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This is to certify that the
dissertation entitled

EXPLORING THE MOTIVATION AND PERSONALITY TRAITS OF
ADVENTURE TRAVELERS: A HIERARCHICAL MODEL
APPROACH

presented by

PAIGE PATRICE SCHNEIDER

has been accepted towards fulfillment
of the requirements for the

Ph.D. degree in Park, Recreation, and Tourism
Resources

 

 

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EXPLORING THE MOTIVATION AND PERSONALITY TRAITS OF ADVENTURE
TRAVELERS: A HIERARCHICAL MODEL APPROACH

By

Paige Patrice Schneider

A DISSERTATION
Submitted to
Michigan State University
In partial fulfillment of the requirements
For the degree of
DOCTOR OF PHILOSOPHY

Park, Recreation, and Tourism Resources

2010

Paige Patrice Schneider

Over a decade has passed since the Travel Industry Association of America (TLA)
investigated the topic of adventure travel experiences. Despite growth in the adventure
industry, studies of adventure tourism and its travelers remain scarce. Existing research is
descriptive rather than predictive and has failed to identify the psychological
underpinnings of consumer behavior related to adventure tourism (Swarbrooke et a1 .,
2003). Drawing on the personality literature found in consumer behavior (Mowen, 2000)
and leisure and tourism (Fodness & Murray, 1997; Godbey, 1981; MacKay, Andereck, &
Vogt, 2002; Pearce, 2005; Pizam & Sussmann, 1995; Tinsley & Tinsley, 1986) literature,
this dissertation seeks to explain the psychological roots of tourism behavior, specifically
adventure travel. A multi-method approach was used to develop the survey instrument.
Self-administered questionnaires were mailed to a stratified random sample (N=IOOO) of
subscribers to National Geographic Adventure magazine (N=220,847) and data collected
during the fall of 2007. Overall response rate (n=339) was 34%. Guttman Scaling
Procedure was employed to categorize respondents in soft/hard categories as a context for
understating the demographic and travel behavior characteristics of the study sample.
Factor analysis was used to identify the underlying dimensions of adventure travel
pr0pensity, an enduring disposition to behave, and next a series of hierarchical

regressions were performed to explore the relationships among variables.

 

 

 

Results indicated that the model that guided the study, Mowen’s (2000) Meta-Theoretic
Model of Motivation and Personality (3M Model), was a useful organizing framework.
Specifically, the 3M Model offers the advantage of a hierarchal approach to personality
in that it identifies the basic elemental and compound traits that account for situational
traits and surface level traits providing a means for identifying the more basic compound
and elemental traits that act as references for behavior. Results of hierarchical regressions
indicated that elemental trait need for arousal and the situational trait interest in cultural
experiences were consistent predictors of the surface trait adventure travel propensity.
The findings of this study enhance knowledge and understanding of the relationship
between personality and tourism behavior, in addition to addressing the many problems

that result from research which lacks a theoretically based organizing structure.

Keywords: adventure, consumer behavior, personality, hierarchical, Guttman Scaling

This dissertation is dedicated to my brother Jack P. Viren 111.
“Go confidently in the directions of your dreams. Live the life you have imagined”
~Henry David Thoreau

iv

 

ACKNOWLEDGEMENTS

In successful completion of this research, my sincere gratitude and thanks goes to
my committee chair, Dr. Christine Vogt. Her guidance and support during my
dissertation adventure has been essential to my success. Equally important to this

research was the guidance of my other committee members, Dr. Donald Holecek, Dr.

 

Richard Paulsen, and Dr. Sandi Smith. While not part of my official committee, a
number of professors advised and encouraged me along my journey; Dr. Kathy
Andereck, Dr. David Klenosky, Dr. Heidi Sung, and Dr. David Wright -I appreciate
your willingness to answer questions and offer insight. A note of special thanks goes
to Dr. Wright for his friendship, encouragement, professional advice, and humorous
quotes.

Special thanks to all of the wonderful people who touched my life while at
Michigan State, I have a special memory or connection to each of you; Angela,
Annie, Ariel, Kaoruko, Kiki, Pavlina, Lanie, and Ryan. Also to my lifelong friends,
Dina, Jackie, Lisa, and Marcia -— thanks for always being there!

Most of all I would like to thank my family for their love and support throughout
this long and sometimes arduous process. Morgan, Thomas, and Patrick -— you are
my sunshine! Special thanks to Tom for holding down the fort and keeping things
together on the home front while I worked. Our kids are lucky to have you as a dad.

Finally, a special thanks to my father. He taught me to value education andithat it

is a useless exercise to contend about inconsequential matters — I love you Dad!

“I want to do it because I want to do it.” Amelia Earhart

TABLE OF CONTENTS

LIST OF TABLES .................................................................. ix
LIST OF FIGURES .................................................................. ,
x111
CHAPTER I: INTRODUCTION ................................................... 1
Personality and Tourism ................................................... 2
Statement of the Problem ................................................... 4
Theoretical Framework ..................................................... 5
Cohen’s Tourist Typology ........................................ 5
Smith’s Tourist Typology ......................................... 6
Plog’s Tourist Typology .......................................... 6
Holland’s Tourism Typology ..................................... 7
Adventure and Independence Typology ........................ 7
Hard and Soft Adventure Typology .............................. 8
Destination and Activity Driven Typology ..................... 8
Meta-Theoretic Model of Motivation and Personality. . . . . 9
Research Questions and Hypotheses ..................................... ll
Delimitations ................................................................ 13
Limitations ................................................................... 15
Definitions ................................................................... 16
Organization of the Study .................................................. 18
CHAPTER II: LITERATURE REVIEW .......................................... 19
Adventure Tourism ......................................................... 19
Personality ................................................................... 22
Personality and Leisure Behavior ................................ 24
Personality and Tourism Behavior .............................. 26
The 3M Model of Motivation and Personality ................. 37
Hypothesis Development ................................................... 41
Elemental Traits .................................................... 41
Compound Traits ................................................... 44
Situational Traits ................................................... 49
Surface Traits ....................................................... 5 3
Summary of the Literature Review ....................................... 55
CHAPTER III: METHODOLGOY ................................................ 58
Methods ....................................................................... 59
Study Population and Sampling .................................. , 59
Data Collection ..................................................... 62
Non-respondent Survey ........................................... 66
Survey Instrument .................................................. 67
Reliability Test ..................................................... 74
Data Analysis ....................................................... 78

Guttman Scaling: Distinguishing Soft and Hard Adventure. 81

vi

Exploratory Factor Analysis ...................................... 91

Hierarchical Regression .......................................... 92
Statistical Procedures of Analysis ......................................... 94
CHAPTER IV: RESULTS ........................................................... 96
Demographic Profile ........................................................ 97
Travel Experience Profile ......................................... 103
Travel Intention Profile ............................................ 1 12
Pre-Trip and Post-Trip Behavior Profile ........................ 132
Descriptive Statistics Personality Traits ................................. 142
Elemental Level Traits ............................................. 142
Compound Level Traits ........................................... 143
Situational Level Traits ............................................ 145
Surface Level Traits ................................................ 148
Factor Analysis .............................................................. 152
Hypotheses Testing ......................................................... 161
Hierarchical Regression ........................................... 161
Summary ..................................................................... 182
CHAPTER V: CONCLUSION ...................................................... 184
Summary of Results ......................................................... 186
Discussion .................................................................... 1 89
Implications .................................................................. 197
Limitation of Findings ...................................................... 203
Future Research ............................................................. 206
Final Thoughts ............................................................... 207
APPENDICES ........................................................................ 209
Appendix A: Survey Instrument .......................................... 211
Appendix B: Survey Cover Letter ....................................... 222
Appendix C: Postcard Reminder ......................................... 224
Appendix D: UCRIHS Approval Letter ................................. 226
Appendix E: Non-response Survey ....................................... 228
Appendix F: Non-response Survey Cover Letter ...................... 231
Appendix G: Survey Instrument Key .................................... 233
Appendix H: Expert Review Survey Request .......................... 246
Appendix 1: Expert Judge Survey ....................................... 248
Appendix J: Expert Judge Definitions ................................... 252

Appendix K: Other Recreation and Travel Activities Experienced. 256
Appendix L: Other Recreation and Travel Activities Intentions. . , 258

Appendix M: Other Lifestyle Changes Experienced .................. 260
Appendix N: Other Technologies Used on Vacation .................. 262
Appendix 0: Descriptive Statistics Elemental Traits and Items ...... 264

Appendix P: Descriptive Statistics Compound Traits and Items. . 267
Appendix Q: Descriptive Statistics Situational Traits and Items. . 270

vii

BIBLIOGRAPHY ..................................................................... 271

viii

Table 1:
Table 2:

Table 3:

Table 4:

Table 5:

Table 6:
Table 7:
Table 8:

Table 9:

Table 10:
Table l l :
Table 12:
Table 13:

Table 14:

Table 15:

Table 16:

Table 17:

Table 18:

LIST OF TABLES

Dichotornies within Adventure Tourism ..............................
Levels of Traits in the 3M Model Hierarchy .........................

Circulation of National Geographic Adventure Magazine
Subscribers ...............................................................

Response Rate of the Mail Survey ....................................

Variables and Sources for Scale Items Used for
Measurement ..............................................................

Cronbach Alpha Coefficients for Composite Scales ...............
Analysis Procedures .....................................................
Results of Expert Judge Destination Categories .....................

Results of Expert Judge Recreation and Travel
Activity Categories ......................................................

Results of Cumulative Scale for Destination Categories ...........
Results of Cumulative Scale for Activity Categories ...............
Demographic Profile of Respondents .................................
Education, Income, and Employment Profile ........................

Mass Destinations Respondents Vacationed in
Lifetime ...................................................................

Soft Adventure Destinations Respondents Vacationed in
Lifetime ...................................................................

Hard Adventure Destinations Respondents Vacationed in
Lifetime ...................................................................

Mass Recreation and Travel Activity Experienced in
Lifetime .................................................................

Soft Adventure Recreation and Travel Activity Experienced in
Lifetime ......................................................................

ix

36

40

62

66

7O

76

78

86

87

89

89

99

101

106

107

108

110

Ill

Table 19:

Table 20:

Table 21:

Table 22:

Table 23:
Table 24:
Table 25:
Table 26:
Table 27:
Table 28:
Table 29:
Table 30:
Table 31:
Table 32:

Table 33:

Table 34:

Table 35:

Table 36:

Table 37:

Hard Adventure Recreation and Travel Activity Experienced in

Lifetime ..........................................................................................

Mass Destinations Respondents Plan to Visit for Vacation in
Lifetime... ......................................................................................

Soft Adventure Destinations Respondents Plan to
Visit for Vacation in Lifetime ..........................................

Hard Adventure Destinations Respondents Plan to
Visit for Vacation in Lifetime ..........................................

Mass Recreation and Travel Activity Intentions .....................
Soft Adventure Recreation and Travel Activity Intentions .........
Hard Adventure Recreation and Travel Activity Intentions ..........
Mass Destination Experience/Intentions Combined .................
Soft Adventure Destination Experience/Intentions Combined. . . ..
Hard Adventure Destination Experience/Intentions Combined. . ..
Mass Activity Experience/Intentions Combined ............. A ........
Soft Adventure Activity Experience/Intentions Combined. . . . . .
Hard Adventure Activity Experience/Intentions Combined ..........
Vacation Trip Planning ..................................................
Sources Used to Book Vacation Travel ...............................

Mean Scores for Helpfulness of Sources Used to Book Vacation
Travel......................

Pre-trip behavior ..........................................................

Communication Types Used During and After a Vacation
Trip .........................................................................

Technologies Used During Vacation Trip ............................

112

115

116

117

119

120

121

123

124

126

128

130

131

133

134

136

137

138

139

Table 38:

Table 39:

Table 40:
Table 41:
Table 42:
Table 43:
Table 44:
Table 45:
Table 46:
Table 47:
Table 48:

Table 49:

Table 50:

Table 51:

Table 52:

Table 53:

Table 54:

Table 55:

Mean Scores of Helpfulness of Technologies Used During
VacationTravel... ........ .. ... ... ... ...

Lifestyle Change as a Result of Vacation Travel
Experience. . . .

Descriptive Statistics for Elemental Traits ...........................
Descriptive Statistics for Compound Traits ..........................
Descriptive Statistics Situational Traits ..............................
Descriptive Statistics Personality Traits ..............................
Mean Scores Dream Travel Experiences .............................
Top Dream Travel Experiences-Hard Adventure Travelers .........
Top Dream Travel Experiences-Soft Adventure Travelers .........
Top Dream Travel Experiences-A11 Adventure Travelers ..........

Factor Analysis Dream Travel Experiences ..........................

Mean Scores for Factors and Items-Ultimate Destination
Experiences ....................................................................................

Mean Scores for Factors and Items-Tropical Adventure
Experiences ...............................................................

Mean Scores for Factors and Items-Extreme Adventure
Experiences ...............................................................

Mean Scores for Factors and Items-Traditional Outdoor
Adventure Experiences .................................................

Results Hierarchical Regression Analyses—Ultimate Destination
Experiences ..............................................................

Significant Hierarchical Regression Results - Ultimate
Destination Experiences ................................................

Results Hierarchical Regression Analyses-Tropical Adventure
Experiences... . .

x1

140

141
143
145
145
148
150
151
151
151

154

157

158

159

160

167

168

171

Table 56:

Table 57:

Table 5 8:

Table 59:

Table 60:

Table 61:
Table 62:
Table 63:

Table 64:

Significant Hierarchical Regression Results-Tropical Adventure
Experiences ...............................................................

Results Hierarchical Regression Analyses-Traditional Outdoor
Adventure Experiences ..................................................

Significant Hierarchical Regression Results-Traditional Outdoor
Adventure Experiences ..................................................

Results Hierarchical Regression Analyses-Extreme
Activity Experiences .....................................................

Significant Hierarchical Regression Results-Extreme Adventure
Activities ..................................................................

Overview of Supported Hypotheses ...................................
Descriptive Statistics for Eight Elemental Traits Items .........
Descriptive Statistics for Compound Traits and Items ............

Descriptive Statistics Interest in Cultural Experiences ..............

xii

172

175

176

178

179

179

265

267

269

Figure 1:
Figure 2:

Figure 3:

LIST OF FIGURES

US. Census Regions and Divisions ...................................
Conceptual Model Adventure Travel Propensity .....................

Response Rate According to Geographic Location ..................

xiii

15

55

102.

CHAPTER
INTRODUCTION

Over a decade has passed since the Travel Industry Association of America (TIA)
investigated the topic of adventure travel experiences. Results of TIA’s Adventure Travel
Report ( 1998) indicated one-half of all US. adults (50% or 98.0 million) took an
adventure vacation trip that included either soft adventure outdoor activities (e. g.,
camping, canoeing, wildlife viewing) and/or hard adventure outdoor activities (e.g.,
mountain biking, whitewater rafting, hanggliding). Among the nearly 100 million adults
who had not taken an adventure trip in the past five years, one-fourth (28% or 28 million)
indicated that they would be very or somewhat likely to do so in the next five years,
suggesting additional growth of the adventure market. Although adventure travel has
continued to be a growth market, research on the topic has remained stagnant.

Consumer trends such as increased interest in healthy lifestyles and concern for
the environment and sustainability are reflected in tourism behavior and in particular,
adventure tourism (Swarbrooke, Beard, Leckie, & Pomfret, 2003). Interest in living
healthy lifestyles will continue to increase the popularity of and demand for active or
activity-focused vacations with an emphasis on environmental sustainability resulting in
more travelers seeking adventure travel experiences. In addition, travelers have become
more sophisticated and seek out the kinds of activities, cultural experiences, and unique
destinations for which adventure travel experiences are known. These changes will have
a positive impact on the adventure travel industry, suggesting further expansion.

Despite growth in the adventure industry, studies of adventure tourism and its

travelers remain scarce. Existing research is descriptive rather than predictive and has

failed to identify the psychological underpinnings of consumer behavior related to
adventure tourism (Swarbrooke et al., 2003). One of the recommendations for future
research suggested by the Canadian Tourism Commission (CTC) in their 2003 Outdoor
Enthusiast Survey was the need for “in-depth psychographic analysis of geographically
dispersed Americans by means of larger-scale American studies” (p. 9). Indeed, a number
of researchers have noted the importance of examining adventure tourism behavior from
a psychological perspective (Brooker, 1983; Cheron & Ritchie, 1982; Jacoby & Kaplan,
1972), expressing the need to establish how factors such as personality characteristics
affect behavior. Today, consumers are driving demand (ETC, 2003); therefore
understanding the underlying psychological and social dimensions that motivate
consumers may offer the tourism industry insight into how to better meet their changing
needs.

Adventure travel represents an interesting form of consumer behavior. An
understanding of how adventure travelers make their decisions to purchase or use tourism
products allows adventure tourism businesses to optimize the effectiveness and efficiency

of marketing activities (Homer & Swarbrooke, 2007).

Personality and Tourism
Previous leisure and tourism research has successfully classified tourists based on
their behavior (Fodness & Murray, 1999; Godbey, 1981; MacKay, Andereck, & Vogt,
2002; Pearce, 2005; Pizam & Sussmann, 1995; Tinsley & Tinsley, 1986). Similarly,
research focused on the adventure tourism market has explored what tourists buy, as well

as when and how they buy, but the psychological forces directing these behaviors have

not been adequately addressed (CTC, 2003; Sung, Morrison, & O’Leary, I997; Sung,
2000; Sung, 2004; TIA, 1998). This study explored the psychological forces that
motivate and influence travel-related decisions (Mayo & Jarvis, 1981), which is essential
to understanding tourist behavior (Crompton, 1979). Traditional research in marketing
has not been particularly successful in finding a link between personality and consumer
behavior (Kassarjian, 1971). Part of the problem may be a result of the application of
theory developed by clinical psychologists interested in studying maladjusted people. Not
surprisingly, research that sought to predict consumer behavior using standard personality
inventories has not been successful. Market researchers have attempted for some time to
gather evidence that personality traits have an influence on consumer behavior. The
evidence is spotty and inconclusive; however, intuition tells us that personality
characteristics should normally have an important influence on certain kinds of behavior
(Mayo & Jarvis, 1981).

Personality has long been a fringe component in the study of consumer behavior
with little research directly devoted to its significance (Kassarjian, 1971). Understanding
an individual in his or her role as a consumer should be a key focus in the study of
consumer behavior. To realize this vision and evaluate its impact, the scope of
personality research should be broadened. Drawing on the personality literature found in
consumer behavior (Kassarjian, 1991; McCrae & Costa, 1999; Schaninger, 1976) and the
leisure and tourism literature (Gilchrist, 1994; Madrigal, 1995; Plog, 1991; Pomfret,
2006) this dissertation sought to explain the psychological roots of tourism behavior,

Specifically adventure travel behavior.

Statement of the Problem

The limited research successfirlly explaining the relationship between personality
and tourism behavior was the catalyst for the current study (Cohen, 1972; 1979; F rew &
Shaw, 1999; Madrigal, 1995; Nickerson & Ellis, 1991; Plog, 1991; 2002; Smith, 1989).
Specifically, the problem focus of the study was to examine the underlying psychological
traits that contribute to adventure travel propensity (ATP) by identifying the motivation
and personality schemas of adventure travelers. In addition, the usefulness of employing
the Meta-Theoretic Model of Motivation and Personality (3M Model) as an organizing
structure for understanding how personality traits impact behavior was tested (Mowen,
2000)

The results of the study can be used to enhance knowledge and understanding of
the relationship between personality and tourism behavior, providing a more effective
means for segmenting the market. Additionally, the results will assist the adventure
tourism industry in classifying tourists according to their personality traits giving
marketing managers the ability to develop promotional themes linking the personality of
their brand to that of the consumer, essentially linking the product characteristics to
consumer personality. In a more technical sense, the results allow for communications to
be created which tap into the self-schema of the desired target market. The results will
clearly contribute to business decisions related to product deveIOpment, price, and
distribution. Finally, the results will address many problems that result from research

which lacks a theoretically based organizing structure.

Theoretical Framework

Personality, as expressed in behavior and communication, affects travel and
tourism (Fridgen, 1991). Leading tourism research has demonstrated that an individual’s
personality influences his or her behaviors and experiences. For more than two decades,
academics have attempted to explain tourist behavior by developing typologies of tourists
and their behaviors (Swarbrooke, 2006). While not developed specific to marketing, these
typologies have an application in tourism marketing and thus can contribute to decisions

regarding product development, price, and distribution.

Cohen’s Tourist Typology
Cohen’s tourist typology is quoted in most tourism textbooks. His early studies

proposed the idea that all tourists seek some element of novelty and strangeness, while
simultaneously wanting to retain some familiarity and security. Cohen (197 2) identified
four types of tourists: (1) mass tourist, (2) individual mass tourist, (3) explorer and, (4)
drifter. Groups were further differentiated based on the level of contact with the tourism
industry. Mass tourists are classified as institutionalized since they rely heavily upon the
tourism industry and desire comfort and safety. While the individual mass tourist, non-
institutionalized, prefer to follow their own path and have little contact with the tourism
industry. In 1979, Cohen amended his typology and defined two groups of tourists - those
who search for pleasure and those who undertake a modern pilgrimage. He suggested a
five-group classification of tourists based on the type of experience they were seeking:
(l) the recreational tourist, for whom the emphasis is on physical recreation; (2)
divisionary tourist, who seeks ways of forgetting their everyday life at home; (3) the

experiential tourist, who looks for authentic experiences; (4) the experimental tourist,

5

whose main desire is to be in contact with local people; (5) the existential tourist, who

wants to become totally immersed in the culture and lifestyles of the vacation destination.

Smith’s Tourist Typology
Another tourist personality typology often found in the tourism literature was
developed by anthropologist Valene Smith (1989). Primarily interested in host-guest
relationships and impact studies, Smith grouped tourists according to their wish to adapt
themselves to local norms. She identified seven categories of tourist ranging from
explorers who have a quest for discovery and a desire to interact with the hosts, to
charter tourists who search for relaxation and good times. The other five tourist

categories in Smith’s model are: elite, off-beat, unusual, incipient, and mass.

Plog’s Tourist Typology
In an effort to directly link personality traits with tourist behavior, Plog (1977)

divided people into psychocentrics and allocentrics. He argued that psychocentrics were
less adventurous, inward-looking people who tend to prefer the familiar and have a
preference for resorts which are already popular. In contrast, allocentrics are outward-
looking people who like to take risks and seem to seek more adventurous vacations. Plog
believed such people would prefer exotic destinations and individual vs. group travel.
Plog suggested a number of intermediate categories between these two extremes, such as
near-psychocentrics, mid-centrics, and near-allocentrics. He suggested psychocentric
American tourists would vacation at Coney Island while allocentrics would take their

vacation in Africa, for example.

Holland’s Personality Typology

Researchers have also attempted to apply personality theories and typologies from
various disciplines to try and explain and predict tourist behavior. Holland (1985)
developed a theory of personality types as a way to use them to guide education and
vocational planning. He defined an individual’s personality type in terms of characteristic
activities, interests, and competences. Holland’s typology consists of six different
personal orientations to life: (1) realistic, (2) investigative, (3) artistic, (4) social, (5)
enterprising, and (6) conventional. F rew and Shaw (1999) employed Holland’s theory of
personality types to explore the relationship between personality and tourism behavior.
They found support for the association between Holland’s personality types and the
likelihood to visit certain types of tourist attractions.

A number of approaches can be taken to categorize adventure tourism.
Adventure tourism is a broad concept and involves a range of products and people, thus a
number of typologies of adventure tourism have been developed. Three adventure

tourism typologies are introduced below.

Adventure and Independence Typology

' Addison (1999) produced the adventure and independence typology. He
developed a matrix of challenge and independence, a grid with two axes. On one axis is
the level of adventure as determined by elements of danger and skills needed, which can
be interpreted as the degree of challenge involved. The other axis is based on the level of
independence or the degree to which participants rely on others to organize the

experience for them. Each axis is a continuum, going from low to high.

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Hard and Soft Adventure Typology

These oft-used terms have been developed by researchers who devised a
continuum to explain the diversity of behavior, beginning with mild adventure (termed
“soft adventure”) at one end of the scale and progressing to ‘hard adventure” at the other
extreme (Swarbrooke et al., 2003). This continuum, involves differing degrees of
challenge, uncertainly, setting, familiarity, personal abilities, intensity, duration and

perceptions of control (Lipscombe, 1995).

Destination and Activity Driven Typology

Millington, Locke, and Locke (2001) proposed a typology that divides the
adventure tourism market between adventure travel that is destination driven and that
which is activity driven. Each of these basic divisions is then subdivided once more. In
destination-driven adventure travel the destination is the most important aspect of the
trip, the traveler being interested in the landscape and scenery, the ecosystems, the people
or the history of the place. The location will often be somewhere unusual, remote or
exotic, providing novelty, stimulation, discovery and challenge for the traveler. In
activity-driven travel, it is the activity rather than the destination that is crucial. The
destination could be a remote or wilderness area if the activity demands it, but could just
as easily be near home or abroad. As the choice of terms suggests, the division used by
Millington et a1. (2001) is based on a tourist’s drive and motivation.

The attempts to classify tourists discussed, and others, have attracted criticism.
The tourist personality typologies generated by Cohen and Smith have been descriptive
rather than quantitative and predictive. F urtherrnore, they were primarily related to

tourism development and impacts of tourism on the destination instead of the

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psychological forces that motivate and influence various travel-related decisions.
Although Plog focused on psychological forces that motivate and influence various
travel-related decisions, the validity and reliability of Plog’s scale has been questioned
(Madrigal, 1995, Plog, 1991; 2002; Smith, 1990a; 1990b), and, while there was some
utility in Holland’s approach to personality typing, the relationship between occupations,
the original focus of Holland’s work, and tourism behavior have yet to be fully
investigated. Finally, the product-based typologies of adventure tourism appear to fall
short as well. Consumers and suppliers do not always confine themselves to one
category, which further complicates creating a typology of adventure tourism. Crossover
is common. For instance, TIA (1998) found a substantial sector of respondents had
participated in both hard and soft adventure in five years leading up to 1997. As
suggested by Swarbrooke et a1. (2003) adventure tourism typologies based on
psychographic segmentation of consumers would be of great utility to the tourism
industry and further research in this area is necessary.

Despite the fundamental importance of the study of motivation and personality,
finding a holistic View of the topic in consumer behavior or psychology is difficult. The
current study utilized an integrated model of motivation and personality to address the
issues outlined above. Mowen’s (2000) Meta-Theoretic Model of Motivation and
Personality provided an organizational structure for understanding how personality traits

impact behavior.

Meta-Theoretic Model of Motivation and Personality

The current research employed The Meta-Theoretic Model of Motivation and

Personality (3M Model) as the organizational structure for understanding how personality

9

traits impact behavior. Four theoretical approaches were combined to develop the 3M
Model: (1) control theory, (2) hierarchical models of personality, (3) evolutionary
psychology, and (4) trait theories of personality. The work in evolutionary psychology
and trait theory provides a set of personality traits. Hierarchical models of personality
supply the basis for the idea that traits diverge in terms of abstractness, while control
theory provides a framework that describes how the hierarchical arrangement of traits
results in goals, emotions, and ultimately behavior.

The 3M Model “integrates diverse psychological theories and consumer behavior
constructs into a coherent general theory of motivation and personality that more
parsimoniously explains a broad set of phenomena” (Mowen, 2000, p. 6). The primary
goal of employing an integrated model of motivation and personality is to overcome the
problems of dealing with a multitude of disconnected constructs in consumer behavior.

As a general theory of motivation and personality, the 3M Model can be applied
across domains —- from consumer behavior, to services marketing, to organizational

behavior (Licata, Mowen, Harris, & Brown, 2003). The 3M Model proposes that
enduring dispositions to respond (e.g., traits) can be arranged into four levels based on
their level of abstraction.

Elemental traits reside at the most abstract level of the hierarchy. Mowen (2000)
used a physical chemistry metaphor to identify eight elemental traits, which are defined

as cross-situational, enduring dispositions to respond that result from genetics and the
early learning history of the individual. Compound traits reside at the next level in the
hierarchy. Similar to elemental traits, they are cross-situational in nature. Compound

traits are defined as enduring dispositions that result from the effects of subsets of

10

elemental traits as well as from cultural and sub-cultural influences. The third type of
constructs in the 3M Model are the situational traits. Situational traits are defined as
enduring dispositions to behave within a general situational context. They are influenced
by the pressures of the situational environment and by the effects of the elemental and
compound traits. Finally, surface traits are the most concrete traits identified in the 3M
Model. These constructs represent highly specific, enduring dispositions to behave that
result from the effects of elemental, compound, and situational traits as well as from the
pressure of the context-specific environment. Surface traits occur in narrow contexts that
fall within the more general context of the situational traits (Mowen, 2000).

The 3M Model provided the means for inserting into a control theory based
nomological network a limited set of mid—range trait theories that provide the elemental,
compound, situational, and category specific surface traits proposed to underlie consumer

behavior. Thus, control theory not only provided the structure within which the traits

were arranged, but also identified how these traits influence behavior.

Research Questions and Hypotheses
Building on existing tourist personality research and utilizing an integrated

approach to motivation and personality, the 3M Model, the following research questions

were formulated:

(1) Does a motivation-personality system of traits predictive of adventure traveler

propensity (ATP) exist?

(2) Does a motivation-personality system of traits predictive of soft ATP exist?

(3) Does a motivation-personality system of traits predictive of hard ATP exist?
(4) What are the trait antecedents of soft ATP?

11

(5) What are the trait antecedents of hard ATP?

(6) Does the 3M Model of motivation and personality provide a useful framework for

examining tourist behavior?

The study was designed to determine the motivation-personality systems of
adventure travelers. A number of traits were proposed to be associated with the surface
trait ATP and rationale for each hypothesis is provided in the literature review. The
proposed trait antecedents of ATP were: the elemental traits need for arousal and
agreeability (Licata et al., 2003), the compound traits competitiveness (Mowen, 2000),
altruism (Mowen & Sujan, 2005), and need for learning (Mowen, 2000), and the
situational traits interest in cultural experiences (Mowen & Carlson, 2003), need for

uniqueness (Tian, Bearden, & Hunter, 2001), and fashion leadership (Goldsmith, Freiden

& Kilsheimer, 1993). The following hypotheses were proposed:

1‘!1 : The elemental trait need for arousal will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor
adventure experiences, and extreme adventure experiences (ATP).

H2: The elemental trait agreeability will positively influence ultimate destination
experiences, tropical adventure experiences, traditional outdoor adventure
experiences, and extreme adventure experiences (ATP).

H3: The compound trait competitiveness will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor

adventure experiences, and extreme adventure experiences (ATP).

12

H4: The compound trait altruism will positively influence ultimate destination
experiences, tropical adventure experiences, traditional outdoor adventure
experiences, and extreme adventure experiences (ATP).

H5: The compound trait need for learning will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor
adventure experiences, and extreme adventure experiences (ATP).

H6: The situational trait interest in cultural experiences will positively influence
ultimate destination experiences, tropical adventure experiences, traditional
outdoor adventure experiences, and extreme adventure experiences (ATP).
H7: The situational trait need for uniqueness will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor
adventure experiences, and extreme adventure experiences (ATP).

H9: The situational trait fashion leadership will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor

adventure experiences, and extreme adventure experiences (ATP).

Delimitations

This study was delimited to a number of factors as shown below:
(1) Budget considerations and issues related to return postage for international mail
logistics delimited the sample to individuals 18 years of age and older living in

households located in the 48 contiguous United States, following the US. Census

Regions and Divisions of the United States (Figure l).

13

(2) Individuals at the household level who are current paid subscribers to National
Geographic Adventure magazine having maintained a subscription for a minimum
of two consecutive years.

(3) Overall adventure travel behaviors including past and future adventure travel
experience to gain an understanding of behavior over a lifetime versus a single
adventure travel vacation experience.

(4) Data were collected fall of 2007 and represent consumers during that time period.

(5) Excluded were individuals who obtained National Geographic Adventure
magazine via: (1) a retail outlet (e. g., bookstore, grocery store), (2) a library
subscription, or (3) an office (e. g., doctors office waiting rooms, businesses).

(6) Excluded were adventure travelers who do not purchase National Geographic
Adventure magazine.

(7) Excluded were individuals or professionals who are focused on a competitive
aspect of sport that form the adventure activity milieu such as mountaineering,
sport climbing or stunt surfing, who are sponsored to develop their techniques and
prowess as part of an ultimate goal of promoting the sport and equipment, unless

the are subscribers of National Geographic Adventure magazine.

14

Figure 1

US. Census Regions and Divisions of the United States

 

   

Census Regions and Divisions of the United States

 

 

 

 

 

 

 

meg-nuns...- muum uncut-w mama“ ‘

 

Limitations

This study was limited by the following:
(1) Travel behaviors of only those individuals who subscribe to National Geographic
Adventure magazine, excluding those adventure travelers who do not subscribe.
(2) Participants who may underestimate or overestimate how much travel experience they
have gained or how much travel experience they plan, or have intentions to take in the

future.

15

(3) Respondent’s ability to use Likert scales and semantic differential scales correctly.
(4) Reliability and validity of scales borrowed from the consumer behavior literature, to

the extent that they were a good representation of tourism consumer behavior.

Definitions

For the purpose of this study, it is important to provide clear and specific
definitions of the terms used in the study. The following terms are defined to clarify their
use:

Adventure travel: Any tourist activity including two of the following three components: a
physical activity, a cultural exchange or interaction, and engagement with nature
(ATTA, 2008; Schneider & Vogt, 2005).

ATP: “The selection of an activity that takes place in an unusual, exotic, remote, or
wilderness destination and tends to be associated with high levels of involvement
and activity by the participants, most of it outdoors” (Tran & Ralston, 2006, p.
429).

Soft adventure: Activities with a perceived risk but low levels of real risk, requiring
minimal commitment and beginning skills; often led by experienced guides (Hill,

1995).

Hard adventure: Activities with high levels of risk, requiring intense commitment and

advanced skills (Hill, 1995).

Motivation: A general term for all processes involved in starting, directing, and

maintaining physical and psychological activities (Gerrig & Zimbardo, 2002).

16

Need for uniqueness: The pursuit of differentness relative to others through acquisition,
utilization, and disposition of consumer goods for the purpose of developing and
enhancing one’s self image and social image (Snyder & Fromkin, 1980; T ian et
al., 2001).

Tourist motivation: The global integrating network of biological and cultural forces
which gives value and direction to travel choices, behavior and experience
(Goeldner & Ritchie, 2009; Pearce, 2005).

Tourist preference: The act of selecting from among a set of choices as influenced by
one’s motivations (Tran & Ralston, 2006).

Traits

Elemental traits: The unidimensional underlying predispositions of individuals that arise
from genetics and early learning history that represent the broadest reference for
performing programs of behavior (Mowen, 2000).

Compound traits: The unidimensional predispositions that result from the effects of
multiple elemental traits, a person’s learning history and culture which provides a
second reference point for how to run programs of behavior (Mowen, 2000).

Situational traits: The unidimensional predispositions to behave within a general
situational context that result from the joint effects of elemental traits, compound

traits, and the situational context (Mowen, 2000).
Surface traits: The delineation of the programs of behavior that individuals run to

complete tasks that occur as a result of a person, situation or product category

interactions (Mowen, 2000).

17

Organization of the Study

Beyond the introduction section of this dissertation, four additional chapters will
examine motivation and personality within a tourism context. Chapter H contains the
literature review, which will first describe current consumer behavior research related to
personality and behavior. Next, personality research found in the leisure and tourism
literature will be discussed, followed by a presentation of the theoretical framework
employed to determine if personality and motivation are predictors of adventure travel

behavior. The methodology section, or Chapter 111, describes the procedures used to
gather data and to test relationships which test the theoretical framework. After data
collection, Chapter TV will present the findings and describe the results of the data
collection and testing of the hypotheses and the model. Finally, Chapter V will evaluate
the findings and draw conclusions conceming the role of personality and motivation in

consumer behavior related to adventure tourism and recommendations will be made for

future research in this area.

18

CHAPTER II
LITERATURE REVIEW
The problem selected for this study was to investigate the relationship between

personality and tourism behavior, specifically adventure travel behavior. To accomplish

this, the literature related to personality and consumer behavior in a leisure and tourism

context is reviewed. This review of literature is organized around the following sections:
(1) adventure tourism, (2) personality, (3), the theoretical framework employed to
identify the motivation and personality systems of individuals, the 3M Model of
motivation and personality, and (4) hypotheses development.

This chapter provides the background and theoretical information needed to

understand personality and consumer behavior in a tourism context. It reviews the most
important research and methods that have been conducted in this area and establishes this

study as one link in a chain of research that advances knowledge in the field of consumer

behavior and leisure and tourism.

Adventure Tourism
Historically characterized by activities, the term adventure travel is often
associated with high levels of physical activity by participants, most of it outdoors. The
Adventure Travel Trade Association (http://wwwggiventmetravelbizh offers a broad
definition of adventure, identifying the diversity of interests among adventure travelers:
any tourist activity including two of the following three components: a physical activity,

a cultural exchange or interaction, and engagement with nature (Schneider & Vogt,

2005).

19

As noted in the introduction, tourism researchers have demonstrated that an
individual’s personality influences his or her behaviors and experiences. Tourist
preference is the act of choosing from a set of choices as influenced by a person’s
motivations. As such, adventure travel preference, or propensity, is defined as the

selection of “an activity in an unusual, exotic, remote, or wilderness destination and tends
to be associated with high levels of involvement and activity by the participants, most of
it outdoors” (Tran & Ralston, 2006, p. 428). Tourists with a propensity for adventure
would like to visit unusual and exotic destinations, gain new experiences, interact with
local culture, engage with nature, and challenge their physical and mental skills.
Adventure travel represents an interesting form of consumer behavior that has
seen tremendous growth as a segment of the tourism industry (Sung, Morrison, &
O’Leary, 1997). The transformations taking place include an interest in healthier
lifestyles, greater concern for environmental sustainability, and preference for
authenticity in many aspects of their lives (Swarbrooke et al., 2003). Drawing from many
varying consumer cohorts, travelers are becoming aware of the importance of
environmental sustainability, cultural authenticity, and preservation as part of their
overall travel experience. This awareness is reflected in their travel behavior, with more
taking interest in adventure travel. As travelers become more sophisticated and
knowledgeable, they find themselves driven to seek out the kinds of activities, cultural
experiences, and unusual destinations for which adventure travel experiences are known.
As a result, the adventure tourism industry is positioned well for continued growth.
Despite growth of the adventure industry, studies focused on adventure tourism

and adventure travelers remain scarce. Those studies conducted have been descriptive

20

rather than predictive and are based on outdoor recreation concepts and theories. The
current state of the literature fails to expand or increase understanding of the diverse
nature of adventure tourism and adventure travelers.

The descriptive research has been geared toward defining adventure tourism (Hall
& Weiler, 1992; Muller & Clever; 2000; Sung, Morrison & O’Leary, 1997; TIA, 1998;
Walle, 1997; Weber, 2001), describing adventure traveler characteristics (CTC, 2003;
Lipscombe, 1995; Millington et al., 2001; Muller & Cleaver, 2000; 01A, 2007; Sung,
2004; Sung et al., 1997; TM, 1998) and activity interests and preferences (CTC, 2003;
Lipscombe, 1995; Millington et al., 2001; OLA, 2007; Sung, 2004; Sung, et al., 2000;
TIA, 1998; Walle, 1997; Weber, 2001).

Studies stemming from traditional outdoor recreation focus primarily on risk
(Ewert, 1989; Meier, 1978; Miles, 1978; Yerkes, 1985). The study of risk has been
prevalent in both the recreation and tourism literature. An example of risk theory that has
been used to explain adventure recreation and travel behavior is Zuckerman’s sensation
seeking scale. Perhaps the foremost authority on risk-taking behavior, Zuckerman (1979)
researched risk in humans centered on sensation seeking as the presumed or general trait
underlying play and novelty seeking. He defined the sensation seeking concept as, “the
seeking of varied, novel, complex and intense sensations and experiences and the
willingness to take physical, social, legal and financial risks for the sake of such
experiences” (p. 13). Zuckerman hypothesized that the principle motive for seeking new
and sometimes risky experiences was a need for sensory stimulation.

In the outdoor recreation literature sensation seeking has been found to be

positively related to individual behaviors including participation in high-risk natural area

21

activities such as mountaineering, spelunking, rock climbing, and ski jumping (Breivik,
1996; Cronin, 1991; Levenson, 1990; Rossi & Cereatti, 1993). The concept has also been
applied successfully in tourism studies, while sensation seeking has been applied in
research on innovative vacations and adventure travel (Gilchrist, Povey, Dickinson, &
Povey, 1995; Wahlers & Etzel, 1985).

While the aforementioned work provides insight into why individuals participate
in adventure travel, it neglects to consider the network of personality traits that play a role
in behavior. Making the assumption that adventure travel behavior is motivated only by
risk, prevents more general models of adventure tourism and their marketing implications
from being explored (Walle, 2002).

It is clear that the subject of consumer behavior in adventure tourism has not been
fully explored (Swarbrooke et al., 2003). In an age where traditional demographics no
longer adequately predict behavior, establishing how factors such as personality
characteristics, and previous experience affect adventure travel behavior, is needed
(Weber, 2001). A number of researchers have noted the importance of examining
adventure tourism behavior from a psychological perspective (Brooker 1983; Cheron &
Ritchie, 1982; J acoby & Kaplan, 1972). Recognizing the underlying psychological and
social dimensions that motivate consumers may offer insight to these experiences that can

benefit the adventure industry as well as address a gap in the literature.

Personality
What makes a person an adventure traveler? One answer may lie in the concept
of personality, which refers to a person’s unique psychological makeup and how it

consistently influences the way a person responds to his or her environment (McCrae &

22

 

-« p... —

-1’.

Costa, 2003). In consumer behavior research, personality is one of the more engrossing
concepts. “Purchasing behavior, media choice, innovation, segmentation, fear, social
influence, product choice, opinion leadership, risk taking, attitude change, and almost
anything else one can think of, have been linked to personality” (Kassarjian, 1971, p.
409).

A variety of approaches to the study of personality can be found in the
psychology literature. Major perspectives of personality theories with the author noted in
parenthesis include: trait and dispositional (Allport, Murray, Cattell, Eysenck, Costa and
McCrae), biological and evolutionary (Darwin), psychoanalytic and neoanalytic (Adler,
Erickson, Freud, Fromm, Horney, and Jung), behavioral and learning (Rotter and
Skinner), phenomenological (Maslow, Rogers, and Wundt) and cognitive (Bandura and
Kelly). The theoretical orientation of the researcher determines the definition of
personality used. The present study employs a trait theory approach to personality, hence
personality was defined as “the hierarchically related set of intra-psychic constructs that
reveal consistency across time that combine with situations to influence the feelings,
thought, intentions, and behavior of individuals” (Mowen, 2000, p. 2).

Trait theory is an approach for analyzing the structure of personality by
measuring, identifying, and classifying similarities and differences in personality
characteristics or traits. A trait is a relatively stable and enduring tendency to behave in a
particular way over a wide range of situations (Plotnik, 2002). Essentially the trait
approach attempts to synthesize and formalize personality traits in order to explain and

predict behavior — in the present case, tourist behavior.

23

Personality and Leisure Behavior

Leading research in leisure has demonstrated that an individual’s personality
influences his or her behaviors and experiences in a leisure setting (Csikszentmihalyi,
1975; Ellis, 1973; Hills & Argyle, 1998; Holland, 1958a; 1985b; Kelly, 1978; Mannell,
1999; Martin & Priest, 1986). A number of different explanations for leisure and
recreation behavior have been proposed. For example, two approaches were developed

by Csikszentmihalyi (1975) and Martin and Priest (1986).

Csikszentmihalyi (1975) developed flow theory to explain leisure and recreation
behavior. The concept of flow has been widely accepted as an explanation of leisure and
recreation behavior. Flow theory suggests people are motivated to participate because of
intrinsic feelings of enjoyment, well-being, and personal competence to achieve. People
enter a flow state when they are so absorbed in an activity that they lose their sense of
time and have feelings of great satisfaction. Csikszentmihalyi identified the following as
accompanying an experience of flow: (1) clear goals — expectations and rules are
discernible and goals are attainable and align appropriately with one's skill set and
abilities, (2) concentration and focus ~— a high degree of concentration on a limited field
of attention, (3) loss of the feeling of selflconsciousness — the merging of action and
awareness, (4) distorted sense of time — one's subjective experience of time is altered, (5)
feedback -— direct and immediate successes and failures in the course of the activity are
apparent (6) balance between ability level and challenge ~ the activity is neither too easy
nor too difficult, (7) control -— a sense of personal power over the situation or activity, (8)
intrinsic rewards - the activity is effortlessness of action, and (9) action awareness merge

_ people become absorbed in their activity and focus of awareness is narrowed to the

24

 

F1

is}

activity itself. It should be noted that not all elements need to be present to experience
flow.

Another approach developed to explain leisure and recreation behavior was the
adventure experience paradigm. The adventure experience paradigm explains behaviors
using the variables of risk and competence (Martin & Priest, 1986). Drawing on previous
research (Csikszentmihalyi, 1975; Ellis, 1973; Mortlock, 1984) the model is based on two
theoretical dimensions, personal skill level and situational challenge. These are viewed as
interacting to create the psychological experience of five distinct states of increasing
degrees of arousal: (1) exploration and experimentation, (2) adventure, (3) peak
adventure, (4) misadventure, and (5) devastation and disaster. For the individual, the
goal of an outdoor adventure experience is to reach peak adventure, since this is the realm
that provides flow and the most positive benefits of adventure experiences. The key lies
in the perception of the individual. Thus, when individuals misperceive both the real risk
and their actual competence, they can overshoot or fall short of the goal of peak
adventure.

Nine types of individuals are identified in Martin and Priest’s (1986) adventure
experience paradigm: ( 1) fearless and arrogant, (2) bold, (3) naive and innocent, (4)
assured, (5) astute, (6) insecure, (7) carefree and exaggerated, (8) overawed, and (9)
timid and fearfid. To illustrate, two examples are provided. The astute individual
correctly perceives the level of risk and competence to perform the activity thus
possesses a high probability of experiencing peak adventure. In contrast, the timid and

fearful individual misperceives adventure by overestimating the risk of the activity, and

25

underestimating his or her competence to perform it, thus falling short of the goal of peak
adventure (Priest & Gass, 2005).

Collectively, these studies support the contention that leisure and recreation
behavior can be viewed as a reflection of the individual’s personality. Consistent with the
trait theory approach of the current study, research relating personality and leisure
behavior has relied primarily on trait theory in order to explain and predict leisure
behavior (Barnett, 2006; Driver & Knopf, 1977; Hills & Argyle, 1998; Lawton, 1994;
Tinsley, Hinson, Tinsley, & Holt, 1993). However, a number of shortcomings have been
noted where personality is used as a predictor of leisure behavior. Mannell (1984) argued
that most research has used general personality inventories to measure individual
differences. He noted that the interaction of personality variables in a situational context
is important and suggested that researchers conceptualize personality dimensions that are
relevant to leisure. Additionally, lso-Ahola (1980) pointed out that the majority of studies
related to personality and leisure have lacked sound theory and measurement has been
inconsistent. These shortcomings may be the reason most research has failed to show a

robust relationship between leisure behavior and personality (N ias, 1985).

Personality and Tourism Behavior

For more than two decades academics have sought to produce meaningful
typologies of tourists and their behavior (Dalen, 1989; Perreault, Dorden, & Dorden,
1979; Westvlaams, Ekonomisch, & Studiebureau, 1986; Wickens, 2002). Some of the
more well-known tourist typologies are those that were developed by Cohen (1972;
1979), Smith (1977 ; 1989), and Plog (1974). In addition, because adventure is a broad

concept involving a wide range of products and people, a number of typologies have been

26

proposed to categorize adventure tourists (Addison, 1999; Lipscombe, 1995; Millington

et al., 2001; TIA, 1998).

Most tourism typologies attempt to group tourists on the basis of their preference
for particular vacation experiences in terms of destinations, activities while on vacation,
and independent travel versus package vacations. Tourist typologies can be grouped into
two general categories: interactional and co gnitive-normative. Interactional typologies
emphasize the way visitors interact with destination areas while cognitive-normative
models highlight the motivation behind travel (Murphy, 1985). To illustrate, the tourist
typologies proposed by Cohen and Smith are considered interactional typologies because
of their focus on the relationships between tourists and their destinations. In contrast,
cogrritive-normative tourist typologies focus on travel motivations of tourists. Plog’s
(1972) model is considered a cognitive-normative typology because it is based on asking
tourists about their general lifestyles or value systems. This psychographic research is
then used to examine tourist motivations, as well as attitudes regarding destinations and
modes of travel (Plog, 1987).

In his typology, Cohen (1972) identified four types of tourists: (1) the organized
mass tourist who buys a package vacation to a popular destination and largely prefers to
travel around with a large group of other tourists, following an inflexible predetermined
itinerary. In general such tourists tend not to stray far from the beach or their hotel; (2)
the individual mass tourist buys a flexible package that allows more freedom, for
example, a fly-drive vacation. Individual mass tourists are more likely, than the organized
mass tourists, to look for the occasional novel experience. However, they still tend to stay

on the beaten track and rely on the formal tourist industry; (3) the explorer makes his or

27

her own travel arrangements and sets out, consciously, to avoid contact with other
tourists. Explorers set out to meet local people but they will expect a certain level of
comfort and security; and, (4) the drifter tries to become accepted as part of the local
community. Drifters have no planned itinerary and choose destinations and
accommodations on a whim. As far as possible, drifters shun all contact with the formal
tourism industry. Cohen further differentiated groups based on their level of contact with
the tourism industry, describing the former two types of tourist as institutionalized
tourists, and the latter two as non-institutionalized. In 1979, Cohen amended his typology
and defined two additional groups of tourists, those who search for pleasure and those
who undertake a modern pilgrimage. Pleasure-seeking tourists include the recreational
tourist, who simply desires entertainment and relaxation as well as the diversionary
tourist, who wishes to escape the routine of everyday life. The modern pilgrimage tourists
encompass three different typologies: the experiential tourist who seeks an authentic
experience but does not totally identify with the foreign culture, the experimental tourist
who wishes to seek an alternative lifestyle but does not become totally immersed in a
foreign culture, and the existential tourist who becomes totally immersed in the foreign
culture.

Sharpley (1994) criticized Cohen’s typology on the grounds that the
institutionalized and non-institutionalized types are not entirely distinct from each other
because even explorers make use of specialist guidebooks to choose their transport routes
and accommodation. He also noted that Cohen’s classification was not based on ‘

empirical research.

28

 

 

{-

Snrith (1989) proposed a typology based on a combination of the number of
tourists and their adaptation to social norms. She identified seven categories of tourists
ranging from explorers who have a quest for discovery and a desire to interact with the
hosts to charter tourists who have little or no interest in the destination itself providing
that the vacation gives them the entertainment and standards of food and acconnnodation
they experience. The other five tourist categories in Smith’s model are: the elite tourist

who is an experienced frequent traveler who likes expensive tailor-made tours; the afl-
beat tourist aims to get away from other tourists; the unusual tourist makes side trips
from organized tours to experience local culture; the incipient mass tourist travelers to
established destinations where tourism is not yet totally dominant; and the mass tourist
expects the same things they use at home.

As in the case of Cohen, Smith’s typology centers around tourism development
and its impacts on destinations. Both typologies are descriptive rather than quantitative
and predictive, and as such, do not increase one’s understanding of tourist behavior.

In contrast to Cohen and Smith’s focus on tourism development and impacts,
Plog’s examined the psychological forces that motivate and influence tourist behavior. In
the 1960’s, Plog was asked by the airline industry to investigate why some travelers were
unwilling to fly and what could be done to encourage them to try air travel (Litvin, 2006).
Plog’s (1972) primary goal was to develOp a typology of travelers that could be used to

predict travel patterns and develop better ways of marketing to these various personality
types. Through in-depth personality research among different types of leisure travelers,
Plog (1972) developed a personality measure specific to tourist behavior. Supporting the

trait approach to personality, he developed a scale of personality traits which included

29

three tourist personality types: psychocentrics, mid-centrics, and allocentrics. Each tourist
type is located on a continuum similar to a bell-curve with psychocentrics at one end of
the continuum and allocentrics at the other end. Psychocentrics are characterized as
anxious, somewhat inhibited, non—adventuresome, inner-focused and primarily in lower
income levels. While in contrast, allocentrics are characterized as adventurous, self-
confident, curious, outgoing and having higher income levels. In the middle of the
continuum, making up the largest number of tourists, are the mid-centrics who travel for
relaxation and pleasure, or the need for a change.

In 1995, Plog modified his model of destination preferences. According to Plog’s
findings, dependables prefer a life that is structured, stable, and predictable. These
individuals follow a set pattern or routine in order to be able to plan their lives. Venturers
tend to go more places more often. Leisure plays a central role in their lives, and they
early seek out new, exotic and/or unknown places.

A number of tourist behavior studies have been based on Plog’s model (Hoxter &
Lester, 1998; Madrigal, 1995; Nickerson & Ellis, 1991; Smith, Williams, Ellis & Daniels,
1986), however, results have been inconclusive. Only partial support for the model was
found by Madrigal (1995), Nickerson and Ellis (1991), and Williams, Ellis, and Daniels
(1986). Results of a study conducted by Hoxter and Lester (1988) were in complete
contrast to Plog. Most notably was the public debate between Smith and Plog. Smith

(1990a) concluded that the allocentric-psychocentric model failed to support the
hypothesized association between personality types and destination preferences. Despite
its widespread application in the private sector, Smith argued that the psychometric

properties of Plog’s scale have not yet been subjected to rigorous examination in the

30

academic literature because of the proprietary nature of the scale. In addition, Smith
(1990b) suggested that rather than concentrate on the relationship between personality
types and destination, research should focus on the possible link between personality type
and travel styles (i.e., how peeple choose to travel).

A great deal of debate has taken place regarding the validity and reliability of
Plog’s scale (Madrigal, 1995; Plog, 1990; 2002; Smith, 1990a; 1990b). Regardless of the
debate surrounding Plog’s model, his work relatexi to the allocentrism-psychocentrism
continuum has received a great deal of attention in academic literature and tourism
textbooks (Gee, Makens, & Choy, 1989; Goeldner & Ritchie, 2003; Gunn, 1994),
suggesting that a suitable alternative for exploring personality as a predictor of adventure
travel behavior has yet to be proposed.

Tourism researchers have also attempted to apply personality typologies from
other disciplines to explain tourism behavior. One example is Holland’s (1985)
personality typology. Developed as a way to identify personality type to guide education
and vocational plarming, Holland (1985) defined an individual’s personality type in terms
of characteristic activities, interests, and competences. Holland’s typology consists of six
different personal orientations to life: (1) realistic, (2) investigative, (3) artistic, (4)
social, (5) enterprising, and (6) conventional. He suggested that a person’s personality
pattern also determines their choice of nonvocational activities and recreation.

Melarned (1995) utilized Holland’s theory to relate work to leisure behavior. To
test the relationship between personality pattern and avocational (i.e., an activity taken up
in addition to one’s regular work or profession, usually for enjoyment; a hobby) choices,

Melamed compared the individual’s vocational personality pattern with the leisure

31

I

activities they most enjoy. A high degree of similarity, or congruence, between group
personality patterns and group leisure patterns was revealed. In an effort to explain tourist
behavior Frew and Shaw (1999) employed Holland’s personality types. They found some
support for the association between Holland’s personality types and tourist behavior.
However, it was concluded that, although there was some utility in the Holland approach
to personality typing, the relationship between occupations (the original Holland focus)
and tourism behavior have yet to be fully investigated.

Addison (1999) proposed the adventure and independence typology. He created a
matrix of challenge and independence. He created a grid based on two axes. On one axis
is the level of adventure, determined by the danger element and skills needed, and thus is
interpreted as the degree of challenge. The other axis is based on the level of
independence or the degree to which participants rely on others to organize the
experience for them (this is particularly relevant and pertinent for the tourism industry as
it reflects the degree to which tourists are reliant on suppliers to organize and manage the
experience). Each axis is a continuum, going from low to high.

A popular typology used by both the tourism industry and academics to describe
the diversity of adventure experiences offered is the hard/soft adventure continuum
(Muller & Cleaver, 2000; OIA, 2007; Pomfret, 2004; Scott & Mowen, 2007; Sung et al.,
2000; TIA, 1998). According to Lipscombe (1995), this continuum involves differing

degrees of challenge, uncertainty, setting, familiarity, personal abilities, intensity,
duration and perceptions of control. Millington et a1. (2001) offered a simpler way to

differentiate between hard and soft adventure. Hard adventure requires some experience

32

and proficiency in the activity prior to the tourism experience, whereas soft adventure
does not necessarily require any previous experience.

Based on this continuum, individual travel behavior may evolve over time from
participating initially in mass recreation and travel activities to a higher level,
participating in soft adventure recreation and travel activities, which may then be
followed by progressing to an even higher level at the top of the hierarchy, participating
in hard adventure recreation and travel activities.

As with any tourist typology, the adventure traveler does not fit into a specific set
of personality characteristics, and all adventure travelers do not share the same tastes or
competencies in adventure activities (Swarbrooke et al., 2003). According to Hill ( 1995),
sofi adventure travelers usually take part in activities with a perceived risk even though
the low levels of real risk only require minimal commitment and beginning skills. In
addition, soft adventure travelers are usually novices to the realm of adventure and enjoy
safe activities which require little or no previous experience (e.g., bird watching in Costa
Rica; bicycling in the South of France; or going on a commercially organized hiking trip
to Machu Picchu).

Research suggests that soft adventurers are motivated by self-discovery, the need
to escape {tom the routine of urban life and experience a new environment with the
potential for excitement, novelty, and the opportunity to socialize in a controlled
environment (Ewert, 1987; Lipscombe, 1995). In some sense, key differences can be
drawn between the soft adventurer traveler and the mass tourist, with the key difference
being that the former type sporadically partakes in adventurous activities while the latter

does not (Cloke & Perkins, 1998).

33

In contrast to soft adventurers, hard adventurers “thrive when exposed to activities
with high levels of risk, requiring intense commitment and advanced skills” (Hill, 1995,
p. 63). These tourists are more likely to engage in physically as well as mentally
challenging outdoor activities, demanding both previous experience and high levels of
competence. According to Lipscombe (1995), hard adventure travelers thrive on the
elements of challenge, danger and risk that contribute towards the adventure. Activities
that appeal to this type of tourist include mountaineering, rock climbing, canyoning,
trekking, exploring remote destinations (e. g., Madagascar), and going on a safari in less
visited wildlife areas in Africa.

The heterogeneous nature of adventure tourism is illustrated by the broad range of
characteristics, motivations, skills and experience of adventure travelers. Evidently,
individuals choose to have a preference for soft or hard adventure for many different
reasons. While this typology is useful in describing different types of adventure travel
activities individuals participate in, the categories do little to explain the underlying
motivations for adventure travel behavior. In the end, it is an individual’s personality and
prior experience that influence behavior and not simply the category of activity.

Lastly, Millington et a1. (2001) proposed a destination and activity driven
adventure tourism typology. They made a basic division within the adventure tourism
market between adventure travel that is destination driven and that which is activity
driven. Destination and activity are then subdivided. In destination-driven adventure
travel, the destination is the most important aspect of the trip, the traveler being interested

in the landscape and scenery, the ecosystems, the people or the history of the place. The

location will often be somewhere unusual, remote or exotic, providing novelty,

34

stimulation, discovery and challenge for the traveler. In activity-driven travel, it is the
activity rather than the destination that is important. The destination could be a remote or
wilderness area if the activity demands it, but could just as easily be near home as abroad.
As the choice of terms suggests, the division used by Millington et a1. (2001) is based on
tourist drive and motivation. However, this means the same experience, for instance an
overland trip in four-wheel drive vehicle, could either be regarded as an activity-driven
trip (if the participant finds the driving activity adventurous) or as destination-driven trip
(if the transport is used merely as a means to access a destination that would otherwise be
inaccessible).

A number of approaches can be taken to categorize adventure tourism
(Swarebrooke et al., 2003). It can be based on product categorization or consumer
categorization. Creating a typology of adventure tourism will always be challenging due
to the fact that consumers and suppliers do not always confine themselves to one
category. Results of a study of adventure travelers have indicated that a substantial sector
of respondents had participated in both hard and soft adventure in five years up to 1997
suggesting cross—over is common (TIA, 1998). Examinations of the dichotomies that

exist within adventure tourism reveal the complexity of the subject as can be seen in

Table 1.

35

 

 

' I!
w

Table 1

Dichotomies within Adventure Tourism

 

Hard +— --> Soft

Remote +— —-> Local

Physical +— -—> Spiritual

Organized +— ——> Independent

Group adventure <— -> Solo adventure

Domestic <— -» International

Artificial environment «— —-> Natural environment
Commercial adventure <— -—+ Voluntary adventure
Wilderness <— -—-> Urban

Low cost <— —+ High cost

Planned «— —+ Unplanned

Set itinerary +— -r ‘Go as you please’

Altruistic s— —-> Hedonistic

Long trips +— ——> Short breaks

100 percent adventure «— —+ Intermittent adventure
Reliance on tourist facilities +— —-> Limited use of tourist facilities
Politically stable destination +— —-> Politically unstable destination
New adventure tourist <— —+ Experienced adventure tourist
High-risk adventure «— -—> Low-risk experience

Real «— -—> Fantasy
Work +— —-§ Play

 

Swarbrooke, J., Beard, C., Leckie,S.,& Pomfret, G. (2003). Adventure tourism: The new frontier.

Despite the fundamental importance of the study of motivation and personality to
consumer researchers, finding a holistic view of the topic in consumer behavior or
psychology is difficult. The inconsistent findings of research on personality and
consumer behavior may be a result of the shortage of unified theories. Additional
problems with current approaches to personality include the focus of many studies on
narrowly defined traits which further fragments the study of personality and motivation.
An excess of individual differences measures have emerged with little effort to find
linkages between the constructs (Mowen, 2000).

Another area where personality and consumer behavior research findings are

inconsistent is the use of psychological scales to investigate consumer phenomena which

36

can be viewed as inappropriate. Personality has traditionally been studied by clinical
psychologists, medical doctors and psychiatrists concerned with mental well-being.
Personality measurement instruments such as the California Personality Inventory
(Gough & Bradley, 1996) and the Edwards Personal Preference Schedule (Edwards,
1959) were developed by psychologists to study abnormal behavior and not consumer
behavior. Tourism behavior can be viewed as “normal behavior” and therefore should be
studied differently (Fridgen, 1991; Jackson, White, & Gronn-White, 2001). Kassarjian
and Sheffet (1991) argued consumer behavior researchers should develop their own
individual difference constructs. However, in a hierarchy of personality traits, these
constructs exist at a surface level (Buss, 1989). It is not enough to know someone is
adventurous or impulsive. A deeper understanding of more basic motives for surface
traits is necessary. Researchers should also identify what underlying psychological traits
contribute to someone being adventurous. Little effort has been made linking constructs
of the numerous individual difference measures that have emerged. It is evident that an
organizing model is necessary for understanding the possible relationships among the
hundreds of extant personality scales. In sum, current models lack a theoretical network
(i.e., nomological net) that explains the underlying psychological antecedents of the

surface traits that have been identified.

The 3M Model of Motivation and Personality
The Meta-Theoretic Model of Motivation and Personality (3M Model), integrates
diverse psychological theories and consumer behavior constructs into a coherent general
theory of motivation and personality. Developed by Mowen (2000), the 3M Model

integrates control theory (Carver & Scheier, 1990), evolutionary psychology principles

37

(Buss, 1988), and elements of hierarchical trait theory (Allport, 1936; Paunonen, 1998).
According to the model, personality traits are arranged in a four—level hierarchy.
Hierarchical models have been previously proposed by consumer researchers

(e.g., Joachimsthaler & Lastovicka, 1984; Lastovick, 1982) as well as tourism researchers
(e.g., Moscardo & Pearce, 1986; Pearce; 1988; 1991; Pearce & Caltabiano, 1983; Pearce
& Lee, 2005); however, the 3M Model is the first to provide a general schema for
classifying the level at which a particular trait resides. The primary goal of using an
integrated model of motivation and personality in this research was to overcome the
problem of dealing with a multitude of disconnected constructs in consumer behavior by
providing an organizational structure for the placement of the individual difference
variables.

The 3M Model employs a control theory approach (Carver & Scheier, 1990) and
proposes that behavior is motivated when an actual or anticipated outcome diverges from
one or more personality traits that act as reference points for evaluating outcomes. Based
on hierarchical approaches to personality (e. g., Allport, 193 7), traits are arranged in a
four-level hierarchy from the most abstract level to the most concrete level. The four
levels are labeled elemental traits, compound traits, situational traits, and surface traits.

Residing at the most abstract level are the elemental traits. Elemental traits are
defined as cross-situational, enduring dispositions to respond that result from an

individual’s genetics and the early learning history. The eight elemental traits are:
openness to experience, conscientiousness, extraversion (operationalized as introversion),
agreeability, neuroticism (emotional instability), material needs, need for arousal, and

physical/body needs. The first five traits were adapted from Saucier’s (1994) version of

38

the Five-F actor model. The need for arousal was adapted from Zuckerman’s (1979) work
on sensation seeking. Developed fiom evolutionary psychology principles were the two
constructs material needs and physical/body needs. That is, two needs that arose from
selective selection pressures and were necessary for the survival of the species. For
example, without a need to create material resources such as tools, weapons, clothing,
and shelter, the species would not have survived.

Residing at the next level of the hierarchy are compound traits. Similar to
elemental traits, they are cross-situational in nature. Compound traits are defined as
enduring dispositions that result from the effects of subsets of elemental traits as well as
from cultural and sub-cultural influences. General self-efficacy, competitiveness, the
need for learning, and the need for activity are examples (Mowen, 2000). Analogous to
physical compounds, compound traits result in part from the effects of elemental traits.

The third type of constructs in the 3M Model are situational traits. They are
defined as enduring dispositions to behave within a general situational context.
Situational traits are influenced by the pressures of the situational environment and the
effects of the elemental and compound traits. For instance, health motivation was
identified as residing at the situational level (Moorrnan & Matulich, 1993; Mowen,
2000). That is, the trait manifests in situations that deal with health — broadly defined.

Finally, at the most concrete level are surface traits. These constructs represent
highly specific enduring dispositions to behave that result from the effects of elemental,

compound, and situational traits as well as from the pressure of the context-specific
environment. Surface traits occur in narrow contexts that fall within the more general

context of the situational traits. For example, Mowen (2000) found that the surface trait

39

of healthy diet lifestyles resulted in part from the more general trait of health motivation
(Moonnan & Matulich, 1993) as well as the elemental traits of physical/body needs and
need for arousal (negative relationship). Because surface traits are context specific, they
have a strong relationship with behavioral measure. In other words, they are associated
with specific behaviors that occur within a specific time period.

In sum, in the 3M Model the four levels of traits provide the reference points for
the control theory model, moving from the most abstract to the most concrete, beginning
with elemental, compound, situational, and finally surface. These traits form an

individual’s self-concept. A summary of the 3M Model hierarchy is provided (Table 2).

Table 2

Levels of Traits in the 3M Model Hierarchy

 

Level 1: Surface Traits
1) Highly specific, context constrained enduring dispositions;

2) very numerous in number; and
3) result from the effects of Level 4-2 constructs and the press of the context.

Examples: surface traits such as health diet lifestyle.

 

 

 

 

Level 2: Situational Traits
1) Situationally specific enduring dispositions;
2) more numerous than Level 3 constructs; and
3) result from combinations of Level 3-4 constructs and the press of the general situation.

Examples: situational traits such as health motivation.

 

 

 

 

Level 3: Compound Traits
1) Abstract, cross-situational enduring dispositions;
2) more numerous than Level 4 constructs; and
3) combine to form more concrete constructs.
Examples: compound traits (Mowen, 2000), instrumental values (Rokeach,

r979)

 

 

 

 

Level 4: Elemental Traits
1) Highly abstract, cross-situational enduring dispositions;
2) very lirrrited in number; and
3) combine to form more concrete constructs.
Examples: elemental traits (Mowen, 2000), terminal values
(Rokeach, 1979).
Mowen, J. C., & Voss, K. E. (2008). On building better construct measures: Implications of a

general hierarchical model.

 

 

 

40

Hypotheses Development

Elemental Traits

At the first level of the hierarchy are the elemental traits. Elemental traits are
defined as “unidimensional underlying predispositions of individuals that arise from
genetics and early learning history and represent the broadest reference for performing
programs of behavior” (Mowen, 2000, p. 21). Based on a series of studies, the 3M Model
proposes eight elemental traits: need for arousal, agreeability, conscientiousness,
openness to experience, neuroticism, material needs, extroversion, and body needs. The
structure, the predictive validity, and the construct validity of the eight elemental traits
were supported in a series of studies (Mowen, 2000). Additionally, the discriminant
validity of the elemental traits was supported in research by Licata, Mowen, Harris, and
Brown (2003).

Considered building blocks for more concrete-level traits, Mowen (2000)
suggested that the all the elemental traits should be included as control variables when
analyzing the full hierarchical model. Elemental traits combine to influence the
development of compound, situational, and surface traits, thus the effects of the elemental
traits should be statistically controlled when evaluating the impact of more concrete
traits. This also minimizes the likelihood of the omitted variable problem. That is, if the
elemental traits are not included, it can appear as though a compound or situational trait is
Predicting a surface trait. However, when the elemental traits are added, the relationship
disappears. Mowen and Voss (2008) have given the name ‘illusory prediction’ to this

phenomenon.

41

Accordingly, each of the eight elemental traits will be investigated in the present
research either as a control variable or as an antecedent of the surface trait ATP. Based on
the previous literature, two of the elemental traits — the need for arousal and agreeability—
were proposed to be associated with ATP.

Need for arousal. The need for arousal is defined as “the desire for stimulation
and excitement” (Mowen, 2000, p. 29). One motivation for taking an adventure travel
vacation may be to gain stimulation through the senses. Based upon the work of
Zuckeiman (197 9), Mowen (2000) deveIOped a scale to measure sensation seeking,
which he labeled the need for arousal (i.e., the desire for stimulation and excitement).
These ideas suggest that individuals who have a greater desire for excitement will show a

stronger propensity for adventure travel.

Berlyne (1978), a leading investigator of arousal theory, proposed that some
people prefer highly stimulating situations that match their high levels of optimal
stimulation, whereas others avoid over stimulation since their preferred levels of arousal
are much lower. In the context of leisure and tourism, Iso-Ahola (1989) offered that
optimal level of stimulation could be understood as a balance between the need for
stability and the need for variety. A number of studies have explored and confirmed the
influence of the need for arousal and recreation and travel behavior.

Research supports participation in recreation and tourism can be used to fulfill the
need for arousal. Zuckerman’s (1994) sensation seeking scale has been used to
understand the influence of need for arousal in both recreation and tourism behavior.

Sensation seeking has been positively related to a number of adventure recreation

activities including: parachuting (Rowland, Franken, & Harrison, 1986), mountain

42

climbing (Robinson, 1985) and down-hill skiing (Bouter, Knipschild, F eij, & Volovics,

1988), tourism (Eachus, 2004), and adventure tourism (Gilchrist, 1994; Gilchrist et al.,

1995)
In a study of overland travelers Gilchrist (1994) found adventure travelers have a

greater desire to engage in risky and adventurous sports and activities involving speed

and danger. Gilchrist (1994) also suggested that adventure travelers “seek more
experiences through mind and senses, travel and non-conforming lifestyles” (p. 35). In a
follow-up study, Gilchrist et a1. (1995) tested the hypothesis that propensity for adventure
vacations and sensation seeking are related. As assumed, the thrill and adventure subscale
of the sensation seeking scale was significantly related to a propensity for adventure
vacations. The authors concluded that the concept of sensation seeking is useful in
tourism research. The association of sensation seeking with adventure activities as

mentioned above attests to its usefulness in predicting certain types of leisure and tourism

activities.

Based on the literature, it is evident that the concept of need for arousal has found
significant currency in the fields of recreation and tourism. Need for arousal has been
proposed to influence the decision to engage in adventure travel. Because of its
relationship to recreation and tourism behavior, it is anticipated that the need for arousal
would be positively influence the surface trait of ATP.

H1: The elemental trait need for arousal will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor

adventure experiences, and extreme adventure experiences (ATP).

43

Agreeability. The second elemental trait proposed to be associated with ATP, is
agreeability. Agreeability is defined as “the need to experience kindness and sympathy
towards others” (Mowen, 2000, p.29). Costa and McCrae (1992) found that individuals
who can be described as agreeable are also are perceived as being trusting, cooperative,
and compliant. As defined, agreeability refers to how individuals relate with others and
how considerate they are of others’ feelings and opinions. Agreeable people see others as
mostly honest and trustworthy; they are straightforward and flank, willing to help out,

yielding rather than aggressive in conflict, modest and unpretentious, and caring,

nurturing and supportive.

Agreeability has been associated with play and adventure recreation and has been
seen by some as a form of adult play (Carpenter & Priest, 1989). Because play is
intrinsically motivated and involves positive emotions, one can anticipate that elemental
traits that have positive emotional tone, such as agreeability and extroversion, would be

associated with play. Thus, the elemental trait of agreeability is proposed to influence

ATP.
H2: The elemental trait agreeability will positively influence ultimate destination
experiences, tropical adventure experiences, traditional outdoor adventure
experiences, and extreme adventure experiences (ATP).

Compound Traits

At the second level of the hierarchy are the compound traits. Compound traits are
defined as “the unidimensional predispositions that result from the effects of multiple
elemental traits, a person’s learning history, and culture” (Mowen, 2000, p. 21).

Compound traits differ from the elemental traits in that elemental traits provide general

44

 

guidelines for selecting and running programs of behavior. Like the elemental traits, they
provide reference points for evaluating and interpreting outcomes, but they are narrower
in application than elemental traits and function specifically to guide programs of the
control model behavior. Traits hypothesized to function at the compound level include:
task orientation - close relative achievement motivation, the need for learning, need for
activity, need for play, and effectance motivation. The compound traits investigated in
the current research are: (1) competitiveness, (2) altruism, and (3) the need for learning.
While other compound traits have been developed (e.g., task orientation, need for

activity), these three were selected as a result of the implications drawn from previous

research.

Competitiveness. According to Spence and Helmreich (1983) the
competitiveness trait is defined as “the enjoyment of interpersonal competition and the
desire to win and be better than others” (p. 41). A study conducted by Deci and Ryan
(2000) found that the sense of competence gained through competition can be
intrinsically motivating. Therefore, people will seek out activities that are likely to

provide them with intrinsic rewards and a sense of autonomy and competence.

The competitiveness trait has been explored extensively in the sport and physical
education literature (Duda, 1993a; 1993b; Frederick-Recascino & Schuster-Smith, 2003;
Roberts, 1992). Mowen (2004) employed a hierarchical personality model approach to
investigate the trait of competitiveness and results indicated the trait was positively
associated with consumer behavior in three contexts: (1) besting others directly in
contests (e.g., playing sports), (2) besting others indirectly through vicarious experiences

(e.g., observing sports as a fan or watching drama-based movies), and (3) besting others

45

via the conspicuous consumption of material goods (e. g., purchasing innovative
electronic products). Frederick-Recascino and Schuster-Smith (2003) suggested
competitiveness exists in other life domains and not only in sporting environments.
Achievement goal theory suggests that goal orientations and the perceived
motivational climate influence recreation behavior (Katzell & Thompson, 1990).

Someone who is competitive should have a higher level of achievement motivation

 

(Ward, 1997). Tran and Ralston (2006) observed individuals with high need for
achievement tended to prefer tourism experiences which were challenging and involved
natural settings. These results are consistent with McClelland’s (1965) theory, in which
achievement motivation was linked to overcoming challenges. The results suggest people
possessing a high need for achievement will be more competitive and most likely prefer ‘1
adventure travel. Based on the literature, competitiveness may be an antecedent of ATP i
and thus, the following hypothesis is proposed.

H3: The compound trait competitiveness will positively influence ultimate

destination experiences, tropical adventure experiences, traditional outdoor

adventure experiences, and extreme adventure experiences (ATP).

Altruism. The third compound trait proposed as a result of previous research is
altruism (Brown & Lehto, 2005; Bussell & Forbes, 2002; Mowen & Sujan, 2005; Unger,
1991; Wearing, 2001). Altruism is defined by Mowen and Sujan (2005) as a “general
predisposition to selflessly seek to help others” (p. 173). Empirical research conducted by

Unger (1991) found support for altruistic motives in volunteerism. She identified the

46

construct as the primary motivator for volunteering to help others. Bussell and Forbes
(2002) also noted “a volunteer must have some altruistic motive” (p. 246).

A growing trend in the tourism industry is the concept of ‘volunteer tourism’
(Wearing, 2001). Brown and Lehto (2005) suggested volunteer vacationers are driven by
the sense of adventure, desires for exploration and novelty that are not as prominent with
the more serious volunteer travelers. Using Plog’s (1974) typology, they went on to
propose volunteer vacationers can also be labeled as allocentrics - explorers and
adventure seekers who tend to choose remote and untouched destinations. The sense of
adventure and desire for exploration and novelty found to be prominent in volunteer
vacations may be why so many adventure travel tour operators offer opportunities to give
back to the communities they visit.

Anecdotal support for the link between the adventure travel industry and travel
philanthropy or altruism can be found in adventure tour operator’s websites and
brochures. The most noted objectives include commitment to the cultural and
environmental well-being of the places visited. These objectives are furthered through
partnerships with an array of non-profit organizations. One example, Geographic
Expeditions (http://www.geoex.com/index.asp), promotes the motto: “we follow
scientifically supported on-the-ground and at-sea minimum-impact practices. We seek to
create inspirational experiences for our travelers, and we partner with a wide array of
nonprofit organizations that further these objectives.” According to Sustainable Travel
International (2009) this is considered travel philanthropy, also known as altruistic travel.
Travel philanthropy or altruistic travel is defined on Sustainable Travel Intemational’s

website as “a voluntary movement of conscientious consumers and responsrble travel

47

 

companies who are donating financial resources, time, talent and economic patronage to
protect and positively impact the cultures and environments they visit”
(http://www.sustainabletravelinternational.org/).

Following Mowen and Sujan (2005), altruism was identified as a cross-
situational, compound-level trait in this study. Based on the literature, it is hypothesized
that altruism will positively influence ATP. Thus, H‘ is proposed:

H4: The compound trait altruism will positively influence ultimate destination

experiences, tropical adventure experiences, traditional outdoor adventure

experiences, and extreme adventure experiences (ATP).

Need for learning. The second compound trait proposed to influence ATP is the
need for learning. Mowen (2000) defined need for learning as “an enduring disposition to
seek information resource” (p. 72). He developed a measure of the need for learning and
identified it as a compound trait. The construct was designed to measure the cross
situational predisposition to obtain information resources.

According to Swarbrooke et a1. (2003), exploration and discovery are core
components of the adventure process. The increased knowledge and self-awareness that
accompanies the discovery of new places, cultures and skills from one of the rewards
travelers seek from their experience. Addison (1999) argued that education and the
hunger to learn from new situations are key motivations for both travel and adventure.
Walle (1997) offered an expansion and redefinition of adventure tourism by proposing
the insight model as its basis. He argued that it is the quest for insight and knowledge

(rather than risk) that underlies adventure tourism. He proposed to replace the prevalent

48

risk theory as the foundation of adventure tourism based on the important role of
knowledge and learning in the adventure experience. Sung et al. (1997) suggested that a
reason for engaging in adventure travel is the educational opportunities. In addition,
Weber (2001) identified learning and insight as motives for engaging adventure travel.
These studies suggest that a motive for engaging in adventure travel may be to learn more
about other people, places, and cultures.

Based on previous research it is anticipated that the need for learning would
positively influence ATP. Thus, the following hypothesis is offered:

H5: The compound trait need for learning will positively influence ultimate

destination experiences, tropical adventure experiences, traditional outdoor

adventure experiences, and extreme adventure experiences (ATP).

Situational Traits

At the third level of the hierarchy are situational traits. Situational traits are
defined as “the unidimensional predispositions to behave within a general situational
context” (Mowen, 2000, p. 21). They are influenced by the pressures of the situational
environment and by the effects of elemental and compound traits. A number of
situational traits exist including: value consciousness, general sports interest, product
leadership, and health motivation. Situational traits result fiom the interaction of the
situational context with more basic personality characteristics, and are predictive of the
more concrete surface traits. Mowen and Sujan (2005) proposed that situational traits act
as motives for engaging in behavior. According to Mowen (2000), a starting point for

identifying the contexts within which situational traits emerge can be found in Belk’s

49

(1974) work on situational influences. Thus, dispositions to behave may emerge with
regard to circumstances involving the social context, time, and task definition.

Mowen and Sujan (2005) proposed that situational traits act as motives for
engaging in behavior. In the present research, three situational traits are investigated: (1)
interest in cultural experiences, (2) need for uniqueness, and (3) fashion leadership. These
three situational traits were selected as a result of the implications drawn from previous
research as described below.

Interest in cultural experiences. Interest in cultural experiences is proposed to
be a reason people participate in adventure travel. Similar to the measure of arts and
humanities (Mowen & Carlson, 2003), the interest in cultural experiences trait was
proposed to be a situational trait. According to Tran and Ralston (2006), interest in
cultural experience comprises the activities that take place on the mosaic of places,
traditions, art forms, celebrations, and experiences portraying the beauty of a country and
its people, reflecting the diversity and character of the country. Individuals interested in
cultural experiences seek out opportunities to broaden their participation in the arts and
involvement with local artisans. An individual may be motivated to travel to gain cultural
experiences such as those that result from exposure to indigenous people, trying local
foods and customs, and diverse destinations.

The diverse nature of adventure tourism means that participants have a wide range
of motives. Adventure research has traditionally focused on gaining skills and
competence in a natural setting involving some risk. However, recently the role of
cultural experiences has been identified as an important motive for adventure travelers. In

a study by Sung et a1. (1997), interpretation of the environment and culture was noted as

50

 

one of the benefits adventure travelers seek from their adventure experiences. According
to Weber (2001), motivations beyond those traditionally identified by adventure
researchers include the desire to travel through peripheral destinations, oflen rich in
cultural traditions. It was concluded that the cultural environment is important to the
adventure tourist. Consumer research conducted on behalf of the Adventure Travel Trade
Association {http://wwwgdventuretrgvelbizfl also supports the importance of culture and
ecotourism in adventure experiences (Schneider & Vogt, 2005).

These studies illustrate the importance adventure travelers place on the cultural
aspect of their adventure travel experience. Thus, the following hypothesis is proposed:

H6: The situational trait interest in cultural experiences will positively influence

ultimate destination experiences, tropical adventure experiences, traditional

outdoor adventure experiences, and extreme adventure experiences (ATP).

Need for uniqueness. The second situational trait proposed as a result of
previous research is need for uniqueness. Consumers’ need for uniqueness is defined as
an individual’s pursuit of differentness relative to others that is achieved through the
acquisition, utilization, and disposition of consumer goods for the purpose of developing
and enhancing one’s personal and social identity (Tian et al., 2001). One way individuals
differentiate themselves is through product purchases of which travel may serve as a

recognizable symbol of uniqueness (T ian et al., 2001).

Status has been related to the purchase of adventure tourism products. The
concept of status clearly varies between different kinds of products and experiences. It
may mean exclusivity on the basis of rarity or the uniqueness of the experience and/or

high price. Alternatively, status may be gained from being away from other tourists or

51

visiting exotic destinations at low cost as a budget traveler. Here, the lower the price paid,
the greater the status. This is particularly the case in the student backpacker market
(Swarbrooke et al., 2003). Thus, travel experiences with distinct characteristics may
allow a person to stand out among others, therefore providing a sense of uniqueness.
Based on the literature H 7 is proposed:
H7: The situational trait need for uniqueness will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor

adventure experiences, and extreme adventure experiences (ATP).

Fashion leadership. The third situational trait proposed to be a motive for
adventure travel is fashion leadership. Goldsmith, Freiden, and Kilsheimer (1993)
described fashion leaders as those who learn about new fashions earlier than the average
buyer and purchase new items soon after they are introduced to the market. The
relationship between the adventure tourism and outdoor fashion industry is evidenced by
the rapid grth of each segment of the adventure industry. Sung et al. (1997) noted the
rapid growth of adventure tour operators matched the growth of equipment and gear
manufacturers, as well as commercial outfitters and retailers. During the past decade

growth has continued with outdoor retailers like North Face, Patagonia, and REI leading

the way.

Fashion leadership may be a motive for adventure travel because of the
requirements of suitable attire for adventure experience. Both technical and non-technical
clothing involved in many adventure tourism activities is a central part of their role in

performance (Buckley, 2007). Tied to the conceptions of looking good, are notions of

“looking like” or having the image of being an adventurer.

52

The idea of an adventure identity is evidenced by an article in Rock and Ice, a
magazine for rock climbers (Bisharat, 2007). In Unconscionable Fashionable, the author
suggests that, while climbers want to “look” like climbers, the biggest taboo in climbing
is admitting that the sport has fashion. The word ”fashion" has always suffered from its
association with fads and materialism, two things climbers prefer to avoid. In the last five
years, a growing number of "climber clothing" companies have emerged such as Climb
It, Khadejha, Blurr, Stonewear Designs, and Nau and Sickle, joining those that have
been around forever, including Gramicci, Patagonia, Prana and Verve.

Leisure and travel behavior has been linked to an individual’s identity (Haggard
& Williams, 1992; Prebensen, Larsen, & Abelsen, 1993). Wearing and purchasing of
adventure clothing and gear allow an individual to form and express his or her personal
identity (Evans, 1989). Research has shown clothing has been an effective category in
identity formation (Dodd, Clark, Baron, & Houston, 2000). Thus, it can be proposed that
individuals express their personal identity through the purchase of adventure travel
clothing and gear. Based on these ideas He is proposed:

He: The situational trait fashion leadership will positively influence ultimate

destination experiences, tropical adventure experiences, traditional outdoor

adventure experiences, and extreme adventure experiences (ATP).

Surface Traits
At the fourth and final level of the hierarchy are surface traits. Surface traits
“delineate the programs of behavior that individuals run in order to complete tasks”
(Mowen, 2000, p. 21). These traits are a result of person, situation, product and category

interactions. Surface traits result from the effects of elemental, compound, and situational

53

traits as well as fiom the pressure of the context specific environment. In contrast to the
more general situational traits, surface traits occur in narrower contexts and can be
expected to lead to a category specific disposition. In the context of the 3M Model,
Mowen (2000) proposed that a combination of traits from the different levels of the
hierarchy directly and/or indirectly influence outcomes. Surface traits are expected to be
strong predictors of outcomes. A new scale was developed for this study to measure ATP,
as a function of adventure travel experiences. ATP is conceptualized as a surface level
trait because of its specificity. ATP represents an enduring disposition, not a specific act
or behavior. Because the 3M Model proposes that partial mediation exists between traits
at each level in the hierarchy, it can be anticipated that a combination of traits will be
predictive of the surface trait. Figure 2 provides a summary of the proposed hypotheses

within the 3M Model hierarchy.

54

Figure 2

Conceptual Model Adventure Travel Propensity

 

Level 1: Surface Traits
Adventure Travel Propensity (ATP)
Ultimate Destination Experiences
Tropical Adventure Experiences
Traditional Outdoor Adventure Experiences
Extreme Adventure Experiences

 

 

 

 

Level 2: Situational Traits
Interest in Cultural Experiences
Need for Uniqueness
Fashion Leadership

 

Level 3: Compound Traits
Competitiveness
Altruism

Need for LearninL

 

Level 4: Elemental Traits
Need for Arousal

Aggability

Summary of the Literature Review

The concept of personality as a predictor of travel behavior makes intuitive sense

to both marketers and academics. However, the review of literature consumer behavior

and tourism research literature related to personality research indicates that it has fallen

short on accurately predicting tourist behavior (Jackson et al., 2001 ). Understanding the

individual person in his or her role as a consumer should be a key issue in the study of

tourist behavior. Therefore, expanding the scope of personality research currently

available in the field of travel and tourism is a useful exercise. Several studies have

indicated a positive relationship between personality and tourist behavior, but results

have been inconsistent. These inconsistencies may be the result of the lack of an

55

 

 

overarching theory, which acknowledges that a hierarchy of personality traits plays a role
in behavior.

Building on the conceptual framework developed by Mowen (2000), the
motivation and personality systems of adventure travelers were examined. To smarize

the following hypotheses were proposed:

H1: The elemental trait need for arousal will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor
adventure experiences, and extreme adventure experiences (ATP).

H2: The elemental trait agreeability will positively influence ultimate destination
experiences, tropical adventure experiences, traditional outdoor adventure
experiences, and extreme adventure experiences (ATP).

H3: The compound trait competitiveness will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor
adventure experiences, and extreme adventure experiences (ATP).

H4: The compound trait altruism will positively influence ultimate destination
experiences, tropical adventure experiences, traditional outdoor adventure
experiences, and extreme adventure experiences (ATP).

H5: The compound trait need for learning will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor

adventure experiences, and extreme adventure experiences (ATP).

56

H6: The situational trait interest in cultural experiences will positively influence
ultimate destination experiences, tropical adventure experiences, traditional
outdoor adventure experiences, and extreme adventure experiences (ATP).

H 7 : The situational trait need for uniqueness will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor
adventure experiences, and extreme adventure experiences (ATP).

H8: The situational trait fashion leadership will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor

adventure experiences, and extreme adventure experiences (ATP).

In Chapter II an in-depth overview of the study’s theoretical concepts and
justification of the constructs were explored in relation to personality and adventure
tourist behavior. The study’s proposed model and hypotheses were also discussed.
Chapter HI outlines the research methodology used to obtain and analyze information for
this study consisting of the sample and population description, data collection techniques,

non-respondents assessment, research instrument (including reliability testing), followed

by statistical procedures.

57

CHAPTER III
METHODOLOGY
The philosophical stance of the researcher is outlined in this section, providing a
briefing on the methodological choices underpinning the current study. In developing a
research proposal, considerable effort should be exerted in determining which
methodologies and methods will be employed (Crotty, 2003).

Paradigms are the fundamental models or frames of reference used to organize
observations and reasoning. They are general frameworks, literally “points from which to
view” providing ways of looking at life that are grounded in sets of assumptions about
the nature of reality. Social scientists use a variety of paradigms to organize and inquire
into social life (Babbie, 2001). Given the research problems and questions outlined
above, a post positivist approach to the research was determined to be best, since it is
concerned with finding the facts and causes of social and human phenomena (Crotty,
2003). This approach permitted the researcher to analyze the situation through hard data
gleaned from replicable research. Using a post positivist approach shaped the
methodology, since data were collected in a structured manner, and the aim of the
researcher was not to intervene in the phenomenon that was investigated.

This study drew on the methods of previous tourism and consumer behavior
research and chose to engage in survey research, employing a quantitative method of
statistical analysis. The following sections discuss the research method used to obtain and
analyze information for this study. First, the population and sample are described. Next,

the data collection techniques and study instrument, non-respondent survey, and

58

reliability tests are described. Finally, the statistical tests used for data analysis are

explained including the scale development.

Methods

Study Papulation and Sampling

Sampling is the process of selecting units (e. g., people, organizations) from a
population of interest. By studying the sample, the results may be generalized back to the
population from which they were chosen (Babbie, 2001; Trochim, 2005). In most applied
social research, it is the group to which the researcher seeks to generalize. In the current
study, the theoretical population of interest is adventure travelers. To draw a sample, a
list of accessible members of the population was required.

With the theoretical population identified as adventure travelers, the accessible
population for the current study was subscribers to National Geographic Adventure
magazine. Accessible populations to study adventure travelers included other adventure
focused magazines such as Outside, Men ’s Journal, Climbing, Rock and Ice. However,
these publications were determined to be either gender-focused, narrow in scope, or too
specialized for the purposes of the current study of general adventure travel behavior. A
number of television programs exist that appeal to the adventure travel market as well,
but an accessible population “list” of viewers does not exist.

Beginning in the fall of 2004, the researcher conducted research at consumer
adventure travel trade shows in partnership with the Adventure Travel Trade Association

(ATTA). The ATTA “serves as a strategic membership organization for companies in the
adventure travel arena. The ATTA is dedicated to raising the profile of adventure travel

in the world travel market and provides valuable services, knowledge and connections to

59

help members succeed in their businesses, thereby contributing to industry-wide growth”
(http://www.adventuretravel.biz/). Through the ATTA, relationships were established
with representatives from National Geographic who agreed to support the study of
adventure travelers for this dissertation. National Geographic provided the funds to cover
the costs involved in printing and mailing the survey, as well as supplying incentives to
ensure the best possible response rate. Finally, National Geographic granted unrestricted
access to their mailing list for the sample to be drawn. Thus, the sampling frame, the
listing of accessible population from which the sample was drawn, was taken from a list
of individuals who were current subscribers to National Geographic Adventure magazine
in 2007.

National Geographic Adventure magazine (N GA) was launched in 1999 and is
published by the National Geographic Society. The National Geographic Society’s
mission is to “Inspire People to Care about the Planet,” and NGA extends that mission by
sending people out to experience cultures and outdoor activities in the world’s most
compelling local and international places. They describes their readers as “consumers
who are curious about the world and all the fun things to do in it, eager to break out of
their comfort zone to achieve a great life experience, and are proactive about their health;
challenge seekers who relish the feeling of accomplishment” (National Geographic
Adventure Media Kit, 2006). The editorial profile for NGA states: “NGA is the only

magazine fully committed to covering the adventure lifestyle, largely characterized by
outdoor sports and adventure travel” making NGA subscribers an ideal p0pulation to

sample to empirically test if a set of personality traits exist that are predictive of ATP.

60

The subscriber group can be considered as actively involved or at least interested
in taking adventure travel trips, therefore representing adventure travelers in the United
States. To generalize findings of a study for strong external validity, most researchers
' recommend selecting a random sample, in which each individual in the sample has equal
probability of being selected (Cresswell, 1994). Other researchers suggest that such
randomly selected samples should be stratified so that specific characteristics can be
represented in the sample and reflect the true characteristics of the entire population
(Fowler, 1988; Levy & Lemeshow, 1999; Morrison, 1996). The stratified random
sampling method adopted in this study was based upon NGA subscriber distribution in
the four census regions within the United States (Table 3), which reflects the proportions
of the samples drawn from each region in order to represent the true distribution of the
entire population. As noted in Alreck and Settle (2004), the maximum practical size for a
sample under ordinary conditions is about 1,000 respondents. Therefore a sample of
1,000 subscribers was drawn based on the total paid and verified subscriptions (220,847).
The subscriber group can be considered as being activity involved or interested in
adventure travel, representing adventure travelers in the United States.

In addition to the NGA sample, a general population sample was also drawn;
however, the focus of this dissertation is the NGA sample only. As an extension of the

current study, results from the NGA population will be compared with the general
population sample to explore difference in motivation-personality traits between the two

groups.

61

Table 3

Circulation of National Geographic Adventure Magazine Subscribers for Stratified
Random Sampling

 

 

Geographic Number of (y
Mons Divisions Subscribers °
Northeast Connecticut, Maine, Massachusetts, New Hampshire, New 41,470 18.7

Jersey, New York, Pennsylvania, Rhode Island, Vermont

South Alabama, Arkansas, Delaware, District of Columbia, Florida, 80,4 79 36.4
Georgia, Kentucky, Louisiana, Maryland, Mississippi, North
Carolina, Oklahoma, South Carolina, Tennessee, Texas,
Virginia, West Virginia

Midwest Indiana, Illinois, Iowa, Kansas, Michigan, Minnesota, 49,517 22.5
Missouri, Nebraska, North Dakota, Ohio, South Dakota,
Wisconsin

West Arizona, California, Colorado, Idaho, Montana, Nevada, 49,381 22.4

New Mexico, Oregon, Utah, Washington, Wyoming1

Total 220,847 100

IAlaska and Hawaii residents were not included in the survey in keeping with a sample from the 48
contiguous states.

Data Collection
Self-administered questionnaires were mailed and data collected during the fall of

2007. The majority of previous studies of adventure travel behavior employed survey
research methods for collecting data. Surveys may be used for descriptive, exploratory
and explanatory purposes. According to Fowler (2001), survey research is one of the
most important areas of measurement in applied social research. Employing probability
sampling allows the administrator to collect data from a group of respondents whose
characteristics reflect those of the population which may be too large to observe directly.
Morrison (1996) pointed out that mail surveys are a popular research method in travel

and tourism because of the many advantages offered. The main advantages of a mail

survey include: they are relatively inexpensive to administer, the exact same instrument

can be sent to a wide number of people, and respondents can complete at their

62

convenience (Trochim, 2005). Additionally, surveys are valid instruments for measuring
attitudes and behaviors (Fowler, 2001). However, a few disadvantages of a mail survey
include: low response rates, as well as lack interaction with respondents (Trochim, 2005).

A multi-method approach was used to develop the survey instrument. First, a
literature review of existing research related to adventure recreation and tourism,
consumer behavior, and personality was completed. Second, a panel interview with
adventure industry leaders was conducted. Key representatives from the Outdoor Industry
Association (OIA), ATTA, and National Geographic were identified as those with the
greatest amount of insight, or information rich cases, on the topic of adventure recreation
and tourism. Patton (1990) described information rich cases as “those from which one
can learn a great deal about the issues of central importance to the purpose of the
research” (p.169). The primary topics of interest and questions salient to the key
representatives of the adventure industry were: (1) What aspects of our self concepts
influence our priorities in becoming tourists or adventurers, (2) What do people aspire to
do on vacations and how does that relate to what they actually do, (3) What is the profile
of the adventure traveler (e.g., owning a passport, pre and post trip lifestyle changes,
international travel experience/intentions, number of vacation trips taken per year), and
(4) What are the most powerful marketing techniques to influence adventurers? A
questionnaire was developed combining previous studies and theories in the consumer
behavior and recreation and tourism literature along with key industry perspectives.

To ensure content validity of the questionnaire and clarity of questions and
instructions, a draft survey was shared with the adventure industry panel and tourism

researchers and feedback requested. In addition, the draft survey was pilot tested with

63

tourism students at Michigan State University. As suggested by Creswell (1994), this
testing is important to establish the face validity of the questionnaire and improve
questions, format, and the scales of the instrument. Next, the questionnaire was modified
as a result of feedback from industry leaders and the pilot study, and a finalized version
of the questionnaire was administered following Dillman’s (2000) total design method
for mail surveys (Appendix A: Survey Instrument). The questionnaire was mailed along
with a cover letter and pre-paid envelope (Appendix B: Survey Cover letter). The cover
letter included a statement guaranteeing respondents’ data confidentiality and protection
of their privacy. One week later, a postcard reminder was sent, followed by a revised
second letter and a replacement questionnaire in another two weeks to reduce non-
response rate (Appendix C: Postcard Reminder).

Ordinarily, response rates for mail surveys are low, resulting in two negative
effects: (1) increased costs because the number of mailing pieces must be several times
the number of respondents required and (2) increased likelihood of non-response bias,
reducing validity. To minimize costs and reduce non-response bias, offering an
inducement to respond to the survey is suggested (Alreck & Settle, 2004; Dillman, 2000).

Inducements tend to catch the recipients’ attention and put them in a more
positive frame of mind. Respondents were offered the chance to have their name drawn
to win two round trip airline tickets anywhere in the contiguous US. or travel related
prizes provided by National Geographic. One disadvantage to using drawings or
sweepstakes is that some people will absolutely refuse to reveal their identity, especially
if the survey topics or issues are controversial or confidential in nature. Therefore, asking

them to relinquish their anonymity may decrease rather than increase response rate. There

64

is also the chance that those who love to enter drawings and those who don’t hold
systematically different views on the issues or topics of the survey. If so, the inducement
will cause non-response bias (Alreck & Settle, 2004). However, because of the non-
controversial nature of the topic of travel as well as the fact most people enjoy talking
about their travel experiences, respondents may find the opportunity to win airline tickets
of interest, making the drawing a logical choice for the audience, as well as keeping
within budget constraints. Winners were selected in January 2008 and prizes were sent by
National Geographic directly to those selected (travel related prizes were a National
Geographic Adventure magazine logo duffle bag, National Geographic Adventure book,
and National Geographic baseball hat and t-ushirt).

Prior to commencing the study, ethical clearance was obtained from University
Committee on Research Involving Human Subjects (UCRIHS) at Michigan State

University (Appendix D: Copy of UCRIHS Approval Letter).

From 1,000 surveys, 17 were undeliverable, and 339 were returned and completed

for an overall response rate of 34%. Response rates by sample and geographic region are

provided in Table 4.

65

Table 4
Response Rate of the Mail Survey

Original Returned Effective

 

1 Sample as Sample Response
Geofiggraphic Region Size Undeliverable Size Respondents Rate
' "/o
Northeast 176 3 173 60 17.7
South 287 5 282 97 28.6
Midwest 209 4 205 8 l 23 .9
West 328 5 323 101 29.8
Total 1,000 17 983 339 34.5

 

rAlaska and Hawaii residents are not included in the survey in keeping with a sample from the 48
contiguous states.

Non-respondent Survey

Once the data collection period ended, a non-response study was conducted to
assess any biases in the dataset. The survey cover letter and non-response instrument
cover used in the study are provided. The non-response survey consisted of several key
variables used in the study to determine differences in responses between the main study
participants and non-respondents. A total of 100 non-response surveys were mailed to
assess any biases in the dataset in January 2008. From the 100 non-response surveys, 5
were undeliverable and 26 were returned and complete for an overall response rate of
27%. The one-page questionnaire included several key variables used in the study:
personality traits, travel experience and intentions. Independent sample t-test was
computed to test for differences between the main study and the non-response study.

No significant differences were found between the main study and non—response
study in terms of personality traits. Participants in the non-respondent survey were also

asked why they did not complete and return the original survey. Multiple responses

66

included: survey came at the wrong time, survey was too long, or don’t participate in

research studies.

Survey Instrument

The survey instrument included demographic and travel behavior variables such
as travel experience and travel intent, and pre-, during and post travel behavior. In
addition, the survey instrument was comprised of a series of personality items based on
previous research, all of which had previously been tested for internal consistency
reliability and convergent validity. As recommended by Mowen (2000), all of the
elemental and compound traits were measured on nine-point scales to give variability in
the positive end of the scale to identify differences and to some extent to avoid restriction
of range issues. Seventeen constructs were investigated in the study: eight elemental traits
(conscientiousness, openness to experience, agreeability, neuroticism, material needs,
extroversion, need for arousal, and body needs), three compound traits (competitiveness,
altruism, and the need for learning), three situational traits (interest in cultural
experiences, the need for uniqueness, and fashion leadership), and one surface trait, ATP
(Appendix G: Survey Instrument Key).

Each of the measures of the elemental traits consisted of four-items, and they
were obtained fi'om Licata et a1. (2003). The items were assessed by asking respondents
to indicate “How often does the characteristic describe how you see yourself in everyday
life?” Respondents answered on a nine—point scale anchored by ‘1 = never’ and ‘9 ==
always.’

Compound traits are cross-situational, enduring dispositions that result from

culture, sub-culture, the learning history of the individual, as well as the effects of the

67

combinations of the elemental traits. The three compound traits proposed to predict ATP
were: (1) competitiveness, (2) altruism, and (3) the need for learning.

The four-item scale measuring the compound trait competitiveness was obtained
from Mowen (2002). The items were assessed by asking respondents to indicate “How
often does the characteristic describe how you see yourself in everyday life?”
Respondents answered on a nine-point scale anchored by ‘1 = never’ and ‘9 = always.’

The four-item scale measuring the compound trait altruism was obtained from
Mowen and Sujan (2005). The items were assessed by asking respondents to indicate
“How often does the characteristic describe how you see yourself in everyday life?”
Respondents answered on a nine-point scale anchored by ‘1 == never’ and ‘9 = always.’

The four-item scale measuring the compound trait need for learning was obtained
from Mowen (2000). The items were assessed by asking respondents to indicate “how
often does the characteristic describe how you see yourself in everyday life?”
Respondents answered on a nine-point scale anchored by ‘l = never’ and ‘9 = always.’

Situational traits act as motives for engaging in behavior. The three situational
traits proposed to predict ATP were: (1) interest in cultural experiences, (2) need for
uniqueness, and (3) fashion leadership.

The scale developed by Mowen and Carlson (2003) to measure interest in the arts
which focused on poetry and institutional art was adapted for this study resulting in a
seven-item measure of cultural travel experiences. The items were assessed by asking
respondents to indicate “How often does the characteristic describe how you) see yourself

in everyday life?” Respondents answered on a nine-point scale anchored by ‘1 = never’

and ‘9 = always.’

68

The nine-item scale measuring the need for uniqueness was obtained :from Tian,
Bearden and Hunter (2001). Because the need for uniqueness is conceptualized as having
three dimensions, indicators were created by taking the mean of the items for each
dimension of the construct. Respondents were asked to indicate their agreement or
disagreement with each of statement, based on a five-point scale where ‘1 = strongest
disagreement’ and ‘5 = strongest agreement.’

The measure of fashion leadership was taken from Goldsmith et a1. (1993) and
consisted of six-items. The items were assessed by asking respondents to indicate “How
often does the characteristic describe how you see yourself in everyday life?”
Respondents answered on a nine-point scale anchored by ‘1 == never’ and ‘9 = always.’

For the surface trait, a measure of ATP was developed. ATP is the selection of an
activity in an unusual, exotic, remote, or wilderness destination and tends to be associated
with high levels of involvement and activity by the participants, most of it outdoors (Tran
& Ralston, 2006). Tourists with a high propensity for adventure would like to visit
unusual and exotic destinations, gain new experience, interact with local culture, engage
with nature, and challenge their physical and mental skills. A 24-item scale consisting of
a list of dream travel experiences was developed (e.g., visiting all seven continents,
hiking in a rainforest). Respondents were asked to indicate whether they “had dreamed of
having the travel experience” based on a five-point scale, where ‘l = not at all’ and ‘5 =
absolutely.’ A higher score indicated a greater interest in having the experience.

Factor analysis was employed to determine the underlying factors of ATP, and the
results are provided in Chapter IV. Four adventure travel experience types were

identified: (1) ultimate destination experiences, (2) tropical adventure experiences, (3)

69

traditional outdoor adventure experiences, and (4) extreme adventure experiences.
However, the individual variables are treated as a function of the surface trait adventure
travel propensity (ATP). ATP represents an enduring disposition and not a specific act or

behavior. The study variables, scale items used for measurements, and sources of the

measurements are summarized in Table 5.

 

 

Table 5

Variables and Sources for Scale Items Used for Measurement

Variable Measurement Source
Elemental Traits

How often do these characteristics describe how Licata et a1. (2003).
you see yourself in everyday life?1

Openness to Experience . Creative-
. Imaginative
0 Find novel solutions
0 Original

How often do these characteristics describe how Licata et a1. (2003).
you see yourself in everyday life? 1

. . o Precise
Conscrentiousness . Efficient
o Organized
o Orderly
How often do these characteristics describe how Licata et al. (2003)
you see yourself in everyday life? 1
Extraversion . Bashful
0 Introverted
0 Quiet
o Shy
How often do these characteristics describe how Licata et a1. (2003).
you see yourself in everyday life? 1
. . 0 Tender hearted
Agreeability . Agreeable
o Sofihearted
o Kind
How often do these characteristics describe how Licata et a1. (2003).
you see yourself in everyday life? 1
Neuroticism . Moody
o Temperamental
0 Emotional
o Touchy

70

Table 5 Continued

Material Needs

The Need for Arousal

Physical/Body Needs

Compound Traits

Consumer Need for
Uniqueness

How often do these characteristics describe how Licata et al. (2003).
you see yourself in everyday life? I

O
0

Enjoy buying expensive products
Like to own nice products more than
most people

Acquiring valuable products is
important to me

Enjoy owning luxurious products

How often do these characteristics describe how Licata et al. (2003).
you see yourself in everyday life? 1

Drawn to experiences with an element
of danger

Seek an adrenaline rush

Actively seek out new experiences
Enjoy taking more risks than others

How often do these characteristics describe how Licata et al. (2003).
you see yourself in everyday life? 1

Focus on my body and how it feels
Devote time each day to improving my
body

Work hard to keep my body healthy
Feel making my body look good is
important

The following statements pertain to preference Tian et al. (2001).
for different or unique products.

An important goal when I buy
merchandise is to find something that
communicates my uniqueness

Often buy products to help shape a more
unusual personal image

Products that are unusual assist me in
establishing a distinctive image

When it comes to the products I buy I
have often broken customs and rules
Often violated the understood rules of
my social group regarding what to buy
Often gone against the understood rules
of my social group regarding how
certain products are properly used
Dislike products or brands that are
customarily purchased by everyone
Once they become popular among the
general public I give up wearing
fashions I’ve purchased

The more commonplace a product or
brand is among the general population,
the less interested I am in buying it

71

Table 5 Continued

Need for Learning

Altruism

Competitiveness

Situational Traits

Interest in Cultural Experience

Fashion Leadership

 

How often do these characteristics describe how
you see yourself in everyday life? I
0 Enjoy learning new things more than
most people
People consider me to be intellectual2
Enjoy working on new ideas
0 Value information as the most important
resource
How often do these characteristics describe how
you see yourself in everyday life?
0 Have an altruistic nature
0 Give to others
0 Sacrifice my goals to help others
0 Selfless in giving time to others
How often do these characteristics describe how
you see yourself in everyday life? I
0 Enjoy competition more than others
0 Feel it is important to outperform others
0 Enjoy testing my abilities against
others’
0 Feel Winning is extremely important

How often do these characteristics describe how
you see yourself in everyday life? 1
0 Enjoy cultural immersion when I travel
0 Seek hands-on cultural encounters as I
travel
0 Embrace the world celebrate its nuances
as I travel
0 Interested in the traditions of indigenous
cultural communities (e.g., festivals,

rituals) as I travel
0 Try to visit local museum or art gallery
as I travel
0 Travel should be about enriching
knowledge
The following statements are about your fashion

style. 2

o Aware of fashion trends and want to be
one of the first to try them

0 First to try new fashion people regard
me as being a fashion leader
Important for me to be a fashion leader
Confident in my ability to recognize
fashion trends

0 Clothes are one of the most important
ways I have of expressing my
individuality

0 Don’t spend a lot of time on fashion-
related activities

72

Mowen (2000).

Mowen & Sujan
(2005).

Mowen (2000).

Adapted from Scott
et al. (2003).

Goldsmith et al.
(1993)

Table 5 Continued

Surface Trait

Adventure Travel Propensity
(ATP)

Demographic Profile

Travel Behavior Variables
Travel experience profile

Thinking about the words “Dream it” read the list
of travel experiences below. Please indicate the

experiences you have dreamed of having.3

Bicycling across the USA

Staying at a hot spring spa in Japan
Visiting all the seven continents
Getting off the beaten track

Surf fishing on the beach at Cape
Hatteras

Camping in Glacier National Park
Visiting a market in India

Hiking in rural Ireland

Shopping in Paris

Making snow angels in Alaska
Visiting the Seven Wonders of the
World

Running with the bulls in Spain
Cage-diving with Great White Sharks
Rock climbing on every continent
Swimming in every ocean

Rafting in the Grand Canyon

Cliff diving in Jamaica

Hiking in a rainforest

Snorkeling the Great Barrier Reef
Visiting the pyramids in Egypt
Going on a safari in Africa

Walking down the ancient paths of
China

Exploring the ancient civilization of
Mayans

Relaxing on the white beaches of Bora-
Bora

Gender

Age

Household composition
Marital status

Ethnicity

Education

Annual income
Employment status

Passport ownership

Past destination experience

Past recreation and travel activity
experience

73

Developed for the
current study
adapting the “Dream
it. Plan it. Do it.”
motto of National
Geographic
Adventure magazine.

Adapted
demographic
questions from the
US. Census (2000).

Measures developed
for this study.
Destination and
activity lists adapted
from: CT C (2003);
J ang, Morrison &
O’Leary (2000);
01A (2006);

Table 5 Continued

 

Pearce & Caltabiano,
(1983);

Sung et al. (1997);
TIA (1998; 2006).

Travel intent profile 0 Destination intentions Developed measures
Recreation and travel activity intentions for this ‘3de to meet
Future travel intentions the needs Of
National Geographic
Adventure magazine.
Pre-, during and post travel 0 Booking sources
behavior 0 Pre-trip activities

Communication types used before,
during and after vacation travel

0 Technologies used before, during and
after vacation travel

0 Lifestyle changes following a vacation
trip Past travel experience

0 Pre and post trip travel behavior

Miscellaneous
Cognitive Age Please specify which of these age decades you Barak (1987).
4
FEEL you really belong to.
0 I FEEL as thoughI am in my
0 I LOOK as though I am in my
0 I DO most things as though I were in
my
0 My recreation and travel INTERESTS
are mostly those of a person in his/her

INine-point scale ranging from 1 = never to 9 = always;TFive-point scale ranging from 1 == strongly
disagree to 5 = strongly agree; 3Five-point scale ranging from 1 = not at all to 5 = absolutely whether

. . 4 . . .
respondent has dreamed of havrng the travel experience; Nme-pomt scale; preteens, teens, twenties,
thirties, forties, fifties, sixties, seventies, or eighties.

Reliability Test

Reliability is a fundamental issue in psychological measurement (Nunnally &
Bernstein, 1994). Scale reliability is the proportion of variance attributable to the true
score of the latent variable. Measurement theory suggests that the relationships among
items are logically connected to the relationships of items to the latent variable. If the
items of a scale have a strong relationship to their latent variable, they will have a strong

relationship to each other. A scale is internally consistent to the extent that its items are

74

highly intercorrelated. High inter-item correlations thus suggests that the items are all
measuring (i.e., are manifestations of) the same phenomenon. Thus, a unidimensional
scale or a single dimension of a multidimensional scale should consist of a set of items
that correlate well with each other (DeVellis, 2003).

Cronbach’s internal consistency reliability (expressed as a correlation coefficient
ranging from 0 to I), has been the most widely used reliability method in tourism studies
for developing scales for measurement of personality traits. A score of 0.7 or higher is an
acceptable reliability coefficient (Nunnally & Bernstein, 1994). Thus, for the current
study reliability was computed using Cronbach Alpha Coefficient (Nunnally & Bernstein,
1994) and corrected item-to-total correlation where the recommended correlation is 0.30
and above (Parasuranam et al., 1988).

Overall, the composite scales exceeded the Cronbach Alpha Coefficient
requirement of 0.70 (Cronbach, 1951). With the exception of the four-item “need for
learning scale” and the four-item dream travel experience factor “traditional outdoor
adventure experiences” which both had a Cronbach Alpha Coefficient of 0.66. Consistent
with Mowen (2000), the need for learning measure was modified, deleting the item
“people perceive me to be intellectual”, resulting in an increase of the Cronbach Alpha
Coefficient to 0.72. Table 6 provides a summary of the Cronbach Alpha Coefficients for

composite scales used in this study.

75

Table 6

Cronbach Alpha Cogflicientsfor Composite Scales Used in this Study

Variable
Elemental Traits

Openness to Experience

Conscientiousness

. l
Extraversron

Agreeability

Neuroticism

Material Needs

Need for Arousal

Physical/Body Needs

Compound Traits
Competitiveness

Altruism

Need for Learning2

Measurement Items

Creative
Imaginative
Find novel solutions
Original
Precise
Efficient
Organized
Orderly
Bashful
Introverted
Quiet

Shy

Tender hearted
Agreeable
Sofihearted
Kind

Moody
Temperamental
Emotional
Touchy

Enjoy buying expensive products.

Like to own nice products more than most people.

Acquiring valuable products is important to me.
Enjoy owning luxurious products.

Drawn to experiences with an element of danger.
Seek an adrenaline rush.

Actively seek out new experiences.

Enjoy taking more risks than others.

Focus on my body and how it feels.

Devote time each day to improving my body.
Work hard to keep my body healthy.

Feel making my body look good is important.

Enjoy competition more than others.

F eel it is important to outperform others.
Enjoy testing my abilities against others'.
Feel winning is extremely important.
Have an altruistic nature.

Give to others.

Sacrifice my goals to help others.
Selfless in giving time to others.

Enjoy learning new things more than most people.

People consider me to be intellectual.
Enjoy working on new ideas.

Value information as the most important resource.

76

Cronbach
Alpha
Coefficient

0.90

0.87

0.88

0.83

0.81

0.90

0.90

0.88

0.94

0.84

0.72

Table 6 Continued
Situational Traits
Interest in Cultural Experience

Need for Uniqueness

Fashion Leadership

Surface Trait
Ultimate Destination
Experiences (ATP)

Tropical Adventure
Experiences (ATP)

Extreme Adventure
Experiences (ATP)

Enjoy cultural immersion when I travel.

Seek hands-on cultural encounters as I travel.
Embrace the world celebrate its nuances as I travel.
Interested in the traditions of indigenous cultural
communities (e.g., festivals, rituals) as I travel.

Try to visit local museum or art gallery as I travel.
Travel should be about enriching knowledge.

An important goal when I buy merchandise is to find
something that communicates my uniqueness.

Often buy products to help shape a more unusual
personal image.

Products that are unusual assist me in establishing a
distinctive image.

When it comes to the products I buy I have often
broken customs and rules.

Often violated the understood rules of my social
group regarding what to buy.

Often gone against the understood rules of my social
group regarding how certain products are properly
used.

Dislike products or brands that are customarily
purchased by everyone.

Once they become popular among the general public
I give up wearing fashions I’ve purchased.

The more commonplace a product or brand is among
the general population, the less interested I am in
buying it.

Aware of fashion trends and want to be one of the
first to try them.

First to try new fashion; therefore, many people
regard me as being a fashion leader.

Important for me to be a fashion leader.

Confident in my ability to recognize fashion trends.
Clothes are one of the most important ways I have of
expressing my individuality.

Don’t spend a lot of time on fashion-related activities.

Visiting all the seven continents.

Visiting the Seven Wonders of the World.
Visiting the pyramids of Egypt.

Going on safari in Africa.

Walking down the ancient paths of China.
Visiting a market in India.

Staying at a hot spring spa in Japan.
Snorkeling the Great Barrier Reef.

Hiking in a rainforest.

Relaxing on the white beaches of Bora Bora.
Exploring the ancient civilizations of Mayans.
Cliff diving in Jamaica.

Cage diving with Great White Sharks.
Running with the Bulls in Spain.

Rock climbing on every continent.

77

0.89

0.77

0.89

0.86

0.77

0.76

Table 6 Continued

 

Traditional Outdoor Adventure Camping in Glacier National Park.

Experiences (ATP) Rafting in the Grand Canyon. 0 66
Making snow angels in Alaska. '
Getting off the beaten track.

Miscellaneous

Cognitive Age I FEEL as though I am in my.
I LOOK as though I am in my.
I DO most things as though I were in my. 0.94

My recreation and travel INTERESTS are mostly
those of a person in his/her.

IOperationalized as introversion; 2Four-item need for learning scale resulted in a Cronbach Alpha
Coefficient of 0.66. Removal of the item “people perceive me to be intellectual” resulted in a Cronbach
Alpha Coefficient of 0.72.

Data Analysis

Several statistical methods were used in data analyses (Table 7). First, descriptive
statistics were used to analyze demographic variables (i.e., gender age, marital status,
household composition, ethnicity, education, income and employment status), travel
experience (i.e., passport ownership, past destination and recreation and travel activity
experience); travel intent (i.e., destination and recreation and travel activity intentions),
and pre-, during and post travel behavior (i.e., booking sources, pre-trip activities,
communication types used, technologies used before, during and after vacation travel,
and lifestyle changes following a vacation trip). Next, the Guttman Scaling Procedure
was employed to categorize respondents in soft/hard categories as a context for
understating the demographic and travel behavior characteristics of the study sample.
Third, factor analysis was used to identify the underlying dimensions of ATP, an
enduring disposition to behave. A series of appropriate tests were performed to examine
necessary assumptions before applying main statistical techniques. Lastly, building on the

model developed by Mowen (2000), a series of hierarchical regressions were performed

78

to explore the relationships among variables. Data were analyzed using the Statistical

Package for Social Sciences (SPSS 16.0).

 

 

Table 7

Analysis Procedures

Statistical Methods Objectives

Descriptive Analysis Explore the overall profile of the samples and identify which motive

Cross-tabulation/Chi-square

Independent Sample t-Test

Guttman Scaling Procedure

Factor Analysis

Hierarchical Regression

items were regarded as most important or unimportant.
Investigate the profiles of the identified travel experience groups.

Examine the difference in the identified motivational patterns
between travel experience groups.

Categorize respondents in soft/hard categories as a context for
understating the demographic and travel behavior characteristics of
the study sample.

Identify the underlying dimensions of ATP, an enduring disposition to
behave.

Explore the relationships amorivariables.

Descriptive statistics. To explore the overall profile of the samples and identify

which motive items were regarded as most important or unimportant descriptive statistics

were used.

Cross-tabulation/Chi-square. Cross tabulation/Chi-square was used to assess the

relationship between two categorical variables. Cross tabulation with Chi-square test

statistics was used to identify significant differences between the two traveler groups

(soft/hard adventure) for demographic and travel related behavior variables 'of categorical

measurement.

79

Causality is not assumed in cross-tabulations; the only statistical requirement is
that the minimum expected cell frequency for the table must be five or more. From a
practical point of View, the only limitation on the use of cross-tabulation is that there
should be a relatively large sample size. Cross-tabulation is a way to show how much the
fiequency or percentage distributions of one variable differ according to various levels of
another variable (Alreck & Settle, 2004). The Chi-square statistic computed from the
cross-tabulation table indicates the statistical significance of the relationship between the
two variables. The Chi-square statistic and the significance probability associated with it
are based on the amount of difference between the expected values for each cell and the

actual count.

Independent sample t-test. The independent sample t-test procedure compares
means for two groups (SPSS, 2002). This statistical method can test two means with
homogenous and heterogeneous variances. The independent sample t—test was used to
identify significant differences between the two traveler groups (soft/hard adventure).
Tabachnick and F idell (1989) described four main assumptions for the independent

sample t-test:

(l) The data must be parametric, that is, they should be measured on an interval
or ratio scale.

(2) The samples should be randomly selected from the population, so that the
results of the t test can be generalized from the sample to the population.

(3) The two samples should come from populations which have approximately
the same variance (i.e., homogeneity of variance assumption). Levene’s test of

homogeneity of variances should be used to test this assumption.

80

(4) The scores of the dependent variable should come from the population which

is normally distributed (i.e., normality assumption).

Guttman Scaling: Distinguishing Soft and Hard Adventure Travelers

Mowen's theory advocates a hierarchical structure to personality traits. The
traveler type hierarchy from mass travelers to hard adventure complements the
personality hierarchy proposed by Mowen (2000). Guttman scaling was used to create
the hierarchical structure for traveler type to parallel Mowen's hierarchy. To initialize the
effort, tourism travel behavior experts were engaged to complete an exercise to identify
places and activities and determine how they aligned with a hierarchy for mass, soft, and
hard travel. The soft/hard adventure typology has been shown to be useful to both
academics and practitioners alike. Thus, an effort was made to group the study
respondents into soft/hard adventure traveler groups using a novel application of the
approach known as Guttman scaling. A description of the procedure follows.

The main purpose of Guttman scaling, also known as cumulative scaling or
scalograrn analysis, is to establish a one-dimensional continuum for a concept (Trochim,
2005). The concept of interest in the present study is adventure travel. The Guttman
scaling procedure was used to categorize respondents according to their past vacation
travel experience using activities and destinations. Three categories of tourist types were
identified: (1) mass tourist, (2) soft adventure tourist, or (3) hard adventure tourist.

Used in psychological and sociological research, a Guttman scale is a
measurement instrument deve10ped using the scaling technique designed by Louis

Guttman in 1944. Guttman scaling is a procedure used to assess unidimensionality

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(Guttman, 1950), which is also seen as an important part of construct validity (Ekinci &
Riley, 1999; Hattie, 1985). The model works best for constructs that are hierarchical and
highly structured such as social distance, organizational hierarchies, and evolutionary
stages (Maslow, 1954). Previous recreation and tourism literature suggests that recreation
and travel behavior follows a hierarchy (Pearce & Lee, 2005; Walle, 1997), thus Guttman
scaling may be useful in establishing a one-dimensional continuum for the concept of
interest in this dissertation, adventure travel.

Guttman’s insight was that for unidimensional scales, those who agree with a
more extreme test item will also agree with all less extreme items that preceded it
(Guttman, 1950). Put more formally, one would like to be able to predict item responses
perfectly knowing only the total score for the respondent. The object is to find a set of
items that perfectly matches this pattern. In practice, we would seldom expect to find this
cumulative pattern perfectly. Scalograrn analysis is used to examine how closely a set of
items corresponds with this idea of cumulativeness. The procedure orders both items and
subjects with respect to the underlying cumulative dimension (Mclver & Carmines,
1981). Researchers have applied the Guttman scale infrequently in scaling, perhaps in
part because of the rather tough requirements for such a scale to be valid. Most important,
the scale items must clearly be ordered in a way that they are, ordinally speaking,

progressively more difficult to meet. However, given the proposed nature of travel
progressing from mass tourism to hard adventure tourism, this may indeed prove a

meaningful application of the Guttman scale.

82

Trochim (2005) provided a succinct list of the steps required in constructing a
Guttman scale: define the focus, develop the items, rate the items, develop the cumulative
scale, and administer the scale.

The first step is to define the focus of the scale. That is, the topic or issue that the
scale will be developed to examine. In this dissertation the focus is adventure travel. As
discussed in Chapter II, it is posited that individual travel behavior may evolve over time
from participating initially in mass recreation and travel activities to a higher level,
participating in soft adventure recreation and travel activities, which may then be
followed by progressing to an even higher level at the top of the hierarchy, participating

in hard adventure recreation and travel activities.

Mass travel is defined as packaging and selling standardized leisure services at
fixed prices to a mass clientele (Poon, 1993). The sofi/hard typology was developed to
explain the diversity of behavior inherent in the adventure travel market. The typology is
based on a continuum reflecting differing degrees of challenge, uncertainly, setting,
familiarity, personal abilities, intensity, duration and perceptions of control (Lipscombe,
1995). At one end of the continuum is soft adventure, which is defined as activities with a
perceived risk but with actual low levels of real risk, requiring minimal commitment and
beginning skills. The continuum progresses toward hard adventure, which is defined as
activities with high levels of risk, requiring intense commitment and advanced skills

(Hill, 1995). In sum, the focus of the present dissertation is to develop a scale capable of

differentiating between the three traveler types: mass, soft adventure, and hard adventure

travelers.

83

The second step in Guttman Scaling is to develop a list of the items (e. g., objects,
attitudinal statements, behaviors) that will comprise the scale. In the present study, two
lists of items were developed to differentiate among the three types of travel behavior.
The first list consisted of tourism destinations, specifically continents/regions that a
person might visit, while the second consisted of recreation and tourism activities that a

person might engage in while traveling.

Based on a review of the recreation, tourism, and adventure literature an initial list
of continents/regions and recreation and travel activities was developed (CTC, 2003;
Jang, Morrison, & O’Leary, 2000; OIA, 2006; Pearce & Caltabiano, 1983; Sung,
Morrison, & O’Leary, 1997; TIA, 1998; 2006). In addition, a panel interview of outdoor
recreation and adventure industry leaders was consulted to identify potential items and to
ensure that current industry trends and changes were represented.

The next step in constructing a Guttman scale is to have a panel of judges rate
each item in terms of how well it represents the topic addressed in the study. In this
study, ten tourism professors were identified and invited to participate in rating the items
(Appendix H: Expert Review Email Request). Seven expert judges agreed to participate
in rating the continents/regions and the recreation and travel activities in terms of how
well the items reflected the concepts of mass, soft and hard adventure travel (Appendix 1:

Expert Judge Survey).
To understand the context in which experts categorized the items they were also
asked to define, in their own words, mass tourism, soft adventure tourism, and hard
adventure tourism. No two definitions were exactly the same; however, similar themes

emerged for each of the three concepts. The definitions provided indicated that experts

84

viewed mass tourism as appealing to the larger population with a focus on familiar
destinations and activities. In contrast, soft and hard adventure tourism were seen as
appealing to smaller groups with a focus on physical activities involving less familiar
(exotic, novel, extreme) destinations and more challenging forms of activity (Appendix J:
Expert Judge Definitions).

Expert judges indicated the type of travel (mass, soft, or hard) they felt best
represented the image of the destination and the image of the recreation and travel
activity. Items were categorized according to travel type based on the highest percentage
level of agreement among judges. Only items with greater than fifty-percent agreement
were included in the final list. Based on this approach, a total of six continents/regions
were categorized as mass tourism destinations, six continents/regions were categorized as

soft adventure tourism destinations, and five continents/regions were hard adventure

tourism destinations (Table 8).

85

Table 8
Results of Expert Judge Destination Categories

Destination %

Mass tourism

Western Europe 10001
North America 85.7
Central Europe 71.4
Caribbean 57.1
Eastern Europe 57.1
Mexico 57.1
Soft adventure tourism
Australia 71.4
South Pacific 71.4
Middle East 57.1
New Zealand 57.1
North Asia 57.1
South—Southeast Asia 57.1
Hard adventure tourism
Antarctica 100.0
Arctic 85.7
Africa 71.4
Central America 57.1
South America 5 7.1

 

1 . . . .
Percent agreeing that the item represented the destination type.

The same approach employed to categorize continents/regions was used to
categorize the recreation and travel activities. A total of 20 recreation and travel activity
items were categorized as mass tourism recreation and travel activities, 13 items as soft
adventure tourism recreation and travel activities, and 4 items as hard adventure tourism

recreation and travel activities as shown in (Table 9).

86

Table 9

Results of Expert Judge Recreation and Travel Activity Categories

 

 

 

 

 

Activity %
m

Mass tourism
Attending concert/play/dance 100.0l
Attending local festivals/fairs 100.0
Attending spectator sporting events 100.0
City tours/short guided excursions 100.0
Dining 100.0
Golfing/tennis 100.0
Night life/visiting night clubs/dancing 100.0
Shopping 100.0
SWimming/sunbathing/beach activities 100.0
Visiting casinos/gambling/gaming 100.0
Visiting fiiends or relatives 100.0
Visiting gardens/botanical gardens 100.0
Visiting museums/galleries 100.0
Visiting places of historical interest 100.0
Visiting spas 100.0
Visiting theme/amusement parks 100.0
Visiting zoos 100.0
Scenic driving 85 .7
Visiting local/state/national parks 71.4
Getting to know local people 57.1

Soft adventure tourism
Skiing/snowmobiling 100.0
Backpacking 85.7
Hiking 85.7
Hunting/fishing 85 .7
Mountain biking 85.7
Observing wildlife/birdwatching 85 .7
Scuba diving/surfing 35 -7
Volunteering on vacation 85-7
Waterskiing/snorkeling 85-7
Kayaking/canoeing 71 -4
Bicycle riding 57-1
Boating 5 7.]
Camping 57. 1

Hard adventure tourism
Climbing mountain/rock/ice 100-0
Cave exploring/spelunking 71-4
Trekkin 57-1

 

Percent agreeing that the item represented that travel type.

87

The next step in Guttman scaling is to develop the cumulative scale. This step,
which represents the essence of Guttman scaling, involves ordering the items to create a
cumulative scale. In the present study, the lowest level of the scale should refer to mass
tourism, the next highest level soft adventure tourism, and the third to the hard adventure
tourism. Thus, for the continent/region items, respondents at the lowest level should have
experience visiting only continents/regions associated with mass tourism. Respondents at
the next level should have experience visiting continents/regions associated with mass
tourism, plus those associated with soft adventure tourism. Finally, respondents at the
highest level should have experience visiting continents/regions in all three categories. A
similar cumulative pattern should be observed for the activity items. If a response pattern
does not match with this profile, then errors are present.

A score was computed for positive responses to past experience with

continent/regions (Table 10) and recreation and travel activities (Table 11) in each

tourism type, with mass positioned at the bottom of the scale, soft adventure at the second
level and hard adventure at the top. Items were re-coded into a new variable to test the

scalability. Each respondent was assigned a scale score ranging from ‘1’ to ‘3’ based on a

positive response in each tourism type category.

88

 

Table 10

 

 

Results of Cumulative Scale for Destination Categories (n = 339)
# Positive Proportion Cumulative
Scale Pattern Responses Frequency of Total Prgiortion
“Perfect” Scale Patterns:
loo1 1 123 .363 .363
110 2 62 .183 .546
Ill 3 97 .286 .832
Error Patterns:
010 l 1 .003 .003
101 2 55 .162 .165
000 0 1 .003 .168

 

rFor each pattern, the first digit refers to Mass Travel, the second to Soft Adventure Travel, and the third to
Hard Adventure Travel; “1” representing passing on that item and “0” representing not passing. Thus, the
pattern of 100 refers to those that passed on the Mass Travel items but did not pass on the Soft or Hard

Adventure items.
Total errors = 57
CR = l (57)/339

 

 

CRgc = .832
Table 11
Results of Cumulative Scalefor Activity Categories (n = 337)
# Positive Proportion Cumulative
Scale Pattern Responses Frequency of Total Proportion
“Perfect” Scale Patterns:
1001 1 13 .039 .039
110 2 117 .347 .386
111 3 203 .602 .988
Error Patterns:
010 l 2 .006 .006
011 2 1 .003 .009
101 2 l .003 .012

 

1For each pattern, the first digit refers to Mass Travel, the second to Soft Adventure Travel, and the third to
Hard Adventure Travel; “1 ” representing passing on that item and “0” representing not passing. Thus, the
pattern of 100 refers to those that passed on the Mass Travel items but did not pass on the Soft or Hard

Adventure items.
Total errors = 4 errors
CR = 1.0 — (4)/337
CRge = .989

89

 

The Guttman scaling procedure requires an ordinal (hierarchical) and cumulative
structure in a scale, with the tmidimensionality of the scale determined by checking the
response patterns in the data. Perfect scales rarely occur, thus using the perfect scale
matrix, the cumulative property of the scales is checked and errors are counted. Guttman
suggested that the coefficient of reproducibility (CR) should be used to assess the number
of errors and the degree of scalability in such cases. Also, the CR score must be .90 or
higher to claim that the dimension is scaleable (or that the scale is unidimensional). The
.90 criteria indicates that the scale contains a maximum of 10% error. The formula for
measuring CF is the following (McIver & Carmines, 1981): CR = 1 - Total Error/Total
Responses and CR = l —- Total Error/(Items x Respondents).

The current study employed the Goodenough-Edwards technique (Edwards,
1957) to compute the CR, and will be referred to as CRge, In this technique, error is
assigned to every observed response that does not correspond to the ideal scale pattern
predicted by the total score with CR3... The result using the Goodenough-Edwards
concept of error, means that the CR reflects the degree to which observed response
patterns deviate from ideal response patterns. Retaining Guttman’s original specification
that a scale is interpretable if it reflects 10% or less error, the scalability criterion now
becomes CR8, > = .90.

Results of the scalograrn analysis for the recreation and travel activities met the
scalability criterion (CRge = .989) and thus convergent categorization was achieved with
these experts. However, results for continents/regions did not meet the scalability

criterion (CR8e = .832) and therefore continents/regions were not used in determining

90

traveler type. The reason may be that destination is a subjective concept and thus
categorizing a destination according to level of “adventure” is less applicable.

The final step is to administer the scale. Each scale item has a scale value
associated with it (obtained from the scalogram analysis). In the current study each

respondent was assigned a scale score ranging from ‘1’ to ‘3’ based their positive

response pattern to recreation and travel activities. Error patterns were categorized into
the highest level of activity experienced. For instance, if a respondent indicated not
having experienced a mass activity, however they indicated a hard activity the respondent
was categorized as a hard adventure traveler. The current study did not examine "non-

travelers," therefore respondents who indicated no activity experience were not included

in the analyses.

Exploratory Factor Analysis
According to Hair, Anderson, Tatham, and Black (1998) “factor analysis is a

generic name given to a class of multivariate statistical methods whose primary purpose
is to define the underlying structure in a data matrix” (p. 90). Exploratory factor analysis
is an essential part of psychometric testing and validation. This analysis explores whether
questionnaire items can be clustered clearly and meaningfully into small groups or

factors. Tabachnick and F idell (1989) described five assumptions that should be

considered prior to conducting factor analysis:

( 1) The sample size is large enough to provide trustworthy results. Tabachnick

and F idell (1989) proposed as a rule of thumb to have at least fiVe participants

per item.

(2) The data should be either interval or ratio.

91

 

(3) All items and all linear combinations of items should be normally distributed.

(4) Item correlations should be of a relatively large size. If the correlations are
very small (i.e., below .30), then it is questionable whether the items are
similar enough to be grouped together under some common factors. Bartlett’s

test of sphericity was used to examine whether the correlations were

sufficiently large to warrant a factor analysis.

(5) Relationships between pairs of items should be linear.

The objective of rotation methods is to simplify the rows and columns of the
factor matrix — simplifying the rows maximizes a variable’s loading on a single factor
and simplifying the columns reduces the number of “high” loadings —- to facilitate
interpretation (Hair et al., 1998). The VARIMAX rotation method gives a clearer

separation of the factors. Factor analysis was used to discover the underlying dimensions

of ATP. Results of the factor analysis are discussed in Chapter IV.

Hierarchical Regression

Hierarchical multiple regression is a variant of the basic multiple regression
procedure where the researcher decides not only how many predictors to enter but also
the order in which they enter. The order of the entry is based on logical or theoretical
considerations (Garson, 2008). As described by Cohen and Cohen (1975), hierarchical
regression is appropriate when the independent variables can be ordered with regard to
their causal priority. In addition, they noted that the procedure allows a unique
partitioning of the total variance accounted for in the dependent variable when correlated
independent variables are present. Pedhazur (1982) provided an even more stringent

guideline by stating that a strong theoretical foundation must be present. T abachnick and

92

F idell (1989) described the assumptions that should be considered prior to conducting a

hierarchical multiple regression analysis:

(1) Sample size. The ratio of participants to independent variables should be at
least 5:1 and ideally 20:1.

(2) The data should be parametric, measured on interval or ratio scale.

(3) Independence. There should be no relationship between the score of the
dependent variable in the different groups.

(4) Homogeneity of variances. The groups should come from populations which

have equal or nearly equal variances in the scores of the dependent variables.
The Levene test is used to check this assumption.

(5) Multicollinearity. The independent variables should not be very highly
correlated (r > .90) or perfectly correlated (i.e., r = 1). The first condition is
called multicollinearity; the second condition is called singularity. Both
conditions indicate that the independent variables contain almost identical
information and, therefore, some of them should be deleted.

(6) Normality. The scores of the dependent variables in each group should come
from populations which are normally distributed. Linearity suggests that
residuals have a straight line relationship with predicted variables scores.
Homoscedasticity assumes that the variance of the residuals about predicted
dependent variables scores are the same for all predictors. Outliers, linearity

and homoscedasticity assumptions can be checked through examination of

residuals scatterplots (Pallant, 2008).

93

(7) Outliers. All univariate and multivariate outliers should be deleted or

transformed. Outliers can be identified fi'om the standardized residual plot
(Tabachnick & Fidell, 1989) ’
With each model tested in this study, the following statistics were reported:
Standardized beta coefficients, which through significance tests determine

whether a specific predictor variable is significantly contributing to the

prediction.
The F-distribution, which through significance tests indicates that a

combination of specific independent variables predicts the dependent
variable.
R Square (R2) which indicates what proportion of the variance in the

dependent variable can be explained by a combination of specific

independent variables.

In the present research, the 3M Model provides the theoretical justification for the

hierarchical ordering of variables. To test the eight proposed research hypotheses,

hierarchical regression was employed.

Statistical Procedures of Data Analysis
This chapter provided the methodology of this study. To investigate relationships

of the constructs in the model of this study, eight hypotheses were proposed in

association with the research questions presented in Chapter I.

The research method design, including sampling frame, sample selection, data
collection, and the deve10pment of the final survey, was discussed and appropriate

statistical analyses were presented. The discussion of survey results, data analyses, and

94

hypothesis testing are presented in Chapter IV. The overall statistical analysis included:

( 1) demographic profile of the sample; (2) travel experience profile; (3) travel intentions
profile (4) pre- and post-travel behavior profile; (5) descriptive statistics of the four
personality trait levels (elemental, compound, situational, and surface); (6) factor analysis

to determine underlying factors of the surface trait ATP; and (7) hierarchical regressions

to test the hypotheses.

95

CHAPTER IV
RESULTS

The problem of this study was to examine the underlying psychological traits that
contribute to the surface trait adventure travel propensity (ATP), by identifying the
motivation and personality schemas of adventure travelers. The research also tested the
usefulness of the 3M Model as an organizing structure for understanding how personality
traits impact behavior. A number of hypotheses were stated regarding personality traits
that influence ATP. In this chapter, the following topics will be reported: ( l)
demographic profile of the sample (gender age, marital status, household composition,
children living in household, ethnicity, education, income and employment status); (2)
travel experience profile (passport ownership, number of domestic/intemational trips);
number of destinations visited; destinations experienced (grouped according to mass, soft
adventure, and hard adventure destinations); number of activities experienced; travel
activity experience (grouped according to mass, soft adventure, and hard adventure
activities); (3) travel intentions profile (number of domestic/intemational vacations
respondents intend to take; number of continents/regions respondents plan to visit);
destination intentions (grouped according to mass, soft adventure, and hard adventure
destinations); travel activity intentions (grouped according to mass, soft adventure, and
hard adventure activities); number of activities plan to experience (grouped according to
mass, soft adventure, and hard adventure activities); destination experience and intentions
combined (grouped according to mass, soft adventure, and hard adventure destinations);
activity experience and intentions combined (grouped according to mass, soft adventure,

and hard adventure activities); (4) pre— and post-travel behavior profile (trip

96

planning; sources used to book or reserve trips; helpfulness of sources; pre-trip activities,
communication types used, technologies used before, during and after vacation travel,
helpfulness of technology, and lifestyle changes following a vacation trip); (5)
descriptive statistics of the four personality trait levels (elemental, compound, situational,

and surface); (6) factor analysis to determine underlying factors of the surface trait ATP;

and (7) hierarchical regressions to test the hypotheses.

Demographic Profile

Respondents’ demographic characteristics including gender, age, marital status,
household composition (number of adults and children under 18 living in the household),
education, income, employment status and geographic location, were gathered to
understand the descriptive profile of respondents. The profile of the study respondents is
shown for all respondents as well as for the two subgroups “Soft Adventure Traveler”
(SAT) and “Hard Adventure Traveler” (HAT). As described in Chapter HI, SAT and
HAT subgroups were formed using Guttman scaling procedures. As previously
discussed, according to the soft-hard continuum, individual traveler behavior may evolve
over time fiom traveling to mass destinations and taking part in mass recreation and
travel activities, then progressing to the next higher level, soft adventure destinations and
recreation and travel activities. Participation in soft adventure destinations and recreation
and travel activities may then progress to the level at the top of the hierarchy,

participating in hard adventure recreation and travel activities and travel to hard

adventure destinations (Millington et al., 2001). Therefore the SAT and HAT subgroups
discussed have evolved from mass travelers to soft adventure travelers, and in some cases

to hard adventure travelers. Characteristics of the entire sample, as well as characteristics

97

for each of the subgroups, referred to as SAT and HAT, are discussed in the following

section.
As shown in Table 12, the majority of respondents were male (58%) for the entire

sample as well as within the traveler type subgroups. However, in the HAT group males’
outnumbered females by twenty—five percent. Overall respondents were between the ages
of 55 and 64 (28%), followed closely by the 45-54 age group (26%). Respondents in the
SAT group were older, with most in the 55-64 (32%) or the 65 years and older group
(26%). In contrast, most of the HAT group were in either the 45-54 age group (30%)

followed by the 55-64 age group (26%). Consequently, the mean age of for the HATS

was six years younger than the SAT group.
The majority of respondents were married (65%) (66% for the SATS and 65% for

the HATS) and roughly eight out of ten respondents in both groups reported living in
households consisting of no more than two people (84% SATS and 79% HATS), with a
similar number indicating that they currently had no children under 18 years of age living

at home (83% SATS and 72% HATS). Almost all respondents, roughly nine out of ten,

reported their ethnicity as white (95% SATS and 93% HATS).

98

Table 12

 

 

Demographic Profile of Respondents
Hard Soft
Adventure Adventure All
Characteristics Traveler Traveler Travelers x Sig.
(n = 205) (n == 118) (N = 323)
Gender % % %
Male 62.4 50.8 58.2 4_ 14‘ .042
Female 37.6 49.2 41.8
(n = 202) (n =119) (N = 321)
Age % % %
18-34 16.3 10.1 14.0 22.252 .000
35-44 18.8 11.8 16.2
45-54 29.7 20.2 26.2
55-64 26.2 31.9 28.3
65 and up 8.9 26.1 15.3
. (n = 205) (n = 119) (N = 324)
Mantal Status % % %
Single 18.5 15.1 17.3 3,602 .463
Married 64.9 66.4 65.4
Widowed 2.4 5.9 3.7
Divorced 7.8 8.4 8.0
Living w/significant other 6.3 4.2 5.6
(n = 205) (n = 118) (N = 323)
Household Composition % % %
1 adult living in household 21.0 16.9 19.5 2.633 .453
2 adults 58.5 66.9 61.6
3 adults 16.6 11.9 14.9
4 or more adults 3.9 4.2 4.0
Children Under 18 Living in Household (n 1,205) (’1 :01 19) (N 2324)
No children living in household 71.7 83.2 75.9 5.593 .002
1 child 15.6 8.4 13.0
2 children 9.3 5.9 8.0
3 or more children 3.4 2.5 3.1
. (n = 203) (n =118) (N== 321)
Ethnicity % % %
White 95.1 93.2 94.4 6054 .301
Black/Afiican American 0.5 0.0 0.3
Asian 1.5 0.8 1.2
Hispanic 2.0 5.1 3.1
Native Hawaiian/Other Pacific Islander 0.0 0.8 0.3
American Indian/Alaska Native 1.0 0.0 0.6

 

Ialf= l; de= 4;Ttlf= 3; 2‘alf= 5.

99

A summary of respondents’ education, income, and employment status are
provided in Table 13. The majority of respondents hold an advanced degree (3 7%) or
four- year college degree (35%). More than three-quarters (78%) of the HAT group have
an advanced degree or four year college degree. For the SAT traveler type group more
than half (61%) have an advanced degree from a four-year college or an advanced degree
such as MBA, MS or PhD. With regard to household income (i.e., 2005 gross household
income), most respondents reported earning between $100,000 and $149,999. In the case
of traveler type groups, five out of ten in each group reported earning $100,000 or more
(46% SAT and 56% HAT); however, the proportion reporting the lowest income level of
under $35,000 was higher in the SAT group (12%) compared to the HAT group (4%),
while the proportion earning the highest income level of $250,000 or more was higher in
the HAT group (12%) compared to the SAT group (6%). In terms of employment status,
while most reported working full-time, the proportion of full-time workers was slightly
lower in the SAT group (56%) compared to the HAT group (67%) and proportion of

retirees was higher in the SAT group (29%) when compared to the HAT group (13%).

100

Table 13

Education, Income, and Employment Profile of Respondents

 

 

Hard Soft
Adventure Adventure All 2
Characteristics Traveler Traveler Travelers x Sig._
(n = 205) (n == 119) (N = 324)
Education % % % I
Some high school or hlgh 2.9 12.6 6. 5 17.17 .002
school degree
Some college 11.2 15.1 12.7
Assoc1ate degree, 2 year 7. 8 10.9 90
college
College degree, 4 year college 40.5 26.1 35.2
Advanced degree 37.6 35.3 36.7
(n =186) (n = 105) (N = 291)
Household Income - 2005 Gross % % %
Under $35,000 4.3 12.4 7.2 10,442 .107
$35,000-$49,999 6.5 9.5 7.6
$50,000-$74,999 17.2 14.3 16.2
$75,000-$99,999 16.1 18.1 16.8
$100,000-$149,999 28.5 28.6 28.5
$150,000-$ 199,999 12.9 7.6 1 1.0
$200,000 or more 14.5 9.5 12.7
(n = 203) (n = 119) (N = 322)
Employment Status % % %
Working full—time 67.0 55.5 62.7 13,793 .017
Working part-time 10.3 8.4 9.6
Going to school 3.4 2.5 3.1
Homemaker 3 .0 3 .4 3.1
Retired 13.3 29.4 19.3
Other 3.0 0.8 2.2

 

1df= 4; de== 6; 3df= 5.

Figure 3 shows the US. geographic location of respondents. The four regions

replicate those used by the US. Census (2000). Almost one—third of all respondents were

from the West region (30%), while only 18% were from the Northeast region. Similarly,

the greatest proportion of respondents for both the SAT and HAT groups were from the

West region (SATS 31% and HATS 30%) and the lowest were from the Northeast region

(SATS 14% and HATS 20%). A decade later, results are similar to those reported by TIA

in the Adventure Travel Report (1998) where adventure travel was more popular among

people who lived in the West region. Accessibility, exposure, and diverse natural

resources may play a role in greater adventure activity participation by respondents

residing in the West region.

Figure 3

Response Rate According to Geographic Location and Traveler T ypel

 

WEST

ALL RESPONDENTS
Sofl Adventure Travelers
Hard Adventure Travelers

NORTHEAST

ALL RESPONDENTS
Soil Adventure Travelers
Hard Adventure Travelers

 

 

3 1%
29%
30%

14%
20%
l 8%

 

NORTHEAST

 

 

MIDWEST

ALL RESPONDENTS 25%
Soft Adventure Travelers 24%
Hard Adventure Travelers 24%
SOUTH

ALL RESPONDENTS 29%
Soft Adventure Travelers 27%
Hard Adventure Travelers 28%

1Percentage values may not sum to 100% owing to rounding.

102

Travel Experience Profile

To develop an understanding of adventure travelers, previous vacation travel
experience was examined. Information regarding passport ownership and the
destinations and activities respondents have experienced in the past are provided. The
following key vacation travel experience variables were explored: passport ownership;
average number of domestic and international trips taken in the past three years; average
number of destinations (continents/regions) visited in the past three years; destinations
(continents/regions) experienced during lifetime (grouped according to mass destinations,
and soft and hard adventure destinations); average number of activities experienced

during lifetime ; and activities experienced during a lifetime (grouped according to mass

activities, and soft and hard adventure activities).

Passport ownership. The majority of respondents, about eight out of ten,
currently hold a valid US. Passport. Three-quarters of SATS, and slightly more HATS
(83%), hold a valid US. Passport. There were no significant differences between the
traveler type groups and valid US. Passport ownership.

The average age respondents applied for their first passport was 28 years of age
(M = 28.2, SD = 13.41). The average for HATS was 26 years of age (M = 26.3, SD =
11.57) and for SATS the average was 32 (M = 31.9, SD = 15.82). An independent sample
t-test was used to examine differences between traveler type groups and the age they first
applied for a passport. Significant differences were found between groups,

t (246) =-3 .22, p < .01 , in particular HATS had applied an average of five years earlier

than SATS.

103

Number of domestic and international trips. Data were collected to measure

respondents domestic (U .S. or Canada) and international vacation travel experience
during the past three years. The average number domestic vacation trips respondents had
taken in the last three years was seven (M = 6.61, SD = 13.29) and the average number of
international vacations was three (M = 3.47, SD = 13.27). The averages were different
between traveler type groups. HATS had taken an average of six (M = 6.27, SD = 10.14)
domestic trips and an average of three (M = 2.82, SD = 9.76) international trips. Whereas,
the SAT traveler group had taken an average of seven (M = 7.20, SD = 17.47) domestic

trips and an average of five (M = 4.58, SD = 17.76) international trips.

An independent sample t-test was used to analyze the relationship between
traveler type groups and domestic and international travel experience. Significant
differences were found between groups for both domestic, t (322) = -.609, p < .05, and
international, t (322) = -1.15, p < .01, vacation intentions. Results indicate that the SAT
group has greater domestic and international travel intentions than HATS.

Number of destinations visited. An examination of the total number of
destinations (continents/regions) respondents reported having visiting for vacation during
their lifetime resulted in an average of five (M = 5.06, SD = 2.90) out of the seventeen
provided. HATS had traveled to an average of six (M = 5.62, SD = 3.11) and SATS had

traveled to an average of four (M = 4.11, SD = 2.20) out of the seventeen destinations
(continents/ regions). It should be noted that these figures do not represent how often a
respondent may have traveled to a particular continent or region, Simply the variety or

mix of destinations (continents/regions) respondents have traveled to during their

104

lifetime. For the HAT group, fifteen was the maximum number of destinations
(continents/regions) visited and thirteen was the maximum for the SAT group.

An independent sample t-test was employed to ascertain if differences existed
between traveler type and number of destinations (continents/regions) visited. Significant
differences were found for the number of destinations respondents visited during their
lifetime, t (322) = 4.66, p < .01. Results indicated HATS have traveled to more

destinations (continents/regions) than the SAT group.

Destinations experienced. Respondent vacation travel experience to select
destinations (continents/regions) during their lifetime was examined and results are
provided. As discussed in Chapter 111, destinations were organized into three groups: (1)
mass, (2) soft adventure, and (3) hard adventure. The groups were formed based on the
results of the expert judge review. Using cross-tabulation analysis, a profile of the two
traveler type groups was identified. To assess whether significant differences exist
between traveler type and destination (continents/regions) experience, Chi-square tests
were estimated. Significant differences between traveler type groups were found for

seven of the seventeen destinations (continents/ regions).

Mass destinations. Because the study population was from the United States, it
was expected that North America (97%) would be the top destination respondents had
visited during their lifetime (Table 14). The second most visited destination was Mexico
(73%) followed by Western Europe (65%).

The t0p three destinations visited for the HAT group were North America (98%),
Western Europe (72%), and the Caribbean (5 8%). For the SAT group t0p destinations

were North America (96%), Western EurOpe (53%) and Caribbean (49%). The Chi-

105

square statistic was used to determine if any statistically significant differences between
HAT and SAT groups existed. The analysis resulted with significant differences for two
of the six mass tourism destinations, Western Europe, x"(l , N = 323) = 12.29, p < .01,
and Central Europe x?( 1, N = 323) = 6.31, p < .05. When compared with the SAT group,
HATS were twenty-percent more likely to have traveled to Western Europe for vacation
and 13% more likely to have traveled to Central Europe for vacation. Overall, results

suggest HATS have more mass destination vacation travel experience than SATS.

Table 14

Mass Destinations Visited During Lyetime

 

 

Hard Soft
Adventure Adventure All 2
Mass Destinations Traveler Traveler Travelers x Sig;
(n = 205) (n == 119) (N = 323)
% % %
Western Europe 72.2 52.9 65.1 12,292 .000
Central Europe 36.1 22.7 31.2 6.31 .012
North America 98.0 95.8 97.2 1.41 .235
Mexico 47.2 25.9 73.1 0.63 .428
Caribbean 57.6 48.7 54.3 2.36 .124
Eastern Europe 13.7 6.7 11.1 3.67 .055

 

1Categories were determined through expert review; de= 1.

Soft adventure destinations. Of the six soit adventure destinations, the top two
visiting by respondents during their lifetime were North Asia (23%) and Australia (18%)
(Table 15). For both traveler type groups the top destinations experienced were North
Asia (SATS 18% and HATS 26%) and Australia (SATS 13% and HATS 20%). The next
most experienced destination for HATS was the Middle East (18%) and for SATS it was
New Zealand (12%). Significant differences between groups existed for two of the six

sort adventure destinations, the Middle East, x20, N = 323) = 10.08, p < .01 and South-

106

Southeast Asia, x2(1, N = 323) = 8.50, p < .01. HATS were twice more likely than SATS
to have traveled to the Middle East (HATS 18% versus SATS 6%) and South-Southeast

Asia (HATS 22% versus SATS 9%).

Table 15

SM! Adventure Destinations Visited During Lifetime

 

 

Hard Soft
Adventure Adventure All
Soft Adventure Destinations Traveler Traveler Travelers x Sig.
(n = 205) (n = 119) (N = 323)
% % %
Middle East 18.5 5.9 13.9 10,032 .001
South-Southeast Asia 22.0 9.2 17.3 8.50 .004
North Asia 26.3 17.6 23.1 3.20 .074
Australia 20.5 13.4 17.9 2.54 .11 1
New Zealand 16.1 11.8 14.5 1.14 .286
South Pacific 13.2 9.2 1 1.7 1.12 .290

 

1Categories were determined through expert review; de= 1.

Hard adventure destinations. Central America (28%) and South America (23 %)
were the top hard adventure destinations respondents had visited during their lifetime
(Table 16). For both traveler type groups, Central America was the top hard adventure
destination (SATS 18% and HATS 34%) followed by South America (SATS 14% and
HATS 29%). Significant differences among groups existed for three of the five hard
adventure destinations, Africa x2( 1, N = 323) = 9.25, p < .01, Central America
x2(1, N = 323) = 9.08,p < .01, and South America, x2(1, N = 323) = 8.81,p<.01. HATS
were more likely than SATS to have traveled to Africa (SATS 11% versus HATS 25%),

South America (SATS 14% versus HATS 29%), and Central America (SATS 18% versus

34%).

107

Table 16

Hard Adventure Destinations Visited During Lifetime

 

 

Hard Soft
Adventure Adventure All 2
Hard Adventure Destinations Traveler Traveler Travelers x SL
(n = 205) (n = 119) (N = 323)
% % %
Africa 24.9 10.9 19.8 9,252 .002
Central America 34.1 18.5 28.4 9.08 .003
South America 28.8 14.3 23.5 8.81 .003
Arctic 2.5 2.5 3.1 0.20 .654
Antarctica 0.0 0.0 1.2 2.35 .125

 

rCategories were determined through expert review; Idf= 1.

Number of activities experienced. Overall, the average number of recreation and
travel activities respondents reported experiencing during their lifetime was 22 (M =
22.40, SD = 6.75). The average for the HAT traveler type group was 25 (M = 24.95, SD =
5.52) and the average for the SAT group was 18 (M = 18.02, SD = 6.43).

An independent sample t—test was employed to ascertain differences between
traveler type groups and the number of recreation and travel activities experienced. No
significant difference was found between groups for recreation and travel activity
experience. See Appendix K for a list of other recreation and travel activities not included

in the list but were reported by respondents as recreation and travel activities experienced

in vacation travel during their lifetime.

Activities experience. Recreation and travel activities experienced during
respondents lifetime were examined. Based on the results of the expert judge review
discussed in Chapter III, recreation and travel activities were organized into three groups:
(1) mass, (2) soft adventure, and (3) hard adventure. Using cross-tabulation analysis, a

profile of respondents and the two traveler type groups were identified. To assess whether

108

significant differences existed between traveler type and recreation and travel activity

experience, Chi—square tests were estimated.

Mass activities. The top recreation and travel activities experienced during
respondents’ lifetime all were in the mass activity category (Table 17). These included:
visited local/state/national parks (93%), dined (92%), and visited places of historical
interest (90%).

In the case of the HAT group, hiking (94%) was the only heavy participation
activity that was not classified as a mass activity. All other recreation and travel activities
identified by HATS belonged to the mass activity category. These were: dined (96%),
visited local/state/national parks (96%), visited places of historical interest (93%), visited
friends or relatives (92%), and visited museums/galleries (90%). For the SAT traveler
type group, the top recreation and travel activities experienced during their lifetime were:
visited local/state/national parks (87%), dined (86%), and visited places of historical
interest (85%), attended local festivals/fairs (81%), scenic driving (80%), and visited
friends or relatives (78%).

HATS reported higher levels of activity experience in all cases except for one,
having visited casinos/gambling/gaming (SATS 42% versus HATS 41%). Significant
differences were found for 14 of the 20 mass recreation and travel activities, with HATS
reporting significantly higher participation in all activities. Compared to the SAT group, a
greater percentage of HATS reported experiences of getting to know local people, x2(1, N
= 324) = 17.74, p < .01 and having visited night clubs/nightlife/dancing, x2( 1, N = 324) =

12.69, p < .01.

109

Table 17

Mass Activities Experienced During Lifetime

 

 

Hard Soft
1 Adventure Adventure All
Mass Activities Traveler Traveler Travelers x’ 3L
(n = 205) (n == 119) (N = 324)
% % %

Getting to know local people 80.5 58.8 72.5 17_742 .000
Night life/visiting night clubs/dancing 60.0 39.5 52.5 12.69 .000
Swimming/sunbathing/bcach activities 89.3 69.7 82.1 19.52 .000
Dining 96.1 85.7 92.3 11.40 .001
Visiting friends or relatives 91.7 78.2 86.7 12.02 .001
Attending concert/play/dance 81.5 66.4 75 .9 9.36 .002
Visiting museums/galleries 89.8 77.3 85.2 9.24 .002
Visiting local/state/national parks 95.6 87.4 92.6 7.41 .006
Visiting gardens/botanical gardens 74.6 62.2 70.1 5.56 .018
Attending spectator sporting events 60.5 47.1 55.6 5.50 .019
Visiting places of historical interest 92.7 84.9 89.8 5.02 .025
Visiting zoos 73.2 62.2 69.1 4.26 .039
Visiting spas 32.2 21.8 28.4 3.96 .046
Scenic driving 87.8 79.8 84.9 3.73 .053
Attending local festivals/fairs 87.8 81.5 85.5 2.40 .121
City tours/short guided excursions 78.0 69.7 75.0 2.77 .096
Golfing/tennis 30.2 22.7 27.5 2.16 .142
Shopping 78.0 69.7 75.0 2.77 .096
Visiting casinos/gambling/garning 41.5 42.0 41.7 0.01 .922
Visitin theme/amusement parks 62.9 56.3 60.5 1.38 .240

 

Categories were determined through expert review; de= 1.

Soft adventure activities. In the soft adventure recreation and travel activity

category, the top three activities reported by respondents were: hiking (86%), camping

 

(83%), and backpacking (68%). As Shown in Table 18, over the course of their lifetime,
the top soft recreation and travel activities experienced by the HAT group were: hiking
(94%), camping (89%), and backpacking (79%). While the SAT group had highest
participation in camping (73%), hiking (72%), and observing wildlife/birdwatching
(48%).

Comparison of the travel type groups showed significant differences existed in 12
of the 13 soft adventure activities. HATS reported a higher proportion experience. A

greater number of HATS reported having backpacked compared to SATS, x2(1, N = 324)

110

 

= 36.20, p < .01. The HAT group also indicated more experience in mountain biking,

7172(1, N = 324) = 28.69, p < .01, and skiing and snowmobiling, x2(1, N = 324) = 25.21, p

< .01 than SATS. Hunting and fishing was the only soft adventure activity where no

significant difference between groups existed.

 

 

Table 18
Sty? Adventure Activities Experienced During Ljfetime
Hard Soft
1 Adventure Adventure All 2
Soft Adventure Activities Traveler Traveler Travelers x Sig,__
(n = 205) (n = 119) (N = 324)
% % %

Backpacking 79.5 47.1 67.6 36,202 .000
Bicycle riding 68.3 38.7 57.4 27.05 .000
Boating 71.7 42.9 61.1 26.37 .000
Camping 88.8 73.1 83.0 13.12 .000
Hiking 93.7 72.3 85.8 28.28 .000
Kayaking/canoeing 67.8 46.2 59.9 14.60 .000
Mountain biking 46.3 16.8 35.5 28.69 .000
Skiing/snowmobiling 67.3 38.7 56.8 25.21 .000
Waterskiing/snorkeling 65.4 40.3 56.2 19. 16 .000
Observing wildlife/birdwatching 67.3 47.9 60.2 11.85 .001
Scuba diving/surfing 43.9 27.7 38.0 8.36 .004
Volunteering on vacation 18.5 9.2 15.1 5.06 .024
Huntin fishin 45.9 37.8 42.9 1.99 .159

 

Categories were determined through expert review; Tdf= 1.

Hard adventure activities. The top hard adventure recreation and travel activities

respondents experienced were: cave exploring/spelunking (36%), climbing

mountain/rock/ice (35%), and trekking (32%) (Table 19). Respondents were grouped

based on past travel experience, therefore no hard adventure activities were experienced

by the SAT group otherwise the respondent would have been placed into the HAT

traveler type group. More than half of the HAT group had experienced two of the four

hard adventure activities, cave exploring/spelunking (57%) and climbing (55%), during

their lifetime.

111

Table 19

Hard Adventure Activities Experienced During Lifetime

 

Hard Soft
] Adventure Adventure All 2
Hard Adventure Activities Traveler Traveler Travelers x SL
(n = 205) (n = 119) (N = 324)
% % %
Cave exploring/spelunking 57.1 0.0 36.1 1015302 .000
Climbing mountain/rock/ice 54.6 0.0 34.6 99.36 .000
Safaris 24.9 0.0 15.7 35.13 .000
Trekkin 50.2 0.0 31.8 87.66 .000

 

Categories were determined through expert review; Tdf== 1.

Travel Intention Profile

To understand short-term and long-term travel intentions, intentions were
examined on two levels, during the next three years and during the respondents’ lifetime.
The following sections present sample statistics on domestic and international vacation
travel intentions for the next three years, destinations (continents/regions) respondents
plan to travel for vacation during their lifetime, and recreation and travel activities
respondents plan to partake while on vacation during their lifetime.

Key travel intention variables were: average number of domestic and international
vacations respondents plan to take during the next three years; average number of
destinations (continents/regions) they plan to travel to during their lifetime; destinations
(continents/regions) respondents plan to experience in the future (organized into three
groups: mass destinations, and soft and hard adventure destinations); and the recreation
and travel activities respondents plan to experience during their lifetime (organized into

three groups: mass activities, and soft and hard adventure activities).

112

Domestic and international vacation plans. Respondents were asked to report '
on the number of domestic (U .S. or Canada) and international vacations they planned to
take in the next three years. The average number domestic vacations respondents plan to
take was seven (M = 7.01, SD = 15.26) and the average number of international vacations
was four (M = 4.31, SD = 15.20). The averages were slightly different between traveler
type groups. HATS plan to take an average of seven (M = 6.52, SD = 12.22) domestic

vacations and SATS plan an average of eight (M = 7.86, SD = 19.46).

Results for international travel intentions were similar with HATS planning to
take an average of four (M = 3.59, SD = 11.82) international vacations during the next
three years and SATS planning an average of Six (M = 5.55, SD = 19.72). Independent
sample t-tests were used to analyze the relationship between traveler type and domestic
and international travel intentions. Significant differences were found between groups for
both domestic, t (322) = -.761, p < .01, and international, t (322) = -1.12, p < .01,
vacation intentions. Results indicated that the SAT group has greater domestic and
international travel intentions than HATS.

Number of continents/regions plan to visit. The average number of
continents/regions respondents intend to visit during their lifetime was six (M = 6.44, SD
= 4.11). For the SAT group the average number of continents/regions they planned to
visit was five (M = 4.67, SD = 3.19) and for the HAT group the average was seven (M =

7.47, SD = 4.23). Averages were based on a count of the number of continents/regions
respondents indicated they plan to travel while vacationing in their lifetime. As
mentioned in the previous section, these figures do not represent how often a respondent

plans to travel to a particular continent or region.

113

An independent sample t-test was employed to ascertain differences between
traveler type groups and the number of destinations respondents planned for future
vacations. Significant differences were found, t (322) = 6.26, p < .01. Results suggest

HATS plan to visit more continents/regions than SATS.

Destination intentions. Respondent destination (continents/regions) intentions
during their lifetime was examined and results are provided. As discussed previously
discussed, based on results of the expert judge review, destinations were organized into
three groups: (1) mass, (2) soft adventure, and (3) hard adventure. Using cross-tabulation
analysis, a profile of respondents and the two traveler type groups were identified. To
assess whether Significant differences existed between traveler type and destination

intention, Chivsquare tests were estimated.

Mass destinations. Table 20 shows that North America (83%) and Western
Europe (60%) were the top two destinations respondents plan to visit in the future. North
America (SATS 82% and HATS 83%) and Western Europe (SATS 57% and HATS 61%)
were the top choices for both traveler groups. The Chi-square statistic was used to
determine if statistically significant differences between traveler type groups and future
mass destination travel plans existed. Results of the analysis Show significant differences
between groups for three of the six mass destinations (Eastern Europe, Central Europe,
and the Caribbean). Compared with SATS, 21% more HATS plan to travel for vacation in
the future to Eastern Europe, x2(1, N = 323) = 26.93, p < .01. HATS also had greater
intentions than SATS to visit Central Europe (SATS 21% versus HATS 38%), .30, N =
323) = 10.08, p < .01. In addition, HATS were 10% more likely than SATS to have plans

to travel for vacation in the future to the Caribbean, x2(1, N = 323) = 4.81, p < .01.

114

Table 20

Mass Destinations Plan to Visit During Lyetime

 

 

Hard Soft

Adventure Adventure All 2
Mass Destination Traveler Traveler Travelers x Si;g_.__

(n = 205) (n = 119) (N = 324)

% % %

Eastern Europe 26.8 5.9 19.1 21, 3 52 .000
Central Europe 38.0 21.0 31.8 10.08 .001
Caribbean 43.4 31.1 38.9 4.81 .028
Western Europe 61.5 57.1 59.9 0.58 .444
Mexico 42.0 32.8 38.6 2.68 .102
North America 83.4 82.4 83.0 0.60 .806

 

1Categories were determined through expert review; 7df= 1.

Soft adventure destinations. As shown in Table 21, the top three soft adventure
destinations respondents plan to visit during their lifetime were North Asia (83%),
Australia (57%), and New Zealand (51%). The top three soft adventure destinations were
the same for both traveler groups. At the top of the list for the HATS (83%) and SAT s
(82%) was North Asia, followed by Australia (HATS 64% and SATS 44%), and then by
New Zealand (HATS 57% and SATS 42%).

The Chi-square statistic was used to determine if any statistically significant
differences between groups existed. Results of the analysis showed significant
differences between traveler type groups for all Six soft adventure destinations. In all

cases, HATS reported greater intentions to visit the destinations for vacation during their
lifetime. The greatest difference was found for plans to visit South-Southeast Asia. HATS
were more likely to plan to visit South-Southeast Asia (SATS 9% and HATS 33%), x2(1,
N = 323) = 4.81, p < .01, than SATS. A significant difference was also found for

intentions to visit the South Pacific, x2 (1, N = 323) = 17.91, p < .01. Seventeen percent of

115

HATS plan to visit Antarctica, whereas 6% of SATS plan to travel to the continent. This

difference was statistically Significant, x2(1, N = 323) = 12.94, p < .01.

Table 21

Soft Adventure Destinations Plan to Visit During Lifetime

 

 

Hard Soft
1 Adventure Adventure All 2
Soft Adventure Destination Traveler Traveler Travelers x Sfiig;_
(n = 205) (n == 119) (N = 324)
% % %
South Pacific 44.4 21.0 35.8 17,912 .000
North Asia 83.4 82.4 83.0 18.02 .000
South-Southeast Asia 33.2 9.2 24.4 23.38 .000
Middle East 28.3 6.7 20.4 21.60 .000
Australia 63.9 44.5 56.8 1 1.51 .001
New Zealand 55.6 42.0 50.6 5.57 .018

 

lCategories were determined through expert review; 2df= 1.

Hard adventure destinations. The top two hard adventure destinations
(continents/regions) respondents plan to visit for vacation during their lifetime were
Central America (45%) and South America (44%) (Table 22). Both traveler groups
indicated Central America and South America as the t0p hard adventure destinations they
plan to travel to for a vacation during their lifetime. More than half of the HAT group
indicated they plan to travel to Central American (53%) and South America (53%) for a
vacation in their lifetime. Similarly, South America (3 0%) and Central America (33%)
were the top destination choices for SATS.

A significant difference was found in four of the five hard adventure destinations,
with the Arctic being the only non-significant hard adventure destination. In all cases,
HATS had greater intentions to travel for vacation. HATS were more likely to have
intentions to travel to Africa for vacation, x2( 1, N = 323) = 26.93, p < .01, than SATS.
HATS were the only group reporting past vacation travel experience to Antarctica (2%),

116

and they reported the greatest level of intention (19%) to visit Antarctica for vacation
travel. None of the respondents from SAT group indicated having past vacation
experience to Antarctica; however a small percentage (5%) reported plans to travel there

for vacation in the fixture.

Table 22

Hard Adventure Destinations Plan to Visit During Lifetime

 

Hard Soft

Adventure Adventure All
Hard Adventure Destination Traveler Traveler Travelers x Sig;

(n = 205) (n = 119) (N = 324)

% % %

South America 52.7 30.3 44.4 15.342 .000
Africa 47.3 18.5 36.7 26.93 .000
Antarctica 19.5 5.0 14.2 12.94 .000
Central America 52.7 32.8 45.4 12.04 .001
Arctic 14.1 9.2 12.3 1.67 .196

 

lCategories were determined through expert review; 7df= 1.

Activity intentions. Respondent’s recreation and travel activity intentions were
examined and results are provided. Based on the results of an expert judge review,
recreation and travel activities were organized into three groups: (1) mass, (2) soft
adventure, and (3) hard adventure. Using cross-tabulation analysis, a profile of the two
traveler groups was identified. To assess whether significant differences exist between
traveler type groups and recreation and travel activity intentions, Chi-square tests were

estimated.

Number of activities plan to experience. The average number of recreation and
travel activities respondents intend to experience during their lifetime was fifteen (M =

15.68, SD = 9.66). For the SAT traveler type group the average was also fourteen (M =

117

13.69, SD = 8.01). In contrast, HATS plan to experience an average of seventeen (M =
16.84, SD = 10.34) recreation and travel activities during their lifetime.

An independent sample t-test was employed to ascertain differences between
traveler type groups and the number of recreation and travel activities they plan to
experience during their lifetime. Significant differences were found between groups t
(322) = 2.87, p < .01. HATS reported intentions to experience three more activities than
SATS. See Appendix L for a list of recreation and travel activities respondents plan to
experience that were no included on the survey, but were reported by respondents.

Mass activities. Among all respondents visiting local, state, and national parks
(69%), followed by places of historical interest (67%) and dining out (67%) were the top
mass recreation and travel activities they intend to take part in during their lifetime (Table
23). In the case of HATS, the mass activities they plan to participate in are: visiting
local/state national parks (69%), visiting places of historical interest (65%), dining (64%),
and visiting friends or relatives (64%). In comparison, the majority of SATS reported
they plan to participate in the following mass activities: dining (71%), visiting
local/state/national parks (69%), visiting places of historical interested (69%) and scenic
driving (64%).

A significant difference between traveler groups was found for only one mass
activity, attending spectator sporting events, x2(1, N = 324) = 6.50, p < .01. HATS were
more likely than SATS to plan to attend spectator sporting events in the future (HATS

41% and SATS 27%).

118

Table 23

Mass Activity Intentions During Lifetime

 

 

Hard Soft
1 Adventure Adventure All 2
Mass Activities Traveler Traveler Travelers x Sig.
(n = 205) (n = 119) (N = 324)
% % %
Attending spectator sporting events 41.0 26.9 35.8 5.502 .01 1
Attending concert/play/dance 49.3 46.2 48.1 0.28 .596
Attending local festivals/fairs 55.1 56.3 55 .6 0.04 .837
City tours/short guided excursions 48.3 54.6 50.6 1.21 .272
Dining 64.4 70.6 66.7 1.30 .254
Getting to know local people 56.6 47.1 53.1 2.74 .098
Golfing/tennis 16.1 15.1 15.7 0.05 .817
Night life/visiting night clubs/dancing 28.8 21.8 26.2 1.87 .172
Scenic driving 62.9 64.7 63.6 0.10 .748
Shopping 51.7 53.8 52.5 0.13 .719
Swimming/sunbathing/beach activities 59.0 55.5 57.7 0.39 .532
Visiting casinos/gambling/gaming 17.1 25.2 20.1 3.11 .078
Visiting friends or relatives 63.9 60.5 62.7 0.37 .542
Visiting gardens/botanical gardens 48.8 44.5 47.2 0.54 .461
Visiting local/state/national parks 68.8 68.9 68.8 0.00 .981
Visiting museums/galleries 61.5 62.2 61.7 0.02 .898
Visiting places of historical interest 65 .4 68.9 66.7 0.42 .514
Visiting spas 25.9 17 .6 22.8 2.88 .090
Visiting theme/amusement parks 28.3 28.6 28.4 0.00 .957
Visitin zoos 39.5 34.5 37.7 0.82 .365

 

Categories were determined through expert review;7df= 1.

Soft adventure activities. Results for soft adventure recreation and travel
activities respondents plan to experience during lifetime are presented in Table 24.
Hiking (59%) was the top soft adventure recreation and travel activity respondents
intended to take part in during their lifetime, followed by camping (48%),
kayaking/canoeing (48%), and observing wildlife/birdwatching (43%). The top, planned
future activity for both traveler groups was hiking (SATS 51% and HATS 64%). For the

SAT hiking was followed by observing wildlife/birdwatching (3 9%) and for the HAT

group it was kayaking/canoeing (56%).

119

A Significant difference between traveler groups was observed for all 11 of the 13
soft recreation and travel activities, with hunting/ fishing and observing
wildlife/birdwatching being the only non-significant cases. In all cases, the HAT group
had greater intentions to participate than SATS. Both groups reported an interest in
volunteering on vacation (HATS 39% and SATS 18%). Significant differences were
found between HATS and SATS with regard to intentions to volunteer on vacation, x2(1,
N = 323) = 5.06, p < .01, with almost a quarter (22%) more HATS planning to volunteer

on vacation in the future.

Table 24

Soft Adventure ActiviQr Intentions During Ljfetime

 

 

Hard Soft
1 Adventure Adventure All 2
Soft Adventure Activities Traveler Traveler Travelers x Sjg.__
(n = 205) (n = 119) (N = 324)
% % %
Volunteering on vacation 39.5 17.6 31.5 16,692 .000
Kayaking/canoeing 55.6 36.1 48.5 1 1.43 .001
Mountain biking 32.2 16.0 26.2 10.25 .001
Skiing/snowmobiling 46.3 26.9 39.2 1 1.95 .001
Boating 46.3 31.1 40.7 9.56 .002
Backpacking 48.8 31.9 42.6 8.74 .003
Waterskiing/snorkeling 45.9 30.3 40. 1 7.63 .006
Bicycle riding 46.3 31.1 40.7 7.25 .007
Hiking 63.9 51.3 59.3 4.98 .026
Scuba diving/surfing 44.4 31.9 39.8 4.88 .027
Carrrping 52.7 41.2 48.5 3.99 .046
Hunting/fishing 25 .9 27.7 26.5 0.14 .712
Observin wildlife/birdwatching 46.3 38.7 43.5 1.81 .179

 

Categories were determined through expert review;7df= 1.

Hard adventure activities. Presented in Table 25 are the results for hard
adventure activities respondents plan to experience in their lifetime. Safaris (40%)
followed by trekking (27%) and climbing mountain/rock/ice (23 %) were the top intended
hard adventure activities reported by respondents. Similarly, safaris were the most

120

popular hard adventure activity that both traveler type groups plan to experience. Almost
half of HATS (48%) and more than a quarter of SATS (27%) plan to take a safari on a
future vacation. Results suggest that a limited number of the SAT group have intentions
to experience hard adventure activities including; trekking (7%), cave
exploring/spelunking (5%), or mountain, rock or ice climbing (5%).

Significant differences were found between groups for all hard activities. HATS
reported greater intentions to take a safari, x2 (1, N = 323) = 13.71, p < .05. In addition,
more HATS (38%) plan to experience trekking than SATS (7 %) on a future vacation,
x2(1, N = 323) = 38.80, p < .05. More than one-quarter (26%) of the HAT group reported
plans to participate in cave exploring/Spelunking compared with just five percent of the

SATs, x2(1, N = 323) = 22.64, p < .01 planning to experience cave exploring/spelunking.

Table 25

Hard Adventure Activity Intentions During Lifetime

 

 

Hard Soft
1 Adventure Adventure A11 2
Hard Adventure Activities Traveler Traveler Travelers x Sig;-
(n = 205) (n = 119) (N = 324)
% % %
Cave exploring/spelunking 26.3 5.0 18.5 22.642 .000
Climbing mountain/rock/ice 34.1 5.0 23.5 35.52 .000
Safaris 47.8 26.9 40.1 13.71 .000
Trekkin 38.5 6.7 26.9 38.80 .000

 

Categories were determined through expert review; 2df= 1.

Destination experience and intentions combined. The relationship between
destination experience and future intentions to visit a destination were examined. Cross
tabulations Show a significant relationship between experience and intention levels. The

results are organized according to three destination type groups; (1) mass destinations, (2)

121

soft adventure destinations, and (3) hard adventure destinations. As discussed in Chapter

III, destination groups were determined based on expert review.

Mass destination experience and intentions. North America was the top mass
destination, however, the assumption was made that all respondents had experienced or
had intentions to experience a vacation in North America. Excluding North America,
Western Europe (86%), Mexico (82%), and the Caribbean (68%) were the top mass
destinations respondents reported having experienced or having plans to experience
(Table 26). An examination of traveler type indicated the top three top mass destinations
for HATS and SATS were also Western Europe, Mexico, and the Caribbean.

Chi-square analysis indicated Significant differences between traveler type groups
and experience or plans to experience five of the six mass destinations. The greatest
difference between HATS and SATS was for Eastern Europe, .90, N = 324) = 21.07, p <
.01, with HATS (35%) reporting more experience and/or plans to experience the
destination than SATS (12%). Next was Central Europe, x2(1, N = 324) = 23.33, p < .01,

with HATS (58%) again reporting greater experience and/or intentions than SATS (3 8%).

122

Table 26

Mass Destination Experience and Intentions Combined

 

Hard Soft
1 Adventure Adventure All 2
Mass Destinations Traveler Traveler Travelers x 8L
(n = 205) (n == 119) (N = 324)
% % %
Central Europe
No experience — No intentions 42.0 62.2 49.4 12.332 .000
Experience and/or Plan to experience 58.0 37.8 50.6
Eastern Europe
No experience - No intentions 64.9 88.2 73.5 21.07 .000
Experience and! or Plan to experience 35.1 1 1.8 26.5
Caribbean
No experience — No intentions 26.3 40.3 31.5 6.84 .009
Experience and/or Plan to experience 73.7 59.7 68.5
Mexico
No experience - No intentions 13.7 25 .2 17.9 6.84 .009
Experience and/or Plan to experience 86.3 74.8 82.1
Western Europe
No experience - No intentions 8.8 23.5 14.2 13.44 .000
Experience and/or Plan to experience 91.2 76.5 85.8
North America
No experience — No intentions 1.5 2.5 1.9 0.46 .496
Experience and/or Plan to experience 98.5 97.5 98.1

 

rCategories were determined through expert review;7df== 1.

Soft adventure destination experience and intentions. Australia (68%) and New
Zealand (60%) were the top soft adventure destinations respondents had experienced or
plan to experience (Table 27). An examination of traveler type indicated the top soft
adventure destinations HATS experienced or plan to experience were also New Zealand
(66%) and Australia (75%). In the case of SATS, while the percentages were not as high
as the HAT group, Australia (56%) and New Zealand (50%) were still the top soft
adventure destinations SATS had experienced or plan to experience during their lifetime.

Chi-square analysis indicated significant differences between traveler type groups
and experience or plans to experience for all six of the soft adventure destinations. The

greatest difference between HATS and SATS was for South-Southeast Asia, x2( 1 , N =

123

324) = 33.01, p < .01, with HATS reporting 32% more experience or plans to experience
travel to South-Southeast Asia on a vacation trip than SATS. Following closely was the
Middle East, x2(1, N = 324) = 30.71, p < .01, with HATS reporting 29% more experience

or intentions to experience traveling to the Middle East than SATS.

Table 27

Soft Adventure Destination Experience and Intentions Combined

 

Hard Soft
1 Adventure Adventure All 2
Soft Adventure Destinations Traveler Traveler Travelers x Sig.
(n = 205) (n = 119) (N = 324)
% % %
North Asia
No experience — No intentions 43.4 68.1 52.5 13.352 .000
Experience and/or Plan to experience 56.6 31.9 47.5
South Pacific
No experience — No intentions 46.8 73.1 56.6 21.16 .000
Experience and/or Plan to experience 53.2 26.9 43.5
South-Southeast Asia
No experience - No intentions 51.2 83.2 63.0 33.01 .000
Experience and/or Plan to experience 48.8 16.8 37.0
Middle East
No experience - No intentions 60.0 89.1 70.7 30.71 .000
Experience and/or Plan to experience 40.0 10.9 29.3
Australia
No experience - No intentions 25.4 43.7 32.1 11.61 .001
Experience and/or Plan to experience 74.6 56.3 67.9
New Zealand
No experience — No intentions 33.7 49.6 39.5 7.99 .005
Experience and/or Plan to experience 66.3 50.4 60.5

 

ICategories were determined through expert review; 2df= 1.

Hard adventure destination experience and intentions. Central America (61%)
and South America (58%) were the top hard adventure destinations respondents had
experienced or plan to experience during their lifetime (Table 28). An examination of
traveler type groups indicated the top hard adventure destinations HATS experienced or

plan to experience were also Central America (71%) and South America (69%). The top

124

hard adventure destinations for SATS were also Central American (44%) and South
America (38%).

To examine differences between traveler type groups, Chi-square analysis was
employed. Results indicated significant differences between traveler type groups and
experience or plans to experience for four out five hard adventure destinations. The
greatest difference between HATS and SATS was for Africa, x2(1, N = 324) = 31.40, p <
.01, with HATS reporting 32% more experience or plans to experience Afi'ica on a
vacation trip than SATS. Following closely was the South America, x2(1, N = 324) =
30.52, p < .01, with HATS reporting 31% more experience or intentions to experience
traveling to the South American than SATS. No significant differences were found
between traveler type groups and experience and/or plan to experience travel to the
Arctic. However, a higher percentage of HATS (17%) indicated experience and/or plans
to experience travel to the Arctic for vacation compared to SATS (10%). At each end of
the destination continuum are the Arctic, where few peOple can travel to, and North

America where respondents live.

125

 

 

 

% % %
Afiica
No experience — No intentions 40.0 72.3 51.9 31,402 .000
Experience and/or Plan to experience 60.0 27.7 48.1
Antarctica
No experience — No intentions 78.5 95.0 84.6 15.56 .000
Experience and/or Plan to experience 21.5 5 .0 15.4
South America _
No experience — No intentions 30.7 62.2 42.3 30.52 .000
Experience and/or Plan to experience 69.3 37.8 57.7
Central America
No experience — No intentions 28.8 56.3 38.9 24.00 .000
Experience and/or Plan to experience 71.2 43.7 61.1
Arctic
No experience — No intentions 83.4 89.9 85.8 2.61 .106
_k Experience and/or Plan to experience 16.6 10.1 14.2

 

ICategories were determined through expert review; 2df= 1.

Activities experience and intentions combined. The relationships between
recreation and travel activity experience and future recreation and travel activity
intentions were examined. Cross tabulations Show a significant relationship between
experience and intention. As previously explained, the results are organized according to
three groups; (1) mass activities, (2) soft adventure activities, and (3) hard adventure
activities.

Mass activity experience and intentions. The top three mass activities
respondents reported having experienced or plan to experience in the fiiture were: visiting
local/state/national parks (94%), visiting places of historical interest (93%), and dining
(93%) (Table 29). An examination of traveler type indicated the top three top mass
activities for HATS were also visiting local/state/national parks (97%), visiting places of

historical interest (95%), and dining (96%). For SATS the top three were: visiting
126

local/state/national parks (91%), visiting places of historical interest (90%), and dining
(87%).

Chi-square analysis indicated significant differences between traveler type groups
and experience or plans to experience for 12 out of 15 mass recreation and travel
activities. The greatest difference was for nightlife, x2(1, N = 324) = 14.16, p < .01, with
HATS (62%) reporting more experience and/or plans to experience nightlife than SATS
(40%). Next, HATS (85%) reported more experience and/or intentions to experience than
SATS (65%) for the getting to know local people, x2(1, N = 324) = 18.59, p < .01.
Visiting spas was next, x2 (1, N = 24) = 10.70, p < .01, with HATS (42%) reporting

greater experience or intentions to experience than SATS (24%).

127

Table 29

Mass Activity Experience and Intentions Combined

 

Hard Soft
1 Adventure Adventure All
Mass Activities Traveler Traveler Travelers x‘2 Sig._
(n = 205) (n = 119) (N = 324)
% % %
Getting to know local people
No experience — No intentions 14.6 35.3 22.2 18. 592 .000
Experience and/or Plan to experience 85.4 64.7 77.8
Night life/visiting night clubs/dancing
No experience — No intentions 38.0 59.7 46.0 14.16 .000
Experience and/or Plan to experience 62.0 40.3 54.0
Visiting spas
No experience — No intentions 57.6 75.6 64.2 10.70 .001
Experience and/or Plan to experience 42.4 24.4 35.8
Dining
No experience — No intentions 3.9 12.6 7.1 8.65 .003
Experience and/or Plan to experience 96.1 87.4 92.9
Visiting friends or relatives
No experience - No intentions 7.8 18.5 11.7 8.30 .004
Experience and/or Plan to experience 92.2 81.5 88.3
Visiting museums/ galleries
No experience — No intentions 8.8 19.3 12.7 7.58 .006
Experience and/or Plan to experience 91.2 80.7 87.3
Visiting gardens/botanical gardens
No experience — No intentions 21.5 35.3 26.5 7.39 .007
Experience and/or Plan to experience 78.5 64.7 73.5
Attending spectator sporting events
No experience — No intentions 33.7 48.7 39.2 7.18 .007
Experience and/or Plan to experience 66.3 51.3 60.8
Attending concert/play/dance
No experience -— No intentions 16.6 26.9 20.4 4.93 .026
Experience and/or Plan to experience 83.4 73.1 79.6
Visiting local/state/national parks
No experience — No intentions 3.4 9.2 5.6 4.88 .027
Experience and/or Plan to experience 96.6 90.8 94.4
Scenic driving
No experience — No intentions 9.8 17 .6 12.7 4.24 .039
Experience and/or Plan to experience 90.2 82.4 87.3
Visiting zoos
No experience — No intentions 24.4 34.5 28.1 3.77 .052
Experience and/or Plan to experience 75.6 65.5 71-9
Visiting places of historical interest
No experience — No intentions 5-4 10-1 7'1 2'54 '11 1
C ExPerience and/or Plan to experience 94.6 89.9 92-9
ity tours/short ided excursions
No expefienciu— No intentions 18.0 25.2 20.7 2.35 -125
Experience and/or Plan to experience 82.0 74.8 79-3
Attending local festivals/fairs. 1 1 7 2.10 .148
No expenence - No mtennons 9.8 15.1 -
Experience and/or Plan to experience 90.2 84.9 38-3

128

. .
1"":
11M.)

Signj
H11
Std:

317

Table 29 Continued

 

Shopping
No experience - No intentions 22.0 27.7 24.1 1.38 .241
Experience and/or Plan to experience 78.8 72.3 75.9

Visiting theme/amusement parks
No experience — No intentions 34.6 40.3 36.7 1.05 .305
Experience and/or Plan to experience 65.4 59.7 63.3

Golfing/tennis
No experience - No intentions 67.8 72.3 69.4 0.71 .400
Experience and/or Plan to experience 32.2 27.7 30.6

Visiting casinos/gambling/ gaming
No experience — No intentions 56.6 55.5 56.2 0.04 .844
Experience and/or Plan to experience 43.4 44.5 43.8

 

jCategories were determined through expert review; 2df== 1.

Soft adventure activity experience and intentions. The top soft adventure
activities respondents reported having experienced or plan to experience in the future
were: hiking (87%), camping (85%) and swimming/sunbathing/beach activities (84%)
(Table 30). In all cases, the HAT group had the highest percentage of experience and or
plans to experience hard adventure activities while SATS reported the greatest percentage
of no experience and no intentions to experience. Hiking (95%), camping (91%), and
swimming/sunbathing/beach activities (90%) were the top soft adventure activity HATS
had experienced or plan to experience. For SATS the top three were the same, but
camping (75%) was first followed by hiking (73%), and swimming/sunbathing/beach
activities (72%).

Chi-square analysis was used to examine if there was an association between
traveler type and soft adventure activity experience and intentions. The analysis revealed
significant differences between HATS and SATS in 13 of the 14 soft adventure activities.
HATS reported greater percentage of experience and/or plans to experience activities

such as backpacking, x2(l, N = 324) = 31 .45,p < .01, bicycle riding, x2(l, N = 324) =

21.74), p < .01, and camping, x2(1, N = 324) = 14.01, p < .01.

129

Table 30

S0}? Adventure Activity Experience and Intentions Combined

 

 

Hard Soft
1 Adventure Adventure All 2
Soft Adventure Activities Traveler Traveler Travelers x Sig.___
(n = 205) (n == 119) (N = 324)
% % %
Backpacking
No experience — No intentions 16.6 45.4 27.2 31.552 .000
Experience and/or Plan to experience 83.4 54.6 72.8
Bicycle riding
No experience — No intentions 26.3 52.1 35.8 21.74 .000
Experience and/or Plan to experience 73.7 47.9 64.2
Boating
No experience - No intentions 27.3 52.9 36.7 21.27 .000
Experience and/or Plan to experience 72.7 47.1 63.3
Camping
No experience - No intentions 9.3 25.2 15 .1 14.91 .000
Experience and/or Plan to experience 90.7 74.8 84.9
Hiking
No experience — No intentions 5.4 26.9 13.3 30.31 .000
Experience and/or Plan to experience 94.6 73.1 86.7
Kayaking/canoeing
No experience — No intentions 19.5 47.9 29.9 28.93 .000
Experience and/or Plan to experience 80.5 52.1 70.1
Mountain biking
No experience — No intentions 46.8 77.3 58.0 28.72 .000
Experience and/or Plan to experience 53.2 22.7 42.0
Scuba diving/surfing
No experience -— No intentions 38.5 62.2 47.2 16.89 .000
Experience and/or Plan to experience 61.5 37.8 52.8
Skiing/snowmobiling
No experience — No intentions 27.3 56.3 38.0 26.86 .000
Experience and/or Plan to experience 72.7 43.7 62.0
Swimming/sunbathing/beach activities
No experience - No intentions 9.8 27.7 16.4 17.78 .000
Experience and/or Plan to experience 90.2 72.3 83.6
Volunteering while on vacation
No experience — No intentions 54.6 77.3 63.0 16.60 .000
Experience and/or Plan to experience 45.4 22.7 37.0
Waterskiing/ snorkeling
No experience - No intentions 31.7 58.0 41.4 21.43 .000
Experience and/or Plan to experience 68.3 42.0 58.6
Observing wildlife/bird watching
No experience -— No intentions 28.8 47.9 35.8 11.97 .001
Experience and/or Plan to experience 71.2 52.1 64.2
Hunting/fishing
No experience — No intentions 50.7 57.1 53.1 1.24 - .265
“Experience and/or Plan to experience 49.3 42-9 46.9

 

. 2
‘Categories were determined through expert revrew; df= 1.

130

11's:

f3,“
“11

F111

.
(151'-
sub.

mi}
12111

1'“

1.41)

Hard adventure activity experience and intentions. As shown in Table 31, the
top hard adventure activities respondents reported having experienced or plan to
experience in the future were safaris (47%) and cave exploring (43%). In all cases, the
HAT group had the highest percentage of experience and or plans to experience hard
adventure activities while SATS reported the greatest percentage of no experience and no
intentions to experience. Cave exploring/spelunking was the top hard adventure activity
HATS had experienced or plan to experience (65 %), whereas the top for SATS going on a
safari (27%).

A Chi-square test was used to determine whether there was a Si gnificant different
between HATS and SATS in hard adventure activity experience and intentions. The
analysis revealed significant differences for all hard adventure activities with HATS
having greater experience and/or plans to experience cave exploring/spelunking x2(1, N =
324) = 111.65, p < .01, climbing, x2(1, N = 324) = 102.27), p < .01, safaris, x2(1, N =
324) =-- 31.19,p < .01, and trekking, x2(1, N = 324) = 87.34,p < .01.

Table 31

Hard Adventure Activity Experience and Intentions Combined

 

Hard Soft
Adventure Adventure All
Hard Adventure Activities1 Traveler Traveler Travelers x2 Sig.
(n = 205) (n = 119) (N = 324)
% % %
Cave exploring/spelunking
No experience — No intentions 34.6 95.0 56.8 1 11.652 .000
Experience and/or Plan to experience 65.4 5.0 43.2
Climbing - mountain/rock/ice
No experience — No intentions 37.6 95.0 58.6 102.27 .000
Experience and/or Plan to experience 62.4 5.0 41.4
Safaris '
No experience —- No intentions 41.0 73.1 52.8 31.19 .000
Experience and/or Plan to experience 59.0 26.9 47.2
Trekking
No experience - No intentions 40.5 93.3 59.9 87.34 .000
prerience and/or Plan to experience 59.5 6.7 40.1

 

. 2
1 Categories were determined through expert revrew; df= l.

131

Pre

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Pre-Trip and Post Travel Behavior Profile
Respondent vacation travel behavior pre-trip, during trip, and post-trip are

discussed in the next sub-section. Included in this section are pre- and post-travel
behavior profile (trip planning; sources used to book or reserve trips; helpfulness of
sources; pre-trip activities, communication types used, technologies used before, during
and after vacation travel, helpfulness of technology, and lifestyle changes following a
vacation trip); (5) descriptive statistics of the personality traits (elemental, compound,
situational, and surface); (6) factor analysis to determine underlying factors of the surface

trait ATP; and (6) hierarchical regressions to test the hypotheses.

Pre-trip planning behavior. Information regarding respondent’s trip planning
behavior (i.e., how far ahead they plan a vacation trip) was collected (Table 32). Most
respondents (61%) strongly agree or agree that they plan trips well in advance or prior to
leaving (64%) The majority of the SAT group agreed or strongly agreed they plan trips
well in advance (71%), whereas the majority of HATS (67%) agreed or strongly agreed

they plan most trips before they leave.

An independent sample t-test was employed to ascertain group differences in
vacation planning behavior. Results indicate a Significant difference between HATS and
SATS for planning trips well in advance t (318) = -2.65, p<.01. The SAT group (M =
3.78, SD = 0.95) had higher agreement level than the HAT group (M = 3.46, SD = 1.13).
Results suggest SATS are more likely to plan trips in advance. No significant differences

were found between groups for planning trips closer to departure or even once arriving at

the destination.

132

 

ild

Table 32

Vacation T ryt Plannirgg

 

Hard Soft
1 Adventure Adventure All
Planning Behavior Traveler Traveler Travelers t Sig;

 

n M SD n M SD N M SD

Plantrips wellinadvance 204 3.462 1.13 116 3.78 0.95 320 3.58 1.08 -2.65 .000

Planmosttripsbefore leave 205 3.61 1.04 116 3.49 0.97 321 3.57 1.02 1.00 .689
Planmostmjisoncelarrive 203 2.16 0.99 116 2.09 1.04 319 2.13 1.01 0.65 .865

TIEased on vacation trip taken in the previous 12 months; 2Based on a five-point scale where 1 =
strongly disagree and 5 = strongly agree.

Sources used to book or reserve vacation trips. Table 33 provides a summary
of sources used by respondents when booking or reserving a vacation trip taken in the
past 12 months. The top five booking sources used were: airline websites (82%); search
engines (77%) such as Google and Yahoo; magazines (67%); accommodations websites
(67%); and guidebooks (66%).

For both HAT and SAT groups, the top three sources used when booking or
reserving vacation trips were: airline websites (HATS 88% and SATS 71%); search
engines (HATS 84% SATS 65%) such as Google and Yahoo; and magazines (HATS 73%
and SATS 67%). HATS reported using guidebooks (73 %) and advice/recommendations of

friends and family (71%). SATS reported using accommodations websites (5 7%) and
magazines (58%). See Appendix M for a list of additional booking sources used by
respondents.
Results of Chi-square analyses indicated differences between HATS and SATS
and the booking sources used. HATS used travel websites such as Expedia and Lonely

Planet one-quarter more, x2(1, N = 318) = 19.24, p < .01 than the SAT group. HATS were

133

more likely to use magazines, x2(1, N = 318) = 7.55, p < .05 and guidebooks, x2(1, N =

318) = 7.31, p < .05, as booking sources than SATS.

 

 

 

Table 33
Sources Used to Book Vacation Travel
Hard Soft
‘ Adventure Adventure All 2
Booking Source Used Traveler Traveler Travelers x Sig.
(n =202) (n =116) (N=3l8)
% % %

Airline websites 88.1 70.7 81.8 15012 .000
Search engines 84.2 65.5 77.4 14.62 .000
Travel websites 65.8 40.5 56.6 19.24 .000
Stories/blogs from travelers and travel writers 47.5 25.0 39.3 15.67 .000
Advice/recommendations of friends or family 70.8 54.3 64.8 8.77 .003
Magazines 72.8 57.8 67.3 7.55 .006
Guidebooks 71.8 56.9 66.4 7.31 .007
Hotwire.com 20.2 9.6 16.4 6.07 .014
Accommodation websites 71.8 5 8.6 67.0 5.77 .016
Travelocity.com 58.1 46.1 53.8 4.28 .039
Local or government tourism websites 60.9 49.1 56.6 4.14 .042
Pricelinecom 28.6 20.9 25.8 2.28 .131
Expediacom 55.7 47.0 52.5 2.23 .135
Orbitz.com 50.7 42.6 47.8 1.94 .163
Chsapticketscom 29. 1 22.6 26.7 1.56 .21 1
Travel trade shows 7.9 4.3 6.6 1.56 .212
Hotels.com 38.4 32.2 36.2 1.24 .265
Tour omentors/Lodges 30.5 25.2 28.6 1.02 .313
Hotel websites 68.5 63.5 66.7 0.82 .364
Newspapers 36.6 31.9 34.9 0.73 .394
TV travel shows 30.2 27.6 29.2 0.24 .622
Travel agents 28.1 30.4 28.9 0.20 .656
Kayakcom 15.8 13.9 15.1 0.20 .658
Tour brochures 40.6 38.8 39.9 0-10 .752
Travel a ents 28.2 27.6 28.0 0.01 .904

 

Based on vacation trip taken in the previous 12 months; 2df= l.

Helpfulness of sources used to book or reserve vacation trips. Respondents

were asked to rate helpfulness (1 = not helpful, 2 = somewhat helpful, and 3 = very

helpfifl) of those booking sources they used during the past 12 months. Results are

Presented in Table 34. The most helpful sources used to book a vacation in the last 12

mOnths were: search engines (M=2.67, SD=0.47); guidebooks (M=2.60, SD=0.51); airline

134

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it!

ope

11111

it]

it

5‘0

websites (M=2.5 8, SD=0.54); accommodation websites (M=2.54, SD=0.55); and tour

operators/lodges (M=2.54, SD=0.54).

For the SAT group, the most helpful booking sources were: airline websites
(M=2.66, SD=0.53); guidebooks (M=2.64, SD=0.48); accommodation websites (M=2.56,
SD=0.50); search engines (M=2.51, SD=0.50); and stories/blogs from travelers and travel
writers (M=2.48, SD=0.69). Most helpfirl sources used by HATS were: search engines
such as Google and Yahoo (M = 2.75, SD = 0.44), tour Operators/lodges, (US and foreign
based) (M = 2.64, SD = .052); guidebooks (M = 2.58, SD = 0.52); airline websites (M =
2.55, SD = 0.54); and travel agents (M = 2.55, SD = 0.57).

The results of the Chi-square analyses reported in Table 34 indicate Si gnificant
differences between traveler groups regarding helpfulness of booking sources Seven of
the booking sources; local government tourism websites, search engines, magazines,
stories/blogs from travelers and travel writers, local/government websites, tour brooches,
and airline websites were Significant, in particular SATS rated stories/blogs from travelers
and travel writers and airline websites as more helpful than HATS. For all other booking

sources HATS rated their helpfirlness higher than SATS.

135

Table 34

Mean Scores for Helpfulness of Sources Used to Book Vacation Travel

 

 

Hard Soft
1 Adventure Adventure A11
Boolgng Source Used Travelers Travelers Travelers t 8L
n M SD n M SD N M SD
Local or government
tourism websites 119 2.472 0.56 55 2.273 0.45 193 2.42 0.54 2.23 .000
Search engines 166 2.75 0.44 73 2.51 0.50 239 2.67 0.47 3.74 .000
Magazines 142 2.37 0.53 65 2.17 0.52 207 2.31 0.53 2.60 .003
Stones/blogs 96 2.36 0.53 29 2.48 0.69 125 2.39 0.57 -0.98 .012
Tour brochures 79 2.28 0.62 42 2.19 0.50 121 2.25 0.58 0.79 .019
Airline websites 172 2.55 0.54 80 2.66 0.53 252 2.58 0.54 -1.59 .045
Guidebooks 141 2.58 0.52 64 2.64 0.48 205 2.60 0.51 -0.77 .088
Accommodation
websites 140 2.54 0.57 66 2.56 0.50 206 2.54 0.55 0.30 .128
NeWSpapers 73 2.27 0.51 36 2.11 0.52 109 2.22 0.52 1.56 .139
Travel agents 55 2.55 0.66 30 2.37 0.56 90 2.48 0.62 1.39 .635
Travel trade shows 16 2.31 0.79 3 1.67 0.58 19 2.21 0.79 1.33 .270
Hotels.com 78 2.24 0.58 37 2.41 0.60 115 2.30 0.59 -1.37 .300
Kayakcom 31 2.45 0.62 16 2.25 0.77 47 2.38 0.68 0.97 .322
Expediacom 111 2.52 0.52 54 2.41 0.57 165 2.48 0.54 1.30 .407
'IV travel shows 61 2.18 0.59 31 2.35 0.55 92 2.24 0.58 -1.37 .557
Travel agents 55 2.55 0.57 30 2.37 0.56 85 2.48 0.57 1.39 .635
Pricelinecom 58 2.16 0.67 25 2.32 0.56 83 2.20 0.64 -1.08 .696
Tour operators/Lodges 61 2.64 0.52 30 2.33 0.55 91 2.54 0.54 2.60 .735
Advice/recommendation
from friends or family 139 2.53 0.58 61 2.46 0.59 200 2.51 0.58 0.74 .756
Orbitzcom 102 2.32 0.62 49 2.35 0.60 151 2.33 0.61 -0.22 .823
Travelocitycom 1 17 2.40 0.53 54 2.39 0.53 171 2.40 0.53 0.15 .902
Cheapticketscom 57 2.12 0.76 27 2.37 0.69 84 2.20 0.74 -1.44 .921
Hotwirecom 40 2.30 0.65 12 2.17 0.72 52 2.27 0.66 0.61 .969
Travel websites 132 2.53 0.54 46 2.5 2 0.55 178 2.53 0.54 0.09 .990

 

1Based on vacation trip taken in the previous 12 monthsyHelpfulness rated only by those respondents who

indicated they had used the booking source; 3Based on a three point scale where
1 = not helpful and 3 = very helpful.

Pre-trip behaviors. Table 35 summarizes pre-trip behaviors respondents

reported they implemented prior to their last vacation trip. More than half of the

respondents indicated they purchased travel guide books (59%) and read books about the

local culture (57%) before their last trip. The majority of both groups purchased -

guidebooks (HATS 61% and S ATS 55%); read books about the local culture (HATS 59%

and SATS 53%); and got into good physical Shape (HATS 48% and SAT 3 36%). One-

136

third of SATS purchased new luggage or gear and more than one-quarter (26%) learned
some of the local language before traveling. HATS also purchased new luggage or gear

(38%) and learned some of the local language (32%).

Results of Chi-square analyses indicated a significant difference for getting into
good physical shape x2(1, N = 316) = 4.15, p < .05. The HAT group was more likely to
get into good physical shape prior to vacation than the SAT group. No significant

difference was found for other pre-trip behaviors.

 

 

Table 35
Pre-trip behavior
Hard Soft
1 Adventure Adventure All 2
Pre-trip Activities Traveler Traveler Travelers x Sig
(n =200) (n=116) (N=316)
% % %

Got into good physical shape 48.0 36.2 43.7 4152 .042
Purchased travel guide books 61.5 55.2 59.2 1.22 .270
Read books about the local culture 59.0 52.6 56.6 1.23 .267
Purchased new luggage/gear 38.0 31.9 35.8 1.19 .275
Watched programs on the local culture 21.0 27.6 23.4 1.78 .183
Learned some of the local lang1_r_age 32.0 25.9 29.7 1.32 .250

 

 

IBased on vacation trip taken in the previous 12 months; Tdf= 1.

Communication types for sharing travel experiences. A summary of
communication types respondents used to share travel experiences during and after
vacation are summarized in Table 36. Results indicate telling stories (89%) is by far the
most common communication type for all traveler types. Electronic communication
sources continue to be more commonplace among travelers with many reporting .posting
photos on-line after a trip (45%), however, results suggest that the tradition of sending

postcards by mail (49%) continues to play an important format for travelers to share

137

travel experiences. An almost equal amount of HATS (49%) and SATS (48%) indicated
they mail postcards when they travel. Blogs were used most by HAT, but the results still
suggest a low number of respondents using blogs to communicate their travel experiences

during or after their trip.

A Chi-square test was performed to examine the relation between HATS and
SATS and the types of communication used during and after vacation trips. The relation
between posting photos on-line after a trip was significant, x2(1, N = 317) = 4.22, p < .05.

HATS were more likely to post photos on-line than were SATS.

Table 36

Communication Types Used During and After a Vacation T rip

 

Hard Soft
1 Adventure Adventure All 2
Communication Type Used Traveler Traveler Travelers x EL
(n =200) (n= 117) (N=317)
% % %
Posting photos on-line after trip 49.5 37.6 45.1 4.222 .040
Blog diary afler trip 5.0 1.7 3.8 2.19 .139
Telling stories 90.0 86.3 88.6 0.99 .320
Blog diary during trip 5.5 3.4 4.7 0.71 .400
Posting photos on-line during trip 8.5 10.3 9.1 0.27 .601
Sendin postcards bLmail 49.5 47.9 48.9 0.08 .778

 

Based on vacation trip taken in the previous 12 monthstdf= 1.

Types of technology used during vacation. A summary of technologies used by
respondents when traveling on a vacation during the past 12 months is provided in Table
37. Results indicate the camera/digital camera is the number one technology used by both
respondent groups (SATS 93% and HATS 96%), followed closely by the mobile phone
(SATS 76% and HATS 7 9%). HATS were most likely to use an I-PodfMP3/MP4 player
(45%) or a laptop with wireless access (43%). One-quarter of SATS used a Global

Positioning System (GPS) and slightly more HATS (30%) used a GPS.

138

The percentage of respondents who used an I-pod/MP3/MP4 player differed by
SAT and HAT groups, 1:2 (1, N = 319) = 17.01 , p < .01. Results showed HATS were two
times more likely than SATS to have used an I-pod/MP3/MP4 player on their last
vacation trip (SATS 22% and HATS 45%). The percentage of participants that used
Internet cafés or wireless areas also differed by respondent groups, x2(l, N = 319) = 6.17,
p < .05. Results indicated the HAT group was 14% more likely than the SAT group to
use an Internet café or wireless areas during their last vacation trip (SATS 37% and HATS

51%). See Appendix N for a list of other technologies used by respondents.

Table 37

Technologies Used During Vacation Trip

 

 

Hard Soft
‘ Adventure Adventure All 2
Technology Used Traveler Traveler Travelers x Sig._
(n = 203) (n =116) (N = 319)
% % %

I-Pod/MP3/MP4 player 44.6 21.6 36.3 17,012 .000
Internet cafe or wireless areas 51.5 37.1 46.3 6.17 .013
Camera/Digital camera 96. 1 93.1 95 .0 1.38 .240
Mobile phone 79.4 75.9 78.1 0.54 .460
Laptop conrputer w/ wireless access 42.6 33.6 39.4 2.52 .112
Global Positioning System 31.4 25.0 29.1 1.46 .227
Cellular phone with Internet access 17.2 15.5 16.6 0.14 .704
Cellular phone w/camera 44.1 36.2 41.3 1.91 .167
Pager 2.9 0.9 2.2 1.49 .222
Personal digital assistant 16.7 16.4 16.6 0.00 .947
Personal digital assistant w/Internet 7.4 9.5 8.1 0.45 .503
Laptop computer 40.7 32.8 37.8 1.98 .160
Desktop conrputer 22.1 19.0 20.9 0.43 .513
Global Positioning System in vehicle 22.5 20.7 21.9 0.15 .699
On Star service in vehicle 3.0 5.2 3.8 1.00 .317

 

IBased on vacation trip taken in the previous 12 months; zdf= l.

Helpfidness of technologies used during vacation trip. Those respondents who

reported using technologies on a vacation trip during the previous 12 months were asked

139

to rate the helpfulness of the technology (1 = not helpful, 2 = somewhat helpful, and 3 =
very helpful) and results are presented in Table 38.

The most helpful technology used during vacation was camera/digital camera was
(M = 2.90, SD = 0.30). SATS reported camera/digital camera to be the most helpful
technology (M = 2.85, SD = 0.36) followed by mobile phone (M = 2.72, SD = 0.53).
HATS also reported the most helpful technology used to be the camera/digital camera (M
= 2.92, SD = 0.26) followed by PDA with Internet (M = 2.92, SD = 0.28).

Significant differences between traveler groups were found for helpfulness of
camera/digital camera t (282) = 2.07, p < .01 and use of intemet café or wireless areas

t (136) = 1.79, p < .01. HATS reported cameras/digital cameras and an intemet café or

wireless areas as more helpful than SATS.

Table 38

Mean Scores iHelpfidness of Technologies Used During Vacation Travel

 

 

Hard Soft
Adventure Adventure All
Technology Used1 Travelers Travelers Travelers t Sig;
n M SD N M SD N M SD
Camera digital camera 186 2,922 0.26 98 2.85 0.36 284 2.90 0.30 2.07 .000
lntemet cafe or wireless
areas 98 2.73 0.44 40 2.58 0.55 138 2.69 0.48 1.79 .002
PDA assistant w/ Internet 13 2.92 0.28 9 2.56 0.73 22 2.77 0.53 1.67 .002
Laptop computer w/wireless 80 2.78 0.45 35 2.60 0.60 115 2.72 0.50 1.72 .003
Mobile phone 152 2.82 0.44 79 2.72 0.53 231 2.7 8 0.47 1.44 .008
On Star service in vehicle 6 2.50 0.84 3 3.00 0.00 9 2.67 0.71 -l.00 .029
Global Positioning System in
vehicle 44 2.82 0.39 21 2.71 0.46 65 2.78 0.41 0.94 .079
ipod Mp3 Mp4 player 84 2.54 0.63 22 2.64 0.49 106 2.56 0.60 -0.69 .097
Personal digital assistant 29 2.59 0.50 16 2.56 0.73 45 2.58 0.58 0.13 .118
Global Positioning System 62 2.71 0.46 25 2.64 0.57 87 2.69 0.49 0.60 .136
Laptop computer 75 2.72 0.45 34 2.68 0.53 109 2.71 0.48 0.44 .246
Cellular phone w/camera 86 2.14 0.72 38 2.24 0.67 124 2.17 0.71 -0.70 .821
Cellular phone w/Internet 34 2.62 0.65 17 2.47 0.62 51 2.57 0.64 0.77 .828
Desktop computer 39 2.62 0.54 18 2.44 0.51 57 2.56 0.53 1.12 .989
Pa er 6 1.83 0.75 0 0.0 0.0 6 1.83 0.75 - -

 

Techonolgy used on vacation trip taken in the previous 12 months; 2Helpfulness rated only by t‘

those respondents who indicated they had used the booking source, based on a three point scale where 1 =
not helpful and 3 = very helpfid.

140

Lifestyle changes resulting from a vacation travel experience. Lifestyle

changes resulting from a vacation travel experience are presented in Table 39.

Respondents indicated the primary lifestyle change they experienced after a vacation was
a change in attitude about cultures/places with almost half of SATS (47%) and more than
half of HATS (55%) reporting a new attitude about cultures/places following a vacation
travel experience. Both traveler type groups indicated interest in healthy habits (SATS
41% and HATS 51%) and diet and cuisine (SATS 37% and HATS 47%) as lifestyle
changes impacted by travel. More than one-quarter of each traveler type group indicated
donating money to a charity or cause as a result of a vacation travel experience (SATS
26% and HATS 28%). Chi—square tests indicated no significant difference between

groups for lifestyle changes resulting from vacation travel experiences.

See Appendix 0 for a list of additional lifestyle changes respondents indicated

having experienced after their last vacation trip.

Table 39

_Lifesty1e Change as a Result of Vacation Travel Ejrperience

 

 

Hard Soft

Adventure Adventure All

lifestyle Chagggl Traveler Traveler Travelers x2 Sig.
(n = 119) (n = 205) (N = 324)

% % %
Attitude changed about cultures/places 55.4 46.6 52.2 23,22 .128
Interested in healthy habits 51.5 40.9 47.6 3.31 .069
Interested in diet and cuisine 47.1 37.1 43-4 3.00 .083
Donated money to a charity or cause 28.4 26.1 27.6 0.20 .653
Volunteered time or resources 20.1 17.4 19.1 0.35 .555
A new recreation activity at home 186 l 1-2 15-9 3.04 .081
__Learned a new 12mm 9.3 6.9 8.4 0.56 .455

 

 

1Based on vacation trip taken in the previous 12 monthgzdf= 1.

141

Descriptive Statistics Personality Traits
Descriptive information for variables used in the data analyses are presented
followed by results of the factor analyses conducted to determine the measures of ATP.
The 3M Model of motivation and personality provides the structure for the
placement of the personality variables in this research. Based on hierarchical approaches
to personality (e.g., Allport, 1937), traits are arranged a priori in a four-level hierarchy
consisting of elemental, compound, situational, and surface traits. Descriptive statistics

for each of the elemental, compound, situational, and surface traits are provided below.

Elemental Level Traits

Elemental traits result from genetics and the early learning history of the
individual. Descriptive statistics for the eight elemental traits; Openness to experience,
conscientiousness, extraversion, agreeability, emotional stability, material needs, the need
for arousal, and physical/body needs are provided in Table 40. See Appendix P for the

descriptive statistics for items comprising each of the eight elemental traits.

Overall, the elemental traits with the highest mean scores were: agreeability (M =
6.97, SD = 1.18), openness to experience (M = 6.72, SD = 1.41), and conscientiousness
(M = 6.67, SD = 1.39). HATS had the highest mean scores for the same elemental traits in
the same order: agreeability (M = 6.96, SD = 1.19), openness to experience (M = 6.92, SD
= 1.38), and conscientiousness (M = 6.75, SD = 1.37). For SATS the top traits with the
highest mean score were the same, however, the order was slightly different: agreeability
(M = 6.99, SD = 1.17), conscientiousness (M = 6.51, SD = 1.42), and openness to

experience (M: 6.38, so --= 1.41).

142

An independent sample t—test was conducted to compare elemental traits for

HATS and SATS. There was no significant difference in the scores for elemental traits.

 

 

Table 40
Descriptive Statisticgor Elemental Traits
Hard Soft
Adventure Adventure All
Elemental Traits Traveler Traveler Travelers t Sig;
n M SD n M SD n M SD
Introversion 202 3,33,1 1.61 115 4.09 1.66 317 3.92 1.63 -1.38 .781
Conscientiousness 202 6.75 1.37 1 15 6.51 1.42 317 6.67 1.39 1.47 .949
Openness to Experience 202 6.92 1.38 114 6.38 1.41 316 6.72 1.41 3.27 .757
Agreeability 202 6.96 1.19 115 6.99 1.17 317 6.97 1.18 -0.20 .517
Neuroticism 202 4.07 1.53 114 4.15 1.49 316 4.10 1.51 -0.41 .663
Need for Arousal 203 6.06 1.63 114 5.01 1.72 317 5.68 1.74 5.38 .276
Physical Resources/Body
Needs 203 6.05 1.65 114 5.69 1.70 317 5.92 1.67 1.84 .669
Material Needs 203 3.74 1.85 114 3.82 1.78 317 3.77 1.82 -0.36 .520

 

IBased on a nine-point scale where respondents indicated how often the characteristic describes how they
see themselves in everyday life, 1 = never and 9 = always.

Compound Level Traits

Compound traits are assumed to result from the effects of elemental traits as well
as from cultural and sub-cultural influences. In the current study, the compound traits of
competitiveness, altruism, and need for learning were identified a priori. Descriptive
statistics of the compound measures are provided in Table 41. See Appendix P for the

descriptive statistics for items making up each of the three compound traits.

Competitiveness. The trait competitiveness is defined as “the enjoyment of
interpersonal competition and desire to win and be better than others” (Spence &
Helmreich, 1983, p. 41). Respondents reported the lowest mean scores competitiveness
(M = 4.59, SD = 2.13). However, HATS (M = 4.74, SD = 2.07) reported Slightly higher

mean scores for competitiveness compared to SATS (M = 4.32, SD = 2.22). Independent

143

sample t-test found no significant difference between groups and the compound trait
competitiveness.

Altruism. The compound trait altruism is defined by Mowen and Sujan (2005) as
“a general predisposition to selflessly seek to help others” (p. 173). The second highest
mean score was reported for altruism (M = 6.19, SD = 1.38). HATS (M = 6.27, SD = 1.39)
had slightly higher mean scores than SATS (M = 6.05, SD = 1.35). An independent
sample t-test indicated no Significant difference between groups and the compound trait

altruism.

Need for learning. The compound trait need for leaming is defined as “enduring
disposition to seek information resources” (Mowen, 2000, p. 72). Need for learning was
the compound trait with the highest mean score (M = 6.93, SD = 1.39). HATS had the
highest mean score for need for learning (M = 7.07, SD = 1.17), as did SATS (M = 6.68,
SD = 1.68).

An independent sample t-test was conducted to compare the need for learning trait
for HATS and SATS. There was a significant difference in the scores for need for learning
for HATS (M= 7.07, SD = 1.17) and SATS (M= 6.68, SD = 1.68); t (315) = 2.41, p < .05.

Results suggest HATS have a higher need for learning.

144

Table 41

Descriptive Statistics for Compound Traits

 

Hard Soft
Adventure Adventure All
Compound Traits Traveler Traveler Travelers t Sig.

 

n M so n MSDN MSD
Competitiveness 203 4,741 2.07 114 4.32 2.22 317 4.59 2.13 1.67 .096

Altruism 203 6.27 1.39 114 6.05 1.35 317 6.19 1.38 1.37 .438
Needforlearningfi 203 7.07 1.17 114 6.68 1.68 317 6.93 1.39 2.41 .050

IBased on a nine-point scale where respondents indicated how oflen the characteristic describes
how they see themselves in everyday life, 1 = never and 9 = always.

Situational Level Traits

Situational traits are differentiated from elemental and compound traits because
they operate within a Situational context. Situational traits identified in the current study
are interest in cultural experiences, need for uniqueness, and fashion leadership. A
summary of the descriptive statistics for each of the Situational traits is provided in Table

42. See Appendix P for the descriptive statistics for items making up each of the three

 

 

situational traits.
Table 42
Descriptive Statistics Situational Traits
Hard Soft

Adventure Adventure All
Situational Traits Traveler Traveler Travelers t gig;

n M SD n M SD N M SD
lnterestinCultural
Experiences 203 7.05' 1.32 114 6.31 1.54 317 6.79 1.44 4.50 .121
NeedforUniqueness 202 2,722 0.67 116 2.60 0.64 318 2.67 0.66 1.52 .476
_F3shionLeadership 203 1,952 .767 116 1.89 .691 319 1.93 0.74 0.78 .275

 

Based on a nrne-pornt scale where respondents mdrcated how ofien the characteristic describes how

they see themselves in everyday life, 1 == never and 9 = always; 2Based on a five-point scale where

respondents indicated their level of agreement with each statement, 1 = strongly disagree and 5 = strongly
agree.

145

 

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Interest in cultural experiences. Interest in cultural experiences is defined as
activities that comprise the mosaic of places, traditions, art forms, celebrations, and
experiences portraying the beauty of a country and its people, reflecting the diversity and
character of the country (Tran & Ralston, 2006). Similar to the measure of arts and

humanities (Mowen & Carlson, 2003) the trait was proposed to be a situational trait.

The trait interest in cultural experiences was the situational trait that respondents
reported the highest mean score was (M = 6.79, SD = 1.44). Results suggest that both
SAT and HAT traveler groups are interested in travel to gain cultural experiences such as
those that result fiom exposure to indigenous peOple, trying local foods and customs, and
diverse destinations. Independent sample t-tests were used to examine differences
between groups and interest in cultural experiences. While significant differences were
found for some of the individual items, no significant difference in HAT and SAT scores

for the interest in cultural experiences was found.

Need for uniqueness. Need for uniqueness is defined as an individual’s pursuit
of differentness relative to others that is achieved through the acquisition, utilization, and
disposition of consumers goods for the purpose of developing and enhancing one’s
personal and social identity (Tian et al., 2001). Results suggest adventure travelers have a
need to be distinctive and special. However, results indicate that SATS and HATS prefer
a moderate level of self-distinctiveness because they still have needs for social
acceptance, approval, and validation as well as a need for uniqueness. SATS (M = 3.19,
SD = 1.00) and HATS (M = 3.27, SD = 1.04) reported that they buy to communicate their

uniqueness and dislike products bought by everyone (SAT group M = 2.94, SD = 0.93

146

and HAT group M = 3.09, SD = 0.94). Significance tests resulted in no differences
between groups for need for uniqueness.
Fashion leadership. The situational trait fashion leadership is described by

Goldsmith et al. (1993) as an individual’s interest to learn about fashions earlier than the
average buyer and purchase new items soon after they are introduced to the market.
Respondents indicated they were confident in their ability to recognize fashion trends -
SATS (60% agree or strongly agree) and HATS (5 7% agree or strongly agree) — however,
results suggest fashion was of little interest to adventure travelers. In fact, the majority of
SATS (89%) and HATS (86%) indicated they do not spend a lot of time on fashion-

related activities confirming adventure travelers are not focused on fashion trends.

An independent sample t~test was employed to ascertain differences between
fashion leadership and traveler types. Significant differences were found between traveler
groups and individual items such as regarding their confidence in their ability to
recognize fashion trends, t (317) = 1.28, p < .01. However, the overall measure of fashion
leadership was not significant. While not fashion leaders, results suggest adventure
travelers can identify trends, with HATS indicated the highest level of agreement. These
results may suggest that while adventure travelers are aware of fashion trends, it is not
necessarily an important part of their identity.

Table 43 provides a summary of the highest mean score for each of the eight
personality traits hypothesized to be associated with ATP. Overall, the top personality
trait for all travelers was the elemental trait agreeability (M=6.97, SD=1.18). For HATS

the top trait was the compound trait need for learning (M=7.07, SD=1.17) and the

elemental trait agreeability was the top trait for SATS (M=6.99, SD=1.17).

147

Table 43

Summary Mean Scores for Personality Traits

 

Hard Soft
Adventure Adventure All
Traveler Traveler Travelers
Personality Trait (n=225) (n=-114) (N=339) Trait Level

 

Mean (SD) Mean (SD) Mean (SD) E C S

~

Agreeability 6.96(l.l9) 6.99(1.l7) 6.97(1.18) x
Needforlearning 7,070.17)l 6.680.68) 6.93(1.39) x
Interestincultural experiences 7,05 (1.32)1 6,310.54) 6.79 (1.44) X
Altruism 6,270.39)l 6.05(l.35) 6.19(l.38) x
Needforarousal 6.06063)1 5.01072) 5.68(l.74) x
Competitiveness 4.74 (2.07)‘ 4820.22) 4.59(2.13) x
Need for uniqueness 2.72(0.67)2 2.60(0.64) 2.67(O.66) x
Fashion leadership 19503.77)2 1.89(0.69) 1.93 (0.74) x

 

1Based on a 9 point scale l=never and 9=aIways7Based on a 5 point scale l=strongly agree to 5=strongly
disagree. E=Elemental trait; C=Compound trait; S=Situational trait; ST =Surface trait.

Surface Level Traits

At the fourth level of the hierarchy are surface traits. Surface traits “delineate the
programs of behavior that individuals carry out in order to complete tasks” (Mowen,
2000, p. 21). These traits are a result of person, by situation, by product category
interactions. Surface traits result from the effects of elemental, compound, and situational
traits as well as from the influence of the context specific environment.

A new scale was developed for this study to measure ATP, as a function of
adventure travel experiences. ATP is conceptualized as a surface level trait because of its

specificity. ATP represents an enduring disposition, not a Specific act or behavior. A 24-
item scale consisting of dream travel experiences was developed and factor analysis was
employed to determine the underlying factors of ATP. Descriptive statistics dream travel
experiences are summarized in Table 44. The top dream travel experiences repOrted by
the SAT group were getting off the beaten track (M = 3.75, SD = 1.15), exploring the

ancient civilization of Mayans (M = 3.62, SD = 1.3 5), rafting in the Grand Canyon (M --=

148

3.58, SD = 1.42), and visiting the pyramids in Egypt (M = 3.55, SD = 1.45). SATS were
less likely than HATS to dream about rock climbing on every continent (M = 1.35, SD =
0.80).

Dream travel experiences reported by HATS were getting off the beaten track (M
= 4.41, SD = 0.98), hiking in a rainforest (M = 4.24, SD = 1.06), visiting the pyramids of
Egypt (M = 4.17, SD = 1.19), and exploring the ancient civilization of Mayans (M = 4.15,
SD = 1.15). HATS were less likely than SATS to dream about cliff diving in Jamaica (M =
1.88, SD = 1.22).

Independent sample t-test was employed to examine differences between traveler
type groups and dream travel experiences. Significant differences were found in 16 of the
24 dream travel experiences. In all 16 cases, HATS scored the highest mean values,
suggesting they have greater dream travel experience aspirations. See Appendix Q for a

list of additional dream travel experiences reported by respondents.

149

Table 44

Mean Scores Dream Travel Experiences

 

 

Hard Soft
Adventure Adventure All
Items Travelers Travelers Travelers t Sig.
n M SD n M SD N M SD
Running with the bulls in 1
Spain 202 1.98 1.33 116 1.46 0.91 318 1.79 1.22 3.72 .000
Rock climbing on every
continent 202 2.15 1.38 115 1.35 0.80 317 1.86 1.26 5.74 .000
Swimming in every ocean 202 2.87 1.58 115 1.90 1.25 317 2.51 1.54 5.66 .000
Hiking in a rainforest 203 4.25 1.06 114 3.35 1.46 317 3.92 1.29 6.28 .000
Snorkeling the Great
Barrier Reef 202 3.97 1.40 117 3.08 1.69 319 3.64 1.57 5.06 .000
Going on a safari in Africa 202 3.97 1.37 118 3.25 1.59 320 3.71 1.49 4.25 .000
Rafting in the Grand
Canyon 203 4.11 1.20 116 3.58 1.42 319 3.92 1.30 3.56 .001
Visiting the pyramids in
Egypt 202 4.17 1.19 117 3.55 1.45 319 3.94 1.32 4.18 .001
Relaxing on the white
beaches of Bora-Bora 203 3.73 1.37 115 3.21 1.61 318 3.54 1.48 3.08 .001
Exploring the ancient
civilization of Mayans 203 4.15 1.15 117 3.62 1.35 320 3.96 1.25 3.78 .004
Visiting a market in India 202 2.94 1.51 115 2.03 1.30 317 2.61 1.50 5.42 .007
Camping in Glacier
National Park 203 3.86 1.33 116 3.38 1.49 319 3.68 1.40 2.96 .009
Cage-diving with Great
White Sharks 201 2.11 1.35 115 1.68 1.20 316 1.95 1.31 2.84 .018
Walking the ancient paths
Of China 203 3.74 1.38 115 3.06 1.53 318 3.50 1.47 4.08 .030
Getting off the beaten
"39k 203 4.41 0.98 115 3.75 1.15 318 4.17 1.09 5.46 .036
Bicycling across the USA 199 2.52 1.55 116 2.07 1.44 315 2.36 1.52 2.58 .049
Surf fishing on the beach
at Cape Hatteras 201 1.93 1.25 115 1.63 1.10 316 1.82 1.21 2.07 .073
Clifl‘diving inJamaica 201 1.88 1.22 115 1.62 1.11 316 1.78 1.19 1.87 .133
Hiking in rural Ireland 203 3.76 1.30 117 3.20 1.39 320 3.55 1.36 3.64 .150
Sta ' atahots rin s a
mils; p g p 201 2.04 1.32 116 1.71 1.24 317 1.92 1.30 2.25 .157
Visiting the Seven
Wonders ofthe World 201 3.68 1.43 116 3.14 1.54 317 3.48 1.49 3.16 .213
Visitin all the sev
continegnts en 201 3.59 1.54 117 2.99 1.58 318 3.37 1.58 3.31 .734
Makin snow '
Alaskag angels m 201 3.15 1.56 116 2.78 1.52 317 3.01 1.55 2.07 .855
Sho in in Paris 202 2.64 1.46 117 2.45 1.45 319 2.57 1.46 1.09 .963

 

Based on a five-point scale where respondents indicated whether they have dreamed of having the
experience 1 = not at all and 5 = absolutely. '

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A summary of the top dream travel experiences for each traveler group are
provided in Tables 45, 46, and 47. Getting off the beaten track was the top dream travel
experience for the traveler type groups. Mean scores for the HAT group were

consistently higher than those of SATS.

 

 

Table 45
Top Mean Scores for Dream Travel Experiences-Hard Adventure Travelers
Hard
Adventure
Traveler

Items n M (SD)
Getting off the beaten track 203 4_41T (0,93)
Hiking in a rainforest 203 4.25 (1.06)
Visiting the pyramids in Egypt 202 4.17 (1.19)
E lon'n the ancient civilization of Mayans 203 4.15 (1.15)

 

Based on a five-point scale where respondents indicated whether they have dreamed
of having the experience 1 = not at all and 5 == absolutely.

 

 

Table 46
33p Mean Scoresfor Dream Travel Experience-Soft Adventure Travelers
Soft

Adventure
Travelers

Items 71 M (SD)

Getting offthe beaten track 115 3.75T (1.15)

Exploring the ancient civilization of Mayans 117 3.62 (1.35)

Rafting in the Grand Canyon 116 3.58 (1.42)

Visitin the pyramids in Egypt 117 3.55 Q45)

 

Based on a five-point scale where respondents indicated whether they have dreamed
of having the experience 1 = not at all and 5 = absolutely.

 

 

Table 47
£212 Mean Scores for Dream Travel Experiences-A 11 Adventure Travelers
All
Travelers
items N M (SD)
Getting off the beaten track 313 4”I (1-09)
Exploring the ancient civilization of Mayans 320 3.96 (1.25)
Visiting the pyramids in Egypt 319 3.94 (1.32)
Rafiin in the Grand Canyon 319 3.92 (1-30)

 

Based on a five-point scale where respondents indicated whether they have dreamed
of having the experience 1 = not at all and 5 = absolutely.

151

Factor Analysis

The final sample size of 339 satisfied the minimum requirement of sample size
for principal component analysis with 24 variables; at least five times as many
observations as variables are recommended (Hair et al., 1998). To find underlying
dimensions of dream travel experiences, an Exploratory Factor Analysis (BE A) with
principal component analysis and orthogonal rotation (V ARIMAX) was employed.
Principal component analysis is generally used when the research purpose is data
reduction (to reduce the information in many measured variables into a smaller set of
components). Factor loadings were examined to identify the appropriateness of items
under each derived factor. Additionally, the reliability of the items measuring each factor
was assessed for the final factor solution.

Principal component analysis with an orthogonal rotation (V ARIMAX) produced
the first estimation with five factors by using the default eigenvalues of one as a cutoff.
According to Hair et al. (1998), factors having eigenvalues greater than one are
considered significant and most reliable when the number of variables is between 20 and
50 (Hair et al., 1998). The five factor solution explained 5 7% of the variance which is
considered satisfactory in social sciences. However, five variables — bicycling across the
USA, surf fishing on the beach in Cape Hatteras, hiking in rural Ireland, shopping in
Paris, and swimming in every ocean — failed to correlate with any factor significantly and
thus were removed. After removing the five variables, four factors resulted from

VARIMAX rotation, again using eigenvalues greater than one as a cutoff.

152

 

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Four factors explaining 58.2% of the variance emerged from the factor analysis of
19 dream travel experience items (Table 48). Each factor was named based on the
common characteristics of the variables included.

The first factor was labeled “ultimate destination experiences” since all of the
experiences involved visiting unique/exceptional destinations. The seven items in factor
one were: visiting all the seven continents, visiting the Seven Wonders of the World,
visiting the pyramids in Egypt, going on a safari in Africa, walking down the ancient
paths of China, visiting a market in India, and staying at a hot Spring spa in Japan. All
items had high/acceptable loadings. This factor had an eigenvalue of 3.82 and explained
20.1% of the total variance. This factor had a reliability alpha of 0.86.

The second factor was labeled “tropical adventure experiences” given the focus
on tropical settings. The four variables in factor two were: snorkeling the Great Barrier
Reef, relaxing on the white beaches of Bora Bora, hiking in a rainforest, and exploring
the ancient civilizations of Mayans. All items had high/acceptable loadings. This factor
had an eigenvalue of 2.62 and explained 13.8% of the total variance. The reliability alpha
of this factor was 0.77.

The third factor had high/acceptable loadings for four items: cliff diving in
Jamaica, cage diving with great white sharks, running with the bulls in Spain, and rock
climbing on every continent. Given the focus on difficult/challenging activities, this
factor was labeled “extreme adventure experiences.” Factor three had an eigenvalue of
2.49 and explained 13.1% of the total variance. The reliability alpha was 0.76.

The fourth factor had high/acceptable loadings for four times: camping in Glacier

National Park, making snow angels in Alaska, rafting in the Grand Canyon, and getting

153

off the beaten track. Since all four items involved traditional outdoor adventure activities
or experiences in North America, this factor was labeled “traditional outdoor adventure
experiences.” The fourth factor had an eigenvalue of 2.13 and explained 11.2% of the

total variance. This factor had a reliability alpha of 0.66.

Table 48

Factor Analysis Dream Travel Experiences

 

 

 

Percent of
Eigen Variance Reliability
Factors Loading value Explained Ayiha
Ultimate Destination Experiences 3.82 20.1 0.86
Visiting all the seven continents .79
Visiting the Seven Wonders of the World .77
Visiting the pyramids of Egypt .72
Going on safari in Africa .70
Walking down the ancient paths of China .69
Visiting a market in India .53
Staying at a hot spring spa in Japan .51
Tropical Adventure Experiences 2.62 13.8 0.77
Snorkeling the Great Barrier Reef .77
Hiking in a rainforest .69
Relaxing on the white beaches of Bora Bora .65
Exploring the ancient civilizations of Mayans .57
Extreme Adventure Experiences 2.49 13.1 0.76
Cliff diving in Jamaica .76
Cage diving with Great White Sharks .75
Running with the Bulls in Spain .69
Rock climbing on every continent .61
Traditional Outdoor Adventure Experiences 2.13 11.2 ‘ 0.66
Camping in Glacier National Park .83
Rafting in the Grand Canyon .61
Making snow angels in Alaska .60
Getting off the beaten track .54

Due to low factor loadings, five items (Bicycling across the USA, Surf fishing on the beach in Cape
Hatteras, Hiking in rural Ireland, Shopping in Paris, and Swimming in every ocean) were excluded;
Extraction Method: Principal Component Analysis; Rotation Method: Varimax with Kaiser Normalization.

154

Next, composite scores were created for each of the four factors --ultimate
destination experiences, tropical adventure experiences, extreme adventure experiences,
and traditional outdoor adventure experiences -— based on the mean of the items which
had their primary loadings on each factor. Nineteen items were used to compute the four
scales. These adventure experience factors exhibited moderate to good internal reliability,
ranging between .66 and .86 (see Table 48). Participants rated the items based on whether
they have dreamed of having the experience. An example item is “visiting all seven
continents.” Responses were on a Likert-type scale, ranging from 1 = not at all to 5 =
absolutely. Higher scores indicated greater interest in dong the dream travel experience.
The skewness and kurtosis were well within tolerable range for assuming normal
distribution and examination of the histograms suggested that the distributions looked
approximately normal. Varimax rotation seeks to maximize the variances of the squared
normalized factor loadings across variables for each factor. This is equivalent to
maximizing the variances in the columns of the matrix of the squared normalized factor
loadings.

Overall, these analyses indicate that four distinct factors were underlying dream
travel experiences and that these factors were moderately internally consistent. An
approximately normal distribution was evident for the composite score data in the current
study, thus the data were well suited for parametric statistical analyses. Descriptive
statistics with t-tests of the factors and items included are provided for each of the factors.

Ultimate destination experiences. Ultimate destination experiences involve
visiting unique/exceptional destinations and included the following activities or

experiences: going on a safari in Africa; visiting the pyramids in Egypt; visiting a market

155

in India; walking down the ancient paths of China; staying at a hot spring spa in Japan;
visiting the Seven Wonders of the World; and visiting all the seven continents. The
composite factor mean and item mean scores as well as t—tests for ultimate destination
experiences are provided in Table 49.

For all respondents visiting the pyramids (M = 3.94, SD = 1.32), going on safari in
Africa (M = 3.71, SD = 1.49), and visiting a market in India (M = 3.71, SD = 1.49) were
dream travel experiences. For the SAT group visiting pyramids in Egypt (M = 3.55, SD =
1.45) and going on a safari in Africa (M = 3.25, SD = 1.59) were top dream travel
experiences. Top dream experiences for HATS were also visiting pyramids in Egypt (M =
4.17, SD = 1.19) and going on a safari in Afiica (M = 3.97, SD = 1.37) however, their
mean scores were much higher than SATS. HATS also had high mean scores for walking
down the ancient paths of China (M = 3.97, SD = 1.37) and visiting the Seven Wonders
of the World (M = 3.68, SD = 1.43)

An independent sample t-test was conducted to compare dream travel experiences
for HATS and SATS. There was a significant difference in the scores for all four of the
individual items making up ultimate destination experiences; going on a safari in Africa, ,
t (317) = 4.25, p < .01, visiting the pyramids in Egypt, , t (317) = 4.18, p < .01, visiting a
market in India, t (317) = 5.42, p < .01, and walking down the ancient paths of China,

t (317) = 4.08, p < .0. In all cases HATS had higher mean scores. There was no significant

difference between groups for the factor ultimate destination experiences.

156

Table 49

Mean Scores for Factors and Items- Ultimate Destination Experiences/A T P

 

Hard Soft
Adventure Adventure All
Traveler Traveler Travelers t Sig.

 

n M SDn MSDNMSD
‘ 1.02 118 2.84 1.10 321 3.23 1.09 5.03 .345
3.71 1.49 4.25 .000
3.94 1.32 4.18 .001

Composite Factor Mean 203 3,45
Going on a safari in Africa 202 3.97 1.37 118 3.25 1.59 320
Visiting the pyramids in Egypt 202 4.17 1.19 117 3.55 1.45 319

Visiting a market in India 202 2.94 1.51 115 2.03 1.30 317 2.61 1.50 5.42 .007
Walking down the ancient

paths ofChina 203 3.74 1.38 115 3.06 1.53 318 3.50 1.47 4.08 .030
Staying at a hot spring spa in

Japan 201 2.04 1.32 116 1.71 1.24 317 1.92 1.30 2.25 .157
Visiting the Seven Wonders of

the World 201 3.68 1.43 116 3.14 1.54 317 3.48 1.49 3.16 .213
Visiting all the seven

continents 201 3.59 1.54 117 2.99 1.58 318 3.37 1.58 3.31 .734

 

IBased on a five-point scale where respondents indicated whether they have dreamed of having the
experience 1 = not at all and 5 = absolutely.

Tropical adventure experiences. Tropical adventure experiences focus on
tropical settings and included the following activities or experiences: hiking in a
rainforest, snorkeling the Great Barrier Reef; relaxing on the white beaches of Bora-Bora;
and exploring the ancient civilization of Mayans. The composite factor mean and item

mean scores as well as t-tests for topical adventure experiences are provided in Table 50.

For all respondents exploring the ancient civilizations of Mayans (M = 3.96, SD =
1.23) and hiking in a rainforest (M = 3.92, SD = 1.29) were the top dream travel
experiences. In the case of the HAT group, hiking in a rainforest (M = 4.25, SD = 1.06)
was top followed by exploring the ancient civilizations of Mayans (M = 4.15, SD = 1.15).
Top dream experiences for SATS exploring the ancient civilizations of Mayans (M =

3.62, SD = 1.35) was first and second was hiking in a rainforest (M = 3.92, SD = 1.29).

157

An independent sample t-test was conducted to compare dream travel experiences
for HATS and SATS. A Significant difference between groups was found for all four of
the dream travel experiences that made up the tropical adventure experience factor.
HATS and SATS were significantly different for tropical adventure experiences with
scores for HATS (M=4.04, SD=0.91) higher than those of SATS (M=3.33, SD=1.22); t

(317)= 5.82, p < .01.

Table 50

Mean Scores for Factors and Items- Tropical Adventure Experience/A T P

 

 

Hard Soft
Adventure Adventure All
Traveler Traveler Travelers 1 Sig;
n M SD n M SD N M SD
Composite Factor Mean 203 4.03I 0.91 118 3.33 1.22 321 3.77 1.09 5.82 .000
Hiking in a rainforest 203 4.25 1.06 114 3.35 1.46 317 3.92 1.29 6.28 .000
Snorkeling the Great Barrier
Reef 202 3.97 1.40 117 3.08 1.69 319 3.64 1.57 5 .06 .000
Relaxing on the white beaches
of Bora-Bora 203 3.73 1.37 115 3.21 1.61 318 3.54 1.48 3.08 .001
Exploring the ancient
civilization of Mayans 203 4.15 1.15 117 3.62 1.35 320 3.96 1.23 3.78 .004

 

1Based on a five-point scale where respondents indicated whether they have dreamed of having the
experience 1 = not at all and 5 = absolutely.

Extreme adventure experiences. Extreme adventure experiences focus on
difficult/challenging activities and included the following activities or experiences:
running with the bulls in Spain; rock climbing on every continent; and cage-diving with
Great White Sharks. The composite factor mean and item mean scores as well as t-tests

for extreme adventure experiences are provided in Table 51.

Of the four factors, the mean scores for extreme adventure experiences Were the
lowest. For all respondents cage diving with Great White Sharks (M = 1.95, SD = 1.31)

and rock climbing on every continent (M = 1.86, SD = 1.26) received the highest mean

158

scores. HATS reported rock climbing on every continent (M = 2.15, SD = 1.38) as their
top extreme adventure experience followed by cage diving with Great White Sharks (M =
2.11, SD = 1.35). The top extreme adventure experience for SATS was cage diving with
Great White Shares (M = 1.68, SD = 1.20) followed by running with the bulls in Spain
(M= 1.46, SD = 0.91).

An independent sample t-test was conducted to compare dream travel experiences
for HATS and SATS. A significant difference between groups was found for all three of
the dream travel experiences that make up the extreme adventure experience factor.
HATS and SATS were significantly different for extreme adventure experiences with

HATS having more interest in extreme adventure experiences; t (317) = 4.64, p < .01.

Table 51

Mean Scores for Factors and Items-Extreme Adventure Experiences/A T P

 

 

Hard Soft
Adventure Adventure All
Traveler Traveler Travelers t Sig.
n M SD n M SD N M SD
Composite Factor Mean 202 2.031 0.99 116 1.53 0.78 318 1.84 0.95 4.64 .001
Running with the bulls in
Spain 202 1.98 1.33 116 1.46 0.91 318 1.79 1.22 3.72 .000
Rock climbing on every
continent 202 2.15 1.38 115 1.35 0.80 317 1.86 1.26 5.74 .000
Cage-diving with Great White
Sharks 201 2.11 1.35 115 1.68 1.20 316 1.95 1.31 2.84 .018

 

IBased on a five-point scale where respondents indicated whether they have dreamed of having the
experience 1 = not at all and 5 = absolutely.

Traditional outdoor adventure experiences. Traditional outdoor adventure
experiences involve outdoor recreation activities or experiences in North America and
included the following activities or eXperiences: rafting in the Grand Canyon; camping in

Glacier National Park; getting off the beaten track; and making snow angels in Alaska.

159

The composite factor mean and item mean scores as well as t-tests for traditional outdoor

adventure experiences are provided in Table 52.

For all respondents getting off the beaten track (M = 4.17, SD = 1.09) and rafting
the Grand Canyon (M = 3.92, SD = 1.30) were the top dream travel experiences. In the
case of both the HAT and SAT groups, the top two were also getting off the beaten track
and rafting the Grand Canyon.

An independent sample t-test was conducted to compare dream travel experiences
for HATS and SATS. A significant difference between groups was found for three of the
traditional outdoor adventure experiences; however HATS and SATS were not

significantly different for the factor traditional outdoor adventure experiences.

Table 52

Mean Scores for Factors and Items- Traditional Outdoor Adventure Experiences/A T P

 

 

Hard Soft
Adventure Adventure All
Traveler Traveler Travelers t Sig;
n M SD n M SD N M SD
Composite Factor Mean 203 3.881 0.90 117 3.37 0.99 320 3.70 0.96 4.74 .168

Rafiing in the Grand Canyon 203 4.11 1.20 116 3.58 1.42 319 3.92 1.30 3.56 .001
Camping in Glacier National

Park 203 3.86 1.33 116 3.38 1.49 319 3.68 1.40 2.96 .009
Getting off the beaten track 203 4.41 0.98 115 3.75 1.15 318 4.17 1.09 5.46 .036
Makin snow an els in Alaska 201 3.15 1.56 116 2.78 1.52 317 3.01 1.55 2.07 .855

Based on a five-point scale where respondents indicated whether they have dreamed of having the
experience 1 = not at all and 5 = absolutely.

160

Hypotheses Testing

Hierarchical regressions are used to test the hypotheses. The results of the

hypotheses tests are discussed in this section of the chapter.

Hierarchical Regression

To test the eight hypotheses, a series of hierarchical regression analyses were
performed. The 3M Model provides the theoretical justification for the hierarchical
ordering of variables; surface traits regressed on elemental, compound, and situational
traits. The conceptual model of this research called for three estimated models. In the
first model, the eight elemental traits were entered in the hierarchical regression. Due to
the fundamental nature of the elemental traits, Mowen (2004) recommended that all of
the elemental traits be included as control variables when analyzing the full hierarchical
model since they are the building blocks for the more concrete-level traits. In addition, it
reduce the likelihood of the omitted variable problem. That is, if all eight elemental traits
are not included, it can appear as though a compound or situational trait is predicting a
surface trait. However, when all eight elemental traits are added, the relationship
disappears. Mowen and Voss (2008) refer to this phenomenon as ‘illusory predication.’
In the current study two elemental traits are proposed to be associated with ATP, need for
arousal and agreeability.

In the second model, elemental traits were entered and were followed by the
inclusion of the three compound traits, competitiveness, altruism, and need for learning.
The third and final hierarchical model included the elemental traits, compound traits, and
the addition of the three situational traits, interested in cultural experiences, need for

uniqueness, and fashion leadership. Hierarchical regression models were estimated for

161

each of the four dependent variables (surface traits) where determined through factor
analyses (ultimate destination experiences, tropical adventure experiences, traditional

outdoor adventure experiences, and extreme adventure experiences), each factor

considered a measure of ATP.

First, H1 and H2 test the relationship between the elemental traits need for arousal

and agreeability and the surface trait ATP. Next, H3 — H5 tests the relationship between
the compound traits competitiveness, altruism, and need for learning and ATP. Finally,
H6 — H8 tests the relationship between the situational traits interest in cultural

experiences, need for uniqueness, and fashion leadership and ATP.

HI : The elemental trait need for arousal will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor
adventure experiences, and extreme adventure experiences (ATP).

H2: The elemental trait agreeability will positively influence ultimate destination
experiences, tropical adventure experiences, traditional outdoor adventure
experiences, and extreme adventure experiences (ATP).

H3 2 The compound trait competitiveness will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor
adventure experiences, and extreme adventure experiences (ATP).

H‘ '. The compound trait altruism will positively influence ultimate destination

experiences, tropical adventure experiences, traditional outdoor adventure

experiences, and extreme adventure experiences (ATP).

162

H5 : The compound trait need for learning will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor
adventure experiences, and extreme adventure experiences (ATP).

H6: The situational trait interest in cultural experiences will positively influence
ultimate destination experiences, tropical adventure experiences, traditional
outdoor adventure experiences, and extreme adventure experiences (ATP).
H7: The situational trait need for uniqueness will positively influence ultimate
destination experiences, trOpical adventure experiences, traditional outdoor
adventure experiences, and extreme adventure experiences (ATP).

H's: The Situational trait fashion leadership will positively influence ultimate
destination experiences, tropical adventure experiences, traditional outdoor

adventure experiences, and extreme adventure experiences (ATP

1n multiple regression, the model takes the form of an equation that contains a
coefficient (b) for each predictor. The beta or b-values indicate the individual
contribution of each predictor to the model. The b—values Show the relationship between
ATP and each predictor. 1f the value is positive, there is a positive relationship between

the predictor and the outcome whereas a negative coefficient represents a negative

relationship (Field, 2008).

Each of the b-values has an associated standard error indicating the extent to
which the values would vary across different samples. These standard errors are used to
determine whether or not the b-value differs significantly from zero, using that-statistic.

Therefore, if the t—test associated with a b-value is significant then the predictor is making

163

 

3112

5111

HE

a significant contribution to the model. The smaller the significance value, and the larger
the value of t, the greater the contribution of the predictor.

According to Field (2008), the b-values and their significance are important
statistics to examine, however, the standardized version of the b-values are easier to
interpret because they are not dependent on the units of measurement of the variables.

The standardized beta values indicate the number of standard deviations that the outcome
will change as a result of one standard deviation change in the predictor. The
standardized beta values ()6) are all measured in standard deviation units and thus are

directly comparable. Therefore, they provide a better insight into the ‘importance’ of a

predictor in the model (Field, 2008).

Ultimate destination experiences. In the first set of hierarchical regression
analyses, the dependent variable was ultimate destination experiences, a measure of the
surface trait, ATP. To identify differences in the adventure traveler subgroups, separate
regression analyses were estimated for the HATS and SATS. Results for all travelers, as
well as both the SAT and HAT traveler subgroups, are provided in Table 53. In all cases

variance inflation factor (VIF) (;<_ 1.95) and condition index (17.34) values were

acceptable as they were below the recommended levels of 10 and 30, respectively (Hair

et al., 1998). This indicates that multicollinearity was not an issue.

All travelers. The first model contained the elemental traits. Compound traits
were added in the second model and the situational traits were added to the third to create
the hierarchy. Model 1 was significant (R2 = .14, p < .001) and four of the eight elemental

traits were significantly related to ultimate destination experiences. Specifically,

introversion (negative relationship) ()6 = —.121, p < .05), openness to experience (6 = .13 9,

164

p < .05), need for arousal ()6 = .233, p < .001), and material needs (15’ == .122, p < .05) were
statistically significant predictors of ultimate destination experiences. When the
compound traits, competitiveness, altruism, and need for learning were added in Model 2,
a significant increase was observed in the variance explained (A R2 = .04, p < .01).
Significant predictors of ultimate destination experiences in Model 2 were two of the
elemental traits, material needs (,6 = .118, p < .05) and need for arousal (B = .229, p <
.01), and one compound trait, need for learning (15’ = .183, p<.05). In Model 2, openness
to experience and introversion were no longer significant. Finally, in Model 3 the
addition of the situational traits significantly increased the variance explained by the
hierarchical regression equation (A R2 = .14, p < .001). In this final model, significant
predictors of ultimate destination experiences were two elemental traits and two
Situational traits. The elemental traits were respondents’ need for arousal (fl = .193, p <
.01) and physical resources (negative relationship) (,6 = -.162, p < .01). The situational
traits were interest in cultural experiences ()6 = .485, p < .001), and fashion leadership (,8
= .171,p < .01).

Sofl adventure travelers. The hierarchical regression undertaken for all travelers
was repeated with the sub-set of travelers who were identified as SATS. Among SATS,
neither Model 1 nor Model 2 was significant. However, Model 3 was significant as was
the observed increase in the variance explained from Model 2 to Model 3 (A R2 = .22, p <
.001). In this final model, significant predictors of ultimate destination experiences for
SATS were the elemental trait physical resources (negative relationship) (,8 = -.205, p <
.05) and the compound traits interest in cultural experiences (,6 = .578, p < .001) and

fashion leadership ()6 = .285, p < -01)-

165

Hard adventure travelers. The hierarchical regression was again completed for
HATS only. As described earlier, the first model contained the elemental traits, the
compound traits were added in the second model, and the situational traits were added to
the third. Model 1 was significant (R2 = .14, p < .001). Elemental traits: need for arousal
(,6 = .187, p < .05) and openness to experience (B = .223, p < .01) were statistically
significant predictors of ultimate destination experiences for HATS. When the compound
traits of competitiveness, altruism, and need for learning were added in Model 2, a
significant increase in the variance explained was obtained (A R2 = .05, p < .01).
Significant predictors of ultimate destination experiences for HATS in Model 2 were the
elemental trait need for arousal (,6 = .196, p < .01) and the compound trait need for
learning (3 = .241, p < .01). However, in Model 2, the elemental trait, openness to
experience was no longer significant.

Finally, in Model 3 the situational traits significantly increased the variance
explained (A R2 = .08, p < .001). In this final model, significant predictors of ultimate
destination experiences were elemental traits of need for arousal (fl = .207, p < .01) and
physical resources (negative relationship) (,8 = -.l43, p < .05) and the situational trait
interest in cultural experiences (,6 = .393, p < .001). Unlike the SATS and all travelers,
fashion leadership was not a significant predictor of ultimate destination experiences for

the HAT subgroup.

166

Table 53

Results Hierarchical Regression Analyses: S T — Ultimate Destination Experiences/A T P

 

 

Hard Soft
Adventure Adventure All
Travelers Travelers Travelers
(n = 201) (n = 110) (N = 324)
Model 1: E b SE B b SE 5 b SE ,8
(Constant) 1.918 .651 2.692 .976 1.931 .545
E-Arousal .119 .046 .187" .089 .071 .143 .147 .038 233*"
E-Openness to Exp. .164 .056 .223“ -.042 .081 -.056 .106 .047 .139*
E-Material Res. .055 .038 .100 .132 .060 .220“ .072 .032 .122*
E-Introversion -.063 .044 -. 100 -.1 l 1 .063 -. 172 -.080 .037 -.121*
E-Physical Res. -.054 .047 -.085 -.063 .063 -. 100 -.056 .038 -.085
B—Neuroticism .024 .046 .037 .085 .070 .120 .045 .039 .064
E-Conscientiousness -.035 .054 -.046 .023 .072 .030 -.006 .043 -.008
E-Agreeability .025 .065 .030 -.036 .095 -.038 -.003 .005 -.004
1'0“le .l38*** .124 .l36***
Model 2: E+C
(Constant) 1.204 .679 2.420 .966 1.490 .551
E-Arousal .125 .047 .196" .054 .084 .086 .145 .041 229*”
C-Learning .215 .071 .241" .120 .072 .189 .144 .050 .183"
E-Material Res. .075 .040 .137 .074 .070 .122 .070 .036 .118*
E-lntroversion -.049 .043 -.O78 -.088 .063 -. 136 -.068 .037 -.103
E-Physical Res. -.048 .046 . -.077 -.086 .063 -. I38 -.O63 .038 -.096
E—Neuroticism .033 .045 .050 .107 .070 . 150 .060 .039 .085
C-Altruism .004 .065 .005 . 172 . 100 .197 .082 .055 .099
C-Competitiveness -.063 .038 -.128 .012 .064 .024 -.043 .033 -.085
E—Agreeability -.002 .073 -.002 -.126 .103 -. 135 -.059 .060 -.064
E—Openness to Exp. .097 .060 .132 -.101 .084 -.135 .044 .049 .058
E-Conscientiousness -.053 .054 -.071 -.019 .073 -.025 -.024 .043 -.031
Total R2 .192" .173 .177...
Totalechange .054M .054 .042"
Model 3: E+C+S
(Constant) .597 .663 1.382 .925 .840 .519
S-Intercst Culture .304 .068 393*" .414 .080 .578**"‘ .369 .050 .485***
E-Arousal .132 .045 .207" -.024 .078 -.038 .122 .038 .193"
E-Physical Res. -.091 .045 -.143"‘ -.129 .057 -.205* -.106 .036 -.162**
S-Fashion .135 .105 .102 .436 .155 .285" .248 .087 .171"
E—Neuroticism .045 .043 .068 .073 .063 . 103 .055 .036 .078
S-Uniqueness -.079 .1 16 -.052 -.132 .161 -.076 -.l 15 .093 -.070
E-Agreeability -.013 .071 -.015 -.101 .090 -.109 -.051 .055 -.056
E-Material Res. .055 .042 .100 -.009 .070 -.015 .033 .036 .056
E—Introversion -.026 .042 -.041 -.021 .056 -.033 -.031 .034 -.046
E—Conscientiousness -.031 .052 -.041 -.028 .066 -.O37 -.024 .040 -.O31
C-Cornpetitiveness -.036 .037 -.072 .080 .05 7 .166 -.008 .031 -.016
0th .053 .077 .059 .000 .069 .000 -.010 .051 -.012
E-Openness to Exp. .075 .058 .101 -.144 .076 -.190 .005 .046 .007
C-Altruism -.048 .063 -.064 .076 .090 .087 -.001 .052“ -.001
1‘0sz 276m" 398“” 316*"
__'Lotal chhflgg 084*" .219m .139***

 

l"p<.05, "p<.01, I'"'“"p<.001; DV: Ultimate Destination Experiences; E=Elemental trait; C=Compound
trait; S=Situational trait; S T =Surface trait.

167

For clarity sake, a summary of only those results that were significant for ultimate

destination experiences for the HAT, and SAT subgroups as well as all travelers is

 

 

provided in Table 54.
Table 54
Significant Hierarchical Regression Results: S T - Ultimate Destination Experiences/A T P
Hard Soft
Adventure Adventure All
Travelers Travelers Travelers
E— Need for Arousal E-Physical Resources E-Need for Arousal
(fl= .207,p< .01) (fl=-.205,p<.05) (fl= .193,p< .01)
(negative relationship)
E-Physical Resources E-Physical Resources
(fi=-.l43,p< .05) (fi=-.162,p< .01)
(negative relationship) (negative {913901151189}
S—Interest in Cultural S-Interest in cultural S-Interest in Cultural
Experiences experiences Experiences
(,6 = .393,p < .001) (,6 = .578, p < .001) (B = .485,p < .001)
S—Fashion Leadership S-Fashion Leadership
()6=.285,p<.01) ()B=.171,p<.01)
R2 = .276 R2 = .398 R2 = .316

 

E=Elemental trait; C=Compound trait; S=Situational trait; ST=Surface trait; Adjusted Rrpresented.

Tropical adventure experiences. In the second set of hierarchical regression
equations to predict/model surface traits, the dependent variable was tropical adventure
experiences (a measure of ATP). To identify differences in the adventure traveler
subgroups, separate regression analyses were estimated for HATS and SATS. Results for
all travelers, as well the HAT and SAT subgroups, are provided in Table 55. In all cases
variance inflation factor (VIE) (S 1.95) and condition index (17.34) values were below
the recommended levels of 10 and 30, respectively (Hair et al., 1998), indicating that

multicollinearity was not an issue.

All travelers. The first model contained the elemental traits, the compound traits

were added in the second model, and the Situational traits were added to the third. Model

168

1 was significant (R2 = .16, p < .001) although there was only one statistically significant
predictor of tropical adventure experiences, the elemental trait need for arousal (,6 = .335,
p < .001). When the compound traits of competitiveness, altruism and need for learning
were added in Model 2, a significant increase in the explained variance was observed (A
R2 = .05, p < .001). Significant predictors of tropical adventure experiences in Model 2
included the elemental trait need for arousal (,8 = .324, p < .001) and the compound trait
need for learning (,6 = .248, p < .001). Finally, in Model 3 addition of the Situational traits
significantly increased the explanatory power of the model (A R2 = .11, p < .001). In this
final model, significant predictors of tropical adventure experiences were the elemental
trait need for arousal (,8 = .269, p < .001), the compound trait altruism (negative
relationship) (6 = -.136, p < .05), and the situational trait interest in cultural experiences
(8 == .439, p < .001).

Sofl adventure travelers. When the SAT subgroup was considered, Models 1 and
3 were significant (Model 1 R2 = .21, p < .01). The elemental trait need for arousal (,6 =
.172, p < .05) was the single statistically significant predictor of tropical adventure
experiences for the SAT group in Model 1. When the compound traits (competitiveness,
altruism, and need for learning) were added in Model 2, there was not a significant
increase in the variance. Addition of the situational traits in Model 3 significantly
increased the variance accounted for (A R2 = .11, p < .01). In this final model, significant
predictors of tropical adventure experiences for the SAT sub group were the elemental
trait need for arousal (,8 = .255, p < .05) and the situational trait interest in cultural

CXperiences (,6 = .446, p < .001).

169

Hard adventure travelers. Among HATS, the first model predicting tr0pical
adventure experiences was significant (R2 = .13, p < .001). The elemental traits need for
arousal (,6 = .172, p < .05), openness to experience (8 = .161, p < .05), and agreeability (,8
= .164, p < .05) were statistically significant predictors of tropical adventure experiences
for the HAT group. When the compound traits were added in Model 2, a significant
increase in variance accounted for was obtained (A R2 = .06, p < .01). Significant
predictors of tropical adventure experiences in Model 2 were the elemental traits need for
arousal (,6 = .183, p < .05) and agreeability (,6 = .191, p < .05), and the compound trait
need for learning (,6 = .263, p < .01). Finally, in Model 3 the variance explained improved
again (A R2 = .07, p < .001) and was significantly explained by the following predictors:
the elemental trait need for arousal (fl = .185, p < .05), the compound trait altruism
(negative relationship) ()6 = -.l71, p < .05), and the Situational trait interest in cultural

experiences (,6 = .362, p < .001).

170

Table 55

Results Hierarchical Regression Analyses: ST - Tropical Adventure Experiences/A T P

 

 

Hard Soft
Adventure Adventure All
Travelers Travelers Travelers
Q: = 205) (n = 119) (N = 324)
Model I: E b SE [9 b SE ,6 b SE ,6
(Constant) 2.634 .586 1.599 1.043 1.811 .534
E—Arousal .098 .042 .172* .298 .076 .423*** .210 .038 335*"
E-Openness to Exp. .106 .051 .161“ -.022 .086 -.026 .081 .046 .107
E—Agreeability . 126 .059 . 164* .021 .102 .020 .073 .053 .080
E-Introversion -.061 .040 -.108 .000 .068 .000 -.036 .036 -.056
E—Material Res. -.024 .034 —.050 .094 .065 .138 .021 .032 .036
E—Conscientiousness -.064 .048 -.096 -.007 .077 -.008 -.022 .042 -.028
E-Physical Res. .002 .042 .003 -.049 .067 -.070 -.013 .038 -.020
E—Neuroticism -.018 .041 -.031 .051 .07 5 .063 .002 .039 .003
Total R2 .131*** .214" .160...
Model 2: E+C
(Constant) 2.000 .611 1.411 1.033 1.324 .539
E-Arousal .104 .042 .183“ .273 .090 .388" .203 .040 324*"
C-Learning .210 .064 .263" .189 .077 264* .194 .049 248*"
E-Agreeability . 146 .066 . 191* .009 .1 10 .009 .075 .058 .082
E—Conscientiousness -.090 .048 -.136 -.036 .078 -.042 -.048 .042 -.O62
C-Competitiveness -.050 .034 -.1 12 .01 l .069 .020 -.023 .032 -.046
C-Altruism -.075 .059 -.1 1 l -.O42 .107 -.043 -.037 .054 -.045
E—Introversion -.048 .039 -.085 .015 .067 .021 -.024 .036 -.036
E-Material Res. -.002 .036 -.005 .065 .075 .095 .022 .035 .037
E—Physical Res. .010 .042 .018 -.063 .067 -.088 -.016 .037 -.025
E—Neuroticism -.012 .040 -.019 .074 .075 .092 .015 .038 .022
E-Openness to Exp. .055 .054 .083 -.091 .090 -.107 .019 .048 .025
Total 3’ .186" .261 205*“
Total a” change .056“ .047 045*"
Model 3: E+C+S
(Constant) 1.559 .603 o .789 1.068 .835 .517
E—Arousal . 105 .041 .185* .180 .090 .255* .169 .038 269*"
S-Interest Culture .251 .062 362*" .361 .092 446*" .333 .050 439*"
C-Altruism -.116 .057 -.171* -.129 .104 -.131 -.111 .051 -.136*
E—Agreeability . 144 .065 .188* .029 .103 .027 .080 .05 5 .087
E-Conscientiousness -.O76 .047 -.1 14 -.063 .076 -.073 -.055 .040 -.072
E—Physical Res. -.017 .041 -.030 —.075 .065 -.106 -.041 .036 -.064
C-Learning .079 .070 .099 .070 .080 .097 .049 .050 .063
S-Fashion Innov. .022 .096 .019 .136 .178 .079 .054 .087 .037
E—Material Res. -.002 .038 -.004 .028 .081 .042 .014 .036 .024
C-Competitiveness -.027 .033 -.060 .070 .066 .129 .01 1 .031 .022
E-Neuroticism .004 .040 .007 .027 .072 .034 .010 .036 .014
E-Openness to Exp. .043 .053 .065 -.119 .087 -.140 -.011 .046 -.014
S-Uniqueness -.096 .105 -.071 .030 .186 .016 -.019 .093 -.012
E-Introversion -.033 .038 -.058 .056 .065 .076 .003 .034 ' .004
Total R2 253*" .369" 311*“
39m 1:2 change 067*" .109" .106***

 

l"p.<.05, l""'p<.01, **"‘p<.001;DV: Tropical Adventure Experiences/ ATP; E=E1ernental trait; C=Compound
trait; S=Situationa1 trait; ST=Surface trait.

171

A summary of only significant results for tropical adventure experiences for the

HAT, SAT and all travelers is provided in Table 56.

 

 

Table 56
Significant Hierarchical Regression Results: S T - Tropical Adventure Experiences/A T P
Hard Soft
Adventure Adventure All
Travelers Travelers Travelers
E-Need for Arousal E-Need for Arousal E-Need for Arousal
(,6 = .185, p < .05) (,6 == .255,p < .05) (fl = .269,p < .001)
C-Altruism C-Altruism
(,6=-.171,p<.05) (fl=-.136,p<.05)
(negative relationship) (negative relationship)
S-Interest in Cultural S-Interest in Cultural S-Interest in Cultural
experiences Experiences Experiences
(fl= .362,p< .001) (,B= .446,p< .001) (,8= .439,p< .001)
E—Agreeability
(fl = .188,p < .05)
R2 = .253 R2 = .369 R2 = .311

 

E=Elemental trait; C=Compound trait; S=Situational trait; S T==Surface trait; Adjusted RTpresented.

Traditional outdoor adventure experiences. In the third set of hierarchical
regression analyses, the dependent variable was traditional outdoor adventure experiences
(a measure of ATP). Results provided in Table 57 and a summary in Table 58. As before,

multicollinearity was not as issue with this analysis.

All travelers. The first model contained the elemental and was significant (R2 =
.22, p < .01). In this model, the elemental trait need for arousal (,8 = .438, p < .001) was
the only statistically significant predictor of traditional outdoor adventure experiences.
When the compound traits were added in the second model, no significant increase in
variance explained was observed. Finally, in Model 3, the situational traits significantly
increased the variance accounted for (A R2 = .03, p < .001). In this complete hierarchical

model, significant predictors of traditional outdoor adventure experiences were the

172

elemental trait need for arousal (fl = .356, p < .001) and the situational trait interest in
cultural experiences (,6 = .203, p < .01).

Soft adventure travelers. The first model contained the elemental traits, the
compound traits were added in the second model, and the situational traits were added to
the third. Model 1 was significant (R2 = .25, p < .001). The elemental trait need for
arousal (,8 = .428, p < .001) was the single statistically significant predictor of traditional
outdoor adventure experiences for the soft adventure traveler subgroup. When the
compound traits were added in Model 2, no significant increase in variance accounted for
was obtained. Finally, in Model 3 the situational traits did not significantly increase the
explanatory power of the regression model.

Hard adventure travelers. The final hierarchical regression tested the relationship
of elemental, compound and situational traits to traditional outdoor adventure experiences
among HATS.

Model 1 which contained only the elemental traits was significant (R2 = .19, p <
.001). The elemental traits need for arousal (,6 = .369, p < .001) and openness to
experience (fl = .152, p < .05) were statistically significant predictors of traditional
outdoor adventure experiences for HATS. When the compound traits of, competitiveness,

altruism, and need for learning were added in Model 2, no significant increase in variance
explained was obtained. Finally, in Model 3, situational traits, increased the variance
explained (A R2 = .06, p < .01). In this final model, significant predictors of traditional
outdoor adventure experiences were the elemental traits need for arousal (,6 = .331, p <

.001) and openness to experience (3 = .170, p < .05), and two situational traits, interest in

173

cultural experiences (fl = .218, p < .05) and fashion leadership (,6 = -.200, p < .05). For

fashion leadership the relationship was negative.

174

 

MKE&5CEEEESCEEC£IT‘tIC

Table 57

Results Hierarchical Regression: ST - Traditional Outdoor Adventure Experiences/A T P

 

 

Hard Soft
Adventure Adventure All
Travelers Travelers Travelers
(n = 205) (n = 119) (N = 324)
Model 1: E b SE b ,B b SE b ,6 b SE b B
(Constant) 2.354 .556 1.033 .816 1.812 .456
E-Arousal .206 .040 369*" .242 .059 .428*** .243 .032 .438***
E—Openness to Exp. .098 .048 .152“ -.065 .068 -.095 .046 .039 .068
E-Neuroticism .008 .039 .013 .096 .059 .150 .038 .033 .060
E-Conscientiousness -.006 .046 -.009 .085 .061 .124 .026 .036 .038
E-Introversion —.030 .038 -.054 -.009 .053 -.016 -.01 8 .031 -.031
E—Physical Res. -.024 .040 -.044 -.008 .053 -.014 -.019 .032 -.033
E—Agreeability -.002 .056 -.002 .064 .080 .076 .01 1 .046 .014
E—Material Res. -.032 .032 -.066 .070 .051 .128 -.002 .027 -.003
Total 32 133*“ 250*" .217"
Model 2: E+C
(Constant) 2.441 .598 .828 .81 1 1.632 .470
E—Arousal .200 .041 357*" .187 .070 .330" .223 .035 .402***
C-Learning -.029 .062 -.037 .126 .060 .221* .054 .042 .079
E-Neuroticism .005 .040 .009 . 1 10 .05 9 .172 .040 .033 .064
C-Competitiveness .027 .033 .062 .053 .054 .123 .030 .028 .067
E—Physical Res. -.027 .041 -.049 -.023 .053 -.041 -.025 .032 -.044
E—Material Res. -.042 .035 -.086 .012 .059 .022 -.021 .030 -.040
E—Openness to Exp. .106 .053 .164“ -.117 .071 -.171 .021 .042 .032
C-Altruism -.006 .057 -.008 .062 .084 .078 .023 .047 .032
E-Conscientiousness -.006 .047 -.009 .060 .062 .088 .018 .037 .026
E—Introversion -.O32 .038 -.057 .009 .053 .016 -.013 .031 -.022
E-Agreeability .010 .065 .013 .019 .086 .023 .002 .051 .002
Total R2 .192 .291 .225
Total chhange .004 .041 .008
Model 3: E+C+S
(Constant) 2.278 .594 .224 .889 1.584 .474
E-Arousal .185 .041 331*" .153 .075 .271* .197 .035 356*"
S-Interest Culture .149 .061 .218“ .097 .076 .150 . 136 .046 .203"
S-Fashion Innov. -.233 .095 -.200* .1 13 .149 .082 —.151 .080 -.1 18
C-Competitiveness .045 .033 .103 .076 .055 .176 .045 .028 .101
E-Neuroticism .025 .039 .043 .099 .060 .155 .039 .033 .062
E-Physical Res. -.026 .041 -.047 -.032 .054 -.056 -.021 .033 -.037
E-Openness to Exp. .110 .052 .170* -.148 .073 -.216* .020 .042 .029
E-Introversion -.031 .038 -.055 .021 .054 .036 -.009 .031 -.016
S-Uniqueness -.036 .104 -.027 .162 .155 .104 .021 .085 .014
C-Learning -.104 .069 —.133 .097 .066 .170 -.009 .046 -.014
E-Conscientiousness -.005 .046 -.007 .064 .063 .093 .007 .036 .010
E-Material Res. .001 .038 .002 -.032 .067 -.059 .006 .033 .011
C-Altruism -.025 .057 -.038 .047 .086 .059 -.007 .047 -.009
E—Agreeability .015 .064 .021 .033 .086 .040 .004 .050 . .005
Total R1 248*" .320 .258W
jptal a” cha_n§e .056" .029 .033"

 

*p<.05, “p<.01, *"p<.001; DV: Traditional Outdoor Adventure Experiences /ATP; E=Elemental trait;
C=Compound trait; S=Situational trait; S T=Surface trait.

175

 

l;

“215:2

To simplify, a summary of only significant results for traditional outdoor

adventure experiences for the HAT, SAT as well as all travelers are provided in Table 5 8.

 

 

Table 58
Significant Hierarchical Regression Results: ST- Traditional Outdoor Adventure
Axperien ces/A T P
Hard Soft
Adventure Adventure All
Travelers Travelers Travelers
E-Need for Arousal E—Need for Arousal
(,B=.331,p<.001) ns (,B=.356,p<.001)
E-Openness to Experience
(fl=.170,p<.05) ns
S-Interest in Cultural S-Interest in Cultural
experiences Experiences
(,B=.218,p<.05) ns (,B=.203,p<.01)
S-Fashion Leadership
(,6 = -.200, p < .05) "3
(negative relationship)
R2 = .243 ns R2 = .258

 

E=Elemental trait; C=Compound trait; S=Situational trait; ST =Surface trait; Adjusted R2 presented.

Extreme adventure experiences. In fourth and final of hierarchical regression
analyses, the dependent variable was extreme adventure experiences (a measure of ATP).
In all other respects this analysis was identical to the previous two analyses. Results are
described in Table 59 for all travelers, as well as both HATS and SATS. VIP and
condition index values indicated that multicollinearity was not an issue in these analyses
(Hair et al., 1998).

All travelers. The first model contained the elemental traits, the compound traits
were added in the second model, and the situational traits were added to the third. Model
1 was significant (R2 = .28, p < .001) and need for arousal (p = .475, p < .001) and
material needs (fl = .143, p < .01) were the only statistically significant predictors of

extreme adventure experiences. When the compound traits were added in Model 2, there

176

was no significant increase in the variance. In Model 3, however, inclusion of the
situational traits significantly increased the variance explained by the model (A R2 = .02,
p < .01). In this final model, significant predictors of extreme adventure experiences were
the elemental trait need for arousal (,6 = .460, p < .001) and the situational trait interest in
cultural experiences (,6 = .178, p < .01).

Soft adventure travelers. The first model contained the elemental traits, the
compound traits were added in the second model, and the situational traits were added to
the third. Model 1 was significant (R2 = .25, p < .001), however the second and third
models failed to increase the regression equation’s predictive ability. In the first (and only
significant) model, the elemental trait need for arousal (6 = .445, p < .001) was the single
statistically significant predictors of extreme adventure experiences for SATS.

Hard adventure travelers. Similar to findings for SATS, only the first hierarchical
model was significantly predictive of HATS propensity to engage in extreme adventure
experiences. In Model 1 (R2 = .27, p < .001) the elemental traits need for arousal (p =
.454, p < .001) and material needs (,6 = .186, p < .01) were statistically significant

predictors of extreme adventure experiences for the HAT subgroup.

177

Table 59

Results Hierarchical Regression Analyses: ST -Extreme Adventure Experiences/A T P

 

 

Hard Soft

Adventure Adventure All

Travelers Travelers Travelers

L= 205) (n=119) (N=324)
Modell:E b SE 6 b SE 6 b SE 6
(Constant) -.273 .587 .822 .669 .048 .444
E-Arousal .281 .042 454*" .205 .049 445*“ .266 .031 .475"M
E-Material Res. .100 .034 .186“ .050 .042 .111 .076 .026 .143"
E—Conscientiousness -.046 .048 -.063 -.O60 .050 -.107 -.051 .035 -.075
E-Openness to Exp. .046 .050 .063 -.016 .056 -.029 .034 .038 .051
E-Neuroticism .054 .041 .083 -.042 .048 -.079 .024 .032 .039
E-Agreeability -.009 .059 -.011 .051 .067 .072 .008 .045 .010
E-Introversion .018 .040 .030 -.036 .044 -.075 -.005 .030 -.008
E-Physical Res. -.003 .042 -.005 -.013 .043 -.028 -.005 .031 -.008
Totallr2 273*" 248*" 280*"
Model 2: E+C
(Constant) -.091 .630 .774 .662 .106 .459
E-Arousal .286 .043 461*" .125 .058 .271 .260 .034 .465***
E-Material Res. .104 .037 .193" -.003 .048 -.006 .070 .030 .133*
E-Conscientiousness -.041 .050 -.057 -.052 .050 -.093 -.050 .036 .072
E-Openness to Exp. .065 .055 .091 -022 .058 -.040 .043 .041 .064
C-Competitiveness -.002 .035 -.005 112 .044 .318“ .021 .027 .047
E-Neuroticism .053 .042 .081 -.048 .048 -.093 .021 .032 .034
C-Learning -.048 .066 -.055 .030 .049 .064 -.020 .041 -.029
E-Agreeability .002 .068 .002 .048 .072 .069 .022 .050 .027
C-Altruism -.018 .060 -.024 -.007 .069 -.011 -.019 .046 -025
E-Introversion .015 .040 .024 -.028 .044 -.057 -.006 .030 -010
E-Physical Res. .000 .043 -.001 -.013 .043 -.027 -.005 .032 -.008
Total”:2 .276 .295 .283
Total R2 change .003 .047 .003
Model 3: E+C+S
(Constant) -.397 .640 .247 .715 -.145 .465
E-Arousal .290 .044 467*" .106 .061 .230" .257 .034 .460**"'
S-InterestCulture .149 .065 .198* .114 .061 .216 .120 .045 .178"
S-Fashionlnnov. .075 .101 .058 .216 .120 .190 .142 .078 .110
E-Material Res. .092 .041 .171* -.048 .054 -.107 .049 .032 .092
C-Learning -.128 .074 -.147 .002 .053 .005 -.068 .045 -.097
E—Conscientiousness -.030 .050 -042 -.045 .051 -.081 -.047 .036 «068
C-Competitiveness .012 .036 .024 .134 .044 .380 .032 .028 .070
C-Altruism -.043 .061 -.058 -.029 .070 -.046 -.045 .046 -.O62
S-Uniqueness -.039 .111 -.026 -.015 .124 -.011 -.064 .083 -.044
E-Physical Res. -.023 .044 -.O37 -.032 .044 -.069 -.024 .032 --041
E-openness to Exp. .054 .056 .075 -.044 .059 -.080 028 .041 ~047-
E-Neuroticism .059 .042 .090 -.052 .048 -.100 .020 .032 .33:
E-Agreeability -.003 .069 -.004 .056 .071 .081 .025 .050 ‘.
E-Introversion .027 .040 .043 -.003 .044 -.007 .009 .031" .015
Totallt2 .297 .343 .306M
gardening. .002 .047 -023

 

*P<-05. "P<-01, ***p<.001; DV: Extreme Adventure Experiences/ATP; E=Elemental trait; C=Compound

trait; S=Situational trait; S T =Surface trait.

178

 

12

[CD

(Tilt:

A summary of only significant results for the HAT, SAT as well as all travelers is

 

 

provided in Table 60.
Table 60
Significant Hierarchical Regression Results: S T -Extreme Adventure Activities/A T P
Hard Soft
Adventure Adventure All
Travelers Travelers Travelers
E-Need for Arousal
"5 "3 (6=.460,p<.001)
S-Interest in Cultural
ns ns Experiences
(6 = .l78,p < .01)
ns ns R2 = .306

 

E=Elemental trait; C=Compound trait; S=Situational trait; ST =

Summary of Hypotheses

Surface trait; Adjusted R2 presented.

An overview of the results of the hypotheses testing is provided in Table 61.

 

 

Table 61
fiverview of Hypotheses
Ultimate Tropical Traditional Extreme
Destination Adventure Outdoor Adventure
g Hypothesis Experiences Experiences Recreation Experiences
ALL/SAT ALL/SAT
H] E: Need for arousal /HAT /HAT ALL/HAT ALL
Hz E: Agreeability ns HAT ns ns
H3 C: Competitiveness ns ns ns M
H4 C: Altruism ns ALLl/HATl ns ns
H5 C: Need for learning ns ns n3 '15
ALL/SAT ALL/SAT
H6 5: Interest in cultural experiences /HAT /I-IAT ALL/HAT ALL
7 , . ns '13
H S. Need for unrqueness ns "3
1
i S: Fashion leadership ALL/SAT ns HAT ns

 

179

. 1 . . .
E=Elemental trait; C=Compound trait; S=Situational trait; S T =Surface tralt; Negative relationship.

C011

Hypothesis one. The first hypothesis proposed that the elemental trait need for
arousal will positively influence ATP. Four hierarchical regressions were estimated to
test the hypothesis with the sets of indicators of travel propensity or the surface traits.

Need for arousal significantly influenced all of the dependent variables (ultimate
destination experiences, tropical adventure experiences, traditional outdoor adventure
experiences, and extreme adventure experiences) for all travelers. For the HAT
subgroup, need for arousal significantly influenced three out of the four dependent
variables. In the case of the dependent variable extreme adventure experiences, need for
arousal was a significant predictor only for all travelers, but not the HAT and SAT
subgroups. For SATS, need for arousal was a significant predictor for two of the four
dependent variables, ultimate destination experiences and tropical adventure experiences.

Data were consistent with the hypothesis, in that a respondent’s need for arousal
was a significant predictor for the surface trait ATP measured by the four travel
experience types. Therefore it is concluded need for arousal has a positive influence on
ATP.

Hypothesis two. The second hypothesis proposed that the elemental trait
agreeability will positively influence ATP. Agreeability was not a significant predictor of
ultimate destination experiences, extreme adventure experiences or traditional outdoor
adventure experiences. Agreeability was only a predictor in the case of tropical adventure
GXperiences and it was only predictive for the HAT subgroup. Therefore the data only
partially supported the hypothesis. _

Hypothesis three. The third hypothesis speculated that the compound trait

Competitiveness would positively influence ATP. Findings from hierarchical regressrons

180

estimated that competitiveness was not a significant predictor for any of the four types of
adventure travel experiences. Data were not consistent with the hypothesis;
competitiveness was not a significant predictor for any of the four travel experience types
(i.e., ATP). Thus, hypothesis three was not supported.

Hypothesis four. The fourth hypothesis stated that the compound trait altruism
would demonstrate a positive influence on ATP. Altruism was not a significant predictor
of ultimate destination experiences, extreme adventure experiences or traditional outdoor
adventure experiences. However, altruism was a significant predictor of tropical
adventure experiences for all travelers and the HAT subgroup, in both cases a negative
relationship. As such, data were partially consistent with the hypothesis and therefore it
was concluded hypothesis four partially supported ATP.

Hypothesis five. The fifth hypothesis was that respondents’ need for learning, a
compound trait, would positively influence their ATP. No significant relationship was
observed between need for learning in the hierarchical regressions with ultimate
destination experiences, tropical adventure experiences, extreme adventure experiences,
and traditional outdoor adventure experiences as the dependent variables. Therefore,
hypothesis five was not supported.

Hypothesis six. According to Hypothesis 6, the situational trait interest in
cultural experiences was expected to positively influence ATP. When ultimate
destination experiences and tropical adventure experiences were the measure of travel
prOpensity, interest in cultural experiences was a significant predictor for all travelers and
the HAT and SAT groups. Interest in cultural experiences was a significant predictor for

all travelers and HATS, but not SATS, when the measure of ATP was traditional outdoor

181

 

“I

fl“
r

mag,

experiences. For extreme adventure experiences, interest in cultural experiences was a
significant predictor for all travelers but not for the HAT or HAT subgroups. Data
supported the hypothesis that interest in cultural experiences would positively influence
ATP. Hypothesis Six was supported.

Hypothesis seven. Hypothesis seven was not supported. This hypothesis posited
that travelers’ need for uniqueness, a situational trait, would positively influence ATP. As
no significant associations were observed in the regressions this hypothesis was not
supported.

Hypothesis eight. Hypothesis 8 speculated that the situational trait fashion
leadership would positively influence ATP. Fashion leadership was not a significant
predictor of tropical adventure or extreme adventure experiences for any segment of
travelers. Fashion leadership was a significant predictor of traditional outdoor adventure
experiences although only for the HAT group, and the relationship was negative. In
contrast, fashion leadership was a significant predictor of ultimate destination
experiences for all travelers and the SAT group, again a negative relationship. Thus, it
may be concluded that data partially supported Hypothesis 8.

The results revealed that two elemental traits were predictive of ATP, which were
not hypothesized. In addition to testing the eight hypotheses, using the final model,
Model 3 these Significant relationships were also found: Openness to experience (6 =
.170, p < .05) was a significant predictor of traditional outdoor recreation

experiences/ATP for the HAT group and physical resources was a Shown to be a
Significant predicator (negative relationship) of ultimate destination experiences/ATP for

all travelers (p = -.162, p < .01), HATS ([3 = -.143, p < .05), and SATS (6 = -.205, p < .05).

182

Summary

Chapter IV provided an overview of data analysis including a description of the
sample and results of hypotheses testing using hierarchical regression. The following

chapter, Chapter V, presents a summary of results, conclusions and discussion of key

findings, implications and limitations of study findings, as well as recommendations for

future traveler personality research.

183

Chapter V

CONCLUSION

The focus of this study was to explore the psychological forces that motivate and
influence travel-related behavior (Mayo & Jarvis, 1981). Mowen’s (2000) Meta-
Theoretic Model of Motivation and Personality (3M Model) was the organizational
structure employed in an effort to understanding how personality traits impact behavior.
Integrating control theory, evolutionary psychology principles, and elements of

hierarchical trait theories the 3M Model provides a holistic view of how personality
interacts with situations to influence feelings, thoughts, and behaviors. The study
extended Mowen’s (2000) model which has been utilized to examine healthy diet
lifestyles, compulsive buying, bargaining proneness, sports participation, modest living,
and now adventure travel.

Data were collected using a mail questionnaire across four geographical regions
following the US. Census model. A random sample of subscribers from National
Geographic Adventure magazine were drawn using sampling frames representing the
four regions. Questionnaires were mailed in October 2007 and used data collection
strategies recommended by Dillman (2000) in October 2007. From 1,000 surveys, 339
were returned and completed for an overall response rate of 34%. After the mail data
collection was completed, a non-response survey was sent out in January 2008 to assess
potential bias in the dataset. Of the 100 non-response surveys, 26 were returned and

complete for an overall response rate of 27%. The results obtained from the non-
respondents were found to be indistinctive from the mail study results, thus there were

assumed to be no major concerns regarding non-response errors in the study.

184

A multi-method approach was used to develop the survey instrument. The survey
was developed based on a literature review of existing research related to adventure
recreation and tourism, consumer behavior, and personality and modified based upon
input obtained from a panel interview with adventure industry leaders. The result was a
questionnaire combining previous studies and theories in the consumer behavior and

recreation and tourism literature along with key industry perspectives.

The overall statistical analysis included: (1) descriptive statistics to analyze
demographic profile of the sample (gender age, marital status, household composition,
children living in household, ethnicity, education, income and employment status); (2)
travel experience profile (passport ownership, number of domestic/international trips);
number of destinations visited; destinations experienced (grouped according to mass, soft
adventure, and hard adventure destinations); number of activities experienced; travel
activity experience (grouped according to mass, soft adventure, and hard adventure
activities); (3) travel intentions profile (number of domestic/international vacations
respondents intend to take; number of continents/regions respondents plan to visit);
destination intentions (grouped according to mass, soft adventure, and hard adventure
destinations); travel activity intentions (grouped according to mass, sofi adventure, and
hard adventure activities); number of activities plan to experience (grouped according to
mass, soft adventure, and hard adventure activities); destination experience and intentions
combined (grouped according to mass, soft adventure, and hard adventure destinations);

activity experience and intentions combined (grouped according to mass, soft adventure,

and hard adventure activities); (4) pre- and post-travel behavior profile (trip

185

 

Slit

ll

till

tip

file

planning; sources used to book or reserve trips; helpfulness of sources; pre-trip activities,
communication types used, technologies used before, during and after vacation travel,
helpfulness of technology, and lifestyle changes following a vacation trip); (5)
descriptive statistics of the four personality trait levels (elemental, compound, situational,
and surface); (6) factor analysis to determine underlying factors of the surface trait ATP;
and (7) hierarchical regressions to test the hypotheses. Guttman scaling procedure was
employed to categorize respondents into soft/hard categories as a context for

understanding the demographic and travel behavior characteristics of the study sample.

Summary of Results

The study sought to extend past research on consumer behavior and personality in
the context of adventure tourism. Mowen’s (2000) 3M Model was theoretical framework
used to examine the personality traits of adventure travelers, and the key results of the
study are discussed in the following section.

Broadly, this study was designed to examine the application of the 3M Model as a
tool to predict adventure travel propensity (ATP). The study identified four measures of

ATP; (1) ultimate destination experiences; (2) tropical adventure experiences; (3)
extreme adventure experiences; and (4) traditional outdoor adventure experiences.

The first measure of ATP, ultimate destination experiences, are those travel
experiences that involve visiting unique/ exceptional destinations, for example, visiting all
the seven continents; visiting the Seven Wonders of the World; visiting the pyramids in

Egypt; going on a safari in Africa; walking down the ancient paths of China; visiting a

market in India; staying at a hot spring spa in Japan.

186

Next, the ATP measure tropical adventure experiences are those travel
experiences that focus on tropical settings and include activities or experiences such as:
hiking in a rainforest; snorkeling on the Great Barrier Reef; relaxing on the white beaches
of Bora-Bora; and exploring the ancient civilization of Mayans.

The third measure of ATP, traditional outdoor adventure experiences, are those
travel experiences that involved activities or experiences in North America such as:
rafting in the Grand Canyon; camping in Glacier National Park; getting off the beaten
track; and making snow angels in Alaska.

The last measure of ATP, extreme adventure experiences consist of travel
experiences that involve difficult/challenging activities and include experiences such as:
running with the bulls in Spain; rock climbing on every continent; and cage-diving with
Great White Sharks.

The soft/hard adventure typology has been shown to be useful to both academics
and practitioners alike. Thus study respondents were grouped into soft/hard adventure
travel subgroups using a novel application of the approach known as Guttman scaling as
outlined in chapter 111. Results indicated significant differences exist between the hard
adventure traveler (HAT) and soft adventure traveler (SAT) subgroups.

In all measures of ATP, the best regression models were often the “full model.”
For the ultimate destination experience measure of ATP, a combination of elemental,
compound, and situational traits in the final hierarchical model accounted for a range of
28% to 40% of the variance. The trait indicators for all travelers were two elemental

traits, need for arousal and physical/body needs (negative relationship); and two

situational traits, interest in cultural experiences and fashion leadership. These accounted

187

for 32% of the variance in ultimate destination experiences. In the case of HATS the same

traits were predictive of ultimate destination experiences (need for arousal, physical/body
needs-negative relationship, and interest in cultural experiences), with the exception of
fashion leadership. These accounted for 28% of the variance for HATS. For SATS, the
elemental trait need for physical/body needs (negative relationship), and two situational
traits, interest in cultural experiences and fashion leadership (negative relationship)
accounted for 40% of the variance in the ATP measure ultimate destination experiences.

The final hierarchical model for the measure of ATP, tropical adventure

experiences, accounted for a range of 25% to 37% of the variance explained. For all
travelers 31% of the variance was explained, for HATS 25%, and for SATS 37% of the
variance was explained for tropical adventure experiences. The elemental trait need for
arousal, the compound trait altruism (negative relationship), and the Situational trait
interest in cultural experiences accounted for 31% of the variance in tropical adventure
experiences for all travelers. For HATS, the same traits were significant along with
agreeability and accounted for 25% of the variance in the measure of ATP, tropical
adventure experience. In the case of SATS, tropical adventure experiences accounted for
37% of the variance explained with the elemental trait need for arousal and the Situational
trait interest in cultural being the trait indicators.

Finally, for the traditional outdoor adventure experience measure of ATP, a
combination of elemental, compound, and situational traits in the final hierarchical model
accounted for a range of 25% to 26% of the variance. In the case of all travelers the
elemental trait, need for arousal, and the Situational trait, interest in cultural experience,

accounted for 26% of the variance. For the HAT group, need for arousal and cultural

188

experience were significant as well as fashion leadership (negative relationship), which
accounted for 25% of the variance. Results for the SAT group were not significant for
the ATP measure, traditional outdoor adventure experiences.

Results for the ATP measure extreme activity experiences were least predictive.
Results indicated no variance explained for HAT and SAT subgroups; however 31 % of
the variance was explained for all travelers. Consistent with other measures of ATP, the
elemental trait need for arousal and situational trait interest in cultural experiences were

the trait indicators of extreme adventure experiences.

Discussion

In an overview of the results the pattern of relationships between elemental level
traits, compound level traits, situational traits to surface traits need for arousal and
interest in cultural experiences were most consistent predictors of ATP.

Need for arousal predicted ATP. An elemental trait, need for arousal was the
single trait that was predictive across all four indicators of ATP (i.e., ultimate destination
experiences, tropical adventure experiences, traditional outdoor adventure experiences,
and extreme adventure experiences). Formally, the need for arousal is the trait that
measures individual differences in the propensity to seek and raise the level of
stimulation (Mown, 2000). Berlyne (1960) suggested that every individual has a
preferred or “optimum stimulation level” and is motivated to increase or decrease
novelty, a construct closely related to arousal/sensation seeking (Lee & Crompton, 1992),
and complexity if the environmental stimulation is below or above the optimum.

Research on the need for arousal can be traced to the work of Mehrabian and Russell

189

(1974) and Zuckerman ( 1979). The effects of the need for arousal can be explained by
optimum stimulation-level theory. A person’s preferred amount of physiological
activation or arousal is their optimum stimulation level.

Adventure travelers have long been associated with a high desire for stimulation
and excitement. Many adventurers report that adventure brings with it heightened
awareness and a sense of immediacy and aliveness (Swarebrooke et al., 2003). According
to Muller and Cleaver (2000) stimulation is one of the main distinguishing features of
adventure tourism and is characterized by its ability to provide the tourist with relatively
high levels of sensory stimulation. Wahlers and Etzel (1985) investigated the relationship
between vacation activity preferences and individual stimulation needs. Results suggested
that persons seeking stimulation had a preference for vacations characterized by as
innovation and invigoration; whereas, those avoiding stimulation preferred vacations
described as structured and/or enriching. At the extremes, a vacation may consist of
unusual and exotic activities, or relatively repetitive commonplace experiences. Results
of the current study are consistent with previous research.

Similar to the need for arousal trait, the interest in cultural experiences trait was a
common trait across indicators of ATP. Consistent with Sung’s (1997) research, the
primary benefits of adventure travel are improved interpretation of the environment and
culture. Results are also consistent with more recent research by Scott and Mowen (2007)
that indicated a strong relationship between interest in the arts and adventure travel.

Results indicated that the ultimate destination experience indicator of ATP was
best explained with the 3M Model and the extreme adventure experiences indicator was

not well explained, tropical adventure and outdoor recreation experiences were in the

190

middle. These types of experiences provide the settings commonly associated with
adventure and offer opportunities and appeal to both HATS and SATS. The question of
how adventure manifests itself in a tourism context depends on the individual. In
contrast, extreme adventure experiences focus on difficult/challenging activities (e. g.,
cliff diving in Jamaica, cage diving with. great white sharks, running with the bulls in
Spain, rock climbing on every continent). The specificity of these experiences may be the
reason this indicator did little to explain ATP.

With regard to the 3M Model that guided the study, results were mixed. On the
one hand, the model was a usefill organizing framework. Specifically the 3M Model
offers the advantage of a hierarchical approach to personality is that it identifies the basic
elemental and compound traits that account for situational traits and surface level traits.
By going underneath the surface and situational context, the hierarchical model provides
a means for identifying the more basic compound and elemental traits that act as
references for behavior. Irrespective of the indicator of ATP, need for arousal and interest
in cultural experiences were the most consistent predictors of ATP.

Contradicting the results of a study by Scott and Mowen (2007), the trait
agreeability was proposed to have a positive influence on ATP; however it was found
only to be a significant predictor for the HAT group for any of the four indicators of
ATP. Agreeability is defined as “the need to express kindness and sympathy to others”
(Mowen, 2000; p. 29). Research conducted by Scott and Mowen (2007) indicated that
agreeability was significantly related to adventure travel. Adventure travel provides the
Opportunity to travel with friends and or family, therefore those who are more likely to

engage in adventure travel may also be more agreeable. Those who are agreeable might

191

also enjoy meeting new people in a distant country. They may also find it easier to get
along and form relationships with those fi'om different cultures. However, results were
inconsistent with these findings.

Inconsistent with other studies (McClellan, 1985; Tran & Ralston, 2006)
competitiveness was not found to be predictive of ATP. Findings from hierarchical
regressions estimated that competitiveness was not a significant predictor for any of the
four measures of ATP. The finding that the measure of competitiveness was not related to
ATP was inconsistent with previous research. Tran and Ralston (2006) observed
individuals with a high need for achievement preferred tourism experiences that involved
natural settings and were challenging. McClellan’s (1985) theory linking achievement
motivation and overcoming challenge suggested individuals who possess a high need for
achievement will be more competitive and most likely will have a propensity for
adventure travel. It may be that a more specific measure of competitiveness, specific to
travel, rather than the global measure used would be related to adventure travel.
Alternatively, it is possible the measure of adventure travel used in the current study did
not cause respondents to think of hi gh-lisk activities.

Altruism was predictive only of the measure of ATP, tropical adventure
experiences. Results are contrary to research supporting altruism as a motivation to
volunteer and growth of the concept of ‘volunteer tourism’ (Wearing, 2003). According
to Brown and Lehto (2005) volunteer vacations are driven by sense of adventure, desire
for exploration and novelty. The findings may be a result of the altruism measures used.

A measure specific to volunteering on vacation as a surface trait may provide different

results.

192

Inconsistent with other studies, need for learning did not predict ATP. Mowen
(2000) defined the need for learning as “an enduring disposition to seek information
resource” (p. 72). He developed a measure of the need for learning and identified it as a
compound trait. The construct was designed to measure the cross situational
predisposition to obtain information resources. Lack of support for this trait as a predictor
was most surprising. A great deal of literature exists that suggested exploration and
discovery are core components of the adventure process (Swarbrooke et al., 2003).
Addison (1999) argued that education and the hunger to learn from new Situations are key
motivations for both travel and adventure. An expansion and redefinition of adventure
tourism based on an insight model was proposed by Walle (1997). He argued that it is the
quest for insight and knowledge (rather than risk) that underlies adventure tourism.
Research conducted by Sung et al. (1997) also supported educational opportunities as
motives for engaging in adventure travel. Anecdotally, companies offering adventure
travel products and services have consistently emphasized discovery and exploration on
their websites and in collateral materials (e.g., brochures, press releases). The current
results were inconsistent with previous research that has suggested a primary motive for
engaging in adventure travel may be to learn more about other people, places, and
cultures. Perhaps the lack of support is due to the measure of learning employed. A
measure tapping into the discovery and exploration facets of learning may be more
effective in identifying the link between learning and adventure travel experiences.

Historically, risk and challenge have been associated with adventure (Walle,
1997; Weber, 2001). This association has resulted in most research of adventure tourism

focusing primarily on risk and challenge. Research by Sung (1997) and Scott and Mowen

193

(2007) suggested a perspective of adventure which addresses the cultural component of
adventure would be beneficial to adventure industry businesses and organizations.
Findings of the current study supported incorporating interest in cultural experiences as a
predictor of ATP and may allow for the expansion of the adventure travel market
segment to consumers not previously viewed as adventure travelers.

Contradicting the results of previous research linking need for uniqueness and
consumer behavior, the trait need for uniqueness was not a predictor of ATP. Snyder and
Fromkin (197 7) developed the need for uniqueness (NFU) scale and examined
differences between high and low NFU individuals. They proposed that striving for
uniqueness was related to a sense of positive self-esteem. Accordingly, people appear to
derive intrinsic satisfaction from the perception that they are unique, Special, and
separable from “the masses,” which is referred to as “need for uniqueness.” A number of
scales have been developed to measure need for uniqueness (Lynn & Harris, 1997;
Snyder & Fromkin, 1977; Tian et al., 2001). The current research employed the consumer
need for uniqueness (CNFU) scale offered by Tian et al. (2001). Consumers’ need for
uniqueness is defined as an individual’s pursuit of differentness relative to others that is
achieved through the acquisition, utilization, and disposition of consumer’s goods for the
purpose of developing and enhancing one’s personal and social identity (Tian et al.,
2001). According to Tian et a1. (2001) one way of differentiating oneself is through
product purchases, and products and their uses that become classified as being outside the
norm may serve as recognizable symbols of uniqueness (Tian et al., 2001). Status has
been related to the purchase of adventure tourism products. Thus, a product that has

distinct characteristics, such as adventure travel when compared with mass travel, may

194

allow a person to stand out among others and provide the person with a sense of
uniqueness.

Findings were inconsistent with previous research that suggested adventure
travelers have a higher need for uniqueness. An explanation may be the measurement
used to determine uniqueness. Snyder (1992) and Sirgy (1993) called for the
development of a new scale designed specifically to measure the desire for unique
consumer products. Lynn and Hanis (1997) developed the desire for unique consumer
products (DUCP) scale, which may be a more sensitive predictor of consumer behavior.
Alternatively, developing a uniqueness scale specific to travel products may yield
different results.

Similar to research conducted by Scott and Mowen (2007), fashion leadership was
found to influence ATP. However, the current study indicated a negative relationship.
Scott and Mowen (2007) proposed that some individuals may travel to purchase clothing
as well as to see how people dress in other cultures. Findings contradict research linking
adventure tourism and outdoor fashion industry evidenced by the rapid growth of
adventure tourism and adventure outfitters. Sung et al. (1997) noted the rapid growth of
adventure tour operators matched the growth of equipment and gear manufacturers, as
well as commercial outfitters and retailers.

Additionally, the growth of outdoor retailers like North Face, Patagonia, and REI
further suggests the link between fashion and adventure. As suggested by Buckley
(2007), fashion leadership may be a motive for adventure travel because of the
requirements of suitable attire for adventure experiences. Many adventure activities

participants require both technical and non-technical clothing to participate suggesting

195

fashion plays both a technical and non-technical role. However, the current research did
not coincide with these previous studies.

Generally, results of the current study indicated respondents had a high level of
travel experience. Previous research supports that previous travel experience is likely to
affect an individual’s perception of what constitutes adventure travel. Pearce and
Caltabiano (1983) proposed the concept of a travel career ladder. While it has been
further developed (Pearce & Moscardo 1985; Pearce, 1988), adopted (Kim, 1997), and
critiqued (Ryan, 1998), the essential premise of the concept based on Maslow’s need
hierarchy is as follows: Tomists are initially more concerned with fulfilling physiological
and safety needs, but with greater experience they increasingly seek to satisfy higher
level needs such as relationship, self-esteem, and self-actualization. Adventure tourism
has so far been mostly related to an individual’s pursuit of peak experiences, attempting
to address a need for self-actualization. According to the travel career ladder, this would
generally refer to more experienced tourists.

In relation to past travel destination experience, results were consistent with
previous research that examined past international travel experience. Past travel
experience has been found to influence filture behavioral intentions (Goodrich 1978;
Mazursky 1989; Perdue 1985). Mazursky (1989) stated that filture travel is influenced not
only by the extent but also the nature of past travel experience and even suggested that

personal experience may exert more influence on travel decisions than information
acquired from external sources. Sommez and Graefe (1998) examined the influences of
past international travel experience and likelihood of travel to various geographic regions

on their next international vacation trip or avoidance of those regions due to perceived

196

risk. Results revealed that past travel experience to specific regions both increases the
intention to travel there again and decreases the intention to avoid areas, particularly risky
areas. Results of the current study indicated that both HATS and SATS were well-
traveled.

To summarize, the results of this study indicated that Mowen’s (2000) Meta-
Theoretic Model of Motivation and Personality (3M Model) provided a useful framework
for examining tourist behavior. As Mannell (1984) stated, most studies examining
personality as a predictor of leisure behavior have employed general personality
inventories to measure individual differences, failing to provide a theoretical approach to.
identify leisure-specific personality differences to aid in understanding leisure behavior.
The theoretical basis of the 3M Model addresses this shortcoming. Additionally, the
findings of the current study are robust, addressing the criticism NiaS (1985) made of
studies examining the relationship between leisure behavior and personality. The 3M
Model presented a consistent measure of personality, provided definitional clarity in the
variable operalizations, and was based on theory for the inclusion of Specific behaviors
addressing concerns regarding the study of personality and leisure behavior proposed by
Iso-Ahola (1980).

Finally, the findings were consistent with the proposal that traits can be arranged

into a four-level hierarchy. These results supported the use of a hierarchical approach for

understanding the relationships among personality traits.

Implications
Tourism can be defined in behavioral terms as persons who travel away from their

normal residential region for a temporary period of at least one night. Their behavior

197

involves a search for leisure experiences fiom interactions with features or characteristics
of places they choose to visit (Leiper, 1979). Based on Leiper’s statement, it can be
confirmed that understanding tourist consumer behavior is not only of interest to
academics, but also provides practitioners with the knowledge needed for effective
tourism planning and marketing. Results of this research will assist the adventure tourism
industry in optimizing the effectiveness and efficiency of their marketing activities by
providing an understanding of how adventure travelers make their decisions to purchase

or use tourism products.

Typically marketing is seen as a department that comes into play after the product
has been made and the remaining job is to sell it. However, marketing should be seen as
setting the strategic direction for the firm. Over thirty years ago, marketing guru Peter
Drucker stated: “A company has only two basic functions: innovation and marketing.”

According to Kotler (1997) the marketing concept holds that the key to achieving
organizational goals consists of being more effective than competitors in integrating
marketing activities toward determining and satisfying the needs and wants of target
markets. The marketing concept rests on four pillars: target market, customer needs,
integrated marketing, and profitability.

Effective target marketing requires breaking a market into segments and then
concentrating marketing efforts on one or a few key segments. Target marketing can be
the key to a small business’s success. It makes the promotion, pricing and distribution of
products and/or services easier and more cost-effective by providing a focus for all

marketing activities.

198

Based on the results of this study, adventure travel industry marketers and
managers should take the following steps: ( 1) position and differentiate products based
upon dominate personality or psychographic characteristics of the target market; (2) scan
the environment to identify dominant cultural values of the target market; (3) use market
research to identify the personality, self-concept and psychographic characteristics that
distinguish the target market; (4) develop promotions to be consistent with dominant

personality characteristics of the target market - create products that fulfill the
motivational needs of the target (e.g., high risk products for high need for arousal group);
and (5) use personality and psychographics to identify segments of consumers to target,
such as culturally focused adventures for interest in cultural experiences group.

The results of this study allow adventure travel industry marketers and managers
to optimize the effectiveness and efficiency of marketing activities, by providing an
understanding of how consumers make their decisions to purchase or use tourism
products. Further, an understanding of adventure travel behavior patterns, gives
marketers and managers the information they need to intervene in the process and obtain
desired results. More importantly, they can persuade consumers to choose certain
products, which have been designed more effectively to meet particular needs and wants.

Results of this study have important implications for both future research studies
and management of the adventure travel industry. By providing a comprehensive analysis

of the adventure travel market by using personality as a more effect means of segmenting
the market, this study is expected to make a unique contribution to future adventure travel
marketing research. The hypothesized relationship between personality and adventure

travel behavior proposed and examined in this study may need additional thought and

199

development, and could be improved with greater reflection into the study findings. For
instance, traveler’s likelihood of participating in different adventure travel experiences
was predicted. Personality was recognized as a way to tailor marketing opportunities
about the adventure travel market.

Although not always supported by empirical research, studies of nature based
tourism (e. g., adventure, nature tourism, ecotourism) have suggested that adventure that
these travelers are likely to be males, middle aged, well educated, and affluent
(Loverseed, 1997; TIA, 1998; Wight, 1996). This general profile appears to describe
adventure travelers in this study. A 2006 study of affluent leisure travelers in the US.
conducted by TIA indicated that affluent leisure travelers accounted for 34.8 million
leisure household trips with vacation spending averaging more than $2,100 per trip.
Defining affluent as households with total incomes of $125,000 or more, almost a quarter
(24%) of respondents in the current study had household incomes of over $150,000
making them part of the affluent segment. Average household incomes of affluent leisure
travelers are $163,100. Affluent travelers represent a lucrative segment for adventure
travel businesses to target. Nearly a third of affluent travelers age 55+ spend $1,000 or
more per leisure trip compared to 19 percent among affluent leisure travelers age 18-34.

Compared with the more than decade old Adventure Travel report (1998) the
sample of this study appears to be younger and have fewer children living in the
household. Overall, adventure travelers are distinctive in some demographic and
socioeconomic characteristics, and therefore, have specific needs and demands for travel

and tourism products and services. The profile of adventure travelers’ identified in this

200

study can provide valuable information for adventure industry managers and marketers in
addressing the most salient managerial issue: who are adventure travelers?

In addition to traditional demographic and socioeconomic characteristics,
examinations of past travel experience and intentions as well as pre and post trip
behavior can provide new dimensions in understanding the specific behavior of adventure
travelers; what they do on an adventure travel trip and how? The inclusion of adventure
travel behavior provided additional insights as to how adventure travel is perceived by
travel, suggesting to managers and marketers how the adventure travel products should
be developed in terms of their ingredients in order to improve customer appeal. The
relative importance of trip related factors to demographic or socioeconomic
characteristics across traveler type also suggests that the inclusion of more behavioral
variables such as travel motivation might yield significant results in determining
traveler’s likelihood of participating in adventure trip types.

Classification of adventure traveler subgroups provides valuable insight for
managers and marketers as to how they pinpoint their target segments for effective use of
marketing resources. For marketers and adventure travel industry providers, it is
recommended that they should pay extensive attention to travelers who have a high need
for arousal and an interest in cultural experiences. This insight allows marketers and
managers to target at a particular time with a particular tourism product. Clearly, this
information is crucial to make marketing activity more successful.

As discussed earlier in the results of the hierarchical regression, all four adventure
travel experience types appeared to be related to both the HAT and SAT subgroups. The

HATS are significantly distinctive from SATS as to the travel experiences they dream of

201

or adventure travel propensity. Likewise a strong contrast is shown between the SAT and
HAT types providing empirical evidence for marketers as to how they enhance different
levels of involvement specific to each target segment.

Adventure travel marketers should also recognize that the nature of the risk
element has to be carefully attached to the notion of “perceived” risk rather than to just
the provision of “dangerous, risky" setting as in traditional leisure or recreation studies
(Sung et al., 1997). This has been consistent in the results of this study suggesting that the
amount as well as the level of risk involved in adventure travel products and services
should be clearly controlled to treat different adventure trips or traveler groups. For the
soft nature type, for example the amount of risk should be controlled at a minimum level,
whereas a certain degree of risk is essential for the ‘hard challenge’ trips.

As previously mentioned, travel and tourism have largely adopted past leisure and
recreation studies to construct initial conceptual frameworks, and this has been the case in
adventure travel (Sung et al., 1997). It appears that there are certain overlaps as well as
differences in three fields, such that no single measurement has ever been able to analyze
leisure, recreation, and tourism in one context. What needs to be understood is that
adventure travel is highly activity-oriented segment emphasizing sophisticated levels of
experience and expertise rather than traditional risk and motivation theories.

According to Swarbrooke and Homer (1999), consumer behavior is the
foundation for all marketing activity carried out to develop, promote and sell tourism
products. An understanding of behavior patterns allows marketers and managers to

manipulate the process in order to obtain the results that we want giving them the ability

to know how to target at a particular time with a particular tourism product. More

202

importantly, consumers can be persuaded to choose certain products, which have been
designed more effectively to meet their particular needs and wants. An understanding of
consumer behavior is therefore crucial to make marketing activity more successful.
Classifying tourists according to their personality traits gives marketing managers the
ability to develop promotional themes linking the personality of their brand to that of the
consmner, essentially linking the product personality to consumer personality.

Although the conceptual linkage between tourism and consumer behavior is yet to
be fully explored, better comprehension of these constructs helps marketers understand
their role particularly in the formation of strategy formulation process. Successful
marketing practices must be based on reliable knowledge of consumer behavior, and
growing comprehension of tourist behavior will likely shed some light on the
consumption of tourism products and services, and the mechanism that underlie the
economics of organizations.

Adventure travel represents an interesting form of consumer behavior that has
seen tremendous grth as a segment of the tourism industry. A hierarchical model of
personality was used to identify the personality traits predictive of a broad measure of
adventure travel. Types of travel are distinguished, and trait predictors of each of the

constructs were examined. The results reveal that the motivational network of traits is

different for the divergent types of travel interest.

Limitation of Findings
The structural limitations of this study included: the limited amount of literature

directly associated with personality and adventure travel. Adventure is often equated with

risk taking and it is assumed that individuals are motivated to participate in adventurous

203

activities to experience risk (Ewert & Hollenhorst, 1989; Meier 1978; Miles 1978; Walle,
1997; Yerkes 1985). A focus on risk taking limits the concept of adventure which can be
generalized to deal with diverse phenomena (Ewert 1987). As a result, a broader
perspective of “adventure” which considers other behaviors and motivations have not
been fully explored (Walle, 1997). Viewing adventure only from the risk viewpoint has
prevented more general models of adventure tourism and their marketing implications
from being fully explored. As a consequence, consumer behavior theories were adopted
to examine adventure travel behavior. It was noted earlier that literature explaining the
relationship between personality and tourism behavior has been inconclusive. Academics
have attempted to explain tourist behavior by developing typologies of tourists and their
behaviors; however the underlying psychological traits that contribute to propensity
toward adventure travel behavior have not been sufficiently explored.

Issues relating to the measurement of some instruments and scales may also invite
additional discussion. One of the limitations was constructing an index to categorize
respondents according to soft versus hard adventure travel. Previous research used cluster
analysis (Sung, 2004) to determine segments. The advantage of this approach is that it is
data driven; the disadvantage is also that it is data driven. The basic alternative to that
approach is to use judgment and the extant literature to select a subset of the variables
included in a survey to create an index (Bloch, Sherrell, & Ridgway, 1986).

Guttman scaling approach seemed an interesting alternative and was used to
categorize respondents according to the soft versus hard continuum. In retrospect,
Mokken scaling may have been a more appropriate analysis method for assessing the

unidimensionality of a set of items. As a nonparametric stochastic version of Guttman

204

scale analysis, the Mokken model provides a useful starting point in scale construction
since it does not impose severe restrictions on the functional form of the item trace line
like Guttman scaling. Mokken requires only that the item trace lines are monotonically
increasing and that they do not cross. Mokken scale analysis can be applied usefully if a
"dominance" relation is assured between the underlying trait (e. g., adventurousness) and
the item scores rather than a "preference" relation. Mokken scale analysis can be applied
usefully if a "dominance" relation between the underlying trait (e. g., adventurousness)
and the item scores exists. To illustrate, a set of hypothesized dominance items in tourism
could be (1) "I have seen Niagara F alls", (2) "I took a tour down Niagara Falls", and (3)
"I walked on a rope above Niagara Falls." A dominance relation means that the more
adventurous a respondent is, the greater the probability that he or she endorses an
activity.

With regard to research methodology, sampling of subjects from National
Geographic Adventure magazine’s subscription list might become an issue in terms of
their representativeness. It was noted earlier that the subjects (N=3 39) were drawn from a
priori known group, having similar interest in adventure travel no matter whether they
had been on an adventure trip. As subscribers to a magazine focused on adventure,
subjects were considered more actively involved in adventure travel. As a result, they
may have unique group characteristics or travel behavior associated with adventure travel
than the general population. Nevertheless, the target population of this study was not the

general public in the US; rather it was adventure travelers who would be interested in
taking an adventure trip. In extending results to the general public, the extension or

generalization of the study results should be treated with a degree of caution.

205

Next, the survey instrument used to assess biases in the dataset from non-
responders included a limited number of questions due to restricted funds and space
constraints in the questionnaire layout. As a result, several constructs specific to the study
problem as well as questions addressing demographics, were not included in the non-
response survey. Finally, the study was limited by a low survey response rate due to the

length of the survey and declining mail survey rates in the US. (Dillman, 2000).

Future Research

The study was somewhat exploratory in that it examined personality traits of
adventure travelers. Further research is needed to understand the role personality plays in
tourist behavior examining various types of tourists and exploring different traits.
Replicating the research with a general population sample may offer insights into the
differences between adventure travelers and mass travelers.

Another area for firture research involves investigating the motivational profile of
individuations who participate in different adventure activities. That is, is the profile
different for kayakers as compared to hikers, walkers, or cyclists? Next, future studies
should improve measurements of compound and situational traits as well as types of
adventure experiences.

Future researchers need to improve the measurement of adventure travel
propensity. The current study factor analyzed a list of dream travel experiences in order
to identify indicators of ATP. However, a more effective tool may be an index where
individuals would have an adventurousness “score.” Development of an adventure travel

index would emphasize different aspects of adventure and result in a more realizable

206

format for categorization the adventure travel market. Use of the traditional typology of
soft versus hard adventure travel fails to address that individuals participate in both types
of travel at different times for different reasons. An adventure travel index would address
varied motivations for participation.

While the current study has demonstrated the positive relationship between
personality traits and adventure travel behavior, this study failed to address specific
benefits adventure travelers seek. from their experiences. Therefore, future studies should
include a collection of qualitative data that would provide more details information
regarding specific benefits sought from adventure travel experiences.

The current study drew participants from a National Geographic Adventure
magazine subscriber list. It can be inferred that this group is representative of adventure
travelers; however adventure travelers who do not subscribe are not accounted for. To
obtain a more accurate understanding of the personality traits predictive of adventure
travel propensity a general population sample is suggested. This study is by no means
definitive; it is merely a contribution to what will hopefully be ever-increasing body of

knowledge in the area of personality and adventure tourism.

Final Thoughts
The current study further extended and tested a Meta-Theoretic Model of
Motivation and Personality (3M Model). In general, testing the 3M Model in a tourism
context further validated the model. Consistent with other studies (Scott & Mowen, 2007;
Todd & Mowen, 2005; Mowen, 2000) hierarchical regression models explained

personality and traits predictive of ATP.

207

Several criteria were proposed for evaluating the 3M Model (Mowen, 2000). First, it
should account for more variance in behavior than traditional models of personality. The
model should account for more than five to ten percent of the variance in measures of
behavioral tendencies to act within specific domains of behavior. Next, the 3M Model
should have practical value. According to one of the fathers of social psychology, Kurt
Lewin, “there is nothing so practical as a good theory” (p. 239). Unless the model shows
promise for applied uses by managers and public-policy makers, it will have not made a
contribution to the literature. Third, does the theory add parsimony to the literature? If
the model cannot identify a limited set of individual differences variables that influence
behavior across a diverse range of situations, it will not be successful. Finally, it should
generate new knowledge.

Previous personality theories represent the basis for integrative models of
personality and motivation. Today, the focus is on developing very tight, mid-range
theories good at identifying relationships among a limited set of constructs within a
single domain of behavior. The time is right for consumer researchers to begin creating
competing models of personality that link the many piecemeal developed constructs
available today into a coherent general structure that shows the relationship among traits,

situations, and the enduring behavioral tendencies of consumers.

208

APPENDICES

209

Appendix A: Survey Instrument

210

The survey has four sections: Section 1 asks about past recreation and travel experiences
and future recreation and travel plans. Section 2 asks about different personality
characteristics. Section 3 asks about travel information needs, pre-trip planning, and
post-travel behavior. Finally, Section 4 asks general demographic information that will
be used for descriptive purposes only. The survey should take about 20-25 minutes to
complete. Thank you in advance for your participation!

Please return your completed questionnaire in the enclosed postage paid envelope to:
Michigan State University-Travel Survey; 131 Natural Resources Building;
East Lansing, MI 48824-1222

 

Sm l().\' l: RI-fif"Rli:\'l‘l()T\‘ AN!) 'l‘R,~\VlaL Exmrumcrs AND lwamasrs

1. Do you currently hold a valid US. passport? Please C] no
mark one.
2. If yes, at what age did you first apply? years (e.g., 21 years)

[:1 yes

3. Thinking of vacation travel only, indicate those continents/regions you visited on a
past trip or plan to visit in the future. Please mark for each column.
Plan to travel

Have traveled to to

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

in the past in the future
Africa - _ D D
Antarctica D D
. Arctic , i E] D
Australia D D
' Caribbean (e.g., Aruba, Cuba, Dominican Republic, El 1:]
Jamaica)
Central America (e.g., Belize, Costa Rica, Guatemala, 1:] Cl
‘ Honduras)
Eentral Europe (e.g., Austria, Czech Republic, Poland) D D
Eastern Europe (e. g., Russian Federation, Ukraine) D E]
Mexico _ D D
__Middle East (e. g., Israel, Jordan, Pakistan, Turkey) D D
,_New Zealand D D
jorth America (Canada or US.) D D
Aorth Asia (e.g., China, Hong KMPMLKOIBEI) D E
South America (e.g., Argentina, Brazil, Chile, Cl El
Ecuador)
fiqumracific (e.g., Fiji, Samoa, Tahiti) D D
South and Southeast Asia (e. g., Cambodia, India, El [3
Malaysia)
7 Westem Europfie' (e.g., France, Germany, Italy, United E] El
5 Kingdom) A , . _

211

4. How many vacations have you taken in the U.S./Canada____ International“
past 3 years?

5. How many vacations do you plan to take in U.S./Canada___ Intemational___
the next 3 years?

6. People plan vacation trips in different ways. Please circle your level of agreement

with the following, where 1 =Strongly Disagree and 5 =Strongly Agree.
Strongly Neither Agree Agree Strongly

 

 

 

Disagree Disagree nor Disagge Agree
I plan my entire trip well in advance 1 2 3 4 5
I plan most of my vacations before I
leave and then fill in the details after 1 2 3 4 5
I arrive -
l I plan most of my vacation once I 1 2 3 4 5
reach mydestination

 

 

7. From the list of recreation and travel activities provided, indicate those you have
experienced or plan to experience in the future. Please mark 13] one for each
column.

Already experienced
during my travels in
the

Plan to experience during my
travels in the future

        

    

 

 

 

 

 

 

 

 

 

 

 

 

 

Nightlife/visiting night clubs/dancing
ziéfiéérfvfih ' {wildlife/bird watching

 

 

   

’— /dance U D
' local festivals/fairs D D
l ' events D U
D C]
E] D
Boating D D
LGémm - D E]
Cave exploring/spelunking [3 D
Cifii‘toursIShort guided excursions D U
Climbing - mountain/rock/ice D D
Getting to know local people D D
-'Gélfingltennis D D
Hiking D D
Huntiir'glfiShing D U
Kayakinglcanoeing D D
Mountambrkrng U D
C1 C1
D . . u, _.
D D

 

    

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t ‘-

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212

Scuba ' '

Swimming/sunbathing/beach

friends or relatives
'cal
local/state/national
museums/ cries
laces of historical interest

theme/amusement
zoos ,
while on vacation

[3
E]
El
Cl
C]
, [:1
Cl
Cl
C]
C]
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C]

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describe

SEC'HON 2: PERSONALI'I‘Y CHARACTERISTICS AND TRAVEL INTERESTS &
PREFERENCES

 

8. People have different personalities. How often do these characteristics describe
how you see yourself in everyday life? Please circle one for each statement, where
I =Never and 9=Always.

Never Always

iashfirl '

.. Introverted

LQuiet ‘ .V -

_§hy

Qrecise " '_ ,

ifficient

,Qrganized

_Qrderly

:Qreativi ' U

imaginative

Jind novel solutions .-

Qriginal

:[ender hearted
Agreeable
Tjgifthearred

. Kind

MoOdy

 

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Temperamentjal‘ , , 1 _ 2 W 3 , 4 5 , 6 7 fl 8 , 9
:‘EmOtional ... f _ _1_ 2 3 4 5 6 7 s , ‘9.
Touchy 1 2 3 4 5 6 7 8 9

 

 

9. The following statements pertain to preference for different or unique products.
Please circle your level of agreement for each statement, where I=Strongly
Disagree and 5 == Strongly Agree.

 

 

 

 

 

 

 

 

 

Neither
3:21;: Disagree Agree nor Agree 8:35;),
V Drsaggee

rAn important goal when I buy
' merchandise is to find something that 1 2 3 4 5
. communicates my uniqueness

Often buy products to help shape a 1 2 3 4 5

more unusual personal image
' Products that are unusual assist me in 1 2 3 4 5
p establishing a distinctive image

When it comes to the products I buy I 1 2 3 4 5

have often broken customs and rules
POften violated the understood rules of

. . l 2 3 4 5

my. social group regarding what to buy

Often gone against the understood

rules of my social group regarding l 2 3 4 5
, how certain products are properly used
" Dislike products or brands that are l 2 3 4 5
pcustomarily (purchased by everyone

Once they become popular among the

general public I give up wearing l 2 3 4 5
. fashions I’ve purchased

The more commonplace a product or
1 brand is among the general population, 1 2 3 4 5
pipe less interested I am in buying it

 

 

10. People have different personalities. How often do these characteristics describe
how you see yourself in everyday life? Please circle one for each statement, where
1 =Never and 9=A lways.

Z
a
<
53
3:
S
‘<
(D

 

 

 

 

 

 

 

 

 

 

LI_)_rawn to experiences with an element of danger 1 2 3 4 5 6 7 8 9
jpek an adrenaline rush 1 2 3 4 5 6 7 8 9
iACtively seek out new experiences 1 . 2 3 4 5 , 6 7 8 9 _'
fipjoy taking more risks than others 1 2 3 4 5 6 7 8 9
LEocus on my body and how it feels 1 2 3 4 5 6 -7 8 _ . 9 __,
ngote time each day to improving my body 1 2 3 4 5 6 7 8 9 i
2.1/0m hard to keep my body healthy 1 2 3 4 5 6 7 8 9
leel making my body look good is important 1 2 3 4 5 6 7 8 9
133130)! cultural. immersion when I travel 1 2 . 3 4 S 6 7 8 9 _

 

214

 

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Seek hands-on cultural encounters as I travel 1
:Embrace the world celebrate its nuances as I travel 1
Interested in the traditions of indigenous cultural

communities (e.g., festivals, rituals) as I travel
I Try to visit local museum or art gallery as I travel
Travel should be about enriching knowledge
Enjoy learning new things more than most people
People consider me to be intellectual
:15an working on new ideas
Value information as the most important resource
pHave an altruistic nature
Give to others
:Sacfifice my goals to help others

 

 

 

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Selfless in giving time to others

 

LEnjoy buying expensive products

 

Like to own nice products more than most people
:AcQuiring valuable products is important to me
Enjoy owning luxurious_products
'pEnjoy competition more than others
Feel it is important to outperform others
'_1Enjoy testing my abilities against others’
Feel winning is extremely important

 

 

 

 

 

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wwwlwwwmwwwwwwwwu
b-b-b-hA-fiA-bA-h-b-h-fi-AA-b
MMMMMMMMMMMMMMMM
ONONQQO\O\O\O\O\O\O\O\O\O\O\O\
\l\l\l\)\l-)-l\l-)'\l'\l\l\1\~l\l‘~l

 

11. The following statements are about your fashion style. Please indicate your level of
agreement with each by circling the number that best describes you, where
1 ==Strong1y Disagree and 5 =Strongly Agree.

Strongly . Neither Agree Strongly
{ .. _ _ _ _ . Disagree Disagree nor Disagree Agree Agree
.. Aware of fashion trends and want 1 2 3 4 5

to be one of the first to try them
First to try new fashion; therefore,
many people regard me as being a l 2 3 4 5
. fashion leader
' Important for me to be a fashion

1 2 3 4 5
.-.leader , .
Confident in my ability to
, , r 2 3 4 5
. recognize fashion trends
' Clothes are one of the most
important ways I have of 1 2 3 4 5
:, expressing my individuality
Don’t spend a lot of time on 1 2 3 4 5

fashion-related activities

 

SH‘ 1 It )N 3: 'I‘RAVH mech‘. .«\\VI) Nil-[)8 lNl-‘(HtMA l'l()T\'

215

12. Over the past 12 months have you used the following sources when booking or
reserving a vacation trip? Please mark each of the sources used, and if used,
circle how helpfirl you found it.

Used Not Somewhat Very
No Yes Hel ful He He
2’ , , - ‘ 12 333:} .'
2

    

Priceline.com

I‘.
:_
ltr'.

Hotel websites

D'DE] C] D. [33131131.
N N N N NpJNtf-twi“

Travel

13. Over the past 12 months have you used the following sources when booking or
reserving a vacation trip? Please mark each of the sources used, and if used,
circle how helpfirl you found it.

Used Not Somewhat Very
No_ l Yes ._ %Hel- ful He ful

«- .0:’-uffi:.:.:- }‘

.: "..L‘fwl' lokur“ ‘ " " '
- - 4‘".

.ra'

..--._

Airline websites

Hut-4H

Stories/blogs from travelers and travel Cl C] 1 2 3

7 if. ”"3936“ 7
Ivar‘lv» Ii: 4‘71"»: l‘igl g¢j( v)“ raifi §{_.1WJL¢

Travel websites (e. g. Expedia, Lonely El [:1 i .
Planet

 

" “.557 {‘2' Ere? ‘Tvl-I"I£O’rfjl K: 23113:
:3"! A ‘x'.¥;~::i-=K" : 1"}5 “‘15?

I

‘-"»‘- - . -..‘ - - .
._ . '1' - . .L‘JTV' ‘ -.. ' x,- ~7Jg. I p‘.‘ .' " , .. '. 4' "
. . 4 - . » » O . . I
' --- I~~“.~<.'-’J li!‘”:.—-¢L‘L{_;JW.‘JM a a

 

Travel . ents

Travel trade shows

 

216

14. Thinking about your last vacation trip, before going did you do any of the following
activities? Please mark one for each.

 

 

 

Purchased new El yes 1:1 Read books about the local I] yes El
luggage/gear “0 culture no
Got into good physical Cl yes C1 Learned some of the local D yes El
shape “0 language n0
Purchased travel guide C1 yes 13 Watched programs on the local Cl yes Cl
books “0 culture “0

 

 

 

 

15. Thinking about your last vacation trip, did you share you travel experiences with
friends/family using any of these communication types? Please mark [3 one for

 

 

 

each.
Pésfing.photos on-line 1:1 1:1 Telling stories Cl yes El no
during trip yes no
Posting photos on-line D 1:] Blog diary during El yes [:1 no
gfter trip yes “0 trip
Sending postcards by 1:1 1:1 Blog diary after trip Cl yes D no
mail yes no

 

 

 

 

16. Over the past 12 months have you used the following technologies when
traveling on a vacation trip? Please mark each of the sources used, and if
used, circle how helpful you found it.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Used Not Somewhat Very
No Yes Helpful Helflrl Helfiul
Lemma/Digital camera [:1 Cl 1 2 3
Internet cafe’ or wireless areas El E1 2 3
Mobile phone Cl Cl 1 2 3
_I-_Pod/MP3/MPiplayer Cl C] 1 2 3
. Laptop computer With [:1 El 1 2 3
_wrreless access
Global Positioning System
_LGPS) 1:] El 1 2 3
Cellular phone With Internet El [:1 1 2 3
ficess
Lellular phone with camera C1 U l 2 3
Pager Cl Cl 1 2 3
Personal digital assistant (e.g.,
_Blackberry) [3 El 1 2 3
Personal digital assrstant wrth Cl [:1 1 2 3
_.Iptemet access
14912101) computer Cl 1:1 1 2 3
Qesktop computer U 1:1 1 2 3
Global Positioning System
. l 2
flPS) in vehicle D D 3
£11 Star service in vehicle 1:1 1:1 1 2 3
_cher, please describe

 

 

217

 

‘Ivl. r..|.l.l..1|.r.r~

 

 

17. Thinking about the words “Dream it” read the list of travel experiences below.

Please indicate the experiences you have dreamed of having by circling 1= Not at
all and 5 =A bsolutely.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I ’ve dreamed of... 1:?
all Absolutely
" :‘i’tiiiiacr'oss the USA 1 2 3 4 5
Staying at a hot spring spa in Japan 1 2 3 4 5
“Sitingall the seven continents 1 2 3 4 5
_Getting;off the beaten track 1 2 3 4 5
.rLSiiif-Tfishing-on the beach at Cape Hatteras 1 2 3 4 5
Cam sing in Glacier National Park 1 2 3 4 5
Visitingfa market in India 1 2 3 4 5
Hiking in rural Ireland 1 2 3 4 5
Shopping in Paris 1 2 3 4 5
Making snow angels in Alaska 1 2 3 4 5
-Visifiggfle Seven Wonders of the World 1 2 3 4 5
Running with the bulls in Spain 1 2 3 4 5
Cage-diving with Great White Sharks l 2 3 4 5
Rock climbing on every continent l 2 3 4 5
Swimming in every ocean I 2 3 4 5
Rafting in the Grand Canyon 1 2 3 4 5
Cliff diving in Jamaica 1 2 3 4 5
_H_iking in a rainforest 1 2 3 4 5
Snorkeling the Great Barrier Reef 1 2 3 4 5
_V_isiting the pyramids in Egypt 1 2 3 4 5
going on a safari in Africa 1 2 3 4 5
Walking down the ancient paths of China 1 2 3 4 5
Exploring the ancient civilization of 1 2 3 4 5
Mayans
Relaxing on the white beaches of Bora- l 3 3 4 5
Bora "
Other, please describe

 

 

18. Thinking about your last vacation trip, did your travel experience change anything
about your lifestyle at home? Please mark E one for each.

 

 

 

 

 

A new recreation activity at 1:1 1:1 Interested in diet and 1:1 D no
31ng yes “0 cuisine yes
Attitude changed about 1:1 1:1 Interested in healthy U D no
flames/places Yes “0 habits yes
Donated money to a charity or 1:1 U Volunteered time or 1:1 [I no
_C__a_use yes "0 resources Yes
Learned a new language D D Other, please describe
_p yes no

 

 

 

218

19. Please specify which of these age decades you FEEL you really belong to:
preteens, teens, twenties, thirties, forties, fifties, sixties, seventies, or eighties.
Please mark one for each.

preteens teens 205 303 403 503 60s 705 80s
fiEEL as though I am in

my

I LOOK as though I am in
my

TDO most things as though

I were in my

[:1 EEEEEEDE

 

E] EDEEEEEE

 

 

My recreation and travel
INTERESTS are mostly Cl E] El Cl El E] El 1:] E
those of a person in his/her

 

   

Slt‘l m 4: D11M( )(iRAl’Hlt‘ lxr‘URMA'l l().\l 130R 1,)IiSL‘Rll’l’IV'li PI'RPUSLS ()NM'

20. What is your gender? Please mark one. Cl female [:1 male

21. What is your ZIP code? zip

22. What year were you born? (e. g.,1966)

23. Counting yourself, how many people are currently living in your household?

 

Number of adults (1 8 years and Number of children (under 18 years)_
Up)_
24. What is your current marital status? Please mark one.
Cl Single 13 Widowed [3 Living with significant other
E Married Cl Divorced Cl Other (please specify)
25. What is your ethnicity and race? Please mark E one.
D White Cl Hispanic/Latino/Spanish [3 Mixed (please specify)
origin
El African Cl Hawaiian/other Pacific El Other (please Specify)
American/Black Islander
Cl Asian E American Indian/Alaska
Native

26. What is your highest level of education? Please mark one.

Cl Some high Cl Some college 13 College degree, 4 year
school college

Cl High school [3 Associate degree, 2 year [:1 Advance degree (e.g., MBA,
degree college MS)

219

27. What was your gross household income in 2005? Please mark E one.
C] $200,000 -

Cl under $35,000 Cl $50,000 - Cl $100,000 -
$74,999 $149,999 $249,999

Cl $35,000 - Cl $75,000 - El $150,000 - 1:] $250,000 or more
$49,999 $99,999 $ 1 99,999

28. Are you currently? Please mark E one.
[3 Working full- Cl Going to Cl Retired
time school
C! Working part- D A homemaker D Other, please describe
time

 

Thank you, we appreciate your time!

220

Appendix B: Survey Cover Letter

221

Date

Name

Address

City, State zip code

Dear Name:

You have been randomly selected to participate in a scientific study on recreation and
travel being conducted by Michigan State University and supported by National
Geographic Adventure magazine. Sharing your thoughts on recreation and travel
experiences and interests will assist in our research related to travel.

As a thank you for taking the time to complete the survey, you have the chance to win
two free airline tickets on Continental Airlines. Simply return your completed survey in
the prepaid envelope we provided and your name will be entered in a drawing for two
free airline tickets to your choice of a variety of gateways in North America, Europe or
South America. There will be additional chances to win travel-related prizes such as
travel gear and accessories, maps, and travel books. These prizes are not part of any sales

effort, but were donated by a reputable partner to the research project.

You must be 18 years of age or older to complete the survey. The survey will take 20-25
minutes to complete. You indicate your voluntary agreement to participate by completing
and retunring this survey. However, if you choose not to complete all or part of the
questions, you will not suffer any penalty. You are free to discontinue your participation
at any time. Your responses will be anonymous and your privacy will be protected to the

maximum extent allowable by law.

If you have any questions regarding your role and rights as a study participant, or would
like to register a complaint about this study, you may contact, anonymously, if you wish,
Dr. Peter Vasilenko, Director of Human Research Protection Programs, at (517) 35 5-
2180, FAX: (517) 432-4503, email: irb@msu.edu, or regular mail: HRPP, 202 Olds Hall,

East Lansing, MI 48824. We greatly appreciate your cooperation!

Sincerely,

Paige P. Schneider, Ph.D. Candidate Dr. Christine A. Vogt, PhD

Michigan State University Michigan State University
vogtc@msu.edu

 

schne252@msu.edu

(517) 432-0312

Enclosures

222

Appendix C: Postcard Reminder

223

10/29/2007

Hello,

Recently you should have received a survey about recreation and

travel interests and preferences from Michigan State University. If you
have already mailed your survey, thank you! Your participation will help
us better understand travel behavior. We appreciate your time in sharing

your thoughts.

If you haven’t found the time to complete, please do so in the next few days.
If you did not receive the survey, please contact us by e-mail or phone.

Paige Schneider (517) 432-0312 or
schne252@msu.edu

Thank you for your participation!

224

Appendix D: UCRIHS Approval Letter

225

 

MICHIGAN STATE initial iRB
U R

N,’ V E ,3 ' T Y Application
‘ ' Determination
cancer 17,. 2007 *Exempt*

To: Christin VOGT
131 Natural Resources

MSU.

Re: IR” XVI-087 Category: EXEMPT 2
Approval Dab: Cobb“ 17. 2007

Title: Adventure Travelers and Their Traits: A Hierarchical Model Approach

The Institulomi Review Board has completed their review of your project. i am pleased to advise you that your
project has been deemed as exempt in accordance with federal regulations.

The ma hasfound thatpur research project meets the ulterlaforexemptstahls andthsctiterlaforths
protection of human subjects in exempt research. Under our exempt policy the Principal Investigator
assumes the rssponsibllltlerfortha protection of human subjects In this project as outlined in the
assurance latter and exempt educational material. The "28 office has received your signed ssstrence for
exempt research. A copy of this signed agreement is appended for, your Information and records.
Renewals: Exempt protocols do not need to be rsnswed. ii the project is completed. please submit an

Application lb! Permanent Closure.
Revisions: Exempt protocols do mt require revisions. ‘ i-iowevsr, if changes are made to a protocol that may no
larger meet the ansmpt criterla. a new initial appilcsflcn will be required.

Problems: it issues should arise during the conduct of the research. such as unanticipated problems, adverse
events, oranyprobiem thatmayhcreasstheriskloths human subjects sndchangsthscelegoryotrevle'w, ,
notify the "RB oii‘ics promotly. Anyccmplahts from pardobants regarding his risk and benefits of the project

must bereportedtothe IRE.
Follow-up: Ifyou- airstrip! project-is not convicted and closed shim the IRB cities wli contaotycu
reporting diestatusofthe pmiectandtovsriiymetnochemes haveoocurrsdthatmayalfedexemptsutus.
PlesssueetheiRB nunberlstsdabovsonanyfonns submittedwhlch monumental-mommy

correspondence Milt the iRB oflics.
Good hair It your research. llwe can be cffurther ”alumnae. please contact us at 517-356-2180 orvla email

at W. Thank you for your cooperation.
Shouflyi '
fle/i

Peter Vasilenko, Ph.D.

BIRBOhalr
0: Paige Schneider
1 72 Neutral Resources

226

Appendix E: Non-response Survey

227

 

nruL.h‘rIJS~P~E~C~C~C\h~rui\flb-rlx AM.\S\K\IVJ.\T\E\L\D rerw\n\w\

Ri;(‘i{ii.-\’i‘i().\i AND 'lfiRAVi-LL PRiii-‘i-IRIZNCiiS SUerav

 

29. Do you currently hold a valid US. passport? Please mark [>3] El El
no yes

one.

30. Thinking of vacation travel during your lifetime, indicate where you have visited on

a past trip or plan to visit in the future. Please mark l3] for each column.
Traveled to in the Plan to travel to in

 

 

past future
North America (U.S.. Canada2 Mexico) D B
International (Continent other than North E] El
America)

 

 

31. How many vacations have you U.S./Canada/Mexico International

taken in the past 3 years?

32. People have different personalities. How often do these characteristics describe
how you see yourself in everyday life? Please circle one for each statement, where

1 =Never and 9=Always.
Never

' Bashful l
Introverted 1
Quiet l
Shy l

.' Precise 1
fl Efficient l
Qrganized . 1
Orderly l
greative g 1
1

l

l

l

l

1

l

l

l

1

1

 

 

imaginative
J: ind novel solutions
_9_riginal
: Tender hearted
Agreeable
§o%eMed
Kind
__Moody
jemperamental
___l_:‘._motional
:Iouchy
_ Drawn to experiences with an element of l
Aanger
_§eek an adrenaline rush I

 

 

 

 

2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7
2 3 4 5 6 7

 

 

228

 

 

activelgseek out new experiences
Enjoy taking more risks than others

HHH

 

L Focus on my body and how it feels
Devote time each day to improving my

H

 

 

wbody -, v
Work hard to keep my body healthy 1

U‘ 0‘ Ur Utmu.
°‘ 0‘ 0‘ moxox
°° 0° 0° oooooo‘

7
7
7
7
47
7

‘°\0\o\oxow>

 

2
2
2
2
2
2

“meww

4
4
4
4
4
4

Feel making my body look good is 1
important

 

 

33. What was the primary reason for not responding to the survey?? Please mark [3

 

one.
D Survey came at El Survey was too long El Questions were too difficult
the wrong time
D Don’t travel [3 Don’t do surveys Cl Don’t participate in research
studies

Cl Other, please
describe

34. What IS your gender? Please mark [3 female [:1

male

one.
35. What year were you born? (e.g.,l966)

Thank you, we appreciate your time!

229

Appendix F: Non-response Survey Cover Letter

230

Date, 2008

Name
Address
City, State zip code

Dear Name:

During fall of 2007 you were randomly selected to receive a Recreation and Travel
Preference survey conducted by Michigan State University and supported by National
Geographic. As To date you have not returned either of the two surveys sent to your
home.

In an effort to accurately understand recreation and travel preferences, we are seeking a
full range of input, including yours Would you please consider answering these few
critical questions and returning the survey in the enclosed prepaid envelope? We assure
you this will be our last attempt to contact you regarding this study.

If you would please take the time to answer this one page survey it would be greatly
appreciated. In addition, by filling out and retuming this survey, your name will still be
included in the drawing for the chance to win two free airline tickets on Continental
Airlines for travel to a number of destinations in North America, South America, and
Europe. The drawing will be held February 6,2008. Thank you for your time and
consideration.

Again, many thanks for your time! Your input is essential to the success of our study.

 

Sincerely,

Paige P. Schneider, Ph.D. Candidate Dr. Christine A. Vogt, PhD
Michigan State University Michigan State University
schne252@msu.edu vogtC@snsu.edu

(517) 432-0312

Enclosures:

Short Survey

Prepaid return envelope

231

Appendix G: Survey Instrument Key

232

 

Construct: Traveler Type; consists of three categories: soft adventure traveler (SAT),
hard adventure traveler (HAT), and mass traveler.

Questions 1, 2, 3, 4, 5, and 7 form an index to determine traveler type.

Source: Measures adapted for this study based (CTC, 2003; OIA, 2006; Jang, Morrison,
& O’Leary, 2000; Pearce & Caltabiano, 1983; Sung et al., 1997; TIA, I998; TIA, 2006).

 

Do you currently hold a valid US. passport? Please mark [it one. Cl no Ci yes
If yes, at what age did you first apply? years (e.g., 21 years)

Thinking of vacation travel only, indicate those continents/regions you visited on a past
trip or plan to visit in the future. Please mark [Xi for each column.
Have traveled Plan to travel

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

to to
. in the past in the fisture
' Africa D D

Antarctica? V D D
Arctic Cl D 4

Australia . D D
1 Caribbean (e.g., Aruba, Cuba, Dominican Republic, Cl C]
Jamaica) , ~

Central America (e.g., Belize, Costa Rica, Guatemala,

E] D
- Honduras)
" Central Europe (e.g., Austria, Czech Republic,

El D
gPoland) ,

Eastern Europe (e.g., Russian Federation, Ukraing D '3
Mexico D D
.. Middle East (egg, Israel, Jordan, Pakistan, Turkey) D D
LNew Zealand D D
1 North American (Canada or US.) D E
North Asia (egg China, Hong Kong, Japan, Korea) CL E

South America (e.g., Argentina, Brazil, Chile,

Ci Ci
jcuador)
jouth Pacific (egg Ffii, Samoa, Tahiti) D D

South and Southeast Asia (e.g., Cambodia, India, Ci Ci
flalaysia)

f Western Europe (e.g., France, Germany, Italy, United D D
fingdom)

 

How many vacations have you taken in the past 3 U.S./Canada International
years?

How many vacations do you plan to take in the U.S./Canada International—
next 3 years?

233

 

 

National Geographic Trip Flaming Behavior
Question 6
Source: Trip Planning Behavior Scale (Vogt, 1997).

 

 

People plan vacation trips in different ways. Please circle your level of agreement with
the following, where I =Strongly Disagree and 5 =Strongly Agree.

 

 

 

 

Strongl . Neither Agree Strongly
Disagre: Disagree nor Disagree A ree Agree
I plan my entire trip well in 1 2 3 4 5
advance
I plan most of my vacations
before I leave and then fill in 1 2 3 4 5
the details after I arrive
I plan most of my vacation 1 V 2 3 4 5
once I reach my destination

 

 

From the list of recreation and travel activities provided, indicate those you have
experienced or plan to experience in the future. Please mark [>3] one for each column.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Already experienced Plan to experience
during my travels in the during my travels in the
past Mg

Attending conCert/play/dance U D

Attending local festivals/fairs D D
Attending spectator sporting E! El

eyents

Backpacking D D

Bicycle riding D D

Boating/water skiing D El

(:51um Ci Ei

Cave exploring/spelunking U D

City-tours/short guided excursions D D

Climbing - mountain/rock/ice D D

Getting to know local petmle D C]

Golfing/tennis D D
jiiking D D
junting/fishing D E! fl
__Kayaking/canoeing D D

Mountain biking D i ‘D -

Night life/visiting night E] El
_c_lubs/dancing __
Qbservingfwildlife/bird watching D .131. ’ ‘ '2'

Safaris D D

 

234

 

Scuba diving/surfing

 

Shopping
Skiing/snowmobiling

 

,vammmg/sunbathmg/beach
act1v1t1es

 

Trekking

 

ViSiting Casinos/gambling/gaming
Visiting friends or relatives

 

ViSifinggardens/botanical gardens
Visiting local/state/national parks

 

Visitig museums/galleries
Visiting places of historical
interest

Visiting spas

Visiting theme/amusement parks
Visiting zoos

Volunteering while on vacation
Waterskiinglsnorkeling

Other, please describe j

DDDDD D DDDDDD D DDDD
DDDDD D DDDDDD D DDDD

 

 

 

Construct: Elemental Traits

Eight Elemental Traits (OCEANMAP)

Openness to experience

Conscientiousness

Extraversion

Agreeableness

Neuroticism (Emotional Instability)

Material needs

Need for arousal

.Physical/body needs

Questions 8 and 10

Sources of the Elemental Traits:

Five Factor Model of personality (Wiggins, 1996) —

A large number of studies have supported it as providing the most fundamental set of
traits.

Evolutionary Psychology (Buss, 1988) —

Added material needs and physical needs based on the proposition that behavioral
tendencies as well as biological mechanisms (e.g., breathing, digesting) evolved as
adaptations to the environment over eons.

Optimum Stimulation Level Theory (Mehrabian & Russell, 1974; Zuckerman, 1979) —
None of the other seven traits had properties related to activation of behavior and how
people control their level of stimulation, therefore Need for arousal was included.
Measurement Source: Licata, Mowen & Brown, 2003.

wsawewwr

235

 

 

 

People have different personalities. How often do these characteristics describe how you
see yourself in everyday life? Please circle one for each statement, where 1=Never and
9=Always.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Never Always
1 9

Bashful
Introverted Elemental Trait:
Quiet Introversion
Shy
Precise
Efficient Elemental Trait:
Organized Conscientiousness
Orderly
Creative
Imaginative Elemental Trait:
Find novel solutions Openness to Experience
Original
Tender hearted
Agreeable Elemental Trait:
Softhearted Agreeable
Kind
Moody ,
Temperamental Elemental Trait:
Emotional Neuroticism/Emotional Instability
Touchy

 

 

Construct: Need for Uniqueness
Measurement: Need for Uniqueness Scale
Question 9

 

 

 

Source: Need for Uniqueness Scale obtained from Tian, Beard & Hunter, 2001
The following statements pertain to preference for different or unique products. Please
circle your level of agreement for each statement, where 1=Strongly Disagree and 5 =
Strongly Agree.

 

 

 

Stron 1 Neither S tro I
. g y Disagree Agree nor Agree ng y
Disagree Disagree Agree
An important goal when I buy
merchandise is to find something 1 2 3 4 5
thatcOmmunicates my
iniqueness
Often buy products to help shape 1 2 3 4 5
i. more unusual personal image
Products that are unusual assist l 2 3 4 5
316111 catabliShing a distinctive '

 

 

236

 

When it comes to the products I

 

buy I have often broken customs l 2 3 4 5
and rules

Often violated the understood

rules of my social group 1 2 3 4 5

regarding what to buy

Often gone against the
understood rules of my social
group regarding how certain
products are properly used

 

Dislike products or brands that
are customarily purchased by 1 2 3 4 5
everyone

 

Once they become popular
among the general public I give
up wearing fashions I’ve
purchased

 

The more commonplace a
product or brand is among the
general population, the less
interested I am in buying it

 

 

Construct: 3M Model: Compound Traits

Question 10

Competitiveness

Measurement Source: Competitiveness Scale (Mowen, 2000).
Need for learning

Measurement Source: Need for Learning Scale (Mowen, 2000).
Altruism

Measurement Source: Altruism Scale (Mowen & Sujan, 2005).

 

 

Construct: 3M Model: Situational Traits

Question 10

Interest in cultural experiences

Measurement: Developed for the purpose of this study.

Need for Uniqueness

Measurement Source: Consumer Need for Uniqueness Scale (Tian, Beard & Hunter,
2001)

Fashion Leadership

Measurement: Fashion Leadership Scale (Goldsmith, F reiden & Kilsheimer, 1993).

 

 

 

Construct: 3M Model: Surface Traits
Question 10

Mass traveler

£011 adventure traveler

 

237

 

 

 

Hard adventure traveler

Measurement Source: Scores on Traveler type Index

 

People have different personalities. How often do these characteristics describe how you
see yourself in everyday life? Please circle one for each statement, where I =Never and

9=A lways.

Never Always
1 9

 

     

' to experiences with an element of danger

 

Seek an adrenaline rush

 

' AcEVely seek out new experiences

 

Elemental Trait:
Need for Arousal

 

Enjoy taking more risks than others
races. on my body and how it feels
Devote time each day to improving my body

 

' Work hard to keepmy body healthy

 

Feel making my body look good is important
Enjoy cultural immersion when I travel
Seek hands-on cultural encounters as I travel

 

Embrace the world celebrate its nuances as I travel
Interested in the traditions of indigenous cultural
communities (e.g., festivals, rituals) as I travel

Try to visit local museum or art gallery as I travel
Travel should be about enriching knowledge
Ery'oy learning new things more than most people
People consider me to be intellectual

Enjoy working on new ideas

Value information as the most important resource
Have an altruistic nature

 

 

 

Elemental Trait:
Physical Resources/Body Needs

Situational trait:
Interest in cultural experiences

Compound trait:
Need for learning

 

 

Give to others Compound tralt:
jgcrifice my goals to help others A trursm

Selfless in giving time to others

Enjoy buying expensive floducts

Like to own nice products more than most people Elemental Trait:

 

Acquiring valuable products is important to me
Enjoy owning luxurious products

Enjoy competition more than others

Feel it is important to outperform others
Enjoy testing my abilities agarinst others’

gel winning is extremely important

 

Need for Material Resources

Compound trait:
Competitiveness

 

 

Construct: Fashion Leadership
Question 11

Source: Fashion Leadership Scale obtained from Goldsmith, Freiden & Kilsheimer,

1993)

 

238

 

 

 

‘1.“ (‘.I.Irr‘.‘1‘ [1‘]

.. 11x

The following statements are about your fashion style. Please indicate your level of
agreement with each by circling the number that best describes you, where 1=Strongly
Disagree and 5 =Strongly Agree.

Neither

Strongly . Strongly
Disagree Disagree Agree nor Agree Agree
Disagree
Aware cf fashion trends and
Swant to be one of the first to l 2 3 4 5
try them
First to try new fashion;
therefore, many people
. . l 2 3 4 5
regard me as being a fashion
leader
Important for me to be a
..fashion leader. 1 2 3 4 5
Confident in my ability to 1 2 3 4 5

recognize fashion trends
Clothes are one of the most
important ways I have of 1 2 3 4 5
expressing my individuality
Don’t spend a lot of time on
fashion-related activities

 

National Geographic
Question 12, 13, 14, 15
Pre trip behavior

 

 

 

Over the past 12 months have you used the following sources when booking or reserving
a vacation trip? Please mark [Xi each of the sources used, and if used, circle how helpful
you found it.

 

 

 

 

 

 

 

 

 

 

 

    

 

Used Not Somewhat Very

No Yes Helpful Helpful Helpful
H6tels.Com D D 1 2 3
Priceline.com D D 1 2 3
Oibitz.com D D 1 2 3
Expedia.com D D 1 2 3
Kayakcom D D 1 2 3
Travelocity.com D D 1 2 3
jiptivirecom D D 1 2 3
Cheaptickets. com U D 1 2 3
Local or government tourism
websrtes D D 1 2 3
gotel websites D D 1 2 . 3
if him I Operators/Lodges . T ; . jg; .
if. ' bréi based) D D I 1' :2 ‘-
Travel agents D D 1 2

 

 

 

239

 

DOther, please describe I

Over the past 12 months have you used the following sources when booking or reserving
a vacation trip? Please mark 13] each of the sources used, and if used, circle how helpful

you found it.

” Accommodation websites (e.g.,

Used Not Somewhat Very

No Yes Helpful Helpful Helpful

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

..hotels.com) . D D g 1 2 _ . 3
Airline websites 4 D D f l 2 3
'yLocal or government tourism websites D D 1 2 3
Stories/blogs from travelers and travel D D 1 2 3
writers
Search engines @gg Googleg, Yahog) D D 1 2‘ 3
Travel websrtes (e.g., Expedia, Lonely D D 1 2 3
WPlanet)
LLTV travel shows D D 1 2 3
_Guidebooks D D 1 2 3
I'Magazines, D D 1 2 3
Newspapers D D 1 2 3
Advice/recommendations from friends D D 1 2 3
ipr famriy
Travel agents D D 1 2 3
g Tour brochures D D l 2 3
Travel trade shows D D f 2 3
flmeg please describe
Thinking about your last vacation trip, before going did you do any of the following
activities? Please mark IZI one for each.
T Purchased new i D D Read books about the local D D
. luggage/gear , yes , no culture yes no ;
Got into good physical D D Learned some of the local D D
shape yes no language yes no
3“ Purchased travel guide D D Watched programs on the D D
_b_ooks . yes no local culture yes no
National Geographic
Question 15
During trip/ Post trip Behavior

 

 

Thinking about your last vacation trip, did you share you travel experiences with
fiends/family usingany of these communication tyms? Please mark IZI one for each.

 

 

 

 

 

T Posting photos on-line during D yes D no I Telling stories D yes D no
iosg'pgpirotos on-line after D yes D no [Blog diary during D yes D no

240

 

 

 

 

 

 

 

tn'p - .. e I s f 1 ml) _ _ .
finding postcards by mail D yes D no LBlog diary after trip D yes D no .

National Geographic

Question 16

During trip Behavior

 

 

Over the past 12 months have you used the following technologies when traveling on a
vacation trip? Please mark 121 each of the sources used, and if used, circle how helpful

you found it.
Used
fi fi Yes
WGEfifialDigital camera
Internet cafe’ or wireless areas
wIND/ribbile phone A
I-Pod/MP3/MP4 player
DLaptop computer with wireless
.f. access
Global Positioning System
(GPS)
, Cellular phone with Internet
; access ,
Cellular phone with camera
:Pager. , ,
Personal digital assistant (e.g.,
wBlackberry)
7 Personal digital assistant with
. Internet access
- Laptop computer
; Desktop computer
Global Positioning System
_(GPS) in vehicle
_._Qn Star service in vehicle
OtherL please describe

Dagmmjmuam El [jamming
DECIDE! [31:11:13 CI [1:113:31]

 

 

Not
Helpful

1
1
1
1D—
1

1

Somewhat
. Helpful
2

N NNN

N

NNNN

NNNNN

Very
Helpful
3

3
3
3
3

3

wuww

mwmww

 

National Geographic
Question 17
Future intentions

 

 

Thinking about the words “Dream it” read the list of travel experiences below. Please
indicate the experiences you have dreamed of having by circling 1 =Not at all and

5 =A bsolutely.
I’ve dreamed of...

:liicyaing across the USA T

241

1

Not at all

3 4

Absolutely
' , 5

 

 

 

 

Staying at a hot spring spa in Japan

 

wTl'ii’sitingiall the, seven continents

 

jGetting off the beaten track

 

.T,Sfiiffish;11_1g on the beach at Cape Hatteras

 

Camping in Glacier National Park

 

"Visiting a market in India

 

Hikingin rural Ireland

 

Shoppiggin Paris
Making snow angels in Alaska

 

Visiting the Seven Wonders of the World

 

Running with the bulls in Spain

 

Cage-diving with Great White Sharks

 

Rock climbing on eveg continent

 

Swimming in every ocean

 

Rafting in the Grand Canyon

 

Cliff diving in Jamaica

 

Hiking in a rainforest

 

Snorkeling the Great Barrier Reef

 

Visiting the pyramids in Egypt

 

Going on a safari in Africa

Walking down the ancient paths of China
Exploring the ancient civilization of
Mayans

Relaxing on the white beaches of Bora-
Bora

Other, please describe

 

r—A—Ah—sy—d—dr—bp—th—th—II—dr—db—dh-dh—ih—fiv—‘HI—Ih—db—Ih—d
NNNNNNNNNNNNNNNNNNNNNN
wwwwwwwwwwwwwwwwwwwwww
b-b-hhkhkh-bhAAA-b-bhhbhbhk

H

h—l
Ix)
DJ
A

MMMMMMMMMMMMMMMMMMMMMM

Ll]

 

 

National Geographic
Question 18
Post trip behavior

 

 

Thinking about your last vacation trip, did your travel experience change anything about

fiur lifestyle at home? Please mark lZl one jar each.

 

 

 

 

 

A new recreation activity at D D Interested in diet and D D
. home yes no cuisine yes no
Attitude changed about D D Interested in healthy D D
inltures/places yes no habits yes no
Donated money to a charity or D D Volunteered time or D D —
£31186 yes no resources yes no
Learned a new language D D Other, please describe .
__ yes no

 

 

 

 

Construct: Age Identity
Measurement: Cognitive age
Question 19

 

 

 

242

 

Source: Barak, 1987 - Explore the idea of biological age vs. chronological age in a
tourism context

 

 

Please specify which of these age decades you FEEL you really belong to: preteens,
teens, twenties, thirties, forties, fifties, sixties, seventies, or eighties. Please mark 55] one

for each.
preteens teens 208 305 405 508 605 708 803

 

I FEEL as though I am in

my

D DDDDDDDD

 

ILOOK as thoughlam in
D D D D D D D D D

my

 

I DO most things as though

I were in my

 

My recreation and travel
INTERESTS are mostly D D D D D D D D D

those of a person in his/her

 

 

 

Demographic Questions
Questions 20, 21, 22, 23, 24, 25, 26, 27, 28
Source: Adapted from the US Census

 

What is your gender? Please mark [21 D female

one. D male
What is your ZIP code? zip
What year were you born? (e.g.,l966)

Counting yourself, how many people are currently living in your household?

Number of adults (18 years and Number of children (under 18 years)
up)
What is your current marital status? Please mark lZl one.
D Single D Widowed D Living with significant other
D Married D Divorced D Other (please specify)

 

What is your ethnicity and race? Please mark l2! one.

D White D Hispanic/Latino/Spanish D Mixed (please specify)
origin __

D African D Hawaiian/other Pacific D Other (please specify)

American/Black Islander

 

243

 

 

D Asian D American Indian/Alaska
Native

What is your highest level of education? Please mark [2! one.

D Some high D Some college D College degree, 4 year

school college

D High school D Associate degree, 2 year D Advance degree (e.g., MBA,

degree college MS)

What was your gross household income in 2005? Please mark D one.

D under $35,000 D $50,000 - D $100,000 - D $200,000 —
$74,999 $149,999 $249,999

D $35,000 - D $75,000 - D $150,000 - D $250,000 or more

$49,999 $99,999 $199,999

Are you currently? Please mark D one.

D Working full- D Going to D Retired

time school

D Working part- D A homemaker D Other, please describe
time

 

244

Appendix H: Expert Review Email Request

245

Dear Tourism Professor:

As part of my dissertation research I’m developing an “adventure travel index” using
Guttman scaling. Guttman scaling is also sometimes known as cumulative scaling or
scalogram analysis. The purpose of Guttman scaling is to establish a one-dimensional
continuum for a concept you wish to measure, in the case of my research - adventure
travel. As a tourism expert, I would like to request your assistance in rating the items in
my survey.

I would like to have you rate the attached list of items in terms of how favorable they are
to the concept of adventure travel. Based on the recreation, tourism, and adventure
travel literature, as well as interviews with an expert panel of recreation, tourism, and
adventure industry leaders a large set of destination and activity items were developed.
Please rate each of the items in terms of how favorable they are to the concept of
adventure travel. Keep in mind, you are not being asked whether you personally agree
with the item. Instead, you are being asked to make a judgment about how the item is
related to the construct of adventure travel.

If you can fill out and return the survey via email at your earliest convenience (no later
than Monday March 26th) it would be greatly appreciated. Simply type your responses
directly into the word document, save the file with your last name appended (e.g., Expert
Judge Survey-Vogt) and email the file in an attachment back to me at

schne252@msu.edu. If you have any problems reading or filling out the survey let me
know and I can provide you with a fax number to print and fax the survey. If you have

any questions or comments, please do not hesitate to email or call (419) 215-7532.
Thank you in advance for your time!

Best regards,

Paige P. Schneider, PhD Candidate
Michigan State University
Tel. (419) 215-7532-cell/voicemail

Skype: paigepatrice

email: schne252@msu.edu

246

Appendix 1: Expert Judge Survey

247

1. Please review the list of destinations provided and indicate the category you think the
image of the destination represents; 1. Mass Tourism, 2. Soft Adventure Tourism, or
3. Hard Adventure Tourism. Some destinations may fit in several categories,
however, please choose one category you feel fits the image of the destination best.

Please check only one for each.
Soft Hard
Adventure Adventure
Tourism Tourism

Mass

Destination ‘ .
Tourism

A Africa
Antarctica
. Arctic,
Australia y
' Caribbean (e.g., Aruba, Cuba, Dominican
,Republic, Jamaica)
Central America (e. g., Belize, Costa Rica,
Guatemala, Honduras)

DD

 

Entral Europe (e.g., Austria, Czech Republic,
. Poland)

 

Eastern Europe (e.g., Russian Federation,
Ukraine)

 

I Mexico

 

h Middle East (e.g., Israel, Jordan: Pakistan,
lurkey)

 

ANew Zealand _

North America (Canada or US.)
North 'Asia (e.g., China, Hong Kong, Japan, ‘
Korea) . ,
South America (e.g., Argentina, Brazil, Chile,
Ecuador)

“South Pacific (egg Fiji, Samoa Tahiti)
South and Southeast Asia (e.g., Cambodia, India,
Malaysia)

' Western Europe (e.g., France, Germany, Italy,

A, United Kingdom)

DDDDDDDDDUDDDDDDD
DDDDDDDDDDDDDDD
DDDDDDDDDDDDDDDDD

 

1. Please review the list of activities provided and indicate the category you think the
image of the activity represents; 1. Mass Tourism, 2. Soft Adventure Tourism, or 3.
Hard Adventure Tourism. Some activities may fit in several categories, however,
please choose one category you feel fits the image of the activity best. Please check
only one for each.

 

 

Mass Soft Hard I
Activity Tourism A1dventure Adventure
ounsm Tourism
. Attending Concert/play/dance D D A D
Attending local festivals/fairs D D D

 

 

248

 

1||Il 1

Hill}!

IJlJaI liar!

II. ...ld

udlualJ

I: .14....l!

...: lid

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Attendingspectator pportingevents D D D ’
fiBackpacking D D D
_' Bicycle riding_ D D D
’_B_oating D D D
Camping 4 D D D
_Cave exploring/spelunking D D D
;City tours/short guided excursions D D A D
Climbing - mountain/rock/ice D D D
: Dining A g g p g D D * _y D
VGetting to know local people D D D
; Golfing/tennis L1 D #D
Hiking D D D
Hunting/fishing D D D
. . Mass Soft Hard
Act1v1ty (cont) Tourism Adventure Adventure
Tourism Tourism
Kayaking/emoeing D D D
.Mountain biking 1:1 1:1 [3
_Night life/visitingnight clubs/dancing D D D
Observing wildlife/bird watching D D D
wSafaris m, D D D
Scenic driving D D D
‘ Scuba diving/ surfing D D D
Shopping D D D
Skiing/snowmobiling D D D
;Swimmingisunbatliing/beach activities D D D
Trekking .2 D D D
gVisitinggcasinos/gambling/gaming E1 E] :1
Visiting friends or relatives D D D
Visiting gardens/botanical gardens D D D
Visiting local/state/national parks D D D
gVisiting museums/ galleries D D D
Visiting places of historical interest D D D
Visiting spas , D D D
Visiting theme/amusement parks D D D
JEiting zoos ' D D [I
. Volunteering while on vacation D D D
;Waterskimg/snorkeling D p D E]

 

 

 

 

Q. In your own words please define the following: I

249

 

 

a. Mass Tourism

 

b. Soft Adventure Tourism

 

 

c. Hard Adventure Tourism

 

 

Thank you for your time!

250

Appendix J: Expert Judge Definitions

251

Expert Judge Definitions for Mass Tourism

 

Expert Judge

Mass Tourism Definition

 

Judge #1

I used number of people, physical challenge, risk, and exoticness as a
definition: Mass tourism has large numbers of participants; is not
physically challenging; “common” destination or activity; and very
secure and safe.

 

Judge #2

Tourism that is do-able by the majority of the population, which does
not require any special skills or instructions to accomplish
successfully.

 

Judge #3

No risk associated activities, easy to access.

 

Judge #4

Staying in a familiar bubble while away... emphasis on comfort,
convenience, mainstream activities... focus on well known
destinations, settings, and experiences.

 

Judge #5

Organized; structured; packaged; large numbers of tourists, often in
large groups; based upon and the cause of large scale development;
significant potential for negative impact (particularly socio-cultural
and environmental).

 

 

Judge #6

Leisure travel to destinations that have infrastructure capable of
hosting large numbers of people; usually characterized by tours,
attractions, or routes that are separate from the activities of local
communities, and by accommodations that emphasize familiar

physical and social comforts.

 

Judge #7

 

Large percent of market (over 50%); No or little skill needed;
“Sightseeing.”

 

252

 

Expert Judge Definitions for Soft Adventure Tourism

 

Expert Judge

Soft Adventure Tourism Definition

 

Judge #1

I used number of people, physical challenge, risk, and exoticness as a
definition: Soft adventure tourism has a moderate number of
participants; some level of physical challenge; less common
destination or activity; and moderate risk.

 

Judge #2

 

Tourism activities that require instruction, a level of skill, but are
generally guided with experts who assume the primary
responsibilities for services, organization, equipment, and logistics,
and generally take care of overall plans. It requires a low-level of
experience and high level enthusiasm for roughing it somewhat and
being taken out of their comfort zone.

 

Judge #3

Some type of difficulty in engaging in activities during trip, fairly
easy to access.

 

Judge #4

Getting out of the bubble on occasion... pursuing activities outside
the norm that involve a limited amount of risk. .. could be pursued in
a range of destinations.

 

 

Judge #5

something beyond generic nature-based tourism; outdoors and
physically active but not as demanding or extreme as hard AT; could
be individually organized or smaller packaged groups; for someone
looking for something different and somewhat off the beaten path (in
terms of activities and destinations) but not the challenge of true hard
AT (i.e., lower effort and risk than hard AT, a ‘tamer’ version).

 

Judge #6

Recreation travel to remote or exotic destinations, where some
aspects of the natural, social, or cultural environments may be
unfamiliar for the traveler; usually characterized by a combination of
familiar comforts and unfamiliar challenges, from a physical or social
perspective.

 

 

irdge #7

 

Outdoor recreation

 

253

 

Expert Judge Definitions for Hard Adventure Tourism

 

Expert Judge

Hard Adventure Tourism Definition

 

Judge #1

I used number of people, physical challenge, risk, and exoticness as a
defimtion: Hard adventure tourism has few participants; very
physically challenging; an “exotic” destination or activity; and high
risk.

 

Judge #2

Tourism activities that require a high level of skill, self reliance, and
expertise in the area to be traveled. May be guided, however the
expectation is that each participant will bring a high level of skill and
expertise to the activity or trip. Extreme travel, environmental, and
socio-cultural conditions can be expected as part of the experience.

 

Judge #3

A lot of difficulty and risk associated with these types of activities.

 

Judge #4

Avoiding the bubble completely... engaging in physically/mentally
demanding activities... in relatively non-mainstream/less traveled

destination.

 

Judge #5

‘Extreme’ destinations and activities; physically demanding and
challenging; remote and pristine settings; low numbers and very
small groups; associated with exploration, technical skills, effort, a
degree of risk; has the potential to minimize negative environmental
impacts and maximize economic and socio-cultural benefits, but not
necessarily (dependent upon the types of activities engaged in and the
carrying capacity of the environment, the latter of which is often low

due to the nature of the setting).

 

Judge #6

Recreation travel to remote or exotic destinations, where the natural,
social, or cultural environments are unfamiliar or extraordinary for
the traveler; usually characterized by activities that may be
challenging from a physical or social perspective.

 

Judge #7

 

 

Skills needed; Risk involved; Specialized; Extreme “scenery” —
mountains, oceans, fast running rivers; Hard to reach location/places

 

n;

254

 

Appendix K: Other Recreation and Travel Activities Experienced

255

Respondents Other Recreation and Travel Activities Experienced

Question 7 in the survey presented respondents with a list of recreation and travel
activities they had experienced in the past. Space was provided for “other” recreation and
travel activates not included in the list. Other recreation and travel activities respondents
participated in were:

mountain running
photography
skydiving/BASE jumping
skydiving

ballooning
sailboat/cruising
horseback riding

attend tradeshows/conferences
photography

sailing

rafting

off road - 4 wheeling
photography

curling

religious sites

parasailing

256

Appendix L: Other Recreation and Travel Activities Intentions

257

mountain running
photography

research trips

hanggliding
sailboat/cruising

horseback riding

rafting

attend tradeshows/conferences
photography

sailing

religious ceremonies

wine tours

sailing

cooking classes

rafting

off road - 4 wheeling

rafting

horseback riding

curling

archeology

religious sites

educational tour/seminar
white water rafting/solar eclipse watching
scenic flights

258

Appendix M: Other Lifestyle Changes Experienced After Last Vacation

259

Other Lifestyle Changes Experienced After Last Vacation

Question 18 in the survey presented respondents with a list of lifestyle changes.
Respondents indicated lifestyle changes they incorporated at home afier their last
vacation travel experience. Space was provided for “other” lifestyle changes not included
in the list. Other recreation and lifestyle changes respondents indicated they experienced
were:

interest in countries news and politics

appreciation for warm water habitats

using less resources (toilet paper, water, energy)
meditation

being more environmental

helped local orphanages

interest in regional economy and history and culture

260

Appendix N: Other Technologies Used on Vacation

261

Respondents Other Technologies Used on Vacation in the Previous 12 months

Question 16 in the survey presented respondents with a list of technologies used
while travelling on vacation in the previous 12 months. Space was provided for “other”
technologies used by respondents when traveling on a vacation trip during the previous
12 months were:

mobile phone TV and GPS

portable DVD player and noise reduction headphones
road atlas

video camera

while note technology, used local guide - very helpful

262

Appendix 0: Descriptive Statistics Elemental Traits and Items

263

Table 62

Descriptive Statistics for Eight Elemental Traits Items

 

 

. Hard Soft
Elemental Traits Adventure Adventure
and Items
Traveler Traveler Total 1 Sig._
n M SD n M SD n M SD

Introversion 202 3,331 1.61 1 15 4.09 1.66 317 3.92 1.63 -l .38 .781
Quiet 201 4.59 1.75 114 4.78 2.06 315 4.66 1.87 -0.86 .047
Introverted 201 3.68 1.99 1 12 3.97 2.15 313 3.79 2.05 -1.21 .486
Bashful 201 3.46 1.79 114 3.64 1.87 315 3.52 1.82 -0.86 .502
Shy 201 3.59 1.93 114 3.93 1.95 315 3.71 1.94 -1.51 .777

Conscientiousness 202 6.75 1.37 1 15 6.51 1.42 317 6.67 1.39 1.47 .949
Precise 202 6.37 1.71 114 5.95 1.89 316 6.22 1.79 2.03 .215
Efficient 202 6.90 1.48 1 14 6.67 1.59 316 6.81 1.52 1.29 .270
Organized 202 6.91 1.56 115 6.71 1.58 317 6.84 1.57 1.08 .842
Orderly 201 6.67 1.67 114 6.52 1.60 315 6.61 1.64 0.77 .460

Openness to Experience 202 6.92 1.38 114 6.38 1.41 316 6.72 1.41 3.27 .757
Creative 202 6.86 1.70 114 6.16 1.71 316 6.61 1.73 3.53 .642
Imaginative 202 7.04 1.64 113 6.51 1.71 315 6.85 1.68 2.69 .148
Find novel solutions 201 7.07 1.50 113 6.48 1.54 314 6.86 1.54 3.33 .595
Original 202 6.69 1.450 112 6.38 1.58 314 6.58 1.53 1.77 .310

Agreeability 202 6.96 1.19 115 6.99 1.17 317 6.97 1.18 -0.20 .517
Tender hearted 201 6.93 1.70 1 14 7.06 1.60 315 6.97 1.66 -0.70 .370
Agreeable 202 6.96 1.28 114 6.96 1.29 316 6.96 1.28 -0.00 .507
Softhearted 201 6.55 1.63 l 13 6.68 1.61 314 6.60 1.62 -0.68 .304
Kind 202 7.41 1.25 111 7.28 1.41 313 7.36 1.31 0.85 .555

Neuroticism 202 4.07 1.53 114 4.15 1.49 316 4.10 1.51 0.41 .663
Moody 200 4.22 1.95 l 12 4.18 2.08 312 4.21 1.99 0.18 .638
Temperamental 202 3.73 1.92 1 14 3.84 1.79 316 3.77 1.87 -0.50 .069
Emotional 201 4.74 2.02 1 14 4.73 1.87 315 4.74 1.96 0.06 .255
Touchy 201 3.60 1.74 113 3.83 1.87 314 3.68 1.79 -1 . 12 .395

Need for Arousal 203 6.06 1.63 114 5.01 1.72 317 5.68 1.74 5.38 .276
Actively seek out new 203 7.15 1.44 1 13 6.16 1.81 316 6.79 1.65 5.31 .002
ex errences
Drgwn to experiences with 203 5.75 2.02 114 4.75 1.99 317 5.39 2.07 4.28 .784
an element of dan er
Seek an adrenalinegrush 203 5.39 2.14 1 14 4.28 2.06 317 4.99 2.18 4.50 .746
Enjoy taking more risks 203 5.95 1.94 114 4.89 2.13 318 5.57 2.07 4.47 .141

than others

264

Table 62 Continued

 

 

see themselves in everyday life, 1 =

never and 9 = always.

265

Physical/Body Needs 203 6.05 1.65 114 5.69 1.70 317 5.92 1.67 1.84 .669
Focusonmybodyand 202 6.14 1.85 114 5.69 1.92 316 5.98 1.89 2.03 .553
how
it feels
Devotetirneeachdayto 203 5.99 1.98 114 5.55 1.93 317 5.83 1.97 1.90 .734
improving my body
Workhardtokeepmy 203 6.23 2.00 114 5.81 1.99 317 6.08 2.00 1.80 .873
body
healthy
Feelmaking mybody 203 5.84 1.84 114 5.71 2.02 317 5.79 1.90 0.57 .234
look
good is important
MaterialNeeds 203 3.74 1.85 114 3.82 1.78 317 3.77 1.82 -O.36 .520
Enjoy buying expensive 203 4.25 2.34 114 4.16 2.04 317 4.22 2.24 0.36 .020
Products
Liketoownniceproducts 203 3.92 2.13 114 4.01 1.98 317 3.95 2.07 -0.38 .154
more than most people
Acquiring valuable 203 3.31 1.87 114 3.37 1.93 317 3.33 1.89 -0.28 .577
products is important to
me
Enjoyowning luxurious 203 3.50 2.13 114 3.75 2.05 317 3.59 2.10 -l.01 .478
_products
IBased on a nine-point scale where respondents indicated how often the characteristic describes how they

Appendix P: Descriptive Statistics Compound Traits and Items

266

Table 63

Descriptive Statistics for Compound Traits and Items

 

 

 

 

 

most important resource

1 . .
Based on a nrne-pornt scale where res
see themselves in everyday life, I =

 

 

 

 

 

 

 

 

 

 

267

 

pondents indicated how ofien the characteristic describes how
never and 9 = always

. Hard Soft
Compound Traits Adventure Adventure
and Items .
Traveler Traveler Total I Sig.
n M SD n M SD N M SD

Competitiveness 203 4,741 2.07 1 14 4.32 2.22 317 4.59 2.13 1.67 .096
Enjoy competition 203 5.06 2.25 114 4.63 2.32 317 4.91 2.28 1.62 .365
more than others
Feel it is important to 202 4.44 2.26 114 4.15 2.32 316 4.33 2.28 1.07 .543
outperform others
Enjoy testing my abilities 203 5.24 2.31 114 4.62 2.46 317 5.02 2.38 2.22 .191
against others’
Feel winning is extremely 203 4.22 2.31 114 3.89 2.48 317 4.10 2.38 1.18 .182
Important

Altruism 203 6.27 1.39 1 14 6.05 1.35 317 6.19 1.38 1.37 .438
Have an altruistic nature 199 6.31 1.72 114 6.09 1.93 313 6.23 1.80 1.06 .429
Give to others 203 6.74 1.51 1 13 6.67 1.48 316 6.72 1.49 0.38 .149
Sacrifice my goals to help 203 6.07 1.67 114 5.68 1.55 317 5.93 1.63 2.02 .365
Others
Selfless in giving time to 201 5.94 1.79 1 13 5.76 1.68 314 5.87 1.75 0.85 .473
others

Need for Learning 203 7.07 1.17 114 6.68 1.68 317 6.93 1.39 2.41 .050
Enjoy learning new things 203 7.29 1.39 114 6.81 1.68 317 7.11 1.52 2.73 .034
more than most people
People consider me to be 202 6.81 1.56 114 6.64 4.97 316 6.75 3.23 0.44 .042
Intellectual
Enjoy working on new 203 7.20 1.39 1 14 6.62 1.59 317 6.99 1.49 3.38 .149
ideas
Value information as the 203 6.97 1.52 114 6.65 1.50 317 6.85 1.52 -1.79 .616

they

Appendix Q: Descriptive Statistics Situational Traits and Items

268

Table 64

Descriptive Statistics Interest in Cultural Experiences

 

 

 

 

 

 

 

 

 

. . . Hard Soft
Situational Traits Adventure Adventure
and Items
Traveler Traveler Total I Sig.

n M SD n M SD N M SD
Interest in Cultural
Experiencesl 203 7.05 1.32 114 6.31 1.54 317 6.79 1.44 4.50 .121
Try to visit local museum or art .
galleryasltravel 203 6.85 1.71 114 6.35 2.06 317 6.67 1.85 2.33 013
Enjoy cultural immersion when
Itravel 203 7.17 1.58 113 6.30 1.89 316 6.86 1.74 4.38 .027
Seek hands-on cultural
encountersasltravel 202 6.92 1.80 113 5.95 2.06 315 6.57 1.95 4.34 .102
Embrace the world celebrate
its nuances as I travel

203 6.90 1.75 114 6.07 1.84 317 6.60 1.82 3.96 .471
Interested in traditions of
indigenous cultural
communities (festivals, rituals)
asItravel 203 7.12 1.64 114 6.30 1.89 317 6.82 1.78 4.03 .129
Travel should be about
enrichingknowledge 203 7.37 1.52 114 6.92 1.72 317 7.21 1.61 2.43 .441

g

IBased on a nine-point scale where respondents indicated how often th

 

 

 

 

 

 

 

 

they see themselves in everyday life, 1 = never and 9 = always.

269

 

 

 

 

 

 

e characteristic describes how

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