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THESIS

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Travel Behaviors of US. University Students: Involvement,
Push Motivations, Pull Motivations, Satisfaction, and
Destination Loyalty

presented by

Kakyom Kim

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PhD degree in Department of Community,
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TRAVEL BEHAVIORS OF US. UNIVERSITY STUDENTS:
TRAVEL INVOLVEMENT, PUSH MOTIVATIONS, PULL MOTIVATIONS,
SATISFACTION, AND DESTINATION LOYALTY
By

Kakyom Kim

A DISSERTATION
Submitted to Michigan State University
in partial fulﬁllment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Department of Community, Agriculture, Recreation, and Resource Studies

2006

ABSTRACT
TRAVEL BEHAVIORS OF US. UNIVERSITY STUDENTS:
TRAVEL INVOLVEMENT, PUSH MOTIVATIONS, PULL MOTIVATIONS,
SATISFACTION, AND DESTINATION LOYALTY
By

Kakyom Kim

This research was primarily designed (1) to identify travel, lodging and meal
characteristics of university students (enrolled at Michigan State University), (2) to
identify the most important push and pull motivation variables and delineate the
underlying push and pull motivational factors of university students, (3) to determine and

U (I

examine the structural associations among “travel involvement , push motivations
“pull motivations”, “satisfaction” with travel experience, and “destination loyalty” of
those students who took a pleasure trip during the last six months, (4) to verify if the
model was statistically acceptable for the university student market, and (5) to determine
the associations between the ﬁve model constructs and various proﬁle characteristics
such as gender, age, nationality, academic year, marital status, number of children, and
main source of funding for tuition.

A total of 411 responses to the Internet-based surveys of students enrolled at
Michigan State University provided the data to develop the structural equation model and
test seven model related hypotheses. Factor analyses conduced on the 3] push and 25
pull motivations resulted in six push and seven pull motivation factors. The following,
labels were assigned to the six push factors: “Getting away “Adventure and

excitement “Discovery and learning “Connecting with family andﬁ'iends

“Engaging nature and “Rejuvenation The seven pull factors included “Lodging and

7! (i U (C

transportation , Convenience and value , Recreation and entertainment ”, “Cultural
opportunities “Natural scenery “Sun and beaches and “Familyfriendly

Of a total of seven different model related hypotheses tested, 3 Hypotheses are
accepted because (1) “travel involvement ” has an extremely strong and positive direct
effect on the levels of “satisfaction ” with travel experience (H3), (2) “push motivations ”
have a strong positive direct effect on “pull motivations” (H4), and (3) the level of
“satisfaction ” with travel experience has a very strong and positive direct effect on
“destination loyalty " (H7). The results of these tests suggest that even though four of the
hypotheses are rejected, the model is statistically acceptable for the university travel
market. There are also statistically signiﬁcant associations between the model constructs
and various student proﬁle characteristics, including “age “nationality ”, “academic
year “marital status and “main source of funding for tuition

The results can be used for positioning destinations relative to certain markets
framing marketing communications and promotional campaigns. Distributing motivation-
speciﬁc messages to colleges and universities can be an effective way to encourage
students to decide to take vacation trips as well- as to promote domestic and international
visits. The push and pu11 factors help identify why and how students decide to take
vacation trips and select trip destinations, and provides researchers and practitioners an
opportunity for developing tourism products, programs, and services for students.
Destination marketers and businesses should continuously concentrate on relationship

marketing strategies to retain existing student travelers based on the systematic

relationships tested by the model.

DEDICATION

This dissertation is dedicated
to my wife, Sangmin Lee-Kim,
whose sacriﬁce, support, and encouragement made this work possible,
to my son, Dongin Kim,
to my family
who supported and encouraged me along the way.

iv

ACKNOWLEDGEMENTS

I would like to take this opportunity to express my sincere appreciation to my
major professor and chair of my committee, Dr. Edward Mahoney, for his assistance and
leadership to successfully complete my programs and dissertation in the Department of
Community, Agriculture, Recreation, and Resource Studies at Michigan State University.
I would like to thank the members of my doctoral committee, Dr. Nora Rifon, Dr. James
Bristor, and Dr. Jeffrey Beck, for their valuable suggestions, opinions, and support.

I also thank the MSU students who participated in the surveys. Without their
participation, this research project would not have been possible. My thank also goes to
my relative, Chulyoung Kim, for assistance in collecting the data.

My special thanks with all my heart go to my wife, Sangmin Lee-Kim, for her
endless support, sacriﬁce, and love to complete my study, and my gorgeous son, Dongin
Kim. I also would like to express my truthful love and appreciation to my family, Seobun
Lim (my mother), Kakyoung Kim (my older brother), Kaknam Kim (my little brother),
Myoungsoon Kim (my older sister), and Chunhwa Kim (my older sister), for their

continuous love, encouragement, and support throughout my study and life.

TABLE OF CONTENTS

LIST OF TABLES ................................................................................... IX
LIST OF FIGURES ............................................................................... XII
LIST OF EXIBITS ................................................................................ XIII
CHAPTER 1
INTRODUCTION .............................................................................................................. 1
Travel and Tourism Market ............................................................................................ 1
Segmentation of the Student Travel Market ................................................................... 4
Problem Statement .......................................................................................................... 7
Research Objectives ........................................................................................................ 8
Research Hypotheses ...................................................................................................... 9
CHAPTER 2
THEORETICAL BACKGROUND .................................................................................. 12
Consumer and Travel Involvement ............................................................................... 12
Push Motivations and Pull Motivations ........................................................................ 17
Consumer and Travel Satisfaction ................................................................................ 21
Consumer and Destination Loyalty .............................................................................. 23
Concept of Structural Equation Model ......................................................................... 27
Prior Studies Employing the Structural Equation Model (SEM) ................................. 28
CHAPTER 3
RESEARCH METHODS ................................................................................................. 34
Advantages of using a Web-based Survey ................................................................... 34
Web Questionnaires ...................................................................................................... 36
First Web-Questionnaire ........................................................................................... 36
Second Web-Questionnaire ...................................................................................... 37
Data Collection ............................................................................................................. 39
Sampling Frame and Procedures .............................................................................. 39
Response Rates ......................................................................................................... 40
Data Preparation ........................................................................................................... 41
. Data Analysis ................................................................................................................ 41

vi

CHAPTER 4

RESULTS ......................................................................................................................... 43
Proﬁle of the Sample .................................................................................................... 43
Characteristics of Respondents’ Most Recent Trips ..................................................... 44
Lodging and Meal Characteristics ................................................................................ 46
Domestic and International Trip Destinations .............................................................. 48
Importance of Push and Pull Motivation Variables ...................................................... 50
Results of Independent Samples t-tests ........................................................................ 53

Differences in Push and Pull Motivations by Students Who Traveled to Domestic
and International Destinations .................................................................................. 54
Differences in Push and Pull Motivations between Domestic Student Travelers and
International Student Travelers ................................................................................. 57
Differences in Push and Pull Motivations by Students Traveling to Florida and Other
States ......................................................................................................................... 6O
Differences in Push and Pull Motivations by Students Traveling to Mexico and
Other Countries ......................................................................................................... 63
Differences in Travel Involvement by Nationality, Type of Trip, Domestic
Destinations, and International Destinations. ........................................................... 66
Results of Factor Analyses Performed on Push and Pull Motivation Variables .......... 67
Objectives of Factor Analysis ................................................................................... 67
Testing Adequacy of Factor Analysis ....................................................................... 68
Identiﬁcation of Push Motivation Factors ................................................................ 69
F ollow-up Factor Analysis without Four Push Motivation Items ............................ 72
Identiﬁcation of Pull Motivation Factors .................................................................. 72
Summative Scales of the Importance of Push and Pull Factors ............................... 76
Testing the Hypothesized Model .................................................................................. 77
Evaluation Procedures of the Measurement Model .................................................. 78
Evaluation of the Measurement Model ..................................................................... 79
Validation of the Hypothesized Model ..................................................................... 81
Testing the Hypotheses ............................................................................................. 84
Testing Gender Bias in the Model ................................................................................ 86
Testing an Alternative Sequenced Model ..................................................................... 87
Results of MANOVA: Associations between the Five Model Constructs and.Student
Proﬁle Characteristics ................................................................................................... 88

CHAPTER 5

CONCLUSIONS AND IMPLICATIONS ........................................................................ 99
Summary of the Findings ............................................................................................ 100
Implications ................................................................................................................ 1 O6

, Study Limitations and Recommendations for Future Studies .................................... 110

vii

APPENDIX A ................................................................................................................. 114

APPENDIX B ................................................................................................................. 119
APPENDIX C ................................................................................................................. 124
APPENDIX D ................................................................................................................. 128
REFERENCES ............................................................................................................... 130

viii

LIST OF TABLES

Table 1. Top 10 Domestic Destinations Visited by Tourists .................................... 2
Table 2. Top 10 International Destinations Visited by Tourists ................................ 3
Table 3. Types of Latent Constructs Examined by Prior Travel Researchers ............... 31
Table 4. Socio-demographic Proﬁles of Respondents .......................................... 45
Table 5. Characteristics of Respondents’ Most Recent Trips ................................. 47
Table 6. Mode of Lodging and Meal Characteristics of their Most Recent Trips .......... 48
Table 7. Destinations of Domestic Trips ......................................................... 49
Table 8. Destinations of International Trips ..................................................... 50
Table 9. Importance of Push Motivation Variables ............................................. 52
Table 10. Importance of Pull Motivation Variables ............................................ 53
Table 11. Differences in the Importance Assigned Push Motivations by Students
Traveling to Domestic and International Destinations ............................. 55
Table 12. Differences in the Importance Assigned Pull Motivations by Students
Traveling to Domestic and International Destinations .............................. 56
Table 13. Differences in the Importance Assigned Push Motivations between Domestic
Student Travelers and International Student Travelers ............................. 58
Table 14. Differences in the Importance Assigned Pull Motivations between Domestic
Student Travelers and International Student Travelers ............................. 59
Table 15. Differences in the Importance Assigned Push Motivations by Students
Traveling to Florida and Other States ................................................ 61
Table 16. Differences in the Importance Assigned Pull Motivations by Students
Traveling to Florida and Other States ................................................ 62
Table 17. Differences in the Importance Assigned Push Motivations by Students
Traveling to Mexico and Other Countries ........................................... 64
Table 18. Differences in the Importance Assigned Pull Motivations by Students

Traveling to Mexico and Other Countries ........................................... 65

ix

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.

Differences in the Level of Travel Involvement by Nationality, Type of Trip,

Domestic Destinations, and International Destinations ............................ 67
Results of Testing for Adequacy of Factor Analysis ............................... 68
Results of Factor Analysis Performed on Push Motivation Variables ........... 70
Results of Factor Analysis Performed on Pull Motivation Variables ............ 74
Summative Mean Scores of the Importance of the Push and Pull Factors ...... 77
Results of the Assessment of Fit of the 1St Measurement Model .................. 79
Results of Overall Model Fit indices for the 2“‘1 Measurement Model ........... 81

The Hypothesized Model’s Standardized Path Coefficients and t-values. . . ....83

Results of Overall Model Fit indices for the Hypothesized Model ............... 84

Results of the Tests of the Hypothesized Associations among Travel
Involvement, Push Motivation, Pull Motivation, Satisfaction, and Destination
Loyalty .................................................................................... 86

Overall Results of the MANOVA Test between the Five Model Constructs and
Student Proﬁle Characteristics ......................................................... 89

Results of the MANOVA Test of the Associations between Proﬁle
Characteristics and Travel Involvement, Push Motivations, Pull Motivations,
Satisfaction, and Destination Loyalty ................................................ 90

Results of the MANOVA Test of the Associations between Gender and Travel
Involvement, Push Motivations, Pull Motivations, Satisfaction, and Destination
Loyalty ................ ‘ .................................................................... 91

Results of the MANOVA Test of the Associations between Age and Travel
Involvement, Push Motivations, Pull Motivations, Satisfaction, and Destination
Loyalty .................................................................................... 92

Results of the MANOVA Test of the Associations between Nationality and
Travel Involvement, Push Motivations, Pull Motivations, Satisfaction, and
Destination Loyalty ...................................................................... 93

Results of the MANOVA Test of the Associations between Academic Year and
Travel Involvement, Push Motivations, Pull Motivations, Satisfaction, and
Destination Loyalty ...................................................................... 94

Table 35. Results of the MANOVA Test of the Associations between Marital Status and
Travel Involvement, Push Motivations, Pull Motivations, Satisfaction, and
Destination Loyalty ..................................................................... 95

Table 36. Results of the MANOVA Test of the Associations between Number of
Children and Travel Involvement, Push Motivations, Pull Motivations,
Satisfaction, and Destination Loyalty ................................................ 96

Table 37. Results of the MANOVA Test of the Associations between Main Source of
Funding for Tuition and Travel Involvement, Push Motivations, Pull
Motivations, Satisfaction, and Destination Loyalty ................................. 98

xi

LIST OF FIGURES
Figure l. Hypothetical Model for the Structural Relationships among Travel Involvement,
Push Motivations, Pull Motivations, Satisfaction, and Destination Loyalty ...... 10
Figure 2. Results of Scree Test Plot for the Importance of Push Motivation Variables. . .71
Figure 3. Results of Scree Test Plot for the Importance of Pull Motivation Variables. ...75

Figure 4. Results of the Structural Relationships among Travel Involvement,
Push Motivations, Pull Motivations, Satisfaction, and Destination Loyalty. . . ..82

Figure 5. An Alternative Sequenced Model for the Structural Relationships among Push

Motivations, Pull Motivations, Travel Involvement, Satisfaction, and
Destination Loyalty ...................................................................... 87

xii

LIST OF EXHIBITS

Exhibit 1. Main Stages of the Analysis ......................................................... 42

xiii

CHAPTER 1

INTRODUCTION

Travel and Tourism Market

The World Tourism Organization (WTO, 1993) deﬁnes tourism as “the activities
of persons traveling to and staying in places outside their usual environment for not more
than one consecutive year for leisure, business and other purposes”. The WTO deﬁnition
offers a broad range of key attributes on tourism. Numerous marketers and researchers
have emphasized the importance of the travel and tourism market as a major ﬁeld that
must be studied and developed based on its positive economic, social, cultural,
environmental, and political impacts on locals, cities, and countries (e.g., Briassoulis and
Straaten, 2000; Robinson, 1998). According to Page (2003), consumers’ largest spending
is associated with purchasing leisure products and services including trip related products,
resulting primarily from growing levels of disposable income in households.
Understanding the leisure and travel market through empirical research is important to
marketing organizations and agents in an effort to precisely predict individuals’ various
leisure behaviors as well as to propose appropriate travel products and services.

In light of the fact that the travel and tourism market is considered one of the
largest industries in the world (Buhalis and Costa, 2006), contributing greatly to the
development of the domestic as well as international economy, consumer behavior
research related to this market is important. Economic growth as a result of domestic and
international travel is evidenced by a Travel Industry Association of America (TIA,

2004) report, which found the number of domestic travelers increased 9.8% from 1,038.7

million in 1994 to 1,140 million in 2003. Total expenditures of travelers in 2003 were
$554.5 billion: $490 billion for domestic trips and $64.5 billion for international trips.
TIA forecasts that by 2006 the number of domestic travelers will be 1,218.4 million with
a total expenditure of $652.9 billion. In addition, TIA revealed the top domestic ‘
destinations visited by US. residents for two major types of trips which are leisure and
business trips (Table 1). The most popular destination selected by residents was
California, followed by Florida, Texas, New York, Pennsylvania, Illinois, Ohio, North

Carolina, Georgia, and Virginia.

Table 1. Top US. A. Destinations Visited by Tourists

 

 

Destinations Rank Spending (in $billions)
California 1 $71.56
Florida 2 $56.27
Texas 3 $34.59
New York 4 $35.43
Pennsylvania 5 $16.42
Illinois 6 $22.97
Ohio 7 --
North Carolina 8 --
Georgia 9 $15.65
Virginia 10 $14.30

 

Source: Travel Industry Association of America (2004).
--: No data provided.

The World Tourism Organization (WTO, 2003) reports the top international
destinations visited by tourists (Table 2). The most popular destination was France,
followed by Spain, United States, Italy, China, United Kingdom, Austria, Mexico,

Germany, and Canada. There will be more than 1.5 billion international tourists by 2020

(WTO, 2004). According to a study by the Ofﬁce of Travel and Tourism, over 25 million
US. resident travelers visited international destinations, an increase of 5% over 2002.
The study also reported international travelers spent $4,072 per travel party and $2,683

per visitor.

Table 2. Top 10 International Destinations Visited by Tourists

 

 

Destinations Rank Number Ofarrlvals
(In millrons)
France 1 750
Spain 2 525
United States 3 404
Italy 4 39.6
China 5 33.0
United Kingdom 6 24.8
Austria 7 191
Mexico 8 18.7
Germany 9 18.4
Canada 1 0 1 7. 5

 

Source: World Tourism Organization (2003).

These projections suggest a bright future for the travel industry, provided that
marketing organizations and businesses conduct consumer behavior and marketing
research utilizing research results in the design of marketing strategies. As previously
stated, this evidence underlines the importance of expanding knowledge and predicting
consumers’ purchase behaviors involving their feelings, thinking, and actions about

products and brands (Peter and Olson, 1999).

Segmentation of the Student Travel Market

Research has shown that segmenting a target market based on consumers’ needs
and desires is essential to design experiences, facilities, and services, and to develop
marketing communication strategies (Ahmed and Chon, 1994; Formica and Uysal,
1998; Sollner and Rese, 2001). A market segment is conceptually deﬁned as a group of
persons who have similar needs and wants toward particular stimuli (e.g., product
attributes, service, advertising messages, pricing), which implies that marketing
strategies should be developed speciﬁc to different segments (Sollner and Rese, 2001)
and a target market is indispensable for establishing an effective marketing system
(McIntosh, Goeldner, and Ritchie, 1995). Formica and Uysal (1998) emphasize that
segmentation is important because it helps identify and proﬁle existing customers, and
communicate with potential customers. As suggested by Ahmed and Chon (1994),
travel marketers need to understand distinctive and unique characteristics of travelers to
effectively design and develop travelers’ products. For example, it may be especially
effective for travel and tourism marketers to customize marketing strategies for the
student travel market because university students are likely to have different attitudes or
perspectives about travel, different motivations inﬂuencing trip decisions, and various
satisfaction levels positively inﬂuencing destination loyalty.

Enrollment at colleges and universities is at an all time high with the trend
expected to continue. The U. S. Census Bureau (2004) estimates that approximately 16
million persons were enrolled in colleges and universities in 2001 and they forecast there
will be over 17 million college students by 2012. The growing population of college

students will have a positive impact on the college travel market (Mattila,

Apostolopoulos, Sonmez, Yu, and Sasidharan, 2001). The student market is generating a
large portion of proﬁts and constitutes a large market segment inside the entire travel
system (Bywater, 1993; Richards and Wilson, 2004). The Federation of International
Youth Travel Organizations (2003) reports young and youth travelers consist of more
than 20% of the total international arrivals as “loyal repeat consumers” and recommends
that travel sectors focus on this market by providing speciﬁc products and services to
meet their individual needs and desires to travel.

To capitalize on this emerging student travel market, it is ﬁrndarnental to identify
and forecast consumers’ product choices and behaviors that must be addressed by
marketers and researchers (Peter and Olson, 1999). When it comes to travel decisions,
product (e. g., destinations) choices involve two sequential steps: ﬁrst deciding whether to
travel and then selecting where to travel (Klenosky, 2002). From this perspective, travel
involvement and motivation are important factors in understanding the student’s
decisions and individual relevance to travel toward speciﬁc travel destinations for
pleasure or vacation (Josiam, Smeaton, and Clements, 1999). While these two elements,
as key factors of traveler’s psychological features, should be thoroughly examined to
promote tourist visits, there has been relatively little information associated with these
and other related variables such as satisfaction with travel experience and intention to
revisit either domestic or international travel destinations in the student travel market.

A number of researchers have segmented the college student travel market using
various segmentation bases including travel motivations (e. g., Josiam, Smeaton, and
Clements, 1999; Kim and J ogaratnarn, 2002; Klenosky, 2002; Richard and Wilson,

2004), preferred leisure related activities and various travel patterns including

transportation, meal, and accommodation selections (Bywater, 1993; Carr, 1999; Carr
2002; Chadee and Cutler, 1996; Field, 1999; Hsu and Sung, 1997; Kim and Jogaratnam,
2003; Michael, Armstrong, and King, 2003; Pizarn et al., 2004; Richards and Wilson,
2004; Shoham, Schrage, and Eeden, 2004), satisfaction (e.g., Babin and Kim, 2001), and
other behaviors based on demographic characteristics (e.g., Carr, 2001; Mattila, et al.,
2001 ), destination images (e.g., Michael, Armstrong, and King, 2003; Son and Pearce,
2005), and travel planning (e.g., Bai, Hu, Elsworth, and Countryman2004). These
researcher all emphasize the importance of the student travel market, and they identiﬁed
some interesting characteristics of student vacationers both domestically and
internationally. Some of the studies attempted to determine what factors were most
important in ﬁnding travel decisions and destination selections of college student
vacationers (Josiam, Smeaton, and Clements, 1999; Kim and Jogaratnam, 2002;
Klenosky, 2002; Richards and Wilson, 2004; Son and Pearce, 2005). For instance,
Richards and Wilson (2004) employed an email/Internet survey to assess motivations of
international student travelers who booked travel products with travel agencies. Findings
suggest that there are motivational differences across international destinations, travel-
styles (backpackers, travelers, and tourists), and traveler types (i.e., student tourists
versus non-student tourists). With respect to travel decisions, Kim and Jogaratnam (2002)
extensively identiﬁed several motivational factors of domestic and Asian international
student travelers in the US. and found some signiﬁcant differences and similarities in the
motivational factors between the two groups. In addition, a study by Shoham, Schrage,
and Eeden (2004), as an extension of Hsu and Sung’s study (1997), analyzed a sample

obtained from college students in three different countries and conﬁrmed differences in

various travel pattems and activities among the groups. These studies commonly
emphasize the growing number of college/university students enrolled and student
travelers, having more time to travel than other segments during spring, summer, and
winter breaks, thus making a ﬁnancially signiﬁcant contribution to the travel and tourism

industry.

Problem Statement

Despite numerous studies of the student travel market, additional research is
needed to better understand more speciﬁc behaviors of student travelers to better target
and service this market. For instance, it would be very useful for travel academicians and
practitioners to increase their knowledge about the student traveler’s overall beliefs or
importance about travel, travel decisions, satisfaction with travel experiences, and their
intentions to retum/re-visit to previous travel destinations. Furthermore, previous studies
examining students’ travel behaviors have not investigated relationships among these
travel factors. As a result, destination marketers targeting the student market have faced
difﬁculty in developing and designing potential travel products and programs to promote
student travel. This current research trend implies a strong need to focus on the cause and
effect relationships between various sets of variables (e. g., motivations, perceptions,
value creating attributes) rather than just describing student trip patterns or behaviors.

Emphasizing the economic importance of the student travel market, Chadee and
Justine (1996) point out travel patterns, behaviors, and motivations of college students
are not well recognized for either domestic or international travel. Besides, this travel

market has not well been segmented using various travel behaviors (Bywater 1993,

Field, 1999; Shoham, Schrage, and Eeden, 2004). This fact is evidence that tourism
researchers have not comprehensively examined effects or relationships of a
combination of factors that inﬂuence students’ travel decisions, measuring their
satisfaction with travel experience, and predicting intention to revisit travel destinations.
Therefore, additional efforts are needed to identify and test factors affecting students’
decisions to travel, their level of satisfaction with travel experience, and intentions to
revisit the same destinations (destination loyalty). Prior studies have failed to determine
whether travel involvement directly inﬂuences push and pull motivations and other
factors including travel satisfaction and destination loyalty in the student and/or travel
market. Further, efforts to apply the Structural Equation Model (SEM) to ascertain and

model factors related to student travel decisions and behaviors have not been attempted.

Research Objectives

This research is designed to achieve the following objectives:

1. To identify various travel, lodging, and meal characteristics of university
students for their most recent vacation trips,

2. To identify the most important push and pull motivation variables and the
underlying push and pull motivational factors of university student travelers,

3. To determine and examine the structural associations among travel
involvement, push motivations, pull motivations, satisfaction with travel
experience, and destination loyalty of university student travelers employing
the Structural Equation Model,

4. To determine if the model was statistically acceptable in the university student

market, and
5. To determine associations between the ﬁve model constructs and student

various proﬁle characteristics.

Research Hypotheses

An empirical study of the structural relationships among the “travel
involvement “push motivations “pull motivations “satisfaction” with travel
experiences, and “destination loyalty ” constructs will contribute to a deeper and more
functional understanding of university student travel behaviors. Figure l graphically
represents the hypothesized model for the causal relationships among the ﬁve latent
constructs. The exogenous construct (cause) of the model is “travel involvement”, while
the endogenous constructs (effect) are “push motivations “pull motivations
“satisfaction” with travel experience, and “destination loyalty”.

Based on an extensive literature review of involvement, push motivations, pull

motivations, satisfaction, and destination loyalty, the following hypotheses are proposed:

Research Hypothesis 1: Travel involvement of student travelers has a positive
direct effect on push motivations.

Research Hypothesis 2: Travel involvement of student travelers has a positive
direct effect on pull motivations.

Research Hypothesis 3 : Travel involvement of student travelers has a positive

direct effect on the levels of satisfaction with travel experiences.

Figure 1. Hypothetical Model for the Structural Relationships among Travel Involvement,
Push Motivations, Pull Motivations, Satisfaction, and Destination Loyalty

Travel
Involvement

Push Pull
Motivations Motivations

 

 

V

Satisfaction

 

 
   
   

Destination
Loyalty

10

Research Hypothesis 4 .' Push motivations of student travelers have positive direct
eﬂects on pull motivations.

Research Hypothesis 5 : Push motivations of student travelers have positive direct
effects on the levels of satisfaction with travel experiences.

Research Hypothesis 6: Pull motivations of student travelers have positive direct
eﬂects on the levels of satisfaction with travel experiences.

Research Hypothesis 7: Levels of satisfaction with travel experiences have

positive direct effects on destination loyalty.

Testing this model will improve understanding of factors that inﬂuence student
travel decisions as well as behaviors that both measure satisfaction level and predict
future intention to return to the same destination as a basis for product development and

marketing communications and decisions.

11

CHAPTER 2

THEORETICAL BACKGROUND

This chapter provides an extensive review of literature related to each latent
construct based on previous studies in the marketing and tourism industry. It details a
review of (1) consumer and travel involvement, (2) push and pull motivations, (3)
consumer and travel satisfaction, (4) consumer and destination loyalty, and (5) the
concept of structural equation model along with major studies that researchers have
undertaken. This chapter focuses on how each construct is interrelated and relevant to this

study and thus suggests the strong need and theoretical importance of the current study.

Consumer and Travel Involvement

Involvement has been recognized as an important concept for marketers and
researchers because it helps provide insightful perspective on understanding consumer’s
purchase behaviors (Arora, 1982; Hwang, Lee, and Chen, 2005; Cai, Feng, and Breiter,
2004; Gursoy and Gavcar, 2003; Josiam, Smeaton, and Clements, 1999; Laurent and
Kapferer, 1985; Lehto, O’Leary, and Morrison, 2004; Mittal, 1995; Peter and Olson,
1999; Varki and Wong, 2003). Laurent et a1. (1985) described early on that involvement
is “a causal or motivation variable with a number of consequences on the consumer’s
purchase and communication behavior” (p. 42). In the marketing industry, involvement is
conceptually deﬁned as “consumers’ perceptions of importance or personal relevance for
an object, event, or activity” (Peter and Olson, 1999, p. 88); more speciﬁcally, product

involvement is viewed as “consumers’ knowledge about the personal relevance of the

12

products in their lives” (p. 53). In a similar view, involvement is regarded as “the level of
perceived personal importance evoked by a stimulus (or stimuli) within a speciﬁc
situation” (Hwang, Lee, and Chen, 2005, p. 145). From this perspective, involvement in
the tourism industry is described as “the interest or motivational intensity toward a
vacation place with behavioral consequences” (Lehto, O’Leary, and Morrison, 2004, p.
805)

Peter and Olson (1999) state that consumers have personal relationships with
speciﬁc products or brands. Within this context, if consumers consider a purchase object
or service to be either relevant or important to their needs and wants, they tend to have a
relatively high involvement level. In contrast, if consumers consider a purchase object or
service to be either irrelevant or unimportant to their needs and wants, they tend to have a
low involvement level. According to Zaichkowsky (1985), the involvement scale is
considered unidimensional. However, another study by Zaichkowsky (1987) indicates
two different dimensions exist in consumer involvement including “cognitive” and
“affective”. A number of studies also suggest that the involvement scale be multi-
dimensional because consurners have various levels of involvement on products or
objects (e. g., Cai, F eng, and Breiter, 2004; Gursoy and Gavcar, 2003; Laurent and
Kapferer, 1985; Lehto, O’Leary, and Morrison, 2004). Laurent and Kapferer (1985)
explored four dimensions of involvement including “importance of negative
consequences”, “subjective probability of mispurchase”, “pleasure value”, and “sign
values” which has been known as “consumer involvement proﬁle (CIP)”. Lehto, O’Leary,

99 ‘6

and Morrison (2004) developed four dimensions of involvement including “prior , risk”,

99 6‘

“activity , economic involvements”. Their study empirically tested the relationships

13

among various types of involvement (e. g., prior, risk, activity, economic) of the UK
tourists visiting the US. and found signiﬁcant effects of prior experience on activity and
economic involvements. Gursoy and Gavcar (2003) also identiﬁed three dimensions of
tourist involvement including “pleasure/interest”, “risk probability”, and “risk
importance”. These studies are outstanding because they attempted to deeply measure
consumer involvernents based on various consumer products or traveler perspectives.
Under the assumption that those who have high involvement levels with a product,
brand, or service would be more interested in or motivated to ﬁnd its related information
(Varki and Wong, 2003) than those who have not, the current researcher viewed
involvement may affect consumers’ or travelers’ motivation as a previous stage of
decisions to travel in the travel industry. In other words, given that a product can be
replaced with personal importance or value of a particular type of trip (e. g., pleasure and
vacation trips including spring break trip, summer break trip, and winter break trip of
university students), the researcher believes travel involvement probably occurs before
students are motivated to travel to speciﬁc destinations. For example, Josiam et a1. (1999)
examined the relationship between travel involvement and travel motivations adopting
the involvement scaling items proposed by Zaichkowsky (1985). The key ﬁnding
revealed that high levels of involvement were signiﬁcantly related to the push (decisions
to travel) / pull motivations (choice of destinations). Their study was signiﬁcant because
it attempted to identify travel involvement associated with push/pull motivations of
student vacationers for spring breaks. The study, however, did not attempt to determine

any structural association between the two sets of variables.

14

Gursoy and Gavcar (2003) tested extensively whether the consumer involvement
proﬁle (CIP) proposed by Laurent and Kapferer (1985) would be applicable in the
international travel market by interviewing hotel tourists in Turkey. Results conﬁrmed
the existence of three involvement dimensional constructs including “pleasure/interest”,
“risk probability”, and “risk importance” and these constructs directly inﬂuenced the
“knowledge” construct about destinations. Targeting the women travel market, Zalatan
(1998) explored wives’ involvement in a decision-making process in taking vacation trips.
Analysis suggested that respondents placed high levels of involvement on shopping,
selecting restaurants, collecting information, and preparing luggage and concluded
socioeconomic and trip characteristics had positive effects on levels of involvement in
tourism decision processes.

In a recent study, surveying multi-national park visitors in Taiwan, Hwang, Lee,
and Chen (2005) tested if travel involvement determined other related variables including
place attachment and perceived interpretation of service quality. The construct of travel
involvement consisted of ﬁve factors: importance, pleasure, sign, risk probability, and
risk consequence about the parks. Findings suggested travel involvement had a positive
inﬂuence on perceived interpretation service quality, which indicates that visitors who
have high involvement are likely to care about the parks as being loyal visitors.

Hwang, Lee, and Chen (2005) note a current research trend in consumer
behaviors is investigating causal relationships between involvement and other related
variables. The reason being is that relationships can help predict how and why individuals
are involved in travel and how travel decisions are made regarding preferred destinations

for vacation or pleasure. Further, a study of tourists’ involvement assists marketers to

15

clearly identify their decision-making processes related to vacation trips (Zalatan, 1998).
Nevertheless, to date no current studies have empirically tested structural relationships
between involvement and other variables in the travel and tourism market, including the
university student market. Therefore, examining involvement of travelers should be
beneﬁcial to destination marketers and researchers because individuals’ various needs,
attitude, and lifestyle can be identiﬁed and understood (Sung, 2004).

Prior studies by adopting and modifying these involvement scales have
investigated the signiﬁcant associations between involvement and various consumer
variables, including satisfaction and service quality (Hwang, Lee, Chen, 2005; Suh, Lee,
Park, and Shin, 1997), the level of opinion leadership (J amrozy, Backman, and Backman,
1996), tourism decision-making (Zalatan, 1998), and tourist motivations (Josiam et al.,
1999). However, the various scales have not been much applied and developed by
tourism researchers due to difﬁculty in measuring tourist involvement on pleasure trips.

In the university student market, one study (J osiam et al., 1999) attempted to
apply the involvement scale to students taking vacation trips because of its easiness and
simplicity to conduct a survey. The current research initially adopted a total of 15
involvement items initially used by Josiam et a1. (1999) developing the 20 items explored
by Zaichkowsky (1985) who referred to “personal involvement inventory (PII). For face
validity, a couple of leisure and tourism professionals (e. g., the committee chairperson)
reviewed and modiﬁed the items, thus discarding 6 items that were considered
semantically duplicated to each other. There are two reasons for adopting and modifying
the involvement items suggested by J osiam et a1. (1999) and Zaichkowsky (1985). They

include that (1) reducing the number of items proposed Zaichkowsky (1985) is

16

recommended by a study (Mittal, 1995) because its low content validity, and (2) a study
demonstrates that the involvement scale is unidimensional in the tourism context

(J amrozy, Backman, and Backman, 1996).

Push Motivations and Pull Motivations

Understanding how travel decisions are made is considered important for travel
businesses to communicate with potential travelers (Beard and Ragheb, 1983; Bieger
and Laesser, 2002; Cha, McCleary, and Uysal, 1995; Crompton, 1979; Mannell and Iso-
Ahola, 1987; Kozak, 2002; Ross and Iso-Ahola, 1991). Within this context, numerous
travel marketers and researchers have sought to understand how and why consumers
make travel decisions about domestic or international travel by focusing on push and
pull motivational factors (Backman et al., 1995; Baloglu and Uysal, 1996; Kim and Lee,
2002; J ang and Cai, 2002; Sirakaya, Uysal, and Yoshioka, 2003). Essentially,
motivations are described as “a state of need, a condition that serves as a driving force
to display different kinds of behavior toward certain types of activities, deve10ping
preferences, arriving at some expected satisfactory outcome” (Backman et al., 1995, p.
17).

Numerous travel and tourism researchers have stressed two main components of
travel motivations that include “push and pull forces”. They represent that individuals’
travel decisions are best explained and predicted by the push and pull approach within
this industry. According to Crompton (1979), push motivational force is deﬁned as “the
desire to travel”, while pull motivational force is viewed as “the choice of destination”.

Within this concept, Klenosky (2002) notes that push factors are associated with

17

“whether to go”, while pull factors are related to “where to go” which are decided in
two separate points in time. It is important to know, however, that the two sets of forces
are not independent even if they appear to be conceptually distinguished from each
other (Figure 1). It implies that individuals’ decisions to travel occur in a two-sequential
stage consciously or unconsciously. In other words, individuals are ﬁrst pushed by
internal or intangible needs such as personal escape, psychological or physical health,
thrill and adventure, and social interactions (Baloglu and Uysal, 1996). They are then
pulled by external or tangible resources such as natural or artiﬁcial attractions existing
on trip destinations.

As another approach to travel motivation, Iso-Ahola (1982) addressed two sets
of motivational forces individuals travel for: “escaping and seeking”. The former is
regarded as the desire of people to leave their normal surroundings, while the latter is
regarded as the needs of people to acquire intrinsic rewards through trip experiences.
This approach associated with basic needs of travelers may be viewed as a form of push
forces, as noted by Fluker and Turner (2000). Based on this framework, other studies
(F luker and Turner, 2000; Ross and Iso-Ahola, 1991; Sirakaya, Uysal, and Yoshioka,
2003) further investigated segmentation of the leisure and pleasure travel market and
conﬁrmed that its approach was helpful for understanding individuals’ various travel
needs and desires.

Adopting the push and pull force approach, several researchers have extensively
tested various samples employing both qualitative and quantitative methods (Crompton,
1979; Baloglu and Uysal, 1996; Klenosky, 2002; Kim and Lee, 2002; Yuan and

McDonald, 1990). The push and pull forces were initially identiﬁed by Crompton (1979)

18

using unstructured in-depth interviews of 39 adult residents. After analyzing the
motivational factors inﬂuencing the selection of types of pleasure vacations and
destinations, the study classiﬁed a total of nine categories. Those categories were then
broken into two main domains, called “socio-psychological motives (push)” and “cultural
motives (pull)”. The former included escape from a perceived mundane environment,
exploration and evaluation of self: relaxation, prestige, regression, enhancement of
kinship relationships, and facilitation of social interaction, while novelty and education
were included in the latter. This study is noteworthy because understanding the nine
categories assist travel and tourism researchers conceptually and empirically to assess the
push and pull relationships.

Targeting the international market, Yuan and McDonald (1990) applied the push
and pull approach to assess travel motives of international travelers ﬁom four diverse
countries including West Germany, Japan, France, and the United Kingdom. The study
identiﬁed that not pull forces, but push forces differed signiﬁcantly across the countries.
Using a secondary data from Tourism Canada and the US Travel and Tourism, Baloglu
and Uysal (1996) analyzed a total of 1,212 responses to determine the existing
relationship between push and pull factors. The results of canonical analysis showed that
four determined push factors were signiﬁcantly associated with four determined pull
factors. However, the limitation of this study is that secondary data does not include a full
range of motivational factors and may cause difﬁculty of identifying any relationship
between push and pull factors. Interestingly, Klenosky (2002) investigated the push and
pull relationships employing the means-end approach that has been used for discovering

consumers’ preferences toward speciﬁc products they purchase and tracking individual

19

consequences from the use of the products. Employing a personal interview method of
students (N =53), this research demonstrated that push and pull factors were interrelated
to each other, although the variables asked included only pull motivation items. This
study does not provide good external validity due to the sampling approach used by the
researcher.

Kim and Lee (2002) undertook an extensive survey of domestic vacationers
(N=2,729) visiting National Parks and conﬁrmed the strong relationship between push
and pull motivational forces in the leisure travel market. The study reported that push
forces captured family togetherness and study, natural resources and health, escaping
from everyday routine, and adventure and building, while various tourist resources,
information and convenient facilities, and easy accessibility to national parks were
included in pull forces. A canonical correlation analysis then identiﬁed that the
associations between two sets of forces existed.

Previous research on travel motivation contends that the push and pull motivation
approach greatly helps anticipate why and how individuals travel toward speciﬁc
destinations. Thus, understanding push and pull motivation is considered critical because
it allows travel marketers to identify factors inﬂuencing individuals’ travel decisions to
meet their needs, desires, and consequences. Nevertheless, none of the studies have
empirically assessed structural relationships among push motivations, pull motivations,
and other factors such as involvement, satisfaction with travel experiences or destination
loyalty in the student market. The current research has viewed the push and pull

motivation as two separate and distinct constructs, given that people are ﬁrst pushed by

20

internal sources and then pulled by external sources at two different points. Within this

context, push factors are viewed as antecedent to pull factors (F luker and Turner, 2000).

Consumer and Travel Satisfaction

Marketing literature stresses that understanding consumer satisfaction is an
important concept and factor that positively inﬂuences building brand loyalty (Bearden
and Teel 1983; Haber and Lerner 1998; Kozak and Rimmington 2000; Peter and Olson
1999; Petrick 2004; Tse and Wilton 1988). Consumer satisfaction appears to be affective
or emotional dimensions and is different ﬁ'om other variables such as quality, price, and
value (Bowen, 2001; Bowen and Clarke, 2002). However, the other variables are
considered signiﬁcantly interrelated with satisfaction (Y uksel and Yuksel, 2002). There is
a general agreement that “the expectations and disconﬁrmation theory” best describe how
customer satisfaction and dissatisfaction are determined (e. g., Bearden and Teel 1983;
Tse and Wilton, 1988). According to this theory, expectations occur, as a pre-evaluation
formation and before consumers experience products or services, while disconﬁrmation,
as a post-evaluation formation, stems from the differences between perceived expectation
and actual performance (Peter and Olson, 1999). Therefore, identiﬁcation of consumers’
satisfaction level plays a vital role as an indicator of evaluating a speciﬁc product or
service that individuals experience (Qu and Ping, 1999).

Previous researchers have determined a positive relationship between satisfaction
and destination loyalty. For example, Bearden and Teel (1983) contend that consumer

satisfaction is associated with “repeat sales , positive word—of—mouth”, and “brand

loyalty”. Not surprisingly, satisﬁed tourists are more likely to revisit the same destination

21

and provide positive referrals to friends and relatives indicating destination loyalty (Y oon
and Uysal 2005). Hence, measuring factors that inﬂuence or are inﬂuenced by
satisfaction should be essential because tourist satisfaction is positively associated with
successful businesses and destinations in the travel and service industry (Haber and
Lerner 1998).

Kozak and Rimmington (2000) employed factor and regression procedures to
examine the relationships among satisfaction with a destination, intentions to re-visit, and
word-of-mouth referrals. Their study which collected survey data from British tourists
found relationships between the three constructs and concluded that more satisﬁed
tourists were more likely to revisit and recommend the destination to others. Petrick
(2004) tested the relationships among satisfaction, perceived value, and quality in order
to predict repurchase intentions of travelers. The analysis implied that quality, not
satisfaction, was the best factor of predicting repurchase intentions. In addition, the
association between culture and satisfaction was investigated by surveying Taiwanese
vacationers visiting Australia (Master and Prideaux, 2000). The study reported culture
was not associated with traveler satisfaction level and concluded service quality was a
key factor to successful travel businesses.

In the travel industry, antecedents of tourist satisfaction have been know as “place
attachment” (Hwang et al., 2005), “culture and perception” (Reisinger and Turner, 1999),
“push/pull motivations” (Y oon and Uysal, 2005), “perceived value” (Gallarza and Saura,
2006), and “quality of the opportunity” (Baker and Crompton, 2000). The authors
extensively investigated these factors inﬂuencing tourist satisfaction with travel

experience. Of these empirical researches, a study by Gallarza and Saura (2006) related

22

to the university market attempted to investigate if perceived value would inﬂuence
satisfaction of Spanish university students for spring break. The study conﬁrmed the
signiﬁcant effect of perceived value on satisfaction.

Heung and Cheng (2000) also noted that assessing satisfaction levels relevant to
tangible or intangible products that consumers experience was critical for- travel retailers
to effectively target tourists. Using data obtained from interviews of international visitors
to Hong Kong, the study identiﬁed four shopping attributes including tangible quality,
staff service quality, product value, and product reliability to test if they were related to
satisfaction levels. Use of the multiple regression procedure indicated that staff service
quality was the most important factor in predicting satisfaction levels, followed by
product value and product reliability. However, tangible quality was not a good predictor
of satisfaction with shopping.

Previous studies have focused on the relationships between satisfaction with
travel experience and some related variables, but none in the university market have
empirically investigated the relationships between satisfaction and critical variables to
predict travel behaviors (e.g., travel involvement, push motivations, and pull motivations)
utilizing a Structural Equation Modeling approach. Further, few studies have attempted to
determine if involvement, as an antecedent of satisfaction, is associated with satisfaction

with travel experience in the university student market.
Consumer and Destination Loyalty

Product or brand loyalty has been recognized as a key concept in the ﬁeld of

relationship marketing and has received great attention from marketers and researchers

23

because understanding customer (or destination) loyalty can help not only identify
consumers’ needs and wants (Chen and Gursoy, 2001; Oppermann, 2000), but also
predict the future demand and revenues (Datta, 2003; Huddleston, Whipple, and
VanAuken, 2004). Irnportantly, creating and keeping loyalty with consumers is regarded
as an ultimate factor for successful management of businesses.

Brand loyalty refers to “an intrinsic commitment to repeatedly purchase a
particular brand and it is differentiated from repeat purchase behavior because the later
focuses only on the behavioral action without concern for the reasons for the habitual
response” (Peter and Olson, 1999, p. 406). From this perspective, a product in the travel
industry is regarded as a travel destination that possesses a variety of travel products
including natural resources, artiﬁcial attractions, or cultures. Viewing destination loyalty
as “a repeat behavior” of tourists (e.g., visiting the same destination), Niininen, Szivas,
and Riley (2004) surveyed vacationers visiting main holiday destinations in UK. and
revealed that about 60 % of the respondents revisited the same destinations three or more
times over a ﬁve year period. It is, however, pointed out that only repeat purchase
behavior cannot be sufﬁcient for explaining why consumers purchase the same products
or services over and over (Huddleston et al., 2004; Oliver, 1999; Peter and Olson, 1999).

In addition, Chen and Gursoy (2001) disagree that repeat behavior (visitation)
fully reﬂects travelers’ loyalty that should include recommendation to others. Although it
is hard to conceptualize loyalty, it suggests both behavioral and attitudinal approaches
should be simultaneously manipulated into tourism (Riley, Niininen, Szivas, and Willis,
2001). For instance, viewing loyalty as the relationship between attitude and repeat

patronage behavior, Huddleston et a1. (2004) classiﬁed four types of loyalty: “no loyalty”,

24

99 6‘

“spurious loyalty , latent loyalty”, and “loyalty” employing focus group interviews in
the food industry. Content Analysis found that respondents were close to spurious loyalty
which means “high repeat patronage and low relative attitude” towards preferred stores.

Oliver (1999) states that consumers become loyal moving from a cognitive level
to an affective level according to four sequential stages: (1) cognitive loyalty, (2)
affective loyalty, (3) conative loyalty, and (4) action loyalty. In the ﬁrst stage, customers
believe that “one brand is preferable to its alternatives” in terms of the brand attribute
information available. The second stage is that “a liking or attitude toward the brand is
developed on the basis of cumulatively satisfying usage occasions”. The third stage is
related to “the behavioral intention inﬂuenced by repeated episodes of positive affect
toward the brand”. Consumers are then involved in “action control” that means being
ready to purchase. Moreover, the author argues that, with respect to the relationship
between satisfaction and loyalty, satisfaction is not a reliable predictor of consumer
loyalty since dissatisfaction does not affect the loyalty state and loyalty is independent of
satisfaction.

In the ﬁeld of consumer marketing, using in-depth and focus group interviews of
25 and 54 years age groups, Datta (2003) investigated and found the product performance,
satisfaction of customers, and levels of involvement were good predictors of brand
loyalty. Huddleston et al. (2004) also stated that satisfaction inﬂuenced loyalty, which
were associated with two indicators: purchase intention and positive word-of-mouth.

Destination loyalty, in the scope of the travel industry, has been also regarded as
the ﬁnal key factor to predict the future demand by being competitive to other similar

destinations (Chen and Gursoy, 2001; Oppermann, 2000; Petric and Backman, 2002;

25

Petrick, Morais, and Norman, 2001; Petrick, Tonner, and Quinn, 2006; Yoon and Uysal,
2005). For example, Chen and Gursoy (2001) examined determinants of destination
loyalty analyzing Korean outbound tourists. The analysis using a multiple regression
procedure assumed that destination loyalty was positively associated with different
culture experiences, safety, and convenient transportation. The study results suggest that
destination marketers should understand why tourists are becoming loyal and what
factors affect loyalty at destinations. The most comprehensive approach to destination
loyalty was shown in a study by Opperrnann (2000). To capture deeper meanings of
loyalty toward destinations, the researcher utilized “lifelong travel patterns” of residents
in New Zealand, which was designed to gather information about the frequency of visit to
Australia for 5 year and 10 year intervals. This study is meaningful in that the survey
explored the comparisons of “the past visit” verses “actual visit” and “predicted visit”
verses “actual visit” each travel interval. However, this study may possess a limit of
being based on solely a behavioral viewpoint of loyalty and excluding the perspective of
positive word-of-mouth (e. g., recommendation to ﬁiends or relatives).

In the cruise market, Petrick, Tonner, and Quinn (2006) explored how moment of
truth was related to passengers’ repurchase intentions employing critical incident
technique (CIT) that is used to comprehend tourists’ true stories or episodes about their
travel experiences. Based on travel attributes described by cruise respondents, either
positive incidents or negative incidents were classiﬁed by travel experts. Results
indicated that the negative incidents included excursion and ports of call, price and
expense, entertainment and activities, children and teen issues, food and beverage,

(service issues, staff issues, ship facilities, polices and procedures, and miscellaneous,

26

whereas the positive incidents included service, staff and crew, ship-related amenities,
cabin and room, excursion and ports of call, dining and food, entertainment, and
miscellaneous. Interestingly, only negative incidents were related to overall satisfaction,
perceived value, word of mouth, and repurchase intentions. This study provides very
speciﬁc and critical factors that the cruise market should focus on and consider in order
to encourage repurchase intentions of passengers.

To reﬂect a full range of destination loyalty, the current study adopts three
operational deﬁnitions from previous studies including ‘likeliness (attitude)’, ‘revisit
(probability)’, and ‘recommendation (word-of-mouth)’ (Huddleston, Whipple, and

VanAuken, 2004; Oppermann, 2000; Petrick , Morais, and Norman, 2001).

Concept of Structural Equation Model

The principal purpose of the Structural Equation Model is “to clarify the patterns
of a series of inter-related dependence relationships simultaneously between a set of
latent constructs, each measured by one or more manifest variables” (Reisinger and
Turner, 1999, p. 71). Latent constructs (or theoretical constructs) refer to unobserved
variables or factors measured by manifest variables, which are actually observed by
researchers. Basically, latent constructs consist of two types of variables: exogenous
(independent or cause) and endogenous (dependent or effect) variables. For example,
travel involvement (an exogenous construct) might include manifest variables such as
“the pleasure trip you took was unimportant or important”, “the pleasure trip you took
was not beneﬁcial or beneﬁcial”, or “the pleasure trip you took was boring or exciting”.

. This construct is not inﬂuenced by other variables, but only directly/indirectly inﬂuences

27

other variables such as satisfaction with travel and destination loyalty. Conversely,
satisfaction with travel (an endogenous construct) is inﬂuenced by other variables (e. g.,
travel involvement, push motivations, pull motivations, or quality of travel products) and

it also directly or indirectly affects other variables (e.g., destination loyalty).

Prior Studies Employing the Structural Equation Model (SEM)

As presented in Table 3, 3 Structural Equation Modeling Approach has been
recognized and employed by a number of travel and tourism researchers as an important
technique to assess structural associations between and/or among various travel factors
(Gursoy, Jurowski, and Uysal, 2002; Gursoy and Rutherford, 2004; Hwang et al., 2005;
Kashyap and Bojanic, 2000; Kim and Littrell, 1999; Lee and Graefe, 2003; Lindberg and
Johnson, 1997; Morais, Dorsch, and Backman, 2004; Petrick and Backman, 2002; Petrick,
Morais, and Norman, 2001; Reisinger and Turner, 1999; Reisinger and Turner, 2002;
Swanson and Horridge, 2004; Yoon, Gursoy, and Chen, 2001; Yoon and Uysal, 2005).
Of these studies, one by Reisinger and Turner (1999) is outstanding in terms of
introducing various types of structural models and providing the appropriate
interpretations of statistical results through the overall procedures of SEM. The study also
extensively examines testing possible models related to tourism research.

A review of SEM suggests that four main types of research exist in the travel and
tourism market. They include “relationships between tourism impacts and related

99 ‘6

variables (e. g., resident or host attitude) , relationships between travel motivations and

related variables (e.g., satisfaction with travel and product attributes) , relationships

between travel satisfaction and related variables (e.g., destination loyalty)”, and

28

relationships between travel decision-making process (e. g., theory of planned behavior)
and behavioral intention. For example, by targeting the association between resident
attitudes and tourism impacts, the structural equation modeling approach was undertaken
by Lindberg and Johnson (1997), Gmsoy et a1. (2002), and Gursoy and Rutherford (2004).
The underlying assumption of the studies were that resident or community attitudes were
inﬂuenced by economic and congestion impacts, tourism development, and determinants
of resident’s support, which include ecocentric values, utilization of tourism resource
base, community concern and attachment, state of the local economy, and economic,
social, and cultural beneﬁts.

In terms of tourism impact, Yoon et al. (2001) also attempted to ﬁgure out the
structural inﬂuences between four dimensions of tourism impacts and total impact and
tourism development through a typical mail survey of residents in the Norfolk/Virginia
Beach/Newport News area. The results of the analysis employing the LISEL (SEM
software) procedure reﬂected that the total tourism impacts had positive effects on the
economic and cultural impacts, but they were negatively associated with environmental
impacts.

Yoon and Uysal (2005) investigated the relationship between motivations,
satisfaction, and destination loyalty of hotel visitors in Northern Cyprus. The study found
tourism destination loyalty was inﬂuenced by motivation and satisfaction, additionally
conﬁrming signiﬁcant relationships between, two motivational forces, push and pull
factors, and destination loyalty. Consequently, this study is meaningful since the

structural relationships between motivations and satisfaction were initially explored and

29

identiﬁed in the tourism industry. However, this study was not associated with travel
involvement with the set of latent constructs.

Studies associated with tourism loyalty were undertaken by Petrick et al. (2001),
Morais, Dorsch, and Backman, (2004), and Petrick and Backman, (2002). Testing the
cause and effect among past behavior, satisfaction, perceived value, and intentions to
revisit, Petrick et a1. (2001) found intentions of visitors were signiﬁcantly inﬂuenced by
three of the constructs, but satisfaction was not predicted by past behavior. However, it
was argued that the perceived value was not appropriate in terms of a measurement
method for consumer loyalty since there was no signiﬁcant relationship found between
them (Petrick and Backman, 2002). In a different way, Morais et al., (2004) looked at
what psychological programs (or factors) determined by consumer loyalty from the view
of tourism providers. The signiﬁcant effects on tourist loyalty included the investment of
love, information, and status, suggesting that tourism agents need to develop programs
related to invisible products rather than visible products.

Two studies (Reisinger and Turner, 2002; Kim and Littrell, 1999) focus on the
angle of retail tourism marketing. Reisinger and Turner (2002) conducted a comparative
causal study on Japanese tourists visiting Hawaii and the Gold Coast in order to discover
relationships among product purchase, product attributes, and satisfaction with shopping.
The analyses using AMOS program (a type of SEM software) showed that product
purchase inﬂuenced product attributes, which consequently inﬂuenced the shopping
satisfaction. of tourists. Analyzing 277 female tourists visiting Mexico, Kim and Littrell
(1999) identiﬁed the direct causal relationships between exogenous constructs (hedonic

(values, interest in other cultures, and open-mind) and endogenous constructs (recreational

30

Table 3. Types of Latent Constructs Examined by Prior Travel Researchers

 

 

Authors Exogenous constructs Endogenous constructs
Baker and Crompton Quality of the opportunity Satisfaction and behavioral intentions
(2000)

Gallarza and Saura
(2006)

Gursoy, Jurowski, and
Uysal (2002)

Gursoy and Rutherford
(2004)

Hwang et a1. (2005)

Kashyap and Bojanic
(2000)

Kim and Littrell (1999)

Lam and Hsu (2006)

Lehto, O’Leary, and
Morrison (2004)

Lindberg and Johnson
( l 997)

Morais, Dorsch, and
Backman (2004)

Petrick and Backman
(2002)

Petrick, Morais, and
Norman (2001)

Reisinger and Turner
( 1 999)

Reisinger and Turner
(2002)

Swanson and Horridge
(2004)

Yoon, Gursoy, and Chen
(2001)

Yoon and Uysal
(2005)

Perceived value

Community concern, community
attachment, ecocentric attitude, and
utilization of tourism resource base
by residents

Community attachment,
community concern, ecocentric
attitude, and utilization of tourism
resource base by residents

Place attachment

Perceived price, quality of room,
quality of public, and quality of
staff services

Personal values and attitude toward
other cultures

Theory of planned behavior (TPB)

Prior involvement

Perceived economic and
congestion impacts, and perceived
crime and aesthetic impacts

Providers’ perceived resource
investments

Acquisition value and transaction
value

Past visit to destination and
satisfaction

Culture and perception

Traveling, alcohol/cigarettes, and
personal

Activities and demographics

Economic impact, social impact,
cultural impact, and environment
impact

Push and pull motivations

Satisfaction and loyalty

State of the local economy, perceived
beneﬁts, perceived costs, and support for
tourism

State of the local economy, economic
beneﬁt, social costs, cultural costs, social
beneﬁts, cultural beneﬁts, and support
for tourism

Tourist’s involvement and interpretation
satisfaction

Overall value, comparative rating, and
intention to revisit

Tourism styles, souvenir attitude, and
purchase intentions

Behavioral intention

Risk, activity, and economic
involvements

Resident attitudes

Customers’ reported resource in
vestrnents, and loyalty

Perceived value and intentions to
repurchase

Perceived value and intentions to revisit
destinations

Satisfaction and repeat visit
Design, unique, and display
Souvenir products, product attributes,

and store attributes

Total impact and support tourism

Satisfaction and destination loyalty

 

31

tourism, ethnic tourism, souvenir attitude on purchase intentions). This study concluded
that tourists take a trip to perform their personal desires and manifest their personal
values.

Recently, Swanson et al. (2004) employed SEM to explore if there were any
causal relationships between travel motivations (travel activities and tourists
demographic characteristics) and souvenir consumption of people traveling to four states:
Arizona, Colorado, New Mexico, and Utah. Analysis showed that, of two motivation
constructs, only travel activities had positive correlations with souvenir consumption. The
ﬁndings implied that the study provided marketers with a more tangible and concrete
path to better target tourists because structural modeling helps clarify which factors
would be causes or effects.

Targeting the international market, Lam and Hsu (2006) surveyed of international
tourists visiting Hong Kong and tested structural relationships between Theory of
Planned Behavior (TPB) including attitude, subjective norm, and perceived behavioral
control and behavioral intention of choosing a trip destination. Analysis employing
LISREL software (a type of SEM program) suggested direct inﬂuences of subjective
norm, perceived behavioral control, and past behavior on behavioral intention. On the
contrary, the attitude construct had no direct inﬂuence on behavioral intention of
choosing Hong Kong as their travel destinations.

It is critical for destination marketers to create and maintain brand (or destination)
loyalty for constructing more competitive and successful businesses. To do so, further
examining the major factors that have direct/indirect impacts on loyalty is essential.

Moreover, although it is known that motivations inﬂuenced satisfaction and in turn

32

satisfaction inﬂuenced destination loyalty (Y oon and Uysal, 2005), no studies have
explored whether there are structural associations between involvement (exogenous
variable) and a set of endogenous variables in the travel market. This study, therefore,
principally targets the causal relationships among ﬁve latent constructs: travel
involvement, push motivations, pull motivations, satisfaction, and destination loyalty of
university student travelers for pleasure travel. To test the set of constructs, the popular
domestic and international travel destinations students traveled to were identiﬁed to
measure the level of satisfaction with their most recent trips and predict their behavioral

intention (destination loyalty).

33

CHAPTER 3

RESEARCH METHODS

This chapter addresses the overall procedures and how the surveys were
conducted. The ﬁrst section describes the main advantages of using a web-based survey
and the second section provides questions used for two web-surveys including the
measurement scales for each construct. In the third section, the data collection method is
discussed in terms of how respondents were identiﬁed and contacted along with the
response rate for each of the surveys. The last section details the data preparation and
analysis, including the main stages used to describe the characteristics of respondents

obtained and to test the hypothesized model.

Advantages of using a Web-based Survey

Web-based surveys of students enrolled at Michigan State University (MSU) in
2004 and 2005 were employed to obtain information to test the hypothesized model. The
number of Internet users has increased dramatically in the past decade, thus more
researchers are collecting data using web-based or Internet surveys to understand their
customers’ consumption patterns, behaviors, and psychological consequences (Tierney
2000; Tingling, Parent, and Wade 2003). Evidence of the growing use of the Internet on
college campuses is found in a study conducted by Perry, Perry and Hosack-Curlin
(1998) where it is was reported that 80% of students enrolled in three regional

universities in the southeastern USA. were using the Internet and had their own email

34

accounts. Especially, the student population is considered one of the most useful Intemet-
survey markets because students are well known to be web-users (Cole, 2005).

Marketing and tourism researchers have noted four primary advantages associated
with the web-based survey compared to conventional survey methods such as personal
interviews, mail and telephone surveys, or paper-pencil surveys (McCullough 1998;
Oppermann 1995; Sheehan and Hoy 1999; Tingling, Parent, and Wade 2003; Truell,
Bartlett, and Alexander 2002; Truell 2003; Weible and Wallace 1998). The ﬁrst
advantage suggested by Weible and Wallace (1998) is associated with “reducing overall
research costs”, which was conﬁrmed by Tierney (2000). These researchers compared the
costs of sending 200 surveys using four different types of survey modes, and reported
that the least expensive survey modes were e-mail and web form surveys at a cost of $59,
compared with mail or fax surveys which cost substantially more at $371 and $169,
respectively. The second advantage is that a web-based survey can obtain “faster
responses” from survey respondents (Litvin and Kar 2001; Sheehan and Hoy 1999). In a
study by Tse (1998), it was demonstrated that the procedure of data collection was much
more time efficient using email surveys with a response time of 23.84 hours, in
comparison to 62.70 hours for mail surveys. The third advantage is that web surveys are
likely to produce “higher response completeness” than mail surveys (Litvin and Kar
2001; Truell, Bartlett, and Alexander 2002). The fourth advantage of adopting the web-
based survey is “the ease of sending follow-ups” (Oppermann 1995). Due to the fact that
a web survey is essentially trouble-free to identify non-respondents, researchers are able
to send follow-up surveys to non-respondents simply by editing the e-mail list.

Consequently, employing the web-based survey approach rather than conventional survey

35

methods permits a shortenal research cycle and the associated costs, providing a more
effective sampling operation and thus researchers obtain a relatively large number of
responses. Given these considerations, as well as the fact that the study is directed at
university students, the overwhehning majority who have access to and are comfortable
using Internet resources, the web-based approach was adopted for data gathering in this

study.

Web Questionnaires

A pleasure trip was operationally deﬁned as any leisure related trip away from
home for various reasons including vacation, recreation, entertainment, and visiting
family and friends during spring break, summer break, and winter break. Targeting the
university student market, two web—based questionnaires were designed to measure the

99 6‘

structural associations among ﬁve latent constructs including “involvement , push

99 6‘ 99 6‘

motivations , pull motivations , satisfaction”, and “destination loyalty”.

First Web-Questionnaige

The ﬁrst web-questionnaire was developed to collect information about push and
pull motivations of student travelers at Michigan State University (MSU) aged 18 years
or older. It consisted of six main sections. Sections one and two pertained to the
respondents’ past trip experiences, including types and purpose, duration, spending, party
size, accommodation, transportation, and meal choice. In the third section, student
respondents were asked about future intentions to travel during the next six months.

(Sections four and ﬁve collected information about “push (31 items) and pull motivations

36

(25 items)”, where student respondents were asked to specify how important each item
was in deciding and planning their next pleasure trips using a ﬁve-point Likert-type scale
ranging from ‘1 = Not at all important’ to ‘5 = Highly important’. The ﬁnal section
collected socio-demographic information, identiﬁed as gender, age, nationality, academic

year in college, marital status, number of children, and main source of funding for tuition.

Second Web-Questionnaire

The second web-questionnaire consisted of four main sections, designed to collect
information about involvement, satisfaction, and destination loyalty of student travelers
who planned a pleasure trip during the next six months. The ﬁrst section focused on
travel characteristics of the student’s most recent trips, including trip type, destination(s),
party size, and with whom respondents traveled. The focus of the second section was
concerned with 9 pairs of “travel involvement items” modiﬁed from a study by
Zaichkowsky (1985), where respondents indicated how they felt each item related to
them regarding their most recent pleasure trips using a semantic differential scaling
method (e. g., “l = Unimportant to 5 = Important” and ‘1 = Boring to 5 = Exciting”). In
the third section, respondents were asked to obtain an evaluation of their most recent
pleasure trips associated with the overall satisfaction items, such as “l = Much worse to 5
= Much better than I expected in general”, “1 = Not worth to 5 = Well worth it in terms
of time and effort”, “1 = Very dissatisﬁed to 5 = Very satisﬁed”, and “l = Much worse to
5 = Much better than I expected compared to other destinations”. In the fourth section
associated with destination loyalty, respondents were asked: (1) In the next two years,

(how likely is it that you will take another trip to the same destination where you visited

37

on the most recent trip? (1 = Not likely at all to 5 = Very likely); (2) In the next two
years, how likely is it that you will pay more if you visit the same destination(s) where
you visited on the most recent trip? (1 = Not likely at all to 5 = Very likely); (3) Please
describe your overall feelings about your most recent trip (1 = The trip was very poor and
I will never come again to 5 = The trip was so good and I will come again); (4) Will you
suggest the destination(s) you visited to your friends or relatives? (1 = Not likely at all to
5 = Very likely).

The questions associated with ‘travel involvement’ (e.g., Josiam, Smeaton, and
Clements, 1999; Zaichowsky, 1985), ‘push motivations’ and ‘pull motivations’ (e.g.,
Crompton and McKay, 1997; Baloglu and Uysal, 1996), ‘satisfaction’ (e.g., Petrick 2004;
Yoon and Uysal, 2005), and ‘destination loyalty’ (e. g., Huddleston et al., 2004;
Oppermann, 2000; Petrick et al., 2001; Yoon and Uysal, 2005) were generated from an
extensive review of previous studies related to the marketing, travel, and tourism
industry. For face validity of each of these items, three tourism professionals (directors of
leisure and tourism centers at US. state universities) were asked to revise the initial
questionnaires. Integrating their comments, the researcher then conducted a pre-test on
undergraduate and graduate students. The pre-test was performed by testing the entire
web-survey process: sending the invitation email letter; receiving responses, to further
reﬁne the survey instruments and decrease the measurement error. The two ﬁnal

instruments were then posted on a web site.

38

Data Collection

To facilitate use of the web survey, three mechanical systems (i.e. Hyper Text
Markup Language (HTML), Active Server Pages (ASP), and ACCESS) were adopted to
create and post a web page, and receive responses ﬁ'om the participants. HTML is the
coded format language used for creating hypertext documents on the World Wide Web
and controls how a Web page appears. ACCESS helps survey researchers to create forms
and reports. ASP enables HTML pages to be dynamic and interactive.

To obtain information about the ﬁve main constructs, two web-based surveys
were projected to students enrolled in Michigan State University between 2004 and 2005.
The ﬁrst survey was conducted using during the fall semester 2004 and the second one,

as a sequential survey, was undertaken during the spring semester 2005.

Sampling Frame and Procedures

An alphabetically ordered email sampling ﬁ'ame consisting of approximately
35,000 students enrolled at Michigan State University in the Fall of 2004 and Spring of
2005 was compiled using the MSU student directory. Every 3rd email address was then
randomly selected. The list was then imported by an email program, which assisted in the
organization and distribution of a letter of invitation to a speciﬁc portion of participants:
the email program allowed only one response from each email address. In an effort to
encourage participation and increase responses, the invitation letter included that each of
ﬁve respondents would be randomly selected to receive a voucher for a book. Students
receiving the letter were asked if they were likely to participate in the survey, and only

_ those who voluntarily agreed were directly linked to the web pages designed for the ﬁve

39

constructs. Those students who chose not to participate in the web-survey clicked an
elimination browser at the bottom of the email invitation and they were automatically

eliminated from the list.

Response Rates

In the ﬁrst web-survey, of a total of 11,600 emailed, 2,482 were returned during
the entire survey period resulting in a ﬁnal response rate of 25%. The email database
showed that 60 people declined to take the survey. Only 45 returned responses were
excluded due to too many missing values and ﬁnally 2,437 were identiﬁed as potential
respondents who planned their future trips during the next six months. Approximately
57% (1,410) of the total responses collected were received during the ﬁrst day of the
survey, accompanied by a huge drop in responses the next day. After the 1st reminder
email was sent, more than 550 (22%) students additionally responded to the web-survey,
followed by 322 (21%) responses aﬁer the 2nd reminder: three days were allowed
between the ﬁrst contact and each reminder.

In the second web-survey, the potential respondents were asked to participate in
the survey using the same approach as the ﬁrst survey. Of a total of 2,437 potential
respondents emailed, 591 responses were collected during the entire survey period
resulting in a ﬁnal response rate of 24%. Approximately 258 responses or 44% of the
total collected were received during the ﬁrst day of the survey, accompanied by a drop in
responses the next day. 219 (3 7%) additional students responded to the web-survey after

the 1st reminder email, followed by 114 (19%) responses aﬁer the 2nd reminder.

40

The two data sets were then merged by matching the email addresses of
respondents for the Structural Equation Model. This research presents the results
pertaining only to the 411 respondents who took the most recent trip to domestic or
international destinations during the previous six months and had no missing values on

questions associated with the ﬁve constructs.

Data Preparation

The researcher regularly monitored the survey pages as well as checked the email
account to see whether any potential problems with participating in and submitting the
surveys were reported by respondents during the entire survey periods. Respondents who
indicated encountering problems with the survey were contacted as soon as possible and
the situation was resolved.

The completed surveys were automatically transmitted into a spreadsheet
database. The researcher tracked the number of surveys completed and saved data on a
daily basis. After two reminder emails, a brief notiﬁcation about closing the surveys was
posted on the main pages of each survey. The data were then imported into the SPSS
(14.0) program. Multiple-ﬁequencies on all variables were run to identify outliers,
errors, and missing values made by survey respondents. The ﬁnal data were prepared for

testing the hypotheses.

Data Analysis

A descriptive analysis was performed on proﬁle characteristics, various travel

‘ characteristics and patterns on students’ most recent vacation trips. The test of the

41

hypotheses required three different analytical procedures (Exhibit 1). First, factor analysis
was performed to identify underlying factors of the importance of the push and pull
motivation items. Second, Conﬁrmatory Factor Analysis (CF A) was performed to test the
measurement model of the ﬁve latent constructs and to determine if various indicators
were signiﬁcantly related with the constructs. Third, Structural Equation Model using the
Maximum-likelihood estimation procedure linked with AMOS (6.0) software was then
employed to assess the causal relationships among involvement, push motivations, pull
motivations, satisfaction with travel experience, and destination loyalty of Michigan State
University student travelers toward domestic and international destinations. In this
procedure, all of the hypothesized associations were simultaneously tested (Kline, 1998).
Lastly, Multivariate Analysis of Variance (MANOVA) was utilized to determine
whether statistically signiﬁcant associations existed between the ﬁve model constructs
and various student proﬁle characteristics including gender, age, nationality, academic

year, marital status, number of children, and main source of funding for tuition.

Exhibit 1. Main Stages of the Analysis

 

Stage one Factor Analysis using SPSS (14.0) program

Stage two Conﬁrmatory Factor Analysis using AMOS (6.0) software
Stage three Structural Equation Model using AMOS (6.0) software

Stage four Multivariate Analysis of Variance using SPSS (14.0) program

 

42

CHAPTER 4

RESULTS

This chapter provides an overview of respondents and statistical results. The
results are presented in ﬁve sections. The ﬁrst section describes various characteristics of
respondents’ most recent vacation trips including socio-demographics, lodging and meal
characteristics, and travel destinations. Section two presents the most important, as well
as, least important push and pull motivation variables indicated by respondents and
determines signiﬁcant associations between the importance of the motivations and
student trip characteristics. In the third section, the underlying dimensions of the push
and pull motivation variables are examined using factor analysis. Section four provides
the results of developing the measurement model as well as testing the hypothesized
models. In the ﬁnal section, signiﬁcant associations between the ﬁve model constructs

and various proﬁle characteristics are presented.

Profile of the Sample

The sample consisted of MSU undergraduate and graduate students (18 years or
older) who took a pleasure trip to either domestic or international destinations during the
last six months (November 2004 to April 2005). The majority of respondents were female
(75%) and mostly between 18 and 19 years old (39%) or 20 and 29 years old (44%)
(Table 4). More graduate students (30%) and seniors (27%) responded to the survey than
freshmen (12%), sophomores (16%), and juniors (15%). The largest proportion of

respondents were domestic (92%), and single (86%), and almost all of them had no

43

children (95%). The main source of funding for tuition was parents/family (46%),
followed by assistantship/scholarship (26%), loans (17%), self-savings (9%), and other
(3%).

Although the proportion of domestic and international students was evenly
distributed between survey respondents and the MSU student population, the gender
and undergraduate and graduate status of respondents did not represent the MSU
student population (Michigan State University, 2006). Female and graduate students
were over-represented among respondents. Female students comprised 54% of the
students enrolled at MSU (Spring 2006) and three quarters (75%) of the respondents.
Graduate students are almost 30% of the respondents and only 18% of the MSU student
population. Other demographic variables were not compared due to the non-existence of

the MSU data and the use of different categories.

Characteristics of Respondents’ Most Recent Trips

Characteristics of respondents’ most recent trips taken during the last six months
are provided in Table 5. Of the 70% of students who took a pleasure trip during the
previous six months (November 2004 to April 2005), approximately 78% of
respondents indicated that they took a domestic trip, while 22% indicated that they took
an international trip. With respect to travel party makeup, the majority of them traveled
with a group (85%) as opposed to individually (15%). Their most recent trips were
primarily taken in March 2005 (47%), followed by December 2004 (16%) and April

2005 (15%). Respondents mostly traveled with friends (45%),

44

Table 4. Socio-demographic Proﬁles of Respondents

 

 

Characteristics Frequencies a %
Gender
Male 97 24.6
Female 298 75.4
Age
18 to 19 155 39.3
20 to 29 173 43.9
30 to 39 34 8.6
40 + 32 8.1
Nationality
Domestic 354 92.2
International 30 7.8
Academic year
Freshmen 48 12.2
Sophomore 64 16.2
Junior 58 14.7
Senior 108 27.3
Graduate 1 17 29.6
Marital status
Single 340 86.1
Married 44 11.1
Other 11 2.8
Number of children
None 372 94.7
One+ 21 5.3
Main source of ﬁmding for tuition
Parents/family l 83 46.3
Assistantship/ scholarship 1 02 25.8
Self-savings 34 8.6
Loans 66 16.7
Other 10 2.5

 

' May not sum to 411 in all cases for all variables due to missing data for some items.

45

followed by family/relatives (27%), signiﬁcant others (19%), mixed friends and
relatives parties (7.7%), and other (1.1%). Almost half (48%) of the trips were one or
two nights in length and about a third (36%) were three to six nights. Trip duration

results are consistent with a report by the Travel Industry of America (2004).

Lodging and Meal Characteristics

In relationship to type of lodging and meal characteristics (Table 6), the majority
(91%) of the respondents used automobile as transportation on their trips, followed by
airplane (50%). Interestingly, Buses and Trains were used a great deal by the student
travelers. Not surprisingly, the two primary types of accommodations selected by
respondents included ﬁ'iends/relatives ’ homes (65%) and hotel/motels (59%).
Campground/trailer parks (21%) and Hostel/condominium (14%) were used much less
frequently. The respondents’ three most popular choices of meals eaten were family-style
restaurants (81%), fast-food restaurants (75%), and self-prepared meals (73%), followed
by formal restaurants (60%), deli/supermarkets (46%), and convenience stores (45%).
With respect to the selections of transportation and accommodations, a report from TIA
(2004) shows similar results. For instance, the two primary modes of transportation for
leisure and business trips included auto (73%) and airplane (16%). The two major modes
of accommodation were hotel/motels (54%) and private homes (40%). However, types of

meals eaten were not provided in the TIA (2004) report.

46

Table 5. Characteristics of Respondents’ Most Recent Trips

 

Characteristics Frequencies ' Percentages

 

Destination of the most recent trip

Domestic 321 78.1
International 90 21 .9
Month of the most recent trip taken
November 2004 21 5.1
December 2004 65 15.9
January 2005 35 8.5
February 2005 37 9.0
March 2005 192 46.8
April 2005 60 14.6
Travel party makeup
Group 349 85.1
Individual 61 14.9
Type of people accompanied
Friends 158 45.3
F amily/relatives 93 26.6
Signiﬁcant others 67 19.2
Mixed (friends, family/relatives, and 27 7 7
signiﬁcant others) °
Other 4 1.]
Duration of the most recent trip
Day trip 30 8.0
One or two nights 178 47.5
Three to six nights 135 36.0
Seven to fourteen nights 32 8.5
Fifteen nights + 30 8.0

 

‘ May not sum to 4] 1 in all cases for all variables due to missing data for some items.

47

Table 6. Mode of Lodging and Meal Characteristics of their Most Recent Trips

 

 

Characteristics Frequencies ' Percentages b
Type of transportation
Automobile 299 91 .2
Airplane 136 50.2
Train 38 17.1
Bus 36 16.4
Ship 33 15.3
Van/RV 22 10.2
Type of accommodations
Friends/relatives’ home 184 64.6
Hotel/motel 164 58.6
Campground/trailer parks 48 21.3
Hostel/condominium 3 1 14.3
Type of meals eaten
Family-style restaurants 243 81.0
F ast-food restaurants 216 75.0
Self-prepared 209 73.3
Formal restaurants 164 60.1
Deli/supermarkets 1 17 46.2
Convenience stores 108 45.2

 

' Cases do not sum to 411 because respondents were permitted to check more than one
response.

b The percentages do not sum to 100% because respondents were permitted to check more
than one response.

Domestic and International Trip Destinations

The respondents were asked to specify the domestic or international destinations
they visited during the previous six months on pleasure or vacation trips. The most
popular domestic destination was Florida (22%), followed by Illinois, Michigan,
California, New York, Arizona, Colorado, Georgia, Ohio, Hawaii, Indiana, Missouri, and
Massachusetts (Table 7). The top international destination was Mexico (30%), followed

by Canada, Bahamas, Puerto Rico, Jamaica, United Kingdom, Australia, England,

48

France, and Italy (Table 8). These destinations are also inﬂuenced by the time of the year

the survey was administered.

Table 7. Destinations of Domestic Trips

 

 

Destinations ' Rank Percentages
Florida 1 21.8 (17.0) b
Illinois 2 10.6 (8.3)
Michigan 3 9.7 (7.6)
California 4 6.5 (5.1)
New York 5 5.3 (4.1)
Arizona 6 4.7 (3.7)
Colorado 7 3.1 (2.4)
Georgia 8 2.5 (2.0)
Ohio 8 2.5 (2.0)
Hawaii 9 2.2 (1.7)
Indiana 9 2.2 (1.7)
Missouri 9 2.2 (1.7)
Massachusetts 10 1.9 (1.5)

 

" Destinations with less than 1% response were not reported.
b 78.1% were domestic trips. So, 17.0% were all trips to Florida.

49

Table 8. Destinations of International Trips

 

 

Destinations ' Rank Percentages
Mexico 1 30.0 (6.6) b
Canada 2 27.8 (6.1)
Bahamas 3 4.4 (1.0)
Puerto Rico 4 4.4 (1.0)
Jamaica 5 3.3 (0.7)
United Kingdom 5 3.3 (0.7)
Australia 6 2.2 (0.5)
Austria 6 2.2 (0.5)
England 6 2.2 (0.5)
France 6 2.2 (0.5)
Italy 6 2.2 (0.5)

 

' Destinations with less than 1% response were not reported.
b 21.1% were intemational-trips. So, 6.6% were all trips to Mexico.

Importance of Push and Pull Motivation Variables

Respondents indicated the importance of various push motivations in deciding
their pleasure trips and pull motivations in choosing destinations either domestically or
internationally during their vacation. On a ﬁve—point scale with 1 being “not at all
important” and 5 being “highly important”, respondents rated “having fun or being
entertained” (4.15) to be their most important push motivation for going on trips (Table
9), followed by “to get physically or emotionally reﬁeshed ” (4.00), “spending time with
someone special” (3.79), “seeing and experiencing a new destination ” (3.74), “to spend
time with friends ” (3.71), “get away ﬁom school” (3.69), and “visiting friends or
relatives” (3.60). On the other hand, “meeting someone of the opposite sex” (2.04),
“going places my friends have not visited ” (2.29), and “indulging in luxury ” (2.46) were

relatively less important reasons for trips. These important push variables can help in

50

understanding why students decide to take pleasure trips and this information can be used
by travel businesses and marketers to design potential travel products to promote
college/university students’ pleasure trips.

Table 10 reports the importance of different pull motivations. “Good value for the
cost " (3.97), “clean and comfortable accommodations” (3.73), “convenient
transportation” (3.60), “beautiful scenery and landscapes” (3.54), “safety and security ”
(3.53), and “warm and sunny weather” (3.44) were the most important motivations for
selecting a trip destination. Less important pull variables were “to view sport event”
(1.88), “to participate in sport events” (1.90), “party(ing) reputation” (2.18), and
“familiarity of a place” (2.32). It is important to recognize that even though these
motivations are less important on average, there are student traveler segments that
consider them to be relatively more important. For example, 26.5% of the students
consider a destination’s “party(ing) reputation” as important or highly important when
selecting a destination. It is the combination of motivations, not just the importance
assigned one motivation, that travel marketers need to understand in order to design

holistic targeted marketing mix strategies.

51

Table 9. Importance of Push Motivation Variables

 

 

Not at all Highly

Importance of push variables ‘ Mean important important
1 2 3 4 5

Be away from demands of home 3.17 5.8% 24.7% 31.3% 22.9% 15.3%
Escaping from ordinary/responsibilities 3.50 3.4% 17.2% 29. 1% 26.7% 23.5%
To do nothing 2.68 16.2% 34.2% 24.9% 14.9% 9.8%
Get away from my job 2.86 14.2% 28.2% 28.2% 15.6% 13.7%
Get away from school 3.69 4.5% 12.6% 25.3% 24.2% 33.4%
To reduce stress 4.03 0.5% 7.9% 19.7% 31.3% 40.5%
To be free 3.59 4.8% 14.9% 25.5% 26.6% 28.2%
T0 g’fig’sllﬁcany 0’ emm‘onany 4.00 0.3% 6.1% 24.4% 31.8% 37.4%
seeégfﬁig‘ligipemmmg a new 3.74 5.0% 11.1% 22.0% 28.8% 33.1%
Seeing many attractions 3.09 8.8% 23.9% 31.6% 21.2% 14.6%
”ﬂag 1:212?“ new °’ ”creasmg 3.18 7.4% 23.9% 30.0% 21.0% 17.8%
Having fun or being entertained 4.15 0.5% 2.6% 19.0% 36.8% 41.0%
Viewing wildlife 2.71 15.3% 31.2% 29.1% 15.6% 8.7%
Enjoying good weather 3.71 2.9% 11.7% 26.6% 28.7% 30.1%
Observing nature 3.04 8.6% 25.1% 32.9% 20.3% 13.1%
Meeting someone of the opposite sex 2.04 41.2% 29.8% 17.8% 6.4% 4.8%
Spending time with special persons 3.79 5.1% 10.4% 23. 1% 23.1% 38.3%
Meeting new ﬁiends/local people 2.82 13.6% 27.9% 31 .6% 16.5% 10.4%
Experiencing a new culture 3.13 10.6% 20.7% 29.8% 22.6% 16.2%
Experiencing new or different lifestyles 3.03 11.6% 25.4% 26.5% 21.4% 15.1%
Being daring and adventuresome 3.10 10.1% 24.9% 25.9% 23.0% 16.1%
Finding thrills and excitement 3.09 11.7% 21.3% 28.0% 23.7% 15.2%
Rediscovering myself 2.66 15.6% 34.5% 27.3% 13.5% 9.0%
Talking about a trip after returning home 2.62 18.4% 30.2% 28.6% 16.3% 6.4%
Going places my friends have not visited 2.29 29.8% 33.2% 19.8% 12.1% 5.0%
Indulging in luxury 2.46 26.3% 32.2% 19.1% 13.8% 8.5%
Visiting friends or relatives 3.60 7.7% 10.3% 28.6% 21.7% 31.7%
To be together with my family 3.39 10.9% 14.4% 26.1% 21.6% 26.9%
Visiting family origins 2.53 25.0% 29.8% 22.9% 11.7% 10.6%
To visit a place recommended by friends 2.60 16.0% 29.9% 35.3% 15.2% 3.5%
To spend time with ﬁiends 3.71 6.3% 7.7% 27.5% 25.1% 33.3%

 

' Importance of each variable was measured using a ﬁve-point Likert scale (1 =Not at all important, 5 =

Highly important).

52

Table 10. Importance of Pull Motivation Variables

 

 

Not at all Highly

Importance of push variables ' Mean important important

1 2 3 4 5

Warm and sunny weather 3.44 8.0% 16.8% 26.6% 20.2% 28.5%
Sea and beaches 3.21 14.1% 18.1% 25.3% 17.6% 24.8%
Snow/ mountains 2.43 29.8% 26.6% 23.7% 1 1.2% 8.8%
River/lake/streams 2.66 16.0% 31.4% 31.4% 13.6% 7.7%
Beautiful scenery and landscapes 3.54 6.4% 10.1% 29.8% 30.9% 22.9%
Clean and comfortable accommodations 3.73 4.5% 7.4% 28.2% 29.8% 30.1%
Convenient transportation 3.60 3.2% 9.0% 34.3% 31.6% 21.8%
Good value for the price 3.97 2.4% 5.1% 22.4% 33.6% 36.5%
Restaurants 3.23 6.1% 20.5% 34.3% 22.3% 16.8%
Nightlife and entertainment 3.23 9.9% 21.1% 26.1% 21.6% 21.3%
Local people 2.79 11.4% 29.5% 36.7% 13.6% 8.8%
Cultural and historic attractions 2.91 11.7% 22.9% 38.1% 17.1% 10.1%
”32233330? “Oman“ “’0‘" a 2.94 1 1.8% 24.3% 32.1% 21.7% 10.2%
Good accessibility 3.04 10.4% 20.0% 37.1% 20.3% 12.3%
Travel time 3.03 9.3% 19.7% 40.3% 20.3% 10.4%
Recreational and sport facilities 2.63 17.6% 34.6% 24.5% 14.6% 8.8%
Shepping opportunities 2.86 15.7% 25.8% 27.9% 17.6% 13.0%
Quiet rest areas 2.49 16.3% 36.8% 33.9% 7.7% 5.3%
Educational opportunities 2.44 19.7% 37.8% 26.6% 10.4% 5.6%
Family oriented 2.46 23.5% 32.3% 25.9% 12.0% 6.4%
Safety and security 3.53 6.9% 10.7% 28.8% 29.6% 24.0%
Familiarity of a place 2.32 23.2% 38.9% 25.3% 7.7% 4.8%
Party(ing) reputation 2.18 36.9% 30.2% 17.1% 9.4% 6.4%
To participate in sport events 1.90 43.7% 34.0% 14.5% 4.6% 3.2%
To view sport events 1.88 44.1% 32.9% 16.3% 4.0% 2.7%

 

" Importance of each variable was measured using a ﬁve-point Likert scale (1 =Not at all important,

5 = Highly important).

Results of Independent Samples t-tests

Independent samples t-tests were performed to identify if there were any

statistically signiﬁcant (mean) differences in the importance assigned push and pull

motivations as well as in the level of travel involvement (1) by students who traveled to

domestic and international destinations, (2) between domestic students and international

students, (3) by students who traveled to Florida and other states, and (4) by students who

traveled to Mexico and other countries.

Differences in Push and Pull Motivations by Students Who Tra_1v_eled to Domestic a_n_d
Intemtional Destinations

Independent samples t-tests were performed to identify if there were any
statistically signiﬁcant (mean) differences in the importance assigned push and pull
motivations by students who traveled to domestic and international destinations (Tables
11 and 12). There were signiﬁcant differences in the following push motivation variables
(Table 11): “seeing and experiencing a new destination” (p = 0.005), “meeting someone
of the opposite sex ” (p = 0.014), “meeting new friends/local people ” (p = 0.006),
“experiencing a new culture ” (p = 0.017), “experiencing new or diﬂerent life-styles ” (p
= 0.021), “being daring and adventuresome ” (p = 0.016), ‘ﬁnding thrills and
excitement” (p = 0.024), and “visiting friends or relatives” (p = 0.005). Interestingly,
students traveling to domestic destinations placed more importance on all these
motivations (except for “visitingﬁ'iends or relatives”) than international destinations.

As Table 12 shows, there were some signiﬁcant differences in the importance
domestic and international destination student travelers assigned these pull motivations,
including “nightlife and entertainment” (p = 0.000), “local people ” (p = 0.000),
“cultural and historic attractions” (p = 0.000), “availability of information about a
destination” (p = 0.005), and “party(ing) reputation ” (p = 0.010). Students who traveled
to international destinations assigned statistically more importance on average to these

‘ motivations.

54

Table l 1. Differences in the lrnportance Assigned Push Motivations by Students

Traveling to Domestic and International Destinations

 

 

Domestic International
. a Destination Destination
Importance of push varrables Travelers Travelers p-value
Mean Mean

Be away from demands of home 2.97 3.23 0.053
Escaping from ordinary/responsibilities 3.33 3.55 0.112
To do nothing 2.75 2.66 0.546
Get away from my job 2.76 2.90 0.362
Get away from school 3.49 3.76 0.063
To reduce stress 4.01 4.04 0.804
To be free 3.59 3.58 0.958
To get physically or emotionally refreshed 4.03 3.99 0.699
Seeing and experiencing a new destination 4.01 3.66 0.005“
Seeing many attractions 3.29 3.03 0.074
Learning something new or increasing knowledge 3.30 3.14 0.292
Having frm or being entertained 4.23 4.13 0.339
Viewing wildlife 2.56 2.76 0.154
Enjoying good weather 3.76 3.70 0.681
Observing nature 2.92 3.08 0.254
Meeting someone of the opposite sex 2.30 1.96 0.014*
Spending time with special persons 3.59 3.85 0.080
Meeting new ﬁiends/local people 3.13 2.73 0.006**
Experiencing a new culture 3.41 3.05 0.017*
Experiencing new or different lifestyles 3.30 2.95 0.021*
Being daring and adventuresome 3.36 3.02 0.016*
Finding thrills and excitement 3.35 3.02 0.024*
Rediscovering myself 2.78 2.62 0.245
Talking about a trip after returning home 2.75 2.58 0.226
Going places my friends have not visited 2.34 2.28 0.659
Indulging in luxury 2.70 2.39 0.036
Visiting friends or relatives 3.26 3.69 0.005”
To be together with my family 3.22 3.45 0.151
Visiting family origins 2.56 2.52 0.834
To visit a place recommended by friends 2.73 2.56 0.183
To spend time with ﬁiends 3.67 3.73 0.693

 

‘ Importance of each variable was measured using a ﬁve-point Likert scale (1 = Not at all important,

5 = Highly important).
*p < 0.05; "p < 0.01.

55

Table 12. Differences in the Importance Assigned Pull Motivations by Students

Traveling to Domestic and International Destinations

 

 

Domestic International
Importance of pull variables a D1? strnatron Destination p-value
ravelers Travelers
Mean Mean

Warm and sunny weather 3.42 3.54 0.425
Sea and beaches 3.18 3.29 0.524
Snow/ mountains 2.46 2.32 0.383
River/lake/streams 2.68 2.57 0.441
Beautiful scenery and landscapes 3.51 3 .64 0.320
Clean and comfortable accommodations 3.70 3.84 0.312
Convenient transportation 3.60 3.61 0.91 1
Good value for the price 3.92 4.14 0.055
Restaurants 3.18 3.39 0.136
Nightlife and entertainment 3.11 3.64 0.000***
Local people 2.66 3.20 0.000***
Cultural and historic attractions 2.80 3.28 0.000***
Availability of information about a destination 2.85 3.24 0.005**
Good accessibility 2.99 3.20 0.149
Travel time 3.03 3.00 0.797
Recreational and sport facilities 2.62 2.66 0.787
Shopping opportunities 2.88 2.83 0.755
Quiet rest areas 2.51 2.44 0.577
Educational opportunities 2.41 2.56 0.245
Family oriented 2.51 2.29 0.122
Safety and security 3.50 3.63 0.379
Familiarity of a place 2.35 2.21 0.257
Party(ing) reputation 2.09 2.48 0.010*
To participate in sport events 1.89 1.93 0.720

To view sport events 1.87 1.92 0.701

 

° Importance of each variable was measured using a ﬁve-point Likert scale (1 = Not at all important,

5 = Highly important).
*p < 0.05; **p < 0.01; ***p < 0001,

56

Differences in Push and Pull Motivations between Domestic Student Travelers and
International Student Travelers

Independent samples t-tests were performed to identify if there were any
statistically signiﬁcant (mean) differences in the importance assigned push and pull
motivations between domestic students and international students (Tables 13 and 14).
There were signiﬁcant differences in the following push motivation variables (Table 13):
“seeing many attractions” (p = 0.002), “learning something new or increasing
knowledge ” (p = 0.032), “meeting someone of the opposite sex ” (p = 0.012), and “going
places my friends have not visited ” (p = 0.008). Interestingly, international students
traveling to domestic and international destinations placed more importance on all these
motivations than domestic students.

Unlike the results of push motivations, about half of the pull motivations
indicated signiﬁcant mean differences between domestic and international student
travelers (Table 14). They included “convenient transportation” (p = 0.002), “good
value for the cost ” (p = 0.022), “cultural and historic attractions ” (p = 0.011),
“availability of information about a destination” (p = 0.001 ), “easy accessibility” (p =
0.000), “travel time ” (p = 0.000), “recreational and sport facilities ” (p = 0.026), “quiet
rest areas” (p = 0.003), “safety and security” (p = 0.001), and “familiarity of a place ” (p
= 0.032). International students traveling to domestic and international destinations
assigned statistically more importance on average to these motivations than domestic

students.

57

Table 13. Differences in the Importance Assigned Push Motivations between Domestic
Student Travelers and International Student Travelers

 

 

Domestic International
Importance of push variables a Student Student p-value
Travelers Travelers
Mean Mean

Be away from demands of home 3.20 3.10 0.662
Escaping ﬁ'om ordinary/responsibilities 3.52 3.38 0.524
To do nothing 2.67 2.72 0.814
Get away ﬁ'om myjob 2.84 3.11 0.286
Get away ﬁ‘om school 3.68 3.86 0.432
To reduce stress 4.01 4.31 0.109
To be free 3.54 3.97 0.063
To get physically or emotionally refreshed 3.99 4.14 0.425
Seeing and experiencing a new destination 3.72 3.79 0.754
Seeing many attractions 3.02 3.72 0.002"
Learning something new or increasing knowledge 3.13 3.62 0.032*
Having tin or being entertained 4.15 4.14 0.958
Viewing wildlife 2.69 2.90 0.355
Enjoying good weather 3.70 3.74 0.856
Observing nature 3.03 3.28 0.271
Meeting someone of the opposite sex 2.00 2.55 0.012*
Spending time with special persons 3.77 3.90 0.586
Meeting new ﬁiends/local people 2.80 3.07 0.228
Experiencing a new culture 3.09 3.48 0.098
Experiencing new or different lifestyles 3.00 3.34 0.149
Being daring and adventuresome 3.08 3.34 0.262
Finding thrills and excitement 3.08 3.17 0.703
Rediscovering myself 2.62 2.93 0.156
Talking about a trip aﬁer returning home 2.60 2.86 0.232
Going places my ﬁiends have not visited 2.24 2.83 0.008“
Indulging in luxury 2.45 2.79 0.165
Visiting ﬁiends or relatives 3.61 3.48 0.606
To be together with my family 3.40 3.45 0.855
Visiting family origins 2.52 2.41 0.661
To visit a place recommended by ﬁiends 2.60 2.66 0.775
To spend time with friends 3.74 3.62 0.614

 

’ Importance of each variable was measured using a ﬁve-point Likert scale (1 = Not at all important,

5 = Highly important).
*p < 0.05; "p < 0.01.

58

Table 14. Differences in the Importance Assigned Pull Motivations between Domestic
Student Travelers and International Student Travelers

 

 

Domestic International
Importance of pull variables ' TStudent Student p-value
ravelers Travelers
Mean Mean

Warm and sunny weather 3.39 3.83 0.079
Sea and beaches 3.15 3.66 0.057
Snow/ mountains 2.41 2.72 0.202
River/lake/streams 2.64 3.03 0.067
Beautiful scenery and landscapes 3.53 3.66 0.564
Clean and comfortable accommodations 3.73 3.97 0.277
Convenient transportation 3.56 4.17 0.002“
Good value for the cost 3.94 4.38 0.022*
Restaurants 3.23 3.38 0.504
Nightlife and entertainment 3.21 3.41 0.421
Local people 2.75 3.10 0.092
Cultural and historic attractions 2.86 3.41 0.011*
Availability of information about a destination 2.88 3.62 0.001"
Easy accessibility 2.96 4.00 0.000***
Travel time 2.96 3.90 0.000***
Recreational and sport facilities 2.59 3.10 0.026*
Shopping opportunities 2.84 3.31 0.052
Quiet rest areas 2.45 3.03 0.0031'”
Educational opportunities 2.42 2.76 0.109
Family oriented 2.43 2.86 0.052
Safety and security 3.47 4.24 0.001“
Familiarity of a place 2.29 2.72 0.032*
Party(ing) reputation 2.15 2.52 0.115
To participate in sport events 1.88 2.21 0.101
To view sport events 1.87 2.14 0.172

 

" Importance of each variable was measured using a ﬁve-point Likert scale (1 = Not at all important,

5 = Highly important).
*1) < 0.05; ** p < 0.01; m p < 0.001.

59

Differences in Push Jand Pull Motivations by Students Traveling to Florida__ and Other
_S_ta_1_t_e_§

Independent samples t-tests were performed to identify if there were any
statistically signiﬁcant (mean) differences in the importance assigned push and pull
motivations by students who traveled to Florida and other states (Tables 15 and 16). The
signiﬁcant differences were shown in the following push motivation variables (Table 15):
“to do nothing” (p = 0.004), “get away from school” (p = 0.038), “enjoying good
weather” (p = 0.000), and “indulging in luxury" (p = 0.014). Interestingly, students
traveling to Florida placed more importance on all these motivations than those traveling
to other states.

As shown in Table 16, there were also signiﬁcant differences in the importance of
pull motivations. These motivation variables were “warm and sunny weather” (p =
0.000), “sea and beaches” (p = 0.000), “clean and comfortable accommodations” (p =
0.002), “convenient transportation” (p = 0.004), “restaurants ” (p = 0.025), “nightlife
and entertainment” (p = 0.009), “shopping opportunities ” (p = 0.000), and “safety and
security” (p = 0.048). Similarly, students who traveled to Florida assigned statistically
more importance on average to these motivations than those traveling to other states.
Speciﬁcally, the biggest mean differences between the two groups were shown in “warm

and sunny weather ”, “sea and beaches and “shopping opportunities

60

Table 15. Differences in the Importance Assigned Push Motivations by Students
Traveling to Florida and Other States

 

 

, a Florida Other states

Importance of push varrables p-value
Mean Mean

Be away ﬁ'om demands of home 3.21 3.16 0.747
Escaping from ordinary/responsibilities 3.68 3.46 0.144
To do nothing 3.06 2.60 0.004Mr
Get away from my job 3.08 2.82 0.126
Get away from school 3.97 3.64 0.038*
To reduce stress 4.24 3.99 0.058
To be free 3.76 3.55 0.192
To get physically or emotionally reﬁ'eshed 4.12 3.97 0.251
Seeing and experiencing a new destination 3.62 3.76 0.375
Seeing many attractions 3.14 3.08 0.726
Learning something new or increasing knowledge 3.09 3.20 0.517
Having ﬁm or being entertained 4.27 4.13 0.203
Viewing wildlife 2.64 2.73 0.563
Enjoying good weather 4.17 3.62 0.000***
Observing nature 3.03 3.05 0.923
Meeting someone of the opposite sex 2.22 2.00 0.163
Spending time with special persons 3.79 3.79 0.972
Meeting new friends/local people 2.88 2.81 0.677
Experiencing a new culture 2.97 3.16 0.240
Experiencing new or different lifestyles 2.88 3.06 0.279
Being daring and adventuresome 3.12 3.10 0.896
Finding thrills and excitement 3.23 3.06 0.332
Rediscovering myself 2.67 2.66 0.946
Talking about a trip aﬁer returning home 2.71 2.60 0.475
Going places my ﬁiends have not visited 2.32 2.29 0.846
Indulging in luxury 2.80 2.39 0.014*
Visiting friends or relatives 3.56 3.60 0.804
To be together with my family 3.42 3.39 0.875
Visiting family origins 2.42 2.55 0.451
To visit a place recommended by friends 2.61 2.60 0.969
To spend time with friends 3.71 3.71 0.987

 

" Importance of each variable was measured using a ﬁve-point Likert scale (1 = Not at all important,

5 = Highly important).
*p < 0.05; “p < 0.01;***p < 0.001.

61

Table 16. Differences in the Importance Assigned Pull Motivations by Students
Traveling to Florida and Other States

 

 

Importance of pull variables " Florrda Other states p-value
Mean Mean
Warm and sunny weather 4.08 3.31 0.000***
Sea and beaches 3.94 3.05 0.000***
Snow/ mountains 2.17 2.48 0.067
River/lake/streams 2.56 2.68 0.447
Beautiful scenery and landscapes 3.70 3.50 0.210
Clean and comfortable accommodations 4.12 3.65 0.002“
Convenient transportation 3.92 3.53 0.004“
Good value for the cost 4.15 3.93 0.102
Restaurants 3.52 3.17 0.025*
Nightlife and entertainment 3.61 3.16 0.009**
Local people 2.59 2.83 0.109
Cultural and historic attractions 2.68 2.96 0.071
Availability of information about a destination 3.03 2.92 0.491
Easy accessibility 3.14 3.02 0.452
Travel time 3.20 2.99 0.163
Recreational and sport facilities 2.85 2.58 0.092
Shopping opportunities 3.41 2.75 0.000***
Quiet rest areas 2.62 2.46 0.282
Educational opportunities 2.27 2.48 0.1 59
Family oriented 2.48 2.45 0.873
Safety and security 3.79 3.48 0.048*
Familiarity of a place 2.53 2.28 0.076
Party(ing) reputation 2.39 2.14 0.1 17
To participate in sport events 1.83 1.91 0.575
To view sport events 1.88 1.88 0.975

 

" Importance of each variable was measured using a ﬁve-point Likert scale (1 = Not at all important,
5 = Highly important).
*p < 0.05; "p < 0.01; ***p < 0.001.

62

Differences in Push and Pull Motiiations by Students Traveling to Mexico and Other
Countries

Independent samples t-tests were performed to identify if there were any
statistically signiﬁcant (mean) differences in the importance assigned push and pull
motivations by students who traveled to Mexico and other countries (Tables 17 and 18).
The signiﬁcant differences were shown in the following push motivation variables (Table
17): “escaping ﬁom ordinary/responsibilities ” (p = 0.007), “viewing wildlife ” (p =
0.044), “indulging in luxury” (p = 0.009), and “visiting ﬂiends or relatives ” (p =
0.011). Students traveling to Mexico placed more importance on “escaping from
ordinary/responsibilities ” and “indulging in luxury while those traveling to other
countries placed more importance on “viewing wildlife” and “visiting ﬁiends or
relatives

Table 18 shows that there were also signiﬁcant differences in the importance of
pull motivations, including “warm and sunny weather” (p = 0.021), “sea and beaches”
(p = 0.006), “clean and comfortable accommodations” (p = 0.003), “convenient
transportation” (p = 0.03 8), “good value for the cost ” (p = 0.043), “nightlife and
entertainment” (p = 0.002), “availability of information about a destination” (p = 0.042),
and “party(ing) reputation ” (p = 0.033). Students who traveled to Mexico assigned
statistically more importance on average to these motivations than those traveling to other
countries. The biggest mean differences between the two groups were shown in “nightlife

and entertainment and “clean and comfortable accommodations

63

Table 17. Differences in the Importance Assigned Push Motivations by Students

Traveling to Mexico and Other Countries

 

 

. , Mexico Other countries
Importance of push varrables p—value
Mean Mean

Be away ﬂom demands of home 3.38 3.16 0.322
Escaping ﬂom ordinary/responsibilities 4.08 3.45 0.007"
To do nothing 3.08 2.65 0.079
Get away ﬂom my job 3.15 2.84 0.216
Get away ﬂom school 3.81 3.69 0.615
To reduce stress 4.31 4.01 0.142
To be ﬂee 3.27 3.61 0.158
To get physically or emotionally reﬂeshed 3.77 4.02 0.196
Seeing and experiencing a new destination 3.7 7 3.74 0.889
Seeing many attractions 2.92 3.10 0.453
Leaming something new or increasing knowledge 2.81 3.21 0.102
Having fun or being entertained 4.04 4.16 0.489
Viewing wildlife 2.27 2.74 0.044*
Enjoying good weather 3.88 3.70 0.411
Observing nature 2.77 3.06 0.209
Meeting someone of the opposite sex 2.15 2.03 0.586
Spending time with special persons 3.50 3.81 0.199
Meeting new friends/local people 2.81 2.82 0.949
Experiencing a new culture 3.23 3.12 0.665
Experiencing new or different lifestyles 3.08 3.03 0.839
Being daring and adventuresome 3.08 3.11 0.911
Finding thrills and excitement 3.08 3.09 0.944
Rediscovering myself 2.35 2.68 0.157
Talking about a trip after returning home 2.72 2.61 0.654
Going places my ﬁiends have not visited 2.54 2.27 0.265
Indulging in luxury 3.08 2.41 0.009**
Visiting ﬂiends or relatives 3.00 3.64 0.011*
To be together with my family 3.38 3.39 0.976
Visiting family origins 2.27 2.55 0.277
To visit a place recommended by ﬂiends 2.58 2.60 0.929
To spend time with friends 3.62 3.72 0.660

 

' Importance of each variable was measured using a ﬁve-point Likert scale (1 = Not at all important,

5 = Highly important).
*p < 0.05; "p < 0.01.

64

Table 18. Differences in the Importance Assigned Pull Motivations by Students
Traveling to Mexico and Other Countries

 

 

, 3 Mexico Other countries
Importance of pull varrables p-value
Mean Mean

Warm and sunny weather 4.00 3.40 0.021*
Sea and beaches 3.92 3.15 0.006**
Snow/ mountains 2.27 2.44 0.514
River/lake/streams 2.50 2.67 0.465
Beautiful scenery and landscapes 3.92 3.51 0.073
Clean and comfortable accommodations 4.35 3.69 0.003“
Convenient transportation 4.00 3.57 0.038*
Good value for the cost 4.36 3.94 0.043*
Restaurants 3.58 3.21 0.108
Nightlife and entertainment 3.96 3.18 0.002Mr
Local people 3.00 2.77 0.305
Cultural and historic attractions 3.00 2.90 0.671
Availability of information about a destination 3.38 2.91 0.042*
Easy accessibility 3.42 3.01 0.077
Travel time 2.92 3.03 0.617
Recreational and sport facilities 2.69 2.62 0.765
Shopping opportunities 3.12 2.85 0.290
Quiet rest areas 2.50 2.49 0.962
Educational opportunities 2.35 2.45 0.635
Family oriented 2.12 2.48 0.121
Safety and security 3.88 3.50 0.109
Familiarity of a place 2.23 2.33 0.657
Party(ing) reputation 2.68 2.15 0.033*
To participate in sport events 2.08 1.88 0.351
To view sport events 2.08 1.87 0.306

 

" Importance of each variable was measured using a ﬁve-point Likert scale (1 = Not at all important,
5 = Highly important).
*p < 0.05; "p < 0.01.

Investigating the importance that student travelers assign to various push and pull
motivations is important to understanding their decisions to travel and where they travel.
This insight can be used to develop travel opportunities and destinations more effectively
relative to various student traveler market segments. Destination marketing organizations

can utilize this information to develop marketing communications strategies to position

65

their destinations relative to the competition. Basically, identifying the importance of
push and pull motivation variables in deciding to take pleasure trips as well as selecting
domestic and international destinations is considered indispensable to segment this and
other travel markets. That is, in order to understand and effectively target this market,
destination marketers should be awafe of these important push and pull motivation
variables associated with travel decisions and destination choices as being discriminators

between domestic and international destinations.

Differences in Travel Involvement bv Natiﬂralitv, Type of Tm), Domestic Destinations,
and IntematioLal Destinations.

Table 19 indicates that there is a signiﬁcant difference in the level of travel
involvement (p = 0.010) by students traveling to Mexico and other countries. Students
who traveled to Mexico (4.61) were statistically more highly travel- involved than those

traveling to other countries (4.27).

66

Table 19. Differences in the Level of Travel Involvement by Nationality, Type of Trip,
Domestic Destinations, and International Destinations.

 

 

 

 

 

 

 

 

Domestic International
Construct Destination Destination -value
Travelers Travelers p
Mean Mean
Travel involvement 3 4.30 4.37 0.319
Domestic International
Student Student
Travelers Travelers
Mean Mean
Travel involvement 4.32 4.24 0.505
Florida Other states
Mean Mean
Travel involvement 4.26 4.30 0.567
Mexico Other countries
Mean Mean
Travel involvement 4.61 4.27 0.010*

 

' Level of travel involvement was measured using a ﬁve-point semantic differential scale (e.g., 1 =
Unimportant, 5 = Important).
* p < 0.05.

Results of Factor Analyses Performed on Push and Pull Motivation Variables
Objectives of Factor Analysis

Factor analysis has two primary objectives: (1) to “identify the structure of
relationships among variables by examining the correlations between the variables, and
(2) “to identify representative variables ﬂom a much larger set of variables for use in
subsequent multivariate analyses” (Hair et al., pp. 95). That is, factor analysis helps

deﬁne the underlying structures of variables by reducing data into a small set of factors.

67

Testig Adeqpacv of F actor Analysis

First, it was necessary to determine whether it was appropriate to conduct a factor
analysis on the push (31 items) and pull motivations (25 items). The decision was made
by examining the Kaiser-Meyer-Olkin measure of sampling adequacy and the Bartlett’s
test of sphericity (Gursoy and Gavcar, 2003). The Kaiser-Meyer-Olkin measure of
sampling adequacy tests if the partial correlations among variables are small, while the
Bartlett’s test of sphericity tests if the correlation matrix is an identify matrix, which
indicates it is inappropriate for factor analysis. Values equal to or greater than 0.60 ﬂom
the Kaiser-Meyer-Olkin measure of sampling adequacy indicate the appropriateness of
using factor analysis. A signiﬁcant result ﬂom the Bartlett’s test of sphericity is also
required to test the appropriateness of factor analysis. Table 20 shows that the values
ﬂom the Kaiser-Meyer-Olkin measure of sampling adequacy test on the push and pull
motivation items were greater than 0.80, indicating the data was adequate for factor
analysis. The results ﬂom the Bartlett's test of sphericity on the push and pull motivation
items were considered signiﬁcant (p = 0.000), indicating the data were also acceptable for

factor analysis.

Table 20. Results of Testing for Adequacy of Factor Analysis

 

 

Test Push motivations Pull motivations
aKdaézeugxeyer-Olkrn measure of samplrng 0.832 0.814
2 2
, . . x (465) = 4950.7, x (300) = 4259.8,
Bartlett s test of spherrc1ty p = 0.000 p = 0.000

 

68

Identiﬁcation of Push Motivation Factors

A factor analysis using the varimax rotation method was ﬁrst performed on the 31
push motivation items. Table 21 shows the eight push motivational factors with
eigenvalues equal to or greater than 1.0 that were extracted. These eight push factors
accounted for 65.10% of the total variance. Based on the eigenvalue criterion above, the
scree test plot also suggested and supported the existence of eight reliable factors among
all the possible factors (Figure 2).

All of the factor loadings of each variable were acceptable, ranging ﬂom 0.38 to
0.85 (the minimum level of practical signiﬁcance is greater than 0.30). Internal
consistency between items representing each factor was estimated using Cronbach’s
alpha coefﬁcient. Since its reliability values were less than 0.60, Factor 6 was removed,
as suggested by Hair et al. (1998). The reliability values for the other six factors were
considered statistically acceptable, ranging ﬂom 0.69 to 0.87. In addition, Factor 8 was
discarded before labeling because only one variable was loaded on the factor (Hair et al.,
1998)

The six factors that were accepted were labeled on the variables with the highest
loadings: “Getting away” (Factor 1), “Adventure and excitement” (Factor 2), “Discovery
and learning " (Factor 3), “Connecting with family and ﬁiends ” (Factor 4), “Engaging
nature” (Factor 5), and “Rejuvenation ” (Factor 7). Seven push motivations loaded on the
“Getting away factor ” (Factor 1) included escaping from ordinary/responsibilities, be
away from demands of home, get away from school, to reduce stress, get away from my

job, to do nothing, and indulging in luxury. Factor 2 was named the “Adventure and

excitement factor ” because these motivations had the highest loadings: being daring

69

Table 21. Results of Factor Analysis Performed on Push Motivation Variables

 

Factor Eigen- Explained

 

Push factors/variables l . . Reliability
oadmgs values varrance
Factor 1: Getting away 7.07 22.81 0.82
Escaping ﬂom ordinary/responsibilities 0.79
Be away ﬂom demands of home ' 0.71
Get away ﬂom school 0.71
To reduce stress 0.69
Get away ﬂom my job 0.68
To do nothing 0.60
Indulging in luxury 0.38
Factor 2: Adventure and excitement 3.80 12.25 0.83
Being daring and adventuresome 0.78
Finding thrills and excitement 0.76
Rediscovering myself 0.63
Talking about a trip after returnrn' g home 0.62
Going places my ﬂiends have not visited 0.62
Meeting new ﬂiends/local people 0.55
Meeting someone of the opposite sex 0.48
Factor 3: Discovery and learning 2.36 7.60 0.87
Experiencing a new culture 0.79
Learning something new or increasing
0.76
knowledge
Seeing and experiencing a new destination 0.74
Experiencing new or different lifestyles 0.72
Seeing many attractions 0.69
Factor 4: Connecting with family and friends 2.02 6.52 0.68
To be together with my family 0.79
Visiting family origins 0.75
Visiting ﬂiends or relatives 0.68
To visit a place recommended by ﬂiends 0.44
Factor 5: Engaging nature 1.39 4.47 0.87
Observing nature 0.85
Viewing wildlife 0.84
Factor 6 'z -- 1.33 4.29 0.48
Having fun or being entertained 0.73
Enjoying good weather 0.63
Spending time with ﬂiends 0.46
Factor 7: Rejuvenation 1.20 3.86 0.69
To get physically or emotionally reﬂeshed 0.69
To be ﬂee 0.53
Factor 3"; n 1.02 3.30 --
Spending time with special persons 0.76
Total variances explained 65.10

 

Scale: 1 =Not at all important, 5 = Highly important. Varimax rotation with Kaiser normalization
' Factor 6 has no label because its reliability values were not acceptable ( < 0.60).

b Factor 8 has no label and reliability values due to only one variable loaded.

70

Figure 2. Results of Scree Test Plot for the Importance of Push Motivation Variables

 

Eigenvalue
A
1

 

 

 

 

Illllllllllllllllllllllllllllll
123456789101112131415161718192021222324255ﬂ2829m31

CormonentNunber

and adventuresome, ﬁnding thrills and excitement, rediscovering myself, talking about a
trip after returning home, going places my friends have not visited, meeting new
friends/local people, and meeting someone of the opposite sex. Five motivations
including experiencing a new culture, learning something new or increasing knowledge,
seeing and experiencing a new destination, experiencing new or diﬂerent lifestyles, and
seeing many attractions were loaded on Factor 3 so it was labeled as the “Discovery and
learning factor”. Four motivations helped name the “Connecting with family and friends
factor ” (Factor 4) including to be together with my family, visiting family origins, visiting

friends or relatives, and to visit a place recommended by friends. The two motivations

71

that deﬁned the “Engaging nature factor ” (Factor 5) were observing nature and viewing
wildlife. To get physically or emotionally refreshed and to be free contributed to naming

the “Rejuvenation factor ” (Factor 7).

Follow-up Factor Analysis without Four Push Motivation Items

An additional (follow-up) factor analysis was performed on 27 items after four
push motivational items with low factor loadings (indulging in luxury: 0.3 8, to visit a
place recommended by ﬁ'iends: 0.44, spending time with friends: 0.46, meeting someone
of the opposite sex: 0.48) were eliminated. No statistical differences were found in the
model constructed with 31 items compared to the model constructed with 27 items, in
terms of reliability values or the eigenvalues of each factor, factor loadings of each item,
and the total variances explained. So, dropping the four items did not inﬂuence the push
motivation construct. As suggested by Hair et al. (1998), any item with factor loadings
less than 0.50 did not signiﬁcantly contribute to the quality of the model. So, those items

were eliminated ﬂom testing the hypothesized model after factor analysis.

Identiﬁcation of Pull Motivation Factors

A factor analysis using the varimax rotation method was also performed on the 25
pull motivation items. Table 22 shows the seven pull motivational factors with
eigenvalues equal to or greater than 1.0 that were extracted. These seven pull factors
accounted for 69.83% of the total variance. Based on the eigenvalue criterion above, the
scree test plot also suggested and supported the existence of the seven reliable factors

among all the possible factors (Figure 3).

72

The factor loadings for each pull motivation item met the minimum requirement
(0.30), ranging ﬂom 0.40 to 0.87. For internal consistency between items representing
each factor, Cronbach’s alpha coefﬁcient was also estimated if its values were equal to or
greater than 0.60 (Hair et al., 1998). The reliability values for the seven factors ranged
ﬂom 0.58 to 0.91, indicating acceptable internal consistency.
Based on higher factor loadings and the uniqueness of each item, the seven pull

factors were accepted and labeled as “Lodging and transportation” (Factor 1),
“Convenience and value” (Factor 2), “Recreation and entertainment” (Factor 3),
“Cultural opportunities” (Factor 4), “Natural scenery” (Factor 5), “Sun and beaches”
(Factor 6), and “Familyﬁ'iendly ” (Factor 7). Four pull motivations were loaded on the
“Lodging and transportation factor ” (Factor 1) including clean and comfortable
accommodation, restaurants, convenient transportation, and shopping opportunities.
Five pull motivations including good accessibility, travel time, good value for the price,
availability of information about a destination, and quiet rest areas were loaded on the
“Convenience and value factor ” (Factor 2). Five motivations helped name the
“Recreation and entertainment factor ” (Factor 3) including recreation and sport
facilities, to participate in sport events, to view sport events, party(ing) reputation, and
nightlife and entertainment. Three motivations that deﬁned the “Cultural opportunities
factor ” (Factor 4) were cultural and historic attractions, local people, and educational
opportunities. Three motivations were loaded on the “Natural scenery factor ” (Factor 5)

including rivers/lake/streams, snow/mountains, and beautiful scenery and landscapes.

73

Table 22. Results of Factor Analysis Performed on Pull Motivation Variables

 

 

Pull factors/ variables lFact or Eigen- Explained Reliability
oadrngs values varrance
Factor 1: Lodging and transportation 6.97 27.87 0.83
Clean and comfortable accommodations 0.82
Restaurants 0.77
Convenient transportation 0.75
Shopping opportunities 0.70
Factor 2: Convenience and value 2.51 10.03 0.79
Good accessibility 0.79
Travel time 0.76
Good value for the price 0.60
Availability of information about a
. . 0.56
destination
Quiet rest areas 0.40
Factor 3: Recreation and entertainment 2.18 8.71 0.77
Recreational and sport facilities 0.85
To participate in sport events 0.75
To view sport events 0.73
Party(ing) reputation 0.73
Nightlife and entertainment 0.52
Factor 4: Cultural opportunities 1.95 7.81 0.73
Cultural and historic attractions 0.85
Local people 0.74
Educational opportunities 0.60
Factor 5: Natural scenery 1.62 6.47 0.79
River/lake/ streams 0.85
Snow/ mountains 0.83
Beautiful scenery and landscapes 0.60
Factor 6: Sun and beaches 1.16 4.66 0.91
Warm and sunny weather 0.87
Sea and beaches 0.87
Factor 7: Family ﬂiendly 1.07 4.28 . 0.58
Family oriented 0.77
Familiarity of a place 0.65
Safety and security 0.42
Total variance explained 69.83

 

Scale: 1 =Not at all important, 5 = Highly important. Varimax rotation with Kaiser normalization

74

Figure 3. Results of Scree Test Plot for the Importance of Pull Motivation Variables

 

Eigenvalue
h
I

 

 

 

 

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10111213141516171819202122232425

an.

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u—l
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03—4
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lD—t

Component Number

Two motivations that deﬁned the “Sun and beaches factor” (Factor 6) were warm and
sunny weather and sea and beaches. Three motivations including family oriented,
familiarity of a place, and safety and security were loaded on the “Family friendly

factor” (Factor 7).

75

Summative Scales of the Importance of Push and Pull Factors

A summative scale was then calculated for both the push and the pull motivations
loaded on each of the six push factors and seven pull factors. The scale is the sum of the
mean average importance scores of the motivations. According to Hair et al. (1998), this
scale has the combined beneﬁts of reducing measurement error and maintaining
parsimony in the number of variables. As Table 23 shows, the highest summative score
of the six push factors, meaning it is the most important to the student traveler, is
“Rejuvenation” (3.79), followed by “Discovery and learning” (3.23) and “Getting
away” (3.21). The factor with the lowest score is “Adventure and excitement ” (2.67). Of
the seven pull factors, “Lodging and transportation” (3.3 6) has the highest summative
score, followed by “Sun and beaches” (3.33) and “Convenience and value” (3.09).
Interestingly, “Recreation and entertainment” (2.37) is the factor with the lowest score
and importance to respondents, indicating that recreational and sport facilities,
participating in or viewing sport events, a destination reputation for partying, and
nightlife and entertainment are relatively less important motivations for selecting a
destination for student trips. However, it must be recognized that sunny weather and
beaches, both of which are obviously recreation related, are high in importance when

selecting student travel destinations.

76

Table 23. Summative Mean Scores of the Importance of the Push and Pull Factors

 

 

 

 

Push factors Mean Median 8
Getting away 3.20 3.20
Adventure and excitement 2.67 2.67
Discovery and learning 3.23 3.23
Connecting with family and ﬁiends 3.03 3.00
Engaging nature 2.88 3.00
Rejuvenation 3.79 4.00

Pull factors
Lodging and transportation 3.35 3.36
Convenience and value 3.09 3.09
Recreation and entertainment 2.37 2.37
Cultural opportunities 2.71 2.67
Natural scenery 2.79 2.80
Sun and beaches 3.32 3.33
Family ﬂiendly 2.76 2.67

 

a : the mid-way point.

Testing the Hypothesized Model

As described in the three previous Chapters, the hypothesized model employing
the structural equation model was tested to determine the relationships among “travel
involvement “push motivations “pull motivations “satisfaction ” with travel
experience, and “destination loyalty Testing the model involved two main steps: (1)
developing the measurement model and (2) validating the structural model. For the next

two steps, the AMOS (6.0) software was used.

77

Evaluation Procedures of the Measurement Model

A conﬁrmatory factor analysis using the Maximum-likelihood (ML) estimation
procedure was performed on the measurement model specifying the relationships
between the observed data and the ﬁve constructs including “travel involvement “push
motivations “pull motivations “satisfaction ” with travel experience, and “destination
loyalty Validity and reliability of the measurement model were assessed by determining
whether the indicator loadings were statistically signiﬁcant. The construct reliability
values of the ﬁve latent constructs were tested to determine if they exceeded the desired
values of 0.60 (Swanson and Horridge 2004; Hair et al., 1998). The values greater than
0.60 underline the high levels of positive relationships within each construct. To evaluate
whether the indicators on each latent construct were statistically valid, the indicator
loadings were reviewed to determine if they were all signiﬁcant (p < 0.001) at a 0.01
signiﬁcance level and if all t-values exceeded 2.58.

Three different types of measures were then reviewed to assess the degree to
which the measurement model ﬁt the observed data (Hair et al., 1998; Kline, 1998)
including: (1) absolute ﬁt measures (e.g., )8 statistic, GFI, and RMSEA), (2) incremental
ﬁt measures (e. g., CFI), and (3) parsimonious ﬁt measures (e.g., xz/df and AGFI). Six
goodness-of—ﬁt indices (J 6reskog and Sbrbom 1996; Kline, 1998) were assessed: ( 1) x2
statistic: non-signiﬁcant p-values are desirable, (2) xz/df (normed )6): values less than 3
are favorable, (3) GFI (goodness-of-ﬁt index): values should be greater than 0.90, (4) CFI
(comparative ﬁt index): values greater than 0.90 are acceptable ﬁt, and (5) RMSEA (root

mean square error of approximation): values less than 0.10 are favorable.

78

Evaluation of the Measurement Model

The results of the tests of ﬁt for the 1St measurement model are supported in Table
24. The ﬁrst Conﬁrmatory Factor Analysis indicates that all of the indicator loadings are
signiﬁcant (p < 0.001) at a 0.01 signiﬁcance level and all t-values exceeded 2.58. The
reliability values of the constructs also exceeded the desired values (0.60): “travel
involvement” = 0.87, “push motivations ” = 0.65, “pull motivations” = 0.73,
“satisfaction ” = 0.84, and “destination loyalty” = 0.74. In terms of the overall model ﬁt,
the measurement model is acceptable based on the RMSEA index (0.09), but is not
acceptable on the other four indices: x2 (395) = 1850.2, p = 0.000, xz/df= 4.68, GFI =
0.75, and CFI = 0.74. So, the model is rejected based on the overall ﬁt and needed to be

enhanced.

Table 24. Results of the Assessment of Fit of the 1St Measurement Model

 

 

Model x2 (dt) “ xz/df" GFI ° CFI d RMSEA °
18‘ Measurement model 18592 (395) 4.68 0.76 0.74 0.09
p — 0.000

 

a )(2 statistic: to be acceptable non-signiﬁcant p-values are desirable;

b xz/df (normed 7(2): to be acceptable values less than 3 are favorable;

c GFI (goodness-of-ﬁt index): to be acceptable values should be greater than 0.90;

d CFI (comparative ﬁt index): to be acceptable values greater than 0.90 are acceptable ﬁt;

6 RMSEA (root mean square error of approximation): to be acceptable values less than 0.10 are favorable.

Since the 1S" measurement model is rejected, the model ﬁt needs to be enhanced.
As suggested by the results of the modiﬁcation indices in the AMOS software, three

1’. u

involvement indicators (“no important effect versus an important effect , not

79

meaningful versus meaningful “not fascinating versus fascinating”), one push factor
(“Engaging nature”), and three pull factors (“Cultural opportunities “Natural
scenery and “Family ﬁiendly”) were recommended to be eliminated because their path
coefﬁcients are less than 0.50 and therefore not practically signiﬁcant to the ﬁt of the
model (Hair et al., 1998). In addition, three push factors (“Getting away “Connecting
with family andfriends and “Rejuvenation ”), one pull factor (“Convenience and
value”), and one destination loyalty indicator (“In the next two years, how likely is it that
you will pay more if you visit the same destination where you visited on the most recent
trip? ”) were eliminated ﬂom the model because they were signiﬁcantly interrelated to
each other on different constructs, which indicated the push factors would be either in the
pull motivation construct or in the destination loyalty construct, suggested by the
modiﬁcation indices in the AMOS software. The measurement model was then re-
analyzed to determine if the data ﬁt the model.

The 2“d Conﬁrmatory Factor Analysis shows that the ﬁt of the revised
measurement model is improved signiﬁcantly and is acceptable based on the four indices:
xz/df = 2.90, GFI = 0.91, and CFI = 0.93, and RMSEA = 0.06. However, it is still not
good enough on the x2 index: p = 0.000 (Table 25). However, according to Kline (1999,
p. 128), the Chi-square statistic has two problems: (1) “its values are not interpretable in a
standardized way” and (2) “it is very sensitive to sample size”. Based on this and the
positive results of the other four ﬁt indices, the model was deemed acceptable and no

additional changes were made to enhance the overall ﬁt of the model.

80

Table 25. Results of Overall Model Fit indices for the 2"‘1 Measurement Model

 

 

Model x2 (dt) 3 xz/dfb GFI ° on d RMSEA ‘
2“d Measurement model 362] (125) 2.90 0.91 0.93 0.06
p — 0.000

 

a x2 statistic: to be acceptable non-signiﬁcant p-values are desirable;

b xz/df (normed x2): to be acceptable values less than 3 are favorable;

c GFI (goodness-of-ﬁt index): to be acceptable values should be greater than 0.90;

d CFI (comparative ﬁt index): to be acceptable values greater than 0.90 are acceptable ﬁt;

6 RMSEA (root mean square error of approximation): to be acceptable values less than 0.10 are favorable.

Validation of the Hypothesized Model

The ﬁnal step was to assess the structural relationships between the theoretical
model’s ﬁve re-conﬁgured constructs by specifying the direct paths (—)) among the ﬁve
constructs. The direct paths among the model’s ﬁve constructs are diagramed in Figure 4.
The diagram conﬁrms the convergent validity of the model. As Table 26 shows, all the
standardized path coefﬁcients ﬂom the latent constructs to the indicators (e. g., “travel
involvement” to “1N1 ”) were acceptable, ranging ﬂom 0.50 to 1.14 (Hair et al., 1998).
All the indicator loadings were signiﬁcant (p < .001) at a 0.01 signiﬁcance level, which
implies that all t-values exceeded 2.58 and thus the indicators on each latent construct are

considered valid.

81

Figure 4. Results of the Structural Relationships among Travel Involvement,
Push Motivations, Pull Motivations, Satisfaction, and Destination Loyalty

 

 

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82

Table 26. The Hypothesized Model’s Standardized Path Coefficients and t-values

 

 

Constructs/indicators Standardized path t - value
coefﬁcrents
Travel involvement (EX) ‘
1N1 0.53 Set to 1.0
1N4 0.52 8.36
IN 5 0.84 10.72
IN 6 0.86 10.82
1N7 0.66 9.65
1N8 0.74 10.34
Push motivations (ED) "
P82 1.14 Set to 1.0
PS3 0.50 5.90
Pull motivations (ED)
PM 0.57 Set to 1.0
PL3 0.82 6.95
PL6 0.57 6.93
Satisfaction (ED)
81 0.74 10.68
82 0.82 1 1.03
S3 0.91 11.50
S4 0.53 Set to 1.0
Destination loyalty (ED)
L1 0.90 Set to 1.0
L3 0.87 12.07
L4 0.88 10.24
Direct impacts among constructs
Involvement —r Push motivations 0.04 0.86
Involvement —r Pull motivations 0.07 1.26
Involvement —r Satisfaction 0.86c 8.21
Push motivations —r Pull motivations 0.55c 4.71
Push motivations —+ Satisfaction 0.03 0.86
Pull motivations —> Satisfaction 0.03 0.71
Satisfaction —+ Destination loyalty 0.67c 7.80

 

' EX = Exogenous variable (cause); ” ED = Endogenous variable (effect)

“paths were signiﬁcant (p < 0.01).

83

In terms of the overall model ﬁt, four goodness-of-ﬁt indices for the theoretical
model were within an acceptable range: xz/df = 2.83, GFI = 0.91, CFI = 0.93 and
RMSEA = 0.06, except for the overall ﬁt of the Chi-square statistic for the model which

was signiﬁcant (x2028) = 363.2, p < 0.001) at a 0.05 signiﬁcance level (Table 27).

Table 27. Results of Overall Model Fit indices for the Hypothesized Model

 

 

Model x2 (dt) a xz/df" GFI ° CFI d RMSEA °
. 363.2 (128)
Hypothesrzed model p = 0.000 2.83 0.91 0.93 0.06

 

a x2 statistic: to be acceptable non-signiﬁcant p-values are desirable;

b xz/df (normed )8): to be acceptable values less than 3 are favorable;

c GFI (goodness-of-ﬁt index): to be acceptable values should be greater than 0.90;

d CFI (comparative ﬁt index): to be acceptable values greater than 0.90 are acceptable ﬁt;

8 RMSEA (root mean square error of approximation): to be acceptable values less than 0.10 are favorable.

Testingthe Hypotheses

The combination of the ﬁndings provides the basis for accepting or rejecting the
seven model related hypotheses. Three of the hypotheses are accepted and four are
rejected.

Hypothesis 1 (Travel involvement of student travelers has a positive direct effect
on push motivations) is rejected because “travel involvement " has a weak direct effect on
“push motivation” (estimated coefﬁcient b = 0.04, t = 0.86).

Hypothesis 2 (Travel involvement of student travelers has a positive direct eﬂect
on pull motivations) is rejected because “travel involvement” has a weak direct effect on

“pull motivation” (estimated coefficient b = 0.07, t = 126)-

84

Hypothesis 3 (Travel involvement of student travelers has a positive direct eﬂect
on satisfaction with travel experience) is accepted given that “travel involvement” has an
extremely strong and positive direct effect on the levels of “satisfaction ” with travel
experience (estimated coefﬁcient b = 0.86, t = 8.21).

Hypothesis 4 (Push motivations of student travelers have positive direct effects on
pull motivations) is accepted because “push motivations” have a strong positive direct
effect on “pull motivations ” (estimated coefﬁcient b = 0.54, t = 4.71).

Hypothesis 5 (Push motivations of student travelers have positive direct effects on
the levels of satisfaction with travel experience) is rejected given that “push motivations”
have weak direct effects on the level of “satisfaction ” with travel experience (estimated
coefﬁcient b = 0.03, t = 0.86).

Hypothesis 6 (Pull motivations of student travelers have positive direct eﬂects on
the levels of satisfaction with travel experience) is rejected because “pull motivations”
has weak direct effects on the levels of “satisfaction ” with travel experience (estimated
coefﬁcient b = 0.03, t = 0.71).

Hypothesis 7 (Levels of satisfaction with travel experience have positive direct
effects on destination loyalty) is accepted because the levels of “satisfaction ” with travel
experience have very strong and positive direct effects on “destination loyalty ”
(estimated coefﬁcient b = 0.67, t = 7.80).

The tests of the hypotheses (summarized in Table 28) suggest “travel
involvement ” of students is not a particularly good predictor of either “push ” or “pull

9“

motivations”, but is a good predictor of students satisfaction” with their travel

experience. “Push motivations” nor “pull motivations” are not good predictors of

85

students’ “satisfaction ” with their travel experience. However, “push motivations” are

good predictors of “pull motivations Finally, “satisfaction ” with travel experience is

found to be a good predictor of students’ “destination loyalty

Table 28. Results of the Tests of the Hypothesized Associations among Travel
Involvement, Push Motivations, Pull Motivations, Satisfaction, and Destination

 

 

Loyalty.

Hypotheses (Latent constructs) Results
Hypothesis 1: Involvement —+ Push motivations Rejected
Hypothesis 2: Involvement —r Pull motivations Rejected
Hypothesis 3: Involvement -—> Satisfaction Accepted
Hypothesis 4: Push motivations —r Pull motivations Accepted
Hypothesis 5: Push motivations —r Satisfaction Rejected
Hypothesis 6: Pull motivations —+ Satisfaction Rejected
Hypothesis 7: Satisfaction —+ Destination loyalty Accepted

 

Testing Gender Bias in the Model

A potential gender bias existed because women survey respondents are

overrepresented compared to their proportion of all MSU students. In an effort to assess

whether gender bias might inﬂuence structural associations of the model, the data were

weighted by gender to determine if overrepresentation of women inﬂuenced the model.

No statistical differences were found in the models developed with weighted and un-

weighted data.

86

Testing an Alternative Sequenced Model

According to some researchers (e. g., Crompton, 1979; Mannell and Iso-Ahola,
1987), travel motivations should be considered as the starting point of understanding and
modeling various travel behaviors. They suggest that push motivations be the ﬁrst
construct (cause) in the model. To test their recommendation, an alternative sequenced
model was developed and then evaluated to determine whether different structural results
emerged among the ﬁve constructs (Figure 5). The results indicate no statistical
differences between the original model and the alternative model in terms of the overall

model ﬁt measures and structural associations among the constructs.

Figure 5. An Alternative Sequenced Model for the Structural Relationships among Push
Motivations, Pull Motivations, Travel Involvement, Satisfaction, and
Destination Loyalty

 
   
 

  
   

  
 

Pull
Motivations

Push
Motivations

 

      
 

Travel
Involvement

 
 
  

.86

 

 
  
 

Satisfaction

 
 

Destination
Loyalty

  

87

Results of MAN OVA: Associations between the Five Model Constructs and
Student Proﬁle Characteristics

Multivariate Analysis of Variance (MANOVA) was utilized to determine whether
statistically signiﬁcant associations existed between summative scales for the ﬁve model
constructs and student proﬁle characteristics including “gender”, “age “nationality”,
“academic year”, “marital status”, “main source of funding for tuition”, and “number
of children”. The MANOVA procedure identiﬁes relationships (e.g., statistical mean
differences) between a set of independent variables (categorical variables) and a set of
dependent variables (non-categorical variables) at the same time. Speciﬁcally, the Wilks'
Lambda statistic is examined to determine signiﬁcant associations between the sets of
variables: signiﬁcant p-value and smaller values of the statistic indicate signiﬁcant
associations. As previously described, the summative scale is the sum of the mean
average scores each construct. For example, all six variables loaded on the “travel
involvement” construct are summed and the average scores are calculated.

Table 29 indicates that at least one of the ﬁve model constructs is signiﬁcantly
associated with the following proﬁle characteristics: “age” (Wilks' Lambda = 0.89, F (15)
= 2.95, p < 0.001), “nationality” (Wilks’ Lambda = 0.96, F (5) = 2.66, p < 0.05),
“academic year” (Wilks' Lambda = 0.87, F (20) = 2.82, p < 0.001), “marital status”
(Wilks'Lambda = 0.94, F (10) = 2.65, p < 0.01), and “main source of funding for tuition”
(Wilks’ Lambda = 0.88, F (20) = 2.54, p < 0.001). However, there are no statistical
associations between any of the model constructs and two proﬁle characteristics:

“gender ” and “number ofchildren

88

Table 29. Overall Results of the MANOVA Test between the Five Model Constructs and

Student Proﬁle Characteristics

 

Wilks'

 

Proﬁle characteristics Lambda F df Sig.

Gender 0.97 2.18 5 0.055
Age 0.89 2.95 15 0.000
Nationality 0.96 2.66 5 0.022
Academic year 0.87 2.82 20 0.000
Marital status 0.94 2.65 10 0.004
Main source of funding for tuition 0.94 2.65 10 0.000
Number of children 0.87 1.82 5 0.107

 

Signiﬁcant results were highlighted.

Table 30 shows which of the student proﬁle characteristics are signiﬁcantly
associated with the “travel involvement”, “push motivations”, “pull motivations’,
“satisfaction and “destination loyalty” constructs. “Satisfaction ” is the only construct
not signiﬁcantly related to any of the student proﬁle characteristics. Conversely, the
“travel involvement” construct is associated with “gender” of the respondents. The “push
motivations” construct (summative score) is statistically associated with all the student
proﬁle characteristics except “gender The pull motivation construct is statistically
related with “age “nationality”, “academic year”, and their “main source of funding
for tuition”. The “destination loyalty” is signiﬁcantly related only to “age” of the

students.

89

Table 30. Results of the MANOVA Test of the Associations between Proﬁle

Characteristics and Travel Involvement, Push Motivations, Pull Motivations,

Satisfaction, and Destination Loyalty.

 

 

. . Travel Push Pull . . Destination
Characteristics . . . . . Satrsfactlon
1nvolvement motlvatron motlvatron loyalty
Signiﬁcant
Gender (p = 0.043) -- -- -- --
A e __ Signiﬁcant Signiﬁcant __ Signiﬁcant
g (p = 0.001) (p = 0.003) (p = 0.007)
. . Signiﬁcant Signiﬁcant
Nat‘ondlty " (p = 0.017) (p = 0.002) “ "
. Signiﬁcant Signiﬁcant
Academ‘c year " (p = 0.000) (p = 0.000) " "
. Signiﬁcant
Marltal status -- (p = 0.000) -- -- --
Number of __ Signiﬁcant __ __ __
children (p = 0.000)
M21: 3::31.“ __ Signiﬁcant Signiﬁcant __ __
tuition (p = 0.002) (p = 0.000)

 

--: Statistically non-signiﬁcant results.

Tables 31 to 37 separately report the tests of associations between each of the
student proﬁle characteristics and the ﬁve model constructs. The purpose of these tests is
to determine if and how the latent constructs are statistically related to various student
proﬁle characteristics. As previously described, “gender” (Table 31) is statistically
related to only the “travel involvement” (F(l) = 4.10, p < 0.05) construct, which implies
that there are signiﬁcant mean differences in the construct between male and female

students. Female students (4.36) are more “travel involved” than are male students (4.21).

90

Table 31. Results of the MANOVA Test of the Associations between Gender and Travel
Involvement, Push Motivations, Pull Motivations, Satisfaction, and Destination

 

 

Loyalty
Sum of Mean F- P
Constructs Mean squares df squares value (2 Jailed)
Travel involvement 1 .53 l 1 l .53 1 4.104 0.043*
Male 4.21
Female 4.36
Push motivations 0.234 1 0.234 0.3 79 0.538
Male 2.91
Female 2.96
Pull motivations 0.299 1 0.299 0.614 0.434
Male 2.91
Female 2.97
Satisfaction 0.007 1 0.007 0.015 0.901
Male 4.04
Female 4.05
Destination loyalty 0.559 1 0.559 0.723 0.396
Male 4.06
Female 3 .97

 

*p<on5

“Age” is signiﬁcantly associated with three of the model constructs (Table 32):
“push motivations” (F(3) = 3.54, p < 0.01), “pull motivations” (F(3) = 4.63, p < 0.01),
and “destination loyalty” (F(3) = 4.08, p < 0.01). In particular, younger students between
“18 and 19” or between “20 and 29 ” place greater importance on “push motivations”
and “pull motivations” than other age categories. Especially, the oldest group (“40 and
over ”) of students demonstrate much greater “destination loyalty” (4.26) than younger
students.

“Nationality” is statistically related to only two of the model constructs (Table
33): “push motivations” (F(l) = 5.72, p < 0.05) and “pull motivations” (F(l) = 10.05, p

< 0.01). International students on average assign more importance to “push motivations”

91

and “pull motivations” than domestic students. These results imply that both “push
motivations” and “pull motivations” are more important factors inﬂuencing trip
decisions and destination selections for international students compared with domestic

students.

Table 32. Results of the MANOVA Test of the Associations between Age and Travel
Involvement, Push Motivations, Pull Motivations, Satisfaction, and Destination

 

 

 

Loyalty
Sum of Mean F- P
Constructs Mean squares df squares value (2-tailed)
Travel involvement 1.039 3 0.346 0.919 0.432
18 to 19 4.28
20 to 29 4.35
30 to 39 4.24
40+ 4.42
Push motivations 10.629 3 3.543 5.976 0.001**
18 to 19 3.02
20 to 29 3.03
30 to 39 2.61
40+ 2.56
Pull motivations 6.577 3 2.192 4.630 0.003**
18 to 19 3.10
20 to 29 2.91
30 to 39 2.73
40+ 2.78
Satisfaction 2.696 3 0.899 1.931 0.124
18 to 19 4.05
20 to 29 4.09
30 to 39 3.79
40+ 4.10
Destination loyalty 9.266 3 3.089 4.083 0.007**
18 to 19 3.96
20 to 29 4.05
30 to 39 3.57
40+ 4.26
** p < 0.01.

92

Table 33. Results of the MANOVA Test of the Associations between Nationality and
Travel Involvement, Push Motivations, Pull Motivations, Satisfaction, and

 

 

Destination Loyalty
Sum of Mean F- P
Constructs Mean squares df squares value (2-tailed)
Travel involvement 0.112 1 0.112 0.292 0.590
Domestic 4.32
International 4.26
Pushmotivations 3.383 1 3.383 5.719 0.017*
Domestic 2.92
International 3.26
Pull motivations 4.667 1 4.667 10.051 0.002**
Domestic 2.96
International 3.34
Satisfaction 0.070 1 0.070 0.147 0.702
Domestic 4.04
International 4.09
Destination loyalty 0.184 1 0.184 0.235 0.628
Domestic 3.97
International 4.06

 

*p < 0.05; "p < 0.01.

“Academic year ” is also statistically associated with the same two model
constructs (Table 34): “push motivations” (F(4) = 8.25, p < 0.001) and “pull
motivations” (F(4) = 7.22, p < 0.001). College sophomores (3.13) and seniors (3.13)
place more importance on “push motivations” than college ﬂeshmen (3.06), juniors
(2.99), or graduates (2.62). College ﬂeshmen (3.23) place the most importance on “pull

motivations

93

Table 34. Results of the MANOVA Test of the Associations between Academic Year and
Travel Involvement, Push Motivations, Pull Motivations, Satisfaction, and

 

 

 

Destination Loyalty
Sum of Mean F - P
Constructs Mean sglares df squares value (2-tailed)
Travel involvement 0.684 4 0.171 0.452 0.771
Freshmen 4.30
Sophomore 4.33
Junior 4.25
Senior 4.30
Graduate 4.37
Push motivations 18.913 4 4.728 8.252 0.000***
Freshmen 3.06
Sophomore 3.1 3
Junior 2.99
Senior 3.13
Graduate 2.62
Pull motivations 13.200 4 3.300 7.223 0.000***
Freshmen 3.23
Sophomore 3.1 1
Junior 3.05
Senior 2.98
Graduate 2.70
Satisfaction 0.259 4 0.065 0.137 0.969
Freshmen 4.10
Sophomore 4.06
Junior 4.02
Senior 4.06
Graduate 4.03
Destination loyalty 2.113 4 0.528 0.682 0.605
Freshmen 4.03
Sophomore 4.07
Junior 3.83
Senior 4.03
Graduate 3.99
*** p < 0.001.

94

“Marital status” is signiﬁcantly related to only one of the model constructs
(Table 35): “push motivations” (F(2) = 11.23, p < 0.001. Speciﬁcally, single students
(3.02) place statistically more importance levels on “push motivations” than married

students (2.75) and divorced or widowed students (2.83).

Table 35. Results of the MANOVA Test of the Associations between Marital Status and
Travel Involvement, Push Motivations, Pull Motivations, Satisfaction, and

 

 

 

Destination Loyalty
Sum of Mean F- P
Constructs Mean squares df squares value (2-tailed)
Travel involvement 0.916 2 0.458 1.220 0.296
Single 4.31
Married 4.44
Other 4.17
Push motivations 13.140 2 6.570 11.234 0.000***
Single 3.02
Married 2.49
Other 2.52
Pull motivations 2.300 2 1.150 2.384 0.094
Single 2.99
Married 2.75
Other 2.83
Satisfaction 0.433 2 0.217 0.462 0.631
Single 4.05
Married 4.13
Other 3.93
Destination loyalty 0.042 2 0.021 0.027 0.973
Single 4.00
Married 3.96
Other 4.00
*** p < 0.001.

95

“Number of children” is also statistically associated with one of the model
constructs (Table 36): “push motivation” (F(l) = 6.91, p < 0.01). Students who had no
children (2.97) placed higher importance levels on “push motivations” than those who
had children (2.51). It indicates that students living without children are more motivated

to take vacation trips to domestic and international destinations.

Table 36. Results of the MANOVA Test of the Associations between Number of
Children and Travel Involvement, Push Motivations, Pull Motivations,
Satisfaction, and Destination Loyalty

 

 

 

Sum of Mean F- P
Constructs Mean squares df srmares value (2-tailed)
Travel involvement 0.038 1 0.038 0.100 0.752
None 4.32
One+ 4.28
Push motivations 4.184 1 4.184 6.907 0.009**
None 2.97
One+ 2.51
Pull motivations 0.010 1 0.010 0.021 0.884
None 2.95
One+ 2.98
Satisfaction 0.005 1 0.005 0.010 0.920
None 4.05
One+ 4.04
Destination loyalty 0.261 1 0.261 0.335 0.563
None 3.99
One+ 4.10
**p<0.01.

The last proﬁle characteristic that shows signiﬁcant associations with the model
constructs is “main source of funding for tuition ” (Table 37): “travel involvement” (F(4)

= 3.61, p < 0.01), “push motivations” (F(4) = 4.32, p < 0.01), and “pull motivations”

96

(F(4) = 5.18, p < 0.001). Particularly, students indicating “other” (4.70) and “self-
savings” (4.61) placed higher levels of “travel involvement” than those indicating
“loans” (4.34), ‘parents/family” (4.28), and "assistantship/scholarship” (4.25). Also,
students indicating “parents/family” (3.08) and “other ” (3.14) were more highly pushed
to travel than “self-savings” (2.91), “loans" (2.97), and "assistantship/scholarship”
(2.69). Similarly, students who indicated “parents/family” (3.09) and “other” (3.06)
were more highly pulled to travel than those indicating other sources of funding. It is
concluded that although students have dissimilar levels of “travel involvement” and
“push motivations”, and “pull motivations” for their vacation trips, they have similar
levels of “satisfaction” with travel experience and degree of “destination loyalty

The results ﬂom MANOVA tests show signiﬁcant associations between the
student proﬁle characteristics and the ﬁve model constructs. It indicates that statistically
signiﬁcant mean differences exist in the constructs between and among the various
proﬁle characteristics. It is important for destination marketers and researchers to know
that students have different levels of “travel involvement” and are likely to be differently
pushed and pulled to travel for vacation. However, overall their satisfaction levels with
travel experience and degree of destination loyalty show relatively no differences across
the proﬁle characteristics. Therefore, it encourages travel businesses and researchers to
segment the university student market based on “travel involvement”, “push

motivations and “pull motivations ” to better understand the student travel market.

97

Table 37. Results of the MANOVA Test of the Associations between Main Source of

Funding for Tuition and Travel Involvement, Push Motivations, Pull
Motivations, Satisfaction, and Destination Loyalty

 

 

Sum of Mean F- P
Constructs Mean squares df squares value (2-tailed)
Travel involvement 5.286 ' 4 1.322 3.609 0.007“
Assistantship/scholarship 4.25
Parents/family 4.28
Self-savings 4.61
Loans 4.34
Other 4.70
Push motivations 10.288 4 2.572 4.322 0.002**
Assistantship/scholarship 2.69
Parents/family 3.08
Self-savings 2.91
Loans 2.97
Other 3.14
Pull motivations 9.649 4 2.412 5.176 0.000***
Assistantship/scholarship 2.73
Parents/family 3.09
Self-savings 2.79
Loans 3.00
Other 3.06
Satisfaction 2.835 4 0.709 1.522 0.195
Assistantship/scholarship 3.96
Parents/family 4.07
Self-savings 4.25
Loans 4.00
Other 4.25
Destination loyalty 6.779 4 1.695 2.221 0.066
Assistantship/scholarship 3.82
Parents/family 4.00
Self-savings 4.25
Loans 4.06
Other 4.31

 

**p < 0.01; ***p < 0.001.

98

CHAPTER 5

CONCLUSIONS AND IMPLICATIONS

The literature reviewed in preparation for this study emphasized the growth and
importance of the college/university student travel market and projected that this market
will continue to grow based on this segrnent’s inclination to travel as well as the
availability of both ﬁnancial resources and the time to travel. However, very few studies
have attempted to determine if and how students’ “travel involvement” inﬂuences “push
motivations” and “pull motivations” or other latent constructs including the levels of
“satisfaction” and “destination loyalty The gap in the research literature limits the
ability of destination marketing organizations to scientiﬁcally ﬂame and structure their
positioning and marketing communication strategies.

This research was primarily designed (1) to identify travel, lodging and meal
characteristics of university students (enrolled at Michigan State University), (2) to
identify the most important push and pull motivation variables and delineate the
underlying push and pull motivational factors of university students, (3) to determine and
examine the structural associations among “travel involvement “push motivations
“pull motivations”, “satisfaction” with travel experience, and “destination loyalty” of
those students who took a pleasure trip during the last six months (November 2004 to
April 2005), (4) to determine if the model was statistically acceptable for the university
student market, and (5) to determine the associations between the ﬁve model constructs

and various proﬁle characteristics such as gender, age, nationality, academic year,

marital status, number of children, and main source of funding for tuition.

99

The ﬁrst chapter of this dissertation provides an overview of the travel and
tourism industry with special emphasis on the current and future importance of the
university and college student market. This chapter also presents the problem statement
and research hypotheses that guided the study. Chapter two reviews literature related to
travel motivations and the various model/motivational constructs focusing on the
construct interrelated and relevant to this study. Chapter three describes the research
design, including the main advantages of the web-based surveys, the survey instruments,
and the primary analyses employed to develop and evaluate the model and to test the
hypotheses. Chapter four presents survey results, including the socio-demographic
characteristics, lodging and meal characteristics, and destination selections of the student
respondents. Also, reported in chapter four, are the most and least important push and
pull motivations and their statistical association with students and their trip
characteristics. The results of factor analyses performed on the push and pull motivations,
the assessment of the hypothesized model, and tests conducted on the seven hypotheses
are also presented in this chapter. This chapter summarizes the major results, discusses
their theoretical and practical implications and makes recommendations related to further

research.

Summary of the Findings
This dissertation has produced a number of signiﬁcant ﬁndings related to student
travel motivations and the relationships between “push and pull travel motivations” and

“travel involvement , satisfaction” with travel experience, “destination loyalty”, and

student characteristics. A total of 411 responses to the Internet-based surveys of students

100

enrolled at Michigan State University conducted in November 2004 and May 2005
provided the data to develop the structural equation model and test seven model related
hypotheses. Most of the students who completed a survey took domestic vacation trips as
opposed to international trips during the previous six months. In large part, they traveled
in a group or with their ﬁiends and most of the trips lasted one or two nights or three to
six nights in length. The majority of students traveled to their destinations by
“automobile” (91%) and “airplane” (50%). They were mostly accommodated at
‘friends/relatives ’ homes” (65%) and “hotel/motels ” (59%) and they most commonly ate
at “family-styles ” (81%) and ‘fast-food restaurants” (75%). The ﬁndings ﬂom a
national survey conducted in 2004 by the Travel Industry of America (TIA) revealed that
leisure and business travelers placed the two primary modes of transportation on auto

(73 %) and airplane (16%). Their two major modes of accommodation also included
hotel/motels (54%) and private homes (40%).

The most poplar domestic destination was Florida (22%), followed by Illinois,
Michigan, and California. The most popular international destination was Mexico (30%),
followed by Canada, Bahamas, and Puerto Rico. The ﬁndings of the 2004 TIA survey
and the 2003 World Tourism Organization survey reveal popular destinations among
students and the general population to be similar.

“Having fun or being entertained” , “being physically or emotionally reﬁeshed
“spending time with someone special “seeing and experiencing a new destination “to
spend time withﬁiends and “getting away ﬁom school” are the primary (push)
motivations that encouraged students to take their pleasure trips. The most important

(pull) motivations for deciding on a destination for their trips are “good value for the

101

’9 66

price ,

,’ (6

clean and comfortable accommodations , convenient transportation
“beautiful scenery and landscapes “safety and security and “warm and sunny
weather

Independent samples t-tests were performed to identify statistically signiﬁcant
differences in the importance assigned push and pull motivations as well as the level of
travel involvement (1) by students who traveled to domestic and international
destinations, (2) between domestic students and international students, (3) by students
who traveled to Florida vs. other states, and (4) by students who traveled to Mexico vs.
other international countries. There are signiﬁcant differences in the importance placed
on various push motivations by students who traveled to domestic vs. international
destinations. Students traveling to domestic destinations place more importance on

9’ ‘6

“seeing and experiencing a new destination , meeting someone of the opposite sex”,

“meeting new ﬁiends/local people ”, “experiencing a new culture ”, “experiencing new
or diﬂerent lifestyles”, “being daring and adventuresome ”, and “finding thrills and

’9 ll

excitement . Visiting ﬁiends or relatives” is a more important trip reason/motivation for
students taking vacation trips to international destinations. On average, international
bound students place more importance on the following motivations when deciding on

9’ 4‘ ’7 (6

vacation destinations: “nightlife and entertainment , local people , cultural and
historic attractions”, “availability of information about a destination”, and “party(ing)
reputation

There are also signiﬁcant differences in the importance that domestic and

international students assign to various push and pull motivations. Interestingly,

international students traveling to domestic and international destinations place more

102

9, 6‘

importance on the following motivations: “seeing many attractions , learning

’3 46

something new or increasing knowledge , meeting someone of the opposite sex”, and
“going places my ﬁiends have not visited” than do domestic students. International

students also assign comparatively more importance to these pull motivations:

.9! C‘ H (C

“convenient transportation , good value for the cost , cultural and historic

H ‘(

attractions” , “availability of information about a destination , easy accessibility ”,

“travel time” , “recreational and sport facilities ”, “quiet rest areas” , “safety and
security”, and “familiarity of a place

Students who traveled to Florida vs. other states place more importance on these
push motivations: “to do nothing ”, “get away ﬁom school”, “enjoying good weather”,
and “indulging in luxury”. The following pull motivations are statistically more
important in deciding to travel to Florida compared to other states: “warm and sunny

H H H 6‘ 7! H

weather , sea and beaches , clean and comfortable accommodations , convenient
transportation”, “restaurants ” , “nightlife and entertainment” , “shopping
opportunities”, and “safety and security

Students who traveled to Mexico place more importance on “escaping ﬁom
ordinary/responsibilities ”, and “indulging in luxury”, while those traveling to other
countries place signiﬁcantly more importance on “viewing wildlife ” and “visiting friends
or relatives Students who traveled to Mexico place signiﬁcantly more importance on
warm and sunny weather ", “sea and beaches ” , “clean and comfortable
accommodations ” , “convenient transportation” , “good value for the cost” , “nightlife
and entertainment , “availability of information about a destination ", and “party(ing)

!

reputation ’ in selecting this destination for their vacation trips. In addition, students

103

who traveled to Mexico are more travel-involved than those who traveled to other
countries.

Factor analyses conducted on the 31 push and 25 pull motivations resulted in six
push and seven pull motivation factors. Based on the factor loadings the following labels

’1 6

were assigned to the six push factors: “Getting away , ‘Adventure and excitement
“Discovery and learning “Connecting with family andfriends “Engaging nature
and “Rejuvenation The seven pull factors included “Lodging and transportation

U 6‘

“Convenience and value “Recreation and entertainment , Cultural opportunities
“Natural scenery”, “Sun and beaches”, and “Familyﬁ'iendly”.

The hypothesized model was then tested to determine the causal relationships
among “travel involvement “push motivation “pull motivation “satisfaction ” with
travel experience, and “destination loyalty”. Testing the model involved two main steps:
developing the measurement model and validating the structural model. In the ﬁrst step,
Conﬁrmatory Factor Analysis was performed to evaluate if all the indicators were
reliably and validly connected with each of the ﬁve constructs. The structural model was
then developed by specifying the direct relationships between the constructs as
hypothesized.

A total of seven different model related hypotheses were tested. Hypotheses 3
(Travel involvement of student travelers has a positive direct eﬂect on satisfaction with
travel experience), 4 (Push motivations of student travelers have positive direct eﬂects on
pull motivations), and 7 (The levels of satisfaction with travel experience have positive

direct eﬁ’ects on destination loyalty) are accepted because (1) “travel involvement” has an

extremely strong and positive direct effect on the levels of “satisfaction " with travel

104

experience (H3), (2) “push motivations” have a strong positive direct effect on “pull
motivations” (H4), and (3) the level of “satisfaction ” with travel experience has a very
strong and positive direct effect on “destination loyalty” (H7). Hypotheses 1 (Travel
involvement of student travelers has a positive direct effect on push motivations), 2
(Travel involvement of student travelers has a positive direct eﬂect on pull motivations),
5 (Push motivations of student travelers have positive direct eﬂects on the levels of
satisfaction with travel experience), and 6 (Pull motivations of student travelers have
positive direct eﬂects on the levels of satisfaction with travel experience) are rejected
given that (1) “travel involvement” has a very weak direct effect on “push motivations”
(H1), (2) “travel involvement” has no direct effect on “pull motivations” (H2), (3) “push
motivations” have no direct effects on the levels of “satisfaction ” with travel experience
(H5), and (4) “pull motivations” have weak direct effects on the levels of “satisfaction”
with travel experience (H6). The results of these tests suggest that even though four of the
hypotheses are rejected, the model is statistically acceptable for the university travel
market.

Finally, there are statistically signiﬁcant associations between the model
constructs and various student proﬁle characteristics, including “age “nationality
“academic year “marital status and “main source of funding for tuition The
“travel involvement” construct is associated with student “gender The “push

H 9!

motivations” construct (summative score) is statistically associated with age ,
“nationality”, “academic year”, “marital status”, “main source of funding for tuition

and “number of children”. The “pull motivations” construct (summative score) is

statistically associated with the “age”, “nationality", “academic year”, and “main

105

source of funding for tuition” of student travelers. The “destination loyalty” is only

signiﬁcantly related to the “age” of students.

Implications

Destination marketers and travel businesses are constantly seeking new ways to
lead the market in an increasingly competitive environment. Greater understanding of
motivations and other factors that play a role in attracting certain visitor segments will
allow destination marketers to develop more targeted marketing strategies. Tourism
related businesses interested in developing or expanding their student travel market will
beneﬁt ﬂom understanding important push (e. g., “having fun or being entertained”) and
pull (e.g., “good value for the price ”) motivations. The ﬁndings ﬂom this study suggest
that students are ﬁrst pushed to have fun and to be entertained during their vacation trips,
and then are pulled by their interest in good values for their travel dollar. The results can
be used for positioning destinations relative to certain markets ﬂaming marketing
communications and promotional campaigns. Distributing motivation-speciﬁc messages
to college and university students can be an effective way to encourage students to decide
to take vacation trips as well as to promote domestic and international visits.

Understanding the important push and pull motivations of different market
segments (e. g., students traveling to domestic and international destinations, domestic
and international students, students traveling to Florida vs. other states, students traveling
to Mexico vs. other countries) also provides travel marketers and destination marketing
organizations insight to tailor product-line. For example, students traveling to domestic

destinations are more concerned with various push motivations (e. g., “seeing and

106

H (6

experiencing a new destination”, “meeting someone of the opposite sex , meeting new
friends/local people ”, “experiencing a new culture”, “experiencing new or different life-
styles ”, “being daring and adventuresome ”, and ‘finding thrills and excitement”) than
pull motivations. What this implies is that marketing to students interested in domestic
destinations should emphasize push motivations and how their destinations are superior
on these dimensions.

This research conﬁrms that six push and seven pull factors are most important to
the student travel market. These factors help identify why and how students decide to
take vacation trips and select trip destinations. Also, understanding these factors provides
researchers and practitioners an opportunity for developing tourism products, programs,
and services for students.

The ﬁndings that (1) “travel involvement” has an extremely strong and positive
direct effect on the level of “satisfaction ” with travel experience, (2) “push motivations”
have a strong positive direct effect on “pull motivations”, and (3) the level of
“satisfaction ” with travel experience has a very strong and positive direct effect on
“destination loyalty The positive and strong associations resulting ﬂom the theoretical
model should be thoroughly focused on by researchers and marketers in terms of
understanding how “destination loyalty ” is established and what marketing efforts are
needed in this market. There are two major reasons to be considered. First, “destination
loyalty”, as the ﬁnal construct that the model measures, cannot be predicted without the
“satisfaction ” construct, which in turn is predicted by “travel involvement”. Second, the
direct and indirect associations between the three constructs suggest that marketers have

to ﬁnd out constructive alternatives to enhance the levels of travel involvement and

107

maximize the levels of satisfaction in order to encourage positive future trip behaviors of
students. This can be accomplished by strengthening students’ personal relevance or
importance to vacation trips, designing productive communication channels to determine
students’ basic needs and wants for vacation trips, and providing satisfactory travel
packages with good value for the price.

In addition, even though “push motivations” and “pull motivations” are not
statistically associated with other model constructs, the fact that “push motivations” have
a strong positive direct effect on “pull motivations” demonstrates the importance of the
theoretical connection between trip decisions and destination selections. It is also
recommended that destination marketers and businesses continuously concentrate on
relationship marketing strategies to retain existing student travelers based on the
systematic relationships tested by the model. Further, since the model is considered
statistically acceptable, it provides a foundation of being applied and tested for other
general travel markets to investigate and conﬁrm the determinants of destination loyalty.
Accordingly, it will greatly assist researchers to estimate tourism demand for the student
market.

The statistical associations between the different model constructs and student
proﬁle characteristics including “age “nationality “academic year “marital status
and “main source of funding for tuition” provide supporting information to further target
travel marketing. Students with different characteristics demonstrate varying degrees of
“travel involvement”, assign different degrees of importance of push and pull
motivations, and display different degrees of destination loyalty. The signiﬁcant

associations between the constructs and the characteristics provide another basis of

108

segmenting the student market. In speciﬁc, marketers can beneﬁt ﬂom understanding the
signiﬁcant association between gender and the level of travel involvement. In this study
population female students are more likely to make pleasure trips than their male
counterparts. This ﬁnding is consistent with that of a previous study (Zalatan, 1998).
This result reﬂects the tendency of the growing propensity of women to participate in
leisure travel (Pennington-Gray and Kerstetter, 2001; Richards and Wilson, 2004).
Previous researchers have also found that women are more apt to be decision makers in
purchasing travel packages or products in the household than male household members
(Anderson and Littrell, 1995; Road and Travel, 2006; Tunstall, 1989). Therefore,
marketers should direct more attention to women travelers including customizing product
offerings, packages and marketing messages to satisfy their needs and expectations.
Finally, there is beneﬁt ﬂom understanding difference in the level of travel
involvement by students traveling to Mexico and other countries. The results indicate that
students traveling to Mexico are more travel-involved than students traveling to other
international destinations. Marketing and trip planning should actively engage these
students including providing them various types of information. In particular, since the
involvement items may be related to affective and cognitive aspects, promoting and
distributing vacation packages containing emotional and psychologically beneﬁcial
messages to colleges and universities will be an effective strategy to encourage students’

pleasure trips as well as increase the levels of travel satisfaction.

109

Study Limitations and Recommendations for Future Studies

The lists of the push motivations (31 items) and pull motivations (25 items) were
obtained ﬂom previous motivational studies of student and non-student populations. As a
consequence, not all the motivation items selected for this research may be relevant or
particularly important to student travelers or their behaviors. More research is needed to
determine whether different segments (e. g., seniors, youth groups) of the travel market
differ in terms of the motivations that are important in deciding whether to take a
vacation trip and the destination for those trips.

Four (“Engaging nature “Getting away “Connecting with family and
ﬁ'iends and “Rejuvenation ”) of the six push factors and four (“Cultural opportunities
“Natural scenery “Familyﬁiendl ”, and “Convenience and value”) of the seven pull

factors were deleted ﬂom the initial model constructs. This may be because these
motivation factors are not speciﬁcally relevant to college students. It would be beneﬁcial
if in the future researchers compile and evaluate more extensive lists of travel
motivations with high levels of signiﬁcance to the model constructs. This can be
accomplished by adopting and testing a wider range of motivational variables.

This study assumed unidimensionality of travel involvement and did not evaluate
the possibility of multi-dimensionality. According to previously cited studies (e. g.,
Gursoy and Gavcar, 2003; Laurent and Kapferer, 1985; Lehto, et al., 2004), the
involvement construct can be theoretically multi-dimensional. This study, however, did
not adopt any of these studies of involvement scales suggested by prior authors due to
different concepts and purposes of this research. An additional factor analysis on the 9

involvement items suggests the existence of two dimensions (Appendix D), indicating

110

 

that, contrary to the assumption of the study, the involvement construct might be multi-
dimensional. Thus, it is recommended that future studies adopt multi—dimensions of the
travel involvement construct, as discussed in the literature section (Chapter 2), to
determine how they are related to other constructs (e. g., motivations, satisfaction,
destination loyalty). It may provide researchers and marketers with a greater
understanding of how student tourists are speciﬁcally travel-involved for their vacation
trips.

This study is exploratory in nature given the fact that is based on data obtained
ﬂom students at Michigan State University (MSU). There is no previous research to
indicate whether or not MSU students are representative of college students in general.
As a result, there is no way to conﬁrm if the hypothesized model is generalizable to
college students in general or any other segments of the travel market (e.g., young
families, seniors). Future studies need to verify the existence of the model constructs and
the structural relationships between the model constructs using data obtained ﬂom other
college/university students and also other segments of the travel market. It would be
useful to collect data on push and pull motivations ﬂom a broader population, statistically
compare the importance they assign to various motivations and then test and compare and
contrast models for different market segments.

Women students were over represented, compared to their proportion of MSU
students, in the survey responses. This may in part be due to the fact that women have a
higher propensity than male students to respond to surveys. This study did not include

tests to determine why an unrepresentative proportion of women students responded to

111

the survey. The survey responses were not weighted to compensate for the higher
proportion of women respondents. Hence, the results may over-represent women.

The response rate for both surveys are lower than desired increasing potential for
various non-response biases in this research. However, the research design did not
include tests for the direction or magnitude of non-response biases.

Although this research conﬁrmed four advantages of employing Web-based
surveys, including reducing overall research costs, quicker responses, higher response
completeness, and the ease of sending follow-ups, there is a need to assess the potential
bias resulting ﬂom the survey method. For example, a study by Hwang and Fesenmaier
(2004) determined that a gender bias occurred in a Web-based survey, compared to a
traditional survey method. It would have been beneﬁcial to also collect data using a
traditional survey method (e.g., phone interviews, on-site surveys) and compare the
results with those obtained ﬂom a Web-based survey.

Considering the total population of US. college/university students, a relatively
small number of responses (N =41 1) were used to test the model. Future studies should
include a larger number of sample sizes, methods to increase the response rate, and
approaches for dealing with potential non-response biases. Some effective ways to
increase response rates as well as to reduce non-responses can be attained by providing
incentives, selecting best time, and sending more follow-ups by extending the entire
survey period (Crompton and Tian-Cole, 2001; Sangster, 2003; Trochim, 2001). In a case
of student samples, it is desirable for researchers to avoid students’ examination periods

in addition to holiday weekends and winter and spring breaks.

112

The current study did not examine whether the model was statistically acceptable
for students traveling to various destinations (e.g., Florida vs. other states, Mexico vs.
other countries) and as a result, it does not demonstrate the appropriateness of the model
regarding speciﬁc popular destinations of students. Lastly, although researchers should
begin with variables (e. g., motivations and latent constructs) that previous studies have
demonstrated as being signiﬁcant to market segments, other potential constructs and

whether they contribute to their hypothesized models should also be explored.

113

APPENDIX A

Survey Instrument l

114

MICHIGAN STATE UNIVERSITY

DEPTARTMENT OF COMMUNITY, AGRICULTURE, RECREATION,
AND RESOURCE STUDIES

“SURVEY OF COLLEGE STUDENTS”
Dear Survey Participant:

This email survey - thus your participation in it - is important to the American
travel and tourism industry, and to university-level research of that industry. At the
close of the survey, each of ﬁve respondents selected by random pick will receive a
gift voucher in the amount of $25 -good at Barnes and Noble booksellers.

The main purpose of this study is to examine the general trip characteristics of
students, such as length of trip, group size, total spending, type of transportation,
accommodations preferences, type of meals eaten, and to measure student travel
motivations in terms of push and pull factors.

Your participation in this survey will take approximately ﬁve to ten minutes and
is purely voluntary. Respondents’ names are not requested, and information given will
be kept anonymous. All data gathered will remain conﬁdential and respondents’
privacy will be protected to the maximum extent allowable by law.

If you are willing to participate in the survey, please CLICK HERE to get into
the web-page. If you have any queries about the study or the procedure, please contact
the researcher listed second, below. If you have any question about your rights as a
human subject of research, please contact the University Committee on Research
Involving Human Subjects, Peter Vasilenko, PhD, Chair at 517-355-2180 or
uchrihs@msu.edu.

Your response to this survey is greatly appreciated and will enhance my research
at the Department of Community, Agriculture, Recreation, and Resource Studies at
Michigan State University.

Thank you, again.

Kakyom Kim, Doctoral Candidate

kimkakyo@msu.edu

(517) 353 5190

Dr. Ed, Mahoney, Thesis Advisor

mahoneye@msu.edu

(517) 353 5190

Department of Community, Agriculture, Recreation, and Resource Studies,
Michigan State University

115

Survey of Travelers

A pleasure trip is deﬁned as “any leisure related trips away from home, which include vacation,
recreation, entertainment, and visiting family and friends”. Pleases answer all of the following
questions as accurately as possible.

S_ECTION I: Trig Characteristics

1. Did you take any pleasure trip between May and October 2004?
1) Yes 2) No (Please go to the section III)

2. If yes, during which month did you take the most recent trip?
1) May 2) June 3) July 4) August 5) September 6) October

3. Was the most recent trip you took a domestic or an international trip?
1) Domestic trip 2) International trip

4. What was the duration of your trip? nights

 

5. How many persons not counting yourself were in your travel party? persons
6. Approximately, how much did your travel party spend for the entire trip?
1) $299 or less 2) $300 - $599 3) $600 - $899 4) $900 to $ 1,199 5) $1,200 or more

S_ECTION II: General Travel Patterns

The following is a list of general travel patterns. Please indicate the type of transportation,
accommodations, and type of meals that you used during the past trips.

98

B. Accommodations

m

C. T of Meals Eaten

 

116

SECTION III: Future Intention

The following is related to YOUR FUTURE INTENTION to travel. Please answer the following
questions as accurately as possible.
1. Are you planning to take any pleasure trips during the Fall 2004 or Spring 2005?

1) Yes 2) No (ﬁase do to Section VI)

2. If yes, is your next trip a domestic or an international trip?
1) Domestic trip 2) International trip

3. What states or countries are you most likely to travel? ( )
4. What will be the duration of your next trip? nights

5. How many persons not counting yourself will be in your next travel party? persons

SECTION IV: Push Motivations

The followin is a list of travel motivations. Please indicate THE IMPORTANCE OF THESE
MOTIVATIO S in planning your next pleasure trip during the Fall 2004 or Spring 2005.

1=Not at all Important;2=Somewhat Important; 3= Important; 4=Very Important; 5=nghly Important

Travel, Motivations. ,
away

stress
to
or

nature
sex
someone
new
a new
new or

or
o

m
0 visit a recom
o

 

117

SECTION V: Pull Motivations

The following is a list of travel motivations. Please indicate THE IMPORTANCE OF THESE
MOTIVATIONS in selecting a destination for your next trips.

1=Not at all lmportant;2=Somewhat Important; 3= Important; 4=Very Important; 5=l~llghly Important

T Motivations , .
arm weather

ravel

rest areas

0 events
0 events

 

_E_CTION VI. Demograghic Characteristics

Please indicate the most appropriate response for the questions below.

1. What is your gender? 1) Male ( ) 2) Female ( )

2. How old are you? (Years)

3. What is your nationality? (e.g. American, Canadian, Korean, etc).

4. What is your current status?
1) Freshman 2) Sophomore 3) Junior 4) Senior 5) Graduate

5. What is your marital status?
1) Single 2) Married 3) Other

6. How many children do you have?
1) None 2) One 3) Two 4) Three 5) Four or over

7. What is your main source of funding for tuition?
1) Assistantship/scholarship 2) Parents/family 3) Self-savings 4) Loans 5) Other

Thank you for your grticiﬂion and coogration in comgleting this surveyl.

118

APPENDIX B

Survey Instrument 2

119

MICHIGAN STATE UNIVERSITY

DEPTARTMENT OF COMMUNITY, AGRICULTURE, RECREATION,
AND RESOURCE STUDIES

“SURVEY OF MSU STUDENTS”
Dear Survey Participant:

This second email survey is critical to the American travel and tourism industry,
and to university-level research of that industry. At the close of the survey, each of
ﬁve respondents (out of potential 1,200 respondents) selected by random pick will
receive a gift voucher in the amount of $1 S-good at Barnes and Noble booksellers.

The main purpose of this study is to test the causal relationships between
travelers’ involvement, satisfaction, and destination loyalty.

Your participation in this survey will take approximately three to four minutes and
is purely voluntary. Any personal information will not be asked of the participants and
those who do not want to take the survey will be removed from the email list
immediately, with no further contacts. Data collected from this survey will be kept
strictly conﬁdential on only this project's principal researcher’s personal computer, and
will be utilized solely for the purpose of this research. Respondents’ privacy will be
protected to the maximum extent allowable by law.

If you are willing to participate in the survey, please CLICK HERE to get into
the web page. If you have any queries about the study or the procedure, please contact
the researcher listed second, below. If you have any question about your rights as a
human subject of research, please contact the University Committee on Research
Involving Human Subjects, Peter Vasilenko, PhD, Chair at 517-355-2180 or
uchrih_s@msu.edu.

Your response to this survey is greatly appreciated and will be used for my
dissertation research, thereby enhancing my research knowledge at the Department of
Community, Agriculture, Recreation, and Resource Studies at Michigan State
University.

Thank you very much.

Kakyom Kim, Doctoral Candidate
kimkakvo@msu.edu

(517) 432 0286

Dr. Ed, Mahoney, Thesis Advisor

gaboneveﬁlmsuedu
(517) 432 0286

Department of Community, Agriculture, Recreation, and Resource Studies,
Michigan State University

120

Survey of Student Travelers

A pleasure trip was deﬁned as “any leisure related trips away from home, which include vacation,
recreation, entertainment, and visiting family and friends” during spring, summer, and winter
breaks. The objective of this survey is to ﬁnd out the involvement levels, satisfaction levels, and
destination loyalty of student travelers. Pleases answer all of the following questions as
accurately as possible.

SECTION I: Trig Characteristics

1. In last October, you indicated you were planning a pleasure trip during the next 6 months.
Did you take any pleasure trip?
1) Yes 2) No (Please go to Submit Section)

2. If yes, when did you take the most recent trip?
1) November 2004 2) December 2004 3) January 2005
4) February 2005 5) March 2005 6) April 2005

3. Was it a domestic or an international trip or both?
1) Domestic trip 2) International trip 3) Both (If both, please answer both Q4 and 05)

4. If domestic trip, which state(s) did you visit? ( )
5. If international trip, what country(ies) did you visit? ( )

6. Did you take the trip alone?
1) No 2) Yes (Please go to Section II)

7. If no, who else traveled with you on the most recent trip?
1) Friends 2) Family/ relatives 3) Signiﬁcant others 4) All of them 6) Other

ECTION II: Involvement

‘ -

Please indicate the response that best describes your feelings about your most recent

 

 

 

pleasure trip. The pleasure trip that you took was_ to you.

Items on scale Items on scale

Unimportant 1 2 3 4 5 Important
No important effect 1 2 3 4 5 An Important effect

Not meaningful 1 2 3 4 5 Meaningful
Not beneﬁcial 1 2 3 4 5 Beneﬁcial
Not pleasant 1 2 3 4 5 Pleasant
No much fun 1 2 3 4 5 Fun

Boring 1 2 3 4 5 Exciting

Unappealing 1 2 3 4 5 Appealing

Not fascinatinL 1 2 3 4 5 FascinatinL

 

121

SECTION III: Satisfaction

The following questions relate to your satisfaction with the most recent trip. Please
indicate the response that best describes the extent to which you were satisﬁed.

1. How does your most recent trip, in general, rate compared to what you expected?

 

Much worse than 1 2 3 4 5 Much better than
I expected I expected

2. Was the most recent trip worth your time and effort?

 

Deﬁnitely not worth it 1 2 3 4 5 Deﬁnitely well worth it

 

3. Overall, how satisﬁed were you with your most recent trip?

 

Very Dissatisﬁed 1 2 3 4 5 Very Satisﬁed

 

4. How would you rate the most recent trip as a trip destination compared to other similar

 

desﬁnaﬁons?
Much worse than I 1 2 3 4 5 Much better than I
expected expected

 

SECTION IV: Destination Loyalty

 

The following is a list of destination loyalty. Please indicate the response that best
describes each question about your most recent trip.

1. In the next two years, how likely is it that you will take another trip to the same destination(s)
where you visited on the most recent trip?

 

Not likely at all 1 2 3 4 5 Very likely

 

2. In the next two years, how likely is it that you will pay more if you visit the same destination(s)
where you visited on the most recent trip?

 

Not likely at all 1 2 3 4 5 Very likely

 

122

3. Please describe your overall feelings about your most recent trip.

 

The trip was very poor Th .
. e trrp was so good
and I Will never come 1 2 3 4 5 and I will come again
39am

 

4. Will you suggest the destination you visited to your friends or relatives?

 

Not likely at all 1 2 3 4 5 Very likely

 

Thank you for your participation and cooperation in completing this survey!

123

APPENDIX C

Sampling Frame Procedure

124

Step 1. Visiting the Web-site of MSU People Search

 

ch — Mirrosoft Internet Explorer provided by [ARRS Tech Team

 

avorites , Tools Help
x“ I, 1&1 fSearch Mfavorites @ £53 “#5 ﬂ ..
rth.msu.edulpeoplelindex.php?

MICHIGAN STATE
UNIVERSITY

MSU Hanna 3 MEL? Peoria Search

 

MSU People Search

Search MSU Find People BrowseA—Z

 

1 Please enter leslneme, ﬁrslneme or lesbians

 

Search FacultylStaﬁMetiree Address System 1 Help Using Search I Contact Us 1 MSU Home 1, Accessibility

13: 2056 Michigan State Linn
: 13 an at‘Forneti

 

125

Step 2. Finding email accounts of students by alphabetical order

Searth — Microsoft Internet Explorer prowded by [ARRS Tech Team
rortes Tools Help

 

E Q ; I» Seach ’7 Favorites 635: “v a, j ' .3

 

:h.msu.edulpeoplelindex.php?uid=450886&prev=ab,%20a

MICHIGAN STATE
UNIVERSITY

MSU Home ) MSU People Search

 

MSU People Search

Search MSU Find People Browse A—Z
m II Search I
Please enter lastname, firstname or lastname

 

 

Abate. Alexander

161 Quail Run Dewitt MI 48820
517-569-1304
abateale@msu.eou

Title: Student

Senior

Journalism

How to Restrict Your Directory Listing

Search FacultylStaﬁlRetiree Address System | Help Using Search I Contact Us 1 M50 Home |Arcessihility

© 2006 Michigan State University Board of Trustees. East Lansmg 1le 4282-1
MSU is an affirmative-amen. equal~opportunitv institution.

 

126

Step 3. Selecting every 31rd email account using SPSS (14.0)

 

} File Edit View Data Transform Analyze Graphs Utilities

BE.E’%E¢’&:E‘? “ﬁr—Egg

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

l1 : Email labazierl@msu.edu
§__aii ' , v2. .
,1; abazierl@msu.edu 1 .00
2 abbottli@msu.edu 1.00
3 abdalste@msu.edu 1 .00
4, abdoalys@msu.edu 1.00
5‘ abedbass@msu.edu 1.00
8 abenheid@msu.edu 1.00
7’ abereggl@msu.edu 1.00
8. abernet2@msu.edu 1 .00
9 abiadals@msu.edu 1.00
10 abneynic@msu.edu 1.00
. 11 abraha?0@msu.edu 1.00
12 abramow3@msu.edu 1.00
.13, accivat2@msu.edu 1 .00
14 ackerm48@msu.edu 1.00
15 aclayton@msu.edu 1 .00
1B adaireli@msu.edu 1.00
17 adamsdia@msu.edu 1.00
‘18 adamsr10@msu.edu 1.00
19 adducije@msu.edu 1.00
20- adirekso@msu.edu 1 .00
21 adkinsn1@msu.edu 1.00
22 adudodla@msu.edu 1.00
' 23 agama19@msu.edu 1.00
24 aguwaok1@msu.edu 1.00
25 ahmedan2@msu.edu 1.00
25 aizazahm@msu.edu 1.00
27 ajseok@msu.edu 1.00
28 akensjes@msu.edu 1.00
‘ 29 akerleym@msu.edu 1.00
30 akinsbet@msu.edu 1.00
31, alammuha@msu.edu 1 .00

 

 

 

V “metres-mi; Variabiemaw r

 

127

APPENDIX D

Factor Analysis for Travel Involvement

128

Results of Factor Analysis Performed on Travel Involvement (9 items)

Total Variance Explained

 

 

 

 

 

 

Component Initialggenvalues Extraction Sums of Squared LoadirLgs_

% of Cumulative "/0 of Cumulative
Total Variance % Total Variance %

1 4.543 50.483 50.483 4.543 50.483 50.483

2 1.195 13.275 63.758 1.195 13.275 63.758

3 .817 9.075 72.833

4 .652 7.241 80.074

5 .452 5.024 85.098

6 .429 4.765 89.863

7 .388 4.309 94.172

8 .333 3.698 97.870

9 .192 2.130 100.000

 

 

 

 

 

 

 

Extraction Method: Principal Component Analysis.

 

 

 

 

Rotated Component Matrix(a)
Component
1 2

IV1 IV1 .754
IV2 |V2 .871
lV3 lV3 .775
lV4 lV4 .552
NS NS .828

IV6 IV6 .874

IV? |V7 .735

1V8 |V8 .721

lV9 IV9 .595

 

 

 

 

 

Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a Rotation converged in 3 iterations.

129

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