Comparing the Active and on-active Leisure- Tourism Connection: Leisure Involvement, Leisure Habit, Tourism Motivation, and Tourism Behavior

Transcription

1 University of Massachusetts Amherst Amherst Tourism Travel and Research Association: Advancing Tourism Research Globally 2010 ttra International Conference Comparing the Active and on-active Leisure- Tourism Connection: Leisure Involvement, Leisure Habit, Tourism Motivation, and Tourism Behavior Seohee Chang Department of Hospitality and Tourism Grand Valley State University Heather Gibson Department of Tourism, Recreation and Sport Management University of Florida Follow this and additional works at: Chang, Seohee and Gibson, Heather, "Comparing the Active and on-active Leisure-Tourism Connection: Leisure Involvement, Leisure Habit, Tourism Motivation, and Tourism Behavior" (2016). Tourism Travel and Research Association: Advancing Tourism Research Globally This is brought to you for free and open access by Amherst. It has been accepted for inclusion in Tourism Travel and Research Association: Advancing Tourism Research Globally by an authorized administrator of Amherst. For more information, please contact

2 Comparing the Active and on-active Leisure-Tourism Connection: Leisure Involvement, Leisure Habit, Tourism Motivation, and Tourism Behavior Seohee Chang Department of Hospitality and Tourism Grand Valley State University and Heather Gibson Department of Tourism, Recreation and Sport Management University of Florida ABSTRACT Researchers have suggested that leisure and tourism are closely related to each other. While the leisure-tourism connection has been observed indirectly in previous research, as yet, few studies have empirically investigated the psychological connection between leisure and tourism activity choices. Moreover, little attention has been given to the relationship between physically active and non-active leisure and tourism choices. Therefore, this study examined the leisure-tourism connection of both physically active (n=316) and non-physically active respondents (n=258) by using four latent variables, leisure involvement, leisure habit, tourism motivation, and tourism behavior. The leisure-tourism causal relationship was found to be statistically significant among the physically active respondents and as such supports trends evident in the existing literature. Keywords: leisure-tourism connection, leisure involvement, leisure habit, tourism motivation, tourism behavior. I TRODUCTIO Researchers have suggested that leisure and tourism are closely connected to each other. Tourism has been defined as a special form of leisure (Butler, 1999; Cohen, 1974) and frequently shares behavioral and psychological (Mannell & Iso-Ahola, 1987), social (Colton, 1987), spatial (Jensen-Verbeke & Dietvorst, 1987), and managerial characteristics (Harris, McLaughlin, & Ham, 1987). Developing this line of thought, several researchers have postulated that tourism behaviors are rooted in leisure lifestyles (Fedler, 1987; Moore, Cushman, & Simmons, 1991). Even though tourism behavior may be more novel and hedonic-oriented, behavioral choices are frequently shaped by an individual s leisure values and lifestyles (Currie, 1997), and there is a strong relationship with the attitudinal and habitual components of leisure (Carr, 2002). Indeed, researchers have found choice of tourism activities is related to everyday attitudes and lifestyles (Chon & Singh, 1995; Hallab, Yoon, & Uysal, 2003). Brey and Lehto (2007) found that individuals who take part in active leisure pursuits such as golf or jogging are more likely to participate in these activities on vacation than those individuals who take part in more passive leisure activities. Similar findings have been observed in other active-leisure contexts such as recreational road runners and their participation in running-related tourism (McGehee, Yoon, & Cardenas, 2003), bicycling tours (Ritchie, 1998), and recreational climbing (Woratschek, Hannich, & Ritchie, 2007). Few studies exist exploring the connection between non-physically active leisure pursuits and tourism choices and none have compared active and non-active leisure and tourism pursuits. Thus, the purpose of this study was to investigate the psychological

3 connection for individuals between active and non-active leisure pursuits and their choice of tourism behavior. LITERATURE REVIEW Involvement According to Carr s (2002) Leisure-Tourism Continuum, attitudinal and habitual components are considered important in explaining the impact of leisure lifestyles on tourism behaviors. In the leisure literature concepts such as recreation specialization (Bryan, 1977) and enduring involvement (McIntyre, 1989) have been used to understand individuals continued attachment to and participation in their chosen leisure activities. Much of this work has used psychological involvement and behavioral frequency to investigate the developmental progression of leisure behavior for individuals within a leisure but not a tourism context (e.g., Iwasaki & Havitz, 2004; Kim, Scott, & Crompton, 1997; Kyle, Graefe, Manning, & Bacon 2004a, 2004b; McIntyre, 1989). The reason that involvement has been often used to understand behavioral consistency within lifestyles is because involvement is considered critical in the development of a narrow range of attitudes, thereby resulting in behavioral consistency (Sherif & Cantril, 1947). More specifically, social judgment theory (Sherif & Cantril, 1947) assumes that people s existing attitudes refer to lenses through which to judge new messages. The more involved individuals are with an attitude or an activity the less likely they are to accept new ideas or messages. This theoretical assumption guided consumer behavior research focused on understanding the buying behaviors of consumers. Consumer behavior researchers in the 1970s defined involvement as interest (Day, 1970), belief strength (Robertson, 1976), the internal state including arousal and interest (Mitchell, 1979), or the perceived importance of values (Lastovicka, 1979). Furthermore, in the 1980s, its definitions tended to be categorized into different types of involvement such as situational and enduring (Richins & Bloch, 1986). Laurent and Kapferer (1985) developed the multidimensional Likert scale, Consumer Involvement Profile (CIP) presenting five dimensions comprising importance, sign value, interest, emotional values, and perceived risk. Connecting these five dimensions to two types of involvement (i.e., enduring and situational involvement), Assael (1998) suggested that sign values and risks are situational involvement combined with a short-term behavior that is easily changed by external situations, whereas importance, interest, and emotional values are enduring involvement associated with a long-term activity with a more focus of its quality. Researchers who have studied leisure behaviors have tended to be more interested in enduring involvement than situational involvement because leisure involvement tends to be associated with quality of life through enjoyable leisure experiences (Backman & Crompton, 1989, 1991; Buchanan, 1985; Csikszentmihalyi, 1975, 1990; Kyle et al., 2004a 2004b; Mannell & Iso-Ahola, 1987; McIntyre, 1989). Bryan (1977) is considered to be the first scholar to introduce the concept of involvement to the leisure field. Bryan investigated the behavioral involvement of sport anglers and found that there are different levels from general to specialized. The more specialized group was characterized by those who spent more money on equipments/magazines, participate more frequently in fishing trips, and most of their social interaction is with other anglers. Bryan provided a good foundation for others to engage in more in-depth studies of leisure involvement. Buchanan (1985) and McIntyre (1989) followed and investigated the psychological components of involvement invoking the concepts leisure commitment and enduring leisure involvement, respectively. In particular, enduring leisure involvement (McIntyre, 1989; McIntyre & Pigram, 1992) included the psychological components

4 of self-expression, attraction, and centrality using the CIP as a foundation (Laurent & Kapferer, 1985). Enduring involvement seems to be a valuable concept when studying the relationship between leisure and tourism because it encapsulates ideas associated with an individual s overall life style (Carr, 2002; Gross, Brien, & Brown, 2008; Mannell & Iso-Ahola, 1987; Moore, Cushman, & Simmons, 1991). For example, if people are engaged in an active lifestyle participating in active leisure, they are more likely to maintain their active lifestyles while on vacation because their involvement with physical activity may be an important part of their identity (Carr, 2002; Sherif & Cantril, 1947). Even though previous studies have not directly investigated the leisure-tourism connection through involvement with activities, many relevant examples can be observed in studies examining the consistent leisure participation patterns in downhill skiing, golf, competitive running (Dimanche, Havitz, & Howard, 1991), fishing (Perdue, 1993), white water recreation (Bricker & Kerstetter, 2000), road racing (McGehee et al., 2003), and hiking (Kyle et al., 2004a 2004b). However, most of these studies have indirectly focused on active leisure and tourism activities. Brey and Lehto (2007) also found that running and playing golf are the activities that are most likely to transfer to the tourism context, however, there are indications within their study that non-active leisure activities may not transfer as consistently as active leisure to the tourism context. Moreover, Brey and Lehto used behavioral involvement as their key concept. Few studies, if any have used the concept of enduring involvement to examine the leisure-tourism connection. Habit Habit should be considered along with enduring involvement to investigate the leisuretourism connection. Habit is an important concept providing insights into the unconscious aspects that influence behavior and as such complements involvement which focuses on the conscious aspects of behavior (Bentler & Speckart, 1979; Triandis, 1977; Verplanken & Aarts, 1999). In leisure studies, habits have tended to be operationalized as behavioral frequency, whereas, habit is more complex than this. Verplanken and Orbell (2003) suggested that habit is characterized as a structure which includes unconsciousness, automaticity, efficiency, and regularity components. Similarly, describing habit as an automatic behavioral sequence associated with a particular situation, Triandis postulated that future behaviors can be predicted more accurately when they are measured as both attitudinal (i.e., involvement) and habitual. Likewise, several scholars suggested that habits help attitudes to actualize as behaviors because habit accounts for variance that cannot be explained by attitudes alone in predicting future behaviors (Anderson, 1990; Kahle, 1984). The cognitive formation behind habit is a well learned schema that encourages people to group numerous objects into several subjective categories and makes it easy to automatically extract the necessary information from the appropriate category. This schema is efficiencyoriented and easily guides behavior. In some situations, when attitudes are too weak that it is hard to make a decision to behave, habits facilitate behavior or when attitudes are strong, habitual schema are not that influential (Ouellette & Wood, 1998). However, it does not mean that habit and attitudes always act in opposition. In some situations, habits result from consistent attitudes and may contribute to certain behaviors without much deliberate effort on the part of the individual (Kahle, 1984; Triandis, 1977). Therefore, whenever individuals face new situations and have less information, they might be assisted by habits held in the subconscious developed from past experiences and insights (Bentler & Speckart, 1979; Triandis, 1977). Therefore, when attitudes (conscious) and

5 habits (unconscious) are combined, they may exert more influence on consistent behavior than when acting alone (Triandis, 1977). Habits have been found to be an important variable predicting health, exercise, and physical activities (Davis, Brewer, & Ratusny, 1993; Valois, Desharnais, & Godin, 1988; Wood, Tam, & Guerrero-Wit, 2005). Wood et al. found that habits encourage people to maintain the same exercise patterns despite environmental change. Aarts and Dijksterhuis (2000) found habitual cyclists were faster to react to bicycling-related destination information than other transportation-related destination information. Similarly, Verplanken, Aarts, and Knippenberg (1997) found that people with strong bicycling habits apply simpler rules in their decision making process, and Verplanken, Aarts, Knippenberg, and Moonen (1998) also found that these people do not tend to solicit new information and alternative options. These findings show that habits are similar to involvement in the acceptance and rejection latitude process associated with social judgment theory (Sherif & Cantril, 1947). Accordingly, it seems that attitudes and habits have a synergetic relationship with each other and may be valuable in understanding the leisure-tourism connection within lifestyle patterns. Motivation The leisure-tourism link is also likely to be mediated by tourism motivation. Motivation has been found to guide tourism behavior (Fodness, 1994; Iso-Ahola, 1982; Pearce & Caltabiano, 1983; Ryan & Glendon, 1998). Eagly and Chaiken (2005) defined motivation as an engine that guides thoughts and behaviors to satisfy their needs. Indeed, Dann (1977, 1981) and Crompton (1979) formulated a tourism motivation theory based on Murray s (1938) manifest needs theory. Murray postulated that needs occur from lack of balance and people are motivated to pursue a balanced state, and needs that are more manifest (i.e., salient) drive behavior. Dann and Crompton suggested that travel needs consist of push and pull motivations. Push motivations are internal needs whereas, pull motivations are induced by external factors such as destination attractions. Crompton identified a range of push factors such as escape from the routine, exploration of self, relaxation, prestige, regression, enhancement of kinship, and facilitation of social interaction. Another approach to motivation also based on Murray (1938) and Maslow (1943) is Beard and Ragheb s (1983) Leisure Motivation Scale (LMS). This scale identifies four motivational dimensions: relaxation, social, intellectual, and mastery. Ryan and Glendon (1998) applied this scale to the tourism contexts and found good reliability and validity. Thus, if leisure motivation and tourism motivations appear to be similar, this may mean that leisure and tourism are not only psychologically connected (Mannell & Iso-Ahola, 1987), but are part of an overall lifestyle (Moore et al., 1995). The connection between leisure and tourism needs may manifest itself in push and pull factors. An individual s leisure needs connected to their favorite leisure activities may make certain destinations more attractive to an individual as the pull factors associated with that destination may include opportunities to participate in favored leisure activities. The potential dynamic relationship between leisure and tourism motivation, push and pull factors may provide additional insights along with involvement and habit to provide a more in-depth understanding of the leisure-tourism psychological and behavioral connection. METHOD The purpose of this study was to examine the leisure-tourism causal connection using four latent variables for physically active and non active leisure and tourism participants. Leisure involvement and leisure habits are considered as exogenous variables and tourism motivation and

6 tourism behavior are deemed endogenous variables. The same hypotheses are applied to both the active and non-active participants: H1) Leisure involvement and leisure habit are correlated with each other, H2) Leisure involvement has a direct effect on tourism motivation, H3) Leisure habit has a direct effect on tourism motivation, H4) Tourism motivation has a direct effect on tourism behavior, H5) Leisure involvement has an indirect effect on tourism behavior, and H6) Leisure habit has an indirect effect on tourism behavior. For instrumentation, a questionnaire consisting of fixed choice and open-ended items was used. Three sections were used for this particular study: Leisure (i.e., a type of favorite leisure activity, leisure involvement, leisure habit), tourism (type of favorite tourism activity, tourism motivation, tourism behavior), and demographics. The open-ended questions asking about type of leisure and tourism activities were used to distinguish the respondents who take part in physically active leisure and tourism activities from those who participate in non-physically active leisure and tourism activities. The leisure involvement items (18 items) were adapted from those used by Kim et al. (1997), Gahwiler and Havitz (1998), Pritchard, Havitz, and Howard (1999), and Kyle et al. (2004a & b); the leisure habit items (10 items) were adapted from the self-reported habit index (SRHI) developed by Verplanken and Orbell (2003); the tourism motivation items were adapted from the Leisure Motivation Scale (LMS) (18 items) developed by Beard and Ragheb (1983); and the tourism behavior items (11 items) were adapted from the leisure participation scale used by Ragheb and Tate (1993) and the self-report leisure behavior items used by Stanton- Rich and Iso-Ahola (1998). All of scales were measured using a 7 point Likert type format. The wording of all the scale items was modified and a few items were created for the purpose of this study. Content validity was established using a panel of 12 experts during a pilot study. For data collection and analysis, the study population comprised alumni members of a university. The scope of the study necessitated access to a population who were likely to be diverse in their leisure and tourism interests. A university educated population was also deemed to be appropriate as higher levels of are associated with higher levels of discretionary income (Griliches & Mason, 1972) and so, these individuals are likely to be able to extend participation in their favorite leisure activities by traveling to different environments. The targeted population size ( ) (i.e., the total number of the university alumni members) was 200,000. The sample size (n) with 2% margin of error at the 99% confidence level was calculated at 4,063 (Kish, 1995). The survey method was on-line and as undeliverable addresses and low response rates associated with web-surveys were anticipated (Dillman, 2000), 80% of the total sample size was added and the ultimate sample size was 7,313. According to systematic sampling procedures, every 25 th name as the sample interval was selected from the sampling frame. A final usable sample of 703 participants was obtained, yielding a response rate of 23% (n= 703 out of 3082; s were undeliverable). Descriptive statistics, Cronbach s alpha coefficients (α), and independent T-test were used to analyze the data using SPSS 17.0, and confirmatory factor analysis (CFA) was used to test the fit of the measurement model and structural equation modeling (SEM) was used to test the causal relationship between latent variables using LISREL 8.80/PRELIS Both the measurement and structural equation model had three broad steps, model specification, model assessment, and model respecification. For sample, of the 703 respondents, 316 engaged in both physically active leisure activities and physically active tourism activities, and 258 engaged in both non-physically active leisure activities and non-physically active tourism activities. For those in the physically active group, 55.3% were male and the average age was years (SD = 12.69) ranging from 18 to 77 years. Two-thirds (64.7%) of those non-active respondents were female with an average age of (SD = 14.48) ranging from 19 to 87 years.

7 RESULTS The active group reported that they prefer outdoor-related sports, water-related sports, golf/ski, fitness, and team sports for leisure and tourism activities. In the CFA conducted as the first step to confirm the reliability and validity of those items comprising the four main variables, the following results were generated using a respecification process. For the Active Group, Leisure Involvement has five factors (Social, α=.67, CR=.66, AVE=.41, Self-Identity, α=.83, CR=.86, AVE=.68, Social Identity, α=.78, CR=.81, AVE=.70, Hedonic, α=.83, CR=.85, AVE=.75, Central, α=.86, CR=.88, AVE=.75); Leisure Habit has three factors (Automatic, α=.72, CR=.77, AVE=.46; Resistant, α=.71, CR=.76, AVE=.51; Regular, α=.79, CR=.86, AVE=.76); Tourism Motivation has four factors (Social α=.84, CR=.88, AVE=.59; Physical α=.87, CR=.91, AVE=.78; Relaxation α=.79, CR=.85, AVE=.56; Intellectual α=.87, CR=.91, AVE=.72); and Tourism Behavior has two factors (Participation α=.83, CR=.81, AVE=.56; Decision α=.81, CR=.73, AVE=.68). As a further step, the mean values of each factor per each main variable were generated. These were used as the new observed variables (i.e., total 14 items) for the initial SEM measurement model. However, this initial measurement model failed to obtain a good fit. After the removal of Social in the respecification process, the final measurement model yielded an acceptable fit (Minimum Fit Function Chi-Square χ2/df = /57 = 0.00; RMSEA = with CI, ; SRMR = 0.070; NNFI = 0.91; CFI= 0.93). The Cronbach s alphas (ranging from.74 to.88), CR (.75 to.87), and AVE (.55 to.63) of each latent variable showed good reliability and validity except tourism motivation (α=.42, CR=.46, AVE=.19). Tourism motivation consists of four different components to explain various internal push factors to travel. The four components may not be strongly correlated with each other. In the aforementioned CFA model, socializing, physical, and relaxation were significantly correlated with each other, but intellectual was not significantly correlated with the other three factors. The reason that intellectual was distant from other motivations may be because it yielded much higher mean values than the other factors. Tourism motives may be diverse and show a wide range of factor loadings. Accordingly, low factor loadings, reliability and validity do not mean that the item is not valuable in measuring the factor. Finally, all four of the tourism motivation items were employed in the SEM. For the structural portion of the SEM, the correlation between involvement and habit was significant (φ=.57). The direct effect of leisure involvement on tourism motivation was significant (γ=.34) as well as the direct influence of leisure habit on tourism motivation was significant (γ=.22). The direct influence of tourism motivation on tourism behavior appeared significant as well (β=.45). The indirect effects of leisure involvement (indirect=0.15; total=0.15) and leisure habit (indirect=.10; total=.10) on tourism behavior were identified as significant. The on-active Group reported that they prefer passive leisure and tourism activities such as watching TV, reading, relaxing, playing cards, creating arts, shopping, dining, visiting museums, etc. Results were a product of the respecification process of the CFA. Leisure Involvement consisted of five factors (Social, α=.71, CR=.80, AVE=.49, Self-Identity, α=.85, CR=.89, AVE=.72, Social Identity, α=.82, CR=.86, AVE=65, Hedonic, α=.86, CR=.91, AVE=.69, Central, α=.85, CR=.88, AVE=.59); Leisure Habit had three factors (Automatic, α=.73, CR=.78, AVE=.46; Resistant, α=.73, CR=.78, AVE=.53; Regular, α=.76, CR=.85, AVE=.75); Tourism Motivation comprised four factors (Social α=.90, CR=.92, AVE=.69; Physical α=.90, CR=.91, AVE=.68; Relaxation α=.86, CR=.89, AVE=.67; Intellectual α=.92, CR=.94, AVE=.81); Tourism Behavior had two factors (Participation α =.74, CR =.81, AVE =.54;

8 Decision α=.87, CR=.90, AVE=.80). The same14 observed variables as the active respondents were generated, and the initial measurement portion also did not have a good fit. After the deletion of social and participation with low factor loadings and relaxation with negative factor loadings, the model had a reasonable fit (Minimum Fit Function Chi-Square χ2/df = /36 = 0.00; RMSEA = with CI, ; SRMR = 0.056; NNFI = 0.92; CFI= 0.95). The Cronbach s alphas (ranging from.84 to.90), CR (.88 to.95), and AVE (.65 to.95) of each latent variable showed good reliability and validity. However, again, tourism motivation (α=.51, CR=.53, AVE=.37) did not have good reliability and validity for the same reasons as that of the active respondents. As with the active respondents, the tourism motivation factors remained in the analysis. For the structural portion of the SEM, leisure involvement and habit were strongly correlated with each other (φ=.66), but the direct effect of leisure involvement on tourism motivation (γ =.25) as well as the direct effect of leisure habit on tourism motivation (γ=.12) was not significant. Also, the direct effect of tourism motivation on tourism behavior appeared insignificant (β=.41). However, leisure involvement (indirect=.15; total=.15) and leisure habit (indirect=.10; total=.10) had a slightly significant indirect effect on tourism behavior. In addition to the causal model comparison, independent t-tests were used to investigate if the physically active and non-physically active respondent groups have different levels of leisure involvement, leisure habit, tourism motivation, and tourism behavior. The results showed that the active respondent group rated social (t= 3.721, p=.000), social identity (t=2.925, p=.004), and centrality (t=2.127, p=.034) significantly higher than the non-active respondent group, whereas the non-active respondent group were much higher in all of the leisure habit variables, regular (t=3.798, p=.000), automatic (t=5.445, p=.000), and resistant (t=.2119, p=.034) than the active respondent group. As expected, the active respondent group rated physical (t=6.802, p=.000) and socializing (t=2.388, p=.017) significantly higher. The active respondent group was also significantly higher in decision-making (t=6.476, p=.000). DISCUSSIO A D CO CLUSIO Leisure involvement and habit were found to be significantly correlated for both the active and non-active respondent groups, which empirically supports Triandis (1977) habit theory, Kahle s (1984) social adaptation theory, and Anderson s (1990) thought theory. These theories assume that consistent attitudes induce repeated behaviors, these repetitions form habitual schema, and in turn, this schema contributes to the reinforcement of attitudes (Anderson, 1990; Kahle, 1984). More specifically, the results suggest that beyond simple behavioral frequency, unconscious and automatic components play an important role in habits and interact with conscious components. This seems to be very crucial in understanding people s lifestyles that cannot be merely explained by intentional and conscious components (Bentler & Speckart, 1979; Triandis, 1977; Verplanken & Aarts, 1999). However, the ratio of consciousness to unconsciousness in each individual s lifestyle is different, and this may influence who has active or passive lifestyles. Likewise, this study found that physically active respondents showed stronger involvement than non-physically active respondents, whereas the non-active respondents had stronger habits. Despite their significant correlation, the ratio of leisure involvement to leisure habit may be different and this different ratio may be an important determinant to see whether leisure and tourism will be connected or disconnected. For example, for active individuals who perceive themselves as a runner in terms of their identity are likely to have very high involvement level with running (Shipway & Jones, 2008). In turn, these runners might be motivated to participate in

9 marathons as an outcome of their involvement in running and also to reinforce their identity as a runner by participating in competitive running events. Yet, even though they intend to take part in a running competition or running event, it is hard to take part if they have not trained regularly, the regularity of which is likely to be habitual. Thus, their running habit and involvement likely motivates them to take part in running events some of which may involve travel away from home (McGehee et al., 2003). However, for those non-active individuals, the combination of too much automaticity of habit and too little involvement may make it hard to generate enough motivational intention to travel to take part in associated leisure activities (Ouellette & Wood, 1998). In other words, although habitual leisure behaviors could be enhanced by the identity or social aspects of leisure involvement, much stronger leisure habitual behaviors may not induce individuals to plan travel that incorporates these activities directly. The habit of non-active leisure, particularly activities such as TV watching, card playing, and shopping seem to be related to a generally non-physically active lifestyle that manifests itself in tourism contexts in the same manner, for example, relaxing by the pool, spending time with family and friends, cultural and historical activities were reported as favored tourism pursuits by the non-physically active group. However, the lack of involvement in these activities seems to be a key difference. Thus, in this study, the leisure-tourism causal relationship was found to be significant only for the active respondent group and as such supports the tenets of Carr s (2002) Leisure- Tourism Continuum and Currie s (1997) LIP behaviors framework explaining the impact of daily behaviors on tourism behaviors. In addition, the findings support the idea of framing tourism behaviors within overall lifestyles (Cohen, 1974; Moore et al., 1991; Pearce, 1988; Rapoport & Rapoport, 1975). Those with active lifestyles showed a significant connection. Perhaps, as assumed by Sherif and Cantril s (1947) social judgment theory, those individuals seem to formulate their identity around their leisure activities and are likely to find and confirm their identity by taking part in associated leisure and tourism experiences (Haggard & Williams, 1992; Shipway & Jones, 2008) Consistent with this assumption, in this study physically active individuals revealed stronger identity with their leisure activities. Their identities may be tied to active and healthy lifestyles and thus, their leisure and tourism behaviors show consistency (Hallab & Gursoy, 2006; Hallab, Yoon, & Uysal, 2003). For the active group, the synergetic effect between conscious and unconscious components seems to push them to pursue relevant identity-projected tourism activities. This may also provide a more in-depth understanding by incorporating the psychological meanings behind Brey and Lehto s (2007) finding that frequent participation in physically active leisure is more likely to be connected to tourism activities. On the other hand, those non-active individuals may perceive leisure and tourism as unconnected. Depending on individuals subjective perception (Hamilton-Smith, 1987; Kelly, 1983; Mannell & Iso-Ahola, 1987), the ratio of involvement to habit seems to be important, with involvement level in a leisure activity in particular predicting tourist activity choices. While it would be incorrect to suggest that non-physically active leisure pursuits are not associated with tourism choices as there were indications within the data that non-physically active leisure was associated with lesser activity in tourism settings, it seems that the level of involvement in a particular leisure activity is very important. Thus, in future research focus should be directed towards how high leisure involvement needs to be in relation to leisure habits to encourage people to travel to pursue their favorite leisure pursuits. Anecdotally, we know that people who are interested in such leisure pursuits as science fiction, quilting or train spotting do travel to engage in these activities. However, such findings were not evident for the non-active participants in this study. For implications, it appears that a variety of physically active tourism forms rooted in favorite leisure activities may be particularly attractive to physically active people. Information

10 about their favorite leisure activities and lifestyles might be very useful in developing more specialized tourism products as well as increasing the industry s ability to better predict their behavioral patterns in vacation settings. As compared to the non-active respondent group, the identity and social (i.e., social identity, social interaction, socializing) components of the experience important to the physically active respondents should be built into any active tourism programs and emphasized in their promotion (Gilbert & Hudson, 1998). Certainly for the active tourism activities, promotion linked to leisure lifestyles might be very effective for tourism marketing. Furthermore, there may be ways of linking active tourism to active lifestyles and the goals for overall health promotion pertinent in many societies today. For example, harnessing the dynamic relationship between leisure and tourism might help encourage people to maintain their active and healthy lifestyles while they are on vacation and may provide a chance to enhance their skills or reinforce their motivation in this regard. The novelty of the vacation context might also be used among those people who are not physically active on a regular basis with a chance to participate in physically active tourism pursuits. From these a physically active habit might be developed that might encourage them to keep active once they return home. For passive leisure more generally, subliminal messages associated with their favored leisure attributes of less physically active, relaxing and socializing might be more effective rather than messages directly connected to their leisure activities per se for tourism promotion. REFERE CES Aarts, H., & Dijksterhuis, A. (2000). Habits as knowledge structures: Automaticity in goaldirected behavior. Journal of Personality and Social Psychology, 78, Anderson, J. R. (1990). The adaptive character of thought. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Assael, H. (1998). Consumer Behavior and Marketing Action, South Western College. Backman, S. J., & Crompton, J. L. (1989). Discriminating between continuers and discontinuers of two public leisure services. Journal of Park and Recreation Administration, 7, Backman, S. J. & Crompton, J. L. (1991). The usefulness of selected variables for predicting activity loyalty. Leisure Sciences, 13, Beard, J. G., & Ragheb, M. G. (1983). Measuring leisure motivation. Journal of Leisure Research, 15, Bentler, P. M., & Speckart, G. (1979). Models of attitude-behavior relations. Psychological Review, 86, Brey, E. T., & Lehto, X. Y. (2007). The relationship between daily and vacation activities. Annals of Tourism Research, 34(1), Bricker, K. & Kerstetter, D. (2000). Level of specialization and place attachment: An exploratory study of whitewater recreationists. Leisure Sciences, 22, Bryan. H. (1977). Leisure value systems and recreational specialization: The case of trout anglers. Journal of Leisure Research, 9, Buchanan, T. (1985). Commitment and leisure behavior: A theoretical perspective, Leisure Science, 7, Butler, R. W. (1999). Understanding Tourism. In E. L. Jackson & T. L. Burton, Leisure studies: Prospects for the twenty-first century (pp ). State College, PA: Venture Publishing Inc. Carr, N. (2002). The tourism-leisure behavioral continuum. Annals of Tourism Research, 29,

11 Chon, K.S., & Singh, A. (1995). Marketing resorts to 2000: Review of trends in the USA. Tourism Management, 16(6), Cohen, E. (1974). Who is a tourist? A conceptual clarification. Sociological Review, 22(4), Colton, C. (1987) Leisure, recreation, tourism: A symbolic interactionism view. Annals of Tourism Research, 14, Crompton, J. (1979). Motivations for pleasure vacations. Annals of Tourism Research, 6, Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Francisco: Jossey-Bass. Csikszentmihalyi, M. (1990). Flow: The psychology of optimal experience. New York: Harper Perennial. Currie, R. R. (1997). A pleasure-tourism behaviors framework. Annals of Tourism Research, 24, Davis, C., Brewer, H., & Ratusny, D. (1993). Behavioral frequency and psychological commitment: Necessary concepts in the study of excessive exercising. Journal of Behavioral Medicine, 16, Day, G. S. (1970). Buyer Attitudes and Brand Choice Behavior. New York: Free Press. Dillman, D. A. (2000). Mail and Internet Surveys: The Tailored Design Method. New York, NY: John Wiley & Sons, Inc. Dimanche, F., Havitz, M. E., & Howard, D. R. (1991). Testing the involvement profile scale with selected recreational and touristic activities. Journal of Leisure Research, 23, Eagly, A. H., & Chaiken, S. (2005). Attitude research in the 21 st Century: The current state of knowledge. In D. Albarracin, B. Johnson, & M. Zanna (Eds.), The handbook of attitudes (pp ). Mahwah, NJ: Lawrence Erlbaum Associates. Fodness, D. (1994). Measuring tourist motivation. Annals of Tourism Research, 21(3), Gahwiler, P. & Havitz, M. E. (1998). Toward a relational understanding of leisure social worlds, involvement, psychological commitment, and behavioral loyalty. Leisure Sciences, 20, Gilbert, D., & Hudson, S. (2000). Tourism demand constraints: A skiing participation. Annals of Tourism Research, 27 (4), Griliches, Z., & Mason, W. M. (1972). Education, income, and ability. Journal of Political Economy, 80(3), Gross, M. J., Brien, C., & Brown, G. (2008). Examining the dimensions of a lifestyle tourism destination. International Journal of Culture, Tourism and Hospitality, 2(1), Haggard, L., & Williams, D. (1992). Identify affirmation through leisure activities: Leisure symbols of the self. Journal of Leisure Research, 24, Hallab, Z., & Gursoy, D. (2006). U. S. travelers healthy-living attitudes impacts on their travel information environment. Journal of Hospitality & Leisure Marketing, 14(2), Hallab, Z., Yoon, Y., & Uysal, M. (2003). Segmentation based on the healthy-living attitude: A market s travel behavior. Journal of Hospitality and Leisure Marketing, 10, Hamilton-Smith, E. (1987). Four kinds of tourism. Annals of Tourism Research, 14, Harris, C., McLaughlin, W., & Ham, S. (1987). Integration of recreation and tourism in Idaho. Annals of Tourism Research, 14, Iso-Ahola, S. (1982). Toward a social psychological theory of tourism motivation: A rejoinder. Annals of Tourism Research, 9,

12 Iwasaki, Y. & Havitz, M. (2004). Examining relationships between leisure involvement, psychological commitment and loyalty to a recreation agency. Journal of Leisure Research, 36(1), Jansen-Verbeke, M., & Dietvorst, A. (1987). Leisure, recreation, tourism: A geographical view of integration. Annals of Tourism Research, 14, Kahle, L. (1984), Attitudes and Social Adaptation: A Person-Situation Interaction Approach, Oxford, U.K.: Pergamon. Kelly, J. R. (1983). Leisure identities and interactions. Winchester, MA: Allen, Ltd. Kim, S., Scott, D., & Crompton, J. (1997). An exploration of the relationships among social psychological involvement, behavioral involvement, commitment, and future intentions in the context of bird watching. Journal of Leisure Research, 29(3), Kish, L. (1995). Survey Sampling. New York: John Wiley and Sons, Inc. Kyle, G., Graefe, A., Manning, R., & Bacon, J. (2004a). Effect of activity involvement and place attachment on recreationists perceptions of setting density. Journal of Leisure Research, 36(2), Kyle, G., Graefe, A., Manning, R., & Bacon, J. (2004b). Predictors of behavioral loyalty among hikers along the Appalachian Trail. Leisure Sciences, 26, Lastovicka, J. L. (1979). Questioning the concept of involvement defined product classes. In W.L. Wilkie (Ed.), Advances in Consumer Research, (Vol. 6, pp ). Ann Arbor, MI: Association for Consumer Research. Laurent, G., & Kapferer, J. N. (1985). Measuring consumer involvement profiles. Journal of Marketing Research, 22, Mannell, R., & Iso-Ahola, S. (1987). Psychological nature of leisure and tourism experience. Annals of Tourism Research, 14, McGehee, N. G., Yoon, Y., & Cardenas, D. (2003). Involvement and travel for recreational runners in North Carolina. Journal of Sport Management, 17, McIntyre, N. (1989). The personal meaning of participation: Enduring involvement. Journal of Leisure Research, 21(2), McIntyre, N., & Pigram, J.J. (1992) Recreation specialization reexamined: The case of vehiclebased campers. Leisure Research, 14, Mitchell, A. A. (1979). Involvement: A potentially important mediator of consumer behavior. In W. L. Wilkie (Ed.), Advances in consumer research (Vol. 6, pp ). Ann Arbor, MI: Association for Consumer Research. Moore, K., Cushman, G., & Simmons, D. (1995). Behavioral conceptualization of tourism and leisure. Annals of Tourism Research, 22, Murray, H. A. (1938). Explorations in personality. New York: Oxford University Press. Ouellette, J. A., & Wood, W. (1998). Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychological Bulletin, 124, Pearce, P. L. (1988). The Ulysses Factor: Evaluating Visitors in Tourist Settings. New York: Springer-Verlag. Pearce, P. L., & Caltabiano, M. L. (1983). Inferring travel motivation from travelers experiences. Journal of Travel Research, 22(2), Perdue, R. (1993). External information search in marine recreational fishing. Leisure Sciences, 15, Ragheb, M. G., & Tate, R. L. (1993). A behavioral model of leisure participation, based on leisure attitude, motivation and satisfaction. Leisure Studies, 12,

13 Rapoport, R., & Rapoport, R. N. (1975). Leisure and the family life cycle. London, UK: Routledge. Richins, M. & Bloch, P. (1986). After the new wears OE the temporal context of product involvement. Journal of Consumer Research, 13, Ritchie, B. W. (1998). Bicycle tourism in the South Island of New Zealand: Planning and management issues. Tourism Management, 19(6), Robertson, T. S. (1976). Low-commitment consumer behavior. Journal of Advertising Research, 16, Ryan, C., & Glendon, A. I. (1998). Tourist motives: An application of the leisure motivation scale to UK tourists. Annals of Tourism Research, 25, Sherif, M., & Cantril, H. (1947). The psychology of ego-involvements: Social attitudes and identifications. New York: Wiley. Shipway, R., & Jones, I. (2007). The great suburban Everest: An insiders perspective on experiences at the 2007 London Marathon. Journal of Sport & Tourism, 13, Stanton-Rich, M., & Iso-Ahola, S. (1998). Burnout and leisure. Journal of Applied Social Psychology, 28, Triandis, H. C. (1977). Interpersonal behavior. Monterey, CA: Brooks Cole. Valois, P., Desharnais, R., & Godin, G. (1988). A comparison of the Fishbein and Ajzen and the Triandis Attitudinal Models for the prediction of exercise intention and behavior. Journal of Behavioral Medicine, 11, Verplanken, B., & Aarts, H. (1999). Habit, attitude, and planned behavior: Is habit an empty construct or an interesting case of goal-directed automaticity? European Review of Social Psychology, 10, Verplanken, B., & Orbell, S. (2003). Reflections on past behavior: A self-report index of habit strength. Journal of Applied Social Psychology, 33, Verplanken, B., Aarts, H., & van Knippenberg, A. (1997). Habit, information acquisition, and the process of making travel mode choices. European Journal of Social Psychology, 27, Verplanken, B., Aarts, H., van Knippenberg, A., & Moonen, A. (1998). Habit, information acquisition, and the process of making travel mode choices. British Journal of Social Psychology, 37, Wood, W., Quinn, J.M., & Kashy, D.A. (2002). Habits in everyday life: Thought, emotion, and action. Journal of Personality and Social Psychology, 83, Woratschek, H., Hannich, F., & Ritchie, B. (2007). Motivations of sport tourists: An empirical analysis in several European rock climbing regions. Unpublished consultation paper, Universität Bayreuth. Retrieved January 26, 2009, from