Tourism ReviewEmerald Article: Sport motivation as driver for segmenting sport tourists in coastal regionsKirstin Hallmann, Svenja Feiler, Christoph Breuer

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To cite this document: Kirstin Hallmann, Svenja Feiler, Christoph Breuer, (2012),"Sport motivation as driver for segmenting sport tourists in coastal regions", Tourism Review, Vol. 67 Iss: 2 pp. 4 - 12

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Sport motivation as driver for segmentingsport tourists in coastal regions

Kirstin Hallmann, Svenja Feiler and Christoph Breuer

Abstract

Purpose – The market for sport tourists is very diverse and motivations of sport tourists are manifold.

This also applies to the field of water sport tourism, which has not yet intensely been analysed by

researchers. In order to analyse motivations and to reach target groups such as water sport tourists

adequately, market segmentation is necessary. The purpose of this paper is to investigate sport

motivations of tourists during their holidays as well as the tourist’s participation in water sport activities,

using the example of the German North Sea island Sylt. Thereby, consumer profiles will be established.

Design/methodology/approach – A quantitative research paradigm was chosen. A survey was

conducted using a standardised self-administered questionnaire. The sample comprised n ¼ 263

participants. Two indices, one for sport motivation and one for travel motivation were constructed.

Factor, as well as cluster, analysis was applied to segment the sample. Furthermore, discriminant

analysis was used to identify differences between the two clusters. Finally, cross tabulations underlined

the differences between the clusters.

Findings – Overall, 47.1 per cent of the sample takes part in water sports. The cluster analysis based on

motivational factors revealed two groups, the casuals and the committed. Significant differences were

detected between the groups with regard to sport and holiday consumption patterns and sport

expenditures. However, there were no significant socio-demographic differences between the clusters.

Practical implications – It is shown that segmentation of travellers is useful to reach the different target

groups and offer unique products and services, depending on, e.g. age and sport preferences.

Originality/value – The results of this research indicate the diverse nature of water sport tourists and

their underlying motivations. It is shown that holiday sport motivation depends on the actual sports

practiced by the travellers, implying that prior sport motivation and involvement influence travellers’

sport motivation. Overall, this research highlights the importance of segmenting sport tourists.

Keywords Consumer profiles, Consumer behaviour, Expenditures, Tourism, Water sports

Paper type Research paper

1. Introduction

As sport activity is often bound to the travel motive which can be either active (participating)

or passive (watching), sports tourism can be described as a heterogeneous phenomenon

(Weed and Bull, 2004) and therefore, travel behaviour is determined by a wide range of

motivations, including different sports activities, e.g. water sports. Especially destinations at

a coast offer tourist operators a good opportunity to reach the tourists’ needs by offering a

range of water-based activities (Morgan et al., 2005). Surfing tourism, for example, has

become a global industry in the twenty-first century (Ponting, 2009). The field of water sport

tourism is not yet a deeply researched area. As the market for sport tourists is very diverse,

market segmentation is necessary in order to reach certain target groups adequately, such

as water sport tourists. Thereby, segmentation makes it easier to understand and target

specific groups that have similar characteristics and behaviours. Segmentation is applied

through different approaches, which can basically be divided into two categories: objective

or physical and subjective or behavioural attributes. The former group includes

PAGE 4 j TOURISM REVIEW j VOL. 67 NO. 2 2012, pp. 4-12, Q Emerald Group Publishing Limited, ISSN 1660-5373 DOI 10.1108/16605371211236097

Kirstin Hallmann is Senior

Lecturer and Researcher,

Svenja Feiler is Lecturer

and Researcher and

Christoph Breuer is

Professor, all at German

Sport University Cologne,

Cologne, Germany.

characteristics such as demographics (age and gender), socio-economics (income and

education), and geographics (residence and area) (Liu et al., 2008). The latter includes

psychographics (attitudes and values) and behavioural attributes (Johns and Gyimothy,

2002). Moreover, motivational factors should be considered when segmenting tourism

markets (Bieger and Laesser, 2002). Traditionally, segmentation has been conducted on the

basis of demographics and socio-economic variables. However, this approach has

repeatedly been criticised and recently, segmentation based on subjective attributes has

been regarded as more effective (Liu et al., 2008).

The purpose of this paper is to investigate sport motivations of tourists during their holidays

as well as the tourist’s participation in water sport activities, using the example of the German

North Sea island Sylt. Thereby, consumer profiles will be established.

2. Literature review

Although sport tourism has attracted high attention among scholars and practitioners with

regard to improving event and destination images and to differentiate the product and

thereby attracting more tourists (e.g. Chalip et al., 2003), the sport economic perspective on

water sport tourism and especially visitor’s expenditures for water sports has only produced

a very small body of literature, apart from economic impact studies (e.g. Kurtzman, 2005).

O’Brien (2007) dealt with event leverages of surfing events in a more regional context as well

as the benefit which can be generated for the host community using Chalip’s (2004) general

model for host community benefit. Apart from investigating different aspects of surfing,

e.g. culture (Booth, 1994; Lanagan, 2002; Law, 2001; Pearson, 1979), motivation (Farmer,

1992; Stranger, 1999), and tourism (Buckley, 2002a; Buckley, 2002b; Dolnicar and Fluker,

2003; Ponting et al., 2005), few studies (e.g. Morgan et al., 2005) have been conducted

dealing with water sports although water sports provide an opportunity for physical exercise

which goes along well with the trend of living a healthy lifestyle (Ratcliffe, 1992). In an attempt

to close this gap, Jennings (2007) provides a general overview of water-based tourism by

dealing with sailing, surfing, fishing, diving, rafting, and kayaking. Apart from the mentioned

literature, several studies dealt with segmentation in a sport (e.g. Mahony et al., 2000;

Zapalac et al., 2010) or tourism (e.g. Hsu and Kang, 2007; Mudambi and Baum, 1997)

context, expenditures (Dolnicar and Fluker, 2003; Downward et al., 2009), and motives of

sport tourists (e.g. Funk et al., 2007).

To add to the small body of literature for water sports, Dolnicar and Fluker (2003) conducted

a study on behavioural market segments among surf tourists and found six segments.

Differences in the segments, e.g. length of the stay, were determined by age of the surfers

and experience. Worldwide surfers appeared to have the highest income level. No

significant differences were detected for travel companions (one to four) and daily budget.

For all groups there was a male dominance (between 90 per cent and 98 per cent). Surfing

was among the first of the so-called extreme sports (Ryan, 2007), which focus on a

combination of fun and risks (Midol, 1993). Participants of these sports formed a sub-cultural

lifestyle (Pearson, 1979), which was characterised by a high degree of individualism (Ryan,

2007) and applied more to younger tourists (Oliveira and Pereira, 2008). Regarding sailing, it

was found that the majority of men and women were aged between 40 and 59, travelling

without children, and had completed tertiary education (Jennings, 2005 cited after Jennings,

2007). A further water-based activity, which was highly attractive for international tourism

was scuba diving. From a global perspective, market characteristics were highly

heterogeneous and the diving market had changed from a formerly male, experienced,

rich or intrepid dominated market to a more dynamic environment. This was due to the

growing number of people travelling for the purpose of diving and snorkelling (Dimmock,

2007). Different empirical studies proved this heterogeneous profile. The average diver at

the Mediterranean coast for example was described as middle-aged (31 to 45), male, of

medium or high socio-economic level, and employed in middle- to high-level professional

activities (Mundet and Ribera, 2001). On the other hand, it was found that in Australia, visitor

profiles to the Great Barrier Reef include various age groups (20-29; 30-39; 40-49).

Moreover, half of the diving tourists were female.

VOL. 67 NO. 2 2012 jTOURISM REVIEWj PAGE 5

Regarding expenditures, the daily budget that surfers had at their disposal ranged from

$A21 to $A100 (Dolnicar and Fluker, 2003) while the average total spending of Germans

being on holidays amounts to e861, with an average of 12.3 days yearly of holidays

(Wiegand et al., 2011). Motives of sport tourists were manifold and sport as well as travel

motivation is likely to originate from the interaction of tourism and sport sources (Funk et al.,

2007) such as destination image (e.g. Baloglu and McCleary, 1999; Dann, 1996), prior sport

motivation, gender (Funk et al., 2007), and cultural background (Hofstede, 2001). This was

proved in a study on the motives of international participants taking part in an Australian

hallmark running event (Funk et al., 2007). It appeared that participation is mainly driven by

prior running involvement, the desire to take part in organized running events, social

interaction, favourable beliefs and feelings toward the host destination, perceived benefits of

escape, relaxation, prestige, as well as cultural experiences (Funk et al., 2007).

3. Methodology

3.1 Measurement

For this study, a quantitative research paradigm was chosen. A survey was undertaken on

the island Sylt in the German North Sea, using a standardised self-administered

questionnaire, which was developed based on previous work in the field of travel and

sport motives (Funk et al., 2007) and sport expenditures (Wicker, 2009). It contained 16 open

as well as closed-ended questions and consisted of different sections investigating travel

motives (using a five-point Likert scale), frequency of sport vacations, importance of sport

during vacations, expenditures for sport activities, and further activities during the

vacations. Moreover, socio-economic data of the respondents was gathered (age, gender,

education, income).

3.2 Data collection

The study population is comprised of sport tourists on the island Sylt which was chosen

because it is a well-established coastal destination and quite popular among water sport

tourists in Germany. The survey was conducted from August 5-11, 2010 by three

interviewers. The study population was approached in the city centre of the island’s main

town, at the beach, in a youth hostel, and at a camping ground. These different sites were

chosen to question a diverse range of tourists at the island and due to accessibility[1]. Thus,

a non-random convenience sample was used. The total sample comprised n ¼ 263

participants.

3.3 Data analysis

The data analysis was conducted by using SPSS 19. Two indices were constructed, one for

sport motivation (based on ten items) and one for travel motivation (based on 15 items), each

ranging from 0 (lowest motivation) to 100 (highest motivation). Both indices showed a good

reliability, with Cronbach’s alpha being satisfactory (0.86 for the sport motivation index and

0.79 for the travel motivation index) and thereby being above the threshold of 0.6 or 0.7

which is frequently reported (Hair et al., 2006).

First, to enable further investigation of sport motivation, these items were factor analysed

using principal components with varimax rotation to determine the underlying components.

Following the scree test and the Kaiser criterion, a two factor solution was suggested.

Subsequently, the two strongest variables loading on the first factor and the three strongest

variables loading on the second factor were used in the cluster analysis to segment the sport

consumers. Two outliers were detected and excluded from the data analysis. The cluster

analysis involved two steps. First, a hierarchical cluster analysis using Ward’s method was

performed with half of the sample to determine the number of clusters. The dendograms

suggested a two cluster solution being appropriate. Hereafter, the quick cluster technique

based on k-means was conducted using the two clusters on the entire sample.

Moreover, the differences between the clusters were identified using discriminant analysis.

The clusters served as dependent variable. Finally, the profiles of the sport tourists were

PAGE 6 jTOURISM REVIEWj VOL. 67 NO. 2 2012

further illuminated using cross tabulations with the chi square statistics indicating significant

differences between the clusters.

4. Results

The sample consists of 49 per cent male and 51 per cent female participants. The average

age is 32 years and 28.4 per cent of the sample has a higher education (at least university

entrance diploma). On average, participants go on two holiday trips per year, which include

physical activities and the average length of a trip in Germany reaches ten days. Sport

tourists have three fellow travellers and 31.2 per cent of all questioned visitors stay in a hotel.

Different sport motives were measured, showing that sport is seen as valuable (3.90),

important (3.94), needed (3.81), involving (3.79), and fascinating (3.68). Furthermore, there

is evidence that people believe that sport on holidays is vitally important to them (3.64), they

regret when they cannot take part in sport on holidays (3.55), and they are really interested in

sport during holidays (3.48). These results are displayed in Table I.

Moreover, the main travel motive of a holiday trip is to relax (4.52) and to leave the normal life

behind (4.28). The overall sport motivation is moderate (64.12) whereas travel motivation is

slightly higher (68.65). Of the sample 47.1 per cent takes part in water sports (including

swimming). Apart from swimming, surfing reaches the highest participation rate among

water sports.

The results of the factor analysis suggest a two-factor solution: running involvement and

strength of running motivation (see Table II) form the two factors. The items loading on

involvement were fascinating, valuable, needed, involving, and important with the latter

three variables loading strongest on involvement. The remaining five variables loaded all on

strength of running motivation. The eigenvalue of the first factor amounted to 4.454 and for

the second factor to 1.311, explaining overall a cumulated variance of 57.64 per cent. The

Table I Summary statistics

Variable Mean Standard deviation

Age 31.690 13.754Female (in %) 0.510 0.501Higher education (in %) 0.384 0.487Net income: e0-e1,000 0.376 0.485Net income: e1,001-e2,000 0.262 0.441Net income . e2,001 0.247 0.432Mundane – fascinating 3.680 0.866Worthless – valuable 3.900 0.895Not needed – needed 3.808 0.917Not involving –involving 3.793 1.013Not important – important 3.934 0.928I regret when I am unable to participate in sports while being on vacations 3.550 1.046I feel that participating in sport while being on vacations events is vitally important to me 3.644 0.928I am really interested in participating in sports while being on vacations 3.479 0.991I feel that spending time participating doing sports while being on vacations is moreworthwhile than spending time participating in other leisure activities 2.880 0.935Even when participating in sports while being on vacations is events is inconvenient, I stilltry to participate 2.900 0.935Sport motivation 64.122 15.802Total motivation holiday trip 68.646 12.369Sport expenditures 37.123 91.002Kite-surfing (in %) 0.027 0.162Sailing (in %) 0.015 0.123Surfing (in %) 0.149 0.357Swimming (in %) 0.272 0.446Diving (in %)Non-water sports (in %) 0.529 0.500No. of holiday trips per year (3 þ ) 0.287 0.453n 261

VOL. 67 NO. 2 2012 jTOURISM REVIEWj PAGE 7

rather average quality of explained variance could be permitted, if other quality criteria are

satisfied. As the factor loadings of all variables are over 0.4 quality can be ensured

(Pohlman, 2004).

Based on the most predominating sport motivation variables, the sample was clustered into

two groups (see Table III). The first cluster encompasses those people who believe that sport

is somewhat needed and important, are medium involved with sports, feel that sport during

holidays is rather important, and are somewhat interested in sports while being on vacations.

This cluster is called Casuals. In contrast, the second cluster is named Committed as the

mean values for all variables integrated into the cluster analysis exceed 4.1.

Significant differences between the clusters were detected through an ANOVA. The largest

F-value was reached for being interested in sports while being on vacations (F ¼ 224.736,

p ¼ 0.000), which shows that the clusters differ most on this variable. All items were

significant between the clusters.

The results of the discriminant analysis confirm the two cluster solution. The eigenvalue of

function 1 amounted to 2.158 and this function has a canonic correlation of 0.827 (Wilks’

Lambda ¼ 0.317, p , 0.000). Therefore, the differences between the clusters are

confirmed. The classification matrix revealed that 98.2 per cent of all cases were

categorised correctly.

The clusters were tested for differences with regard to the socio-demographic and sport

profile. The results (see Table IV) suggest that the socio-demographic profile does not differ

significantly between the two clusters. However, the sport consumption differs significantly

between the Casuals and the Committed. The Committed tend to go more sailing, surfing,

Table II Results of the exploratory factor analysis

Variable Strength of sport motivation Involvement

Mundane – fascinating 0.544Worthless – valuable 0.509Not needed – needed 0.621Not involving – involving 0.619Not important –important 0.729I regret when I am unable to participate in sports while being on vacations 0.618I feel that participating in sport while being on vacations events is vitally important to me 0.683I am really interested in participating in sports while being on vacations 0.873I feel that spending time participating doing sports while being on vacations is moreworthwhile than spending time participating in other leisure activities 0.616Even when participating in sports while being on vacations is events is inconvenient, I stilltry to participate 0.547Eigen value 4.454 1.311Variance explained in % (57.64) 44.536 13.106KMO 0.868Bartlett’s Test for Sphericity x 2¼1,007.108*

Notes: Principal components analysis with varimax rotation; *p , 0.001

Table III Sport motivation variable means among clusters

Variable Cluster 1: Casuals Cluster 2: Committed F-value p-value

Not needed – Needed 3.34 4.24 80.403 0.000Not involving – Involving 3.14 4.39 157.934 0.000Not important – Important 3.30 4.51 192.556 0.000I feel that participating in sport while being onvacations events is vitally important to me 3.06 4.18 145.741 0.000I am really interested in participating in sportswhile being on vacations 2.78 4.13 224.736 0.000n 125 136

PAGE 8 jTOURISM REVIEWj VOL. 67 NO. 2 2012

and kite-surfing while the Casuals are more involved with swimming, diving and non-water

sports. Moreover, the Committed go significantly more often annually on holidays and have

higher sport expenditures.

5. Discussion

The descriptive results confirm prior research insofar as the sport tourist market is very

heterogeneous (e.g. Mundet and Ribera, 2001; Shafer et al., 1998) and encompasses

various age groups, depending on the actual sports practiced. The average age of this

sample is 32 years, but the age range goes from 12 to 74 years. This might imply that sports

such as sailing might be predominantly practiced by committed sportspersons who are

middle aged and older people whereas surfing is preferred by a younger generation which

is also committed to sports while being on holidays (cluster 2). This is confirmed in prior

studies (Oliveira and Pereira, 2008). It cannot be confirmed that sport tourists are

predominantly male, as in the study of Dolnicar and Fluker (2003), since 51 per cent are

female within this study. Nevertheless, this might be ascribed to the fact that Dolnicar and

Fluker (2003) only dealt with surfing, not with water sports in general. Insofar, the second

cluster fits to the outcomes of the surfing study, as members of this cluster are male and take

part in surfing amongst other sports.

The results of the factor analysis support the findings of prior research (Funk et al., 2007) with

regard to a two factor structure labelled involvement and strength of motivation, although

tested on a sample of runners instead of water sport tourist and employing confirmatory

Table IV Demographic and sport profile of the two clusters of sport tourists (in percentage)

Variable Cluster 1: Casuals Cluster 2: Committed x2 p-value

Gender 2.053 0.095Male 44.8 53.7Female 55.2 46.3Age 4.181 .382Up to 18 27.2 22.118-24 18.4 14.025-34 20.8 19.135-44 18.4 21.345þ 15.2 23.5Higher education 6.340 0.175Basic compulsory schools 13.8 9.8Secondary school 41.5 30.1Secondary school with 6th form 12.2 15.8A-levels (university entrance diploma) 11.4 13.5University degree 21.1 30.8Net income (e) 3.929 0.2690-1,000 38.4 37.51,001-2,000 31.2 22.1.2,001 20.8 27.2Missings 9.6 13.2Sports 19.700 0.003*Kite-surfing 1.7 3.8Sailing 0 3.0Surfing 8.6 21.8Swimming 33.6 24.1Diving 1.7 0Non-water sports 54.3 47.4No. of holidays per year 8.939 0.002*Up to 2 80.0 63.23 þ 20.0 36.8Sport expenditures (e) 10.766 0.001*Up to 50 92.0 77.251 þ 8.0 22.8

Note: *p , 0.01

VOL. 67 NO. 2 2012 jTOURISM REVIEWj PAGE 9

factor analysis. Yet, the prevalence of involvement and strength of motivation as important

factors of sport tourists is obvious and confirms Funk et al.’s work (2007). Apparently, the

involvement and the strength of motivation is higher for one of the clusters, cluster 2, which

was therefore named Committed. Yet, even for the Casuals, sport plays some role while

being on holidays, indicating the importance of that type of leisure activities.

Moreover, this result fits well to what was found by Jennings (2005 cited after Jennings,

2007), namely that people with a higher socio-economic status can afford to take part in

water sports, particularly sailing and surfing (cluster 2). Contrary to the results of Funk et al.

(2007), gender did not have a significant influence on sport motivation. Thereby, it could be

inferred that motives of water sport tourists might differ from other sport tourists. The

significant differences among the clusters for sport expenditure can be attributed to the

different involvement and strength of motivation. A person that is higher involved (and has

more money at his/her disposal) is more likely to spend more (cluster 2).

A limitation of this study is the fact that the survey took only place on one German island.

Thus, to make generalisations, investigations in further coastal regions would be needed.

Nevertheless, what can be stated is that taking part in surfing, hiking, and other non-water

sport such as golf actually do influence the sport motivation of tourists which might be

transferable to other islands or coastlines where these sports are offered. This could be

explained by the fact that these sports are particularly practiced during vacations and are

therefore main motives of tourists. Another limitation is the non-random sample. Yet, the

summary statistics suggest that the sample is very diverse. The values for total expenditure

and average length of travel correspond with previous findings (Wiegand et al., 2011), which

applies as well to the socio-demographics (Funk et al., 2007) indicating that a representative

sample was drawn.

6. Conclusions and implications

The aim of this study was to identify market segments of tourists with regard to their holiday

sport motivation and participation in different types of sports in coastal regions. Through

cluster analysis, two consumer segments were identified. This shows that tourists in coastal

regions differ in their motives and the sport they perform during their vacation.

Several implications arise based on the results. On the one hand, with regard to practice it is

shown that a segmentation of travellers is useful in order to reach the different target groups

and offer unique products and services, depending on, e.g. age and sport preferences. An

example pertaining to the second cluster could be to offer medium-aged and older travellers

the opportunity to stay in good accommodation, close the waterfront where surfing

programs are offered, swimming is possible, and sailing opportunities exist. In contrast,

swimming seems to be of particular importance for the Casuals and in targeting this group,

this activity should be highlighted as well as non-water sport activities. This could be done

using adequate visuals that portray these leisure opportunities and the particular ambiance

and atmosphere associated with them. Moreover, the results implicate for theory that holiday

sport motivation depends on the actual sports practiced by the travellers. This also means

that prior sport motivation and involvement certainly do influence the sport motivation of

travellers. Thus, sport offers of coastal destinations should be adapted to what the different

tourists are seeking. Future research should thus look into the diverse water sport activities

and collect data from a wider sport tourist population and different coastal regions to permit

generalisability.

Note

1. Camping grounds and youth hostels are quite popular with younger people and families while

almost every tourist on Sylt spends some time at the beach. Medium-aged and older people are

often seen in the city centre.

PAGE 10 jTOURISM REVIEWj VOL. 67 NO. 2 2012

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Corresponding author

Kirstin Hallmann can be contacted at: k.hallmann@dshs-koeln.de

PAGE 12 jTOURISM REVIEWj VOL. 67 NO. 2 2012

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