Customer-perceived value and loyalty: how do key service quality

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Serv Bus
DOI 10.1007/s11628-015-0269-y
EMPIRICAL ARTICLE
Customer-perceived value and loyalty: how do key
service quality dimensions matter in the context of B2C
e-commerce?
Ling Jiang • Minjoon Jun • Zhilin Yang
Received: 11 April 2013 / Accepted: 3 February 2015
Ó Springer-Verlag Berlin Heidelberg 2015
Abstract This paper develops a research model to examine the effect of e-service
quality dimensions on customer-perceived value and customer loyalty. Based on a
survey of 235 online customers, we identify five key e-service quality dimensions:
care, reliability, products portfolio, ease of use, and security. Our empirical results
show that all the five dimensions have significant and positive impacts on customerperceived value which, in turn, increases customer loyalty. We further examine the
mediating role of customer-perceived value in the relationship between each
e-service quality and customer loyalty. The results suggest that customer-perceived
value plays a partially mediating role in the effect of ease of use, care, product
portfolio, and reliability on customer loyalty, and a fully mediating role in the
relationship between security and customer loyalty. Managers may be in a position
to benefit by employing the model presented in this study in an effort to improve
service performance and, hence, retain customers.
Keywords E-Service quality Customer-perceived value Customer loyalty B2C e-commerce Service quality dimensions
Ling Jiang, Minjoon Jun and Zhilin Yang contributed equally to this work.
L. Jiang
School of Business, Macau University of Science and Technology, Avenida Wai Long, Taipa,
Macau
e-mail: [email protected]
M. Jun
Management Department, College of Business, New Mexico State University, Las Cruces, NM,
USA
e-mail: [email protected]
Z. Yang (&)
Department of Marketing, City University of Hong Kong, Kowloon, Hong Kong
e-mail: [email protected]
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L. Jiang et al.
1 Introduction
The relationship between customer loyalty and its antecedents has been intensively
examined (e.g., Ibanez et al. 2006; McMullan and Gilmore 2008; Wang 2010; Zeng,
et al. 2009). One issue, in particular, has assumed the status of special importance,
in light of the accelerating expansion in the volume of companies and customers
embracing e-commerce as a method of operation: How can an organization
effectively retain online customers and sharpen its competitive advantage?
The literature provides a logical point of departure. In their conceptual study,
Parasuraman and Grewal (2000) propose a quality-value-loyalty chain model in a
traditional ‘‘bricks-and–mortar’’ business setting, where three factors––service
quality, product quality, and price––determine customer-perceived value and, in
turn, high customer-perceived value generates loyalty. The authors have raised two
important questions for future research directions: ‘‘Can this same conceptual model
be applied to technology-based environments?’’ and ‘‘What is the role of key
e-service quality in this chain?’’
Researchers have long examined the antecedents of customer loyalty in the
traditional brick-and-mortar environment. Relatively modest research effort,
however, has been focused on how key dimensions of e-service quality affect
customer loyalty through the mediation role of customer-perceived value. We posit
that not all service quality attributes have equal impacts on customer-perceived
value and loyalty (e.g., Yang et al. 2005). It is imperative, therefore, to uncover,
among various potentially predictive service quality attributes, particular dimensions that are most crucial in enhancing customer-perceived value and customer
loyalty, and to assess the degree to which they are associated.
The study thus intends to address these central research questions in the context
of business-to-consumer (B2C) e-commerce. Utilizing the Parasuraman and
Grewal’s (2000) conceptual model as a reference point, we examined the linkages
between customer-perceived e-service quality dimensions, customer-perceived
value, and customer loyalty in the B2C e-commerce context. More specifically,
the present study sought to (1) identify the salient e-service quality dimensions; (2)
examine the relationships between the derived e-service quality dimensions and
customer-perceived value; (3) investigate the association between customerperceived value and customer loyalty; and (4) determine if each key e-service
quality dimension has a direct or indirect effect on their loyalty.
2 Conceptual framework and hypothesis development
Based on the literature review, we construct a research model of customer-perceived
service quality (mainly five key e-service quality dimensions identified in this
study)––customer-perceived value-customer loyalty chain (see Fig. 1). The major
findings of prior research addressing the key constructs of this study are discussed
below.
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Customer-perceived value and loyalty
Key e-Service Quality
Dimensions
Care
Reliability
Perceived
Value
Product
Portfolio
Ease of
Use
Customer
Loyalty
Security
Fig. 1 Conceptual model
2.1 Identifications of key e-service quality dimensions
It is a formidable task to identify the key e-service quality dimensions because of
tremendous number of studies in this arena. To select salient dimensions of
e-service quality in our research setting of B2C e-commerce, we first consider the
theoretical foundation of B2C e-commerce. Scholars have posited that online
services involve interactions between customers and online information systems
(e.g., Yang et al. 2004; Yang et al. 2005). Drawn from this theoretical springboard,
we review two streams of literature. One is the service quality literature, mainly the
SERVQUAL model developed from the traditional service setting (Parasuraman
et al. 1988). The other is the information system and Web site design quality
literature, which concentrates on computer and networking-based impersonal
interactions. Among numerous dimensions of e-service quality, we only consider
those attributes that are empirically validated, applicable for our research setting,
and are salient in their effects on either customer-perceived service quality or
customer loyalty.
Key Quality Dimensions Related to Customer Services. The well-known
SERVQUAL model (Parasuraman et al. 1988) encompasses appearance of physical
facilities, equipment, and personnel (tangible), willingness to help customers and
provide prompt service (responsiveness), ability to perform the promised service
dependably and accurately (reliability), knowledge and courtesy of employees and
their ability to convey trust and confidence (assurance), and approachability, ease of
contact, and making the effort to know customers and their needs (empathy)
(Parasuraman et al. 1988). Numerous inquiries have sought to apply the
SERVQUAL model to discover the attributes of services that contribute most
significantly to quality assessments in the online service environment (e.g. Ho and
Lin 2010; Lee and Lin 2005; Wolfinbarger and Gilly 2003; Yang et al. 2005; Yang
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and Peterson 2004; Yen and Lu 2008). These empirical studies have demonstrated
that the SERVQUAL’s service quality dimensions can be incorporated into the
online setting with appropriate modifications. For example, the tangible dimension
approximates the Web site design quality aspects instead of physical facilities,
equipment, and personnel.
In addition to the dimensions derived from the SERVQUAL model, we further
identify one salient dimension, Product Portfolio, through literature review and our
focus groups with online consumers. The role of product portfolio in determining
e-service quality has been less empirically studied though it has been discussed
frequently and is significantly important (Page and Lepkowska-White 2002;
Srinivasan et al. 2002; Yang et al. 2004). Many online customers are inclined to
patronize firms which offer a substantial variety of goods and services. The primary
reason for this preference is that it is more likely that diverse needs can be fulfilled
when they arise. This is especially acute for desired products which are not widely
distributed or are unavailable at conveniently located physical outlets (Barcia 2000).
Thus, a strategy for gaining customer satisfaction and loyalty may be to provide a
mix of offerings preferred by target customers. Cho and Park (2001) have identified
‘‘variety of products’’ as one of the seven major dimensions that influence Internet
shopper satisfaction. Further, Page and Lepkowska-White (2002) have pointed out
that a suitable selection of products and services is one of the important ingredients
for developing consumer value in online companies. In the same vein, Srinivasan
et al. (2002) have found that online customer loyalty is positively influenced by a
wide product mix and a great variety of products within any given category.
Another major reason for customer use of the Internet as a purchasing channel is
convenience (Jiang et al. 2013). When possible, many customers prefer to fulfill
their diverse purchasing needs at one site––‘‘one stop shopping’’. For example,
some online banking customers wish to pay bills electronically and automatically,
view and print monthly bank statements, and purchase stocks, insurance, and other
financial offerings at one Web site. Thus, companies offering a wide range of
products may be able to attract incremental numbers of customers to their Web sites.
Key Quality Dimensions Related to Online Systems. Most commercial Web sites
function as structured and well-defined information systems comprising browsers,
search engines, encryption, other e-commerce software, and databases. To measure
end-users’ satisfaction with information systems, Doll and Torkzadeh (1988) have
developed twelve items that gage five quality dimensions influencing end-user
satisfaction. These dimensions are content, accuracy, format, ease of use, and
timeliness. The reliability and validity of the scale which they have produced has
been confirmed in other studies (Doll et al. 1994; Hendrickson and Collins 1996).
Subsequently, several inquiries have been undertaken to identify Web sites
attributes which are critical to business success (e.g., Chiu et al. 2005; Li 2007;
Yang et al. 2005). For example, Yang et al. (2005) discovered six dimensions of
Web portal service quality: usefulness of content, adequacy of information, usability
(i.e., user friendliness), accessibility, privacy/security, and interaction. All the
dimensions have a significant effect on online service quality and customer
satisfaction. Among various aspects of online systems quality, two dimensions, ease
of use and security/privacy, have been widely acknowledged as critical in shaping
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Customer-perceived value and loyalty
consumer perceptions of information systems quality (Cox and Dal, 2001; Jiang
et al. 2013; Li 2007; Yang et al. 2005; Zeithaml et al. 2002).
2.2 The effect of key e-service quality dimensions on customer-perceived value
Customer-perceived value has its root in equity theory which relates the ratio of the
consumer’s outcome/input to that of the service provider’s outcome/input (Oliver
and DeSarbo 1988). Equity refers to customer evaluation of what is ‘‘fair,’’ ‘‘right,’’
or ‘‘deserved’’ (benefit) for the perceived cost of the offering (Bolton and Lemon
1999). Perceived costs include monetary payments and other sacrifices such as time
consumption and consumer stress. Outcomes in equity theory are compared to
sacrifices and rewards received by the other party (ies) to an exchange. In this sense,
customer-perceived value results from an overall evaluation of the rewards and
sacrifices associated with the service.
Equity theory is relevant in the e-commerce context, where it is essential for the
company to establish an ongoing relationship with a client base. Customers are
likely to feel equitably treated if they believe the ratio of their outcome to inputs is
comparable to the ratio of outcome to inputs accruing to the company (Oliver and
DeSarbo 1988). Further, customers often benchmark a company’s ratio of outcome
to inputs by comparing these to ratios for competitors’ offerings. Due to rigorous
online competition and the relative ease of instant comparisons, customer values
have become more critical in retaining customer loyalty (Yang and Peterson 2004).
From this perspective, the present study focuses on service performance as the key
reward, and perceived costs as key sacrifices associated with an exchange.
Customer-perceived overall service quality has been regarded to have a
significant and positive relationship with customer-perceived value (Cronin et al.
2000). In the context of B2C e-commerce, it is not clear whether or not each salient
e-service quality dimension significantly affects customer-perceived value. Among
the very few studies focusing on the antecedents of customer-perceived value in the
context of e-commerce, Chen and Dubinsky (2003) find that three e-service quality
attributes, ease of use of the Web site, relevant information, and customer service,
along with product quality, collectively and positively affect customer-perceived
value through customer experience. They further argue that relevant information
provided by the Web site and quality customer service offered by human Web
assistants whose task is to assist customers in Web shopping are perceived by
consumers to be useful and valuable. On the other hand, unfriendly online user
interfaces may lead them to feel confused and ultimately develop negative feelings
about the e-shopping experience. From an information system perspective, Teo
et al. (2003) find that efficiency and effectiveness of information systems are the key
determinants of user-perceived overall value. Based on these limited studies
devoted to revealing the effect of various e-service quality dimensions on customerperceived value, we are able to tentatively postulate,
H1 Each key e-service quality dimension has a significant, positive impact on
Customer-perceived value.
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2.3 Customer-perceived value and customer loyalty
Customer loyalty is attitudinally measured in terms of (1) customers’ intention to
continuously or increasingly conduct business with their present company, and (2)
their inclination to recommend the company to other persons (Boulding et al. 1993;
Zeithaml et al. 1996). Prior research efforts have identified customer-perceived
value as a major precursor of customer loyalty. In the setting of e-commerce, high
value is one of the primary motivations for customer patronage (Chen and Dubinsky
2003; Tsao and Tseng 2011; Zeng, et al. 2009). In the empirical study of online
customer services, Yang and Peterson (2004) have confirmed that customer value
exerts a positive effect on customer loyalty. Customer-perceived value is not
necessarily directly related to price. A company may assess a premium price for an
offering, but if it attaches useful services to the core products, customers may
perceive the value of this service as superior to competitor’s offerings. According to
equity theory, everything else being equal, high customer-perceived value can
significantly increase customer loyalty (Oliver and DeSarbo 1988). Therefore,
H2 Customer-perceived value has a significant, positive impact on customer
loyalty.
2.4 E-service quality dimensions and loyalty
Loyalty may be influenced by a positive level of satisfaction toward the service
provider. In a traditional business setting, many researchers have found a positive
relationship between service quality perceptions and customer loyalty (e.g., Cronin
et al. 2000; Pollack 2009; Ranaweera and Neely 2003; Zeithaml et al. 1996).
Scholars have recently examined this relationship in the context of B2C
e-commerce. Heim and Sinha (2001) have investigated the relationship between
customer loyalty and the order procurement and order fulfillment processes of
e-retailers. They have found that six variables, website navigation, product
information, price, product availability, timeliness of delivery, and ease of return,
have a significant and positive association with customer loyalty. All of the six
variables, except for price, relate to e-service quality dimensions. Focusing on
Internet as a self-service technology, Yen and Gwinner (2003) have found that four
factors of e-service quality, perceived control, convenience, efficiency, and
performance of the technology, have significant and positive effects on customer
loyalty through two mediating variables, confidence and special treatment benefits.
Zhang and Prybutok (2004) have demonstrated that customer-perceived service
quality and two online systems quality attributes, namely Web design and ease of
use, have a significant and positive association with customer loyalty. Furthermore,
Srinivasan et al. (2002) have empirically found that the greater the levels of care,
choice, customization, customer cultivation, community, and positively perceived
character of the e-retailer, the greater the e-loyalty of the customer. A thorough
review of the e-service quality literature indicates that different key e-service
quality dimensions identified by various empirical studies seem to exert a significant
effect on customer loyalty. Therefore,
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H3a Each key e-service quality dimension has a direct and positive impact on
customer loyalty.
In line with the quality-value-loyalty chain model proposed by Parasuraman and
Grewal (2000), customer-perceived value exerts a mediating effect on the
relationship between service quality and customer loyalty. In terms of the role of
key e-service quality dimensions, we posit that they can affect either customerperceived value or loyalty. In addition, customer-perceived value has a significant
effect on customer loyalty. Thus, the remaining issue is: Will customer-perceived
value play a partially or fully mediating role in the relationships between each key
service quality dimension and customer loyalty? No prior study has investigated the
issue. Following the analytic procedure for testing mediating effects proposed by
Baron and Kenny (1986) and our H1, H2, H3a, we propose
H3b Customer-perceived value plays a partially mediating role in the relationships between key dimensions of e-service quality and customer loyalty.
3 Method
3.1 Samples and data collection
Our sampling frame consisted of e-retailing and financial customers with personal
e-mail addresses provided by an online e-mail address broker. An e-mail solicitation
letter was forwarded to 4000 subjects randomly selected from the e-mailing list. The
message described the research purpose and invited each receiver to participate in
the online survey. A total of 1101 e-mails were returned as undeliverable. Of 257
responses, 22 were eliminated because they were incomplete or duplicated (The ISP
address of each respondent has been checked) responses. Thus, the effective sample
size was 235 and the effective response rate was 8.1 % (235 of 2899). Since the
number of collected useable responses was sufficient for further data analysis,
follow-up e-mails were not sent. No comparison was made between early and late
responses for checking non-response bias, since appropriately 90 % of the responses
were garnered within 5 days after the initial e-mail.
3.2 Profile of respondents
Of the 235 respondents, 144 subjects answered the questions based on their online
finance service experiences (i.e., e-banking and online stock brokerage) and the
remaining 91 responded based on their e-retailing service experiences. Approximately, 80.8 % of the respondents were male; 76.9 % were between the ages
of 25 and 54; 68.0 % had earned a bachelor’s degree or higher; and 40.1 % earned
an annual household income of US $ 70,000 or above. The characteristics of these
respondents were similar to Internet user profiles gathered in other studies (e.g.,
Kehoe et al. 1999; Sheehan and Hoy 2000).
As to the computer and Internet usage profile, 90.2 % of the sample had been
using personal computers for more than 6 years; 94.1 % reported that they logged
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Table 1 Means, standard deviations, and correlation matrices
Means
S.D.
1
2
3
4
5
6
1. Care
4.27
0.71
1.00
2. Reliability
3.56
0.73
0.52**
1.00
3. Product portfolio
3.76
0.70
0.63**
0.36**
1.00
4. Security
3.80
0.71
0.45**
0.56**
0.36**
1.00
5. Ease of use
3.63
0.74
0.47**
0.55**
0.42**
0.51**
6. Customer loyalty
3.59
0.80
0.65**
0.50**
0.41**
0.40**
0.47**
1.00
7. Customer perceived
value
3.56
0.65
0.37**
0.35**
0.36**
0.35**
0.42**
0.66**
7
1.00
1.00
** p \ 0.01 (2-tailed)
onto the internet at least once a day on average; and 64.6 % spent more than 6 h per
week on browsing Web sites. Table 1 lists means and standard deviations of all the
constructs and correlations among them.
3.3 Measures
The research instrument was developed based upon the mostly validated measures
of prior studies. To ensure content and face validity of the measure, a pretest of the
questionnaire was conducted to assess the face validity of the measurement scales.
Five academics and four local professionals, who are specialized in e-commerce,
reviewed the scales and, based on their feedback, some items were reworded, added,
or deleted. Next, the questionnaire was forwarded by an e-mail attachment to 50
online customers selected from two news groups: online financial investment and
e-commerce. A total of 14 respondents replied with useful suggestions. Based on
their feedback, the questionnaire was further revised and finalized.
A total of 37 scale items assessing the key constructs of the present study were
developed and included in the survey. A total of 16 items adapted from the
SERVQUAL measures were used to gage the five quality dimensions related to
customer service except for tangibility, inasmuch as its measurement items are
highly relevant to online services. The scale of product portfolio consisted of three
items. The first two items, range and variety of product offerings, were adapted from
the scale developed by Szymanski and Hise (2000). The last was designed to
measure the degree of Internet-related free services (e.g., message board). For the
two dimensions of online systems quality, ease of use and security, we adapted
measures from Cox and Dale (2001) and Liu and Arnett (2000). The ease of use
construct, measured by four items, covered usability of a Web site, organization and
structure of online content, ease of conducting transactions, and adequateness of
content. The security dimension, assessed by three items, focused on the risk and
safety of e-transactions and privacy of personal information.
We measured customer-perceived value using an adapted version of a scale verified
by Levesque and McDougall (1996). The scale, consisting of five items, indicates that
customers tend to compare what they received from a company with (1) what a
competitor could offer and (2) what they pay (Oliver and DeSarbo 1988). Previous
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Customer-perceived value and loyalty
studies have measured the construct of customer loyalty by examining their behavioral
intentions: (1) consumer willingness to recommend the company (Parasuraman et al.
1988, 1991; Zeithaml et al. 1996), and (2) repurchase intention (Boulding et al. 1993;
Zeithaml et al. 1996). The scale, consisting of six items, was adapted from
Parasuraman et al. (1991) and Zeithaml et al. (1996). The items measured customers’
willingness to recommend the company and their repurchase intention. For each scale
item, a five-point Likert scale was used, anchored by ‘‘1 = strongly disagree’’ and
‘‘5 = strongly agree’’ with ‘‘3 = neutral: neither agree nor disagree’’ as the midpoint.
3.4 Measurement validation
We employed Anderson and Gerning’s (1988) two-step approach to evaluate the
convergent validity for modeled constructs. We first ran exploratory factor analysis
to assess the underlying factor structure of the scale items. A total of 26 scale items
addressing the specific characteristics of customer service quality, online systems
quality, and product portfolio were subjected to a series of factor analyses. The
initial factor analysis extracted six factors. We further eliminated those items that
did not load strongly on any factor (below 0.5) or had cross-loadings. Six items were
deleted after four iterations. The retained 20 items were factor analyzed again. Five
factors were generated. All items in a scale loaded strongly on one factor and
weakly on all the other factors, thereby satisfying the requirements of convergent
and discriminant validity (Cohen et al. 1992). The issue of common method
variance was then found to be no problem in that the first factor failed to comprise a
majority of the variance and there was no general factor in the unrotated factor
structure (Podsakoff and Organ 1986).
In the second phase, confirmatory factor analysis was performed. It indicated that all
factor loadings were greater than the recommended 0.4 cut-off and were statistically
significant (Nunnally and Bernstein 1994). (See Table 2). Other fit indexes also indicate
that the model fitted the data reasonably well. The internal validity of the measurement
model appears to be adequate as the composite reliability of each construct is above 0.7
and the average variance extracted (AVE) of each measure extracted more than or equal
to 50 % of the variance (Bagozzi and Yi 1988; Fornell 1992). These indicators show the
fit of the measurement model to the aggregate data. Therefore, we further ran the
structural model to reveal the relationships among the constructs.
4 Results
We tested our hypotheses using the structural equation model. As shown in Table 3,
All the major fit indexes indicate that the structural model fits well. The five
independent variables, care, reliability, product portfolio, ease of use, and security,
have statistically significant and positive relationships with customer-perceived
value at the significant level of p \ 0.05. Therefore H1 is supported. Insofar as the
relative impact of the service quality dimensions on customer-perceived value is
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L. Jiang et al.
Table 2 CFA results of measures
Constructs and scale items
Load-ing
T-value
1. The contact employees understand my specific needs.
0.80
14.65
2. Company employees comply with my requests.
0.68
11.22
Care
3. The company gives me individual attention.
0.77
13.03
4. Top management gives me personal attention when I
encounter serious problems.
0.82
16.92
5. Company employees have the knowledge to answer
my questions.
0.79
15.44
6. Company employees properly handle any problems
that arise.
0.91
17.77
0.92
18.82
Reliability
1. My online transactions are always accurate.
2. The company keeps my records accurately.
0.63
16.09
3. The company performs the service correctly the first
time.
0.84
16.46
4. When the company promises to do something by a
certain time, it does so.
0.64
15.92
1. Using the company’s web site requires a lot of effort
(R).
0.61
10.14
2. The organization and structure of online content is
easy to follow.
0.68
11.22
3. It is easy for me to complete a transaction through the
company’s web site.
0.77
13.03
4. The company’s web pages have the contents that
meet my needs.
0.90
16.32
1. I feel the risk associated with online transactions is
low.
0.75
12.74
2. I feel secure in providing sensitive information for
online transactions.
0.68
11.22
3. I feel safe in my online transactions.
0.89
16.17
1. The company provides me many useful free services.
0.75
12.74
2. The company provides wide ranges of product
packages.
0.69
11.22
3. The company provides services with the features I
want.
0.77
13.03
1. Compared to alternative companies, the company
offers attractive product costs.
0.58
9.56
2. Compared to alternative companies, the company
charges me fairly for similar products/services.
0.87
9.28
3. Compared to alternative companies, the company
provides more free services.
0.55
8.85
Ease of use
Security
Product portfolio
Customer-perceived value
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CR
AVE
a
0.85
0.58
0.86
0.84
0.58
0.84
0.76
0.51
0.81
0.72
0.56
0.83
0.82
0.50
0.61
0.89
0.57
0.80
Customer-perceived value and loyalty
Table 2 continued
Constructs and scale items
Load-ing
T-value
4. Comparing what I pay to what I get, I think the
company provided me with good value.
0.95
19.00
5. Comparing what I pay to what I might get from other
competitive companies, I think the company provides
me with good value.
0.86
16.21
1. I say positive things about the company to other
people.
0.91
18.00
2. I would recommend the company to those who seek
my advice about such matters.
0.81
13.86
3. I would encourage friends and relatives to use the
company.
0.93
18.93
4. I would post positive messages about the company on
some Internet message board.
0.80
14.72
5. I intend to continue to do business with the present
company.
0.45
5.52
6. I intend to do more business with the present
company.
0.69
11.73
Customer loyalty
CR
AVE
a
0.90
0.63
0.91
Model fit indices
v2 = 196.80 (P = 0.00), d.f. = 108, v2/d.f. = 1.82, RMSEA = 0.06, GFI = 0.93, CFI = 0.98,
NFI = 0.97, NNFI = 0.97
CR composite reliability; AVE average variance extracted
concerned, the ease of use dimension is the most significant independent variable
with the largest standardized beta coefficient (b = 0.28), followed by care
(b = 0.26), product portfolio (b = 0.22), and two ties, reliability (b = 0.15) and
security (b = 0.13). The relatively low R2 reflects that the five dimensions of
e-service quality only account for a portion of customer-perceived value. Other
factors such as price and product quality may also play a critical role in customer
perception of service value.
Customer-perceived value exerts a significant and positive effect on customer
loyalty (b = 0.46). Thus, H2 is supported. Our H3a and H3b examined the direct
effect and mediating effect of key e-service quality dimensions on customer loyalty.
Among the five dimensions, only security had no significant effect on loyalty. Yet,
security has a significant effect on customer-perceived value which in turn affects
loyalty. Thus, customer-perceived value plays a full mediating role in the
relationship between security and loyalty. The remaining four dimensions have a
significant effect on customer loyalty. The most important dimension is care,
followed by reliability, ease of use, and product portfolio. Because their coefficients
are lower than the coefficient of customer-perceived value, customer-perceived
value is considered as partially mediating the effect of the four dimensions on
customer loyalty (Baron and Kenny 1986). Thus, both H3a and H3b are only
partially supported.
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L. Jiang et al.
Table 3 Structural equation models of key e-service quality dimensions, customer perceived value, and
loyalty
Independent variable
Dependent variable
Customer perceived value
Loyalty
Coefficient
t value
Coefficient
t value
Care
0.26
4.30**
0.35
7.31**
Reliability
0.15
2.71*
0.16
2.89*
Ease of use
0.28
4.59**
0.15
2.69*
Security
0.13
2.41*
0.05
0.97
Product portfolio
0.22
3.97**
0.14
2.54*
Customer perceived value
–
–
0.46
13.18**
R2
0.25
0.67
Goodness-of-fit statistics
Chi-square (p-value) = 137.17(0.00); d.f. = 89; v2/d.f. = 1.53; GFI = .95; RMSR = 0.05; RMSEA = 0.06;
(90% CI) = (0.043,0.072)
** p \ 0.01, * p \ 0.05
5 Discussion
5.1 Theoretical implications
This study identifies five key dimensions of e-service quality, care, reliability, ease
of use, security, and product portfolio, which are considered as substantially
important to customer-perceived value. The ‘‘care’’ factor relates to two constructs,
employees’ understanding of customer-specific needs and their personal attention to
them, and employees’ ability to answer customer questions and resolve problems
that arise promptly. The ‘‘reliability’’ dimension concerns accurate e-transactions,
accurate records, correct initial performance, and promise accomplishment. Next,
the ‘‘ease of use’’ dimension referred to moderate effort required to navigate a Web
site, well-organized/structured and easy-to-follow catalogs, and ease of completing
an online transaction. The ‘‘security’’ dimension is concerned with online
transaction safety and customer privacy. Finally, the ‘‘product portfolio’’ factor
referred to useful free services, a wide range of product packages, and desired
service features.
Our study examines the relative impacts of the e-service quality dimensions on
customer-perceived value. Ease of use to be the foremost critical factor in achieving
a high level of customer value, followed by care, product portfolio, and two ties,
reliability and security. First, the ease of use dimension is directly related to the
unique characteristics of online systems. Consistent with the technology adoption
model (Davis 1989), this dimension is a major factor leading to customer adoption
of and customer-perceived value with online purchasing. In maintaining their Web
sites, online companies need to focus on easy navigation for their online systems,
well-organized and well-structured e-catalogs, concise contents, and easy-tounderstand terms and conditions, and easy check-out processes in their Web sites.
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Customer-perceived value and loyalty
More specifically, a Web site should be configured to allow customers to
conveniently reach a desired Web page from anywhere in the Web site’s hierarchy
(Kim and Eom 2002). Otherwise, customers could experience considerable
difficulty in navigating pages and might be unlikely to complete desired
transactions.
The care dimension is the second most important driver of customer-perceived
value and the most important factor directly leading to customer loyalty. Care refers
to the degree to which online firms provide personalized services to meet their
customers’ specific needs. Although a Web site is basically an impersonal medium,
in order to attract and retain customers, a company is well-advised to differentiate
its products from those of competitors based on its personalized services to
customers. Thus, it is recommended that online firms devote special attention to all
the pre- and post-purchase customer interface activities designed to establish and
maintain long-term customer relationships (Srinivasan et al. 2002).
The product portfolio dimension is the third most influential factor for customerperceived value and refers to the range and depth of products and services, and to
the provision of free service offerings. Many customers seek products that are
unavailable in their local outlets. A limited selection of products or outdated product
information is most likely to deter numerous customers from purchasing online.
Moreover, a Web site can benefit if it provides a range of adequate service functions
in the menu options. It would also be desirable, when feasible, to provide valueadded free services by linking to useful informational Web sites.
Finally, the reliability and the security dimensions were a tie. The ‘‘reliability’’
factor related to accurate online transactions, accurate records, correct performance,
and fulfillment of promises. In reality, product order fulfillment still remains the
most troublesome area for online retailers, and most online consumers feel
frustrated with the poor service reliability provided by virtual stores (Parasuraman
et al. 2005). A reliable e-service is also one of the most influential determinants for
attaining a high level of customer-perceived value. On the other hand, ‘‘security’’
encompasses low risk associated with e-transactions, safeguarding personal
information, and safety in completing e-transactions. It has no direct effect on
customer loyalty. Yet, consistent with the prevailing viewpoint, security was
significant in determining and service value as perceived by online customers. In
fact, it is considered that the lack of confidence motivated by the perceived absence
of security in the online business environment is a stumbling block to the growth of
e-commerce.
Consistent with Chen and Dubinsky (2003) and Parasuraman and Grewal (2000),
we find that there is a significant and positive relationship between customerperceived value and customer loyalty. It should be noted that obtaining more
valuable products is a primary reason that customers choose the Internet as an
alternative purchasing channel. As e-commerce has made cost transparency more
feasible, the total product cost, not solely the price, has become an increasingly
important vehicle for attracting customers. The total cost constitutes both explicit
expenses (i.e., product price) and implicit expenses such as shipping costs, return
costs, coupon usages, discounts rewards, and free services.
123
L. Jiang et al.
As one of our major contributions, this study examines the mediating role of
customer-perceived value in the relationship between each e-service quality
dimension and customer loyalty. The quality-value-loyalty chain model proposed by
Parasuraman and Grewal (2000) only considers overall quality. Our study reveals
that customer-perceived value plays a partial role in the effect of ease of use, care,
product portfolio, and reliability on customer loyalty, respectively. Thus, customerperceived value mainly has a partial mediating effect on the relationship between
each e-service quality dimension and customer loyalty. In addition, customerperceived value plays a full mediating role in the relationship between security and
customer loyalty. This finding implies that security as a salient e-service quality
dimension can increase customer loyalty only through enhancing customerperceived value.
5.2 Managerial implications
The key e-service quality measurement developed in this study is designed to
provide an effective tool to assess Internet-based service quality encompassing
customer service, online systems, and product portfolio. Online companies can use
the quality measurement tool to detect their service quality weaknesses and
strengths. Based on their quality assessment and chosen business strategies, online
companies can devote corporate resources to the important service quality attributes
uncovered by this study.
All of the five dimensions do significantly and positively affect the assessment of
customer-perceived value and have a direct or indirect influence on customer
loyalty. Thus, it is recommended that online firms maintain and sharpen the levels
of ease of use, care, product portfolio, reliability, and security simultaneously to
broaden a loyal customer base by adoption of diverse Internet-based customer
relationship management (e-CRM) features. For example, site customization, one of
the important e-CRM features, enables individual customers to readily access
information they need by allowing them to filter the content they see, thereby
enhancing ease of use and in turn customer-perceived value. Various e-CRM
features (see Feinberg and Kadam (2002), for a comprehensive list of e-CRM
features) are primarily used for building and reinforcing relationships with existing
customers rather than acquiring new ones. Further, constant assessments of
customer-perceived service quality based on the five salient dimensions could serve
as a continuous service delivery control system to enable prompt corrective actions
when service performance on any of these dimensions falls below a customer
tolerance level.
5.3 Limitations and future research
Caution should be taken
methodological concern is
The response rate was low
online-based questionnaire
123
when generalizing the findings of this study. A
that the sample is concentrated on male customers.
though it has been a common phenomenon for many
surveys. Future research could choose more gender-
Customer-perceived value and loyalty
balanced samples to validate the findings of this study and address the issue of nonresponse bias.
Another limitation lies on our selection of key e-service quality dimensions.
While we identify five salient e-service quality dimensions based on literature
review, focus groups, and empirical purification, inclusion of these five dimensions
is subject to our selection bias and is constrained by the service contexts. We only
investigate two industries in the B2C e-commerce: online finance and retailing.
Future research could reduce such arbitrary selection of key e-service quality
dimensions by (1) including more attributes of e-service quality; (2) surveying more
diversified industries; and (3) expanding to B2B e-commerce. If pursued, such a
study would enhance sample representativeness and generalization of the empirical
results.
One important issue raised by this study is how to optimize service quality levels
within organizational capabilities, such as financial and human resources, in order to
achieve maximum profit by providing customer value and gaining customer loyalty.
This topic is deserving of extensive research effort. Another interesting issue is how
to discover sources from which e-service quality problems frequently arise. It would
be useful to find solutions on how to reduce service failures and to fulfill the gaps
between customers’ and managers’ perceptions of service quality. The solution will
have to deal with internal integration of functional departments and external
integration of channel partners.
Acknowledgments The authors acknowledge grants from the Research Grant Council of Hong Kong
SAR (CityU 196513), City University of Hong Kong (9680022) and National Science Foundation of
China (71172215).
References
Bagozzi RP, Yi Y (1988) On the evaluation of structural equation models. J Acad Market Sci 16(1):74–94
Barcia SM (2000) Internet pharmacies: all hype with no help. Health Manag Technol 21(4):24–25
Baron RM, Kenny DA (1986). The moderator–mediator variable distinction in social psychological
research: conceptual, strategic, and statistical considerations. J Personal Soc Psychol
51(6):1173–1182
Bolton RN, Lemon KN (1999) A dynamic model of customers’ usage of services: usage as an antecedent
and consequence of satisfaction. J Mark Res 36(2):171–186
Boulding W, Kalra A, Staelin R, Zeithaml VA (1993) A dynamic process model of service quality: from
expectations to behavioral intentions. J Mark Res 30:7–27
Chen Z, Dubinsky AJ (2003) A conceptual model of perceived customer value in e-commerce: a
preliminary investigation. Psychol Mark 20(4):323–347
Chiu HC, Hsieh YC, Kao CY (2005) Website quality and customer’s behavioural intention: an
exploratory study of the role of information asymmetry. Total Qual Manag Bus Excell
16(2):185–197
Cho N, Park S (2001) Development of electronic commerce user-consumer satisfaction index (ECUSI)
for Internet shopping. Ind Manag Data Syst 101(8):400–405
Cohen RJ, Swerdlik MK, Smith DK (1992) Psychological testing and assessment: An introduction to tests
and measurement. Mayfield Publishing Company, Mountain View
Cox J, Dale BG (2001) Service quality and e-commerce: an exploratory analysis. Manag Serv Qual
11(2):121–131
Cronin JJ, Brady MK, Hult GTM (2000) Assessing the effects of quality, value, and customer satisfaction
on consumer behavioral intentions in service environments. J Retail 76(2):193–218
123
L. Jiang et al.
Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information
technology. MIS Q 13(3):319–340
Doll WJ, Torkzadeh G (1988) The measurement of end-user computing satisfaction. MIS Q 12:259–274
Doll WJ, Xia W, Torkzadeh G (1994) A confirmatory factor analysis of the end-user computing
satisfaction instrument. MIS Q 18:43–461
Feinberg R, Kadam R (2002) E-CRM Web service attributes as determinants of customer satisfaction
with retail Web sites. Int J Serv Ind Manag 13(5):432–451
Fornell C (1992) A national customer satisfaction barometer: the Swedish experience. J Market
56(1):6–21
Heim GR, Sinha KK (2001) Operational drivers of customer loyalty in electronic retailing: an empirical
analysis of electronic food retailers. Manuf Serv Oper Manag 3(3):264–271
Hendrickson AR, Collins MR (1996) An assessment of structure and causation of is usage. Database Adv
Inf Syst 27:1–67
Ho CT, Lin WC (2010) Measuring the service quality of internet banking: scale development and
validation. Eur Bus Rev 22(1):5–24
Ibanez VA, Hartmann P, Calvo PZ (2006) Antecedents of customer loyalty in residential energy markets:
service quality, satisfaction, trust and switching costs. Serv Ind J 26:633–650
Jiang L, Yang Z, Jun M (2013) Measuring consumer perception of online shopping convenience. J Serv
Manag 24(2):191–214
Kehoe C, Pitkow J, Sutton K, Aggarwal G, Rogers JD (1999) Results of GVU’s tenth world wide web
user survey. Graphics Visualization and Usability Center, College of Computing, Georgia Institute
of Technology, Atlanta, GA
Kim EB, Eom SB (2002) Designing effective cyber store user interface. Ind Manag Data Syst
102(5):241–251
Lee G, Lin H (2005) Customer perceptions of e-service quality in online shopping. Int J Retail Distrib
Manag 33(2):161–176
Levesque T, McDougall GHG (1996) Determinants of customer satisfaction in retail banking. Int J Bank
Mark 14:12–20
Li HF (2007) The impact of website quality dimensions on customer satisfaction in the B2C e-commerce
context. Total Qual Manag Bus Excell 18(4):363–378
Liu C, Arnett KP (2000) Exploring the factors associated with web site success in the context of
electronic commerce. Inf Manag 38:23–34
McMullan R, Gilmore A (2008) Customer loyalty: an empirical study. Eur J Mark 42:1084–1094
Nunnally JC, Bernstein IH (1994) Psychometric theory. New York: McGraw-Hall
Oliver RL, DeSarbo WS (1988) Response determinants in satisfaction judgments. J Consum Res
14:495–508
Page C, Lepkowska-White E (2002) Web equity: a framework for building consumer value in online
companies. J Consum Mark 19(2/3):231–248
Parasuraman A, Grewal D (2000) The impact of technology on the quality-value-loyalty chain: a research
agenda. J Acad Mark Sci 28(1):168–174
Parasuraman A, Zeithaml VA, Berry LL (1988) SERVQUAL: a multiple-item scale for measuring
consumer perceptions of service quality. J Retail 64(1):12–40
Parasuraman A, Zeithaml VA, Berry LL (1991) Refinement and reassessment of the SERVQUAL scale.
J Retail 67(4):420–450
Parasuraman A, Zeithaml VA, Malholtra A (2005) E-S-QUAL: a multiple-item scale for assessing
electronic service quality. J Serv Res 7(3):213–235
Podsakoff PM, Organ DW (1986) Self-reports in organizational research: problems and prospects.
J Manag 12(4):531–543
Pollack BL (2009) Linking the hierarchical service quality model to customer satisfaction and loyalty.
J Serv Mark 23(1):42–50
Ranaweera C, Neely A (2003) Some moderating effects on the service quality-customer retention link. Int
J Oper Prod Manag 23(2):230–248
Sheehan KB, Hoy MG (2000) Dimensions of privacy concerns among online consumers. J Public Policy
Mark 19(1):62–73
Srinivasan SS, Anderson R, Ponnavolu K (2002) Customer loyalty in e-commerce: an exploration of its
antecedents and consequences. J Retail 78(1):41–50
Szymanski DM, Hise RT (2000) E-satisfaction: an initial examination. J Retail 76(3):309–322
123
Customer-perceived value and loyalty
Teo HH, Oh LB, Liu C, Wei KK (2003) An empirical study of the effect of interactivity on web user
attitude. Int J Hum Comput Stud 58(3):281–305
Tsao WC, Tseng YL (2011) The impact of electronic-service quality on online shopping behavior. Total
Qual Manag Bus Excell 22(9):1007–1024
Wang CY (2010) Service quality, perceived value, corporate image, and customer loyalty in the context
of varying levels of switching costs. Psychol Mark 27(3):252–262
Wolfinbarger MF, Gilly MC (2003) eTailQ: dimensionalizing, measuring and predicting eTail quality.
J Retail 79(3):183–198
Yang Z, Peterson RT (2004) Customer perceived value, satisfaction, and loyalty: the role of switching
costs. Psychol Mark 21(10):799–822
Yang Z, Jun M, Peterson RT (2004) Measuring customer perceived online service quality: scale
development and managerial implications. Int J Oper Prod Manag 24(11):1149–1174
Yang Z, Cai S, Zhou Z, Zhou N (2005) Development and validation of an instrument to measure user
perceived service quality of information presenting Web portals. Inf Manag 42(4):575–589
Yen HJR, Gwinner KP (2003) Internet retail customer loyalty: the mediating role of relational benefits.
Int J Serv Ind Manag 14(5):483–500
Yen CH, Lu HP (2008) Effects of e-service quality on loyalty intention: an empirical study in online
auction. Manag Serv Qual 18(2):127–146
Zeithaml VA, Berry LL, Parasuraman A (1996) The behavioral consequences of service quality. J Mark
60:31–46
Zeithaml VA, Parasuraman A, Malhotra A (2002) Service quality delivery through Web sites: a critical
review of extant knowledge. J Acad Mark Sci 30(4):362–375
Zeng F, Hu Z, Chen R, Yang Z (2009) Determinants of online service satisfaction and their impacts on
behavioral intentions. Total Qual Manag Bus Excell 20(8):953–969
Zhang X, Prybutok VR (2004) An empirical study of online shopping: a service perspective. Int J Serv
Technol Manag 5(1):1–13
123
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