Description
This study focuses on the Portuguese tourist decision process in terms of traveling to
exotic places. Based on the push-pull motive model defined by Crompton in 1979, this paper seeks to
propose an integrated approach to understand tourist motivations and how these contribute to the
perception of a destination.
International Journal of Culture, Tourism and Hospitality Research
Why people travel to exotic places
Antónia Correia Patricia Oom do Valle Cláudia Moço
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Antónia Correia Patricia Oom do Valle Cláudia Moço, (2007),"Why people travel to exotic places",
International J ournal of Culture, Tourism and Hospitality Research, Vol. 1 Iss 1 pp. 45 - 61
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Songshan (Sam) Huang, Cathy H.C. Hsu, (2009),"Travel motivation: linking theory to practice",
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dx.doi.org/10.1108/17506180910994505
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. 411-424 http://
dx.doi.org/10.1108/IJ CTHR-05-2012-0022
Sameer Hosany, Yuksel Ekinci, Muzaffer Uysal, (2007),"Destination image and destination personality",
International J ournal of Culture, Tourism and Hospitality Research, Vol. 1 Iss 1 pp. 62-81 http://
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Why people travel to exotic
places
Anto´nia Correia and Patricia Oom do Valle
Faculty of Economics, University of Algarve, Faro, Portugal, and
Cla´udia Moc¸o
University of Algarve, Faro, Portugal
Abstract
Purpose – This study focuses on the Portuguese tourist decision process in terms of traveling to
exotic places. Based on the push-pull motive model de?ned by Crompton in 1979, this paper seeks to
propose an integrated approach to understand tourist motivations and how these contribute to the
perception of a destination.
Design/methodology/approach – A structural model and a categorical principal component
analysis are used to assess to what degree motivational factors may in?uence perceptions about a
destination. The empirical study is supported through data from a sample of 1,097 individuals who
travelled by plane to exotic places, during 2004.
Findings – The ?ndings show that push and pull motivations in?uence the way tourists perceive the
destination but the resulting image does not determined the intrinsic motivations.
Research limitations/implications – The study has the restriction of being limited to the
Portuguese case. However, these ?ndings open paths for further investigation, namely extending to
other destinations and to tourists with different incentives and nationality.
Originality/value – This study contributes to the overall understanding of why tourists adopt
speci?c behaviors. In speci?c, motivations and perceptions were combined in order to understand why
people could be pushed to travel to exotic destinations and how they form their perceptions.
Keywords Travel, Motivation (psychology), Tourism, Portugal
Paper type Research paper
Introduction
Portugal is one of the most important receiving tourist destinations in Europe. The short
break holiday tradition, the low cost of living of Portuguese citizens, and the country’s
economic development explains this position. Only recently have Portuguese citizens
begun to travel abroad. Factors that account for this change are related to lower
traveling costs, shorter holiday periods and higher socio-economic conditions. This
study is a ?rst attempt to explore what stimulates travel behavior of Portuguese tourists.
Considering human, the indication would be that research into why people travel
and into what they intend to do on holidays, would generate a multiplicity of motives
related to the tourist destinations. In this sense, motivations and perceptions are
fundamental constructs in the de?nition and testing of a model that asks the question:
why do people travel to exotic places?
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1750-6182.htm
The authors acknowledge grant support from Air Luxor, SA for this study and the suggestions
of Arch Woodside.
Why people
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Received July 2005
Revised November 2005
Accepted August 2006
International Journal of Culture,
Tourism and Hospitality Research
Vol. 1 No. 1, 2007
pp. 45-61
qEmerald Group Publishing Limited
1750-6182
DOI 10.1108/17506180710729600
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Motivations are forces that in?uence and predispose to a speci?c behavior
(Dann, 1981; Pearce, 1982). In tourism research, a perception is the image of
a tourist destination that makes effective the behavior intentions (Gnoth, 1997).
Baloglu and McCleary (1999) state that perceptions about the destination are a function
of internal motivations (push motives) and external motivations (pull motives).
Each tourist has his/her own internal and external motivations to travel which lead to
different perceptions about a tourist destination.
Founded on Crompton’s (1979) push-pull motive model and supported by the
literature review, the present study proposes an integrated approach to understanding
the motivations of tourists in relation to the underlying associations between push and
pull motives and their contributions to the perception of the tourist destination as a
whole. A structural equation modeling procedure (Joreskog and Sorbom, 1986) is used
to test the theoretical model suggested. In order to further explore the links between the
push motives, pull motives and perceptions, we use a categorical principal components
analysis (CATPCA). This last statistical data analysis technique produces perceptual
maps which allow a clearer understanding of the simultaneous connections among the
observed variables considered to measure the latent constructs in the structural model.
Since, CATPCA allows a joint analysis of a set of (categorical) observed variables, this
statistical method represents a step forward in comparison with traditional correlation
measures which only focus on pairs of variables. The implications of this study are
apparent in terms of de?ning market strategies well-suited to the motivating factors
which play a strong role in the general perception of a travel destination.
The paper is organized as follows. The ?rst section provides the theoretical
framework of the study and reviews the previous literature on the models and
empirical results about the constructs of the proposed model. The following section
presents the conceptual model and de?nes the set of research hypotheses. The study
proceeds with a description of the methods which are applied, including information
about the data and statistical procedures. Results are presented and some of their
implications and limitations are discussed in the ?nal section.
Literature review
“Motivation is the need that drives an individual to act in a certain way to achieve the
desired satisfaction” (Beerli and Mart? ´n, 2004, p. 626). Many different reasons and
motives compel people to travel. These forces are perceived as being able to decrease
the condition of tension felt by the individual. The state of tension then gives way to
the necessity that encourages an action or attitude (Fodness, 1994). Although the
decision to satisfy needs may rely on other psychological variables, in reality, all
human behavior is motivated (Crompton, 1979).
Most studies looking to explain the tourist decision are based on the expectancy
value theory (Fishbein, 1967). This theory de?nes expectation as the probability that a
certain attitude will lead to positive or negative bene?ts, thus allowing the isolation of
determining factors of behavior and, furthermore, specifying how expectations and
values can be combined in order for choices to be made. The possibilities for combining
expectation with value are numerous. The motivation for adopting a certain form
of behavior is determined by the value and by the expectation for each bene?t.
The greater or lesser tendency to adopt certain behavior depends on expectations
and the consequent value of these attitudes for the individual.
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In general, the main advantages of the expectancy value theory include the following
points (Cohen et al., 1972). This theory enables the use of some of the concepts present in
the same model; allows the integration of the emotional component in tourist motivation;
the theory can incorporate all the reasons for travelling put forward in the studies on
motivation; the expectancy value theory also enables the resolution of the problem of
“push” and “pull” factors, as well as the evaluation of personality; the theory allows a
more realistic and sophisticated view of tourist motivation.
Most tourism literature on the factors behind the tourist decision has focused on a
single motivational construct, whether it be cognitive or emotional (Gnoth, 1997;
McCabe, 2000). Research focusing fundamentally on cognitive aspects does not
consider the relations between these factors and emotional aspects. In this ?eld
empirical evidence is lacking.
The existence of internal and external factors which motivate human behavior is
assumed by several authors. Kotler (1982), for instance, states that motivations can be the
result of internal and external stimuli. Internal stimuli arise from personal needs that can
be physiological, social, egocentric, safety and self-actualization. External stimuli result
from publicity and promotion. Motivations around traveling can be personal (personal
training, compensation, rest and knowledge) and interpersonal (resulting from the social
relations) (Crompton, 1979; Dann, 1977; Yoon and Uysal, 2005). Dann (1977) classi?es
personal motives as those that predispose the individual for traveling: escape from daily
routines, the desire to escape fromsolitude. According to this study, interpersonal motives
arise fromthe need to seek some formof social recognition that is obtained through travel.
Crompton (1979) refers to more speci?c and direct motives that can direct the tourist
in his/her decision about the type of holiday or the travel destination. Psychological or
social motives (push motives) which sustain the desire to travel are identi?ed by the
author. On the other hand, pull motives affect the travel decision and are associated to
the destination’s characteristics (Lundberg, 1990). Gnoth (1997) states that the
necessity for holidays depends on desires such as self actualization, sense of
self-esteem and social status. In the last case, the tourist produces his/her perceptions
in accordance to his/her social group. In this sense, Cohen (1972) introduces
sociological motives which direct the tourist to a socially accepted behavior.
Based on intrinsic and extrinsic motivations, the tourist builds his/her perceptions
(Gartner, 1993; Dann, 1996; Baloglu, 1997). Perceptions can be different from the true
attributes of the product depending on how the individual receives and processes
information. In other words, perceptions focus on the attributes of products that affect
behavior and not on the real attributes of products (Dann, 1981; Pearce, 1982).
According to Morrison (1989), perceptions are a cognitive measure of tourism
destination value. This value represents the opportunity cost of the product (value for
money), that is, that perceptions are formed based on a cost bene?t assessment.
Gnoth (1997) reports that the perception of a destination may be analysed from a
cognitive or behavioral perspective. This author argues that perceptions are of several
types: they can have a cognitive component (which results from the evaluation of the
destination attributes) and a personal component (that depends on how the individual
intends to perceive that destination). The cognitive structure comprises the shaping of
a perception represents of internal and external stimuli into the “awareness set” which
is, in fact, a cognitive structure (Woodside and Lysonski, 1989; Crompton, 1979).
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A general conclusion can be drawn that personal motives (push motives), as well as
the view of the characteristics of the tourism destination (pull motives), determine
perceptions. These motives interact in a dynamic and evolving context (Correia, 2000).
From another point of view, the tourist motivation should be seen as a
multidimensional concept which explains the tourist decision (McCabe, 2000).
Most of the studies on motivations and perceptions formation rely on multivariate
methods that allow us to determine multidimensional structures. The techniques more
often applied are factor analysis, multidimensional scaling, principal components
analysis (PCA), segmentation procedures, correlational tests, ANOVAS and
MANOVAS.
Formation of perceptions, from a conceptual point of view, is presented by Kim and
Yoon (2003) and also by Vogt and Andereck (2003). These authors propose structural
equation models which look to analyse how emotions and cognitions can in?uence
tourist destination perceptions. Seddighi and Theocharous (2002) use a conditional
logit model to measure the perceptions/feelings about the characteristics of tourist
destination. From this methodology, the authors detected the probabilities of revisiting
a travel destination. Murphy et al. (2000) de?ne a structural model that relates the
tourist intention to return (as a proxy of satisfaction/quality) with his/her perceptions
of the travel experience.
In general, these models combine motivations, expectations and choice and are
estimated by using regressions techniques and structural models. Despite the power of
these analyses, nothing has been done in order to deeply evaluate the relationships
among the observed variables in the proposed models, which can be done by observing
the graphical displays provided by CATPCA. The conceptualized model in the
following section incorporates insights from the literature review. The objective of this
study is to develop and test a structural equation model of overall perception of the
exotic destinations which is a function of perceptions and motivations, in a cognitive
and emotional perspective. Perceptual maps via CATPCA complement the conclusions
from applying the proposed model.
Theoretical model and hypotheses
Figure 1 shows the hypothetical causal model that proposes interactions among the
constructs of motivations and perceptions. The choice of each component of the model
was based on the literature review. The model’s contribution depends upon the
Figure 1.
Proposed hypothetical
model
H
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Perceptions
Push motives
Pull motives
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identi?cation of the relationship between the two constructs of motivation (push and
pull motives).
The hypotheses presented in the conceptual model, which will be tested in this
study, are the following:
H1. Push motives lead to different pull motives.
McCabe (2000) shows that the relationship between push and pull factors is the result of
a sequential decision. Firstly, a tourist decides to travel depending on his/her emotional
state (push-motives). Next, the tourist determines the place to visit and related activities
(pull-motives). These choices are a function of push motives that determine the decision
to travel. More speci?cally, Russel and Pratt (1980) suggest that the attributes of the
destination are perceived by their ability to achieve affective motives:
H2. The overall perception of the destination depends on the evaluation of the pull
motives.
According to Murphy et al. (2000), positive perceptions about a destination are related
to a positive summary evaluation of tourist destination attributes:
H3. Different push motives lead to different perceptions.
Choy (1992) and Murphy and Pritchard (1997) ?nd that more than the infrastructures
of a tourist destination, emotional states affect the perceptions regarding that
destination. In the same way, Beerli and Mart? ´n (2004) conclude that the emotional
motives directly in?uence the affective perceptions of the destination.
Method
Survey and sample
A survey was developed in order to test the proposed hypotheses. The survey includes
three sections: the ?rst one tries to measure the push motives that may lead the tourist to
the decision to travel. The second section presents the rate of destination attributes and
landscape features (i.e. the pull motives) whichrepresent what the tourist intends to do at
the exotic destinations. The latter section considers the overall level of perceptions.
The set of push and pull motives considered in this work is the most quoted on
literature (Uysal et al., 1996; Iso-Ahola and Mannel, 1987; Lundberg, 1990; Fodness, 1994;
Holden, 2003; Mohsin and Ryan, 2003; Shoemaker, 1989; Cossens, 1989). Speci?cally, the
following push motives were included: “relieving stress,” “escaping from the routine,”
“physical relaxing,” “doing different things,” “stimulating emotions and sensations,”
“beingan adventurer,” “having fun,” “increasing knowledge,” “knowingdifferent cultures
and lifestyles,” “enriching myself intellectually,” “knowing new places,” “meeting
interesting people,” “developing close friendships,” “going places my friends have not
been,” “talking with my friends about the trip.” Pull factors considered were the following:
“landscape,” “natural environment,” “cultural attractions,” “night-life,” “sports
equipment,” “transport,” “lodging,” “weather,” “accessibility,” “beaches,” “gastronomy,”
“security,” “distance,” “shopping facilities,” “relaxing atmosphere,” “social environment,”
“hospitality,” “different ethnics,” “standard of living.”
As Maio and Olson (1994) propose, push and pull motives, as well as perceptions, were
assessed by a seven point Likert-type scale. This scale ranged from “not important” (1) to
“extremely important” (7) concerning motives and from “very low” (1) to “very high” (7)
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regarding perceptions. Owing to sampling convenience, the study took place on ?ights to
the destination. The ?ights were onAir Luxor, SA, a Portuguese air travel companywhich
has a signi?cant market share as a tour operator.
A pre-test of the survey with a sample of 150 tourists enhances the validity and
reliability of the questionnaire. After the pre-test, which resulted in only minor
amendments, a sample of 1,097 Portuguese tourists was taken on ?ights to exotic
places (such as, Brazil, Morocco, Egypt, Mexico, Sao Tome and Principe) during
August and September, 2004. These are the months during which most Portuguese
citizens have holidays. Respondents were invited to participate in the survey and asked
to ?ll out the survey during the ?ight, and just before arriving at the airport.
As reported in Table I, the larger proportion of respondents are married, have high
level education, average age of 35 and belong to social middle class (Table I).
Statistical data analysis method
Three main stages of statistical data analysis follow in this report. The ?rst stage
entails the reduction of the data through the application of PCA to the set of push and
pulls motives. To assess the pertinence of using PCA in this research, the
Kaiser-Meyer-Olkin (KMO) statistic was computed and the Bartlett test was performed
(Bartlett, 1947). The reliability of the obtained factors was measured by a Cronbach’s
coef?cients (Cronbach, 1951). This analysis was carried out with statistical package for
the social sciences (SPSS) software, version 12.
A structural equation model was estimated in the second stage in order to assess the
underlined research hypotheses. The factors obtained with PCA were used as
indicators of the constructs push and pull motives. The model was estimated with the
software analysis of moment structures (AMOS 5) (Arbuckle and Wothke, 1999) and
the weighted least squares estimation method was applied. This is an asymptotically
distribution-free method, which is not sensitive to the non-normality of the data. The
model ?t was evaluated by following the approach suggested by Hair et al. (1998),
Socio-demographic characteristics Percent
Gender
Male 48.6
Female 51.4
Age (mean) 35.4 years old
Educational level
4 years 8.7
6 years 12.2
9 years 7.3
12 years 29.7
College 42.0
Family
Single 30.6
Married 64.8
With children 17.0
Social class
High 25.0
Medium 26.3
Medium/low 48.8
Table I.
Sample characteristics
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which ?rst requires the assessment of the overall model ?t and then the measurement
and structural models individually.
Measures of overall model ?t include absolute, incremental and parsimonious ?t
measures. The x
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goodness-of-?t test is the best known index of absolute ?t. However,
this index is quite sensitive in large samples, showing signi?cant differences between
the covariance matrices in any proposed model (Garc? ´a and Martinez, 2000). Therefore,
besides the x
2
test, the goodness of ?t index (GFI) (Joreskog and Sorbom, 1986), the
root mean square residual (RMSR) and the root mean square residual of approximation
(RMSEA) (Steiger, 1990) were used to evaluate the proposed model’s overall absolute
?t. Six incremental ?t measures were used to evaluate the proposed model’s ?t: the
adjusted goodness of ?t index (AGFI) (Joreskog and Sorbom, 1986), the normed ?t
index (NFI) (Bentler and Bonnet, 1980), the Tucker and Lewis index (TLI) (Tucker and
Lewis, 1973) and the incremental ?t index (IFI) (Bollen, 1988), the relative ?t index
(RFI) (Bollen, 1986) and the comparative ?t index (CFI) (Bentler, 1990). Parsimonious ?t
was measured by the normed x
2
(Joreskog, 1969) that should range from 1 to 5.
Excluding RMSR and RMSEA, in which smaller values are better (zero indicates
perfect ?t) all other measures and indexes range from 0 (no ?t) to 1 (perfect ?t).
In evaluating the measurement model, each latent variable was assessed separately
through examining the standardized loading, the construct reliability and the variance
extracted. In analyzing the structural model ?t, parameter estimates were examined in
relation to their sign and statistical signi?cance. Standardized estimates are useful in
comparing the parameters’ effect throughout the model since they remove scaling
information. All proposed hypotheses were tested by observing the statistical
signi?cance of the corresponding paths in the structural model.
The ?nal stage involved focusing on the relationship between push factors, pull
factors and perceptions. The analysis began by recoding these variables in order to
obtain categorical variables. Then, through the application of a CATPCA, it was
possible to explore the nature of these relationships. This method allows us to
represent the various relationships of categorical variables in a low-dimensional space,
also known as a perceptual map. In this sense, CATPCA can make data interpretation
easier since the relative positions of categories on this map represent the relations
among them. Categories with similar distributions are represented as points on the
map and the proximities means that they are associated. On the contrary, categories
with quite different distributions will be positioned far apart on the map, suggesting
that they are not related. Thus, in this study, the perceptual maps depicting the
relationships among push and pull factors, push factors and perceptions and, lastly,
pull factors and perceptions, were presented. These maps complete the analyses
provided by the structural equation model since they allow a detailed evaluation of the
relations among each pull and push factor and perceptions. As PCA, this analysis was
carried out with SPSS, 12.
Results
Principal components analysis
Push factors. The reduction of the initial 15 push motives into three new factors,
together accounting for 68.4 percent of the total variance (KMO ¼ 0.9; Bartlett test:
p ¼ 0.05), was obtained through PCA. These ?ndings are presented in Table II.
Considering the meaning of the motives with higher loadings, the push factors were
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labelled knowledge, leisure and socialization. The internal consistency of these factors
was measured by the corresponding Cronbach’s a coef?cients (they exceed 0.8 in all
cases).
Knowledge is the ?rst factor and is speci?cally related to the need to explore new
cultures and places as well as to do and learn new things. In the Leisure factor the
principal motives are connected to personal well-being. The third factor, socialization,
is primarily the desire to share travel experiences, develop close friendships and go to
destinations not yet visited by friends.
Table II also shows the mean importance level of each push motive. The importance
ranking was based on the mean scores on the Likert seven-point scale. These results
are in accordance with the push motives determined in previous research (Sefton, 1989;
Loundsbury and Franz, 1990; Pearce, 1988; Laing, 1987; Smith, 1991). Most of these
studies are based on the leisure motivation scale of Beard and Raghep (1983) and show
that the main push motivations to travel are related to intellectual motives (learning,
exploring, discovering), social motives (friendship and interpersonal relationships,
need for esteem of the others) and relaxation motives (escape from daily routine,
get-away).
Pull factors. Table III presents results fromthe application of PCAto the nineteen pull
motives. As with push motives, three new factors were extracted, together accounting
for 63.5 percent of the total variance (KMO ¼ 0.9; Bartlett test: p ¼ 0.0). Pull factors
were labelled facilities, core attractions and landscape features. Cronbach’s a for these
factors also exceeds 0.8, indicating an adequate degree of internal consistency.
Facilities of the travel destination such as lodging, weather, food, security, roads
and hospitality are included in the facilities factor. Motives related to the social
environment, shopping facilities, sports activities and night life are encompassed by
the second factor, core attractions. Landscape features is the last pull factor and is
linked to the natural and cultural environment of the holiday destination.
Push motives and factor Loadings
Percent
variance explained
Reliability
(a Cronbach) Mean Rank
Knowledge
Do different things 0.7 5.9 7
Stimulate emotions and sensations 0.6 5.4 10
Be an adventurer 0.6 5.2 11
Have fun 0.7 6.0 4
Increase knowledge 0.8 33.4 1.0 5.9 6
Know different cultures and lifestyles 0.8 5.1 13
Enriching myself intellectually 0.8 5.8 8
Know new places 0.8 6.0 3
Find interesting people 0.6 5.4 9
Leisure
Relieving stress 0.8 6.1 2
Escape from the routine 0.8 18.7 0.9 6.1 1
Relaxing physically 0.8 5.9 5
Socialization
Developing close friendships 0.6 5.1 12
Going places my friends have not been 0.9 16.3 0.8 3.7 15
Talking with my friends about the trip 0.9 4.1 14
Table II.
Principal components of
push motives (after
varimax rotation), means
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The last two columns of Table III prove that the social and sports motives are the least
important in choosing a tourist destination. Inversely, the natural and regional
component clearly determines the destination image. This especially includes natural
environment, weather, beaches and hospitality and can be considered as an indicator of
how the natural resources of a tourist destination were perceived as competitive factors
par excellence. These results are also in accordance to previous studies in the ?eld
which have been quoted above.
However, despite the fact that these studies have provided important contributions
in order to de?ne push and pull motivations, they do not examine the interactions
among them (Ryan and Glendon, 1998). Yoon and Uysal (2005) state that inherent push
motivations are stimulated and reinforced by destination attributes. Sequentially,
different perception levels of a tourist destination are expected to result from different
combinations of push and pull factors.
Structural equation model
Examining the nature of the relationships among push and pull factors and overall
perceptions of the destination includes estimating the structural equation model
proposals in Figure 1. Figure 2 shows the estimated standardized path coef?cients on
the model itself. The values for the selected overall ?t measures are reported in
Table IV. As expected due to the large sample size, the observed value for the x
2
statistic is high and statistically signi?cant, suggesting that the observed and
predicted covariance matrices are not equal. In considering the dependence of the
x
2
-test on the sample size, the evaluation of the absolute ?t of the model relied on
Items and principal components Loadings
Percent variance
explained
Reliability
(a Cronbach) Mean Rank
Facilities
Weather 0.8 5.8 2
Lodging 0.7 5.1 7
Beaches 0.7 5.7 4
Hospitality 0.7 26.4 0.9 5.5 5
Gastronomy 0.7 4.8 11
Security 0.7 4.7 13
Relaxing atmosphere 0.7 5.3 6
Accessibilities 0.6 4.6 14
Core attractions
Standard of living 0.7 3.3 19
Different ethnics 0.7 4.8 10
Distance 0.7 4.4 17
Shopping facilities 0.7 23.3 0.9 4.7 12
Sports equipment 0.7 4.4 16
Social environment 0.6 4.9 9
Night-life 0.6 4.5 15
Transports 0.6 4.3 18
Landscape features
Landscape 0.8 5.7 3
Natural environment 0.8 13.9 0.9 5.8 1
Cultural attractions 0.7 5.0 8
Table III.
Principal components of
pull motives items (after
varimax rotation)
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the other absolute measures, which are very high. The proposed model also presents
high values for the remaining measures, suggesting an adequate incremental and
parsimonious ?t.
A measurement model analysis follows the analysis. This model could be improved
if all the observed variables had signi?cant loadings in corresponding latent variables.
This was true for all indicators except for Leisure ( p . 0.05). On the other hand, the
constructs reliability and variance extracted for the latent variables push motives and
pull motives do not exceed the desirable levels of 0.7 and 0.5, respectively. Owing to
these results, the model was re-estimated by excluding the indicator leisure. The results
of this model, concerning the GFI and the standardized loadings, were essentially the
same but the measurement model has clearly improved. For this reason, we decided to
go on considering the model as had been proposed initially.
Figure 2 also shows that two speci?ed paths between the constructs are statistically
signi?cant which supports only research hypotheses H1 and H2. The same results,
with similar path estimates, were obtained in the restricted model: H1 and H2 are still
supported by the data and H3 is rejected.
Categorical principal components analysis
In order to simultaneously analyze the relationship among each push factor, pull factor
and perceptions, these variables were transformed into categorical variables. Table V
shows the relative distribution of respondents by the categories of the new variables.
Figure 2.
Standardized estimates of
proposed model
Note: (*) p < 0.01
-0.31
H1
H2
H3
0.80 (*)
0.81 (*)
0.36 (*) 0.41 (*) 0.77 (*)
0.69 (*)
0.02
0.52 (*)
0.34 (*)
0.80
0.78 0.87 0.40
0.72
0.96
0.50
Pull motives
Perceptions
Socialization
Knowledge
Leisure
Facilities
Core
attractions
Landscape
features
Push motives
Perceptions
Absolute ?t measures Incremental ?t measures Parsimonious ?t measures
x
2
¼ 22.23 ( p ¼ 0.008) AGFI ¼ 0.98 Normed x
2
¼ 2.47
RMSR ¼ 0.038 NFI ¼ 0.97
RMSEA ¼ 0.046 TLI ¼ 0.96
IFI ¼ 0.98
RFI ¼ 0.93
CFI ¼ 0.98
Table IV.
Goodness-of-?t indices
for the estimated
structural model
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Having transformed the pull and push factors into ordinal variables, the study
includes applying CATPCA to complement the evaluation that the structural equation
model provides. CATPCA helps to deeply analyze the relationship between push and
pull categorized factors and, afterwards, to relate pull factors and perceptions. The
decision was made not to present the perceptual map connecting push factors and
perception because the estimated model showed a non-signi?cant relationship between
these constructs.
Figure 3 shows the combination of categories of each pull factor with categories of
each push factor through a perceptual map. As can be observed, high valorization of
pull factors (represented by the full lines) is related with high valorization of push
factors (represented by the broken lines) and vice-versa. This map also suggests which
push and pull factors are strongly related, which was not detected with the structural
equation model: socialization and knowledge are particularly related to facilities;
leisure is specially associated to core attractions.
Figure 4 shows a similar analysis but in what concerns the connections between
perceptions and pull factors. The relationship appears to be more fragile than the one
Figure 3.
Joint plot of category
points for push and pull
factors
?1.5 ?1.0 ?0.5 0.0 0.5 1.0
Dimension 1
?0.6
?0.3
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LM
H
Knowledge
Socialization
Leisure
Facilities
Core
attractions
Landscape
features
L - Low valorization
M - Medium valorization
H – High valorization
Motives and perceptions
Low valorization
(L)
(percent)
Medium valorization
(M)
(percent)
High valorization
(H)
(percent)
Total
(percent)
Knowledge 19.7 55.1 25.2 100
Leisure 13.3 56.8 29.9 100
Socialization 48.9 32.0 19.0 100
Facilities 16.0 58.9 25.0 100
Core attractions 13.0 56.8 30.2 100
Landscape features 9.6 55.9 34.5 100
Perceptions 43.1 56.9 – 100
Table V.
Relative distribution of
respondents by the
categories of the
variables
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previously reported between pull and push factors. As can be observed on the
perceptual map, landscape features is the pull factor least related to perceptions and
there is also a very similar connection between perceptions and facilities, on the one
hand, and perceptions and core attractions on the other hand.
Discussion and managerial implications
The theoretical model proposals offer a logical sequence of the formation of tourist
perceptions. The empirical study proves that perceptions of tourism destinations are
formed based on push and pull factors. The study supports the view that all
destination attributes contribute to the perceived image of the destination. The
formation of perceptions seems to happen in the following sequence: push factors are
determinants of pull factors which, in turn, explain perceptions.
In the model, the relationship between push factors and perceptions is not signi?cant,
and that proves that the tourist decides to go on holiday because he/she needs to solve a
con?ict arousal (rest, social and intellectual rewards). Then, he/she decides where to go
based on the destination attributes. The destination attributes (pull motives) are
perceived as the way to solve intrinsic motives (push motives), but these constructs
are not directly related to the overall perception of the destination because they are
apparently solved when the tourist turns her/his attention to speci?c attributes. Figure 3
also supports the view that a high valorization of all pull factors is associated to a high
valorization of all push factors. This evidence depends upon the very essence of humans’
nature. Humans are continuously seeking and solving problems, with different levels of
involvement with the decision. This conclusion also stresses the need for testing the
inclusion of emotions and learning as constructs of the theoretical model.
Looking deeply into the factors identi?ed for the pull and push attributes, this study
proved that knowledge and socialization are the major motives which cause the need to
Figure 4.
Joint plot of category
points for pull factors and
perceptions
L - Low valorization
M - Medium valorization
H– High valorization
?1.0 ?0.5 0.0 0.5 1.0
Dimension 1
?1.0
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L M H
Perceptions
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Landscape
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travel abroad. This evidence is in accordance to Oppermann (1996), who stresses that
travelling to unknown places (and this is the case of exotic places) gives rise to a
variety seeking behavior, looking for social and intellectual rewards. Similarly, Gnoth
(1997) highlights the difference between social trip and a variety seeking trip. While the
?rst one represents the choice of a fashionable exotic resort, the second one is more
related to savage and unexplored environments. So, the social trip is more associated to
social status, self esteem and sense of belonging. The variety seeking trip is related
to adventure and intellectual rewards.
The destination attributes highlighted by the PCA represent the core tourism
product: facilities, core attractions and landscape features. Figure 4 shows that the
facilities factor is the prior motive that contributes to overall perception. Although
knowledge is one of the major push motives which generally determine the choice of an
exotic destination, tourists assume that these places abound in landscape and scenic
aspects and so they do not look for much information about these aspects (they are
assumed to be intrinsic characteristics of the destination).
Considering the correlation between push and pull motives that Figure 3 shows,
socialization and knowledge, the more reliable push motives in the structural model,
stimulate the mind of the tourist for the need for attributes related to the facilities of the
destination. The tourist who decides to travel in order to increase his/her knowledge
would be expected to reveal more concern about the landscape features and sport
activities. In turn, the tourist who travels in order to increase his/her social status
would rank higher facilities and core attractions. However, the empirical results prove
that the tourist who travels due to intellectual or social rewards decides where to go
based on facilities. Even though this result could seem strange, the result reveals that
tourists are conscious that they are traveling to destinations where human and social
development is low and, therefore, main concerns turn to where they will sleep, eat as
well as to how they will travel throughout the destination. This is an issue that needs
more research.
Still concerning the relationship between push and pull motives, Figure 3 shows
that leisure is mainly correlated with core attractions. This result can also seem strange
if rest and relaxation are perceived in a physical perspective. Portuguese tourists seem
to understand rest and relaxation from a different point of view: relaxation and rest
does not mean “doing nothing” but, instead, “doing different things.” In this sense, in
the case of Portuguese tourists, the statement that leisure is more mental than physical
can be made.
The major ?ndings of this study have signi?cant managerial implications for
destination marketing. Firstly, the exploratory analysis shows that the decision to travel
to exotic places arises fromthe desire of knowledge, having social status and intellectual
leisure and also that these factors determine the perceived pull motives: facilities, core
attractions and landscape features. Since, tourists were found to be more aware of
facilities and core attractions, marketing of these destinations must be especially
focused on these factors rather than on beautiful images of natural landscapes. These
empirical results could be fundamental in order to direct and target the destination
marketing strategy to enhance the overall perception of these exotic places.
Secondly, special attention must be given to the type of activities which are
offered to tourists. Even tourists who simply want to relax do not relate leisure to
“doing nothing.” According to the structural model and CATPCA analyses, social and
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intellectual rewards are in?uencing factors in what pertains to the demand for exotic
destinations. The offering of appropriate activities and attractions to the right tourists
may be the result of the knowledge gained through identifying why people travel the
way they do. These results indicate that marketers and managers of exotic destinations
should concentrate on improving push factors in order to enhance the destination’s
competitiveness.
Thirdly, CAPTCA results suggest two levels of awareness in what concerns the
perception of an exotic location: one with tourists who are highly involved and the
other with tourists who are only moderately involved. To avoid dissatisfaction at
the end of the trip the latter group should receive special attention from destination
managers.
Conclusions
This study contributes to the overall understanding of why tourists behave the way
they do from four different perspectives. First, despite the number of models which had
considered the relations between push and pull motives, the inclusion of perceptions in
the theoretical model is a reason to believe that this research provides a step forward in
literature. Second, this was the ?rst time that structural equation modelling and
CATPCA were put together in order to prove the relationships between push, pull
motives and overall perceptions. Third, only now has the outbound Portuguese tourist
market been studied at a more scienti?c level. Lastly, this was the ?rst time that
motivations and perceptions were combined in order to understand why people could
be pushed to travel to exotic destinations and how they form their perceptions.
Empirical evidence in this study opens paths for further investigation. The study
does have some limitations, however, the main one being the domain which can be
considered as restricted. Generalizing the model is an important step to better
understand tourist behavior. Extending the study using other destinations and
attributes, and tourists with different incentives would be a useful step.
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destination loyalty: a structural model”, Tourism Management, Vol. 26 No. 1, pp. 45-56.
Corresponding author
Anto´nia Correia can be contacted at: [email protected]
Why people
travel to exotic
places
61
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doc_801141555.pdf
This study focuses on the Portuguese tourist decision process in terms of traveling to
exotic places. Based on the push-pull motive model defined by Crompton in 1979, this paper seeks to
propose an integrated approach to understand tourist motivations and how these contribute to the
perception of a destination.
International Journal of Culture, Tourism and Hospitality Research
Why people travel to exotic places
Antónia Correia Patricia Oom do Valle Cláudia Moço
Article information:
To cite this document:
Antónia Correia Patricia Oom do Valle Cláudia Moço, (2007),"Why people travel to exotic places",
International J ournal of Culture, Tourism and Hospitality Research, Vol. 1 Iss 1 pp. 45 - 61
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Songshan (Sam) Huang, Cathy H.C. Hsu, (2009),"Travel motivation: linking theory to practice",
International J ournal of Culture, Tourism and Hospitality Research, Vol. 3 Iss 4 pp. 287-295 http://
dx.doi.org/10.1108/17506180910994505
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. 411-424 http://
dx.doi.org/10.1108/IJ CTHR-05-2012-0022
Sameer Hosany, Yuksel Ekinci, Muzaffer Uysal, (2007),"Destination image and destination personality",
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Why people travel to exotic
places
Anto´nia Correia and Patricia Oom do Valle
Faculty of Economics, University of Algarve, Faro, Portugal, and
Cla´udia Moc¸o
University of Algarve, Faro, Portugal
Abstract
Purpose – This study focuses on the Portuguese tourist decision process in terms of traveling to
exotic places. Based on the push-pull motive model de?ned by Crompton in 1979, this paper seeks to
propose an integrated approach to understand tourist motivations and how these contribute to the
perception of a destination.
Design/methodology/approach – A structural model and a categorical principal component
analysis are used to assess to what degree motivational factors may in?uence perceptions about a
destination. The empirical study is supported through data from a sample of 1,097 individuals who
travelled by plane to exotic places, during 2004.
Findings – The ?ndings show that push and pull motivations in?uence the way tourists perceive the
destination but the resulting image does not determined the intrinsic motivations.
Research limitations/implications – The study has the restriction of being limited to the
Portuguese case. However, these ?ndings open paths for further investigation, namely extending to
other destinations and to tourists with different incentives and nationality.
Originality/value – This study contributes to the overall understanding of why tourists adopt
speci?c behaviors. In speci?c, motivations and perceptions were combined in order to understand why
people could be pushed to travel to exotic destinations and how they form their perceptions.
Keywords Travel, Motivation (psychology), Tourism, Portugal
Paper type Research paper
Introduction
Portugal is one of the most important receiving tourist destinations in Europe. The short
break holiday tradition, the low cost of living of Portuguese citizens, and the country’s
economic development explains this position. Only recently have Portuguese citizens
begun to travel abroad. Factors that account for this change are related to lower
traveling costs, shorter holiday periods and higher socio-economic conditions. This
study is a ?rst attempt to explore what stimulates travel behavior of Portuguese tourists.
Considering human, the indication would be that research into why people travel
and into what they intend to do on holidays, would generate a multiplicity of motives
related to the tourist destinations. In this sense, motivations and perceptions are
fundamental constructs in the de?nition and testing of a model that asks the question:
why do people travel to exotic places?
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1750-6182.htm
The authors acknowledge grant support from Air Luxor, SA for this study and the suggestions
of Arch Woodside.
Why people
travel to exotic
places
45
Received July 2005
Revised November 2005
Accepted August 2006
International Journal of Culture,
Tourism and Hospitality Research
Vol. 1 No. 1, 2007
pp. 45-61
qEmerald Group Publishing Limited
1750-6182
DOI 10.1108/17506180710729600
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Motivations are forces that in?uence and predispose to a speci?c behavior
(Dann, 1981; Pearce, 1982). In tourism research, a perception is the image of
a tourist destination that makes effective the behavior intentions (Gnoth, 1997).
Baloglu and McCleary (1999) state that perceptions about the destination are a function
of internal motivations (push motives) and external motivations (pull motives).
Each tourist has his/her own internal and external motivations to travel which lead to
different perceptions about a tourist destination.
Founded on Crompton’s (1979) push-pull motive model and supported by the
literature review, the present study proposes an integrated approach to understanding
the motivations of tourists in relation to the underlying associations between push and
pull motives and their contributions to the perception of the tourist destination as a
whole. A structural equation modeling procedure (Joreskog and Sorbom, 1986) is used
to test the theoretical model suggested. In order to further explore the links between the
push motives, pull motives and perceptions, we use a categorical principal components
analysis (CATPCA). This last statistical data analysis technique produces perceptual
maps which allow a clearer understanding of the simultaneous connections among the
observed variables considered to measure the latent constructs in the structural model.
Since, CATPCA allows a joint analysis of a set of (categorical) observed variables, this
statistical method represents a step forward in comparison with traditional correlation
measures which only focus on pairs of variables. The implications of this study are
apparent in terms of de?ning market strategies well-suited to the motivating factors
which play a strong role in the general perception of a travel destination.
The paper is organized as follows. The ?rst section provides the theoretical
framework of the study and reviews the previous literature on the models and
empirical results about the constructs of the proposed model. The following section
presents the conceptual model and de?nes the set of research hypotheses. The study
proceeds with a description of the methods which are applied, including information
about the data and statistical procedures. Results are presented and some of their
implications and limitations are discussed in the ?nal section.
Literature review
“Motivation is the need that drives an individual to act in a certain way to achieve the
desired satisfaction” (Beerli and Mart? ´n, 2004, p. 626). Many different reasons and
motives compel people to travel. These forces are perceived as being able to decrease
the condition of tension felt by the individual. The state of tension then gives way to
the necessity that encourages an action or attitude (Fodness, 1994). Although the
decision to satisfy needs may rely on other psychological variables, in reality, all
human behavior is motivated (Crompton, 1979).
Most studies looking to explain the tourist decision are based on the expectancy
value theory (Fishbein, 1967). This theory de?nes expectation as the probability that a
certain attitude will lead to positive or negative bene?ts, thus allowing the isolation of
determining factors of behavior and, furthermore, specifying how expectations and
values can be combined in order for choices to be made. The possibilities for combining
expectation with value are numerous. The motivation for adopting a certain form
of behavior is determined by the value and by the expectation for each bene?t.
The greater or lesser tendency to adopt certain behavior depends on expectations
and the consequent value of these attitudes for the individual.
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In general, the main advantages of the expectancy value theory include the following
points (Cohen et al., 1972). This theory enables the use of some of the concepts present in
the same model; allows the integration of the emotional component in tourist motivation;
the theory can incorporate all the reasons for travelling put forward in the studies on
motivation; the expectancy value theory also enables the resolution of the problem of
“push” and “pull” factors, as well as the evaluation of personality; the theory allows a
more realistic and sophisticated view of tourist motivation.
Most tourism literature on the factors behind the tourist decision has focused on a
single motivational construct, whether it be cognitive or emotional (Gnoth, 1997;
McCabe, 2000). Research focusing fundamentally on cognitive aspects does not
consider the relations between these factors and emotional aspects. In this ?eld
empirical evidence is lacking.
The existence of internal and external factors which motivate human behavior is
assumed by several authors. Kotler (1982), for instance, states that motivations can be the
result of internal and external stimuli. Internal stimuli arise from personal needs that can
be physiological, social, egocentric, safety and self-actualization. External stimuli result
from publicity and promotion. Motivations around traveling can be personal (personal
training, compensation, rest and knowledge) and interpersonal (resulting from the social
relations) (Crompton, 1979; Dann, 1977; Yoon and Uysal, 2005). Dann (1977) classi?es
personal motives as those that predispose the individual for traveling: escape from daily
routines, the desire to escape fromsolitude. According to this study, interpersonal motives
arise fromthe need to seek some formof social recognition that is obtained through travel.
Crompton (1979) refers to more speci?c and direct motives that can direct the tourist
in his/her decision about the type of holiday or the travel destination. Psychological or
social motives (push motives) which sustain the desire to travel are identi?ed by the
author. On the other hand, pull motives affect the travel decision and are associated to
the destination’s characteristics (Lundberg, 1990). Gnoth (1997) states that the
necessity for holidays depends on desires such as self actualization, sense of
self-esteem and social status. In the last case, the tourist produces his/her perceptions
in accordance to his/her social group. In this sense, Cohen (1972) introduces
sociological motives which direct the tourist to a socially accepted behavior.
Based on intrinsic and extrinsic motivations, the tourist builds his/her perceptions
(Gartner, 1993; Dann, 1996; Baloglu, 1997). Perceptions can be different from the true
attributes of the product depending on how the individual receives and processes
information. In other words, perceptions focus on the attributes of products that affect
behavior and not on the real attributes of products (Dann, 1981; Pearce, 1982).
According to Morrison (1989), perceptions are a cognitive measure of tourism
destination value. This value represents the opportunity cost of the product (value for
money), that is, that perceptions are formed based on a cost bene?t assessment.
Gnoth (1997) reports that the perception of a destination may be analysed from a
cognitive or behavioral perspective. This author argues that perceptions are of several
types: they can have a cognitive component (which results from the evaluation of the
destination attributes) and a personal component (that depends on how the individual
intends to perceive that destination). The cognitive structure comprises the shaping of
a perception represents of internal and external stimuli into the “awareness set” which
is, in fact, a cognitive structure (Woodside and Lysonski, 1989; Crompton, 1979).
Why people
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A general conclusion can be drawn that personal motives (push motives), as well as
the view of the characteristics of the tourism destination (pull motives), determine
perceptions. These motives interact in a dynamic and evolving context (Correia, 2000).
From another point of view, the tourist motivation should be seen as a
multidimensional concept which explains the tourist decision (McCabe, 2000).
Most of the studies on motivations and perceptions formation rely on multivariate
methods that allow us to determine multidimensional structures. The techniques more
often applied are factor analysis, multidimensional scaling, principal components
analysis (PCA), segmentation procedures, correlational tests, ANOVAS and
MANOVAS.
Formation of perceptions, from a conceptual point of view, is presented by Kim and
Yoon (2003) and also by Vogt and Andereck (2003). These authors propose structural
equation models which look to analyse how emotions and cognitions can in?uence
tourist destination perceptions. Seddighi and Theocharous (2002) use a conditional
logit model to measure the perceptions/feelings about the characteristics of tourist
destination. From this methodology, the authors detected the probabilities of revisiting
a travel destination. Murphy et al. (2000) de?ne a structural model that relates the
tourist intention to return (as a proxy of satisfaction/quality) with his/her perceptions
of the travel experience.
In general, these models combine motivations, expectations and choice and are
estimated by using regressions techniques and structural models. Despite the power of
these analyses, nothing has been done in order to deeply evaluate the relationships
among the observed variables in the proposed models, which can be done by observing
the graphical displays provided by CATPCA. The conceptualized model in the
following section incorporates insights from the literature review. The objective of this
study is to develop and test a structural equation model of overall perception of the
exotic destinations which is a function of perceptions and motivations, in a cognitive
and emotional perspective. Perceptual maps via CATPCA complement the conclusions
from applying the proposed model.
Theoretical model and hypotheses
Figure 1 shows the hypothetical causal model that proposes interactions among the
constructs of motivations and perceptions. The choice of each component of the model
was based on the literature review. The model’s contribution depends upon the
Figure 1.
Proposed hypothetical
model
H
3
H
1
H
2
Perceptions
Push motives
Pull motives
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identi?cation of the relationship between the two constructs of motivation (push and
pull motives).
The hypotheses presented in the conceptual model, which will be tested in this
study, are the following:
H1. Push motives lead to different pull motives.
McCabe (2000) shows that the relationship between push and pull factors is the result of
a sequential decision. Firstly, a tourist decides to travel depending on his/her emotional
state (push-motives). Next, the tourist determines the place to visit and related activities
(pull-motives). These choices are a function of push motives that determine the decision
to travel. More speci?cally, Russel and Pratt (1980) suggest that the attributes of the
destination are perceived by their ability to achieve affective motives:
H2. The overall perception of the destination depends on the evaluation of the pull
motives.
According to Murphy et al. (2000), positive perceptions about a destination are related
to a positive summary evaluation of tourist destination attributes:
H3. Different push motives lead to different perceptions.
Choy (1992) and Murphy and Pritchard (1997) ?nd that more than the infrastructures
of a tourist destination, emotional states affect the perceptions regarding that
destination. In the same way, Beerli and Mart? ´n (2004) conclude that the emotional
motives directly in?uence the affective perceptions of the destination.
Method
Survey and sample
A survey was developed in order to test the proposed hypotheses. The survey includes
three sections: the ?rst one tries to measure the push motives that may lead the tourist to
the decision to travel. The second section presents the rate of destination attributes and
landscape features (i.e. the pull motives) whichrepresent what the tourist intends to do at
the exotic destinations. The latter section considers the overall level of perceptions.
The set of push and pull motives considered in this work is the most quoted on
literature (Uysal et al., 1996; Iso-Ahola and Mannel, 1987; Lundberg, 1990; Fodness, 1994;
Holden, 2003; Mohsin and Ryan, 2003; Shoemaker, 1989; Cossens, 1989). Speci?cally, the
following push motives were included: “relieving stress,” “escaping from the routine,”
“physical relaxing,” “doing different things,” “stimulating emotions and sensations,”
“beingan adventurer,” “having fun,” “increasing knowledge,” “knowingdifferent cultures
and lifestyles,” “enriching myself intellectually,” “knowing new places,” “meeting
interesting people,” “developing close friendships,” “going places my friends have not
been,” “talking with my friends about the trip.” Pull factors considered were the following:
“landscape,” “natural environment,” “cultural attractions,” “night-life,” “sports
equipment,” “transport,” “lodging,” “weather,” “accessibility,” “beaches,” “gastronomy,”
“security,” “distance,” “shopping facilities,” “relaxing atmosphere,” “social environment,”
“hospitality,” “different ethnics,” “standard of living.”
As Maio and Olson (1994) propose, push and pull motives, as well as perceptions, were
assessed by a seven point Likert-type scale. This scale ranged from “not important” (1) to
“extremely important” (7) concerning motives and from “very low” (1) to “very high” (7)
Why people
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regarding perceptions. Owing to sampling convenience, the study took place on ?ights to
the destination. The ?ights were onAir Luxor, SA, a Portuguese air travel companywhich
has a signi?cant market share as a tour operator.
A pre-test of the survey with a sample of 150 tourists enhances the validity and
reliability of the questionnaire. After the pre-test, which resulted in only minor
amendments, a sample of 1,097 Portuguese tourists was taken on ?ights to exotic
places (such as, Brazil, Morocco, Egypt, Mexico, Sao Tome and Principe) during
August and September, 2004. These are the months during which most Portuguese
citizens have holidays. Respondents were invited to participate in the survey and asked
to ?ll out the survey during the ?ight, and just before arriving at the airport.
As reported in Table I, the larger proportion of respondents are married, have high
level education, average age of 35 and belong to social middle class (Table I).
Statistical data analysis method
Three main stages of statistical data analysis follow in this report. The ?rst stage
entails the reduction of the data through the application of PCA to the set of push and
pulls motives. To assess the pertinence of using PCA in this research, the
Kaiser-Meyer-Olkin (KMO) statistic was computed and the Bartlett test was performed
(Bartlett, 1947). The reliability of the obtained factors was measured by a Cronbach’s
coef?cients (Cronbach, 1951). This analysis was carried out with statistical package for
the social sciences (SPSS) software, version 12.
A structural equation model was estimated in the second stage in order to assess the
underlined research hypotheses. The factors obtained with PCA were used as
indicators of the constructs push and pull motives. The model was estimated with the
software analysis of moment structures (AMOS 5) (Arbuckle and Wothke, 1999) and
the weighted least squares estimation method was applied. This is an asymptotically
distribution-free method, which is not sensitive to the non-normality of the data. The
model ?t was evaluated by following the approach suggested by Hair et al. (1998),
Socio-demographic characteristics Percent
Gender
Male 48.6
Female 51.4
Age (mean) 35.4 years old
Educational level
4 years 8.7
6 years 12.2
9 years 7.3
12 years 29.7
College 42.0
Family
Single 30.6
Married 64.8
With children 17.0
Social class
High 25.0
Medium 26.3
Medium/low 48.8
Table I.
Sample characteristics
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which ?rst requires the assessment of the overall model ?t and then the measurement
and structural models individually.
Measures of overall model ?t include absolute, incremental and parsimonious ?t
measures. The x
2
goodness-of-?t test is the best known index of absolute ?t. However,
this index is quite sensitive in large samples, showing signi?cant differences between
the covariance matrices in any proposed model (Garc? ´a and Martinez, 2000). Therefore,
besides the x
2
test, the goodness of ?t index (GFI) (Joreskog and Sorbom, 1986), the
root mean square residual (RMSR) and the root mean square residual of approximation
(RMSEA) (Steiger, 1990) were used to evaluate the proposed model’s overall absolute
?t. Six incremental ?t measures were used to evaluate the proposed model’s ?t: the
adjusted goodness of ?t index (AGFI) (Joreskog and Sorbom, 1986), the normed ?t
index (NFI) (Bentler and Bonnet, 1980), the Tucker and Lewis index (TLI) (Tucker and
Lewis, 1973) and the incremental ?t index (IFI) (Bollen, 1988), the relative ?t index
(RFI) (Bollen, 1986) and the comparative ?t index (CFI) (Bentler, 1990). Parsimonious ?t
was measured by the normed x
2
(Joreskog, 1969) that should range from 1 to 5.
Excluding RMSR and RMSEA, in which smaller values are better (zero indicates
perfect ?t) all other measures and indexes range from 0 (no ?t) to 1 (perfect ?t).
In evaluating the measurement model, each latent variable was assessed separately
through examining the standardized loading, the construct reliability and the variance
extracted. In analyzing the structural model ?t, parameter estimates were examined in
relation to their sign and statistical signi?cance. Standardized estimates are useful in
comparing the parameters’ effect throughout the model since they remove scaling
information. All proposed hypotheses were tested by observing the statistical
signi?cance of the corresponding paths in the structural model.
The ?nal stage involved focusing on the relationship between push factors, pull
factors and perceptions. The analysis began by recoding these variables in order to
obtain categorical variables. Then, through the application of a CATPCA, it was
possible to explore the nature of these relationships. This method allows us to
represent the various relationships of categorical variables in a low-dimensional space,
also known as a perceptual map. In this sense, CATPCA can make data interpretation
easier since the relative positions of categories on this map represent the relations
among them. Categories with similar distributions are represented as points on the
map and the proximities means that they are associated. On the contrary, categories
with quite different distributions will be positioned far apart on the map, suggesting
that they are not related. Thus, in this study, the perceptual maps depicting the
relationships among push and pull factors, push factors and perceptions and, lastly,
pull factors and perceptions, were presented. These maps complete the analyses
provided by the structural equation model since they allow a detailed evaluation of the
relations among each pull and push factor and perceptions. As PCA, this analysis was
carried out with SPSS, 12.
Results
Principal components analysis
Push factors. The reduction of the initial 15 push motives into three new factors,
together accounting for 68.4 percent of the total variance (KMO ¼ 0.9; Bartlett test:
p ¼ 0.05), was obtained through PCA. These ?ndings are presented in Table II.
Considering the meaning of the motives with higher loadings, the push factors were
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labelled knowledge, leisure and socialization. The internal consistency of these factors
was measured by the corresponding Cronbach’s a coef?cients (they exceed 0.8 in all
cases).
Knowledge is the ?rst factor and is speci?cally related to the need to explore new
cultures and places as well as to do and learn new things. In the Leisure factor the
principal motives are connected to personal well-being. The third factor, socialization,
is primarily the desire to share travel experiences, develop close friendships and go to
destinations not yet visited by friends.
Table II also shows the mean importance level of each push motive. The importance
ranking was based on the mean scores on the Likert seven-point scale. These results
are in accordance with the push motives determined in previous research (Sefton, 1989;
Loundsbury and Franz, 1990; Pearce, 1988; Laing, 1987; Smith, 1991). Most of these
studies are based on the leisure motivation scale of Beard and Raghep (1983) and show
that the main push motivations to travel are related to intellectual motives (learning,
exploring, discovering), social motives (friendship and interpersonal relationships,
need for esteem of the others) and relaxation motives (escape from daily routine,
get-away).
Pull factors. Table III presents results fromthe application of PCAto the nineteen pull
motives. As with push motives, three new factors were extracted, together accounting
for 63.5 percent of the total variance (KMO ¼ 0.9; Bartlett test: p ¼ 0.0). Pull factors
were labelled facilities, core attractions and landscape features. Cronbach’s a for these
factors also exceeds 0.8, indicating an adequate degree of internal consistency.
Facilities of the travel destination such as lodging, weather, food, security, roads
and hospitality are included in the facilities factor. Motives related to the social
environment, shopping facilities, sports activities and night life are encompassed by
the second factor, core attractions. Landscape features is the last pull factor and is
linked to the natural and cultural environment of the holiday destination.
Push motives and factor Loadings
Percent
variance explained
Reliability
(a Cronbach) Mean Rank
Knowledge
Do different things 0.7 5.9 7
Stimulate emotions and sensations 0.6 5.4 10
Be an adventurer 0.6 5.2 11
Have fun 0.7 6.0 4
Increase knowledge 0.8 33.4 1.0 5.9 6
Know different cultures and lifestyles 0.8 5.1 13
Enriching myself intellectually 0.8 5.8 8
Know new places 0.8 6.0 3
Find interesting people 0.6 5.4 9
Leisure
Relieving stress 0.8 6.1 2
Escape from the routine 0.8 18.7 0.9 6.1 1
Relaxing physically 0.8 5.9 5
Socialization
Developing close friendships 0.6 5.1 12
Going places my friends have not been 0.9 16.3 0.8 3.7 15
Talking with my friends about the trip 0.9 4.1 14
Table II.
Principal components of
push motives (after
varimax rotation), means
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The last two columns of Table III prove that the social and sports motives are the least
important in choosing a tourist destination. Inversely, the natural and regional
component clearly determines the destination image. This especially includes natural
environment, weather, beaches and hospitality and can be considered as an indicator of
how the natural resources of a tourist destination were perceived as competitive factors
par excellence. These results are also in accordance to previous studies in the ?eld
which have been quoted above.
However, despite the fact that these studies have provided important contributions
in order to de?ne push and pull motivations, they do not examine the interactions
among them (Ryan and Glendon, 1998). Yoon and Uysal (2005) state that inherent push
motivations are stimulated and reinforced by destination attributes. Sequentially,
different perception levels of a tourist destination are expected to result from different
combinations of push and pull factors.
Structural equation model
Examining the nature of the relationships among push and pull factors and overall
perceptions of the destination includes estimating the structural equation model
proposals in Figure 1. Figure 2 shows the estimated standardized path coef?cients on
the model itself. The values for the selected overall ?t measures are reported in
Table IV. As expected due to the large sample size, the observed value for the x
2
statistic is high and statistically signi?cant, suggesting that the observed and
predicted covariance matrices are not equal. In considering the dependence of the
x
2
-test on the sample size, the evaluation of the absolute ?t of the model relied on
Items and principal components Loadings
Percent variance
explained
Reliability
(a Cronbach) Mean Rank
Facilities
Weather 0.8 5.8 2
Lodging 0.7 5.1 7
Beaches 0.7 5.7 4
Hospitality 0.7 26.4 0.9 5.5 5
Gastronomy 0.7 4.8 11
Security 0.7 4.7 13
Relaxing atmosphere 0.7 5.3 6
Accessibilities 0.6 4.6 14
Core attractions
Standard of living 0.7 3.3 19
Different ethnics 0.7 4.8 10
Distance 0.7 4.4 17
Shopping facilities 0.7 23.3 0.9 4.7 12
Sports equipment 0.7 4.4 16
Social environment 0.6 4.9 9
Night-life 0.6 4.5 15
Transports 0.6 4.3 18
Landscape features
Landscape 0.8 5.7 3
Natural environment 0.8 13.9 0.9 5.8 1
Cultural attractions 0.7 5.0 8
Table III.
Principal components of
pull motives items (after
varimax rotation)
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the other absolute measures, which are very high. The proposed model also presents
high values for the remaining measures, suggesting an adequate incremental and
parsimonious ?t.
A measurement model analysis follows the analysis. This model could be improved
if all the observed variables had signi?cant loadings in corresponding latent variables.
This was true for all indicators except for Leisure ( p . 0.05). On the other hand, the
constructs reliability and variance extracted for the latent variables push motives and
pull motives do not exceed the desirable levels of 0.7 and 0.5, respectively. Owing to
these results, the model was re-estimated by excluding the indicator leisure. The results
of this model, concerning the GFI and the standardized loadings, were essentially the
same but the measurement model has clearly improved. For this reason, we decided to
go on considering the model as had been proposed initially.
Figure 2 also shows that two speci?ed paths between the constructs are statistically
signi?cant which supports only research hypotheses H1 and H2. The same results,
with similar path estimates, were obtained in the restricted model: H1 and H2 are still
supported by the data and H3 is rejected.
Categorical principal components analysis
In order to simultaneously analyze the relationship among each push factor, pull factor
and perceptions, these variables were transformed into categorical variables. Table V
shows the relative distribution of respondents by the categories of the new variables.
Figure 2.
Standardized estimates of
proposed model
Note: (*) p < 0.01
-0.31
H1
H2
H3
0.80 (*)
0.81 (*)
0.36 (*) 0.41 (*) 0.77 (*)
0.69 (*)
0.02
0.52 (*)
0.34 (*)
0.80
0.78 0.87 0.40
0.72
0.96
0.50
Pull motives
Perceptions
Socialization
Knowledge
Leisure
Facilities
Core
attractions
Landscape
features
Push motives
Perceptions
Absolute ?t measures Incremental ?t measures Parsimonious ?t measures
x
2
¼ 22.23 ( p ¼ 0.008) AGFI ¼ 0.98 Normed x
2
¼ 2.47
RMSR ¼ 0.038 NFI ¼ 0.97
RMSEA ¼ 0.046 TLI ¼ 0.96
IFI ¼ 0.98
RFI ¼ 0.93
CFI ¼ 0.98
Table IV.
Goodness-of-?t indices
for the estimated
structural model
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Having transformed the pull and push factors into ordinal variables, the study
includes applying CATPCA to complement the evaluation that the structural equation
model provides. CATPCA helps to deeply analyze the relationship between push and
pull categorized factors and, afterwards, to relate pull factors and perceptions. The
decision was made not to present the perceptual map connecting push factors and
perception because the estimated model showed a non-signi?cant relationship between
these constructs.
Figure 3 shows the combination of categories of each pull factor with categories of
each push factor through a perceptual map. As can be observed, high valorization of
pull factors (represented by the full lines) is related with high valorization of push
factors (represented by the broken lines) and vice-versa. This map also suggests which
push and pull factors are strongly related, which was not detected with the structural
equation model: socialization and knowledge are particularly related to facilities;
leisure is specially associated to core attractions.
Figure 4 shows a similar analysis but in what concerns the connections between
perceptions and pull factors. The relationship appears to be more fragile than the one
Figure 3.
Joint plot of category
points for push and pull
factors
?1.5 ?1.0 ?0.5 0.0 0.5 1.0
Dimension 1
?0.6
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Knowledge
Socialization
Leisure
Facilities
Core
attractions
Landscape
features
L - Low valorization
M - Medium valorization
H – High valorization
Motives and perceptions
Low valorization
(L)
(percent)
Medium valorization
(M)
(percent)
High valorization
(H)
(percent)
Total
(percent)
Knowledge 19.7 55.1 25.2 100
Leisure 13.3 56.8 29.9 100
Socialization 48.9 32.0 19.0 100
Facilities 16.0 58.9 25.0 100
Core attractions 13.0 56.8 30.2 100
Landscape features 9.6 55.9 34.5 100
Perceptions 43.1 56.9 – 100
Table V.
Relative distribution of
respondents by the
categories of the
variables
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previously reported between pull and push factors. As can be observed on the
perceptual map, landscape features is the pull factor least related to perceptions and
there is also a very similar connection between perceptions and facilities, on the one
hand, and perceptions and core attractions on the other hand.
Discussion and managerial implications
The theoretical model proposals offer a logical sequence of the formation of tourist
perceptions. The empirical study proves that perceptions of tourism destinations are
formed based on push and pull factors. The study supports the view that all
destination attributes contribute to the perceived image of the destination. The
formation of perceptions seems to happen in the following sequence: push factors are
determinants of pull factors which, in turn, explain perceptions.
In the model, the relationship between push factors and perceptions is not signi?cant,
and that proves that the tourist decides to go on holiday because he/she needs to solve a
con?ict arousal (rest, social and intellectual rewards). Then, he/she decides where to go
based on the destination attributes. The destination attributes (pull motives) are
perceived as the way to solve intrinsic motives (push motives), but these constructs
are not directly related to the overall perception of the destination because they are
apparently solved when the tourist turns her/his attention to speci?c attributes. Figure 3
also supports the view that a high valorization of all pull factors is associated to a high
valorization of all push factors. This evidence depends upon the very essence of humans’
nature. Humans are continuously seeking and solving problems, with different levels of
involvement with the decision. This conclusion also stresses the need for testing the
inclusion of emotions and learning as constructs of the theoretical model.
Looking deeply into the factors identi?ed for the pull and push attributes, this study
proved that knowledge and socialization are the major motives which cause the need to
Figure 4.
Joint plot of category
points for pull factors and
perceptions
L - Low valorization
M - Medium valorization
H– High valorization
?1.0 ?0.5 0.0 0.5 1.0
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?1.0
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Landscape
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travel abroad. This evidence is in accordance to Oppermann (1996), who stresses that
travelling to unknown places (and this is the case of exotic places) gives rise to a
variety seeking behavior, looking for social and intellectual rewards. Similarly, Gnoth
(1997) highlights the difference between social trip and a variety seeking trip. While the
?rst one represents the choice of a fashionable exotic resort, the second one is more
related to savage and unexplored environments. So, the social trip is more associated to
social status, self esteem and sense of belonging. The variety seeking trip is related
to adventure and intellectual rewards.
The destination attributes highlighted by the PCA represent the core tourism
product: facilities, core attractions and landscape features. Figure 4 shows that the
facilities factor is the prior motive that contributes to overall perception. Although
knowledge is one of the major push motives which generally determine the choice of an
exotic destination, tourists assume that these places abound in landscape and scenic
aspects and so they do not look for much information about these aspects (they are
assumed to be intrinsic characteristics of the destination).
Considering the correlation between push and pull motives that Figure 3 shows,
socialization and knowledge, the more reliable push motives in the structural model,
stimulate the mind of the tourist for the need for attributes related to the facilities of the
destination. The tourist who decides to travel in order to increase his/her knowledge
would be expected to reveal more concern about the landscape features and sport
activities. In turn, the tourist who travels in order to increase his/her social status
would rank higher facilities and core attractions. However, the empirical results prove
that the tourist who travels due to intellectual or social rewards decides where to go
based on facilities. Even though this result could seem strange, the result reveals that
tourists are conscious that they are traveling to destinations where human and social
development is low and, therefore, main concerns turn to where they will sleep, eat as
well as to how they will travel throughout the destination. This is an issue that needs
more research.
Still concerning the relationship between push and pull motives, Figure 3 shows
that leisure is mainly correlated with core attractions. This result can also seem strange
if rest and relaxation are perceived in a physical perspective. Portuguese tourists seem
to understand rest and relaxation from a different point of view: relaxation and rest
does not mean “doing nothing” but, instead, “doing different things.” In this sense, in
the case of Portuguese tourists, the statement that leisure is more mental than physical
can be made.
The major ?ndings of this study have signi?cant managerial implications for
destination marketing. Firstly, the exploratory analysis shows that the decision to travel
to exotic places arises fromthe desire of knowledge, having social status and intellectual
leisure and also that these factors determine the perceived pull motives: facilities, core
attractions and landscape features. Since, tourists were found to be more aware of
facilities and core attractions, marketing of these destinations must be especially
focused on these factors rather than on beautiful images of natural landscapes. These
empirical results could be fundamental in order to direct and target the destination
marketing strategy to enhance the overall perception of these exotic places.
Secondly, special attention must be given to the type of activities which are
offered to tourists. Even tourists who simply want to relax do not relate leisure to
“doing nothing.” According to the structural model and CATPCA analyses, social and
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intellectual rewards are in?uencing factors in what pertains to the demand for exotic
destinations. The offering of appropriate activities and attractions to the right tourists
may be the result of the knowledge gained through identifying why people travel the
way they do. These results indicate that marketers and managers of exotic destinations
should concentrate on improving push factors in order to enhance the destination’s
competitiveness.
Thirdly, CAPTCA results suggest two levels of awareness in what concerns the
perception of an exotic location: one with tourists who are highly involved and the
other with tourists who are only moderately involved. To avoid dissatisfaction at
the end of the trip the latter group should receive special attention from destination
managers.
Conclusions
This study contributes to the overall understanding of why tourists behave the way
they do from four different perspectives. First, despite the number of models which had
considered the relations between push and pull motives, the inclusion of perceptions in
the theoretical model is a reason to believe that this research provides a step forward in
literature. Second, this was the ?rst time that structural equation modelling and
CATPCA were put together in order to prove the relationships between push, pull
motives and overall perceptions. Third, only now has the outbound Portuguese tourist
market been studied at a more scienti?c level. Lastly, this was the ?rst time that
motivations and perceptions were combined in order to understand why people could
be pushed to travel to exotic destinations and how they form their perceptions.
Empirical evidence in this study opens paths for further investigation. The study
does have some limitations, however, the main one being the domain which can be
considered as restricted. Generalizing the model is an important step to better
understand tourist behavior. Extending the study using other destinations and
attributes, and tourists with different incentives would be a useful step.
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Corresponding author
Anto´nia Correia can be contacted at: [email protected]
Why people
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