Visitors’ Behavior in Heritage Cities:
The Case of Girona
NURIA GALÍ ESPELT AND JOSÉ ANTONIO DONAIRE BENITO
This article presents the results of the study of the behavior
of visitors in the monumental city of Girona, Spain. The focus
of this study has been the classification of clusters of visitors
who show the same behavior. We wanted to define the visitors’
hierarchical conglomerates (those internally homogeneous
and externally different groups) that will help to appreciate
the subtleties in the apparent uniformity of the approach taken
to visiting heritage sites. The groups of visitors will show
specific needs, ways of looking, and behaviors.
Keywords: monumental cities; cultural tourists; visitors’
behavior; cluster analyses
Studies of the behavior of cultural tourists demonstrate
that there are various categories of visitors. The most
obvious distinction differentiates two subcategories depending on whether the motivation is primary or secondary.
Ashwoth and Turnbridge (1990), for example, identified two
types of cultural tourist. The first is “intentional,” the tourist
attracted by the variety of heritage sites in a particular
destination; and the second is “incidental,” the tourist whose
primary motivation is not cultural. According to Ashworth
and Turnbridge, business tourists are an example of this
second type.
Greg Richards (1996) distinguished between the “specific”
cultural tourist, a habitual consumer of culture, and the “general” cultural tourist, only an occasional consumer. Santana
(2003) also made this double distinction: he described, on one
hand, the “real cultural tourist” as someone who has a genuine
interest in culture (to know, marvel at the whole, and delight in
the details), and, on the other hand, “leisure consumers of cultural heritage,” or those for whom culture is not the principal
motivation but rather a complement, a plus.
Antón (1993), using the theory of the intelligence unit,
incorporated a third category and wrote of three major types:
motivated tourists, inspired tourists, and attracted tourists.
The first one chooses a destination according to the cultural
opportunities there. The second type chooses a destination
in recognition of its international reputation as a leading
cultural site, with the intention of visiting it and not returning. The third type is not primarily motivated by culture
but, at any given moment, may feel attracted to visiting a
cultural site.
Empirical studies, based commonly on factorial analysis
and hierarchical cluster analysis, identify a larger number
of categories. Cohen (1972) was one of the first sociologists
to propose a classification based on the diversity of motivations. The four types identified (the common tourist, the
explorer, the individual mass tourist, and the grouporganized mass tourist) have served as a basis for studies
that have followed it.
Santana (2003) differentiated five possible subgroups:
(1) those nostalgic for culture and life forms, (2) those who are
moved by the desire to temporarily form part of the local community, (3) those who want to learn more about the past and
present of a place, (4) those who want to avoid mixing with
other tourists, and (5) those who believe that the places visited
are the antithesis of the city’s rhythm of life. Wickens (2002),
in a qualitative study from a sample of 86 British tourists in
Chalkidiki, Greece, identified five subcategories of tourists:
the Cultural Heritage, the Raver, the Heliolatrous, the Shirley
Valentine, and the Lord Byron (the reproduction of the romantic model).
Although not specifically about cultural tourism, one of the
studies that we found most interesting from a methodological
point of view is by Ryan and Glendon (1998). The authors
established a classification from a factorial analysis and a
matrix of correlations of the motivations that make tourists go
on holiday. Given 14 items (concerning the main motivation)
on a Likert-type scale with which the visitor has shown his
or her degree of agreement or disagreement, they succeed in
establishing a classification of four large categories of tourists:
(1) those who look for rest; (2) the social ones, whose motivation is to be in contact with people; (3) the intellectual tourists,
who are interested in the discovery factor; and (4) the total
tourists, who look for a combination of the first three factors.
There does not seem to be any relation among the different empirical categories of cultural tourists. It could be said
that each destination generates a specific typology of cultural tourist based on the specific characteristics of the place.
Notwithstanding, in all the classifications, we detect a recurring group of “romantic” visitors. They are the tourists or
“voyagers” whose form of travel maintains the characteristics and differential traits of the romantic voyager of the
19th century: individualism, a taste for rural life, an interest
in history and ancient culture, and so on.
Dr. Nuria Galí Espelt is an associate professor in the School of
Tourism at the University of Girona, Girona, Spain. Dr. José Antonio
Donaire Benito is a lecturer of geography in the School of Tourism
and in the Department of Geography at the University of Girona,
Girona, Spain. This project was financially supported by the City of
Girona and the University of Girona.
Journal of Travel Research, Vol. 44, May 2006, 442-448
DOI: 10.1177/0047287505282956
© 2006 Sage Publications
JOURNAL OF TRAVEL RESEARCH
Neither is there any consensus when it comes to defining
the factors that explain the categories. Once again, the unique
characteristics of the destinations determine specific differentiating factors; in addition, the methodological differences or
the sources (especially the questionnaires) certainly determine
some of the results. Thus, Venancio Bote (1998) distinguished
among three necessary criteria to establish types of cultural
tourists: the duration of the stay, the visitor’s age, and the visitor’s place of origin. Wickens (2002) considered that the difference among each group is determined by the motivation at
the moment of choosing the holiday, the type of activity, and
the prevailing perception of the destination.
A fairly precise study was carried out by Greg Richards
(2002) from a sample of 6,000 visitors to different cultural
attractions. Tourists were questioned about the moment
they decided to visit these particular sites. They had to
choose between three possible answers: (1) while in their
place of origin (46.5%) (2) while on holiday (23.7%), (3)
and at the destination (30%). This study also collected
information highlighting differences concerning their
motivation, the characteristics of their journey, the information they used and aspects of their socioeconomic conditions items were combined using a factorial analysis. The
results obtained by Richards indicate a close relationship
among the tourists’ demographic origins, their sociodemographic characteristics, their means of travel, the moment
of making their decisions, and their motivation. In a way,
Richards’s results reveal the weight of social variables in
the behavior and impressions of the visitors, more than
their individuality.
The importance of sociodemographic characteristics in
defining the clusters has been pointed out by some authors,
such as Formica and Uysal (1998), who mentioned three variables in their study of the Spoleto Festival (age, income, and
marital status), or Master and Prideaux (2000), who emphasized
the relevance of age, gender, and occupation, as well as that of
previous experience.
Some authors like Bieger and Laesser (2002) have
demonstrated that, in the definition of the clusters, sociodemographic factors (age, gender, income, and occupation) are
combined with factors related to the characteristics of the
trip (destination, length of the trip, number of people in the
group, type of trip, and so on). Kim (1998) concluded that
the type of cultural visitors can be established by combining
four subjective factors: gender, the degree of individualism
or collectivism, geographical origin, and incertitude (the
degree to which society and different cultures develop ways
to avoid insecurity). Ryan (2000) has also analyzed the
groups that are formed around interest in the aboriginal culture in Australia’s Northern Territory. The results demonstrate that sociodemographic factors like age, gender, origin,
and occupation are very relevant, but that of equal relevance
are related aspects connected with the characteristics of the
trip, such as the length and the use of tour operators. This
relevance of general factors of the trip and the individual
characteristics of the tourists is especially evident in the
study of the interests of American tourists in heritage by
Kerstetter, Confer, and Graeffe (2001).
Table 1 provides a summary of the most relevant factors
in eight studies of the creation of clusters of cultural tourists.
It is clear that there is a great diversity of factors that depend
on the conditions of the study and of the sources and methodology used. In general, the weight of sociodemographic
443
TABLE 1
FACTORS THAT DETERMINE THE CREATION
OF CLUSTERS OF CULTURAL TOURISTS
1a
2
3
4
5
6
X
X
X
X
X
X
X
X
X
X
X
7
8
Sociodemographics
Age
Gender
Geographic origin
Income
Occupation
Educational level
Marital status
X
X
X
X
X
X
X
X
X
X
X
Characteristics of the Visit
Information
Previous visits
Duration
Moment of the decision
Activities
Individual—group
Psychological elements
Motivation
Perception of the community
Security—insecurity
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
a. 1: Kim (1998); 2: Formica and Uysal (1998); 3: Bote (1998);
4: Master and Prideaux (2000); 5: Ryan (2000); 6: Kerstetter,
Confer, and Graefe (2001); 7. Wickens (2002); and 8. Richards
(2002).
variables such as age, gender, occupation. or origin of the
visitors is important. In short, we can identify three groups of
factors: the social and demographic conditions of the visitors,
characteristics of the visit, and psychological elements of the
tourist. Dolnicar (2004) has proposed a synthetic methodology, which attempts to integrate the different proposals differentiating the a priori factors from the a posteriori ones.
This article attempts to contribute to this debate. The principal objective of the study is to identify the clusters of visitors to the Old Quarter of Girona that demonstrate unique
behavior. Until now, the majority of studies of clusters of cultural tourists have been based only on survey results. This
method poses two main problems: the difference between
expressed opinion and real opinion, and the lack of detail in
the responses. Therefore, this article proposes a definition of
the clusters of visitors based on the effective behavior of the
visitors to the Old Quarter of Girona. From a methodological
perspective, that implies combining traditional questionnaires
with the direct observation method.
With such a combination of data from questionnaires and
direct observation, we will try to confirm the following
hypotheses. First of all, despite the differences between the
clusters of visitors, there is a series of universal “game rules”
that groups of tourists to the city follow. Secondly, we will
attempt to demonstrate the existence of various groups or
clusters of visitors with their own ways of behaving in the
city center. These groupings result from the tension between
individual experience and collective ritual. Finally, we believe
that the factors that explain the specific ways of “consuming”
the monumental center of the city are more related to the
characteristics of the visit (degree of information, number of
444
MAY 2006
traveling companions, and guided visit) than to conventional
sociodemographic variables.
METHODOLOGY
The setting for the study is the Old Quarter of the city of
Girona. Girona is a small city (approximately 100,000 inhabitants), located 90 kilometers north of Barcelona, 30 km from
the Costa Brava, and 60 km south of France. It is notable for
its historical-monumental value, because it brings together, in
the small perimeter of its old medieval city walls, the weight
of more than 2,000 years of history and a rich cultural and
artistic heritage, which includes the Cathedral of Santa Maria,
the Romanic Monastery of Saint Peter, the old Jewish Quarter,
and the misnamed Arabian Baths. In recent decades, the city
has become an important center for cultural tourism. Thanks
to its specific characteristics, Girona is considered an archetypal city of the places representing European culture in our
country, Spain, which is why we have chosen it as the setting
for our study.
In addition to the survey, the principal method was direct
observation of visitors’ behavior. That is, we observed the
behavior of visitors who go into the town’s old quarter and
gathered basic information from their visits: the visited nodes
(elements of interest), the length of stay, the time taken for
the visit, the time taken for the walk, the edges walked (segments of street in between intersections), the total distance
walked, and so on.
Observations of the visitors have been carried out, above
all, in closed spaces, such as museums, where technical means
(security cameras and security staff) allow for that observation
and for the analysis of their behavior. Most of these studies
have focused on specific aspects of the space, especially the
actual itinerary of the visitors, their behavior, and their movement through the rooms.
One example is the study carried out by Carme Prats
(1989) of the itinerant exhibition The Ecology, which was
shown in different places in Catalonia, a region of Spain.
In her study, the impact of the exhibition on the public was
analyzed from the opinions they expressed, and their behavior during the visit was analyzed from direct observation.
Also very interesting is the study carried out by Alcalde
and Rueda (1999) about visitors’ behavior in local and
regional museums in Catalonia. Alcalde and Rueda noted
that the time devoted to visiting permanent shows in such
museums is very short. In fact, in some museums it is
around 20 minutes. The authors also stated that there is no
direct correlation between the length of the visit and the
dimensions of the museum (its size).
Along the same lines was the study done by Mikel
Asensio and Elena Pol (1994) of the exhibition North American
Indians at the Milwaukee Public Museum, Wisconsin. The
authors found that most of the visitors followed the main
itinerary in a lineal way, dedicating little time to and showing little interest in the exhibition. They also noted that visitors showed almost no interest in the side rooms. And,
finally, they found that some spaces of the exhibition had
almost no attraction whatsoever for visitors (one of the
rooms, for instance, although passed by 100% of the visitors, was visited by only 24% of them). Another study, by
Asensio, Garcia, and Pol, was carried out in 1993 at the
exhibition Los bronces romanos en España at the Velázquez
Palace. In it, a comparison was made between results obtained
by direct observation and those obtained from the questionnaires filled in by interviewers. The most interesting result
refers to the actual time spent on the visit: 53% of the visitors interviewed said they had spent between one half hour
and one hour in the exhibition, but observations proved that
the actual time was fewer than 30 minutes.
An interesting point raised by Asensio, Pol, and Gomis
(2001) is in their study of the public in the Maritime Museum
of Barcelona. They concluded that there are stable categories
that segment the public. This allows them, for example, to
draw seven models of itineraries corresponding to seven ways
of visiting the exhibition (which vary between extreme simplicity and relative complexity). One of the most attractive
methodological proposals is the relationship between the time
of the visit and its percentage for each area of the exhibition,
which helps to define four quadrants.
The sample in our study was established from a prospective number of visitors based on several sources: the Tourism
Information Office, qualified observations, and tickets from
paid exhibitions in closed spaces, among others. All of these
sources have allowed us to draw from a sample of 532 individuals. With an error of margin of 4%, the level of trust is
95.5% (the average and two sigma) and the maximum indetermination ( p = q = .5).
The sample was randomized and stratified by months
and entrance points. The percentage of registers for each
month of the year was obtained from the above mentioned
sources (Tourism Information Office, museums, paid exhibition spaces, and booking offices, among others), with two
intense periods (spring and summer) and two quieter periods
(autumn and winter). The effect of seasons is more apparent
in Girona than in other heritage towns, due to the fact that a
significant percentage of visitors come from the coast, especially in the warm months. The proportion of entrance points
(the access bridges to the Old Quarter) was established based
on a prospective study.
The information was gathered from a combination of
direct observation and a questionnaire. For the direct observation, the Old Quarter has been modeled in a graph made up
of edges and nodes. The 158 edges are the sections of street
between one intersection and another. For each edge, information about the time of entrance, the time of exit (and therefore the time and the speed of the visit), the attitude, and the
photographed elements were gathered. The 28 nodes are the
main attractions of the Old Quarter, identified from a systematic study of tourist guides of the city. For each node, data
were also gathered about the entrance time, the exit time, the
attitudes, and the photographed elements.
The research was conducted between July 2002 and
September 2003. The visitors observed were selected using
systematic random criteria: the fifth visitor who crossed the
sampling point at the sampling time and on the sampling
day. The research team was made up of two persons who
collected the information in voice recordings; to avoid bias,
the teams went unnoticed and only identified themselves
when the observed visitor abandoned the Old Quarter and,
therefore, had ended his or her visit. At that moment, they
were given a questionnaire based on three types of information: conventional sociodemographic data, characteristics of
the visit, and general perception of the city and its heritage
elements. Simultaneously obtaining observed data and data
JOURNAL OF TRAVEL RESEARCH
TABLE 2
FIGURE 1
PHOTOGRAPH POINTS OF THE OLD
QUARTER OF GIRONA
STATISTICS OF THE CLUSTERS FOR
THE REFERENCE’S VARIABLES
+
ERUDITE
TOURISTS
NON CULTURAL
TOURIST
INTERESTED
TOURISTS
NAN
NVN
TTV
TSN
LEN
NFE
PAA
ATE
NEW
NSN
Ritual
RITUAL
TOURISTS
−
−
445
Cluster 1
Cluster 2
Cluster 3
Cluster 4
Mean
8.20
1.82
0.54
0.11
1.654
11.04
36.79
02:56
19.82
0.37
11.15
3.10
1.29
0.26
2.144
12.64
33.33
03:50
24.99
0.73
12.42
4.23
2.06
0.41
2.425
13.35
33.82
04:53
27.31
1.05
16.00
6.08
3.04
1.07
3.646
12.83
40.60
05:05
38.22
1.53
10.84
3.18
1.33
0.28
2.158
12.31
35.07
03:54
24.79
0.75
+
Experience
provided by the visitors allowed the clusters based on the
effective behavior to be identified and the internal and external
factors explaining these clusters to be determined.
DEFINITION OF THE TOURIST
CLUSTERS IN THE TOWN
The first conclusion drawn from the study is that there are
some basic rules concerning the behavior of visitors and shared
by the majority of them. First of all, the “consumption” of the
city is focused on a few main streets that function as tourist
corridors, and a large area of the Old Quarter remains far from
the eyes of the tourists. Therefore, there are some “tourist
routes” that all the visitors follow, and there are some empty
spaces. Secondly, the study presents evidence that some nodes
are visited by the majority of tourists. This is especially the
case of the cathedral, which has become the most seen sight of
Girona. These principal nodes cannot necessarily be explained
by their historic or artistic value, but rather by being the product of a social construction. Consensus was also shown in the
direction of the visitors’ looks. Figure 1 shows a concentration
of photographs from specific points of view that reproduce the
same angles and the same perspectives.
But beyond this standard “consumption,” we have also
detected the presence of groups of visitors who show a specific behavior. To identify these clusters, we have chosen to
analyze hierarchical conglomerates. This procedure attempts
to identify relatively homogeneous groups from selected variables. The analysis of cluster or conglomerates focuses more
on the analysis units (individuals) than on the variables. Thus,
it allows us to classify individuals in homogeneous groups,
and, therefore, each unit pertaining to one of the groups or
conglomerates will be very similar and at the same time very
different from the units of the other groups. According to the
classification of Dolnicar (2004), this is a segmentation study
of Concept 5, in which the definition of data-driven subgroups
has been preceded by commonsense segmentation.
The first step in the analysis of conglomerates is to establish the measure of dissimilarity. In our study, we have used a
conventional option, the square of the Euclid distance, which
establishes the conglomerates from adding the squares of the
differences of the value of the elements. The model used is the
Ward method, which has lately been the most popular. The variables used to establish the conglomerates are as follows:
• NAN (number of accessible nodes): number of sights,
which could be visited or passed by tourists in the basic
itineraries.
• NVN (number of visited nodes): number of sights that
have actually been visited (aim of the tourist’s attention).
• TTV: total time of the visit.
• TSN (time spent in nodes): time spent at the sights.
• ATE: average time spent walking the edges.
• LEN: length of the itinerary.
• NEW: number of edges walked.
• PAA (percentage of the attitudes of ambulation): the
ambulation attitude corresponds to a lack of interest
attitude. The edge becomes an instrument that provides
access to another edge or to a principal sight.
• NFE: number of frequent edges (the 20 most popular
blocks) walked by.
• NSN: number of secondary nodes visited.
Because the units of measurement and the amplitudes
of the variables are very different, the work has been done
with the data normalized to that of Z. Using the study of the
dendrogram, distance matrix, and conglomerate history, we
have determined that the optimal solution is four clusters.
Table 2 shows the behavior of each group in the different
variables used to define the clusters. The immediate reading
of results shows that only two variables remain unchanged
in the four clusters (percentage of ambulation attitude and
number of edges walked), so values are similar among the
groups. The other eight variables are always modified in the
same direction. Furthermore, the dispersions of the averages
are relatively low, so the groups respond to two basic principles in the cluster analysis: few internal differences and
significant external differences.
From the results, we can define the characteristics of the
four identified groups (see Figure 2):
1. The noncultural tourists: 32.9% of individuals are part
of the first cluster. The main characteristic of this conglomerate is that the indicators of reference present
446
MAY 2006
FIGURE 2
CLUSTERS OF HERITAGE CONSUMERISM OF THE OLD QUARTER
Percentage of Photographs
less than 5%
between 5% and 15%
between 15% and 25%
more than 25%
Edges
60
exceptionally low, below average values. This group
visits an average of 1.82 nodes (and only 0.37 secondary
nodes), at a noticeable speed (2 minutes 56 seconds
on average) and over a very short itinerary (less than
1.5 km). That is why the general time of visit (shorter
than hour) and the time to visit nodes (11 minutes) are
far from the average values, which are already significantly low. Thus, this group shows a very superficial
relationship with the visited space, so its experience is
almost “nontourist.”
2. Ritual tourists: the most important group of visitors
(34.2%) is formed by visitors whose behavior is
almost identical to the average values. The description
of this group is very similar to the average profile: 3.1
nodes (and 0.73 secondary nodes), in a 1.5-hour visit,
dedicating half an hour to nodes, with a distance
slightly greater than 2 km. The speed is close to
4 minutes. Therefore, one-third of the visitors follow
a kind of canonical pattern: they are guided more by
a collective ritual than by individual experience.
3. Interested tourists: this group makes up 26.1% of the
visitors. The indicators certainly increase but not with
the same intensity. We should, for instance, consider the
itinerary (2,425 meters) or the number of edges (27.31),
0
60
120(mm)
all very similar to the previous ones. Variables that
could be associated with the quality of the experience
are, however, increased: more nodes (4.23), a prolonged
stay (2 hours), a greater time spent in the nodes
(41 minutes), and a slower speed (average time per
edge is about 5 minutes). In this case, visitors are not
guided by universal canons of heritage consumerism
as much as they are by singular experience, a real-life
experience of heritage.
4. Erudite tourists: this is the group with the lowest percentage: only 6.8 of the total. The erudite tourist is the
real cultural tourist, who looks for not only an experience but also knowledge. In this case, the indicators
are especially high, and, in some cases, they duplicate the average values. This tourist visits an average
of six nodes, which take him or her more than an hour,
out of the 3 hours of itinerary, covering about 4 km
(38 edges) at a very slow speed, with a clearly contemplative attitude toward the city’s elements as well
as of the urban itineraries that are described from the
visit. A characteristic of this cluster is its high internal
coherence. In the process of elaboration of the clusters,
we have noted three options: simple clusters (formed
by few variables), complex clusters (the final option),
JOURNAL OF TRAVEL RESEARCH
TABLE 3
FACTORS STRUCTURE
Factors
Gender
Female
Male
Age
18 and younger
19 to 30
31 to 40
41 to 50
51 to 60
60+
Weather
Heavy rain
Light rain
Cloudy
Partly cloudy
Sunny
Congestion
Very high
High
Normal
Low
Very low
Companions
Alone
Couple
Group
Tour guide
Yes
No
Published tour
guide
Yes
No
Previous visits
Yes
No
Locations
Girona city
Costa Brava
Another tourist
destination
Excursion
Tour
%
Chi-Square
Value
GL
Significance
Level
2.445
3
0.485
10.007
15
0.819
25.343
12
0.013
16.629
12
0.164
14.556
6
0.024
16.678
3
0.001
44.9
55.1
0.4
23.7
19.9
22.4
17.6
16.1
0.8
8.3
28.8
25.8
36.5
10.2
26.9
39.1
20.1
3.8
5.8
23.7
70.5
23.9
76.1
447
evaluated the effect of the sociodemographic factors (age
and sex), environmental factors (meteorology and degree of
congestion), and characteristics of the visit (lodging, previous
visits, number of companions, guided visit, and information
from a published guide). The results of the chi-square analysis
(Table 3) demonstrate that neither age nor sex has any influence
on the cluster assignment. Unlike results obtained in similar
studies, analysis of the effective behavior of the visitors to
the Old Quarter of Girona shows that the classic variables do
not affect the way the urban space is consumed. Age, for
example, does not act as a filter of either the physical limitations (which could determine differences in speed) or the
different possible motivations.
Regarding the environmental factors, meteorological differences determine behavior, as is to be expected in an open
area. The rain or excessive heat can reduce the itineraries
and increase the time spent in the nodes (closed spaces). No
statistical relation, however, has been detected between the
degree of congestion and the behavior of visitors.
In fact, the factors that determine the assignment of visitors
to the different clusters in an obvious way are the characteristics of the visit. A major factor is the type of visit: tourists who
stay in the city of Girona have a more intense and prolonged
experience than visitors from the coast who make a side trip to
the city or tourists on a tour. Also related are the number of
companions, previous experience (which can lead to richer and
more complex behavior), and guided visits (the routes are made
the most of, and greater interest is shown in the nodes).
CONCLUSIONS
7.608
3
0.055
17.5
82.5
8.762
3
0.033
32.259
12
0.001
25.4
74.6
9.1
45.6
15.9
24.2
5.3
or intermediate clusters (with a selection of the most
representative variables). Although the size of the other
three groups has been slightly modified as the variables changed, this conglomerate has remained unaltered. It is shown in all the options seen.
There is a strong relationship among these results and two
basic factors that we could identify as the ritual (the canonical, repetitive, mimetic behavior of tourists) and the experiential (the real-life experience of heritage far from the socially
agreed on ritual). In this case, the four clusters seem to coincide with the four quadrants of a matrix that link these two
factors.
The relation between the various factors and the definition of the clusters has been analyzed. Specifically, we have
Studies of the segmentation of cultural tourists are characterized by a high degree of heterogeneity of both the
resulting clusters and the factors influencing their definition.
These differences are explained by the sources and methods
used, and also by the particular characteristics of the destination. Despite these differences, the research studies coincide in identifying a recurring cluster: a visitor especially
interested in the culture and the heritage elements, with a
high level of previous knowledge, and very rich experiences
responding to the image of the romantic visitor. This cluster
usually represents a very small percentage of the total number
of visitors to a cultural destination.
This study combines obtaining conventional information
from questionnaires with information about the behavior of
visitors based on direct observation. The study of the effective
models of consumption of the visitors (routes, nodes visited,
time, attitudes, what was seen, and so on) provides, first of all,
objective information that is not biased by the perception of
the visitors. In fact, if we compare the data gathered from
observations with the data collected through declarations, a
significant difference is confirmed. Secondly, this methodology allows us to specify the behavior of visitors to a great
degree, and that can be very useful for the public and private
management of tourism at the destination. The principal limitations of this methodology are its high economic and material costs and the requirement that the analyzed area be a closed
one with very precise limits.
The study of visitors’ behavior has allowed us to draw some
basic conclusions about the norms related to tourist consumption of heritage sites. A more detailed analysis of the various
448
MAY 2006
indicators, however, changes this statement slightly. In fact,
the multivariate statistics have allowed us to demonstrate
that the relationship between tourist and heritage responds
to four distinct ways of consumption, which we have labeled
noncultural tourist, ritual, interested, and erudite. Once again,
the study of clusters has identified a group (which we have
called erudite) that is characterized by a very intense patrimonial experience.
The results allow us to conclude that cluster analysis
demonstrates a clear segmentation of cultural tourists in the
city of Girona, which is not determined by their sociodemographic characteristics but rather by external aspects. In fact,
the factors that explain the various ways of tourist consumption are the characteristics of the visit itself (the number of
companions, the previous visits, the tour guide, and the location), on one hand, and the meteorological conditions on the
day of the visit, on the other.
In the last analysis, the motivation that explains the relationship between heritage sites and visitors is the tension
between ritual and experience. The ritual is the unwritten code
that guides visitors and responds to universal elements. It is
essentially a social act, an individual reproduction of socially
agreed on behavior. On the contrary, the experience is the individual ability of connecting with the essence of heritage above
and beyond universal parameters. Each tourist experience is a
subtle combination of these two forces: the intensity of one or
the other determines, to a great degree, the final characteristics
of the relationship between visitor and heritage site.
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