Description
The purpose of this paper is to analyze tourist and trip-related characteristics and tourist
motivations in connection with the decision to participate in shopping and for those tourists who decide
to participate, the main determinants of the amount of expenditure
International Journal of Culture, Tourism and Hospitality Research
Tourist characteristics that influence shopping participation and expenditures
J oaquín Alegre Magdalena Cladera
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J oaquín Alegre Magdalena Cladera, (2012),"Tourist characteristics that influence shopping participation and expenditures", International
J ournal of Culture, Tourism and Hospitality Research, Vol. 6 Iss 3 pp. 223 - 237
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Fang Meng, Yingjiao Xu, (2012),"Tourism shopping behavior: planned, impulsive, or experiential?", International J ournal of Culture, Tourism
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Antónia Correia, Metin Kozak, J oão Ferradeira, (2013),"From tourist motivations to tourist satisfaction", International J ournal of Culture,
Tourism and Hospitality Research, Vol. 7 Iss 4 pp. 411-424http://dx.doi.org/10.1108/IJ CTHR-05-2012-0022
Tammy R. Kinley, J udith A. Forney, Youn-Kyung Kim, (2012),"Travel motivation as a determinant of shopping venue", International J ournal
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Tourist characteristics that in?uence
shopping participation and expenditures
Joaqu? ´n Alegre and Magdalena Cladera
Abstract
Purpose – The purpose of this paper is to analyze tourist and trip-related characteristics and tourist
motivations in connection with the decision to participate in shopping and for those tourists who decide
to participate, the main determinants of the amount of expenditure.
Design/methodology/approach – By estimating a Heckman model this paper analyses characteristics
relating to the decision to participate in shopping and characteristics related to the amount of
corresponding expenditure. The explanatory variables included in the model are tourist motivations and
tourist and trip-related characteristics. Data used for the analysis come from a survey conducted in the
high season of 2008 in Mallorca (Spain), a leading Mediterranean sun and sand destination.
Findings – The results indicate different motivations and tourist and trip-related characteristics are
associated with the decision whether or not to participate in shopping and with the level of shopping
expenditure. This facilitates the identi?cation of the type of tourist, which may be of more interest to the
destination in terms of shopping behaviour.
Practical implications – The results are useful in identifying tourist pro?les with a different propensity to
participate in shopping and with different levels of expenditure. This information may be useful for
destination managers interested in promoting shopping activities. Encouraging shopping behaviour
may be a way of increasing tourist expenditure at destinations and of providing direct bene?ts for the
local economy.
Originality/values – Tourism literature has given only very limited attention to research on
characteristics related to shopping behaviour. This study deals with this subject and it provides
information that can help promote shopping activities by tourists. The main contribution of this paper
consists of the joint analysis of shopping participation and expenditure amount as a result of trip-related
characteristics and travel motivations.
Keywords Tourist destination, Shopping expenditure by tourists, Tourist pro?le, Tourist motivations,
Heckman model, Tourism, Consumer behaviour, Shopping, Spain
Paper type Research paper
Introduction
Many Mediterranean sun-and-sand destinations are now mature destinations. One of the
main strategies used by this type of destination to attract tourists is to decrease prices.
However, although this strategy may lead to more tourists, it does not necessarily entail an
increase in the destination’s tourism revenue (Alegre and Pou, 2008). Some authors suggest
the strategy to maintain sustainable tourism levels at mature destinations is to increase
tourism revenue rather than to increase the number of arrivals (Butler, 1997; Urtasun and
Gutie´ rrez, 2006). Promoting shopping activities by tourists may be a way of raising tourist
expenditure at destinations. The latter boosts the local economy directly and indirectly
through its links with other sectors of the economy (Vaughan et al., 2000; Gelan, 2003).
By understanding visitors’ shopping expenditure patterns, destinations focus their
marketing efforts on increasing the economic bene?ts of the tourist sector (Regan and
Damonte, 1999; Cannon and Ford, 2002; Fredman, 2008). To achieve this objective,
DOI 10.1108/17506181211246375 VOL. 6 NO. 3 2012, pp. 223-237, Q Emerald Group Publishing Limited, ISSN 1750-6182
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INTERNATIONAL JOURNAL OF CULTURE, TOURISM AND HOSPITALITY RESEARCH
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PAGE 223
Joaqu? ´n Alegre and
Magdalena Cladera are
both Professors in the
Department of Applied
Economics, University of
the Balearic Islands, Illes
Balears, Spain.
Received April 2010
Revised August 2010
Accepted September 2010
The authors are grateful to the
Spanish Ministry of Science
and Technology for its ?nancial
support during the
SEJ2007-65255/ECON project
and to the Conselleria de
Turisme and Conselleria
d’Economia, Hisenda I
Innovacio´ for their ?nancial
support in conducting the
survey that has been used in
the present study.
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information regarding variables related to tourist shopping behaviour may be useful. In this
sense, the purpose of this paper is twofold. First, the objective is to identify tourist and
trip-related characteristics and tourist motivations related to the decision by tourists whether
or not to participate in shopping during their stay at the destination. Second, the interest
appeal is also to identify tourist and trip-related characteristics and tourist motivations
related to the amount of corresponding expenditure by tourists. This study conducts, by
estimating a Heckman model, a joint analysis of those characteristics related to the decision
whether or not to participate in shopping and, for those tourists who do so, those
characteristics related to the corresponding amount of expenditure.
The explanatory variables included in the model are tourist motivations and tourist and
trip-related characteristics. Data used for the analysis come from a survey conducted in the
high season of 2008 in Mallorca (Spain), one of the Mediterranean’s leading sun and sand
destinations. The results show different motivations and tourist and trip-related
characteristics are associated with the decision whether or not to participate in shopping
from those associated with the level of expenditure. This would make it possible to identify
the type of tourist that might be more interesting for the destination, in terms of shopping
behaviour. This information could be used by destination managers interested in promoting
shopping by tourists and in boosting tourism revenue by increasing this kind of tourist
expenditure.
Literature review
The tourist industry has given increasingly importance to shopping as a travel activity due to
its substantial economic contribution to the retail trade in various tourist markets around the
world. Academics have also given increasing attention to this topic in recent years
(Jansen-Verbeke, 1998; Norman, 1998; Hu and Yu, 2007). Although it is not normally
considered to be a primary travel motive, shopping is probably an essential component of
the tourist experience (Kent et al., 1983; Jansen-Verbeke, 1991; Hu and Yu, 2007) and, in
some cases it can become a major motivation in pleasure travel (Lau and Au, 2000). Existing
literature recognizes shopping as an activity tourists often do while travelling
(Jansen-Verbeke, 1990; Jansen-Verbeke, 1991; Timothy and Butler, 1995; Hobson, 1998,
Heung and Cheng, 2000; Cai et al., 2001). Some studies indicate travellers spend
approximately one third of their travel expenditure on retail shopping (Grattan and Taylor,
1987; Littrell et al., 1994). As a popular common tourist activity and signi?cant source of
revenue for destinations, tourist shopping has been a focal topic for many researchers.
A number of studies examined tourist typologies and group pro?les of tourist consumers in
order to obtain meaningful market segmentations (Anderson and Littrell, 1996; Kinley et al.,
2003; Josiam et al., 2004; Moscardo, 2004). However, while the importance of tourist
shopping is widely recognized and tourist destinations are aware of the contributions of
shopping, little is known about the characteristics of these shoppers, the actual behaviour
and expectations of tourists, and what in?uences their preferences and behaviour (Oh et al.,
2004). The ?ndings of previous research suggest certain associations exist between
socio-demographic characteristics, trip typologies and travel activities and tourists’
shopping behaviors and preferences.
Several studies show associations between age and gender and the propensity to shop and
behaviour of tourists (Anderson, 1993; Littrell et al., 1994; Anderson and Littrell, 1995, 1996).
Different authors have shown trip typologies are another important variable that might
determine the consumer pro?les of tourist shoppers. Keown (1989) reports that shopping
expenditure patterns are closely related with trip typologies and life-cycle stages as different
factors and constraints that in?uence tourists’ levels of expenditure. Thus, for marketing
experts, trip typologies could be used as a useful underlying factor in understanding tourist
behaviors and expectations.
Oh et al. (2004) examine socio-demographic characteristics and trip typologies, de?ned as
experiences sought by tourists during trips, as effective predictors of tourist involvement in
shopping activities. They ?nd that age, gender and trip typologies can serve as useful
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indicators in the con?guration of tourist shopper consumer pro?les. Lehto et al. (2004)
examine tourists’ shopping preferences and behaviours in relation to their
socio-demographic characteristics and the attributes of trips. Their results indicate the
travel purpose, travel style, age and gender are signi?cant factors, in?uencing the amount of
money travellers spent on shopping and the items that they preferred to buy.
Littrell et al. (1994) study the relationship between travel style and tourists’ souvenir-buying
patterns. They identify four types of travellers based on their travel style: people-oriented
visitors, travellers interested in history and parks, those in search of urban entertainment,
and active outdoor-pursuit enthusiasts. These four types of travellers exhibit differences in
souvenir purchasing behaviour. This research also indicates that there are gender
differences in shopping behaviour. A separate study by Littrell (1996) ?nds that the tourists’
propensity to shop varies according to the cultural background of the travellers and the
range and nature of shopping opportunities at the destination.
In their research on souvenir shopping, Anderson and Littrell (1995) discover women made
the majority of craft, gift and souvenir purchases during trips. Lawson (1991) observes age,
marital status, sex, income, the length of stay, and type of accommodation are factors that
impacted on shopping expenditures. Jansen-Verbeke (1991) also ?nd that the length of the
trip, types of activities and expenditure patterns account for behavior differences among
tourist shoppers. In another study, Jansen-Verbeke (1998) report the mature travel market
(travellers aged 50 and older) is the most important market segment because they spend
the most on shopping.
Moscardo (2004) ?nds differences among different groups of shoppers depending on their
socio-demographic and trip-related characteristics and motivations in choosing the
destination. Moscardo’s (2004) study suggest shopping activities could be related to
bene?ts associated with relaxation, social stimulation and/or status. Dholakia (1999) also
demonstrates travel motivations are related to the choice of shopping context and shopping
behaviors. These ?ndings coincide with several studies identi?ng the existence of a
relationship between motivations in choosing a destination and the activities that tourists do
during their stay (Crompton, 1979; Crandall, 1980; Dann, 1981; Gitelson and Kerstetter,
1990; McIntosh et al., 1994; Moscardo et al., 1995;Wong and Lau, 2001; Johns and
Gyimo` thy, 2002; Lee et al., 2002; Chhetri et al., 2003; Lau and McKercher, 2004; Prebensen,
2004, 2006). Through their effect on tourist activities during trips, it is expected that tourist
motivations in choosing a destination affect the type and amount of tourist expenditures
(Spotts and Mahoney, 1993; Jang et al., 2004).
Lau and Au (2000) model the relations that exist among a set of mixed numerical and
non-numerical tourist shopping data. These authors select shopping expenditure as the
dependent variable, while the independent variables are a set of individual and trip-related
characteristics (the region, age, gender, marital status, career, hotel stay, length of stay,
repeat visitation, joining local tours during the stay). Lau and Au (2000) state a formal model
representing the relationship between tourist shopping and associated socio-demographic
and travel-related factors could help tourism policy-makers and practitioners gain a clearer
understanding of this type of shopping behavior.
In accordance with the review of existing literature on shopping behaviour, this study
explores the effect that a set of tourist and trip-related characteristics and tourist motivations
in choosing the destination have on shopping decisions. The decision whether or not to
participate in shopping and the amount spent by tourist shoppers are analyzed jointly, but
taking into account that different variables might determine each of these two decisions.
Tourism literature shows travel motivations in choosing a destination in?uence shopping
behavior. Therefore it seems to make sense to consider motivational factors too when
analysing the variables that in?uence participation in shopping and shopping expenditures.
This study considers a set of pull motivations for choosing a sun and sand destination as
potential determinants of both decisions: participation in shopping by tourists and the
amount of expenditure.
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Data analysis
This study uses data obtained from a survey in which tourists from the two main nationalities
that make up tourism to Mallorca (Germans and Britons) were interviewed at the end of their
holiday. These two nationalities account for 55.6 per cent of all high-season tourism to
Mallorca (Govern de les Illes Balears, 2008). The survey was conducted at the Palma Airport
between July 28-August 24 2008. A random sample was selected, using information about
departures as noti?ed by the airport authorities. In the end, 2,464 tourists were interviewed.
To perform the following analyses, the database was previously ?ltered, ?rst to eliminate
those tourists who own a house or apartment in Mallorca, since their answers might be
heavily conditioned, and second to avoid other atypical types of tourism. Tourists with a very
low declared per capita daily expenditure (, 5 per cent percentile) or very high one (. 95
per cent percentile) were excluded. The ?nal sample comprised a total of 2,027 tourists.
In the survey, information was requested about the tourists’ socio-demographic
characteristics, how the trip was arranged, their expenditure levels, satisfaction levels,
and their motivations in choosing the destination. Using several expenditure categories, the
interviewee was asked to indicate which categories he/she had spent money on at the
destination and the amount that he/she had paid. No food shopping (souvenirs, etc.) was
included among the categories. With the information obtained from this question, it can be
ascertained whether the tourist participated in shopping activities and, in such an event, the
amount that he/she spent. With regard to tourist motivations, the interviewee was asked to
indicate how important a total of 24 (tangible and intangible) attributes that are common
characteristics of sun and sand destinations were in motivating them to choose the
destination. Their importance was rated using a ?ve-point Likert scale ranging from1 (‘‘not at
all important’’) to 5 (‘‘very important’’). The attributes used in the survey were chosen
following a review of leading analyses of the attributes of sun-and-sand destinations (Aguilo´
et al., 2005; Cossens, 1989; Fodness, 1994; Iso-Ahola and Mannel, 1987; Kozak, 2002;
Kozak and Rimmington, 1999; Mohsin and Ryan, 2003; Shoemaker, 1989; Uysal et al., 1996;
Yoon and Uysal, 2005; Alegre and Cladera, 2006). The list of attributes ?nally included in the
survey was: the quality of the accommodation, cultural activities (museums, festivals,
exhibitions, etc.), nightlife, tourist attractions (leisure parks, etc.), the climate, local cuisine, a
cheap destination, contact with nature (hiking, etc.), the local lifestyle, easy access from the
country of origin, facilities for the elderly and/or children, easy access to information and/or
an easy holiday to arrange, the destination’s presence in travel or tour operator brochures,
cleanliness and hygiene, scenery, beaches, sports activities, the presence of friends and/or
relatives, familiarity with the destination, interesting towns or cities, getting to know other
holiday companions, safety, tranquillity, prices that ?t in with the budget and, ?nally, visits to
historic sites.
The information relating to these 24 attributes was summarized into four variables. Following
a principal components analysis (PCA) with quartimax rotation, the components obtained
were included in the models as explanatory variables (see Table I). The four components
extracted account for 49.26 per cent of the total variance and all the communalities are
above 0.4. The ?rst variable (basics) summarizes ratings of the basic components of the
holiday (the quality of the accommodation, climate, local cuisine, easy access from the
country of origin, cleanliness and hygiene, scenery, beaches, safety and security,
tranquillity, and a holiday that ?tted in with the budget).
The second variable (the natural and cultural environment) covers ratings of natural, cultural
and historical attributes. The third (fun and social life) averages out ratings of the nightlife,
sports and social relationships. Finally, the fourth variable (tourist facilities) summarizes the
importance of speci?c tourist attractions, facilities for children and older people, easy
access to information and/or an easy holiday to arrange, and the destination’s presence in
travel and tour operator brochures.
The four motivational dimensions identi?ed coincide with those revealed in tourism literature
in other studies that apply a factor or principal components analysis to summarize ratings of
individual motivations (Kastenholz, 2005; Beh and Bruyere, 2007; Correia et al., 2007; Zhang
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and Marcussen, 2007; Sangpikul, 2008; Boo and Jones, 2009; Park and Yoon, 2009). In
general, the dimensions identi?ed include social/interaction, excitement/fun, sightseeing,
family/friends, sports, novelty and knowledge-seeking, ego-enhancement, rest and
relaxation, travel arrangement and facilities, cultural and historical attractions, shopping
and leisure activities, safety and cleanliness, escape, personal growth, adventure, learning,
nature, core attractions, landscape features, value for money, physical activities, information
and access, basic attributes, and tourist infrastructures.
Table II shows the descriptive statistics of the sample group for those variables that were
later considered to be potential explanatory variables of shopping behavior by tourists. As
for motivational factors, those considered to be the basic attributes of the holiday product
(the climate, beaches, cleanliness and hygiene, safety and security, a holiday that ?tted in
with the budget, the quality of the accommodation, scenery, easy access from the country of
origin, tranquillity, and the local cuisine) obtained the highest ratings.
Table III shows the descriptive statistics for shopping expenditures per person per day.
Almost 50 per cent of the tourists included in the sample did not participate in shopping
activities. For those tourists with non-zero shopping expenditure, the mean value was 6
euros per person per day. Figure 1 shows the distribution of shopping expenditure per
person per day. This distribution shows a signi?cant positive skewness (the skewness
coef?cient equals 2.33).
Table IV shows the percentage of zero expenditures and the mean value for positive
expenditures according to tourist and travel characteristics. As for nationality, British tourists
account for a higher percentage of zero expenditures than German tourists (6.7 percentage
points more). However, for those who participate in shopping, the average expenditure per
person per day for British tourists is higher than that of German tourists (1.8 euros more).
Table I PCA of importance ratings for motivational factors
Component Loadings
Per cent
variance
Per cent
cumulative
variance
Basics 19.09 19.09
Quality of accommodation 0.67
Climate 0.66
Local cuisine 0.47
Easy access from country of origin 0.54
Cleanliness and hygiene 0.79
Scenery 0.69
Beaches 0.67
Safety and security 0.73
Tranquillity 0.54
A holiday that ?tted in with the budget 0.64
Natural and cultural environment 14.18 33.27
Cultural activities 0.64
Getting back to nature 0.65
Local lifestyle 0.48
Interesting towns and villages/cities 0.69
Visits to historic sites/attractions 0.76
Fun and social life 8.98 42.26
Nightlife 0.74
Sports 0.48
The presence of friends and/or relatives 0.71
Familiarity with the destination 0.46
Getting to know other holiday companions 0.53
Tourist facilities 7.00 49.26
Tourist attractions 0.55
Facilities for children and/or older people 0.71
Easy access to information and/or an easy holiday to arrange 0.66
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Table II Descriptive statistics of the sample
Mean (%)
Number of nights 9.2
Number of people 2.4
Motivational factors
Climate 4.4
Beaches 4.2
Cleanliness and hygiene 4.2
Safety and security 4.1
A holiday that ?tted in with the budget 4.0
Quality of accommodation 4.0
Scenery 4.0
Easy access from country of origin 3.8
Tranquillity 3.7
Local cuisine 3.6
Easy access to information/an easy holiday to arrange 3.2
Interesting towns/villages/cities 3.0
Familiarity with the destination 3.0
Nightlife 2.9
Local lifestyle 2.9
Cheap destination 2.8
Facilities for children/older people 2.8
Visits to historic sites/attractions 2.6
Sports 2.6
Tourist attractions 2.6
Presence of friends and/or relatives 2.6
Cultural activities 2.5
Getting back to nature 2.5
Getting to know holiday companions 2.5
Nationality
German 47.1
British 52.8
Gender
Man 44.6
Woman 55.3
Age
18-29 29.7
30-44 38.6
45-59 25.8
60-65 3.1
Over 65 2.5
Education
Pre-primary 1.4
Primary 13.8
Secondary 36.4
Post-secondary 16.8
Third level or higher 31.4
Profession
Self-employed 10.2
Salaried employee 62.4
Civil servant 7.6
Retired 3.9
Student 11.0
Not employed 1.1
Housewife/husband 3.5
Visits in the last ?ve years
One 27.2
Two 25.7
Three 18.9
Four 11.1
Five 4.0
More than ?ve 12.8
(continued)
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When the gender of the interviewee is considered, a greater percentage of women
participate in shopping (7.17 percentage points more), with a higher average expenditure
(1.2 euros more). As for age, a higher percentage of younger tourists (18 to 29 years old) and
those over the age of 65 fall into the zero expenditure category. Among those that do
participate, the two segments exhibiting the highest average expenditures are younger
tourists (aged between 18 and 29) and older tourists (over the age of 60), with mean values
Table III Descriptive statistics for shopping expenditures
Percentage of 0 for shopping expenditure 49.8 per cent
Descriptive statistics for positive shopping expenditures (euros)
Mean Standard deviation Minimum Maximum
6.0 7.5 0.1 108.1
Figure 1 Distribution of shopping expenditures per person per day (euros)
Table III
Mean (%)
Type of accommodation
Hotel 67.1
Apartment hotel 11.2
Apartment 7.6
Others 13.9
Services booked
Without package 32.6
Flights and room 6.7
Flights/bed and breakfast 4.1
Flights/room/HB 37.2
Flights/room/FB 3.3
All inclusive 15.8
No children 57.0
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of 6.7 and about 7 euros per person per day respectively. With regard to education, tourists
with a pre-primary level of education account for the highest percentage of zero expenditure
(63.16 per cent), while also having a high average expenditure (7.1 euros).
In contrast, tourists with a primary school education present the lowest percentage of zero
expenditure (47.06 per cent), but they spend less than other tourists on shopping (4.9
Table IV Descriptive statistics for shopping expenditures by tourist and trip-related
characteristics
Per cent of zero shopping
expenditures
Mean of positive
expenditures
(e per person per day)
Nationality
German 46.3 5.1
British 53.0 6.9
Gender
Man 53.8 5.2
Woman 46.6 6.4
Age
18-29 52.3 6.7
30-44 48.2 5.7
45-59 48.5 5.4
60-65 46.5 6.9
Over 65 64.7 7.0
Education
Pre-primary 63.1 7.0
Primary 47.0 4.9
Secondary 52.5 5.9
Post-secondary 47.1 6.5
Third level or higher 48.2 6.2
Profession
Self-employed 45.0 7.7
Salaried employee 49.2 5.4
Civil servant 50.0 6.3
Retired 51.8 5.3
Student 53.3 7.8
Not employed 60.0 4.3
Housewife/husband 56.2 4.3
Visits in the last ?ve years
One 45.4 5.9
Two 49.4 4.9
Three 52.8 7.0
Four 56.0 6.2
Five 44.4 6.8
More than ?ve 52.9 6.6
Type of accommodation
Hotel 50.2 6.3
Apartment hotel 46.7 4.4
Apartment 52.8 5.0
Others 48.9 6.1
Services booked
Without package 52.1 6.4
Flights and room 52.8 6.9
Flights/bed and breakfast 57.1 4.1
Flights/room/HB 46.8 5.8
Flights/room/FB 44.4 4.6
All inclusive 50.0 5.7
Children in travel party
Yes 45.7 4.7
No 53.0 7.1
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euros). As for the tourists’ professional status, tourists without a job and
housewives/husbands account for the highest percentage of non-participation (60 and
56.25 per cent respectively) and the lowest average expenditure when they participate in
shopping (4.3 euros). Self-employed tourists account for the lowest percentage of
non-participation (45 per cent), with a high average expenditure when they participate in
shopping (7.7 euros). Students account for the highest average expenditure (7.8 euros)
when they participate in shopping. As for repeat visitation, in general it seems ?rst-timers
have a higher propensity to participate in shopping activities (45.43 per cent of zeros) than
repeat visitors. However, the segment tending to spend more when they participate in
shopping is tourists who have visited the destination three times or more. With regard to the
type of accommodation, tourists staying at apartment hotels show the lowest percentage of
zero expenditure (46.75 per cent). Nonetheless, among those tourists that do participate,
tourists staying at hotels have the highest mean expenditure (6.3 euros). When the services
that are booked are considered, differences in shopping participation and shopping
expenditure were also observed. Tourists who booked a ?ight and bed and breakfast
account for the highest percentage of non-participation (57.14 per cent) and the lowest
average expenditure (4.2 euros).
Tourists who booked a ?ight and accommodation with half or full board tended to participate
in shopping more than other tourists, and tourists who travelled on a non-package holiday or
just booked a ?ight and a room have the highest average expenditure when they engage in
shopping activities (6.4 and 6.9 euros respectively). Finally, as for the presence of children in
the travel party, there is a positive relationship to participation in shopping (7 percentage
points more) but negatively related to average expenditure (2.3 euros less).
The results in Table IV are valid as a description of the data and they highlight the existence
of differences in shopping behaviour according to tourist and trip-related characteristics
and tourist motivations. However, possible interrelations among the different characteristics
do not allow reaching de?nitive conclusions from this descriptive analysis. The speci?cation
and estimation of an econometric model will facilitate the identi?cation of possible signi?cant
relations between tourist and trip-related characteristics and tourist motivations and the
decision whether or not to participate in shopping and corresponding shopping
expenditures.
Method
To achieve the objectives of the study, a Heckman model was estimated in order to make a
joint analysis of characteristics related to the decision whether or not to participate in
shopping and, for those who choose to shop, characteristics related to the amount of
expenditure. Tourist motivations and tourist and trip-related characteristics were included as
explanatory variables. As previously commented, the distribution of shopping expenditures
shows a high concentration of observations at zero. This fact must be taken into account
when estimating the relationship between this variable and other explanatory variables.
In the case of shopping expenditures, the selected explanatory variables might in?uence
both the probability of a tourist deciding to shop and the amount actually spent, if he/she
decided to buy anything. If the probability of participating in shopping were the only
dynamic needed explaining, a probit analysis would provide a suitable statistical model, but
it is inef?cient to discard information relating to the value of the dependent variable when this
data are available. This is the case here, because if a tourist engaged in shopping activities,
we know how much he/she spent. If, on the other hand, there were no concentrations at a
lower limit and we only cared to explain the amount of shopping expenditure, a multiple
regression would be the appropriate statistical technique. Nevertheless, since there is a
concentration of values for the dependent variable at a certain limit (in this case at zero), OLS
estimates are biased because the dependent variable is not continuous and unbounded. A
tobit model is a hybrid of these two methods as a solution to the problem. However, in a tobit
model, the same set of variables and coef?cients determine both the probability that an
observation will be censored and the value of the dependent variable. The sample selection
or Heckman model address this shortcoming by allowing a different set of variables and
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coef?cients to determine the probability of censoring and the value of the dependent
variable, given that it is observed. These explanatory variables may overlap at a point or be
completely different.
As for shopping expenditure, tourists may or may not decide to shop but for those tourists
who participate in this activity, their amount of expenditure is observed. Thus two dependent
variables are considered. A dichotomous variable y
1
that takes a value of 1 if the tourist
participates in shopping and a value of 0 otherwise, and an outcome variable y
2
that
determines the corresponding amount of expenditure in the case of those tourists who
participate in shopping. The two-equation model comprises a selection equation for y
1
, and
a resulting outcome equation for y
2
. The error terms of both equations are possibly
correlated. If this is the case, estimating a shopping expenditure model without ?rst
estimating an equation for whether or not the tourist decides to participate in shopping would
lead to biased results. However, if the correlation between the error terms is zero, the
likelihood function can be split into two parts: a probit for the probability of the tourist
participating in shopping and an OLS regression for the expected value of expenditure on
shopping.
In the Heckman model, it is assumed that the correlated errors (1
1
and 1
2
) are jointly normally
distributed and homoskedastic:
1
1
1
2
" #
N
0
0
" #
;
1 s
12
s
12
s
2
2
" # " #
After estimating the model, the hypothesis that the two parts of the model are independent
can be tested by testing whether the correlation between the errors equals zero.
Results
The dependent variable for the selection equation was a binary variable that takes a value of
1 if the tourist participates in shopping and a value of 0 otherwise. As for the outcome
equation, the dependent variable was the logarithm of expenditure on shopping per person
per day for those tourists who spent a positive amount on shopping. Logarithms have been
taken because the scale variable cannot be assumed to be normal (see Figure 1), but when
taking logarithms, normality cannot be rejected. The skewness/kurtosis test and
Shapiro-Wilk test for normality were performed for the logarithm of shopping expenditure
and the p-value of these tests was 0.9638 and 0.3385 respectively. After estimating the
model, the likelihood-ratio test of independent equations had a p-value of 0.8067. Thus the
estimated correlation between the errors is not signi?cantly different from zero, and the
hypothesis that the two parts are independent cannot be rejected.
Initially the length of stay, group size, motivational factors, nationality, gender, age, level of
education, profession, number of previous visits, type of accommodation, inclusion or not of
children in the travel party, and services included in the package holiday were used as
independent variables for the selection equation and also for the outcome equation. Some of
these variables were not signi?cant and were excluded when the de?nitive model, shown in
Table V, was estimated. Tourist motivations in choosing the destination were included as
explanatory variables, using the four motivational factors identi?ed with the previously
presented PCA.
Table V shows the results of the estimated Heckman selection model for shopping
expenditures. Signi?cant variables in the selection equation were the nationality, level of
education, inclusion or not of children in the travel party, number of visits and some
motivational factors. The nationality, profession, number of visits, length of stay and number
of people in the travel party were all signi?cant variables in the outcome equation.
For the selection equation, the marginal effects of each explanatory variable on the
probability of participating in shopping are shown in Table V. In the Heckman model, when
an explanatory variable appears in both the selection and outcome equations, the marginal
effect on the outcome variable is not given by the coef?cient estimate itself, but rather it must
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be corrected for the selectivity effect. However, given that in this study the hypothesis that
the two parts are independent cannot be rejected, the marginal effects on the outcome
equation are equal to the estimated coef?cients.
As for the effects of the explanatory variables, with regard to the decision whether or not to
participate in shopping, British tourists have a lower probability of engaging in shopping
activities. Tourists with a post secondary school level of education are more likely to
participate in shopping. If there are children in the travel party, there is a greater probability
of shopping expenditure. The more times a tourist has visited the destination, the less likely
he/she is to participate in shopping. With regard to motivational factors, motivations related
to the basic attributes of the holiday and those related to natural and cultural attributes are
signi?cant in determining the probability of expenditure on shopping. The higher the tourist’s
level of motivation for these speci?c factors, the more likely he/she is to participate in
shopping. Other motivational factors (related to fun, a good social life and tourist facilities)
are not signi?cant in determining participation in shopping.
As for factors that affect the amount of expenditure on shopping, British tourists tend to
spend more than German tourists. In terms of the tourists’ professional status, being
self-employed has a positive effect on expenditure on shopping. As for the number of visits,
tourists who have visited the destination more than three times spend more on shopping
Table V Estimated results of the Heckman selection model
B Sig. Marginal effects
Participation in shopping
Nationality
British 20.42 0.00 20.16
German – – –
Education
Post-secondary education 0.21 0.06 0.08
Others – – –
Children in the travel party 0.27 0.00 0.10
Number of visits
First visit – –
Two or three visits 20.17 0.09 20.07
Four or more visits 20.27 0.02 20.11
Motivational factors
Basic 0.11 0.00 0.04
Nature and cultural 0.11 0.01 0.04
Constant 0.14 0.16 –
Logarithm expenditure on shopping
Nationality
British 0.49 0.00
German – –
Profession
Self-employed 0.26 0.03
Others – –
Number of visits
One to three visits – –
Four or more visits 0.24 0.01
Number of nights 20.09 0.00
Number of people 20.22 0.00
Constant 2.35 0.00
/athrho 0.08 0.80
/lnsigma 20.20 0.00
Rho 0.08
Sigma 0.81
Lambda 0.07
LR test of indep. eqns (r ¼ 0) x
2
(1)¼0.06 Prob . x
2
¼0.8067
Notes: Heckman selection model ¼ Number of observations ¼ 892; Censored observations ¼ 475;
Uncensored observations ¼ 417. Wald x
2
(5)¼121.83. Log likelihood ¼ 21098.09. Prob . x
2
¼0.000
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than other tourists. The length of stay and number of people in the travel party have a
negative effect on shopping expenditure per person per day.
According to these results, German tourists with a post secondary school level of education,
travelling with children and visiting the destination for the ?rst time, motivated by the basic
attributes of a sun and sand holiday and/or by the destination’s natural and cultural
attributes, are more likely to participate in shopping activities than other tourists. However,
when it comes to the amount of expenditure, British self-employed tourists on their fourth visit
or more tend to spend more than other tourists.
In this sense, it is worth focusing attention on the different sign of the effects of being a British
tourist and the number of visits in the two equations of the selection model. While British and
repeat visitors show a lower probability of participating in shopping activities, when they do
decide to participate, they spend more than other tourists. Therefore efforts to promote and
highlight shopping opportunities at the destination among the British and repeat visitor
markets could boost spending on shopping there.
Conclusions
The results of this study show links between shopping behaviour and certain tourist and
trip-related characteristics and motivational factors. In terms of shopping behaviour, tourists
with certain characteristics and motivations are preferable to others. For instance, being
motivated by the basic attributes of a sun and sand holiday and/or by natural and cultural
aspects of the destination, travelling with children, having a post secondary school level of
education or being self-employed are all positive characteristics in terms of shopping
behaviour. However, the results of the analysis for British tourists and repeat visitors are
contradictory. When the decision whether or not to participate in shopping is considered,
both characteristics are undesirable. However, when they decide to participate, British
tourists and visitors who are more familiar with the destination tend to spend higher amounts
on shopping. If managers at the destination want to bene?t fromthis trend, they should direct
promotional activities at the British and repeat visitor markets, trying to highlight the
shopping opportunities available at the destination and encouraging these segments to
shop.
This study also demonstrates the in?uence of tourist motivations on shopping behaviour.
Tourist motivations affect the decision whether or not to participate in shopping but not the
amount of expenditure. This ?nding provides important information in helping to target those
market segments that offer the highest potential as shoppers. In this sense, tourists primarily
motivated by the basic attributes of a sun and sand holiday and those in search of
complementary aspects, like the natural environment or cultural attractions, are more likely
to participate in shopping. Therefore promotional efforts directed at highlighting these
destination attributes can help to attract tourists that are potentially bene?cial as shoppers.
The results of this study are useful in helping to identify tourist pro?les with a different
propensity to participate in shopping, and with different levels of expenditure. This
information may be useful for destination managers interested in promoting shopping by
tourists and in increasing revenue from tourism by boosting this kind of expenditure by
holidaymakers.
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Corresponding author
Magdalena Cladera can be contacted at: [email protected]
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doc_945167257.pdf
The purpose of this paper is to analyze tourist and trip-related characteristics and tourist
motivations in connection with the decision to participate in shopping and for those tourists who decide
to participate, the main determinants of the amount of expenditure
International Journal of Culture, Tourism and Hospitality Research
Tourist characteristics that influence shopping participation and expenditures
J oaquín Alegre Magdalena Cladera
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J oaquín Alegre Magdalena Cladera, (2012),"Tourist characteristics that influence shopping participation and expenditures", International
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Tourist characteristics that in?uence
shopping participation and expenditures
Joaqu? ´n Alegre and Magdalena Cladera
Abstract
Purpose – The purpose of this paper is to analyze tourist and trip-related characteristics and tourist
motivations in connection with the decision to participate in shopping and for those tourists who decide
to participate, the main determinants of the amount of expenditure.
Design/methodology/approach – By estimating a Heckman model this paper analyses characteristics
relating to the decision to participate in shopping and characteristics related to the amount of
corresponding expenditure. The explanatory variables included in the model are tourist motivations and
tourist and trip-related characteristics. Data used for the analysis come from a survey conducted in the
high season of 2008 in Mallorca (Spain), a leading Mediterranean sun and sand destination.
Findings – The results indicate different motivations and tourist and trip-related characteristics are
associated with the decision whether or not to participate in shopping and with the level of shopping
expenditure. This facilitates the identi?cation of the type of tourist, which may be of more interest to the
destination in terms of shopping behaviour.
Practical implications – The results are useful in identifying tourist pro?les with a different propensity to
participate in shopping and with different levels of expenditure. This information may be useful for
destination managers interested in promoting shopping activities. Encouraging shopping behaviour
may be a way of increasing tourist expenditure at destinations and of providing direct bene?ts for the
local economy.
Originality/values – Tourism literature has given only very limited attention to research on
characteristics related to shopping behaviour. This study deals with this subject and it provides
information that can help promote shopping activities by tourists. The main contribution of this paper
consists of the joint analysis of shopping participation and expenditure amount as a result of trip-related
characteristics and travel motivations.
Keywords Tourist destination, Shopping expenditure by tourists, Tourist pro?le, Tourist motivations,
Heckman model, Tourism, Consumer behaviour, Shopping, Spain
Paper type Research paper
Introduction
Many Mediterranean sun-and-sand destinations are now mature destinations. One of the
main strategies used by this type of destination to attract tourists is to decrease prices.
However, although this strategy may lead to more tourists, it does not necessarily entail an
increase in the destination’s tourism revenue (Alegre and Pou, 2008). Some authors suggest
the strategy to maintain sustainable tourism levels at mature destinations is to increase
tourism revenue rather than to increase the number of arrivals (Butler, 1997; Urtasun and
Gutie´ rrez, 2006). Promoting shopping activities by tourists may be a way of raising tourist
expenditure at destinations. The latter boosts the local economy directly and indirectly
through its links with other sectors of the economy (Vaughan et al., 2000; Gelan, 2003).
By understanding visitors’ shopping expenditure patterns, destinations focus their
marketing efforts on increasing the economic bene?ts of the tourist sector (Regan and
Damonte, 1999; Cannon and Ford, 2002; Fredman, 2008). To achieve this objective,
DOI 10.1108/17506181211246375 VOL. 6 NO. 3 2012, pp. 223-237, Q Emerald Group Publishing Limited, ISSN 1750-6182
j
INTERNATIONAL JOURNAL OF CULTURE, TOURISM AND HOSPITALITY RESEARCH
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PAGE 223
Joaqu? ´n Alegre and
Magdalena Cladera are
both Professors in the
Department of Applied
Economics, University of
the Balearic Islands, Illes
Balears, Spain.
Received April 2010
Revised August 2010
Accepted September 2010
The authors are grateful to the
Spanish Ministry of Science
and Technology for its ?nancial
support during the
SEJ2007-65255/ECON project
and to the Conselleria de
Turisme and Conselleria
d’Economia, Hisenda I
Innovacio´ for their ?nancial
support in conducting the
survey that has been used in
the present study.
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information regarding variables related to tourist shopping behaviour may be useful. In this
sense, the purpose of this paper is twofold. First, the objective is to identify tourist and
trip-related characteristics and tourist motivations related to the decision by tourists whether
or not to participate in shopping during their stay at the destination. Second, the interest
appeal is also to identify tourist and trip-related characteristics and tourist motivations
related to the amount of corresponding expenditure by tourists. This study conducts, by
estimating a Heckman model, a joint analysis of those characteristics related to the decision
whether or not to participate in shopping and, for those tourists who do so, those
characteristics related to the corresponding amount of expenditure.
The explanatory variables included in the model are tourist motivations and tourist and
trip-related characteristics. Data used for the analysis come from a survey conducted in the
high season of 2008 in Mallorca (Spain), one of the Mediterranean’s leading sun and sand
destinations. The results show different motivations and tourist and trip-related
characteristics are associated with the decision whether or not to participate in shopping
from those associated with the level of expenditure. This would make it possible to identify
the type of tourist that might be more interesting for the destination, in terms of shopping
behaviour. This information could be used by destination managers interested in promoting
shopping by tourists and in boosting tourism revenue by increasing this kind of tourist
expenditure.
Literature review
The tourist industry has given increasingly importance to shopping as a travel activity due to
its substantial economic contribution to the retail trade in various tourist markets around the
world. Academics have also given increasing attention to this topic in recent years
(Jansen-Verbeke, 1998; Norman, 1998; Hu and Yu, 2007). Although it is not normally
considered to be a primary travel motive, shopping is probably an essential component of
the tourist experience (Kent et al., 1983; Jansen-Verbeke, 1991; Hu and Yu, 2007) and, in
some cases it can become a major motivation in pleasure travel (Lau and Au, 2000). Existing
literature recognizes shopping as an activity tourists often do while travelling
(Jansen-Verbeke, 1990; Jansen-Verbeke, 1991; Timothy and Butler, 1995; Hobson, 1998,
Heung and Cheng, 2000; Cai et al., 2001). Some studies indicate travellers spend
approximately one third of their travel expenditure on retail shopping (Grattan and Taylor,
1987; Littrell et al., 1994). As a popular common tourist activity and signi?cant source of
revenue for destinations, tourist shopping has been a focal topic for many researchers.
A number of studies examined tourist typologies and group pro?les of tourist consumers in
order to obtain meaningful market segmentations (Anderson and Littrell, 1996; Kinley et al.,
2003; Josiam et al., 2004; Moscardo, 2004). However, while the importance of tourist
shopping is widely recognized and tourist destinations are aware of the contributions of
shopping, little is known about the characteristics of these shoppers, the actual behaviour
and expectations of tourists, and what in?uences their preferences and behaviour (Oh et al.,
2004). The ?ndings of previous research suggest certain associations exist between
socio-demographic characteristics, trip typologies and travel activities and tourists’
shopping behaviors and preferences.
Several studies show associations between age and gender and the propensity to shop and
behaviour of tourists (Anderson, 1993; Littrell et al., 1994; Anderson and Littrell, 1995, 1996).
Different authors have shown trip typologies are another important variable that might
determine the consumer pro?les of tourist shoppers. Keown (1989) reports that shopping
expenditure patterns are closely related with trip typologies and life-cycle stages as different
factors and constraints that in?uence tourists’ levels of expenditure. Thus, for marketing
experts, trip typologies could be used as a useful underlying factor in understanding tourist
behaviors and expectations.
Oh et al. (2004) examine socio-demographic characteristics and trip typologies, de?ned as
experiences sought by tourists during trips, as effective predictors of tourist involvement in
shopping activities. They ?nd that age, gender and trip typologies can serve as useful
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indicators in the con?guration of tourist shopper consumer pro?les. Lehto et al. (2004)
examine tourists’ shopping preferences and behaviours in relation to their
socio-demographic characteristics and the attributes of trips. Their results indicate the
travel purpose, travel style, age and gender are signi?cant factors, in?uencing the amount of
money travellers spent on shopping and the items that they preferred to buy.
Littrell et al. (1994) study the relationship between travel style and tourists’ souvenir-buying
patterns. They identify four types of travellers based on their travel style: people-oriented
visitors, travellers interested in history and parks, those in search of urban entertainment,
and active outdoor-pursuit enthusiasts. These four types of travellers exhibit differences in
souvenir purchasing behaviour. This research also indicates that there are gender
differences in shopping behaviour. A separate study by Littrell (1996) ?nds that the tourists’
propensity to shop varies according to the cultural background of the travellers and the
range and nature of shopping opportunities at the destination.
In their research on souvenir shopping, Anderson and Littrell (1995) discover women made
the majority of craft, gift and souvenir purchases during trips. Lawson (1991) observes age,
marital status, sex, income, the length of stay, and type of accommodation are factors that
impacted on shopping expenditures. Jansen-Verbeke (1991) also ?nd that the length of the
trip, types of activities and expenditure patterns account for behavior differences among
tourist shoppers. In another study, Jansen-Verbeke (1998) report the mature travel market
(travellers aged 50 and older) is the most important market segment because they spend
the most on shopping.
Moscardo (2004) ?nds differences among different groups of shoppers depending on their
socio-demographic and trip-related characteristics and motivations in choosing the
destination. Moscardo’s (2004) study suggest shopping activities could be related to
bene?ts associated with relaxation, social stimulation and/or status. Dholakia (1999) also
demonstrates travel motivations are related to the choice of shopping context and shopping
behaviors. These ?ndings coincide with several studies identi?ng the existence of a
relationship between motivations in choosing a destination and the activities that tourists do
during their stay (Crompton, 1979; Crandall, 1980; Dann, 1981; Gitelson and Kerstetter,
1990; McIntosh et al., 1994; Moscardo et al., 1995;Wong and Lau, 2001; Johns and
Gyimo` thy, 2002; Lee et al., 2002; Chhetri et al., 2003; Lau and McKercher, 2004; Prebensen,
2004, 2006). Through their effect on tourist activities during trips, it is expected that tourist
motivations in choosing a destination affect the type and amount of tourist expenditures
(Spotts and Mahoney, 1993; Jang et al., 2004).
Lau and Au (2000) model the relations that exist among a set of mixed numerical and
non-numerical tourist shopping data. These authors select shopping expenditure as the
dependent variable, while the independent variables are a set of individual and trip-related
characteristics (the region, age, gender, marital status, career, hotel stay, length of stay,
repeat visitation, joining local tours during the stay). Lau and Au (2000) state a formal model
representing the relationship between tourist shopping and associated socio-demographic
and travel-related factors could help tourism policy-makers and practitioners gain a clearer
understanding of this type of shopping behavior.
In accordance with the review of existing literature on shopping behaviour, this study
explores the effect that a set of tourist and trip-related characteristics and tourist motivations
in choosing the destination have on shopping decisions. The decision whether or not to
participate in shopping and the amount spent by tourist shoppers are analyzed jointly, but
taking into account that different variables might determine each of these two decisions.
Tourism literature shows travel motivations in choosing a destination in?uence shopping
behavior. Therefore it seems to make sense to consider motivational factors too when
analysing the variables that in?uence participation in shopping and shopping expenditures.
This study considers a set of pull motivations for choosing a sun and sand destination as
potential determinants of both decisions: participation in shopping by tourists and the
amount of expenditure.
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Data analysis
This study uses data obtained from a survey in which tourists from the two main nationalities
that make up tourism to Mallorca (Germans and Britons) were interviewed at the end of their
holiday. These two nationalities account for 55.6 per cent of all high-season tourism to
Mallorca (Govern de les Illes Balears, 2008). The survey was conducted at the Palma Airport
between July 28-August 24 2008. A random sample was selected, using information about
departures as noti?ed by the airport authorities. In the end, 2,464 tourists were interviewed.
To perform the following analyses, the database was previously ?ltered, ?rst to eliminate
those tourists who own a house or apartment in Mallorca, since their answers might be
heavily conditioned, and second to avoid other atypical types of tourism. Tourists with a very
low declared per capita daily expenditure (, 5 per cent percentile) or very high one (. 95
per cent percentile) were excluded. The ?nal sample comprised a total of 2,027 tourists.
In the survey, information was requested about the tourists’ socio-demographic
characteristics, how the trip was arranged, their expenditure levels, satisfaction levels,
and their motivations in choosing the destination. Using several expenditure categories, the
interviewee was asked to indicate which categories he/she had spent money on at the
destination and the amount that he/she had paid. No food shopping (souvenirs, etc.) was
included among the categories. With the information obtained from this question, it can be
ascertained whether the tourist participated in shopping activities and, in such an event, the
amount that he/she spent. With regard to tourist motivations, the interviewee was asked to
indicate how important a total of 24 (tangible and intangible) attributes that are common
characteristics of sun and sand destinations were in motivating them to choose the
destination. Their importance was rated using a ?ve-point Likert scale ranging from1 (‘‘not at
all important’’) to 5 (‘‘very important’’). The attributes used in the survey were chosen
following a review of leading analyses of the attributes of sun-and-sand destinations (Aguilo´
et al., 2005; Cossens, 1989; Fodness, 1994; Iso-Ahola and Mannel, 1987; Kozak, 2002;
Kozak and Rimmington, 1999; Mohsin and Ryan, 2003; Shoemaker, 1989; Uysal et al., 1996;
Yoon and Uysal, 2005; Alegre and Cladera, 2006). The list of attributes ?nally included in the
survey was: the quality of the accommodation, cultural activities (museums, festivals,
exhibitions, etc.), nightlife, tourist attractions (leisure parks, etc.), the climate, local cuisine, a
cheap destination, contact with nature (hiking, etc.), the local lifestyle, easy access from the
country of origin, facilities for the elderly and/or children, easy access to information and/or
an easy holiday to arrange, the destination’s presence in travel or tour operator brochures,
cleanliness and hygiene, scenery, beaches, sports activities, the presence of friends and/or
relatives, familiarity with the destination, interesting towns or cities, getting to know other
holiday companions, safety, tranquillity, prices that ?t in with the budget and, ?nally, visits to
historic sites.
The information relating to these 24 attributes was summarized into four variables. Following
a principal components analysis (PCA) with quartimax rotation, the components obtained
were included in the models as explanatory variables (see Table I). The four components
extracted account for 49.26 per cent of the total variance and all the communalities are
above 0.4. The ?rst variable (basics) summarizes ratings of the basic components of the
holiday (the quality of the accommodation, climate, local cuisine, easy access from the
country of origin, cleanliness and hygiene, scenery, beaches, safety and security,
tranquillity, and a holiday that ?tted in with the budget).
The second variable (the natural and cultural environment) covers ratings of natural, cultural
and historical attributes. The third (fun and social life) averages out ratings of the nightlife,
sports and social relationships. Finally, the fourth variable (tourist facilities) summarizes the
importance of speci?c tourist attractions, facilities for children and older people, easy
access to information and/or an easy holiday to arrange, and the destination’s presence in
travel and tour operator brochures.
The four motivational dimensions identi?ed coincide with those revealed in tourism literature
in other studies that apply a factor or principal components analysis to summarize ratings of
individual motivations (Kastenholz, 2005; Beh and Bruyere, 2007; Correia et al., 2007; Zhang
PAGE 226
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and Marcussen, 2007; Sangpikul, 2008; Boo and Jones, 2009; Park and Yoon, 2009). In
general, the dimensions identi?ed include social/interaction, excitement/fun, sightseeing,
family/friends, sports, novelty and knowledge-seeking, ego-enhancement, rest and
relaxation, travel arrangement and facilities, cultural and historical attractions, shopping
and leisure activities, safety and cleanliness, escape, personal growth, adventure, learning,
nature, core attractions, landscape features, value for money, physical activities, information
and access, basic attributes, and tourist infrastructures.
Table II shows the descriptive statistics of the sample group for those variables that were
later considered to be potential explanatory variables of shopping behavior by tourists. As
for motivational factors, those considered to be the basic attributes of the holiday product
(the climate, beaches, cleanliness and hygiene, safety and security, a holiday that ?tted in
with the budget, the quality of the accommodation, scenery, easy access from the country of
origin, tranquillity, and the local cuisine) obtained the highest ratings.
Table III shows the descriptive statistics for shopping expenditures per person per day.
Almost 50 per cent of the tourists included in the sample did not participate in shopping
activities. For those tourists with non-zero shopping expenditure, the mean value was 6
euros per person per day. Figure 1 shows the distribution of shopping expenditure per
person per day. This distribution shows a signi?cant positive skewness (the skewness
coef?cient equals 2.33).
Table IV shows the percentage of zero expenditures and the mean value for positive
expenditures according to tourist and travel characteristics. As for nationality, British tourists
account for a higher percentage of zero expenditures than German tourists (6.7 percentage
points more). However, for those who participate in shopping, the average expenditure per
person per day for British tourists is higher than that of German tourists (1.8 euros more).
Table I PCA of importance ratings for motivational factors
Component Loadings
Per cent
variance
Per cent
cumulative
variance
Basics 19.09 19.09
Quality of accommodation 0.67
Climate 0.66
Local cuisine 0.47
Easy access from country of origin 0.54
Cleanliness and hygiene 0.79
Scenery 0.69
Beaches 0.67
Safety and security 0.73
Tranquillity 0.54
A holiday that ?tted in with the budget 0.64
Natural and cultural environment 14.18 33.27
Cultural activities 0.64
Getting back to nature 0.65
Local lifestyle 0.48
Interesting towns and villages/cities 0.69
Visits to historic sites/attractions 0.76
Fun and social life 8.98 42.26
Nightlife 0.74
Sports 0.48
The presence of friends and/or relatives 0.71
Familiarity with the destination 0.46
Getting to know other holiday companions 0.53
Tourist facilities 7.00 49.26
Tourist attractions 0.55
Facilities for children and/or older people 0.71
Easy access to information and/or an easy holiday to arrange 0.66
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Table II Descriptive statistics of the sample
Mean (%)
Number of nights 9.2
Number of people 2.4
Motivational factors
Climate 4.4
Beaches 4.2
Cleanliness and hygiene 4.2
Safety and security 4.1
A holiday that ?tted in with the budget 4.0
Quality of accommodation 4.0
Scenery 4.0
Easy access from country of origin 3.8
Tranquillity 3.7
Local cuisine 3.6
Easy access to information/an easy holiday to arrange 3.2
Interesting towns/villages/cities 3.0
Familiarity with the destination 3.0
Nightlife 2.9
Local lifestyle 2.9
Cheap destination 2.8
Facilities for children/older people 2.8
Visits to historic sites/attractions 2.6
Sports 2.6
Tourist attractions 2.6
Presence of friends and/or relatives 2.6
Cultural activities 2.5
Getting back to nature 2.5
Getting to know holiday companions 2.5
Nationality
German 47.1
British 52.8
Gender
Man 44.6
Woman 55.3
Age
18-29 29.7
30-44 38.6
45-59 25.8
60-65 3.1
Over 65 2.5
Education
Pre-primary 1.4
Primary 13.8
Secondary 36.4
Post-secondary 16.8
Third level or higher 31.4
Profession
Self-employed 10.2
Salaried employee 62.4
Civil servant 7.6
Retired 3.9
Student 11.0
Not employed 1.1
Housewife/husband 3.5
Visits in the last ?ve years
One 27.2
Two 25.7
Three 18.9
Four 11.1
Five 4.0
More than ?ve 12.8
(continued)
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When the gender of the interviewee is considered, a greater percentage of women
participate in shopping (7.17 percentage points more), with a higher average expenditure
(1.2 euros more). As for age, a higher percentage of younger tourists (18 to 29 years old) and
those over the age of 65 fall into the zero expenditure category. Among those that do
participate, the two segments exhibiting the highest average expenditures are younger
tourists (aged between 18 and 29) and older tourists (over the age of 60), with mean values
Table III Descriptive statistics for shopping expenditures
Percentage of 0 for shopping expenditure 49.8 per cent
Descriptive statistics for positive shopping expenditures (euros)
Mean Standard deviation Minimum Maximum
6.0 7.5 0.1 108.1
Figure 1 Distribution of shopping expenditures per person per day (euros)
Table III
Mean (%)
Type of accommodation
Hotel 67.1
Apartment hotel 11.2
Apartment 7.6
Others 13.9
Services booked
Without package 32.6
Flights and room 6.7
Flights/bed and breakfast 4.1
Flights/room/HB 37.2
Flights/room/FB 3.3
All inclusive 15.8
No children 57.0
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of 6.7 and about 7 euros per person per day respectively. With regard to education, tourists
with a pre-primary level of education account for the highest percentage of zero expenditure
(63.16 per cent), while also having a high average expenditure (7.1 euros).
In contrast, tourists with a primary school education present the lowest percentage of zero
expenditure (47.06 per cent), but they spend less than other tourists on shopping (4.9
Table IV Descriptive statistics for shopping expenditures by tourist and trip-related
characteristics
Per cent of zero shopping
expenditures
Mean of positive
expenditures
(e per person per day)
Nationality
German 46.3 5.1
British 53.0 6.9
Gender
Man 53.8 5.2
Woman 46.6 6.4
Age
18-29 52.3 6.7
30-44 48.2 5.7
45-59 48.5 5.4
60-65 46.5 6.9
Over 65 64.7 7.0
Education
Pre-primary 63.1 7.0
Primary 47.0 4.9
Secondary 52.5 5.9
Post-secondary 47.1 6.5
Third level or higher 48.2 6.2
Profession
Self-employed 45.0 7.7
Salaried employee 49.2 5.4
Civil servant 50.0 6.3
Retired 51.8 5.3
Student 53.3 7.8
Not employed 60.0 4.3
Housewife/husband 56.2 4.3
Visits in the last ?ve years
One 45.4 5.9
Two 49.4 4.9
Three 52.8 7.0
Four 56.0 6.2
Five 44.4 6.8
More than ?ve 52.9 6.6
Type of accommodation
Hotel 50.2 6.3
Apartment hotel 46.7 4.4
Apartment 52.8 5.0
Others 48.9 6.1
Services booked
Without package 52.1 6.4
Flights and room 52.8 6.9
Flights/bed and breakfast 57.1 4.1
Flights/room/HB 46.8 5.8
Flights/room/FB 44.4 4.6
All inclusive 50.0 5.7
Children in travel party
Yes 45.7 4.7
No 53.0 7.1
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euros). As for the tourists’ professional status, tourists without a job and
housewives/husbands account for the highest percentage of non-participation (60 and
56.25 per cent respectively) and the lowest average expenditure when they participate in
shopping (4.3 euros). Self-employed tourists account for the lowest percentage of
non-participation (45 per cent), with a high average expenditure when they participate in
shopping (7.7 euros). Students account for the highest average expenditure (7.8 euros)
when they participate in shopping. As for repeat visitation, in general it seems ?rst-timers
have a higher propensity to participate in shopping activities (45.43 per cent of zeros) than
repeat visitors. However, the segment tending to spend more when they participate in
shopping is tourists who have visited the destination three times or more. With regard to the
type of accommodation, tourists staying at apartment hotels show the lowest percentage of
zero expenditure (46.75 per cent). Nonetheless, among those tourists that do participate,
tourists staying at hotels have the highest mean expenditure (6.3 euros). When the services
that are booked are considered, differences in shopping participation and shopping
expenditure were also observed. Tourists who booked a ?ight and bed and breakfast
account for the highest percentage of non-participation (57.14 per cent) and the lowest
average expenditure (4.2 euros).
Tourists who booked a ?ight and accommodation with half or full board tended to participate
in shopping more than other tourists, and tourists who travelled on a non-package holiday or
just booked a ?ight and a room have the highest average expenditure when they engage in
shopping activities (6.4 and 6.9 euros respectively). Finally, as for the presence of children in
the travel party, there is a positive relationship to participation in shopping (7 percentage
points more) but negatively related to average expenditure (2.3 euros less).
The results in Table IV are valid as a description of the data and they highlight the existence
of differences in shopping behaviour according to tourist and trip-related characteristics
and tourist motivations. However, possible interrelations among the different characteristics
do not allow reaching de?nitive conclusions from this descriptive analysis. The speci?cation
and estimation of an econometric model will facilitate the identi?cation of possible signi?cant
relations between tourist and trip-related characteristics and tourist motivations and the
decision whether or not to participate in shopping and corresponding shopping
expenditures.
Method
To achieve the objectives of the study, a Heckman model was estimated in order to make a
joint analysis of characteristics related to the decision whether or not to participate in
shopping and, for those who choose to shop, characteristics related to the amount of
expenditure. Tourist motivations and tourist and trip-related characteristics were included as
explanatory variables. As previously commented, the distribution of shopping expenditures
shows a high concentration of observations at zero. This fact must be taken into account
when estimating the relationship between this variable and other explanatory variables.
In the case of shopping expenditures, the selected explanatory variables might in?uence
both the probability of a tourist deciding to shop and the amount actually spent, if he/she
decided to buy anything. If the probability of participating in shopping were the only
dynamic needed explaining, a probit analysis would provide a suitable statistical model, but
it is inef?cient to discard information relating to the value of the dependent variable when this
data are available. This is the case here, because if a tourist engaged in shopping activities,
we know how much he/she spent. If, on the other hand, there were no concentrations at a
lower limit and we only cared to explain the amount of shopping expenditure, a multiple
regression would be the appropriate statistical technique. Nevertheless, since there is a
concentration of values for the dependent variable at a certain limit (in this case at zero), OLS
estimates are biased because the dependent variable is not continuous and unbounded. A
tobit model is a hybrid of these two methods as a solution to the problem. However, in a tobit
model, the same set of variables and coef?cients determine both the probability that an
observation will be censored and the value of the dependent variable. The sample selection
or Heckman model address this shortcoming by allowing a different set of variables and
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coef?cients to determine the probability of censoring and the value of the dependent
variable, given that it is observed. These explanatory variables may overlap at a point or be
completely different.
As for shopping expenditure, tourists may or may not decide to shop but for those tourists
who participate in this activity, their amount of expenditure is observed. Thus two dependent
variables are considered. A dichotomous variable y
1
that takes a value of 1 if the tourist
participates in shopping and a value of 0 otherwise, and an outcome variable y
2
that
determines the corresponding amount of expenditure in the case of those tourists who
participate in shopping. The two-equation model comprises a selection equation for y
1
, and
a resulting outcome equation for y
2
. The error terms of both equations are possibly
correlated. If this is the case, estimating a shopping expenditure model without ?rst
estimating an equation for whether or not the tourist decides to participate in shopping would
lead to biased results. However, if the correlation between the error terms is zero, the
likelihood function can be split into two parts: a probit for the probability of the tourist
participating in shopping and an OLS regression for the expected value of expenditure on
shopping.
In the Heckman model, it is assumed that the correlated errors (1
1
and 1
2
) are jointly normally
distributed and homoskedastic:
1
1
1
2
" #
N
0
0
" #
;
1 s
12
s
12
s
2
2
" # " #
After estimating the model, the hypothesis that the two parts of the model are independent
can be tested by testing whether the correlation between the errors equals zero.
Results
The dependent variable for the selection equation was a binary variable that takes a value of
1 if the tourist participates in shopping and a value of 0 otherwise. As for the outcome
equation, the dependent variable was the logarithm of expenditure on shopping per person
per day for those tourists who spent a positive amount on shopping. Logarithms have been
taken because the scale variable cannot be assumed to be normal (see Figure 1), but when
taking logarithms, normality cannot be rejected. The skewness/kurtosis test and
Shapiro-Wilk test for normality were performed for the logarithm of shopping expenditure
and the p-value of these tests was 0.9638 and 0.3385 respectively. After estimating the
model, the likelihood-ratio test of independent equations had a p-value of 0.8067. Thus the
estimated correlation between the errors is not signi?cantly different from zero, and the
hypothesis that the two parts are independent cannot be rejected.
Initially the length of stay, group size, motivational factors, nationality, gender, age, level of
education, profession, number of previous visits, type of accommodation, inclusion or not of
children in the travel party, and services included in the package holiday were used as
independent variables for the selection equation and also for the outcome equation. Some of
these variables were not signi?cant and were excluded when the de?nitive model, shown in
Table V, was estimated. Tourist motivations in choosing the destination were included as
explanatory variables, using the four motivational factors identi?ed with the previously
presented PCA.
Table V shows the results of the estimated Heckman selection model for shopping
expenditures. Signi?cant variables in the selection equation were the nationality, level of
education, inclusion or not of children in the travel party, number of visits and some
motivational factors. The nationality, profession, number of visits, length of stay and number
of people in the travel party were all signi?cant variables in the outcome equation.
For the selection equation, the marginal effects of each explanatory variable on the
probability of participating in shopping are shown in Table V. In the Heckman model, when
an explanatory variable appears in both the selection and outcome equations, the marginal
effect on the outcome variable is not given by the coef?cient estimate itself, but rather it must
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be corrected for the selectivity effect. However, given that in this study the hypothesis that
the two parts are independent cannot be rejected, the marginal effects on the outcome
equation are equal to the estimated coef?cients.
As for the effects of the explanatory variables, with regard to the decision whether or not to
participate in shopping, British tourists have a lower probability of engaging in shopping
activities. Tourists with a post secondary school level of education are more likely to
participate in shopping. If there are children in the travel party, there is a greater probability
of shopping expenditure. The more times a tourist has visited the destination, the less likely
he/she is to participate in shopping. With regard to motivational factors, motivations related
to the basic attributes of the holiday and those related to natural and cultural attributes are
signi?cant in determining the probability of expenditure on shopping. The higher the tourist’s
level of motivation for these speci?c factors, the more likely he/she is to participate in
shopping. Other motivational factors (related to fun, a good social life and tourist facilities)
are not signi?cant in determining participation in shopping.
As for factors that affect the amount of expenditure on shopping, British tourists tend to
spend more than German tourists. In terms of the tourists’ professional status, being
self-employed has a positive effect on expenditure on shopping. As for the number of visits,
tourists who have visited the destination more than three times spend more on shopping
Table V Estimated results of the Heckman selection model
B Sig. Marginal effects
Participation in shopping
Nationality
British 20.42 0.00 20.16
German – – –
Education
Post-secondary education 0.21 0.06 0.08
Others – – –
Children in the travel party 0.27 0.00 0.10
Number of visits
First visit – –
Two or three visits 20.17 0.09 20.07
Four or more visits 20.27 0.02 20.11
Motivational factors
Basic 0.11 0.00 0.04
Nature and cultural 0.11 0.01 0.04
Constant 0.14 0.16 –
Logarithm expenditure on shopping
Nationality
British 0.49 0.00
German – –
Profession
Self-employed 0.26 0.03
Others – –
Number of visits
One to three visits – –
Four or more visits 0.24 0.01
Number of nights 20.09 0.00
Number of people 20.22 0.00
Constant 2.35 0.00
/athrho 0.08 0.80
/lnsigma 20.20 0.00
Rho 0.08
Sigma 0.81
Lambda 0.07
LR test of indep. eqns (r ¼ 0) x
2
(1)¼0.06 Prob . x
2
¼0.8067
Notes: Heckman selection model ¼ Number of observations ¼ 892; Censored observations ¼ 475;
Uncensored observations ¼ 417. Wald x
2
(5)¼121.83. Log likelihood ¼ 21098.09. Prob . x
2
¼0.000
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than other tourists. The length of stay and number of people in the travel party have a
negative effect on shopping expenditure per person per day.
According to these results, German tourists with a post secondary school level of education,
travelling with children and visiting the destination for the ?rst time, motivated by the basic
attributes of a sun and sand holiday and/or by the destination’s natural and cultural
attributes, are more likely to participate in shopping activities than other tourists. However,
when it comes to the amount of expenditure, British self-employed tourists on their fourth visit
or more tend to spend more than other tourists.
In this sense, it is worth focusing attention on the different sign of the effects of being a British
tourist and the number of visits in the two equations of the selection model. While British and
repeat visitors show a lower probability of participating in shopping activities, when they do
decide to participate, they spend more than other tourists. Therefore efforts to promote and
highlight shopping opportunities at the destination among the British and repeat visitor
markets could boost spending on shopping there.
Conclusions
The results of this study show links between shopping behaviour and certain tourist and
trip-related characteristics and motivational factors. In terms of shopping behaviour, tourists
with certain characteristics and motivations are preferable to others. For instance, being
motivated by the basic attributes of a sun and sand holiday and/or by natural and cultural
aspects of the destination, travelling with children, having a post secondary school level of
education or being self-employed are all positive characteristics in terms of shopping
behaviour. However, the results of the analysis for British tourists and repeat visitors are
contradictory. When the decision whether or not to participate in shopping is considered,
both characteristics are undesirable. However, when they decide to participate, British
tourists and visitors who are more familiar with the destination tend to spend higher amounts
on shopping. If managers at the destination want to bene?t fromthis trend, they should direct
promotional activities at the British and repeat visitor markets, trying to highlight the
shopping opportunities available at the destination and encouraging these segments to
shop.
This study also demonstrates the in?uence of tourist motivations on shopping behaviour.
Tourist motivations affect the decision whether or not to participate in shopping but not the
amount of expenditure. This ?nding provides important information in helping to target those
market segments that offer the highest potential as shoppers. In this sense, tourists primarily
motivated by the basic attributes of a sun and sand holiday and those in search of
complementary aspects, like the natural environment or cultural attractions, are more likely
to participate in shopping. Therefore promotional efforts directed at highlighting these
destination attributes can help to attract tourists that are potentially bene?cial as shoppers.
The results of this study are useful in helping to identify tourist pro?les with a different
propensity to participate in shopping, and with different levels of expenditure. This
information may be useful for destination managers interested in promoting shopping by
tourists and in increasing revenue from tourism by boosting this kind of expenditure by
holidaymakers.
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Corresponding author
Magdalena Cladera can be contacted at: [email protected]
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