer experience evaluations. For the tourism
sector, while 720 participants took part in the survey, the final sample results in 289
respondents. The high number of non-usable questionnaires in this case is a consequence
of the low incidence of people having visited both a physical travel agency and the latter’s
website in the last year which was a prerequisite for the purpose of this study. Eleven
respondents were removed owing to extreme values and contradictory or repetitive
responses, resulting in a final sample of 289 adult Canadians.
Survey respondents comprised equal proportions of women and men (50% for each of
the two sectors, banking and tourism) and stemmed mainly from the ‘35–54’ (37% and
38%, respectively) and ‘54+’ (36% and 37%, respectively) age brackets. Unsurprisingly,
respondent income in the banking sector varied more given that the majority of people
are bank account holders (regardless of income). Income in the tourism industry tended
to be higher given the necessity of being able to afford travel-related expenses (discretion-
ary spending). More specifically, in the tourism sector some 80% of respondents indicated
an income of $60 000+, while the corresponding figure for the banking sector dropped to
60%.

Measurements
To ensure proper measurement of the concepts and a quality instrument, a pretest was
administered which consisted of a Web-based survey completed by a convenience
sample of 115 consumers. The survey was posted on researcher Facebook pages, and
friends and acquaintances invited to respond provided that they met the criteria for par-
ticipation: (1) Canadian citizen over 18 years of age, (2) conducted business with a financial
institution, and (3) had completed in-branch and online banking transactions during the
last year.
This pretest allowed us to review, modify and refine the questionnaire by deleting,
adding or reformulating items, or changing wording and layout as required, etc. For this
pretest, an exploratory factor analysis was performed to detail the dimensions of customer
experience. From this analysis, seven items associated with the cognitive, affective and
behavioural dimensions were removed owing to factor loadings of less than 0.40 or
cross-loadings.
In the final questionnaire, consumer loyalty was measured based on three items. For
customer experience, defined in accordance with the five dimensions advocated by
Schmitt (1999a) and including negative affective experience, 23 statements were used
to identify customer experience (see Appendix 1 for items and authors). All measurements
 THE SERVICE INDUSTRIES JOURNAL 13

were presented using 7-point Likert-type scales where 1 = totally disagree and 7 = totally
agree. It was necessary to complete and adapt existing items for the service sector, in par-
ticular the banking and tourism industries. The same questions were used to measure
branch/agency and Web-based experiences.
Since we used self-reported data, there exists the potential for the occurrence of
common method variance. Two procedures were carried out to address the issue.
Firstly, a Harmon one-factor test was conducted (Podsakoff & Organ, 1986). The results
of the principal component factor analysis revealed that one factor accounted for
28.72% (less than 50%) of the variance, but did not account for a majority of the variance
(Podsakoff, Mackenzie, & Lee, 2003). Further, as recommended by Podsakoff et al. (2003),
the multifactor measurement model was tested using an additional method factor.
Overall, this model demonstrated acceptable data fit (CFI of 0.91 and a root mean
square error of approximation [RMSEA] of 0.069). All paths remained significant and of
similar amplitude which could not be explained by a systematic error inherent in the
method (Grégoire, Laufer, & Tripp, 2010).

Findings
In the following sections, the theoretical framework is tested using structural equation mod-
elling (EQS 6.2). A maximum likelihood estimation procedure was favoured and deemed the
most appropriate owing to the lack of normality in the population (Mardia’s (1970) coeffi-
cient = 59.2708), which could have led to an overestimation of the chi-square statistic and
an underestimation of the fit indices (Byrne, 1994). The scaled chi-square and ‘robust’ stan-
dard errors using maximum likelihood estimation are advocated by Satorra and Bentler
(1994), and appear to be a good general approach for dealing with non-normality (Hu,
Bentler, & Kano, 1992). A two-step approach, such as recommended by Anderson and
Gerbing (1988), is employed where we first estimate the measurement model and then
the structural model. Table 3 synthesizes results obtained for the measurement and struc-
tural models tested in the banking industry. Lastly, we perform a multiple-group analysis
to test the moderating effect of channel on the impact of the dimensions of customer experi-
ence on loyalty. This analysis is first carried out in the banking industry to test Hypothesis 7
and then replicated in the tourism industry to compare results.

Measurement model
Firstly, for the measurement models and as indicated in Table 3, the goodness-of-fit indices
show that results fit the data well when examined using EQS 6.2 software. While the χ2 value

Table 3. Measurement and structural model results.

Indices Measurement model Structural model
χ value
2
1120.17 1114.66
Sig. 0.00 0.00
Degrees of freedom (df) 231 231
χ 2/df 4.85 4.82
NNFI 0.90 0.90
CFI 0.91 0.91
RMSEA 0.07 0.07
90% confidence interval of RMEA 0.066–0.073 0.066–0.073
14 I. BRUN ET AL.

is presented, the relative chi-square statistic (χ2/df) is increasingly used as a measure of fit
since the likelihood ratio of the chi-square statistic is known to be sensitive to sample
size (Byrne, 2006). The value in this study stands at 4.85 which indicates a good fit given
the value of less than 5 (Schumacker & Lomax, 2004). The non-normed fit index (NNFI)
works out to 0.90 which is consistent with the 0.90 threshold recommended by Kline
(2005). As for the CFI, the recommended cut-off of 0.90 (Hu & Bentler, 1999) is respected,
the figure for the model being 0.91. The RMSEA is an indicator of how well the model
would fit the population covariance matrix if it were available; the values (between 0.066
and 0.073) obtained for this model indicate a satisfactory fit (Hu & Bentler, 1999).
The final confirmatory factor analysis results determine unidimensionality and show
that the indicators each load on their respective construct (see Appendix 1). More specifi-
cally, all coefficient alpha estimates are greater than 0.70 (Nunnally, 1978) (ranging from
0.72 for the behavioural dimension to 0.91 for the loyalty construct). As for composite
reliabilities, they are all greater than 0.70 (Fornell & Larcker, 1981), ranging from 0.75 for
the behavioural dimension to 0.92 for the loyalty construct. Reliability through internal con-
sistency is thereby confirmed.
To demonstrate convergent validity, it is recommended that factor loadings be signifi-
cant and greater than or equal to 0.70 (Fornell & Larcker, 1981). This threshold is achieved
for all items (see Appendix 1) except for one (‘I tend to compare the financial institution’s/
travel agency’s products or services’) but the value of 0.67 remains close to the required
threshold. In addition, the average variance extracted (AVE) is examined to see if it is
greater than or equal to 0.50, demonstrating that variance owing to measurement error
is less than variance explained by the construct (Fornell & Larcker, 1981). All values are
equal or greater than the 0.50 threshold. To show discriminant validity of the constructs,
AVE must be greater than the variance (squared correlations) between the proposed factor
and all other factors (Fornell & Larcker, 1981). Results in Table 3 show that discriminant
validity is achieved in this study.

Structural model
As for the structural model (see Table 3), it fits the data well (goodness-of-fit indices: χ2
(231) = 1114.66, χ2/df = 4.82, NNFI = 0.90, CFI = 0.91, RMSEA = 0.07 with a 90% confidence
interval of 0.066–0.075). The results show that the conceptual model explains 23.5% of
loyalty variance. By examining the structural model estimates (see Table 5 – Global
impact on loyalty column), support is found for the hypothesized causal paths of the six
dimensions except for affective (+) (H3) and sensory (H4) which do not significantly
impact loyalty, as well as behavioural (H5) which has an impact albeit opposite to what
had been estimated. More specifically, the behavioural dimension exerts a negative as
opposed to a positive impact on loyalty. We elaborate further on these points in the dis-
cussion which follows. Regarding the importance of the impact of the various dimensions
on loyalty, we observe that it is the affective dimension (−) which exerts the greatest impact
(γ = −0.37, p < .01), followed by the (cognitive γ = 0.25, p < .01), social (γ = 0.20, p < .01) and
behavioural (γ = −0.14, p < .01) dimensions (Table 4).
As for the moderating variable (H7), the impact of certain dimensions on loyalty varies
depending on channel for the banking sector as seen in Table 5. Hence, the results of the
multiple-group analyses confirm Hypothesis 7. More specifically, the impact of the
 THE SERVICE INDUSTRIES JOURNAL 15

Table 4. Discriminant validitya (Banking, n = 968).

Constructs (1) (2) (3) (4) (5) (6)
Cognitive (1) 0.62
Affective (−) (2) 0.00 0.64
Affective(+) (3) 0.24 0.04 0.66
Sensory (4) 0.36 0.02 0.50 0.69
Behavioural (5) 0.25 0.04 0.08 0.08 0.50
Social (6) 0.09 0.02 0.34 0.31 0.01 0.65
a
Average variance extracted on-diagonal and squared correlations among constructs off-diagonal.

Table 5. Standardized parameter estimates.

Impacts of moderating variable (H7)
Banking Tourism
Constructs Global impact on loyalty Branch (n = 484) Web (n = 484) Branch (n = 289) Web (n = 289)
H1 cognitive γ = 0.25** γ = 0.21** γ = 0.22** γ = 0.44** γ = 0.41**
H2 affective (−) γ = −0.37** γ = −0.36** γ = −0.33** γ = −0.29** γ = −0.28**
H3 affective (+) γ = ns γ = ns γ = ns γ = ns γ = ns
H4 sensory γ = ns γ = ns γ = ns γ = ns γ = 0.24*
H5 behavioural γ = −0.14** γ = −0.24** +
γ = ns γ = ns γ = −0.24* +
H6 social γ = 0.20** γ = 0.35** +
γ = 0.12* γ = 0.29** γ = ns
R2 (loyalty) 23.5% 31% 17.8% 58.4% 32.4%
**Significant at 99%,*significant at 95%, ns – non-significant, (+) significant difference between branch and Web.

behavioural dimension is greater in a branch context (γ = −0.24, p < .01 versus non-signifi-
cant for a Web-based environment). The same is true for the social dimension (γ = 0.35,
p < .01) versus for a Web-based environment (γ = 0.12, p < .01).
These results confirm that the impact of customer experience dimensions on loyalty
differs based on the channel used (branch/agency versus Web-based). To see if these
results were sector-specific or not, we retested our hypothesis in another industry. Accord-
ingly, a multiple-group analysis was carried out in the tourism industry using a different
database. Results substantiate that there are differences between agency and Web-
based environments in this case, especially for the behavioural dimension (γ = −0.24,
p < .01 for Web-based context versus non-significant for an agency setting). We also
find that the sensory dimension exerts an impact in a Web-based environment but not
in an agency-based setting. The opposite is true for the social dimension which exerts
an impact in an agency-based setting but not in a Web-based environment.
Customer experience and the dimensions of the latter therefore vary based on context
regardless of channel or industry. We examine these findings more closely in the following
section.

Discussion
This study contributes handsomely to topical literature on a number of different levels.
Indeed, to date, few authors have chosen to focus on an examination of the impact of
the different dimensions of customer experience on loyalty. In addition, through the
use of a multichannel approach (branch/agency versus Web-based), this research contrib-
utes to a broader understanding of customer experience. In fact, at present, there are pre-
cious few studies which measure the impact of channel-specific customer experience on
16 I. BRUN ET AL.

customer loyalty; Terblanche and Boshoff (2006) examined the impact of in-store shop-
ping experience on retailer loyalty and Mhaya, Najjar, and Ben Jannet (2013), the
impact of social interaction and emotional reactions on loyalty in the case of social
media. In substantiating that customer experience can and does vary based on the
sector under investigation, this study’s multisector examination (banking and tourism)
demonstrates that consumers reap different types of experiences based on one or
other of the channel or service targeted.
The remaining sections highlight noteworthy findings and resultant managerial impli-
cations. Study limitations and possible avenues of future research are then presented.

Impact of the dimensions of customer experience on customer loyalty:

A multichannel, multisector examination
This study brings to the fore interesting results relating to the impact of the dimensions of
customer experience (cognitive, affective, sensory, behavioural and social) on loyalty in
both online and offline channels in each of the banking and tourism sectors. Hence, our
discussion focuses on four different contexts, namely branch/banking, online/banking,
agency/tourism and online/tourism.
Firstly, topical literature had led us to believe that the cognitive dimension would have a
greater impact in an electronic environment. However, this dimension was found to have
an impact on customer loyalty in all four models whether in an online or offline context.
Results show that the fact of causing consumers to learn something and remain attentive
to events around them can result in enhanced customer loyalty all around. It is noteworthy
to point out that this dimension is the one which exerts the greatest impact on loyalty in
tourism both online and offline. Service providers in the tourism industry are thus encour-
aged to embrace strategies designed to foster positive cognitive responses. Respecting
managerial implications, in a traditional physical setting, brochures, posters, prospectuses
and lighted display panels may be available and used to detail current highlights and pro-
motions. In instances where customers have recourse to services provided by employees,
the latter should be trained to share their knowledge of the services on offer, including
service characteristics, benefits and usefulness. In a Web-based context, ‘the service pro-
vider must provide opportunities for interaction and feedback through a personal back-
up system, typically a consumer-oriented help desk function’ (Fuglsang & Sundbo, 2006,
p. 379). Additionally, to foster customer learning and discovery, it is also advisable to
include in one’s Web strategy useful articles, forums, blogs, newsletters, infographics,
reports, testimonials and studies.
Secondly, topical literature purports that both positive and negative affective dimen-
sions will have a greater impact in a Web-based environment. However, findings reveal
that the positive affective dimension exerts no significant impact on loyalty, whatever
the nature of the context. This finding could owe to the scale of measurement. Indeed,
strong, spirited, positive emotions (surprise, entertainment, enchantment) were measured.
People experience emotions of the like to a very slight extent in the cases under study (e.g.
average of 3.05/7 in the branch/banking sector context). In the banking industry, could it
be that customers are not especially fond of being surprised or caught off guard, especially
given the utilitarian nature of the sector and the high level of personal involvement? Find-
ings perhaps would have been different had simpler, less intense emotions been used (e.g.
 THE SERVICE INDUSTRIES JOURNAL 17

joy, happiness). In future research, it would therefore be relevant to make allowance for
the intensity of the emotions measured.
Studies examining the affective dimension (e.g. Brakus et al., 2009; Tsaur et al., 2006)
focus on positive emotions to the exclusion of their negative counterparts. Often neg-
lected, inclusion of the negative aspect constitutes added value for the research at
hand. More particularly, findings demonstrate that the negative affective dimension
exerts a significant impact in all models especially in the banking context where it is
found to be the most important dimension in both branch-based and Web-based environ-
ments. Results indeed substantiate that the arousal of negative consumer emotions is not
conducive to building customer loyalty. This observation is not surprising given that con-
sumers not wishing a repeat of a negative emotional experience will tend to avoid the
company or service entity responsible in the future. In the hospitality industry, for
example, negative emotions tend to have a greater impact on satisfaction than positive
emotions (Han & Back, 2007). Ideally, action should be taken to avoid all manner of
online and offline customer frustrations. Online, it would be important to ensure that
browsing is easy and intuitive. In a branch setting, it would be important that staff be cour-
teous, competent and properly trained. While upstream prevention remains the option of
choice, service entities must be poised to react quickly and effectively when issues occur.
Thirdly, the sensory dimension is found to have no real impact. In the image of the posi-
tive emotional dimension, the sensory dimension is ranked low by consumers (average of
3.21/7). This could be explained by the sector under investigation. Indeed, in the banking
industry, services deemed generally more functional, structured and rigid can be per-
ceived as less stimulating or sensorial. In the tourism sector, compared with their European
counterparts, Canadian travel agencies have yet to deploy exceptional efforts at the servi-
cescape level which could explain the absence of the sensory dimension in the agency/
tourism sector model. It had been predicted that the sensory dimension would have a
lesser impact in an electronic context given the fact that three out of the five senses
are not solicited. For example, Luo, Chen, Ching, and Liu (2011) do not find support for
the impact of the senses on browsing and purchase intentions which, in their online
study, impacted loyalty. This having been said, the sole context in which the sensory
dimension is found to have a significant impact in our study is in the Web-based environ-
ment/tourism sector model. Hence in the context of a more hedonic service, such as travel,
sensory stimuli present on the Web contribute to a positive customer experience and
enhance customer loyalty. More precisely, according to Sindhav and Adidam (2012),
hedonic goods and services are more experiential by nature, meaning that they procure
greater affective gratification and come replete with more salient sensory attributes. For
example, the viewing of a video in an online context will necessarily prove more important
in the tourism sector than in the banking industry. In the tourism sector, more than half of
all travellers viewed videos relating to chosen destinations (Google, 2014). From a practical
point of view, auditory and visual cues, such as colour, hue, graphics, design and music,
must be well utilized to engage and arouse customers in an electronic environment
(Eroglu et al., 2003). For example, companies could use colour intensity and luminosity
to highlight designs or certain services. The stimuli could then be congruent or different
based on novelties, promotions, period of the year or simply brand image.
As for the behavioural dimension, it negatively impacts customer loyalty in a branch/
banking sector context, as well as in an online/tourism sector context. Indeed, the
18 I. BRUN ET AL.

behavioural aspect of customer experience is difficult to grasp in the banking sector and
not nearly as evident as readily observable audience reactions (body movements, singing,
etc.) to the likes of live stage performances. Moreover, in both sectors, could it be that
behaviour measured (e.g. reviewing bank accounts/travel plans, comparing products
and services) corresponds to behaviour exhibited by customers neither satisfied nor
engaged? This might explain the negative impact on loyalty. That said, in addition to
the fact that this dimension is not consistently defined or measured by the different
authors, this study confirms that it should be examined in greater depth in the future.
Lastly, as predicted, the social dimension is found to have an impact in the physical/
branch or agency environment in both sectors. Albeit marginal, the effect of this dimen-
sion manifests in online environments in the tourism industry. Indeed, social context is
more evident in a physical setting (e.g. with employees and other customers) but does
also appear to be relevant in some online environments. This could be explained by the
fact that in a Web-based environment, co-creation is commonplace. Employee help and
support therefore remain crucial. Accordingly, it is extremely important for service provi-
ders to ensure courteous service and positive attitudes from frontline employees in a phys-
ical setting and from resources tasked with chat functions in a virtual environment. The
social aspect of a website can be further enhanced in some instances through the use
of avatars. Finally, service providers would be advised to foster communication among
customers as the latter play a role in shaping the social dimension of customer experience
(e.g. creation of online discussion forums).

Limitations and directions for future research

Some limits respecting measurements and variables must be mentioned. When consider-
ing the affective dimension, we opted to measure powerful emotions (e.g. surprise, enter-
tainment). However, in a utilitarian context such as banking, these emotions are little
frequent. Simpler emotions (e.g. joy, pleasure) could have been chosen. Moreover, even
if the constructs are discriminant, a high level of correlation (0.71) was observed
between the ‘emotions +’ and ‘sensory’ constructs, a result also obtained by Brakus
et al. (2009). This could have impacted overall results.
From another standpoint, even if choosing the banking and tourism sectors made it
possible to differentiate the impact of the dimensions of customer experience on custo-
mer loyalty, any generalization of findings and application to other service industries
would present its lot of challenges since this study confirms the context-specific nature
of customer experience. Further research could focus on investigating whether differences
relate more specifically to utilitarian or hedonic services. Although the research at hand
revealed differences between the banking and tourism industries, results remain generally
exploratory.
Moreover, the multichannel environments present in today’s world mean that consu-
mer experiences in each of the channels impact consumer experiences in other channels
(e.g. online experience is impacted by in-store experience and vice versa) (Verhoef et al.,
2009). It would be interesting to examine the impact of the experience of one channel on
the experience of another. Readers will wish to bear in mind that just two channels were
examined for the purpose of this study and that consumers may also use other forms (e.g.
mobile, etc.). A comparative study of the synergy between branch/agency, Web-based and
 THE SERVICE INDUSTRIES JOURNAL 19

mobile experiences would be relevant in an era in which consumers ever increasingly use
smartphones and tablets to seek out information and conduct business.
Lastly, a comparison between different countries could bring to the fore cultural differ-
ences which impact customer experience. It could well be that cognitive, affective,
sensory, behavioural and social dimensions are more or less important in some cultures
than in others.
In conclusion, given the growing theoretical and practical importance of experiential
marketing for fostering loyalty and other behavioural constructs in the service sector,
we believe the field to be ripe with potential for future research.

Acknowledgements
The authors would like to thank the Financial Services Management Chair of the University of
Quebec in Montreal for making this research possible.

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

ORCID
Lova Rajaobelina http://orcid.org/0000-0003-3953-9428
Line Ricard http://orcid.org/0000-0003-0145-842X

References
Ali, F., Hussain, K., & Ragavan, N. A. (2014). Memorable customer experience: Examining the effects of
customers experience on memories and loyalty in Malaysian resort hotels. Procedia – Social and
Behavioral Sciences, 144, 273–279.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and rec-
ommended two-step approach. Psychological Bulletin, 103(3), 411–423.
Babin, B. J., & Attaway, J. S. (2000). Atmospheric affect as a tool for creating value and gaining share of
customer. Journal of Business Research, 49, 91–99.
Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The role of emotions in marketing. Journal of the
Academy of Marketing Science, 27(2), 184–206.
Bakini Driss, F., Jerbi, S., & Ben Lallouna Hafsia, H. (2009). Effet de la valeur perçue de magasinage sur
le comportement du consommateur: Cas d’un point de vente spécialisé. Revue des Sciences de
Gestion, 237(3), 177–185.
Barnes, S. T., & Vidgen, R. T. (2002). An integrative approach to the assessment of e-commerce quality.
Journal of Electronic Commerce Research, 3(3), 114–125.
Barsky, J., & Nash, L. (2002). Evoking emotion: Affective keys to hotel loyalty. The Cornell Hotel and
Restaurant Administration Quartely, 43(1), 39–46.
Brakus, J. J., Schmitt, B. H., & Zarantonello, L. (2009). Brand experience: What is it? How is it measured?
Does it affect loyalty? Journal of Marketing, 73, 52–68.
Byrne, B. M. (1994). Structural equation modeling with EQS and EQS/Windows: Basic concepts, appli-
cations, and programming. Thousand Oaks, CA: Sage Publications.
Byrne, B. M. (2006). Structural equation modeling with EQS: Basic concepts, applications, and program-
ming (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.
Canadian Bankers Association. (2015). How Canadians bank. Retrieved from http://www.cba.ca/en/
media-room/50-backgrounders-on-banking-issues/125-technology-and-banking
20 I. BRUN ET AL.

Carù, A., & Cova, B. (2006). Expériences de consommation et marketing expérientiel. Revue Française
de Gestion, 32, 99–115.
Chang, T.-Y., & Horng, S.-C. (2010). Conceptualizing and measuring experience quality: The custo-
mer’s perspective. The Service Industries Journal, 30(4), 2401–2419.
Chebat, J.-C., & Slusarczyk, W. (2005). How emotions mediate the effects of perceived justice on
loyalty in service recovery situations: An empirical study. Journal of Business Research, 58(5),
664–673.
Cielle, A. (2014). Comment trouver et fidéliser vos clients: 7 clés pour vendre plus et mieux (2nd ed.). Paris:
Dunod.
Donovan, R. J., Rossiter, R. J., Marcoolyn, G., & Nesdale, A. (1994). Store atmosphere and purchasing
behavior. Journal of Retailing, 70(3), 283–294.
Eroglu, S. A., Machleit, K. A., & Davis, L. M. (2003). Empirical testing of a model of online store atmos-
pherics and shopper responses. Psychology & Marketing, 20(2), 139–150.
Filser, M. (2002). Le marketing de la production d’expérience: Statut théorique et implications
managériales. Decisions Marketing, 28, 13–23.
Filser, M. (2003). Le marketing sensoriel: La quête de l’intégration théorique et managériale. Revue
Française du Marketing, 194(4), 5–11.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables
and measurement error. Journal of Marketing Research, 18(1), 39–50.
Fornerino, M., Helme-guizon, A., & De Gaudemaris, C. (2005, November). L’immersion dans une
expérience de consommation : vers une échelle de mesure. Presented at 10ème Journée de
Recherche en Marketing de Bourgogne, Dijon.
Fornerino, M., Helme-Guizon, A., & Gotteland, D. (2006, May). Mesurer l’immersion dans une expérience
de consommation: premiers développements. Presented at 22ème Congrès de l’Association
Française de Marketing, Nantes.
Fuglsang, L., & Sundbo, J. (2006). Flow and consumers in e-based self-services: New provider–consu-
mer relations. The Service Industries Journal, 26(4), 361–379.
Gentile, C., Spiller, N., & Noci, G. (2007). How to sustain the customer experience: An overview of
experience components that co-create value with the customer. European Management Journal,
25(5), 395–410.
Genzi, P., & Pelloni, O. (2004). The impact of interpersonal relationships on customer satisfaction and
loyalty to the service provider. International Journal of Service Industry Management, 15(3), 365–
384.
Google. (2014). The 2014 traveler’s road to decision. Retrieved from https://storage.googleapis.com/
think/docs/2014-travelers-road-to-decision_research_studies.pdf
Grégoire, Y., Laufer, D., & Tripp, T. M. (2010). A comprehensive model of customer direct and indirect
revenge: Understanding the effects of perceived greed and customer power. Journal of the
Academy of Marketing Science, 38(6), 738–758.
Guest, L. (1964). Brand loyalty revisited: A twenty-year report. Journal of Applied Psychology, 48(2), 93–
97.
Han, H., & Back, K. J. (2007). Assessing customers’ emotional experiences influencing their satisfaction
in the lodging industry. Journal of Travel and Tourism Marketing, 23(1), 43–56.
Helme-Guizon, A. (2001). Le comportement du consommateur sur un site marchand est-il fondamen-
talement différent de son comportement en magasin? Proposition d’un cadre d’appréhension de
ses spécificités. Recherche et Applications en Marketing, 16(3), 25–38.
Holbrook, M. B., & Hirschman, E. C. (1982). The experiential aspects of consumption: Consumer fan-
tasies, feelings and Fun. Journal of Consumer Research, 9(2), 132–140.
Holbrook, M. B. (2000). The millennial consumer in the texts of our times: Experience and entertain-
ment. Journal of Macromarketing, 20(2), 178–192.
Hosany, S., & Witham, M. (2010). Dimensions of cruisers’ experiences, satisfaction, and intention to
recommend. Journal of Travel Research, 49(3), 351–364.
Hsu, L. C., Wang, K. Y., & Chih, W. H. (2013). Effects of web site characteristics on customer loyalty in
B2B e-commerce: Evidence from Taiwan. The Service Industries Journal, 33(11), 1026–1050.
 THE SERVICE INDUSTRIES JOURNAL 21

Hu, L., Bentler, P. M., & Kano, Y. (1992). Can test Statistics in Covariance Structure Analysis be Trusted?
Psychological Bulletin, 112, 351–362.
Hu, L., & Bentler, P.M. (1999). Cut-off criteria for fit indexes in covariance structure analysis:
Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1−55.
Iglesias, O., Singh, J. J., & Batista-Foguet, J. M. (2011). The role of brand experience and affective com-
mitment in determining brand loyalty. Journal of Brand Management, 18(8), 570–582.
Jaakkola, E., Helkkula, A., & Aarikka-Stenroos, L. (2015). Service experience co-creation:
Conceptualization, implications, and future research directions. Journal of Service Management,
26(2), 182–205.
Jacoby, J., & Kyner, D. B. (1973). Brand loyalty vs. repeat purchasing behavior. Journal of Marketing
Research, 10, 1–9.
Khan, I., & Rahman, Z. (2015). A review and future directions of brand experience research.
International Strategic Management Review, 3, 1–14.
Klaus, P., & Nguyen, B. (2013). Exploring the role of the online customer experience in firms’ multi-
channel strategy: An empirical analysis of the retail banking services sector. Journal of Strategic
Marketing, 21(5), 429–442.
Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). New York: The
Guildford Press.
Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer
behavior. Information Systems Research, 13(2), 205–223.
Lee, S., Heere, B., & Chung, K. (2013). Which senses matter more? The impact of our senses on team
identity and team loyalty. Sport Marketing Quarterly, 22(4), 203–213.
Leelakulthanit, O., & Hongcharu, B. (2011). The determinants of brand loyalty in the online and offline
banking sectors. Journal of Global Business Management, 7(1), 1–13.
Lemke, F., Clark, M., & Wilson, H. (2011). Customer experience quality: An exploration in business and
consumer contexts using repertory grid technique. Journal of the Academy of Marketing Science, 39
(6), 846–869.
Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer
journey. Journal of Marketing, 80(6), 69–96.
Lin, C. P., & Bhattacherjee, A. (2008). Elucidating individual intention to use interactive information
technologies: The role of network externalities. International Journal of Electronic Commerce, 13
(1), 85–108.
Luo, M. M., Chen, J. S., Ching, R. K., & Liu, C. C. (2011). An examination of the effects of virtual experi-
ential marketing on online customer intentions and loyalty. The Service Industries Journal, 31(13),
2163–2191.
Ma, J., Gao, J., Scott, N., & Ding, P. (2013). Customer delight from theme park experiences: The ante-
cedents of delight based on cognitive appraisal theory. Annals of Tourism Research, 42, 359–381.
Maklan, S., & Klaus, P. (2011). Customer experience: Are we measuring the right things? International
Journal of Market Research, 53(6), 771–792.
Mardia, K. V. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57,
519–530.
Mathwick, C., Malhotra, N. K., & Rigdon, E. (2001). Experiential value: Conceptualization, measurement
and application in the catalog and internet shopping environment. Journal of Retailing, 77(1),
39–56.
Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. Cambridge, MA: The
MIT Press.
Meyer, C., & Schwager, A. (2007). Understanding customer experience. Harvard Business Review, 85(2),
1–12.
Mhaya, I., Najjar, H., & Ben Jannet, I. (2013). Effet de l’expérience en ligne sur la fidélité au site du
réseau social: Le rôle médiateur de la satisfaction des internautes. Journal of Global
Management Research, 9(1), 5–14.
Montour-Brunet, I., Rajaobelina, L., Ricard, L., & Brun, I. (2015). Échelle de mesure de l’expérience client
dans le secteur bancaire : une approche multicanale. Presented at 43e Congrs de l’Association des
Sciences Administratives du Canada, Halifax, Canada.
22 I. BRUN ET AL.

Mudie, P., Cottam, A., & Raeside, R. (2003). An exploratory study of consumption emotion in services.
The Service Industries Journal, 23(5), 84–106.
Nambisan, S. (2005). How to prepare tomorrow’s technologists for global networks of innovation.
Communications of the ACM, 48(5), 29–31.
Nasermoadeli, A., Ling, K. C., & Maghnati, F. (2013). Evaluating the impacts of customer experience on
purchase intention. International Journal of Business and Management, 8(6), 128–138.
Novak, T. P., Hoffman, D. L., & Yung, Y.-F. (2000). Measuring the customer experience in online
environments: A structural modeling approach. Marketing Science, 19(1), 22–42.
Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill.
Oliver, R. L. (1999). Whence consumer loyalty? Journal of Marketing, 63, 33–44.
Pan, Y., Sheng, S., & Xie, F. T. (2012). Antecedents of customer loyalty: An empirical synthesis and reex-
amination. Journal of Retailing and Consumer Services, 19(1), 150–158.
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring
consumer perceptions of service quality. Journal of Retailing, 64(1), 12–40.
Pareigis, J., Edvardsson, B., & Enquist, B. (2011). Exploring the role of the service environment in
forming customer’s service experience. International Journal of Quality and Service Sciences, 3(1),
110–124.
Payne, A. F., Storbacka, K., & Frow, P. J. (2008). Managing the co-creation of value. Journal of the
Academy of Marketing Science, 36(1), 83–96.
Pine II, B. J., & Gilmore, J. H. (1998). Welcome to the experience economy. Harvard Business Review, 76,
97–105.
Pine II, B. J., & Gilmore, J. H. (2011). The experience economy (updated). Cambridge, MA: Harvard
Business Review Press.
Podsakoff, P. M., Mackenzie, S. B., & Lee, J.-Y. (2003). Common method biases in behavioral research:
A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5),
879–903.
Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: Problems and pro-
spects. Journal of Management, 12(4), 69–82.
Reichheld, F. F. (1996). L’Effet Loyauté. Réussir en fidélisant ses clients, ses salariés et ses actionnaires.
Paris: Dunod.
Reniou, F. (2009). Opérations participatives des marques: Pourquoi et comment faire participer les con-
sommateurs? (Unpublished doctoral dissertation). Université de Paris–Dauphine & ESSEC, France.
Richins, M. L. (1997). Measuring emotions in the consumption experience. Journal of Consumer
Research, 24(2), 127–146.
Roos, I., Friman, M., & Edvardsson, B. (2009). Emotions and stability in telecom-customer relationships.
Journal of Service Management, 20(2), 192–208.
Rose, S., Clark, M., Samouel, P., & Hair, N. (2012). Online customer experience in e-retailing: An empiri-
cal model of antecedents and outcomes. Journal of Retailing, 88(2), 308–322.
Sahin, A., Zehir, C., & Kitapçı, H. (2011). The effects of brand experiences, trust and satisfaction on
building brand loyalty; An empirical research on global brands. Procedia Social and Behavioral
Sciences, 24, 1288–1301.
Satorra, A., & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance
structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications for devel-
opmental research (pp. 399–419). Thousand Oaks, CA: Sage.
Schmitt, B. (1999a). Experiential marketing. Journal of Marketing Management, 15, 53–67.
Schmitt, B. (1999b). Experiential marketing: How to Get customers to sense, feel, think, Act, relate to your
company and brands. New York: Free Press.
Schumacker, R. E., & Lomax, R. G. (2004). A beginner’s guide to structural equation modeling (2nd ed.).
Mahwah, NJ: Lawrence Erlbaum Associates.
Shobeiri, S., Mazaheri, E., & Laroche, M. (2014). Improving customer website involvement through
experiential marketing. The Service Industries Journal, 34(11), 885–900.
Sindhav, B., & Adidam, P. T. (2012). Hedonic and utilitarian values of a service experience with a non-
profit: The role of identification. International Management Review, 8(1), 37–43.
 THE SERVICE INDUSTRIES JOURNAL 23

Sivadas, E., & Baker-Prewitt, J. L. (2000). An examination of the relationship between service quality,
customer satisfaction, and store loyalty. International Journal of Retail & Distribution Management,
28(2), 73–82.
Slåtten, T., Mehmetoglu, M., Svensson, G., & Sværi, S. (2009). Atmospheric experiences that emotion-
ally touch customers: A case study from a winter park. Managing Service Quality, 19(6), 721–746.
Srivastava, M., & Kaul, D. (2016). Exploring the link between customer experience–loyalty–consumer
spend. Journal of Retailing and Consumer Services, 31, 277–286.
Swinyard, W. R. (1993). The effects of mood, involvement, and quality of store experience on shop-
ping intentions. Journal of Consumer Research, 20(2), 271–280.
Terblanche, N. S., & Boshoff, C. (2006). The relationship between a satisfactory in-store shopping
experience and retailer loyalty. South African Journal of Business Management, 37, 33–43.
Tsaur, S.-H., Chiu, Y., & Wang, C. (2006). The visitors behavioral consequences of experiential market-
ing : An empirical study on Taipei Zoo. Journal of Travel & Tourism Marketing, 21(1), 47–64.
Verhoef, P. C., Lemon, K. N., Parasuraman, A., Roggeveen, A., Tsiros, M., & Schlesinger, L. A. (2009).
Customer experience creation: Determinants, dynamics and management strategies. Journal of
Retailing, 85(1), 31–41.
Voss, C., Roth, A. V., & Chase, R. B. (2008). Experience, service operations strategy, and services as des-
tinations: Foundations and exploratory investigation. Production and Operations Management, 17
(3), 247–266.
Yi, Y., & Gong, T. (2009). An integrated model of customer social exchange relationship: The moder-
ating role of customer experience. The Service Industries Journal, 29(11), 1513–1528.
Yu, Y.-T., & Dean, A. (2001). The contribution of emotional satisfaction to consumer loyalty.
International Journal of Service Industry Management, 12(3), 234–250.
Zhou, T., & Lu, Y. (2011). Examining mobile instant messaging user loyalty from the perspectives of
network externalities and flow experience. Computers in Human Behavior, 27(2), 883–889.
Zomerdijk, L. G., & Voss, C. A. (2010). Service design for experience-centric services. Journal of Service
Research, 13(1), 67–82.
24 I. BRUN ET AL.

Appendix 1. Items of the questionnaire (n = 968)

Comp.
Standard Factor Rel.
Constructs Mean deviation loadings AVE Alphas (CFR) Adapted from
Loyalty 5.62 1.29 0.78 0.91 0.92
In the future, I will be loyal to 0.94 Brakus et al. (2009)
this financial institution
(travel agency)
In the future, I will conduct 0.91
most of my (bank)
transactions with this
financial institution (travel
agency)
I recommend this financial 0.80
institution (travel agency)
to others
Experience dimensions
Cognitive 4.47 1.54 0.62 0.82 0.83
I engage in a thinking process 0.77 Brakus et al. (2009) and
I am really focused 0.75 Fornerino et al. (2006)
My attention is captivated 0.83
Affective (−) 2.75 1.50 0.64 0.87 0.88
I sometimes feel 0.76 Mehrabian and Russell
disappointed (1974), Richins (1997)
I sometimes feel angry 0.81 and Ma, Gao, Scott and
I sometimes get bored 0.82 Ding (2013)
I sometimes get impatient 0.81
Affective (+) 3.05 1.53 0.66 0.85 0.85
I am sometimes surprised 0.70 Same as emotional (−)
I sometimes feel entertained 0.87
I sometimes feel enchanted 0.86
Sensory 3,21 1,69 0.69 0.86 0.87
My senses are involved 0.89 Brakus et al. (2009)
My visual sense is stimulated 0.84
My sense of hearing is 0.76
stimulated
Behavioural 4.37 1.65 0.50 0.72 0.75
I tend to review my bank 0.70 Montour-Brunet,
accounts (travel plans) Rajaobelina, Ricard, and
I tend to take an active part in 0.74 Brun (2015)
the management of my
personal finances (travel
arrangements)
I tend to compare the 0.67
financial institution’s (travel
agency) products or
services
Social 3.13 1.69 0.65 0.90 0.90
I live a pleasant social 0.71 Barnes and Vidgen (2002)
experience and Nasermoadeli et al.
I feel that I am a part of a 0.83 (2013)
community
I identify myself with the 0.81
other customers
I develop relationships with 0.82
the staff
I socialize 0.85