Investigating Demographic and Attitude Characteristics of Recreational Skiers: An Application of Behavioral Segmentation

Abstract

The objective of this study was to investigate the most important constraints facing recreational skiers, and profile recreational skiers according to their levels of participation and demographic characteristics. The sample of the study consisted of two hundred and sixty eight (N=268) recreational skiers from a skiing resort in Greece. The results indicated that the most important constraints against participation in winter skiing were related to economic and lack of time problems. Participants were then categorised according to their level of participation (infrequent, moderate, and frequent participants). Comparisons in terms of demographic characteristics indicated that younger and single people participated more in skiing activities than older and married ones. Furthermore, males participated more than females. Comparisons in terms of the perception of constraints indicated several differences with the most striking on the item reading ‘skiing is not among my priorities’. The managerial implications of the results are discussed.

Introduction

Market segmentation is the process of dividing a market into groups of consumers who share similar characteristics. Segmentation is a widely used marketing strategy by marketers today. Four main bases for market segmentation have been suggested: demographic, geographic, psycho graphic and behavioural. Demographic segmentation involves the division of consumers into groups based on variables such as gender, age, family size, income, occupation and religion, while geographic segmentation includes variables such as nation, counties, states etc. Demographic and geographic segmentation are the most widely and easily most applied strategies by marketers and practitioners. Psychographic segmentation includes the division of consumers into groups based on social class, lifestyle, and personality characteristics, while in behavioural segmentation consumers are divided to form groups based on knowledge, attitudes, uses or responses to services. The value of benefit segmentation has been indicated by Hendricks (2004) who applied it in recreation participants. Involvement profiles have been used as a way of behavioural segmentation by Dimanche, Havitz & Howard (1993) in a tourism context, while Havitz, Dimanche & Bogle (1994) applied it in a fitness context. It is clear from all these studies that not all participants are the same with respect to their interests, attitudes and needs.

In the present study we used a combination of behavioural and psychographic segmentation in order to classify recreational skiers. We originally classified consumers into groups according to the frequency of doing ski (behavioural segmentation), and we then profiled each group by examining a) demographic characteristic and b) perceived constraints on skiing participation in terms of different frequency of skiing participation.

Theoretical Background

Leisure Constraints

Leisure constraint research has been a very popular topic in the leisure literature the last two decades. This is due to the theoretical developments made by key papers such as those written by Crawford & Godbey’s (1987) Crawford, Jackson & Godbey’s (1991) Jackson & Rucks (1993) and they great applicability of constraint research data (Alexandris & Carroll, 1999). A variety of studies have successfully indicated how leisure constraint data can help practitioners and policy -makers to more effectively design and promote sport and leisure services (Kay & Jackson, 1991).

Constraints have been defined as “factors that are assumed by researchers and perceived or experienced by individuals to limit the formation of leisure preferences and to inhibit or prohibit participation in leisure activities” (Jackson, 1991, p. 276). It is widely accepted today that constraints are classified into intrapersonal, interpersonal and structural. This categorization was introduced by Crawford and Godbey (1987) and adopted by the majority of researchers in this area. Intrapersonal are internal constraints related to individual psychological states and attributes. Examples of intrapersonal constraints include perceived skill levels, perceived fitness levels, perceived confidence, stress and anxiety. Interpersonal constraints are related to lack of social interaction and social isolation. Examples of interpersonal constraints include inability to find partners to participate with, social isolation, and social disapproval. Finally, structural constraints are external ones. They are related to unavailability or resources to participate in leisure activities. Examples of structural constraints include lack of money, problems related to facilities and services and accessibility issues.

Studies on leisure constraints have been conducted in a variety of leisure, recreation and sport setting, as well as different countries and populations. In the area of sport tourism, leisure constraints research is growing but it is still limited. Constraints have been investigated among nature-based tourists (Nyaupane, Morais & Graefe, 2004), skiers (Williams & Fidgeon, 2000), fans of soccer teams who travel to other countries (Kim & Chalip, 2004), tourists with physical disability problems (Daniels, Drogin-Rodgers & Wiggins, 2005) and destination tourists (Dellaert, Ettema & Lindh, 1998).

Objectives of the Study

The objectives of this study were: a) to investigate the most important constraints facing recreational skiers; b) profile recreational skiers according to their levels of participation, demographic characteristics and perception of constraints.

Methodology

Participants and Procedures

Data were collected by means of a site survey, conducted in a skiing resort, which was located at the biggest ski centre in South Greece. Recreational skiers were approached and asked to fill the questionnaires while relaxing in the cafeteria of the resort after skiing. Two hundred and sixty eight skiers were approached, and two hundred and twenty (N=268) of them accepted to fill the questionnaires, achieving a response rate of 88%.

Three demographic variables were included as follows: gender (males and females), the age of the respondents, which was coded in three categories (18-25, 26-35, 36-65), and level of education (primary education, secondary education and university graduates). The demographic characteristics of the sample are presented in Table 1.

Skiers were also categorized according to their level or participation: infrequent, moderate, and frequent participants.

Research Instruments

Constraints Scale

An adjusted version of the leisure constraints questionnaire (Alexandris & Carroll, 1997a, 1997b) was used in order to investigate the perception of constraints on skiing participation. This was a twenty six item instrument, with was developed and standardized by the Greek population (Alexandris & Carroll, 1997a). It was reported by Alexandris and Carroll (1977b) to have good psychometric properties (Cronbach’s alpha for the whole scale = .85, all items with factor loadings >.40, and Cronbach’s’ alpha >.60 in each factor). Furthermore, it was tested against demographic groups, and showed adequate discriminatory power. This scale was adapted to recreational skiing constraints after conducting interviews with six experienced skiers and five ski instructors. This procedure led to the addition of one more constraint reading ‘problems related to weather conditions’. Respondents were asked to evaluate the importance of each of the twenty three statements as limiting or prohibiting factors for their participation in skiing, using a seven point Likert scale ranking from very important (7) to not important (1). The internal reliability of the whole ski constraints scale was successfully (Cronbach’s alpha = .88).

Results

The demographic characteristics of the sample are presented in Table 1.

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See Table1 on Page 2

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The top-ten constraints for the whole population

The ten top highest scored constraints were: the three financial related constraints C19/M=4.6, C20/M3.6, and C21/M=3.4), the three lack of time related constraints (lack of time because of work / studies, family or social obligations, C1/M=4.8, C2/M=2.9, and C3/M=3.1), the two lack of partner related constraints (C22/M=3.2, C23/M=3.0), problems related to the weather conditions (C16/M=3.3), and the lacks of skills problems (‘no effective ski technique’, C8/M=4.6). These results are presented in Table 2.

Levels of skiing participation.

In order to examine the frequency of skiing participation, the proportions of participants who fell into the three categories (infrequent, moderate, and frequent participation) were calculated. The results indicated that there was a certain group of individuals (32.5%) who were shown to be only ‘infrequently’ participants in winter skiing (one to four times per winter season). The second subgroup (54.5%) participated ‘moderately’ in skiing (five to 9 times per year). Finally 13.3% of the respondents stated that they participated ‘frequently’ (more than 10 times per winter season).

The top-ten constraints by the level of participation

Generally speaking the lack of time related constraints were cited as the most important ones for all the three participation groups. Among the few differences, the item reading “skiing is not among my priorities” was included only in the top-ten list of the ‘infrequently’ participation group, and the constraints reading ‘I don’t like the ski resort environment” and “I do not feel safe” were included only within the ‘frequently’ level top ten list.

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See Table2 on Page 2

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Constraints and levels of participation.

Univariate analysis of variance (ANOVA) revealed significant differences in thirteen constraints among the three different participation levels. The most significant difference was found in constraint C12 ‘skiing is not on my priorities’, F (2,235) = 29.4, p< .001), followed by the C8 constraint ‘no effective ski technique’, F (2,230) = 18.3, p< .001), and the C25 constraint ‘my family doesn’t like skiing’, F (2,234) = 13.2, p< .001). Each of the significant ANOVAs was followed by Scheffe’s post-hoc comparisons to determine between which groups the differences were statistically significant. The ANOVA’s results are presented in detail in Table 3.

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See Table3 on Page 2

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Skiing Participation by Age, Gender and Marital status (% of the population).

Age and frequency of participation

A cross-tabulation of the age groups against the levels of participation (infrequently, moderately, and frequently) revealed statistical significant differences (see Table 4). The level of participation was negatively correlated with ascending age group levels (x 2=12, p<.01). Age 1 group achieved the highest rate (40.2 %) in ‘infrequently’ participation level and the lowest rate in ‘frequently’ level. In contrast, the older participant group (age 3) achieved the highest rate (52.9 %) in ‘frequently’ participation level and the lowest in ‘infrequently’ level.

Gender and frequency of participation

An association also found between participation and gender (x 2=5.7, p<.05), with male recreational skiers having higher participation rates than females. Contrary, younger female ski groups participated in skiing more ‘infrequently’ (45.5%) than the older female groups in ‘frequently’ participation levels (21. 2%).

Marital status and frequency of participation

Non significant relationship (x 2= 4, p< n. s.) revealed between participation levels and participants marital status. There was only a trend for the single individuals to participate more ‘frequently’ in skiing that the married ones.

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See Table4 on Page 2

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Discussion

Lack of time related constraints were revealed by all studies that investigated constraints on recreation participation. (Alexandris & Carroll, 1997a; 1997b; Kay & Jackson, 1991 ). Skiing is an even more time consuming activity since it required traveling to the skiing resorts, which usually are far away from the urban places. Resorts managers have almost no influence on removing these constraints. The results also indicated that financial problems were reported as important ones by the majority of participants. This finding is once again related to the specific requirements of the activity in question (skiing). Skiing is still considered as an expensive sport for the majority of the population. While lowering prices is not obviously a realistic suggestion for resort managers, efforts should be made towards promoting skiing packages for families (family packages) and specific groups of the population (e.g., students) that are facing financial problems, if these groups are to be targeted.

The high mean score of the item reading “skiing is not among my priorities” for the lowest participation level group (infrequently) explains in a degree their unwillingness to participate more frequently. While this is obviously an intrapersonal constraint related to preferences and personal interest, it could be argued that this constraint could in a way be removed by providing outdoor education and making winter skiing in Greece a more “mass” sport.

The high statistical differences that revealed on the constraints “I do not have good skiing skills”, “I do not have self-confidence”, and I do not know how to skiing” are also important findings, since they indicated that intrapersonal constraints are in a degree responsible for the low participation rates of some individuals. This finding is in line with previous research that conducted in other leisure and recreation settings (e.g., Alexandris & Carroll, 1997). As previously discussed, intrapersonal are internal constraints that are related to individual psychological states and attributes. The removal of intrapersonal constraints is not an easy task since they are not beyond the control of the organization (Alexandris & Carroll, 1999). In the case of skiing, however, it is clear that there are a certain groups of individuals who do not feel confident about their skills and abilities, and this limits their participation levels. Once again efforts should be made towards the promotion of skiing. Having free teaching classes could help towards this direction. It is important that beginners should get as much support as possible by the repost teachers and staff.

In terms of profiling recreational skiers that results indicated that the most frequent skiers are young, single and male individuals. This once again suggests that there is space for better promotion on the side of resort marketers. There should be promotional strategies targeting females, families and older individuals ( Havitz et al, 1994; Dimanche et al, 1993) . Different promotional strategies are obviously required as well as different design of the main product. Examples could be offering skiing opportunities for the whole family, offering light programs for old individuals, improving the whole experience by emphasising on the physical environment.

References

  1. Alexandris, K., & Stodolska, M. (2004). The influence of perceived constraints on the attitudes towards recreational sport participation. Leisure and Society, 27, 197-217.
  2. Alexandris, K., & Carroll, B. (1999). Constraints on Recreational Sport Participation in Adults in Greece: Implications for Providing and Managing Sport Services. Journal of Sport Management, 13, 317-332.
  3. Alexandris, K. (1998a). Patterns of recreational sport participation among the adult population in Greece. Cyber Journal of Sport Marketing, 2(2), 1-9.
  4. Alexandris, K., & Carroll, B. (1997a). An analysis of leisure constraints based on different recreational sport participation levels: Results from a study in Greece. Leisure
  5. Sciences, 19, 1-15.
  6. Alexandris, K., & Carroll, B. (1997b). Motives for recreational sport participation in Greece: Implications for planning and provision of sport services. European Physical Education Review, 3(2), 129-143.
  7. Crawford, D., Jackson, E., & Godbey, G. (1991). A hierarchical model of leisure constraints. Leisure Sciences, 13, 309-320.
  8. Crawford, D., & Godbey, G. (1987). Reconceptualizing barriers to family leisure. Leisure Sciences, 9, 119-127.
  9. Daniels, M., Drogin Rodgers, E., & Wiggins, B., (2005). ‘‘Travel Tales’’: an interpretive analysis of constraints and negotiations to pleasure travel as experienced by persons with physical disabilities. Tourism Management, ??, ???,???
  10. Dellaert, B. Ettema, D., & Ch., Lindh, (1998). Multi-faceted tourist travel decisions: a constraint-based conceptual framework to describe tourists’ sequential choices of travel components. Tourism Management, 19, No 4, 313-320.
  11. Dimanche, F., Havitz, M. E., & Howard, D. R. (1993). Segmenting recreationists and tourists using involvement profiles. Journal of Travel and Tourism Marketing, 1 (4), 33-52.
  12. Havitz, M. E., & Dimanche, F., & Bogle, T. (1994). Segmenting the adult fitness market using involvement profiles. Journal of Park and Recreation Administration. 12 (3), 35-56.
  13. Hendricks, W. W. (2004). Extending Importance-Performance Analysis with Benefit-Based Segmentation. Journal of Park and Recreation Administration, 22, 1. 53-74.
  14. Jackson, E. (1991). Special issue, introduction. Leisure constraints/constrained leisure, Leisure Sciences, 13, 273-8.
  15. Jackson, E. (1993). Recognizing patterns of leisure constraints: Results from alternative analyses. Journal of Leisure Research, 25, 129-149.
  16. Jackson, E., & Rucks, V. (1993). Reasons for ceasing participation and barriers to participation: Further examination of constrained leisure as an internally homogeneous concept. Leisure Sciences, 15, 217-230.
  17. Kay, T., & Jackson, G., (1991). Leisure despite constraint: The impact of leisure constraint on leisure participation. Journal of Leisure Research, 23, 301-313.
  18. Kim, N., & Chalip, L., (2004). Why travel to the FIFA World Cup? Effects of motives bachground. Tourism Management, 25, 695-707
  19. McIntyre, N., & Pigram, J.J. (1992). Recreation specialization re-examined: The case of vehicle-based campers. Leisure Sciences, 14 (1), 36-40.
  20. Nyaupane, G., Morais, D., & Graefe, A., (2004). Nature tourism constraints. A cross activity comparison. Annals of Tourism Research, 31, No 3, 540-555.
  21. Williams, P., & Fidgeon, P., (2000). Addressing participation constraint: a case study of potential skiers. Tourism Management, 21, 379-393.

 

Table 1. Demographic Characteristics of the Sample

Gender Age of groups Education level Marital Status
Males 63%Females 37% 18<25 36.3% Primary level 35% Single 79,4%
26<32 35.5% Secondary level 42% Married 20,6%
36<65 23,2% University level 23,9%

Table 2 The most significance constraints according to the frequency of participation

a/a The most significant constraints for recreation skiing
1 <p”> C1 Time: work/studies
2 <p”> C2 Time: family
3 <p”> C3 Time: social commitments
4 <p”> C8 No effective ski technique
5 <p”> C12 Skiing is not on my priorities
6 <p”> C15 Don’t like ski resort environment
7 <p”> C16 Difficult weather conditions
8 <p”> C18 Don’t feel safe
9 <p”> C19 Cannot afford
10 <p”> C20 Accessibility is a problem
11 <p”> C21 Difficulty to find money
12 <p”> C22 Have no always friends to participate with
13 <p”> C23 Friends don’t like participation
The Top 10 for all Participants The Top 10 for Occasional Participants The Top 10 for Often Participants The Top 10 for Systematic Participants
1 C1 , M=4.8, SD=1.8 C19 , M=4.9,SD=1.7 C1 , M=4.9,SD=1.8 C19 , M=4.3,SD=2.1
2 C19 ,M=4.6, SD=1.8 C1 , M=4.8,SD=1.9 C19 , M=4.5,SD=1.8 C1 , M=3.9,SD=2.0
3 C20 ,M=3.6, SD=1.8 C20 , M=4.4,SD=1.9 C16 , M=3.4,SD=1.7 C20 , M=3.2,SD=2.0
4 C21 ,M=3.6, SD=1.8 C21 , M=4.2,SD=1.8 C20 , M=3.2,SD=1.8 C16 , M=3.0,SD=1.4
5 C16 ,M=3.4, SD=1.8 C22 , M=4.1,SD=1.9 C21 , M=3.2,SD=1.9 C15 , M=2.8,SD=1.9
6 C22 ,M=3.3, SD=1.9 C12 , M=3.9,SD=1.9 C3 , M=3.0,SD=1.8 C2 , M=2.5,SD=1.3
7 C3 , M=3.2, SD=1.8 C8 , M=3.8,SD=1.9 C22 , M=2.9,SD=2.0 C18 , M=2.4,SD=1.9
8 C23 ,M=3.1, SD=1.8 C23 , M=3.5,SD=1.8 C23 , M=2.8,SD=1.7 C3 , M=2.4,SD=1.8
9 C8 , M=3.0, SD=1.9 C3 , M=3.5,SD=1.8 C2 , M=2.8,SD=1.8 C22 , M=2.3,SD=1.5
10 C2 , M=2.9, SD=1.8 C16 , M=3.4,SD=2.0 C8 , M=2.6,SD=1.7 C23 , M=2.3,SD=1.6

 

Table 3. Anova’s between constraints and different frequency of participation

Constraints F change & probability Differences between groups
C12, Skiing is not on my priorities F (2,235) = 29.4, p<.001 1-2**, 1-3**
C8 , No effective ski technique F (2,230) = 18.3, p<.001 1-2**, 1-3**
C25, My family doesn’t like skiing F (2,234) = 13.2, p<.001 1-2**, 1-3**
C22, Have no fiends to participate with F (2,234) = 11.7, p<.001 1-2**, 1-3**
C21, Difficulty to find money F (2,234) = 11.2, p<.001 1-2**, 1-3**
C10, I don’t have self confidence F (2,235) = 8.3, p<.001 1-2*, 1-3*
C11, I don’t know why to skiing F (2,233) = 6.8, p<.001 1-2*, 1-3*
C20, Accessibility is a problem F (2,240) = 6.5, p<.01 1-2*
C23, My friends don’t like skiing F (2,232) = 6.1, p<.01 1-3*
C14, I don’t like very much skiing F (2,235) = 5.2, p<.01 1-2*, 1-3*
C3, Time: Social commitments F (2,236) = 4.0, p<.05 1-3*
C1, Time: Work/studies F (2,247) = 3.7, p<.05 2-3*
C2, Time: Family F (2,234) = 3.1, p<.05 1-3*

<p”>** p<.oo1, *p<.05

Table 4. Ski Participation by Age, Gender and Marital status (% of the population).

DemoVariables Different frequency of annual participation
Occasionally Often Systematic
Age x 2= 12, p< .01 Age 140.2% Age 229.3% Age 330.5% Age 128.1% Age 230.2% Age 341.7% Age 18.8% Age 238.2% Age 352.9%
Gender x 2= 5.7, p< .05 Male54.5% Female45.5% Male59.8% Female40.2% Male78.8% Female21.2%
Marital Status x 2= 4, p= n.s. Single84.2% Married15.8% Single78% Married22.7% Single65.6% Married34.4%
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