E-S-QUAL: A Multiple-Item Scale for Assessing Electronic Service Quality

TL;DR: In this article, a multiple-item scale (E-S-QUAL) is proposed for measuring the service quality delivered by a service provider. But, the scale is based on the means-end framework.

Abstract: Using the means-end framework as a theoretical foundation, this article conceptualizes, constructs, refines, and tests a multiple-item scale (E-S-QUAL) for measuring the service quality delivered b...

Summary

TRADITIONAL SERVICE QUALITY VERSUS ELECTRONIC SERVICE QUALITY

• Extensive research on traditional SQ has been conducted during the past 20 years (see Parasuraman and Zeithaml 2002 for a review).
• In contrast, only a limited number of scholarly articles deal directly with how customers assess e-SQ and its antecedents and consequences.
• The authors briefly overview the relevant aspects of traditional SQ and describe the reasons why that research needs to be repeated in the electronic context.

Traditional Service Quality

• By traditional SQ the authors are referring to the quality of all non-Internet-based customer interactions and experiences with companies.
• Using insights from these studies as a starting point, Parasuraman, Zeithaml, and Berry (1988, 1991) conducted empirical studies in several industry sectors to develop and refine SERVQUAL, a multiple-item instrument to quantify customers’ global (as opposed to transaction-specific) assessment of a company’s SQ.
• This scale measures SQ along five dimensions: reliability, responsiveness, assurance, empathy, and tangibles.
• As such, whether the preceding conclusions extend to e-SQ contexts and what the similarities and differences are between the evaluative processes for SQ and e-SQ are open questions.
• The items in the scale were changed to adapt to the electronic context (e.g., tangibles were represented in part by an item about appearance of the Web site), and therefore the scales were not comparable across the research contexts.

Why e-SQ?

• Insights from studies dealing with people-technology interactions imply that customer evaluation of new technologies is a distinct process.
• Another major qualitative study by the same authors (Mick and Fournier 1998), focusing on people’s reactions to technology, suggests that technology may trigger positive and negative feelings simultaneously.
• Earlier studies focusing on specific technologies have also shown that consumers’ beliefs about, and reactions to, the technology in question are distinct and positively correlated with acceptance (Cowles 1989; Cowles and Crosby 1990; Dabholkar 1996; Eastlick 1996).
• Other research shows that perceived usefulness and ease of use are correlated significantly with self-reported (Davis 1989) and actual (Szajna 1996) usage of technology.
• In other words, customer-specific attributes (e.g., technology readiness) might influence, for instance, the attributes that customers desire in an ideal Web site and the performance levels that would signal superior e-SQ.

Research on e-SQ

• Some academic researchers have developed scales to evaluate Web sites.
• This scale’s primary purpose is to generate information for Web site designers rather than to measure service quality as experienced by customers.
• Therefore, although some WebQual dimensions might influence perceived service quality, other dimensions (e.g., innovativeness, business processes, and substitutability) are at best tangential to it.
• Using an online survey, Szymanski and Hise (2000) studied the role that customer perceptions of online convenience, merchandising (product offerings and product information), site design, and financial security play in esatisfaction assessments.
• A number of studies have examined various aspects of these criteria.

Definition and Domain of e-SQ

• The extant literature and extensive focus group research in Zeithaml, Parasuraman, and Malhotra’s (2000) study suggested that customers’assessment of a Web site’s quality includes not only experiences during their interactions with the site but also postinteraction service aspects (i.e., fulfillment, returns).
• To represent the full range of evaluative criteria emerging from their focus groups, the researchers proposed a theoretical framework that is anchored in the means-end-chain approach to understanding consumers’ cognitive structures.
• Fourth, the linkages implied in the theoretical framework (Figure 2) between the e-SQ evaluative process (i.e., perceptual/dimension-level assessments) and its consequences (i.e., higher-order abstractions) constitute a natural “nomological net” for verifying the construct validity of an e-SQ scale consisting of perceptual-attribute level items.
• Zeithaml, Parasuraman, and Malhotra’s (2000) study identified dozens of Web site features at the perceptualattribute level and categorized them into 11 e-SQ dimensions: 1. Reliability: Correct technical functioning of the site and the accuracy of service promises (having items in stock, delivering what is ordered, delivering when promised), billing, and product information.
• Site is simple to use, structured properly, and requires a minimum of information to be input by the customer, also known as Efficiency.

Preliminary Scale

• A set of 121 items representing all facets of the e-SQ domain formed their initial scale.
• The authors incorporated this scale into two questionnaire versions with different scale anchors and formats.
• The authors then evaluated the alternative versions in two focus group interviews with graduate students at a major university in the eastern United States.
• The specific goals of the focus groups were to (a) understand respondents’ reactions to alternative ways of phrasing scale items and anchors (Likert-type scale versus low-high performance anchors); (b) reword items to improve clarity; (c) eliminate redundant items; and (d) obtain feedback on the length, format, and clarity of the instructions and initial questionnaire draft.
• The revised questionnaire had 113 items with 5-point scales ranging from 1 (strongly disagree) to 5 (strongly agree).

Sample Design and Data Collection

• The authors selected two online stores—amazon.com and walmart.com—to verify the psychometric properties of the E-S-QUAL and E-RecS-QUAL Scales.
• Table 3 contains descriptive profiles of the two samples.
• The third part contained multiple-item measures of two constructs—perceived value and loyalty intentions—that were used subsequently in assessing the scales’ validity.

Data Analysis and Scale Reduction

• The survey data, pooled across all sites, were subjected to various scale-reduction/refinement analyses consistent with standard procedures for developing and refining scales.
• The authors then went through a series of iterations, each involving elimination of items with low loadings on all factors or high cross-loadings on two or more factors, followed by factor analysis of the remaining items.
• The authors next analyzed the items they had set aside earlier for constructing a scale for measuring the quality of recovery service provided by Web sites.
• The degree to which the site compensates customers for problems.
• As in the case of E-S-QUAL, the authors conducted CFA analysis to verify the factor structure of the E-RecS-QUAL Scale.

Reliability and Validity Assessment

• These values together with the strong loadings of the scale items on their corresponding factors (in both EFA and CFA) support the convergent validity of each scale’s component dimensions.
• Estimating such a second-order measurement model requires at least two other reflective indicators for the second-order construct, in addition to the formative indicators already in the model (Diamantopoulos and Winklhofer 2001; Jarvis, Mackenzie, and Podsakoff 2003).
• The CFA loadings and fit statistics from this reanalysis were very similar to those reported in Table 1 for The interfactor correlations between pairs of dimensions in the CFA ranged from .67 to .83 for the E-S-QUAL dimensions and .68 to .73 for the E-RecS-QUAL dimensions.
• The correlations of the E-SQUAL dimensions with the overall measures ranged from .47 to .60 for quality and .44 to .54 for value.

Reassessment of Reliability and Validity

• Table 4 presents coefficient alpha values for, and intercorrelations among, the four E-S-QUAL dimensions, the three E-RecS-QUAL dimensions, and the measures of perceived value and loyalty intentions.
• The overall goodness-of-fit statistics and results from the structural-model portion of Table 6 (i.e., the structural coefficients and R2 values) imply that the data from each of the two samples fit the proposed model reasonably well— all fit indices are well above conventional cutoff values (Hu and Bentler 1999), although the RMSEA values are somewhat high.
• A related issue is statistical power, which depends on sample size as well as the degrees of freedom in the structural model and can be either too low (leading to nonrejection of incorrect models) or too high (leading to rejection of correct models) (McQuitty 2004).
• Given the aforementioned results, it is reasonable to interpret each factor-score measure as predominantly representing the corresponding E-S-QUAL dimension.

DISCUSSION

• Informed by insights from the extant literature and using the means-end framework as a theoretical foundation, the authors set out to conceptualize, construct, refine, and test a multiple-item scale (E-S-QUAL) for measuring the service quality delivered by Web sites.
• In the preliminary stage of scale development, a large number of respondents did not provide ratings on a subset of the initial pool of items.
• An examination of these items revealed that they all pertained to nonroutine or recovery service encounters that many respondents apparently had not experienced.
• Therefore, in subsequent stages of scale development and refinement, the authors created a subscale of E-S-QUAL—called E-RecS-QUAL—containing items focusing on handling service problems and inquiries, and being salient only to customers who had had nonroutine encounters with the sites.
• The authors hope that the two scales will stimulate and facilitate additional scholarly research on e-SQ and also assist practitioners in systematically assessing and improving e-SQ.

Directions for Further Research

• Both scales demonstrate good psychometric properties based on findings from a variety of reliability and validity tests.
• Of the four E-S-QUAL dimensions, customers’ assessments of a Web site on these two dimensions have the strongest influence not only on overall quality perceptions but also on perceived value and loyalty intentions.
• Fifth, E-S-QUAL and E-RecS-QUAL are generic and parsimonious scales, intended for obtaining a global (as opposed to transaction-specific) assessment of a Web site’s service quality.
• Companies can also enhance the diagnostic value of the perceptual ratings from the two scales by comparing those ratings with customers’ minimum- and desired-service levels (Parasuraman, Zeithaml, and Berry 1994a).

E-S-QUAL

• Respondents rated the Web site’s performance on each scale item using a 5-point scale (1 = strongly disagree, 5 = strongly agree).
• The items below are grouped by dimension for expositional convenience; they appeared in random order on the survey.
• The symbols preceding the items correspond to the variable names in Tables 1 and 5 in the body of the article.

Efficiency

• This site makes it easy to find what I need.
• Information at this site is well organized.

System Availability

• This site is always available for business.
• Pages at this site do not freeze after I enter my order information.

Fulfillment

• This site makes items available for delivery within a suitable time frame.
• It has in stock the items the company claims to have.
• It makes accurate promises about delivery of products.

Privacy

• It protects information about my Web-shopping behavior.
• It does not share my personal information with other sites.
• This site protects information about my credit card.

E-RecS-QUAL

• Respondents rated the Web site’s performance on each scale item using a 5-point scale (1 = strongly disagree, 5 = strongly agree).
• The items below are grouped by dimension for expositional convenience; they appeared in random order on the survey.
• The symbols preceding the items correspond to the variable names in Table 2 in the body of the article.

Compensation

• This site compensates me for problems it creates.
• It compensates me when what I ordered doesn’t arrive on time.

Contact

• This site provides a telephone number to reach the company.
• This site has customer service representatives \available online.
• The value measure consisted of four items; respondents rated the Web site on each item using a scale of 1 (poor) to 10 .
• The overall value you get from this site for your money and effort.

Figures

TABLE 5 CFA Results for the E-S-QUAL Scale

FIGURE 1 Process Employed in Developing the Scale to Measure e-SQ

FIGURE 2 A Means-End Framework for Understanding the Domain and Consequences of e-SQ

TABLE 3 Profiles of the Two Samplesa

TABLE 6 SEM Analysis to Examine E-S-QUAL’s Nomological Validity

TABLE 2 CFA and EFA Results for the E-RecS-QUAL Scale

TABLE 4 Reliabilities and Intercorrelationsa,b

TABLE 1 CFA and EFA Results for the E-S-QUAL Scale

TABLE 7 Regression Analyses of Quality, Value, and Loyalty on Summed and Factor Scores for E-S-QUAL Dimensions

Full text

E-S-QUAL
A Multiple-Item Scale for Assessing
Electronic Service Quality
A. Parasuraman
University of Miami
Valarie A. Zeithaml
Arvind Malhotra
University of North Carolina at Chapel Hill
Using the means-end framework as a theoretical founda-
tion, this article conceptualizes, constructs, refines, and
tests a multiple-item scale (E-S-QUAL) for measuring the
service quality delivered by Web sites on which customers
shop online. Two stages of empirical data collection re-
vealed that two different scales were necessary for captur-
ing electronic service quality. The basic E-S-QUAL scale
developed in the research is a 22-item scale of four dimen
-
sions: efficiency, fulfillment, system availability, and pri
-
vacy. The second scale, E-RecS-QUAL, is salient only to
customers who had nonroutine encounters with the sites
and contains 11 items in three dimensions: responsive
-
ness, compensation, and contact. Both scales demonstrate
good psychometric properties based on findings from a
variety of reliability and validity tests and build on the re
-
search already conducted on the topic. Directions for fur
-
ther research on electronic service quality are offered.
Managerial implications stemming from the empirical
findings about E-S-QUAL are also discussed.
Keywords: e-service quality; online stores; customer ser
-
vice; scale development
Although no longer believed to be the revolution previ-
ously conceived, the Internet remains a critical channel for
selling most goods and services. Companies such as Ama-
zon distribute products and services solely through Web
channels, and virtually all companies are creating Web
channels as sources for prepurchase information (cars),
alternative ways to buy products (retailers such as GAP,
Talbot’s, and Eddie Bauer), approaches to expand services
(industrial products), and ways to capture time-conscious
and upscale consumers (online banking). If these channels
are to be viable, they must be perceived by consumers as
effective and efficient.
Even though low price and Web presence were initially
thought to be the drivers of success, service quality issues
soon became pivotal. When consumers could not com
-
plete transactions, products were not delivered on time or
at all, e-mails were not answered, and desired informa
-
tion could not be accessed, the viability of Web channels
was jeopardized. Mounting business and academic evi
-
dence demonstrated a widespread lack of adequate ser
-
vice quality delivered through the Internet (Ahmad 2002;
Lennon and Harris 2002; LoCascio 2000; Pastore 2001).
This problem still persists (Cox 2002; Gaudin 2003;
InternetNewsBureau 2003). If Web channels are to be
The authors gratefully acknowledge research grants from the Marketing Science Institute and DellStar, without which this research
could not have been conducted. They also thank three anonymous reviewers for their constructive and helpful comments.
Journal of Service Research, Volume 7, No. X, Month 2005 1-21
DOI: 10.1177/1094670504271156
© 2005 Sage Publications

accepted by consumers, companies must shift the focus of
e-business from e-commerce—the transactions—to e-
service—all cues and encounters that occur before, dur
-
ing, and after the transactions.
To deliver superior service quality, managers of compa
-
nies with Web presences must first understand how con
-
sumers perceive and evaluate online customer service.
Although there are many different types of Internet sites,
the research described in this article focuses only on online
shopping sites. The article does not deal with other Inter
-
net sites—such as online newspapers, portals, free down
-
load sites, customer-to-customer sites such as eBay or
Topica, sites that are collections of links, or job sites such
as Monster.com—that exist for purposes other than online
shopping and that are advertiser supported. The purpose of
this article is to describe the development, refinement,
psychometric evaluation, properties, and potential appli
-
cations of a multiple-item scale for measuring e-service
quality (e-SQ) of sites on which customers shop online.
The process that produced the scale involved a sequence of
steps consistent with conventional guidelines for scale
development (Churchill 1979; Gerbing and Anderson
1988). Figure 1 provides an overview of the steps.
The remainder of this article consists of five sections.
The first section provides a synopsis of the extant literature
on traditional SQ and e-SQ. Drawing on insights from the
extant literature and a comprehensive qualitative study, the
second section offers a formal definition of e-SQ and
delineates its domain (Step 1 in Figure 1). The next section
describes a preliminary scale, the process used in refining
it through both qualitative and empirical research, and the
scale’s psychometric properties (Steps 2 through 5). The
fourth section discusses additional empirical research that
was conducted to further assess the refined scale’s reliabil
-
ity and validity, and to explore the nature and extent of e-
SQ’s impact on customers’ overall quality and value per
-
ceptions, as well as their loyalty intentions (Step 6). The
final section offers directions for future research and dis
-
cusses managerial implications.
TRADITIONAL SERVICE QUALITY
VERSUS ELECTRONIC SERVICE QUALITY
Extensive research on traditional SQ has been con
-
ducted during the past 20 years (see Parasuraman and
Zeithaml 2002 for a review). In contrast, only a limited
number of scholarly articles deal directly with how cus
-
tomers assess e-SQ and its antecedents and consequences.
In this section, we briefly overview the relevant aspects of
traditional SQ and describe the reasons why that research
needs to be repeated in the electronic context.
Traditional Service Quality
By traditional SQ we are referring to the quality of all
non-Internet-based customer interactions and experi
-
ences with companies. Early scholarly writings on SQ
(Grönroos 1982; Lehtinen and Lehtinen 1982; Lewis and
Booms 1983; Parasuraman, Zeithaml, and Berry 1985;
Sasser, Olsen, and Wyckoff 1978) suggested that SQ
stems from a comparison of what customers feel a com
-
pany should offer (i.e., their expectations) with the com
-
pany’s actual service performance. Using insights from
these studies as a starting point, Parasuraman, Zeithaml,
and Berry (1988, 1991) conducted empirical studies in
several industry sectors to develop and refine SERV
-
QUAL, a multiple-item instrument to quantify customers’
global (as opposed to transaction-specific) assessment of a
company’s SQ. This scale measures SQ along five dimen
-
sions: reliability, responsiveness, assurance, empathy, and
tangibles. The SERVQUAL instrument and its adaptations
have been used for measuring SQ in many proprietary and
published studies. It has also generated debate in the litera
-
ture about the most appropriate ways to assess SQ (Brown,
Churchill, and Peter 1993; Carman 1990; Cronin and
Taylor 1992; Parasuraman, Berry, and Zeithaml 1991,
1993; Parasuraman, Zeithaml, and Berry 1994a, 1994b;
Teas 1993.
Three broad conclusions that are potentially relevant to
defining, conceptualizing, and measuring perceived e-SQ
emerge from the traditional SQ literature: (a) The notion
that quality of service stems from a comparison of actual
service performance with what it should or would be has
broad conceptual support, although some still question the
empirical value of measuring expectations and operation
-
alizing SQ as a set of gap scores; (b) the five SERVQUAL
dimensions of reliability, responsiveness, assurance, em
-
pathy, and tangibles capture the general domain of SQ
fairly well, although (again from an empirical stand
-
point) questions remain about whether they are five dis
-
tinct dimensions; and (c) customer assessments of SQ
are strongly linked to perceived value and behavioral
intentions.
A noteworthy feature of the extant SQ literature is that
it is dominated by people-delivered services. As such,
whether the preceding conclusions extend to e-SQ con
-
texts and what the similarities and differences are between
the evaluative processes for SQ and e-SQ are open ques
-
tions. One author who has extended the SERVQUAL con
-
ceptualization to the electronic context is Gefen (2002),
who found that the five service quality dimensions col
-
lapse to three with online service quality: (a) tangibles; (b)
a combined dimension of responsiveness, reliability, and
assurance; and (c) empathy. In that research, tangibles
were found to be the most important dimension in increas
-
ing customer loyalty and the combination dimension most
2 JOURNAL OF SERVICE RESEARCH / February 2005

critical in increasing customer trust. However, the items in
the scale were changed to adapt to the electronic context
(e.g., tangibles were represented in part by an item about
appearance of the Web site), and therefore the scales were
not comparable across the research contexts. For this and
other reasons discussed below, studying e-SQ requires
scale development that extends beyond merely adapting
offline scales.
Why e-SQ?
Insights from studies dealing with people-technology
interactions imply that customer evaluation of new tech
-
nologies is a distinct process. For instance, findings from
an extensive qualitative study of how customers interact
with, and evaluate, technology-based products (Mick and
Fournier 1995) suggest that (a) customer satisfaction with
Parasuraman et al. / E-S-QUAL 3
Step 4: Developed a parsimonious scale through an iterative process:
Step 1: Articulated the meaning and domain of e-service quality based on
insights from the extant literature and a comprehensive qualitative study.
Step 2: Developed a preliminary scale (containing 121 items and representing
11 e-service quality dimensions) and revised it based on feedback from two
focus groups.
Step 3: Administered the revised scale to a nationally representative sample of
Internet users through an online survey – roughly one third of the respondents
evaluated their favorite sites, another third evaluated their second-favorite
sites, and the rest evaluated their third-favorite sites; a total of 549 completed
questionnaires were collected.
22-item, 4-dimensional E-S-QUAL scale (and 11-item, 3-dimensional E-RecS-QUAL scale)
Step 5: Conducted CFA and validity tests on the final scales.
Step 6: Administered the final scales via online surveys to representative
samples of customers of Amazon.com (n = 653) and Walmart.com (n = 205) to:
(a) re-confirm the scales’ reliability and validity and (b) assess the relative
importance of the various e-service quality dimensions in influencing
consumers’ overall qualit
y
and value perceptions and lo
y
alt
y
intentions.
Deletion of items
Reassignment of items and restructuring of dimensions as necessary
Examination of dimensionality through exploratory factor analysis
Examination coefficient alpha and item-to-total correlations by dimension
FIGURE 1
Process Employed in Developing the Scale to Measure e-SQ
NOTE: e-SQ = e-service quality.

such products involves a highly complex, meaning-laden,
long-term process; (b) the process might vary across dif
-
ferent customer segments; and (c) satisfaction in such con
-
texts is not always a function of preconsumption compari
-
son standards. Another major qualitative study by the
same authors (Mick and Fournier 1998), focusing on peo
-
ple’s reactions to technology, suggests that technology
may trigger positive and negative feelings simultaneously.
Moreover, other research involving both qualitative and
empirical components demonstrates that customers’ pro
-
pensity to embrace new technologies (i.e., their technol
-
ogy readiness) depends on the relative dominance of posi
-
tive and negative feelings in their overall technology
beliefs (Parasuraman 2000). Earlier studies focusing on
specific technologies have also shown that consumers’
beliefs about, and reactions to, the technology in question
are distinct and positively correlated with acceptance
(Cowles 1989; Cowles and Crosby 1990; Dabholkar 1996;
Eastlick 1996). Other research shows that perceived use
-
fulness and ease of use are correlated significantly with
self-reported (Davis 1989) and actual (Szajna 1996) usage
of technology.
Collectively, the findings of these studies reveal impor-
tant differences in acceptance and usage of technologies
across customers depending on their technology beliefs
and suggest that similar differences might exist in the eval-
uative processes used in judging e-SQ. In other words,
customer-specific attributes (e.g., technology readiness)
might influence, for instance, the attributes that customers
desire in an ideal Web site and the performance levels that
would signal superior e-SQ.
Research on e-SQ
Some academic researchers have developed scales to
evaluate Web sites. Loiacono, Watson, and Goodhue
(2000) created WebQual, a scale for rating Web sites on 12
dimensions: informational fit to task, interaction, trust,
response time, design, intuitiveness, visual appeal, inno
-
vativeness, flow-emotional appeal, integrated communi
-
cation, business processes, and substitutability. However,
this scale’s primary purpose is to generate information for
Web site designers rather than to measure service quality
as experienced by customers. The research that produced
the scale involved students visiting Web sites to evaluate
them rather than actual purchasers evaluating their experi
-
ences. Therefore, although some WebQual dimensions
might influence perceived service quality, other dimen
-
sions (e.g., innovativeness, business processes, and sub
-
stitutability) are at best tangential to it. Moreover, the scale
developers excluded a dimension called customer service
because it could not be measured under the research meth
-
odology that was used. For the same reason, WebQual
does not include fulfillment as a dimension.
Barnes and Vidgen (2002) developed a completely dif
-
ferent scale to measure an organization’s e-commerce
offering, which they also call WebQual. This scale pro
-
vides an index of a site’s quality (customer perceptions
weighted by importance) and has five factors: usability,
design, information, trust, and empathy. Data used in
developing and testing the questionnaire were obtained
from convenience samples of university students and staff
who were directed to visit one of three bookstore sites, to
collect some information about a book of their choice, and
then to rate their experience on the scale items. The scale is
designed to be answered without a respondent needing to
complete the purchasing process and is therefore a trans
-
action-specific assessment of a site rather than a compre
-
hensive evaluation of the service quality of a site.
Yoo and Donthu (2001) developed a nine-item SITE
-
QUAL scale for measuring site quality on four dimen
-
sions: ease of use, aesthetic design, processing speed, and
security. As in the case of Barnes and Vidgen’s (2002)
WebQual scale, data for developing and testing SITE-
QUAL were gathered from convenience samples. Specifi-
cally, students enrolled in marketing classes were asked to
visit and interact with three Internet shopping sites of their
own choice and then evaluate each site. Like WebQual,
SITEQUAL does not capture all aspects of the purchasing
process and therefore does not constitute a comprehensive
assessment of a site’s service quality.
Using an online survey, Szymanski and Hise (2000)
studied the role that customer perceptions of online conve-
nience, merchandising (product offerings and product in
-
formation), site design, and financial security play in e-
satisfaction assessments. This study did not include
aspects of customer service or fulfillment; rather, it dealt
only with aspects of the Web site. Furthermore, it mea
-
sured satisfaction rather than service quality.
Wolfinbarger and Gilly (2003) used online and offline
focus groups, a sorting task, and an online-customer-panel
survey to develop a 14-item scale called eTailQ. The scale
contains four factors: Web site design (involving some
attributes associated with design as well as an item dealing
with personalization and another dealing with product
selection), reliability/fulfillment (involving accurate rep
-
resentation of the product, on-time delivery, and accurate
orders), privacy/security (feeling safe and trusting of the
site), and customer service (combining interest in solv
-
ing problems, willingness of personnel to help, and
prompt answers to inquiries). Wolfinbarger and Gilly’s
goal of creating a scale to measure customer percep
-
tions of e-tailing quality is excellent, and their three-
study aproach is comprehensive. The resulting scale
raises several questions, however. Although two of their
4 JOURNAL OF SERVICE RESEARCH / February 2005

dimensions—security/privacy and reliability/fulfillment—
show strong face validity and are highly descriptive of the
items they represent, the other two dimensions appear less
internally consistent and distinct. Web site design, for
example, embraces aspects of in-depth information, level
of personalization, selection, and speed of completing
transactions. The factor called customer service contains
items relating to the company’s willingness to respond to
customer needs, the company’s interest in solving prob
-
lems, and the promptness with which inquiries are
answered. These dimensions, as well as other items that
might be relevant to customer assessment of service qual
-
ity on Web sites, need to be tested further.
Thus, although past studies provide insights about cri
-
teria that are relevant for evaluating e-SQ, the scales devel
-
oped in those studies also raise some important questions
that call for additional research on the topic. On the basis
of a comprehensive review and synthesis of the extant lit
-
erature on e-SQ, Zeithaml, Parasuraman, and Malhotra
(2002) detailed five broad sets of criteria as relevant to e-
SQ perceptions: (a) information availability and content,
(b) ease of use or usability, (c) privacy/security, (d) graphic
style, and (e) reliability/fulfillment. A number of studies
have examined various aspects of these criteria. Some
have been hypothesized to be critical, whereas the impor-
tance of others has been demonstrated empirically. Avail-
ability and depth of information appear to be important
because when users can control the content, order, and
duration of product-relevant information, their ability to
integrate, remember, and thereby use information im-
proves (Ariely 2000). Ease of use appears relevant because
Internet-based transactions are complex and intimidating
to many customers. Privacy (the protection of personal
information) and security (the protection of users from the
risk of fraud and financial loss) have been shown empiri
-
cally to have a strong impact on attitude toward use of
online financial services (e.g., Montoya-Weiss et al.
2003). Graphic style—which embodies such issues as
color, layout, print size and type, number of photographs
and graphics, and animation—has also been shown to
affect customer perceptions of online shopping (Hoffman
and Novak 1996; Hoque and Lohse 1999; Schlosser and
Kanfer 1999). Finally, reliability/fulfillment has been
cited as an important facet of e-SQ (Palmer, Bailey, and
Faraj 1999; Wolfinbarger and Gilly 2003). In fact,
Wolfinbarger and Gilly (2003) found that reliability/
fulfillment ratings were the strongest predictor of cus
-
tomer satisfaction and quality, and the second strongest
predictor of intentions to repurchase at a site.
Insights from the research on e-SQ reviewed above and
a comprehensive conceptual study of the nature and struc
-
ture of e-SQ (Zeithaml, Parasuraman, and Malhotra 2000)
formed the starting point for developing the e-SQ scale
that is the focus of this article. The following sections
describe in detail the various scale-development steps out
-
lined in Figure 1.
DEVELOPMENT AND REFINEMENT OF A
SCALE TO MEASURE e-SQ
Definition and Domain of e-SQ
The extant literature and extensive focus group re
-
search in Zeithaml, Parasuraman, and Malhotra’s (2000)
study suggested that customers’assessment of a Web site’s
quality includes not only experiences during their inter
-
actions with the site but also postinteraction service
aspects (i.e., fulfillment, returns). As such, e-SQ is defined
broadly to encompass all phases of a customer’s interac
-
tions with a Web site: The extent to which a Web site facili
-
tates efficient and effective shopping, purchasing, and
delivery.
In discussing what they considered to be desirable
characteristics of Web sites, the focus group participants
in Zeithaml, Parasuraman, and Malhotra’s (2000) study
mentioned a variety of features—ranging from specific,
concrete cues (e.g., tab structuring, search engines, one-
click ordering), to more general perceptual attributes (e.g.,
perceived ease of finding what one is looking for, per-
ceived transaction speed) to broad dimensions (e.g., ease
of navigation in general, responsiveness to customer
needs), to higher-order abstractions (e.g., overall per-
ceived quality and value). To represent the full range of
evaluative criteria emerging from their focus groups, the
researchers proposed a theoretical framework that is
anchored in the means-end-chain approach to understand
-
ing consumers’ cognitive structures. This approach holds
that consumers retain product information in memory at
multiple levels of abstraction (Olson and Reynolds 1983;
Young and Feigen 1975). The proposed framework is
summarized in Figure 2.
The antecedents of e-SQ are specific concrete cues—
such as one-click ordering, Trust-e symbols, and search
engines—that trigger perceptual attributes. Evaluations of
e-service quality along the perceptual attributes coalesce
into evaluations along more abstract dimensions. The
attribute- and dimension-level evaluations lead to more
global assessments at higher levels of abstraction (e.g.,
overall assessment of e-SQ and perceived value), which in
turn influence behavioral intentions and actual behavior
(Zeithaml, Parasuraman, and Malhotra 2000).
A critical initial step in the scale development is the cor
-
rect specification of the domain from which items are to be
drawn in constructing the scale (Churchill 1979). As
the theoretical framework in Figure 2 implies, the core
Parasuraman et al. / E-S-QUAL 5

Frequently asked questions

Q1. What are the contributions mentioned in the paper "A multiple-item scale for assessing electronic service quality" ?

Using the means-end framework as a theoretical foundation, this article conceptualizes, constructs, refines, and tests a multiple-item scale ( E-S-QUAL ) for measuring the service quality delivered by Web sites on which customers shop online. Directions for further research on electronic service quality are offered. 

Q2. What future works have the authors mentioned in the paper "A multiple-item scale for assessing electronic service quality" ?

As the discussion in the preceding section illustrates, there is a need for further research to deepen their understanding of the assessment, antecedents, and consequences of e-SQ. The four perceptual attributes that constitute system availability suggest that companies may not have full control over performance on this dimension ; the equipment at the customer ’ s end ( e. g., type of computer and Internet connection ) is also likely to affect performance on this dimension. Companies should be ( a ) sensitive to potential deleterious effects of sophisticated Web site design features on system availability and ( b ) proactive in identifying aspects of system availability that are beyond their control and devising appropriate communication scripts to appease complaining customers. Online companies can best use the scales in tandem ( with the latter being administered only to customers who have had problems or questions ) to track over time—and across competing Web sites—customers ’ overall e-SQ perceptions. 

Q3. What incentive was used to get participants to complete the surveys?

As an incentive for participation, respondents completing the surveys were entered into a random drawing to receive one of several cash prizes. 

Q4. Why was the pooling of data appropriate at this scale refinement/reduction stage?

The pooling of data was appropriate at this scale refinement/reduction stage because the purpose was to produce a general scale that would be appropriate for assessing service quality of a variety of sites. 

Q5. Why did the authors set aside these items for analysis?

Because recovery was an important aspect of service, the authors set aside these items for separate analysis to develop an e-recovery service scale. 

Q6. What did they use to develop a scale for measuring site quality?

Yoo and Donthu (2001) developed a nine-item SITEQUAL scale for measuring site quality on four dimensions: ease of use, aesthetic design, processing speed, and security. 

Q7. What scale is relevant for a Web site’s entire customer base?

The basic E-S-QUAL Scale (relevant for a Web site’s entire customer base) is a four-dimensional, 22-item scale, whereas E-RecS-QUAL (relevant for the portion of the customer base with recovery service experience) is a three-dimensional, 11-item scale. 

Q8. What are the three dimensions of the e-SQ scale?

Parasuraman, and Malhotra’s (2000) study identified dozens of Web site features at the perceptualattribute level and categorized them into 11 e-SQ dimensions:1. Reliability: Correct technical functioning of the site and the accuracy of service promises (having items in stock, delivering what is ordered, delivering when promised), billing, and product information. 

Q9. What is the reason for the nonsignificant effects of system availability and privacy?

multicollinearity due to the strong correlations among the summed-score measures of the four E-S-QUAL dimensions seemed to be a plausible explanation for the nonsignificant effects of system availability and privacy. 

Q10. What are the five broad sets of criteria that are relevant to e-SQ perceptions?

On the basis of a comprehensive review and synthesis of the extant literature on e-SQ, Zeithaml, Parasuraman, and Malhotra (2002) detailed five broad sets of criteria as relevant to eSQ perceptions: (a) information availability and content, (b) ease of use or usability, (c) privacy/security, (d) graphic style, and (e) reliability/fulfillment. 

Q11. What did they use to develop a scale called eTailQ?

Wolfinbarger and Gilly (2003) used online and offline focus groups, a sorting task, and an online-customer-panel survey to develop a 14-item scale called eTailQ. 

Q12. What is the strongest predictor of customer satisfaction and quality?

In fact, Wolfinbarger and Gilly (2003) found that reliability/ fulfillment ratings were the strongest predictor of customer satisfaction and quality, and the second strongest predictor of intentions to repurchase at a site. 

Q13. How many observations were needed to verify the dimensionality of the refined scales?

To have a sufficient number of observations for verifying the factor structures and dimensionality of the refined scales through confirmatory factor analysis, the authors set a minimum sample size of 200 respondents for each site.