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San Sebastián / Donostia 2015
The Influence of the Electronic Service Encounter as a
Determinant of the Relationships Between Perceived Benefits-Risks
and Service Quality-Satisfaction-Loyalty Intentions
Ramón Barrera Barrera
rbarrera@us.es
Universidad de Sevilla
Antonio Navarro García
anavarro@us.es
Universidad de Sevilla
José Manuel Ramirez Hurtado
jmramhur@upo.es
Universidad de Pablo de Olavide
ABSTRACT
In the context of electronic commerce B2C, two different service encounters can
take place: 1) service encounters without incidents during which customers get the service
for themselves and without the presence of employees and 2) service encounters with
incidents with interpersonal and non-interpersonal interactions. Taking the traditional
service quality-satisfaction-loyalty intention chain as a reference, in this work we analyze the
effect of a Website’s service quality on the benefits and risks that online shoppers perceive
and the effects of these benefits and risks on loyalty intentions, taking into account these two
scenarios. Data collection was obtained from a convenience sample of online shoppers. We
followed a quota sampling approach, with the intention of reproducing the sociodemographic profile of the population of Spanish online shoppers. The results obtained
reflect that 1) the type of the service encounter has a moderating effect in these relationships.
In this sense, the effects are stronger when incidents take place and are satisfactorily resolved;
2) the electronic service quality is a determinant of the online shoppers’ perceived benefits
and risks; 3) regardless of the type of service encounter, reliability and recovery are the most
important dimensions in the assessing of a Website’s service quality; 4) furthermore,
consumers who have had no incident during the service encounter perceive a greater service
quality, show higher levels of satisfaction and loyalty intentions toward the Website and
perceive more benefits and less risks from online shopping than those who have had a
problem during the service provision.
KEY WORDS: electronic service quality, online shopping behavior, satisfaction, loyalty
intentions.
INTRODUCTION
Internet has revolutionized commerce and business (e.g., Hoffman and Novak, 1996) and
one of the most significant indicators of this transformation has been the adoption of the
online retail channel. Specifically, 43% of the population of the EU 27 has purchased goods
or services through the Internet (Eurostat, 2012). This volume of business generated by the
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B2C e-commerce accounts for 14% of the total turnover of companies in these countries. In
addition, 73% of households and 87% of companies in the EU 27 are connected to the Web
(Eurostat, 2012). The face to face interpersonal interactions between sellers and customers
has been replaced with technology-based Web interfaces. The management of these service
encounters should be a priority for any organization with a presence on the Internet. This
paper develops and tests a model that reflects the importance of service encounter in Internet
shopping.
Typically, online customers can more easily compare alternatives than offline customers and
a competing offer is just a few clicks away on the Internet (Shankar et al., 2003). Add to that
online consumers have a wider range of choices in selecting products and services, and highly
competitive prices. As a result, competition between different Websites is high in order to
attract the users’ attention and make them repeat a visit. In this situation, it is generally not
easy for online retailers to gain competitive advantages based solely on a cost leadership
strategy (Jun et al., 2004). Many researchers point out that to deliver a superior service quality
is one of the key determinants of online retailers’ success (Zeithaml et al., 2002) and it is a
major driving force on the route to long-term success (Fassnacht and Koese, 2006). This also
involves a greater development of this electronic model and will also allow the online
suppliers to differentiate themselves from the competition (Alt et al., 2010).
To set out which aspects must be evaluated in the service quality, many researchers have
used the service encounter approach (Bitner, 1990; Bitner et al., 1990; etc.). Shostack (1985:
p.243) defines the term service encounter as “a period of time during which a consumer
directly interacts with a service”. This definition encompasses all aspects of the service firm
with which the consumer may interact, including its personnel, its physical facilities and other
tangible elements, during a given period of time. Shostack (1985) does not limit the encounter
to the interpersonal interactions between the customer and the firm. In fact, she suggests
that service encounters can occur without any human interaction element. This view of a
service encounter is still valid in the online services context. In the evaluation of e-service
quality, it is necessary to consider all the cues and encounters that occur before, during and
after the transactions (Zeithaml et al., 2002). Specifically, two different service encounters
can take place in the context of Internet: (1) service encounters with non-interpersonal
interactions, during which customers get the service for themselves, without the presence of
employees (service encounter without incidents) and (2) service encounters with
interpersonal and non-interpersonal interactions. Generally, the interactions with a member
of the organization take place when a customer needs to solve any problem or doubt that
may arise during the service delivery (service encounter with incidents). However, many
works do not differentiate these two types of service encounter in the evaluation of the
electronic service quality. In this sense, Parasuraman et al. (2005) criticize the work of
Wolfinbarger and Gilly (2003), as the items of the customer attention dimension are
answered by all the respondents instead of only by those who had problems or doubts. In
other cases, the dimensions proposed to measure the electronic service quality does not
consider how the problems or doubts are resolved when there are incidents in the service
encounter (e.g., Aladwani and Palvia, 2002).
On the other hand, in the literature about electronic services, most authors have limited
themselves to studying the influence of the service quality (or its dimensions) on satisfaction
and loyalty intentions. However, recent works have made it clear that other variables perform
an important role in this chain. For example, Barrutia and Gilsanz (2012) propose a model
in which the consumer knowledge-related resources are integrated into the e-service qualityvalue-satisfaction-behavior intentions chain. Ranaweera et al. (2004) suggest that the user
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characteristics have a moderating effect on the relationship between Website satisfaction and
consumer behavioral and attitudinal outcomes. Therefore, taking the traditional service
quality-satisfaction-loyalty intention chain as a reference, in this work we analyze the effect
of a Website’s service quality on the benefits and risks that online shoppers perceive and the
effects of these benefits and risks on loyalty intentions. We do so taking into account the
two scenarios previously differentiated. Moreover, we are going to analyze if the assessment
of the perceived quality, the satisfaction with the purchase, the loyalty intentions toward a
Website and the benefits and risks of online shopping perceived by the shoppers differ from
one service encounter to another.
To achieve the objectives proposed, the article is structured as follows. First, we review the
most relevant research to help us identify the dimensions of e-service quality and the main
online shopping benefits and risks. We describe the sample and measures used in the study.
Then, we show the results of the empirical research. Finally, we discuss the conclusions and
implications for management, the limitations and future research lines.
THEORETICAL BACKGROUND
The use of technology in service delivery
The application of technology in services provisions also means the appearance of a new
concept: electronic services. The contributions which have been made in the literature about
the study of electronic services originate in the areas of marketing services (e.g., Janda et al.,
2002), of electronic commerce (e.g., Yoo and Donthu, 2001), of research about information
systems (e.g., Aladwani and Palvia, 2002) or in works which are centered on the technology
acceptation model (TAM) (e.g., Davis 1989; Davis et al., 1989; etc.). Although there is not a
commonly-accepted definition (Fassnacht and Koese, 2006), some have been proposed in
the literature about the electronic services concept. For example, Rust (2001) defines the
concept as “that service which is offered by an organization through an electronic system”
(p. 283). Colby and Parasuraman (2003) suggest that “electronic services are services offered
by an electronic means –normally Internet – and which refer to transactions begun and to a
great extent controlled by the consumer” (p. 28). Fassnacht and Koese (2006) state that they
are “those services that are offered using information and communication technologies in
which the consumer only interacts with a user’s interface” (p.23). In these definitions two
basic properties of electronic services stand out. Firstly, they are services which are offered
through an electronic system–e.g., ATMs, telephonic banking, automatic billing in hotels
through an interactive television, vending machines, etc. Secondly, electronic services are
technological self-services or self-services based on technology (SSTs) (Dabholkar, 1996;
Bitner et al., 2000; Dabholkar, 2000; Meuter et al., 2000). Customers begin and control the
transaction performing active roles in the services provisions, in such a way that they are able
to obtain the product or the service by themselves, even managing to get by without
employees who attend the public. Nevertheless, some customers prefer interaction with
employees, considering the service encounter as a social experience (Zeithaml and Gilly,
1987).
The delivery of these electronic services offers benefits for both firms and customers. The
use of technology enables the service provider to have a standardized service delivery,
reduced labor costs, to expand the delivery options (Curran and Meuter, 2005) and to
improve productivity and convenience for their employees and customers (La and
Kandampully, 2002). However, the infusion of technology can also raise concerns of privacy,
confidentiality and the receipt of unsolicited communications (Bitner et al., 2000). Some
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studies have analyzed the factors that contribute to (or not) the use of an SST. For example,
the ease of use and usefulness are critical constructs that influence an individual’s attitude
toward a technology (Davis, 1989). Curran and Meuter (2005) propose four antecedents for
attitudes toward the SSTs: ease of use, usefulness, risk and need for interaction. Dabholkar
(1996) also found control and waiting time to be important determinants for using an SST.
More recently, Belanche et al. (2011) suggest that the use of online services is determined by
the perceived usefulness, the attitude toward its use and the perceived control. Consumers
will weigh up these advantages and disadvantages when deciding whether or not to use an
SST. For online shopping, their use will depend on the benefits and risks perceived by
Internet users.
Online shopping benefits and risks
Different studies have identified two major types of behaviors which can be recognized as
the motivations or benefits sought in Internet shopping (Hoffman and Novak, 1996;
Hoffman and Novak, 1997; Wolfinbarger and Gilly, 2001): experiential or pleasure shopping
and task or goal-oriented shopping.
Experiential shopping responds to a more spontaneous and exploratory behavior in which
the customer’s aspiration is to simply achieve positive shopping experiences, without any
guiding beyond the desire to be entertained, the fun itself or to be immersed in this
experience. The second type of behavior is the so-called task or goal-oriented shopping. In
this type of behavior there are underlying functional motivations or the search for efficiency
in the purchase. Unlike the previous consumer, this one uses the Internet as a means to carry
out shopping for its convenience, prices, time saving, greater offer, etc.
The literature suggests that, among the different factors valued by consumers when they
purchase online, functional or utilitarian motivations prevail over those that are nonfunctional or hedonistic (Wolfinbarger and Gilly, 2001). In the literature, the main functional
motivations which lead an Internet user to shop online are: 1) convenience, 2) the greater
variety of products and services and 3) lower prices than in traditional establishments.
Contrariwise, the most cited inconveniences were: 1) the fear of financial losses, 2) logistical
problems and 3) not knowing how to do it.
Convenience means a greater flexibility and time saving for the customer (Wolfinbarger and
Gilly, 2001; Zeithaml et al., 2000; Rohm and Swaminathan, 2004; Brengman et al., 2005). In
this sense, online shopping can be done at any time of the day and 365 days a year so the
customer is not limited to the shopping hours of traditional establishments. Furthermore, it
can be done from any place which has an Internet connection. In this way, customers save
time as they do not need to go the sales point. Secondly, Internet users state that in the Web
they can find a greater variety of products and services and at better prices than in traditional
establishments (Electronic Commerce Study B2C, 2012; Swinyard and Smith, 2003; Forsythe
et al., 2006; Brengman et al., 2005). Occasionally, the Web is even the only means to find a
product or a service.
With respect to the inconveniences of online purchases, Internet users are concerned about
suffering some kind of fraud (Allred et al., 2006; Forsythe et al., 2006; Brengman et al., 2005).
In this sense, the main reasons that Internet users give for not making these purchases are:
1) insecurity and mistrusting the payment means, 2) fear of giving personal data and 3)
mistrusting the provider (Electronic Commerce Study B2C, 2012). Secondly, online non-
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shoppers compared to online shoppers consider that Internet shopping can cause logistical
problems (Forsythe et al., 2006; Brengman et al., 2005; Swinyard and Smith, 2003). In this
way, some people reject online shopping as they do not like to pay delivery costs, they think
that it will be more difficult to return the product bought on Internet, they value the
immediate possession of the purchase more, without having to wait for the mail delivery,
they think that they can have trouble with the delivery, etc. Finally, some Internet users reject
online shopping because they do not know how to do it or they have problems finding
something in Internet (Swinyard and Smith, 2003; Forsythe et al., 2006; Allred et al., 2006).
Measurement of electronic service quality
Since the pioneering work of Zeithaml et al. (2002), the quality of online services has been
explored in some depth. Parasuraman et al. (1985) suggest that service quality is an abstract
and elusive construct because of three features that are unique to services: the intangibility,
heterogeneity and inseparability of production and consumption. The best-known approach
for measuring service quality is the SERVQUAL model (Parasuraman et al., 1988). The
original five dimensions of SERVQUAL are tangibles, reliability, responsiveness, assurance
and empathy. Some academic researchers have extended the SERVQUAL dimensions to the
online context (Kaynama and Black, 2000; Sanchez-Franco and Villarejo-Ramos, 2004; Long
and McMellon, 2004). However, traditional theories and concepts about service quality
cannot be directly applied to the online context due to the important differences between
the two settings. First, the service quality literature is dominated by people-delivered services,
while in online services, human-to-human interactions are substituted by customer-toWebsite interactions (Parasuraman et al., 2005). Therefore, responsiveness and empathy
dimensions can be evaluated only when the online customer contacts a member of the
organization. Second, although reliability and security dimensions may be useful, tangibles
are irrelevant as the customer only interacts with the Website. Third, new dimensions are
relevant, such as Website design or information quality. Fourth, if the evaluation of the
quality of a traditional service is going to depend especially on the personnel in charge of the
service provision, the quality of the services which are offered through Internet are going to
largely depend on the consumers themselves and their interaction with the Website
(Fassnacht and Koese, 2006). Fifth, compared to the traditional quality of service, the eservice quality is an evaluation which is more cognitive than emotional (Zeithaml et al., 2000).
In this way, these authors state that negative emotions such as annoyance and frustration are
less strongly shown than in the quality of the traditional service, while positive feelings of
affection or attachment which exist in traditional services do not appear in the Internet
context.
Various conclusions can be inferred from reviewing the literature: (1) the e-service quality is
a multidimensional construct (Zeithaml et al., 2000) whose measurement must gather the
evaluation of the interaction with the Website, the evaluation carried out by the customer of
the product or service received and, if any problem arises, how the Website of the online
firm handles it (Collier and Bienstock, 2006). Although most researchers are in favor of the
evaluation of this latter aspect, Fassnacht and Koese (2006) state that we should not evaluate
the human interaction which can take place in the electronic services provisions, given their
self-service nature. (2) There are basically two approaches when tackling the
conceptualization and measurement of e-service quality (Table 1). The epicenter of the first
approach is the technical characteristics of the Website (technical quality). The first studies
about Internet service quality belong to this first group. They centered uniquely on the
interaction that takes place between the customer and the Website. None of this research
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gathers all the aspects of the online purchasing process and therefore they do not carry out
a complete evaluation of e-service quality. The main proposal of these measurement
instruments is to generate information for the site designers, more than measuring the quality
of the service which customers perceive (Parasuraman et al., 2005). This weakness is the
main motive for the appearance of the second approach (service quality) which offers a more
complete vision of the field of the e-service quality construct. The dimensions and the
measurement instruments gather not only the technical aspects of the Website, but also how
the customers perceive the quality of the product or service received and how their problems
or doubts were solved during the service provision. (3) The researchers do not agree when
identifying the dimensions of the quality of an electronic service. Moreover, the meaning,
the importance and the items of the same dimension vary from one study to another. These
differences are partly due to the scales being focused on one service in particular. (4) The
evaluation of e-service quality is carried out at different levels of abstraction depending on
the study. Most researchers offer a set of dimensions (first order constructs) and a series of
indicators to measure each of them (e.g., Ho and Lee, 2007). However, other authors propose
second order hierarchical models (e.g., Wolfibarger and Gilly, 2003), or even third order
models (e.g., Fassnacht and Koese, 2006; O´Cass and Carlson, 2012). (5) Some authors
propose scales in which problem solving does not appear (e.g., Liu et al., 2009) or is evaluated
for the whole sample (e.g., Wolfinbarger and Gilly, 2003). However, this last aspect must
only be evaluated by those people who had problems during the transaction (Parasuraman
e.g., 2005; Collier and Bienstock, 2006).
Table 1. Online service quality scales in previous studies
Focus: Technical quality
Article
Dimensions
Aladwani and Palvia (2002)
Appearance; specific content; content quality; technical
adequacy
Bressolles and Nantel (2008)
Information; ease of use; site design; security/privacy
Duque-Oliva and Rodríquez-Romero (2012)
Efficiency; performance; privacy; system; variety
Information and service quality; system use; playfulness; system
design quality
Adequacy of information; appearance; usability; privacy;
security
Ease of understanding; intuitive operation; information quality;
interactivity; trust; response time; visual appeal; innovativeness;
flow
Liu and Arnett (2000)
Liu, Du, and Tsai (2009)
Loiacono, Watson, and Goodhue (2002)
Ranganathan and Ganapathy (2002)
Information content; design; security; privacy
Sabiote, Frías, and Castañeda (2012)
Ease of use; availability; efficacy; privacy; relevant information;
Sanchez-Franco and Villarejo-Ramos (2004)
Assurance; tangibles; reliability; empathy, ease of use,
enjoyment; responsiveness
Trocchia and Janda (2003)
Performance; access; security; sensation; information
Yoo and Donthu (2001)
Ease of use; design; speed; security
Focus: Electronic Service quality
Article
Barrutia and Gilsanz (2012)
Bauer, Falk, and Hammerschmidt (2006)
Collier and Bienstock (2006)
Dimensions
Process quality: efficiency; system availability; design;
Information and Outcome quality
Functionality / design; enjoyment; process; reliability;
responsiveness
Process dimension: functionality; information; accuracy; design;
privacy; ease of use; Outcome dimension: order accuracy; order
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Fassnacht and Koese (2006)
Ho and Lee (2007)
Janda, Trocchia, and Gwinner (2002)
Kaynama and Black (2000)
O´Cass and Carlson (2012)
Parasuraman, Zeithaml, and Malhotra (2005)
Rolland and Freeman (2010)
condition; timeliness; Recovery dimension: interactive fairness;
procedural fairness; outcome fairness
Quality of the environment: graphics quality, clear presentation,
quality of delivery: attractive assortment, quality of information,
ease of use, technical quality, outcome quality: reliability,
functional benefit; emotional benefit;
Information quality; security; functionality; customer
relationships; responsiveness
Performance; access; security; sensation; information
Content; accessibility, navigation, design and presentation;
responsiveness; environment; customization
e-Communication quality; e-Systems operation quality; eAesthetic quality; e-Exchange process quality
E-S-QUAL: efficiency; system availability; fulfillment; privacy;
E-RecS-QUAL: responsiveness; compensation; contact
Ease of use; information content; fulfillment; reliability;
security/privacy; post-purchase customer service
Sheng and Liu (2010)
Efficiency; fulfillment; system accessibility; privacy
Sohail and Shaikh (2008)
Efficiency and security; fulfillment; responsiveness
Tsang, Lai, and Law (2010)
Wolfinbarger and Gilly (2003)
Yen and Lu (2008)
Functionality; information quality and content; fulfillment and
responsiveness; safety and security; appearance and
presentation; customer relationship
Design; fulfillment/reliability; privacy/security; customer
service
Efficiency; privacy; protection; contact; fulfillment
Source: own elaboration
If we set out from the conceptualization proposed by Collier and Bienstock (2006, p. 263),
the domain of the service quality construct should gather the evaluation of the quality of the
process of online interaction (technical aspects), the result of how the service or the product
is delivered (result) and the way in which the service failures (if they occur) are managed
(service recovery). The technical characteristics of the Website must consider: 1) the design
(Yoo and Donthu, 2001), also called appearance (Aladwani and Palvia, 2002), the visual
aspect (Loiacono et al., 2000), or aesthetics (Zeithaml et al., 2000); 2) the functionality (Collier
and Bienstock, 2006), also called technical adequacy (Aladwani and Palvia, 2002), efficiency
(Parasuraman et al., 2005) or ease of use (Janda et al., 2002); and 3) privacy (Collier and
Bienstock, 2006) or the security that the Website offers (Wolfinbarger and Gilly, 2003).
Secondly, the evaluation of the product or service delivery has been carried out with a single
dimension generally called reliability (Wolfinbarger and Gilly, 2003; Yang and Jun, 2002;
Fassnacht and Koese, 2006) or performance (Janda, Trocchia and Gwinner, 2002;
Parasuraman et al., 2005). Thirdly, if we take as a reference the works of Parasuraman et al.
(2005) and Collier and Bienstock (2006), the evaluation of the quality of the e-service
recovery responds to two aspects: the possibility of getting into touch with the firm (access
or contact), and the effectiveness of problem solving (usually called response capacity).
Following the literature review, the dimensions proposed to evaluate e-service quality are:
design, functionality, privacy, reliability and recovery. These dimensions are herewith defined
and explained.
Design
The design of a Website plays an important role in attracting, sustaining and retaining the
interest of a customer in a site (Ranganathan and Ganapathy, 2002). Numerous studies in
the literature consider the Website design as a dimension of e-service quality (Aladwani and
Palvia. 2002; Loiacono et al., 2000; Yoo and Donthu, 2001; Liu et al., 2009; etc.). The
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literature review about the key factors of a Website design highlights three important issues:
attractiveness, proper fonts and proper colors. Although it has sometimes been regarded as
a purely aesthetic element, prior studies have demonstrated the influence of Website design
on site revisit intention (Yoo and Donthu, 2001), customer satisfaction (Tsang et al., 2010)
and loyalty intentions (Wolfinbarger and Gilly, 2003).
Functionality
Functionality refers to the correct technical functioning of the Website. It is one of the most
basic requirements for any kind of Website and its meaning is closely related to the
dimensions of the system availability (Parasuraman et al., 2005), or technical adequacy
(Aladwani and Palvia, 2002). The five items of functionality that we considered were: always
up and available, has valid links, loads quickly, enables us to get on to it quickly and makes it
easy and fast to get anywhere on the site. Its impact on online customers´ higher-order
evaluations pertaining to Websites has also been observed. For example, Tsang et al. (2010)
conducted an investigation in the travel online context in which the functionality was found
to be the most important dimension in increasing customer satisfaction.
Privacy
Websites are usually collecting and storing large amounts of data concerning their users’
activities, user evaluations of online questionnaires or personal data (Tan et al., 2012). As a
result, one of the aspects that most concern online consumers is the privacy of personal
information (ONTSI, 2012). In our study, privacy refers to the degree to which the customer
believes that the site is safe from intrusion and personal information is protected
(Parasuraman et al., 2005; p. 219). The privacy of a Website should be reflected through
symbols and messages to ensure the security of payment and the customer's personal
information not being shared with other companies or Internet sites. As such, there appears
to be a high degree of support for privacy as an important e-service quality dimension and it
was found to be one of the most significant dimensions in increasing customer satisfaction
(Janda et al., 2002).
Reliability
The evaluation of service delivered quality has been carried out with the dimensions of:
fulfillment/reliability (Wolfinbarger and Gilly, 2003), reliability (Yang and Jun, 2002),
performance (Janda et al., 2002), fulfillment (Parasuraman et al., 2005), etc. Congruent with
these articles, our study considers reliability as an important dimension of e-service quality.
Moreover, in the context of online services, the information made available by the Websites
is an important component of the service delivered. Therefore, reliability refers to the
accuracy of the service delivered by the company, the billing process is correct and the
information that appears on the Website is clear, current and complete. The service delivered
quality or reliability has been empirically shown to have a strong impact on customer
satisfaction and quality, and the second strongest predictor of loyalty intentions and attitude
towards the Website (Wolfinbarger and Gilly, 2003).
Recovery
An essential aspect in the evaluation of the quality of an electronic service is the way in which
the company solves problems or doubts which may arise during its provision. There is no
doubt that errors in the electronic service provision cause the loss of customers in many
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cases and a negative word of mouth. What is more, the physical separation between the
customer and the supplier and the fact that customers can choose another company with a
simple click accentuates even more the importance of solving these mistakes (Collier and
Bienstock, 2006). Different dimensions have been proposed in the literature to evaluate this
aspect: responsiveness (Zeithaml et al., 2000), customer attention (Wolfinbarger and Gilly,
2003), communication (Cai and Jun, 2003), access (Yang and Jun, 2002), etc. In our study,
service recovery refers to the customer’s capacity to communicate with the organization and
how any problem or doubt that may arise is solved. Thus, the Website should show its street,
e-mail, phone or fax numbers, the customer service must be available 24 hours a day/7days
a week and the response to the customer´s inquiries must be quick and satisfactory.
Moreover, this latter measure should only be evaluated by individuals who needed help or
the solving of a problem.
PROPOSED MODEL AND HYPOTHESIS DEVELOPMENT
Our model is based on the service quality-satisfaction-loyalty intention chain (Figure 1). The
choice of a model and the hypotheses proposed must be made using a theoretical basis and
supported by empirical results (Hair et al., 1999). Previous studies (e.g., Cronin and Taylor,
1992; Dabholkar et al., 2000; Cronin et al., 2000; Bagozzi, 1992; Oliver, 1997) give both
theoretical and empirical reasons whi
intentions relationship. In the electronic context, recent research also confirms the mediator
effect of satisfaction (Carlson and O´Cass, 2010; Udo et al., 2010; Kassim and Abdullah,
2008; Chen and Kao, 2010; Yen and Lu, 2008; Collier and Bienstock, 2006; Gounaris et al.,
2010). Other authors suggest that service quality has a direct effect on behavior intentions
(e.g., Boulding et al., 1993; Parasuraman et al., 1988; 1991; Bloemer et al., 1999; Zeithaml et
al., 1996). In the electronic services context, this effect is likewise confirmed (Parasuraman
et al., 2005; Wolfinbarger and Gilly, 2003). Therefore, we expect that:
Hypothesis 1: the electronic service quality will have a positive effect on the consumer’s satisfaction.
Hypothesis 2: the electronic satisfaction will have a positive effect on loyalty intentions.
Hypothesis 3: the electronic service quality will have positive effect on loyalty intentions.
Some authors suggest that the perceived benefits and risks in online purchases depend on
the customer’s shopping experience and more specifically on the performance of the service
offered by the Website (Forsythe et al., 2006). Hence, the better the online shopping
experience, the greater the perceived benefits will be and the fewer the perceived risks will
be. Therefore, we expect that:
Hypothesis 4: the electronic service quality will have a positive effect on the online shopping benefits.
Hypothesis 5: the electronic service quality will have a negative effect on the online shopping risks.
Previous studies about adopting new technologies suggest that the perceived benefits and
risks are antecedents of the use of a technology (Davis, 1989; Rogers, 1995). In the case of
online shopping, Forsythe et al. (2006) suggest that its benefits and risks have an important
role in the present behavior and in predicting the intention of continuing shopping in
Internet. In this sense, these authors show that there is a positive (negative) correlation
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between the perceived benefits (inconveniences) and future intentions of continuing
shopping in the Internet. Therefore, we expect that:
Hypothesis 6: the online shopping benefits will have a positive effect on loyalty intentions.
Hypothesis 7: the online shopping risks will have a negative effect on loyalty intentions.
FIGURE 1. Proposal model and hypotheses
MEASUREMENT SCALES AND DATA COLLECTION
Based on the previous research discussed above, we use five dimensions to evaluate
electronic service quality: design, functionality, privacy, reliability and recovery. The first four
dimensions are answered by all the respondents, while the recovery dimension is only
evaluated by those people who had problems during the transaction (Parasuraman et al.,
2005; Collier and Bienstock, 2006). The scales proposed are based on previous studies and
the items aim to collect the full meaning of each dimension. To measure electronic
satisfaction, we have used Oliver’s (1980) scale adapted to electronic services. The loyalty of
intentions construct was measured with Zeithaml et al.’s (1996) loyalty behavior scale and
reflects the repeat purchase and Website recommendation intentions. To measure the online
shoppers’ perceived benefits and risks, we have used an adaptation of the scales proposed
by Swinyard and Smith (2003) and Forsythe et al. (2006). We have chosen these research
works because: 1) the procedures carried out to develop these scales guarantee their validity
and 2) these scales have been used later in other relevant research. The survey instrument
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contains 49 items and it is based on a 7-point Likert-type scale which ranges from strongly
disagree to strongly agree (see Appendix).
Data collection was obtained from a convenience sample of online shoppers. We surveyed
purchasers who had already completed online transactions and who had sufficient online
shopping experience. The respondents were asked to evaluate a particular Website of their
choice, through which they had recently made a purchase. We followed a quota sampling
approach, with the intention of reproducing the sociodemographic profile of the population
of Spanish online shoppers. The respondents were able to access the Website where the
online questionnaire was posted and they received a small incentive for participating. The
field work took place from April to June 2012, and 915 questionnaires were received. 718 of
them were valid questionnaires and 267 respondents said that they had a problem or doubt
during the online service delivery (Table 2). The service failures or incidents are classified
according the categories that appear in the B2C e-commerce Spanish survey: it has arrived
damaged (35.8%), the delivery was done later than promised (30.6%), payment problems
(18.6%), problems for return (13.7%), lack of information (8.4%) and problems downloading
(6.8%). The research covered a wide range of websites, including a great variety of both
tangible and intangible offerings.
Table 2. Profile of the respondents and profile of the Spanish online shopper
Online shopper
(Sample)
Gender
Men
Women
n
400
318
%
55.7
44.3
Online shopper
(B2C e-commerce Spanish Survey)
%
52.6
47.4
Age
18-24 years old
25-34 years old
35-49 years old
50-64 years old
233
283
143
59
32.5
39.4
19.9
8.2
13.5
29.9
36.3
20.3
Level of education
Primary education
Secondary education
University education
25
394
299
3.48
54.87
41.64
2.7
56.7
39.9
Population
Less than 10,000
10,001-20,000
20,001-50,000
50,001-100,000
Over100,000
83
69
66
38
462
11.6
9.6
9.2
5.3
64.3
18.9
11.8
14.6
12.2
42.5
Social class
Middle-Upper
Middle
Middle-Lower
150
511
57
20.89
71.17
7.94
40.2
37.5
22.3
Experience of Internet use
More than three years
Between one and three years
Less than one year
664
42
12
92.48
5.85
1.67
80.8
8.9
5.1
Frequency of Internet use
Everyday
424
59.05
71.9
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San Sebastián / Donostia 2015
3 to 6 days per week
One day per week or less
262
32
36.49
4.46
11.4
16.3
Note: Profile of the Spanish online shopper ‘B2C e-commerce Survey – ONTSI (2012).
RESULTS
Assessment of the Measurement Model
To evaluate the scales proposed, we have followed the traditional procedures used in
marketing research (Gerbing and Anderson, 1988). In Table 3 we present the results of
dimensionality, convergent validity and reliability assessment. We also offer the standardized
loadings, the composite reliability and the average variance extracted (AVE). As can be seen,
all the items significantly load in their respective dimensions. The AVE values obtained are
all above the recommended value of 0.50. This indicates that each construct’s items have
convergent validity. What is more, each construct shows good internal consistency, with
reliability coefficients which vary between 0.709 and 0.965.
With respect to the importance of the e-service quality dimensions, reliability is the most
important dimension in the assessment of a Website’s service quality, regardless of the type
of service encounter. Moreover, in the service encounter without incidents, the second most
important aspect of the service quality is how the organization solves the problems or doubts
the customers had during the service provision.
Table 3. Dimensionality, convergent validity, and reliability assessment
First order factors
Design
DES1
DES2
DES3
Functionality
FUN1
FUN2
FUN3
FUN4
FUN5
Privacy
PRI1
PRI2
PRI3
Reliability
REL1
REL2
REL3
REL4
REL5
Recovery
REC1
REC2
REC3
REC4
REC5
REC6
REC7
Satisfaction
SAT1
Service encounter without incidents
(451 participants)
SL
CR
AVE
0.804
0.577
0.772
0.733
0.774
0.876
0.640
0.677
0.801
0.84
0.869
Deleted
0.769
0.531
0.652
0.873
0.639
0.811
0.517
0.736
0.665
Deleted
0.681
0.79
0.945
0.816
0.741
Service encounter with incidents
(267 participants)
SL
CR
AVE
0.804
0.578
0.783
0.732
0.764
0.899
0.690
0.763
0.852
0.846
0.859
Deleted
0.803
0.578
0.699
0.859
0.712
0.824
0.540
0.806
0.729
Deleted
0.701
0.698
0.922
0.631
0.776
0.826
0.823
0.868
0.668
0.768
0.815
0.965
0.823
0.88
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SAT2
SAT3
SAT4
SAT5
SAT6
Loyalty intentions
INT1
INT2
INT3
INT4
INT5
Convenience
CON1
CON2
CON3
Variety and good prices
OFE1
OFE2
Fear of financial losses
FEA1
FEA2
FEA3
FEA4
Logistical problems
PRO1
PRO2
PRO3
Don´t know how
NOS1
NOS2
NOS3
Second order factors
e-SQ
e-SQDesign
e-SQ Functionality
e-SQPrivacy
e-SQ Reliability
e-SQRecovery
Benefits
BenefitsConvenience
Benefits Variety and good
prices
Risks
RisksFear of financial losses
Risks Logistical problems
Risks Don´t know how
0.802
0.86
0.885
0.886
0.911
0.912
0.924
0.905
0.909
0.911
0.921
0.700
0.745
0.749
0.876
0.929
0.869
0.836
0.718
Deleted
0.874
0.82
0.775
0.801
0.669
0.735
0.581
0.822
0.536
0.767
0.525
0.838
0.722
0.814
0.501
0.713
0.561
0.797
0.585
Deleted
0.85
0.784
0.709
0.550
0.79
0.69
0.777
0.747
0.826
0.544
0.736
0.841
0.668
0.695
0.737
0.799
0.698
0.69
0.738
0.502
0.803
0.598
0.679
0.799
0.712
0.656
0.746
0.602
Deleted
0.903
0.624
Deleted
0.803
0.894
0.768
0.521
0.538
0.597
0.590
0.932
-
0.522
0.599
0.608
0.901
0.755
0.768
0.630
0.923
0.862
0.640
0.616
0.802
0.899
0.778
0.577
0.945
0.842
0.852
0.902
0.919
0.883
0.582
0.995
0.719
0.497
Note: SL = standardized loadings; CR = Composite Reliability; AVE = Average Variance Extracted; All t-values were greater than
2.576 (p < 0.001).
Discriminant validity, which verifies that each factor represents a separate dimension, was
analyzed examining whether inter-factor correlations are less than the square root of the
average variance extracted (AVE) (Fornell and Larcker, 1981). Table 4 shows that the square
roots of each AVE are greater than the off-diagonal elements. With this result, it should
therefore be understood that there is discriminant validity in the e-service quality
measurement scale.
Table 4. Discriminant validity of measures
XXIX AEDEM Annual Meeting
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Design
Functionality
Privacy
Reliability
Satisfaction
Loyalty
intentions
Convenience
Variety and
good prices
Fear
Logistical
Problems
Design
0.731
Functionality
0.426
0.780
Privacy
0.371
0.369
0.733
Reliability
0.444
0.58
0.569
0.705
Satisfaction
0.396
0.393
0.454
0.681
0.861
Loyalty
intentions
0.386
0.375
0.381
0.589
0.762
0.830
Convenience
0.206
0.235
0.168
0.291
0.223
0.216
0.857
Variety and
goodprices
0.143
0.228
0.193
0.233
0.254
0.216
0.572
0.748
Fear
-0.058
-0.098
-0.077
-0.055
-0.044
-0.004
-0.386
-0.196
0.736
Logistical
Problems
-0.019
-0.053
-0.048
-0.011
-0.01
-0.031
-0.28
-0.161
0.693
0.724
Don´t know
how
-0.102
-0.186
-0.13
-0.259
-0.152
-0.07
-0.455
-0.274
0.469
0.424
Don´t know
how
0.781
Note: The bold numbers on the diagonal are the square root of the AVE. Off-diagonal elements are correlations between constructs.
Assessment of the Structural Model
As can be seen in Table
confirmed in the two contexts. If we look at the structural coefficient value between the
service quality and satisfaction with the online shopping, we can see that this coefficient is
significant and positive for both types of service encounters. Specifically, when there are
problems during the service provision, this coefficient is 0.858 (p<0.001), compared to 0.718
(p<0.001) in the case of there not having been any incident. Likewise, the relationship
between satisfaction and loyalty intentions is greater when the service encounter takes place
with incidents (0.745 compared to 0.620; p<0.001). However, the direct effect of the service
quality on loyalty intentions is not significant. Therefore, hypotheses 1 and 2 are accepted
and hypotheses 3 is rejected. Furthermore, the type of the service of the service encounter
has a moderating effect in the service quality-satisfaction-loyalty intentions chain. In these
sense, these relationships are stronger for the service encounter with incidents.
On the other hand, the service quality positively influences the benefits of online shopping
(0.431; p<0.001) and negatively influences the risks when the service encounter takes place
without incidents (-0.131; p<0.05). In this way, when the customer perceives that the
Website offers a high service quality, he/she positively values the benefits of online shopping
and plays down its risks. In the case of the service encounter with incidents only the positive
influence of the service quality on benefits is confirmed (0.427; p<0.001). These results lead
us to accept hypotheses 4 and to partially accept hypotheses 5. However, in our study no
statistically significant effect of the benefits or the risks of online shopping on loyalty
intentions was observed. Therefore, hypotheses 6 and 7 are rejected.
The values of the variance explained for the constructs of satisfaction and loyalty intentions
are rather good. Nevertheless, the variance explained for the benefits and risks of online
shopping are fairly low. To measure the model’s fit some indices supplied by the AMOS
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statistical software were used. Values were recommended close to: 0.95 (CFI), 0.95 (TLI),
0.06 (RMSEA) and 0.08 (SRMR) (Hu and Bentler, 1999). Regarding the RMSEA index, there
is also a confidence interval (LO90 and HI90), following the recommendation of Byrne
(2009). In both contexts the model has a reasonably good fit of the data.
Table 5. Structural models estimation
H1: e-SQSatisfaction
H2: SatisfactionLoyalty intentions
Service encounter without
incidents
(451 participants)
0.718***
Service encounter with
incidents
(267 participants)
0.858***
0.620***
0.745***
0.140 (n.s.)
0.132 (n.s.)
H4: e-SQ Benefits
0.431***
0.427***
H5: e-SQ Risks
-0.131**
-0.121 (n.s.)
H6: BenefitsLoyalty intentions
0.031 (n.s.)
0.068 (n.s.)
H7: RisksLoyalty intentions
0.048 (n.s.)
0.045 (n.s.)
Satisfaction
0.516
0.736
Loyalty intentions
0.601
0.784
Benefits
0.177
0.182
Risks
0.017
0.015
χ2
2621.295
1844.470
Df
724
928
P
0
0
CFI
0.908
0.895
TLI
0.900
0.888
SRMR
0.061
0.0589
RMSEA
0.054
0.061
0.052-0.056
0.057-0.065
H3: e-SQ Loyalty intentions
Variance explained (R2)
Fit statistics
LO90 and HI90
Note: **p<0.05; ***p<0.001; n.s.: not significant.
Comparison of Means
Next, we carried out the t-Student test and the Mann-Whitney test to analyze if the perceived
quality assessment, the customers’ satisfaction, their loyalty intentions toward the Website
and the perceived benefits and risks of online shopping differed according to the type of
service encounter (Table 6). The results show that the mean scores of the e-service quality
are significantly greater for the service encounter without incidents. Therefore, the
consumers who did not have any problem or doubt during the service encounter have a
significantly greater valuation of the Website’s service quality than those who had an incident
during the service provision. Likewise, the satisfaction levels and the loyalty intentions are
significantly higher for those consumers who did not have any problem. The consumers who
did not have any incident give a greater score to the benefits of online shopping than those
consumers who stated that they had an incident, although the differences are not statistically
significant. Finally, those consumers who had an incident when shopping have significantly
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greater difficulties doing this and perceive a higher risk of losing money than those who had
no problem when shopping.
Table 6. Student t-test and Mann-Whitney test
Levene´s Test
Mean
(Enc. without
incidents)
Mean
(Enc. with
incidents)
4,882
5,369
4,967
5,707
5,822
5,323
4,720
5,045
4,707
5,261
5,249
4,919
4,919
4,854
3,898
4,575
2,751
e-SQ
Design
Functionality
Privacy
Reliability
Satisfaction
Loyalty intentions
Benefits
Convenience
Variety /good prices
Risks
Fear
Logistical Problems
Don´t know how
Note: **p<0.05
T-test
Mann–Whitney Test
Sig.
T
Sig.
(2-tailed)
0,019
3,097
4,588
10,673
57,754
16,632
0,891
0,079
0,033**
0,001**
0,000**
0,000**
-1,969
-3,563
-
0,049**
0,000**
-
4,800
4,914
0,072
0,054
0,789
0,816
-1,028
0,584
0,304
0,559
4,194
4,581
3,163
0,168
0,363
10,899
0,682
0,547
0,001**
2,800
0,058
-
0,005**
0,954
-
F
Z
Asym. Sig.
(2-tailed)
-2,526
-5,190
-4,981
-3,133
0,012**
0,000**
0,000**
0,002**
-3,297
0,001**
DISCUSSION
Theoretical implications
Numerous works in the literature show that an essential aspect for the success of B2C ecommerce is for consumers to perceive high quality services. This not only involves a greater
development of this e-business model, it also allows firms to differentiate themselves from
their competitors. In recent years, many researchers have analyzed the components or
dimensions that shape the quality of the services offered through Internet. Furthermore,
service quality has become the main way to achieve customer satisfaction and, therefore,
their loyalty. In our study, the originality of the contribution lies in 1) integrating the benefits
and risks which online shoppers perceive in the traditional service quality-satisfaction-loyalty
intention chain and 2) analyzing these relationships in two contexts: service encounters
without incidents versus service encounters with incidents. Next we show the main
conclusions of our work.
Firstly, our study confirms that the e-service quality has a direct effect on satisfaction and
that the effect of satisfaction on loyalty intentions is important. Moreover, these relationships
are statistically significant when the service encounter takes place with or without incidents.
Theoretically, the mediator effect of satisfaction on the
relationship is based on the model of Bagozzi (1992), in which the cognitive assessments
(service quality) precede emotions (satisfaction with the service), and on the model of Oliver
(1997), according to which the cognitive assessment of the service generates an affective or
emotional response that leads to behavior or behavior intention. However, the direct effect
of the service quality on loyalty intentions is not significant. This study therefore up holds
that satisfaction mediates the effect of the service quality on loyalty intentions. Previous
studies also empirically supported this mediator effect of satisfaction (e.g., Cronin et al., 2000;
Dabholkar et al., 2000). However, this study’s first relevant contribution is that there are
variables which can moderate these relationships. Specifically, the type of service encounter
(with or without incidents) increases or diminishes the strength of these effects. In this sense,
when errors occur during the electronic service provision, the measures carried out by the
organization to solve these problems are an essential part of the assessment of the service
XXIX AEDEM Annual Meeting
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quality provided. Moreover, in these cases, if the customers’ problems or doubts are
satisfactorily settled, the effects of service quality-satisfaction-loyalty intentions become
stronger.
The second interesting contribution of this work refers to the role of the online customers’
perceived benefits and risks in the service quality-satisfaction-loyalty intentions chain. In this
sense, to offer a high e-service quality also means that the customers will positively value the
benefits of Internet shopping and underestimate its risks. Nonetheless, a significant effect of
the benefits and risks which online consumers perceived on loyalty intentions toward the
Website where they shopped was not noted. This construct is basically determined by the
satisfaction with the shopping experience on this Website.
Thirdly, regardless of the type of service encounter, reliability is the most important
dimension in the assessing of a Website’s service quality. These results coincide with the
conclusions of previous studies, which also empirically demonstrated that reliability has a
strong influence on the perceived quality of certain e-services (Bauer et al., 2005;
Wolfinbarger and Gilly, 2003). As a result, the managers of online services must center
themselves specifically on questions such as the exactitude of the service offered and correct
billing, and offer clear, complete and error-free information. However, in spite of there being
a strong consensus about the fact that privacy is one of the most important in the evaluation
of an online service quality (B2C-ONTSI study on e-commerce) and one of those that have
the most influence on customer satisfaction (Janda et al., 2002), this research shows the slight
importance of this dimension. This fact is possibly due to the technological advances of
recent years concerning online purchase payment security (Udo et al., 2010) and there being
a growing tendency in the number of customers who are familiar with this type of electronic
transactions (B2C-ONTSI study on e-commerce). In our study, we ask the respondents to
evaluate the Website which they use the most. Therefore, it seems that there is a certain
familiarity and trust with the Websites chosen. In this line, previous studies point out that
privacy may not be a critical factor in those who use Internet more often (Wolfinbarger and
Gilly, 2003). For those users who do not carry out online purchases, privacy is probably not
a factor of great importance. A third explanation may be the fact that younger consumers
perceive fewer risks in this type of purchases than older consumers (Udo et al., 2010)
(approximately 80% of our sample’s purchasers were between 18 and 34 years old).
Fourthly, the consumers who have not had an incident during the service encounter perceive
a better service quality, show greater levels of satisfaction and loyalty intentions toward the
Website and perceive more benefits and less risks of online shopping than the consumers
who had a problem during the service provision. Furthermore, these latter consumers have
significantly lower skills in carrying out online purchases and perceive a higher risk of losing
money
Managerial implications
From the management point of view, firstly, an essential aspect for the success of B2C ebusiness is for the online suppliers to know which aspects determined the quality of the
services offered through Internet. During the first years of e-business, organizations paid
more attention to the technical characteristics of the Website: design, functionality, privacy,
etc. However, although these aspects are important, the customer’s evaluation of the product
or service delivery and the way in which their problems or doubts have been resolved during
the service provision must not be ignored by any organization. In this vein, the results of this
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research show that the main aim for any online supplier must be to offer a reliable service
for their customers to perceive high quality services and be satisfied. Reliability must be
understood as the firm’s capacity to fulfill their commitments regarding e-service delivery or
provision as agreed in the conditions. That is to say, the organization must offer exactly the
service which the customer has contracted on the Website, the billing of this service must be
carried out without mistakes, the packing of the products has to be secure, the products must
be delivered to the customer on the date promised and their refund must be guaranteed. In
the same way, the online suppliers must offer clear, detailed and error-free information about
the products and services which appear in their Website.
Another very important component of the quality of an e-service is how the consumer
perceives that their problems or doubts are resolved by the organization. From the
management point of view, online companies must identify the nature of these errors and
start up service recovery programs and policies to attain their customers’ satisfaction and
loyalty (Holloway and Beatty, 2003). When mistakes take place during the service provision,
the online suppliers must make an effort to solve them or offer the consumer some kind of
compensation, given that their satisfaction with the Internet shopping will be greater when
no incident occurs and this will therefore increase their loyalty toward the Website. However,
our study shows that the performance of the dimensions which make up the e-service quality
and the satisfaction and loyalty levels is lower when these incidents exist. These results
indicate that organizations often ignore aspects which are subsequent to the online shopping.
This results in less customer satisfaction and loyalty. Online suppliers must offer different
ways (email, telephone, etc.) for the consumer to be able to get in touch with the customer
attention service. Moreover, these problems or doubts must not be resolved with a general
response but a specific response to each customer’s problems.
Although previous studies suggest that to get a lower price is not an important attribute for
online shoppers (Bhatnagar and Ghose, 2004), in this study it was noted that online
consumers very positively value the great variety of products and services which Internet
offers and being able to find better prices than in traditional establishments, more than the
convenience of online shopping. On the other hand, Bhatnagar and Ghose (2004) conclude
that consumers are more concerned about the inconveniences of online shopping than about
its benefits. However, this research shows that consumers value the benefits of Internet
shopping more than its risks. According to Swinyard and Smith (2003), this research shows
that fear of financial loss is one of the main concerns of Internet users when shopping on
Internet. In any case, starting up strategies aimed at emphasizing the benefits of Internet
shopping and reducing the risks perceived by the consumer will help the developing of
electronic commerce.
LIMITATIONS AND FUTURE RESEARCH LINES
Lastly, some limitations of this work must be recognized and certain future research lines
proposed. The convenience samples do not allow the generalizing of the results to the rest
of the population. Future studies must be carried out to try and validate and generalize the
results of this study using a larger sample. Previous studies have analyzed the effect of eservice quality on the perceived value of online shopping (e.g., Bauer et al., 2006;
Parasuraman et al., 2005). It would be interesting to analyze how the perceived value is
integrated into the service quality-satisfaction-loyalty intentions chain. On the other hand,
although utilitarian motives predominate in online shopping, it would be interesting in future
research lines to analyze if those online shoppers whose motivation is mainly hedonistic
XXIX AEDEM Annual Meeting
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perceive a greater service quality, are more satisfied with the shopping and have a stronger
loyalty toward a Website. Finally, the perception of the benefits and risks is changing over
time (Forsythe et al., 2006). A longitudinal study could be proposed to observe how these
perceptions change and what their causes are.
REFERENCES
Aladwani, A.M. and Palvia, P.C. (2002), “Developing and validating an instrument for
measuring user-perceived Web quality”, Information and Management, Vol. 39, pp. 467476.
Alt, R., Abramowicz, W. and Demirkan, H. (2010), “Service-orientation in electronic
markets”, Electronic Markets, Vol. 20, pp. 177-180.
Bagozzi, R.P. (1992), “The self-regulation of attitudes, intentions and behavior”, Social
Psychology Quarterly, Vol. 55 No. 2, pp. 178-204.
Barrutia, José M. and Ainhize Gilsanz, A. (2012), “Electronic Service Quality and Value: Do
consumer knowledge-related resources matter?,” Journal of Service Research, DOI:
10.1177/1094670512468294.
Bauer, H.H., Hammerschmidt, M. and Falk, T. (2005), “Measuring the quality of e-banking
portals”, International Journal of Bank Marketing, Vol. 23 No. 2, pp. 153-175.
Belanche, D., Casaló, L.V. and Flavián, C. (2011), “Adopción de servicios públicos online:
Un análisis a través de la integración”, Revista Europea de Dirección y Economía de la
Empresa, Vol. 20 No. 4, pp. 41-56.
Bhatnagar, A. and Sanjoy Ghose (2004), “A Latent Class Segmentation Analysis of EShoppers,” Journal of Business Research, Vol. 57, pp. 758-767.
Bitner, M.J. (1990), “Evaluating service encounters: The effects of physical surroundings and
employee responses”, Journal of Marketing, Vol. 54 No. 2, pp. 69-82.
Bitner, M.J., Booms, B.H. and Tetrault, M.S. (1990), “The service encounter: Diagnosing
favorable and unfavorable incidents”, Journal of Marketing, Vol. 54, pp. 71-84.
Bitner, M.J., Brown, S.W. and Meuter, M.L. (2000), “Technology infusion in service
encounters”, Journal of the Academy of Marketing Science, Vol. 28 No. 1, pp. 138-149.
Bloemer, J., de Ruyter, K. and Wetzels, M. (1999), “Linking perceived service quality and
service loyalty: A multi-dimensional perspective”, European Journal of Marketing, Vol.
33 No. 11/12, pp. 1082- 1106.
Boulding, W., Kalra, A., Staelin, R. and Zeithaml, V.A. (1993), “A dynamic process model of
service quality: From expectations to behavioral intentions”, Journal of Marketing
Research, Vol. 30, pp. 7-27.
Brengman, M., Geuens, M., Weijters, B., Smith, S.M. and Swinyard, W.R. (2005),
“Segmenting Internet shoppers based on their Web-usage-related lifestyle: A crosscultural validation,” Journal of Business Research, Vol. 58 No. 1, pp. 79-88.
Bressolles, G. and Nantel, J. (2008), “The measurement of electronic service quality:
Improvements and application”, International Journal of E-Business Research, Vol. 4 No.
3, pp. 1-19.
Brown, T.J., Churchill, G.A. and Peter, J.P. (1993), “Improving the measurement of service
quality”, Journal of Retailing, Vol. 69 No. 1, pp. 127-139.
Byrne, B. (2009), “Structural equation modelling with AMOS: Basic concepts, applications,
and programming”, (2nd Ed.). New York: Routledge/Taylor and Francis.
Cai, S. and Jun, M. (2003), “Internet users’ perceptions of online service quality: A
comparison of online buyers and information searchers”, Managing Service Quality, Vol.
13 No. 6, pp. 504-519.
XXIX AEDEM Annual Meeting
San Sebastián / Donostia 2015
Carlson, J. and O´Cass, A. (2010), “Exploring the relationships between e-service quality,
satisfaction, attitudes and behaviors in content-driven e-service Web sites”, Journal of
Services Marketing, Vol. 24 No. 2, pp. 112-127.
Chen, C. and Kao, Y. (2010), “Relationships between process quality, outcome quality,
satisfaction, and behavioral intentions for online travel agencies - evidence from Taiwan”,
The Service Industries Journal, Vol. 30 No. 12, pp. 2081-2092.
Colby, C. and Parasuraman, A. (2003), “Technology still matters”, Marketing Management,
Vol. July/August, pp. 28-33.
Collier, J.E. and Bienstock, C.C. (2006), “Measuring service quality in e-retailing”, Journal of
Service Research, Vol. 8 No. 3, pp. 260-275.
Cronin, J.J., Brady, M.K. and Hult, T.M. (2000), “Assessing the effects of quality, value, and
customer satisfaction on consumer behavioral intentions in service environments”,
Journal of Retailing, Vol. 76 No. 2, pp. 193-218.
Cronin, J.J. and Taylor, S.A. (1992), “Measuring service quality: A reexamination and
extension”, Journal of Marketing, Vol. 56, pp. 55-68.
Curran, J.M. and Meuter, M.L. (2005), “Self-service technology adoption: Comparing three
technologies”, The Journal of Services Marketing, Vol. 19 No. 2, pp. 103-113.
Dabholkar, P.A. (1996), “Consumer evaluations of new technology-based self-service
options: An investigation of alternative models”, International Journal of Research in
Marketing, Vol. 13 No. 1, pp. 29-51.
Dabholkar, P.A. (2000), “Technology in service delivery: Implications for self-service and
service support”, In: T. A. Swartz and D. Iacobucci (eds) Handbook of Services
Marketing (New York: Sage, pp. 103-110.
Dabholkar, P.A., Shepherd, C.D. and Thorpe, D.I. (2000), “A compressive framework for
service quality: An investigation of critical conceptual and measurement issues through a
longitudinal study”, Journal of Retailing, Vol. 76 No. 2, pp. 139-173.
Davis, F. (1989), “Perceived usefulness, perceived ease of use, and user acceptance of
information technology”, MIS Quarterly, Vol. 13 No. 3, pp. 319-339.
Davis, F., Bagozzi, R.P. and Warshaw, P.R. (1989), “User acceptance of computer
technology: A comparison of two theoretical models”, Management Science, Linthicum:
August, Vol. 35 No. 8, pp. 982-1003.
Duque-Oliva, E.J. and Rodríguez-Romero, C.A. (2012), “Perceived service quality in
electronic commerce: An application”, Rev. Innovar, Vol. 21 No. 42, pp. 89-98.
Eurostat
(2012),
“Information
Society
Statistics”,
Available
at
http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Ecommerce_statistics.
Fassnacht, M. and Koese, I. (2006), “Quality of electronic services: conceptualizing and
testing a hierarchical model”, Journal of Service Research, Vol. 9 No. 1, pp. 19-37.
Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with
unobservable variables and measurement error”, Journal of Marketing Research, Vol. 18
No. 1, pp. 39-50.
Forsythe, S., Liu, C., Shannon, D. and Gardner, L.G. (2006), “Development of a scale to
measure the perceived benefits and risks of online shopping,” Journal of Interactive
Marketing, Vol. 20 No. 2, pp. 55-75.
Gerbing, D.W. and Anderson, J.C. (1988), “An updated paradigm for scale development
incorporating unidimensionality and its assessment”, Journal of Marketing Research, Vol.
25, pp. 186-192.
Gounaris, S., Dimitriadis, S. and Stathakopoulos, V. (2010), “An examination of the effects
of service quality and satisfaction on customers’ behavioral intentions in e-shopping”,
Journal of Services Marketing, Vol. 24 No. 2, pp. 142-156.
XXIX AEDEM Annual Meeting
San Sebastián / Donostia 2015
Hair, J.F., Anderson, R.E., Tatham, R.R. and Black, W.C. (1999), “Multivariate data analysis”,
London: Prentice Hall.
Ho, C. and Lee, Y. (2007), “The development of an e-travel service quality scale”, Tourism
Management, Vol. 28, pp. 1434-1449.
Hoffman, D.L. and Novak, T.H. (1996), “Marketing in hypermedia computer-mediated
environments: Conceptual foundations”, Journal of Marketing, Vol. 60, pp. 50-68.
Hoffman, D.L. and Novak, T.H. (1997), “A new marketing paradigm for electronic
commerce”, Information Society, Vol. 13 No. 1, pp. 43-54.
Holloway, B.B. and Beatty, S.E. (2003), “Service failure in online retailing: A recovery
opportunity”, Journal of Service Research, Vol. 6 No. 1, pp. 92-105.
Hu, Li-tze and Bentler, P.M. (1999), “Cutoff criteria for fit indexes in covariance structure
analysis: Conventional criteria versus new alternatives”, Structural Equation Modeling,
Vol. 6, pp. 1-55.
Janda, S., Trocchia, P.J. and Gwinner, K.P. (2002), “Consumer perceptions of Internet retail
service quality”, International Journal of Service Industry Management, Vol. 13 No. 5, pp.
412-431.
Jun, M., Yang, Z. and Kim, D. (2004), “Customers’ perceptions of online retailing service
quality and their satisfaction”, International Journal of Quality and Reliability
Management, Vol. 21 No. 8, pp. 817-840.
Kaynama, S.A. and Black, C.I. (2000), “A proposal to assess the service quality of online
travel agencies: An exploratory study”, Journal of Professional Services Marketing, Vol.
21 No. 1, pp. 63-88.
Kim, E. and Lee, B. (2009), “E-service quality competition through personalization under
consumer privacy concerns”, Electronic Commerce Research and Applications, Vol. 8,
pp. 182-190.
La, K. and Kandampully, J. (2002), “Electronic retailing and distribution of services: Cyber
intermediaries that serve customers and service providers”, Managing Service Quality,
Vol. 12 No. 2, pp. 100-116.
Liu, C. and Arnett, K.P. (2000), “Exploring the factors associated with Web site success in
the context of electronic commerce”, Information and Management, Vol. 38, pp. 23-33.
Liu, C., Du, T.C. and Tsai, H. (2009), “A study of the service quality of general portals”,
Information and Management, Vol. 46, pp. 52-56.
Loiacono, E.T., Watson, R.T. and Goodhue, D.L. (2002), “Webqual: A measure of Website
quality”, In K. Evans and Scheer (Eds.), Marketing Educators’ Conference: Marketing
Theory and Application, pp. 433-437.
Long, M. and McMellon, C. (2004), “Exploring the determinants of retail service quality on
the Internet”, Journal of services marketing, Vol. 18 No. 1, pp. 78-90.
Meuter, M.L., Ostrom, A.L., Roundtree, R.I. and Bitner, M.J. (2000), “Self-service
technologies: Understanding customer satisfaction with technology-based service
encounters”, Journal of Marketing, Vol. 64 No. 3, pp. 50-64.
Observatorio Nacional de las Telecomunicaciones y de la Sociedad de la Información. B2C
e-commerce
Survey
(2012),
Available
at
http://www.red.es/notasprensa/articles/id/4878/conclusiones-del-informe-sobre-comercio-electronico-b2c2010-del-ontsi.html.
O´Cass, A. and Carlson, J. (2012), “An empirical assessment of consumers’ evaluations of
web site service quality: conceptualizing and testing a formative model”, Journal of
Services Marketing, Vol. 26 No. 6, pp. 419–434.
Oliver, R.L. (1980), “A cognitive model of the antecedents and consequences of satisfaction
decisions”, Journal of Marketing Research, Vol. 17 No. 4, pp. 460-469.
Oliver, R.L. (1997), “Effect of expectations and disconfirmation on post exposure product
evaluations”, Journal of Applied Psychology, Vol. 62, pp. 480-486.
XXIX AEDEM Annual Meeting
San Sebastián / Donostia 2015
Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1985), “A conceptual model of service
quality and its implications for future research”, Journal of Marketing, Vol. 49, pp. 41-50.
Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1988), “SERVQUAL: A multiple-item
scale for measuring consumer perceptions of service quality”, Journal of Retailing, Vol.
64 No. 1, pp. 12-40.
Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1991), “Understanding customer
expectations of service”, Sloan Management Review, Spring, pp. 39-48.
Parasuraman, A., Zeithaml, V.A. and Malhotra, A. (2005), “E-S-QUAL. A multiple-item
scale for assessing electronic service quality”, Journal of Service Research, Vol. 7 No. 3,
pp. 213-233.
Ranaweera, C., McDougall, G. and Bansal, H. (2004), “A model of online customer behavior:
moderating effects of customer characteristics, Business & Economics, January, pp. 1-18.
Ranganathan, C. and Ganapathy, S. (2002), “Key dimensions of business-to-consumer Web
sites”, Information and Management, Vol. 39, pp. 457-465.
Rogers, E.M. (1995), “Diffusion of Innovations”, 4th Ed., The Free Press, New York, NY.
Rohm, A.J. and Swaminathan, V. (2004), “A typology of online shoppers based on shopping
motivations,” Journal of Business Research, Vol. 57, pp. 748-757.
Rolland, S. and Freeman, I. (2010), “A new measure of e-service quality in France”,
International Journal of Retail and Distribution Management, Vol. 38 No. 7, pp. 497-517.
Rust, R. (2001), “The rise of e-service”, Journal of Service Research, Vol. 3, pp. 283-84.
Sabiote, C.M., Frías, D.M. and Castañeda, J.A. (2012), “E-service quality as antecedent to esatisfaction. The moderating effect of culture”, Online Information Review, Vol. 36 No.
2, pp. 157-174.
Sánchez-Franco, M.J. and Villarejo, A.F. (2004), “La calidad de servicio electrónico: Un
análisis de los efectos moderadores del comportamiento de uso de la Web”, Cuadernos
de Economía y Dirección de la Empresa, Vol. 21, pp. 121-152.
Shankar, V., Smith, A.K. and Rangaswamy, A. (2003), “Customer satisfaction and loyalty in
online and offline environments”, International Journal of Research in Marketing, Vol.
20 No. 2, pp. 153-175.
Sheng, T. and Liu, C. (2010), “An empirical study on the effect of e-service quality on online
customer satisfaction and loyalty”, Nankai Business Review International, Vol. 1 No. 3,
pp. 273-283.
Shostack, G.L. (1985), “Planning the service encounter”, In Czepiel, J.A; Solomon, M.R. and
Surprenant, C.F. (Eds). The Service Encounter, Lexington Books, Lexington, MA.
Sohail, M.S. and Shaikh, N.M. (2008), “Internet banking and quality of service”, Online
Information Review, Vol. 32 No. 1, pp. 58-72.
Swinyard, William R. and Scott M. Smith (2003), “Why people (don´t) shop online: A lifestyle
study of the Internet consumer,” Psychology & Management, Vol. 20 No. 7, pp. 567-597.
Teas, R.K. (1993), “Expectations, performance evaluation, and consumers’ perceptions of
quality”, Journal of Marketing, Vol. 57, pp. 18-34.
Trocchia, P.J. and Janda, S. (2003), “How do consumers evaluate Internet retail service
quality?”, Journal of Services Marketing, Vol. 17 No. 3, pp. 243-253.
Tsang, N.K., Lai, M.T. and Law, R. (2010), “Measuring e-service quality for online travel
agencies”, Journal of Travel and Tourism Marketing, Vol. 27 No. 3, pp. 306-323.
Udo, G.J., Kallol, K. and Kirs, P.J. (2010), “An assessment of customers’ e-service quality
perception, satisfaction and intention”, International Journal of Information
Management, Vol. 30, pp. 481-492.
Wolfinbarger, M. and Gilly, M. (2001), “Shopping online for freedom, control, and fun”,
California Management Review, Vol. 43 No. 2, pp. 34-55.
Wolfinbarger, M. and Gilly, M. (2003), “Etailq: Dimensionalizing, measuring and predicting
e-tail quality”, Journal of Retailing, Vol. 79 No. 3, pp. 183-198.
XXIX AEDEM Annual Meeting
San Sebastián / Donostia 2015
Yang, Z. and Jun, M. (2002), “Consumer perceptions of e-service quality: From Internet
purchaser and non-purchaser perspectives”, Journal of Business Strategies, Vol. 19 No.
1, pp. 19-41.
Yen, C. and Lu, H. (2008), “Effects of e-service quality on loyalty intention: An empirical
study in online auction”, Managing Service Quality, Vol. 18 No. 2, pp. 127-146.
Yoo, B. and Donthu, N. (2001), “Developing a scale to measure the perceived quality of an
Internet shopping site (SITEQUAL)”, Quarterly Journal of Electronic Commerce, Vol.
2 No. 1, pp. 31-46.
Zeithaml, V.A. and Gilly, M. (1987), “Characteristics affecting the acceptance of retailing
technologies: A comparison of elderly and nonelderly consumers”, Journal of Retailing,
Vol. 63 No. 1, pp. 49-68.
Zeithaml, V., Berry, L.L. and Parasuraman, A. (1996), “The behavioral consequences of
service quality”, Journal of Marketing, Vol. 60 No. 2, pp. 31-46.
Zeithaml, V.A., Parasuraman, A. and Malhotra, A. (2000), “A conceptual framework for
understanding e-service quality: Implications for future research and managerial practice”,
Working Paper, Cambridge, MA: Marketing Science Institute.
Zeithaml, V.A., Parasuraman, A. and Malhotra, A. (2002), “Service quality delivery through
Websites: A critical review of extant knowledge”, Journal of Academy of Marketing
Science, Vol. 30 No. 4, pp. 362-375.
APPENDIX
Electronic service quality
Design
DES1: The Website looks attractive
DIS2: The Website uses fonts properly
DIS3: The Website uses colors properly
Adapted from Liu et al. (2009)
Functionality
FUN1: This Website is always up and available
FUN2: This Website has valid links
FUN3: This Website loads quickly
FUN4: This Website enables me to get on to it quickly
FUN5: This Website makes it easy and fast to get anywhere on the site
Adapted from Aladwani and Palvia (2002), Parasuraman et al. (2005) and Collier and
Bienstock (2006)
Privacy
PRI1: In the Website appear symbols and messages that signal the site is secure
PRI2: The Website assures me that personal information is protected
PRI3: The Website assures me that personal information will not be shared with other parties
Adapted from Janda et al. (2002), Collier and Bienstock (2006) and Parasuraman et al. (2005)
Reliability
REL1: The service received was exactly the same as what I ordered
REL2: The billing process was done without mistakes
REL3: Website information is clear
REL4: Website information is current
REL5: Website information is complete
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Adapted from Parasuraman et al. (2005), Wolfinbarger and Gilly (2003) and Aladwani and
Palvia (2002)
Recovery
REC1: The Website shows its street, e-mail phone or fax numbers
REC2: The Website has customer service representatives
REC3: If I wanted to, I could easily contact a customer service representative
REC4: The Website responds to my inquiries
REC5: The Website gives me a satisfactory response
REC6: When I have a problem the Website shows a sincere interest in solving it
REC7: The website responds quickly to my inquiries
Adapted from Collier and Bienstock (2006) and Parasuraman et al. (2005)
Satisfaction
SAT1: I am satisfied with my decision to purchase from this Website
SAT2: If I had to purchase again, I would feel differently about buying from this Website
SAT3: My choice to purchase from this Website was a wise one
SAT4: I feel good regarding my decision to buy from this Website
SAT5: I think I did the right thing by buying from this Website
SAT6: I am happy that I purchased from this Website
Adapted from Oliver (1980)
Loyalty intentions
INT1: I consider this Website to be my first choice to buy this kind of services
INT2: I will do more business with the Website in the next few years
INT3: I say positive things about the Website to other people
INT4: I would recommend the Website to someone who seeks my advice
INT5: I encourage friends and relatives to do business with the Website
Adapted from Zeithaml et al. (1996)
Online purchase benefits
Convenience
COM1: Online purchases are easy to do
COM2: I like to buy on Internet as I can do it any time and any place
COM3: I like to buy from home
Variety /good prices
OFE1: Internet offers products and services at better prices than traditional shops
OFE2: I find a greater variety of products and services on Internet
Risks of online purchasing
Fear of financial losses
MIE1: I don’t feel sure purchasing on Internet
MIE2: I’m afraid of financial losses when I purchase on Internet
MIE3: I don’t like to give my personal data if I buy online
MIE4: I don’t trust companies which sell products on Internet
Logistical problems
PRO1: If I buy on Internet I can get product delivery problems
PRO2: It’s complicated to return a product bought on Internet
PRO3: It’s difficult to know the quality of products bought on Internet
XXIX AEDEM Annual Meeting
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Don’t know how
NOS1: I don’t like to surf on Internet very much
NOS2: It’s difficult for me to buy on Internet
NOS3: It’s difficult for me to find what I want on Internet
Adapted from Swinyard and Smith (2003) and Forsythe, Liu, Shannon and Gardner (2006)
Note: All items are measured with a seven-point Likert scale, anchored at 1 “strongly
disagree” and 7 “strongly agree”.