A competitive study of two tourism destinations through the application of conjoint analysis techniques: the case of the Canary Islands

              Vol. 2 Nº 2 págs. 163-177. 2004
www.pasosonline.org
© PASOS. Revista de Turismo y Patrimonio Cultural. ISSN 1695-7121
A competitive study of two tourism destinations through the
application of conjoint analysis techniques:
the case of the Canary Islands1
Eduardo Parra López i; Mercedes Melchior Navarroii
Ángel Ramos Domíngueziii
Universidad de La Laguna (Tenerife, España)
Resumen: La aspiración de conocer y corresponder las expectativas de los consumidores, supone un continuo
objetivo en la gran mayoría de las empresas, así como un tema central de análisis y debate a lo largo y ancho de la
literatura. Existe un amplio consenso sobre la importancia que la orientación al cliente tiene para la competitividad
de las empresas actuales. Este hecho se acentúa aún más si cabe en las empresas del sector turístico. En este trabajo
tratamos de profundizar en el conocimiento de las ventajas competitivas del sector hotelero de dos destinos turísticos
a través del estudio de la utilidad que aportan a la demanda los diferentes productos ofertados. Mediante la aplica-ción
de técnicas estadísticas de análisis conjunto y de simulación hemos obtenidos un modelo de aplicación en la
toma de decisiones empresariales, y que permite reconocer no sólo el producto que, entre los ofertados, mayor valor
aporta a la demanda de cada destino turístico sino la existencia de diferencias significativas entre destinos.
Palabras clave: Orientación al cliente; Ventaja competitiva; Productos hoteleros; Destino turístico;
Análisis de conjunto
Abstract: The aspiration to know and to correspond to consumer expectations, supposes a continuous challenge
that companies must confront and has become a central issue in an extant literature. There is ample agreement about
the importance of consumer orientation for the competitiveness of companies. Businesses are faced with the need to
satisfy customers today and to develop new products for the future. These requirements are accentuated in the tour-ist
sector because they have a particular dependence on “tourist preferences”. The aim of this paper is to contribute
to this debate with the results of an analysis that seeks to deepen the knowledge of competitive advantages in the
hotel sector of two tourism destinations by studying the utility that the different products offered provides to de-mand.
By means of the application of the statistical techniques of conjoint analysis and simulation, we have obtained
a model to apply to entrepreneurial decision-making that enables us to recognise the product that, among those
supplied, most value provides to the demand of each tourism destination, as well as the observation of significant
differences between those destinations.
Keywords: Customer orientation; Competitive advantage; Hotel products; Tourism destination; Con-joint
analysis
i Profesor Titular de Escuela Universitaria. Doctor en Organización de Empresas. Diplomado en cien-cias
Empresariales y Licenciado en Ciencias Económicas y Empresariales por la Universidad de La
Laguna. Master en Comercio Internacional por la Escuela de Organización Industrial (EOI). E-mail:
eparra@ull.es
ii Profesora Titular de Escuela Universitaria del Área de Organización de Empresas del Departamento
de Economía y Dirección de Empresas de la Universidad de La Laguna. Diplomada en Ciencias Em-presariales
y Licenciada en Ciencias Económicas y Empresariales por la Universidad de La Laguna.
E-mail: mmelchio@ull.es
iii Doctor en Ciencias Económicas y Empresariales por la Universidad de La Laguna. Es profesor Titular
de Escuela Universitaria del Departamento de Economía de las Instituciones, Estadística Económica y
Econometría de la Universidad de La Laguna. E-mail: aramos@ull.es
164 A competitive study of two tourism destinations …
Introduction
Aspiring to discover and correspond to
consumer expectations is an on-going chal-lenge
faced by many present-day firms in
their search for competitiveness. This ca-pacity
to offer and increase value for the
customer is a critical factor, which is accen-tuated
even more in firms within the hotel
sector, where customer loyalty shows dy-namic
and volatile characteristics that re-quire
continuous, in-depth study of their
expectations, motivations and preferences.
Slater and Narver (19982; 19993) point
out differences between market-orientation
and customer orientation, distinguishing
between those businesses whose activities
are entirely directed towards current de-mands
(customer-led), and those whose
activities focus entirely upon the future
(market-led). In this regard, Connor (1999)4
argues that firms are always in the short-and
long-term at the same time as they
must survive in the short-term to ensure a
long-term, and that it is inappropriate to
think in terms of choice between customer
and market orientation. Both approaches
seek to provide an strategic alignment of
organizations with the external environ-ment.
The heart of much of the strategic man-agement
literature engages to strive for
competitive advantage. The essence of
strategy entails an attempt by a firm to
achieve and sustain competitive advantage
over other firms. This is why different ap-proaches
have developed around the con-cept
of competitive advantage within the
field of strategic analysis. The “Strategy
Theory” (Andrews, 1971; Ansoff, 1980, Sel-znick,
1957) is concerned with the distinc-tive
competencies in strategic processes,
particularly in their relationship with the
generation of competitive advantages and
competitiveness. From this perspective, the
competitiveness of the company will depend
on the way in which it adjusts its resources
to environmental conditions and on the
strengths and weaknesses that it shows in
connection with competition (Wernerfelt,
1984; Rumelt, 1991; Hunt, 1995). (See Fig-ure
1)
The traditional industry analysis ap-proach
points that there are two compo-nents
to distinguish in every competitive
strategy: the structure of the industry in
which the firm evolves and the position of
the enterprise within the industry (Porter
1980). The resource-based view of the firm
points to the firm’s unique resources, core
competencies, and dynamic capabilities in a
rapidly changing market as the real justifi-cations
of the differences in results in the
same activity (Hansen and Wernerfelt,
1989; Rumelt, 1991; Wernerfelt and Mont-gomery,
1988; Barney, 1991 ; Prahalad y
Hamel, 1990 ; Teece et al., 1997 ). While
resources are the source of a firm’s capa-bilities,
these are the main source of its
competitive advantage. Core Competencies
evolve over time as the firm adapts to new
circumstances and opportunities. (See Fig-ure
2).
Finally, the marketing concept says that
a firm’s purpose is to discover needs and
wants in its target markets and to satisfy
those needs more effectively and efficiently
than competitors. What establishes a firm’s
competitive advantage, and has therefore
become a critical factor for its long term
success, is the ability to serve customers’
present and future needs; it is the firm’s
awareness and fulfilment of customers’
evolving needs that nurture and validate
their ongoing relationship with the cus-tomer
(Kandampully and Duddy, 1999:51).
This is especially important in the hotel
sector, where customer loyalty shows dy-namic
and volatile characteristics, which
demands an on-going, in-depth study of
their expectations.
The adjustment between supply and
demand in the hotel sector increases in
complexity owing to the fact that some
components of what is perceived and ex-pected
by the customer as the product are
not merely one but the combination of a
variety of products, partly outside the ho-tel’s
control. The value of an accommoda-tion
service is also influenced by facilities
and attractions offered by the tourism des-tination
in which the hotel is located, which
are a part of customer expectations and
experiences. Therefore, the need arises for
a systematic approach, which includes a
group of interrelated elements where some
properties of the system are additions of an
individual nature, while others are holistic,
Eduardo Parra, Mercedes Melchior y Ángel Ramos 165
a result of the relation between the parts
(Oreja, 2000) (See Figure 3).
Figure 1. Schematic of the Resource-Advantage Theory of Competition Source: Adapted
from Hunt(1995)
Figure 2. The Relationship between the resources and capacities of the firm and competi-tive
advantage. Source: Adapted from Barney (1991).
The Hospitality sector in the Canary
Islands
With just over 2,000 km2, Tenerife is
the largest of the Canary Islands and is
internationally known as the island of
eternal spring, owing to its climate of
mild all-year-round temperatures, espe-cially
in the coastal area where the tour-ist
resorts are located. The island econ-omy
is fundamentally based on the ser-vices
sector, and tourism is considered to
be the driving force behind the economy.
The Tourism contribute of over 76.7% the
Gross Added Value (GVA) in 1996 in the
Canary Islands. There is a fixed popula-tion
of around 730,000 inhabitants, but
Tenerife receives a large number of tour-ists
every year: in the year 2000, there
were 4,730,425 visitors (see Graph 1).
Throughout its history, Tenerife has
been a destination for travellers and visi-tors,
but it was mainly in the 1960’s that
tourism began to play a significant eco-nomic
and quantitative role.
At first, tourism was located mainly in
the north of the island (Puerto de la
Cruz), but in the 1980’s the south of the
island gained ground with the develop-ment
of the necessary infrastructures (see
Graph 2).
More recently, Tenerife has been con-fronted
with increased competitiveness in
tourism products and destinations, a
Resources
● Comparative Advantage
● Parity
● Comparative Disadvantage
Market Position
● Competitive Advantage
● Parity
● Competitive Disadvantage
Financial Performance
● Superior
● Parity
● Inferior
Social Resources Social Institutions
Competitors Consumers Public Policy
Hotel Resource
Heterogeneity
Hotel Resource
Immobility
Value
Rareness
Imperfect Imitability
*History Dependent
*Causal Ambiguity
Social Complexity
Imperfect Substitutability
Sustained
Competitive
Advantage
Competences
166 A competitive study of two tourism destinations …
change in visitor expectations and habits,
along with the concentration and restruc-turing
processes to which the tourism
business sector is being subjected. In par-ticular
within the hotel industry, the need
has arisen for the analysis and awareness
of these trends, in order to adequately
anticipate and respond to them. This may
lead to an eventual reorientation of poli-cies
undertaken by both public and pri-vate
institutions in relation to tourism
development and management.
Figure 3. The Marketing Concept and his purpose to discover needs and wants in its target
markets and to satisfy those needs more effectively and efficiently than competitors in
the Hospitality Sector. Source: Own elaboration
Evolución número total de turistas alojados isla de Tenerife
0
500.000
1.000.000
1.500.000
2.000.000
2.500.000
3.000.000
3.500.000
4.000.000
4.500.000
5.000.000
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
GRAPH 1. Evolution of total number of tourists accommodated on the island of Tenerife.
Source: Cabildo Insular de Tenerife (Tenerife Island Council). Receptive Tourism Sta-tistics.
.
Marketing
Concept in the
Hospitality
Sector
Discover
*Needs and Wants
(Target market)
Adjustment
Supply-demand
* Variety of products
* External and Internal Services
•Accommodation
• Tourism destination
Part of customer
Expectations and
experiences
Competitive
Advantage
Eduardo Parra, Mercedes Melchior y Ángel Ramos 167
Evolution of the total number of accommodation places (*) per main
tourism area
-
20.000
40.000
60.000
80.000
100.000
120.000
140.000
160.000
180.000
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
North Area South Area
Total
GRAPH 2. North zone South zone Island Total. Source: Cabildo Insular de Tenerife
(Tenerife Island Council). Receptive Tourism Statistics. (*) The island is divided into 4 tour-ism
zones.
Research Methodology
This study applied a model of competi-tive
analysis for tourism destinations
and, in particular, for the hotel sector of
these destinations, developed from the
work of Oreja, 1998 and 2000; Melchior,
Ramos and Jiménez, 2000; and Melchior,
Parra and Ramos, 2000.
The research objective was to establish
a model based on techniques of multi-variant
analysis with which to simulate
the dynamic relations that occur between
supply and demand in the hotel sector.
The aim is to recognise and predict the
product that contributes most utility to
the demand of each destination analysed,
and to discover the existence of signifi-cant
differences in the competitive posi-tion
of these tourist destinations, North
zone and South zone of Tenerife. This
study has been applied to two well-differentiated
tourism destinations on the
island of Tenerife (Oreja, 1995; Melchior
and Gutiérrez, 1995; Melchior, 1998).
The research was guided by two hy-potheses:
• Hypothesis no. 1: The conjoint
analysis technique enables us to observe
the competitiveness of tourism destina-tions
by studying the fit between the
product offered and demand expectations.
• Hypothesis no. 2: The analytical
model proposed enables the utilities from
the different hotel products to be distin-guished,
and, with that, the competitive
differences between and within tourism
destinations.
Methodology
In order to reach the objective put for-ward,
we have used a group of statistical
techniques denominated “Conjoint Analy-sis”.
This methodology allows us to calcu-late
the structure of individual prefer-ences
or of a group of potential customers,
bearing in mind that the consumer con-siders
the product as a set of attributes
(Green and Srinivasan, 1978). Hence,
from the results, we can measure the
extent to which the customer is prepared
to sacrifice any of the attributes, in order
to gain more benefits from another.
This methodology is applied by follow-ing
a process that includes defining the
problem to be solved, identification of the
reference population, sample and ques-tionnaire
design, market simulation and
conclusions.
THE MODEL: The model for the ri re-sponse
for the i-th card of a tourist is:
Σ=
= β +
p
j
i jk ji r u
1
0
168 A competitive study of two tourism destinations …
Where ujk is the partial utility associ-ated
with the kji-th level of the j-th factor
in the i-th card.
The competitive analysis was per-formed
on two aggregation levels: first,
the basic units for analysing the offer
and, second, including the preferences
and utilities experienced by demand in
relation to the product received5.
COMPONENTS OF OFFER ANALYSIS:
• Accommodation and Services: This
study is centred on the hotel offer on
the island of Tenerife, the weight and
distribution of which can be observed
in Table 1. The island is statistically
divided into four tourism areas, two of
which are clearly outstanding (South
zone and North zone) and which will
be the object of our study.
• Price of the product/service: the study
of prices is based on the price scale for
restaurant services in a sample of ho-tels
in Tenerife. The data is provided
by the Cabildo Insular de Tenerife
(Tenerife Island Council) and the Min-istry
of Tourism and Transport of the
Government of the Canaries (see Table
2). Price classification is a result of the
interquartilic intervals of the series of
prices offered in Tenerife.
• External Services: The standard of-fered
by these services has been done
by applying an analysis of the princi-pal
components to the data provided
by the Ministry of Tourism and Trans-port
of the Government of the Canar-ies,
concerning the number of bars,
restaurants and cafeterias existing in
the different boroughs of Tenerife. Ta-ble
3 shows a classification of those af-fected
by this study.
• Holiday Environment: while the South
zone under study offers an almost ex-clusively
beach environment, the
North zone is not typically associated
with beach tourism, but has the at-traction
of a much more varied land-scape.
Type of accommodation Total Island (*) North zone South zone
5* 5.174 1.052 3.545
4* 40.563 12.799 27.634
3* 23.727 4.595 17.996
2* 1.911 699 357
1* 946 311 388
Total hotel places 72.321 19.456 49.920
Total non-hotel places 94.521 13.051 79.447
TABLE 1. Distribution of the hotel offer on the island of Tenerife. (*) Total 4 tourism areas.
Source: Cabildo Insular de Tenerife (Tenerife Island Council). Receptive Tourism Statistics
2001. Places referring to 01/01/2001
Hotel Category Breakfast Cost Cost Half-board Cost full board
1* - - -
2* Low Low Low
3* Low Low Low
4* High High High
5* High High High
TABLE 2. Hotel prices according to category Source: Cabildo Insular de Tenerife (Tenerife
Island Council). Receptive Tourism Statistics 2001 and own elaboration.
Eduardo Parra, Mercedes Melchior y Ángel Ramos 169
Borough
Area
No.
bares
No.
cafeterias
No.
restaurants
Factorial
score External Services
LOS REALEJOS 146 12 63 -0,07166 full
LA OROTAVA North 208 13 61 0,03823 full
PUERTO DE LA CRUZ 304 94 217 1,86372 full
ARONA 503 71 465 2,74385 full
ADEJE South 217 68 308 1,67783 full
SANTIAGO DEL TEIDE 65 13 78 -0,13999 full
TABLE 3. External services in the different boroughs of the island of Tenerife. Source:
ISTAC (2001). Chart: Own elaboration.
2001 Total island (*) North zone South zone
GERMANY 818.564 238.662 453.199
UNITED KINGDOM 1.548.065 93.668 1.496.196
SPAIN 1.026.009 478.979 343.736
ITALY 122.972 7.938 108.920
FRANCE 166.992 27.661 147.419
OTHER COUNTRIES 959.202 136.510 888.991
TOTAL 4.641.804 983.418 3.438.461
TABLE 4. Number of tourists per main nationality and tourism area. Source: Cabildo In-sular
de Tenerife (Tenerife Island Council). Receptive Tourism Statistics 2001
Nationality Maximum estima-tion
error
No. Tourists
Sept 98-Aug 99 Sample Size Months Sample
Size
December 33
Spanish ±3.81% 963.073 160 April 49
August 78
December 45
British ±3.69% 1.531.775 144 April 45
August 54
December 67
German ±3.43% 712.559 171 April 62
August 42
December 24
French ±4.49% 174.523 121 April 58
August 39
December 30
Italian ±4.51% 115.972 115 April 34
August 51
December 44
Rest ±4.8% 100.1956 86 April 27
August 15
TABLE 5. Sample of tourists interviewed (technical card)Source: Own elaboration.
.
170 A competitive study of two tourism destinations …
COMPONENTS OF DEMAND ANALY-SIS:
The reference population considered
for this study is composed of tourists vis-iting
the island of Tenerife. Table 4 shows
the nationalities and areas studied.
Sample Design: the data collection
process was undertaken with a sample of
797 tourists interviewed on their depar-ture
from the island, at the departure
terminal of the Tenerife South Interna-tional
Airport (see Table 5).
The information collected through the
survey included personal characteristics
of the tourists interviewed and the prod-uct
consumed, in addition to an ordered
preference structure of the different op-tions
presented, ranging from 1 for the
preferred option to 9 for the least pre-ferred.
The option design provided was
the result of an orthogonal design based
on the four factors considered as most
determinant of the tourism product in
Tenerife (see Table 6), with three levels
for each.
These four factors are the result of ap-plying
a analysis of principal components
to the 24 group characteristics considered
by the Tenerife Island Council as repre-sentative
of the products and services
offered to tourists visiting the island
(Jiménez and Ramos, 1995).
Variable COMP1 COMP2 COMP3 COMP4 COMP5 Determining
Factor Eigenvalues % va-riance
QUALITY ACCOMMODA-TION
0.79 0.06 0.15 0.08 0.10 3.607 15.029
ACCOMMODATION
TREATMENT 0.75 0.31 0.06 0.05 0.02 3.607 15.029
FOOD QUALITY 0.69 -0.03 0.15 0.19 0.13 Accommodation
and services 3.607 15.029
SERVICE ATTENTION 0.66 0.39 0.09 0.10 0.01 3.607 15.029
SATISFACTION/PRICES 0.63 0.20 0.38 0.13 0.15 3.607 15.029
OVERALL 0.61 0.34 0.13 0.29 0.15 3.607 15.029
SAFETY 0.40 0.67 0.12 -0.04 -0.05 2.992 12.466
LANDSCAPE -0.02 0.65 0.05 0.21 0.08 2.992 12.466
TOWN PLANNING 0.15 0.64 0.12 0.41 0.10 Holiday envi-ronment
2.992 12.466
TRANQUILLITY 0.34 0.63 0.11 -0.12 -0.08 2.992 12.466
PUBLIC HYGIENE 0.20 0.61 0.13 0.10 -0.09 2.992 12.466
BEACH 0.04 0.43 0.18 0.36 0.17 2.992 12.466
INSTALLATION PRICES 0.05 0.23 0.76 0.17 0.07 2.868 11.948
BAR PRICES 0.02 0.12 0.76 0.25 0.06 Price 2.868 11.948
MEAL PRICES 0.27 0.03 0.72 0.14 0.08 Product 2.868 11.948
ACCOMMODATION PRI-CES
0.40 0.07 0.66 0.07 0.12 service 2.868 11.948
QUALITY TRANSPORT 0.10 0.32 0.33 0.29 0.05 2.868 11.948
NUMBER DISCOS 0.12 0.01 0.16 0.83 0.02 2.589 10.787
NUMBER BARS 0.15 0.13 0.14 0.81 0.07 External Servi-ces
2.589 10.787
QUALITY BARS 0.17 0.25 0.36 0.59 0.02 2.589 10.787
QUALITY INSTALLATIONS 0.24 0.31 0.37 0.43 0.07 2.589 10.787
CLIMATE 0.11 0.08 0.11 0.07 0.90 2.572 10.716
SUN 0.11 -0.08 0.07 0.05 0.88 Climatic condi-tions
2.572 10.716
TEMPERATURE 0.11 0.03 0.09 0.05 0.90 2.572 10.716
TABLE 6. Factors that determine the tourism product of Tenerife Source: Own elaboration
Eduardo Parra, Mercedes Melchior y Ángel Ramos 171
Kozak and Rimmington (1998) pro-posed
a model grouping the most relevant
characteristics of a tourism destination in
the following components:
Attractions: environment, landscape,
natural resources, climate, history, cul-ture.
• Facilities and services: accommoda-tion,
restaurants and bars, transport,
complementary leisure, commerce, etc.
• Infrastructure: water, energy, commu-nication
networks, health, safety,
road, airport and maritime infrastruc-ture,
etc.
• Hospitality: courtesy, willingness to
lend aid and assistance, attending
complaints, etc.
• Costs: quality/price ratio for accommo-dation,
restaurants, transports, shops.
In its survey, the Tenerife Island
Council identifies the components men-tioned
above through the twenty four
variables shown in the first column in
Table 6.
We should bear in mind that the rela-tion
between the variable and the differ-ent
factors and their levels is explained
by the following models (Ramos 1999):
Table 7.
Results
Table 8 shows the estimations of the
partial utilities of each type of the four
factors considered most determinant.
Measuring the level of the goodness-of-fit
reached with the estimated model and
the confidence in the results obtained was
done with Pearson’s r coefficients and
Kendall’s τ.6 In both cases, significantly
high correlation levels are reached be-tween
the data observed and the data
derived from the estimated model. This
can be understood as a high level of confi-dence
in the inferences made from these
models (see Table 9).
If we consider the factors as a whole,
both the models obtained point to “ac-commodation
and services” as being the
most important for both tourism destina-tions,
with a level of 34.84% and 37.75%,
respectively, followed in second place by
the factor “holiday environment”, with
29.97% and 27.10%. In relation to the last
two factors (“Price product/service” and
“external services”), there are differences
between both destinations (see Table 8
Importance box).
As for each of the factors and their
types, the analysis produces the fol-lowing
results (see Table 8 Utilities
box):
Holiday Environment: demand in the
South zone shows a higher estimated
preference for an exclusively beaching
environment, as opposed to visitors to the
North zone, who opt for a holiday envi-ronment
of countryside and beach.
O HOLIDAY ENVIRONMENT
DISCRETE FACTOR
o Accommodation and services Positive linear factor
o Price of the product/service Negative linear factor
o External services Positive linear factor
TABLE 7. Explanatory models of the relation between the different factors and their levels
and the response variable. Source: Own elaboration.
172 A competitive study of two tourism destinations …
Factor Level Utility Importance
SOUTH NORTH SOUTH NORTH
Holiday environment
Beach
Countryside and
Beach
Countryside
0.5869
0.3023
-0.8893
0.0728
0.3474
- 0.4202 29.67% 27.10 %
1 Star
3 Stars
5 Stars
0.6459
1.9377
3.2295
0.7300
2.1901
3.6502
Accommodation and
Services
Coefficient 0.6459 0.7300
34.84% 37.75 %
Low
Medium
High
0.2630
0.5260
0.7890
- 0.0399
- 0.0798
Price Product/Service - 0.1197
Coefficient 0.2630 - 0.0399
17.64% 17.13 %
Minimum
Regular
Full
0.2442
0.4884
0.7326
0.2770
0.5540
External Services 0.8310
Coefficient 0.2442 0.2770
17.55% 17.84 %
Constant 2.0468 2.3357
TABLE 8. Estimations of the partial utilities of each of the types of each of the four factors
considered to be most determinant. Source: Ramos (1999).
South Zone North Zone
Coefficient Significance Coefficient Significance
Pearson: 0.983 0.0000 Pearson: 0.975 0.0000
Kendall: 0.833 0.0009 Kendall: 0.833 0.0009
TABLE 9. Correlation between the data observed and the data derived from the estimated
model Source: Own elaboration.
Accommodation and services: this fac-tor
shows a positive relation with the
utility level reached by its types, so that
the higher the category of accommodation
and services, the higher the resulting
utility. This increase in utility when pass-ing
from a lower to a higher level is ob-served
to be more pronounced in the
North zone.
Price of Product/Service: demand in
the South zone reveals a positive relation
between the price and utility variables
achieved, in that the tourist is apparently
willing to pay more for a product that
provides better features. Contrary to this,
visitors to the North zone are not appar-ently
prepared to pay more and show a
preference for lower prices.
External Services: this last factor
shows a positive relation with the de-pendent
variable utility in both tourist
zones, so that there seems to be a prefer-ence
for a higher standard of external
services offered.
CONTRAST OF THE RESULTS
At this stage of the research, we de-cided
to discover the level of significance
of the estimations of the partial utilities
corresponding to each attribute level.
With this aim in mind, a variance analy-sis
was performed that compared the four
tourist areas found in Tenerife: Puerto de
la Cruz, Las Américas-Los Cristianos,
Fañabé-Puerto Santiago-Los Gigantes
and Costa del Silencio-Ten Bel. The first
destination is in the north, while the
other three are located in the south.
All the variation sources were signifi-cant,
while in zone 3 “Fañabé-Puerto
Santiago-Los Gigantes” and “Costa del
Silencio-Ten Bel”, both the price and the
external services do not appear to have a
significant influence on the variation of
the preferences of tourists staying in that
area.
In other words, these two factors ap-pear
to have much less influence on the
preference structure of tourists staying in
the two areas mentioned.
Eduardo Parra, Mercedes Melchior y Ángel Ramos 173
.
Zone Source
Sum of type
III squared
Degrees of
freedom
Quadratic
average Snedecor’s F Significance
Corrected model 2302.75 8 287.84 52.54 0.00
Intersection 47200.01 1 47200.01 8616.19 0.00
Price 84.27 2 42.14 7.69 0.00
Accommodation 1919.27 2 959.63 175.18 0.00
Surroundings 215.83 2 107.91 19.70 0.00
Ext. Services. 83.39 2 41.69 7.61 0.00
Error 10304.23 1881 5.48
Total 59807.00 1890
1
Corrected total 12606.99 1889
Corrected model 4551.19 8 568.90 104.37 0.00
Intersection 92365.03 1 92365.03 16944.95 0.00
Price 71.65 2 35.82 6.57 0.00
Accommodation 3308.19 2 1654.09 303.45 0.00
Surroundings 957.28 2 478.64 87.81 0.00
Ext. Services. 214.08 2 107.04 19.64 0.00
Error 20113.78 3690 5.45
Total 117030.00 3699
2
Corrected total 24664.97 3698
Corrected model 1160.18 8 145.02 27.85 0.00
Intersection 19115.00 1 19115.00 3670.71 0.00
Price 8.80 2 4.40 0.85 0.43
Accommodation 975.85 2 487.92 93.70 0.00
Surroundings 168.87 2 84.43 16.21 0.00
Ext. Services. 6.66 2 3.33 0.64 0.53
Error 3936.82 756 5.21
Total 24212.00 765
3
Corrected total 5097.00 764
Corrected model 474.66 8 59.33 10.91 0.00
Intersection 9040.04 1 9040.04 1661.89 0.00
Price 3.17 2 1.59 0.29 0.75
Accommodation 358.11 2 179.05 32.92 0.00
Surroundings 104.77 2 52.39 9.63 0.00
Ext. Services. 8.61 2 4.30 0.79 0.45
Error 1909.30 351 5.44
Total 11424.00 360
4
Corrected total 2383.96 359
Table 10.Level of significance of the estimations of the partial utilities corresponding to
each attribute level. Source: Own elaboration.
SIMULATION: Below are the profiles
that we have simulated by way of exam-ple
for each of the zones studied (see Ta-ble
11):
Thus, in the case of the North zone,
the estimated preference level for this
type of offer is 0.3474+2.9201-
0.1197+0.5540+2.3757=6.0775, which
represents an extremely high preference
level, especially if compared with the
range of scores where the highest value is
7.1643 and the lowest 2.8028. Nonethe-less,
owing to the fact that tourists stay-ing
in this zone showed a higher prefer-ence
for lower prices, this simulation was
174 A competitive study of two tourism destinations …
performed with a resulting utility level of
6.1573.
The simulation corresponding to the
conditions of the South zone (see Table
10) shows an estimated preference level
for this type of offer of
0.5869+2.5836+0.7890+0.7326+2.0468=6.
7389, which is extremely high, in a scor-ing
range where the highest value is
7.3848 and the lowest 2.799. Satisfaction
with the offer in this zone is higher than
that registered in the North zone.
CONTRAST OF THE FULFILMENT OF
TOURIST EXPECTATIONS ACCORD-ING
TO ACCOMMODATION ZONE
We consider comparing the average
preference scoring of each group of tour-ists,
staying in the north and south of the
island, with the stimuli provided by the
current offer in each of these zones. A
higher preference would indicate greater
fulfilment of customer expectations, since
customers show a higher degree of prefer-ence
and, therefore, satisfaction.
1 1 2
0 1 2
H :
H :
μ ≠ μ
μ = μ
A priori, and bearing in mind the sam-pling
data, tourists staying in the south
zone of Tenerife reveal a higher average
preference level towards the stimulus
provided by the current offer in their area
than do tourists staying in the north.
Following is a table of results of the
Variance Analysis. (See Table 13)
We can confirm the existence of sig-nificant
differences in the average prefer-ence
levels of the two tourist groups to-wards
the respective offer profiles. There-fore,
we may conclude that the south zone
meets customer expectations to a greater
extent than the north zone, since prefer-ence
levels show this to be the case.
SIMULATED PROFILES
NORTH ZONE SOUTH ZONE
Environment of countryside and
beach Beach environment
Hotel 4* Hotel 4*
High prices High prices
Regular external services Full external services
TABLE 11. Simulations for each of the zones studies. Source: Own elaboration.
Accommodation
Zone Average Stand. Deviation N (*)
North 5.69 1.86 210
South 6.20 2.03 587
Total 6.07 2.00 797
Table 12. The average preference scoring of each group of tourists staying in the north and
south of the island. *N= Number of tourist interviewed. Source: Own elaboration
Source Sum of squared
Degree of
freedom Quadratic average Snedecor’s F Sign.
Corrected model 40.22 1 40.22 10.18 0.00
Intersection 21863.04 1 21863.04 5534.55 0.00
ZONE 40.22 1 40.22 10.18 0.00
Error 3140.47 795 3.95
Total 32500.08 797
Corrected Total 3180.69 796
Table 13.Results of the Variance Analysis. Source: Own elaboration
Eduardo Parra, Mercedes Melchior y Ángel Ramos 175
Conclusions and implications
The empirical evidence available for
studying the breach that exists between a
tourism destination’s supply and demand
and their repercussions on the destina-tion’s
competitiveness are somewhat in-conclusive,
since most of the studies un-dertaken
are centred on partial theoreti-cal
models or experiments at specific
tourism destinations. This article aims to
analyse the effects of the definition of the
tourist product offered by two different
tourism destinations on their level of
competitiveness as destinations. To this
end, a theoretical framework is defined,
which enables us to create an empirical
model of tourist consumer behaviour at
both destinations, by crossing tourist
preferences with the product/service
characteristics offered by the destination.
The demand at both destinations as-sessed
is evaluated by the level of utility
reached by the tourist through the tour-ism
product/service consumption received
or likely to be received, by measuring the
product through “accommodation and
services”, “holiday environment”, “price”
and “external services”. The preference
structure of tourists visiting each of the
destinations considered is calculated by a
conjoint methodology, which facilitates
the decomposition of the tourism destina-tion’s
total utility into partial utilities of
each attribute and the level of the attrib-utes
that define destination profile.
The sign and quantity of the parame-ters
calculated in this model enable us to
reach another series of conclusions about
the preferred characteristics of the prod-uct
consumed by tourists, which will sub-sequently
influence the competitiveness
of the destination. Specifically, the exis-tence
of a positive effect of the destina-tion’s
accommodation, price and comple-mentary
service level category is corrobo-rated
over the utility of the tourist lodg-ing
in the South zone destination, while
these same parameters reveal similarities
regarding accommodation and services,
but a negative effect where price is con-cerned.
Nevertheless, given the level of
importance attributed to price for estab-lishing
the utility in both destinations,
here is justification against using a pric-ing
policy as a sole competitive strategy
for both the destinations analysed.
From the results obtained, it can be
concluded that these are two well differ-entiated
destinations and that they are
perceived as such by the demand. The
main difference lies in the factors con-cerning
the holiday environment per-ceived
as different (beach in the South
zone, beach-countryside in the North
zone) and the price, with a preference for
low prices in the North zone, as opposed
to a willingness to pay higher prices in
the South zone. This latter result has
negative implications for the competitive-ness
of the North zone, as opposed to the
South of the island, since, though in the
first case there is a higher incremental
utility of the product as the hotel category
increases, the demand for this destination
is not willing to pay for it.
This study has aimed to provide an
initial approach to the development of a
methodology that will facilitate a conjoint
analysis for studying the complex ad-justment
between hotel offer and demand
in a tourism destination, with a view to a
more extensive, in-depth future study
with the inclusion of other variables,
which would provide more knowledge
about them, thereby facilitating a basis
for designing a competitive hotel product
at a specific destination.
Bibliography
Andrews K.R.
1971 The Concept of Corporate Strategy.
Homewood. IL Richard D. Irwin.
Ansoff H. I
1980 “Strategic Issue Management”.
Strategic Management Journal, 1:
131-148.
Cabildo Insular de Tenerife.
s/f Estadísticas de Turismo receptivo:
Santa Cruz de Tenerife.
Consejería de Turismo y Transportes,
Gobierno de Canarias
1998 "Infraestructura Turística".
http://www.gobcan.es/turismo/dgoit/est
adisticas/bcr/1998/bcrtf98.html
176 A competitive study of two tourism destinations …
Green P. E. and Srinivasan V.
1978 “Conjoint Analysis in Consumer
Research: Issue and Outlook”. Journal
Consumer Research, 5.
Hansen, G. and Wernerfelt. B.
1989 “Determinants of Firm Performance:
the Relative Importance of Economic
and Organizational Factors”. Strategic
Management Journal, 10: 399-411.
Hunt K.A.
1995 “The Relationships Between Chan-nel
Conflict and Information Process-ing”,
en Journal of Retailing, 71(4):
417-436.
Instituto Canario de Estadística (ISTAC)
1999 Anuario estadístico de Canarias.
(http://www.istac.rcanaria.es)
Jiménez, V. y Ramos, A.
1995 “Definición de los Atributos Deter-minantes
del Producto Turístico de
Tenerife”. V Congreso Nacional de
Economía. Economía de los Servicios.
Las Palmas de Gran Canaria.
Kandampully, J. and Duddy, R.
1999 “Relationship Marketing: A Concept
Beyond The Primary Relationship”.
Marketing Intelligence and Planning,
17 (7): 315-323
Melchior, M.
1998 “La Actividad turística en Cana-rias”.
El Turismo en Canarias, coord.
M. Melchior. Colección Investigación
Empresarial, Fundación FYDE-CajaCanarias.
Melchior, M. y A.T. Gutiérrez
1995 “Adecuación estratégica de la explo-tación
hotelera al cambio del entorno”.
V Congreso Nacional de Economía.
Economía del Turismo 6, Ilustre Cole-gio
de Economistas de Las Palmas. Pp.
259-271.
Melchior, M.; A. Ramos; y V. Jiménez
2000 “La edad como factor contextual en
el diseño de estructuras organizativas
hoteleras”. Turismo 1999. Pp. 371-395.
II Congreso Universidad y Empresa.
Tirant Lo Blanch. Valencia.
Melchior, M; E. Parra; y A. Ramos
2000 “Análisis del impacto de factores
organizativos en las configuraciones
empresariales”. X Congreso Nacional
de ACEDE, Oviedo. Septiembre.
Melchior, M; E. Parra; y A. Ramos
2000 “Analysis of the Impact of Organisa-tional
Factors in Managerial Hospital-ity
Configurations”, Tourism and Hos-pitality
Research: The Surrey Quar-terly
Review, 4(2) December: 130-142
Oreja, J.R.
1995 “Estrategias de fidelización en mer-cados
turísticos maduros”. V Congreso
Nacional de Economía. Tomo 6, Eco-nomía
del Turismo. Ilustre Colegio de
Economistas de Las Palmas, CIES. Pp.
293-106.
Oreja, J.R.
1998 “Análisis estratégico de la empresa
hotelera en Canarias”. El Turismo en
Canarias. Coord. M. Melchior. Colec-ción
Investigación Empresarial, Fun-dación
FYDE-CajaCanarias.
Oreja, J.R.
2000 “Revitalización de destinos turísti-cos
maduros”. Turismo 1999. Pp. 199-
232. II Congreso Universidad y Em-presa.
Tirant Lo Blanch. Valencia.
Parra López E.
2002 Determinantes estratégicos para la
consecución de ventajas competitivas
en el canal de distribución de servicios
turísticos. Tesis Doctoral. Pendiente
de publicación.
Porter M.E.
1985 Competitive Advantage: Creating
and Sustaining Superior Performance.
New York. Free Press.
Ramos, A.
1999 Análisis de las Preferencias del Tu-rista
Mediante Análisis Conjunto: El
Caso de Tenerife. Tesis Doctoral.
Rumelt, R.
1991 “How Much Does Industry Matter?”
Strategic Management Journal, 12:
167-185.
Selznick P.
1957 Leadership in Administration: A
Sociological Perspective. New York:
Harper & Row.
Wernerfelt, B. and C. A. Montgomery
1988 “Tobin's q and the importance of
focus in firm performance”. American
Economic Review, 78 (1): 246-50.
NOTAS
1 An earlier version of this paper was pre-sented
at the “I International Symposium of
Tourism” and “VI National Conference of
Spanish Scientists in Tourism”. Ceuta
Eduardo Parra, Mercedes Melchior y Ángel Ramos 177
(Spain) 2001. We would like to thank Tom
Baum and Alison Morrison for their very
helpful comments and suggestions. The
FYDE-CajaCanarias Foundation, in collabo-ration
with the Directorate General for Eco-nomic
Promotion of the Government of the
Canaries, on the sixth occasion of the FYDE-CajaCanarias-
Regional Ministry of the
Economy, the Treasury and Commerce
Awards, granted this paper the prize for
Business Research and the Publication of
Business Issues for 2001.
2 Slater, S.F. and J.C. Narver (1998): Cos-tumer-
led and market-oriented: Let’s not
confuse the two. Strategic Management
Journal, 19: 1001-1006.
3 Slater, S.F. and J.C. Narver (1999): Mar-ket-
oriented is more than being customer-led.
Strategic Management Journal, 20:
1165-1168.
4 Connor, T. (1999): Costumer-led and mar-ket-
oriented: a matter of balance. Strategic
Management Journal, 20: 1157-1163.
5 The term “card” refers to the format chosen,
so as to present the tourists interviewed with the
various alternatives of products for them to then
place in order of preference. This is as follows:
since the method chosen for this stage was the
full profile, the card contains a theoretical alter-native
to the product chosen by the interviewee.
Conjoint analysis methodology is a decomposi-tional
method, and, unlike other econometric
models, is performed on an individual scale. In
this way, the number of models obtained to
explain the structure of preferences is the same
as the number of tourists interviewed. Neverthe-less,
through a process of calculating the aver-age
partial utilities or coefficients of each prod-uct
attribute type, it is possible to pass from an
individual to a group scale, which is less useful
and has less value, since it is an average.
6 The ordinal nature of the measuring scale of
the model-dependent variable, the tourist’s
preference level, obliges us to measure the
goodness-of-fit of the actual model with Kend-all’s
τ coefficient, since this coefficient meas-ures
the concordance between the preferences
expressed by the tourists interviewed and those
predicted by the model.
Pearson's r is always between -1 and +1,
where -1 means a perfect negative, +1 a
perfect positive relationship and 0 means the
perfect absence of a relationship. Pearson's r
is symmetric. The correlation between x and
y is the same as the correlation between y
and x. Pearson's r is also referred to as the
"bivariate correlation coefficient" or the
"zero-order correlation coefficient. Word of
caution: The correlation coefficient assumes
that the relationship is linear.
Recibido: 15 de abril de 2004
Aceptado: 20 de mayo de 2004