1-s2.0-S0278431907000722-main
-
Upload
leonardo-anton-ramirez -
Category
Documents
-
view
214 -
download
0
Transcript of 1-s2.0-S0278431907000722-main
-
8/18/2019 1-s2.0-S0278431907000722-main
1/13
International Journal of Hospitality Management 27 (2008) 504–516
The characteristics of hotel websites and their implications
for website effectiveness
Serje Schmidta,, Antoni Serra Cantallopsb, Cristiane Pizzutti dos Santosc
aCentro Universitá rio Feevale, RS 239, 2755, 93352-000, Novo Hamburgo, RS, Brazil bUniversitat de les Illes Balears, Ctra. de Valldemossa, km 7.5, Edifici Jovellanos DB211, 07122, Palma de Mallorca, Spain
cUniversidade Federal do Rio Grande do Sul, Escola de Administrac - ão, Rua Washington Luis, 855, 90010-460, Porto Alegre, RS, Brazil
Abstract
Hotels are increasingly taking advantage of the Internet as a marketing tool able to provide direct contact with customers, but is the
full potential of this tool being exploited? This article constructs and validates an instrument for the measurement of website
characteristics and relates those characteristics to website performance, using structural equation modeling. The results indicate that
small and medium size hotels in the Balearic Islands in Spain, a developed tourist destination, and in the South of Brazil, a developing
destination, are using their websites as mass media tools; ignoring the potential for interactivity and one-to-one communication. It is
suggested that hoteliers should adopt a more strategic approach to the Internet, preparing the ground for direct contact with customers.
r 2007 Elsevier Ltd. All rights reserved.
Keywords: Hotel; Website; Internet
1. Introduction
There is little doubt that the Internet is changing
marketing practices, from the detection of what consumers
need to manage their relationships with companies. Some
websites offer a highly interactive experience, such as the
Amazon site (www.amazon.com), where users can rate and
review products and read other consumers’ opinions, and
so be better equipped to decide between purchasing
alternatives. Nevertheless, not all products are suited to
web commerce. Certain distinctions can be made between
products that are appropriate for Internet commerce and
those unsuited to this distribution channel. Some featuresof the first group are: products where purchasing decisions
are based on information, products that can be distributed
through the web, products that offer consumers a better
deal when compared to other distribution channels and
those whose customers have Internet access (Chaffey et al.,
2003).
From this perspective, the hospitality industry is in anideal position to exploit the potential of the Internet
(Palmer and McCole, 2000). With the exception of large
hotel chains, however, most hotel websites have a limited
range of functions, such as promotion and point-of-sale.
Only a few of them are exploring other potentialities, such
as a support tool for customer relationship management.
Despite massive promotion of the Internet, it appears that
hotels are missing out on the opportunity to use the web as
an effective business tool. However, is this truly the case?
The aim of this paper is to investigate the impact of
website characteristics on website effectiveness in the
context of small and medium size hotels. To this end,two tourist regions were chosen for study, as much because
of their differences in terms of tourism as for their relative
similarity in terms of Internet access: the Balearic Islands in
Spain and the South of Brazil.
In order to accomplish our objective, this paper is
structured as follows. First we address Internet marketing
and its marketing mix perspectives. We then explore and
classify previous research focused on website features. We
continue by constructing a measurement instrument based
on the marketing mix and website characteristics, and
ARTICLE IN PRESS
www.elsevier.com/locate/ijhosman
0278-4319/$- see front matter r 2007 Elsevier Ltd. All rights reserved.
doi:10.1016/j.ijhm.2007.08.002
Corresponding author. Tel.: +55 51 99643185; fax: +55 51 35868999.
E-mail addresses: [email protected] (S. Schmidt), [email protected]
(A.S. Cantallops), [email protected] (C.P. dos Santos).
http://www.amazon.com/http://www.elsevier.com/locate/ijhosmanhttp://localhost/var/www/apps/conversion/tmp/scratch_5/dx.doi.org/10.1016/j.ijhm.2007.08.002mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]://localhost/var/www/apps/conversion/tmp/scratch_5/dx.doi.org/10.1016/j.ijhm.2007.08.002http://www.elsevier.com/locate/ijhosmanhttp://www.amazon.com/
-
8/18/2019 1-s2.0-S0278431907000722-main
2/13
applying it the websites of hotels in the Balearic Islands
in Spain and in the South region of Brazil. We proceed
by describing validation procedures and results and,
finally, round off with a general discussion about this
study.
2. Tourism and Internet penetration in Spain and Brazil
The differences between the two countries and regions
can most clearly be illustrated with reference to statistics.
Spain is considered the world’s second-ranked tourism
destination, behind the United States in terms of receipts
from international tourism and behind France in numbers
of tourist arrivals. The region of the Balearic Islands, with
an area of less than 5000 km2, is the third-ranked tourist
destination in Spain, receiving 9.5 million tourists in 2002,
which represents 10.4% of the country’s tourists. In
contrast, Brazil has an area of more than 8.5 million km2,
but occupies fourth position in the Americas in terms of
tourist receipts and arrivals, far behind the United States,
Canada and Mexico, and receives less than half the number
of tourists of Spain: 3.7 million. Furthermore, the two
states in the South of Brazil that are studied here—Rio
Grande do Sul and Santa Catarina—are ranked third in
Brazil in tourist arrivals, after the states of Sa ˜o Paulo and
Rio de Janeiro (EMBRATUR, 2004; Instituto Nacional
De Estadı ´stica, 2003; Instituto de Estudios Turı ´sticos,
2004; World Tourism Organization, 2003).
Spain is also more advanced than Brazil in terms of
Internet network penetration, but the difference is smaller
than in tourism. The digital access index (DAI), managed
by the International Telecommunication Union (2003), is aworldwide standard measure of Internet penetration and
classifies countries into one of four categories of digital
access: high, upper, medium and low. According to this
index, Sweden is the top-rated country in the high access
group, with a DAI of 0.85, while Niger is the lowest rated
in the low access group, with a DAI of 0.04. Spain and
Brazil are in the same upper digital access group, with
DAIs of 0.67 and 0.50, respectively. These two regions were
chosen for the present study because of their differences
from the perspective of the economics of tourism, and their
similarities in terms of Internet access.
3. Internet marketing
According to Hoffman and Novak (1997), the commu-
nication structures used by companies can be classified as
one-to-many or many-to-many. In the first case, companies
must provide content that reaches the public through
their exposure to mass media, such as TV, radio, news-
papers, etc. If these companies wish to receive any
customer feedback, they must provide access via telephone
lines or mail addresses. In the second case, on the Internet,
people can interact with content provided by companies,
expressing their opinions, suggestions and comments.
These opinions can also be read by other consumers,
forming interest groups. People can also provide their
own content to the media, about themselves or about
companies.
As the Internet has penetrated people’s lives and
companies’ business practices, providing interactivity and
commercial support, it has had a great impact on market-
ing practices. As a result of this interactivity, in order for aconsumer to be exposed to any given media content, they
must first be interested in it and take the initiative (Chaffey
et al., 2003; Deighton, 1996). In order to maintain that
interest, the user has to feel comfortable and absorbed
while experiencing the media content. This behavior is
defined by Hoffman and Novak (1997) as ‘‘flow’’ and by
Deighton (1996) as ‘‘high intensity’’.
As the Internet affects marketing practices, some
attention has been paid to the potential applicability of
the marketing mix (McCarthy, 1976) in this new environ-
ment. Some authors argue that the product, price, point-of-
sale and promotion dimensions fit in well with the Internet
(Chaffey et al., 2003), while others propose a complete
replacement (Constantinides, 2002; Kotler, 1998). The
marketing mix was already subject to criticism even before
the Internet, but it continues to offer the simplicity desired
by management practices. Some limitations, however, must
be recognized, especially in the context of the web. The
following chapters analyze the marketing mix considering
the influence of the new media.
3.1. Promotion
Promotion is the process by which a company commu-
nicates with the market, providing information about itsproducts and services or about the company itself
(McCarthy, 1976). Up to this point, it can be considered
a one-to-many communication process. The Internet,
however, provides interactivity as an important additional
development to this process, and the new concept of
promotion must therefore embrace a many-to-many
communication model. One implication of this new
concept is that decisions about content must be taken
more carefully, since users pay more attention to the
website experience (Chaffey et al., 2003).
3.2. Point-of-sale
The Internet offers the possibility of being used as a tool
both for promotion and for point-of-sale. Depending on
the market involved, it has not only threatened distribu-
tors, but also created alternative forms of distribution, an
effect called redistribution (Pitt et al., 1999). Before
establishing direct contact with the consumer, suppliers
must evaluate their relationship with current distribution
channels, for making direct contact might endanger a
valuable situation. If the buyer is also the distributor and
its bargain power is relatively high; then the direct-to-
consumer approach must be handled carefully (Porter,
1980).
ARTICLE IN PRESS
S. Schmidt et al. / International Journal of Hospitality Management 27 (2008) 504–516 505
-
8/18/2019 1-s2.0-S0278431907000722-main
3/13
3.3. Price
The consumer now has a greater variety of comparable
offers, which forces market prices down. Nevertheless,
pressure does not only come from consumers. Yelkur and
Dacosta (2001) state that, since the Internet can provide more
exact information about consumer identification, location,and products desired, it is a better environment for price
segmentation, or differential pricing, as they describe it.
3.4. Product
The potential for product configuration is also greater
using the Internet than with the traditional market (Ghosh,
1998). Both basic and extended products can be improved
with information-based service. In depth technical doc-
umentation, online support and discussion forums are
examples of such improvements, resulting in improved use
of products. Online consumer surveys and improved
information exchange between suppliers and their partners
can also offer future product enhancements (Chaffey et al.,
2003; Quelch and Klein, 1996).
3.5. Customer relationship and customer retention
Distinct from McCarthy’s (1976) four Ps, Gro ¨ nroos
(1995) proposes a dimension that considers service
industries and which has gained importance among
scholars and executives: the customer relationship.
Although the term customer relationship is widely used,
no consensus has been reached on its definition. Harker
(1999) cited 26 different definitions for this term. However,the same basic principles permeate most studies: the
establishment of long-term relationships between the
company and the customer, mutual perception of value
added and feelings that reinforce the relationship, such as
trust, loyalty and commitment.
There is a general agreement among scholars that the
Internet is an appropriate environment for supplementing
consumer relationships by increasing customer retention
(Chaffey et al., 2003; Gilbert et al., 1999; Peppers and
Rogers, 2000; Yelkur and Dacosta, 2001). Certain website
features help provide the conditions for this, such as the
possibility of users signing up and further identification
and the opportunity to reach a large number of people.
However, users have concerns related to inputting their
personal information on websites, and so websites must
provide security and privacy mechanisms.
4. Website evaluation
Investigations focused on the evaluation of websites can
be classified into three categories, based on their research
method: (1) evaluation by phases, (2) evaluation by
characteristics and (3) evaluation by characteristics and
effectiveness. Each category will be dealt with in more
detail in the following sections.
4.1. Evaluation by phases
Research employing this evaluation method presumes
that the richness of a website’s characteristics is propor-
tional to the company’s experience in electronic commerce.
This experience is expressed in website phases, also called
steps or layers, each comprising certain features. In otherwords, according to these studies, the more experience a
company has in electronic commerce, the richer its website
will be.
Two Australian authors, Burgess and Cooper (1999)
developed the model of Internet commerce adoption,
abbreviated to MICA, which consists of three layers:
(1) promotion that concerns information about the
company; (2) provision, which is associated with inter-
activity; and (3) processing, related to online transactions.
It could be observed that items belonging to each layer are
not completely coherent with the concept of promotion
proposed by McCarthy (1976). For example, value-added
information and technical information are classified as
interactivity, rather than as promotion. These authors later
‘‘upgraded’’ their instrument, including new measurement
items, and renaming it the extended MICA, or eMICA
(Burgess and Cooper, 2000). The instrument has since been
employed (Burgess et al., 2001; Doolin et al., 2002) without
significant modifications.
Teo and Pian (2003) proposed a web adoption model in
terms of levels of characteristics, based on a company’s
objectives in using the Internet: Level 0 is when there is no
website or just an e-mail account; at Level 1 the company
wants to occupy a web address or simply establish an initial
online presence; at Level 2 the company is prospecting,delivering actual information about products; Level 3
entails business integration, online links to clients and
suppliers; Level 4 is business transformation. The instru-
ment was applied to 159 companies in Singapore and some
relationships between adoption levels and company size or
strategy were tested using one-way ANOVA.
Research based on phases or layers tend to reduce the
complexity of website evaluation, which is desirable for
practical purposes. However, some limitations should be
taken into account. The objectives of businesses using the
Internet are as diverse as their strategies. For example, a
company may want to integrate its value chain back-
wards—toward its suppliers—and might achieve business
integration before even prospecting market. Depending on
the industry or the firm considered, some characteristics
may be more developed than other ones, resulting in
website classification within more than one category and
distorting subsequent analysis.
4.2. Evaluation by characteristics
This method does not suggest a path for website
development, as evaluation by phases does. On the
contrary, evaluation by characteristics bases its analysis
on the presence of website characteristics or functionalities.
ARTICLE IN PRESS
S. Schmidt et al. / International Journal of Hospitality Management 27 (2008) 504–516 506
-
8/18/2019 1-s2.0-S0278431907000722-main
4/13
Therefore, it is more flexible for website evaluation than
the method described above. Some of the studies that fit
into this class of evaluation method are described
immediately below.
Ho (1997) has been cited by investigations that used the
evaluation by phases approach (Burgess and Cooper, 1999,
2000; Burgess et al., 2001; Doolin et al., 2002) and also byinvestigations that used evaluation by characteristics
(Rachman and Buchanan, 1999). He suggests an evalua-
tion structure based on a two-dimension matrix. The first
dimension is named ‘‘purpose’’ and is composed of three
categories:
Promotion: information about products and services
offered to consumers.
Provision: information to obtain good will, exposure,
credibility.
Processing: business transactions.
The other matrix dimension is named ‘‘value-created’’ and
has four categories: timely value, custom value; logistic
value and sensational value.
Wan (2002) proposed an instrument for evaluating the
websites of international tourist hotels and tour operators
in Taiwan. This author used three categories: user inter-
face, variety of information and online reservation. User
interface was defined in terms of ease of access, search
mechanisms, standard layout and helpful interface. Variety
of information was about simplicity, relevancy of informa-
tion, information coverage and hyperlinks. Online reserva-
tion referred to the presence or absence of online
reservation systems. The instrument contained a consider-able number of subjective items, such as ‘‘physical access to
website’’ measured by a 5-point Likert scale. To reduce the
undesirable effects of this subjectivity, the instrument was
applied by two assistants.
In one of the few studies focusing on Brazilian hotels,
Rocha (2003) qualitatively analyzed the websites of 50
hotels in Rio de Janeiro using a 61-item instrument which
were broken down into general characteristics, travel
information, general information, special characteristics,
design and functionality, product information and reserva-
tion facilities. On the subject of future research in the area,
the author indicated the need for studies focusing on hotel
characteristics related to the perception of hotel marketers
and comparisons of distinct tourist regions.
One study using evaluation by characteristics that
employed a more consistent method, relative to other
studies found in the literature, was carried out by Muylle et
al. (2004). Their objective was to define and validate the
‘‘website user satisfaction’’ construct, in the context of the
tourism distribution industry. The scale was constructed
using a qualitative approach and then validated quantita-
tively. After cleaning up the initial constructs, the final
scale included the following categories: information,
connection, layout and languages. The measurement
instrument was then applied to 719 web users and
statistically validated, using confirmatory analysis and
structural equation modeling.
With the exception of the study cited above, studies that
used characteristics for classification did not present
sufficient evidence of construct validation. This is relevant
to the extent that the ideas proposed theoretically may not
actually be represented by the measurement items appliedempirically, which seriously limits the analysis of results.
Furthermore, this study methodology suggests that the
adoption of certain website characteristics should be based
on what other competitors have, in a benchmarking
approach. However, can benchmarking alone help practi-
tioners decide on their website structure? On what grounds
can an organization decide which characteristics their
website should have? How relevant is analysis of website
characteristics if it does not associate them with the
effectiveness of websites as marketing tools? Other studies
have addressed these issues by introducing effectiveness
assessment to website analysis.
4.3. Evaluation by characteristics and effectiveness
When websites are approached from a perspective of
their effectiveness, their characteristics gain a fresh prag-
matic relevance, probably welcomed by practitioners.
Authors that have adopted this approach have understood
the construct ‘‘website effectiveness’’ in different ways:
financial results, consumer intentions, etc. Not many
studies have been undertaken with this perspective; some
that have are described immediately below.
Mummalaneni (2005) proposed an analysis structure in
which the features web shopping environments areassociated with shoppers’ emotional status and this in turn
with behavior and shopping intentions. Previously existing
scales were used and the author verified their reliability
using Cronbach’s alpha, but the scale’s validity was not
assessed. After regression analysis, the author concluded
that website characteristics were associated with emotional
status, but not with shopping intentions. Neither was
emotional status associated with shopping intentions.
Investigating the influence of content, design and privacy
and security on shopping intentions, Ranganathan and
Ganapathy (2002) evaluated these dimensions using
exploratory factor analysis and associated them with
shopping intentions by multiple discriminant analysis.
Security was found to be the primary factor affecting
shopping intentions, followed by privacy, design and, last
of all, content. The model was able to explain just 21.9% of
variance in shopping intention, which left much of the
variance out of the model.
Using an approach from cognitive psychology, Rosen
and Purinton (2004) created a website preference scale
(WSPS). Their initial constructs for website characteristics
were coherence, complexity, legibility and mystery. Website
effectiveness was measured by (1) general impression of
website and (2) probability of a return visit to it.
Exploratory factor analysis was applied, rejecting the
ARTICLE IN PRESS
S. Schmidt et al. / International Journal of Hospitality Management 27 (2008) 504–516 507
-
8/18/2019 1-s2.0-S0278431907000722-main
5/13
mystery construct. A bivariate procedure, ANOVA, was
used to verify the relationship between website character-
istics and their effectiveness, and the authors concluded
that all constructs had a strong impact on website results.
After observing the studies presented here, from evalua-
tion by phases and characteristics through to approaches
using effectiveness analysis, it is possible to state that thereis no single consolidated method for the purposes of this
investigation. This may be due to the different back-
grounds from which this theme has been approached,
possibly because of its complexity or even because of the
short period for which it has been subject to academic
investigation.
5. Method
This study can be qualified as descriptive, because it
describes the scenario of website structure in small hotels,
and quantitative, because it uses quantitative data for this
purpose. Data collection and analysis was a four-stage
process:
1. items for observing website characteristics were collected
from literature;
2. e-mails were sent to hotel marketing managers request-
ing their opinion of their website’s effectiveness;
3. the websites of hotels that answered the e-mail
were measured by the author using the items collected
in step 1;
4. the measurement model was validated and a struc-
tural model was developed for the purposes of this
investigation.
Each of these steps is detailed below.
5.1. Measurement items for website characteristics
The characteristics of each website were collected by
reference to a series of items organized into categories.
Initially, the four Ps of McCarthy’s (1976) were elected as
categories: promotion, price, product, and point-of-sale.
The name of this last category was changed to reservation
system, in order to make it more applicable to the hotel
industry. Then, in response to the limitations of
McCarthy’s marketing mix in the new marketing environ-
ment, new categories were included: multimedia, navig-
ability, customer retention and a single category addressing
both privacy and security issues. The complete measure-
ment instrument is given in Table 1.
A brief description follows of the main references on
which each category is grounded:
Promotion: The concept of promotion used in this
research adheres to that of McCarthy (1976), i.e., commu-
nication from the company to the market, about its
products and services or about company identity. Most
of the authors referred to have used this concept in their
research (Bell and Tang, 1998; Burgess and Cooper, 2000;
Cox and Dale, 2002; Ho, 1997; Huizingh, 2000; Muylle
et al., 2004; Ranganathan and Ganapathy, 2002; Rocha,
2003; Teo and Pian, 2003; Wan, 2002), but not all of them
use the term ‘‘promotion’’ to describe the concept. For
example, Bell and Tang (1998), Huizingh (2000) and
Ranganathan and Ganapathy (2002) use ‘‘content’’. Other
expressions used in this sense are ‘‘provision’’ (Burgess etal., 2001), ‘‘variety of information’’ (Wan, 2002) and
‘‘online resources’’ (Cox and Dale, 2002), to mention just a
few variations. This category included text and photos
about the hotel, its rooms and the tourist region. Ho (1997)
and Cox and Dale (2002) included website design and
graphics in their concept of promotion, whereas most
authors include these in assessment of navigability. The
items used to measure promotion in the present study were
related to hotel-specific information about hotel services,
rooms and the tourism opportunities of the surrounding
region, taking account of the volume and form of
presentation of this information, the amount of text and
photos.
Price: In this category we measured whether price
segmentation was being practiced by hotels on their
websites. If a hotel requested any form of identification
in order to access room prices, this was considered a
segmentation strategy, in a simpler scale than the one used
by Yelkur and Dacosta (2001).
Product: This category assesses the presence of product
configuration practices, represented by any structured
information that could possibly be entered during the
reservation process. Any information such as proximity to
the elevator, sea view, pillow type, etc. was considered
product configuration (Ghosh, 1998; Piccoli et al., 2002;Quelch and Klein, 1996).
Multimedia: Assesses the availability of videos or 3D
photos of hotel services, rooms and the tourist region.
Some authors have used the term ‘‘design’’ to indicate the
presence of such characteristics (Cox and Dale, 2002;
Ranganathan and Ganapathy, 2002; Rocha, 2003), but
the term multimedia was preferred here, since ‘‘design’’
was also used to represent website navigation struc-
ture (Huizingh, 2000). Some authors even include both
concepts—structure and multimedia—under the term
‘‘design’’, which may confuse its meaning.
Navigability: Measures how easy it is for users to access the
information they want on the website, including standard
menu structure, home-page links, standard page design and
the indication of user position in the menu structure. Most
authors have used this same concept and items in their
research (Bell and Tang, 1998; Cox and Dale, 2002; Huizingh,
2000; Muylle et al., 2004; Ranganathan and Ganapathy,
2002; Rocha, 2003; Rosen and Purinton, 2004; Teo and Pian,
2003; Wan, 2002), but some included the same meaning
under other headings, such as ‘‘design’’, ‘‘structure’’, ‘‘user
friendliness’’, ‘‘ease of use’’, ‘‘coherence’’, and so on.
Reservation system: Measures the capacity of the hotel’s
website to provide room reservations. This concept has
also been used by Bell and Tang (1998), Burgess et al.
ARTICLE IN PRESS
S. Schmidt et al. / International Journal of Hospitality Management 27 (2008) 504–516 508
-
8/18/2019 1-s2.0-S0278431907000722-main
6/13
(2001), Huizingh (2000), Piccoli et al. (2002) and others;
although it was referred to as ‘‘online transaction’’,
‘‘processing’’, ‘‘reservation facilities’’, and so on. However,
the available literature did not explore the fact that the
mere existence of a reservation system, whether by e-mail
or automatic information system, does not ensure that the
reservation process actually works. Therefore, reservation
requests were placed with all hotels, and the time between
the reservation request and their response was recorded.
The items included in this category were the presence of a
reservation process, sales policy (Cox and Dale, 2002) and
the reservation process response time.
Customer retention: Refers to website characteristics that
help hotels to retain their clients, helping to establish long-term
relationships with them. There was no consensus in the
literature about the term used to represent this concept. Terms
like ‘‘customer service’’ and ‘‘relationship services’’ are related
to this concept, but others like ‘‘website usefulness’’ (Bell and
Tang, 1998), ‘‘provision’’ (Burgess et al., 2001) or ‘‘processing’’
(Ho, 1997), that include items referring to customer retention,
are more difficult to associate. In common with the reservation
system category, an item measuring the time taken to provide
client feedback was included. Customer forms and e-mails
were sent to hotels in order to ask for information, and the
time between sending and receiving a reply was registered. The
items included in this category were the presence of a loyalty
program, user registration form, newsletter, FAQ and the time
taken to provide client feedback.
Privacy and security: Refers to items that afford website
customers a sense of privacy and security (Burgess et al.,
2001; Cox and Dale, 2002; Ranganathan and Ganapathy,
2002; Rocha, 2003). This has also been referred to as
‘‘customer confidence’’ (Cox and Dale, 2002). Items
recorded were secure credit card web page, security policy
and privacy policy.
5.2. Measurement items for website effectiveness
Measuring the effectiveness of marketing tools in general
is very useful for managers. It helps them understand which
ARTICLE IN PRESS
Table 1
Measurement items for website characteristics
Promotion
HServText Hotel services text 0 ¼ no text; 0.33 ¼ citation; 0.67 ¼ simple; 1 ¼ complete Ordinal
HServPhoto Hotel services photos 0 ¼ no photo; 0.33 ¼ 1 photo; 0.67 ¼ 2 to 4 photos; 1 ¼ +4 photos Ordinal
RoomText Room text 0 ¼ sin text; 0.33 ¼ citation; 0.67 ¼ simple; 1 ¼ complete Ordinal
RoomPhoto Room photos 0 ¼ no photo; 0.33 ¼ 1 photo; 0.67 ¼ 2 to 4 photos; 1 ¼ +4 photos Ordinal
RegionText Surroundings text 0 ¼ sin text; 0.33 ¼ citation; 0.67 ¼ simple; 1 ¼ complete Ordinal
RegionPhoto Surroundings photos 0 ¼ no photo; 0.33 ¼ 1 photo; 0.67 ¼ 2 to 4 photos; 1 ¼ +4 photos Ordinal
Price
PriceAccessID Presence of price segmentation 0 ¼ absent; 1 ¼ present Ordinal
Product
ProductConfig Presence of product configuration features 0 ¼ absent; 1 ¼ present Ordinal
Multimedia
HServVideo Hotel services videos or 3D photos 0 ¼ absent; 1 ¼ present Ordinal
RoomVideo Room videos or 3D photos 0 ¼ absent; 1 ¼ present Ordinal
RegionVideo Surroundings videos or 3D photos 0 ¼ absent; 1 ¼ present Ordinal
Navigability
StandDesign Standard page design 0 ¼ no; 1 ¼ yes Ordinal
StandMenu Standard menu structure 0 ¼ absent; 1 ¼ present OrdinalMenuPosition Structure localization information 0 ¼ absent; 1 ¼ present Ordinal
LinksHome Home page links 0 ¼ absent; 1 ¼ present Ordinal
Reservation system
ReservSystem Type of reservation system 0 ¼ no reservation; 0.33 ¼ e-mail; 0.67 ¼ form; 1 ¼ automatic system Ordinal
ReservTime Reservation system response time Time, in hours, from reservation request to confirmation of availability Metric
SalesPolicy Sales policies (canceling reservations, refunds, etc.) 0 ¼ no; 0.5 ¼ partly; 1 ¼ yes Ordinal
Customer retention
UserRegister User registration 0 ¼ absent; 0.5 ¼ basic data form; 1 ¼ profile data form Ordinal
NewsLetter Newsletter 0 ¼ absent; 0.5 ¼ basic; 1 ¼ personalized Ordinal
FidelityProgr Fidelity program 0 ¼ absent; 1 ¼ present Ordinal
FAQ FAQ 0 ¼ absent; 1 ¼ present Ordinal
ClientServTime Customer service response time Time, in hours, from inquiry to response Metric
Privacy and securityPrivacyPolicy Privacy policy 0 ¼ absent; 1 ¼ present Ordinal
SecCrdtCardPg Secure credit card page 1 ¼ not secure; 0 ¼ not applicable; 1 ¼ secure Ordinal
SecurityPolicy Security policy 1 ¼ not present; 0 ¼ not applicable; 1 ¼ present Ordinal
S. Schmidt et al. / International Journal of Hospitality Management 27 (2008) 504–516 509
-
8/18/2019 1-s2.0-S0278431907000722-main
7/13
tools work and which do not. As a result, companies are
able to change the way they do things and so improve their
overall results. In order to measure website effectiveness, it
is important to know what can be measured and how to
measure it.
For the purposes of this study, website effectiveness, in
the context of marketing, was defined as the results thewebsite may bring to the company in terms of marketing.
Chaffey et al. (2003) proposes some objective indicators for
measuring website effectiveness, including sales, market
share and customer retention. However, the adoption of
these indicators as objective measures would have imposed
certain practical limitations to this research study, since
practitioners would be concerned about leakage of
strategic information. Venkatraman and Ramanujam
(1987) have proposed that there is convergence between
economic measures of business performance and the
perceptions of managers of that performance, so that the
latter can be used to represent the former. This conver-
gence was also corroborated by Kohli et al. (1993) and
Perin and Sampaio (1999) —the latter study being carried
out in Brazil. Despite the subjective character of these
kinds of measures, the authors pointed out that there are
advantages to using managers’ perceptions: increased
number of responses, better understanding of what
is being measured and less concern about strategic
information outflow.
Managers’ perceptions about their website’s effectiveness
were therefore used in this study as performance indicators
for those websites, based on their convergence with
objective measures and the practical implications of that
convergence. Therefore, e-mails were sent to hotel market-ing managers asking them four questions about hotel
website effectiveness, requesting their perception of (1) new
client acquisition, (2) market share, (3) sales volume and
(4) customer retention. The answers to these questions
comprised a 5-point Likert scale, defining the degree of
effect the website has on each item as: null, weak positive,
reasonable positive, strong positive or extremely strong
positive.
5.3. Procedures for website evaluation and analysis
The first step was to collect e-mail addresses using
generic search engines, such as Google and Yahoo, as well
as on specific tourist portals, such as Embratur for Brazil
and Turespan ˜ a for Spain. An e-mail was then sent to each
of 1800 hotels—715 hotels in South Brazil and 1085 in
the Balearic Islands—and resent within a week to
non-respondents. The only variable that significantly
differentiated between the early respondents and the late
respondents was room price ( p ¼ 0.049), suggesting
that higher-priced hotels were more interested in the
effectiveness of their websites.
The majority of the e-mails sent were not answered
(79.9%), undeliverable (9.1%) or sent to a hotel without a
website that could be analyzed (1.2%). Table 2 lists data
collection process statistics. The final sample comprised
167 (9.3%) websites, which were then evaluated using the
instrument described earlier.
Eighty-four percent of the hotels in the sample had 220
beds or less, which characterizes small and medium size
hotels. After data collection, a confirmatory factor analysis
was performed, in order to evaluate the constructsdeveloped during the literature review and to assess
convergent validity. Discriminant validity and reliability
were also estimated (Garson, 2005; Hair et al., 2005;
Malhotra, 2001). The measurement model was then
validated using structural equation modeling and finally
its causal relationships were verified with the structural
model.
The use of structural equations demands care with
certain issues, such as sample size, multivariate normality,
outlier presence and the number of observed items per
construct. There is no consensus among authors on
indications of sample. Garson (2005) states that the median
sample size in 72 SEM studies was 198. Anderson and
Gerbing (1988) accept sample sizes greater than 150. Hair
et al. (2005) suggest that sample size depends on the
number of estimated parameters: a minimum of 5 and a
maximum of 10 cases per parameter. MacCallum and
Austin (2000) warn that a given number established in
order to test a model is not necessarily adequate for other
purposes, and that general rules should not be generally
accepted. Based on these indications, the sample size of the
present study—167 cases—is considered acceptable. How-
ever, it does not allow for the construction of comparative
models of Brazil with Spain, and so the model presented in
this study combines the two samples. Although they havesimilar Latin roots, it is possible that they would exhibit
differences in terms of the business behaviors of marketing
managers and in terms of characteristics embedded in their
hotel websites.
Some of the items on the instrument are measured on a
dichotomous ordinal scale, reflecting characteristics that
are either present or absent. Although structural equations
can tolerate this type of scale, its use influences multivariate
normality (Garson, 2005). This was calculated using
Mardia’s coefficient, which, as was expected, indicated a
ARTICLE IN PRESS
Table 2Data collection process
Process Brazil Spain Total
n % n % n %
E-mails sent 715 100.0 1085 100.0 1800 100.0
E-mails not delivered 73 10.2 91 8.4 164 9.1
E-mails not answered 545 76.2 893 82.3 1438 79.9
No website 10 1.4 11 1.0 21 1.2
Invalid respondent 1 0.1 0 0.0 1 0.1
Respondent 46 months in hotel 4 0.6 3 0.3 7 0.4
Website offline 0 0.0 2 0.2 2 0.1
Websites evaluated 82 11.5 85 7.8 167 9.3
S. Schmidt et al. / International Journal of Hospitality Management 27 (2008) 504–516 510
-
8/18/2019 1-s2.0-S0278431907000722-main
8/13
strong deviation from normality. As there were no relevant
outliers in the sample, data transformations could not be
processed and other estimation methods would have
demanded much higher sample sizes and therefore careful
selection of fit indexes was finally adopted as work-around
method (Hair et al., 2005; Schumacker and Lomax, 1996).
Fit indexes less sensitive to non-normal distribution wereselected to minimize this bias (Kline, 1998). The absolute fit
indexes chosen were the ratio of chi-square to degrees of
freedom (w2/DF) and the root mean square error of
approximation (RMSEA). The incremental fit indexes
employed were the Tucker–Lewis Index (TLI), the
Bentler–Bonett normed fit index (NFI) and the compara-
tive fit index (CFI). Additionally, a parsimonious fit index
was selected for future model comparison: the parsimony
normed fit index (PNFI).
Data screening was performed in order to identify lower
item variance. Price segmentation and product configura-
tion (PriceAccessID and ProductConfig) exhibited extre-
mely low variance (0.006 and 0.018, respectively) indicating
that these are not current practices among the hotel
websites in this sample. Only one of the hotels practices
price segmentation and three provide product configura-
tion features on their website. These items were then
excluded from the analysis.
6. Results
6.1. Validation of the measurement model
The first step in the validation process was to perform
exploratory factor analysis (EFA) on the website char-acteristics instrument with the number of factors fixed at
six, to determine whether the items collected were in fact
associated with the categories identified from the literature.
The choice of six factors was determined from the number
of constructs identified in the literature and the number of
factors suggested by screenplot analysis. The EFA method
employed was principal axis factoring, as indicated for use
with SEM (Garson, 2005). In view of the sample size, items
with a factor loading of less than 0.45 in any factor were
considered non-significant and were discarded (Hair et al.,
2005). Explanatory factor analysis returned a KMO of
0.746 and a total explained variance of 60.394%, which
were considered adequate. Table 3 lists the EFA factor
loadings, suggesting a different view from the literature in
some dimensions, as will be described in detail next.
Factor 1 grouped items that in the literature were
associated with customer retention: fidelity program, user
register, FAQ and newsletter. Additionally, privacy policy
was included here, which makes sense, since, whenever
users need to register on a website to participate in the
fidelity program, a privacy policy is necessary to ensure
that their private information is not misused by the hotel.
The item privacy policy was also significantly associated
with privacy and security, represented by factor 4. In the
case of this factor, the items secure credit-card web page,
security policy, sales policy and privacy policy all indicate
a concern about information transparency between
hotel and tourist, assuring hotel clients that they can
trust the information provided by the website, and
management that they can trust the information they are
receiving.
Promotion items all show significant loadings on factor2, with the exception of hotel services photo. As most
hotels provided photos showing their properties and/or
grounds, this item exhibited lower variance (0.04) than the
other items in this construct (0.076–0.181). This suggests
that the practice is common among hotels, but on the other
hand, the item does not help explain promotion, due to its
low variance.
Navigability items are represented by factor 3. In this
case, the item links home presented a factor loading of
0.397, approaching the 0.45 limit. This item was considered
important to this construct’s meaning, and was kept in the
instrument.
Multimedia items were all represented in factor 5 with
significant factor loadings.
Items related to the response time of the reservation
process and client service were loaded in factor 6. Although
it is not found in the literature, this concept has been
mentioned previously by Cox and Dale (2002), Harker
(1999), Peppers and Rogers Group (2000) and Buhalis
(1998). Given the nature of these items, this new category
was named ‘‘service promptness’’.
Finally, the category reservation system was not
identified by factor analysis. The item reservation system
was not significantly loaded in any factor and was
discarded. The other two items were divided into differentcategories from those described previously: sales policy was
related to privacy and security, represented by factor 4, and
reservation system time formed a new category with client
service time, represented by factor 6.
These factor loadings exhibited by the items, related to
their respective factors, provided adequate convergence
validity of the measurement instrument. A final EFA
calculated without the discarded items returned a KMO of
0.709 and a total explained variance of 61.345%.
Discriminant validity was measured by means of
correlation between constructs. This was calculated using
the software program AMOS. The greatest correlation was
between customer retention and privacy and security
(0.712), as would be expected after the factor analysis,
since privacy policy correlated significantly with both
factors. Since there was no correlation greater than 0.85
(Garson, 2005; Kline, 1998), discriminant validity was
confirmed.
Compound reliability was measured for each construct,
including website effectiveness, in order to verify multi-
variate reliability. The lowest result was 0.668, attributed to
service promptness. As all resultant values were over the
suggested limit of 0.5 (Hair et al., 2005), the instrument was
considered to have adequate reliability. The final constructs
and items are listed in Table 4.
ARTICLE IN PRESS
S. Schmidt et al. / International Journal of Hospitality Management 27 (2008) 504–516 511
-
8/18/2019 1-s2.0-S0278431907000722-main
9/13
The measurement model was then subjected to structural
equations modeling, using AMOS. No transgression
estimates were observed, i.e., standardized regression
weights greater than 1.0 or negative error variances (Hair
et al., 2005). Fit indexes were then verified and their results
are presented in Table 5.
Comparing target values with calculated values, the
model can be considered with adequate fit (Anderson and
Gerbing, 1988; Garson, 2005; Hair et al., 2005).
6.2. Analysis of the structural model
Once the measurement model had been validated, the
structural model was then designed, as illustrated in Fig. 1.
The resulting standard regression weights, standard errors
and significance levels are listed in Table 6. According to
these results, only promotion has a significant association
with website effectiveness. The other categories—multimedia,
navigability, customer retention, privacy and security and
service promptness—are not associated with results perceived
by hoteliers. This may indicate that the Internet is being
employed as merely another form of mass media, like TV or
radio, which is extensively criticized by Hoffman and Novak
(1997) and others.
Website characteristics involving multimedia may not be
valued by customers, or their value may be overshadowed
ARTICLE IN PRESS
Table 4
Final instrument items
Category Items
Promotion HservText Hotel services text
RoomText Room text
RoomPhoto Room photos
RegionText Surroundings text
RegionPhoto Surroundings photos
Multimedia HservVideo Hotel services videos or 3D photos
RoomVideo Room videos or 3D photos
RegionVideo Surroundings videos or 3D photos
Navigability StandDesign Standard page design
StandMenu Standard menu structure
MenuPosition Structure localization information
LinksHome Home page links
Customer retention UserRegister User registration
NewsLetter Newsletter
FidelityProgr Fidelity program
FAQ FAQ
PrivacyPolicy Privacy policy
Privacy and security PrivacyPolicy Privacy policy
SecCrdtCardPg Secure credit card page
SecurityPolicy Security policy
SalesPolicy Sales policies
Service promptness ReservTime Reservation system response time
ClientServTime Customer service response time
Table 3
Exploratory factor analysis
Item Factor
1 2 3 4 5 6
FidelityProgr 0.758
UserRegister 0.716FAQ 0.675
PrivacyPolicy 0.664 0.501
NewsLetter 0.486
ReservSystem
RoomText 0.722
HServText 0.662
RegionText 0.648
RegionPhoto 0.646
RoomPhoto 0.503
HServPhoto
StandMenu 0.884
StandDesign 0.710
MenuPosition 0.429
LinksHome 0.397
SecCrdtCardPg 0.442 0.730
SecurityPolicy 0.599
SalesPolicy 0.509
HServVideo 0.824
RoomVideo 0.823
RegionVideo 0.480
ReservTime 0.641
ClientServTime 0.480
Extraction method: principal axis factoring
Rotation method: varimax
Source: SPSS output.
S. Schmidt et al. / International Journal of Hospitality Management 27 (2008) 504–516 512
-
8/18/2019 1-s2.0-S0278431907000722-main
10/13
by the time they take to download. The more multimedia
content, more download time—and user patience—are
needed.
Despite exhibiting a moderate correlation with promo-
tion (r ¼ 0.317; p ¼ 0.00), navigability did not present an
association with website effectiveness. This could be
explained by the intensive use of navigability character-istics, making it a common practice among hotels.
Websites containing features to support customer reten-
tion also failed to demonstrate any relation to hoteliers’
perceptions of effectiveness. A closer look indicated that,
out of 27 hotel websites offering user registration, 15 did
not publish a privacy policy. This lack of attention to users’
concerns about private information may explain part of the
absence of any customer retention impact on website
effectiveness.
Contrary to what is proposed by Ranganathan and
Ganapathy (2002) and others, privacy and security did notpresent an association with website effectiveness. This may
corroborate the suggestion that the intended use of hotel
websites is as promotional mass media, rather than
exploiting its potential as a point-of-sale or customer
ARTICLE IN PRESS
Table 5
Fit indexes for the measurement model
Index type Index Target value Calculated value
Absolute fit w 2 – 492.508
DF – 278w2/DF o5 1.772
RMSEA o0.8 0.068
Incremental fit TLI 40.9 0.951
NFI 40.9 0.917
CFI 40.9 0.961
Parsimonious fit PNFI – 0.726
Fig. 1. Structural model.
Table 6
Standard regression weights
Relationship Standard
weights
Standard
error
p
Promotion - Effectiveness 0.619 0.459 0.000
Multimedia - Effectiveness 0.046 0.317 0.576Navigability - Effectiveness 0.090 0.325 0.353
Customer
retention
- Effectiveness 0.019 1.086 0.892
Privacy and
security
- Effectiveness 0.123 0.487 0.414
Service
promptness
- Effectiveness 0.102 0.299 0.293
S. Schmidt et al. / International Journal of Hospitality Management 27 (2008) 504–516 513
-
8/18/2019 1-s2.0-S0278431907000722-main
11/13
retention tool. As this potential is not being taking
advantage of, privacy and security become less relevant.
In fact, most of the hotels did not need a security policy
(85%), but a little more than half (52%) of those that did
need a policy did not have one.
Service promptness was heavily influenced by the
information technology responsible for room reservationsbehind the website. Automatic reservation systems pro-
vided room availability confirmation almost instantly,
while reservation forms linked to an e-mail-sending process
took up to several days to be answered—when there
actually was an answer. Overall, 18.6% of reservation
requests were answered after more than one week or
not answered at all. When non-working forms or wrong
e-mails are included, this number rises to 28.8% of all the
hotels investigated. Response times for client service were
no different. Indeed, response times longer than one
week—or non-existent responses—accounted for 28.7%
of the sample. According to these results, a significant
proportion of hotel websites are ‘‘inert’’, that is, they do
not have the appropriate organizational support to
respond to user-initiated contact through the Internet.
The results presented here indicate very limited use of
websites by small and medium size hotels in the South
region of Brazil and in the Balearic Islands, resembling
mass-media marketing promotion. However, some reasons
for this can be hypothesized.
Most tourists do not make room reservations through
the websites of small and medium size hotels. Hoteliers
may think that, if this point-of-sale is not important, there
is no reason to be effective in an organizational process
that deals with small demands. If website reservationprocesses were really the main source of hotels’ revenues,
they would certainly be more efficient. They would reply
more promptly to reservation requests, in contrast with
what was observed in this study.
Major income may still be provided by traditional
distribution channels. Tourist operators and travel agencies
may have enough bargaining power to inhibit hotels’ direct
contact with clients. Even if Internet transaction costs are
lower, hotels may not be comfortable with offering lower
prices than their intermediaries, possibly fearing commer-
cial retaliation. Internet tourists value lower prices (Rach-
man and Buchanan, 1999), so when they are evaluating
available quotations, they may find local agent prices more
attractive. Another reason tourists turn to traditional
distribution channels may be associated with a sense of
security. Dealing with a local tourist agency is convenient
when problems arise, rather then with a distant hotel,
which, sometimes, a tourist will not know. The generally
deficient security and privacy policies observed in the
present study may compound this. Most hotel tourists may
be still going to local travel agencies for commercial
transactions.
Since tourists perform most transactions with travel
agencies, hotel websites may be used as a secondary source
for hotel information, because they can provide more
current, extensive and detailed information about hotel
services, rooms and the tourist environment. This may
corroborate the finding that promotion is the only
characteristic associated with website effectiveness.
7. Discussion
The objective of this paper was to investigate the
characteristics of hotel websites and their implications for
website effectiveness. It was not the intention here to deal
with the strategic relationship of hotels with their clients.
As the results described above show, hoteliers should focus
investment on promotion in order to enhance their
websites’ effectiveness, a practice inherited from conven-
tional mass media. Extensive informational texts and
photos about hotel services, rooms and nearby attrac-
tions seem to be associated with website effectiveness in
terms of new client acquisition, market share, client
retention and sales. However, it is possible to elaborate
on certain considerations about the reasons why other
website characteristics did not present associations with
effectiveness.
The results presented earlier suggest there is a circular
effect between website characteristics and consumer
demands. It seems that hotel websites respond inefficiently
to consumer demands for commercial transactions, en-
couraging consumers to use traditional tourist distributors.
As a result, hotel revenues continue to originate from
tourism operators and travel agencies, reducing hoteliers’
interest in developing effective website reservation systems.
Internet promotion exhibited a significant impact on
perceived website effectiveness, probably because consu-mers use websites as a secondary source of information.
If this is so, hoteliers should give some attention to
certain issues. First, direct contact with consumers offers
the possibility of turning distributors’ commissions into
profits. This market opportunity is open and could be
exploited through cooperative strategies to reduce distri-
butor bargaining power. So, once the circular effect has
been broken, the prospects for using the Internet as a
marketing tool are optimistic, but the return on hotel
website investments should be expected to be in the
long run.
Second, the reservation and client support systems on
some hotel websites are not working properly and efforts
must be employed to achieve reliability or this functionality
should be excluded from these websites. Offering online
room reservation and a client communication channel
presume the responsibility of responding to these demands.
By not doing so, hotels may not only lose clients that have
shown an interest in them—after all, they have navigated
to the website looking for information and placed a
reservation or sent a question—they might also damage
their market image over the long term.
Third, companies that develop hotel websites, marketing
consultants, specialized media and other institutional
forces may put pressure on hoteliers to implement
ARTICLE IN PRESS
S. Schmidt et al. / International Journal of Hospitality Management 27 (2008) 504–516 514
-
8/18/2019 1-s2.0-S0278431907000722-main
12/13
advanced functionalities in their websites. However, if
promotion is the only dimension that influences website
effectiveness, as demonstrated by our research, investments
in other website dimensions should be carefully considered.
In addition to practical implications for managers, some
theoretical implications can also be indicated. The litera-
ture review section analyzed website evaluation methodsand those based on evaluation by phases and by
characteristics proved simple to use, but lacked the
relevancy needed by practitioners. On the other hand,
evaluation methods that consider website effectiveness
lacked consistent validation methods. For example, only
Ranganathan and Ganapathy (2002) used multivariate
statistics as an approach to model construction. The
present study included measurement of website effective-
ness in order to improve the relevancy of website
evaluation. Since this was done using consistent validation
procedures, it may be of use as a foundation to future
research on tourist distribution strategies using the Inter-
net. Alternatively, further studies on website evaluation
could propose new measurement instruments and use the
theoretical framework proposed here for comparison. In
this way instruments could be refined and be used to assist
practitioners when investing in this new marketing media.
References
Anderson, J.C., Gerbing, D.W., 1988. Structural equation modeling in
practice: a review and recommended two-step approach. Psychological
Bulletin 103 (3), 411–423.
Bell, H., Tang, N.K.H., 1998. The effectiveness of commercial internet
web sites: a user’s perspective. Internet Research: Electronic Network-ing Applications and Policy 8 (2), 219–228.
Buhalis, D., 1998. Strategic use of information technologies in the tourism
industry. Tourism Management 19 (5), 409–421.
Burgess, L., Cooper, J., 1999. A model of internet commerce adoption
(MICA). Paper presented at the 12th International Bled Electronic
Commerce Conference.
Burgess, L., Cooper, J., 2000. Extending the viability of MICA (model of
internet commerce adoption) as a metric for explaining the process of
business adoption of internet commerce. Paper presented at the
ICTEC3.
Burgess, L., Cooper, J., Alcock, C., 2001. The adoption of the web as a
marketing tool by regional tourism associations (RTAS) in Australia.
Paper presented at the 12th Australasian Conference on Information
Systems.
Chaffey, D., Mayer, R., Johnston, K., Ellis-Chadwick, F., 2003. InternetMarketing, second ed. Prentice-Hall, Englewood Cliffs, NJ.
Constantinides, E., 2002. The 4s web-marketing mix model. Electronic
Commerce Research and Applications 1, 57–76.
Cox, J., Dale, B.G., 2002. Key quality factors in web site design and use:
an examination. International Journal of Quality and Reliability
Management 19 (7), 862–888.
Deighton, J., 1996. The future of interactive marketing. Harvard Business
Review.
Doolin, B., Burgess, L., Cooper, J., 2002. Evaluating the use of the
web for tourism marketing: a case study of New Zealand. Tourism
Management 23 (5), 557–561.
EMBRATUR, 2004. Anua ´ rio estatı ´stico 2003.
Garson, D., 2005. Pa 765 statnotes: an online textbook.
Ghosh, S., 1998. Making business sense of the internet. Harvard Business
Review.
Gilbert, D.C., Powell-Perry, J., Widijoso, S., 1999. Approaches by hotels
to the use of the internet as a relationship marketing tool. Journal of
Marketing Practice: Applied Marketing Science 5 (1), 21–38.
Gro ¨ nroos, C., 1995. Marketing: Gerenciamento e Servic-os. Ed. Campos,
Rio de Janeiro.
Hair, J.F., Anderson, R.E., Tatham, R.L., Black, W.C., 2005. Análise
Multivariada de Dados, fifth ed. Bookman, Porto Alegre.
Harker, M.J., 1999. Relationship marketing defined? An examination of current relationship marketing definitions. Marketing Intelligence and
Planning 17 (1), 13–20.
Ho, J.K., 1997. Evaluating the world wide web: a global study of
commercial sites. Journal of Computer-Mediated Communication 3 (1).
Hoffman, D.L., Novak, T.P., 1997. A new marketing paradigm for
electronic commerce. The Information Society 13, 43–54.
Huizingh, E.K.R.E., 2000. The content and design of web sites: an
empirical study. Information and Management 37 (3), 123–134.
Instituto de Estudios Turı ´sticos, 2004. Encuesta de ocupacio ´ n hotelera.
Retrieved on 12 April 2004 from /http://www.iet.tourspain.esS.
Instituto Nacional De Estadı ´stica, 2003. Espan ˜ a en cifras 2002-cuentas
nacionales.
International Telecommunication Union, 2003. Itu digital access index:
world’s first global ICT ranking education and affordability key to
boosting new technology adoption. Retrieved on 16 January 2004 from/http://www.itu.int/newsarchive/press_releases/2003/30.htmlS.
Kline, R.B., 1998. Principles and Practice of Structural Equation
Modeling. Guilford Press, New York.
Kohli, A.K., Jaworski, B.J., Kumar, A., 1993. Markor: a measure of
market orientation. Journal of Marketing XXX, 467–477.
Kotler, P., 1998. Administrac-a ˜o de Marketing, fifth ed. Atlas, Sa ˜o Paulo.
MacCallum, R.C., Austin, J.T., 2000. Applications of structural equation
modeling in psychological research. Annual Review of Psychology 51,
201–226.
Malhotra, N.K., 2001. Pesquisa de Marketing, third ed. Bookman, Porto
Alegre.
McCarthy, E.J., 1976. Marketing Ba ´ sico-uma Visa ˜o Gerencial, second ed.
Zahar Editores, Rio de Janeiro.
Mummalaneni, V., 2005. An empirical investigation of web site
characteristics, consumer emotional states and on-line shoppingbehaviors. Journal of Business Research 58 (4), 397–551.
Muylle, S., Moenaert, R., Despontin, M., 2004. The conceptualization
and empirical validation of web site user satisfaction. Information and
Management 41 (5), 543–560.
Palmer, A., McCole, P., 2000. The role of electronic commerce in
creating virtual tourism destination marketing organizations. Interna-
tional Journal of Contemporary Hospitality Management 12 (3),
198–294.
Peppers, D., Rogers, M., 2000. The physical-virtual future. Intelligent
Enterprise.
Peppers and Rogers Group, 2000. CRM series-marketing 1 to 1: Peppers
and Rogers Group.
Perin, M.G., Sampaio, C.H., 1999. Performance empresarial: uma
comparac-a ˜o entre indicadores subjetivos e objetivos. In: ENANPAD,
23, 1999, Foz do Iguac-u (PR). Anais. Anpad, Foz do Iguac-u.Piccoli, G., Spalding, B.R., Ives, B., 2002. The customer-service life cycle:
a framework for improving customer service through information
technology. The Cornell Hotel and Restaurant Administration
Quarterly 42 (3).
Pitt, L.R., Berthon, P., Berthon, J.-P., 1999. Changing channels: the
impact of the internet on distribution strategy. Business Horizons.
Porter, M.E., 1980. Competitive Strategy: Techniques for Analyzing
Industries and Competitors. Free Press, New York.
Quelch, J.A., Klein, L.R., 1996. The internet and international marketing.
Sloan Management Review 37 (3), 60–75.
Rachman, Z.M., Buchanan, J., 1999. Effective tourism web sites, part 2:
expectation versus delivery of tourism web sites. University of
Waikato.
Ranganathan, C., Ganapathy, S., 2002. Key dimensions of business-to-
consumer web sites. Information and Management 36 (6), 457–465.
ARTICLE IN PRESS
S. Schmidt et al. / International Journal of Hospitality Management 27 (2008) 504–516 515
http://www.iet.tourspain.es/http://www.itu.int/newsarchive/press_releases/2003/30.htmlhttp://www.itu.int/newsarchive/press_releases/2003/30.htmlhttp://www.iet.tourspain.es/
-
8/18/2019 1-s2.0-S0278431907000722-main
13/13
Rocha, S.B., 2003. Estrate ´ gia on-line: Uma Ana ´ lise dos WebSites na
Indústria Hoteleira do Municı ´pio do Rio de Janeiro, Brasil.
Observato ´ rio EMBRATUR-FGV.
Rosen, D.E., Purinton, E., 2004. Website design: viewing the web as a
cognitive landscape. Journal of Business Research 57 (7), 787–794.
Schumacker, R.E., Lomax, R.G., 1996. A Beginner’s Guide to Structural
Equation Modeling. Lawrence Erbaum, New Jersey.
Teo, T.S.H., Pian, Y., 2003. A model for web adoption. Information andManagement 41 (4), 457–468.
Venkatraman, N., Ramanujam, V., 1987. Measurement of business
economic performance: an examination of method convergence.
Journal of Management 13 (1), 109–122.
Wan, C.-S., 2002. The web sites of international tourist hotels and tour
wholesalers in Taiwan. Tourism Management 23 (2), 155–160.
World Tourism Organization, 2003. Tourism highlights 2003. Retrieved
on 26 June 2003 from /http://www.world-tourism.orgS.
Yelkur, R., Dacosta, M.M.N., 2001. Differential pricing and segmentationon the internet: the case of hotels. Management Decision 39 (4), 252–262.
ARTICLE IN PRESS
S. Schmidt et al. / International Journal of Hospitality Management 27 (2008) 504–516 516
http://www.world-tourism.org/http://www.world-tourism.org/