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The Relationship between Active Leisure and Active Vacations

Permanent Link: http://ufdc.ufl.edu/UFE0024249/00001

Material Information

Title: The Relationship between Active Leisure and Active Vacations
Physical Description: 1 online resource (254 p.)
Language: english
Creator: Chang, Seohee
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: active, activities, behavioral, habit, health, involvement, leisure, motivation, physical, psychology, recreation, schema, sport, tourism, vacations
Tourism, Recreation, and Sport Management -- Dissertations, Academic -- UF
Genre: Health and Human Performance thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy THE RELATIONSHIP BETWEEN ACTIVE LEISURE AND ACTIVE VACATIONS By Seohee Chang May 2009 Chair: Heather J. Gibson Major: Tourism, Leisure, and Sport With an increase in active life styles which incorporate active leisure pursuits, interest in active vacation has increased (Chon & Singh, 1995; Henderson, 2005a, 2005b; Sung, 2004), subsequently, the range of sport-tourism types, especially active sport tourism has become increasingly popular (Gibson, 1998a, 1998b; Glyptis, 1991). The link between leisure and tourism has been discussed by researchers in terms of a psychological and behavioral connection (Brey & Lehto, 2007; Carr, 2002; Currie, 1997; Mannell & Iso-Ahola, 1987). Particularly, Carr (2002) suggested that while tourism behaviors tend to be more hedonic-oriented, they are rooted in leisure behaviors, and can be explained by individuals attitudes, habits, or personality. However, few researchers have empirically examined the leisure-tourism connection. Thus, this study set out to empirically examine if active leisure participation is connected to participation in active vacations and if so, to examine the complexities of this relationship. Data were collected from UF Alumni Association members using an on-line survey and ultimately 316 active leisure-active vacation participants were identified. The results provide a more in-depth understanding of the relationship between active leisure participation and active vacations. The findings support the leisure-tourism continuum suggested by Currie (1997) and Carr (2002). First of all, the significant direct and indirect influences of leisure involvement and leisure habits on vacation motivation and vacation behaviors support the leisure-tourism connection. Second, many of the participants chose activities from the same category such as water sports for leisure and water sports for vacations but there were slight differences in the activities identified as favorite leisure or vacation activities. Seemingly, many of them preferred experiencing novel, more hedonic activities during vacations, but their values or active lifestyles remained constant. Consistent with this, the majority of respondents preferred more novel than familiar destinations for their vacations (Lee & Crompton, 1992). While novel experiences were pursued by many respondents, they still maintained the same active lifestyles and preferred the same category of physical activities while on vacation. Last, the respondents who reported they visited their family or friends or had different primary motivations for their trips also participated in active sports and physical activities while on vacation. Based on these findings, an Expanded Framework of Active Leisure (EFAL) was proposed to explain a wider range of sport tourism types than had been previously identified, considering both activity and destination, based upon the suppositions of previous work (Gammon & Robinson, 1997; Woratschek et al., 2007). Moreover, this framework was generated from psychological and behavioral patterns of a sample of participants who were not members of a specialized sports group sample. However, some of the types of active vacationers identified were hard to explain using the theories framing this study. Therefore, it is suggested that more information about external factors such as destination attractions combined with internal factors such as personality should be used to explain different types of active sport tourism.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Seohee Chang.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Gibson, Heather J.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024249:00001

Permanent Link: http://ufdc.ufl.edu/UFE0024249/00001

Material Information

Title: The Relationship between Active Leisure and Active Vacations
Physical Description: 1 online resource (254 p.)
Language: english
Creator: Chang, Seohee
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: active, activities, behavioral, habit, health, involvement, leisure, motivation, physical, psychology, recreation, schema, sport, tourism, vacations
Tourism, Recreation, and Sport Management -- Dissertations, Academic -- UF
Genre: Health and Human Performance thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy THE RELATIONSHIP BETWEEN ACTIVE LEISURE AND ACTIVE VACATIONS By Seohee Chang May 2009 Chair: Heather J. Gibson Major: Tourism, Leisure, and Sport With an increase in active life styles which incorporate active leisure pursuits, interest in active vacation has increased (Chon & Singh, 1995; Henderson, 2005a, 2005b; Sung, 2004), subsequently, the range of sport-tourism types, especially active sport tourism has become increasingly popular (Gibson, 1998a, 1998b; Glyptis, 1991). The link between leisure and tourism has been discussed by researchers in terms of a psychological and behavioral connection (Brey & Lehto, 2007; Carr, 2002; Currie, 1997; Mannell & Iso-Ahola, 1987). Particularly, Carr (2002) suggested that while tourism behaviors tend to be more hedonic-oriented, they are rooted in leisure behaviors, and can be explained by individuals attitudes, habits, or personality. However, few researchers have empirically examined the leisure-tourism connection. Thus, this study set out to empirically examine if active leisure participation is connected to participation in active vacations and if so, to examine the complexities of this relationship. Data were collected from UF Alumni Association members using an on-line survey and ultimately 316 active leisure-active vacation participants were identified. The results provide a more in-depth understanding of the relationship between active leisure participation and active vacations. The findings support the leisure-tourism continuum suggested by Currie (1997) and Carr (2002). First of all, the significant direct and indirect influences of leisure involvement and leisure habits on vacation motivation and vacation behaviors support the leisure-tourism connection. Second, many of the participants chose activities from the same category such as water sports for leisure and water sports for vacations but there were slight differences in the activities identified as favorite leisure or vacation activities. Seemingly, many of them preferred experiencing novel, more hedonic activities during vacations, but their values or active lifestyles remained constant. Consistent with this, the majority of respondents preferred more novel than familiar destinations for their vacations (Lee & Crompton, 1992). While novel experiences were pursued by many respondents, they still maintained the same active lifestyles and preferred the same category of physical activities while on vacation. Last, the respondents who reported they visited their family or friends or had different primary motivations for their trips also participated in active sports and physical activities while on vacation. Based on these findings, an Expanded Framework of Active Leisure (EFAL) was proposed to explain a wider range of sport tourism types than had been previously identified, considering both activity and destination, based upon the suppositions of previous work (Gammon & Robinson, 1997; Woratschek et al., 2007). Moreover, this framework was generated from psychological and behavioral patterns of a sample of participants who were not members of a specialized sports group sample. However, some of the types of active vacationers identified were hard to explain using the theories framing this study. Therefore, it is suggested that more information about external factors such as destination attractions combined with internal factors such as personality should be used to explain different types of active sport tourism.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Seohee Chang.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Gibson, Heather J.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024249:00001


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1 RELATIONSHIP BETWEEN ACTIVE LEISURE AND ACTIVE VACA TIONS By SEOHEE CHANG A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2009

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2 2009 Seohee Chang

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3 To my parents

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4 ACKNOWLEDGMENTS My long-time interest in the active leisure-active vacation/tourism connection pushed me to attend the University of Florida to receive guid ance from my chair, Dr. Gibson. Whenever I expressed my ideas, she listened carefully and rece ived my ideas with patience and encouragement. While I found I had confined myself to focusing on details, Dr. Gibson helped me to develop a bigger picture by contributing her incredible knowledge about sport tourism and tremendously insightful comments. Without her, I mi ght be aimless and lose my vision. In the whole Ph.D. process, her carrot and stick encourage d me to keep developing my study. I am very grateful to Dr. Gibson. I also benefited from helpf ul comments on sport and tourism from my committee members, Dr. Pennington-Gray and Dr. Zhan g and my research professor, Dr. Kiki. Their diverse knowledge about sport and tourism gav e me inspiration. I also received useful and valuable comments and feedbacks from my current com mittee member, Dr. Chambers and my former committee member, Dr. Albarracin when I was confused with psychological theories and concepts. In addition, I would like to say “special thanks” to Drs. Mark Havitz, Laurence Chalip, Douglas Kleiber, James Petrick, and Bas Verplanken who were my content validity expert members as well as other panel members. Without the ir important feedback and advice, the data collection itself would have been impossible. Dr. A lgina helped me hugely with the structural equation model analysis. All of my colleagues in my department also gave me helpful suggestions throughout the whole process of my diss ertation. My family was always with me whenever I needed them regardless of physical distance. I owe countless emotional and intellectual debt to my family. Particularly, I would like to thank my parents who supported me without limits. My fath er always gave me confidence and my mother has been interested in my research, adding v alue to my study all the time. I dedicate my dissertation to my parents.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................... ................................................... ........................4 LIST OF TABLES..................................... ................................................... ...................................8 LIST OF TERMS...................................... ................................................... ..................................10 ABSTRACT........................................... ................................................... .....................................11 CHAPTER 1 INTRODUCTION..................................... ................................................... ..........................13 Statement of the Problem........................... ................................................... ..........................16 Theoretical Model.................................. ................................................... ..............................20 Purpose of Study................................... ................................................... ...............................23 Research Questions................................. ................................................... .............................24 Hypotheses......................................... ................................................... ..................................25 2 REVIEW OF LITERATURE............................. ................................................... .................27 Leisure and Tourism................................ ................................................... ............................27 What Is Leisure?................................... ................................................... ........................27 What Is Tourism?................................... ................................................... ......................29 What Is the Relationship between Leisure and Touris m?...............................................32 Sport as Leisure and Tourism....................... ................................................... ................38 Involvement........................................ ................................................... .................................48 Theoretical Foundation in Social Psychology........ ................................................... ......48 Consumer Involvement............................... ................................................... .................51 Leisure Involvement................................ ................................................... .....................53 Habitual Behavior.................................. ................................................... ..............................62 Motivation......................................... ................................................... ...................................69 Motivation Theories................................ ................................................... .....................69 Tourism Motivation................................. ................................................... .....................74 Leisure and Sport Motivation....................... ................................................... ................80 Summary............................................ ................................................... ..................................82 3 METHODS.......................................... ................................................... ................................84 Data Collection.................................... ................................................... ................................84 Instrumentation.................................... ................................................... ................................86 Face Validity and Pre-Test......................... ................................................... ..................86 Content Validity................................... ................................................... ........................88 Content validity procedure......................... ................................................... ...........88 Content validity analysis.......................... ................................................... .............93

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6 Data Collection Procedures......................... ................................................... ........................97 Participants....................................... ................................................... .................................100 Data Analysis...................................... ................................................... ...............................102 4 RESULTS.......................................... ................................................... ................................121 Types of Leisure Activities........................ ................................................... ........................121 Leisure Participation Patterns..................... ................................................... .......................121 Types of Vacation Activities....................... ................................................... ......................122 Vacation Participation Patterns.................... ................................................... ......................123 Similarity between Favorite Leisure and Favorite Va cation Activities................................12 4 Leisure Activity Participation Patterns During Vaca tion............................................... ......127 Levels of Leisure Involvement...................... ................................................... ....................129 Levels of Leisure Habit............................ ................................................... .........................130 Levels of Vacation Motivation...................... ................................................... ....................130 Levels of Vacation Behavior........................ ................................................... .....................131 Confirmatory Factor Analysis (CFA)................. ................................................... ...............131 Confirmatory Factor Analysis (CFA) of Leisure Invol vement.....................................132 Confirmatory Factor Analysis (CFA) of Leisure Habit ................................................134 Confirmatory Factor Analysis (CFA) of Vacation Moti vation.....................................135 Confirmatory Factor Analysis (CFA) of Vacation Beha vior........................................136 Measurement Portion of Structural Equation Modeling (SEM)...........................................13 8 Structural Portion of Structural Equation Modeling (SEM).............................................. ...140 Model A............................................ ................................................... ..........................140 Model B............................................ ................................................... ..........................141 Model C............................................ ................................................... ..........................142 Model Comparisons.................................. ................................................... ..................142 5 DISCUSSION....................................... ................................................... .............................165 Leisure-Vacation Connection........................ ................................................... ....................165 Involvement, Habit, Motivation, and Behavior....... ................................................... ..........169 Leisure Involvement................................ ................................................... ...................169 Leisure Habit...................................... ................................................... ........................172 Vacation Motivation................................ ................................................... ...................173 Vacation Behavior.................................. ................................................... ....................175 Leisure Involvement Leisure Habit..................................... .....................................176 Leisure Involvement Leisure Habit Vacation Motivation............................... ...177 Vacation Motivation Vacation Behavior.................................. ...............................178 Implications of the Study.......................... ................................................... .........................178 Implication for a New Theoretical Framework of Acti ve Leisure and Vacations........178 Implication for Applied Settings................... ................................................... .............181 Recommendation for Future Research................. ................................................... .............195 Delimitations...................................... ................................................... ................................199 Limitations........................................ ................................................... .................................199 Conclusion......................................... ................................................... ................................200

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7 APPENDIX A DEFINITIONS OF INVOLVEMENT....................... ................................................... .......203 B INSTITUTIONAL REVIEW BOARD APPROVAL FOR CONTENT V ALIDITY..........204 C SURVEY INSTRUMENT FOR CONTENT VALIDITY........... ........................................208 D INSTITUTIONAL REVIEW BOARD APPROVAL FOR THE STUDY SAMPLE..........216 E SURVEY INSTRUMENT FOR THE STUDY SAMPLE........... ........................................220 LIST OF REFERENCES................................. ................................................... .........................226 BIOGRAPHICAL SKETCH................................ ................................................... ....................253

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8 LIST OF TABLES Table page 3-1 Leisure involvement scale for content validity. ................................................... ............107 3-2 Leisure habit scale for content validity....... ................................................... ..................108 3-3 Vacation motivation scale for content validity. ................................................... ............109 3-4 Vacation behavior scale for content validity... ................................................... .............110 3-5 One sample t-test for content validity......... ................................................... ..................111 3-6 CVI agreement measures for content validity.... ................................................... ..........113 3-7 Revised leisure involvement scale.............. ................................................... ..................115 3-8 Revised leisure habit scale.................... ................................................... ........................116 3-9 Revised vacation motivation scale.............. ................................................... ..................117 3-10 Revised vacation behavior scale............... ................................................... ....................118 3-11 Demographic characteristics of the respondents ................................................... ...........119 4-1 Favorite leisure activities and favorite vacati on activities...................................... .........144 4-2 Categories of the different types of favorite l eisure and vacation activities....................1 45 4-3 Similarity between leisure categories and vacat ion categories..................................... ...146 4-4 Goodness fit indices for each construct........ ................................................... ................148 4-5 Reliability and validity of the leisure involve ment CFA model..................................... .149 4-6 Reliability and validity of the leisure habit C FA model........................................... .......150 4-7 Reliability and validity of the vacation motiva tion CFA model..................................... .151 4-8 Reliability and validity of the vacation behavi or CFA model....................................... ..152 4-9 Goodness fit indices for the measurement model and structural equation models..........153 4-10 Reliability and validity of the measurement mo del................................................ .........154 4-11 Direct, indirect and total effects of the stru ctural equation model.............................. .....155

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9 LIST OF FIGURES Figure page 1-1 Full model of the relationship between active l eisure and active vacations......................26 4-1 Similarity between favorite leisure and vacatio n activities....................................... ......156 4-2 First-order CFA model of leisure involvement... ................................................... ..........157 4-3 First-order CFA model of leisure habit......... ................................................... ................158 4-4 First-order CFA model of vacation motivation... ................................................... .........159 4-5 First-order CFA model of vacation behavior..... ................................................... ...........160 4-6 Measurement model of active leisure and vacatio ns................................................. ......161 4-7 Model A: Measurement and structural model of ac tive leisure and vacations................162 4-8 Model B: Competing model nested in model A..... ................................................... ......163 4-9 Model C: Competing model nested in model A and in model B.....................................164 5-1 Expanded framework of active leisure (EFAL).... ................................................... ........202

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10 LIST OF TERMS INVOLVEMENT Belief structure associated with ego-value that le ads to extreme attitudes LEISURE INVOLVEMENT Belief structure that encourages extreme leisure a ttitudes generated from identification between ego-value and leisure activity HABITUAL BEHAVIOR Behavior associated wholly or partially with uncon scious components resulting from repetitive behaviors and that encourages consistency between past behavior, curre nt behavior, and future behavior HABITUAL LEISURE BEHAVIOR Leisure behavior associated wholly or partially wi th unconscious components resulting from repetitive le isure behaviors and that encourages consistency between p ast leisure behavior, current leisure behavior and future leisu re behavior NEEDS/MOTIVES General end state like self-regard gained from ach ievement of specific goals (Eagly & Chaiken, 2005) MOTIVATION Engine of motives to guide thoughts and behaviors (Eagly & Chaiken, 2005) VACATION MOTIVATION Engine of motives to guide thoughts and behav iors to travel SPORT TOURISM Leisure-based travel that is temporarily away from home to participate in physical activities, to observe phys ical activities and to visit sport-related attractions (Gibson, 199 8b, p.49) ACTIVE SPORT TOURISTS People who travel to take part in sport and physic al activities (Gibson, 1998b) LEISURE ACTIVITY Activity people take part in during their free tim e, usually close to home VACATION ACTIVITY Activity people take part in when they travel away from their home for a vacation (i.e., for pleasure and stay fo r at least one night) ACTIVE LEISURE Leisure related to participation in sports, physic al activities, and active outdoor recreation ACTIVE VACATIONS/TOURISM Vacations in which participation in sports, physic al activities, and active outdoor recreation is an important part of the vacation experience, regardless of primary or secon dary motivation to travel

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11 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy RELATIONSHIP BETWEEN ACTIVE LEISURE AND ACTIVE VACA TIONS By Seohee Chang May 2009 Chair: Heather J. Gibson Major: Health and Human Performance With an increase in active life styles which incorp orate active leisure pursuits, interest in active vacation has increased, subsequently, the ra nge of sport-tourism types, especially active sport tourism has become increasingly popular. The link between leisure and tourism has been discussed by researchers in terms of a psychologica l and behavioral connection. Particularly, while tourism behaviors tend to be more hedonic-ori ented, they are rooted in leisure behaviors, and can be explained by individuals’ attitudes, hab its, or personality. However, few researchers have empirically examined the leisure-tourism conne ction. Thus, this study set out to empirically examine if active leisure participation is connecte d to participation in active vacations and if so, to examine the complexities of this relationship. D ata were collected from UF Alumni Association members using an on-line survey and ult imately 316 active leisure-active vacation participants were identified. The results provide a more in-depth understanding o f the relationship between active leisure participation and active vacations. The fin dings support the leisure-tourism continuum suggested by researchers1. First of all, the significant direct and indirect influences of leisure involvement and leisure habits on vacation motivati on and vacation behaviors support the 1 Carr, N. (2002). The tourism-leisure behavioral co ntinuum. Annals of Tourism Research, 29 972-986.

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12 leisure-tourism connection. Second, many of the par ticipants chose activities from the same category such as water sports for leisure and water sports for vacations but there were slight differences in the activities identified as favorit e leisure or vacation activities. Seemingly, many of them preferred experiencing novel, more hedonic activities during vacations, but their values or active lifestyles remained constant. Consistent with this, the majority of respondents preferred more novel than familiar destinations for their vac ations. While novel experiences were pursued by many respondents, they still maintained the same active lifestyles and preferred the same category of physical activities while on vacation. Last, the respondents who reported they visited their family or friends or had different primary mo tivations for their trips also participated in active sports and physical activities while on vaca tion. Based on these findings, an Expanded Framework of A ctive Leisure (EFAL) was proposed to explain a wider range of sport tourism types tha n had been previously identified, considering both activity and destination, based upon the suppo sitions of previous work. Moreover, this framework was generated from psychological and beha vioral patterns of a sample of participants who were not members of a specialized sports group sample. However, some of the types of active vacationers identified were hard to explain using the theories framing this study. Therefore, it is suggested that more information about externa l factors such as destination attractions combined with internal factors such as personality should be used to explain different types of active sport tourism.

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13 CHAPTER 1 INTRODUCTION Increasingly more people are concerned about health y and active lifestyles (Glyptis, 1991). Consequently, many individuals have adopted active leisure pursuits which in turn have influenced tourism behaviors and opportunities as m ore people have sought active vacations (Chon & Singh, 1995; Fluker & Turner, 2000; Hall, 1 992; Jefferson, 1995; Redmond, 1991; Sung, 2004). Indeed, over the past ten years the te rm sport tourism has been used to describe sport and physically active vacations. Sport touris m of various types has become increasingly popular and many communities are using sport to att ract tourists (Redmond, 1991; Ritchie, 1998). Most researchers agree there are both passiv e, primarily spectator-oriented event-based sport tourism and active forms where tourists trave l to take part in sport (Gammon & Robinson, 1997; Gibson, 1998a, 1998b; Hinch & Higham, 2001; N ogawa, Yamaguchi, & Hagi, 1996; Standeven & DeKnop, 1999). Taking a lead from Redmo nd (1991), Gibson (1998a, 1998b) proposed a third type called “nostalgia” sport tour ism and refers to travel associated with sport attractions and other sports-themed vacations. Mega event-based sport tourism such as the Olympic Games and the FIFA football World Cup tends to draw the most attention from academics and the industry. However, besides eventbased sport tourism, numerous recreational sport ac tivities, programs, facilities, and resorts have become popular with active sport tourists (Gibson, 1998a; Glyptis, 1991; Redmond, 1991). In a study of 220 tour companies, Adventure Travel Trade Association (ATTA) found that clients tended to rank such activities as hiking, kayaking, rafting, cycling, and mountain biking as more popular vacation activities than more passive pursu its (JOPERD, 2007). Moreover, in a study of sports-related travel to Florida, golf was found to be the most popular reason for visiting the state when compared to all other sports-related opportuni ties including all forms of event sport

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14 tourism with the exception of motor sports because motor sport tourists did not participate in the study (Villamil & Cruz, 2005). Nonetheless, while active lifestyles and regular pa rticipation in active leisure seem to be associated with the increasing popularity of active sport tourism, there has been little empirical research on the relationship between every day leis ure activity and choice of vacation behavior. Existing studies have tended to treat leisure and t ourism contexts as completely unrelated entities. This lack of connection between leisure a nd tourism has made it difficult to gain a real understanding as to how tourist behaviors relate to the wider life context of individuals. Mannell and Iso-Ahola (1987) postulated that leisur e and tourism have a psychological and behavioral relationship from an experiential standp oint. Developing this line of thought further, Carr (2002) noted that individuals’ norms, values, preferences, personality, and habits are likely to induce similar behavioral patterns between leisu re activities and tourism behaviors. A similar finding was made by Brey and Lehto (2007) who expla ined behavioral consistency between leisure and tourism using the concept of leisure in volvement. Particularly, physical activity tends to be a bridge connecting leisure, recreation, and travel within the overall context of healthy and active lives (Bocarro, Kanters, & Casper, 2006; God bey, Caldwell, Floyd, & Payne, 2005; Henderson, 2005a, 2005b; Henderson, & Bialeschki, 2 005; Sallis, Linton, & Kraft, 2005). Active living is a way to include physical activity in everyday life, while participating in sport and physical activity is seen as part of thes e active lives and tends to be regarded as an important part of the leisure of these individuals (Henderson, 2005b). Physically active lifestyles have increased the demand for active vacations (Flu ker & Turner, 2000). For example, according to the American Volkssport Association (2008), ther e are 350 walking clubs throughout the US, and over 3,000 events are held every year. Particip ants take walks close their homes as well as

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15 traveling to go on walks further. They also occasio nally report taking part in other sports such as biking, swimming, or skiing and further traveling f or those sports. This example shows how people who are absorbed in sports, physical activit ies, and active outdoor recreation in the leisure context are getting involved in sports, physical ac tivities and active outdoor recreation while on vacation. In North American sport tourism studies in the 1980 s and the early 1990s, there was a tendency to ignore active vacations and to focus on mega sport events and event based sport tourism, while in European sport tourism research t here was more of a focus on active sport tourism from the beginning of the1980s (e.g., De Kn op, 1987; Glyptis, 1982). In recent years, active sport tourism is beginning to spread beyond the European context and researchers around the world have investigated various types of active sport tourism including: mountaineering tourists (Pomfret, 2006), participants in the Maste rs Games (Ryan & Locker, 2002; Trauer, Ryan, & Locker, 2003), recreational runners (McGehee, Yoo n, & Cardenas, 2003), golf tourism (Gibson & Pennington-Gray, 2005), and snow sports ( Hudson, 2000; Williams & Fidgeon, 2000). Involvement and the habits of people participating in active leisure activities seem to be the most important variables in understanding the psych ological and behavioral relationships between leisure and vacations/tourism (Brey & Lehto 2007; Maddux, 1993; Valois, Desharnais, & Godin, 1988). Involvement is a belief related to ego-value (Sherif & Cantril, 1947), and habit or habitual behavior refers to a behavior partially or entirely associated with unconscious mental processes that emerge from repeating an activity (V erplanken, Aarts, Knippenberg, & Moonen, 1998). Both leisure involvement and leisure habit e ncourage people to limit their choices and as a result, reject alternative leisure activities (Sh erif & Cantril, 1947; Verplanken, et al., 1998). This helps maintain behavioral consistency even in different environments (Havitz & Dimanche,

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16 1997). As such, this psychological and behavioral p rocess helps to understand the close relationship between leisure and vacation/tourism p references and behaviors. Statement of the Problem While there have been few empirical studies about t he connection between leisure and tourism, many researchers have pointed out that und erstanding the relationship between leisure and tourism is important because psychological and behavioral influences on participation in leisure activities and in vacation activities are l ikely to be strongly shared (Brey & Lehto, 2007; Carr, 2002; Fedler, 1987; Mannell & Iso-Ahola, 1987 ; Moore, Cushman, & Simmons, 1995). Of particular interest to this study, while active spo rt tourism opportunities have expanded in popularity in response to demand from people who ar e physically active or involved in sports during their leisure (Glyptis, 1991; Redmond, 1991) the relationship between active leisure and vacation/tourism behaviors is underdeveloped empiri cally. We know little about how, or if leisure involvement influences tourism behaviors, i n particular the relationship between active leisure and active sport tourism. There have been s ome studies in which leisure involvement has been investigated in relation to future leisure act ivity or in developing leisure activities (Gahwiler & Havitz, 1998; Iwasaki & Havitz, 2004; K im, Scott, & Crompton, 1997). However, there has been little focus on how leisure activity involvement in everyday environments may influence vacation/tourism behaviors occurring in d ifferent environments away from the routine. In addition to examining psychological involvement with leisure activities, it is suggested that a more in-depth understanding may be achieved through examining the habitual behaviors associated with leisure activities. The underlying premise of the involvement construct is that an individual’s choice of behaviors is conscious and i ntentional. However, behaviors, especially those related to lifestyles, are not always deliber ate and intentional (Bentler & Speckart, 1979; Fazio, 1990; Triandis, 1977). While engaging in a n ew activity requires or involves intentional

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17 choice, over time repetitive activity becomes habit ual and unconscious behavior partly or wholly (Beatty & Kahle, 1988; Triandis, 1977). Hence, alon g with involvement, it is proposed that considering habitual behavior will be complementary in predicting future behaviors. Particularly, habit tends to be a more significant variable in ph ysical activity than other leisure activities (Valois, Desharnais, & Godin, 1988). However, habit should not be operationalized and measured merely by frequency of past behaviors. It is a multidimensional construct including various features such as automaticity, limited info rmation processing and quicker reaction to certain situational cues, as well as regularity (Aa rts, Verplanken, & Knippenberg, 1997; Verplanken & Orbell, 2003). Furthermore, even though leisure involvement and ha bit influence vacation/tourism behaviors, tourism motivation may mediate the assoc iation between leisure and tourism. Presumably, to alleviate the impacts of dissonance between leisure activities and tourism activities, people are motivated to balance tourism activities with their leisure activities (Festinger, 1957; Kelly, 1987). Iso-Ahola (1982, 19 83) asserted that people have two main motivations to travel: seeking and escaping. Seekin g is a motivation whereby individuals strive to gain intrinsic rewards, and escaping is a motiva tion where individuals attempt to get away from their routine environments. More specifically, Beard and Ragheb (1983) suggested that individuals are motivated by four different motivat ional dimensions: intellectual, social, competence/mastery and stimulus avoidance motives. Ryan and Glendon (1998) applied Beard and Ragheb’s leisure motivation scale to a tourism setting and found that it was a valid measure of tourism motivation. In many tourism studies rese archers have attempted to categorize tourism behaviors from tourism motivations (Bieger & Laesse r, 2002; Cha, McCleary, & Uysal, 1995;

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18 Formica & Uysal, 1998), or have tried to infer tour ism motives from observed behaviors (Bryant & Morrison, 1980; Davis & Sternquist, 1987). As such, a study of the relationship between leisur e activity involvement, leisure habit, vacation/tourism motivation and vacation/tourism be havior might provide an initial empirical and theoretical foundation for the leisure-tourism continuum proposed by Carr (2002). Additionally, furthering the understanding of a tie between active leisure behaviors and sport tourism behaviors is likely to give rise to some id eas for future sport tourism research that are still underdeveloped. This study contributes to testing empirically the l inkages between leisure and tourism, and establishing a theoretical model of this relationsh ip. Particularly, as the relationship between leisure involvement, leisure habit, tourism motivat ion, tourism behaviors, and future tourists’ behavioral intentions is tested, it may be possible to see how leisure activity involvement and habit are related to tourism behaviors. This study contributed to measuring more complex fa ctors of habitual behavior by means of self-perceived habit constructs in addition to a ctual behavioral frequency, which could produce more reliable results. From these results, a theoretical framework was developed suggesting an explanation of the relationship betwe en leisure and vacation/tourism, especially the relationship between active leisure and active sport tourism. As such, this study contributed to the growing body of knowledge in sport tourism, particularly to understand the ‘why’ of sport tourism instead of the ‘what’ (Gibson, 2004). Furthermore, this study had implications for establ ishing sport tourism policy, marketing, and product development by providing a better under standing of the leisure-tourism linkage. Indeed, existing studies have tended to separate ac tive leisure participants who are immersed in

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19 sports, physical activities, and active outdoor rec reation from tourists who are involved in sports, physical activities, and active outdoor recreation. This approach hinders the whole leisuretourism process, especially in developing policy, m arketing strategies, or products to satisfy both leisure participants and tourists. The supply side of leisure and tourism might offer opportunities that can satisfy people’s needs by providing activi ties that are more consistent across the two contexts. More positively, the supply side can prov ide interesting products for new leisure forms and tourism forms developed from the dynamic intera ction between leisure and tourism. For example, some individuals travel to develop their f avorite leisure activity in a familiar destination during vacations, whereas other people want to experience new leisure activities similar to their favorite leisure activity in a dif ferent destination. Both the cases might have different vacation behaviors, but they stem from th e same root. Also, some groups of people who participate in certain leisure activities often gen erate or need to make trips to satisfy their shared specific interest. Conversely, people who meet in t ourism settings often maintain their friendships in leisure settings and may create new leisure activity groups once they return home. The supply side could actively respond to these new situations. Finally, this study may have implications for impro ving people’s quality of life by satisfying the needs of people who want to maintain and develop their preferred leisure activities in tourism settings, or alternatively who want to h ave the chance to participate in new tourism activities developed from leisure activities. Parti cularly, this study could encourage active and healthy lifestyles of people to extend from the lei sure realm to the tourism realm. People’s interest and needs for physical and psychological h ealth in everyday leisure may be more satisfied by taking part in sport tourism (Standeve n & De Knop, 1999). As physical activities and

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20 mental well-being have a close relationship (Ingham 1990), a synergetic relationship between leisure activities and tourism activities may enhan ce people’s health and overall quality of life. Theoretical Model For the purpose of this study, a theoretical model is proposed to show the relationship between leisure involvement, leisure habit, vacatio n motivation and vacation behavior (Figure11). The basic premises of this model are that invol vement with preferred leisure activities encourages repetitive behaviors. Overtime repetitiv e leisure behaviors become habitual behaviors that are characterized as behaviors that do not nee d deliberation due to well learned schemata (Beatty & Kahle, 1988). Greater involvement leads t o this habitual behavior. More specifically, the process of the micro-units (i.e., beliefs, atti tudes, and behaviors) comprising this involvement-habit connection is that beliefs influe nce attitudes, and in turn, attitudes influence behaviors. However, on the contrary, there is an a lternative assumption that habit might increase involvement. Several studies supported this assumpt ion that behaviors produce beliefs (Bem, 1965; Chaiken & Baldwin, 1981; Fazio, 1986; Schlenk er & Trudeau, 1990). Self-perception theory (Bem, 1965) assumes that people infer their beliefs and attitudes from their past behaviors. Thus, in turn, these inferred beliefs and attitudes become stronger through behaviors (Fazio, Sherman, & Harr, 1982). This means that an action b y itself encourages involvement to occur or increase. This has been underpinned by the results from some experimental studies related to commitment theory. Miller (1965) found that after p eople were forced to write down a specific issue, they began having positive beliefs towards t his issue and then, became involved in this issue. Halverson and Pallak (1978) found that peopl e who were encouraged to verbally express their attitudes towards a certain issue in public i ncreased their involvement with the issue more than people who were not encouraged to express thei r attitudes towards the issue. Miller and

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21 Marks (1996) also postulated that purchasing a prod uct over a long period increases involvement. Accordingly, both involvement and habi ts could enhance each other. Both involvement and habit encourage people to narr ow their range of beliefs and attitudes towards certain objects (Kahle, 1984; Sherif & Cant ril, 1947; Verplanken & Orbell, 2003), and as a consequence, to reject other alternative activ ities, inhibit attitude change, and promote consistent behavior (Miller, 1965). Particularly, i nvolvement encourages consistent behavior at the conscious level (Sherif & Hovland, 1961), where as habit enhances it at the unconscious level (Triandis, 1977). Certainly, researchers in leisure studies have found that leisure involvement and past behavior influence future leisure behavior s (Gahwiler & Havitz, 1998, Kim, Scott, & Crompton, 1997; Prichard, Havitz, & Howard, 1999), however, as yet nobody has examined habit and leisure. In this respect, leisure involvement and leisure ha bit may also influence vacation/tourism motivation, and vacation/tourism behavior, although inherently tourism takes place in a different environment away from a routine environment. Noneth eless, leisure and tourism as entities share similar features (e.g., quality of experience, intr insic motivation, perceived freedom, free time, etc). Thus, the possibility that psychological and behavioral consistency exists between both leisure and tourism contexts is high (Carr, 2002; H amilton-Smith, 1987; Mannell & Iso-Ahola, 1987; Moore, Cushman, & Simmons, 1995). For example given that individuals are motivated to travel to develop their preferred leisure activi ties, leisure and tourism behaviors are likely to be consistent. Even if people may be motivated prim arily to visit family or friends (Moscardo, Pearce, Morrison, Green, & O’Leary, 2000), people w ho are immersed in a particular leisure activity are likely to keep their leisure activitie s while visiting friends or their family during a

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22 vacation. That is, distinct from their primary moti vation to travel, their main activities during a vacation may be the same, or similar to their prefe rred leisure activities. For each relationship depicted in the theoretical m odel, the leisure involvement-tourism motivation link is accounted for by many theories t hat hypothesize the influence of beliefs on attitudes (e.g., Carlson’s (1956) expectancy-value model, Fishbein and Ajzen’s (1975) theory of reasoned action). The relationship between leisure habit and tourism motivation is explained by Triandis’ (1977) theory, Bentler and Speckart’s (19 79) model, and Bem’s (1965) self-perception theory assuming that habits or past behaviors influ ence beliefs and attitudes. Particularly, to reduce the dissonance between leis ure and tourism activities, people may be motivated to balance their choice of tourism activi ties with their leisure activities (Festinger, 1957; Kelly, 1987). The relationship between leisur e habit and tourism behavior is also explained by Triandis’ (1977) theory, Bentler and S peckart’s (1979) model, and Verplanken, Aarts, and Knippenberg’s (1997) habit model that hy pothesize the influence of past behaviors on future behaviors. The relationship between leisure involvement and tourism behavior is accounted for by theories that assume the influence of beliefs or attitudes on behaviors and the relationship between tourism motivation and tourism behavior can be explained by the impact of attitudes on behaviors. In particular, the relation ship between tourism motivation and tourism behavior has received a lot of attention from resea rchers, and a significant relationship has been found (e.g., Crompton, 1979; Dann, 1981; Deci, 1975 ; Iso-Ahola, 1982, 1983; Pearce & Caltabiano, 1983; Yoon & Uysal, 2005). To help illustrate how this theoretical model can b e used to understand the relationship between leisure involvement, leisure habit, vacatio n/tourism motivation, and vacation/tourism behavior (Figure 1-1), the following scenario is pr oposed. As people get involved in running,

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23 people run everyday for exercise. This habit of run ning enhances involvement with running. In turn, running involvement reinforces habitual runni ng. People who habitually run and are highly involved in running during their leisure time narro w down their acceptable range of other leisure activities, and in turn reject taking part in other leisure activities (Sherif & Cantril, 1947; Iwasak i & Havitz, 2004). This narrow range of acceptable le isure activities (i.e., a strong attitude towards a specific leisure activity) is likely to encourage people to keep running even while on vacation (Wood, Tam, & Guerrero-Wit, 2005). Furthermore, sim ilar attributes between leisure and tourism encourage consistent running from a leisure setting to a tourism setting (Carr, 2002). People are likely to be motivated as a part of thei r vacations to maintain consistency of running or some people might take their interest in running one step further and use their vacations to take part in organized running events such as marat hons. They may also be more likely to participate in other active tourism pursuits such a s water sports, bicycling, golf, skiing, or adventure sports. Basically this study hypothesized that physically a ctive people are more likely to take part in their preferred leisure activity during their va cations, provided that they are highly involved in their leisure activity. Specifically, given that pe ople are physically active in their leisure, they a re more likely to be physically active in tourism sett ings when they travel. In brief, people who have an intense involvement with sports, physical a ctivities and active outdoor recreation during leisure have a higher probability of being active s port tourists. Purpose of Study The purposes of the study are to identify the types of leisure and vacation activities that physically active people take part in, to examine t he relationship between leisure involvement, leisure habit, vacation/tourism motivation, and vac ation/tourism behavior and to further establish

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24 a theoretical foundation for the connection between active leisure and vacation behaviors. More specifically, goals of this study were: 1. to identify the types of leisure and vacation activ ities that physically active people take part in, 2. to assess their involvement level in active leisure activities, 3. to evaluate the habit strength associated with thei r active leisure activities, 4. to examine their vacation/tourism motivation relate d to active leisure activities, 5. to investigate their vacation/tourism behaviors rel ated to active leisure activities, and 6. to test and obtain predictive validity of the relat ionship between leisure involvement, leisure habit, vacation/tourism motivation, and vac ation/tourism behavior through structural equation modeling. Research Questions For the purposes of the study, the following resear ch questions were examined: Research question 1a : what types of favorite leisure activities do phys ically active people take part in? Research question 1b : What are the participation patterns in the favori te leisure activities of the respondents? Research question 2a : What types of favorite vacation activities do the respondents participate in? Research question 2b : What are the vacation patterns of the respondents ? Research question 3a : Is there a similarity between the favorite leisur e and favorite vacation activities of the respondents? Research question 3b : What are the participation patterns in the favori te leisure activities of the respondents during vacations? Research question 4 : What are the levels of involvement in the favorit e leisure activities of the respondents? Research question 5 : What are the levels of habit associated with the favorite leisure activities of the respondents? Research question 6 : What are the levels of motivation associated with the favorite vacation activities of the respondents?

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25 Research question 7 : What are the patterns of vacation behavior relate d to the favorite vacation activities of the respondents? Hypotheses To examine the theoretical linkages among the const ructs, the following hypotheses were tested: Hypothesis 1 : Involvement with active leisure and habit associa ted with active leisure are correlated. Hypothesis 2 : Involvement with active leisure has a direct infl uence on vacation motivation. Hypothesis 3 : Habit associated with active leisure has a direct influence on vacation motivation. Hypothesis 4 : Involvement with active leisure has a direct and indirect influence on active vacation behavior. Hypothesis 5 : Habit associated with active leisure has a direct and indirect influence on active vacation behavior. Hypothesis 6 : Vacation motivation has a direct influence on act ive vacation behavior.

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26 Figure 1-1. Full model of the relationship between active leisure and active vacations H1 H2 H3 H4 H5 H6 Leisure involvement Leisure habit Vacation/ tourism motivation Vacation /tourism behavior

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27 CHAPTER 2 REVIEW OF LITERATURE Leisure and Tourism What Is Leisure? Over the centuries leisure has been described in ma ny different ways. For the Romans, leisure was free time away from work (De Grazia, 19 62), whereas leisure was described by Aristotle as an opposite to work, namely a non-work state in which labor never exists (Cooper, 1999). However, many researchers pointed out that t his simple distinction of work versus nonwork has not reflected the true characteristics of leisure. Thus, another way that has been used to describe leisure was as activity. Pieper (1952) and De Grazia (1962) defined leisure as an activity delimited to spiritual and cultural activity for co ntemplation and worship with a focus on the quality of activity. Developing this perspective, many leisure researche rs suggested that the primary factors associated with the quality of leisure activity are perceived freedom, intrinsic motivation, selfexpression, and self-development (Gunter, 1987; Gun ter & Gunter, 1980; Iso-Ahola 1979; Neulinger, 1981a, 1981b, 1982; Tinsley & Tinsley, 1 986). Csikszentmihalyi (1990) suggested that the quality of leisure activity is closely rel ated to enjoyment gained from optimal or flow experiences that occur when challenges and skills o f activity are balanced. However, leisure researchers realized that even if the aforementioned internal factors are critical to the quality of the leisure activity, th ese factors are interactively influenced by social structures such as social roles, social supports, a nd the pervasive constraints of available time and money to take part in leisure activities (Kelly 1987; Neulinger, 1981b; Samdahl, 1988, 1991). From this view, Kelly (1987) suggested leisu re is contextual and is influenced by

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28 existential and social factors. As such, leisure is described as “structured action with a core of self-determination” (Kelly, 1992, p253) and seems t o be embedded in everyday lifestyle. Where leisure is defined as an activity, and the ma in components to determine this activity are perceived freedom, self-expression, intrinsic m otivation, self-determination, and social structural factors, what types of activity constitu te leisure? Two approaches, objective and subjective leisure types have been discussed in the leisure l iterature (Neulinger, 1974). Objective leisure refers to activities occurring in physical leisure settings. As an illustration, objective leisure activities are golfing, playing tennis, wat ching a movie, or appreciating the arts in settings such as golf courses, tennis courts, theaters, or m useums. Subjective leisure refers to activities subjectively felt or perceived as leisure. Subjecti ve leisure activities could be all activities in which individuals feel the core internal factors of leisure such as perceived freedom, intrinsic motivations, or self-expression (Jafari, 2000). Some studies have strived for a better understandin g of leisure activities through a combination of objective and subjective perspective s. Tinsley and Kass (1978) identified ten leisure activities in which their respondents parti cipated (e.g., watching TV, reading books, attending concerts, jogging, playing tennis, bicycl ing, scuba diving and mountaineering, watching basketball, playing cards, and drinking an d socializing), and then investigated how these leisure activities were related to 45 interna l needs such as self-esteem, relaxation, achievement, social status, and so forth. They foun d that 33 of the 45 needs were significantly related to the activities, and they reported that p articularly several needs such as advancement, catharsis, reward, getting along with others, indep endence, activity, ability utilization, tolerance, and exhibition had the greatest discrimination amon g leisure activities. Likewise, Iso-Ahola (1979) asserted that when objective leisure activit ies are combined with intrinsic reasons, these

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29 activities can be defined as true leisure activitie s. In a similar vein, Shaw (1984) defined pure leisure as activities that are freely chosen and in trinsically motivated. Lounsbury and Hoopes (1988) compared the five-year stability of actual leisure activities and leisure motivational factors. They created five factors from among more than 100 leisure activities developed by McKechnie’s (1975) Leisure Activities Blank (LAB): easy leisure (e.g., driving, visiting friends, etc), sports/recreation (e.g., basketball, jogging/running, camping, etc), domestic activities (e.g., cooking, sewing), organi zational activities (e.g., civic organizations, public meetings, political activities), and intelle ctual activities (e.g., concerts, lectures). They also extracted six leisure motivational factors (i. e., supervising others, achievement, physical activity, social interaction, mental activity, and creativity/crafts) from leisure motivation items (Tinsley, Barrett, & Kass, 1977). They found that m ost actual leisure activities indicated stability across the five years, whereas leisure motivational factors revealed relatively lower stability. However, Lounsbury and Hoopes assumed that if peopl e had focused on the motivations associated with several preferred leisure activitie s, they could have gained greater stability. In summary, the major conclusion of the previous studi es is that even though objective leisure activities are varied, perceived freedom, self-expr ession, intrinsic motivation, and selfdetermination are likely to be mainly conceived of as the core entities of leisure irrespective of activity. What Is Tourism? To simply define tourism is very difficult because tourism is very complex, heterogeneous, and dynamic (Butler, 1999; Cohen, 1979). Cohen (197 4) described tourism using fuzzy set theory, which refers to a vague concept devoid of a clear boundary to define it. However, in general, tourism is related to visiting a specific place for vacations, having fun, and visiting family and friends, spending leisure time involved in various sports, relaxing, or touring, and for

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30 some researchers tourism includes business (Goeldne r & Ritchie, 2003). A technical definition of a tourist described by the National Travel Survey o f the Travel Industry Association of America (TIA) is one who travels away from home for a dista nce of 100 miles or more one-way, or who is involved in trips spending one or more nights re gardless of distance (Goeldner & Ritchie, 2003). Broadly, tourists have been classified into two types of traveler by their main purposes even if tourists have many specific reasons for tra vel (Leiper, 1979): leisure travelers and business travelers. In contrast to business travele rs, “leisure tourists are defined as people who travel for pleasure and thus, not under any obligat ions to frequent specific destinations or facilities, concentrating their touristic activitie s to specific times” (Jafari, 2000, p.356). However, some scholars have not agreed with includi ng any business or work related travelers in the definition of a tourist. In accord ance with this tradition, Cohen (1974) depicted a tourist as a person who is not in pursuit of work a nd is not traveling because of obligation or production. More specifically, tourists described b y Cohen have several key characteristics. Tourists should have a round trip in a limited time (temporary) and non-recurrent and noninstrumental purpose associated with their trips. N on-recurrent and non-instrumental characteristics are closely related to pleasurable and novel experiences sought by tourists. Cohen’s (1974) ultimate definition of tourists is “ a voluntary, temporary traveler, traveling in the expectation of pleasure from the novelty and change experienced on a relatively long and nonrecurrent round-trip” (p. 533). Supporting Cohen’s view that tourism is a form of l eisured activity, Smith (1977) defined a tourist as “a temporarily leisured person who volun tarily visits a place away from home for the purpose of experiencing a change” (p.1). Iso-Ahola (1983) also noted that recreational or leisure travelers are ones who travel to gain enjoyment or pleasure, and enjoy leisure activity within the

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31 context of leisure behaviors. Leisure travel descri bed by Iso-Ahola is characterized as intrinsically motivated activities, and self-expres sion reflecting needs for optimal experience. Supporting Cohen’s (1974) and Iso-Ahola’s (1983) pe rspective of leisure travel as non-work travel, Yiannakis and Gibson (1992) depicted touris ts as people who engage in touristic activity, for pleasure, without duty and instrumental payoffs Cohen (1974) postulated that there is more than one type of tourist. Using a continuum of novelty and familiarity he identified a typology co ntaining four different types of tourists or what he referred to as tourist roles (Cohen, 1972). He s uggested that people who seek the highest level of familiarity in tourism experiences were depicted as organized mass tourists, whereas people who seek the highest level of novel experience were portrayed as drifters who try to live the way that the residents live. Between these types of tou rist roles, Cohen suggested that individual mass tourists seek a higher level of familiarity and exp lorers seek a higher level of novelty in their tourism experience. Cohen’s (1972) typology is base d on tourists’ behavioral patterns, or what he terms tourist roles. Pearce (1982) developed Cohen’s work further by ide ntifying fifteen types of traveler role, which could be divided into five categories: enviro nmental traveler, high contact traveler, spiritual traveler, pleasure first traveler, and ex ploitative traveler. Developing Cohen and Pearce’s ideas, Yiannakis and Gibson (1992) suggest ed that one problem with Pearce’s work was the conceptual fuzziness in his definition of trave ler and tourists. Defining a tourist as leisure based travel (Cohen, 1972), Yiannakis and Gibson di stinguished fourteen leisure based tourist roles: sun lover, action seeker, anthropologist, ar chaeologist, organized mass tourist, thrill seeker, explorer, jetsetter, seeker, independent ma ss tourist, high class tourist, drifter, escapist, and sport lover. Furthermore, Yiannakis and Gibson investigated how each of the tourist roles

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32 was characterized by three dimensions of tourist ex perience/preference: simulation-tranquility, structure-independence, and familiarity-novelty. Gi bson and Yiannakis (2002) found in their later study that preference for each of these touri st roles was closely linked to an individual’s socio-psychological needs, both unsatisfied and sat isfied needs. What Is the Relationship between Leisure and Touris m? In the early days of work in the sociology and anth ropology of tourism, tourism was consistently viewed as a “special form of leisure” (Cohen, 1974). Mieczkowski (1981) demonstrated that recreation is included in the lei sure sphere because recreation is an experience that takes place during leisure time, and the natur e of most tourism is recreational. From this perspective, Butler (1999) suggested that “tourism is something which takes place during leisure time….because tourism also implies travel, and ther efore some activity on behalf of the tourist, then it is logically a part of leisure and recreati on” (p. 98). Nevertheless, in the introduction of the special is sue, Interrelationship of Leisure, Recreation, and Tourism of the Annals of Tourism Research Fedler (1987) pointed out that a common problem raised by the authors of the article s included in this special issue was that conceptual problems result in an obstacle to specif ying any theoretical relationship between leisure, recreation, and tourism, and result in an inadequate understanding of the association between the three domains. Fedler also pointed out that most authors in the special issue had commented that leisure and recreation have been res earched in one realm most commonly within the discipline of leisure studies, whilst tourism h as been studied in another realm within that of tourism studies, due to unknown reasons. Consequent ly, they had been isolated from each other, even though leisure, recreation and tourism share c ommon psychological and behavioral outcomes. From suggestions by all of the authors in this special issue, Fedler concluded that an integrative approach with a well established concep tual and theoretical relationship would

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33 benefit leisure, recreation and tourism. In this sp ecial issue, Mannell and Iso-Ahola (1987) presented psychological and experiential approaches to understand the relationship between leisure and tourism and Colton (1987) suggested soc ial meanings and roles shared by leisure, recreation and tourism from a symbolic interaction perspective. Hamilton-Smith (1987) identified two dimensional fields consisting of sub jective perception and objective environmental impacts to explain the relationship between leisure and tourism behaviors. Taking a geographical point of view, Jensen-Verbeke and Dietvorst (1987) emphasized the importance of spatial management to reflect an increasing need for integr ating leisure, recreation and tourism. From a management standpoint, Harris, McLaughlin and Ham ( 1987) also raised the issue of integrative environmental and resources management based on the commonality of leisure, recreation and tourism needs. More specifically, in their article, “Psychological Nature of Leisure and Tourism Experience” of the aforementioned special issue, Ma nnell and Iso-Ahola (1987) suggested that leisure refers to everyday activities embedded in p eople’s lives, and touristic activities are infrequent leisure episodes in people’s lives. They explained that both leisure and tourism behaviors are not only influenced by a distinction between work time and free time, but also common psychological and experiential characteristi cs. In particular, to explain the quality of experience influencing leisure and tourism activiti es, Mannell and Iso-Ahola referred to the previous literature describing that true leisure ex perience is related to freedom of choice, enjoyment, intrinsic motivation, self-determination self-development (Csikszentmihalyi, 1975; Kelly, 1983; Neulinger, 1974), and true tourism exp eriences are associated with authenticity and a quest for values and meanings (MacCannell, 1973; Meyersohn, 1981; Przeclawski, 1985). From this perspective, Mannell and Iso-Ahola pointe d out that previous studies had provided

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34 empirical evidence in which subjectively perceived reasons and experiences of leisure and vacations have been repeatedly categorized into sev eral similar need dimensions without variation and appear as equally important (Beard & Ragheb, 1983; Lounsbury & Hoopes, 1988; Tinsley et al, 1977; Tinsley & Kass, 1978), whereas non-experience-related factors such as demographics seemed not to be important determinant s of leisure and vacation experience and satisfaction. From a similar perspective as Mannell and Iso-Ahola (1987) but with more consideration of the socially perceived meanings through a symbol ic interactionist perspective, Colton (1987) demonstrated that leisure, recreation and tourism a re not objective activities but meanings, values and attitudes behind action, and these meanings are subjectively interpreted. Activities such as swimming, bicycling, hunting, fishing, hiking, snow skiing or camping are socially perceived as recreation activities and at the same time, tourism activities. According to Colton, this interpretation is learned from social interaction w ith social groups such as family and friends, and leisure, recreation, and tourism have socially shared meanings in terms of benefits, needs, and satisfaction. However, more detailed explanatio n related to symbolic interactionism of leisure, recreation and tourism remained for future work. To more systematically categorize the relationship between leisure and tourism behaviors, Hamilton-Smith (1987) identified two dimensional fi elds: subjective perception (i.e., existential) and objective environmental influences (i.e., struc tural). Certain types of tourism share subjective leisure attributes such as intrinsic mot ivations (Neulinger, 1981), perceived freedom (Kelly, 1983), flow (Csikszentmihalyi, 1975), perso nal competence and self-determination (Deci & Ryan, 1985), and stimulus-arousal (Ellis, 1973). Leisure and tourism behaviors also are influenced by time, space and social structure (e.g ., class and status). Consequently, four

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35 dimensions were identified from existential and str uctural features of leisure and tourism. As an illustration, individuals who are highly positive i n both existential and structural dimensions of leisure and tourism are deemed to be a serious leis ure participant and an authenticity-seeker in tourism. People who are highly positive in the exis tential domain but negative in the structural dimension seek pure leisure without an ultimate goa l, and travel to escape from routine. However, when individuals are negative in the exist ential domain and positive in the structural domain, they take part in leisure as if it is an oc cupation at the elite levels of competition, and choose extrinsically motivated and goal-directed tr avel such as winning the competition. This idea is similar to a combination of serious leisure (Stebbins, 1982) and tourist roles (Cohen, 1979). Likewise, Ryan (1994) argued that intrinsic motivat ions and enjoyment experiences conceptually overlap in leisure and tourism. Furthe rmore, he suggested that Beard and Ragheb’s (1983) Leisure Motivation Scale (LMS) derived from the hierarchical needs of Maslow (1970) could be applied to tourism motivations. The four m otivation factors in the LMS are: intellectual, social, competence-mastery and stimulus-avoidance Later, in a more specific study, Ryan and Glendon (1998) applied Beard and Ragheb’s Leisure M otivation Scale to study vacation behaviors and choices and then, subsequently found that the leisure motivations had a high degree of reliability and validity in a tourism con text. Currie (1997) developed the liminoidal, inversionar y, and prosaic (LIP) behavior framework underlying the impact of daily behaviors on tourism behaviors. Arguing that former work had tended to describe tourism behaviors as op posite activities of home-based activities, he emphasized that tourism behaviors may be rooted in daily activities. Burch’s (1969) familiarity concept and compensatory concept were reviewed for upholding his argument. On one hand,

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36 using the assumption of the familiarity concept, he postulated that particular activities that individuals enjoy in their daily life could be main tained or developed during vacation. Although individuals may have new experiences in a novel env ironment while on vacation, the experiences could be based on their daily routine activities. O n the other hand, the compensatory concept is related to unfamiliar behaviors. That is, some peop le consider vacation behaviors as an opportunity to avoid regular routine behaviors. Acc ording to Currie’s LIP behavior framework, familiarity-seeking behaviors could be connected to prosaic vacation behaviors in a liminoid space (Turner, 1969), whereas compensatory behavior s might relate to inversionary vacation behaviors. Even though both the familiarity and com pensatory-seeking behaviors might result in different patterns of vacation behaviors, Currie hi ghlighted that both the prosaic and inversionary behaviors are a reflection of individuals’ routine lifestyles. Similarly, Carr (2002) described how leisure and to urism can be consistently united on a continuum. Even though tourism behaviors might be m ore hedonic-oriented than leisure behaviors, some individuals retain the same values from their everyday life. Carr’s leisure and tourism continuum identifies three primary reasons for this consistency: subjective norms and attitudes, preference and personality, and deep-roo ted habits. First, as individuals are strongly influenced by their subjective norms and values, th ey exercise self-control so as to keep the same attitudes even in new environments. For example, so me people maintain a sexually conservative attitude in both home and vacation settings. Sub-cu ltural values may be another part of this consistency in subjective norms and values. Members hip of a specific subculture such as those associated with various sports may result in somewh at consistent behaviors between leisure and tourism contexts. Second, individual preference and personality may enhance the consistency between leisure and tourism behaviors. Some people prefer more secure and familiar settings and

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37 therefore they choose chain hotels and franchised r estaurants when they travel (Cohen, 1972; Ryan & Cave, 2005). Third, Carr (2002) explained th e parallel between leisure and tourism by deep-rooted habits. During vacation, habitual behav iors such as social skills or physical activity acquired from everyday life appear spontaneously in tourism contexts. In a more recent study, Brey and Lehto (2007) sugge sted that behavioral consistency between leisure and tourism could be explained by l eisure involvement. Pointing out that previous studies have stressed the importance of le isure and recreation in tourism product development (Chubb & Chubb, 1981; Clawson, Held, & Stoddart, 1960), Brey and Lehto suggested that leisure involvement plays a critical role in the decision making process for travel choices. To empirically investigate this suppositio n, they asked their study participants about the frequency of their daily recreation activities, and then, whether they took part in these same activities during their vacations. Their findings r evealed that golf, jogging, and biking among different leisure sport activities had the highest levels of participation frequency in both leisure and tourism contexts. Even though Brey and Lehto’s study can be critiqued for a lack of complexity in investigating the degree of involveme nt with leisure activities and how this translates to the tourism context, their study can be regarded as a good first step in investigating this relationship, particularly the apparently stro ng relationship between physical activity participation in both leisure and tourism contexts. Likewise, Henderson (2005a, 2005b) suggested that p hysical activities, leisure, recreation, and travel are interrelated, and might be explained by the psychological benefits gained from active and healthy lifestyles. Psychological benefi ts such as pleasurable experiences of physical activities in every day leisure life facilitate rec reational choices, which in turn, may encourage people to continue to be involved in travel associa ted with these activities as part of their overall

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38 lifestyles. This extension of enjoyable experiences from leisure to tourism is likely to contribute to increasing the overall quality of life (Godbey, et al., 2005; Ingham, 1990; Sallis, et al., 2005). Physically active leisure as a part of active lifes tyles seems to influence the number of people who engage in active vacations and sport-related to urism activities (Chon & Singh, 1995; Fluker & Turner, 2000; Redmond, 1991). Some researchers su ggest that leisure lifestyles could explain travel patterns more precisely than socio-demograph ics (Bieger & Laesser, 2004). Sung (2004) attempted to understand trip characteristics throug h leisure lifestyles including leisure involvement. Based on their lifestyles, Sung classi fied adventure travelers into six subgroups, general enthusiasts, budget youngsters, soft modera tes, upper high naturalists, family vacationers, and active soloists and found that the six subgroup s were different in travel decision-making styles, preferred travel activities, travel informa tion sources, travel expenditures, and types of preferred destinations. Hallab, Yoon, and Uysal (20 03) found a positive relationship between active and healthy living attitudes and active and healthy travel pursuits. In another study, Hallab and Gursoy (2006) found that positive attitudes tow ards exercise as an active and healthy leisure style encouraged people to seek more information on active forms of travel. Sport as Leisure and Tourism Seemingly, sports, physical activities and active o utdoor recreation appeal to people as both leisure and tourism activities. Walking, running, b icycling, swimming, playing tennis, and golf are popular as leisure activities as well as touris m activities (Brey & Lehto, 2007; De Knop, 1987; Tinsley & Tinsley, 1986). People are involved in these sports, physical activities and active outdoor recreation in either casual or serio us ways (Jones & Green, 2006). Indeed sports, physical activities and active outdoor recreation h ave often been linked to the concept of serious leisure. Stebbins (1982) postulated that serious le isure activities are characterized by six distinctive elements: perseverance, career, persona l effort to acquire knowledge, training or skill,

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39 durable benefits such as self-actualization or self -expression, self-identification, and a unique ethos (i.e., social worlds). As an illustration, to be immersed in bicycling, people should persevere through hardships, have long-term achieve ment with bicycling, attempt to acquire more knowledge and skills related to bicycling, gai n real enjoyment and self-actualization through bicycling, and have their self-identity tie d to bicycling. Furthermore, this commitment to cycling is enhanced further through social world me mbership (Unruh, 1979). In a study of recreational road runners, many of wh om also exemplify the characteristics of serious leisure, McGehee, Yoon and Cardenas (2003) investigated their participation in running and running-related tourism. In terms of behavioral patterns between different levels of involvement with recreational running, the high inv olvement group tended to have higher levels of participation in road races and tended to make m ore overnight trips than those with medium levels of involvement. McGehee et al’s study classi fies participation in road races as a form of active sport tourism and as such is part of the gro wing attention being given to sports-related travel or sport tourism. Then, what is sport tourism? The historical origins of sport tourism described by Standeven and De Knop (1999) were the ancient Olympic Games i n 776 B.C. (Finley & Pleket, 1976), followed by football tournaments and crossbow conte sts in Medieval times (500-1400 A. D), international tennis and archery tournaments viewed as intellectual activities in the Renaissance (1400-1600), and international sports exchange thro ugh the Grand Tour in the Pre-modern world (1600-1800). In the nineteenth and early twentieth centuries, sport tourism was increasingly influenced by industrialization. Under colonialism as one part of industrialization, European countries engaged in the so-called civilizing of th e native peoples of North America and beyond, and sport and tourism were used as a means of cultu ral diffusion. Moreover, technology

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40 advanced by industrialization improved transportati on, which resulted in more travel and encouraged sports participants and spectators to mo ve out of their home towns. As a result, particularly, skiing, climbing, football, tennis, c ycling, hiking, and baseball became popular in North America, activities with roots in the Europea n countries. However, it was not until the mid 1970s when travel industry analysts and a growing b ody of academics started writing about the potential of sport related tourism (Schreyer, 1976) As an initial academic endeavor, sport tourism was studied by a British scholar, Sue Glypt is (1982). She focused on the importance of active sport activities undertaken on vacation. She compared sport tourism participation patterns among tourists in six European countries (i.e., Fra nce, Germany, Sweden, Netherlands, Spain, and Britain). As her study was commissioned by the Sports Council of the United Kingdom, her goal was to examine better ways for sport tourism d evelopment in a benchmarking process. Overall, she found that participation in active for ms of recreation was increasing in the six countries, whereas passive leisure forms were in de cline. She also found that sport and physical recreation played a major part in tourism. Glyptis reported that more and more people in the six countries had taken part in nature and health sport s activities such as walking, cycling, swimming, and canoeing during vacation on account o f an increasing interest in the social and health benefits of sports rather than competition. Similarly, De Knop (1987, 1990) demonstrated that active sport tourism participation was replaci ng passive sport tourism participation as a new international trend. In turn, he suggested that the re was an increasing overlap between everyday leisure activity and vacation activities. As such, the early focus of both academics and providers of sport tourism tended to be on active sport touri sm, especially in the European context. However in contrast, in the 1980s North America’s s port tourism studies still put more focus on mega event based sport tourism (Ritchie, 1 984), even though there was some attention

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41 on outdoor adventure recreation as a form of sport tourism at the end of 1980s (Ewert, 1987). To recover from the worst economic situation resulting from the world recession of the early 1980s, local communities attempted to expand their interes t into new service industries (Roche, 1992, 1994), and their choice to achieve this goal was me ga and hall mark sports events as the accompanying media promotion was thought to attract more international tourists as well as domestic tourists into their communities. Therefore the overall trend of North America sport tourism studies in the 1980s tended to focus more o n event sport tourism, particularly the large scale rather than the small scale sport events, wit h an emphasis on passive sport tourism (e.g., spectators or sport fans) rather than active sport tourism (i.e., travel to take part in sports). Furthermore, economic and social impacts as perceiv ed by the residents were the specific focus of these studies as opposed to social, cultural, an d health benefits perceived by both residents and tourists. Despite the different foci between European and Nor th American academics, on both continents there was a tendency to regard sport and tourism as separate areas even though they recognized that sport and tourism are interrelated. Glyptis’ (1991) notion that “sport and tourism tend to be treated by academic and practitioner ali ke as separate spheres of activity. Each has its own journals, academic departments, learned societi es, and government agencies” (p.165) reflected this tendency. Tourism-relevant organizat ions merely treated mega sporting events as a way to attract more visitors, and sports organizati ons limited their efforts to sport spectators and sporting events within the stadium rather than coop erating with the tourism-related agencies in their communities. In the mid 1990s, however, sport tourism as an acad emic endeavor began to develop (Gibson, 1998a, 1998b). Many of the early writings were devoted to defining sport tourism.

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42 Sport tourism was generally defined as sport-relate d activities that involved traveling away from home to participate (Gibson, 1998a, 1998b; Hall, 19 92; Hinch & Higham, 2001; Nogawa, et al., 1996; Standeven & DeKnop, 1999; Weed & Bull, 1997). For more specific definitional approaches to sport tourism, Hall (1992) distinguis hed between adventure tourism, sport tourism, and health tourism. Adventure tourism is defined as outdoor touristic activities, often performed in the natural environment away from home with some level of risk, whereas sport tourism is defined as travel to participate in or attend sport s with non-commercial motives. Health tourism is described as travel away from home with health a s the most important motive. The types of adventure, sport, and health were classified as hav ing active and competitive dimensions. Health tourism tends to be viewed in terms of non-competit ive motives, sport tourism in terms of competitive motives, and adventure tourism in the m iddle between non-competitive and competitive. As less active tourism, spa-relevant h ealth tourism, yacht adventure tourism, and spectating sport tourism were given as examples. As examples of more active tourism, scuba diving, climbing adventure tourism, and ocean racin g sport tourism were included. However, this distinction has a limitation in that except for sev eral activities at the extreme ends of a continuum, most motives and activities in adventure sport, and health tourism tend to overlap. Kurtzman and Zauhar (1995) defined sport tourism as the use of sport for touristic endeavors. Seemingly, this definitional approach pu t more weight on tourism rather than an integrative perspective of sport and tourism. Disti nct from the 1980s, they classified various types of sport tourism activities: sport tourism ev ents (e.g., the Olympic games, regional/national/international sport games, champi onships, scheduled league games professional and amateur teams, friendship games, etc), sport to urism tours (e.g., professional sport games tour, sport adventure tour, game safaris, cycling/c limbing tours, etc), sport tourism cruises (e.g.,

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43 sport celebrity cruises, sailing, scuba cruises, fi shing, canoeing, etc), sport tourism resorts (e.g., golf resorts, fitness and spa resorts, camping, etc ) and sport tourism attractions (e.g., sport museums, sport theme parks, bungee jumping, stadium s, etc). Their classification was very much based on the attributes of each type of sport touri sm as an attraction. In contrast, Nogawa, et al. (1996) defined sport to urists as visitors who spend at least 24 hours away from home, taking part in a sport event as a primary reason and visiting other attractions as their secondary reason. This definit ion is based on motivations and is notable as it is one of the first to address the issue of primary and secondary motivations in sport and tourism. This study is also notable in that it is the first sport tourism study to distinguish between excursionists (i.e., day trippers) and tourists in the sport tourism realm. However, their definition is more oriented to the event based sports and it s eems insufficient to embrace recreational activities or outdoor based sport tourists. Gammon and Robinson (1997) attempted to provide a m ore integrative definition of sport tourism. They described sport tourists as individua ls or groups taking part in competitive or recreational sport in either active or passive ways in the vacation environment away from their routine life. Gammon and Robinson also distinguishe d sport as a primary motivation (i.e., sport tourism) from tourism as primary motivation (i.e., tourism sport). Their approach was more comprehensive than previous definitions as it encom passed individual and group, active and passive, and primary and secondary motivations. The y also addressed the issue of competition as related to sport tourism. They used the term hard s port tourism to describe sport tourists who participate in competitive events, and soft sport t ourists are those who participate in recreational sporting activities. Furthermore, they describe har d tourism sport as those sport tourists for whom sport is a secondary motivation for their trip but are still competitive, whereas soft

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44 tourism sport is related to visitors who may dabble in recreational sport while on vacation. Despite their endeavor to develop a more specific d efinition, the distinction between soft sport tourism and hard tourism sport is not likely to be evident. Even though they noted that this distinction is important in consumer segmentation a nd services, it is questionable if clearly distinct services can be provided between soft spor t tourism and hard tourism sport. Gibson (1998b) defined sport tourism as “leisure-ba sed travel that is temporarily away from home to participate in physical activities, to observe physical activities and to visit physical activities-relevant attractions” (p.49). Specifical ly, she defined sport tourist as three types: 1) active sport tourists who travel to take part in sp ort, 2) event sport tourists who travel to watch sport, and 3) taking a lead from Redmond’s (1991) w ork, nostalgia sport tourists who visit sport tourism attractions such as halls of fame, famous s tadia, or sport-themed cruises. According to Standeven and DeKnop (1999), sport tou rism is delineated as travel for noncommercial, holiday and commercial, non-holiday or business reasons to take part in or observe sporting activities. Furthermore, they suggested th at there should be passive and active sport tourism under a distinction of holiday and non-holi day. For example, holiday active sport tourism consists of holiday sport activities and sp ort activity holiday (i.e., holiday sport activitie s is travel where sport is secondary, whereas sport a ctivity holiday is travel in which sport is a main motivation of the trip), and holiday passive s port tourism comprises casual observer and connoisseur (i.e., connoisseur observers are those who regularly watch sports and are avid fans, whereas casual observers are those who enjoy attend ing an event incidentally). However, they did not provide any specific forms of passive and a ctive sport tourism under non-holiday. However, by including commercial reasons, non-holid ay, their definition distinguished it from previous definitions.

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45 Hinch and Higham (2001) defined sport tourism as “s port-based travel away from the home environment for a limited time, where sport is char acterized by unique rule sets, competition related to physical prowess, and a playful nature”( p. 49). They identified three dimensions of sport tourism: the sport activity dimension, the te mporal dimension, and the spatial dimension. The sport activity dimension entails the rule struc ture, physical competition, and playfulness. The temporal dimension consists of duration, season ality, and evolution. The spatial dimension comprises location, regions, and landscape. This fr amework seems to be valuable for researchers as it enables them in comparing different levels of competition by specified temporal and spatial factors, or different spatial and temporal dimensio ns for elite or recreational sport tourists. Deery, Jago, and Fredline (2004) criticized Gammon and Robinson’s (1997) definition of sport tourism as too broad. They argued that the ke y distinguishing characteristic of sport tourism is the level of competitiveness associated with a sport event. They postulated that if a sport is non-competitive, it should be regarded as recreational or leisure tourism rather than sport tourism. Additionally they concluded that sport tou rism and sport event tourism are synonymous and they discounted the existence of any other type of sport tourism. However, their arguments are also ambiguous in several perspectives. Firstly suppose that we identify sport tourism as other than that associated with events distinguishe d solely by level of competition, are individuals’ primary motivations to participate in an event always about competition? Other studies suggest that the primary motivations for ta king part in event sport tourism may also entail socializing, exercise or pure enjoyment in which ca se are these tourists recreational tourists or sport tourists? In many respects, by defining sport tourism solely in terms of competitive sport events is very narrow and as such only encompasses a small segment of the overall sport tourist population. Certainly the early writings by Glyptis (1982) and DeKnop (1991) provided

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46 sufficient evidence to suggest that numerous sport tourism forms involving minimal levels of competition exist. Hall (1992) and Hinch and Higham (2001) would also support this position. Moreover, Robinson and Gammon’s (2004) argument tha t sport tourism encompasses both primary and secondary motivations seems to be impor tant, in that “the secondary motives had an enriching affect upon the primary ones…therefore, s econdary motives should not be perceived as inferior or second rate, but rather as sources of e nrichment to the primary ones” (pp. 224-225). This perspective is likely to be supported by Gibso n’s (2004) notion that people have multiple roles rather than one single tourist role while on vacation. Sport tourism research in the 1990s and 2000s has b ecome more diverse in its research foci. Research on the mega events has continued (e.g., Gr atton, Shibli, & Coleman, 2005), however, there has been growing attention on recreational fo rms of active sport tourism such as bicycling and adventure tourism as well as on active sport to urists who take part in small scale sport events. Ritchie (1998) studied bicycling tourism as active sport tourism. In his study, the types of bicycling tourists consisted of hard-core recreatio nal cyclists, enthusiasts on one end of a continuum and soft-core bicycle tourists, occasional riders on the opposite. The main motivation of enthusiasts is cycling itself, whereas for occas ional riders, cycling is one enjoyable mode of transportation among various alternatives when tour ing destinations. This continuum is very similar to leisure specialization (Bryan, 1977), be havioral loyalty (Iwasaki & Havitz, 2004), and serious leisure (Stebbins, 1982) that have mainly b een used in leisure studies. From Ritchie’s notion that “bicycling is perceived by tourists as an integral part of vacation and as a positive way of enhancing leisure time” (Ritchie, 1998, p. 5 68), we can infer that active sport tourists have some behavioral connection between their leisu re activities and tourism activities.

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47 As a form of active sport tourism, Pomfret (2006) g enerated a conceptual framework of mountaineering adventure tourists. In his conceptua l framework of adventure tourism, push and pull motivational factors, personality, and lifesty les may influence participation in adventure tourism, and all those factors affect the cognitive and emotional experience during adventure activities. This experience is in turn combined wit h motivations, personality, and lifestyles in the decision making process associated with future part icipation. In another form of active sport tourism, focusing o n small-scale sport events, Ryan and Lockyer (2002) investigated how importantly partici pants perceive Master’s Games-relevant elements and how they were satisfied with the event Indeed, Trauer, et al. (2003) dimensionalized sport tourists who participated in the 2000 and 2002 South Pacific Masters’ Games held in New Zealand into four types based on the degree of social-sport orientation and the degree of competence involvement. High competen ce involvement and high sport orientation were found to be associated with the serious compet itor group, while low competence involvement and high social orientation were relate d to the novice/dabbler group. In fact, the current pattern of active sport touris m studies is likely to concentrate more on internal factors of those tourists (e.g., motivatio ns and involvement) (Gibson, 2004). Moreover, as shown in the examples such as hard and soft comp etitive groups or individuals whose primary motivation is sport (i.e., sport tourist) versus pr imary motivation is tourism (i.e., tourism sportists) (Gammon & Robinson, 1997), or sport-soci al oriented groups (Trauer, et al., 2003), and a variety of types segmented by temporal, spati al, and activity (Hinch & Higham, 2001), active sport tourism is diverse in its types.

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48 Involvement Theoretical Foundation in Social Psychology Several researchers have suggested leisure involvem ent as an important variable to better understand individuals’ participation in active spo rt tourism, especially in the connection of leisure to tourism (e.g., McGehee et al., 2003; Tra uer et al., 2003). The study of involvement originated from social judgment theory formulated b y Sherif and Cantril (1947). Social judgment theory explains how an individual’s perception infl uences the judgmental process and why the individual who is greatly involved in a certain obj ect tends to look for same or similar ones to the object with which they are involved. According to s ocial judgment theory, an individual’s existing attitudes refer to lenses through which to judge a newly incoming message. These attitudes interpret meanings of the message and fur ther judge the information. People have different positions toward this incoming informatio n in this regard. Social judgment theory posited that a variety of positions are categorized into three ranges: the latitude of acceptance, the latitude of rejection and, the latitude of non-comm itment. Many positions within agreement (e.g., from slightly agree to strongly agree ) are included in the range of acceptance, and diff erent levels of disagreement likewise range in the latitu de of rejection. However some people have a neutral position considering neither agreement nor disagreement, which is in the latitude of noncommitment. In the persuasion process, people who h ave acceptable and non-committal attitudes toward the message are more easily persuaded but in dividuals with attitudes in the range of rejection are hard to change. The larger latitude o f acceptance, the easier it is to change attitudes. Specifically, if an individual has a wider range of acceptance, he/she has a narrower range of rejection and more room to change their existing at titudes (Sherif, Sherif, & Nebergall, 1965). A crucial determinant that influences this larger l atitude of rejection whereby attitudes resist change is ego involvement (Sherif & Cantril, 1947; Sherif & Hovland, 1961). Ego-

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49 involvement is a structure in which individuals pro ject their self-concept to objects, and further affirm the value of self through such objects (Sher if & Cantril, 1947). When a given issue is very critical to the self-identity of an individual, it is assumed that he/she becomes ego-involved in the issue and takes an extreme position (the so-called anchor position) on that issue. High ego involvement is associated with a narrow latitude of acceptance (Sherif, et al., 1965). When becoming immersed in an issue, people use fewer cat egories, instead of a diversity of positions, in developing their attitudes toward the issue (She rif & Hovland, 1961). This narrow range of viewpoints toward a highly involving issue could ma ke the interpretation of incoming information biased because if the message issue is closer to the anchor position within the latitude of acceptance, people perceive this messag e as more akin to their position and judge it as more acceptable. Existing attitudes in this highly involved position strive to maintain consistent by assimilating or contrasting a given issue (Sheri f et al., 1965). Sherif, Kelly, Rodgers, Sarup, and Tittler (1973) further suggested that when atti tudes of individuals are more ego-involved, their future behaviors are better predicted. Johnson and Eagly (1989) paid more attention to the relationship between involvement and persuasion (i.e., attitude change). They defined in volvement as “a motivational state induced by an association between self-concept and an activate d attitude” (p.290). A highly involving issue would generate less attitude change, which leads to selective perception to maintain consistency with it and minimizes the impact from external sour ces (Johnson & Eagly, 1989). However, Johnson and Eagly argued that social judgment theor y did not cover different types of involvement in its formulation, and three different types of involvement might have different impacts on attitude change (persuasion): value-rele vant involvement, outcome-relevant involvement, and self-impression-relevant involveme nt. Value-relevant involvement is identical

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50 with ego-involvement mentioned in social judgment t heory, whereas outcome-relevant involvement refers to the involvement on the specif ic consequence that an individual wants to acquire, and self-impression-relevant involvement r elates to involvement with the impression that an individual wants to show to others. They fo und that value and impression involvement revealed a similar pattern to the traditional assum ptions of social judgment theory such that high involvement results in a wider range of rejection a nd less persuasion, but the relationship between outcome-relevant involvement and persuasion is unstable in relation to the quality of the argument (i.e., the strength of argument). Against this finding, Petty and Cacioppo (1990) arg ued that value and outcome-relevant involvement should be regarded as one type of invol vement termed issue involvement because both are not clearly distinguished from each other and not separately measured in the persuasion process. They argued that issue involvement encompa sses all issues associated with personal importance regardless of more abstract values (e.g. freedom) or more concrete goals (e.g., obtaining an education) and it is not necessary for involvement to be overspecified. That is, an issue in which an individual is highly involved is an intrinsically important and personally meaningful issue (Petty & Cacioppo, 1996). However these specified types of involvement and their measurement in social judgment theory are sti ll arguable. In particular, how much different kinds of involvement will be influenced by the cont ent of a message such as the strength or credibility of the argument and how accurately thes e involvements are measured have been the crux of the matter in these debates. Nonetheless, t hese arguments stand on the assertion that all of these involvements are related to self-perceptio n. Two ways to measure these involvements have mainly been used in social psychology. One way is to distinguish members from nonmembers of a group to see the difference between th e high-involvement group and the low-

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51 involvement group (Sherif & Hovland, 1961), and the other way is to classify the participants by self-reported rate on the level of involvement in a given issue (Powell, 1977). Consumer Involvement To predict future behaviors, marketing studies star ted having an interest in the involvement concept because it was posited that ego involvement that stimulates a narrow latitude of acceptance and reinforces resistance to attitude ch ange is more likely to lead to consistency of behavior (e.g., Day, 1970; Havitz & Dimanche, 1990) Specifically, in consumer behavior research, ego involvement has been used to predict the buying behavior of consumers (e.g., Bloch, 1981; Mitchell, 1979; Robertson, 1976; Roths child, 1984). However, conceptual and operational definitions of involvement in consumer behaviors have varied by different studies. For example, interest (Day, 1970), belief strength (Robertson, 1976), the internal state including arousal and interest (Mitchell, 1979), and the perc eived importance of values (Lastovicka, 1979) were used as the terms to conceptualize consumer in volvement in the 1970s. Further Houston and Rothschild (1978) even classified involvement i nto situational concern, consistent behavioral concern, and decision making concern. In the 1980s, definitions of involvement became mor e specific to deal with the more complex aspects related to consumption of products or brands. A general pattern of approaches to involvement was developed to further classify th is construct. Internal (i.e., personal value), external (i.e., influences from objects), and situa tional involvement (Bloch & Richins, 1983), enduring involvement such as self, pleasure and lei sure activity and situational involvement such as products or brands (Bloch & Bruce, 1984; Richins & Bloch, 1986), and mental and behavioral involvement (Stone, 1984) were attempts to account for different elements included in involvement. Furthermore, emotional attachment (Blo ch, 1981) or affective response (Manfredo,

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52 1989) were included in involvement definitions in a ddition to interest and arousal. Appendix A presents different definitions of involvement. In the mid 1980s, several scales to measure involve ment were developed. The unidimensional semantic scale, Personal Involvement Inventory (PII) developed by Zaichkowsky (1985) and the multidimensional Likert scale, Consu mer Involvement Profile (CIP) developed by Laurent and Kapferer (1985) are the representative scales that have been used to measure responses. Zaichkowsky’s PII provided the 20 adject ive pairs such as “essential,” “desirable,” “important,” “interesting,” “relevant,” “useful,” “ valuable” to measure unidimensional involvement. On the other hand, Laurent and Kapfere r’s IP scales provided five multifaceted domains of involvement: 1) the importance of the pr oduct perceived by the consumer, 2) the sign-value related to the product identified with g roup standards, 3) continuous interest, 4) a perceived risk related to the likelihood for a misp urchase and the negative consequences occurring from a mispurchase, and 5) emotional valu es such as pleasure. Later, Assael (1998) categorized importance, interest, and emotional val ues into enduring involvement, and risks and sign values into situational involvement. Particula rly, Beatty, Kahle, and Homer (1988) noted that situational involvement is influenced by envir onments, prices, services, or alternatives. Many researchers in the consumer behavior studies h ave applied Zaichkowsky’s (1985) PII and Laurent and Kapferer’s (1985) IP to measure pro duct involvement and purchase involvement. For example, Warrington and Shim (2000) used eight items adapted from the PII scale to measure product involvement. However, their product involvement consists of situational involvement toward the use of a product in a specif ic situation and enduring involvement toward the relationship of the product to people’s central values over the buying situation. The items were measured on a 7-point semantic differential sc ale such as “ unimportant (1) to important

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53 (7),” “ no concern (1) to concern (7),” and “ unappealing (1) to appealing (7).” Using the IP scale, Quester and Lim (2003) employed 16 items consisting of hedonic value, importance, risk probability, risk consequences, and sign value dime nsions to measure the product involvement and the purchase involvement on the basis of a 5 po int-Likert scale where 1 = totally disagree and 5 = totally agree Leisure Involvement The approach to involvement in the field of leisure studies has been similar to that of consumer behavior although the major difference is that in leisure studies, more focus has been put on enduring involvement in ego-valued activitie s. Many leisure researchers have viewed the idea of involvement as one of the most important fa ctors in determining the quality of leisure experience in terms of long-term participation, eve n though a range of terms and similar concepts such as flow, specialization, commitment, serious leisure, and loyalty have been used (Backman & Crompton, 1989, 1991; Bryan, 1979; Bucha nan, 1985; Csikszentmihalyi, 1975; Mannell & Iso-Ahola, 1987; Neulinger, 1974; Stebbin s, 1982; Warnick & Howard, 1985). The concept of specialization developed by Bryan (1 979) is considered an original framework from which to observe involvement with le isure activities. Bryan noted that a specialized process from general to particular leis ure participation could be described by the extent to which people are involved in or committed to a particular leisure activity and its associated leisure social groups. The suggested met hod of measuring this degree of involvement or commitment was to examine equipment ownership, s kills used in leisure activity, and preference for particular leisure settings. Wellman Roggenbuck, and Smith (1982) in their study of seriousness of canoeists in canoeing adapted the concept of specialization and measurement suggested by Bryan (1977) to include past experienc es and current participation in river canoeing, equipment ownership, social interaction w ith other canoeists through organizations,

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54 purchase of magazines or books, participation in ka yak building and formal canoeing instruction, and the perceived role as a canoeist in their life. Focusing more on the product and equipmentoriented leisure involvement, Bloch and Bruce (1984 ) used a sample consisting of members of local sports car clubs and customers of fashion clo thing boutiques. They examined involvement with products (i.e., automobiles and clothing) and satisfaction, and found a positive relationship between involvement and satisfaction. However, pointing out that Bryan (1977) had merely concentrated on behavioral aspects with the purpose of observing the degree of involve ment or specialization in a leisure activity, many researchers (Buchanan, 1985; Schreyer & Beauli eu, 1986; McIntyre, 1989) suggested that psychological aspects along with behavioral compone nts should be studied. Leisure commitment is a concept that has been used to understand psych ological components of leisure specialization (Buchanan, 1985). Leisure specialization was consid ered to be an observable manifestation of leisure commitment. Furthermore, Buchanan attempted to comprehensively associate the concept of commitment with existing leisure theories such a s leisure conflict (Kanter, 1968), leisure social worlds (Bryan, 1977; Unruh, 1979), leisure s ubstitution (Vaske, 1980), and serious leisure (Stebbins, 1982), as well as leisure specialization (Bryan, 1977). Buchanan regarded commitment as a concept similar to involvement, loy alty, dedication, and attachment, however, he felt that if the concept of commitment was opera tionalized appropriately, this might contribute to the higher predictability of leisure behavior. T o describe leisure commitment, Buchanan used Becker’s (1960) side bet concept (i.e., investment such as financial or extended activities derived from the main bet or activity) and Kiesler’s (1968) commitment definition as a binding to behavioral acts. Leisure commitment was defined as a binding of an individual to a specific leisure behavior producing emotional attachment, re levant roles and behaviors, and benefits. It

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55 was further suggested that the three major componen ts of leisure commitment are a rejection of alternative behaviors due to a focused behavior, a function of side bets, and some affective attachment to the goals and values of a role, an ac tivity or an organization. He noted that the amount of past experience, the centrality of partic ipation to lifestyle and the degree of investment could be used to measure this leisure commitment. Similarly, Schreyer and Beaulieu (1986) endeavored to connect the concept of commitment to specialization. They examined the relationship b etween recreational activity commitment (i.e., the relative importance compared to other recreatio nal activities) and the choice of certain environments (i.e., specialization operationalized by behavioral frequency consisting of participation history in wilderness recreation, the average number of trips made per year, and the number of different wilderness areas visited). Howe ver, they did not clearly account for why they studied the relationship between activity comm itment and destination specialization instead of activity specialization. It seems to be importan t to distinguish between activity and destination because individuals could consistently visit one pl ace instead of different wilderness areas despite participating in wilderness recreation for a long time. In addition, there was no apparent explanation as to why relative importance was regar ded as commitment, whereas the history of different destination choices is deemed specializat ion. Buchanan (1985) strived to associate the concept of commitment with specialization in more sociological terms, whereas McIntyre (1989) su ggested the concept of enduring involvement should be linked to specialization from a more psychological perspective. McIntyre specified the concept of involvement in a leisure e xperience-oriented way. He described enduring involvement as a central role of leisure a ctivity in an individual’s personal life. McIntyre (1989) suggested the leisure involvement s cale adapted from involvement items

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56 developed by Arora (1982), Bloch and Bruce (1984), and Laurent and Kapferer (1985) in consumer research. Distinct from consumer involveme nt, McIntyre’s leisure involvement scale consisted of centrality, attraction, and self-expre ssion dimensions with the removal of the risk dimension. McIntyre suggested that the risk factor should be included in situational involvement that it is irrelevant to leisure experiences. His s tudy found that campers who used three different types of camp site revealed different levels of cen trality, whereas they were not significantly different in attraction and self-expression. McInty re and Pigram (1992) took a more multidimensional approach (i.e., behavioral, affective, and cognitive), combining Little’s (1976) specialization loop with three factors (i.e., centr ality, attraction, self-expression) of leisure involvement. They examined past experience in the b ehavioral aspect, enduring involvement (i.e., centrality, attraction, self-expression) in the aff ective aspect, and familiarity in the cognitive aspect to compare four groups of specialized camper s. This multidimensional approach seems to be more suitable for understanding different types of leisure activity that cannot be exactly examined by Bryan’s (1979) behavioral approach. For example, the need of higher level skills or equipment purchase varies across the types of activ ities. Indeed, Bloch, Black, and Lichtenstein (1989) found that involvement with equipment (i.e., running shoes) purchase was not significantly related to psychological components ( i.e., importance and favorability) toward running. McIntyre (1989) focused more on enduring involvemen t in the leisure and recreation contexts, whereas Havitz and Dimanche (1990) took p urchase-related situational components such as risk probability and risk consequences into consideration in the tourism context. The inclusion of the risk factor in the tourism context seems to be reasonable due to more impact of financial and time risks and more influence of prom otion and advertising on the travel decision

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57 making. Similarly, other tourism studies included t he risk dimension in the tourism settings (Gursoy, & Gavcar, 2003; Jamrozy, Backman, & Backma n, 1996). However, the levels of spending time and money vary across the types of tourism activities, although certain risks associated with purchasing g oods exist. Madrigal, Havitz and Howard’s (1992) study shows an example that different types of leisure and tourism activity may have different levels of risk. They assumed that purchas e involvement would entail risk facets because family vacations need a high-involvement purchase d ecision, but the risk dimension was found not to be closely related to other dimensions of in volvement. There were several possible reasons why the risk facet had low communality with the oth er involvement dimensions. One reason was small sample size and the other reason was that the difference between the family vacation purchase process and general product purchase proce ss may lead to low communality (Madrigal et al., 1992). The risk items associated with purch asing might not reflect this family experience aspect. Risks associated with family-related vacati on experiences rather than risks associated with purchasing a product would be better examined separately, leading to a higher communality. Another possible reason unexplained by Madrigal et al. (1992) is that pleasure, importance, and sign-related items were more relevant to family vac ation experiences, whereas risk-related items were related to the family vacation destination cho ice, even though a destination is confined to a place, but experiences encompass all activities, pl aces, and people. However, differing from Madrigal et al., Havitz and his colleagues (Havitz, Dimanche, & Howard, 1993; Havitz, Green, & McCarville, 1993) applied the CIP scale including the risk domain (Laurent & Kapferer, 1985) to different leisure, recreation, and tourism activ ities and demonstrated they obtained acceptable reliability and validity.

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58 Kim et al. (1997) also adapted the CIP scale includ ing the risk facets to examine the relationship between involvement and commitment wit h bird watching. However, they considered that the involvement construct consists of importance-pleasure, risk, and sign, while centrality is included in the commitment construct. Kim et al. concluded that centrality would be a more appropriate indicator to examine commitment after they reviewed Johnson’s (1973) commitment concept that consists of personal and be havioral (i.e., behavioral commitment comprised of social and cost commitment) persistenc e. Perceived risk was found to be negatively related to other involvement dimensions (i.e., impo rtance-pleasure and sign). This finding verified Havitz and Dimanche’s (1999) assumption th at participants who are relatively less involved in an activity might perceive higher risks than people who are more highly involved in an activity (Havitz, Dimanche, & Bogle, 1994). Several leisure researchers have also been interest ed in distinguishing involvement from commitment. Bloch, et al. (1989) examined the relat ionship between recreational commitment and involvement with equipment. Recreational commit ment was considered psychological (i.e. the importance of running, favorite activity, and t ime spent thinking about it), behavioral (i.e. the number of races participated in, the number of runn ing magazines read, the mile run per week), and experience (i.e. years of experience as a runne r). Equipment involvement was operationalized as perceived importance and knowled ge (i.e. familiarity) and outcome of equipment involvement, as spending levels and opini on leadership (i.e., equipment-related discussions and information). Multidimensional cons tructs of both involvement and commitment were confirmed but several factors between two cons tructs did not have a significant relationship. For example, psychological commitment to running had a positive effect on the perceived importance of running equipment involveme nt, whereas behavioral commitment was

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59 not significantly associated with the perceived imp ortance factor of equipment involvement, but had a significant relationship with the knowledge d imension in equipment involvement. However, the distinction between commitment and inv olvement in their study is not clear. Both commitment and involvement were considered to have the same meaning as each other (i.e., perceived importance), but were applied to activity and equipment, respectively. If their meanings are not much different from each other, it is ambiguous why they used the commitment term for activity and the involvement term for equi pment. In contrast to Bloch et al. (1989), Siegenthaler and Lam (1992) attempted to discrimina te between commitment and involvement toward the same object (i.e., recreational tennis). They hypothesized that commitment in tennis is indicated by continuance, sacrifice, and dedication and ego-involvement in tennis is indicated by self-image, interest, enjoyment, centrality, and im portance. However, these hypotheses were rejected even if another hypothesis that both const ructs would be correlated was accepted. Furthermore, beyond the distinction between involve ment and commitment, some researchers also distinguished loyalty from those o f involvement and commitment. As part of this phase of involvement research, Gahwiler and Ha vitz (1998) examined social worlds, leisure involvement (i.e., attraction, sign, risk probabili ty, risk consequence, centrality), psychological commitment (i.e., cognitive complexity, resistance to change, volition, position involvement) and behavioral loyalty (i.e., frequency, spending time) of YMCA members. Particularly, this study supported the utility of Bryan’s (1979) idea about specialized members of leisure social worlds using Unruh’s (1979) social worlds categories. They found that members of deeply engaged social subworld groups were not only more highly in volved in leisure activities but also more psychologically committed and behaviorally loyal to the service provider, in this case the YMCA. In a similar study, Iwasaki and Havitz (1998, 2004) found the influence of leisure

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60 involvement (i.e., attraction, sign, centrality, an d risk) of fitness participants on psychological commitment (i.e., informational complexity, volitio nal choice, and position involvement) and behavioral loyalty to a recreation agency was signi ficant. But risk probability had a negative correlation with the other involvement factors, rec onfirming their assumption that those who are highly involved are less concerned about their poor choice. In the first decade of the 21st century, several researchers started focusing on i nvolvement combined with contextual constructs such as place a ttachment (Bricker & Kerstetter, 2000; Kyle, Graefe, Manning, & Bacon, 2004a; Kyle & Mowen, 2005 ). Most of these studies did not take the risk dimension into consideration and tended to use McIntyre’s (1989) involvement dimensions. Kyle and Mowen (2005) assumed that leisure involvem ent (i.e., attraction, centrality, selfexpression) would influence commitment (i.e., place dependence and identity, affective attachment, value congruence, and social bonding) t o a public leisure service provider in Cleveland Metroparks settings and this assumption w as partially supported. Later, questioning the validity of the involvement factors, however, K yle, Absher, Norman, Hammitt, and Jodice (2007) tested five involvement factors, creating so cial bonding, identity-expression and identityaffirmation factors along with attraction and centr ality. They found that a correlated factors model was the best fit model as compared to a singl e factor model, an uncorrelated factors model and a hierarchical model. The researchers found tha t the identity-related items have some variability between two different settings. However, this study did not explain the theoretical and conceptual differences between identity-expression and identity-affirmation. If id entity-affirmation means self-affirmation theory (Steel, 1988), the given items do not seem to refle ct this theory, adequately. According to selfaffirmation theory, people cannot be troubled by in consistency provided they can affirm their

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61 larger identity in a way irrelevant to the concerne d problem. For example, some students do not have good academic performance, but if they think t hey are very good athletes, their overall selfidentity is not threatened by their poor academic p erformance. In other words, individuals can maintain their self-esteem by generating a global p ositive self-view, whereas self-verification theory (Swann, 1992) assumes that people are troubl ed by inconsistency and are motivated to reduce the relevant issue. In this process, they te nd to look for others’ evaluations to be consistent with their own self-perceptions. For exa mple, if some individuals think they are athletic, but other people do not evaluate them in the same way, their self-identity is threatened and thereby, they attempt to look for more evaluati ons consistent with their athletic images from other people. Even though the aforementioned theori es were not deemed for the study, used by Kyle et al. (2007), the item, “I identify with the people and image associated with___” for identity-affirmation and the item, “You can tell a lot about a person by seeing them ____” for identity-expression are not distinct. It looks like both the items belong to either identityaffirmation or identity-expression. Rather, self-identity and social identity are propo sed to examine more specifics of identity. Self-identity is an individual level identity, wher eas social identity refers to the identification of the self with a social group (Thoits & Virshup, 199 7). From a social identity theory perspective (Tajfel, 1978; Tajfel & Turner, 1979), people can e nhance their self by identifying themselves with positively valued groups. For example, people who prefer, or are highly involved in active leisure can identify themselves with other active l eisure participants and feel more positive about their identity by comparing like minded participant s of their ingroups with those of less active leisure groups or the outgroups. Social identity re fers to self-enhancement in this regard. Selfidentity focuses more on self-consistency in which an individual strives to have balance between

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62 their existing self-definition and their newly gene rated self-view to decrease uncertainty (Heider, 1958). Consistency between an existing self-view an d the attitudes developed from participation in leisure or tourism activities refers to self-ide ntity, whereas self-enhancement is derived from identifying themselves with other active leisure pa rticipants and refers to social identity. To sum, involvement is defined as a belief structur e related to self-value that was formed within the social environment and that leads to ext reme perception or attitudes. This belief structure fosters consistent behavior. Particularly involvement with participation in leisure activities is more likely to relate to enduring cha racteristics rather than situational characteristic s. Enduring involvement is characteristic of literally “endure” that results from consistent participation in certain leisure activities and mig ht diminish perceived risks. The centrality and identity components of involvement seem to be more important in understanding enduring leisure involvement. Specifically, identity is crit ical in social judgment theory (Sherif & Cantril, 1947). From this perspective, self-identity and soc ial identity (Thoits & Virshup, 1997) are likely to valuable for better understanding specific ident ities of leisure participants. Habitual Behavior Involvement is a psychological factor, whereas habi tual behavior is an automatic behavior which reinforces the behavioral consistency between past behavior and current behavior. Even though the theories of reasoned action and planned behavior (Ajzen, 1985, 1991; Fishbein & Ajzen, 1975) have been employed in numerous academi c areas related to behavioral research as well as social psychology to predict future behavio r, these theories have excluded the influence of an unconscious component on behaviors. These the ories hypothesize that attitudes, subjective norms, and perceived control lead to behavior media ted by behavioral intention (Ajzen & Fishbein, 1981).

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63 Social psychologists demonstrated that people are n ot always conscious, intentional, or deliberate when they behave (Bentler & Speckart, 19 79, 1981; Triandis, 1977). Therefore, Triandis included habit in addition to intention to predict behavior. Triandis (1977, p 9) postulated that the probability of an act depends o n three major factors: 1) the strength of the habit of emitting the act, which is indexed by the number of times the act has already occurred in the history of the organism, 2) the behavioral inte ntion to emit the act, and 3) the presence or absence of conditions that facilitate performance o f the act. Accordingly, the stronger the habit and intention, the higher the probability to act. W hen in new social situations, where behaviors have not become unconscious, the weight of intentio n may be greater than in familiar situations. In contrast, habit has a stronger impact on behavio r in social situations where the act has already occurred in the past. At the outset, cognitive fact ors like attitudes and norms are activated, but over the passage of time, a behavioral shift away f rom these cognitive factors occurs, and eventually habit becomes more influential. Triandis (1977) suggested that most non-verbal beha viors are controlled by habit as many people behave without thinking about how to act. Tw o ways to measure habit are frequency of behaviors reported by the respondents and the degre e of agreement with a given statement by respondents (Triandis, 1977). By using both approac hes, self-perceived habit and actual habit can be attained and may complement each other. In B entler and Speckart’s (1979) model, attitudes and past behavior were highly significant in predicting future behavior, whereas intentions were not. Some studies found that habit influences intention significantly (e.g. Bagozzi, 1981; Charng, Piliavin, & Callero, 1988), but in other studies, habit had a direct impact on behavior without intention (Albarracin, & McNatt 2005; Mittal, 1988; Montano & Taplin, 1991; Verplanken, Aartz, & Knippenberg, 1994).

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64 Theories such as social adaptation theory (Beatty & Kahle, 1988; Kahle, 1984) and thought theory (Anderson, 1990) are in favor of a standpoin t that habit facilitates the attitude-behavior link because habit forms a well learned schema lead ing to behavior. This schema refers to grouping numerous objects into several subjective c ategories, which makes it easy to automatically extract necessary information from th e appropriate category. Even though habit itself is defined as repeated behavior without deli beration, this cognitive formation of the schema behind habit is operating (Kahle, 1984). In such a manner, it is postulated that the attitude that is consistent over time leads to repeated behavior whe reby habit becomes better to predict future behavior (Beatty & Kahle, 1988). Furthermore, when the behavior becomes routine, future behavior is more predictable in examining attitude, intentional and habit, unintentional. For example, provided that frequency of group fitness a ttendance and attitudes towards participation in group fitness are asked together, the predictabi lity of future participation in the group fitness i s improved. Jaccard and Blanton (2005) addressed that in genera l, social psychologists have used three ways to see the consistency between past behavior a nd future behavior. One is that causal factors that have influenced behavior in the past continue to influence behavior in the future, thereby resulting in behavioral consistency across time but this model does not regard direct impact of past behavior on future behavior to see the past be havior-future behavior consistency (i.e., a proxy model, Ajzen, 1991; 2002). Another is that past behavior encourages attitudes or beliefs that are consistent with the behavior and those attitudes or beliefs developed f rom past behavior have an influence on future behavior (i.e., a mediator model, Aronson, 1969; Be m, 1967, 1972; Cooper & Fazio, 1984; Steele, 1988). In terms of cognitive dissonance the ory, dissonance is a negative state that occurs

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65 whenever an individual holds two or more inconsiste nt cognitions simultaneously. To alleviate this negative state, people change one or both cogn itions to make them consistent. In this manner, people attempt to change attitudes that are different from past behavior, whereby they justify their past behavior and feel more comfortab le. As an alternative explanation to cognitive dissonance theory, self-perception theory (Bem, 196 7, 1972) is consistent with the assumption in which people have attitudes consistent with past be havior. However, unlike cognitive dissonance theory, people in the self-perception process do no t necessarily feel discomfort. When individuals need to report an attitude, they often infer it from the implications of a past behavior that happens to be salient to them through a situat ional cue. Instead of an internal negative state, an external situation could cause current behaviors by inducing the inference of attitudes consistent with their past behaviors. Finally, habit accounts for the variance that past behavior, intention, or attitudes could not explain in the past-future behavioral link (i.e., a habit model, Triandis, 1977, 1980; Ouellette & Wood, 1998; Verplanken & Ouellette, 2003). In a hab it model, behavior cannot be predicted without past behavior, which is different from othe r models. The repetition of the past behavior creates the new psychological construct of habit. B oth social adaptation theory (Beatty & Kahle, 1988; Kahle, 1984) and thought theory (Anderson, 19 90) of the earlier notion account for this unique psychological process of habit in which sche mata formed through adaptive process to environment is associated with unconscious behavior s. In terms of a conceptual definition and the measure ment of habit, many studies have described it as behavioral repetition and frequency However, several researchers postulated that habit entails more complex components such as autom aticity, goal-obtaining concepts, situation sequences, less complex information processing, and efficiency of behavior (Aarts, et al., 1997;

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66 Bargh, 1989; Betsch, Fiedler, & Brinkmann, 1998; Ho nkanen, Olsen, & Verplanken, 2005; Verplanken & Orbell, 2003; Wood, Quinn, & Kashy, 20 02). Triandis (1980) described habit as situation-behavior sequences that are automatic. Ve rplanken and Aarts (1999) defined habit as “learned sequences of acts that have become automat ic responses to specific cues, and are functional in obtaining certain goals or end states ” (p. 104). One difference between habit and attitudes pointed out by Oskamp et al. (1991) is th at habit is a behavior but attitudes are not, and thus, habit needs the presence of the appropriate s timuli, whereas attitudes occur even in the absence of the stimuli. To measure habit, Verplanke n and Orbell (2003) and Verplanken, Friborg, Wang, Trafimow, and Woolf (2007) developed the Self Report Habit Index (SRHI) that consists of different components such as frequency, lack of awareness, lack of control, and mental efficiency. Influential studies that explain the psychological processes of habit have mainly investigated the relationship between habit and int ention, informational involvement of habitual behaviors, and reinforcers of habits. Some studies found that strong intention is associated with weak automaticity (see, Betsch et al, 2004; Heckhau sen & Beckmann, 1990; Orbell, Hodgkins, & Sheeran, 1997; Ouellette & Wood, 1998). Honkanen, et al. (2005) found that well-developed intention was influenced by attitude and ambiguous intention was affected by past behavior, and further the strength of habit was more related to p ast behavior-based intention rather than attitude-based intention. In terms of habit and inf ormation acquisition, individuals with habitual patterns had little deliberate information acquisit ion (Ronis, Yates, & Kirscht, 1989) or engaged in little information processing (Verplanken, Aarts & Knippenberg, 1997). Some studies found that variables reinforcing habit were social benefi ts or incentives (Bamberg, Ajzen, & Schmidt, 2003; Fujii & Kitamura, 2003), behavioral efficienc y, profitability and convenience (Verplanken

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67 & Holland, 2002), stable situations and opportuniti es to behave (Ouellette & Wood, 1998) or the favorability of intention (Wood, et al., 2005). Habitual behavior has primarily been used in the fi elds of health studies and consumer behavior, focusing especially on exercise habits (e .g., Davis, Brewer, & Ratusny, 1993; Godin, Valois, Shepherd, & Desharnias, 1987; Iso-Ahola & C lair, 2000; Maddux, 1993; Valois et al., 1988), eating habits (e.g., Jimenez, Lendoiro, Garc ia, Perez, & Simal, 2006), and consumption habits (e.g., Eagly & Chaiken, 1993; Verplanken, He rabadi, Perry, & Silvera, 2005). Particularly, in exercise and physical activities, habit was foun d to be more important in predicting future behavior in terms of behavioral consistency than at titudes, norms, and perceived control (Norman & Smith, 1995). Habit also induced the same exercise patterns despite environmental change (Wood et al., 2005). It is likely that exerc ise or physical activities are more susceptible to habit rather than other attitudes or beliefs becaus e they are more closely related to biological components such as addiction. Several researchers s tudied bicycling habits as a travel mode: a strong bicycling habit was related to quicker react ion to bicycling related destination information than other transportation related destination infor mation (Aarts & Dijksterhuis, 2000), and stronger bicycling habits were associated with simp ler strategies or rules in the decision making process (Verplanken et al., 1997), and less access to new information or alternatives (Verplanken, et al., 1998). Overall, the earlier literature shows two types of habitual behavior. One is a single habitual action and the other is a habitual sequence of mult iple activities. Eating (e.g., Conner, Fitter, & Fletcher, 1999; Oliver, Wardle, & Gibson, 2000), sm oking or drinking (e.g., Chassin et al, 1981; Gruenewald & Treno, 1996), or seat belt use (e.g., Ozminkowski, et al., 2004) correspond to a single habitual action. Examples such as the consum ption process involved in entering and

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68 ordering at a restaurant (e.g., entering, giving co at, being seated, studying the menu, ordering, etc, Abelson, 1981), travel mode choices based on situat ional cues (e.g., Aarts et al., 1997; Matthies, Klockner, & Preibner, 2006) or food choices (e.g., Honkanen et al., 2005) are pertinent to a habitual sequence of multiple activities. Specifica lly, routine lifestyles (e.g., getting up, brushing teeth, and wearing clothes in the morning) are a ha bitual ordering of a variety of single habitual actions. In addition, there may exist a slightly different h abit from the previous examples, this is the idea of expanded habit rooted from one single habit As an illustration, people with a bicycling habit as a routine leisure activity may participate in periodic bicycling events during their vacation. This habitual pattern is distinct from me rely a single habit or a cluster of multiple habits. Given that individuals have strong bicyclin g habit, such a strong habit could foster them to categorize even different environments or extern al objects into a schema related to bicycling. More specifically, individuals actively create one schema by classifying various tangible and intangible external stimuli into a similar context and then making these different stimuli automatically connect one another. It is likely tha t individuals expand the domain of habitual schema through spontaneously contextualizing differ ent objects and circumstances into a homogeneous category. Hence, multiple habits in a h abitual schema might be associated with various situational cues. This habitual schema is s imilar to some theoretical claims as to how knowledge is processed by experts. Experts are used to saving large amounts of knowledge within a narrower schema, thereby easily retrieving information from the schema (Lewandowsky & Kirsner, 2000). To explain, habit explains partially or wholly unco nscious parts guiding behavior. In particular, as people’s lifestyles do not always en tail intentions, the behavioral process of leisure

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69 physical activities in routine lifestyle may be mor e clearly explained by habitual behaviors. Furthermore, the fact that leisure physical activit ies in routine environments appear similar even in different environments such as vacations might b e more clearly understood with the aforementioned habitual schema. Motivation Motivation Theories Although leisure involvement and leisure habit migh t influence vacation/tourism behavior, the link between leisure and vacations is likely to be mediated by tourism motivation because tourism motivation closely guides vacation/tourism behavior (Crompton, 1979; Iso-Ahola, 1983; Pearce & Caltabiano, 1983). Then, what is motivatio n? To describe motivation, Eagly and Chaiken (2005) distinguished how motivation is diff erent from needs and motives, even though classic needs theorists such as Murray (1938) did n ot distinguish needs from motives or motivation. According to Eagly and Chaiken, needs r efer to a general end state such as selfregard gained from achievement of specific goals su ch as a good job and motives refer to the goals or end-states that people strive to reach. Mo tivation refers to the engine of motives that guide thoughts and behaviors. Needs and motives see m to be the same. However, by this definition, needs are more abstract, and motivation is more concrete. In a similar vein, some studies suggest that needs lead to motivations and then motivations guide behaviors (McDonough & Crocker, 2007). That is, needs are mor e related to internal drives such as selfrelevant rewards, whereas motives or motivations re fer to behavioral goals to satisfy the internal drives. For example, when needs occur from disequil ibrium (Murray, 1938) or dissonance (Festinger, 1957) such as loneliness, people strive to decrease this dissonance by taking some action such as meeting new friends, which is a moti vation. Although people have different

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70 motives, they could have the same needs in this res pect (Gnoth, 1997). Accordingly, needs are a broader concept, and motivation is a more specific concept (Eagly & Chaiken, 2005). Gnoth (1997) also attempted to distinguish motives from motivations for a more in-depth understanding of tourist behaviors. His distinction between motives and motivations is that motives (i.e., latent needs) are related to lasting dispositions resulting from long-held learned behaviors (Hull, 1943), whereas motivations refer t o situation-specific goals through the interaction between an object and a situation (Hart manm, 1982). His approach is very similar to Eagly and Chaiken’s (2005) distinction, and their u ltimate claim is the same despite employing different logical processes. According to Gnoth, ev en if motives underlie directions or targets, motivations entail concrete targets or objects thro ugh the interaction of motives and situations. For excitement or relaxation motives, for example, individuals could have motivations to go to a specific destination or beach, and they might expre ss “I am going to Bali because of its pleasurable weather” or “I will go to the theme par k” for a new experience. However, different from Eagly and Chaiken’s (2005) distinction, Gnoth (1997) tried to explain motives in the behavioral realm (i.e., beha viorism), and motivations in the cognitive realm (i.e., cognitivism). According to Gnoth, moti ves function to narrow the perceived gap between the ideal self and the actual self. Therefo re, a felt need to self-actualize is viewed as a motive. Gnoth claims that this is supported by driv e theory (Hull, 1943). When a deprivation is reduced satisfactorily, people tend to remember thi s behavioral process and subsequently learn it as a satisfactory process so that their behaviors b ecome habits. From this perspective, motives are relevant to retrospective, non-selective activi ty, and learning from the past. In contrast to motives, motivations might be explained by expectan cy value theory (Aronson & Carlsmith, 1962) in the cognitive realm. Motivations underlie knowledge as an anticipatory factor to predict

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71 behaviors, whereby motivations are a forward-lookin g concept rather than a retrospective approach. Gnoth described motivations as situationa l parameters and thus, often ephemeral. Furthermore, with the combinational view of behavio r analysis and cognitive psychology, Gnoth attempted to apply the motive-motivation distinctio n to push and pull motivations of tourism (Crompton, 1979; Dann, 1977) in which motives are t ourism push factors (i.e., internal factors) and motivations are tourism pull factors (i.e., ext ernal factors or destination attractions), and they are in a dynamic relationship (Atkinson & Birch, 19 74). Despite his interesting point of view to distinguis h motives from motivations with behavioral analysis and cognitive psychology, his a ttempt to explain motives through behaviorism (i.e., behavior analysis) seems to be m isleading. Behaviorism has a basic assumption that all of an organism’s behaviors are observable and explicit (Skinner, 1938). Radical behavior analysis and cognitive psychology have had a long history of debates about the scientific evidence about observable and unobservab le aspects of human behaviors (Chiesa, 1994). Behavior analysis attempts to discover the p rinciples or rules of an organism through experimental conditioning, and extend their princip les to all species (Pierce & Cheney, 2004). Behaviorists argue that all organisms’ behavior inc luding human behavior should be explicitly observed and measured, resulting in a situation whe reby unobservable or implicit parts (e.g., cognitions and emotions) of human beings have rarel y been accepted by behaviorism. On the contrary, cognitive psychology has conceived such i mplicit aspects as parts of human behavior (Zuriff, 2003). The verbal behavior of humans was a main argument between behavior analysis and cognitive psychology, and as such has not been sufficiently explained by Skinnerian behaviorism (Chomsky, 1959; Lena, 2002; Palmer, 200 4; Place, 1997) even though postSkinnerian behavior analysis attempted to establish global rules of verbal behavior by creating

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72 relational frame theory (Hayes, Barnes-Holmes, & Ro che, 2001). However, motives (e.g., selfactualization or self-realization as push factors) that Gnoth (1997) included in the behaviorism domain are rather more implicit and unobservable th an motivations. Therefore, the motivemotivation distinction through the behaviorism-cogn itivism distinction is likely to cause more confusion in this regard. With a different standpoint from Gnoth (1997), IsoAhola (1999) suggested biological needs and psychological motivations as underpinning leisure and tourism. Needs are more associated with physiological needs such as hunger, whereas motivations are more relevant to higher levels of psychological needs such as self-a ctualization. In this respect, needs are at a lower level of the hierarchical structure than moti vations which are more cultivated because physiological needs such as hunger are scarcely cal led motivations. Nevertheless, most researchers have hardly distingu ished the difference between needs, motives, and motivations. To better understand the aforementioned distinctions, more specific needs theories should be reviewed. Applied studies such as marketing, leisure, or tourism have developed relevant motives or motivations from seve ral needs theories. In particular, two main psychological need theories for defining and develo ping leisure and tourism motivations have been used: manifest needs theory (Murray, 1938) and hierarchical theory of needs (Maslow, 1970). According to manifest needs theory, needs oc cur from an inner state of disequilibrium, and in turn drive motivations to behave. For the al leviation of this internal tension or the elimination of the inner disequilibrium, people are driven to behave in certain ways. This psychological process is similar to cognitive consi stency theories such as cognitive dissonance theory (Festinger, 1957) in which individuals striv e to reduce dissonant states. However, needs occur under the absence of something needed but dis sonant state appears under the presence of

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73 the situation in which individuals need to opt for one among equally attractive alternatives. Moreover, distinct from a dissonance theory, manife st needs theory includes biological or physiological needs in addition to psychological or cognitive needs. Biological needs are related to eating and having sex, whereas psychological nee ds are associated with achieving, affiliating and having autonomy. Needs that are more salient or manifest to individuals drive their behavior. Similar to Murray (1938), Maslow (1970) also distin guished physiological needs from psychological needs. However, he suggested that nee ds assume a hierarchical order. Physiological needs are more basic than psychologic al needs. To reach psychological needs, individuals should have already satisfied their phy siological needs. He identified five hierarchical needs: physiological needs, safety and security needs, love and belongingness needs, esteem and autonomy needs, and self-actualization n eeds. Physiological needs correspond to the lowest level of needs, and self-actualization belon gs to the highest level of needs. In this hierarchical model, conceivably, if people are hung ry, they do not concern themselves with other higher needs such as love or self-esteem. Likewise, if people feel unsafe, they are no longer interested in other psychological needs. However, l ater some researchers argued against the idea that all people hierarchically achieve their needs. For example, although some backpackers are unsatisfied with the low level needs such as hunger or safety yet, they explore cultural or historical experiences and also seek intimate relat ionship through social interaction (Max-Neef, 1991). In addition to these two theories, self-determinati on theory developed by Deci (1975) and Deci and Ryan (1985) has been influential particula rly in leisure, sports, and recreation studies. Self-determination is conceived as a continuum wher e at one end is amotivation (non selfdetermined end) and at the other end is intrinsic m otivation (self-determined end). Extrinsic

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74 motivation is placed in the middle of the continuum (Deci & Ryan, 2000). According to Deci and Ryan (1985, 2000), the fundamental needs to determi ne this range consist of competence, relatedness, and autonomy. Competence is a need to experience mastery or to have optimal experience in the physical and social environment, relatedness is a need to have intimate relationships with other people, and autonomy is a need to have self-regulation or self-control over one’s behavior. Deci and Ryan (2000) suggest t hat amotivation has no self-regulation and its locus of causality is impersonal, whereas intri nsic motivation has intrinsic regulation and its locus of causality is internal. Regulation in extri nsic motivation entails external regulation, introjected regulation, identified regulation, and integrated regulation by the degree of regulation, and further their locus of causality are external, somewhat external, somewhat internal, and internal, respectively. This range has often been u sed to explain social well being and health. That is, a state closer to intrinsic motivation is healthier and more enjoyable than one that is closer to extrinsic motivation (Deci & Ryan, 1985, 2000). In terms of physical activity, physical exercise associated with self-determined motivation (i.e., intrinsic motivation) tends to be more stable than extrinsically motivated physical exerci se (Chatzisarantis & Biddle, 1998). Thus, manifest needs theory (Murray, 1938), the hierarchi cal theory of needs (Maslow, 1970), and selfdetermination theory (Deci & Ryan, 1985) have been the foundational theories in developing approaches to tourism, leisure, and sports motivati ons. Tourism Motivation People travel for a range of reasons. Historically, escaping the heat and seeking social interaction at the summer resorts in Roman times, t aking a pilgrimage tour in the Middle Ages, and participating in the Grand Tours at the end of eighteenth century have been prevalent forms of travel. These journeys show that the historical origins can be used to explain present day tourism motivations (Goeldner & Ritchie, 2003). For example, to avoid hot or cold weather,

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75 people travel to cooler or warmer places during vac ation. This motivation has been denoted as “escaping” motivations (Iso-Ahola, 1980). Seeking s ocial interaction has become one of the most important motivations in post modern society as man y modern people feel lonely in today’s highly individualistic society (Kelly, 1983). To ha ve religious or spiritual experience such as a pilgrimage tour is also an important motivation of post modern people as they want to fulfill their spiritual needs in their stressful lifestyles (Rins chede, 1992). Motivations that can be explained from the Grand Tour are to explore new things and t o gain knowledge based on intellectual curiosity (Brodsky-Porges, 1981). Current education al tourism helps individuals to achieve this motivation. However, needs or motivations in post m odern society are multidimensional in response to the complexity of today’s social struct ures and environments. Dann (1977, 1981) described tourism motivations as a meaningful state of mind which encourages individuals to travel. He used the conce pt of pull factors and push factors to understand tourist motivations. Pull factors are as sociated with the external attraction of a destination (e.g., sunshine, sea, or specific resor ts) drawing tourists, whereas push factors are associated with internal states. Dann suggested tha t tourists are influenced by two push motivations: anomie and ego enhancement. Anomie is similar to Murray’s (1938) disequilibrium concept that is described as loss of balance. Howev er, Dann’s anomie is more closely connected to social influences and is aligned with a sociolog ical perspective. That is, the gap between an individual and his or her societal values results i n an anomic state. He explains that individuals may feel tension in today’s mass society. As an ill ustration, people feel conflict from wars, strikes, or violent situations. Anomie pushes peopl e to get away from these uncomfortable states. The other push factor that Dann identified is ego-e nhancement. He argues that to enhance their ego through social recognition or prestige, people travel. This notion is akin to the Theory of

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76 Leisure Class described by Veblen (1899) in which l eisure class conspicuously consumes their leisure to exhibit their social status. Under the same push and pull concept, Crompton (197 9) identified seven push factors and two pull factors associated with tourism motivation s. Pull factors are derived from destinations, whereas push factors arise from the socio-psycholog ical states of individuals. According to Crompton, the two main pull factors are novelty and education and particularly relate to cultural motives. Crompton distinguished between tourism for pleasure and non-pleasure tourism. Applying the specific and non-specific motivations suggested by Howard and Sheth (1969), Crompton postulated that specific motivations are s atisfied by pleasure tourism, but non-specific motivations are satisfied by other activities. Thro ugh in-depth interviews, he found the following socio-psychological, or push, internal motivations with vacations, escape from the routine, exploration of self, relaxation, prestige, regressi on, enhancement of kinship, and facilitation of social interaction, and the following cultural, or pull, destination attractions motivations associated with vacations, novelty and education. C rompton’s study is significant in that it provided further studies with the foundations for u nderstanding decision making, specifically understanding the dynamic interrelation between pus h and pull factors. Indeed, Crompton argued that push factors are much more influential than pu ll factors in choosing a destination. Tourism motivations described by Iso-Ahola (1982, 1 983) also rely on the idea of pushpull factors. However, slightly differently, he foc used on the seeking and escaping processes inherent in internal motivations. Seeking is a moti vation where individuals strive to gain intrinsic rewards, and escaping is a motivation where individ uals attempt to get away from their everyday life and environments. Iso-Ahola’s escaping motivat ion is similar to the anomie of Dann (1977, 1981) and escape from the routine of Crompton (1979 ). However, Iso-Ahola suggests that

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77 seeking motivation is a result of the interaction b etween push and pull factors. In other words, seeking motivation does not arise merely from the a ttractiveness of destinations. Motivations emerge from a combination of a variety of sources, rather than from one source. More specifically, he proposed interpersonal and persona l dimensions of escaping and seeking. Escaping from the personal world is associated with personal problems and difficulties, whereas escaping from the interpersonal world relates to co -workers, family members and friends. Seeking personal rewards is relevant to feelings of mastery, ego-enhancement, and prestige, whereas seeking interpersonal rewards refers to inc reased social interaction. Pearce and Caltabiano (1983) investigated tourist m otivations based on Maslow’s hierarchy of needs. Further they developed the idea of the Tr avel Career Ladder (TCL), and found that travel motivations are quite well fitted to Maslow’ s (1970) hierarchical needs. The TCL is based on the idea of associating an individual’s level of travel experience with lower and higher order needs. These needs consist of relaxation (i.e., bio logical needs), stimulation (i.e., safety and security needs), relationship development, self-est eem, and fulfillment (i.e., self-actualization needs). The lowest level of this ladder is a relaxa tion need. The next level is a stimulation need. The third level is a relationship need. A self-este em need is at the fourth level. The final level is a fulfillment need. Different from Maslow’s hierarchi cal model, however, each level consists of internal and external needs. For example, self-este em’s internal needs refer to the development of skills, competence, and mastery, and external ne eds are relevant to social rewards or prestige. Overall, self-esteem needs are satisfied by social recognition as well as internal mastery. Fulfillment of these needs occurs, once the interna l and external needs are identified, which is the optimal level where people reach a peak experie nce. However, according to the TCL, individuals begin with the different levels of moti vation, as being affected by their personality,

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78 experiences, and skills. For example, an individual ’s motivation could start from a stimulation level, instead of a relaxation level. The model is dynamic and flexible in this respect. Later, Pearce and Lee (2005) modified the travel career la dder, but reconfirmed the basic factors (i.e., relaxation, relationship, and self-development) as useful for all tourist behaviors. As already mentioned above, Gnoth (1997) viewed mot ives, push motives as internally driven (e.g., self-actualization, excitement, relax ation, etc) arising from deprivation, and as more global than motivations, whereas motivations, pull motivations refer to specific goals associated with destination attractions. He gave several examp les of the dynamic flow between push motives and pull motivations such as categorization of tourists according to their needs, different destinations sought by psychocentric and allocentric tourists (Plog, 1974), and different tourist roles generated from the different types of behavio r that they seek in the tourism settings. Since the late 1980s, tourism researchers have tend ed to address the interaction between push and pull factors (Coltman, 1989; Yiannakis & G ibson, 1992; Yoon & Uysal, 2005). Yiannakis and Gibson (1992) suggested that individu als are motivated by internal push factors, but they decide specific destinations from the opti mal combination of push and pull factors and which facilitate the ability to enact various touri st roles (e.g., sun lover, archaeologist, or jetsetter). In their later study, Gibson and Yianna kis (2002) investigated the relevance of need clusters based on life stage and gender and the typ ology of tourist roles established by their previous study. Their results tentatively upheld th at such clusters push individuals to select certain tourist roles. They found, for example, tha t men peak in terms of their interest in the anthropologist role when they are 50 years old, but women reached peak interest in this role five years later than men. Their interpretation as cultu ral constraints such as motherhood concerning

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79 this finding is interesting because they regarded m ore social and cultural influences on push factors. From the dynamic perspective between push and pull, Ryan and Glendon (1998) also investigated how tourist clusters and tourism motiv ations are related. Tourists were clustered into eleven groups: unimaginative relaxers, relaxing mod erates, relaxed discoverers, positive holidaytakers, intellectual active isolates, competent int ellectuals, mental relaxers, active relaxers, noisy socializers, friendly discoverers, and social relax ers. Tourism motivations were identified with the four factors from Beard and Ragheb’s (1983) LSM : relaxation, social, intellectual, and mastery. One of findings indicated that mental rela xers were high on relaxation motivation but they were low in other motivations, while active re laxers were high on relaxation and mastery motivations, medium in intellectual motivation, and low in social motivation. Thus, they suggested that different types of tourism motivatio n tended to be associated with different vacation types. Including more utilitarian destination values, Fodn ess (1994) developed a leisure traveler motivation scale and identified five factors: knowl edge function, punishment minimization, reward maximization, self-esteem value-expressive, and ego-enhancement value-expressive. The knowledge function factor is similar to Crompton’s (1979) education and novelty motives. The punishment minimization factor is almost identical to Crompton’s escape from a routine, and the reward maximization factor is similar to regression (i.e., nostalgia) motives of Crompton. The ego-enhancement value-expressive factor is related to Crompton’s prestige motives. However, the items of the self-esteem value-expressive facto r are closely related to seeking destination attractions such as luxury food, good restaurants, the importance of accommodations, and fashionable places. As work on tourism motivation c ontinued, researchers began including more

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80 specific items measuring destination attractions su ch as entertainment, resorts, sports, and budget accommodations as well as natural and cultural attr actions (Turnbull, & Uysal, 1995), drinking opportunities, personal connection to history, chan ge of routine environment, travel distance (Sirakaya & McLellan, 1997), casino/gambling, relia ble weather, tennis, cleanness, local cuisine, and water sports (Yoon & Uysal, 2005). Leisure and Sport Motivation The study of leisure motivations has taken a slight ly different path from tourism motivations. While researchers studying tourism mot ivations have taken both the influence of destination attributes (i.e., pull) and the push fa ctors into consideration, studies on leisure motivations have focused more on the optimal experi ence of activity, and tend to focus on more of a range of emotional and cognitive benefits of a ctivities (i.e., push). Leisure motives such as harmavoidance, justice, nurturance, responsibility, sentience, social status, succorance (Tinsley, 1978), altruism and creativity (Crandall, 1980) hav e been identified. In particular, leisure motivations are associated with the mental and phys ical well being of individuals in their social environment (Csikszentmihalyi, 1990; Kelly, 1987; S haw, 1984). For example, the flow state emerges from the balance between the skills and cha llenges on activities, and is the ultimate happiness and enjoyment state sought by people (Csi kszentmihaly, 1990). Flow experience and perceived freedom are important for the quality of leisure activity and life (Iso-Ahola, 1979; Neulinger, 1981b, 1982; Tinsley & Tinsley, 1986). I so-Ahola’s (1999) seeking and escaping motivations based on the concept of optimal level o f stimulation (Berylne, 1960) have also been used to explain the flow or optimal experience of l eisure activity. People who are less stimulated in their routine life may strive to seek more stimu lation to achieve flow experiences through their leisure. By contrast, people who are over stimulate d may try to escape from the stimulation (e.g., stress or tension).

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81 Leisure motivations provided a foundation in the de velopment of tourism motivations (IsoAhola, 1980, 1982; Ryan, 1994). Leisure motivations (i.e., intellectual, social, competence/mastery, and stimulus avoidance motives) identified by Beard and Ragheb (1983) have often been applied to tourism motivations with good reliability and validity (Ryan, 1994; Ryan & Glendon, 1998). These leisure motives seem t o be less affected by different external variables. Indeed, Graefe, Ditton, Roggenbuck, and Schreyer (1981) demonstrated that river floaters in different environments shared the same leisure motivation structure across diverse settings. As such, leisure motivations have been ap plied across different types of vacations and diverse samples. Sport motivations also have the same basic structur e of seeking and escaping (McDonald, Milne, & Hong, 2002). People take part in sport act ivities to seek optimal level of stimulation and to escape from stress. Indeed, similar motivati ons have been found among people who take part in sport, exercise, and fitness (Duda, 1988; F luker & Turner, 2000). More specifically, Recours, Souville, and Griffet (2004) identified fo ur dimensions of sport participation motivations: competition, exhibitionism, sociabilit y, and playing to the limit. Other studies have included intellectual, accomplishment, stimulation, optimal experience (Pelletier, et al., 1995), interest and enjoyment (Frederick & Morrison, 1996) and mastery, health, recognition, solitude, and social affiliation (Raedeke & Burton, 1997). In fact, motives in leisure, tourism, and sport par ticipation have similar basic components because they have used social psychological theorie s as their foundation. In the structure of seeking and escaping, individuals behave to satisfy the physiological and psychological needs. Particularly, the previous literature shows that fu ndamental motives across leisure, tourism, and

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82 sport participation seem to share four domains: soc ial interaction, competence or achievement, relaxation or escaping from stress, and exploration or knowledge. Summary The relationship between leisure and vacation/touri sm has been explained by psychological and behavioral factors, notably, psychological mean ings such as perceived freedom and behavioral patterns in structural environments such as free time and space have been identified (Colton, 1987; Hamilton-Smith, 1987; Iso-Ahola, 198 3; Kelly, 1983). From this perspective, Carr (2002) postulated that attitudes, preferences, and habits encourage people to behave consistently between leisure and tourism contexts. In further empirical study, Brey and Lehto (2007) found that the likelihood of taking part in similar activities on vacation as in general leisure is higher for activities such as golfing an d jogging than other activities such as entertainment, dining, and cultural activities. As such, sports, physical activities and active out door recreation seem to play an important role in connecting leisure to vacations/tourism. He nderson (2005a, 2005b) noted that physical activity, leisure, recreation and travel are relate d and can be integrated to form an active and healthy lifestyle. Enjoyable physical activity expe riences are related to recreational activities in leisure contexts, which may encourage relevant trav el. This process seems to increase the quality of life related to a healthy lifestyle (Coleman & I so-Ahola, 1993; Henderson & Ainsworth, 2002, 2003; Iwasaki, 2003). Consequently, active leisure pursuits may influence the choice of active vacation pursuits (Chon & Singh, 1995; Glyptis, 199 1; Hall, 1992; McGehee, et al., 2003; Redmond, 1991). However, little empirical study has investigated th e relationship between leisure activities and tourism behaviors, especially in terms of activ e leisure and active vacations. To investigate this relationship, leisure involvement and habits s eem to be very important factors because both

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83 encourage people to focus on fewer activities, reje cting other alternative activities, and encourage individuals to maintain behavioral consis tency (Bentler & Speckart, 1979, 1981; Johnson & Eagly, 1989; Sherif & Cantril 1947; Trian dis, 1977; Verplanken & Orbell, 2003). Supporting this perspective, several researchers ha ve demonstrated that psychological and behavioral leisure involvement significantly influe nces future leisure behavioral consistency (Iwasak & Havitz, 2004; Kim et al., 1997). However, previous literature related to leisure involvement has tended to focus only on leisure set tings. This study assumed that there would be an impact of leisure involvement and habit on vacation/tourism behaviors but the association betw een leisure and vacation/tourism would be mediated through tourism motivation. Motivations ha ve been widely used to predict tourism behaviors because motivations guide behaviors (Crom pton, 1979; Iso-Ahola, 1982, 1983). Indeed, Ryan and Glendon (1998) found that the Leis ure Motivation Scale developed by Beard and Ragheb (1983) was useful in explaining vacation /tourism activities. Beyond asking which tourism motivations predict tourism behaviors, many researchers have examined actual tourism behaviors by either asking whether people took part in certain tourism activities (Fesenmaier, Vogt, & Stewart, 1993) or how much they agree with the given statements related to certain behaviors (Bakeman & Casey, 1995; Stanton-Rich & Is o-Ahola, 1998). In fact, it is assumed that all variables, involvement, habit, motivations and behaviors are likely to directly and indirectly influence one another (Albarracin et al., 2005; Tor mala & Petty, 2002).

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84 CHAPTER 3 METHODS The purpose of this study was to investigate the ps ychological and behavioral connections between active leisure and active vacations/tourism In particular, this study assumed that active leisure pursuits related to sports, physical activi ties and active outdoor recreation would influence vacation/tourism behaviors. Particularly, using a cross-sectional survey design, the study was designed primarily for structural equatio n modeling to examine if two exogenous variables (i.e., leisure involvement and leisure ha bit) associated with active leisure have causal relationships with two endogenous variables (i.e., vacation motivation and vacation behavior) associated with active vacations. This chapter pres ents the data collection procedure (i.e., including the sampling design and procedure), instr umentation, participant description, and data analysis. Data Collection To locate a population who are diverse in their int erests and who are likely to take a range of vacations, the study population was the UF Alumn i Association members. Another reason why the alumni members were chosen as the study sam ple is that in previous literature active sport tourists have been identified as having highe r education (i.e., college graduates or over) (Delpy, 1998; Gibson, 1998b) and the alumni members of a university or college would be comprised of individuals with at least a bachelor’s degree. Therefore, the likelihood of this population being involved in active leisure and act ive sport tourism was considered to be relatively high. Possibly, a high level of educatio n is also associated with discretionary income (Griliches & Mason, 1972) and thereby making it pos sible to extend participation in their favorite leisure activities by traveling to differe nt environments. Furthermore, those who have a high level of education and discretionary income ma y pay more attention to their health (Ettner,

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85 1995; Veenstra, 2000) and thus pursue being active during their leisure and their vacations. The UF Alumni Association members seem to be an appropr iate sample in this regard. The sampling frame was the database of the Alumni A ssociation of the University of Florida. The researcher received access to the UF A lumni database as a member of the UF Alumni Association. A systematic random sample was drawn from the list of the UF Alumni database. The targeted population size ( N ) (i.e., the total number of members of the UF Alum ni Association) is 200,000 and this population size wa s the same as the sampling frame. Based on this population size, the sample size ( n ) with 2% margin of error at the 99% confidence lev el was calculated at 4,063 (Kish, 1995). However, since un deliverable email addresses and a low response rate resulting from characteristics of web -surveys (Dillman, 2000) were anticipated, 80% of the total sample size was added. Thus, the u ltimate sample size was 7,313. The sample interval (i.e., the sample size divided by the targ eted population size) was 1/25. According to systematic sampling procedures, every 25th name was selected from the sampling frame. In terms of testing structural equation modeling (S EM), no absolute guidelines exist to determine the sample size, but a general rule of th umb is that a sample size of 200 is considered sufficient and may be necessary for a complicated S EM (Kline, 2005). However, too large of a sample size (i.e., exceeding 400) is associated wit h over sensitivity and leads to poor goodnessfit-measures based on maximum likelihood estimation (Hair, Anderson, Tatham, & Black, 2003). Accordingly, a more appropriate way of designing sa mple size identification in structural equation modeling is to use a ratio of the number o f cases to the number of free parameters of 10:1 (Hair et al., 2003; Kline, 2005). A web survey was used for this study because it was deemed the most appropriate way to access a probability sample of this size. Moreover, having access to the e-mail addresses of the

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86 members of the sampling frame made it a logical cho ice. Dillman (2000) noted that the internet survey has certain advantages such as the ability t o access a geographically dispersed sample, low cost, and shorter data collection period despit e some disadvantages such as low response rates and poor control of response situations. To o vercome these disadvantages, this study attempted to follow Dillman’s suggestions about res pondent-friendly email messages and a welldesigned web survey. Instrumentation The instrument consisted of fixed choice, partially closed-ended and open-ended questions (Appendix E). The final questionnaire was divided i nto three broad sections: leisure, vacation, and demographics. More specifically, the leisure se ction included 11 questions (i.e., a type of favorite leisure activity, leisure involvement scal e, leisure habit scale, behavioral involvement with leisure activity, and leisure activity partici pation patterns during vacation). The vacation section contained ten questions (i.e., a type of fa vorite vacation activity, vacation motivation scale, vacation behavior scale, vacation behavioral involvement, and vacation participation patterns). The demographics section included seven questions, gender, year born, educational level, employment, income, racial or ethnic backgro und and residence. Face Validity and Pre-Test The questions about the type of leisure activities and vacation activities were used to distinguish the respondents who take part in active leisure and vacations from those who do not. In the initial survey designed for a preliminary st udy, categorical multiple choices of leisure activity types were provided and respondents were a sked to select one category. Five categories of leisure activities were adapted from the leisure dimensions of Lounsbury and Hoopes (1988) based on the leisure activity blank developed by Mc Kechnie (1975): “sports, physical activities and active outdoor recreation-related leisure,” “cu ltural, arts and history-related leisure,”

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87 “ entertainment, dining and shopping-related leisur e,” “domestic activities-related leisure (e.g., cooking, sewing, gardening, etc)” “organizational a ctivities-related leisure (e.g., civic, or political activities)” and “other.” Along with the multiple choice question, the respondents were asked to specify their favorite leisure activity in the chosen category. In the same way, the six vacation categories adapted from the vacation activ ities developed by Davis and Sternquist (1987) and Pizam et al. (2004) were used: “sports, physical activities and outdoor recreationbased travel,” “visiting scenic natural attractions -based travel (e.g., National parks),” “culture and history-based travel,” “entertainment (e.g., th eme parks, gambling), dining and shoppingbased travel,” “beach-based travel,” “visiting fami ly, relatives, and friends-based travel” and “other.” Like the leisure activities, the responden ts were asked to specify their most preferred vacation activity within the chosen category. These questions were to sort participants into active leisure and active vacation categories based on the respondents who had chosen the dimension, “sports, physical activities and active outdoor rec reation-related leisure and vacation.” After the face validity of these questions was esta blished by four graduate students, the principle researcher pre-tested the items with 114 paddlers who participated in the Paddle Florida event held from March 20th to 27th, 2008. However, some problems within the leisure a nd vacation categories were found. Although the partic ipants were asked to choose one category and to express their favorite activity, some respondent s selected several categories, being confused with the given vacation categories. For example, th ose who enjoyed water-related sports chose both the “sports, physical activities and active ou tdoor recreation-based vacation” or “beachbased vacation” categories. Several respondents rec ognized “camping” as “sports, physical activities and active outdoor recreation,” whereas other people perceived it as included in the “visiting scenic natural attractions” domain. There fore, instead of providing the categorical

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88 multiple choices, an open-ended question was used i n the current study for the purpose of eliminating confusion between categories by asking the UF alumni members to describe one of their favorite leisure and vacation activities. Content Validity Face validity and logical validity are two types of content validity. Face validity is used to measure validity at face value, whereas logical val idity involves more strict processes, depending on the evaluation of a panel of experts (Rubio, Ber g-Weger, Tebb, Lee, & Rauch, 2003). Both face validity and logical validity were used to exa mine the validity of the leisure involvement scale, leisure habit scale, vacation motivation sca le, and vacation behavior scale. These scales were adapted from the scales already employed in th e existing leisure and tourism literature, with the exception of the habit scale that has only ever been used in the psychology literature. The wording of all the scales was modified and a few it ems of the scales were newly created for the purpose of this study. The content of each item for all of the scales was evaluated by 12 experts by asking them to assess relevance, representativen ess, and clarity of each item belonging to each pre-assigned factor. Content validity procedure A panel of experts was selected from the academic f ields of leisure, tourism, sport and psychology. The criteria used to select the experts were to approach individuals who had developed the corresponding scales or had extensive ly investigated those scales and who were most knowledgeable about the subject matter. Evalua tion of these criteria was based on the quality and the number of publications in the relev ant areas. The number of content experts is recommended from a minimum of three to a maximum of 20 (Gable & Wolf, 1993; Lynn, 1986). Rubio et al. (2003) suggested a sample size of ten experts as the most appropriate number. However, at the initial stage, the researcher selec ted 30 potential content experts, anticipating

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89 that the larger number of experts would provide mor e information as well as satisfy concerns about the response rate. An email cover letter, the informed consent, the survey questionnaire for content validity and one-page additional material t o explain the study model and hypotheses were approved by the IRB on 21st May 2008 (Appendix B). The email cover letter expl ained the purpose of the study was to establish content valid ity and thus, asked the experts to open the word files containing the informed consent, the que stionnaire and the additional material, attached to the email cover letter if they agreed t o be a member of the panel of experts. The purpose of the study, the study benefits, confident iality, voluntary participation, an opportunity to withdraw anytime without penalty, no risk associ ated with the study, and no compensation were referred to in the informed consent. However, any anonymity-relevant notion was not stated in the informed consent because the content validity study cannot guarantee anonymity of the experts because the researcher may need to cont act the experts to clarify their answers and comments after their feedback (Rubio et al., 2003). The format of the content validity questionnaire wa s designed on the actual survey that would be used for alumni members, but was slightly modified so that the expert members could rate three criteria (i.e., relevance, representativ eness, and clarity) and write in their comments (Appendix C). Some instructions concerning the ways to evaluate, the definitions of the terms, the sources of scales and the content validity scal e points were added to give them clear guidelines. The experts were asked to score each it em already assigned to a factor, instead of asking them to propose a factor congruent with each item. In this process, the expert members were asked to rate on three criteria (i.e., relevan ce, representativeness, and clarity) employed for logical validity (Grant & Davis, 1997), using the 5 point scale (1= unacceptable 2= poor 3= acceptable 4= good 5= excellent ). Relevance was assessed to demonstrate how closel y each

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90 item is relevant to the construct; representativene ss assessed how much each item represents the construct; and clarity assessed how clearly each it em was worded. The content validity survey was emailed to 30 exper ts on 26th May 2008. However, most experts did not reply until the middle of June. Sev eral experts emailed back to explain that they could fill out the survey after the middle of June because they were on their summer vacation. Accordingly, an email reminder was sent to those wh o had not answered by June 20th, 2008. The content validity survey was open until August 20th, 2008, assuming that the experts’ summer vacation would be finished in the middle of August as they are faculty of the universities where fall semester starts in the middle of August. The f inal sample size was 13 members out of 30 experts with 43.3% response rate, but one survey wa s incomplete. As a consequence, the evaluations from 12 experts were used for the conte nt validity analysis. The four scales to be evaluated were as follows: Leisure involvement scale : First, for the leisure involvement scale, 19 invo lvement items were adapted from those used by Kim, Scott, and Cro mpton (1997), Gahwiler and Havitz (1998), Pritchard, Havitz, and Howard (1999), and Kyle, Gra fe, Manning, and Bacon (2004). Almost all of these items were originally based on the Consume r Involvement Scale (CIP) developed by Laurent and Kapferer (1985). The multidimensional c onstruct of the CIP (Laurent & Kapferer, 1985) consists of interest (i.e., centrality), pleasure (i.e., hedonic value) sign and risk importance (i.e., importance of negative consequences) and risk probability Adapting this multidimensional involvement construct, McIntyre (1 989) created leisure activity-oriented items. McIntyre dropped the risk factor and added the centrality factor. He also reworded the sign factor to form the self-expression factor, and combined the pleasure value with interest value and then, renamed them attraction Several studies in the leisure and recreation fie ld have established

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91 the scale’s validity and reliability, adapting the CIP (Havitz & Dimanche, 1997; Havitz, Dimanche, & Howard, 1993; Havitz, Green, & McCarvil le, 1993), even though some researchers have argued that, by and large, the reliability of the risk dimension in leisure activities had failed (Kim et al., 1997; Kyle, Absher, Norman, Hammitt, & Jodice, 2007; McIntylre & Pigram, 1992). For the purpose of this study, the involvement item s were categorized into hedonic including three items, central including six items, social including two items, self-identity including four items, and risk dimensions including four items. For the hedonic dimension, one satisfaction item (Kyle et al., 2004) and one pleasure item and one e njoyment item (Gahwiler & Havitz, 1998) were used. For the central dimension, importance and interest items as origina lly proposed by the CIP (Laurent & Kapferer, 1985) were included. A dditionally, a commitment item used by Kim et al. (1997), a position involvement item used by Pritchard et al. (1999), and two centrality items used by Kyle et al. (2004) were contained in the central dimension. Two social items used by Gahwiler and Havitz (1998) were included in the social dimension. The self-identity dimension was comprised of the items from the sign value used by Gahwiler and Havitz and from the self-expression factor employed by Kyle et al. (2004). For the risk dimension, four items selected from the risk probability and risk consequence factors used by Gahwiler and Havitz were employed. The leisure involvement scale for content validity is depicted in Table 31 Leisure habit scale : Second, for the leisure habit scale, this study u sed the items adapted from the self-reported habit index (SRHI) including regularity, lack of awareness, lack of control and mental efficiency components developed by Verpl anken and Orbell (2003). Verplanken and Orbell used test-retest to establish the reliabilit y of the index. The results indicated a high internal reliability in which the Cronbach’s alphas of the pretest and posttest were .89 and .92,

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92 and a high test-retest reliability reporting a sign ificant correlation of .91 ( p <.001) between two the tests. While Verplanken and Orbell (2003) measu red the habit items as a single factor, however, this study considered the habit construct as multidimensional because several researchers including Verplanken and Orbell have of ten demonstrated three main characteristics of habit, lack of awareness, frequent and resistant (i.e., lack of control ) in their studies (Aarts, et al., 1997; Betsch, et al., 1998; Honkanen, et al., 2005; Wood, et al., 2002). Accordingly, the adapted 12 habit items were categorized into three factors: automatic including four items, regular including five items, and resistant including three items. Leisure habit scale for cont ent validity is presented in Table 3-2. Vacation motivation scale : Third, for the vacation motivation scale, the res earcher extracted 32 items, a shorter version of the LMS su ggested by Beard and Ragheb (1983), representing the socializing domain including eight items, the competency/mastery domain including eight items, the stimulus avoidance domain including eight items, and the intellectual domain including eight items from the 48 Leisure Mo tivation Scale (LMS) items developed by Beard and Ragheb. The leisure motivation scale has been widely used in leisure studies and was applied to tourism by Ryan and Glendon (1998). The four motivation factors identified by Beard and Ragheb have high Cronbach’s coefficient alphas in the leisure realm: socializing (a = .92), competency/mastery (a = .91), stimulus avoidance (a = .90) and intellectual (a = .90). The four motivation factors applied to tourism by Ryan and G lendon (1998) also had reasonable Cronbach’s alphas: social (a = .81), competency/mastery (a = .64), stimulus avoidance (a = .76) and intellectual (a = .69). The vacation motivation scale for content validity is presented in Table 3-3.

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93 Vacation behavior scale : Last, for the vacation behavior scale, six vacati on participation items were adapted from the leisure participation s cale used by Ragheb and Tate (1993) and the self-report leisure behavior items used by StantonRich and Iso-Ahola (1998). Ragheb and Tate’s original six items are related to regularity and co mmitment of leisure participation (a =.89) and Stanton-Rich and Iso-Ahola’s original six items ref er to regularity and social networks of leisure behaviors (a =.73). The vacation behavior items adapted from bo th the scales were reworded to be applied to vacation behavior. In addition, five decision behavior items were adapted from eight decisional involvement items (i.e., its relia bility (a) was .83) developed by Verplanken, Aarts, van Knippenberg, and van Knippenberg (1994). These decisional behavior items were reworded for vacation decision behavior. The vacati on behavior scale is illustrated in Table 4-4. Content validity analysis Two methods were used to analyze the data for conte nt validity: one sample t-test and Content Validity Index (CVI) suggested by Davis (19 92). For the one sample t-test, the average score and standard deviation of each item as evalua ted by the 12 experts were analyzed. All scores were found to be significant at the p < .001 level. The mean values that are 3.0 (= acceptable ) or above were deemed valid. The results showed th at the mean scores of all the items were higher than 3.0 in the relevance, repres entativeness, and clarity criteria but one item (i.e., “this leisure activity makes me feel weird i f I do not do it”). This item is part of the resist ant domain of leisure habit scale and attained an avera ge of 2.80 with its clarity. Several panel experts suggested that the word, “weird” should be changed to “strange” or other words. The one sample t-test content validity results are presente d in Table 3-5. The CVI was used to access the extent to which the experts agreed with relevance, representativeness, and clarity in relation to its associated factor. For this assessment, all scores

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94 rated on a 5 point scale were changed to dummy vari ables. “ Unacceptable ” and “ poor ” were grouped into disagreement (=0), whereas “ acceptable ,” “ good ” and “ excellent ” were included in agreement (=1). According to Davis (1992), to measu re the CVI, the total number of agreement (i.e., the number of experts who agreed on each ite m) was divided by the total number of agreement and disagreement (i.e., the total number of experts). A score of .80 or more was considered valid (Lynn, 1986). The CVI measure is u seful to obtain information concerning the level of agreement of the expert members regarding each item. However, this measure is more conservative than one sample t-tests. The results s howed that all four of the items of the risk dimension of the leisure involvement scale were hig her in disagreement than the other dimensions in all the relevance, representativeness and clarity criteria, ranging from .42 to .67. Of the regular dimension of the leisure habit scale, the item, “t his leisure activity is typically me” was rated low in its agreement of relevance, re presentativeness and clarity, ranging from .50 to .58. The item, “this leisure activity makes me f eel weird if I do not do it” from the resistant dimension of leisure habit scale also had low agree ment scores on the three criteria, ranging from .58 to .67. Of the vacation motivation scale, around half of the expert members disagreed that the items, “to be active” and “to keep in shap e physically” are relevant to (.67 and .58) or representative of (.58 and .58) the competence/mastery domain. More than half of the experts disagreed that the item, “to unstructure my time” h ad clarity (.42). Around half of them also disagreed with the clarity of the item, “there is n o doubt in my mind about taking part in my favorite vacation activity” in the decision behavior domain (.58) of the vacation behavior scale. The CVI content validity results are reported in Ta ble 3-6 Along with rating on the items, quantitatively, the expert panel members also provided open-ended feedback. Their comments were mainly rel ated to the reasons why certain items

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95 were scored low and they provided suggestions about better wording. For example, in terms of the leisure involvement scale, for the item “I woul d rather do my favorite leisure activity than do most anything else,” a suggestion was made to elimi nate the word, “most.” One of the experts pointed out that the item, “I enjoy discussing my f avorite leisure activity with my friends and family” was double-barreled and therefore, was chan ged to “my friends or family” for the final version of the Alumni survey. A few members pointed out singular-plural conflicts. One of the experts suggested that two items included in the self-identity domain of the leisure involvement scale seemed to be more associated with social iden tity and identity would be better divided into social identity and self-identity Considering this suggestion, on the basis of rele vant literature, several items were newly created for the two factor s, social identity and self-identity in the final survey. The risk dimension had entirely low scores in the content v alidity analysis. The problems raised by many experts were that “risk” seems not t o be a relevant measure of involvement with leisure activity and the “risk” items are not reall y related to “risk” meanings. Another expert suggested that the “interest” item should be includ ed in the hedonic domain. For the final survey, the risk dimension was excluded from the leisure involvemen t scale and “interest” was moved to the hedonic domain. The revised final questionnaire is shown i n Table 3-7. The main concerns with habit items were related to wording. For example, as the experts suggested, “this leisure activity belongs to my rou tine” was reworded to “this leisure activity is a part of my routine” and “this leisure activity make s me feel weird if I do not do it” was changed to “I feel strange if I do not participate in this activity.” According to the suggestions of using partially automatic characteristics instead of tota lly unconscious characteristics, the item “I do not need any effort to think about doing this leisu re activity” was modified to “I do not need much of an effort to think about doing this activit y” and “I do this activity without thinking” was

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96 changed to “I do this activity without much thinkin g.” Furthermore, the item, “this leisure activity is typically me” was removed as the item w as evaluated as unsuitable for the regular factor (Table 3-8). The vacation motivation scale suggestions were made to reduce its length by eliminating the items with lower factor loadings presented in t he original article of Beard and Ragheb (1983). Moreover, some “double-barreled” items pointed out by several experts had lower factor loadings in Beard and Ragheb’s (1983) original stud y. For the final survey, 18 items of 32 leisure motivation scale (LMS) items were employed. As it w as pointed out that the items, “to be active” and “to keep in shape physically” are not suitable for the competence/mastery factor, a new factor name, active/competence was generated. The revised vacation motivation sca le is presented in Table 3-9. Likewise, the vacation beha vior items were also reworded on the basis of feedback, but there were minor changes such as “tak e an adequate amount” to “spend an adequate amount,” “useless” to “frustrating,” and “ usually find” to “attempt to find.” The revised vacation behavior scale is shown in Table 3-10. On the whole, the items that had low scores in the quantitative evaluation and had suggestions for modification in the open-ended comm ents were changed or deleted and furthermore, new items and factors were created. Mo re specifically, the items that received the negative feedback in the assessment of clarity were reworded on the basis of the experts’ comments, whereas the names of factors were changed for the items with low scores in the assessment of relevance and representativeness. Bes ides the modification of the given scales, other questions to be included in the final survey were modified, following the suggestions of experts. One member of the expert panel suggested s pecifying each degree of a 7-point Likert scale (i.e., 1= strongly disagree 2= disagree 3= somewhat disagree 4= neither 5= somewhat agree

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97 6= agree and 7= strongly agree ) across all the scales of the four constructs. Aft er all modifications, face validity was assessed by three faculty members and three doctoral students of the Department of Tourism, Recreation and Sport Managem ent of the University of Florida for the revised questionnaire. In the final survey, simple words were chosen, inst ead of complicated or pedantic words and vague words were avoided. Double-barreled items were revised as previously discussed. To eliminate biased results from unequal comparison, t he number of positive and negative options included in a question was made equal and both side s of psychological perception were equally stated such as two options of agreement at each sid e, for example, strongly agree and agree at one side, and strongly disagree and disagree at the other side. To avoid an order impact, the items within one factor were separately distributed to be mixed with other items included in other factors. The brief instructions and explanati ons about the terms (e.g., the difference between leisure and vacation) were provided to guid e the respondents because of the need for clarity with a self-administered survey. Data Collection Procedures The researcher contacted the Alumni Association of the University of Florida in January 2008 and received access to the database as a membe r of the UF Alumni Association on 6th February 2008. The informed consent, protocol and r elevant documents (i.e., the survey questionnaire and an email cover letter) were appro ved by the Institutional Review Board (IRB) on 10th October 2008 (Appendix D). The informed consent i ncluded the study purpose, the study benefits, participation without compensation, volun tary participation, confidentiality, security, a chance to withdraw without penalty and an assumptio n that no potential risks were associated with participation. The informed consent also infor med them that their responses would not be linked to their names and would automatically go in to a database file. On 20th October 2008, an

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98 email cover letter and the informed consent were di stributed via e-mail to 7,313 members that were drawn using systematic random sampling procedu res from the list of the UF Alumni Association database. The email cover letter reques ted that the email recipients take part in the study and then, if they agreed to participate in th e survey, they were asked to read the informed consent located below the email cover letter and ac cess the URL housing the link to the survey that was posted on the College of Health and Human Performance website of the University of Florida. To increase the response rate, the email message wa s personalized by using each member’s name instead of just calling them ‘UF Alumni member s’ (Dillman, 2000). The email message was also designed to be respondent-friendly by emph asizing their identity as UF alumni members such as being part of the Gator Nation (e.g ., “go gators!” as a closing). In addition, the email message stressed why their participation in t he survey would be important. Each email cover letter also contained information about the s tudy purpose, voluntary participation and instructions to access the URL. Furthermore, the re spondents were informed that if they were interested in seeing the results of the study, the principal investigator would share a summary of the results with them. Seven days after the first e-mail, a follow up mess age was sent to all of the respondents, with the exception of those who were unwilling to p articipate, on 27th October 2008. This message was to thank the participants who had alrea dy completed the questionnaire, and to serve as a reminder to participate for those who had not yet done so. However, as 4,353 of 7,313 email addresses were found to be undeliverable due to inc orrect addresses or system errors, the researcher decided to draw new email addresses from the data base list. Every 25th name was selected, but from a different starting point in a list consisting of individuals who had not been

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99 selected during the first wave of sampling. The sur vey was sent to 500 new members on 2nd November 2008 and later a reminder was emailed to t hem on 6th November 2008. However there were around 378 undeliverable email addresses as we ll. From the entire sample, six respondents emailed back to decline participating. The on-line survey was closed on 1st December 2008. Excluding undeliverable emails, 703 out of 3082 sur veys were received and the response rate was 23%. Out of 703 respondents, the original numbe r of participants classified as active leisure and active vacationers were 322. However, six surve ys of the 322 were incomplete. Accordingly, the final usable sample was 316. The participants c onsist of both sport tourists ( n = 183) and tourist sports ( n = 133). Sport tourists are defined as those who travel to p articipate in sports, physical activities and active outdoor recreation as a primary motivation, whereas tourist sports are defined as those who participate in sports, physical activities and active outdoor recreation while on vacation but their primary motivation is to travel (Gammon & Rob inson, 1997). Some tourist sports from the study sample reported their favorite vacation is to visit family or friends but this motivation does not reflect what kind of favorite activities they p articipate in during these vacations. Therefore, as a supplementary question, the respondents were a lso asked to describe the favorite activities they mainly take part in with their family or frien ds during their visits. Those who answered their favorite activities were related to sports, physica l activities and active outdoor recreation while on vacation were included in the study target sampl e. In addition, other tourist sports from the study sample described their favorite vacation acti vities as “hiking to explore (or along with exploring) new places,” “walking or hiking or campi ng or swimming to spend time with their family or friends,” and “golf/hiking/camping to enj oy new scenery (or with sightseeing).” As an additional step, to determine whether sport tourism and tourism sport should be combined or not,

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100 confirmatory factor analysis and structural equatio n modeling of the constructs (i.e., leisure involvement, leisure habit, vacation motivation, va cation behavior) of both the samples were separately implemented and the results were compare d. Notwithstanding that the mean value of physical motivation of sport tourists was slightly higher than that of tourist sports, the confirmatory factors and causal path patterns of bo th groups were almost the same. Accordingly, using both groups consisting of sport tourists and tourist sports was ultimately determined. The on-line survey was designed following Dillman’s (2000) survey design rules. The words suitable for the online survey were employed. For example, instructions such as “please select one answer” instead of “please circle one an swer” were used. Since the existing on-line survey service companies can rarely offer designs s pecialized by customers’ needs, the researcher designed the web-survey using HTML (Hype rtext Mark-up Language) because the web survey design and its image influence the respo nse rate (Dillman, 2000). The web-survey was designed to display the UF logo with the specia lized colors and format and was posted on the UF Health and Human Performance College web-sit e. In addition, all the questions of the survey were displayed on one screen, instead of mul tiple screens so that participants could perceive the structural organization of questions a nd thus, expect the end of the questions. This design may help decrease missing values. If partici pants can predict the length and the organization of the survey beforehand, they do not tend to discontinue it in the middle of filling out the survey. Participants The sample size was 316. More than half of the resp ondents (55.3%, n = 172) were male and 44.7% ( n = 139) were female. Their average age was 45.18 ye ars ( SD = 12.69) ranging from 18 to 77 years. Of the respondents, one respondent (0.3%) was 18 years old, 12.4% ( n = 39) aged between 20 and 29 years, 23.5 % ( n = 74) aged between 30 and 39 years, 23.5% ( n = 74) were

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101 between 40 and 49 years of age, 26.0% ( n = 82) were between 50 and 59 years of age, and 11. 4% ( n = 36) were between 60 and 69 years of age. A very small number of the respondents (2.9%, n = 9) were in the 70-79 year-old group. When the res pondents were asked to describe their highest level of education, 42.4% ( n =133) reported they had earned a bachelor’s degree followed by a master’s degree (28.7%, n = 90), a M.D/J.D. or equivalent (15.0%, n = 47) and a Ph.D/Ed.D. or equivalent (9.6%, n = 30). A small percentage of the respondents (2.9% n = 9) answered other (i.e., Ed.S., D.M.D. specialist, pos t-graduate degree, DVM, post M.D. training) and one respondent (0.3%) reported being a high sch ool graduate. When their current employment status was asked, the majority of respon dents (76.6%, n = 242) reported they were employed full time. However, a small number of the respondents reported other employment statuses: employed part-time (8.5%, n = 27), retired (7.3%, n = 23), other (i.e., stay at home mom, self-employed, etc) (5.7%, n = 18), full time student (3.2%, n = 10), unemployed (2.2%, n = 7) and part-time student (1.6%, n = 5). In terms of their total income from all sour ces in 2007, 30.4% ( n = 92) reported their total income to be $150,001 o r more and 14.5% ( n = 44) indicated their income was between $90,001 and $110,000, foll owed by $110,001-$130,000 (12.9%, n = 39), $50,001-$70,000 (12.5%, n = 38), $30,001-$50,000 (10.2%, n = 31), $70,001-$90,000 (9.6%, n = 29), $130,001-$150,000 (6.3%, n = 19) and $30,001 or less (3.6%, n = 11). When asked about their racial or ethnic background, the majority of participants (87.5%, n = 272) were white, not of Hispanic origin. A small number of the respondents (5.1%, n = 16) were Hispanic, followed by Asian or Pacific Islande r (2.9%, n = 9), black, not of Hispanic origin (2.3%, n = 7), other (i.e., Arabic, Irish Polish, etc) (1.3 %, n = 4) and multiracial (1.0%, n = 3). In terms of the current state of residence, almost all the respondents (96.8%, n = 306) reported their current resident country to be the United States, w hereas a few respondents (3.2%, n = 10)

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102 resided in other countries (i.e., Ethiopia, France, Germany, Hungary, Kazakhstan, Korea, Switzerland, Netherland, etc). Of the US resident r espondents, the most frequently reported state was Florida (53.8%, n = 170), whereas the remaining respondents were alm ost equally distributed among 30 states (i.e., Georgia, 7.9%, n = 25; North Carolina, 4.4%, n = 14; California, 3.8%, n = 12; Virginia, 3.2%, n = 10; New York, 2.8%, n = 9; Maryland, 2.5%, n = 8; Texas, 1.9%, n = 6; Tennessee, 1.9%, n = 6; Pennsylvania, 1.9%, n = 6; Alabama, 1.6%, n = 5; etc). The demographic characteristics are depicted in Table 3 -11. Data Analysis All analyses in this study were conducted with SPSS 15.0 (George & Mallery, 2007) and LISREL 8.51/PRELIS 2.30 (Joreskog, 1993). The descr iptive statistics (e.g., frequency) and ANOVA for the research questions were analyzed usin g SPSS 15.0. Confirmatory factor analysis (CFA) was used to test the fit of the measurement m odel and structural equation modeling (SEM) was used to test the causal relationship betw een latent variables using LISREL 8.51. In addition, Cronbach’s alpha coefficients () of the constructs were tested using SPSS 15.0. Th e asymptotic covariance matrix to be used for ordinal variables in the CFA models was obtained running PRELIS 2.50 included in LISREL 8.51. Structural equation modeling assumes causal relatio nships between latent variables on a basis of a measurement model (Kline, 2005). That is the SEM is a combination of factor, path and regression analyses (Bollen, 1989). The latent variables are indirectly measured from the observed variables in the measurement model and the significance of causal relationships between the latent variables is tested. Though a me asurement model should be specified and if necessary, should be respecified prior to structura l equation model, both measurement and structural equation model have three broad steps to be implemented: model specification, model assessment and model respecification (Byrne, 1998).

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103 First, in the model specification step, by theoreti cal rationale and justification, researchers should determine which observed variables represent each latent variable. There may be a correlation between exogenous or endogenous variabl es, but usually correlations between endogenous variables are discouraged (Hair et al., 2003). The correlation matrix is widely utilized in many applications using continuous vari ables rather than the covariance matrix on account of its standardized unit of coefficients to be directly compared across different variables. However the polychoric correlation matrix and asymp totic covariance matrix should be employed for ordinal variables. The PRELIS program serves to obtain the asymptotic covariance matrix and the polychoric correlation matrix, but a ll missing variables should be treated before the use of PRELIS because this program makes it imp ossible to run it with any missing data. In addition, while the maximum likelihood (ML) estimat ion is performed for continuous variables, the diagonally weighted least squares (DWLS) estima tion method should be conducted for ordinal variables (Joreskog, 1993). Second, the suitability of parameter estimates, the appropriateness of standardized errors, the statistical significance of parameter estimates and the overall model fit should be assessed. The parameters that have negative variances, correl ations higher than 1.00 and non-positive definite covariance or correlation matrices are con sidered unreasonable (Bryne, 1998). Moreover if the model has extremely large or small standardi zed errors, it leads to a poor fit. The zero residuals assume the perfect fit. Accordingly, the standardized residuals greater than + 2.58 are deemed to be large and in contrast, the values less than -2.58 are considered to be small. In terms of statistical significance of parameter estimates, the t-statistic value should be over 1.96 at a significance level of p <0.05. The non-significant parameters imply that t hose parameters make little contribution to the model (Byrne, 1998). For the overall model fit, the Likelihood Ratio

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104 Test statistic is demonstrated by chi-square ( c2). The significance of chi-square value means the rejection of the null hypothesis that the model is valid. Nevertheless, as the Likelihood Ratio Test is highly sensitive to sample size, any non-sa turated model with a large sample is rejected albeit adequate. Therefore, the chi-square values s carcely serve to examine the overall model fit, but are utilized for the model comparison (Kline, 2 005). The suggested main indexes to test the overall model fit are the root-mean square-error of approximation, RMSEA (Steiger & Lind, 1980) with a 90% confidence interval, the standardi zed root mean square residual, SRMR (Hu & Bentler, 1995), the comparative fit index, CFI (Ben tler, 1990) and the non-normed fit index, NNFI (Bentler & Bonett, 1980). The better the fit, the closer the RMSEA and SRMR v alues are to 0.00 and the closer the NNFI and CFI values are to 1.00. In terms of RMSEA and SRMR cutoff points, values less than 0.05 represent good fits, values between 0.08 and 0 .10 indicate acceptable fits, and values higher than 0.10 are considered to be poor fits (Browne & Cudeck, 1992a, 1992b; MacCallum, Browne, & Sugawara, 1996). NNFI and CFI values greater than 0.90 indicate acceptable fits (Bentler, 1992). As additional indices, the Goodness of Fit I ndex (GFI) and Adjusted Goodness of Fit Index (AGFI) are absolute indices ranging from 0.00 to 1.00 and the closer both the values are to 1.00, the better the fit. The expected cross-valida tion index (ECVI) indicates the probability that the model can be valid across different groups (i.e ., similar sample size from the sample population). The model with the smallest ECVI value among the hypothesized model, the saturated model and the independent model have the highest probability of being replicated (Browne & Cudeck, 1992a). Last, the misspecified model should be respecified. Deleting indicators is one way to be respecified and the other way of respecification is that the errors are allowed to correlate, which

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105 should be underpinned by theories or rationales (Jo reskog, 1993). Residuals and modification indices are two main sources to identify misfits in the model. Standardized residuals exceeding 2.58 are a baseline for respecification. The second source is the modification indices that represent how appropriately the hypothesized model is described. The largest modification index may often be associated with the largest expected c hange value (Saris, Satorra, & Sorbom, 1987). On the baseline of large residuals and large expect ed change values, the researcher should determine how the model can proceed to be respecifi ed. If the variables related to the largest modification index are so critical that it is hard for them to be eliminated, the next largest modification index could be used for the respecific ation. Cronbach’s alpha coefficients () and composite reliability (CR) have been widely u sed to estimate the reliability of confirmatory factors. A recommended cut off point of Cronbach’s alpha coefficients is greater than 0.70 (Nunnally, 1978; Nunnally & Bernstein, 1994). However, provided that the number of items is less than six, alpha coefficients greater than 0.60 are considered acceptable (Cortina, 1993). The square o f the sum of standardized factor loadings divided by the sum of indicator errors added to the square of the sum of standardized factor loadings constitutes composite reliability (CR). Fo rnell and Larker (1981) suggested that a composite reliability (CR) greater than 0.7 as adeq uate, but later Bagozzi and Yi (1988) recommended that a cutoff point of 0.6 should be co nsidered reasonable. For convergent validity, the average variance extra cted (AVE) is offered, being calculated as the sum of squared standardized loadings divided by the sum of squared standardized loadings added to the sum of indicator measurement error. Th e AVE value that is greater than 0.5 is deemed acceptable (Bagozzi, 1994; Fornell & Larker, 1981). In spite of the general usage of CR and AVE, Fornell and Larker (1981) did not manifest how to calculate CR and AVE under the

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106 correlated errors. Another criterion for convergent validity is factor loadings. T-statistics for factor loadings ( l ) greater than 1.96 at a significance level of p <0.05 are regarded as significant. For obtaining discriminant validity, the correlatio ns between variables should be less than 0.85 (Kline, 2005). After the assessment of the measurement model fit a nd structural equation model fit, a comparison between a full model (i.e., every exogen ous and endogenous variables have arrows to every endogenous) and several nested models woul d be conducted. To compare both models, the null hypothesis assumes that the nested model f its the data, whereas the target hypothesis has an assumption that the full model fits the data. Un less the null hypothesis is rejected after the difference between two chi-squares and degrees of f reedom is tested, it is implied that the nested model fit is better than the full model. On the con trary, given the rejection of the null hypothesis, the full model is deemed a better model.

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107 Table 3-1. Leisure involvement scale for content va lidity Hedonic My favorite leisure activity is pleasurable I really enjoy my favorite leisure activity Participating in my favorite leisure activity is on e of the most satisfying things that I do Central I attach great importance to my favorite leisure ac tivity My favorite leisure activity interests me a lot I find a lot of my life is organized around my favo rite leisure activity My favorite leisure activity has a central role in my life I would rather do my favorite leisure activity than do most anything else My favorite leisure activity reflects my life style Social Most of my friends are in some way connected with m y favorite leisure activity I enjoy discussing my favorite leisure activity wit h my friends and family Most of my family members are in some way connected with my favorite leisure activity My favorite leisure activity provides the chance to socialize with my friends Self-identity My favorite leisure activity reflects who I am My participation in my favorite leisure activity te lls something about me I can tell things about a person by seeing them par ticipating in the favorite leisure activity When I participate in my favorite leisure activity, others see me the way I want them to see me Risk It is not complicated to choose my favorite leisure activity over other activities Whenever I participate in my favorite leisure activ ity, I am confident that it is the right activity choice When I mistakenly choose to do other activities ins tead of my favorite leisure activity, it really matters to me If I participated in my favorite leisure activity a nd my choice proved to be poor, I would be upset

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108 Table 3-2. Leisure habit scale for content validity Regular I take part in this leisure activity frequently I have been taking part in this leisure activity fo r a long time This leisure activity belongs to my routine This leisure activity is typically “me” Automatic I do this leisure activity automatically I do this leisure activity without thinking I start doing this leisure activity before I realiz e I am doing it I do this leisure activity without having to consci ously remember I do not need an effort to think about doing this l eisure activity. Resistant This leisure activity would require effort not to d o it I would find it hard not to take part in this leisu re activity This leisure activity makes me feel weird if I do n ot do it

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109 Table 3-3. Vacation motivation scale for content va lidity Socializing To build friendships with others To interact with others To develop close friendships To meet new and different people To reveal my thoughts, feelings, or physical skills to others To be socially competent and skillful To gain a feeling of belonging To gain other’s respect Competence/Mastery To challenge my abilities To be good in doing them To improve my skill and ability in doing them To be active To develop physical skills and abilities To keep in shape physically To use my physical abilities To develop physical fitness Stimulus-Avoidance To slow down Because I sometimes like to be alone To relax physically To relax mentally To avoid the hustle and bustle of daily activities To rest To relieve stress and tension To unstructure my time Intellectual To learn about things around me To satisfy my curiosity To explore new ideas To learn about myself To expand my knowledge To discover new things To be creative To use my imagination

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110 Table 3-4. Vacation behavior scale for content vali dity Vacation participation I take an adequate amount of vacation to take part in my favorite vacation activity each year I schedule vacation related to my favorite vacation activity regularly I have a network of friends with whom I travel to t ake part in my favorite vacation activity Whenever I take a vacation, I am usually involved i n my favorite vacation activity Whenever I take a vacation, I usually take a chance to improve my favorite vacation activity Whenever I visit my family and friends, I usually s pend time taking part in my favorite vacation activity with them Vacation decision The trips that immediately come to mind are usually related to my favorite vacation activity There is no doubt in my mind about taking part in m y favorite vacation activity I think it is useless to expend time and energy fin ding out about other activities instead of my favorite vacation activity I usually expend effort finding out which place is the best to take part in my favorite vacation activity I usually find detailed information about taking pa rt in my favorite vacation activity

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111 Table 3-5. One sample t-test for content validity Relevance Representativeness Clarity Variable name ( N =12) Ma SD t ( ** ) Ma SD t ( ** ) Ma SD t ( ** ) Involvement Hedonic Pleasure 4.50 .522 29.850 4.50 .522 29.850 4.42 .793 19.294 Enjoy 4.75 .452 36.382 4.67 .492 32.833 4.75 .452 36.382 Satisfy 4.09 1.044 12.990 4.00 1.206 11.489 4.17 1.030 14.015 Central Important 4.08 .996 14.199 4.33 .985 15.244 3.92 1.165 11.651 Interest 4.25 .866 17.000 4.17 .937 15.397 4.33 .778 19.282 Organize 4.58 .669 23.748 4.67 .651 24.819 4.58 .669 23.748 Central 4.58 .669 23.748 4.67 .651 24.819 4.50 1.000 15.588 Rather do 4.50 .674 23.121 4.33 .778 19.282 4.33 .778 19.282 Lifestyle 4.25 1.138 12.935 4.25 1.138 12.935 3.58 1.564 7.935 Social Friend connect 4.50 .674 23.121 4.58 .669 23.748 4.25 1.055 13.951 Discuss 4.75 .452 36.382 4.75 .452 36.382 4.50 .798 19.541 Family connect 4.42 .793 19.294 4.58 .669 23.748 4.33 1.155 13.000 Socialize 4.67 .492 32.833 4.67 .651 24.819 4.83 .389 43.014 Self-identity Who I am 4.58 .669 23.748 4.67 .651 24.819 4.50 .798 19.541 Tell something 4.58 .669 23.748 4.58 .669 23.748 4.17 1.267 11.389 See them 3.42 1.165 10.164 3.58 1.311 9.466 3.73 1.555 7.950 See me 4.25 .866 17.000 4.33 .888 16.912 3.92 1.311 10.346 Risk Complicated 3.08 1.443 7.400 3.42 1.505 7.864 3.17 1.586 6.917 Confident 3.33 1.497 7.711 3.50 1.567 7.739 3.50 1.624 7.467 Mistakenly 3.08 1.443 7.400 3.25 1.545 7.288 3.17 1.467 7.479 Poor 3.08 1.564 6.828 3.33 1.614 7.153 3.25 1.913 5.886 Habit Regular Frequent 4.58 .669 23.748 4.67 .492 32.833 4.58 .669 23.748 Long time 4.50 .798 19.541 4.50 .798 19.541 4.33 .888 16.912 Routine 4.33 .985 15.244 4.42 .996 15.358 3.42 1.311 9.025 Typical 3.00 1.706 6.093 3.17 1.642 6.680 3.08 1.621 6.588 Automatic Automatic 3.92 1.676 8.093 4.00 1.537 9.013 3.75 1.545 8.409 Without thinking 4.08 1.564 9.043 4.00 1.595 8.685 3.67 1.557 8.158 Realize 4.00 1.279 10.832 3.92 1.379 9.839 3.92 1.165 11.651 Conscious 3.83 1.528 8.693 3.83 1.528 8.693 3.33 1.371 8.424 No effort 3.83 1.642 8.086 3.83 1.642 8.086 3.50 1.784 6.797 Resistant Effort not 3.92 1.443 9.400 3.92 1.443 9.400 3.08 1.782 5.995 Hard not 4.42 .996 15.358 4.42 .996 15.358 4.08 1.379 10.258 Weird 3.50 1.508 8.042 3.50 1.508 8.042 2.83 1.749 5.610 Motivation Socializing Friendship 4.67 .651 24.819 4.75 .622 26.472 4.75 .452 36.382 Interact 4.83 .389 43.014 4.83 .389 43.014 4.83 .389 43.014 Close 4.75 .452 36.382 4.83 .389 43.014 4.83 .389 43.014 New people 4.75 .452 36.382 4.75 .452 36.382 4.75 .452 36.382 Reveal 3.58 1.165 10.660 3.92 1.084 12.521 3.75 1.138 11.413 Socially 3.83 1.030 12.894 4.00 1.128 12.282 3.58 1.084 11.455

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112 Table 3-5. Continued. Relevance Representativeness Clarity Variable name ( N =12) Ma SD t ( ** ) Ma SD t ( ** ) Ma SD t ( ** ) Motivation Belonging 4.67 .492 32.833 4.50 .674 23.121 4.67 .492 32.833 Respect 4.00 1.206 11.489 3.92 1.240 10.941 3.83 1.115 11.913 Competence Challenge 4.58 .669 23.748 4.58 .669 23.748 4.50 .798 19.541 /mastery Good 4.08 .900 15.711 4.17 .937 15.397 3.33 1.614 7.153 Improve 4.67 .651 24.819 4.58 .669 23.748 4.00 1.477 9.381 Active 3.58 1.676 7.404 3.50 1.732 7.000 4.00 1.477 9.381 Develop physical 4.67 .651 24.819 4.67 .651 24.819 4.67 .492 32.833 Shape 3.42 1.564 7.566 3.42 1.564 7.566 4.08 1.311 10.786 Use physical 4.09 1.221 11.112 4.09 1.221 11.112 4.45 1.036 14.264 Fitness 3.83 1.337 9.931 3.83 1.337 9.931 4.33 .985 15.244 Stimulus Slow 4.25 .965 15.252 4.33 .985 15.244 4.08 1.084 13.053 /avoidance Alone 4.00 1.348 10.276 4.08 1.379 10.258 4.42 .793 19.294 Physical relax 4.58 .900 17.635 4.58 .900 17.635 4.75 .452 36.382 Mental relax 4.58 .900 17.635 4.58 .900 17.635 4.67 .651 24.819 Avoid 4.67 .651 24.819 4.67 .651 24.819 4.58 .900 17.635 Rest 4.33 .985 15.244 4.50 .905 17.234 4.58 .900 17.635 Relieve 4.67 .651 24.819 4.67 .651 24.819 4.75 .452 36.382 Unstructured 3.50 1.314 9.225 3.67 1.303 9.750 3.00 1.537 6.760 Intellectual Learn about 4.42 .900 16.993 4.42 .900 16.993 4.42 1.165 13.138 Curiosity 4.42 .900 16.993 4.42 .900 16.993 4.42 1.165 13.138 Explore 4.50 .798 19.541 4.50 .798 19.541 4.42 1.165 13.138 Learn myself 4.17 1.193 12.094 4.17 1.193 12.094 4.08 1.379 10.258 Knowledge 4.67 .651 24.819 4.67 .651 24.819 4.33 1.231 12.195 Discover 4.50 .798 19.541 4.50 .798 19.541 4.42 1.165 13.138 Creative 4.42 .900 16.993 4.42 .900 16.993 4.25 1.288 11.430 Imagination 4.17 1.115 12.949 4.17 1.115 12.949 4.00 1.414 9.798 Behavior Participation Adequate 4.42 .515 29.712 4.33 .888 16.912 3.67 1.557 8.158 Schedule 4.50 .674 23.121 4.50 .674 23.121 3.83 1.337 9.931 Network 4.33 .985 15.244 4.33 .888 16.912 4.17 1.267 11.389 Usually 4.75 .452 36.382 4.75 .452 36.382 4.67 .651 24.819 Chance 4.58 .669 23.748 4.42 .996 15.358 3.92 1.505 9.015 Spend time 4.33 .778 19.282 4.42 .793 19.294 4.25 1.055 13.951 Decision Immediately 4.75 .452 36.382 4.75 .452 36.382 4.42 .793 19.294 Doubt 4.08 1.165 12.147 4.00 1.206 11.489 3.33 1.670 6.916 Frustrating 4.17 .937 15.397 4.08 .996 14.199 3.42 .996 11.881 Place 4.67 .492 32.833 4.75 .452 36.382 4.50 .905 17.234 Information 4.67 .492 32.833 4.75 .452 36.382 4.33 .888 16.912 a Mean score based on a 5-point scale where 1 equals unacceptable, 2 equals poor, 3 equals acceptable, 4 equals good and 5 equals excellent ** p < .01

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113 Table 3-6. CVI agreement measures for content valid ity Variable names Relevance a Representativeness a Clarity a Involvement Hedonic Pleasure 1.00 1.00 1.00 Enjoy 1.00 1.00 1.00 Satisfy .83 .83 .92 Central Important .92 .92 .83 Interest .92 .92 1.00 Organize 1.00 1.00 1.00 Central 1.00 1.00 .92 Rather do 1.00 1.00 1.00 Lifestyle .83 .83 .67 Social Friend connect 1.00 1.00 .92 Discuss 1.00 1.00 1.00 Family connect 1.00 1.00 .83 Socialize 1.00 1.00 1.00 Self-identity Who I am 1.00 1.00 1.00 Tell something 1.00 1.00 .92 See them .83 .83 .75 See me .92 .92 .83 Risk Complicated .50 .58 .58 Confident .58 .58 .67 Mistakenly .50 .50 .67 Poor .42 .50 .58 Habit Regular Frequent 1.00 1.00 1.00 Long time 1.00 1.00 1.00 Routine .92 .92 .75 Typical .50 .50 .58 Automatic Automatic .75 .75 .67 Without thinking .83 .83 .67 Realize .92 .83 .83 Conscious .75 .75 .67 No effort .75 .75 .67 Resistant Effort not .83 .83 .58 Hard not .92 .92 .83 Weird .67 .67 .58 Motivation Socializing Friendship 1.00 1.00 1.00 Interact 1.00 1.00 1.00 Close 1.00 1.00 1.00 New people 1.00 1.00 1.00 Reveal .83 .92 .83 Socially .92 .92 .83 Belonging 1.00 1.00 1.00

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114 Table 3-6. Continued. Motivation Relevance a Representativeness a Clarity a Respect .83 .83 .92 Competence Challenge 1.00 1.00 1.00 /mastery Good 1.00 1.00 .75 Improve 1.00 1.00 .75 Active .67 .58 .75 Develop physical 1.00 1.00 1.00 Shape .58 .58 .83 Use physical .75 .75 .83 Fitness .75 .75 .92 Stimulus Slow .92 .92 .92 /avoidance Alone .83 .83 1.00 Physical relax .92 .92 1.00 Mental relax .92 .92 1.00 Avoid 1.00 1.00 .92 Rest .92 .92 .92 Relieve 1.00 1.00 1.00 Unstructured .67 .75 .42 Intellectual Learn about 1.00 1.00 .92 Curiosity 1.00 1.00 .92 Explore 1.00 1.00 .92 Learn myself .83 .83 .83 Knowledge 1.00 1.00 .92 Discover 1.00 1.00 .92 Creative 1.00 1.00 .92 Imagination .92 .92 .83 Behavior Participation Adequate 1.00 .92 .75 Schedule 1.00 1.00 .83 Network .92 1.00 .92 Usually 1.00 1.00 1.00 Chance 1.00 .92 .75 Spend time 1.00 1.00 .92 Decision Immediately 1.00 1.00 1.00 Doubt .83 .83 .58 Frustrating .92 .92 .83 Place 1.00 1.00 .92 Information 1.00 1.00 1.00 a Proportion calculated by the number of agreement di vided by the total number (i.e., x /12)

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115 Table 3-7. Revised leisure involvement scale Hedonic I really enjoy my favorite leisure activity Participating in my favorite leisure activity is on e of the most satisfying things that I do My favorite leisure activity is pleasurable My favorite leisure activity interests me a lot Central I attach great importance to my favorite leisure ac tivity I find a lot of my life is organized around my favo rite leisure activity My favorite leisure activity has a central role in my life I would rather do my favorite leisure activity than do most anything else My favorite leisure activity reflects my lifestyle Social Most of my friends or family members are in some wa y connected to my favorite leisure activity I enjoy discussing my favorite leisure activity wit h my friends or family My favorite leisure activity provides the chance to socialize with my friends or family Self-identity Participation in my favorite leisure activity says something about me My favorite leisure activity reflects who I am My favorite leisure activity is an important part o f who I am Social identity Other people see an important side of me when I par ticipate in my favorite leisure activity I can tell things about other people by seeing them participating in their favorite leisure activity When I participate in my favorite leisure activity, others see me the way I want them to see me

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116 Table 3-8. Revised leisure habit scale Regular I take part in this activity frequently I have been taking part in this activity for a long time This activity is part of my routine Automatic I do this activity without much thinking I start doing this activity before I realize I am d oing it I do this activity without having to consciously re member it I do not need much of an effort to think about doin g this activity Resistant This activity would require effort not to do it I would find it hard not to take part in this activ ity I feel strange if I do not participate in this acti vity

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117 Table 3-9. Revised vacation motivation scale Socializing To build friendships with others To interact with others To have a good time with friends To develop close friendships To gain a feeling of belonging Active/competence To be active To develop physical skills and abilities To keep in shape physically To develop physical fitness To use my physical abilities Relaxation To relax physically To relax mentally To avoid the hustle and bustle of daily activities To rest Intellectual To learn about things around me To explore new ideas To expand my knowledge To discover new things

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118 Table 3-10. Revised vacation behavior scale Vacation participation I spend an adequate amount of vacation to take part in my favorite vacation activity each year I schedule vacations related to my favorite vacatio n activity regularly I have a network of friends/family with whom I trav el to take part in my favorite vacation activity Whenever I take a vacation, I am usually involved i n my favorite vacation activity Whenever I take a vacation, I usually take a chance to improve my favorite vacation activity Whenever I visit my family/friends, I usually spend time taking part in my favorite vacation activity with them Vacation decision The trips that immediately come to mind are usually related to my favorite vacation activity There is no doubt in my mind about taking part in m y favorite vacation activity I think it is frustrating to expend time and energy finding out about other activities instead of my favorite vacation activity I usually expend effort finding out which place is the best to take part in my favorite vacation activity I attempt to find detailed information about taking part in my favorite vacation activity

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119 Table 3-11. Demographic characteristics of the resp ondents Frequency Percent (%) Gender Male 172 55.3 Female 139 44.7 Total 311 100.0 Age 18 to 19 1 0.3 20 to 29 39 12.4 30 to 39 74 23.5 40 to 49 74 23.5 50 to 59 82 26.0 60 to 69 36 11.4 70 to 79 9 2.9 Total 315 100.0 Mean ( SD ) 45.18 ( SD =12.69) Education High school graduate 1 0.3 Some college 4 1.3 Bachelor's degree 133 42.4 Master's degree 90 28.7 M.D/J.D. or equivalent 47 15.0 Ph.D/Ed.D. or equivalent 30 9.6 Other 9 2.9 Total 314 100.0 Employment ( multiple answers ) Employed full time 242 76.6 Employed part time 27 8.5 Full time student 10 3.2 Part time student 5 1.6 Unemployed 7 2.2 Retirement 23 7.3 Other 18 5.7

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120 Table 3-11. Continued. Frequency Percent (%) Ethnic or racial background White, not of Hispanic origin 272 87.5 Hispanic 16 5.1 Black, not of Hispanic origin 7 2.3 Asian or Pacific Islander 9 2.9 Multiracial 3 1.0 Other 4 1.3 Total 311 100.0 Income $30,000 or less 11 3.6 $30,001-$50,000 31 10.2 $50,001-$70,000 38 12.5 $70,001-$90,000 29 9.6 $90,001-$110,000 44 14.5 $110,001-$130,000 39 12.9 $130,001-$150,000 19 6.3 $150,001 or more 92 30.4 Total 303 100.0

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121 CHAPTER 4 RESULTS The research questions were used to identify the sp ecific types of favorite leisure activities and favorite vacation activities of the respondents The hypotheses served to examine the relationship between leisure involvement, leisure h abit, vacation motivation, and vacation behavior constructs. Types of Leisure Activities Research question 1a : What types of favorite leisure activities do phys ically active people take part in? On the basis of a variety of answers to the open-en ded question about the respondents’ favorite leisure activity, six categories were yiel ded: 1) outdoor-related sports, 2) water-related sports, 3) fitness, 4) golf/ski, 5) team sports, an d 6) other. Table 4-1 presents more specific activities pertaining to given categories. In terms of frequency distribution of respondents in these categories, more people (36.1%, n = 114) were represented in the outdoor-related spor ts category of active leisure than in the water-relate d sports (17.7%, n = 56), fitness (16.8%, n = 53), golf/ski (15.8%, n = 50), team sports (10.8%, n =34) and other (2.8%, n = 9). These results are presented in Table 4-2. Leisure Participation Patterns Research question 1b : What are the participation patterns in the favori te leisure activities of the respondents? Regarding participation frequency in their favorite leisure activity, the respondents were asked to report how many times on average during th e last year (in season) they had participated in their favorite leisure activity. Out of the res pondents, 28.2% ( n = 89) indicated about 1-2 times a week, 23.1% ( n = 73) described about 3-4 times a week, 16.8% ( n = 53) reported about 2-3 times a month and 13.6% ( n = 43) answered that they had participated in their favorite

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122 leisure activity almost everyday during the last ye ar. A low percentage of the respondents (9.8%, n = 31) reported about once a month or less, 7.9% ( n = 25) indicated a few times a year or less and 0.6% ( n = 2) demonstrated they had never participated in. With respect to participation per occurrence, durat ion in their favorite leisure activity, a large percentage of the respondents (64.8%, n = 204) usually participate in their favorite leisu re activity for 61-90 minutes per occasion. Next, 32.7 % ( n = 103) indicated taking part for 30-60 minutes per time. In contrast, a very small percent age of the respondents (2.5%, n = 8) answered they participate in their favorite leisure activity less than 30 minutes per time. When the respondents were asked to report how many years they had been participating in their favorite leisure activity, years of participa tion ranged from 1 to 64 years. More specifically, regarding a breakdown by percentage of participatio n years, 25.0% ( n = 79) indicated 11-20 years and 19.3% ( n = 61) reported 21-30 years, followed closely by 1-5 years (17.7%, n = 56), 31-40 years (14.9%, n = 47), 6-10 years (14.2%, n = 45), 41-50 years (6.6%, n = 21) and 51-64 years (2.2%, n = 7). Types of Vacation Activities Research question 2a : What types of favorite vacation activities do the respondents participate in? Active vacation activities were broken down into se ven subcategories. Like the active leisure categories, outdoor-related sports, water-r elated sports, fitness, golf/ski, team sports and other were identified. However, visiting family and friends was identified as another new category. Table 4-1 reports more detailed informati on of activities included in given categories. Particularly, the respondents in the final category visiting family and friends, reported that they take part in active leisure (i.e., golfing, tennis, hiking, walking, camping, skiing, swimming, water sports, outdoor-related sports, etc) while th ey are visiting family and friends. For example,

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123 these “tourist sports” included outdoor-related spo rts, water-related sports, fitness and golf/ski domains described “hiking/walking to explore some n ew places,” “hiking/swimming/beach activities/sport activities to spend or spending ti me with my family or friends” and “hiking/camping/fishing/golf/ski with sightseeing o r to view new scenery.” Of the 316 respondents, 43.4% ( n = 137) identified outdoor-related sports as their favorite vacation activities. The next highest rated categor y was water-related sports which accounted for 25.9% ( n = 82), followed by golf/ski (19.3%, n = 61), visiting family and friends (8.2%, n = 26), and fitness (1.9%, n = 6). Team sports and other have an equal rating o f 0.6% ( n = 2). The percentage of the total “tourist sports” who partic ipate in sports, physical activities and active outdoor recreation so as to spend time with their f amily and friends, explore something and view new scenery or sightsee was 42% ( n = 133), whereas 58% ( n = 183) could be categorized as sport tourists. The proportion of “tourist sports” in each category were 57.6% ( n = 79) of 137 outdoor activities-related vacationers, whereas “sp ort tourists” were 42.4% ( n = 58); 12.6% ( n = 11) of 82 water sports-related vacationers were “to urist sports” and 87.4% ( n = 71) were “sport tourists”; and 22.9% ( n = 14) of 61 golf/ski-related vacationers were “tou rist sports” and 77.1% ( n = 47) were “sport tourists.” Of the 6 fitness-rela ted vacationers, 50.0% ( n = 3) were involved in tourism sport activities and the remaining half of them 50.0% ( n = 3) were “sport tourists.” Table 4-2 demonstrates these results. Vacation Participation Patterns Research question 2b : What are the vacation patterns of the respondents ? Regarding vacation frequency, when the respondents were asked about how many vacations they take in an average year, the most co mmonly reported number of vacations was 23 vacations (57.1%, n = 180). This was followed by 4-5 vacations (18.7%, n = 59), 1 vacation (13.0%, n = 41), 6-7 vacations (6.0%, n = 19) and 8 or more vacations (4.1%, n = 13). The

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124 number of respondents reporting none was very few ( 1.0%, n = 3). In terms of vacation duration, when the respondents were asked about how long thei r typical vacation is, the most common response was 3-6 days (46.2%, n = 144). Roughly one fourth of the respondents (26. 0%, n = 81) indicated 1 week to be their typical vacation durat ion, followed closely by a 1-2 week vacation (20.2%, n = 63). A few respondents (5.4%, n = 17) reported 1-2 days and 1.3% ( n = 4) indicated 3-4 weeks. The least frequently answered vacation d uration (1.0%, n = 3) was other (i.e., 4-6 weeks, 8 weeks, etc). With regard to vacation companions, when asked abou t who typically accompanies them on vacation, the majority of respondents (75.3%, n = 235) answered their family accompanies them and 17.3% ( n = 54) reported their friends to be their vacation companions. A very small percentage of the respondents (3.8%, n = 12) answered they travel alone. The remaining respondents (3.5%, n = 11) described others such as both friends and fa mily, all answers, or a team. When the respondents were asked if they trav el as a part of a special interest group, the most common response was that they do not travel as a part of a special interest group (82.7%, n = 258), whereas 17.3% ( n = 54) reported they traveled with a special interes t group (i.e., golfing buddies, ski club, softball team, adventure club, m arathon club, outdoor social group, fitness roundtable, fishing buddies, church, boy scouts, al umni, scuba diving group, tennis team, ultimate team, Intrepid, water sport team, rotary v olunteers, fencing team, etc). With respects to their preference for familiar or novel destinations the predominant preference was for new destinations (72.1%, n = 227) rather than familiar destinations (27.9%, n = 88). Similarity between Favorite Leisure and Favorite Va cation Activities Research question 3a : Is there a similarity between the favorite leisur e and favorite vacation activities of the respondents?

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125 Leisure and vacation activity choices were examined to see if participants take part in the same vacation activity as their favorite leisure ac tivity. One third of the respondents (35.6%, n = 112) took part in the same activities in both the l eisure and vacation contexts, whereas 64.2% ( n = 203) were engaged in different favorite activitie s between the two contexts though they still took part in both the active leisure and active vac ations (Figure 4-1). Nevertheless, in terms of similarity between the ca tegories, of the 114 outdoor-related sports participants during leisure, more than two t hirds of them (68.4%, n = 78) indicated their favorite vacation activities were in the outdoor-re lated sports category, whereas 14.0% ( n = 16) took part in water-related sports during vacation. Nearly nine percent (8.8%, n = 10) reported they visited family and friends during their vacati on, followed closely by golfing or skiing during vacation (7.9%, n = 9). One respondent (0.9%) indicated that his or her vacation activity was team sports. Of those who answered that they visit family and friends, 60.0% ( n = 6) reported that outdoor-related sports were their favorite vac ation activities while spending time with their family or friends. Water-related sports (20.0%, n = 2) and golf/ski (20.0%, n = 2) were equally popular vacation activities among the respondents w ho spent time with their family or friends while on vacation. Of the 56 participants who took part in water-relat ed sports during leisure, 64.3% ( n = 36) also took part in water-related sports during vacat ion, whereas 17.9% ( n = 10) reported they participate in outdoor-related sports while on vaca tion, followed by golf/ski (7.1%, n = 4), visiting family and friends (7.1%, n = 4) and fitness (3.6%, n = 2). Specifically, for four of the family or friends visitors, 75.0% ( n = 3) took part in outdoor-related sports with thei r family or friends and one respondent (25.0%) engaged in water -related sports.

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126 Of the 53 leisure participants in fitness, the most commonly reported vacation category was outdoor-related sports (50.9%, n = 27). Next, one fourth of them (24.5%, n = 13) took part in water-related sports as their favorite vacation activities, followed by golf/ski during their vacations (13.2%, n = 7) and fitness (5.7%, n = 3). Of the three respondents (5.7%) who visited family and friends, two people (66.7%) spent time w ith their family or friends, taking part in outdoor-related sports and one person (33.3%) took part in the same fitness activities while visiting family or friends. Of 50 participants in golf/ski as their favorite le isure activities, a large proportion of them (60.0%, n = 30) indicated the same golf/ski category during their vacations, whereas 16.0% ( n = 8) answered that their favorite vacation activities were related to water sports and 14.0% ( n = 7) indicated visiting family and friends. Five people (10.0%) reported their favorite vacation activities to be outdoor-related sports. Of the sev en family or friends visitors, 85.7% ( n = 6) equally enjoyed playing golf or skiing with their f amily and friends, and one visitor (14.3%) took part in outdoor-related sports while visiting famil y and friends. Of the 34 team sports participants during leisure, roughly half of them (41.2%, n = 14) were involved in the outdoor-related sports categor y while on vacation, followed by golf/ski (26.5%, n = 9), water-related sports (17.6%, n = 6), visiting family and friends (5.9%, n = 2), fitness (2.9%, n = 1), team sports (2.9%, n = 1) and other (2.9%, n = 1). Two respondents (100.0%) who reported visiting family and friends i ndicated they take part in the same team sports while they visit their family or friends. Of the nine respondents included in the other leisu re category, frequency of vacation activity participation was equally distributed betw een outdoor-related sports (33.3%, n = 3) and water-related sports (33.3%, n = 3). The next most frequently reported category w as golf/ski

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127 (22.2%, n = 2). One person (11.1%) indicated other vacation activity. Nobody reported that visiting family or friends is their favorite vacati on activity in the other category. These results ar e illustrated in Table 4-3. Leisure Activity Participation Patterns During Vaca tion Research question 3b : What are the participation patterns in the favori te leisure activities of the respondents during vacation? With a purpose of understanding their participation patterns in favorite leisure activity during vacation, the following five issues were add ressed: 1) participation in favorite leisure activities as a primary vacation motivation, 2) par ticipation in favorite leisure activities as a secondary vacation motivation, 3) the influence of favorite leisure activities on vacation types and activities, 4) the likelihood of participating in their favorite leisure activities as a primary vacation motivation, and 5) the relationship betwee n the level of leisure involvement and the likelihood of participating in their favorite leisu re activities as a primary vacation motivation. First, the respondents were asked to report how oft en their favorite leisure activity has been the main purpose of their vacation over the past fi ve years. Almost two thirds of the respondents (60.8%, n = 192) indicated positive responses as follows, al ways (5.7%, n = 18), frequently (20.9%, n = 66) and occasionally (34.2%, n = 108), whereas 39.2% ( n = 124) answered they never participated in their favorite leisure activi ty as the main purpose of a vacation over the past five years. Second, the respondents were asked to indicate how frequently they take part in their favorite leisure activity during their vacations re gardless of the primary purpose of their vacation. The most frequently reported response was less than half the time (29.4%, n = 93) and next, 18.0% ( n = 57) answered they participate in their favorite leisure activity about half the time during vacations, followed closely by almost all of the time (17.4%, n = 55). Those who

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128 indicated most of the time were 13.6% ( n = 43) of the total, whereas 12.7% ( n = 40) do not participate in their leisure activity at all during vacations. Approximately nine percent (8.9%, n = 28) reported they take part in their favorite leisu re activity all of the time. Overall, 87.3% of the respondents reported taking part in their favorite leisure activity while on vacation irrespective of the overall purpose of the vacation at least half o f the time to all of the time. Third, the respondents were asked how much they thi nk their favorite leisure activity influences their vacation type and activities. The majority of the respondents (66.2%, n = 208) acknowledged its impact with the responses ranging from somewhat to extremely influential, but 33.8% ( n = 106) perceived that their favorite leisure activ ity was not influential at all. Fourth, the respondents were asked how likely it is that their favorite leisure activity would be the main purpose of their vacation over the next five years. Almost half of them (45.2%, n = 142) said they were likely to participate in their favorite leisure activity as the main purpose, whereas 43.0% ( n = 135) were unlikely to take part in their favorit e leisure activity as the main purpose. Roughly one out of ten (11.8%, n = 37) reported they are neither likely nor unlikel y to participate in their favorite leisure activity as t he main purpose of their vacation in the future. Last, ANOVA was implemented to investigate the rela tionship between the level of leisure involvement and the likelihood of participating in the favorite leisure activity during vacation as their primary motivation. The upper 25 percent and the lower 25 percent were considered cutoff percentiles to produce three groups at different in volvement levels (Zaichkowski, 1985): high involvement group (HI) (i.e., 84 respondents in the 75th percentile with scores ranging from 5.86 to 7.00), medium involvement group (MI) (i.e., 156 respondents the 26th 74th percentile with scores ranging from 4.76 to 5.85) and low involveme nt group (LI) (i.e., 76 respondents the 25th percentile with scores ranging from 1.72 to 4.75). The results showed that the high, medium, and

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129 low involvement groups had the significant differen ce in their likelihood of participating in their favorite leisure activity during vacation [ F (2, 313) = 14.99, p = .00]. The mean values of likelihood were in the predicted direction. At high er levels of involvement in a leisure activity, the more likely participants were to take part in t his activity on vacation (HI, M = 4.83, SD = 2.09; MI, M = 3.74, SD = 2.04; LI, M = 3.09, SD = 2.04, on a scale of 1=very unlikely, 7=very likely). On the whole, as this research question 6 relates to only one favorite leisure activity, the likelihood of participating in it during vacation s eems to be lower than for the broader sports categories. Levels of Leisure Involvement Research question 4 : What are the levels of involvement in the favorit e leisure activities of the respondents? Almost the entire sample demonstrated a high level of involvement ( M = 5.28, SD = .88) in their favorite leisure activities in terms of the m ean value rated using a 7 point Likert scale (1=strongly disagree, 2=disagree, 3=somewhat disagr ee, 4=neither, 5=somewhat agree, 6=agree, and 7=strongly agree). More specifically, of 18 leisure involvement items, the item with the strongest level of agreement was “I really enjoy my favorite leisure activity” ( M = 6.33, SD = .92). “My favorite leisure activity is pleasurable” was the n ext highest item ( M = 6.14, SD = 1.01), followed by “I enjoy discussing my favorite leisure activity with my friends or family” ( M = 5.89, SD = 1.26) and “my favorite leisure activity interests m e a lot” ( M = 5.87, SD = 1.10). The respondents were less likely to agree with the items, “I find a lot of my life is organized around my favorite leisure activity” ( M = 4.18, SD = 1.62) and “most of my friends or family members a re in some way connected to my favorite leisure activity” ( M = 4.18, SD = 1.66). Consistent with the levels for the individual involvement items, the hedonic component of five involvement factors was the highest-rated ( M = 5.98, SD = .88) and the self-identity factor was the next highest-rated ( M =

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130 5.31, SD = 1.14). The social identity domain ( M = 5.09, SD = 1.14) and the social domain ( M = 5.01, SD = 1.19) were rated similarly. The central component was represented by the lowest mean ( M = 4.98, SD = 1.14), however, on a 7 point scale it is still mo derately high. Levels of Leisure Habit Research question 5 : What are the levels of habit associated with the favorite leisure activities of the respondents? Of 10 leisure habit items (7 point Likert scale wit h 1=strongly disagree, 2=disagree, 3=somewhat disagree, 4=neither, 5=somewhat agree, 6 =agree, and 7=strongly agree), “I have been taking part in this activity for a long time” showe d the highest mean score ( M = 5.83, SD =1.47). The item with the next highest mean was “I take par t in this activity frequently”( M = 5.46, SD = 1.37), followed by “I would find it hard not to tak e part in this activity” ( M = 5.09, SD = 1.58) and “I do not need much of an effort to think about doing this activity” ( M = 5.01, SD = 1.75). However, “I start doing this activity before I real ize I am doing it” was the lowest-rated ( M = 2.43, SD = 1.56). With regard to the three habit factors, th e factor with the highest level of agreement was the regular factor ( M = 5.29, SD = 1.21), followed by the resistant factor ( M = 4.12, SD = 1.39) and the automatic component ( M = 3.74, SD = 1.33). Levels of Vacation Motivation Research question 6 : What are the levels of motivation associated with the favorite vacation activities of the respondents? Of the 18 vacation motivation items (7 point Likert scale with 1=strongly disagree, 2=disagree, 3=somewhat disagree, 4=neither, 5=somew hat agree, 6=agree, and 7=strongly agree), “to relax mentally” ( M = 5.79, SD = 1.27) was the most highly rated, followed closely by “to discover new things” ( M = 5.77, SD = 1.41), “to have a good time with friends” ( M = 5.63, SD = 1.43) and “to be active” ( M = 5.59, SD = 1.35). On the contrary, the lowest rated motivati on items were “to gain a feeling of belonging” ( M = 3.98, SD = 1.80) and “to develop physical skills

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131 and abilities” ( M = 3.95, SD = 1.79). In terms of the four vacation motivation f actors, the mean for the intellectual motivation factor ( M = 5.32, SD = 1.34) was higher than those of the relaxation motivation factor ( M = 5.18, SD = 1.27), the socializing motivation factor ( M = 4.63, SD = 1.29) and of the active/competence motivation factor ( M = 4.59, SD = 1.42). Levels of Vacation Behavior Research question 7 : What are the patterns of vacation behavior relate d to the favorite vacation activities of the respondents? Of 11 vacation behavior items (i.e., a 7 point Like rt scale with 1=strongly disagree, 2=disagree, 3=somewhat disagree, 4=neither, 5=somew hat agree, 6=agree, and 7=strongly agree), the most strongly agreed item was “there is no doub t in my mind about taking part in my favorite vacation activity” ( M = 5.92, SD =1.21). The next highest mean was “the vacation tri ps that immediately come to mind are usually related to my favorite vacation activity” ( M = 5.78, SD = 1.28), followed by “whenever I take a vacation, I a m usually involved in my favorite vacation activity” ( M = 5.37, SD = 1.49). However, the item, “I think it is frustrat ing to expend time and energy finding out about other activities instead o f my favorite vacation activity” was the lowestrated ( M = 3.18, SD = 1.55). With respect to the two vacation behavior factors, the mean values of the vacation decision factor ( M = 5.05, SD = .98) and the vacation participation factor ( M = 5.01, SD = 1.17) were similar. Confirmatory Factor Analysis (CFA) Prior to testing the measurement model and structur al equation model of leisure involvement, leisure habit, vacation motivation and vacation behavior, a first order confirmatory factor analysis (CFA) of each construct was used to determine which variables should be included in the models based on good fits. However, structural equation models with a third order measurement model based on a second order CFA are so complicated that the current study

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132 sample size ( N = 316) was deemed marginally acceptable to measure it. Therefore, the mean values of each factor for each construct were emplo yed to test the SEM with a first order confirmatory factor analysis (i.e., measurement par t). In this process, the mean values of each factor are treated as observed variables. Rather th an using the second order model, many researchers have used this procedure to make their models simpler (e.g., Iwasaki & Havitz, 2004), even though the use of the mean values can hardly e xplain covariance between factors. Originally the hedonic domain of leisure involvement was a factor explain ed by four observed variables (i.e., pleasurable, enjoyable, s atisfying, and interest). However, for the SEM, the hedonic domain was treated as an observed indicator using the average score of the aforementioned four items. Likewise, the hedonic it em, the social item, the social identity item, the self-identity item and the central item were re garded as observed indicators to account for leisure involvement in the SEM model. Accordingly, the measurement process was broadly br oken down into three stages. The first stage was to test the first order confirmator y factor analysis (CFA) of each construct (i.e., leisure involvement, leisure habit, vacation motiva tion, and vacation behavior). The second stage was to specify the measurement model, using observe d variables treated as the mean values of items included in CFA models with good fits that we re confirmed in the first stage. The last stage was to test the structural equation models so as to examine the causal relationship between the four latent variables (i.e., leisure involvement, l eisure habit, vacation motivation, and vacation behavior). Confirmatory Factor Analysis (CFA) of Leisure Invol vement On the basis of the assumption that all of the erro rs are uncorrelated, the results of the CFA for the total 18 items revealed poor fit with unacc eptable RMSEA (Satorra-Bentler Scaled ChiSquare 2/df = 574.26/125 = 0.00; RMSEA = 0.11 with CI, 0.098-0.12; SRMR = 0.08; NNFI =

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133 0.97; CFI = 0.98; GFI = 0.98). During the model res pecification process based upon the large standardized residuals and the modification indices the researcher decided to correlate the errors. Subsequently, the model was respecified with the fo llowing two correlated errors: 1) the correlated errors between the item, “I really enjoy my favorite leisure activity” and the item, “my favorite leisure activity is pleasurable” in the hedonic factor and 2) the correlated errors between the item, “most of my friends or family members are in some way connected with my favorite leisure activity” and the item, “my favorite leisur e activity provides the chance to socialize with my friends or family” in the social factor. The use of correlated errors must be suppo rted by a substantive rationale (Byrne, 1998). In this case, because the meanings of the two items, pleasurable feelings and enjoyable feelings are more similar within the hedonic factor than th e meanings of the other items, “my favorite leisure a ctivity interests me a lot” and “participating in my favorite leisure activity is one of the most sat isfying things that I do,” the errors of the former two items were correlated. From this perspective, t he correlated errors are reasonable. That is, as pleasurable feelings and enjoyable feelings enhance each other, and socializing and connection are positively related, these respecifications are underpinned by a logical and empirical rationale and so the use of correlated errors is reasonable. The final CFA model with the two correlated errors had no negative variances or nonpositive definite covariance and thus, revealed an acceptable fit (Satorra-Bentler Scaled ChiSquare 2/df = 444.89/123 = 0.00; RMSEA = 0.09 with CI, 0.08-0.10; SRMR = 0.07; NNFI = 0.98; CFI = 0.98; GFI = 0.98) (Bentler, 1992; Brown e & Cudeck, 1992a, 1992b; MacCallum, Browne, & Sugawara, 1996). The significance of chisquare ( c2) can be influenced by a large sample size and any non-saturated model should be r ejected (Kline, 2005) (Table 4-4).

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134 In terms of reliability, Cronbach’s alphas () showed that all factors had good internal consistency ( Social = .67, Self-Identity = .83, Social Identity = .78, Hedonic = .83, Central = .86) (Cortina, 1993). Composite reliability (CR) also had acceptable values ( Social = .66, Self-Identity = .86, Social Identity = .81, Hedonic = .85, Central = .88) (Bagozzi & Yi, 1988). Regarding convergent validity, all of the fa ctor loadings of the corresponding items on the latent variables were statistically significant (i. e., t-statistics > 1.96 at a significance level of p <0.05) ranging from 0.51 to 0.90. Furthermore, the Average Variance Extracted (AVE) ranged from 0.41 to 0.75 ( Social = .41, Self-Identity = .68, Social Identity = .70, Hedonic = .75, Central = .75). The social domain appears lower than other domains in its con vergent validity (Table 45). In terms of discriminant validity, the correlat ions among the observed variables were not greater than 0.85, ranging from 0.17 to 0.78. This model is portrayed in Figure 4-2. Confirmatory Factor Analysis (CFA) of Leisure Habit The initial CFA model with all 10 items of leisure habit had a poor fit (Satorra-Bentler Scaled Chi-Square 2/df = 208.81/32 = 0.00; RMSEA = 0.13 with CI, 0.12-0.15; SRMR = 0.09; NNFI = 0.94; CFI = 0.96; GFI = 0.96). The model mis fit was diagnosed by the largest standardized residuals, modification indices, expec ted changes and low factor loadings. In the respecified model, the item, “I have been taking pa rt in this leisure activity for a long time” was deleted and further the errors between the item, “I take part in this leisure activity frequently” and the item, “I would find it hard not to take par t in this leisure activity” were correlated according to a logical rationale (Bamberg, Rolle, & Weber, 2003). However, after the item, “I have been taking part in this leisure activity for a long time” was removed, the standardized factor loading of the item, “this leisure activity is part of my routine” was greater than 1.00 (i.e., negative theta-delta that is known as a Heywood cas e). To solve this matter, the error variance

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135 was constrained to .05 (Hair et al., 2003). Therefo re, one item was deleted, the errors were correlated, and the error variance was constrained to a very small positive value in the final CFA model in which model fit was good (Satorra-Bentler Scaled Chi-Square 2/df = 80.47/24 = 0.00; RMSEA = 0.086 with CI, 0.066-0.11; SRMR = 0.06; NNFI = 0. 98; CFI = 0.99; GFI = 0.99) (Table 4-4). The three leisure habit factors had satisfactory re liability and validity. Cronbach’s alphas () of the three factors ranged from 0.71 to 0.72 ( Automatic = .72, Resistant = .71, Regular = .79). Composite reliability (CR) was slightly highe r than Cronbach’s alphas, ranging from 0.76 to 0.86 ( Automatic = .77, Resistant = .76, Regular = .86). All of the factor loadings ranged from .53 to .98, all of which were greater than t-s tatistics of 1.96 at a significance level of p <0.05. The AVE ranged from 0.46 to 0.76 ( Automatic = .46, Resistant = .51, Regular = .76) (Table 4-6). The correlations between the items ran ged from 0.14 to 0.75, all of which were less than 0.85, satisfactory in terms of discriminant va lidity. Figure 4-3 depicts this leisure habit model. Confirmatory Factor Analysis (CFA) of Vacation Moti vation The total number of vacation motivation items was 1 8. The initial model including all of these items gained an acceptable fit (Satorra-Bentl er Scaled Chi-Square 2/df = 499.98/129 = 0.00; RMSEA = 0.096 with CI, 0.087-0.10; SRMR = 0.077; NNFI = 0 .97; CFI = 0.98; GFI = 0.98). However, one item (“to keep in shape physica lly”) showed values exceeding 0.85 with other items in the correlation matrix and the other item (“to be active”) had the largest standardized residuals. Accordingly, these two item s were omitted from the model in order to increase reliability and validity. Thus, the final CFA model showed a better fit (Satorra-Bentler

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136 Scaled Chi-Square 2/df = 314.78/98 = 0.00; RMSEA = 0.084 with CI, 0.074-0.094; SRMR = 0.066; NNFI = 0.99; CFI = 0.99; GFI = 0.99) (Table 4-4). After the two observed variables were deleted in th e active/competence domain, the domain name was changed to “physical.” The four va cation motivation factors showed good reliability in both Cronbach’s alphas ( Social = .84, Physical = .87, Relaxation = .79, Intellectual = .87) and composite reliability ( Social = .88, Physical = .91, Relaxation = .85, Intellectual = .91). For convergent validity, the factor loadin gs on the four latent variables ranged from 0.65 to 0.93 with all the significant t-statis tics greater than 1.96 at a significance level of p <0.05. The Average Variance Extracted (AVE) was als o good, ranging from 0.59 to 0.78 ( Social = .59, Physical = .78, Relaxation = .59, Intellectual = .72) (Table 4-7). Discriminant validity was obtained as all variables in the correlation matrix were less than 0.85, ranging from -0.13 to 0.83. However the intellectual latent variable was not si gnificantly correlated with the other latent variables of vacation motivation. Figure 4-4 repres ented this vacation motivation model. Confirmatory Factor Analysis (CFA) of Vacation Beha vior The initial fit of the vacation behavior CFA model consisting of 11 items was not good (Satorra-Bentler Scaled Chi-Square 2/df = 459.94/43 = 0.00; RMSEA = 0.18 with CI, 0.16-0.19; SRMR = 0.13; NNFI = 0.87; CFI = 0.90; GFI = 0.90). One item (“I think it is frustrating to expend time and energy finding out about other acti vities instead of my favorite vacation activity”) of this model had a low factor loading ( l = 0.33) on the vacation decision factor. In addition, another vacation decision item (“I attemp t to find detailed information about taking part in my favorite vacation activity”) had high correla tions with other items exceeding 0.85. In terms of standardized residuals, two items (“I usually ex pend effort finding out which place is the best to take part in my favorite vacation activity” and “I attempt to find detailed information about

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137 taking part in my favorite vacation activity”) had an extremely high standardized residual ( d = 82.63). Considering all these causes of misfit, several ite ms were deleted. Only six items remained for the final model: four items for the vacation pa rticipation factor and two items for the vacation decision factor. Besides the deletion of five items the errors between two items (“I spend an adequate amount of vacation to take part in my favo rite vacation activity each year” and “I schedule vacations related to my favorite vacation activity regularly”) were correlated. The two aforementioned items were more closely related to e ach other in terms of a regular vacation schedule as compared to the other two items, “whene ver I take a vacation, I am usually involved in my favorite vacation activity” and “whenever I t ake a vacation, I usually take the chance to improve my favorite vacation activity.” From this p erspective, the correlated errors were reasonable and supported by a substantive rationale The final CFA vacation behavior model showed a good fit (Satorra-Bentler Scaled ChiSquare 2/df = 23.81/7 = 0.00; RMSEA = 0.087 with CI, 0.051-0.13; SRMR = 0.044; NNFI = 0.99; CFI = 1.00; GFI = 0.99) (Table 4-3). Cronbach ’s alphas () for the participation factor and the decision factor were .83 and .81, respectively. The participation behavior factor and the decision behavior factor had composite reliabilitie s of 0.81 and 0.73. For convergent validity, all of the factor loadings were significant, ranging fr om 0.64 to 0.92. The respective AVE of the participation behavior and the decision behavior fa ctors were 0.56 and 0.68, indicating satisfactory convergent validity (Table 4-8). Discr iminant validity was also obtained with correlations ranging from 0.39 to 0.72, all below 0 .85. This vacation behavior model is shown in Figure 4-5.

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138 Measurement Portion of Structural Equation Modeling (SEM) On the basis of each model with good fits, the mean values of each factor were generated and constituted the new observed variables for stru ctural equation modeling. Consequently, the initial measurement model of SEM consisted of 14 ob served variables (i.e., social, self-identity, social identity, hedonic, central, automatic, resis tant, regular, socializing, physical, relaxation, intellectual, participation, and decision) and four latent variables (i.e., leisure involvement, leisure habit, vacation motivation, and vacation be havior). However, this initial measurement model failed to o btain a good fit (Minimum Fit Function Chi-Square 2/df = 272.31/71 = 0.00; RMSEA = 0.093 with CI, 0.081-0.10; SRMR = 0.072; NNFI = 0.84; CFI= 0.87; GFI = 0.89). The social ite m of leisure involvement revealed not only a relatively low factor loading ( l = 0.46) on the leisure involvement latent variable when compared to other variables such as the self-identi ty item ( l = 0.88), the social identity item ( l = 0.75), the hedonic item ( l = 0.72) and the central item ( l = 0.89), but also a large residual covariance with other observed variables such as so cializing and hedonic. Subsequently this resulted in large modification indices. These resul ts were consistent with the outcomes that appeared in the first order CFA of leisure involvem ent. With a purpose of respecifying this measurement mod el, the social item was removed and the errors between the central indicator and the re gular indicator and between the self-identity indicator and the social identity indicator were co rrelated. These correlated errors are corroborated by logical and empirical rationales. T he more routine and frequent participation in leisure activity is, the more central the role of l eisure activity in life (Havitz & Mannell, 2005; Kim et al., 1997). Moreover, self-identity and soci al identity may reinforce each other even though these items constitute different forms of id entity (Thoits & Virshup, 1997). This final

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139 measurement model reported an acceptable fit (Minim um Fit Function Chi-Square 2/df = 156.52/57 = 0.00; RMSEA = 0.074 with CI, 0.060-0.088; SRMR = 0.070; NNFI = 0.91; CFI= 0.93; GFI = 0.93) (Table 4-9). With respect to reliability, the Cronbach’s alphas of each latent variable showed good internal consistency (i.e., leisure involvement, = .88; leisure habit, = .78; vacation behavior, = .74) except vacation motivation ( = .42) and similarly composite reliability (CR) fo r each factor was satisfactory (i.e., leisure involvement = .87; leisure habit = .78; vacation behavior = .75), again with the exception of vacation motiva tion (.46). As vacation motivation consists of four different components to explain various intern al push factors to travel, the four components may not be strongly correlated with each other. In the aforementioned CFA model of vacation motivation, the socializing factor, the physical fa ctor and the relaxation factor were significantly correlated with each other, but the intellectual fa ctor was not significantly correlated with the other three factors. Consistent with the CFA model, the intellectual item in the measurement model of the SEM had a low factor loading on the va cation motivation latent variable, thereby resulting in low reliability for vacation motivatio n (socializing, l = 0.57; physical, l = 0.31; relaxation, l = 0.49; intellectual, l = 0.29). Nevertheless, low factor loadings, reliability and validity do not mean that the item is not valuable in measuring the factor, however it does m ean that to a certain extent, this motivation item is distant from other motivation items loaded on a factor in this case the intellectual motivation was much higher than other motivational factors. Moreover, being distinct from involvement, habit, and behavior, vacation motives may be diverse and so a wide range of factor loadings may be evident from very low to very high. Accordingly, because all of these

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140 motivation items were, albeit uncorrelated, signifi cant in their factor loadings, all four of the vacation motivation items were employed in the stru ctural equation model. In terms of convergent validity, all of the factor loadings on leisure involvement, habit and vacation behavior latent variables were significant ranging from 0.60 to 0.90. The AVE of leisure involvement, leisure habit, vacation motiva tion and vacation behavior were 0.63, 0.55, 0.19 and 0.60, respectively (Table 4-10). Discrimin ant validity was satisfactory with correlations ranging from -0.16 to 0.78. Figure 4-6 portrays thi s model. Structural Portion of Structural Equation Modeling (SEM) Model A A structural equation model based on the measuremen t model of active leisure and vacations was tested. This hypothesized SEM model w as a full model, a so-called just-identified model (i.e., Model A) and thereby the goodness-fitindices were exactly the same as the measurement model (Minimum Fit Function Chi-Square 2/df = 156.52/57 = 0.00; RMSEA = 0.074 with CI, 0.060-0.088; SRMR = 0.070; NNFI = 0. 91; CFI= 0.93; GFI = 0.93) (Table 4-9). However, distinct from the measurement model, direc t and indirect effects between latent variables were identified (Table 4-11). In terms of the results of the hypothesis testing, Hypothesis 1 (i.e., involvement with active leisure and habit associated with active leisure ar e correlated) was corroborated by a significant positive correlation between leisure involvement an d leisure habit (Phi, f = 0.57). Hypothesis 2 (i.e., involvement with active leisure has a direct influence on vacation motivation) was corroborated with a significant positive direct eff ect (Gamma, g = 0.26). Hypothesis 3 (i.e., habit associated with active leisure has a direct influen ce on vacation motivation) was upheld with a significant positive direct effect (Gamma, g = 0.22). Hypothesis 4 (i.e., involvement with acti ve

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141 leisure has a direct and indirect influence on acti ve vacation behavior) was partially supported whereby the direct effect was significant, whereas the indirect effect was not significant (direct = 0.18; indirect = 0.07; total = 0.25). Hypothesis 5 (i.e., habit associated with active leisure has a direct and indirect influence on active vacation be havior) was not supported by the results with both non-significant direct and indirect effects (d irect = 0.01; indirect = 0.06; total = 0.07). Hypothesis 6 (i.e., vacation motivation has a direc t influence on active vacation behavior) was verified by a significant positive direct effect (B eta, b = 0.25). These results are presented in Table 4-11 and Figure 4-7. Model B With the elimination of hypothesis 4 that was not s upported by the results of Model A, a competing model, Model B nested in Model A was test ed. Leisure habit is mediated by vacation motivation in order to reach vacation behavior in t his model. The RMSEA of Model B was slightly better than for Model A, but the results o f other indices were exactly the same (Minimum Fit Function Chi-Square 2/df = 156.54/58 = 0.00; RMSEA = 0.073 with CI, 0.0590.087; SRMR = 0.070; NNFI = 0.91; CFI= 0.93; GFI = 0.93). Moreover, the relationship between the latent variables was not dissimilar. Th e correlation between involvement with active leisure and active leisure habit was the same as th at of Model A (Phi, f = 0.57). The direct effect of involvement with active leisure on vacation moti vation was the same as that of Model A, as well (Gamma, g = 0.26). The direct effect of habit associated wit h active leisure on vacation motivation was also exactly the same as Model A (Ga mma, g = 0.22). The direct effect of vacation motivation on active vacation behavior was identical (Beta, b = 0.25). However, the direct effect of involvement with active leisure on active vacation behavior increased slightly but

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142 the indirect impact of leisure involvement on vacat ion behavior was not significant (direct = 0.19; indirect = 0.07; total = 0.26). Table 4-11 an d Figure 4-8 present these results. Model C Therefore, the other competing model, Model C with the removal of hypotheses 4 and 5 that were not supported by the results was tested, which was nested in Model A and B. As a result, Model C had a good fit, albeit with a sligh tly higher RMSEA (Minimum Fit Function ChiSquare 2/df = 160.12/59 = 0.00; RMSEA = 0.075 with CI, 0.061-0.088; SRMR = 0.070; NNFI = 0.91; CFI= 0.93; GFI = 0.93). Leisure involvement a nd leisure habit were mediated through vacation motivation before reaching vacation behavi or in this model. In terms of the causal relationship between the latent variables, the corr elation between involvement with active leisure and active leisure habit remained constant (Phi, f = 0.57) in Model A, B, and C. However, the direct influence of leisure involvement on vacation motivation became much stronger (Gamma, g = 0.34), whereas the direct influence of leisure ha bit on vacation motivation remained steady (Gamma, g = 0.22). The direct influence of vacation motivati on on vacation behavior surged (Beta, b = 0.45). The significant positive indirect effects of leisure involvement (indirect = 0.15; total = 0.15) and leisure habit (indirect = 0.10; t otal = 0.10) on vacation behavior being mediated through vacation motivation were newly identified, which was not present in Model A and Model B. These results are demonstrated in Table 410 and Figure 4-9. Model Comparisons To identify the best model among Model A, Model B, and Model C with a statistical significance, the chi-squares and degrees of freedo m of those models were compared. In the comparison between Model A and Model B, the null hy pothesis was “Model B fits the data (H1)” and the alternative hypothesis was “Model A fits th e data (H2).” The model comparison test was

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143 computed using c12 2 = (c1 2 c2 2) = 0.02 and df1– df 2 = 1. The result was c2 (1) = 0.02, p > 0.05. Since p was larger than 0.05, the null hypothesis was not rejected. Model A was rejected against Model B. To compare between Model A and Model C, the null hy pothesis (i.e., “Model C fits the data”) and the alternative hypothesis (i.e., “Model A fits the data”) were established. The model comparison test statistic was c12 2 = (c1 2 c2 2) = 3.60 and df1– df 2 = 1. The result showed c2 (1) = 3.60, p > 0.05. As the p -value was greater than 0.05, the null hypothesis w as not rejected, which means Model C fits better than Model A. In the comparison between Model B and Model C, “Mod el C fits the data (H1)” was the null hypothesis, whereas “Model B fits the data (H2)” was offered as the alternative hypothesis. The model comparison test statistic was c12 2 = (c1 2 c2 2) = 3.58 and df1– df 2 = 1, thereby resulting inc2 (1) = 3.58, p > 0.05. Model B was rejected in favor of Model C. Accordingly, Model C was ultimately determined as the best-fit m odel.

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144 Table 4-1. Favorite leisure activities and favorite vacation activities Category Activities Leisure Outdoor-related sports Walking, running, hiking, tr ekking, orienteering, bicycling, mountain biking, road biking, horseback riding, hunting, camping, and other active outdoor recreation activities. Water-related sports Swimming, diving, scuba diving water skiing, whitewater rafting, boating, kayaking, canoeing, rowing, pontooning, sailing, fishing, and other water activities Fitness Exercise, working out, weight training, lif ting, dancing, aerobics, karate, Pilates, and martial art s Golf/ski Golfing and skiing Team sports Football, soccer, baseball, softball, r acquetball, volleyball, tennis, fencing, and hockey Others Auto racing, motor cycle riding, off-roading and flying aerobatics Vacation Outdoor-related sports Adventure activities, bicycl ing, mountain biking, camping, walking, hiking, horseback riding, hunting, and other active outdoor recreation Water-related sports Swimming, surfing, diving, sno rkeling, whitewater rafting, canoeing, kayaking, boating, fishing, cruising, sailing, and other water/beach activities Fitness Dancing and other sports Golf/ski Golfing and skiing Team sports Softball and Ultimate Frisbee Others Driving a car Visiting family and friends Golfing, tennis, hiking, walking, camping, skiing, swimming, water sports, outdoor-related sports, etc

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145 Table 4-2. Categories of the different types of fav orite leisure and vacation activities Types of activities Frequency Valid percent Leisure Outdoor-related sports 114 36.1 Water-related sports 56 17.7 Fitness 53 16.8 Golf/ski 50 15.8 Team sports 34 10.8 Others 9 2.8 Total 316 100.0 Vacation Outdoor-related sports Sport tourism 58 42.4 Tourism sport 79 57.6 Total 137 43.4 Water-related sports Sport tourism 71 87.4 Tourism sport 11 12.6 Total 82 25.9 Fitness Sport tourism 3 50.0 Tourism sport 3 50.0 Total 6 1.9 Golf/ski Sport tourism 47 77.1 Tourism sport 14 22.9 Total 61 19.3 Team sports Sport tourism 2 100.0 Tourism sport 0 0.0 Total 2 0.6 Others Sport tourism 2 100.0 Tourism sport 0 0.0 Total 2 0.6 Visiting family and friends Sport tourism 0 0.0 Tourism sport 26 100.0 Total 26 8.2

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146 Table 4-3. Similarity between leisure categories an d vacation categories Leisure category Vacation category Frequency Valid percent Outdoor-related sports Outdoor-related sports 78 68.4 Water-related sports 16 14.0 Fitness 0 0.0 Golf/ski 9 7.9 Team sports 1 0.9 Other 0 0.0 Visiting family and friends 10 8.8 Total 114 100.0 Water-related sports Outdoor-related sports 10 17.9 Water-related sports 36 64.3 Fitness 2 3.6 Golf/ski 4 7.1 Team sports 0 0.0 Other 0 0.0 Visiting family and friends 4 7.1 Total 56 100.0 Fitness Outdoor-related sports 27 50.9 Water-related sports 13 24.5 Fitness 3 5.7 Golf/ski 7 13.2 Team sports 0 0.0 Other 0 0.0 Visiting family and friends 3 5.7 Total 53 100.0 Golf/ski Outdoor-related sports 5 10.0 Water-related sports 8 16.0 Fitness 0 0.0 Golf/ski 30 60.0 Team sports 0 0.0 Other 0 0.0 Visiting family and friends 7 14.0 Total 50 100.0 Team sports Outdoor-related sports 14 41.2 Water-related sports 6 17.6 Fitness 1 2.9 Golf/ski 9 26.5 Team sports 1 2.9 Other 1 2.9 Visiting family and friends 2 5.9 Total 34 100.0 Other Outdoor-related sports 3 33.3 Water-related sports 3 33.3

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147 Table 4-3. Continued Leisure category Vacation category Frequency Valid percent Other Fitness 0 0.0 Golf/ski 2 22.2 Team sports 0 0.0 Other 1 11.1 Visiting family and friends 0 0.0 Total 9 100.0

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148 Table 4-4.Goodness fit indices for each construct CFA model 2/df RMSEA RMSEA CI SRMR NNFI CFI GFI Leisure involvement Original 574.26/125 0.11 0.098-0.12 0.08 0.97 0.98 0.98 Respecified 444.89/123 0.09 0.08-0.10 0.07 0.98 0.98 0.98 Leisure habit Original 208.81/32 0.13 0.12-0.15 0.09 0.94 0.96 0.96 Respecified 80.47/24 0.086 0.066-0.11 0.06 0.98 0.99 0.99 Vacation motivation Original 499.98/129 0.096 0.087-0.10 0.077 0.97 0.98 0.98 Respecified 314.78/98 0.084 0.074-0.094 0.066 0.99 0.99 0.99 Vacation behavior Original 459.94/43 0.18 0.16-0.19 0.13 0.87 0.90 0.90 Respecified 23.81/7 0.087 0.051-0.13 0.044 0.99 1.00 0.99 Note. 2 = chi square test statistic; df = degree of freedom; RMSEA = root-mean square-erro r of approximation; CI = 90% confidence interval; SRMR = standardized root mean square residual; NNFI = non-normed fit index; CFI = comparative fit index; GFI = goodness of fit index

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149 Table 4-5. Reliability and validity of the leisure involvement CFA model Factors and items Mean SD l CR AVE Social .67 .66 .41 I enjoy discussing my favorite leisure activity with my friends or family 5.89 1.26 .79* Most of my friends or family members are in some way connected to my favorite leisure activity 4.18 1.66 .51* My favorite leisure activity provides the chance to socialize with my friends or family 4.95 1.68 .57* Self-identity .83 .86 .68 Participation in my favorite leisure activity says something about me 5.82 1.15 .77* My favorite leisure activity reflects who I am 4.96 1.39 .79* My favorite leisure activity is an important part of who I am 5.16 1.42 .90* Social identity .78 .81 .70 Other people see an important side of me when I participate in my favorite leisure activity 5.10 1.45 .88* I can tell things about other people by seeing them participating in their favorite leisure activity 4.88 1.45 .78* When I participate in my favorite leisure activity, others see me the way I want them to see me 5.30 1.21 .63* Hedonic .83 .85 .75 I really enjoy my favorite leisure activity 6.33 .9 2 .88* Participating in my favorite leisure activity is one of the most satisfying things that I do 5.57 1.30 .76* My favorite leisure activity is pleasurable 6.14 1 .01 .59* My favorite leisure activity interests me a lot 5.8 7 1.10 .86* Central .86 .88 .75 My favorite leisure activity has a central role in my life 5.13 1.48 .82* My favorite leisure activity reflects my lifestyle 5.45 1.28 .75* I attach great importance to my favorite leisure activity 5.24 1.38 .82* I would rather do my favorite leisure activity than do most anything else 4.91 1.47 .71* I find a lot of my life is organized around my favorite leisure activity 4.18 1.62 .74* Note. = t-statistic (> 1.96) at a significance le vel of p <0.05; l = factor loadings; = Cronbach’s alpha coefficients; CR = composite reliability; AVE = ave rage variance extracted

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150 Table 4-6. Reliability and validity of the leisure habit CFA model Factors and items Mean SD l CR AVE Automatic .72 .77 .46 I start doing this activity before I realize I am doing it 2.43 1.56 .62* I do not need much of an effort to think about doing this activity 5.01 1.75 .53* I do this activity without much thinking 3.88 1.93 .74* I do this activity without having to consciously remember it 3.65 1.99 .77* Resistant .71 .76 .51 I feel strange if I do not participate in this activity 3.98 1.89 .73* This activity would require effort not to do it 3.3 0 1.77 .76* I would find it hard not to take part in this activity 5.09 1.58 .65* Regular .79 .86 .76 This activity is part of my routine 4.57 1.82 .98* I take part in this activity frequently 5.47 1.37 .72* Note. = t-statistic (> 1.96) at a significance le vel of p <0.05; l = factor loadings; = Cronbach’s alpha coefficients; CR = composite reliability; AVE = ave rage variance extracted

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151 Table 4-7. Reliability and validity of the vacation motivation CFA model Factors and items Mean SD l CR AVE Socializing .84 .88 .59 To build friendships with others 4.08 1.79 .83* To interact with others 5.04 1.49 .78* To have a good time with friends 5.63 1.43 .69* To develop close friendships 4.47 1.73 .87* To gain a feeling of belonging 3.95 1.79 .65* Physical .87 .91 .78 To develop physical skills and abilities 3.98 1.80 .84* To develop physical fitness 4.45 1.65 .87* To use my physical abilities 4.59 1.72 .93* Relaxation .79 .85 .59 To rest 4.54 1.81 .79* To relax mentally 5.79 1.27 .79* To avoid the hustle and bustle of daily activities 5.47 1.62 .66* To relax physically 4.92 1.75 .81* Intellectual .87 .91 .72 To learn about things around me 5.25 1.61 .84* To discover new things 5.77 1.41 .85* To expand my knowledge 5.28 1.60 .90* To explore new ideas 4.97 1.60 .81* Note. = t-statistic (> 1.96) at a significance le vel of p <0.05; l = factor loadings; = Cronbach’s alpha coefficients; CR = composite reliability; AVE = ave rage variance extracted

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152 Table 4-8. Reliability and validity of the vacation behavior CFA model Factors and items Mean SD l CR AVE Participation .83 .81 .56 I spend an adequate amount of vacation to take part in my favorite vacation activity each year 5.10 1.67 .67* I schedule vacations related to my favorite vacation activity regularly 5.06 1.57 .64* Whenever I take a vacation, I am usually involved in my favorite vacation activity 5.37 1.49 .92* Whenever I take a vacation, I usually take the chance to improve my favorite vacation activity 5.00 1.50 .72* Decision .81 .73 .68 The trips that immediately come to mind are usually related to my favorite vacation activity 5.78 1.28 .84* There is no doubt in my mind about taking part in my favorite vacation activity 5.92 1.21 .81* Note. = t-statistic (> 1.96) at a significance le vel of p <0.05; l = factor loadings; = Cronbach’s alpha coefficients; CR = composite reliability; AVE = ave rage variance extracted

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153 Table 4-9.Goodness fit indices for the measurement model and structural equation models Model 2/df RMSEA RMSEA CI SRMR NNFI CFI GFI Measurement 154.38/57 0.074 0.060-0.088 0.070 0.91 0.93 0.9 3 SEM model A 156.52/57 0.074 0.060-0.088 0.070 0.91 0.93 0.9 3 SEM model B 156.54/58 0.073 0.059-0.087 0.070 0.91 0.93 0.9 3 SEM model C 160.12/59 0.075 0.061-0.088 0.070 0.91 0.93 0.9 3 Note. 2 = chi square test statistic; df = degree of freedom; RMSEA = root-mean square-erro r of approximation; CI = 90% confidence interval; SRMR = standardized root mean square residual; NNFI = non-normed fit index; CFI = comparative fit index; GFI = goodness of fit index

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154 Table 4-10. Reliability and validity of the measure ment model Latent variables and observed variables N Mean aSD l CR AVE Leisure involvement .88 .87 .63 Hedonic 316 5.98.88.71* Central 316 4.981.14.91* Social identity 316 5.091.14.69* Self-identity 316 5.311.14.86* Leisure habit .78 .78 .55 Regular 316 5.021.46.63* Automatic 316 3.741.33.60* Resistant 316 4.121.39.95* Vacation motivation .42 .46 .19 Socializing 316 4.631.29.57* Physical 316 4.341.56.31* Relaxation 316 5.181.27.49* Intellectual 316 5.321.34.29* Vacation behavior .74 .75 .60 Participation 316 5.131.25.75* Decision 316 5.851.10.80* Note. a = 7 point Likert scale (1=strongly disagree, 2=disa gree, 3=somewhat disagree, 4=neither, 5=somewhat agree, 6=agree, 7=strongly agree); = t -statistic (>1.96) a significance level of p <0.05; l = factor loadings; = Cronbach’s alpha coefficients; CR = composite re liability; AVE = average variance extracted

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155 Table 4-11. Direct, indirect, and total effects of the structural equation model Causal relationship between latent variables Dire ct Indirect Total Model A Involvement (KSI, x ) Habit (KSI, x ) 0.57* Involvement (KSI, x ) Motivation (ETA, h ) 0.26* Involvement (KSI, x ) Behavior (ETA, h ) 0.18* 0.07 0.25* Habit (KSI, x ) Motivation (ETA, h ) 0.22* Habit (KSI, x ) Behavior (ETA, h ) 0.01 0.06 0.07 Motivation (ETA, h ) Behavior (ETA, h ) 0.25* Model B Involvement (KSI, x ) Habit (KSI, x ) 0.57* Involvement (KSI, x ) Motivation (ETA, h ) 0.26* Involvement (KSI, x ) Behavior (ETA, h ) 0.19* 0.07 0.26* Habit (KSI, x ) Motivation (ETA, h ) 0.22* Habit (KSI, x ) Behavior (ETA, h ) 0.06 0.06 Motivation (ETA, h ) Behavior (ETA, h ) 0.25* Model C Involvement (KSI, x ) Habit (KSI, x ) 0.57* Involvement (KSI, x ) Motivation (ETA, h ) 0.34* Involvement (KSI, x ) Behavior (ETA, h ) 0.15* 0.15* Habit (KSI, x ) Motivation (ETA, h ) 0.22* Habit (KSI, x ) Behavior (ETA, h ) 0.10* 0.10* Motivation (ETA, h ) Behavior (ETA, h ) 0.45* Note. = t-statistic (>1.96) at a significance lev el of p <0.05; KSI ( x ) = exogenous variable; ETA ( h ) = endogenous variable

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156 Figure 4-1. Similarity between favorite leisure and vacation activities Different ( n = 203, 64%) Identical ( n = 113, 36%) Identical Different

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157 Figure 4-2. First-order CFA model of leisure involv ement Social (SOC) Selfidentity (SEI) Social identity (SOI) Hedonic (HDN) Centrality (CTL) d 2 d 3 d 4 d 5 d 6 d 7 d 8 d 9 d 10 d 11 d 12 d 13 d 14 d 15 d 16 d 17 d 18 Social connection Socialize Say something about me Reflects who I am Important who I am Important side of me Tell things about others Others see me the way Enjoyable Satisfying Pleasurable Interest Central role Lifestyle Importance Would rather do Organized Discussing .51* .57* .74* .67* .40* .37* .19 .22 .39* .60* .23 .43* .65* .33* .43* .33* .49* .45* .27* .77* .79* .90* .88* .78* .63* .88* .76* .59* .86* .82* .75* .82* .71* .74* .64* .82* .79* .56* .52* .86* .71* .87* .78* .92* .33* .24* d 1 .37* .79*

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158 Figure 4-3. First-order CFA model of leisure ha bit Do before I realize Do not need effort Without much thinking Without consciously Feel strange if do not Effort not to do it Hard not to take part Routine Frequently Regular (REG) Automatic (AUT) .74* .53* .77* .73* .76* .65* Resistant (RES) .72* .98* .59* .81* .78* .21* d 1 d 2 d 3 d 4 d 5 d 6 d 7 d 8 d 9 .61* .71* .45* .40* .46* .43* .58* .05* .48 .62*

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159 Figure 4-4. First-order CFA model of vacation mo tivation Interact with others Good time with friends Close friendships A feeling of belonging Physical skills & abilities Physical fitness Physical Abilities Rest Relax mentally Avoid daily activities Relax physically Learn about things Discover new things Expand knowledge Explore new ideas Friendships .83* .78* .69* .84* .87* .93* .79* .66* .79* .81* .84* .85* .90* .81* Socializing (SCZ) .87* .65* Active/ competence (ACT) Relaxation (REX) Intellectual (INT) .38* .06 .11 .29* .23* .15 d 1 d 2 d 3 d 4 d 5 d 6 d 7 d 8 d 9 d 10 d 11 d 12 d 13 d 14 d 15 d 16 .31* .38* .53* .25* .58* .30* .24* .13 .38* .38* .56* .34* .30* .28* .19 .34*

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160 Figure 4-5. First-order CFA model of vacation b ehavior d 2 d 3 d 4 d 5 d 6 d 1 Decision (DEC) Participation (PAR) Schedule regularly Usually involved in Chance to improve Immediately come to mind No doubt in my mind Adequate amount 8 .59* .16* .48* .29* .34* .24* .64* .92* .72* .84* .81* .81* .55* .67*

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161 Figure 4-6. Measurement model of active leisure and vacations Hedonic Central Social identity Self-identity Regular Automatic Resistant Socializing S Physical Relaxation Intellectual Participation Decision Vacation behavior (VB) d 1 d 2 d 3 d 4 d 5 d 6 d 7 d 8 d 9 d 10 d 11 d 12 d 13 Vacation motivation (VM) Leisure habit (LH) Leisure involvement (LI) .50* .16* .53* .27* .57* .64* .11 .68* .90* .76* .92* .44* .37* .71* .91* .69* .86* .63* .60* .95* .57* .31* .49* .29* .75* .80* .57* .37* .32* .39* .29* .21* .11* .13*

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162 Figure 4-7. Model A: Measurement and structural model of active leisure and vacations Hedonic Central Social identity Self-identity Regular Automatic Resistant Socializing Physical Relaxation Intellectual d 1 d 2 d 3 d 4 d 5 d 6 d 7 d 9 LI VM LH Participation Decision d 8 d 10 d 11 d 12 d 13 .71* .91* .69* .86* .63* .60* .95* .57* .31* .49* .29* .75* .80* VB .57* .26* .22* .25* .18* .01 .50* .17* .53* .27* .59* .64* .11* .44* .37* .68* .90* .76* .92*

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163 Figure 4-8. Model B: Competing model nested in model A Hedonic Central Social identity Self-identity Regular Automatic Resistant Socializing Physical Relaxation Intellectual d 1 d 2 d 3 d 4 d 5 d 6 d 7 d 9 LI VM LH Particip ation Decision d 8 d 10 d 11 d 12 d 13 .71* .91* .69* .86* .62* .60* .95* .57* .31* .49* .29* .74* .80* VB .57* .26* .22* .25* .19* .50* .17* .53* .27* .59* .64* .10* .45* .36* .68* .90* .76* .91*

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164 Figure 4-9. Model C: Competing model nested in model A and in model B Hedonic Central Social identity Self-identity Regular Automatic Resistant Socializing Physical Relaxation Intellectual d 1 d 2 d 3 d 4 d 5 d 6 d 7 d 9 LI VM LH Participation Decision d 8 d 10 d 11 d 12 d 13 .71* .91* .69* .86* .62* .60* .95* .51* .25* .45* .36* .79* .75* VB .57* .34* .22* .45* .50* .17* .53* .27* .59* .64* .11* .37* .44* .74* .94* .80* .87*

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165 CHAPTER 5 DISCUSSION This study was designed to enhance understanding of the relationship between leisure activities and vacation/tourism behaviors, especial ly between active leisure and active vacation behaviors. Several leisure and tourism researchers have suggested theoretical assumptions concerning the leisure-tourism connection (Carr, 20 02; Currie, 1997; Fedler, 1987; Mannell & Iso-Ahola, 1987), and in addition, countless exampl es in everyday life have been observed (Brey & Lehto, 2007; Glyptis, 1982). Nonetheless, few emp irical studies have investigated this relationship. Accordingly, this study strived to em pirically corroborate this connection, investigating the types and the patterns associated with favorite leisure and vacation activities and further testing the relationship between releva nt psychological constructs (i.e., leisure involvement, leisure habit, vacation motivation, an d vacation behaviors). This study not only empirically verified and embodied the previously su ggested theoretical relationship between leisure activities and vacation activities, but als o proposed a new theoretical framework for the active leisure-vacation connection and proposed imp lications for practice, which are discussed in this chapter. Leisure-Vacation Connection It has been argued that leisure and tourism are dif ferent realms even though both share many psychological and behavioral components (Fedle r, 1987; Mannell & Iso-Ahola, 1987). Based upon this argument, this study corroborated t he substantial leisure-tourism connections. In particular, this study provided critical findings u nderpinning Currie’s (1997) LIP behavior frameworks and Carr’s (2002) leisure-tourism contin uum. In this study, the favorite leisure activities and the favorite vacation activities des cribed by almost two thirds of the respondents were not identical. Nevertheless, the favorite leis ure and vacation activities of a large percentage

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166 of the participants did fall into the same category For example, those who were involved in the outdoor-related sports category during leisure also preferred taking part in the outdoor-related sports category during vacations. However, more res pondents in the fitness category and the team sports category described their favorite vacat ion activities as being in the outdoor-related sports category. A plausible explanation for this i s that team sports may have inherent constraints that limit their availability in vacation settings and some fitness activities such as dancing (e.g., weight training, dancing, etc) might also have limi ted opportunities (Crawford & Godbey, 1987; Crawford, Jackson, & Godbey, 1991). Even though peo ple might be able to find fitness facilities in the tourism settings, they might prefer new outd oor experiences as one of the main reasons for taking a vacation is new experiences (Crompton, 197 9). For the most part, the respondents preferred partic ipating in vacation activities from the same category as their usual leisure activities, al though they engaged in different activities. Indeed, these findings are enough to confirm the pr evious assumptions that people on vacation in tourism settings tend to enjoy exploring more novel activities, experiences and places, although they engage in activities that are similar in type, but may vary somewhat from their normal daily activities (Carr, 2002; Cohen, 1974; Currie, 1997) For example, some participants enjoyed walking as their favorite leisure activity, while t hey preferred hiking in new places as a vacation experience. Other respondents spent leisure time bi cycling, but their favorite vacation activity was mountain biking. From these examples that most people’s vacation activities are not completely divergent from their leisure activities, there is a level of consistency in activity type, which is supported by Sherif and Cantril’s (1947) s ocial judgment theory as people tend to keep seeking self-identity through ego-involving objects Similarly, Atchley’s (1989, 1999) continuity theory that internal continuity causes behavioral c ontinuity can explain these results. Atchley

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167 (1989) explains that through the life course, an ov erall internal system associated with selfidentity encourages people to behave consistently b ased on their past experiences, and this consistency in identity carries over into old age. Consistent with the aforementioned behavioral patte rns, the leisure-vacation continuum is also evident in other results of this study. A larg e percentage of the respondents preferred visiting new places for their vacations instead of familiar destinations, but simultaneously a majority of the respondents were still influenced to a large ex tent by their favorite leisure activities in determining their vacation activities. Moreover, in linking these findings to the sport tourism literature, these findings are essential for explai ning the category, tourism sport as defined by Gammon and Robinson (1997) whereby sport is not the primary purpose of a trip. Almost half of the respondents were tourist sports who participate in active vacations regardless of their primary motivation. In particular, it was revealed that tou rist sports enjoyed sports and recreational activities, as well as exploring new places and new experiences, as a way of spending time with their friends or family. In fact, the overwhelming majority of respondents have participated in their favorite active leisure activity while on vac ation, even if it was not a primary motivation, and nearly two thirds of the respondents have taken part in their favorite active leisure activity during vacation as a primary motivation. Furthermor e, approximately half of the respondents stated that they were likely to take a vacation in the next five years with participation in their favorite leisure activity as a primary motivation. Therefore, the respondents’ vacation activities were likely to be affected by their daily leisure a ctivities. However, rather than the vacation activities being identical to the leisure activities, the vacation activities seem to be expanded to include new and more pleasurable experiences (Bello & Etzel, 1985; Crompton, 1979; Lee & Crompton, 1992 ). Crompton suggested pleasure

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168 vacations are primarily driven by novelty-seeking m otives. Lee and Crompton (1992) found that destination choice in relation to novelty is influe nced by some constraints individuals face, but the impact of novelty-seeking motives still remaine d predominant in the selection of destination. Indeed, throughout the tourism literature, novelty and searching for new experiences through travel is a pervasive theme (Bello & Etzel, 1985; W ahlers & Etzel, 1985). Furthermore, Robinson and Gammon (2004) asserted th at a secondary motive should not be disregarded as any less important than primary m otives. In other words, even though its motivation is secondary, its importance is by no me ans secondary. Such a notion is supported as well as accentuated by the finding that sport touri sts and tourist sports did not show different patterns in the leisure-vacation psychological flow Active leisure pursuits seem to be combined with active vacation pursuits to explore new experi ences (Chon & Singh, 1995; Glyptis, 1991; Henderson, 2005a, b; Hall, 1992) and are even linke d to choice of certain new environments (Schreyer & Beaulieu, 1986). Those respondents who were more immersed in their favorite leisure activities had a higher likelihood of parti cipating in the same leisure activities during vacation. This result can also be explained by eith er Bryan’s (1979) specialization or Buchanan’s (1985) commitment that participants who were more h ighly involved or committed to leisure activity were more willing to develop their leisure activity through travel. As might be expected, many respondents participated in sports, physical activities, and active outdoor recreation during their vacations, b ut tended to opt for slightly different activities or different destinations. As already mentioned, fo cusing on the broader activity categories, most of the respondents’ vacation categories were not di stinct from their leisure categories, even if the activities themselves were different. A series of t hese findings tends to confirm Carr’s (2002) leisure-tourism continuum assumption that participa nts in leisure and tourism retain their

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169 attitudes, values, and habit, but tend to be more h edonic or seek novel experiences in the tourism context. In this regard, there are subtle differenc es between the current findings and the former studies related to leisure specialization (Bryan, 1 977), leisure commitment (Buchanan, 1985), and serious leisure (Stebbins, 1982), which assumed that involvement encourages people to develop or improve the same activities. Instead, th e current findings revealed that more respondents altered their vacation activities from their leisure activities, but the activities remained in similar categories (Carr, 2002; Currie, 1997). Involvement, Habit, Motivation, and Behavior Brey and Lehto (2007) investigated behavioral frequ ency between daily leisure activities and tourism activities but did not provide a psycho logical connection to explain how everyday leisure activities are related to vacation behavior s. Accordingly, the current study examined the psychological relationship between favorite leisure activities and vacation activities using four multidimensional constructs. Each construct was ide ntified with several subfactors and further the relationship between the constructs was found t o be significant. Leisure Involvement Prior to testing the causal paths between four late nt variables, each construct was identified with several factorial components. The leisure invo lvement construct was identified as having four factors (i.e., hedonic, self-identity, social identity, and central ). The social domain had low validity and reliability, revealing low mean values for a few indicators. In particular, “most of my friends or family members are in some way connec ted to my favorite leisure activity” was rated much lower than other items and “my favorite leisure activity provides the chance to socialize with my friends or family” was also low, whereas “I enjoy discussing my favorite leisure activity with my friends or family” was ver y high in its mean value. In other words, the respondents enjoyed talking with family members or friends about their favorite leisure activity,

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170 but did not necessarily participate with them and d id not perceive the activity as a chance to socialize with them. Probably, they could perceive leisure with their family distinct from their favorite leisure activity because family members ma y have different interests based on their different ages and even due to gender-based roles ( Shaw, 1992; Shaw, 1997; Shaw & Dawson, 2001), even though some individuals could attempt t o negotiate with their family members in taking part in their leisure (Crawford et al., 1991 ). Consequently, two items with lowest average means also shared the correlated errors in the CFA results. Furthermore, this finding might re flect Dubin’s (1979) notion that leisure activity could be adversely affected by leisure soc ial groups or could be irrelevant to some leisure social groups. In other words, the more foc us people have on their leisure activity, the less focus they have on the social groups because t he social groups might inhibit the participants who want to concentrate on the leisure activity its elf. In addition, involvement with a leisure activity might not be a significant explanation of involvement with social groups, although in most of the leisure literature, the contrary idea t hat leisure activities and leisure social groups ar e closely related is more pervasive. Following this line of thought, Buchanan (1985) did not distinguish “commitment to leisure activity” from “commitment to leisure socia l groups.” In developing Bryan’s (1977) leisure specialization he showed a positive relatio nship between activity and social groups. To date, in line with Bryan’s leisure specialization, many leisure researchers have assumed that a social factor is a very strong component in the involveme nt construct (Gahwiler & Havitz, 1998; Kyle et al., 2007). Contrary to the previous assump tions, this study found that social-related characteristics are very weak in explaining vacatio n motivation and vacation behavior, as well as in leisure involvement. Additionally, most responde nts answered that they have no special social

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171 groups with whom they travel. One possible explana tion of these results is that the previous leisure studies used homogenous samples such as run ners, hikers, or paddlers who were engaged in certain activities in particular leisure setting s or were members of certain leisure clubs or institutions (Bryan, 1977; Gahwiler & Havitz, 1998; Iwasaki & Havitz, 2004; Kim et al., 1997; Kyle et al., 2004, 2007; McIntyre, 1989). This stu dy differs in that the sample is comprised of a general population who are not necessarily members of specific leisure settings, tourism events, or relevant leisure clubs. This study sample may possess different characteris tics and tendencies from the specialized groups investigated in the prior studie s. The statements including terms such as “connected” or “organized” may not be relevant when measuring leisure involvement of the general population. These statements may specifical ly correspond only to a very small percentage of people who are highly specialized (Br yan, 1977) or seriously involved (Stebbins, 1982) in leisure activities, or regulars or insider s in leisure social worlds (Unruh, 1979). When applied to the general population with more of a ba lance between everyday life and leisure, the utility of these statements may need to be reconsid ered in this respect. Another explanation is that the term “connected” ma y be contingent on the particular leisure activity, as noted by one of the expert pan el members who participated for content validity. For example, although some individuals ar e highly involved in a particular leisure activity, “running” during leisure time, their fami ly or friends may not participate in “running.” However, participants in certain leisure activities such as camping or team sports might more strongly agree with the statement, “most of my frie nds or family members are in some way connected to my favorite leisure activity” as Havit z and Dimanche (1999) pointed out that subfactors such as risk, sign, and importance within l eisure involvement may have different degrees

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172 of relevance, depending on different types of activ ities. Nevertheless, the leisure activities reported by this study sample were diverse such as walking, running, hiking, trekking, horseback riding, camping, swimming, diving, kayaking, whitew ater rafting, dancing, skiing, golfing, volleyball, tennis, soccer, hockey, auto racing, et c. Across all these leisure activities, social connection-related factors were not high. According ly, an assumption that each of these activities would vary in terms of the relevance of the social factor does not seem to be appropriate for this sample. Differing from the social factor, the utility of self-identity and social id entity (Tajfel, 1978; Thoits & Virshup, 1997) was confirmed with satisfac tory reliability and validity. First and foremost, the findings provided substantial evidenc e that self-identity and social identity play core roles in the leisure involvement construct. Fu rthermore, each identity operates separately in a different domain, even if some parts of both iden tities are correlated. This result is supported by previous studies related to the relationship bet ween leisure activity and individual and social identity formation (Josselson, 1980; Kleiber & Kirs hnit, 1991; Shaw, Kleiber, & Caldwell, 1995). Particularly, it is consistent with the previous fi nding that sport and physical activities-related leisure activity plays a more active and positive r ole in self-identity and social identity formation (Shaw et al., 1995). Leisure Habit The multidimensionality of leisure habit was identi fied with three sub-dimensions: regular resistant automatic Contrasting with Verplanken and Aarts’ (1999) sin gle habit factor, for the first time this study proposed a multidimensional h abit construct and obtained reasonable reliability and validity in leisure settings. As th e automatic component was slightly lower than the other two factors in its average score, leisure activity is likely to be characterized as partiall y automatic rather than wholly unconscious. Since lei sure has its own intentional, conscious

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173 components such as freedom of choice and intrinsic motivation (Csikszentmihalyi, 1990; IsoAhola, 1979; Kelly, 1987), excluding consciousness associated with leisure is unavoidable. However, at the same time, leisure is closely assoc iated with automatic components such as lifestyles (Henderson & Bialeschki, 2005; Sung, 200 4). Accordingly, partial automaticity (Shiffrin, 1988) appears to be an important compone nt of leisure habit. Specifically, the respondents subjectively perceived that they partic ipate frequently in their favorite leisure activity and felt they would find it difficult not to take part in their favorite leisure activity. Vacation Motivation The motivation items adapted from the leisure motiv ation scale (Beard & Ragheb, 1983) had good internal validity on each of the four fact ors (i.e., socializing, physical, intellectual, and relaxation ) in the vacation setting. However, the intellectua l factor and the other three factors were not strongly correlated with each other in the CFA model, and subsequently the intellectual domain had a low factor loading on the motivation l atent variable in the measurement and structural model, which led to low reliability and validity. The explanation for this is that motivation factors are comprised of a wide range of needs and some factors may inevitably result in low communality, which affects validity and reli ability of the factors in the overall causal model. Ryan and Glendon (1998) also found that moti vations varied, reporting their results that the category of tourists they called “mental relaxe rs” exhibited a high level of relaxation motivation combined with low levels of other motiva tions, whereas, what they called “active relaxers” had high relaxation and mastery motivatio ns, but had medium intellectual motivation and low social motivation. However, the findings of this study demonstrated th at the intellectual motivation of the respondent sample was much higher than other motiva tions. One possible reason that the intellectual motivation was superior is that many r espondents were tourist sports who reported

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174 that they pursued exploring new experiences and nov elty during vacation. Some respondents enjoyed participating in vacation activities that d iffered from their normal leisure activities due to intellectual curiosity. This finding is consiste nt with the findings of previous studies in which intellectual or knowledge motivation is closely rel ated to novel experiences-seeking (Cha, McCleary, & Uysal, 1995; Jamrozy & Uysal, 1994; Oh, Uysal, & Weaver, 1995). Motivation to improve physical skills for their own sake seemed to be rather low because most respondents appear to enjoy recreational sport s as opposed to participating in competitive sport events with high involvement levels in the sp ort (Glyptis, 1982). The item, “to be active” originally included in the physical motivation fact or was much higher in its average score than other physical motivation statements and therefore was deleted to attain validity and reliability on the physical motivation factor. As a result of t his deletion, the mean values of the remaining physical items became lower, demonstrating that mor e respondents preferred being active but did not focus on developing or refining physical skills or abilities during vacations. They focused more on the exploration of new endeavors (Cohen, 19 72; Crompton, 1979; Dann, 1981; Lee & Cropmton, 1992; Lepp & Gibson, 2003, 2008; Uysal et al., 1993), while remaining active at the same time. It is notable that Gandhi-Ahora and Shaw (2002) assumed a negative relationship between novelty-seeking and loyalty to sport touris m, but failed to confirm this negative association. Their results might show the possibili ty that novelty seeking does not mean that people change their value to be active and maintain their behaviors in the same categorical types of activities. Based on basic values and attitudes people possess in a broader context, novelty seeking might rather encourage their consistent beh avior. If leisure motivation was explored instead of vacat ion motivation presumably the physical factor might be higher than other factors with this sample, but vacation motivation appears to be

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175 different. The other plausible explanation is that the respondents in the study sample have a high educational level and therefore have stronger intel lectual motivation. There are no previous studies that have verified if higher intellectual t ourism motivation is connected to a higher level of education, but in specialized tourism such as ed ucational tourism, cultural tourism, or sport tourism, it has been reported that if respondents’ education level is high such as a college degree or over, that intellectual curiosity or learning co mponents are often preferred (Gibson, 1998b; Delpy, 1998; Stoddard, Evans, & Dave, 2008; Wahlers & Etzel, 1985). Vacation Behavior The vacation behavior construct was represented by two factors: participation and decision. This vacation behavior scale consisted of items ada pted from the leisure participation scale and the leisure behavior scale (Ragheb & Tate, 1993; St anton-Rich & Iso-Ahola, 1998), and for the first time, satisfactory reliability and validity w ere established in the vacation realm. In terms of the vacation decision factor, the results of this s tudy showed that the respondents’ certainty about a decision to participate in their favorite vacatio n activities was much higher than other items related to detailed information-seeking behavior. T his is supported by previous studies that uncertainty encourages more information-seeking beh avior (Bennett & Mandell, 1969; Lanzetta, 1963; Reilly & Conover, 1983). Therefore, the certa inty-related items remained for reliability and validity of the vacation decision factor in the SEM model. The results showed that the respondents regularly take part in their favorite v acation activities, and show a high degree of certainty about their previous decisions to partici pate in their favorite vacation activities. This finding can be supported by psychological theories that have assumed the impact of attitudes such as certainty on behaviors (Krosnick, & Petty, 1995; Fishbein & Ajzen, 1975) or the impact of past behavior on attitudes (Bem, 1965; Festinger 1957; Triandis, 1977).

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176 As briefly mentioned above, the social component-re lated item, “I have a network of friends/family with whom I travel to take part in m y favorite vacation activity” was removed from the vacation participation factor. Like the so cial components of leisure involvement, this item was very low in its mean when compared with ot her vacation participation items, and resulted in large residuals and unacceptable reliab ility and validity. Social components consistently appeared weak across all of the findin gs of this study including involvement, motivation and behavior. The most plausible explana tion for this is due to the particular sample that was used. A general population whose members a re involved in various types of leisure and vacation activities was used for this study. This differs from many previous leisure studies, where samples have been largely collected from a ce rtain group engaged in a leisure activity or belonging to a certain leisure organization such as a specialized group of anglers (Bryan, 1979). Another possible reason is that people with a high level of education might also show different psychological and behavioral patterns in leisure an d travel behaviors (Kyle, Kerstetter, & Guadagnolo, 2002), as many studies showed different socio-demographic characteristics led to different travel behaviors (Baloglu, 1997; Goodall & Ashworth, 1988; Kyle, Kerstetter, & Guadagnolo, 2002; Weaver, McCleary, Lepisto, & Damo nte, 1994; Zimmer, Brayley, & Searle, 1995). Certainly, in UK tourism contexts, Urry (199 0) suggests that working-class individuals prefer what he calls the collective gaze, or vacati ons with lots of opportunities for socializing, compared to middle-class individuals who prefer the more solitary romantic gaze. Leisure Involvement Leisure Habit The findings showing a positive relationship betwee n leisure involvement and leisure habit verified many theories which assume that both invol vement at a conscious level and habit at an automatic level reinforce each other, and thereby m ore strongly influence future attitudes and

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177 behaviors (Beatty & Kahle, 1988; Bem 1965; Fazio, 1 986; Miller & Marks, 1996; Triandis, 1977). Even if leisure involvement was not strongly correlated with the wholly unconscious components of habit, it was significantly associate d with the partially automatic components of leisure habit, which may support previous studies r elated to leisure lifestyles consisting of conscious and unconscious components (Henderson & B ialeschki, 2005; Sung, 2004). Leisure Involvement Leisure Habit Vacation Motivation Furthermore, leisure involvement and leisure habit had a significant influence on vacation motivation. Mannell and Iso-Ahola (1987) postulated that the alleged leisure-vacation connection is mediated by psychological components. Likewise, it was evident that those who participated in active leisure and active vacations showed strong motives regarding the desire to participate in their favorite leisure activity whil e on vacation. More specifically, the findings are underpinned by social judgment theory (Sherif & Can tril, 1947), in which previous attitudes affect the judgment of new information, and the jud gments associated with ego value lead to a large latitude of rejecting new incoming alternativ es. Involvement in active leisure is likely to encourage people to participate in active vacations by narrowing their choices into a certain category of activities such as outdoor-related spor ts, water-related sports, or golf/skiing. The findings of this study revealed that people’s choic es were internally motivated by intellectual curiosity, in particular. Supporting social adaptat ion theory (Beatty & Kahle, 1988; Kahle, 1984), the results also underlie that leisure habit, the s o-called well-learned schema, encouraged people to be consistent with their previous attitudes by c ategorizing different or novel external information and objects into the same active vacati on domain (Lewandowsky & Kirsner, 2000).

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178 Vacation Motivation Vacation Behavior The results showed that the strongest direct impact on vacation behavior was vacation motivation, which has been discussed and examined b y various researchers over the years working with the assumption that tourism motivation guides tourism behavior (Crompton, 1979; Iso-Ahola, 1983; Pearce & Caltabiano, 1983). Leisur e involvement or leisure habit did not directly influence vacation behavior in the best-fi t SEM model, but had significant indirect effects on vacation behavior through vacation motiv ation. Notwithstanding that Triandis (1977) assumed that conscious, intentional and automatic, unintentional components could directly and indirectly affect behavior, more attention should b e paid to the fact that this study investigated leisure activity in one realm and vacation activity in another realm. Leisure settings and vacation settings are tangibly and intangibly distant from e ach other, and some constraints on transitioning from leisure to tourism may exist (Crawford et al., 1991; Nyaupane et al., 2004). Surmounting this physical and psychological distance, people mi ght be motivated by specific factors to travel. The indirect effect of leisure involvement and leis ure habit on vacation behavior appears to be a more reasonable account of the leisure-vacation con junction as ostensibly manifested in the final best-fit model rather than a direct influence. Implications of the Study Implication for a New Theoretical Framework of Acti ve Leisure and Vacations This study provided substantial empirical evidence germane to the psychological and behavioral connections between active leisure parti cipation and active vacation behaviors (Brey & Lehto, 2007; Carr, 2002; Currie, 1997; Mannell & Iso-Ahola, 1987). Not only were previous theories and assumptions related to involvement, ha bit, motivation and behavior amplified and further developed, but in addition new findings wer e generated. On the basis of these findings, a newly created theoretical framework of the relation ship between active leisure and active

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179 vacations is proposed in this chapter (Figure 5-1). This theoretical framework is called the Expanded Framework of Active Leisure (EFAL). In the Expanded Framework of Active Leisure (EFAL), conscious (e.g., involvement) and unconscio us, automatic (e.g., habit) psychological components associated with active leisure behaviors reinforce each other, accelerating their synergetic effect on the choice of an active vacati on. Both the conscious and unconscious factors of active leisure behaviors encourage people to be active during their vacations. However, when active leisure is mingled with the unique character istics of tourism, its forms are expanded in the vacation setting. Those who enjoy active vacation a ctivities were segmented into eight groups in this regard. Sport tourists and tourist sports are the basic root groups, which produce eight subclusters. Sport tourists travel to participate in s ports, physical activities, and active outdoor recreation as a primary motivation. Tourist sports participate in sports, physical activities and active outdoor recreation while on vacation, but th e activities themselves are not the primary motivation to travel (Gammon & Robinson, 1997). Spo rt tourists consist of four different groups: (1) sport tourists who participate in the same acti vity as their favorite leisure activity in a famili ar destination, (2) sport tourists who take part in th e same activity in a new destination, (3) sport tourists who participate in different activities fr om their favorite leisure activity in a familiar destination, and (4) sport tourists who take part i n different activities in a new destination. In the same manner, tourist sports are comprised of four s ubgroups: (1) tourist sports who engage in the same activity as their favorite leisure activity in a familiar place, (2) tourist sports who enjoy participating in the same activity, but experiencin g a novel place, (3) tourist sports who seek different activities in a familiar destination, and (4) tourist sports who participate in activities different from their favorite leisure activity, see king a new destination. All these categories emerge from the association between active sport to urism and novelty-seeking tourism

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180 motivation (Cohen, 1972; Lepp & Gibson, 2003; Zucke rman, 1979), which should be further examined in the future. This theoretical framework could not only provide a systematic framework to understand different behavioral active vacation patterns of ac tive leisure participants, but also could help define the degree of novelty and familiarity in ter ms of the association between activity and destinations. A group that seeks the same activity and a familiar destination is at one end of a continuum, while a group that looks for different a ctivities and a novel destination is at the other end of a continuum. This categorical framework can help profile more specific characteristics of leisure participants in each group. Cohen (1972) pr ovided four different types of tourists on the novelty-familiarity seeking continuum and Plog (197 4) connected two personality types, allocentric and psychocentric to emerging destination and mature destination bas ed on destination life-cycle, respectively. In terms of p ush and pull factors, Dann (1977) viewed novelty seeking as a socio-psychological internal p ush factor, whereas Crompton (1979) put more focus on novelty as a cultural motive in terms of a destination pull factor and Zuckerman (1979) suggested that novelty seeking is a type of personality trait. However, neither the push/pull factor destination attribute approach nor the personality explanation can provide a holistic explanation of the complexity of tourist b ehavior. For example, it is difficult to determine whether people who simultaneously seek a familiar activity and a novel destination in the EFAL framework have a novelty-seeking personali ty or a familiarity-seeking personality. Plog (1974) demonstrated that a large number of peo ple are distributed in the mid-centric zone possessing both allocentric and psychocentric chara cteristics. However different characteristics between the familiar activity-novel destination seeking group and the novel activity-familiar destination seeking group should be further examined, especiall y since most tourists are within

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181 these middle zones. Indeed, Yiannakis and Gibson (1 992) using multidimensional scaling found that active sport tourists tended to prefer moderat e levels of familiarity and novelty consistent with Cohen’s (1972) independent mass tourist or Plo g’s (1974) midcentrics. Considering all the previous theories suggested by Cohen (1972), Plog ( 1974), Dann (1977), Crompton (1979), and Zuckerman (1979), the researcher hypothesizes that the group characterized as the familiar activity-novel destination segment might be more in fluenced by destination pull factors, whereas the group included in the novel activity-familiar d estination segment might be more affected by internal push factors, but there is a need for thes e groups to be further studied. Implication for Applied Settings Both the sport tourists and tourist sports were str ongly motivated to be active, and therefore the causal paths from active leisure to a ctive vacation of both groups showed the same patterns. Moreover, many sport tourists and tourist sports not only preferred taking part in the same activities, but also choosing different sports physical activities, and active outdoor recreation from their favorite leisure activity for their vacation activities. Some people attempted to expand their experience by making a choice of di fferent activities, but still remained in the same general activity category. For example, the fi ndings demonstrated that those who enjoyed walking during leisure expanded their vacation acti vity to hiking, but still remained in the same line of outdoor-related sports. Some sport tourists preferred swimming for their leisure activity, but this swimming was diversified into water sports or beach activities in the tourism contexts. Other sport tourists modified their bicycling durin g leisure to mountain biking while on vacation. Some people seemed to have links such as locomotion from walking (i.e., leisure activity) to bicycling (i.e., vacation activity), yet choosing a ctivities in the same domain. Others demonstrated a shift from hiking (i.e., outdoor-rel ated sports) to water sports or golf/skiing and other sport tourists changed their favorite domain, as well.

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182 On the other hand, many responses provided by touri st sports included activities such as hiking and other sports, physical activities and ac tive outdoor recreation for the purpose of exploring or experiencing “something new” during th eir vacations. Indeed, Standeven and de Knop (1999) postulated that sport is a cultural exp erience of physical activity and tourism is a cultural experience of place. Similar findings that “something new” specific to different cultures and the nature of destinations were revealed by thi s study. The tourism literature also shows that novelty seeking is closely related to the cultural experience motivation (Crompton, 1979; McGehee, Loker-Murphy, & Uysal, 1996). Nevertheless, it was obvious that respondents did n ot discard their active leisure values during vacations, but rather their active leisure v alues blended with the unique experiences acquired through tourism. Some people reported that they enjoy golf as their leisure activity, but described their favorite vacation activity as viewi ng scenery in different places while playing golf. These responses demonstrate two elements: 1) the generation of tourism cultures through sports as often noted in the previous sport tourism literature (Bull, 2005; Hinch & La Barre, 2005), and 2) the maximization of destination attra ctiveness through the combination of sports and other local authentic cultures and natural sett ings. As an example, the first element is related to nostalgia sport tourism, such as touring Olympic stadiums or museums (Gibson, 1998a, 1998b), which is centered on the subject matter of sports. As an additional example of the first element, Newquay, Cornwall was a small fishing vill age in southwest England but was transformed into a famous surfing destination inclu ding surf shops, schools, accommodations and bars, and is often visited by many backpackers who enjoy surfing (Bull, 2005). Accordingly, some tourism advertisements emphasize images associ ated with destination-specific sport activities and events to attract sport tourists (Hi nch & La Barre, 2005).

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183 The second element relates to tourism resources and sport resources which are different but have a synergetic relationship with each other, rat her than tourism resources which are developed for sports. Getz (1998) underscored the importance of real local values experienced by sport tourist visitors, the so-called authentic cultural experience. Combinations such as “playing golf and dining on unique local foods,” “hiking and lear ning local history,” “climbing, looking for unique local scenery and nature, and photographing that scenery,” and “canoeing and taking part in local community ecotourism courses” are examples of the second element. Indeed, in a study of golf tourists, Gibson and Pennington-Gray (2006) found that while pure golf tourists do exist, the majority of golf tourists blend golf with a ran ge of other tourist activities. Perhaps, there is a difference between the active sport tourists and to urist sports surveyed in this study compared to the previous literature where the overall finding h as been that event sport tourists in particular tend to be “sport junkies” (Faulkner et al., 1998) and interested in very few other tourist-related activities (Gibson, Willming, & Holdnak, 2003). In this study, some active sport tourists are also interested in destination specific characteristics. For example, a participant in bicycling during leisure preferred bicycling during vacations and at the same time, was interested in local history tours. Taken together, the active leisure and active vacat ion patterns seem to call for the creation of new, comprehensive programs, policies, products, and marketing strategies. First of all, if the supply side provides people with vacation products or programs using activities in the same category as their leisure category, these products or programs might be more attractive to them. For example, if marketers or policy makers can prom ote a variety of outdoor recreation sportsrelated programs or products in tourism destination s, this might be attractive to physically active

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184 people and help them maintain a consistency of life style between their everyday and their vacation context. Furthermore, given that there are tourist sports wh o want to experience different destinations but who are eager to take part in the same activity as their favorite leisure activity, specific programs to keep satisfying these needs al ong with easy access to this information has not been provided until fairly recently. Some touri st sports may want to participate in, for example, various cultural heritage tours by hiking or bicycling, and other tourist sports may prefer canoeing and experiencing unique local scene ry and cultures while on vacation. Some tourist sports might want to interact with local pe ople and satisfy their intellectual curiosity about local culture such as foods and sports, taking part in their favorite leisure sports with local people through tourism opportunities. Yiannakis and Gibson ’s (1992) comment that individuals may choose more than one tourist role on a single vacat ion is noteworthy in this regard. Familiarity of favorite leisure sports might facilitate sharing co mmon interests in order to interact with local people and learning interesting aspects of cultures while mediating the strangeness and novelty of a new environment. In the same manner, if sport tourists want to enjoy different activities in a familiar place, policy makers or product developers should ask if t here are satisfactory and viable programs for these people. Some tourists may feel more comfortab le visiting a familiar destination (Cohen, 1972), however they may want to experience differen t physical activities on their vacations. They may want to look for trekking this year, horse back riding next year, and mountain biking after that, all in a familiar destination and perha ps for convenience using the same travel company. On the condition that a travel company can offer these products and programs through networking with other agencies or organizations, th ey could satisfy their customers’ needs,

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185 thereby retaining “loyal” active tourist consumers in the long term (Petrick, 2002; Prichard et al., 1999; Selin, Howard, & Cable, 1988). It appears that while the niche market of sport tou rism is growing and sport tourists’ needs and requests are evolving rapidly, suppliers may no t have kept up with providing programs or products suitable for meeting their customers’ dema nds. As a result of this delayed reaction, some active sport tourists have created programs an d products themselves and are actively involved in the sport tourism destination developme nt process. For example, the sport teams and the administration sides of professional sporting b odies work together to develop an optimal environment for their teams’ performance, consideri ng all the elements of both on and off the sports field such as facilities, accommodations, at tractions, food and beverage, services, and retail businesses (Francis & Murphy, 2005).The role of active sport tourists is no longer assigned to that of receptors who simply consume products of fered by suppliers and the traditional roles of providers and demanders are changing steadily in the sport tourism market (Amis & O’Brien, 2001). The involvement of active sport tourists in destination development beyond products development is making it feasible to have more sens itive and sophisticated approaches to meet their needs and to be responsive to the environment based on their previous experiences. Therefore, strategic partnerships and collaboration s between traditional providers (e.g. travel agencies and government and event organizations) an d unconventional providers (e.g. sport tourists) must be considered in the future planning process of sport tourism and tourism sport markets. A more systematic, comprehensive, and cooperative a pproach to facilitating the expansion of active leisure is needed, paying heed to the bes t way to keep people active. From this perspective, this study provides empirical informat ion germane to conjoint leisure-tourism

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186 patterns. In particular, going beyond providing a p sychological and behavioral causal path between active leisure and active vacations, a theo retical framework developed from a substantial sample exemplifying different stages of the leisure-tourism continuum was established and could serve as a viable guideline i n applied settings in the future. In particular, it seems that different products, ma rketing strategies, and promotions for eight segments in the EFAL profile should be develo ped by obtaining more information about each of the target eight groups with a larger sampl e in future research. An interesting study conducted by Woratschek, Hannich, and Ritchie (2007 ) identified four cluster groups, Scene Climbers, Adventure Climbers, Novelty Seeking Touri sts, and Sport and Leisure Tourists based on the different motivations of rock climbing parti cipants, and further found specific destination attributes preferred by those types of sport touris ts. Scene climbers and adventure climbers were more focused on needs directly connected to climbin g such as climbing tourism infrastructure, climbing scene venue, climbing conditions, and clim bing novelty seeking, whereas novelty seeking tourists and sport and leisure tourists wer e interested in other attributes besides climbing such as destination novelty seeking and non-climbin g sports and leisure activities. More specifically, adventure climbers preferred more nov el climbing experiences, whereas scene climbers tended to like more quiet and convenient c limbing conditions. More novelty seeking tourists were pushed by destination cultures and no n-climbing sport and leisure activities, whereas more sport and leisure tourists were motiva ted by a variety of sport and leisure opportunities and general tourism attractions. Wora tschek et al.’s four different groups are likely to be explained within Gammon and Robinson’s (1997) sport tourist and tourist sport categories. The former two groups are likely to correspond to s port tourists and the latter two groups seem to be tourist sports. Also these needs pursued by the four groups seem to be similar to the findings

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187 of this study that there were sport tourists who pr eferred developing the same leisure activity either in new or familiar environment and tourist s ports who preferred experiencing different activities and unique attractions of different dest inations even though the respondents of this study were more extensively segmented. Woratschek e t al. (2007) briefly suggested that in terms of destination attributes to be offered for each gr oup, sport and leisure tourists might enjoy well developed tourism infrastructure including diverse sports and leisure opportunities, whereas calm, natural climbing environments without a need for ma ss tourism facilities would be attractive to scene climbers. Their suggestion is likely to be a useful base for not only further investigating more specific destination attributes, but also for providing more practical marketing strategies in the specified segments of the active leisure-active vacation participants of this study. Woratschek, et al.’s (2007) destination attributes associated with leisure activity seem to be a basic example for further establishing marketing strategies for eight segments provided by the EFAL framework. Detailed marketing strategies canno t be provided in this study because this study did not reveal sufficient information about e ach segment, however broad level planning and marketing strategies can be described here. “Se gment A” (i.e., sport tourists who take part in the same activity at a familiar destination) may be serious sport tourists. Those people prefer developing their skills or abilities associated wit h their favorite leisure activity. Accordingly, thi s segment may show a greater likelihood of becoming l oyal customers of both travel providers and destinations. For example, while the Segment B golf ers prefer experiencing different golf courses at different destinations, the Segment A go lfers want to play golf every year at the same destination during vacations. To promote the destin ation or place, suppliers or marketers should investigate what Segment A golfers liked about this destination, and should reflect their feedback in their future strategies to maintain their loyal customers. In terms of promotional message

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188 content, using rational appeals would be better rat her than using emotional appeals for this group, because this target group has already experienced t his destination and seems to be interested in improving their golf skills, rather than choosing a new destination. Furthermore, using relationship marketing as a form of direct marketin g is likely to be more useful for this group rather than using indirect marketing such as newspa per or TV advertising. For example, an individual email contact providing detailed informa tion about loyal customer programs, rewards, and benefits is likely to be effective. Also, devel oping and promoting a variety of programs related to different courses to improve their activ ity skills at the destination may be critical to maintaining loyal customers. This might encourage t hose participants to visit the destination more frequently. Additionally, marketing strategies using a social networking system of the agent or the destination organization to increase t he interaction between providers and customers as well as among participants may be effective for this segment group. “Segment B” (i.e., sport tourists who participate in the same activity at a novel destination) may be “stable sport tourists.” This group has a high likelihood of using an intermediary travel body (e.g., using the same trav el agent). Those people may tend to like taking part in the same activity as their favorite leisure activity with their social group, preferring to visit different destinations. For example, hikers w ant to experience different mountains and nature, but they prefer using a travel company that can provide information about interesting destinations for hikes with their group members. Th is segment is likely to be loyal customers of private travel agents rather than national, state, or local tourism organizations. An effective marketing strategy would be that the travel company creates its own social networking site such as Southwest Airlines’ Nuts about Southwest so that their customers can interact with each oth er through this networking system. Through monitoring this interaction, the agent could gain useful

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189 information about specific attributes of certain de stinations where their customers are likely to prefer visiting. Particularly, relevant information should be provided aggressively for customers who want some challenges, for example, those lookin g for a particular destination with more difficult hiking routes. If the travel company can recommend destinations of a certain challenge level, this will be a good marketing strategy for t his segment. However, the travel company should have partnerships with sports-related organi zations of different destinations as well as national, state, and local destination organization s such as Convention and Visitor Bureau (CVB) so that necessary services and products can be prov ided for the customers. In terms of effective ways to promote, word of mouth marketing through so cial networking systems as well as publications utilizing audiovisual materials would be useful for this group. For “Segment C” category (i.e., sport tourists who take part in different activities at a familiar destination), these people have a greater possibility of choosing a familiar destination because of its easy accessibility and because it po ses less constraints to enjoying a vacation with their family members (e.g., children, parents, and grandparents) and with friends. Instead of travel companies, destination organizations may be better managing this group. Destination organizations need to investigate what kind of acti vities this target group has taken part in before and prefer to participate in. On the basis of this information, promoting sport-related attractions such as a grouping of similar recreational activiti es (e.g., “running, hiking, and bicycling,” “walking, camping, and horseback riding,” “swimming scuba diving, and water skiing,” “snorkeling, kayaking, and fishing,” etc) on the de stination website may be an effective marketing tool for attracting them. The organizatio ns need to retain and upgrade their visitors’ database, regularly. Furthermore, collecting data a bout this segment’s preferences and providing them with novel activities may be helpful for the l ong-term management of this group. In

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190 addition, the creation of new events may be a power ful promotion strategy because this group prefers experiencing new activities in a familiar d estination. Furthermore, promoting sales-andprofit contributions to the encouragement of health y and active lifestyles of people through this kind of event may make event participants feel more attractive about the event. “Segment D” (i.e., sport tourists who take part in different activities at a novel destination) might be adventure tourists who enjoy adventure spo rts. This segment may prefer activities combined with specific destinations in a unique way : for example, hiking combined with a particular mountain; bicycling associated with a sp ecific trekking course; camping combined with a particular campsite location; horseback ridi ng associated with a specific place. This segment may tend to change their sport and recreati onal types of activity by traveling to different destinations. It might be harder to understand the behavioral patterns of this group as compared to the aforementioned groups. Therefore, it is sugg ested that after investigating information sources this group uses, suppliers should generate an interconnected system among the different information sources. This informational connection may be a useful base not only to create new products for potential customers with similar inter ests, but also to understand their behavioral patterns in a certain extent. For example, there ma y be several main information sources if this group is looking for particular mountains combined with hiking. Similarly, there may be other main information sources if they are seeking certai n trekking courses to run or bicycle and other main information sources to look for scuba diving c ombined with preferred destinations. Along with the establishment of an interconnected system among these sources, trips could be created and promoted. Posting this network on the main webs ite of the supplier would be informative and a good promotional tool. In addition, providing a counseling program for this group would be helpful for suppliers to create specialized form s of tourism fitted to customers’ preferences

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191 and needs and thereby increase customers’ satisfact ion. The supplier should establish a multichannel marketing system rather than a convent ional marketing system for effective partnerships with different destination sport and r ecreational organizations. Sponsorship can also offer discounted prices to this sport adventure gro up. “Segment E” (i.e., tourist sports who participate i n the same activity at a familiar destination) may be structured sports habituators w ho habitually participate in their preferred leisure activity during their vacations. Unlike the four aforementioned groups, their primary tourism motivation is not to take part in sports. F or example, these people prefer to keep running, swimming or using the gym in familiar destinations, however their primary vacation motivations lie in other activities not sport. Accordingly, one of the most important management skills may be related to maintaining the quality of facilities at the destination. Moreover, local tourism organizations should investigate the kind of touris m activities this group may take part in. After this investigation, tourism organizations can promo te good places to take part in their habitual physical activities combined with their preferred t ourism activities at the same destination. Relevant magazines or brochures promoting tourism a ctivities should be displayed inside sport and recreational facilities. Additionally, particul ar tourism programs or activities that this segment prefers experiencing can be offered nearby or developed alongside the sport and recreational facilities. Perhaps, more diverse heal th-themed tourism activities other than sports and physical activities may be attractive to this g roup. “Segment F” (i.e., tourist sports who participate i n the same activity at a novel destination) has a high possibility to experience the culture an d natural environment of new destinations during their vacations. Their sport and physical ac tivities may be habitual like “Segment E.” In this case, providing trips to different destination s combined with chain-brand accommodations

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192 including sport and recreational facilities dispers ed over the world may be appealing to them. That is, providing programs for experiencing cultur es of different destinations along with stable environments to maintain their habitual physical ac tivity may be appropriate. An emotional appeal may be a better way to promote tourism attra ctions than rational and persuasive appeals for this group. “Segment G” (i.e., tourist sports who participate in different activities at a familiar destination) may be people who prefer taking part i n different recreational activities with their friends or family while visiting them. This group h as a high possibility of engaging in more family-oriented sports/recreation and tourism activ ities while spending time with them. Their sports and recreation activities may be extended to encompass different types of activity as well as within the same activity. For example, those peo ple might be involved in water-based sports or golf/ski on vacation rather than their favorite leisure activity, outdoor-related sports. Suppliers should investigate what kinds of leisure activities family members or friends are engaged in. Based on the connection among favorite activities o f their family members or friends, a recreational package such as biking-running-hikingswimming may be provided so that everybody can enjoy the activities together. Market ing strategies centered on more familyoriented or social interaction-focused tourism prog rams may be more attractive to this group. “Segment H” (i.e., tourist sports who take part in different activities at a novel destination) may be active explorers. This segment might be the hardest group to predict in terms of their behavioral patterns among the aforementioned segmen ts. This segment’s vacation activities may tend to vary, encompassing a variety of cultural an d entertainment activities blended with sports or recreational activities. These active explorers may participate in unique local sport events or competitions with local residents as a way of exper iencing local cultures and may tend to be

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193 more cultural curiosity-oriented. Accordingly, a hi king program to experience unique cultures and nature, or a paddling experience taking them in to remote locations might be attractive to them. Using both informative and emotional appeal s trategies would be a more effective promotion way for this group. It is suggested that multi-level marketing strategies through partnerships among travel agents, specialists, loca l/state/national organizations, and global distribution should be implemented with short-term and long-term plans. Overall, the aforementioned segments are people who tend to consider “being active” as one of their most important values and simultaneous ly have a higher level of education and are high in intellectual motivation for travel. Accordi ngly, university-centered marketing strategies may be a good way for promoting vacation activities and tourism programs, possibly through alumni association magazines and brochures with an emphasis on images related to active lifestyles combined with cultural experiences. Furt hermore, other than the aforementioned marketing strategies for each segment, there may be a possibility that people might transition from one segment to another with the impact of mark eting strategies. For example, people in Segment A could change their behavioral patterns to Segment B. Given strong informative and persuasive appeals explaining how much better this type of vacation could be to develop their favorite sports and physical activities at differen t destinations, Segment A changes their previous beliefs or attitudes and thus, becomes included in Segment B. In this manner, the transition from Segment B to Segment C or the extension from Segmen t A to Segment B and C may be possible. All the marketing strategies mentioned above were t o facilitate the segments to maintain or develop their active leisure lifestyles in differen t tourism environments away from their routine. However, there is a need to emphasize the importanc e of involvement and habit factor in developing leisure lifestyles. This study found tha t involvement and habit are triggers for

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194 encouraging people to extend active leisure lifesty les to vacation environments. More importantly, weak involvement and habit in leisure activity could be converted by proactively providing vacation information and programs in whic h individuals are encouraged to take part in active vacations. In other words, engagement in vac ation activities could increase the strength of involvement and habit in active leisure. Active vac ations may play an importance role in enhancing active leisure lifestyles. Furthermore, t he encouragement of the reciprocal relationship between vacation and leisure will be useful for ena bling people to maintain their healthy lifestyles in the long term. Although people may no t have strong habits and involvement with physical activities in their routine life, special experience during vacation may produce a motivation to be more involved in active leisure on ce they return home. It is assumed that providing information about acti ve vacation and relevant vacation programs would influence active leisure involvement and habit, positively. In particular, informing people about the location of sport and re creation facilities in tourism destinations may prevent them from abandoning their active lifestyle s while on vacation. When people travel away from home, they may face some constraints and disco ntinue keeping active and healthy lifestyles (Crawford et al., 1991) and become more sedentary a nd eat unhealthy foods. Providing a list of best places for activities by distributing a free b ooklet including this information as well as posting it on destination websites would give peopl e more chances to be active, possibly encouraging stronger habit and involvement in activ e leisure activities. Furthermore, information about the best time (i.e., when) for participation along with the list of places (i.e., where) would help people to preplan their future vacations in an organized way. This would be a good way to strengthen people’s self-control feelings toward th eir active and healthy life.

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195 In terms of a macro-level policy to promote healthy and active leisure lifestyles (i.e., increasing leisure involvement and habit) through v acation opportunities, building physical environments designed for those within the active l eisure-tourism connection should be a longterm plan. Furthermore, public campaigns in vacatio n places are likely to be influential in enhancing involvement and habit in physically activ e leisure. All these attempts may contribute to not only reinforcing the existing involvement an d habit, but also creating new ones. Taken together, giving information and benefits, providin g attractive programs to connect active leisure to active vacation or active vacation to active lei sure, and establishing physical environments and policies supportive for this connection would contr ibute to active and healthy lifestyles. Recommendation for Future Research Six suggestions for future research are proposed. F irst, it is suggested that the utility of the social connection items of leisure involvement and vacation behavior are retested using different samples. The respondent sample did not exhibit very strong social bonding or networks centered on their leisure and vacation activities. Although most respondents enjoyed talking with family or friends about their favorite leisure activity an d had a high level of vacation motivation to have a good time with friends, their agreement level wit h the “social connection and network formed through leisure and vacation activities and a vacat ion” was not strong and therefore a motivation to gain “a feeling of belonging” was weak as well. Since it is not clear whether these results emerged due to the characteristics of the sample or the utility of the items, it is likely to be necessary to reinvestigate it with different target samples, particularly since socializing or social bonding motives are frequently noted in the existin g tourism, leisure and sport tourism literature (Fairley & Gammon, 2005; Kyle & Chick, 2002; Smith & Turner, 1973). Second, more in-depth studies with respect to indiv iduals classified as sport tourists and tourist sports with a larger sample size are recomm ended. No difference between sport tourists

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196 and tourist sports in their causal paths was presen ted, and thereby both groups were combined for the study analysis. However, Gammon and Robinson (1 997) distinguished hard sport tourism (i.e., competitive sport activities) from soft spor t tourism (i.e., recreational sporting activities) as well as hard tourism sport (i.e., secondary motivat ion) from soft tourism sport (i.e., minor form). In light of this distinction, most of the responden t sample seemed to be soft sport tourists who take part in recreational sport forms and hard tour ist sports who participate in recreational sports as a secondary motivation. This may be why differen t patterns between sport tourists and tourist sports of the sample were not manifested in the res ults. Provided that a sample consists of both hard sport tourists and soft tourist sports, the ca usal path-relevant results between both groups might be distinct. Furthermore, this second issue m ight be intimately correlated with the first issue relevant to social networks mentioned above. There is a possibility that most of the family or friends of hard-core sport tourists who have hig h levels of commitment and take part in competitive sport events (Stebbins, 1982) could be mainly connected to their leisure and tourism activities. Third, it is recommended that a better way to inves tigate the types of favorite leisure activity and vacation activity be developed for fut ure research. Some respondents reported a combinational form of several activities even thoug h they were asked to describe one of their most favorite activities. Consequently, it was diff icult to distinguish which of the information obtained from the open-ended question was primary a nd which was secondary. It is acknowledged, however, that it is very hard for one activity to be selected especially for tourist sports because some of them have an equal preferenc e for several activities, and moreover some activities are best illustrated as an aggregate for m. As already mentioned in the instrument section, in the preliminary Paddle Florida study to assess the utility of a categorical multiple

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197 choice question asking about types of favorite leis ure and vacation activities, it was revealed that the categorical dimensions made it hard to provide a clear boundary between one activity and another. Consequently, for this study, an open-ende d question was created in order that the weakness of the categorical question was eliminated yet some complementary device still seems to be necessary. It would probably be better if re spondents were asked to list their favorite activities in order of priority, as suggested by on e of the content validity expert panelists. Fourth, the investigation of more specific informat ion within each segment of the Expanded Framework of Active Leisure (Figure 5-1) i s recommended with a larger sample size in order to further improve marketing strategies, p rograms, and policies. Priestley (1995) posited that sports are good opportunities through which to experience tourism destinations, and therefore specific sports associated with specific destinations can increase the attractiveness of travel. Sports and unique cultural attractions of d estinations seem to interact dynamically with each other, maintaining the balance between physica l motivations and intellectual or novelty motivations in a complementary way (Hall et al., 19 91; Hinch & La Barre, 2005). Accordingly, not only would personality and specific lifestyles of the respondents included in each categorical domain be important for an in-depth understanding, but information about more specific destination attributes preferred by each segment be yond two distinctions of familiarity and novelty suggested by Cohen (1972) or Zuckerman (197 9). For example, for some people who want to participate in a familiar activity, visitin g novel destinations, it is necessary to examine what kind of destination attributes should be provi ded to participate in a familiar activity and at the same time to experience a novel destination. Furthermore, it is recommended that the influence o f demographic factors such as gender, age, education, income, and nationality might affec t preference for each segment in the EFAL as

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198 well as exhibiting different patterns in the leisur e-vacation connection with a larger sample size. For example, Lepp and Gibson (2008) found that male s have higher novelty or sensation seeking motives than females in travel. Galloway, Mitchell, Getz, Crouch, and Ong (2008) found that higher novelty seeking people had higher income and higher education than lower novelty seeking people in wine tourism, but there was no si gnificant difference in age. Pizam et al. (2004) found that individuals from 11 different cou ntries were significantly different in their levels of perceived risk (Jackson, Hourany, & Vidma r, 1972) and sensation seeking (Zuckerman, 1979). Therefore, it is suggested that the influenc e of these characteristics are examined in relation to the active leisure-active vacation real m. Moreover, if perception of health and detailed lifestyles of the active leisure-active vacation pa rticipants are examined for future research, it would be more helpful for an in-depth understanding of their behavioral consistency. Fifth, it is suggested that the active leisure-vaca tion patterns and the non-active (i.e., passive) leisure-vacation patterns be compared in t erms of a causal path model. The findings showed that a positive causal relationship between leisure involvement, leisure habit, vacation motivation and vacation behavior was found with the target people who were involved in active leisure and active vacation, but would non-active l eisure-vacation participants show different patterns from active leisure-vacation participants? In particular, the degree to which involvement and habit with non-active leisure activities should be examined to see if the same patterns regarding active leisure and active tourism are obs erved. Accordingly, it could be determined whether the extension of the leisure-tourism contin uum to the non-active leisure realm would be possible. Furthermore, it will be necessary to exam ine psychological elements of some examples in which non-active leisure is developed leading to active leisure, and, conversely, in which active leisure leads to non-active leisure.

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199 Finally, it is suggested that a longitudinal study should be conducted using the same variables, leisure involvement, leisure habit, vaca tion motivation, and vacation behavior for future research. Over long periods of time, such as consisting of one year, three years, and five years, whether people are still involved in the sam e favorite leisure activity and vacation activity should be investigated, and if they are still in th e same leisure activity, whether their involvement and habit have been changed should be further exami ned. Observing how much the strength of leisure involvement and habit has changed by polici es or marketing strategies supporting the leisure-tourism connection would be useful for deve loping new ways to encourage active and healthy lifestyles such as through the leisure-vaca tion link. Delimitations This study was delimitated to the members of the UF Alumni Association. This affects the generalizability of these findings in several ways. As the UF alumni sample represents a collegeeducated population, the findings may be generalize d to other college-educated people with similar backgrounds. Also, as almost all the sample respondents were residents of the United States, this sample might be generalized to the US residents in terms of nationality. As this study used a web survey, the respondents’ ability to comp lete the survey due to potential limitations such as Internet access might have affected the com position of the sample, because people with certain socio-demographic characteristics might be more or less likely to use the Internet. However, for this study population, this is not lik ely. As such, this may have further affected the generalizability of the findings. Limitations To reduce the possible limitations that might have harmed the purity of the study, the face validity and content validity of the questionnaire were established by carefully considering details such as item wording, the order effects, so cial desirability (Paulhus, 1984), and response

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200 bias. Relevant to the response rate, since a low re sponse rate of a web-survey (Dillman, 2000) might have inhibited significant results in examini ng numerous parameters of structural equation modeling, a user-friendly questionnaire and a remin der were employed to help overcome this potential limitation. However, regarding the open-ended questions that re quested the respondents to identify one favorite leisure activity and one favorite vaca tion activity, a few of the respondents identified a number of activities, which made it hard to disti nguish between primary and secondary activities. Thus, the first named activity was trea ted as the favorite activity in each case and activities listed thereafter were treated as second ary activities. This might influence the internal validity of the data and ultimately the results rel ated to the other constructs such as involvement, habit, motivation, and behavior that were subsequen tly connected to the types of favorite leisure and vacation activities. However, as involvement, h abit, motivation, and behavior are subjectively perceived, it is assumed that individu als who have more than one favorite leisure activity or vacation activity would be consistent i n their subjective evaluations of these activities. Conclusion This study examined the ways active leisure is asso ciated with active vacations, using leisure involvement, leisure habit, vacation motiva tion and vacation behavior as explanatory constructs. The study confirmed the multidimensiona lity of each construct using CFA models and further found a significant causal relationship between the four psychological and behavioral constructs, upholding previous theoretical assumpti ons concerning the leisure-tourism continuum (Carr, 2002; Currie, 1997) using measurement models and structural equation models. Distinct from Brey and Lehto’s (2007) study, this study prov ided empirical evidence that psychological connections between leisure and tourism exist beyon d behavioral patterns. Furthermore, in a more specific way, analyzing the psychological and behavioral patterns between favorite leisure

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201 and vacation activities, this study not only establ ished the Expanded Framework of Active Leisure (EFAL) and contributed to a growing body of knowledge on sport tourism, but also offered practical suggestions as to how applied are as should develop further marketing strategies, vacation programs, and relevant policies for sport tourists and tourist sports on the active leisurevacation continuum. Almost thirty years ago, Glyptis (1982) predicted t he growing popularity of recreational forms of active sport tourism rather than large sca le competitive event sports and passive sport tourism. Consistent with her anticipation, most res pondents of this study sample, which was randomly selected from a more general population in stead of being selected from sport tourist samples belonging to certain events or places, fell into the soft sport tourist and hard tourist sport domains (Gammon & Robinson, 1997). Sports, coupled with unique cultural and natural attractions of destinations, seem to be more attrac tive stimuli to those people who want to maintain their active values in a recreational spor ting form. However, gaining more detailed information germane to the destination attributes p referred by each segmented group in the EFAL will be essential for future research with a p articular focus on the novelty and familiarity preferences of the different sport tourists and tou rist sports. In addition, it is suggested that soci al components of the psychological constructs and inte llectual vacation motivation be retested, using larger, different samples, possibly consistin g of different types of sport tourists such as hard sport tourists and soft tourist sports.

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202 Figure 5-1. Expanded framework of active leisure (E FAL) Unconsious psychic (Habit) Conscious psychic (Involvement) Different activity Same activity Different activity Sport tourist Novel destination Novel destination Familiar destination Familiar destination Same activity Novel destination Novel destination Familiar destination Familiar destination Tourist sport Vacation/ tourism motivation Active leisure Active vacation/ tourism Segment A Segment B Segment C Segment D Segment E Segment F Segment G Segment H

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203 APPENDIX A DEFINITIONS OF INVOLVEMENT Authors Areas Definitions of involvement Johnson and Eagly (1989) Social psychology Motivational state induced by an association between an activated attitude and some aspect of th e self-concept Day (1970) Marketing The general level of interest in the object or the centrality of the object to the persons’ ego-struct ure Robertson (1976) Marketing Strength of the individu al’s belief system with regard to a product or brand Houston and Rothschild (1978) Marketing Situational involvement is an ability of a situation to elicit from individuals concern for their behavior in that situation. Enduring involvement reflects the strength of the preexisting relationship between an individual and the situation in which behavior will occur. Response involvement is the complexity or extensiveness of cognitive and behavioral processes characterizing the overall consumer decision process. Mitchell (1979) Marketing An internal state variabl e that indicates the amount of arousal, interest, or drive evoked by a particul ar stimulus or situation Bloch (1981) Marketing An unobservable state reflec ting the amount of interest, arousal or emotional attachment evoked by the product in a particular individual Rothschild (1984) Marketing A state of motivations, arousal, or interest, which exists in a process driven by current external variables and past internal variables Manfredo (1989) Marketing The degree of interest in the product and the affective response associated with it Selin and Howard (1988) Leisure The state of identification existing betwee n an individual and a recreational activity, at one poin t in time, characterized by some level of enjoyment and self expression being achieved through the activity Havitz and Dimanche (1997) Leisure An unobservable state of motivations, arou sal or interest toward a recreational activity and have developed multidimensional scales for leisure involvement construct premised on leisure activitie s Shaw and Havitz (1999) Leisure A relatively enduring attitude or value co nsisting of several sub-dimensions Kyle and Chick (2002) Leisure A cognitive link between the self and stimu lus object

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204 APPENDIX B INSTITUTIONAL REVIEW BOARD APPROVAL FOR CONTENT VAL IDITY

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208 APPENDIX C SURVEY INSTRUMENT FOR CONTENT VALIDITY nrrrrrrrrrr rr r !!!"#r! !r !rrrr $rr rrrr" rrrnrnnrr rnnr nrrnnrnn nrnnrn r!n!nr"r#$n%&&' ()n *++, ( )(n&&(rrn&&& $rnrnnrn rrrnr nnn.n$ rrrnn nnn nrr -n/0rnn 1nrr21nrr Evaluation for the Content Validity 5=Excellent, 4=Good, 3=Acceptable, 2=Poor, 1=Unacce ptable Relevance Representativeness Clarity 3rnrnnr 4r5rnrnn Factor 1 Hedonic (Emotional) rnnrnrnnnnnnnn4 4nnrnrnnrnrnn 3rnrnnnrnn 4nr%rrnrnn 3rnrnnnrr 4rnrrnrnnnnn Factor 2 Centrality 3rnrnnrnn

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209 Evaluation for the Content Validity 5=Excellent, 4=Good, 3=Acceptable, 2=Poor, 1=Unacce ptable Relevance Representativeness Clarity 3nrrnnrnrnn 45rnrnnnr 3nrrnnrnrnn Factor 3 Social 3rnrnnrnn%nr 3rnrnnrn4 3rnnrnrnnnnn 4nnnrnrnnnrnrnn Factor 4 Self-identity 4rnnrnrnn(nrn4nnn 4nnnnrnrnnrnrnn r4rnnrnrnn(4nnnnnrnnn 4n0nnrnnnrnrnn(nrnnrn Factor 5 Risk 44rnnrnrnnrnr(4n

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210 r%&rn12rrnn6r0# 7r*++8 8 $rnrnnrn rrrrn rnn$rrr nnnnn -n/0rnn1nrr21nr r Evaluation for the Content Validity 5=Excellent, 4=Good, 3=Acceptable, 2=Poor, 1=Unacce ptable Relevance Representativeness Clarity 4n0rnnrnnrn 4n0rnnrnnrn rnnnrn Factor 1 Regularity rnnn9: 4nrnnnn 4nrnnnnn0 4nrnnrnnr4r%4n 4nrnnnnnrr Factor 2 Automaticity 4nrnnn0nnrnn rnnrrrnnnn 4nrnnn0rnnrnn Factor 3 Resistance rnn0r4nn rrr'rrr' ,$nrrnnr nn*n rnn rrnrnn;;!nrr-;?r

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211 =$nnn0rnn rrnrnn ;08;=0,;,0 =;80>;2*0-;?r >$nr@n r rnnrrn rnn;?r*;/n8+n8;8+2>+n,;>2&+n =;&2*+n>;*2=+n-;3rn=+n rrr'rrr(r)r rnrrnnr rnrnn ;!nn*;!nn8;3nnn ,;!nnn=;/nnn>;?nn $nrnnrr nrnnrnn nr ;!*;Arn8;7,; ?r & Bnnrnnrrn rnnrrnnCn rDrnn282*2+*8Drn +$0nnnrnrn nrrnrnnrr nnCnr6r0282*2+*86r0 *n)r+rrr)rrrrrrr r$! $r"#r! !r rrrr $rr rrrr ,"" rr rr r rr -" )rrrnnrnnrrr nn n nrrnnnnn 4rrnnnn rrnrnn(rn nn

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212 )r+r.rrn/r3nn1rnrr(8*n Er#F&'8 nn@nr nnnn rnF#"(&&' *$rnnnrrr nn0rnrrnn nn$rrrnn nnn-n/0rn n1nrr21nrr Evaluation for the Content Validity 5=Excellent, 4=Good, 3=Acceptable, 2=Poor, 1=Unacce ptable Relevance Representativeness Clarity rnnr nrnnnr r nrn rnn((r0nnr nn0 Factor 1 Social nrGrn n n r0nn n 0n 0 n Factor 2 Competence/Mastery n E4n0n rC rCn nnnnn rn rnrn Factor 3 Stimulus-Avoidance nrnrn Evaluation for the Content Validity

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213 5=Excellent, 4=Good, 3=Acceptable, 2=Poor, 1=Unacce ptable Relevance Representativeness Clarity rnnr nrn Cr rn C0 rn rn Factor 4 Intellectual n )r+r/r6nErnnr/r rnn1F#n&& 8 (12Frn/rErn 1nn2F#42!&&' 6n BErn nrB4n1 6r0(!rn( )r(#)r&&, 8 $rnrnnnrn rnrrn0rnr rnnnn$r rrnnnnn -n/0rnn1nrr 21nrr Evaluation for the Content Validity 5=Excellent, 4=Good, 3=Acceptable, 2=Poor, 1=Unacce ptable Vacation Participation Relevance Representativeness Clarity 4n0nnnnn0rnrnnnnr 4nrnnrnnnnrr 4nr0rn4nrnn0rnrnnnn r4n0n(4rnnnn r4n0n(4n0nrrnnnn r4nr(4nn0rnrnnnnnn

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214 $rnrrnnn 0rnrrnnnn $rrrnn nnn-n/0rnn 1nrr21nrr Evaluation for the Content Validity 5=Excellent, 4=Good, 3=Acceptable, 2=Poor, 1=Unacce ptable Vacation Decisional Behavior Relevance Representativeness Clarity nrnnnnrrnnrnnnn rnnn0rnrnnnn 4n0nnCnrnnnrnnnrnnnn 4Crnnnnnn0rnrnnnn 4nrnnn0rnrnnnn nrnnnnrrnnrnnnn = n0rnrrnnn n(rrrnnr nn;Arnn*;? nn > (.01'% !r;3(*;A* 4nrrrHHHHHHHHHIr8 nrnrnr rnnrr *++-;J8+(+++r,;J-+(++nJ&+(+++*;J8+(++nJ=+(+++=;J&+(++rr8;J=+(++nJ-+(+++ nnnn n ;1D8;D*;DBr,;!Br = $rrrrnn nn1nnn ;<2n=;K*;;Fnr8;Annn-;7nrHHHHHH HHHHHHHHHHH ,;rn2nnn

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215 > nrrrn0r ;E0(n$r=;$*;?n!rr!r4>;3nr8;!r4r-;7nr HHHHHHHHHHHHHHHHH ,;n(n$r rrrnr K1Fn1nnHHHHHHHHHHHHHHHHHLDHHHHH HHHHHHHHHHHHH 7nrnrDnrHHHHHHHHHHHHHHHHHDnHHHHH HHHHHHHHHHHHHHHHH Thank you for taking the survey! Comments or Suggestions Related to Content Validity

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216 APPENDIX D INSTITUTIONAL REVIEW BOARD APPROVAL FOR THE STUDY S AMPLE

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220 APPENDIX E SURVEY INSTRUMENT FOR THE STUDY SAMPLE nrrrr rrrrrrr rr r !!!"#r! !r!r rrr $r rrr 2rr" nrrnrnn rnrnn HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH n0nrnn rnnn.n rnnnnn-2n ;nrr1B (*;r(8; nr(,;nrrrr? (=;nr(>;r(-; nrr1! r r MMMMMMM 45rnr nnnrr 8 = > rnnrnr nnnn 8 = > 3rnrnnnr r 8 = > rnnrnr nnnnn n4 8 = > 3rnrnnrn n 8 = > 7nrrnn 4rnnrn rnn 8 = > 3nrrrrnnrnrnn *8,=>4nnrnrnn rnrnn 8 = > 4rnnrnrnn(nrn4nnn *8,=>4r5rnrnn 8 = > 4rnrrnrnnnnn *8,=>3rnrnnrn n%nrr 8 = > 3rnrnnrn4 *8,=>4nr%r rnrnn 8 = >

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221 r r MMMMMMM 3rnrnnr*8, =>4nnnnr nrnnnr rnrnn 8 = > 3rnrnnnrnn *8,=>3rnrnn rnnrn4 8 = > 8 n0nnrnnr rnrnnnnn n.n rnnn nn-n! r r MMMMM MM 4nrnnnnr4r%4n *8,=>4nr4nrnnnn n 8 = > 4n0rnnnnr n *8,=>4nrnnn0n nnn 8 = > nnrrrnnnn* 8,=>nnrnrn 8 = > 4nnnnnn0*8,= >4nrnnn0rnnn n 8 = > 4n0rnnnnrn*8,=> 4nnnnnn rrn 8 = > rrr'rrr' $nrrnnr rnnr rnrnnnnnnn n.n !nr* !n82,n08 !n2*n0, !n*28nn = !nnr> !nrr?r = $nn rrr rnnr rnrnnnnnnn n.n ?r* /n8+n8 8+2>+n, >2&+n = &2*+n> *2=+n3rn=+n > $rrnnr rnrnnnnn nnn.n HHHHHHHHHHHHHHH HHHHHHHHHHHHHHHHHHHHHHHHHHHI
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222 rrr'rrr(r)r,r" $!$ !!r $rnn0rnrrn rnnrrn rrnrrrrn !nn* !nnn8 3nnn !nnn= /nnn> ?nn rrnrnnnr rnrnCn=r Drnn282*2+*8Drn & $nrrnrnnn rrnrn n=r !* Arn8 7, ? r + $n0rrnrnn rnn nn ?nnn* 1nn 8 6rn, 0n 8 = >

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223 r r rr MMMMMMM rn *8,=>rnnr 8 = > nrnnnr*8,=>n 8 = > rCn*8,=>rn 8 = > n*8,=>nnr 8 = > C0*8,=>nnn nn 8 = > r*8,=>n 8 = > Cr*8,=>rC 8 = > *8,=>0 8 = > )r/r n0nrnrr nnrrnnnn nnnn.n* rnnnnn-n r r MM M MM M M 4nnnrnnrnnnnr *8,=>4nrnnrn nnnrr 8 = > 4nr0r@n4nrnn0rnrnnnn *8,=>r4n0n(4 rnnnn 8 = > r4n0n(4n0nnrrnnnn0 *8,=>r4n@r(4 nn0rnrnn nnnn 8 = >

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224 = n0nrrnn n0rnrrnn nnnnnn.n rnnnnnn! r r MMM MMMM nnrnnnnrrnnrnnnn *8,=>rnnn0 rnrnnnn 8 = > 4n0nrnrnnCnrnnnrnnnrnnnn *8,=>4Crnn nnnn0rnrn nnn 8 = > 4nnnnnrnnn0rnrnnnn *8,=>> nrrrn (n0nnn0 rnHHHHHHHHHHHHHHHHHHHHHHHHHHH HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH n0rnrrnnn n(rrrnn nr rnn Arnn* ?nn 4rr(nn0 ?* 8 *28, ,2== >2> 'rr 4r n.n'( !3r** & $rnn 2*, 2*0* 82>= 82,08 0> 7nrHHHHH HH *+ nn !* Ar8 A, 7nr HHHHHHHHHHHHHHHHHHH Bnrrnnrnr (0((! !n ?* I*24(nnrHHHHHHHHHHHHHHHHH HHHHHHHHHHHHHHHHHHHHHHHH *2*4(rrn n0nnr ?* 8 *28, ,2== >2> 'rr

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225 4n(r $$2r!r ** !r 3* A*8 4nrrrHHHHHHHHHIr*, nnnn n $rn* 8 1, ErGr = 3nrGr> 3B@NBrnB@ Fnr7nrHHHHHHHHHHHHHHHHH *> nnrnr rnnrr*++4rnK1r(0 nrrnrn nK1r J8+(+++r* J8+(++nJ=+(+++8 J=+(++nJ-+(+++, J-+(++nJ&+(+++ = J&+(++nJ+(+++> J+(++nJ8+(+++J8+(++nJ=+(+++' J=+(++rr*nrrrn0r n(n$r* $8 E0(n$r, !r4r = ?n!rr!r4> 3nr7nrHHHHHHHHHHHHHHHHH *' rrrnr K1Fn1nnHHHHHHHHHHHHHHHHHLDHHHHH HHHHHHHHHHHHH 7nrnrDnrHHHHHHHHHHHHHHHHHDnHHHHH HHHHHHHHHHHHHHHHHThank you for your participation. Please click “ submit ” to complete this survey.

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253 BIOGRAPHICAL SKETCH Seohee Chang studied French at Hanyoung Foreign Lan guage High School (HYFL), Seoul, Korea, and Portuguese and Spanish at the Hankuk Uni versity of Foreign Studies (HUFS), Seoul, Korea. A motivation to connect her interests in for eign languages and cultures to tourism arose from when she traveled to many foreign countries an d worked in the Brazilian airline company. Her desire to obtain in-depth knowledge about touri sm pushed her to keep studying in the graduate school of the Department of Tourism Scienc e at Hanyang University, Seoul, Korea. During this program, her research was specific to p roduct development and marketing strategies of cultural and health tourism. She worked on the p roject titled “The Development of a Cultural Town Combined with Healthcare Tourism,” working as a research assistant for Dr. Sohn and received a master’s degree with her thesis, titled “Cultural Merchandising of Homestays.” After graduation, she worked as a researcher at the Korean Regional Cultural Event Institute (KRCEI) and at the Korea Tourism Research Institute (KTRI) of the Ministry of Culture and Tourism. In particular, when worked in the KTRI she was awarded the certificate of commendation from Minister of the Ministry of Cultu re and Tourism for her outstanding work in planning and organizing the International Conferenc e on Sport and Tourism hosted by the World Tourism Organization (WTO) and Republic of Korea in collaboration with the International Olympic Committee (IOC). After working on this proj ect related to sport and tourism, she became determined to study in more depth her intere st areas of active leisure and active tourism at the University of Florida. Before entering into the Ph.D. program at the University of Florida, she taught many tourism courses such as social psyc hology of tourism, tourism law, convention business, tourism resource management, internationa l tourism trends, and tourism and hospitality terminology while working as a lecturer at several universities in Korea.

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254 While studying at the University of Florida, her ac ademic papers have focused on in-depth studies with particular psychological and behaviora l variables such as involvement, commitment, loyalty, habit, benefits sought, motivation, satisf action, destination images, perception, intentions, social worlds, and behavioral patterns in the field s of tourism, leisure, recreation, and sport, using quantitative methods. She received her Ph.D. from the University of Florida in the spring of 2009. Her future research will focus more on the connection of tourism, leisure, recreation, sport, and health, particularly, using psychologica l theories and developing relevant scales.