DOI: 10.1002/mar.21096
RESEARCH ARTICLE
The effect of service quality on customer satisfaction, loyalty,
and happiness in five Asian countries
Taeshik Gong1
Youjae Yi2
1 Hanyang University ERICA
2 Seoul National University
Correspondence
Taeshik Gong, College of Business and
Economics, Hanyang University ERICA,
55 Hanyangdaehak-ro, Sangnok-gu, Ansan
Gyeonggi-do, 15588, Republic of Korea.
Email: gongts@hanyang.ac.kr
Abstract
This research investigates and validates the cross-national applicability of a service quality model
in five Asian countries: China, Hong Kong, Japan, South Korea, and Singapore. The objectives of
this research are to establish whether or not a service quality model can be conceptualized in
the same way across Asian countries and to explore whether or not scores on the items can be
meaningfully compared among the Asian countries. The findings show that overall service quality has a positive influence on customer satisfaction, which in turn leads to customer loyalty and
customer happiness and that the general pattern of structural paths is valid in the five countries.
Furthermore, the comparisons of paths show that most of them are not significantly different
across the five countries. The results of this study reveal four key findings. First, customer wellbeing or happiness was driven by service quality. Second, customer loyalty was driven by service
quality across the five Asian countries, demonstrating that the economic values of service quality
could be applied to Asian countries just as they are in North American and European countries.
Third, customer satisfaction was driven by service quality. Fourth, customer income increased the
effect of service quality on customer happiness via customer satisfaction in China, Hong Kong, and
South Korea.
KEYWORDS
cross-national analysis, customer happiness, customer loyalty, customer satisfaction, service
quality
1
INTRODUCTION
models are relevant to Asia without an actual validation of model constructs. This assumption can lead to invalid cross-national inferences
As service quality models accumulate in North America and Europe
(Durvasula et al., 1993).
(Brady & Cronin, 2001; Grönroos, 1984; Parasuraman, Zeithaml, &
The purpose of this study is thus to test the applicability of service
Berry, 1988), so do questions concerning their applicability to Asia.
quality models to Asia. More specifically, the current study puts for-
These questions are even more pronounced as the world becomes
ward a service quality scale. This research investigates and validates its
an interdependent service marketing system and the globalization of
cross-national applicability in five Asian countries: China, Hong Kong,1
service businesses results in increased competition among multina-
Japan, South Korea, and Singapore. The objectives of this research are
tional firms. As such, it becomes increasingly important to examine
to establish whether or not a service quality model can be conceptu-
the cross-national applicability of service quality models developed in
alized in the same way across Asian countries and to explore whether
North America and Europe to Asia (Durvasula, Andrews, Lysonski, &
or not scores on the items can be meaningfully compared among the
Netemeyer, 1993; Netemeyer, Durvasula, & Lichtenstein, 1991). Most
Asian countries. Therefore, metric equivalence is analyzed. In addition,
constructs and theories of service quality have been developed and
this study examines whether the relationships among constructs in a
tested exclusively in North America and Europe. Thus, it is unknown
service quality model are applicable across Asian countries. Further-
whether the theory, constructs, measures, and relationships among
more, the present study conducts an importance–performance map
constructs are culturally bound. Although many scholars have called
analysis (IPMA) (Ringle & Sarstedt, 2016). IPMA contrasts the struc-
for an examination of the applicability of these theories to Asia (Blut,
tural model's total effects, representing the predecessor constructs’
2016; Collier & Bienstock, 2006), few studies have actually done so.
importance, with their average values of the latent variable scores
There is a need to test models cross-nationally because researchers
indicating their performance to identify predecessors that are rela-
have assumed that North America and Europe-based concepts and
tively more important to the target construct and highlight significant
Psychol Mark. 2018;35:427–442.
wileyonlinelibrary.com/journal/mar
c 2018 Wiley Periodicals, Inc.
427
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GONG AND YI
areas for improving management activities (Ringle & Sarstedt, 2016;
SERVPERF scale is efficient compared to the SERVQUAL scale. Fur-
Schloderer, Sarstedt, & Ringle, 2014). These findings, therefore, pro-
ther, they show that the analysis of the structural models supports
vide managers with specific information about measures they need to
the theoretical superiority of the SERVPERF scale. Expanding beyond
take to increase customer happiness (Hock, Ringle, & Sarstedt, 2010).
the question of “Is SERVPERF superior to SERVQUAL?” Park and Yi
In addition, while much of the extant research on service quality has
(2016) ask the question: “When is SERVPERF superior to SERVQUAL?”
focused on enhancing customer loyalty, little research has focused on
By comparing the two approaches from an analytic perspective,
increasing social performance such as customer happiness and well-
Park and Yi (2016) show that SERVPERF is superior to SERVQUAL
being. That said, lately there has been a substantially increased inter-
when the effect of performance on customer satisfaction is greater
est in examining the relationship between service quality and customer
than the effects of expectation on performance and customer satis-
well-being. Interestingly, recent research has called for more focus on
faction or when customers are heterogeneous in the evaluation of
improving customer well-being through transformative service. This
expectation.
topic was one of 12 service research priorities (Ostrom et al., 2015).
Third, Brady and Cronin (2001) adopt Rust and Oliver (1994) view
Therefore, the present research examines how service quality affects
that customers evaluate service quality based on three dimensions: (1)
customer happiness. This study also tests the moderating role of cus-
the customer–employee interaction, (2) the physical environment, and
tomer income in the relationship between overall service quality and
(3) the outcome. In addition, they adopt Dabholkar (1996) view that
customer happiness through customer satisfaction. The article opens
service quality has a hierarchical factor structure. More specifically,
by reviewing the literature on the conceptualization and measurement
Dabholkar (1996) proposes that customers think of service quality at
of service quality models. The research methodology is explained, fol-
different levels, such as the dimension level and the overall level. They
lowed by an analysis of empirical research. Finally, the findings are dis-
argue that service quality dimensions are distinct but highly correlated.
cussed and the managerial implications are drawn.
Thus, they conclude that service quality dimensions share an underlying theme and that a common higher-order factor is present, which is
called overall service quality. In their effort to synthesize these concep-
2
THEORY AND HYPOTHESES
2.1
Service quality model
tualizations, Brady and Cronin (2001) propose the hierarchical service
quality model. Here, service quality is viewed as a hierarchical factor
structure. That is, there is a common higher order factor called overall
service quality, and it consists of three dimensions: performance qual-
In the service marketing literature, there has been considerable
ity, delivery quality, and physical environment quality. Since this is the
progress in discussing how service quality should be measured. First,
first measure synthesizing all major prior conceptualizations, it is the
Grönroos (1984) argues that service quality consists of two dimen-
most fruitful approach to service quality assessment to date (Dagger,
sions: technical quality and functional quality. Technical quality refers
Sweeney, & Johnson, 2007; Pollack, 2009; Yi & Gong, 2008).
to what customers receive as a result of their interactions with a ser-
According to Grönroos (1984), the performance (outcome) quality
vice firm. This aspect can be called the outcome quality dimension. On
dimension refers to the result of the service transaction. It is con-
the other hand, functional quality represents how the service is deliv-
cerned with what the customer actually receives from the service
ered. In other words, the way service employees interact with cus-
transaction. Prior studies show that performance quality is a signifi-
tomers has an impact on customers’ view of the service. This aspect is
cant determinant of overall service quality and the addition of outcome
called the interaction quality dimension.
quality significantly improves the explanatory power and predictive
Second, Parasuraman et al. (1988) propose five dimensions of ser-
validity of the service quality model (Powpaka, 1996). Furthermore,
vice quality. More specifically, (1) tangibles are appearances of physical
Bolton and Drew (1991) assert that service performance levels are
elements, (2) reliability is dependable and accurate performance, (3)
inputs to customers’ perceptions of overall service quality. In addition,
responsiveness is promptness and helpfulness, (4) assurance is cred-
Brady and Cronin (2001) argue that there is a consensus that the per-
ibility, security, competence, and courtesy, and (5) empathy is easy
formance quality of a service encounter significantly affects customer
access, good communication, and customer understanding. To measure
perceptions of overall service quality. Thus, the following hypothesis is
service quality, they develop a survey instrument called SERVQUAL,
proposed:
which is based on the premise that customers evaluate a firm's service quality by comparing their perceptions of its service with their
own expectations (Sivakumar, Li, & Dong, 2014). That is, SERVQUAL
H1:
Perceptions of the quality of service performance directly contribute to overall service quality perceptions.
measures the service quality as the gap between expectation and per-
Service delivery quality focuses on customers’ perception of the
formance. Meanwhile, Cronin and Taylor (1992) point out that lit-
employee–customer interactions that take place during service deliv-
tle theoretical and empirical evidence supports the relevance of the
ery (Grönroos, 1984). Interpersonal interactions have an influence
expectations–performance gap as the basis for measuring service qual-
on customer perceptions of overall service quality because of the
ity. Instead, they argue the superiority of simple performance-based
intangibility and inseparability of services (Brady & Cronin, 2001).
measures of service quality (Babakus & Boller, 1992; Park & Yi, 2016).
More specifically, customers evaluate overall service quality based on
Accordingly, they develop the performance-only measure (SERPERF)
their perception of employees’ responsiveness, empathy, reliability,
as an alternative to the SERVQUAL measure. They conclude that the
and professionalism (Ekinci & Dawes, 2009). Choi and Kim (2013) also
429
GONG AND YI
suggest that interpersonal interactions have a critical impact on cus-
H4:
esis is proposed:
H2:
Overall service quality is positively related to customer satisfaction.
tomer perception of overall service quality. Thus, the following hypothH5:
Customer satisfaction is positively related to customer loyalty.
Perceptions of the quality of service delivery directly contribute
to overall service quality perceptions.
2.3
Customer happiness
Brady and Cronin (2001) report that services require the cus-
Service has been firmly established as a critical means for enhancing
tomer to be present during the process and that the surrounding
firm performance. Furthermore, service now dominates the lives of
physical environment can serve as an important basis for customers’
consumers and therefore marketers have the opportunity to improve
evaluations of the overall quality of the service encounter. Baker,
consumer happiness and begin to concentrate on enhancing customer-
Parasuraman, Grewal, and Voss (2002) show that the physical store
related outcomes as well (Anderson et al., 2013; De Keyser & Lariviere,
environment can affect customer service quality evaluations. Bitner
2014). The primary focus of service marketing has thus shifted from
(1992) argues that the physical environment, such as the type of office
satisfying customer needs to enhancing customer happiness. In
furniture and the décor, may influence a client's beliefs about a lawyer's
other words, the purpose of service marketing has been broadened
performance or overall service evaluations because the perceived
and centered on the improvement of customer happiness beyond
servicescape elicits cognitive responses. In-store cleanliness is asso-
customer satisfaction (Sirgy, Samli, & Meadow, 1982). This emerging
ciated with the service quality of a shopping environment. Customers
area has been referred to as transformative service research, which
utilize environmental cues to make inferences about the quality of
is defined as any research that investigates the relationship between
products/services (Chao, 2008). Thus, the following hypothesis is
service and customer happiness aiming at improving the lives of
proposed:
customers (Anderson & Ostrom, 2015). In a similar manner, a social
H3:
Perceptions of the quality of the service environment directly
contribute to overall service quality perceptions.
marketing perspective emphasizes that marketing should deliver value
to customers in a way that improves customers’ happiness. Therefore,
under the social marketing concept, firm performance is measured
by social outcomes such as customer happiness (Su, Swanson, &
2.2
Service quality and its consequences
Researchers see service quality as having an important influence
Chen, 2016). Furthermore, the social marketing concept assesses the
societal impact of service marketing on customer happiness (Dagger &
Sweeney, 2006).
on customer satisfaction, customer loyalty, and customer happiness.
Customer happiness is conceptualized as customers’ perception of
According to Lazarus's theory of emotion and adaptation (Lazarus,
the extent to which their well-being and quality of life are enhanced.
1991), the appraisal processes of situational conditions lead to emo-
Thus, customer happiness reflects the culmination of customers’
tional responses, which in turn induce coping activities: appraisal →
subjective evaluation of their current life circumstances (Dagger &
emotional response → coping (Bagozzi, 1992). Adapting this theory to
Sweeney, 2006; De Keyser & Lariviere, 2014; Hellén & Sääksjärvi,
a service context, it is likely that the overall service quality appraisal
2011). Dagger and Sweeney (2006) point out that a series of ser-
precedes emotional responses such as customer satisfaction. Further,
vice encounters results in perceptions that form the basis of cus-
in the presence of a particular emotion, coping responses such as intent
tomers’ satisfaction evaluation, which in turn leads to customer reac-
to maintain and enjoy the outcome are possible (e.g., customer loyalty
tions such as customer happiness. In addition, Sweeney, Danaher, and
and customer happiness) (Cronin, Brady, & Hult, 2000). The service
McColl-Kennedy (2015) suggest that customer satisfaction with con-
literature reports empirical results suggesting that customer satisfac-
crete events spills over to life domains, which in turn leads to cus-
tion is an intervening variable that mediates the relationship between
tomer happiness. In a similar logic, the bottom-up theory of customer
overall service quality perception and customer loyalty (Taylor & Baker,
happiness states that customer satisfaction with the specific service
1994). In addition, Szymanski and Henard (2001) conduct a meta-
encounter spills over upward to the overall service satisfaction, which
analysis and document that performance (e.g., overall service quality)
in turn spills over upward to the most superordinate domain of cus-
positively affects customer satisfaction and that the outcome of cus-
tomer life satisfaction such as customer happiness (Neal, Uysal, & Sirgy,
tomer satisfaction is customer loyalty (e.g., word-of-mouth and repur-
2007).
chase intentions). Furthermore, Hellier, Geursen, Carr, and Rickard
Although the extensive body of research on customer loyalty has
(2003) find that overall service quality influences customer satisfac-
focused primarily on benefits to the firm, customer loyalty can also
tion, which in turn leads to customer loyalty. Early research identifies
result in benefits to the customer in the form of customer happiness
customer satisfaction as the main predictor of customer loyalty (Hume
(Aksoy et al., 2015). According to Aksoy et al. (2015), the primary
& Mort, 2010; Patterson, Johnson, & Spreng, 1997; Sweeney, Soutar, &
role of customer loyalty is to make customers happy because the core
Johnson, 1999).
principle of customer loyalty is to connect friends and family, which
All in all, it is expected that overall service quality is an antecedent
are the primary determinants of customer happiness (Nicolao, Irwin,
of customer satisfaction and that satisfied customers are more likely
& Goodman, 2009). Gilbert (2005) asserts that friends and families
to engage in positive word-of-mouth and repurchase (Pollack, 2009).
offer strong social connections, interactions, and a sense of security,
Thus, the following hypotheses are proposed:
all contributing to customer happiness. Furthermore, customer loyalty
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GONG AND YI
Performance
service quality
Delivery
service quality
Customer
loyalty
H1
H2
H5
Overall
service quality
H4
Customer
satisfaction
H3
H7
H6
Customer
happiness
Environment
service quality
FIGURE 1
Conceptual framework
is driven by the interactions that customers develop with employees,
The demographics of the sample are presented in Table 1 The sam-
which in turn lead to customer happiness. All individuals have needs
ple consists of 175 (China), 178 (Hong Kong), 172 (Japan), 180 (South
for belonging and interdependence, and these needs can be fulfilled
Korea), and 174 (Singapore) valid responses. The unit of analysis of
through customer loyalty, which can be defined as a desire to maintain
this study is an individual shopper who had made three purchases
the relationship (Aksoy et al., 2015). In addition, customers develop
within three months at a major department store at the time of data
affectionate bonds with services, which in turn lead to customer loy-
collection. Self-administered questionnaires were used as the method
alty, which is argued to be a catalyst for customer happiness (Yim, Tse,
of data collection. The potential respondents were approached when
& Chan, 2008). This view is also supported by Orth, Limon, and Rose
they were leaving department stores and asked to participate in a short
(2010) who find that customer loyalty toward the service arouses cus-
survey by a study assistant. They were informed about the investiga-
tomer happiness. Furthermore, a customer's interaction with the ser-
tion and told that the individual responses were to be kept strictly con-
vice employee may arouse positive emotions, which in turn lead to
fidential. A study assistant waited while participants completed the
customer loyalty. Interestingly, rewarding experiences with services
research questionnaires.
through customer loyalty make the customer feel better. Finally, hap-
As the survey was conducted in five countries, five versions of the
piness results from customers’ repeated experience with services, that
questionnaire were administered. The questionnaire, originally writ-
is, customer loyalty (Bettingen & Luedicke, 2009). Thus, the following
ten in English, was translated into Mandarin Chinese, Cantonese Chi-
hypotheses are proposed:
nese, Japanese, and Korean by bilingual people whose native language
H6:
Customer satisfaction is positively related to customer happiness.
H7:
Customer loyalty is positively related to customer happiness.
Figure 1 provides a conceptual model of service quality and illustrates the hypothesized relationships among the key constructs.
was Mandarin Chinese, Cantonese Chinese, Japanese, or Korean,
respectively. These translated questionnaires were then translated
back into English by another bilingual person whose native language
was Mandarin Chinese, Cantonese Chinese, Japanese, or Korean,
respectively. These two English versions were then compared and no
item was found to contain a specific cultural context in terms of language (Brislin, 1980). The questionnaire was pretested with 20 shoppers at the department store, and there were no major problems with
understanding or wording.
3
METHOD
3.2
3.1
Sample and procedures
Instrumentation
The research derived measures for key constructs from existing scales
Data were collected through a survey that was distributed to con-
in the literature. All constructs were measured with items using 9-point
sumers in each of the five countries: China, Hong Kong, Japan, South
Likert scales ranging from 1 = strongly disagree to 9 = strongly agree.
Korea, and Singapore. Quota sampling was used to generate samples
Measurement scales for all constructs are summarized in Table 2. Ser-
that were representative of the population in terms of age and gender.
vice quality questions were from Dabholkar, Thorpe, and Rentz (1996)
China, Hong Kong, Japan, South Korea, and Singapore served as the
as well as Brady and Cronin (2001). More specifically, performance ser-
countries of study because they share similar cultural values and norms
vice quality was measured by six items that assessed the availability,
(Hofstede, Hofstede, & Minkov, 2010). Finding differences between
quality, differentiation of merchandise, the extent to which service was
countries with similar cultural backgrounds allows us to make a more
customer-oriented, and the extent to which new products were pro-
convincing argument than conducting the same study across countries
vided compared to others. Delivery service quality was measured by
that differ greatly in cultural background. Moreover, using countries
six items that assessed the extent to which employees gave prompt,
with highly disparate cultural backgrounds could introduce significant
courteous, individual, voluntary, and knowledgeable service to cus-
biases into our samples, which could limit the possibility of generalizing
tomers. In addition, these items assessed the extent to which employ-
the findings.
ees were able to handle customer complaints directly and immediately
431
GONG AND YI
TA B L E 1
Demographic profile of respondents
Percent
China
Gender
Age
Education level
Hong Kong
Japan
South Korea
Singapore
Male
25.71
25.84
26.16
26.10
25.86
Female
74.29
74.16
73.84
73.90
74.14
20–29
18.28
17.98
18.02
18.30
18.39
30–39
31.43
31.46
31.98
31.70
31.61
40–49
31.43
31.46
31.98
31.70
31.61
50–59
18.86
19.10
18.02
18.30
18.39
Secondary
10.28
41.01
18.02
27.80
38.51
Bachelor
74.86
48.88
73.26
63.80
50.00
Master/Ph.D.
14.86
10.11
8.72
8.70
11.49
on the site. Environment service quality was measured by six items that
Henseler, Ringle, & Sarstedt, 2015; Voorhees, Brady, Calantone, &
assessed the extent to which the department store had a professional,
Ramirez, 2016). The composite reliabilities for all variables exceed the
modern-looking, and convenient appearance. In addition, these items
cutoff value of 0.70, and the AVE for all focal variables exceeds the 0.50
assessed the extent to which customers perceived a positive physical
benchmark, demonstrating that each construct has acceptable psycho-
environment, parking places that were large and convenient, and a lay-
metric properties. In support of the convergent validity of the scales,
out that made it easy to find products.
all indicators load significantly (p < 0.05) and substantially (>0.70) on
Overall service quality and customer satisfaction were measured
their hypothesized factors (see Table 2). Furthermore, all HTMT val-
using a one-item scale because these constructs are easily understood
ues are lower than the threshold value of 0.85. In addition, neither of
and imagined (e.g., overall service quality, overall customer satisfac-
the 95% bias-corrected and accelerated confidence intervals (CIs) of
tion) (Bergkvist & Rossiter, 2007; Rossiter, 2002). Customer loyalty
the HTMT ratio of correlations statistic includes the value 1.00 (see
was measured by a two-item scale. These items were “I will say posi-
Table 3), thus supporting discriminant validity.
tive things about XYZ to other people” and “I intend to continue doing
This study relies on one source of data, that is, ratings by customers,
business with XYZ” (Zeithaml, Berry, & Parasuraman, 1996). Finally,
so potential common method bias is statistically controlled (MacKen-
customer happiness was measured by two items, “My quality of life is
zie, Podsakoff, & Jarvis, 2005). First, following the procedure suggested
enhanced by doing business with XYZ” and “I think XYZ contributes
by Williams and Anderson (1994), a method factor was added with
to customers’ happiness” (Dagger & Sweeney, 2006; Sweeney et al.,
all indicators for all latent variables loading on this factor. The struc-
2015).
tural results are consistent with the original structural model for all five
countries. This study also implemented the procedure used by Liang,
Saraf, Hu, and Xue (2007). The results show that method factor load-
4
RESULTS
ings are not significant and the ratio of substantive variance to method
variance is more than 100:1 for all five countries, which means that
The present study used the SmartPLS 3 software (Ringle, Wende,
common method bias is not a serious issue.
& Becker, 2015) to validate the measurement model and test the
Henseler, Ringle, and Sarstedt (2016) advocate the test of mea-
hypotheses. Partial least squares structural equation modeling (PLS-
surement invariance before performing a multigroup analysis between
SEM) is a composite-based approach to structural equation modeling
two or more groups when using SEM. They suggest the measurement
(SEM) that forms composites as linear combinations of their respec-
invariance of composites (MICOM) that is suitable for PLS-SEM. Given
tive indicators, which in turn serve as proxies for the conceptual vari-
that the current study aims to compare a model over two groups
ables (Hair, Hult, Ringle, & Sarstedt, 2017). Recent research argues
via PLS-SEM, MICOM was adopted. MICOM is a three-step process
that employing modeling constructs as composites is a more realistic
involving (1) configural invariance assessment (i.e., equal parameteri-
approach to measurement (Sarstedt, Hair, Ringle, Thiele, & Gudergan,
zation and way of estimation), (2) compositional invariance assessment
2016). Furthermore, this study focuses on predicting customer satis-
(i.e., equal indicator weights), and (3) assessment of equal means and
faction, customer loyalty, and customer happiness via service quality,
variances. If configural and compositional invariance are established,
which calls for the use of PLS-SEM as a prediction-oriented approach
partial measurement invariance is also established. If partial measure-
to SEM (Hair, Hult, Ringle, Sarstedt, & Thiele, 2017).
ment invariance is confirmed, one can compare the path coefficient
Assessment of the measurement models includes composite reli-
estimates across the groups.
ability to evaluate the internal consistency and average variance
Step 1 of the MICOM procedure, configural invariance, was estab-
extracted (AVE) to evaluate the convergent validity. Assessment
lished because the PLS path model setups are equal across the five
of measurement models also involves discriminant validity. The
countries, and group-specific model estimations draw on identical
heterotrait–monotrait (HTMT) ratio of correlations can be used to
algorithm settings. Next, to establish compositional invariance (step
examine discriminant validity (Hair, Hult, Ringle, & Sarstedt, 2017;
2), the original composite score correlation c was compared with the
0.87
0.90
0.88
0.70
0.70
2. XYZ offers high quality
merchandise.
3. The service of XYZ is
customer-oriented.
4. I achieve my purpose
when I use the service of
XYZ.
5. XYZ continuously
provides new products
compared to others.
6. XYZ provides
differentiated services
that others do not.
0.83
0.84
0.87
0.87
0.92
0.86
1. Employees of XYZ have
the knowledge to answer
customers’ questions.
2. Employees of XYZ are
consistently courteous
with customers.
3. XYZ gives customers
individual attention.
4. The attitude of XYZ's
employees demonstrates
their willingness to help
me.
5. Employees of XYZ give
prompt services to
customers.
6. Employees of XYZ are
able to handle customer
complaints directly and
immediately.
Delivery
0.86
1. XYZ has merchandise
available when the
customers want it.
Performance
Loadings
China
Measurement model
Construct/indicator
TA B L E 2
0.96
0.92
Reliability
0.70
0.67
AVE
0.90
0.93
0.93
0.94
0.92
0.89
0.75
0.78
0.88
0.87
0.87
0.88
Loadings
Hong Kong
0.97
0.93
Reliability
0.84
0.67
AVE
0.89
0.91
0.83
0.89
0.90
0.88
0.78
0.70
0.86
0.87
0.88
0.83
Loadings
Japan
0.96
0.92
Reliability
0.78
0.67
AVE
0.90
0.93
0.92
0.89
0.90
0.82
0.79
0.72
0.87
0.90
0.86
0.86
Loadings
South Korea
0.96
0.93
Reliability
0.80
0.70
AVE
Singapore
0.84
0.91
0.85
0.92
0.92
0.89
0.75
0.73
0.75
0.83
0.89
0.79
Loadings
0.96
0.91
Reliability
(Continues)
0.79
0.63
AVE
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GONG AND YI
(Continued)
0.88
0.9
0.82
0.74
3. XYZ has modern-looking
equipment and fixtures.
4. XYZ has clean, attractive,
and convenient public
areas (restrooms, fitting
rooms).
5. XYZ provides plenty of
convenient parking for
customers.
6. The store layout of XYZ
makes it easy for
customers to find what
they need.
0.95
2. I intend to continue
doing business with XYZ.
0.94
0.94
1. My quality of life is
enhanced by doing
business with XYZ.
2. I think XYZ contributes
to customers’ happiness.
Customer happiness
0.95
1
1. I will say positive things
about XYZ to other
people.
Customer loyalty
1. Overall, I am satisfied
with XYZ.
Customer satisfaction
1. I believe XYZ offers
excellent service.
1
0.86
2. I would rate XYZ's
physical environment
highly.
Overall service quality
0.86
Loadings
China
1. Employees of XYZ have a
neat, professional
appearance.
Environment
Construct/indicator
TA B L E 2
Reliability
0.96
0.94
1
1
0.93
AVE
0.92
0.89
1
1
0.70
0.96
0.96
0.95
0.94
1
1
0.81
0.88
0.87
0.88
0.88
0.89
Loadings
Hong Kong
Reliability
0.96
0.95
1
1
0.95
AVE
0.92
0.90
1
1
0.75
0.96
0.96
0.91
0.88
1
1
0.71
0.76
0.87
0.84
0.90
0.89
Loadings
Japan
Reliability
0.96
0.90
1
1
0.93
AVE
0.92
0.81
1
1
0.70
0.96
0.97
0.96
0.96
1
1
0.70
0.82
0.85
0.86
0.88
0.82
Loadings
South Korea
Reliability
0.96
0.96
1
1
0.92
AVE
0.93
0.92
1
1
0.67
0.96
0.97
0.96
0.96
1
1
0.75
0.79
0.90
0.88
0.90
0.89
Loadings
Singapore
Reliability
0.97
0.97
1
1
0.94
AVE
0.94
0.94
1
1
0.73
GONG AND YI
433
434
GONG AND YI
TA B L E 3
Discriminant validity assessment results
Variable
Performance
Delivery
Environment
Service quality
Customer satisfaction
Customer loyalty
Customer happiness
China
[0.78, 0.92]
Hong Kong
[0.79, 0.91]
Japan
[0.84, 0.94]
South Korea
[0.68, 0.88]
Delivery
Singapore
[0.73, 0.87]
China
[0.67, 0.89]
Hong Kong
[0.76, 0.88]
[0.75, 0.87]
Japan
[0.57, 0.81]
[0.56, 0.82]
Environment
Service quality
Customer satisfaction
Customer loyalty
[0.71, 0.89]
South Korea
[0.56, 0.79]
[0.55, 0.82]
Singapore
[0.69, 0.86]
[0.79, 0.92]
China
[0.72, 0.93]
[0.71, 0.88]
[0.56, 0.83]
Hong Kong
[0.71, 0.85]
[0.79, 0.89]
[0.75, 0.86]
Japan
[0.71, 0.85]
[0.70, 0.84]
[0.69, 0.85]
South Korea
[0.74, 0.87]
[0.74, 0.86]
[0.58, 0.79]
Singapore
[0.63, 0.84]
[0.66, 0.86]
[0.68, 0.86]
China
[0.75, 0.92]
[0.66, 0.84]
[0.55, 0.80]
[0.74, 0.91]
Hong Kong
[0.72, 0.85]
[0.80, 0.89]
[0.68, 0.83]
[0.76, 0.84]
Japan
[0.71, 0.86]
[0.71, 0.85]
[0.66, 0.83]
[0.79, 0.86]
South Korea
[0.70, 0.88]
[0.76, 0.88]
[0.55, 0.77]
[0.71, 0.84]
Singapore
[0.58, 0.81]
[0.61, 0.84]
[0.52, 0.82]
[0.75, 0.94]
China
[0.78, 0.95]
[0.63, 0.84]
[0.60, 0.85]
[0.68, 0.86]
[0.73, 0.87]
Hong Kong
[0.63, 0.82]
[0.68, 0.84]
[0.67, 0.82]
[0.79, 0.89]
[0.77, 0.89]
Japan
[0.77, 0.95]
[0.72, 0.89]
[0.76, 0.96]
[0.72, 0.87]
[0.69, 0.85]
South Korea
[0.62, 0.83]
[0.66, 0.84]
[0.59, 0.86]
[0.66, 0.83]
[0.69, 0.85]
Singapore
[0.46, 0.72]
[0.56, 0.82]
[0.60, 0.82]
[0.70, 0.84]
[0.64, 0.83]
China
[0.78, 0.97]
[0.71, 0.92]
[0.61, 0.88]
[0.69, 0.87]
[0.71, 0.86]
[0.70, 0.87]
Hong Kong
[0.74, 0.88]
[0.80, 0.91]
[0.72, 0.86]
[0.74, 0.86]
[0.73, 0.85]
[0.72, 0.87]
Japan
[0.73, 0.88]
[0.65, 0.83]
[0.75, 0.88]
[0.63, 0.84]
[0.62, 0.84]
[0.73, 0.85]
South Korea
[0.57, 0.77]
[0.68, 0.82]
[0.57, 0.78]
[0.65, 0.82]
[0.63, 0.83]
[0.71, 0.85]
Singapore
[0.59, 0.83]
[0.55, 0.81]
[0.61, 0.83]
[0.71, 0.86]
[0.69, 0.86]
[0.75, 0.90]
Notes: The numbers in brackets are the 95% bias-corrected and accelerated confidence intervals of the HTMT statistic.
empirical distribution of the composite score correlation resulting
invariance, the samples from five countries were compared by means
from the permutation procedure (cu ) with 1000 permutations and a
of multigroup analysis. In the first step, the omnibus test of group dif-
5% significance level for each combination of countries. If c exceeds the
ferences was applied to assess if the path coefficients are equal across
5% quantile of cu , compositional invariance is established. The results
the five groups. The analysis reveals that, in respect of all five structural
in Table 4 show that partial measurement invariance is established
model relations, the null hypothesis that the seven path coefficients
among all five countries, thus allowing for a multigroup analysis that
are equal across the five groups can be rejected. These results suggest
compares the path coefficients among the samples from these five
that, in respect of all relationships, at least one path coefficient differs
countries to identify significant differences. However, this study did
from the remaining four across the five countries (Sarstedt, Henseler,
not assess the equality of the composite mean values and variances
& Ringle, 2011). Next, Table 6 shows the differences in seven path
(step 3) because the purpose of this study is to focus on cross-country
coefficient estimates across five countries and provides the results of
comparisons and not to pool the data.
multigroup comparison. The analysis shows that path coefficient esti-
R2
Table 5 lists the beta coefficients for five countries, along with the
mates are partially invariant across the samples from five countries, as
value for each endogenous construct. The models demonstrate
only two path coefficient estimates are significantly different.
good explanatory power, as the R2 values range from 0.53 to 0.87
Furthermore, this study uses an IPMA to extend the PLS-SEM
(Henseler, Hubona, & Ray, 2016). The bootstrapping analyses using
results by taking the performance of each construct into account. The
5000 samples show that all the path coefficients are significant, sup-
results permit the identification of determinants with a relatively high
porting all the hypotheses. Finally, in light of the partial measurement
importance and relatively low performance. These determinants with
435
GONG AND YI
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.998
0.999
1.000
1.000
0.997
0.999
1.000
tively. When the IPMA results are analyzed, the prioritization of man-
2014). Figures 2–6 show the IPMA results for five countries, respecagerial activities of high importance becomes obvious.
0.999
1.000
1.000
1.000
(Figure 2 shows that in comparison with other service quality dimensions, the performance quality's importance is the highest. In other
words, a one-unit increase in the performance quality's performance
from 70.22 to 71.22 would increase the performance of customer
happiness by 0.47 points. Hence, when managers wish to improve
1.000
1.000
1.000
1.000
1.000
0.999
1.000
1.000
1.000
0.997
1.000
0.997
1.000
0.998
0.997
1.000
More specifically, the importance–performance map for China
1.000
c
c
5%
Quantile of
cu
5%
Quantile of
cu
5%
Quantile of
cu
that should be addressed by marketing activities (Schloderer et al.,
the performance of customer happiness by means of overall service
1.000
1.000
ity because this construct has the highest importance among service
1.000
1.000
1.000
1.000
1.000
0.999
0.999
1.000
1.000
0.999
0.998
1.000
5%
Quantile of
cu
c
quality, their first priority should be to improve performance qual-
that delivery quality has the highest importance among service qual-
quality dimensions. On the other hand, Figure 3 for Hong Kong shows
ity dimensions but a relatively low performance. Thus, it is obvious
1.000
1.000
1.000
1.000
Kong. Interestingly, Figure 4 shows that environment quality has the
highest importance among service quality dimensions and a relatively
high performance in Japan. Thus, improvement of delivery quality is
not a top priority in Japan. In addition, Figure 5 shows that in South
Korea, delivery quality and performance quality are important, but
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.999
1.000
0.999
1.000
0.999
1.000
0.998
1.000
1.000
1.000
c
c
that improvement of the delivery quality is a top priority for Hong
5%
Quantile of
cu
Hong Kong vs.
South Korea
Hong Kong vs.
Singapore
Japan vs. South
Korea
Japan vs.
Singapore
South Korea vs.
Singapore
high importance and low performance are major improvement areas
their performance is rather low. Therefore, managers in South Korea
1.000
0.999
1.000
1.000
1.000
1.000
1.000
0.999
0.999
1.000
1.000
0.998
0.999
1.000
Therefore, resources should be equally allocated to service quality
sions are rather similar in terms of their importance and performance.
dimensions in Singapore. Beyond service quality dimensions, across
1.000
1.000
tomer loyalty has the second highest importance, and overall service
quality is the third priority, except for in Japan.
In addition to the theoretically hypothesized paths illustrated in
Notes: If c < 5% quantile of cu , compositional invariance requirements are violated.
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Customer
happiness
Customer loyalty
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Customer
satisfaction
1.000
1.000
1.000
1.000
0.999
1.000
1.000
1.000
0.998
1.000
1.000
0.999
0.998
1.000
0.999
1.000
0.999
1.000
1.000
1.000
Service quality
Environment
0.998
1.000
0.999
1.000
0.998
1.000
1.000
1.000
1.000
0.998
1.000
0.999
0.998
1.000
0.999
1.000
Delivery
c
c
c
sions. Lastly, Figure 6 shows that in Singapore, service quality dimen-
five countries, customer satisfaction has the highest importance, cus-
Performance
c
c
5%
Quantile of
cu
5%
Quantile of
cu
5%
Quantile of
cu
5%
Quantile of
cu
5%
Quantile of
cu
China vs. South
Korea
China vs. Japan
China vs. Hong
Kong
Variable
TA B L E 4
Measurement invariance (MICOM) assessment
China vs.
Singapore
Hong Kong vs.
Japan
should devote efforts toward improving these service quality dimen-
Figure 1 this study also tests the potential moderating effect on
the key path in an exploratory way. The current research performs
this analysis with customer income, which was measured by asking
“how much money does your household earn monthly?” (1 = less
than 150 USD, 2 = 151–200 USD, 3 = 201–250 USD, 4 = 251–
300 USD, 5 = 301–400 USD, 6 = 401–500 USD, 7 = 501–600 USD,
8 = 601–700 USD, 9 = 701–800 USD, and 10 = more than 801
USD). Prior research argues that people with higher income tend to
be happier than those with lower income because those with higher
income are better able to fulfill their aspirations and feel better off
(Blanchflower & Oswald, 2004; Easterlin, 2001). Previous research
also shows that upper-income customers have lower expectations
about service quality than middle- and lower-income customers, which
in turn increase customer satisfaction and customer happiness (Scott &
Shieff, 1993).
Therefore, this study tested the moderating effect of customer
income on the relationship between overall service quality and customer happiness mediated by customer satisfaction. A moderated
mediation analysis was performed using the PROCESS macro (Model
14; Hayes, 2015), with overall service quality as the independent variable, customer satisfaction as the mediator, customer income as the
436
GONG AND YI
TA B L E 5
Results of the country-specific structural model
Path relationships
China
Hong Kong
Japan
South Korea
Singapore
H1: Performance→service quality
0.34***
0.14***
0.31***
0.38***
0.28***
H2: Delivery→service quality
0.35***
0.48***
0.25**
0.38***
0.28**
H3: Environment→service quality
0.23***
0.30***
0.36***
0.16*
0.32***
H4: Service quality→customer satisfaction
0.89***
0.90***
0.93***
0.89***
0.87***
H5: Customer satisfaction→customer loyalty
0.75***
0.78***
0.76***
0.74***
0.73***
H6: Customer satisfaction→customer happiness
0.35***
0.48***
0.18*
0.39***
0.41***
H7: Customer loyalty→customer happiness
0.50***
0.34***
0.69***
0.44***
0.48***
R2
Service quality
0.69
0.73
0.71
0.72
0.66
Customer satisfaction
0.80
0.81
0.87
0.80
0.76
Customer loyalty
0.57
0.61
0.59
0.55
0.53
Customer happiness
0.64
0.61
0.71
0.60
0.68
Notes: * p < 0.05; ** p < 0.01; *** p < 0.001.
second-stage moderator, and customer happiness as the dependent
loyalty, and happiness, are applicable across the five countries in Asia
variable. As Table 7 shows, the results suggested a significant inter-
considered in this study. The service quality model has been developed
action effect between customer satisfaction and customer income in
in countries such as the United States and Europe, and there has been a
three countries: China, Hong Kong, and South Korea. The index of mod-
need for testing this model in Asian countries. By doing so, researchers
erated mediation indicated that CI did not include zero in China (CI
could examine the applicability of the service quality model to Asian
[0.04, 0.07]), Hong Kong (CI [0.00, 0.07]), and South Korea (CI [0.01,
countries. The cross-cultural psychology literature suggests that the
0.04]). In other words, the indirect effect of service quality on customer
metric invariance and the relationships among constructs in a model
happiness via customer satisfaction is moderated by customer income
must be established for a model to be applicable across countries
in these three countries. In contrast, the index of moderated media-
(Durvasula et al., 1993). Accordingly, this study used a national-
tion included zero in Japan (CI [−0.04, 0.04]) and Singapore (CI [−0.03,
level analysis and a multigroup analysis to examine the model cross-
0.03]), and the interaction effect of customer satisfaction and customer
nationally in five Asian countries. The results suggest that overall ser-
income was insignificant, suggesting no moderation effect of customer
vice quality has a positive influence on customer satisfaction, which in
income (Hayes, 2015).
turn leads to customer loyalty and customer happiness, and that the
To probe the moderation of the indirect effect, a spotlight analysis
general pattern of structural relationships is valid for the five countries.
was run (Spiller, Fitzsimons, Lynch, & McClelland, 2013). Using the beta
Furthermore, the comparisons of paths show that most of them were
coefficient estimates, the bottom of Table 7 shows the indirect effect
not significantly different across five countries. However, there were
of service quality on customer happiness via customer satisfaction at
two paths that were significantly different. For instance, the path from
low (−1 SD), moderate (mean), and high (+1 SD) levels of customer
performance quality to overall service quality was significantly differ-
income. Focusing on the three countries with significant moderation
ent between China and Hong Kong. In addition, the path from customer
effects (i.e., China, Hong Kong, and South Korea), the indirect effects of
satisfaction to customer happiness was significantly different between
service quality on customer happiness via customer satisfaction were
Hong Kong and Japan.
all significant at low (−1 SD), moderate (mean), and high (+1 SD) levels
It can be noted that this research is the first cross-national com-
of customer income. Furthermore, the indirect effect was stronger for
parative study of service quality and customer satisfaction in the five
customers with higher income. For example, in Hong Kong, the effect is
Asian countries. According to a review of cross-cultural customer stud-
0.23 when customer income is low (one SD below the mean), whereas it
ies, most previous studies involve only two countries (Sin, Cheung, &
is 0.41 when customer income is high (one SD above the mean). A sim-
Lee, 1999). Thus, previous studies may have limited value compared
ilar pattern was found in China and South Korea. Taken together, cus-
to studies done in several countries. Studies done in several countries
tomer income seems to increase the effect of service quality on cus-
could provide researchers a deeper understanding of the effects of
tomer happiness via customer satisfaction in China, Hong Kong, and
country on service quality models. Hence, this study empirically exam-
South Korea.
ined the service quality model using data collected from five Asian
countries: China, Hong Kong, Japan, South Korea, and Singapore. Overall, the results support the proposed model of service quality for China,
5
CONCLUSION AND IMPLICATIONS
Hong Kong, Japan, South Korea, and Singapore. As expected, service
performance, service delivery, and service environment were found
The current study examines whether the relationships between ser-
to be determinants of overall service quality perceptions. In addition,
vice quality and its consequences, such as customer satisfaction,
overall service quality perceptions were found to be a determinant of
0.18
0.26
0.02
0.01
0.16
0.21
Delivery→
service quality
Environment→
service quality
Service quality→
customer
satisfaction
Customer
satisfaction→
customer loyalty
Customer
satisfaction→
customer
happiness
Customer loyalty→
customer
happiness
Notes: ** p < 0.01; *** p < 0.001.
0.44
Performance→
service quality
│diff
0.83
0.93
0.62
0.75
0.99
0.92
0.00***
0.14
0.14
0.00
0.05
0.33
0.05
0.26
0.91
0.09
0.48
0.97
0.99
0.36
0.02
0.11
0.07
0.03
0.01
0.13
0.08
0.19
0.16
0.72
0.32
0.62
0.84
0.72
0.06
0.07
0.09
0.04
0.01
0.29
0.02
0.29
0.23
0.82
0.26
0.43
0.44
0.44
0.89
0.34
0.30
0.02
0.03
0.07
0.24
0.19
0.99
0.00**
0.38
0.85
0.77
0.93
0.95
0.09
0.09
0.04
0.01
0.14
0.10
0.25
0.77
0.25
0.22
0.43
0.09
0.20
0.99
0.14
0.07
0.05
0.03
0.02
0.21
0.15
0.90
0.24
0.18
0.29
0.58
0.55
0.94
0.25
0.21
0.02
0.04
0.20
0.13
0.07
0.88
0.95
0.97
0.99
0.65
0.95
0.78
0.21
0.22
0.04
0.06
0.04
0.03
0.04
0.92
0.98
0.28
0.11
0.35
0.59
0.37
0.04
0.02
0.01
0.02
0.16
0.10
0.10
0.78
0.99
0.99
0.87
0.43
0.65
0.55
│p-value
South Korea vs.
Singapore
│p-value │diff
Japan vs.
Singapore
│p-value │diff
Japan vs. South
Korea
│p-value │diff
Hong Kong vs.
Singapore
│p-value │diff
Hong Kong vs.
South Korea
│p-value │diff
Hong Kong vs.
Japan
│p-value │diff
China vs.
Singapore
│p-value │diff
China vs. South
Korea
│p-value │diff
China vs. Japan
│p-value │diff
China vs. Hong
Kong
Multigroup comparison test results
Relationship
TA B L E 6
GONG AND YI
437
438
GONG AND YI
80
80
75
75
70
Performance
Environment
SQ
65
CS
Delivery
60
Performance
Performance
Loyalty
55
50
0.0
0.1
0.2
0.3
0.4
0.5
Importance
0.6
0.7
SQ
Performance
CS
Delivery
60
0.0
0.1
0.2
0.3
0.4
0.5
Importance
0.6
0.7
0.8
F I G U R E 5 Importance–performance map analysis for South Korea
[Color figure can be viewed at wileyonlinelibrary.com]
80
75
70
Environment
65
Performance
Loyalty
75
Loyalty
SQ CS
Delivery
60
Performance
Performance
65
50
0.8
80
Environment
70
Delivery
65
CS
SQ
Performance
60
55
55
50
0.0
0.1
0.2
0.3
0.4
0.5
Importance
0.6
0.7
0.8
F I G U R E 3 Importance–performance map analysis for Hong Kong
[Color figure can be viewed at wileyonlinelibrary.com]
80
0.0
0.1
0.2
0.3
0.4
0.5
Importance
0.6
0.7
0.8
F I G U R E 6 Importance–performance map analysis for Singapore
[Color figure can be viewed at wileyonlinelibrary.com]
that can be accomplished by means of general convergence (Calantone,
Schmidt, & Song, 1996).
75
Performance
Loyalty
Environment
55
F I G U R E 2 Importance–performance map analysis for China [Color
figure can be viewed at wileyonlinelibrary.com]
50
70
Because of the recent increase in the globalization of the service
Loyalty
70
Environment
65
business, marketers have a growing need for cross-national constructs
SQ CS
and measures that are reliable, valid, and applicable across countries.
Globalization of markets has resulted in increased competition among
Delivery
60
Asian brands. Maintaining consistently high quality services is a pow-
Performance
erful means of increasing the overall performance of a global Asian
55
enterprise (Ostrom et al., 2015). Measures with sound psychometric
50
0.0
0.1
0.2
0.3
0.4
0.5
Importance
0.6
0.7
0.8
FIGURE 4
Importance–performance map analysis for Japan [Color
figure can be viewed at wileyonlinelibrary.com]
properties across Asian countries will facilitate service marketing
strategies in Asian markets (Netemeyer et al., 1991). This study examines the measures of service quality, customer satisfaction, customer
loyalty, and customer happiness in a cross-national context. Strong
support for these constructs’ psychometric properties is found across
five Asian countries.
customer satisfaction. Customer satisfaction was found to be a deter-
Given recognition of the impact of service marketing on social per-
minant of customer loyalty and customer happiness. Finally, customer
formance (e.g., transformative service research, customer well-being
loyalty was found to be a determinant of customer happiness. These
or happiness) (Anderson et al., 2013), the present study represents an
results provide strong evidence for the cross-country stability of the
important step forward. The results of this study reveal three key find-
service quality model (Cadogan, Diamantopoulos, & De Mortanges,
ings. First, social performance, such as customer happiness, was driven
1999). Cook and Campbell (1979) note that to demonstrate robust
by service quality. This finding makes a key contribution to the service
causal relationships, using one sample of respondents is not appropri-
literature, extending the understanding of service co-creation beyond
ate. The current study tests the model using data collected from five
economic indicators. This finding is significant, especially because
countries to increase the confidence of a robust causal relationship
the role of customer happiness as an outcome of service quality is
439
GONG AND YI
TA B L E 7
Conditional indirect effects of service quality on customer happiness through customer satisfaction
Country
China
Predictor
Hong Kong
Japan
South Korea
Singapore
Effect
Customer satisfaction
Constant
0.19
0.51**
0.29
0.60***
1.16***
Service quality
0.95***
0.92***
0.96***
0.91***
0.84***
Constant
1.18
2.47**
0.89
0.86
0.93
Customer happiness
Customer satisfaction
0.36*
0.09
0.25
0.33*
0.36*
Service quality
0.41***
0.51***
0.47*
0.39***
0.45***
Income
−0.13
0.24*
0.02
−0.04
0.05
CS × Income
0.02*
0.04*
0.01
0.02*
−0.00
Income
Boot indirect effect
−1 SD
0.37 CI [0.15, 0.62]
0.23 CI [0.01, 0.47]
0.26 CI [−0.05, 0.59]
0.35 CI [0.18, 0.57]
0.29 CI [0.11, 0.52]
Mean
0.41 CI [0.20, 0.63]
0.32 CI [0.13, 0.56]
0.27 CI [−0.02, 0.57]
0.36 CI [0.22, 0.61]
0.29 CI [0.14, 0.52]
+1 SD
0.45 CI [0.21, 0.71]
0.41 CI [0.21, 0.65]
0.30 CI [−0.03, 0.61]
0.43 CI [0.24, 0.65]
0.28 CI [0.13, 0.54]
Index of moderated mediation
0.02 CI [0.04, 0.07]
0.03 CI [0.00, 0.07]
0.01 CI [−0.04, 0.04]
0.02 CI [0.01, 0.04]
−0.00 CI [−0.03, 0.03]
Notes: * p < 0.05; ** p < 0.01; *** p < 0.001.
not well investigated, despite the growing interest in transformative
service quality and internal processes. The proposed scales could be
service, which enhances customer happiness (Garma & Bove, 2011;
used as diagnostic tools to identify specific areas where improve-
Guo, Arnould, Gruen, & Tang, 2013; Mick, Pettigrew, Pechmann, &
ments are needed and pinpoint aspects of the firm's service quality
Ozanne, 2012). Apparently, there is a need for firms to move beyond
that require work. In addition, the service quality scale can easily be
financial performance and evaluate firm performance according to
added to the annual satisfaction survey or questionnaires for loyalty
social performance. Second, customer loyalty was driven by service
programs. Service quality information would be useful for managers in
quality across the five Asian countries, demonstrating that the eco-
investigating customer happiness or well-being. Databases containing
nomic values of service quality could be applied to Asian countries as
the level of service quality could be used to enhance the level of cus-
well as North American and European countries. Third, individual per-
tomer happiness (Hellén & Sääksjärvi, 2011).
formance, such as customer satisfaction, was driven by service quality.
This paper also shows that customer income can influence the indi-
All in all, the present study highlights the crucial role of service quality
rect effect of overall service quality on customer happiness through
in enhancing social, firm, and individual performances by meeting cus-
customer satisfaction. Specifically, customer income is found to mod-
tomer needs during service co-creation. This understanding makes an
erate the mediating effect of customer satisfaction on customer hap-
important contribution to service research.
piness. Nevertheless, the moderating effect of customer income var-
The findings of this study highlight the value of measuring service
ied across countries; the moderation effect was significant in China,
quality, primarily because service quality enhances customer satisfac-
Hong Kong, and South Korea, but not in Japan and Singapore. That
tion, customer loyalty, and customer happiness. The three dimensions
is, although the overall service quality model is robust across the
of service quality (performance, delivery, and environment) were found
countries, the particular moderation effect of customer income varies
to influence overall service quality universally for five Asian countries.
across the countries. Furthermore, in the three countries where the
Nevertheless, the relative importance of the three quality dimensions
moderating effect of customer income exists, customer income tends
seems to vary slightly across the five countries. Thus, managers should
to magnify the effect of customer satisfaction on customer happiness.
have flexibility and strategy in resource allocation when they want to
That is, as customer income increases, the importance of customer sat-
increase overall service quality depending on the countries in which
isfaction becomes higher in achieving customer happiness. Consider-
they operate. Indeed, performance quality, delivery quality, and envi-
ing that little research has investigated the moderating role of cus-
ronment quality play a key role in the development of overall service
tomer income in the service quality model, the findings of this study
quality, which in turn increases customer satisfaction, customer loy-
might be meaningful.
alty, and customer happiness. Nevertheless, managers should focus
This study is not without limitations. It only addresses one service
on improving specific service quality dimensions based on the find-
(the department store). Future studies should seek to extrapolate the
ings of IPMA of this study. For that purpose, managers might want
analysis into other service areas. Further research should also con-
to segment their Asian customer base according to levels of service
sider the role that unobservable traits such as personality or lifestyle
quality. Such segmentation would enable firms to allocate a larger
play in explaining service quality and customer happiness. It could be
amount of resources to customers who need more support in forming
argued that segments identified by means of specific unobservable
positive customer happiness. Further, they should constantly monitor
variables are usually more homogenous and their customers respond
440
consistently to marketing actions, but customers in these segments are
difficult to identify from variables that are measured (Schloderer et al.,
2014). Using a similar logic, it is possible that the importance of various
service quality factors differs with regard to how often they visit the
department store due to habituation effects. Future research should
therefore consider this issue by segmenting the data along such behavioral variables (Hock et al., 2010). The study also presents a crosssectional evaluation of service quality, but a longitudinal study could
enrich the findings and generate a deeper understanding of the dynamics of service quality (Rindfleisch, Malter, Ganesan, & Moorman, 2008).
Future research using experiments may detect accurately more the
causality between service quality, customer satisfaction, customer loyalty, and customer happiness.
ACKNOWLEDGMENT
This work was supported by the research fund of Hanyang University
(HY-2017-G).
ENDNOTE
1 Although
Hong Kong is a part of China, it is politically & culturally distinct from China. It is a separately administered region that has its own
currency and culture. Hence it is treated as a different country in this
paper.
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How to cite this article: Gong T, Yi Y. The effect of service quality on customer satisfaction, loyalty, and happiness in five Asian
countries. Psychol Mark. 2018;35:427–442. https://doi.org/
10.1002/mar.21096