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Travel career pattern and travel horizon: Some common ground?
Karin Teichmann, Vienna University of Economics and Business, karin.teichmann@wu.ac.at
Andreas H. Zins, Vienna University of Economics and Business and MODUL University
Vienna, andreas.zins@wu.ac.at
Abstract
This study explores the role of travel career pattern and travel horizon on future travel plans.
The study examines if these two concepts show some systematic links which are useful in
explaining future destination preferences. The first research question investigates the
motivational dimensions as proposed by Pearce’s travel career pattern. The results show that
motives for near future leisure trips exhibit the expected pattern and differ by age and travel
experience. The second question focuses on a re-interpretation of travel horizons as expressed
by future destination preference patterns based on cultures zones instead of geographic
distances. Five distinct travel horizon patterns are identified using cluster analysis to show
that travel career factors have little influence on future destination preferences.
Keywords: travel career pattern, travel horizon, future destination preference, cultural zone
ANZMAC 2009
Travel career pattern and travel horizon: Some common ground?
Introduction
The fact that tourist motivation is a key issue in tourist behaviour has long been recognized in
literature. Researchers have put a lot of effort in exploring why people travel. The underlying
assumption is that tourists have certain needs which they want to meet and satisfy when going
on vacation. One conceptualization of tourist motivation refers to the push/pull model
(Crompton, 1979; Dann, 1981). Push factors relate to intrinsic factors that motivate tourists to
seek activities in order to reduce the gap between actual and aspired states (Blichfeldt, 2007).
For instance, desire for escape, rest and relaxation, or seeking adventures are internal motives
for travelling (Uysal and Jurowski, 1994). Pull factors are related to tourists’ knowledge about
destinations or destination-generated factors such as a destination’s attractiveness that drive
people to travel (Gnoth, 1997).
Pearce (1982) applied Maslow’s hierarchy of needs to the field of tourist behaviour. In his
paper, he argues that tourists travel because of self-actualization, love and belongingness, and
physiological needs on the one hand. On the other hand, they have a concern for safety and
avoid failure to satisfy physiological, love and belongingness and self-esteem needs. Later,
Pearce and his colleagues developed the travel motivation theory further known as “travel
career ladder (TCL)” (Moscardo and Pearce, 1986; Pearce, 1993; Pearce, 1988; Pearce and
Caltabiano, 1983). The theory describes that tourist motivation can be arranged in a hierarchy
of five categories: relaxation needs, safety/security needs, relationship needs, self-esteem and
development needs, and self-actualization/fulfilment needs in that increasing order of
importance. The TCL assumes that with increasing travel experience, tourists ascend the
ladder towards higher-level needs. This ladder, however, has been criticized as lack of
evidence was found for travellers moving towards higher intellectual motivation for travelling
with increasing experience (Ryan, 1998).
Pearce and his colleagues recently addressed this criticism by proposing a “travel career
pattern (TCP)” (e.g. Pearce and Lee, 2005). The TCP approach recognizes that travellers’
motivational patterns change over their life stages. Different to the TCL, the TCP considers
“the dynamic, multilevel motivational structure that is seen as critical in understanding travel
motivation, and it is these patterns that reflect and define careers” (Pearce and Lee, 2005, p.
227). Thus, the pattern of motivations rather than the hierarchy of needs and motives is
emphasized. In their study, Pearce and Lee (2005) identified 14 motivation factors as driving
forces behind tourist behaviour. Among these are novelty, escape/relax, relationship
(strengthen), autonomy, nature, self-development (host-site involvement), stimulation, selfdevelopment (personal development), relationship (security), self-actualization, isolation,
nostalgia, romance, and recognition in that order of importance. Thus, in research question
one it will be investigated if TCP shows differences across age groups (life stages) or travel
experience levels?
Pearce and his colleagues relate the TCL as well as the TCP approach to accumulated travel
experience. The basic assumption therefore is that travel experience is the main determinant
for changing the traveller’s pattern/ladder of her/his travel career. However, many approaches
exist in literature for how to conceptualize travel experience. For instance, travel experience
can be measured as simply as counting how often people travel or visit destinations. A more
complex approach was advanced by Oppermann (1998). Oppermann based his study on
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Schmidhauser’s (1976) conceptualization of travel horizon defined as the maximum achieved
distance zone in the past thus focusing on geographical and cultural distance. The basic
premise was that individuals follow an expanding travel/destination horizon in the course of
their lives.
Studies focusing on the role of travel experience and its influence on future travel plans are
needed with respect to demand forecasting. Therefore, this paper also explores in research
question two what role travel experiences and TCP has on future destination preferences.
Method
This research study used a self-administered questionnaire delivered by hand to each
respondent. The data were collected by 35 undergraduate students taking a course on research
methods. Each student was instructed to collect data from at least 7 subjects. The survey was
conducted in December 2008 in Austria. The purposive sampling strategy included quotas for
each interviewer: a balanced gender distribution (female = 54%) and an almost equal share of
respondents in the age brackets of 20 to 30 (n = 156) and 50 to 60 (n = 127) years were
assigned. In total, 283 complete questionnaires are available for analysis.
The first part of the questionnaire included questions about the subjects’ previous travel
experience. For this purpose, the society clusters according to the GLOBE study (House et al.,
2004) were used. The GLOBE study organized 62 countries into 10 distinct clusters. These
clusters are Anglo, Latin Europe, Nordic Europe, Germanic Europe, Eastern Europe, Latin
America, Sub-Saharan Africa, Middle East, Southern Asia, and Confucian Asia. The
questionnaire included a list with these 10 clusters and examples of countries for each specific
cluster. A coloured world map was handed over to the respondents for a better identification
of the society clusters. In order to measure how often respondents visited each society cluster
the response format ranged from never (= 0) to more than 30 times (= 7) with six answer
categories in between representing frequency ranges of five times each. Whereas the first
question in the questionnaire measured the frequency of travelling into the ten society clusters
during one’s lifetime, a similar question was included asking for destinations visited during
the past five years (from 2004 to 2008). The latter horizon overlaps with the former more or
less depending on the age of the traveller. Respondents had to elicit the destinations (at
country level) visited each year during this period for trips that lasted longer than 4 days. To
capture individuals’ destination planning horizon, respondents were required to enter those
country destinations they plan to visit the years 2009 to 2011. Within three years, it is argued,
many people shift, postpone or bring forward those destination plans they consider really
feasible. Cutting off the planning horizon beyond this threshold should avoid capturing too
many unrealistic dreams. No differentiation was recorded whether this plan is binding for a
particular year of this period. The final part of the questionnaire comprised questions on
demographic characteristics including one question on language capabilities. To measure
travel motivation, the 69 motive items identified by the study by Pearce and Lee (2005) were
used and contextualized for leisure travels in the near future.
Results and discussion
Data were analyzed in three stages. In accordance with Pearce and Lee (2005), a confirmatory
factor analysis was conducted using Mplus and a ML algorithm (Muthén and Muthén, 1998)
to identify the underlying 14 dimensions for the 69 motive items. The global goodness-of-fit
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ratios do not indicate a very successful identification (Cmin/df = 2.2, CFI = .78, TLI = .76,
RMSEA = .065). Standardized loadings are on average above .70 with only 4 out of 69 items
on the level of .40. However, Cronbach’s alpha (Nunnally, 1978) and Fornell and Larcker’s
(1981) composite reliability ratios are all passing the recommended threshold of 0.70 (see
Table 1 last two columns).
In a first attempt, previous findings on the Travel Career Pattern are critically reviewed in
view of the current data set. Overall, the same group of motivational factors appears to be
most important like in Pearce and Lee’s study (2005): novelty, strengthening relationship with
others, self-development by host-site involvement, autonomy and escape. In line with their
results, aspects such as isolation, nostalgia and social recognition are expressed to be less
important.
Instead of combining age with past travel frequency this study simply considered two age
cohorts (20 to 30 and 50 to 60 years) to represent two different levels of travel experience. In
fact, by transforming the ordinal responses about the past lifetime travel destination zones
(using the lower boundary of trip frequencies) the younger cohort reveals a cumulative
frequency of 20 trips whereas the older group spent already at least 38 trips.
Table 1 highlights the differences in future travel motivations between the two age cohorts.
Means with an asterisk demonstrate significant differences (t-test). Overall, nine out of the 14
motive factors exhibit different profiles across the two age groups representing two different
natural levels of travel experience. Differences occur for similar factors like in Pearce and
Lee’s study (2005). However, some results deviate. Strengthened relationships are more
important for the younger age cohort. Interestingly, self-development through host-site
involvement and recognition appear to be also more relevant for younger travellers. Selfactualization does not seem to be different. Factors such as nature, relationship (security) and
isolation are valued higher by older travelers wheras factors like stimulation, personal selfdevelopment and romance demonstrate the expected differences.
The second stage of analysis tried to identify patterns of (future) travel experiences. A
topology representing network approach (Mazanec, 2008) – a quantisation method derived
from Kohonen’s Self Organizing Map principle – was chosen to analyse the frequency
patterns hidden in the ten cultural destination zones for which travel plans were stated for the
next three years. Cluster solutions between two and seven segments have been investigated.
Applying the relative increase of homogeneity criterion a five-cluster solution turned out to be
best suited. Table 2 exhibits some descriptives about the five identified segments representing
different future travel horizons.
Table 1: Age cohorts and mean scores of motive factors
Motive factor
20 – 30 50 – 60
years
years
Novelty
5.3*
5.0
Strengthen relationships
4.6
4.4
Self-development: host-site involvement
4.6*
4.3
Autonomy
4.4
4.2
Escape
4.4
4.4
Stimulation
4.3*
3.3
Self-development: personal
3.8*
3.3
Nature
3.8*
4.5
Cronbach
alpha
.70
.81
.83
.83
.88
.90
.89
.88
Composite
reliability
.70
.82
.84
.84
.88
.90
.90
.89
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Motive factor
20 – 30
years
3.4
3.4*
3.3*
3.6*
2.8
2.8*
Self-actualization
Romance
Relationship: security
Isolation
Nostalgia
Recognition
Note:
50 – 60
years
3.3
2.4
3.6
4.2
2.8
2.4
Cronbach
alpha
.84
.82
.89
.81
.91
.80
Composite
reliability
.85
.82
.89
.80
.91
.82
Factors as indices from raw scales ranging from 1 “totally unimportant” to 6 “very important”;
* means: t-test, significantly different at p < .05;
At a first glance, it becomes obvious that age impacts upon these different travel horizons.
However, the large differences detected in their past lifetime travel frequency vanish due to a
mixture of different age cohorts. The differences in past travel frequency are statistically not
significant. Future destination zones (as active variables for the segment generation) show a
very distinct mixture for the five segments. The first one has a particular focus on German
speaking and Nordic destinations. The second segment – the largest by size – shows a rather
low travel experience in general despite the fact that it is the relatively oldest. Germanic,
Nordic and Latin European destinations exhibit the lowest preferences among all five
segments. In contrast, Middle East and Confucian Asian countries are much more
appreciated. The youngest – and least experienced – travel segment has quite different travel
intentions: Anglo-American, Latin-American and South Asian countries range on top: within
and across segments. The fourth segment demonstrates a clear preference towards Latin
European destinations however not completely neglecting Germanic countries and AngloAmerican destinations. The final segment exhibits a distinct preference for Eastern Europe
including mediterranean countries like Croatia. Overall, eight out of ten destination zones are
significantly different across this segmentation solution. Past travel horizons (lifetime and five
years back) are not congruent with future ones. Only a few destination zones reveal
significant differences along the five future horizon segments which demonstrates shifts and
transitions of preferred destinations.
The third stage of analysis follows the premise if travel horizons for the near future follow
particular travel motives (bottom part of Table 2). Only three out the 14 TCP factors turn out
to be linked to specific destination patterns. Self-development through host-site involvement
appears more relevant for the fifth segment committed to closer destinations (Germanic and
Eastern Europe). Stimulation is most important for the third segment with a high preference
for Anglo-american regions, Latin-America and South Asia. Autonomy is particulary
important for travellers in the second segment with a rather low travel frequency in general
and some favor towards Confucian Asia.
Table 2: Characteristics of five future travel horizon pattern segments
Travel horizon pattern segments
Segment number
Share
Age: average1)
20 – 30 years2)
Past travel experience (no. of trips)
Future travel plans: 2009 – 2011
Germanic Europe1)
Nordic Europe1)
1
16%
38
60%
32
2
32%
41
42%
26
3
20%
32
80%
23
4
20%
39
51%
30
5
12%
41
49%
35
1.8
0.5
0.2
0.1
0.4
0.5
0.7
0.4
0.8
0.4
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Segment number
Eastern Europe1)
Latin Europe1)
Anglo-American zone1)
Latin America1)
Sub-Sahara Africa
Middle East
South Asia1)
Confucian Asia1)
Past lifetime travel zones4):
Germanic Europe1)
Eastern Europe1)
Past 5 years‘ travel zones4):
Germanic Europe1)
Eastern Europe1)
Latin Europe1)
Motive factors4):
Self-development: host-site1)
Stimulation1)
Autonomy3)
Isolation3)
Note:
1
0.6
1.0
0.7
0.1
0.1
0.2
0.1
0.0
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Travel horizon pattern segments
2
3
4
0.3
0.4
0.5
0.4
0.7
2.4
0.3
2.5
0.7
0.3
0.5
0.2
0.1
0.2
0.1
0.3
0.2
0.3
0.2
0.4
0.2
0.2
0.1
0.1
5
2.6
1.4
0.4
0.1
0.3
0.2
0.3
0.1
14.6
5.5
12.3
4.7
9.1
4.5
14.4
4.3
15.7
8.8
4.5
1.9
2.2
2.5
1.5
1.8
2.7
2.1
2.4
3.2
2.1
3.0
4.0
4.1
2.6
4.2
3.5
4.1
3.6
4.3
3.7
4.5
4.1
4.7
4.6
4.5
3.7
4.4
3.8
4.2
3.8
4.8
3.6
3.9
4.1
1) F-test significant at p < .01; 2) Chi²-test significant at p < .001; 3) F-test significant at p < 0.05;
4) Only significant items are shown due to space restrictions;
Finally, it can be stated that the TCP approach materializes in principle. The dimensional
configuration appears to be stable even within the rather small sample used in this study.
However, the basic premise of a shift from internally to externally oriented needs along
higher levels of travel experiences could not be corroborated entirely (research question 1).
Yet, travel motives seem to change with age and accumulated travel experience. Further, only
limited evidence was found for travel motives (expressed by TCP factors) affecting future
destination horizons (research question 2). Since it became more and more common to travel
to different destinations within even a relatively short time of life it seemed appropriate to
identify similar destination patterns occurring within the next three years. Though, only four
factors out of 14 show significant differences between the five travel horizon pattern
segments identified in this study. Therefore, it is argued that travel motives may influence
destination preferences in the very short term or for a single destination choice. Travel
experiences into different cultural zones are obviously collected for very different reasons,
which makes destination marketing focusing on a narrow range of travel needs and motives
rather difficult and risky. Segmenting travelers simply on the choice of the immediate
following trip destination has to be treated with caution. Limitations, though, have to be
considered in view of the single country data which this study is based on.
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References
Blichfeldt, B. S., 2007. A nice vacation: variations in experience aspirations and travel
careers. Journal of Vacation Marketing 13 (2), 149-164.
Crompton, J., 1979. Motivations for pleasure vacation. Annals of Tourism Research 6 (4),
408-424.
Dann, G., 1981. Tourist motivation: an appraisal. Annals of Tourism Research 8 (2), 187-219.
Fornell, C., Larcker, D. F., 1981. Evaluating structural equation models with unobservable
variables and measurement error. Journal of Marketing Research 18 (1), 39-50.
Gnoth, J., 1997. Tourism motivation and expectation formation. Annals of Tourism Research,
24 (2), 283-304.
Mazanec, J. A., 2008. TRN2008. Available from
http://www.wu.ac.at/itf/downloads/software/trn32, accessed on 18 June
2009.Moscardo, G. M., Pearce, P. L., 1986. Historical theme parks: an Australian
experience in authenticity. Annals of Tourism Research 13 (3), 467-479.
Muthén, L. K., Muthén, B., 1998. Mplus User's Guide: The comprehensive modeling program
for applied researchers. Los Angeles.
Nunnally, J. C., 1978. Psychometric theory (2nd ed.). New York: McGraw-Hill.
Oppermann, M., 1998. Travel horizon: a valuable analysis tool? Tourism Management 19 (4),
321-329.
Pearce, P. L., 1982. The social psychology of tourist behaviour, Pergamon Oxford, UK.
Pearce, P. L., 1988. The Ulysses factor: evaluating visitors in tourist settings, SpringerVerlag, New York.
Pearce, P. L., 1993. Fundamentals of tourist motivation. In: Pearce, D., Butler, R. (Eds.),
Tourism research: critiques and challenges. Routledge and Kegan Paul, London,
pp. 85-105.
Pearce, P. L., Caltabiano, M. L., 1983. Inferring travel motivation from travellers'
experiences. Journal of Travel Research 22 (2), 16-20.
Pearce, P. L., Lee, U., 2005. Developing the travel career approach to tourist motivation.
Journal of Travel Research 43 (3), 226-237.
Ryan, C., 1998. The travel career ladder: an appraisal. Annals of Tourism Research 25 (4),
936-957.
Schmidhauser, H., 1976. Neue Erkenntnisse über Gesetzmäßigkeiten bei der Wahl des
Reiseziels. Jahrbuch für Fremdenverkehr 25-26, 86-102.
Uysal, M., Jurowski, C., 1994. Testing the push and pull factors. Annals of Tourism Research
21 (4), 844-846.