Segmenting the market of first time visitors to an island destination

Description
The purpose of this study is to segment the market of first-time visitors based on the activities
travelers engage in while at a destination using demographics, socio-economic variables, and
trip-related characteristics

International Journal of Culture, Tourism and Hospitality Research
Segmenting the market of first-time visitors to an island destination
Sean Hennessey Dongkoo Yun Roberta Macdonald
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To cite this document:
Sean Hennessey Dongkoo Yun Roberta Macdonald, (2012),"Segmenting the market of first-time visitors to an island destination",
International J ournal of Culture, Tourism and Hospitality Research, Vol. 6 Iss 2 pp. 154 - 172
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J enny Cave, Keith G. Brown, (2012),"Island tourism: destinations: an editorial introduction to the special issue", International J ournal of
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Antónia Correia, Metin Kozak, J oão Ferradeira, (2013),"From tourist motivations to tourist satisfaction", International J ournal of Culture,
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Sameer Hosany, Yuksel Ekinci, Muzaffer Uysal, (2007),"Destination image and destination personality", International J ournal of Culture,
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Segmenting the market of ?rst-time visitors
to an island destination
Sean Hennessey, Dongkoo Yun and Roberta Macdonald
Abstract
Purpose – The purpose of this study is to segment the market of ?rst-time visitors based on the activities
travelers engage in while at a destination using demographics, socio-economic variables, and
trip-related characteristics.
Design/methodology/approach – The research analyzes 1,104 exit surveys completed by ?rst-time
visitors to the Canadian province of Prince Edward Island. Clustering analysis identi?es three segments
that are re?ned and tested by multivariate and bivariate analyses.
Findings – The results indicate that there are three distinct segments of ?rst-time visitors based on
travel activities: culture-oriented (26 percent of the market), active (37 percent), and casual (37 percent).
The key differences among the three segments are demographic, socio-economic, trip-related
characteristics, and spending patterns. These results con?rm the sustainability and pro?tability of the
market segments.
Practical implications – Segmenting markets for products or services, in any industry, is vital to gain a
better understanding of the customer, and to better allocate scarce tourism resources to product
development, marketing, service, and delivery. Therefore, all tourism industry stakeholders must be
aware of the market segments that are currently visiting the destination.
Originality/value – Tourist segments based on activities are not absolutes, but a continuum. The
majority of ?rst-time visitors to a destination engage in a variety of travel activities across the segments,
running from more to less involved. Successful tourism destinations are those that meet the various
activity needs of their segments in both their marketing and on the ground.
Keywords Travel activities, Continuum, Market segmentation, Cluster analysis; First-time visitors,
Cultural tourism, Islands, Canada
Paper type Research paper
1. Introduction
How consumers de?ne a product or service when considering its relevant attributes is a
product’s position, the place the product occupies in consumers’ minds relative to
competing products (Kotler et al., 2003). Product positioning is certainly relevant and
important to tourist destinations. Due to the development of more destination choices
resulting in increased global competition for visitors, customer attraction and retention is an
important and challenging issue faced by tourism marketers worldwide.
Understanding why people travel to a particular destination, and why they may or may not
return, is vital to ensuring the continuing growth in the value of tourism to the destination. In
addition, key stakeholders in the industry must understand the needs/wants of current and
potential visitors in order to ensure that marketing expenditures produce a return for public
and private sector stakeholders. This process will also increase the probability that the
tourism development undertaken meets the needs of the traveling public, while insuring the
sustainability of the industry.
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VOL. 6 NO. 2 2012, pp. 154-172, Q Emerald Group Publishing Limited, ISSN 1750-6182 DOI 10.1108/17506181211233081
Sean Hennessey is a
Professor and Faculty
Director in the School of
Business & Tourism
Research Centre at the
University of Prince Edward
Island, Charlottetown,
Canada. Dongkoo Yun is a
Senior Development
Analyst in the Tourism
Research Centre,
University of Prince Edward
Island, Charlottetown,
Canada. Roberta
Macdonald is Dean of the
School of Business
& TourismResearch Centre,
University of Prince Edward
Island, Charlottetown,
Canada.
Received: November 2009
Revised: May 2010
Accepted: July 2010
The authors acknowledge the
Tourism Department of the
Government of Prince Edward
Island for allowing use of the
2007/2008 Exit Survey data in
this paper. Anonymous referees
and the Guest Editors of the
Special Issue of the journal
provided many insightful
comments and suggestions
that greatly helped in
developing the paper.
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Tourism researchers have been studying the application of the various elements of
segmentation since the 1970s. Applying the various elements of the segmentation process
allows the tourismindustry to identify unmet customer needs and apply target marketing and
positioning to allocate scarce marketing resources effectively. Tourism industry players gain
an edge to outperform the competition when they tailor offerings to those segments that are
measurable, substantial, accessible, and sustainable by developing uniquely appealing
products and services and allocating their scarce tourism resources to product
development, marketing, service, and delivery.
Segmenting visitors to numerous destinations is a technique used extensively, over many
years, to understand tourists’ behaviors and improve competitiveness. This work includes:
Boorstin (1971), Cohen (1972), Graham and Wall (1978), Etzel and Woodside (1982), Hsieh
et al. (1992), Rao et al. (1992), Mudambi and Baum(1997), Flognfeldt (1998), Oppitz (1998),
Burns (1999), McIntosh (1999), Dolnicar (2002), McKercher (2002), McKercher et al. (2002),
Kim and Jogaratnam (2003), Littrell et al. (2004), McKercher et al. (2006), Spencer and
Holecek (2007), Yun et al. (2008), and Kim and Agrusa (2008). Many of these and other
studies illustrate the segmentation of groups of travelers who react in homogeneous ways.
Factors used to segment the travel market include trip demographics, traveler motivations,
behaviors, activities undertaken, trip purpose, reactions to marketing activities, or the
bene?ts sought from consuming products and services. Yet, the activities in which visitors
engage at destinations are an important way to differentiate segments of the visitor
population.
Segmentation of the visitor population enables destinations to develop products and
services that effectively satisfy the differing needs of each segment, and grow the
importance and competitiveness of the tourism industry in ways that are socially,
environmentally, and culturally sustainable (Ritchie and Crouch, 2003). Travel market
segmentation based on activities engaged in while visiting a destination provides important
insights for tourism marketers and operators, plus aids in the development of products and
services. In addition, identifying the relationships between the travel activities engaged in by
visitors and their demographics, socio-economic situation, and trip-related characteristics is
important to provide tourism marketers with critical information on travel activity, potential for
economic contribution to the destination by the various market segments, product and
service development, and marketing communication strategies. Successful destinations are
?exible, customer-focused, and pro?cient, while taking advantage of the rapidly changing
environment.
The main purpose of the study is to examine the relevance and signi?cance of market
segmentation based on the activities ?rst-time visitors engage in while at a destination. The
paper segments pleasure travelers (spending at least one night) to a major island travel
destination and develops pro?les of the segments using demographics, socio-economic
variables, and trip-related characteristics.
The results indicate that activities can be the basis of ?rst-time visitors’ segmentation at a
destination. For about a quarter of the ?rst-time visitors to Prince Edward Island, cultural
themes are an important factor when visiting. In addition, these culture-seekers are valuable
in terms of their economic contribution and for their cultural and social interaction with
communities. A further 37 percent of visitors are either active or casual visitors.
2. Literature on activity-based segmentation
Activity is a variable that plays an important role in many studies about travel market
segmentation. The activities travelers participate in while visiting a destination or their stated
activity preferences are useful to understand tourists’ behaviors and to help segment
markets for visitors in general and for individual destinations. Most attempts at de?ning
unique segments of the total travel market start with the consumption of an activity (see
Richard, 1996a, b, for culture).
Activity-based segmentation approaches have evolved considerably since they were ?rst
recognized as a new development in the study of travel behavior at the Third International
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Conference on Travel Behavior in Australia in April 1977. The growing interest in these
approaches is re?ected in the increased number of studies undertaken as well as the range
of approaches used, and a wide range of issues have now been addressed from an activity
based perspective (Jones et al., 1990). From a broader view, the different types of preferred
activities participated in can be considered subgroups of the total travel market (Morrison,
1989; Lang et al., 1994; Lang and O’Leary, 1997; Choi and Tsang, 1999; Sung et al., 2000;
Moscardo et al., 2001; Littrell et al., 2004).
Traveler choice of attractions or activities while at a destination is determined by differences
in the characteristics of the destinations visited, the travel elements that can be purchased
prior to departure, as well as the characteristics of travelers to those destinations (Hyde,
2004). Visitors to destinations such as London or Rome are likely to have very different travel
motivations and to be seeking very different types of travel activities than visitors to
destinations such as Phuket or Hawaii. Travel activities in and of themselves are useful
indicators to understand tourists’ behaviors (McIntosh and Goeldner, 1990) and to identify
their experiences at a destination (Ryan, 2002). Bowden (2003), based on a study of
international visitors to China, reports that where visitors go and what they do is in?uenced
by cultural backgrounds, geographic origin, socio-economic factors, and nationality.
Therefore, tourists’ backgrounds appear to in?uence their behaviors while at a destination,
supporting results earlier reported by Lew (1988) for visitors to Singapore.
The travel and tourism industry has paid attention to travelers’ needs, wants, and
preferences by supplying a much greater inventory of products and services, facilities, and
packages. Certain travelers may prefer sightseeing, visiting landmarks or historic places,
and going to museums and galleries. Others may focus on different activities such as going
to a beach, playing sports, dining, and relaxing. Some may want to do all of the above on the
same vacation (Hsieh et al., 1992). Therefore, expectations are that travel activities play an
important role in segmenting the market of visitors to an individual destination and across
various destinations.
In effect, the different types of activities chosen by visitors while vacationing are subgroups of
the total travel market. Analyzing the visitors to a destination by activity preferences can
provide advantages to both the travel industry and the travelers. For the travel industry, such
an analysis can improve industry pro?tability by enhancing appeal to speci?c target markets,
help in attracting newmarkets, and/or increase the volume of visitors in off-peak periods (Lang
et al., 1996). In addition, Morrison (1989) suggests that activity packages offer travelers
enhanced and convenient vacation planning, at an attractive price, while providing the exact
products and services required at the appropriate time and place. Packages can also result in
increased demand for more specialized activities and experiences.
De Grazia (1964) classi?es activities into active-passive, participant-spectator,
indoor-outdoor, in the home-outside the home and solitary-social. Later, Burch (1964)
identi?es four types of auxiliary activities such as family ?shing camps, nature study camps,
family water-skiing camps and overnight transient tourist group at forested campgrounds in
the Paci?c Northwest. Bishop (1970) uses a factor analytic technique to segment leisure
activities that included indoor and outdoor recreation. Hendee et al. (1977) suggest four
segments of category and de?nition of activity types: appreciative-symbolic,
extractive-symbolic, passive-free play and sociable-learning. McCool (1979) argues that
grouping activities into packages by their function might help tourism planners and
operators better understand what visitors are seeking while at a destination, and explain
their consequent behaviors and actions.
Davis and Chappelle (1993) segment the local tourist market of Michigan’s Upper Peninsula
into four groups based on the travel attributes sought by visitors. These four tourist segments
are gregarious sportsperson, rest and relaxation planners, camping enthusiast and
economical nature buff. Morrison and O’Leary (1994) segment the Australian domestic
travel market into six groups: younger beach resort, older VFR (visiting friends and relatives)
and sightseeing, older low activity and VFR, outdoor recreation, family beach and
sightseeing and younger active outdoor recreation.
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Lang et al. (1994) adopt activity-based segmentation to identify ?ve groups of Japanese
female overseas travelers. They are outdoor sports, sightseeing, life-seeing, activity combo,
and naturalists. Based on detailed interviews with visitors to Hong Kong, McKercher et al.
(2006) propose six different segments based on the activity styles of tourists. The different
consumption styles re?ect different movement patterns within the destination and re?ect
different personalities, motivations, the desired level of engagement and comfort with a
different culture. McKercher et al. (2002) segment the cultural tourism market in Hong Kong
into six discrete cultural tourism market segments based on activities. Spencer and Holecek
(2007), using a large sample of residents of six US states and one Canadian province,
highlight ?ve segments of visitors based on the activities participated in while traveling
during the fall season.
However, some criticize the practice of segmenting the tourist market for particular
destinations based on activities. McKercher and Chan (2005) suggest that many
researchers in the arena of special interest tourism (unique tourism segments such as
eco, cultural, sport, and culinary) confuse actions with motives. In addition, they suggest that
the literature that reports the percentage of special interest visitors to a destination may be
highly overestimated. In McKercher and Chan’s (2005) view, a tourist party which, for
example, visits a museum are not cultural tourists, unless visiting museums (engaging in
cultural activities) is the prime motivator for visiting the destination. In other words, a
three-hour visit to a museumto ?ll an afternoon while on a two-week holiday does not turn the
trip into a cultural tourism experience.
However, the sheer volume of literature supporting activity-based segmentation is
overwhelming. A total of years of literature support segmentation of the market for visitors
to a destination based on the activities pursued while at the destination. However, one
conclusion from a review of much of the literature on activity-based segmentation is the
tendency for many researchers to pigeonhole people, to be one-dimensional in their
?ndings. The tendency is to label a group of visitors one way, without recognizing that most
visitor behaviors are multi-dimensional. That is, for a person to travel to a destination and only
engage in one type of travel activity would be unusual. In a similar vein, one can assume that
very few travelers would have only one reason for visiting a destination (the exception might
be those visiting for business). For example, a cultural visitor may also engage in culinary
activities, or vice versa. Similarly, conventions held in exotic locations tend to attract more
participants implying that many delegates have other reasons for attending the business
event. Therefore, considering tourist segments on a continuum rather than as absolutes
seems a reasonable approach. Therefore, while cultural tourists may also try local cuisine,
they are more likely to be actively engaged in cultural rather than culinary pursuits.
This concept of continuums in tourism research is not new. Echtner and Ritchie (1993)
design techniques for the measurement of destination image based on the functional and
psychological components of the destination. They suggest a continuum exists from the
functional to the psychological, on which the different destination attributes will be located.
Ap and Crompton (1993), in a study of the impact tourism has on local residents, describe a
continuum of four responses for responding to tourism impacts: embracement, tolerance,
adjustment, and withdrawal. The number of tourists and their behaviors rather than a cultural
gap triggers their reactions.
Sautter and Leisen (1999) propose a tourism-planning model utilizing stakeholder theory
that suggests planning authorities consider the relationship/transaction strategy continuum
as a tool for developing and marketing relevant tourism services leading to a sustainable
tourism ventures. Orams (1995), based on a review of the various de?nitions of ecotourism,
presents the concept along a continuum that classi?es the various types of ecotourism
operations. He argues that desirable management strategies should be implemented that
shift the ecotourism experience to a more sustainable position. Carr (2002) models the
relationship between leisure and tourism and concludes there is a commonality between the
underlying in?uences that de?ne how people behave during their leisure and tourism
experiences. He suggests viewing leisure and tourismbehaviors on a continuumaffected by
individual culture, environment, motivations, and characteristics.
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Apostolakis (2003) develops a model that integrates the demand and supply side theories of
heritage tourism and highlights the existence of a continuum between the contrasting
theoretical approaches that links them in a coherent way. Weed and Bull (2004) develop a
sports tourism participation model that allows for the pro?ling of a range of characteristics of
sports tourism and illustrates a wide range of sports tourism types.
While the concept of continuums is not new in tourism research, this paper is one of the ?rst
that applies the concept to activity-based segments of the travel market.
3. Research questions
This article considers ?ve speci?c research questions. Is it possible to segment the market of
?rst-time pleasure visitors based on the activities the visitors undertake while at an island
destination? If so, which activities are the most important means by which to segment the
market? Can demographics, socio-economic variables, and tip-related characteristics
identify and pro?le distinct activity-related markets? Do the various segments exhibit
different spending patterns and are the identi?ed segments pro?table and sustainable? Are
there overlaps between the activity-based visitor segments? That is, are the identi?ed
segments absolutes or are they on a continuum? If on a continuum, the expectation is that
the range progresses from more to less involved in a particular activity.
To answer these research questions, ?rst-time pleasure travelers who spend at least one
night in a major island travel destination are studied.
4. Study data
This paper uses on the data collected during the Prince Edward Island Travel Survey of
Visitors (hereafter called the exit survey). Prince Edward Island (PEI) is Canada’s smallest
province, with just 1.4 million acres of land and a population of 139,000. PEI is located on the
east coast of Canada, and separated from its sister provinces of Nova Scotia and New
Brunswick by the Northumberland Strait. The 1997 opening of the Confederation Bridge
provided a permanent link to the mainland, resulting in a signi?cant boomin tourist numbers.
The natural products from the land and water of PEI, in part describe its unique character.
Agriculture and the ?sheries are the ?rst and third largest industries. PEI is called the
million-acre farm, and ?elds with rows of green potato plants set in the red soil of the Island
are a common sight. A combination of the red and green of the ?elds and the blue of the
water and sky make for striking scenery. This island landscape is one of the reasons why
over 1.1 million visitors per year are attracted to PEI, making tourism the second largest
industry.
The exit survey collects data from pleasure visitor parties (excluding business travelers)
spending at least one night in PEI during the 12-month period July 1, 2007 to June 30, 2008.
During this period approximately 367,000 of these travel parties exited PEI at one of the three
points at arrival or departure points for the province: the Confederation Bridge (77.5 percent
of travel parties), Northumberland Ferry (14.5 percent of travel parties), or the Charlottetown
Airport (8 percent of travel parties). On certain days throughout the year, as vehicles (at the
ferry) or individuals (at the airport) exit PEI, an intercept takes place and a qualifying
question asked. Depending on the response, the surveyor asks if the person will complete
the exit survey. The interviewer provides the respondent with the self-administered,
completed on site. In some cases, the individual does not have suf?cient time to complete
the survey, in which case the interviewer provides the person with a pre-paid return
envelope. The response rate to this survey distribution method is 74 percent.
At the Confederation Bridge, there is insuf?cient time to administer the survey in person. On
various days during the week, every non-Island vehicle receives an envelope as they pay the
bridge toll to leave PEI. The envelope contains a bilingual covering letter discussing the
survey and its purpose, an English and French copy of the survey, and a pre-paid return
envelope. The response rate to this survey distribution method is 17.5 percent (Tourism
Research Centre, 2008).
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This method achieved 4,539 surveys over the year, exceeding the original goal of 4,150
surveys. Overall, 69.9 percent of respondents are from Canada, 23.9 percent from the
US, and 6.2 percent from other countries. Following the actual visitor travel patterns, the
highest number of respondents is in the main season of July and August 2007, with a
subsequent fall shoulder, winter off-season, and spring shoulder. In terms of statistical
accuracy, a sample of this size has a very small sampling error of only 1.4 percent at a 95
percent con?dence level. The margins of error for each of the exit points is slightly higher,
however, the methodology over-samples the two exit points with less traf?c ensuring the
results are unbiased. Of all the overnight pleasure visitors to PEI over the survey year,
21.2 percent are ?rst-time visitors. This paper uses a sample of 1,104 exit surveys
completed by these ?rst-time visitors to PEI.
5. Variables
On the exit survey, respondents select from a list of 16 activities indicating the ones in which
they participated during this visit to PEI. This paper uses a subset of nine of these items.
They are: visiting historical and cultural attractions, visiting Canada’s birthplace attractions,
visiting Anne of Green Gables attractions, visiting a national or provincial park, attending a
live theatre performance, going to a beach, shopping for local craft/souvenir/antique, going
to a lobster dinner (meal), participating in other sports and/or outdoor activities. Analysis
calculates the R-square value of each item to cluster ?rst-time travelers.
While some of these variables are self-explanatory, others require some discussion. The
second item is associates PEI with the birthplace of Canada. In 1864, Charlottetown, the
capital of PEI, was host to an important conference that gradually evolved into a proposal to
unite the ?ve colonies to formthe country of Canada. In 1867, Canada became a country and
the Charlottetown Conference identi?ed as the beginning point of the process.
The third item, Anne attractions, refers to the book Anne of Green Gables written by the
internationally known Island author Lucy Maud Montgomery. The book, published in 1908, is
translated into 15 different languages, ?lmed, made into a television series, and is the title of
a musical production that has been staged in Charlottetown since 1965 and has toured the
world. The story imparts an image of PEI that each year draws thousands of visitors. As a
result, Anne of Green Gables is a major focus of the tourism industry in PEI.
Many national or provincial parks in PEI that provide hiking and biking trails, water and/or
beach access, picnic areas, playgrounds, and campgrounds. Normally, those visiting a
park engage in activities. Finally, lobster suppers have been a staple of PEI tourism and
part of the local dining experience for over 40 years. Community groups often run these
suppers in church halls, and view them as an integral part of the cultural experience on
PEI.
The pro?le of ?rst-time traveler characteristics in this study include several
socio-demographic variables, such as: origin, gender, age, marital status, education
level, employment status, annual household income. Trip related variables include primary
feature that attracted ?rst-time travelers to PEI, primary destination, party size and
composition of travel party, PEI regions stayed overnight, type of accommodations used,
number of nights stayed in PEI, number of nights stayed by region and by type of
accommodation. Expenditures by category are also included and in total, ratings of travel
service and quality, travel evaluation, future behavioral intentions, as well as
complaints/issues while visiting PEI.
6. Data analysis
A three-step process analyzes the exit survey data. First, all respondents are grouped by
using a K-means clustering procedure whereby a set of points is partitioned into k groups
(Pollard, 1981). This clustering method ?nds disjoint clusters (SAS Institute, 1990) with the
means of each activity item serving as an input. The algorithm groups respondents into
mutually exclusive cluster groups using nearest centroid sorting (Aldenderfer and Blash?eld,
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1984). Several repeating cluster solutions occur since the number of cluster groups is
subjectively decided based on interpretation and the number of cases within each cluster.
In the second step of the study, analysis of variance (ANOVA), multivariate analysis of
variance (MANOVA), and discriminant analysis are completed. Separate ANOVAs,
conducted on each of the nine activity items determines whether the variables in each
cluster group differed. MANOVA and discriminant analysis checks the overall signi?cance of
cluster group differences that statistically con?rmthe results of cluster analysis. Discriminant
analysis identi?es the selected activity variable’s in?uence on the cluster.
Finally, Chi-Square analyses for categorical variables, cross-tabulation results for
multiple-response variables, and ANOVA tests for parametric variables are run to
compare the differences between the clusters, identify socio-demographic and
trip-related characteristics of the clusters, and pro?le the clusters.
7. Results
The following ten tables present the results of the study. Table I indicates the characteristics
of the sample of ?rst-time visitors to PEI. Of the total surveys completed, 584 are Canadian
residents (52.9 percent), 364 are US residents (33.0 percent), while 156 are residents of
other countries (international) (14.1 percent). Among respondents, about 62 percent are
female, 84 percent are married, 56 percent worked full time, and 28 percent are retired.
Respondents vary widely in age, education level, and annual household income.
Table II summarizes the statistics relating to the clustering, ANOVA, MANOVA, and
discriminant analyses. This Table partitions the 1,104 ?rst-time travelers to PEI into three
cluster groups based on the nine activity items. Determination of the number of clusters is
based on the examination of the F-statistics from a two-, three-, four-, ?ve-cluster, etc.
solution derived from a K-means cluster analysis (Milligan and Cooper, 1985; Reynolds and
Beatty, 1999). The three-cluster solution is the most meaningful and interpretable.
Table II provides the clustering statistics for the 1,104 ?rst-time visitors to PEI. Of the total,
289 (26.2 percent) report high involvement in culture activities and are termed
culture-oriented tourists. A further 407 (36.9 percent) are high participants in nature- and
outdoor-based activities and are termed active tourists. Finally, 408 (37.0 percent) of the
respondents have very low participation rates in almost all of the nine activity items (with the
exception of going to a beach and attending a live theatre production) and are termed
casual tourists. This latter group seems to have traveled to PEI for relaxation purposes and
appears to be the group that closely ?ts the Gentle Island marketing theme adopted by the
PEI provincial government and tourismindustry in 2005. This theme, and the advertisements
developed around the theme, portrays PEI as the place to go to get away from your hectic
lifestyle and relax. In addition, once you arrive, you never want to leave. The remaining
clustering statistics indicate that the clustering model was an excellent ?t for the data.
The ANOVA statistics indicate the percentage of the respondents in each cluster that report
participating in the stated activity. A reviewof these numbers clearly illustrates that the clusters
have very different levels of participation for the selected activity items, supporting the labels
used to describe the clusters. The F-values reveal that the mean scores for all nine activities
are signi?cantly different at better than the 0.001 level for the three clusters. This result clearly
supports the method used to analyze the data. To further con?rm the clusters, four types of
MANOVA analyses indicate that the group differences in the activity items are all signi?cant at
better than the 0.001 level. Clearly, there are three distinct groups in this data.
Discriminant analysis examines which activity items highly contribute to the clusters (the
R-square and F-value in Panel B) and what percentage of hit ratio (or error count estimates
for cluster) exists in the identi?ed clusters (Panel D). The results indicate that the model
correctly classi?es 96.2 percent of the survey respondents into cluster groups. Of the nine
activity measures, visiting historical and cultural attractions is the most signi?cant contributor
to the clustering segments, closely followed by visiting a national or provincial park. The next
two activities (attending live theatre and shopping for local craft/souvenir/ antique) are
PAGE 160
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VOL. 6 NO. 2 2012
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signi?cant but minor contributors.
Table III indicates that active visitors are primarily from Ontario and the rest of Canada, while
casual visitors are more likely to be fromthe two other Maritime Provinces, fromQuebec, and
from International origins. This later result is surprising, as Tideswell and Faulkner (1999)
report that people traveling long distances engage in more activities while at a destination.
This is not the case for ?rst-time visitors to PEI. Consistent with Table II, culture seekers are in
the minority for all origin markets, though culture is a stronger motivation for those for the rest
of Canada and the US outside New England.
Table I Socio-demographic pro?le of the sample
Number %
Origin of ?rst-time visitors
Maritime (Nova Scotia and New Brunswick) 41 3.7
Quebec 168 15.2
Ontario 248 22.5
Rest of Canada 127 11.5
New England 95 8.6
Rest of US 269 24.4
International 156 14.1
Gender
Male 412 37.9
Female 675 62.1
Age
18 to 24 41 3.7
25 to 34 162 14.8
35 to 44 256 23.4
45 to 54 219 20.0
55 to 64 264 24.1
65 and over 152 13.9
Marital status
Married or living common-law 901 83.6
Single 177 16.4
Education level
Graduated high school or less 95 8.9
Some post-secondary 101 9.4
Graduated community or technical college 250 23.3
Graduated university (undergraduate) 371 34.5
Post graduate degree/Professional designation 257 23.9
Employment status
Working full time 607 55.5
Working part time or seasonally 75 6.9
Unemployed/retraining or upgrading 8 0.8
Retired 310 28.3
Homemaker 52 4.8
Student 30 2.7
Other 12 1.1
Annual household income ($)
Under 40,000 78 8.3
40,000 to 59,999 110 11.7
60,000 to 79,999 143 15.2
80,000 to 99,999 141 15.0
100,000 to 124,999 159 16.9
125,000 to 149,999 107 11.4
150,000 to 174,999 85 9.1
175,000 to 199,999 50 5.3
200,000 or more 66 7.0
Notes: Differences in frequency between total number of samples used (1,104) and respondents in
each category are due to missing values; total n=1,104
VOL. 6 NO. 2 2012
j
INTERNATIONAL JOURNAL OF CULTURE, TOURISM AND HOSPITALITY RESEARCH
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PAGE 161
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Table IV indicates that while males and females are equally likely to be culture-oriented,
females are more likely to be active visitors, while males heavily lean toward the casual
category when visiting PEI for the ?rst time.
Table V indicates that about 43 percent of the four age groups between 18 and 54 are either
active or casual visitors. A higher percentage of culture- oriented visitors are in the two older
age groups of over 55. Almost 47 percent of culture-oriented visitors are older visitors.
Table VI indicates that the largest portion of visitors with post-secondary education are
casual visitors, while those with high school or less or with post secondary education are
most likely to be active visitors.
Table VII illustrates that those working full-time are almost equally likely to be active or casual
visitors, while retirees are almost equally likely to be the culture-oriented or casual visitors. Of
interest too is that while retirees are 28.3 percent of total sample of ?rst time visitors, this
group accounts for 35.4 percent of the culture-oriented.
Table VIII indicates that ?rst-time visitors attracted by the natural beauty and pastoral setting
of PEI (42.2 percent of the overall sample) are more likely to be active visitors. This result
makes perfect sense as those attracted to a destination for this reason are more likely to go
Table III Origin of ?rst-time visitors by cluster
Cluster 1:
culture-seeking tourists
Cluster 2:
active tourists
Cluster 3:
casual tourists Total
Maritime
n 7 10 24 41
% (row) 17.1 24.4 58.5 100.0
% (column) 2.4 2.5 5.9 3.7
Quebec
n 29 63 76 168
% (row) 17.3 37.5 45.2 100.0
% (column) 10.0 15.5 18.6 15.2
Ontario
n 56 119 73 248
% (row) 22.6 48.0 29.4 100.0
% (column) 19.4 29.2 17.9 22.5
Rest of Canada
n 45 50 32 127
% (row) 35.4 39.4 25.2 100.0
% (column) 15.6 12.3 7.8 11.5
New England
n 26 34 35 95
% (row) 27.4 35.8 36.8 100.0
% (column) 9.0 8.4 8.6 8.6
Rest of US
n 80 87 102 269
% (row) 29.7 32.3 37.9 100.0
% (column) 27.7 21.4 25.0 24.4
International
n 46 44 66 156
% (row) 29.5 28.2 42.3 100.0
% (column) 15.9 10.8 16.2 14.1
Total
n 289 407 408 1,104
% (row) 26.2 36.9 37.0 100.0
% (column) 100.0 100.0 100.0 100.0
Notes: Chi-square statistics: x
2
value ¼ 46.88; df ¼ 12, p ¼ 0.000
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out and actively explore the area. Table VIII also shows that ?rst-time visitors attracted by
beaches and the coastline are equally likely to be active or casual visitors. The almost 15
percent of ?rst-time visitors attracted by the world of Anne of Green Gables are much more
likely to be the culture-oriented. Fittingly, those attracted by other features are casual visitors.
Table IV Gender of ?rst-time visitors by cluster
Cluster 1:
culture-seeking tourists
Cluster 2:
active tourists
Cluster 3:
casual tourists Total
Male
n 107 113 192 412
% (row) 26.0 27.4 46.6 100.0
% (column) 37.5 28.3 47.8 37.9
Female
n 178 287 210 675
% (row) 26.4 42.5 31.1 100.0
% (column) 62.5 71.8 52.2 62.1
Total
n 285 400 402 1,087
% (row) 26.2 36.8 37.0 100.0
% (column) 100.0 100.0 100.0 100.0
Notes: Chi-square statistics: x
2
value ¼ 32.45; df ¼ 2, p ¼ 0.000
Table V Age of ?rst-time visitors by cluster
Cluster 1:
culture-seeking tourists
Cluster 2:
active tourists
Cluster 3:
casual tourists Total
18-24
n 11 12 18 41
% (row) 26.8 29.3 43.9 100.0
% (column) 3.8 3.0 4.4 3.7
25-34
n 35 68 59 162
% (row) 21.6 42.0 36.4 100.0
% (column) 12.2 16.9 14.6 14.8
35-44
n 48 94 114 256
% (row) 18.8 36.7 44.5 100.0
% (column) 16.8 23.3 28.1 23.4
45-54
n 59 94 66 219
% (row) 26.9 42.9 30.1 100.0
% (column) 20.6 23.3 16.3 20.0
55-64
n 79 95 90 264
% (row) 29.9 36.0 34.1 100.0
% (column) 27.6 23.6 22.2 24.1
65 and over
n 54 40 58 152
% (row) 35.5 26.3 38.2 100.0
% (column) 18.9 9.9 14.3 13.9
Total
n 286 403 405 1,094
% (row) 26.1 36.8 37.0 100.0
% (column) 100.0 100.0 100.0 100.0
Notes: Chi-square statistics: x
2
value ¼ 29.78; df ¼ 10, p ¼ 0.001
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Table IX shows that of the ?rst-time visitors whose primary destination is PEI; the majority are
active visitors, while those with primary destinations other than PEI are mostly casual visitors.
Previous studies have indicated that visitor type (?rst time versus repeat) is a useful tool for
segmentation; this study also indicates origin is also useful supporting a number of earlier
studies (Lew, 1988; Flognfeldt, 1998; Bowden, 2003).
Table X presents spending data by travel segment. Clearly, the culture-oriented are the
highest spenders in total, per-party and per person per night. For this latter category, note
that while casual visitors do not engage in a great deal of activities, they do spend a
comparable amount on a per person per night basis as the culture-oriented visitors. This is
due to higher spending on accommodations and in restaurants.
In results that are unreported, travel party size for the culture-oriented (3.45 people) was
signi?cantly larger than for active (3.07) or casual (2.88) visitors, as is number of nights spent
on PEI (4.71 versus 4.51 versus 3.21). These differences explain why the total average
spending per party per visit for the culture-oriented segment is so much higher than the
other segments. The very large difference in total per party spending between the
culture-oriented and casual visitors is noteworthy, particularly when the average spending
per person per night is quite similar for the two segments. Finally, marital status, household
income, and travel party composition are not useful measures to segment this group of
visitors into one of the three clusters. For all three variables, the Chi-squares statistics are
insigni?cant.
8. Conclusions and implications
Segmenting the market for any product or service, in any industry, is vital in order to gain a
better understanding of the customer. Those operations that correctly segment the market
for their product or service will bene?t by being able to uncover groups of consumers that
Table VI Education level of ?rst-time visitors by cluster
Cluster 1:
culture-seeking tourists
Cluster 2:
active tourists
Cluster
3: casual tourists Total
Graduated high school or less
n 25 36 34 95
% (row) 26.3 37.9 35.8 100.0
% (column) 8.8 9.0 8.7 8.8
Some post-secondary
n 33 32 36 101
% (row) 32.7 31.7 35.6 100.0
% (column) 11.7 8.0 9.2 9.4
Graduated community or technical college
n 60 85 105 250
% (row) 24.0 34.0 42.0 100.0
% (column) 21.2 21.3 26.8 23.3
Graduated university (undergraduate)
n 93 123 155 371
% (row) 25.1 33.2 41.8 100.0
% (column) 32.9 30.8 39.5 34.5
Post graduate degree/professional designation
n 72 123 62 257
% (row) 28.0 47.9 24.1 100.0
% (column) 25.4 30.8 15.8 23.9
Total
n 283 399 392 1,074
% (row) 26.4 37.2 36.5 100.0
% (column) 100.0 100.0 100.0 100.0
Notes: Chi-square statistics: x
2
value ¼ 29.31; df ¼ 8, p ¼ 0.000
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are measurable, substantial, accessible, and sustainable. In that way, marketing dollars are
better spent and products or services developed that meet the needs of consumers,
resulting in operations that grow, prosper, and are sustainable.
Given the ever-expanding number of tourism destinations and the increased supply of
products and services, individual tourism destinations (and operators) should understand
their visitor market. The competition for visitors is intense and bound to become more so in
the future. The implication is that market segmentation is a strategic imperative. All tourism
industry stakeholders (various levels of government and the members of the industry) must
be aware of the market segments that are currently visiting their destination. If policy makers
understand their current customers, then strategies can be developed and implemented
that will result in more of these types of visitors traveling to the destination, or attempts made
to attract new and different segments. In this regard, islands, which are often more dif?cult
(and expensive) to travel to, may face unique challenges when compared to other
destinations.
This study segments the market for ?rst-time visitors to one Island destination, Prince
Edward Island (PEI), a small province on the east coast of Canada, and a major tourist
destination. The results answer ?ve important research questions concerning visitors to PEI.
First, segmentation of the market of ?rst-time visitors based on the activities the visitors
Table VII Employment status of ?rst-time visitors by cluster
Cluster 1:
culture-seeking tourists
Cluster 2:
active tourists
Cluster 3:
casual tourists Total
Working full time
n 136 238 233 607
% (row) 22.4 39.2 38.4 100.0
% (column) 47.2 59.1 57.8 55.5
Working part time or seasonally
n 25 26 24 75
% (row) 33.3 34.7 32.0 100.0
% (column) 8.7 6.5 6.0 6.9
Unemployed/retraining or upgrading
n 2 4 2 8
% (row) 25.0 50.0 25.0 100.0
% (column) 0.7 1.0 0.5 0.7
Retired
n 102 93 115 310
% (row) 32.9 30.0 37.1 100.0
% (column) 35.4 23.1 28.5 28.3
Homemaker
n 12 26 14 52
% (row) 23.1 50.0 26.9 100.0
% (column) 4.2 6.5 3.5 4.8
Student
n 10 9 11 30
% (row) 33.3 30.0 36.7 100.0
% (column) 3.5 2.2 2.7 2.7
Other
n 1 7 4 12
% (row) 8.3 58.3 33.3 100.0
% (column) 0.3 1.7 1.0 1.1
Total
n 288 403 403 1,094
% (row) 26.3 36.8 36.8 100.0
% (column) 100.0 100.0 100.0 100.0
Notes: Chi-square statistics: x
2
value ¼ 24.56; df ¼ 12, p ¼ 0.017
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undertake while at a destination. The results indicate that there are three distinct segments of
visitors: culture-oriented (26 percent of the market), active (37 percent of the market), and
casual (37 percent of the market).
The results for the casual tourists seemto suggest that the millions that the public and private
sectors are spending on branding and marketing PEI as The Gentle Island are only partially
working. These visitors seem to view PEI as a place to lay back, relax, and get away from a
hectic lifestyle. While this segment is a substantial portion of visitors to PEI, the other two
segments account for almost two-thirds (63 percent) of visitors, and do not appear to be
re?ected in the marketing campaign. This ?nding highlights a potential marketing
opportunity for the PEI tourism industry.
Second, for this study the four key activity factors used to segment the market are visiting
historical and cultural attractions, visiting a national or provincial park, attending a live
theatre performance, and shopping for local crafts, souvenirs, and/or antiques. The
differences in the participation rates for these four activities between the three segments are
striking. As expected, the culture-oriented segment reports the highest participation rate for
Table VIII Primary features that attracted ?rst-time of ?rst-time visitors by cluster
Cluster 1:
culture-seeking tourists
Cluster 2:
active tourists
Cluster 3:
casual tourists Total
Natural beauty and pastoral settings
n 117 177 137 431
% (row) 27.1 41.1 31.8 100.0
% (column) 44.5 44.7 37.7 42.2
Beaches and coast line
n 33 97 96 226
% (row) 14.6 42.9 42.5 100.0
% (column) 12.5 24.5 26.4 22.1
World of anne of green gables
n 64 40 48 152
% (row) 42.1 26.3 31.6 100.0
% (column) 24.3 10.1 13.2 14.9
Canada birthplace attractions
n 8 7 1 16
% (row) 50.0 43.8 6.3 100.0
% (column) 3.0 1.8 0.3 1.6
Golf
n 3 7 6 16
% (row) 18.8 43.8 37.5 100.0
% (column) 1.1 1.8 1.7 1.6
Culinary experience
n 6 11 9 26
% (row) 23.1 42.3 34.6 100.0
% (column) 2.3 2.8 2.5 2.5
Outdoor activities
n 1 16 3 20
% (row) 5.0 80.0 15.0 100.0
% (column) 0.4 4.0 0.8 2.0
Other features
n 31 41 63 135
% (row) 23.0 30.4 46.7 100.0
% (column) 11.8 10.4 17.4 13.2
Total
n 263 396 363 1,022
% (row) 25.7 38.7 35.5 100.0
% (column) 100.0 100.0 100.0 100.0
Notes: Chi-square statistics: x
2
value ¼ 70.44; df 14, p ¼ 0.000
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the ?rst and third activity, while the active segment clearly preferred activity two and four.
Given their laid-back status, the casual tourists do not lead in the participation in any of the
activities; though over half do visit a beach, an activity that is often a part of a relaxing
holiday. The implication of this result is that destinations can be very speci?c when marketing
to speci?c activity-based segments for ?rst-time visitors. These visitors appear drawn to PEI
due to the availability of these activities.
Third, demographics, socio-economic variables, and tip-related characteristics identify and
pro?le distinct activity-related markets. Based on these results, the activities visitors pursue
while on PEI because of their origins, supporting earlier results reported by Bowden (2003),
among others. In addition, gender, age, education, employment status, trip motivation, and
primary destination visited are all useful variables to differentiate visitors to PEI. These results
support many previous studies that have used these and other variables to segment the
visitor market. The implication of this result is that these basic visitor and trip variables,
already collected by most destinations around the world, are useful to segment the ?rst-time
visitor market.
Table IX Primary destination of ?rst-time visitors by cluster
Cluster 1:
culture-seeking tourists
Cluster 2:
active tourists
Cluster 3:
casual tourists Total
Prince Edward island
n 161 237 181 579
% (row) 27.8 40.9 31.3 100.0
% (column) 56.7 59.1 45.0 53.3
Other destinations
n 123 164 221 508
% (row) 24.2 32.3 43.5 100.0
% (column) 43.3 40.9 55.0 46.7
Total
n 284 401 402 1,087
% (row) 26.1 36.9 37.0 100.0
% (column) 100.0 100.0 100.0 100.0
Notes: Chi-square statistics: x
2
value ¼ 17.79; df ¼ 2, p ¼ 0.000
Table X Travel expenditures of ?rst-time visitors by cluster
Cluster 1:
culture-seeking
tourists
(n ¼ 289; 26.2%)
Cluster 2:
active tourists
(n ¼ 407;
36.9%)
Cluster 3:
casual tourists
(n ¼ 408;
37.0%)
Total
(n ¼ 1,104) F-value
Total average spending per party per visit $1,345.96
a
$1,099.06 b $935.64 c $1,102.65 14.79***
Total average spending per party per night $321.35
a
$277.80
b
$305.56
ab
$298.97 4.73**
Total average spending per person per visit $529.07
a
$422.50
b
$382.00
b
$434.95 11.51***
Total average spending per person per night $128.06
a
$107.47
b
$124.51
a
$118.90 7.58**
Categories of spending
Accommodation $49.19
a
$39.80
b
$53.13
a
$47.03 10.89***
Restaurants $24.70
ab
$23.08
b
$27.13
a
$24.96 4.04*
Food and beverage at stores $5.74
ab
$6.62
a
$4.80
b
$5.73 4.05*
Vehicle operation and local transportation $10.48 $11.00 $11.48 $11.04 0.43
Car rentals $4.19
a
$1.14
b
$2.59
b
$2.45 7.81***
Shopping $15.47 $15.39 $11.01 $13.82 2.80
Recreation and entertainment $14.20
a
$7.46
b
$13.03
ab
$11.20 20.32***
Other expenditures $4.08 $2.97
ab
$1.35
b
$2.67 3.67*
Notes: Total average expenditures and categories of spending in these results were based on all ?rst-time travelers rather than those who
only reported spending on that category; Categories of spending indicate average spending per person per night;
a
,
b
, and
c
indicate
results of the post hoc test for each variable using Duncan’s multiple range test; *p,0.05; **p , 0.01; ***p , 0.001
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Fourth, the various segments do show different spending patterns implying that certain
?rst-time visitor markets are more attractive and more pro?table for the tourism industry on
PEI. While the average spending of ?rst-time visitors to PEI is about $119 per person per day,
the culture-seeking segment is the highest spending on both a person per day and total trip
spending basis. Apparently, the three segments are sustainable and pro?table for the PEI
tourism industry. The implication of this result is that different segments vary in terms of their
economic importance to destinations. While all segments must be measurable, some are
more substantial than are others.
Fifth, the study identi?es three visitor segments but based on these results, these represent a
continuum of activities rather than absolutes. That is, culture-oriented tourists are highly
involved in cultural activities while visiting PEI, but they also engage in many nature and
outdoor-based activities, while the active visitors also participate in some cultural activities.
In addition, the casual tourists participate in activities while visiting PEI, but at much lower
rates when compared to the other segments. Thus, while these visitors do participate in
activities, the participation is not at the same level as the two other segments. So, the
continuumof highlighted activities across the segments range frommore to less involved. All
of the segments are involved in all of the activities, but to very different degrees.
Based on these results, tourismresearchers, policy makers, and operators should recognize
that the majority of visitors to a destination do not engage in only one type of travel activity
(Hsieh et al., 1992). This key ?nding also suggests that travelers have more than one reason
for visiting a destination. Therefore, when marketing to a particular segment, marketing
should highlight other major activities that are available at the destination.
For example, when marketing to a culture-oriented segment, also highlight the culinary or
outdoor activities available at the destination. Logically then, the marketing of destinations
could use packages of products or services, with the package detail contingent on the
market segment of interest (McCool, 1979; Morrison, 1989). Consequently, destinations that
cater to the needs of their important segments of visitors will increase their probability of
success in this highly competitive industry but those that ignore this maxim may struggle to
?nd a sustainable consumer base.
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Further reading
Kotler, P. and Armstrong, G. (1991), Principles of Marketing, 5th ed., Prentice Hall International,
Englewood Cliffs, NJ.
Kotler, P., Haider, J. and Rein, I. (1993), Marketing Places: Attracting Investment, Industry and Tourismto
Cities, States and Nations, The Free Press, New York, NY.
Sollner, A. and Rese, M. (2001), ‘‘Market segmentation and the structure of competition: application of
the strategic group concept for an improved market segmentation on industrial markets’’, Journal of
Business Research, Vol. 51 No. 1, pp. 25-36.
About the authors
Sean Hennessey is a Professor in the School of Business at the University of Prince Edward
Island (PEI) in Canada. He is also the founding Faculty Director of the Tourism Research
Centre located in the School of Business. His research interests include pro?ling the
characteristics of visitors and their impact on destinations. He has published 12
tourism-related papers, written numerous reports, and presented to various stakeholders
on this topic. He is the author of three books and has published over 20 other papers in
peer-reviewed journals. He teaches in the areas of ?nance and business research. Sean
Hennessey is the corresponding author and can be contacted at: [email protected]
Dongkoo Yun is Senior Development Analyst at the Tourism Research Centre (TRC) at the
School of Business at the University of PEI, an independent agency dedicated to tourism
research, funded by both the provincial and federal governments. He received his PhD from
the Department of Tourism Management at Kyonggi University, Seoul, Korea. He taught
tourism-related courses in Korea for many years. His current research embraces the
experiential aspects of tourists’ consumption, and he is a specialist in analyzing and mining
tourism data.
Roberta Macdonald is a Professor and Dean of the School of Business at the University of
PEI. She teaches in the marketing ?eld as well as business research and strategy. Her
research interests include tourist behaviors and cultural tourism, international business
marketing, and real-world management education. She has published over 30
peer-reviewed articles. Before entering academia, she worked for several national and
international ?rms in marketing management.
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