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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

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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).

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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).

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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.

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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

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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.

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(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

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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


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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

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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


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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.

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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.


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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

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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


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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

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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.

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