E TransQual A Transaction Process Based Approach For Capturing SQ in Online Shopping
E TransQual A Transaction Process Based Approach For Capturing SQ in Online Shopping
E TransQual A Transaction Process Based Approach For Capturing SQ in Online Shopping
Abstract
Existing e-service quality scales mainly focus on goal-oriented e-shopping behavior excluding hedonic quality aspects. As a consequence,
these scales do not fully cover all aspects of consumer's quality evaluation. In order to integrate both utilitarian and hedonic e-service quality
elements, we apply a transaction process model to electronic service encounters. Based on this general framework capturing all stages of the
electronic service delivery process, we develop a transaction process-based scale for measuring service quality (eTransQual). After conducting
exploratory and confirmatory factor analysis, we identify five discriminant quality dimensions: functionality/design, enjoyment, process,
reliability and responsiveness. All extracted dimensions of eTransQual show a significant positive impact on important outcome variables like
perceived value and customer satisfaction. Moreover, enjoyment is a dominant factor in influencing both relationship duration and repurchase
intention as major drivers of customer lifetime value. As a result, we present conceptual and empirical evidence for the need to integrate both
utilitarian and hedonic e-service quality elements into one measurement scale.
2006 Elsevier Inc. All rights reserved.
Keywords: Electronic service quality; Online shopping; Transaction process; Scale development
1. Introduction
The rapid expansion of information and communication
technologies in daily business activities is the most important
long-term trend in the business world (Rust, 2001). Accordingly,
a large growth potential is forecasted especially for the provision
of products and services via the Internet (Evanschitzky et al.,
2004). If and how this potential can be exploited sufficiently
depends largely on Internet retailer's ability to meet customers'
expectations in the virtual shopping environment (Zeithaml et
al., 2002). According to Meuter et al. (2000) the number of
dissatisfied online customers experiencing service breakdowns,
lost orders, or inadequate complaint handling is notable. These
unsatisfying service encounters cause annual Web sales losses of
Corresponding author. Tel.: +49 621 181 1572; fax: +49 621 181 1571.
E-mail addresses: hans.bauer@bwl.uni-mannheim.de (H.H. Bauer),
tomas.falk@bwl.uni-mannheim.de (T. Falk),
maik.hammerschmidt@bwl.uni-mannheim.de (M. Hammerschmidt).
1
Tel.: +49 621 181 1562; fax: +49 621 181 1571.
2
Tel.: +49 621 181 1569; fax: +49 621 181 1571.
0148-2963/$ - see front matter 2006 Elsevier Inc. All rights reserved.
doi:10.1016/j.jbusres.2006.01.021
2.1. E-services
A review of the relevant literature reveals the existence of
various approaches to conceptualize e-services. Rust and
Lemon (2001, p. 86) very generally describe e-services as
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868
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Information
Phase
Agreement
Phase
Fulfillment
Phase
After-Sales
Phase
Market offerings
are examined
and compared
Provider and
customer agree
on the transaction conditions
Accomplishment
of the transaction
Customer care
and relationship
building
Important service
quality elements:
Important service
quality aspects:
Important service
quality aspects:
Important service
quality aspects:
Functionality
Accessibility
Efficiency of
navigation
Content
Web site design
Enjoyment of
Web site use
Frictionless
activities
Efficient order
process
Navigation tools
Web site
architecture
Security
Privacy
Reliable service
delivery
Complaint
handling
Responsiveness
Return policy
Nonroutine
services
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variables are used to evaluate the predictive validity of our eservice quality dimensions. Perceived value was measured as
agreement with three cost/benefit statements. Customer satisfaction was assessed by four items suggested by HenningThurau et al. (2002).
To examine the economic relevance of our e-service quality
measure, we aimed to investigate its impact on relationship
duration and repurchase intention as important drivers of
customer lifetime value (Anderson et al., 2004). Relationship
duration was assessed by the question I invest maximum effort
to maintain the relationship (Henning-Thurau et al., 2002)
following the reasoning that such relationship-specific, idiosyncratic investments rise when the relationship lengthens. This
item seems to be more reliable than merely asking respondents
when the provider was first selected, as the latter provides little
information about how long an intensive relationship will be
maintained in future. Thus, we employ a measure which better
captures a relationship's expected duration in terms of its
continuity compared to measures focussing on past behaviour.
Repurchase intention was captured by one item in line with
Homburg and Giering (2000). All items were assessed using the
same numeric scale ranging from 1 = strongly disagree to
5 = strongly agree.
On the basis of control questions relating to online shopping
experience and frequency of usage irrelevant questionnaires
could be identified and were not taken into account. This
resulted in 384 fully usable questionnaires. In order to assess the
representativeness of the sample, we collected and compared
socio-demographic data of the respondents with those reported
in an extensive national study of Internet users conducted by
W3B, one of the leading German Market Research Institutes for
interactive media (W3B, 2004). Our comparison revealed a
close match between both samples. Table 1 summarizes the
basic demographic characteristics of our sample.
Table 1
Sample profile
Variable
Gender
Male
Female
Age
< 20
2040
4160
> 60
Education
Low (secondary school)
Middle (high school; apprenticeship)
High (university; polytechnic)
Experience with online shopping provider
< 3 months
36 months
612 months
> 12 months
Frequency of using the provider in the last 12 months
< 3 times
36 times
> 6 times
Percentage
60
40
7
63
25
5
26
32
42
7
7
12
74
16
39
45
Table 2
Psychometric properties and CFA results for the retained 25 items of the
eTransQual scale
Dimensions
Items
Functionality/design
1. Efficiency of
navigation
2. Accessibility of
relevant content
3. Clarity of the
Web site
4. Relevance of
information
5. Timeliness of
information
6. Visual appeal
7. Professional
Web site design
Enjoyment
8. Personalization
of information
and offerings
9. Fun of using the
Web site
10. Excitement when
shopping online
11. Entertainment
provided by the
Web site
Process
12. Availability of the
Web site
13. Stability of data
transmission
14. Efficiency of online
order processing
15. Waiting time
Reliability
16. Timeliness of order
delivery
17. Accuracy of order
delivery
18. Product availability
19. Breadth and depth
of product range
20. Encoding of
personal information
21. Confidentiality
Responsiveness
22. Availability of
alternative
communication channels
23. Return policy
24. Availability of
service personnel
25. Promptness of
reactions to requests
Mean Factor
Indicator Cronbach's AVE
loadings reliability
(CFA)
3.8
0.74
0.55
3.8
0.81
0.66
4.0
0.79
0.62
4.2
0.71
0.50
4.1
0.66
0.44
4.0
4.2
0.69
0.64
0.48
0.41
3.6
0.60
0.36
4.0
0.99
0.98
3.2
0.82
0.67
3.1
0.88
0.77
4.3
0.77
0.59
4.4
0.68
0.46
4.1
0.69
0.48
4.2
0.64
0.41
4.3
0.73
0.53
4.6
0.67
0.45
3.9
4.3
0.68
0.66
0.46
0.44
4.0
0.68
0.46
4.0
0.68
0.46
3.8
0.75
0.56
3.7
3.7
0.77
0.81
0.59
0.66
3.6
0.95
0.90
0.89
0.52
0.84
0.70
0.88
0.50
0.83
0.47
0.85
0.68
eTransQual
Responsiveness
.95
Promptness
of reactions
to requests
Return
policy
.81
.77
Availability
of service
personal
.73
Timeliness
of order
delivery
Reliability
Product
availability
.68
.77
.67
Accuracy of
order
delivery
Availability
of Web site
.66
Breadth and
depth of
product
range
.94
.64
Waiting time
.68
Confidentiality
.77
Functionality/
Design
Process
.75
Availability of
alternative
communication
channels
.87
.85
.69
68
Stability of
data
transmission
.68
Encoding of
personal
information
Enjoyment
.60
Efficiency of
online order
processing
.74
Efficiency of
navigation
.99
Personalization of
service
.79
Clarity of
the Web site
.81
Accessibility
of relevant
content
.82
Fun of using
Web site
.71
Relevance
of
information
.88
Excitement
when
shopping
online
.66
Timeliness
of
information
.69
Visual
appeal
Entertainment
provided by
the Web site
.64
Professional
Web site
design
.67
Fit measures: 2 = 653, df= 270, RMSEA = .10, CFI = .99, RMR = .07, GFI = .98, AGFI = .97
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Table 3
Fornell/Larcker Test for the five quality dimensions
Functionality/design
Enjoyment
Process
Reliability
Responsiveness
Functionality/design
Enjoyment
Process
Reliability
Responsiveness
0.52
0.51
0.66
0.64
0.39
0.70
0.43
0.42
0.26
0.50
0.52
0.33
0.47
0.31
0.68
Mean Factor
Cronbach's
loadings
Perceived value
1.Overall convenience of Web site use
4.1
2.Costbenefit ratio (value for money and 4.0
effort)
3.Reasonable price (economical offers)
3.9
Satisfaction
4.Overall satisfaction with provider
4.2
5.Decided for the best provider
4.3
6.Satisfaction with decision
4.3
7.Wise choice
4.0
0.86
0.82
0.90
0.75
0.95
0.91
0.94
0.94
0.86
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Table 6
Relationships of eTransQual dimensions to major drivers of customer
profitability
Construct
Relationship duration
Repurchase intention
Functionality/design
Enjoyment
Process
Reliability
Responsiveness
R2
0.06
0.35
0.13
0.02
0.33
0.29
0.10
0.16
0.11
0.30
0.12
0.41
(2004) state that customers become operant resources (coproducers) in the service delivery chain. Thus, customer value
is created by the customer himself throughout the relationship. Consequently, the willingness to provide customers with
functional tools and efficient processes for co-production is
critical for value creation. In total, the derived e-service
quality dimensions explain 63% of the variance in perceived
value.
Four of the five quality dimensions show a strong positive
effect on customer satisfaction. Comparable to the findings for
perceived value, reliability and functionality/design are the most
important satisfaction drivers with Beta weights of 0.41 and
0.20. Altogether, our quality factors explain 65% of the variance
of customer satisfaction.
Reliability seems to be the most powerful driver of all
dependent variables. This finding confirms that the reliability
issues represent the most critical factor for assessing the
perceived value and satisfaction with online retailers.
Perceived value
Satisfaction
Functionality/design
Enjoyment
Process
Reliability
Responsiveness
R2
0.19
0.12
0.12
0.36
0.16
0.61
0.26
0.12
0.22
0.23
0.15
0.63
0.20
0.07
0.14
0.41
0.15
0.65
This study compares a newly developed scale, eTransQual, vis--vis two scales well established in the literature
the eTailQ scale developed by Wolfinbarger and Gilly
(2003) and the E-S-Qual Scale presented by Parasuraman et
al. (2005) (Fig. 3). We integrate hedonic quality aspects
which result from intrinsic shopping motives. Neither eTailQ
nor E-S-Qual considers this dimension. Strong evidence for
the importance of hedonic aspects for evaluating online
shopping experiences is demonstrated both by the results
from the scale validation procedure as well as the
exploration of their impact on marketing outcome variables.
Their strong influence on perceived value indicates that
shopping behavior cannot be described as purely goaloriented and rational as suggested by several authors.
Instead, hedonic and emotional motives play an important
role. By providing a flow experience online retailers can
strongly improve quality perceptions and thereby enhance
perceived value. The weak relationship to satisfaction
provides some evidence that experiencing fun and excitement during Web site usage is expected from consumers
without explicit articulation as this lies in the nature of
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eTailQ
E-S-Qual
eTransQual
(Wolfinbarger and
Gilly 2003)
Core E-S-Qual
E-RecS-Qual
Compensation (3)
Contact (3)
Responsiveness (4)
Confidentiality (2)
Reliability (4)
Process (3)
Responsiveness (4)
Privacy (3)
Fulfillment (7)
utilitarian quality
(extrinsic)
Availability (4)
Functionality (5)
Efficiency (6)
hedonic quality
(intrinsic)
Enjoyment (4)
Fig. 3. Comparison of eTransQual with two existing scales. The size of the rectangles indicates the conceptual richness (content coverage) of the dimensions. The
number of items is shown in parentheses. The terms in italics refer to quality subdimensions.
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