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322
Services Marketing Quarterly, 34:322–338, 2013
Copyright © Taylor & Francis Group, LLC
ISSN: 1533-2969 print/1533-2977 online
DOI: 10.1080/15332969.2013.827068
The Influence of Customer Experience Quality
on Customers’ Behavioral Intentions
HYUNSIK KIM
College of Business Administration, Hallym University,
Gangwon-do, South Korea
BEOMJOON CHOI
College of Business Administration, California State University,
Sacramento, California
The current study proposes and tests a theoretical model of the
relationship among service outcome quality, interaction quality,
peer-to-peer quality, and customer experience quality, and the
impact of customer experience quality on customer loyalty. The
findings indicate that service outcome quality, interaction quality,
and peer-to-peer quality perceptions significantly influence cus-
tomer experience quality, which, in turn, influences customer loy-
alty. Furthermore, the findings show that the relationship between
the antecedents of customer experience quality, service outcome
quality and peer-to-peer quality, and customer experience quality
are moderated by gender.
KEYWORDS service outcome quality, interaction quality, peer-to-
peer quality, customer experience quality, customer loyalty
INTRODUCTION
A recent survey by Bain & Co. of 362 companies found that 80% of the senior
executives interviewed said they provided an excellent customer experience,
but interestingly, only 8% of their customers agreed (Coffman & Stotz, 2007).
The discrepancy may be mainly due to the difference of the point of views.
From a company standpoint, companies might think they created an
Address correspondence to Beomjoon Choi, College of Business Administration, California
State University, Sacramento, 6000 J Street, Sacramento, CA 95819-6088. E-mail: bchoi@csus.edu
Customer Experience Quality and Behavioral Intentions 323
excellent customer experience by providing excellent services. But often
times, this may not turn into excellent customer experience as customer
experience quality is likely to be determined from the point of view of an
individual customer (Vargo & Lusch, 2004). For example, customers who go
to a movie theater and receive high-quality services from employees may
end up having a terrible experience if other customers keep talking on a cell
phone during a movie. Other examples may include the offense of a cus-
tomer being intoxicated (drunk) in a public place and displaying abusive
behavior to employees or other customers. As such, customer experience
quality is likely to be determined based on “total experience,” not just ser-
vices provided from a service provider.
Customer experience is defined as the customer’s subjective response
to the encounter with the firm, which includes the communication encoun-
ter, the service encounter, and the consumption encounter (Lemke, Clark, &
Wilson, 2011; Meyer & Schwager, 2007). Customer experience quality is
likely to determine the perceived value of service and further, leads to other
outcomes such as repurchase intention. Surprisingly, the relationship between
customer experience quality and success in businesses has been only recently
explored (Lemke etal., 2011; Payne, Storbacka, & Frow, 2008; Verhoef etal.,
2009). Previous research suggests that engendering superior customer expe-
rience is one of the ways to achieve successful marketing outcomes and
further improve a firm’s chance of success (Berry, Carbone, & Haeckel, 2002;
Verhoef etal., 2009). However, no research has been conducted to empiri-
cally examine the antecedents and consequence of customer experience
quality. To bridge the gap, we test a theoretical model that includes the con-
structs such as service outcome quality, interaction quality, peer-to-peer
(interaction) quality, customer experience quality, and customer loyalty.
Service outcome quality, interaction quality, and peer-to-peer quality were
selected based on Verhoef etal.’s (2009) conceptual model.
The primary objective of this study is threefold. First, the current study
investigates the relationship between service outcome quality, interaction
quality, and peer-to-peer quality and customer experience quality. Second,
we examine the effects of customer experience quality on customer loyalty.
Third, we explore the moderating role of gender on the relationship between
the antecedents of customer experience quality (service outcome quality,
interaction quality, and peer-to-peer quality) and customer experience qual-
ity. To test the model, we collected data using self-administered surveys. The
proposed relationships were tested using the structural equation modeling.
Our findings indicate that outcome quality, interaction quality, and peer-to-
peer quality perceptions significantly influence customer experience quality,
and that customer experience quality greatly influences customer loyalty. In
all, this study shows that outcome quality, interaction quality, and peer-to-
peer quality should be treated as key variables to create superior customer
experience, and that customer experience quality should be considered one
324 H. Kim and B. Choi
of key elements of building customer loyalty. The rest of the study is orga-
nized in the following manner. The next section provides a theoretical model
along with the proposed hypotheses. Next, the methodology section
describes the research methods, followed by the results section, which dis-
cusses the findings. Finally, the article concludes with a discussion of the
implications, limitations, and future research.
Theoretical Model and Hypotheses Development
CUSTOMER EXPERIENCE
Gentile, Spiller, and Noci (2007) proposed six primary dimensions of
customer experience that influence customers’ perception of customer expe-
rience. These dimensions are sensorial component, emotional component,
cognitive component, pragmatic component, lifestyle component, and rela-
tional component. Lemke, Clark, and Wilson (2011) also posited that customer
experience consists of three dimensions: communication encounter, service
encounter, and usage encounter (Lemke etal., 2011). However, this approach
might have some pitfalls as customer experience is typically holistic in nature
as it is shaped based on the subject response customers have to a combina-
tion of all types of offerings and interactions including direct and indirect
contact with a company (Verhoef et al., 2009). Therefore, following the
approach suggested by Verhoef etal. (2009), we conceptualize the customer
experience quality as an “aggregate” construct and analyze the relationships
between the antecedents and customer experience (see Law, Wong, &
Mobley, 1998).
Verhoef etal. (2009) suggested eight primary antecedents of customers’
holistic perception of customer experience. These antecedents are social
environment, service interface, (retail) store atmosphere, assortment, price,
customer experiences in an alternative channel, and past customer experi-
ence. Verhoef etal. (2009) elaborated further four major antecedents, which
are social environment, service interface, retail store atmosphere, and past
customer experience. We derived three dimensions from those four anteced-
ents: service outcome quality, interaction quality, and peer-to-peer quality. In
the following section, we examine how these antecedents influence cus-
tomer experience.
SERVICE OUTCOME QUALITY AND CUSTOMER EXPERIENCE QUALITY
Service quality and customer satisfaction have been considered important
and, thereby investigated by numerous researchers in marketing, retailing,
and service management (e.g., Parasuraman, Zeithaml, & Berry, 1988; Verhoef,
Langerak, & Donkers, 2007). Meanwhile, the importance of customer experi-
ence has been recognized only by a few researchers (e.g., Lemke etal., 2011;
Verhoef et al., 2009) though it seemed that the practitioners already
Customer Experience Quality and Behavioral Intentions 325
considered customer experience a crucial factor in engendering loyalty
(Badgett, Boyce, & Kleinberger 2007).
Verhoef etal. (2009) proposed a conceptual model of customer experi-
ence and suggest several determinants of customer experience quality, which
include the social environment, the service interface, the retail atmosphere,
the assortment, the price, and promotions. In the present article, we suggest
outcome quality as one of the determinants of customer experience quality.
Outcome quality (i.e., technical quality; Grönroos, 1982, 1984) refers to the
customers’ perceptions of the superiority of what they receive during service
encounters (Brady and Cronin, &; Grönroos, 1982, 1984). Czepiel, Solomon,
and Suprenant (1985) also posited that the service outcome is critical in
assessing the quality of a service encounter. Provided that customer experi-
ence is considered the customer’s subjective response to the holistic direct
and indirect encounter with the firm (Lemke etal., 2011), we argue that there
exists a positive relationship between service outcome quality and customer
experience quality. Therefore, we hypothesize:
H1: The success of the service outcome (service outcome quality) will
have a positive influence on customer experience quality.
INTERACTION QUALITY AND CUSTOMER EXPERIENCE QUALITY
Interaction quality refers to the customers’ perceptions of the superiority of the
manner in which the service is delivered (Lemke etal., 2011) and from the
initial contact through service delivery, customers interact with service provid-
ers across multiple touch points (e.g., making an appointment or reservation,
contact with a receptionist, receiving a service from a service provider, etc.)
and, if employees display good interaction skills such as being polite, friendly,
trustworthy, and helpful in face-to-face encounters with customers and hence,
customers perceive a high level of interaction quality, we argue that customers
will be more likely to experience a high level of experience quality. That is,
perceived quality of a set of interactions are likely to be a critical determinant
of customer experience quality. Therefore, we propose that customer experi-
ence quality is determined based on perceived quality of interactions between
a customer and service providers, and thereby, hypothesize:
H2: Interaction quality will have a positive influence on customer experi-
ence quality.
PEER-TO-PEER QUALITY AND CUSTOMER EXPERIENCE QUALITY
Lemke etal. (2011) suggested that peer-to-peer quality is the perceived judg-
ment of the superiority of customers’ interaction among one another and a criti-
cal element of delivering a superior customer experience in their conceptual
model. Specifically, they stated, “one of the origins of customers experience is
326 H. Kim and B. Choi
the contact with other customers in the consumption process … customers
view the quality of the peer-to-peer encounter as part of their overall experi-
ence assessment.” McGroth and Otnes (1995) posited that a customer’s helping
behavior influence other customer’s service experience positively. Wu (2007)
also argued that knowledgeable customers influence other customers’ experi-
ence by disseminating useful customer knowledge.
On the other hand, a customer’s misbehavior such as talking loudly
during a movie (Verhoef etal., 2009) may destroy customers’ service experi-
ence. More specifically, jay customer behaviors (Lovelock, 1994), deviant
customer behavior (Moschis & Cox, 1989), and aberrant customer behavior
(Fullerton & Punj, 1993) not only cause direct negative effect on the com-
pany but also ruin the experience of other customers (Verhoef etal., 2009).
Also, customers can influence one another indirectly. For example, crowding
or standing too close to others may create anxiety (Bateson & Hui, 1986;
Fisher & Byrne, 1975; Hall, 1966), age incompatibility (Thakor, Suri, & Saleh,
2008), and eye contact between strangers can be negatively perceived
(Aronoff, Woike, & Hyman, 1992). This leads us to suggest that there exists
a positive relationship between peer-to-peer quality and customer experi-
ence quality. Therefore, we hypothesize:
H3: Peer-to-peer quality will have a positive influence on customer expe-
rience quality.
CUSTOMER EXPERIENCE QUALITY AND CUSTOMER LOYALTY
Loyalty is defined as “an intention to perform a diverse set of behaviors that
signal a motivation to maintain a relationship with the focal firm, including
allocating a higher share of the category wallet to the specific service pro-
vider, engaging in positive word-of-mouth and repeat purchasing”
(Sirdeshmukh, Singh, & Sabol, 2002, p. 20). Previous research suggests that
service quality and customer satisfaction as two major antecedents of loyalty
towards firms. Parasuraman, Zeithaml, and Berry (1998) examined service
evaluations through quality dimensions and suggested the link between ser-
vice quality and loyalty, whereas Reynolds and Beatty (1999) emphasized
satisfaction as a direct antecedent of loyalty.
In addition, we posit customer experience quality as one of the ante-
cedents of loyalty. Customer experience quality is defined as the perceived
superiority of customer experience (Lemke etal., 2011). While the distinction
appears to be unclear from firm standpoint in service contexts, customer
service quality is conceptually distinct from service quality. Service quality is
considered a perceived judgment of its excellence or superiority (Parasuraman,
Zeithaml, & Berry, 1998; Zeithaml, 1988) and its main focus lies in a judg-
ment about the firm’s process and, not the customer’s (Payne, Storbacka, &
Frow, 2008). However, customer experience is formed based on numerous
Customer Experience Quality and Behavioral Intentions 327
contextual factors such as the presence/contact with other customers and a
level of participation in a service process, and hence, cannot be viewed as
only influenced by service firms (Pullman & Gross, 2004; Schembri, 2009).
Given that our conceptualization of customer service encompasses not only
perceived quality of services provided by service firms but also customers’
perception of “total experience,” we propose that customer experience qual-
ity leads to customer loyalty. Therefore, we hypothesize:
H4: Customer experience quality will have a positive influence on cus-
tomer loyalty.
In all, the service outcome quality, interaction quality, and peer-to-peer
quality influences customer experience quality, which in turn affects cus-
tomer loyalty. Figure 1 illustrates the research model for this study.
RESEARCH METHODOLOGY
Sample
A total of 1,168 junior high school students (735) and high school students
(433) in Korea participated in a survey in exchange for extra credit; the par-
ticipants were 80.5% male. The survey was conducted in a self-completed
questionnaire format. Subjects were asked to recall their most recent experi-
ence and write down the organization’s name to enhance recall accuracy.
The reported service types include movie theater, bowing sport center, city
tour, university tour, folk village, museum, historical monuments, and modern
monuments; the various service types reported in the sample are expected
FIGURE 1 Research model.
328 H. Kim and B. Choi
to enhance the applicability of the findings of the current research to most
service categories.
Measures
Based on previous research on service marketing research, we select
measurement items that are deemed appropriate to the context of the
current study. Utilizing measurement items used in the existing literature
provided a basis for specification of each construct. Measurement items
were taken either directly or modified to measure the latent constructs.
All measures used for the current study are shown in Table 1. The sub-
jects were asked to respond on a 5-point Likert scale (1 = strongly dis-
agree; 5 = strongly agree).
TABLE 1 Measurement Items
Construct Measurement items References
Service
outcome
quality
I feel good about what XYZ provides to
its customers (V1).
Brady and Cronin (2001)
I believe that XYZ provides superior
outcome to its customers. (V2).
Mohr and Bitner (1995)
I would say that XYZ gi ve requested
outcome to the customers. (V3).
Interaction
quality
I think that the quality of my interaction
with XYZ and XYZ’s employees is
excellent (V4).
Brady and Cronin (2001)
I would say that XYZ and XYZ’s employ-
ees are interested in the customers
(V5).
Mohr and Bitner (1995)
I believe that XYZ and XYZ’s employees
are caring the customers (V6).
Peer-to-peer
quality
I would say that the quality of my
interaction with other customers at
XYZ is excellent (V7).
Brady and Cronin (2001)
I believe that we get superior interactions
with other customers at XYZ (V8).
Lemke, Clark, and Wilson
(2010)
I think that total contact with other
customers at XYZ is excellent (V9).
Customer
experience
quality
I would say that the experience at/with
XYZ is excellent (V10).
Brady and Cronin (2001)
I believe that we get superior experience
at XYZ (V11).
Lemke, Clark, and Wilson
(2010)
I think that total experience procedure at
XYZ is excellent (V12).
Customer
loyalty
I will continue to visit XYZ in the future
(V13).
Gruen, Osmonbekov, and
Czaplewski (2007)
I will recommend XYZ and its services to
others in my school (V14).
Yim, Tse, and Chan (2008)
I will recommend XYZ and its services to
others outside my school (V15).
Customer Experience Quality and Behavioral Intentions 329
ANALYSIS AND RESULTS
Measurement Model
The adequacy of the measurement model was evaluated based on the criteria
of overall fit with the data, reliability, convergent validity, and discriminant
validity. First, reliability and validity tests of the measurement model were
conducted (Churchill, 1979). The properties of all the items were located as
reflective measures on their respective factors and evaluated through a com-
prehensive confirmatory factor analysis (CFA) using AMOS 18.0. The overall
measurement model fit indices indicate that the comprehensive confirmatory
factor model fits the data well (
χ
2 = 301.290, df = 80, p = .000, CFI = .981,
TLI = .976, NFI = .975, standardized RMR = .028, RMSEA = .049).
The range of the Cronbach’s alpha coefficients for each construct was
acceptably high (.792 [service outcome quality] ~ .928 [peer-to-peer quality]).
As a result, the composite reliability was satisfactory. To test convergent valid-
ity, t-value and average variance extracted (AVE) were employed (Fornell &
Larcker, 1981). T-values of lambda (
λ
) loadings of each measure were signifi-
cant (p < .01) and AVEs for each construct were good (all exceeded over .70).
Overall, the results suggested good convergent validity as shown in Table 2.
Next, discriminant validity was assessed by developing a confidence
interval of
ψ
± 2
σ
e for each pair of factors and examining whether 1 is
included in a confidence interval. The
ψ
notation indicates the correlation
between two factors, whereas
σ
e represents the standard error between two
factors. The high end of the confidence interval between two factors does
TABLE 2 Summary of Measurement Results
Construct
Measurement
items
Factor
loading t-values
Composite
reliabilityaAverage variance
extracted (AVE)b
Service outcome
quality
V1 .773 28.634 .887 .724
V2 .770 28.611
V3 .704 25.283
Interaction
quality
V4 .887 37.425 .899 .749
V5 .905 38.762
V6 .800 32.041
Peer-to-peer
quality
V7 .885 37.875 .914 .781
V8 .923 40.537
V9 .894 38.708
Customer
experience
quality
V10 .848 25.737 .893 .736
V11 .830 27.242
V12 .792 33.196
Customer
loyalty
V13 .781 20.490 .899 .747
V14 .834 21.170
V15 .819 22.254
aComposite reliability: (∑
λ
i)2/[(∑
λ
i)2 + ∑ivar(
ε
i)], where
λ
i is the component loading to an indicator and
var(
ε
i)=1 −
λ
i2. bAverage variance extracted: ∑
λ
i2/[∑
λ
i2 + ∑ivar(
ε
i)].
330 H. Kim and B. Choi
not include 1, which provides evidence of discriminant validity (Koufteros,
1999).
Structural Model
The structural equation modeling (SEM) analysis was conducted to test the
hypothesized relationships. The model fit indices are acceptable. The struc-
tural model has a statistically significant value of chi-square test (
χ
2 = 491.835,
df = 83, p = .000). All other relevant fit indices are also within the acceptable
range (CFI = .966, TLI = .957, NFI = .959, standardized RMR = .048, RMSEA = .065).
Therefore, we conclude that the proposed model fits the data well. The esti-
mated path coefficients together with hypotheses test results are shown in
Figure 2.
TABLE 3 Interconstruct Correlations
Variables
Service
outcome
quality
Interaction
quality
Peer-to-peer
quality
Customer
experience
quality
Customer
loyalty
Service outcome
quality
— .368 .241 .484 .524
Interaction
quality
.607
(.029)
— .300 .355 .462
Peer-to-peer
quality
.491
(.026)
.548
(.027)
— .368 .441
Customer
experience
quality
.696
(.031)
.596
(.029)
.607
(.028)
— .588
Customer
loyalty
.724
(.031)
.680
(.030)
.664
(.028)
.767
(.032)
—
Note. Intercorrelations are presented in the lower triangle of the matrix. Standard errors appear in the
parentheses. Squared correlations are given in the upper triangle of the matrix.
FIGURE 2 Structural equation model with the estimated path coefficients and test results.
Note. Standard errors appear in the parentheses. *p < .05. **p < .01.
Customer Experience Quality and Behavioral Intentions 331
The estimated standardized structural coefficients for the hypothesized
associations among constructs and their significance are shown in Table 4.
The parameter estimates were consistent with the proposed direction in the
hypothesized paths and all hypotheses were supported.
H1 is related to the path from service outcome quality to customer experience
quality. The path from Interaction service quality to customer experience quality
(H2) and the path from peer-to-peer quality to customer experience quality (H3)
were significant. Customer experience quality also had a significant positive
influence on customer loyalty lending support for H4.
Moderating Effect Analysis
To deepen the understanding of the relationships between service outcome
quality, interaction quality, and peer-to-peer quality and customer experi-
ence quality, we investigated the moderating role of gender within the cur-
rent framework. Previous research suggests that men have agentic, “agent of
action” (assertive and instrumental) traits, whereas women display commu-
nal (nurturing and yielding) traits (Archer, 1996; Iacobucci & Ostrom, 1993;
Powell, Betterfield, & Parent, 2002). As a result, men tend to be instrumental
and task-oriented and hence, emphasize the outcome (i.e., what they will
actually receive). On the other hand, women have more emphasis on pro-
cess (i.e., delivery style) and relational aspects of interpersonal encounters
than outcomes compared to men (Gilligan, 1982; Iacobucci & Ostrom, 1993;
Oakley, 2000; Rosener, 1990). Applying these works in the context of the
current study, we propose that men are likely to perceive a higher level of
customer experience quality with the increase of service outcome quality
while women are likely to perceive a higher level of customer experience
quality with the increase of interaction quality and peer-to-peer quality.
We used a retrospective self-report data approach so as to investigate
the moderating role of gender in the suggested model. To compare samples
across gender, we performed chi-square difference test (∆
χ
2), which consists
TABLE 4 Structural Equation Model Results: Path Coefficients
Hypothesized path Hypothesis
Standardized
coefficient t-value Results
Service Outcome Quality →
Customer Experience Quality
H1 .480 12.863** Accepted
Interaction Quality →
Customer Experience Quality
H2 .191 5.821** Accepted
Peer-to-peer Quality →
Customer Experience Quality
H3 .316 10.851** Accepted
Customer Experience Quality →
Customer Loyalty
H4 .840 24.090** Accepted
**p < .01.
332 H. Kim and B. Choi
of two steps. First, we develop a constraint model by imposing an equality
constraint on the focal link. Next, we compare the chi-square between the
free model and the constraint model. The participants were divided by
gender into two groups (male vs. female) and each link in the suggested
model was compared between the groups.
The results of chi-square difference test indicated that the relationship
between service outcome quality and customer experience quality was mod-
erated by gender. Consistent with previous research, service outcome quality
is more critical in determining customer experience quality for men than
women. The relationship between peer-to-peer quality and customer experi-
ence quality was found marginally significant, whereas the relationship
between interaction quality and customer experience quality was not signifi-
cant. It is noteworthy that the link between peer-to-peer quality and cus-
tomer experience quality is stronger for women than men, whereas the link
between interaction quality and customer experience quality is not different
depending on gender. The results of the chi-square difference test are
reported in Table 5.
DISCUSSION AND IMPLICATIONS
Theoretical Implications
Provided that creating superior customer experience is a key to success, it is
crucial to understand the antecedents and consequences of customer
experience quality. Extending conceptual studies (Lemke etal., 2011; Verheof
etal., 2009) that propose a link between peer-to-peer quality and customer
experience quality, the present study investigates the relationships between
customer experience quality and other constructs such as service outcome
quality, interaction quality, peer-to-peer quality, and customer loyalty. The
current findings identify service outcome quality and interaction quality as
antecedents of customer experience quality. That is, customers’ perception
TABLE 5 The Moderating Effect of a Gender on the Relationship Between Service Outcome
Quality, Interaction Quality, and Peer-to-Peer Quality on Customer Experience Quality
Hypothesized path
Male
path estimates
(SE)
Female
path estimates
(SE)
Chi-square
difference
(df difference)
Service Outcome Quality →
Customer Experience Quality
.521 (.043) .174 (.048) 24.747(1)**
Interaction Quality →
Customer Experience Quality
.152 (.032) .099 (.055) 0.672(1)
Peer-to-peer Quality →
Customer Experience Quality
.253 (.029) .365 (.060) 2.917(1)*
*p < .05. **p < .01.
Customer Experience Quality and Behavioral Intentions 333
of service outcome and interactions with service firms has a substantial
influence on customer experience quality. Furthermore, the results also
demonstrate that customers’ perception of interactions with other customers
(peer-to-peer quality) influences customer experience quality. This validates
previous studies’ proposition on the relationship between peer-to-peer
(interaction) quality and customer experience quality (Verhoef etal., 2009).
The validation of the link between peer-to-peer quality and customer
experience quality has profound implications. Previous research has shown
vast interests in creating the relationships between customers and compa-
nies, but not the relationship among customers. It is partly due to the fact
that peer-to-peer interaction may not be completely under marketers’ con-
trol. Though we may need to admit that it is more difficult to monitor and
improve peer-to-peer interaction quality than service quality, we argue that
marketers can foster customer-to-customer interactions and help customers
disseminate useful knowledge that can influence others’ experience, which
is related to the notion of using customers as partial employees, to enhance
customer experience.
The relationship between perceived service quality and brand loyalty
has been validated numerous times (Boulding etal., 1993; Gremler & Brown,
1996) but the link between customer experience quality and customer loy-
alty has not been empirically validated yet. The present research makes a
theoretical contribution by providing empirical evidence for the link between
customer experience quality and customer loyalty. Customer experience
quality is relatively ignored or draws less attention compared to overall ser-
vice quality. Provided that customer service quality is considered a critical
factor to build loyalty, we suggest that managers should pay more attention
to creating a total customer experience quality than simply focusing on ser-
vice quality.
Third, the present study also suggests that the link between service
outcome quality and customer experience quality is stronger for men than
women, whereas the link between peer-to-peer quality and customer experi-
ence quality is stronger for women than men. The stronger link between
service outcome quality and customer experience quality for men indicates
that service outcomes are likely to lead to a more enriched customer experi-
ence for male than female customers. This is congruent with the previous
study, which proposed that men are more sensitive to the successful delivery
of the core service than women (Mattila, Grandey, & Fisk, 2003). On the
other hand, peer-to-peer quality, which is likely to be determined based on
interactions among customers, has more significant impact on customer
experience quality for women than men. Consistent with previous research
which posits that women are socialized to pay more attention to the rela-
tional aspects of interpersonal aspects of interpersonal encounter (Gilligan,
1982), the current study shows that interaction among customers have more
profound effect on customer experience quality for women than men.
334 H. Kim and B. Choi
Managerial Implications
There are several managerial implications. As illustrated when the results
validate the significant effect of customer experience quality on customer
loyalty, creating a high level of customer experience is of importance and
hence, managers may need to understand the factors which help enhance
customer experience quality. In an attempt to help managers in need of
looking for ways to create customer experience, the current study suggests
several antecedent of customer experience quality. First, the findings show
that service outcome quality, which is most likely to be determined based on
core services, has a positive effect on customer experience. For example, the
core services such as food, comfortable rooms, security, and facilities in the
case of hotel context have a significant effect on customer experience so if
the core services are not delivered properly, customer experience quality is
likely to be low.
Second, provided that the quality of the interpersonal interaction con-
sumers receive is identified one of determinants of customer experience
quality, we recommend that organization should devise their service strate-
gies to ensure a high level of interaction quality. For example, by offering the
right setting for the desirable interactions between customers and employees
who provide services, companies can help customers co-create their own,
unique experience by actively interacting with service providers. We also
suggest that service organizations have a system which can help encourage
employees to put more efforts into engaging with customers (e.g., an incen-
tive system, training, etc.).
Third, the peer-to-peer quality has a significant impact on customer
experience quality. This suggests that managers may need to monitor and
improve customers’ perception of peer-to-peer quality to create superior
customer experience. The present research suggests a well-designed portfo-
lio of strategies that employs “the notion of using customers as partial
employee” (Verhoef etal., 2009, p. 35) as a way to enhance peer-to-peer
quality. For example, in order to foster relationships among other customers,
marketers may need to provide environments where customers can interact
with each other and provide helpful information and tips to others (e.g.,
online/offline community).
At the same time, it may be important to prevent dysfunctional cus-
tomer behavior. Customers often destroy the experience of other customers
by cutting in line at amusement parks and providing abusive or insulting
behavior or words to other customers or employees. Such dysfunctional
behavior, which has been also termed “aberrant customer behavior” (Fullerton
& Punj, 1993), “problem customers” (Bitner, Booms, & Mohr, 1994), and “jay-
customers” (Lovelock, 1994, 2001) may not only directly disrupt functional
service encounters but also disrupt experience of other customers.
Furthermore, dysfunctional behavior may result in domino effects (Harris &
Customer Experience Quality and Behavioral Intentions 335
Reynolds, 2003). To prevent such disruptive behavior and encourage positive
interactions among customers, service organizations may need to have a
systematic management of customer experience such as posting dress codes
(e.g., dress codes which ban torn clothing, tank tops, and muscle shirts) and
grouping compatible customers by offering multiple sections (e.g., beginner-
vs. intermediate-level golfers).
Limitations and Future Research
To help with appropriate interpretation of the findings, the limitations of the
study must be discussed. First, the model used in the current study was
tested using a self-administered survey. Provided that subjects’ recall bias
might have influenced the results (Tax, Brown, & Chandrashekaran, 1998),
further research using an experiment may help enhance the validity of the
current findings. Nonetheless, we believe that the survey is appropriate in
the current context as a laboratory experiment, which is considered an alter-
native method to survey, and might have pitfalls as well. Secondly, the cur-
rent study is based on a survey of junior high and high school students. We
believe that future research, which could collect data across diverse subjects,
might help generalize the current findings. Third, the moderating effect of
gender on the relationship between interaction quality and customer experi-
ence quality was not significant unlike our expectation. Provided that women
are more sensitive to relational aspects of interpersonal encounters com-
pared to men, the results might be somewhat puzzling at first glance.
However, Mattila, Grandey, and Fisk (2003) suggested that the more focus on
the interactional aspect for women than men might be limited to negative
affective displays in interactions during service encounters. That is, both
male and female subjects might have a positive customer experience when
the service employees exhibit positive affective displays in interacting with
customers, which may explain the nonsignificant role of gender as a mod-
erator in the relationship between interaction quality and customer experi-
ence quality. Despite our effort to explain the seemingly puzzling findings,
we admit this is one of our limitations and hence, suggest that the moderat-
ing role of gender need to be examined further in various settings to validate
our arguments so we leave it to future research.
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