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This is to certify that the

dissertation entitled

A STUDY OF PLEASURE TRIP PLANNING BEHAVIOR WITH
IMPLICATIONS FOR IMPROVED TOURISM PROMOTION

presented by

SEMOK YOON

has been accepted towards fulfillment
of the requirements for

Ph.D. degmin PARK, RECREATION, AND
TOURISM RESOURCES

(”WM zfl<

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6/01 cJCIRC/DateDUOpGS-p. 15

A STUDY OF PLEASURE TRIP PLANNING BEHAVIOR WITH IMPLICATIONS
FOR IMPROVED TOURISM PROMOTION

By

Semok Yoon

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Department of Park, Recreation, and Tourism Resources

2000

ABSTRACT

A STUDY OF PLEASURE TRIP PLANNING BEHAVIOR WITH IMPLICATIONS
FOR IMPROVED TOURISM PROMOTION

By

Semok Yoon

The role of promotion in the tourism industry has increased as competition has
increased. While most of the scholarly literature on tourism promotion has focused on
identification of media selection behaviors of pleasure travelers and the effectiveness of
promotion programs using various promotion vehicles, the issue of timing of promotional
messages has received limited attention.

The focus of this study was on the timing aspects of trip planning behavior of
Michigan pleasure travelers, with the goal of providing information to tourism marketers
so that they can schedule tourism promotion distribution to achieve maximum impact.
Four elements were involved and investigated in this study: (1) the duration and
frequency distribution for three trip planning intervals, (2) two different decision making
approaches underlying the trip planning and decision making process, (3) variables that
influence the duration of the total trip planning interval, and (4) the distribution of the
three study relevant dates.

The findings of this study are based on data collected from telephone interviews
conducted during the three year period January 1996 through December 1998. The data
set included 1,476 completed cases during this three year period. The analyses performed

were primarily descriptive in nature; however, ordinary least square regression analysis

was performed to identify variables that influence the duration of the total trip planning
interval.

Almost 68% of Michigan pleasure travelers began to plan their trips and made
final decisions within one month of travelling. The information processing interval was
found to be a surprisingly short—seven days long—with a strongly skewed distribution
toward zero. In fact, 85% of respondents reported zero number of days engaged in
information processing.

Two different decision making approaches, instant decision-makers and hesitant
decision-makers, were defined and compared across selected variables. Analyses
revealed several statistically significant differences between the two groups. Michigan
pleasure travelers are likely to take a longer time to plan their trips if: (1) trips are taken
during summer; (2) the travel party is large; (3) they participate in outdoor recreation and
attend a festival or event; (4) it is a vacation trip; (5) they stay at a friend's or relative's
home; (6) the duration of trip was longer; and (7) if total trip expenditures are greater. An
examination of detailed frequency plots of dates when: trip planning began, trip
destination was selected, and the trip began revealed a clustering of frequencies early in
the month.

Collectively, the results from this study suggest that: (1) most promotional
messages would be likely more effective if timed to appear relatively close to when a trip
is expected to begin; (2) somewhat appear to be promotion releases are desirable when
targeting summer vacation travelers; and (3) advertisements that appear early in the
month are likely to have a greater impact than those that appear later in the month. Of

these, the first may be the most at odds with current tourism industry promotion practices.

Copyright by
SEMOK YOON

2000

ACKNOWLEDGMENTS

I would like to express my appreciation to the following people for their assistant
in the development of this dissertation. I would first like to thank Dr. Donald Holecek,
my graduate committee chairman for his guidance in selecting a topic and for his
assistance though the analysis and writing process. Through my degree program, he
provided financial supports, encouragement, and guidance. His support and guidance
enable me to complete my Ph.D. program. I would also like to thank the members of my
graduate committee, Dr. John Hoehn, Dr. Larry Leefers, and Dr. Daniel Spencer for their
insights and assistance in this process.

My parent, Ha-Heon Yoon and Mi-Ja Won, has been supportive through my life.
Without their sincere love, encouragement, and sacrifice, I could not finish my degree
program. I really dedicate this dissertation to them with love from the bottom of my
heart. I would like to thank my wife, Myunghee Lee, for all of her love, encouragement,
and support. Also, my beautiful daughters, Kimberly and Kristine, continued to show me
the affection and warmth when I was less than fun. Finally, I would like to thank my

brother and sisters, Se-Eun, Se-Hwa, and Se-Nam, for their warmth and love.

TABLE OF CONTENTS

LIST OF TABLES .............................................................................................................. x
LIST OF FIGURES ......................................................................................................... xiv
CHAPTER I
INTRODUCTION .............................................................................................................. 1
Significance of the Tourism Industry ............................................................................. 1
Unique Characteristics of Tourism ................................................................................. 1
Role of Promotion in Tourism Marketing ...................................................................... 3
Promotion Efforts of Tourism Destinations .................................................................... 3
Previous Studies on Tourism Promotion ........................................................................ 4
Objectives of Promotion ................................................................................................. 5
Time Frames Underlying the Trip Flaming and Decision Making Process .................. 5
Previous Studies and Problem Statement ....................................................................... 6
Study Objectives ............................................................................................................. 8
Discussion of Objectives ................................................................................................ 8
Duration and Frequency Distributions for Three Trip Planning Intervals
(Objective 1) ............................................................................................................... 8
Two Different Decision Making Processes (Objective 2) .......................................... 9
Variables That Influence the Duration of the Total Trip Planning Interval
(Objective 3) ............................................................................................................. 10
Frequency Distributions of Trip Related Dates (Objective 4) .................................. 10
Central Research Hypotheses ....................................................................................... 11
Organization of the Paper ............................................................................................. 12
CHAPTER II
LITERATURE REVIEW ................................................................................................. 13
Previous Studies of Tourism Promotion ....................................................................... 13
The Travel Decision Making Process and Implications for Tourism Promotion ........ 14
Decision Making Approaches ....................................................................................... 20
Information Search Behavior ........................................................................................ 20
Studies of the Trip Planning Interval ............................................................................ 22
Regression Analysis ...................................................................................................... 25
Regression vs. Correlation ........................................................................................ 26
Asymptotic Property Assumptions of the Classical Regression Model ................... 27
Hypotheses Tests ...................................................................................................... 28
Econometric Models for Censored Data ....................................................................... 29
Sampling Design and Random Digit Dialing ............................................................... 31
Computer-Assisted Telephone Interviewing ................................................................ 32

vi

CHAPTER III

METHODS AND PROCEDURES ................................................................................... 34
Survey Design ............................................................................................................... 34
Household Telephone Survey ................................................................................... 34
Mode of Survey Administration and Data Collecting Instrument ............................ 35
Sampling and Time Frames ...................................................................................... 37
Length of Interview ................................................................................................... 37
Interviewing and Supervising ................................................................................... 37
Response Rate ........................................................................................................... 38
Study Population and Region ................................................................................... 39
Operational Definition of Trip .................................................................................. 39
Preparation of Data ....................................................................................................... 41
Most Recent Michigan Pleasure Travelers ............................................................... 41
Visiting Friends and Relatives Market ..................................................................... 41
Data Weighting ......................................................................................................... 43
Study Relevant Time Frames ........................................................................................ 43
Time Frames in Questionnaire .................................................................................. 43
Defining Study Relevant Time Frames Underlying the Trip Planning and Decision
Making Process of Pleasure Travelers ...................................................................... 44
Mathematical Definitions of Time Frames of the Travel Decision Making Process 45
The Date Trip Planning Began ................................................................................. 47
Valid Cases for This Study ....................................................................................... 48
Analyses of Data ........................................................................................................... 49
Duration and Frequency Distributions for the Three Planning Intervals
(Objective 1) ............................................................................................................. 50
Two Different Decision Making Approaches (Objective 2) ..................................... 50
Variables that Influence the Duration of the Total Trip Planning Interval
(Objective 3) ............................................................................................................. 55
The Model ............................................................................................................. 55
Defining Independent Variables ........................................................................... 55
Regression Estimates ............................................................................................ 58
Ideal Conditions of Least Square Regression and Tests ....................................... 58
Double Censored Distribution of the Dependent Variables ................................. 6O
Distributions of the Planning Dates .......................................................................... 61
CHAPTER VI .
RESULTS AND DISCUSSION ....................................................................................... 62
Duration and Frequency Distributions of the Three Trip Planning Intervals
(Objective 1) ................................................................................................................. 62
Distribution of the Total Trip, Post Decision, and Information Processing
Intervals .................................................................................................................... 64
Distribution of Total Trip Planning and Post Decision Intervals ......................... 64
Frequency Distribution of the Information Processing Interval ........................... 72
Two Different Decision Making Approaches (Objective 2) ......................................... 74
Sources of Information and Media Habits of Instant and Hesitant Decision
Makers ...................................................................................................................... 82

vii

Trip Characteristics and Behaviors of Instant and Hesitant Decision Makers ......... 82
Demographic and Socioeconomic Characteristics of Instant and Hesitant

Decision-Makers. ...................................................................................................... 83
Variables That Influence Duration of the Total Trip Planning Interval (Objective 3). 83
The Model ................................................................................................................. 84
Estimation Results .................................................................................................... 85
Goodness of Fit ......................................................................................................... 87
Comparisons of Independent Variables .................................................................... 88
The Total Trip Planning Interval and Internet Use ................................................... 89
Test for Normality .................................................................................................... 91
Multicollinearity and Singularity .............................................................................. 94
Doubly Censored Normal Distribution ................................................................. 96
Distributions of the Dates Trip Planning Began, Trip Destination was Selected, and
Trip Began (Objective 4) .............................................................................................. 99
Three Part Month Segmentation Results ................................................................ 100
Monthly Analysis of Trip Related Flaming Dates ............................................. 106
Seasonal Analysis of Trip Related Planning Dates ................................................. 108
Results With and Without Visiting Friends and Relatives (VF R) Included ............... 110
CHAPTER V
SUMMARY AND CONCLUSIONS ............................................................................. 112
Summary of Results .................................................................................................... 112
Duration and Frequency Distributions for the Three Trip Planning Intervals
(Objective 1) ........................................................................................................... 112
Two Different Decision Making Approaches (Objective 2) ................................... 114
Planning Interval and Selected Socioeconomic and Trip Related Variables
(Objective 3) ........................................................................................................... 115
Distributions of Time Frames Underlying the Travel Decision Making Process
(Objective 4) ........................................................................................................... 117
Results With and Without Visiting Friends and Relatives (VFR) Included ........... 118
Implications of Results ............................................................................................... 119
Implications for Promotion Timing ........................................................................ 119
Implications for Information Distribution Timing .................................................. 121
Study Limitations ........................................................................................................ 121
Nonresponse and Refusal Rates .............................................................................. 121
Secondary Nature of Data ....................................................................................... 122
Recall Bias .............................................................................................................. 123
Generalizability ....................................................................................................... 123
Suggestions for Further Study .................................................................................... 124
APPENDIX A: QUESTIONNAIRE ............................................................................... 127

APPENDIX B: RESULTS EXCLUDING THE VISITING FRIENDS AND
RELATIVES (VFR) MARKET ..................................................................................... 155

viii

APPENDIX C: DURATION OF TOTAL TRIP PLANNING INVERVAL FOR
SELECTED VARIABLES ............................................................................................. 176

LITERATURE CITED ................................................................................................... 180

ix

LIST OF TABLES

Table 1. The stages of decision making in pleasure trip choice. ...................................... 15
Table 2. The elements of customers' travel decisions ....................................................... 16
Table 3. Leisure traveler information search model. ........................................................ 24

Table 4. Definitions and descriptions of the time frames of the travel decision making
process from the study questionnaire ........................................................................ 44

Table 5. Sources of information and media habits of Michigan pleasure travelers .......... 52

Table 6. Demographic and socioeconomic characteristics of Michigan pleasure

travelers. .................................................................................................................... 52
Table 7. Travel behavior of Michigan pleasure travelers. ................................................ 53
Table 8. Descriptions of independent variables. ............................................................... 57
Table 9. Summary of statistics for the three planning intervals. ...................................... 63
Table 10. Frequency distribution for the total trip planning interval. ............................... 66
Table 11. Frequency distribution for the post decision interval. ...................................... 67

Table 12. Reported frequencies by selected time intervals for the total trip planning
and post decision intervals. ....................................................................................... 71

Table 13. Frequency distribution for the information processing interval. ............... 73

Table 14. Sources of information and media habits of instant and hesitant decision-
makers. ...................................................................................................................... 76

Table 15. Trip characteristics and behaviors of instant and hesitant decision-makers. 77

Table 16. Demographic and socioeconomic characteristics of instant and hesitant
decision-makers. ....................................................................................................... 8 1

Table 17. Estimated influence of selected variables on total trip planning interval-OLS
regression results ....................................................................................................... 85

Table 18. Total planning interval by: Do you or any member of your household have
access to the Internet? ............................................................................................... 89

Table 19. Total planning interval by: During the past 12 months, have you or any
member of your household used the Internet to obtain travel information? ............. 90

Table 20. Total planning interval by: During the past 12 months, have you or any
member of your household used the Michigan Travel Bureau's site on the World
Wide Web to obtain travel information? .................................................................. 90

Table 21. Total planning interval by the degree of Internet involvement. ....................... 91

Table 22. One-sample Kolmogorov-Smimov Test for normal distribution of residuals. 94

Table 23. Multicollinearity test statistics -Tolerance test. ................................................ 95

Table 24. Estimated influence of selected variables on total trip planning interval
-OLS, negative binomial, and double bounded tobit regression results. .................. 98

Table 25. Relative frequencies of three different dates related to trip planning by
three segments of the month. .................................................................................. 101

Table 26. Significance test of relative frequencies of trip related dates by segment of
month in which they occur ...................................................................................... 102

Table 27. Relative frequencies of three different dates related to trip planning by
three segments of the month excluding July and September. ................................. 104

Table 28. Significance test of relative frequencies of trip related dates by segment of
month that they occur-excluding two months: July and September. ...................... 105

Table 29. The differences of relative frequencies of trip related dates by segments of
month between the data sets including and excluding the July and September. 106

Table 30. Frequency distributions for three tn'p related dates by month. ....................... 107
Table 31. Frequency distributions for three travel related dates by season. ................... 109
Table Bl. Summary of statistics for the three planning intervals (VFR excluded). ....... 156
Table Bl-l. Summary of statistics for the three planning intervals (VF R included). 156
Table B2. Frequency distributions for total trip planning interval (VFR excluded). ..... 157
Table B3. Frequency distributions for post decision interval (VFR excluded). ............. 158

Table B4. Reported frequencies by selected time intervals for the total trip planning
and post decision interval (VFR excluded) ............................................................. 159

xi

Table 34-1. Reported frequencies by selected time intervals for the total trip
planning and post decision interval (VFR included). ............................................. 159

Table B5. Frequency distributions for information processing interval
(VFR excluded) ....................................................................................................... 160

Table B5-l. Frequency distributions for information processing interval
(VFR included). ...................................................................................................... 161

Table B6. Sources of information and media habits of instant and hesitant decision-
makers (VFR excluded). ......................................................................................... 162

Table B7. Trip characteristics and behaviors of instant and hesitant decision-makers
(VFR excluded) ....................................................................................................... 163

Table B8. Demographic and socioeconomic characteristics of instant and hesitant
decision-makers (VFR excluded). .......................................................................... 167

Table B9. Relative frequencies of three different dates related to trip planning by
three parts of months of the month (VFR excluded). ............................................. 168

Table 89-] Relative frequencies of three different dates related to trip planning by
three parts of months of the month (VFR included). .............................................. 169

Table B10. Significance test of relative frequencies of trip related dates by segment
of month that they occur (VFR excluded). ............................................................. 170

Table BIO-1. Significance test of relative frequencies of trip related dates by segment
of month that they occur (VFR included). .............................................................. 170

Table Bl 1. Relative frequencies of three different dates related to trip planning by
three parts of the month excluding July and September (VFR excluded). ............. 171

Table Bl 1-1. Relative frequencies of three different dates related to trip planning by
three parts of month excluding July and September (VFR included) ..................... 172

Table B12. Significance test of relative frequencies of trip related dates by segment
of month that they occur excluding July and September (VFR excluded). ............ 173

Table B12-1. Significance test of relative frequencies of trip related dates by segment
of month that they occur excluding July and September (VFR included) .............. 173

Table B13. Frequency distributions for three trip related dates by month
(VFR excluded) ....................................................................................................... 174

xii

Table Bl3-l. Frequency distributions for three trip related dates by month

(VFR included). ...................................................................................................... 174
Table 314. Frequency distribution for three travel related dates by season

(VFR excluded) ....................................................................................................... 175
Table Bl4—1. Frequency distribution for three travel related dates by season

(VFR included). ...................................................................................................... 175
Table C 1. Duration of the total trip planning interval for selected variables. ................ 177

xiii

LIST OF FIGURES

Figure 1. The travel decision making process--A model. ................................................ 18
Figure 2. Flow chart for the survey questionnaire. ........................................................... 36
Figure 3. Study region. ..................................................................................................... 40
Figure 4. Trip planning and decision making process phases and time frames ................ 44

Figure 5. Frequency distribution of reported number of days in the total trip planning
interval. ..................................................................................................................... 68

Figure 6. Frequency distribution for reported number of days in the post decision
interval. ..................................................................................................................... 69

Figure 7. Comparisons between frequencies of reported total trip and post decision
intervals for six selected time frames ........................................................................ 71

Figure 8. Histogram of regression standardized residuals of the total trip planning

interval. ..................................................................................................................... 93
Figure 9. Frequency distribution plots for three trip related dates by month. ................ 107
Figure 10. Frequency distribution plots for three travel related dates by season. .......... 109

xiv

CHAPTER I

INTRODUCTION

3.5 “1.11

The tourism industry contributes significantly to local, state, and national
economies by generating high volumes of employment and taxes. In 1997, in the United
States, tourism was responsible for over sixteen million jobs and added over $500 billion
to the Gross Domestic Product. It generated over $70 billion in state and local taxes,
contributed over $127 billion in employee compensation, was among the top three
leading employers in 32 states, and catered to 45.6 million international visitors, resulting
in a net trade surplus of over $24 billion (Travel Industry Association of America, 1998).
During the next ten years, these numbers are expected to grow by as much as 24%

(Travel Industry Association of America, 1998).

11' :1 .. [1.

Many states and local destination marketing organizations (DMOs) are increasing
marketing efforts to attract more tourists for these economic benefits (English, 1981;
Kreisman, 1982; Perdue, 1985). However, destination marketers have been faced with
several risks related to tourism marketing (Morrison, 1989; Schmoll, 1977). The origins
of these risks are the unique characteristics of tourism, including: instability of demand,
inflexibility of supply, and competition among destinations.

A group of interacting factors contributes to an unusually high degree of demand

instability in tourism. These factors include a high degree of elasticity of demand in

relation to price and to income, strong seasonal variations in demand, and a low level of
customer loyalty with respect to trip destinations.

Demand instability is especially critical because it is combined with a low degree
of flexibility on the supply side of the industry. On the supply side, most tourism
enterprises cannot easily and quickly react to changes in demand by adapting the quality
or the quantity of the services provided.

Another risk in tourism marketing is competition among services and
destinations. Over the past decade, the travel industry has become increasingly
competitive (Perdue & Gustke, 1992). As a result, substitution is intense between
competing products or services whose main characteristics and customer benefits are
similar to one another if not virtually identical (Schmoll, 1977). For example, there is
strong competition among airlines serving the same routes with identical equipment and
minimal differences in schedules of services because one carrier can readily be
substituted for any other carrier. Many other tourist services are equally vulnerable to
substitution although they are not at all identical.

There is also a high degree of substitution among travel destinations. The
potential tourist is confronted with a wide range of alternative services, travel modes,
types of arrangements, and destinations. A direct consequence of abundance of choice is
the low level of customer loyalty in tourism (Gitelson & Crompton, 1983; Schmoll, 1977;
Schul & Crompton, 1983). Few tourists visit the same destination regularly, consistently
prefer a certain type of transportation or accommodation, or use the same travel agent or
tour operator year after year to prepare their vacation travel. With increasing mobility—

by private automobile and by other means of transport, especially air charters—the range

of travel opportunities widens, and destinations and services previously not in direct

competition with one another are being considered as alternative choices.

11le "I'lll'

Marketing literatures suggest that there are two purposes of promotion. First one
is to influence consumers' affect and cognition—their evaluations, feelings, knowledge,
meanings, beliefs, attitudes, and images concerning product and brands. The purpose of
promotion is to inform, to persuade, to remind, and more specifically, to influence
potential customers through communications to think and act in a certain manner (Kotler,
1996; Morrison, 1986; Peter and Olson, 1993; Schmoll, 1977). Promotion in tourism
marketing is a tool to reduce the marketing risks described previously and attract more
tourists (Kotler, 1996; Morrison, 1986; Peter and Olson, 1993; Schmoll, 1977). For
example, the vulnerability of a tourist service or destination to substitution can be
reduced through promotional efforts. Destination marketers may reduce the vulnerability
to substitution through the communication of messages with potential pleasure travelers
that emphasize the unique or unusual characteristics or appeal of the destination
(Schmoll, 1977). They also may attempt to obtain a preferential position in the tourism
sector through special advantages offered to tourism representatives and/or through sales

support efforts that lend additional impact to advertising (Schmoll, 1977).

E . E If: [I i E . .
Many state and local DMOs spend a considerable amount of money on tourism

promotion for these benefits of tourism promotion (English, 1981; Kreisman, 1982;

Perdue, 1985). State tourism offices spent over $478 million for promotion programs in
fiscal year 1997-98, an increase of 6.5% over the previous year (Travel Industry
Association of America, 1998). The state of Michigan spent $14.7 million for tourism
promotion programs and ranked tenth in the amount of money spent on promotion during
fiscal year 1997-98. As states continue to promote increasing numbers of pleasure trip
alternatives and spend huge amounts on tourism promotion, the tourism industry has
become more competitive which has led to development of more sophisticated research-

based promotion programs to maximize the effects of their efforts (Crask, 1981).

EV'SI'I'E'

Several studies have identified the media selection behaviors of pleasure travelers
and the effects of promotion programs using various promotion vehicles (Ballman,
Burke, Korte, & Blank, 1984; Burke & Gitelson, 1990; Burke & Lindblom, 1989; Hunt
& Dalton, 1983; Purdue, 1985; Purdue, 1986; Perdue & Botkin, 1988; Woodside, 1981;
Woodside, 1990; Woodside & Reid, 1974; Woodside & Ronkainen, 1982; Woodside &
Ronkainen, 1984; Yochum, 1985). These studies focused on consumer behaviors related
to a variety of promotion tools. Specifically, they revealed which promotion tools
attracted the most visitors to a destination. A variety of promotion vehicles were studied,
including coupons, information packets, welcome centers, and brochures.

While most of the tourism promotion literature has focused on identification of
media selection behaviors of pleasure travelers and the effect of promotion programs
using various promotion vehicles, the issue of how tourism promotion messages should

be timed has received limited attention in the tourism marketing literature. Proper timing

would appear to be of equal importance to targeting one's high potential customers with
effective messages in their preferred media. Timing is more important than ever before
given the ever growing numbers of advertising messages which compete for travelers'
attention and an increasingly time stressed population with a growing tendency to totally

ignore all but the most pertinent and timely promotion messages.

According to the marketing literature, the issue of promotion timing depends on
the objectives of promotion (Coltman, 1989; Peter & Olson, 1993; Kotler, Brown, &
Makens, 1996; Morrison, 1989). If the promotion objective is to improve a destination's
image among current and potential pleasure travelers, the promotion messages need not
be distributed at specific times (Coltman, 1989). On the other hand, if the promotion
objective is to persuade present and potential pleasure travelers to take trip to a
destination, the promotion must reach them at the time they are beginning to think about
their vacation trips (Coltman, 1989). Information about when pleasure travelers begin to
plan their trips may obtained from survey such as that from which data for this study
were derived.

u,‘ 111‘ 11' 191' n ' 9111' «.10. D‘ '01 .U!\.° ' o ‘

The trip planning and decision making process involves several phases, including
need arousal, information collection and processing, and decisions on destination,
services, and trip date (Moutinho, 1987). Along with this series of trip planing and

decision making phases, several relevant time frames can be identified.

Trip planning can be viewed as a continuum bounded by the date trip planning
began on one pole and by the date the trip itself began on the other pole. The interval
between these extremes is defined herein as the "total trip planning interval". An
additional date along this continuum, the date the trip destination was selected, divides
the total trip planning interval into two parts which can be defined as the "information
processing interval" and the "post decision interval". The former is the number of days
between the date trip planning began and the date the trip destination was selected. The
latter is the number of days between the dates when the trip destination was selected and
the trip began. I

These time frames are cited as informants in preparing effective and efficient
tourism promotion programs or information distribution schedules. For example, Schmoll
(1977) stressed that the promotion efforts of travel marketers must be timed in such a
way that they reach potential pleasure travelers during the need arousal phase so that their
interest and desire to know more about a destination or service is aroused at the most

appropriate moment.

E v' S 1 IE I l 5

Several studies have dealt with the time frames of the travel decision making
process (Fodness & Murray, 1997; Gitelson & Crompton, 1983; Perdue, 1985; Schul &
Crompton, 1983). These studies have reported variables that influence the duration of the

length of the total trip planning interval (Gitelson & Crompton, 1983; Schul & Crompton,

 

I For detailed conceptual and operational definitions of these time frames of the travel decision making
process, see Chapter III.

1983) and have segmented and profiled the planning interval (Fodness & Murray, 1997;
Perdue, 1985).

These studies have focused on primarily one relevant planning interval, that being
the total trip planning interval. However, the total trip planning interval alonemay not
provide sufficient information for preparing effective and efficient promotion or travel
information distribution schedules to destination marketers. For example, if a destination
marketer has information about only the total trip planning interval and does not know
when pleasure travelers make final decisions on trip destinations, he might continue to
spend his promotion efforts or budget to attract travelers who already have decided on
their trip destinations, or, in the terminology adopted for this study, those out of the
information processing interval.

Therefore, further study of this and other identifiable trip planning intervals and
their associated frequency distributions is required to more precisely schedule tourism
promotion and thereby improve its effectiveness.

The researchable questions that emerge from the above discussion are: do trip
planning intervals vary across pleasure travelers, if so, how and why do they, and what
are the frequency distributions of the study relevant dates? The answers to these research
questions will provide more information about pleasure trip planning behavior to
destination marketers who may use them to improve their promotion program distribution

schedules.

mm
The objectives of this study were developed from the researchable questions
described above, and they are:

1. To investigate the duration and frequency distributions for the three trip planning
intervals defined previously (total trip planning, post decision, and information
processing intervals).

2. To investigate two different decision making approaches underlying the trip planning
and decision making process.

3. To investigate variables that influence the duration of the total trip planning interval .

4. To investigate the distribution of the three study relevant dates defined previously

(the date the trip planning began, the trip destination was selected, and the trip

began).
Ll . [21' 'v
D.o.01-_H ‘131 '11-” .0 1“ I" ’11113 n , 01' 'V

The three trip planning intervals assessed in this study were the: (1) total trip
planning interval (length of time between the beginning of trip planning and the date the
trip begins), (2) information processing interval (length of time from the date trip
planning begins through the date trip destination selected), and (3) post decision interval
(length of time from the date the trip destination is selected through the date the trip
begins). The central research question was: do the trip planning intervals vary across
pleasure travelers? The duration of these intervals was hypothesized to vary across

pleasure travelers. If the duration of these planning intervals is proven to vary across

pleasure travelers, the frequency distributions of these intervals can be used to more
effectively time the release of travel promotion to reach specific target audiences.
General knowledge of these frequency distributions is useful especially for those
marketers who plan to attract visitors during a specific time period, such as the warm
season or a particular festival or event. The distributions of trip planning intervals provide
information about how early and late pleasure travelers begin to plan trips (total trip
planning interval), make final decisions on trip destinations prior to their trip dates (post

decision interval) and after the date trip planning began (information processing interval).

Tw ' ' ' M i Pr ' 'v

As stated previously, the information processing interval is the length of time
between the date the trip planning begins and the date the trip destination is selected.
During this time interval, people search for relevant information to select their trip
destinations. It was expected that some people take less time searching the relevant
information and others may take more time. These two groups are expected to differ with
respect to: information sources used, media habits, trip behavior, past experience and
socioeconomic characteristics. For example, those with short information processing
intervals may be those who: visit a destination frequently, do not stay as long, or visit
friends or relatives. Therefore, it is potentially beneficial to segment and profile the
pleasure travel market based on length of the information processing interval. Two
possible groups were defined for this study: (1) those whose information processing

interval is zero days—defined as 'instant decision-makers' and (2) those whose

information processing interval is one day or more—defined as 'hesitant decision-

makers'.

V 11 ‘ 1-. 1331 ‘ 1' 9.1010 1‘ 1 -. JO .'_-.1 . ‘ .1 ' ._ 01- 'V

The variables that influence the duration of the total trip planning interval were
also investigated. Objective 1 was included in the study objective because it would
provide information about how trip planning behavior differs among pleasure travelers.
This objective (Objective 3) concerns why planning varies across pleasure travelers.
Specifically, this objective involves identification of variables that influence the duration
of the total trip planning interval.

This study objective has been addressed in previous studies. Pitegoff (1990) and
Davison (1988) both questioned if it is appropriate to assume that the same decision
process occurs for such diverse groups as repeat travelers and first-time visitors; day
visitors and overnight or long stay visitors; and visitors on shopping trips and those
visiting friends and relatives. Schmoll (1977) stressed that the total trip planning interval
is variable and, to some degree, is related to the duration of the pleasure trip and its

expense.

E 12' 'l' [I' El 12 :1. .V I;

The frequency distributions for trip planning intervals provide useful information
about the trip planning behavior of pleasure travelers. They are especially useful for those
marketers who seek to attract visitors during a specific time period. However, these

planning intervals are not so useful when tourism marketers plan to allocate their

10

promotion efforts or budgets across days of the month or months or seasons of the year.
Suppose that a destination marketer plans to distribute promotion programs across the
months of the year and has information that, on the average, two-thirds of his target
market begins to plan within one month of taking a trip. Without information about the
distribution of travel across months of the year, marketers lack information necessary to
guide allocation of one's promotion across months of the year. Therefore, it is necessary
to examine the frequency distributions of the study relevant dates (the date planning
began, destination selected, and the trip began). Knowledge of the frequency distributions
for these dates will guide tourism marketers in finding the best time to distribute
promotion programs and travel information and also allocate their finite resources of time

and money across the year.

WW

Hypothesis 1. The planning intervals underlying the trip planning and decision making
process are the same across pleasure travelers.

Hypothesis 2. No differences exist between instant decision makers and hesitant decision
makers with respect to information sources used, media habits, socioeconomic
characteristics, travel party composition and trip characteristics, trip behavior, or
expenditures.

Hypothesis 3. Selected socioeconomic characteristics, travel party composition, trip
characteristics and behavior, and expenditure variables have no effect on the duration

of the total trip planning interval.

11

C . . E 1 E

The next chapter contains a review of literature related to the t0pics and
techniques used in the study. Background material as well as related research are
presented for the topics and techniques included in this study. The methods and
procedures used in the study follow the literature review. This chapter includes how the
data used were collected and how the analyses proceeded. The results of the study are
presented in the Chapter VI in the order that study objectives were presented. The final
chapter contains a summary of the procedures and findings along with implications and
limitations of the study. Suggestions for further study are also presented in this last

chapter.

12

CHAPTER II

LITERATURE REVIEW

The purpose of this study was to provide information about trip planning
behaviors of pleasure travelers to marketers by providing some insight into the relevant
time frames underlying the trip planning and decision making process of pleasure
travelers. Background material as well as related research are presented for the: (1)
concepts related to the topic of the study and (2) methods used in the study.

Initial sections of this chapter describe previous tourism promotion studies, the
decision making process of pleasure travelers, and previous studies of the planning
intervals of pleasure travelers. Later sections explain techniques used in the studys, such

as computer-assisted telephone interviewing and regression analysis.

v' i ' 1

Previous studies of tourism promotion have focused on evaluations of promotion
effectiveness. Empirical studies intended to evaluate the effects of promotion on sales
date back to the 19305. The early studies found that promotion significantly affected
market share and firm sales within particular industries. Both Schmalensee (1972) and
Comanor and Wilson (1974a, 1974b) recognized the strong correlation between sales and
promotion in the tourism industry.

More recently, Fesenmaier and Vogt (1993) evaluated the effectiveness of travel
information provided at Indiana welcome centers in modifying travel behavior. The travel

behaviors they considered were the amount of time spent in Indiana, the selection of

13

alternative attractions, and the incremental expenditures produced by longer visits or
visiting a variety of places. Their findings suggest that pleasure travelers can be
influenced by the information distributed in welcome centers to extend their stay and
select alternative attractions which resulted in substantial direct economic impact to the
state.

Butterfield, Deal, and Kubursi (1998) estimated the impact of tourism advertising
on tourist spending for the "1987-88 Ontario Incredible Advertising Campaign." They
linked advertising expenditures to changes in attitudes toward and awareness of potential
travel destinations based on advertising tracking data. They then related changes in
attitudes and awareness to changes in the number of visits to the destinations, based on
LISREL and econometric analysis of advertising tracking data. Finally, they translated
changes in the number of visits into changes in tourism expenditures, based on actual
visits and expenditures. They found that advertising changes attitude and generates

positive impacts on expenditures.

1' ,V'I'°'1u..1:' 1 ° -_ 1111111 f1r 1.111,
The decision making process is based on several factors, including: motivation
levels, needs and desires of individuals, and their expectations when facing a travel
decision (Moutinho, 1987) According to Schmoll ( 1977) and Moutinho (1987), the

decision making process involves four principal phases: tourism need, information

gathering and deliberation, decision, and travel preparation (See Table 1).

l4

Table 1. The stages of decision making in pleasure trip choice.

 

Phase

Events and decisions

Influence and considerations

 

Tourism need

Information gathering
and deliberation

Decision

Travel preparation

A general desire to travel is
felt. Reasons for and against it
are weighed, but no specific
information is collected and
evaluated.

A study of travel catalogues
and travel advertising,
discussions with friends,
consultation with travel agents
and other specialists occurs

Decisions are made about:

- destination, travel mode

- timing

- intermediary and tourism
service enterprise

Bookings and confirmations
are made.

Travel funds, clothing and
equipment secured.

General travel motivations
exist.

Questions considered are:
When to travel?

How much can be spent?
Previous travel experiences?

Advice and reports from
friends, advertising and
promotion, suggestions from
travel agent are considered.

Intennediaries' advice.
Images.
Previous experiences.

Travel intermediary, bank,
retail stores.

 

Source: Schmoll (1977).

According to Schmoll (1977), this travel decision making model suggests several

conclusions for tourism promotion: (1) advertising and sales support efforts must be

timed in such a way that they reach potential customers during the tourism need phase so

that their interest in and desire to know more about a destination or service is aroused at

the most appropriate moment, (2) the choice of a destination occurs fairly early and not

infrequently during the information gathering and deliberation phase. In other words,

most customers already have a destination firmly in mind when consulting the travel

agent or other intermediary. The intermediary's advice is, therefore, mainly sought on

destination arrangements (e.g., hotels, sightseeing, activities) and travel modes (e.g.,

15

private car, air, rail), travel arrangement type (e.g., individual or package tour), and (3)
the time lapse between the travel decision and departure is variable. To some degree, this
time lapse is related to the duration of the vacation trip and its expense (longer and more
expensive travel is booked earlier than shorter and less expensive trips).

Schmoll (1977) and Moutinho (1987) suggested that the travel decision is
composed of a range of decision elements or sub-decisions (Table 2).

Table 2. The elements of customers' travel decisions.

 

Where to go? Destination (country, area, or locality)

How to get there? Transportation (e. g., private car, air, rail, bus, sea)

Where to stay? Accommodations (e.g., hotel, motel, camping site)

What to do there? Activities (e.g., museum visits, shopping, outdoor recreation)
What travel ‘ Individual arrangements (direct at destination or through

arrangements to make? intermediary), package tour (with or without full service at
destination), etc.

How much to spend? Overall travel budget including transportation, food,
accommodations, a reserve for unforeseen purchases, and
needs.

Where to book? Individual arrangements with tourist service enterprises

(transport, accommodation, etc.) or booking through a travel
agent or tour operator.

 

Source: Moutinho (1987).

The existing models of buyer behavior describe and explain the processes of
purchasing physical goods (consumer products, industrial supplies or equipment) and the
factors that have a bearing on the decision to purchase them. Decision making process

models for service industries are still in an early stage of development.

16

The model presented in Figure l was adapted from Moutinho's (1986) travel decision
making model. The model suggested here can be utilized in four areas. First, it indicates
where marketing actions--especially promotions--can be used to influence the decision
process in favor of a given travel service or destination. Second, it shows which factors
have a bearing on travel decisions, thus indicating which positive influences should be
reinforced and which negative influences should be counteracted. Also, it can be used in
research planning. Areas where information is incomplete or altogether missing can be
readily identified. Finally, the model can be used to determine the criteria by which target
markets or market segments of special interest and value to a tourist enterprise or
destination can be identified.
The model is based upon the following premises:

1. The decision process and its eventual outcome are influenced by four sets of
variables: customer goals, travel opportunities, communication efforts and an
intervening or independent variable.

2. It is possible to identify these sets of variables and their individual components
and to determine how and when they influence the decision process.

3. The eventual decision (e.g., choice of a destination, travel time, type of
accommodations, type of travel arrangement) is in fact the result of a distinct

process involving several successive stages or phases.

17

I. TRAVEL
STIMULI

 

Advertising and

 

 

 

 

 

 

II. PERSONAL AND SOCIAL DETERMINANTS OF TRAVEL BEHAVIOR

 

 

Socio-economic
status

 

 

Personal features

 

 

Soc 1al influences and
aspirations

 

Attitudes and
values

 

 

 

l

l

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1—1
Promotion l i
, MOTIVATIONS DESIRES NEEDS EXPECTATIONS
I Travel Literature ’— I I j
{ Word-of-Mouth J—— " "
Travel trade L—
recommendation
TRAVEL INFORNLATION ASSESSKFE? TRAVEL
‘ ‘ ‘ ‘ ' " DESIRES SEARCH ALTERNATIVES DECISION
III. EXTERNAL
VARIABLES

 

Confidence in travel
trade intermediary

 

 

 

 

 

 

 

image of destination:
service

 

 

Previous travel
experience

 

 

Assessment of risk
lobjective’subjective)

_

 

 

Travel constraint
(timexcost)

 

 

p—r

 

 

 

 

 

L

C osW alue
Relations

 

 

 

 

IV. CHARACTERISTICS
AND FEATURES OF
DESTINATION]
SERVICE

 

l

 

 

Attraction/Amenities
Offered

 

 

 

 

Quality-Quantity of
travel information

 

 

1

 

Range of travel
opportunities

 

 

 

 

 

Type of travel

 

arrangements
offered

 

 

Figure 1. The travel decision making process--A model.
(Adapted from Moutinho, 1986).

18

In accordance with the premises above, the model is composed of four fields: (1)
travel stimuli (2) personal and social determinants of travel behavior, (3) external
variables, and (4) characteristics and features of service and destination (Figure 1). The
first field, travel stimuli, is comprised of the external stimuli reaching the prospective
traveler in the form of promotion messages, travel literature of all kinds, word-of-mouth
including suggestions and comments from friends and relatives, and suggestions and
recommendations from travel trade intermediaries in response to inquiry.

The second field includes the personal and social determinants of travel behavior.
The personal features, socioeconomic status, attributes and values, and social influences
and aspirations together determine pleasure travelers' motivations, travel needs and
desires, and the satisfaction expected from travel.

External variables, the third field, includes the prospective traveler's confidence in
the travel intermediary and the tourist enterprise, the images of competing services and/or
destinations, previous experience, assessment of risks, and cost and time constraints that
the prospective traveler has to take into account.

The fourth field of the model, characteristics and features of destination and
services, illustrate the destination and service related characteristics that have a bearing
on the decision process and its outcome. The model presents a visualization of the travel
decision process, especially of the different stages or phases of this process. The different

stages or phases of the process are influenced by each of the four fields simultaneously.

19

12"lll' |

Pleasure travelers make decisions using different approaches, from the highly
routine to the extensive (Bogart, 1969). Most of marketing literature suggests two
different decision making'approaches: routine and extensive decision making approaches
Engel, Blackwell, & Miniard, 1986; Morrison, 1989; Peter & Polson, 1993; Kotler,
1993). In the case of the routine decision making approach, decisions are made quickly
and with little mental effort. The perceived knowledge about the available alternatives is
high. When the extensive approach is taken, there is a need for considerable time and
effort to be invested in the search for information and the evaluation of alternatives.

Fodness and Murray (1997) studied these two decision making approaches by
dividing auto travelers who stopped at official Florida centers into two groups routine
searchers and extended searchers. They defined routine searchers as those who took less
than one month and considered no more than two information sources in planning their
trips. Extended searchers took more than one month and considered more than two
information sources. They found significant differences between these groups with
respect to socioeconomic characteristics, traveling party and trip characteristics, trip

behavior, and expenditures.

I E . S 1 E 1 v'

Understanding the information search behavior of pleasure travelers is vital to
understanding the time frames of the travel decision making process since most planning
time may consist of searching for information. Consumer awareness, selection, and

choice of tourism and hospitality products depends on the information available and used

20

by the tourist (McIntosh & Goeldner, 1990; Moutinho, 1987). Identification of
information sources and planning behavior offers opportunities to increase the probability
that consumers would, at least, be exposed to information about specific destinations.

According to Moutinho (1987):

Information seeking is the expressed need to consult various sources prior

to making a purchasing decision. Initially there is the recognition of the

problem which is a result of a perceived imbalance or need to shift to a

desired state. It activates the decision process, through the search for

information about alternatives (p. 12).

The marketing literature generally differentiates between internal and external
searches for information by a consumer (Crompton, 1983). Internal searches entail
recalling information to which the individual has been exposed in the past. The marketer
has little opportunity to influence these internal searches. However, even an individual
who has some internal store of knowledge upon which to draw might seek additional
information before making a purchase decision.

External searches might be used more frequently in making travel related
decisions than in making decisions to purchase many other types of products. Pleasure
travelers are likely to turn to such external sources in order to learn about the number of
alternative destinations which might meet their needs, the characteristics and attributes of
those destinations, their relative desirability, and the relative costs associated with
visiting them.

An external search represents a conscious effort to seek out new information
through communication with others, from media, from commercial brochures or

guidebooks or through attention to commercials. Because of the effort required, the

natural tendency of consumers is to keep external searches to a minimum. However, there

21

are at least three reasons why external searches may be expected to be frequent in the
tourism field (Crompton, 1983).

First, a pleasure trip is a high risk purchase. It involves not only a considerable
investment of discretionary dollars but also a considerable investment of discretionary
time. In general, the greater the degree of perceived risk in a purchase, the greater the
propensity to search. Obtaining information through an external search is one way of
reducing perceived risk to a more acceptable level.

Second, unlike the retail consumer in a store, the pleasure traveler can neither
directly observe what he is buying, nor try it out inexpensively. Therefore, there is
considerable reliance on secondary and tertiary sources of information. This suggests that
the search for information about potential destinations is likely to be much longer and
involve more and a greater variety of consumer products and services than searches for
information about other products.

Third, pleasure travelers have a tendency to visit new destinations on each trip. A
primary motivation for a vacation is to see new places or to do new things in a different
environment (Crompton, 1979). Previous studies in the consumer behavior literature have
found that the greater the need for variety, the greater the external search effort is likely
to be (Engel, 1994). Unfamiliarity with a new destination suggests that an individual

might spend more time searching for information about it.

5 1' E] 1' El . I 1
An early study of the trip planning interval was conducted by Schul and

Crompton (1983). They segmented the international vacation market in Texas by: (l) the

22

length of time indicated by the respondent during which overt trip planning activities
occurred prior to the vacation which was the furthest away from the respondent’s home
and taken in the past 12 months, and (2) the number of travel organizations (e.g. private
and public travel organizations, transportation carriers, tour operators, etc.) consulted by
the respondent during the trip planning process. They found that four out of six
psychographic factors (cultural interest, comfort, activity, and opinion leadership) were
statistically significant in the variation of the total trip planning intervals.

Just a few months later, Gitelson and Crompton (1983) published another article
about trip planning intervals. Their study examined differences in vacationers’ planning
intervals and how they related to the length of the trip in terms of distance and length of
stay, and trip purposes including desire for excitement, desire for relaxation, and desire
for a well—planned trip. These differences were then related to respondents’ use of
information sources, including printed media, broadcast media, consultants, and
destination-specific literature. They found that the most frequently reported total trip
planning interval was less than one month (43.4%) followed by one to three months
(28.5%), and over 3 months (28.2%). They also found that the total trip planning interval
was significantly associated positively with the duration of the trip and distance traveled
to the primary destination. A significant level of positive association was found between
the total trip planning interval and whether or not it involved a visit to. friends or relatives.

Perdue (1985), in an inquiry-conversion study in Nebraska, segmented state travel
information inquirers by the timing of the destination decision. The timing of the
destination decision was divided into two categories: decisions made about the

destination before receiving an information packet and after receiving an information

23

packet. He found that the information packet was considered the primary influence on the
destination decision. People who decided on their trip destinations after receiving
information packet about Nebraska were more likely to decide to visit Nebraska than
those who made their destination decisions before receiving the information packet.

Rao et al. (1992) examined American pleasure travelers' trip planning behavior
and the importance attached to a variety of activities, amenities, and locational variables
in considering four foreign destinations (Canada, Mexico, the Caribbean Island, and
Europe). They found that the more the expense and the greater the distance involved, the
longer the total trip planning interval is for US. outbound pleasure travelers.

Fodness and Murray (1997) segmented the leisure tourism market in Florida on
the basis of consumer information search behavior. They examined the usefulness of this
segmentation by contrasting two approaches to segmenting this market: post hoc and a
priori. Two variables were used to segment the Florida leisure tourism market: (1) the
length of time based on the response to the question “How long before your most recent
trip to Florida did you begin making your travel plans?,” and (2) the number of
information sources used. From these two variables, they developed the contingency
table presented as Table 3.

Table 3. Leisure traveler information search model.

 

Number of Sources Considered

 

 

 

 

 

 

 

 

Fewer More
Pre-trip Shorter Routine Search Time-limited Search
Planning Longer Source-limited Search Extended Search
Interval

 

(Adapted from Fodness and Murray, 1997).
They found that the pleasure travelers were more likely to spend more time if the trip was

a vacation, the length of stay increased, they visited more destinations, and their

24

expenditures were higher. The length of the total trip planning interval was negatively

associated with the use of unpaid lodging such as a friend's of relative's home.

RegressiannaIxsis

The term regression was introduced by Francis Galton (1886) in his famous paper
"Family Likeness in Stature." Galton found that, although there was a tendency for tall
parents to have tall children and for short parents to have short children, the average
height of children born of parents of a given height tended to move or regress toward the
average height in the population as a whole. In other words, the height of the children of
unusually tall or unusually short parents tended to move toward the average height of the
population. Galton's law of universal regression was confirmed by his friend Karl
Pearson, who collected more than a thousand records of heights of members of family
groups. He found that the average height of sons of a group of tall fathers was less than
their fathers' height and the average height of sons of a group of short fathers was greater
than their fathers' height thus "regressing" tall and short alike toward the average height
of all men. In the words of Galton, this was "regression to mediocrity."

The modern interpretation of regression is, however, quite different. According to
Gujarati (1988),

Regression analysis is concerned with the study of the dependence of one

variable, the dependent variable, on one or more other variables, the

explanatory variables, with a view to estimating and/or predicating the

(population) mean or average value of the former in s of the known or
fixed (in repeated sampling) values of the latter. i j i

1 Lo

25

Wanda

Closely related, but conceptually very different from regression analysis, is
correlation analysis where the primary objective is to measure the strength or degree of
linear association between two variables. The correlation coefficient measures this
strength of (linear) association (Gujarati, 1988). For example, we may be interested in
finding the correlation (coefficient) between smoking and lung cancer, between scores on
statistics and mathematics examinations, between high school grades and college grades,
and so on. Regression analysis does not provide such measures. Instead, regression
analysis tries to estimate or predict the average value of one variable on the basis of the
fixed values of other variables (Gujarati, 1988).

The two techniques of regression and correlation have some fundamental
differences that are worth mentioning. According to Gujarati (1988),

In regression analysis, there is an asymmetry in the way the dependent and

explanatory variables are treated. The dependent variable is assumed to be

statistical, random, or stochastic, that is, to have a probability distribution.

Explanatory variables, on the other hand, are assumed to have fixed values
(in repeated sampling).2

\

In correlation analysis, on the other hand, any (two) variables are treated
symmetrically; there is no distinction between the dependent and explanatory variables.
After all, the correlation between scores on mathematics and statistics examinations is the
same as that between scores on statistics and mathematics examinations. Moreover, both

variables are assumed to be random. Most of correlation theory is based on the

assumption of randomness of variables, whereas most of the regression theory is

 

2 It is crucial to note that the explanatory variables may be intrinsically stochastic, but for the purpose of
regression analysis it is assumed that their values are fixed in repeated sampling (i.e., X assumes the same
values in various samples), thus rendering them in effect nonrandom or nonstochastic.

26

conditional upon the assumption that the dependent variable is stochastic but the

explanatory variables are fixed or nonstochastic.3

A 1111 '11‘s 1. .1111 1 1‘ -_ '. 12°47 11.11117

.W—l ..

The value of an estimator changes as the sample size it increases. Asymptotic

 

-u-
“U. , "W. p...._ ‘ z "- . ~ __ _”,‘. “.1-.-M

properties are the properties of an estimator that become true only when the sample size

”H”, 11““

) .-. ..
LPV, v! "‘- .
sup-W

is infinitely large. Three criteria are used to evaluate the performance of the estimator
W...
(Greene, 1994).

(1) Consistency: An estimator of a parameter is said to be consistent if

H P—>67

 

What consistency means is the estimation error will gradually reduce to zero as the

pun, ,. 1 "1 --.~v~n- - 1.1

 

w“ . r;""’*"'
“N wwmfifij. «-A M‘.M , u 1h.“ ‘ .H -,-. 1. .\...,.,,—_-..A. 0.1., ‘.Wnuu.- .\ yaw-n0"

sample size increases, so the change in the value of estimator as the sample size increases

‘ (1.“. A!"
F-W :Mm'RI-‘k up-OD’M-H-nwur'. J'w—an ‘4 -r "\ «3“ .a 4' "T‘-

 

is "in the right direction. " In most estimation problems, proving finite sample property

I...
‘4‘.- #1.”. “-r

M.

appears intractable, and consistency has become the minimum requirement for any
estimator.

(2) Asymptotic normality: A consistent estimator of the parameter is said to have an
WW wumm"“““‘m' . , ,.-—.... '

asymptotically normal drstnbutron if

”a “w
h- .0-
-_‘MWVI M

 

3 In advanced treatment of econometrics one can relax the assumption that the explanatory variables are
nonstochastic.

27

 

Jn—(é—a) d—> N(0,Z),
01‘,

.A 1
€~N(€,—Z).
It

Here, Z/n is called the asymptotic variance-covariance matrix of estimator. A consistent
and asymptotically normal estimator is sometimes referred to as a consistently
asymptotically normal estimator. The result of asymptotic normality is always based on
the central limit theorem.

(3) Asymptotic efficiency: An asymptotically normal estimator of a parameter is said to
be asymptotically efficient if its asymptotic variance-covariance matrix is smaller than
that of any other asymptotically normal estimator. A consistent, asymptotically efficient,
and asymptotically normal estimator is sometimes called a best asymptotically normal

estimator.

prmheseflcsts

Tests of hypotheses are not valid, in general, when the error term is not normally

 

,. .‘ ._......' he.“ 'I-‘l-r—V .—
..-.. N‘AH-fl.‘ WM‘ <~.'\1_‘ ‘uw‘u .1-r {Iran—am 4 «~11! “1 1“. F
..

distributed. Indeed, this fact is the crux of the problem. It still possible to estimate
coefficients in a reasonable fashion—the OLS estimator is unbiased, consistent, and
indeed BLUE (Best Linear Unbiased Estimator) (Greene, 1994). However, one cannot
make probability statements about these estimates because the distributions of estimators
and of variance are not known. Of course, if the particular type of nonnormal distribution
of error is known, it may be possible to work out the distribution of estimator and of
variance, and hence to make the usual type of probability statements about the estimates.

Whether or not this can actually be done would naturally depend on the tractability of the

28

particular distribution. In any case, the usual test procedures are asymptotically justified

whether or not the disturbances are normal. The OLS estimator has the same asymptotic

 

 

distribution whether or not the disturbances are normal. The test is only asymptotically

__._.-..-' WMMWMNHWM

 

memm

valid. Thet- test, Chi- square test, and F test are also asymptotically valid (Greene, 1994).
MW

Tobit models refer to regression models in which the range of the dependent
variable is constrained in some way. in economics, such a model was first suggested in a
pioneering work by Tobin (1958). He analyzed household expenditures on durable goods
using a regression model which specifically took account of the fact that the expenditure
(the dependent variable of his regression model) cannot be negative. Tobin called his
model: "the model of limited dependent variables". It and its various generalizations are
known popularly among economists as Tobit models, a phrase coined by Godlberger
(1964), because of similarity to probit models. These models were also known as
censored or truncated regression models. The model was called truncated if the
observations outside a specified range are totally lost and censored if one can at least
observe the exogenous variables.

Censored and truncated regression models have been developed in other
disciplines (notably biometrics and engineering) more or less independently of their
development in econometrics. Biometricians use the model to analyze the survival time
of a patient. Censoring or truncation occurs either if a patient was still alive at the last
observation date or if he or she could not be located. Similarly, engineers used the model

to analyze the time to failure of material or of a machine or a system. These models were

29

called survival models (Kalbfleisch & Prentice 1980; Miller, 1981). Sociologists and
economists have also used survival models to analyze the duration of such phenomena as
unemployment, welfare receipts, employment in a particular job, residing in a particular
region, marriage, and the period of time between births (Bartholomew 973; Flinn &
Heckman 1982; Lancaster 1979; Singer & Spilerman 1976; Tuma, Hannan, &
Groeneveld 1979; Tuma & Robins 1980).

The tobit model has the following structures:
Latent Underlying Regression:
y: zfl'xi +6} £~ N[O,0'2]
Observed Dependent Variable :
if y: s Li , then yi = L. or unobserved (lower tail censoring or truncation)

if y: 2 Li , then yi = Ui or unobserved (upper tail censoring or truncation)

ifLi <yi‘ <Ui,then yi =y: =fl'x, +5}.

In practice, most of the published applications involve censoring rather than truncation.
The thresholds, L1 and U1, may be constants or variables. Censoring in the upper or lower
(or both) tails of the distribution may be accommodated.

Somewhat more elaborate specification is obtained when the range of y* is
censored in both tails (Greene 1995; Rosett & Nelson 1975). This is the two limited
probit model. An application is the model of weekly hours worked developed by
Nakamura and Nakamura (1983), in which less than half time is reported as 20 hours and
more than 40 hours is reported as full time. First they run the model using OLS and, then
apply the double bounded (two limited) probit model. They found statistical evidence of
parameter instability in a conventional empirical model of the labor force behavior of

marn'ed women over the range of variation in annual hours of work.

30

5112' IE 1 L"E'l'

The ultimate purpose of sampling is to select a set of elements from a population
in such a way that descriptions of those elements accurately portray the parameters of the
total population from which the elements are selected (Babbie 1998). A good sample is a
miniature version of the population. The best sample is representative of the population
(Fink 1995a and 1995b). Survey samples are not meaningful in themselves. Their
importance lies in the accuracy with which they represent or mirror the population (Fink
1995b). Sampling methods are usually divided in two ways (Babbie 1990 and 1998; Fink
1995b; Kalton 1983). The first is called probability sampling. Probability sampling
provides a statistical basis for saying that a sample is representative of the study
population. In probability sampling, every element of the population has a known,
nonzero probability of being included in the sample (Babbie 1990 and 1998; Pink 1995b;
Kalton 1983). Probability sampling implies the use of random selection. The reasons for
using random selection are twofold. First, this procedure serves as a check on conscious
or unconscious bias on the part of the researcher. The researcher who selects cases on an
intuitive basis might very well select cases that would support his or her research
expectations or hypotheses. Random selection eliminates this danger. Moreover, random
selection offers access to the body of probability theory, which provides the basis for
estimates of population parameters and estimates of error (Babbie 1990 and 1998; Fink
1995b; Kalton 1983).

The second type of sampling is nonprobability sampling. The weakness of all
nonprobability sampling is its subjectivity, which precludes the development of a

theoretical framework for it. With nonprobability sampling, some members of the eligible

31

population have a chance of being chosen, whereas others do not. By chance, the survey's
findings may not be applicable or generalizable to the population at all (Babbie 1990 and
1998; Pink 1995b; Kalton 1983).

The telephone survey has a rather bad reputation among professional researchers
(Babbie 1998). Telephone surveys are limited by definition to peOple who have
telephones. Years ago this method produced a substantial social class bias by excluding
poor people from the surveys. However, over time, the telephone has become a standard
fixture in almost all US. homes (Babbie 1998). The Federal Communication
Commission (1998) estimates that 93.8 percent of all household had telephone service in
1995 and 1996, so this earlier form of social class bias has been substantially reduced.

Random digit dialing procedures were developed as a reaction to the problems of
under coverage in telephone directories (Babbie 1990 and 1998; Frey 1989; Frey & Oishi
1995). It was necessary to develop a technique that would overcome the problems of
incomplete, inaccurate, and out-of-date directory listings. Random digit dialing designs
not only provide for the inclusion of unlisted numbers, but they also have the additional
advantage of eliminating the need to list sampling elements thereby reducing the time it

takes to implement a random digit dialing survey (Frey 1989; Frey & Oishi 1995).

: -§ . II I l I . w'

Computer-assisted telephone interviewing (CATI) was developed in response to
problems with existing survey methods. Even with the rapid developments that had
occurred in telephone survey research, there continued to be some concern with

controlling the interview process and interviewer-respondent interactions (Shure &

32

Meeker, 1978). In addition, surveying large populations and screening to specialized
subgroups were discouraged because of cost considerations and the burden such tasks
placed on all phases of survey operations (Shanks, Nichols, & Freeman, 1981). Wait
times for data retrieval and reporting using telephone surveys proved to be unacceptable,
particularly to policy makers who need immediate feedback on a potential action (Frey
1989). Paper-and-pencil or manual telephone surveys were proving to be inefficient with
large surveys because they produced an inordinate amount of interviewer error,
particularly when numerous screening or filter questions were used. Pencil-and paper

surveys were also proving to take too long for completion.

33

CHAPTER III

METHODS AND PROCEDURES

In this chapter, the procedures and methods employed in this study are discussed.
The initial sections describe the study population and data collection procedures. The
latter sections explain: how trip planning intervals and dates were defined conceptually,
graphically, and mathematically; the variables used in comparisons of two different types
of decision makers; what independent variables were included in the regression model;

and tests of the regression model's basic assumptions.

W

The findings reported herein were derived from a household telephone survey
funded by Travel Michigan, a state government agency charged with promoting pleasure
travel to Michigan, and various units of Michigan State University. Its fundamental
purpose was to evaluate Travel Michigan’s promotional programs and to measure the
characteristics and behavior of tourists in Michigan’s primary market area.

Data were collected in a computer-assisted telephone interviewing (CATI)
laboratory maintained by the Travel, Tourism, and Recreation Resources Center at
Michigan State University during the three year period January 1996 through December

1998.

34

 

The CATI laboratory has one main server and six stations. The data collection
instrument for the survey was an electronic questionnaire programmed for each
interviewing station using software called StatPac (StatPac, 1995). Each interview was
immediately transmitted electronically to the main server in the laboratory. The
questionnaire that was used is shown in Appendix A. Approximately 160 total questions
focused on : promotion awareness, Michigan trip profile, Michigan image, pleasure trip
profile, Michigan pleasure trip profile, trip origin and destination, advertising influence,
pleasure trip expectations, and socioeconomic profiles.

The questionnaire was designed to profile both the respondent's most recent
pleasure trip (within the past 12 months) in general and the respondent's most recent
pleasure trip to Michigan (within the past 12 months). A flowchart depicting the structure
of the questionnaire is presented in Figure 2. The questions in the "Most Recent Pleasure
Trip Profile Block" profiled the most recent pleasure trip taken by all respondents who
had taken a pleasure trip in the past 12 months. If the destination of this trip was
Michigan, the resulting trip profile was also a profile of the respondent's most recent
pleasure trip in Michigan. If the destination was not Michigan, the respondent was asked
if they had taken a pleasure trip to Michigan at any time during the past 12 months. Those
who answered in the affirmative were routed into the "General Michigan Pleasure Trip
Block." It was possible for a respondent to be asked questions in the "Most Recent
Pleasure Trip Profile Block" and the "General Michigan Pleasure Trip Block", if their
most recent pleasure trip was to a non-Michigan destination but they had also taken a less

recent trip to a Michigan destination in the past 12 months.

35

Have you traveled in the past 12 months? (1)
\L
No Yes
Introduction Block (2-8)
Promotion Awareness and Response Block (9-16)
Michigan Image Block (17-35)
Have you taken a pleasure trip to any destination in the past 12 months? (36)
No Yes
11
How many pleasure trips have you taken? (37)
Attractions Block (38-51)
Most Recent Pleasure Trip Profile Block (52-85)
What was main destination of trip? (86)
Non-MI Ml
Have you taken
a pleasure trip

to M1 in the past
12 months? (87)

 

No Yes
v + 11
Have you ever taken General MI Pleasure trip Profile

 

a pleasure trp in MI? (88) Block (90-124) l

1

No Yes Influence Block (125-135)
1 When was the last time? (89) MI Pleasure Trip History Block (136-139)
MI Travel Expectations Block (140-142)

MI Trip Volume Block (143-148)

 

 

> Personal/Household Characteristics Block (149-163)

Quit

Figure 2. Flow chart for the survey questionnaire.

36

S l' l I. E

The survey employed random digit-dial sampling of household telephone numbers
in the study region purchased from Survey Sampling, Inc. Interviewing occurred on
weekdays from 6 pm. until 10 pm. and on weekend afternoons throughout the year. The
data set included 17,690 completed cases for the three year period January 1996 through

December 1998.

W

The time to complete the survey depended on whether or not the respondent had
taken any kind of trip to any destination in the past twelve months, if the destination of
the most recent pleasure trip taken was Michigan or other states or countries, and if the
respondent had taken a less recent pleasure trip to Michigan within the past twelve
months (See Figure 2). The length of interviews ranged from a few seconds to twenty
minutes, with an average length of twelve minutes. Although the questionnaire contained
164 questions, no respondents were asked all questions due to the branching structure of

the questionnaire (See Figure 2).

I .. IS ..

In September 1995, twenty interviewers were hired and trained to work on the
survey. Interviewers were both undergraduate and graduate students at Michigan State
University. A large majority of the interviewers were women.

On average, about 491 interviews were conducted each month. All interviewers

were trained and supervised by two doctoral graduate students during the study years.

37

Trainees received detailed information about their jobs, the concepts and definitions used
in the survey, and specific interviewing techniques. Each interviewer conducted several
practice interviews as part of their initial training. The work of each interviewer was
monitored by supervisors, and feedback was provided. The supervisors checked each
interviewer's performance. Interviewer turnover was relatively high over the course of the
year, but this was not a data quality concern because only fully trained interviewers were
used and each was monitored.

Interviewing occurred on weekday evenings and weekend aftemoons. Up to three
attempts were made to contact each household in the designated sample. Interviewers
randomly selected respondents within households by asking to speak “to the adult over

17 years old who will have the next birthday”.

W

The response rate, including partially-completed interviews, was 44%. The
response rate, including only fully-completed interviews, was 35%. About 29% of
eligible potential respondents refused the interview. Similar median refusal rates were
computed in reviews of telephone surveys conducted by Groves and Kahn (1979), Steeh
(1981), and Wiseman and McDonald (1979). A test for possible nonresponse bias in the
data revealed few important differences between the characteristics of 173
nonrespondents (other than refusals)4 and a subsample of 173 randomly selected
respondents on 84 variables, including demographic and socioeconomic characteristics.

The only differences between the two groups that were found to be statistically

 

4 It was not possible to test for non-response bias within the refusal population due to the established
human subjects guidelines which protect subjects from undue harassment.

38

significant at the .05 level were: (1) nonrespondents were more likely to have visited a
state or national park on their most recent pleasure trip in Michigan (43% vs. 28%), (2)
nonrespondents, on the average, rated the desirability of Ontario as a pleasure trip
destination on a 10-point scale higher than did respondents (6.7 vs. 5.2), and (3)
nonrespondents, on the average, tended to live in households containing somewhat fewer

persons than did respondents (2.6 vs. 3.1).

S 1 E l . IE .

The survey population consisted of adults, age 18 or older, who permanently
resided in Michigan's primary market area. The primary market area was defined as the
six states of Illinois, Indiana, Michigan, Minnesota, Ohio, and Wisconsin and the
province of Ontario, Canada. A map of the study region is presented in Figure 3. The
primary market or study region generates the vast majority (88%) of Michigan's pleasure

travelers (Kim, 1999).

: 'lLfi" [1'

During interviews the word “trip” was defined as “any overnight or day trip to a
place at least 50 miles from your home, unless it was taken in commuting to work or
school”. A “pleasure trip” was defined as “any overnight or day trip to a place at least 50
miles from your home that was made for your enjoyment, including vacations, weekend

getaways, shopping hips, and trips to visit friends or relatives”.

39

 

Figure 3. Study region.

40

E . [L
I I E I I. l . El I I

This study focused on the most recent pleasure trips taken in the past 12 months
to Michigan prior to the interview. As explained in previous a section, the study
questionnaire was designed to profile both the respondent's most recent pleasure trip
(within the past 12 months) in general and the respondent's most recent pleasure trip in
Michigan (within the past 12 months). Because this study focused on the respondents
who had visited Michigan during their most recent pleasure trips within the past 12
months, those same respondents were selected for this study.

Based on branches of the questionnaire, an SPSS syntax program was prepared to
select respondents who had visited Michigan during their pleasure trip within the past 12

months.

V... E! lEl'v 111

There has been arguments whether or not to include "visiting friends/relative
(VFR)" travel market in a destination's marketing strategy. Kim et a1. (1998) stressed the
importance of VFR market in tourism marketing because this market is a large and
lucrative one. They defined the hard core VFR tourist as those who participated in an
above-average number of other tourist activities on their recent pleasure trips. Then, they
found that the hard core VFR tourists were distinguishable from less active VFR tourists
in terms of trip length, trip expenditures, participation in tourists activities, main
destination of trip, and other behavior patters. The hard core VFR tourists stayed longer

and spent more money during their pleasure trips to Michigan. They concluded that

41

targeting hard core VFR tourists in marketing campaigns is possible, but challenging, and
that on-site marketing to this group through efforts designed to increase length of stay
and encourage repeat visits may be especially important.

While their study found the possibility of targeting the hard core VFR tourists,
this is not a common practice across DMOs. For example, Travel Michigan has declared
that VFR market is excluded from its target markets.

Based on these arguments about the VFR market, including VFR market in this
study could be legitimately questioned. The purpose of this study was to provide
information about trip planning behaviors of Michigan pleasure travelers to Michigan
DMOs, especially Travel Michigan. If Michigan DMOs, including Travel Michigan, do
not target the VFR market, including it in this study may not be appropriate. However, as
reported by Kim et a1 (1998), a considerable portion of VF R tourists spend a considerable
amount of money and time during their Michigan visits. Therefore, two data sets were
used: the data set including VFR market and the data set excluding VFR market. The
same analyses were conducted for both data sets. The analyses included: the duration and
frequency distributions of trip planning intervals, two different decision making
approaches, and frequency distributions for study relevant dates. Separate regression
analyses were not performed because the VFR market was included as an independent
variable in the regression model fitted to the full data set.

The results from analyses of the data without the VFR market were almost
identical to those from analyses of the full data set with VF R market included. Therefore,
either data set could have been selected as the basis for this study. It was decided to

present results for both the full data set with VFR included and for the partial data set

42

with VFR excluded. However, the tables related to the latter are reported in (Appendix B)

without accompanying discussion in the interest of brevity.

Data were weighted to correct for uneven participation across state and provincial
boundaries of the study region such that the resulting weighted sample conformed to the
distribution of households in the six states and Ontario, Canada. Data were also weighted
by month to correct for minor variations in the number interviews completed each month
of the study period. The 1997 Survey of Buying Power (Sales & Marketing Management,
1997) was used to weight the sample distribution of households to the actual population
distribution of households in the study region. The year 1997 was selected because this

year is the middle year of the survey periods (from 1996 through 1998).

S 1 E l v I. E
T' E . : . .

Three study relevant time frames were collected via the study questionnaire.
Respondents were asked to provide the following information: (1) how far in advance of
their trip departure they began to make plans for the trips (the total trip planning interval
in the terminology adopted in this study); (2) how far in advance of their trip departure
they made a final decision about the trip destination (the post decision interval in
terminology adopted in this study); and (3) the date that the pleasure trip began (the date
the trip began in terminology adopted in this study). These time frames are listed in Table

4 along with related supplemental information.

43

Table 4. Definitions and descriptions of the time frames of the travel decision making
process from the studyquestionnaire.

 

 

 

 

 

 

 

 

 

 

Type of Level of
Term Operational Definitions Questions Measurement
Total trip planning About how far in advance of this Open- Ratio
interval trip did you begin to make plans for ended
it?
Post decision interval About how far in advance of this Open- Ratio
trip did you make a final decision ended
about where to go?
Date trip began Approximately when did trip begin Open- Ordinal
— the month and day? ended
D' 11) 1.0 ("V-.1 .11‘ 111‘ 10‘. in 1‘ u'-.111.°-.10|‘ ”on
' r v r

The following figure (Figure 4) was adapted from the comprehensive model of
the travel decision making process (Figure 1). As seen in this figure, there are three
different intervals and three different dates. The three different dates are when: (l) the

trip planning began, (2) the trip destination was selected, and (3) the trip began.

Total trip planning interval

 

 

 

 

 

 

4
Information processing Interval Post Decision Interval
4 >|< >
I
The Date Trip The Date Trip The Date The
Planning Began Destination was Trip Began
Selected

Figure 4. Trip planning and decision making process phases and time frames.

This figure also shows how the study relevant time frames defined in Chapter I are
related to the trip planning and decision making process phases faced by pleasure
travelers. From the beginning of awareness through the date the trip began, corresponding

dates and intervals are defined graphically. Recall that the total planning interval is the

44

length of time between the date trip planning begins and the date the trip begins; the post
decision interval is the length of time between the date the trip destination is selected and
the date the trip begins; the information processing interval is the length of time between
the date the trip planning begins and the date the trip destination is selected.

.1-1,1..'._ .. - H . 11: .11: . 7.- rV‘ .. 'o1u.. 1: . ..

Three study relevant time frames were collected from respondents: the total trip
planning and the post decision intervals and the date the trip began. The other three study
relevant time frames were not provided by respondents: the information processing
interval, the date trip planning began, and the date trip destination was selected.
However, it is simple to calculate these time frames from the information that was
collected.

The total trip planning interval can be expressed as:

TPI, =DTB,--DPB,~ (l)

The post decision interval was the length of time between the date the trip destination is
selected and the date the trip begins. Therefore, the post decision interval is expressed as:
PD],- = DTB; - DDS,- (2)

,where T P1,- = total trip planning interval for individual i;

DTB; = the date the trip begins for individual i;

DPB; = the date the trip planning begins for individual i;

PDI, = the post decision interval for individual i;

DDS,- = the date the trip destination is selected for individual i.

45

The operational definition of the information processing interval is the length of
time between the date trip planning begins and the date the trip destination is selected.
Thus, the information processing interval for individual i may be expressed as
1P1,- = DPB; - DDS,- (3)

Because the date the trip planning begins (DPBi) and date the trip destination is selected
(DDSi) were not known from the survey data, this equation may be modified by adding
and subtracting the same term (the date the trip began, DTBi ) so that,

[P], = DPB; - DDS,- = (DPB, - DTBJ - (DDS,- - DTBJ (4)
From the equations for total and post decision intervals,

TPI; =DTB,--DPB,~ (1)

PD], = DTB; - DDS,- (2)

the information processing interval for individual i can be expressed by two terms, T P],-
and PDI,, which are known from the survey data, as

[P],- = DPB. - DDS,- = (DPB; - DTBJ - (DDS,- - DTBJ= T PI,-- PDI,- (5)
Consequently, the information processing interval of individual i is equivalent
mathematically to the length of time between the length of time between the total trip
planning and post decision intervals of individual i which are known values from the
survey.

The next variable to be calculated in this equation is the date trip planning begins
(DPBi). Figure 4, trip planning and decision making process phases and time frames,
shows that the date trip planning begins for individual i is the date backward from the
date the trip begins by the total trip planning interval. It can be defined and calculated by

the following mathematical expression.

46

DPB; = DTB; - TPI, (6)
,which is the difference between the date the trip begins and the total trip planning
interval. Because the date the trip begins (DTBi) and the total trip planning interval (T P1,)
are known from the survey, the date trip planning begins (DPBi) can be calculated using
this equation.

Finally, the date trip destination is selected (DDSi) can be calculated from
equation (2). From equation (2),
DDS; = DPB; - PD], (7)
,which is the difference between the date the trip planning begins and the post decision
interval. Because the date trip planning begins (DPBJ is known from equation (6) and the
post decision interval (PDI,-) is known from the survey. the date trip destination is

selected (DDSi) can be calculated from this mathematical expression.

I] E I . El . B

As described in the introduction, the objective of most tourism promotion is to
persuade potential pleasure travelers to purchase trips to a destination or other travle
related services and such promotion should reach potential pleasure travelers at the time
they begin to make plans for trips. The premise underlying this study is that when asked:
"when did you begin to make plans for this trip" respondents focused when "purchase
behavior" began rather than when "awareness raising" began.

However, this premise may be challenged and confound interpretation of results if
respondents perceive this question differently. Chubb and Chubb (1980) suggested in

their decision making model that when they become aware of the need of trips, pleasure

47

travelers may react in two alternative ways: (1) react immediately to their awareness of
the need of trip, (2) postpone their decision for longtime unless indefinitely or react
negatively to the awareness. Of these, the second reaction group may report very long
total trip planning intervals.

Only two cases of total trip planning intervals of longer than 365 days were found
out of the 2,300 respondents who had visited Michigan during the past 12 months. This
small number of cases suggests that the vast majority of respondents interpreted when
trip planning began as assumed throughput this report that being: not when they were first
made aware of Michigan as a travel destination but rather when they entered the

"purchase behavior" mode.

W

The information processing interval was calculated by subtracting the post
decision interval from the total trip planning interval. Because of this, only cases which
included both the total trip planning and post decision intervals were analyzed in this
study. A total 1478 cases were found to meet the screening criteria established to be
subjected to further analyses. Of these, two additional cases were eliminatedbecause they
- contained extreme values (730 days and 1825 days) of questionable reliability.

There are several other reasons why these extreme values were excluded. First,
most promotion campaigns schedule are prepared yearly. Often, they are prepared for
seasons, months, or even days. Therefore, pleasure travelers whose total trip planning
intervals were over one year would not appropriate targets for these travel marketers.

Second, as explained in the previous section, these two extreme cases are the reaction (or

48

awareness) group who postpone their decision whether to take a trip or not for longtime.
During their initial awareness phase, their interest and desire to know about alternative
trip destinations or services is very low. Therefore, promotion campaign during this phase
would not be effective because they would not react (i.e., make a purchase decision) to
any promotion campaign at that time. Since the purpose of this study is to provide useful
information about trip planning behavior of pleasure travelers to destination marketers so
that they can prepare more effective and efficient promotion message distribution
schedules, these two cases were excluded from the data set for this study. Two hundred
additional cases were eliminated because the third required datum, the date trip began,
was missing. Thus, when all screening criteria had been applied, a total of 1266 valid
cases remained for further analyses.

Finally, it is important to note that the somewhat elaborate process involved in
screening out invalid cases was deemed important to developing a high quality data set
for further analyses. The multiple step pairing procedure employed insures that only
cases that included all study relevant data were included thereby eliminating missing

cases as a possible source of bias in the final results.

Analysesotlflata

This section explains how the data set prepared was analyzed to fulfill the study
objectives. Discussion is presented in the order that objectives are listed on p. 7.
Definitions of variables, steps in the analyses, relevant statistics, and computer programs

used in analyses of data are presented in each section.

49

1“” 1., 1:1 .- "L H , ._. '1“ .111'1: 1 0.. 'v

The duration of the three planning intervals underlying the trip planning and
decision making process were studied. Valid cases, minimum and maximum values,
ranges, mean, median, standard deviation of these intervals are included as statistical
descriptors. SPSS for Windows version 8.0 (Norusis and SPSS, Inc., 1998) was used to
develop reported statistics.

The frequency distributions for these intervals were investigated across different
time bases. First, the frequencies of the time frames are presented based on individual
planning days such as 0 day, 1 days, 2 days, 365 days. While the distributions of the
time frames based on individual days provide detailed frequencies of pleasure travelers'
planning and decision intervals, such frequency distributions are too complicated to
identify the more general trip planning behaviors of pleasure travelers. Therefore, day
specific data were grouped into longer time intervals. Individual days were grouped into
six time intervals: less than one week, 8-15 days, 16-30 days, 31-60 days, 61-90 days,
and over 90 days. These groups were consistent with previous studies based upon this
data set (Yoon, Spencer, Holecek & Kim, 1998; Holecek, Yoon & Spencer, 1997; Yoon,
Holecek, Spencer & William, 1999). The relevant frequencies are presented for each

grouping of data for each of three previously defined trip planning and decision making

intervals.

As stated in the discussion of the objectives section, the information processing

interval has implications for tourism marketing. Recall that the information processing

50

interval is the length of time between the date the trip planning begins and the date the
trip destination is selected. The total number of cases were divided into two groups
identified as: instant and hesitant decision makers.

Cases with a reported zero information processing interval were placed into the
instant decision maker group while all others were placed into the hesitant decision
maker group. No alternative classification scheme was considered to be viable in this
case because 85% of the data set consisted of a zero information processing interval.

These two groups of decision makers were profiled and compared in terms of
information sources used and media habits, trip related variables, and socioeconomic
variables. The relevant variables for these categories are listed and defined in Tables 5 to
7. Each row contains the definition of a variable, level of measurement, descriptive

technique used to analyze the variable and resulting statistics.

51

Table 5. Sources of information and media habits of Michigan pleasure travelers.

 

 

Level of Test

Variable Measurement Data analysis Statistics
Media Considered Most Helpful When Frequency/
Selecting Tourist Destinations Nominal Percentage Chi-square
Have Access to the Internet Nominal Frequency/ Chi-square

Percentage
Have Used the Internet to Obtain Travel Nominal Frequency/ Chi-square
Information Percentage
Have Used Michigan Travel Bureau's Web Site Nominal Frequency/ Chi-square
to Obtain Travel Information Percentage
Have Called Any State or Province's Toll-Free Nominal F requency/ Chi-square
Number to Request Travel Information Percentage

 

Table 6. Demographic and socioeconomic characteristics of Michigan pleasure travelers.

 

 

Variable Level of Measurement Data analysis Statistics

Permanent residency Nominal Frequency/ C hi-square
Percentage

Composition of household Nominal Frequency/ Chi-square
Percentage

Household size Ratio Mean/ Median t-test

Number of full-time wage earners Ratio Mean/ Median t-test

Employment situation Nominal Frequency/ «-
Percentage

Household income Ordinal Frequency/ C hi-square
Percentage

 

52

Table 7. Travel behavior of Michigan pleasure travelers.

 

 

Level of Test
Variable Measurement Data analysis Statistic
Month When Trip Began Nominal Frequency/ Chi-square
Percentage
Primary Purpose of Trip Nominal F requency/ C hi-square
Percentage
Activities Participated In:
General touring or driving for pleasure Nominal Frequency/ C hi-square
Percentage
Shopping Nominal Frequency/ Chi-square
Percentage
Outdoor recreation Nominal F requency/ C hi-square
Percentage
Explore small city or town Nominal Frequency/ Chi-square
Percentage
Visit other attraction Nominal Frequency/ C hi-square
Percentage
Dine at unique restaurant Nominal F requency/ Chi-square
Percentage
Nightlife Nominal Frequency/ Chi-square
Percentage
Visit an historic site Nominal Frequency/ Chi-square
Percentage
Visit state or national park Nominal F requency/ Chi-square
Percentage
Visit museum or hall of fame Nominal Frequency/ C hi-square
Percentage
Casino gaming Nominal F requency/ Chi-square
Percentage
Fall color touring Nominal Frequency/ Chi-square
Percentage
Main Type(s) of Lodging Used Nominal Frequency/ Chi-square
Percentage
Mode(s) of Transportation Used Nominal Frequency/ ---
Percentage
Travel Party:
Average party size Ratio Mean/ Median t-test
Average aggregate age of all persons in Ratio Mean/ Median t-test
Party
No. Places Where Spent Night Ratio Mean/ Median t-test

 

53

Table 7. Travel behavior of Michigan pleasure travelers, continued.

 

 

Level of Test
Variable Measurement Data analysis Statistic
Main Destination Region in Michigan Nominal Frequency/ C hi-square
Percentage
No. Pleasure Trips Taken to Places in Michigan Ratio Mean/ Median t-test
Type of Trip:
Overnight trip Nominal Frequency/ C hi-square
Percentage
Vacation trip Nominal Frequency/ C hi-square
Percentage
Family trip Nominal Frequency/ Chi-square
Percentage
Arranged by travel agent Nominal Frequency/ C hi-square
Percentage
Package tour with lodging Nominal Frequency/ Chi-square
Percentage
Trip Duration (Avg):
Number of nights spent in Michigan Ratio Mean/ t-test
Median
Estimated Total Trip Expenditures in Ratio Mean/ t-test
Michigan Median

 

54

Van-.1 ‘ 1.. 1371 ‘ 1‘D_ 1111 1' 1 . 11 «111°,1'ag 01- 'v

This study employed multiple regression analysis to investigate the relationship
between the dependent variable, the total trip planning interval, and independent
variables, including selected socioeconomic characteristics, traveling party composition,
trip characteristics, trip behavior, and trip related expenditures.

Regression analysis is primarily used for two purposes: (I) for estimating
coefficients of interest and testing hypotheses about them (2) and for forecasting (Greene,
1994). Multiple regression analysis in this case was used to estimate the coefficients of
independent variables which, if any, impact the length of the total trip planning interval.
The Model

The basic model used is:

Y=Xfl+£ (8)

where Y = le column vector of observations on the dependent variable, the total trip
planning interval, X = ka matrix giving N observations on k-l variables X; to Xi, the
first column of Is representing the intercept term, B = kxl column vector of the unknown

parameters ,6], fl», ,6}, a = le column vector of N disturbances .5;-

Defining Independent Variables
Independent variables were selected based on previous studies (Gitelson &

Crompton, 1983; Roehl & Fesenmaier, 1992). Gitelson and Crompton (1983) examined

 

5 From preliminary analysis, it was found that almost 85% of respondents who answered planning interval
questions decided the trip destination as they began to plan trip. This preliminary result implies that total
and post decision intervals of almost 85% of respondents are the same.

55

differences in pleasure travelers' planning intervals and related them to the purpose of the
trip (if they were visiting friends or relatives), trip distances, and trip duration.

The work of Roehl and Fesenmaier (1992) represents a preliminary step in
understanding the relationship between risk attitudes and trip behavior. They included
several independent variables including: trip duration, number of previous visits, party
size, trips with children, visit friends or relatives as the trip purpose, accommodations at
the home of friends or relatives, information acquired from travel agents, benefits sought,
and household description (the presence of children 6 years of age or younger in the
household). Based on these studies, the variables described in Table 8 were selected as
independent variables for the regression analysis.

Internet use behavior is a recent but growing matter of interest in tourism
marketing circles. The number of Internet users in Michigan is increasing rapidly year
after year (TTRRC, 1997). Reasons for this increasing trend of Internet use in tourism
include: (1) 24 hour access to information, (2) near instant response, and (3) low cost of
access. Since so little is currently known about Internet use in tourism, it is quite
attractive to include Internet use behavior variables in the regression model. It is expected
that those who use the Internet will have a relatively short average total trip planning
interval. However, the questions related to Internet use behavior were included in the
study questionnaire only since September, 1997, which only covered half of the survey
period. Therefore, instead of including these variables in the regression model, the
significance of these variables in explaining the variation in the dependent variable was

tested using the independent sample t-test and one way ANOVA.

56

Table 8. Descriptions of independent variables.

 

 

Variable Type of Description
Variable

Ititz
PEAKSEAS Dummy 0 for non-peak season, I for peak season trip
PUR_VFR Dummy 0 for other purposes, 1 for visiting friends and relatives
PARTYSIZ Continuous Average party size
ACT_GEN Dummy 0 for other activities, 1 for general touring or driving for pleasure
ACT_SHOP Dummy 0 for other activities, 1 for shopping
ACT_OR Dummy 0 for other activities, 1 for outdoor recreation
AC T_OTH Dummy 0 for other activities, I for visiting other attraction
ACT_NITE Dummy 0 for other activities, I for nightlife
ACT_HIST Dummy 0 for other activities, 1 for visiting an historic site
ACT_PARK Dummy 0 for other activities, 1 for visiting state/national park
ACT_MUSE Dummy 0 for other activities, I for visiting museum/hall of fame
ACT _CASI Dummy 0 for other activities, 1 for casino gaming
ACT_EVNT Dummy 0 for other activities, 1 for attending a festival or event
ACT_FALL Dummy 0 for other activities, 1 for fall color touring
LOG_FRH Dummy 0 for other type of lodging, 1 for friend's/relative's home
NOPTMI Continuous Number of pleasure trips taken to places in MI
TRP_FAM Dummy 0 for other trip, 1 for family trip
TRP_OVER Dummy 0 for day trip, 1 for overnight trip
TRP_VACA Dummy 0 for other trip, I for vacation trip
DURATION Continuous Number of nights spent in MI
EXPENDIT Continuous Estimated total trip expenditures in MI

. .

W! r . .
MIRESIDE Dummy 0 for other states/province residence, 1 for MI residence
MEDINCOM Dummy 0 for below median income, 1 for above median income
HHS_PRE Dummy 0 for household not contained preschool child(ren), l for household

contained preschool child(ren)

HHS_SCH Dummy 0 for household not contained school age child(ren),

l for household contained school age child(ren)

 

57

Regression Estimates

The multiple regression model was used to test the hypothesis that selected
socioeconomic characteristics, trip party, characteristics, and behavior, and expenditure
variables are not different from zero in explaining the duration of the total trip planning
interval. The OLS regression model was employed to test this hypothesis. Coefficients,
standard errors, t-statistics, p-values and means of the independent variables are reported
to test this hypothesis. Standardized or beta coefficients were also reported to compare
the relative impact of the independent variables on the duration of the total trip planning
interval.

Regression coefficients provide the estimate for the parameter associated with
each independent variable. The t-statistic, which is each coefficient divided by its
associated standard error, serves as a statistical test of whether a coefficients is
significantly different from zero (significance in the statistical sense, not in a managerial
importance sense). The larger the value of the t-statistic, the more statistically significant .
is the associated estimated coefficient. Generally, a t-test greater than 2 indicates
significance. Standardized coefficients may be used to facilitate comparisons between
regression coefficients (Neter & Wasserman, 1974). The comparisons of the standardized

coefficients provide the ranks of significance level of impact of independent variables on

{W "1

”\ (.. f... _/

I

"Accra-«fl W”*"““-‘v~--mm.m "

the dependent variable (Neter & Wasserman, 1974). \2 8\ O G"

‘51-‘- ~.n a... -‘-""

Ideal Conditions of Least Square Regression and Tests
Basically, the OLS regression model can be used if the dependent variable

distributes normally and is continuous (Allen, 1997). However, the ideal conditions for

vv
5

.-
, . .‘.~ ., 'K . ' fi‘l'
. .,_-' ... l . u‘ ‘ g , .
. 1., 'l o, ._ . .1
‘- A .. 4’. '..’¢ -.,

58

. -.’—
>~.r---‘ WM“\ .--..
-. .

the multiple regression model include two additional conditions: (1) constant variance, or m

 

homgsséastisityiand (2) Eeltissrl'insaiwraisingulariv (Greene, 1994).

These conditions are tested to prove whether or not the model is estimated under
ideal conditions. The Kolmogorov-Smimov (K-S) test is used to test the normality of the
error terms by analyzing the residuals. K-S compares the cumulative distribution function
for a variable with a specified distribution, which may be uniform, normal, or Poisson.
The K-S Z is computed from the largest difference (in absolute value) between the

observed and theoretical distribution functions (Neter & Wasserman, 1974). Higher

 

values from the K- S test mean a higher chance to reject the null hypothesis that the

.. .IWM N .w_ “mm cur-AM m .rJn-‘A-v-H “ ‘ “ "H H" . .nn-u' "

distribution is not normal distribution. The histogram of standardized residuals is also

.W ”.5 MM

‘ .. nun-M J--~w4,\ . . . ,
— («*w-l. ’1 W “'4‘“ -- 3.1.4 erln. _. .. ‘1"; «¢.- aw» »--‘- ..

‘-4hl(.-..-ln :0- >1-

 

 

 

 

typically presented to provide a visual check concerning the distribution of error terms.
Multicollinearity occurs when two variables in a matrix are perfectly, or nearly

perfectly, correlated and when they show a similar pattern of correlation with the other

variables. Singularity occurs when one score is a linear combination of others. Detection

of these conditions is often with the use of tolerance measures. Tolerance is a statistic

used to determine how closely the independent variables are linearly related to one

another (multicollinear). Although multicollinearity and singularity are different, they
cause similar problems in multivariate analyzes, specifically by prohibiting or rendering
an unstable matrix inversion (Tabachnick & Fidell, 1983). Multicollinearity and
singularity issues in this study were evaluated by the tolerance values calculated during
the regression analysis. These values are also a measure of independence among the

variables.

59

Double Censored Distribution of the Dependent Variables

The multiple regression model defined above was estimated by the ordinary least
square (OLS) regression method because the dependent variable is continuous and
assumed to be normally distributed and to satisfy the ideal conditions listed previously.
However, closer investigation of the distribution of the dependent variable revealed a
possible question in using the OLS: the data are censored by two bounds—0 and 365.

Although the normality of the dependent variable may be confirmed by the K-S
test, employing OLS regression for this doubly censored dependent variable should be
tested. A commonly used econometric technique that deals with the censored problem is
the tobit model.

The tobit model assumes that the dependent variable is censored at some lower or
upper level or both. The total trip planning interval was doubly censored at the lower and
upper levels. Hence, a double bounded (censored) tobit model would fit for the
distribution of the dependent variable of this study which was doubly censored. The
double bounded tobit regression model as an alternative regression model was employed
to test the robustness of the OLS model used in this study. The coefficients and the
significance level for each model were compared to test the robustness of the model.

SPSS version 8.0 was used to run the OLS regression. LIMDEP version 7.0
(Econometric Software, Inc., 1995) was used to run the double bounded tobit regression
model on the limited dependent variable. The LIMDEP program was developed to use for

limited dependent variables such as logit, probit, or tobit distributions.

60

['1' ElEl'l;

The planning and decision making dates were presented based on three time
segments: (1) three parts of a month—early (the first day of the month through 10'"), mid
(11th to 20'"), and the end of a month (21St to the end of month), (2) month, and (3)
season. The reason to present the frequency distributions for the dates based on these
three different time segments was to provide appropriate information to the marketers
who develop promotion program distribution schedules by seasons, months, or more
detailed time intervals.

The distributions of these study relevant dates were tested by using the one-
sample chi-square test. Chi-square tabulates a variable into categories and computes a
chi-square statistic based on the difference between observed and expected frequencies

(SPSS Inc., 1986). By default, the chi-square test assumes equal expected frequencies.

61

CHAPTER VI

RESULTS AND DISCUSSION

The following four objectives for this study were presented in Chapter 1:

Objective 1. To investigate the duration and frequency distribution of the three trip
planning intervals.

Objective 2. To investigate two different decision making approaches underlying the
trip planning and decision making process.

Objective 3. To investigate variables that influence the duration of the total trip
planning interval.

Objective 4. To investigate the distribution of the three study relevant dates defined
previously.

In this chapter, results based upon the research methods outlined in the previous chapter
will be presented and discussed in order from Objective 1 to Objective 4. The final
section includes the results with and without visiting friends and relatives (VFR)
included.

I. 1'1...” .. 1 . u. '11 . 1- I1.“ 11 , .1119 .1- 1.0-“

The various planning intervals in the travel decision making process were defined
in the previous chapter and included the: total trip planning, post decision, and
information processing intervals. They were defined conceptually, operationally, and
mathematically. Recall that the total trip planning interval is the length of time between
when trip planning begins through when the trip begins; the post decision interval is the

length of time from when a final decision on trip destination is made through when the

62

trip begins; and the information processing interval is the length of time between when
trip planning begins through when a final decision on trip destination is made.

Table 9. Summary of statistics for the three planning intervals.

 

Total trip Post Information
planning decision processing
interval interval interval

(n=1476) (n=l476) (n=1476)

 

Minimum 0.0 0.0 0.0
Maximum 365 365 363
Range 3656 365 363
Mean 70.1 63.3 6.9
Median 30.0 30.0 0.0
Standard
deviation 104.4 100.3 31.1

 

Table 9 above contains the statistical descriptions of these planning intervals.
Note that they vary considerably across Michigan pleasure travelers. Travelers begin to
plan and make final decisions on trip destinations from 0 day to one year prior to when
their trips begin. They make final decisions on trip destinations from 0 day to 363 days
after the beginning of trip planning. Trip planning is, like pleasure travel, a year round
activity.

The mean values of the planning intervals are presented in Table 9. Michigan
pleasure travelers, on average, begin to plan about 70 days and make final decisions on
trip destinations about 63 days prior to travelling. They decide on trip destinations, on

average, only 7 days after the beginning of trip planning.

 

° Two extreme values were found, 730 and 1825, for both the total trip planning and the post decision
intervals. These two responses exceeding far over 365 days were deleted from the data set to mitigate
outlier problems in further analyses of this study.

63

The first hypothesis presented in Chapter I is:
Hypothesis 1. The planning intervals underlying the trip planning and decision making
process are the same across pleasure travelers.
The standard deviation gives an indication of how closely or widely the individual
independent variable values spread around the mean value (Gujarati 1988). Theoretically,
the standard deviation is zero for a constant which has no variation. Analysis of
information collected from respondents reveals that the standard deviation is high across
the variables relevant to this study. Clearly, trip planning and destination selection

behavior vary widely across this set of respondents. Therefore, this hypothesis is rejected.

D' 11". '11 . ’_ . ._ '.. H r .7.“ a“ 1,.11111'11' ._ '1-1-11.

The intention of this section is to answer three questions about the planning or
decision making process of pleasure travelers: (1) how far in advance do Michigan
pleasure travelers begin to plan trips (e.g., length of the total trip planning interval), (2)
how far in advance do Michigan pleasure travelers make final trip destination decisions
(e.g., length of the post decision interval), and (3) how far in advance do Michigan
pleasure travelers select the trip destinations from the beginning of trip planning (e.g.,

length of the information processing interval)?

Distribution of Total Trip Planning and Post Decision Intervals
The frequency distributions for the total trip planning and post decision intervals of
Michigan pleasure travelers are presented in Tables 10 and 11. The total trip planning

interval ranges from less than 24 hours to one year prior to the date the trip begins (Table

64

10). The most frequently reported total trip planning interval is one month (17.6%)
followed by one week (13.9%), two weeks (12.2%), two months (10.4%), one year
(8.8%), and three months (5.6%). Almost 29% of Michigan pleasure travelers begin to
plan within one week of taking their trips, and 64% begin to plan 30 days or less in
advance of their trips.

The frequency distribution of the post decision interval is very similar to that
observed for the total trip planning interval. The most frequently reported length of post
decision interval is also one month (16.7%) followed by one week (14.3%), two weeks
(11.8%), two months (9.0%), one year (7.7%), and one day (7.3%) (See Table 11).
Michigan pleasure travelers are likely to make final decisions on trip destinations quite
close to the date when trips begin. Almost 34% of them make final decisions on trip
destinations within one week, and almost 68% of them do so within one month.

The distributions of total trip planning and post decision intervals are plotted in
Figure 5 and 6 respectively. These plots have many similarities. Several intervals have
exceptionally frequencies. These intervals are: within one week, two weeks, one month,

two months, three months, six months, and one year.

65

Table 10. Frequency distribution for the total trip
planning interval.

 

 

Length of Percent of Cumulative
planning interval respondents percent
(Days) (n=1476) (n= 1476)
less than 24 hours 2.7 2.7
l 5.1 7.8
2 4.2 12.0
3 2.1 14.1
4 0.5 14.6
5 0.4 15.0
7 13.9 28.9
10 0.1 29.0
11 0.1 29.1
14 12.2 41.3
18 0.1 41.4
21 4.4 45.8
28 0.1 45.9
30 17.6 63.5
35 0.1 63.6
42 1.3 64.9
45 0.2 65.1
56 0.1 65.2
60 10.4 75.6
70 0.2 75.8
75 0.0 75.8
90 5.6 81.4
120 3.0 84.4
150 0.9 85.3
180 4.8 90.1
210 0.2 90.3
240 0.3 90.6
270 0.4 91.0
300 0.1 91.1
360 0.1 91.2
364 0.1 91.3
365 8.8 100.0
Total 100.0

 

66

Table 11. Frequency distribution for the post
decision interval.

 

 

Length of post Percent of Cumulative
decision interval respondents percent
(Days) (n= 1 476) (n=1476)
less than 24 hours 3.6 3.6
1 7.3 10.9
2 5.1 16.0
3 2.5 18.5
4 0.6 19.1
5 0.5 19.6
7 14.3 33.9
10 0.2 34.1
11 0.1 34.2
14 l 1.8 46.0
18 0.1 46.1
21 4.4 50.5
28 0.3 50.8
30 16.7 67.5
35 0.1 67.6
42 1.1 68.7
45 0.2 68.9
56 0.1 69.0
60 9.0 78.0
70 0.2 78.2
90 4.9 83.1
120 2.8 85.9
150 0.8 86.7
180 4.4 91.1
210 0.3 91.4
240 0.3 91.7
270 0.3 92.0
300 0.2 92.2
360 0.1 92.3
364 0.1 92.4
365 7.7 100.0
Total 100.0

 

67

 

20.0

 

 

 

 

 

 

 

 

 

 

15.0
0
DD
5
5 10.0
8
D
O-
5.0
00 L- .7 . J; - 1 l l 1 l 4

 

a:zassezagsasasssaéaisass§2§§§§
E
F: Days

Figure 5. Frequency distribution of reported number of days in the total trip planning
interval.

68

 

 

 

 

 

 

 

 

 

 

 

 

20.0
15.0
Q)
:0
€13
H
C
010.0
9
$—
6'.)
a.
5.0
00 A IlAl I I l l l A A
ecaaasaasaaazssaaasasaasaszas§a
: ————————NNNNNNNNmn—.nn m
2
‘7
Pl
7: Days
3
m
.2

Figure 6. Frequency distribution for reported number of days in the post decision interval.

69

The peaking displayed in Figures 5 and 6 might be taken to suggest that travel
planning behavior is an erratic rather than even flowing process, but it is probably more
reasonable to assume that the observed patterns have more to do with how respondents
benchmark time intervals. For example, a few days is perceived as one week; a little
longer than one week is seen as two weeks; a few weeks is seen as one month; etc. Thus,
rather than focus on the specific reported peaks in these frequency distributions, it is
probably more meaningful to consider the peaks as defining broader time intervals such
as: 0-7 days, 8-15 days, 16-30 days, 31-60 days, 61-90 days, and over 90 days.

Frequencies of responses reported for each of these broader time intervals are
presented in Table 12 and Figure 7 for both the total trip planning and the post decision
intervals. The most popular total trip planning and post decision intervals are: 0-7 days
(28.9% and 33.9%) followed by 16-30 days (22.2% and 21.5%), over 90 days (18.7% and
16.9%). Once again, both the length and frequency of these total trip planning and post
decision intervals are nearly identical. In other words, Michigan pleasure travelers are
very likely to make final decisions on trip destinations at the beginning of trip planning
and devote very little time to collecting additional information. This result is supported
by the findings of Schmoll (1977). He concluded from his analysis that the choice of a
destination occurs fairly early in the planning process and frequently is made during the
information gathering and deliberation phase. In other words, most travelers already have
a destination firmly in mind when first consulting a travel agent or other intermediary.
The brevity of the information processing interval (on the average, 6.9 days) was reported
earlier. Its distribution, presented in the next section, will provide further insights into this

aspect of trip planning behavior.

70

Table 12. Reported frequencies by selected time
intervals for the total trip planning and post
decision intervals.

 

 

 

 

 

 

 

 

 

 

 

 

Time interval Total trip planning Post decision
(Days) interval interval
(n=1476) (n=1476)
0-7 28.9% 33.9%
8-15 12.4% 12.1%
16-30 22.2% 21.5%
31-60 12.0% 10.6%
61-90 5.9% 5.0%
Over 90 18.7% 16.9%
40% "
33.9%1
35% r
23.9%
30% r
25% ' 22.2%
a) 21.5%
N
E 20% ‘
'2’
E ‘5‘" I 12.4% 12.1% 12.0%
‘ 10.6%
10%
5.9%
5% ‘
0% 1
0-7 8-15 16-30 31-60 61-90
Days

5 .0%

 

18.7%

16.9%

 

91+

 

1

[:1 Total Trip Planning Interval

.Post Decision Interval

1

Figure 7. Comparisons between frequencies of reported total trip and post decision
intervals for six selected time frames.

71

Frequency Distribution of the Information Processing Interval

As noted earlier in Table 9, the mean information processing interval for
Michigan pleasure travelers is only 6.9 days. However, the mean in this instance is
somewhat misleading as the vast majority of respondents reported spending no time at all
on this stage of trip planning. Almost 85% of respondents answered that they made final
decisions on their trip destinations at the same time as they began to plan their trips, as
can be seen from the frequency distribution provided in Table 13. The rest of them
(almost 15% of respondents) reported information processing intervals from 1 to 363
day(s).

A possible explanation for this short information processing interval with a
strongly skewed distribution toward zero could be perceived risks. According to Roehl
and F esenmaier (1992), when individuals plan to visit a destination, the perceived risks to
them are low if they have previous experience with the destination. Also, pleasure
travelers with low perceived risks may not heavily use sources of travel information. The
portion of first time visitors among the respondents was only about 9%. Thus, this data
set id dominated by represents who are Michigan residents or who have visited the state
on at least one pervious occasion. It is reasonable to assume that the majority perceive
minimal risk in travel in Michigan, hence they do not feel the need to engage in an

extended information processing intervals.

72

Table 13. Frequency distribution for the information processing interval.

 

 

 

 

 

Length of Percent of Cumulative Length of Percent of Cumulative
information respondents percent information respondents percent
processing processing

interval (Days) (n=1476) (n=1476) interval (Days) (n=1476) (n=1476)

0 85.1 85.1 65 0.1 97.7
1 0.5 85.6 69 0.2 97.9
2 0.7 86.3 76 0.1 98.0
3 0.4 86.7 83 0.0 98.0
4 0.2 86.9 89 0.1 98.1
5 0.2 87.1 90 0.4 98.5
6 0.9 88.0 95 0.1 98.6
7 1.7 89.7 99 0.1 98.6
9 0.3 90.0 106 0.1 98.6

11 0.1 90.1 119 0.1 98.6

12 0.6 90.7 120 0.4 99.0

13 0.3 91.0 150 0.3 99.3

14 0.3 91.3 155 0.1 99.4

15 0.1 91.4 180 0.0 99.4

16 0.7 92.1 185 0.4 99.7

18 0.1 92.2 305 0.0 99.7

19 0.2 92.4 335 0.1 99.8

20 0.1 92.5 351 0.2 99.9

21 0.1 92.6 362 0.1 99.9

23 0.4 93.0 363 0.1 100.0

25 0.1 93.1

27 0.2 93.3

28 0.2 93.5

29 0.4 93.9

30 1.6 95.5

35 0.1 95.6

37 0.1 95.7

39 0.3 96.0

40 0.0 96.0

42 0.1 96.1

46 0.4 96.5

53 0.4 96.9

57 0.1 97.0

58 0.2 97.2

60 0.4 97.6

73

Iw E'Efi 1.". .. 111' E 1 £1. 'vz;

Most destination marketing organizations focus much of their marketing strategy
on attracting travelers who have not decided on their travel destinations, or, in the
terminology adopted for this study, those engaged in the information processing interval
of the trip planning process. Their advertising messages encourage potential travelers to
request an information packet designed to convince them to select that particular
destination. The costs of preparing and distributing these information packets is
substantial.

The results presented above bring into question the wisdom of basing a promotion
strategy on undecided travelers since they constitute a very small percentage (15%) of
Michigan's pleasure travel market. And, the fact that about half of these undecided
travelers make their destination decisions 21 days after beginning to plan their trips
implies that, as often as not, undecided travelers select their destinations before they
receive forwarded destination information. A couple of implications that can be made
here are: (l) prompt response to information requests is essential if forwarded
information is to have an impact on the destination decision and (2) it should be
recognized in designing information packets that the vast majority of recipients have
already made their trip destination decision. The latter point suggests that the information
packet should feature materials that will confirm the correctness of their destination
decision, enhance a traveler's experience at the destination, encourage length of stay, and
stimulate spending money at the destination, as well as general information designed to

lure travelers to that destination.

74

Although the results reported above discourage over reliance on targeting
potential travelers during the information processing interval, further analyses may prove
helpfirl when this segment is selected as a target market.

The frequency distribution in Table 13 suggests that this population can logically be
grouped into two categories: (1) those whose information processing interval is zero
days—defined as 'instant decision-makers' and (2) those whose information processing
interval is one day or more—defined as 'hesitant decision-makers'. These two groups of
travelers are compared below across the following three general categories of variables:
(1) source of information and media habits, (2) trip characteristics and travel behavior,
and (3) demographic and socioeconomic characteristics. Results are presented in Tables

14-16.

75

Table 14. Sources of information and media habits of instant and hesitant decision-

 

 

makers.
All Instant Hesitant
Pleasure Decision- Decision- Test
Variable Travelers Makers Makers Statistic Significance
mfonnauonmmmst
£31011:me 1
AAA/CAA 24.3% 24.1% 25.3%
Travel agency 18.7% 19.5% 14.4%
Friends/relatives/co-workers 19.0% 17.8% 25.9%
Chamber of commerce 4.8% 4.9% 4.4%
Other travel guide 5.4% 5.4% 5.4%
Magazine 4.1% 3.9% 5.2%
Intemet/online service 8.2% 8.2% 8.2%
State travel office 3.3% 3.2% 4.3%
Travel section of newspaper 2.2% 2.2% 2.0%
Convention/visitors bureau 1.9% 1.8% 2.9%
Mobil Travel Guide 1.4% 1.5% 0.8%
Highway welcome centers 0.4% 0.3% 0.9%
Travel show 0.2% 0.1% 0.8%
C D-ROM 0.1% 0.1% 0.0%
Other source 9.9% 10.0% 9.5%
No source 14.0% 14.4% 1 1.9%
”1.: '1 111 ”IE!
W n_1= 152 = 7 n=181 x2 = 8.76 0.033
Magazine 54.5% 54.7% 53.0%
Newspaper 23.6% 22.3% 30.4%
Television 18.8% 19.9% 12.7%
Radio 3.2% 3.10/0 3 .9°/o
W n__l=1 21 11ml 7 115.113 x2 = 3.72 0.054
% of Yes 52.6% 51.5% 59.5%
WW0
1mm n=6z4 = 74 n=100 x2=0.59 0.444
0/0 Of YCS 57.50/0 56.90/0 61.00/0
W
' ' ' T v
W 9:353 3:393 [1:110 x2 = 0.62 0.430
% of Yes 15.0% 14.3% 18.3%
W
v' ' -
W = 4 4 0:21 .4_4 11:22.0 x3=0.04 0.849
% of Yes 33.7% 33.8% 33.2%

 

' Percentages add to more than 100% due to multiple responses.

76

Table 15. Trip characteristics and behaviors of instant and hesitant decision-makers.

 

 

All Instant Hesitant
Pleasure Decision- Decision- Test
Variable Travelers Makers Makers Statistic Sijpificance
xii-1.4.4.2 [131221 0221.8 x2 = 2.75 0.433
Winter (December through 14.0% 14.3% 12.4%
February)
Spring (March through May) 13.8% 14.3% 1 1.5%
Summer (June through August) 44.6% 43.8% 49.1%
Fall (September through 27.5% 27.6% 27.1%
November)
Brimfiumgfltin E15162 n=_1243 n=219 x2 = 15.31 0.018
Outdoor recreation 14.7% 14.2% 17.8%
Entertainment 13.8% 14.3% 1 1.0%
VFR 29.2% 30.2% 23.7%
Relaxation 10.5% 10.5% 1 1.0%
General touring 3.6% 3.5% 4.1%
Vacation/holiday/recreation/
amusement/pleasure 23.2% 23.2% 23.3%
Other 4.9% 4.2% 9. 1 %
General touring or driving for 58.7% 57.2% 67.4% x2 = 8.01 0.005
pleasure
Shopping 53.8% 53.2% 57.3% x?- = 1.29 0.256
Outdoor recreation 56.5% 55.5% 62.1% x2 = 3.33 0.068
Explore small city or town 52.8% 51.9% 57.5% x2 = 2.35 0.126
Dine at unique restaurant 48.6% 48.0% 52.1% X2 = 1.23 0.267
Visit other attraction 44.6% 43.8% 49.1% x2 = 2.12 0.145
Nightlife 32.6% 31.6% 38.1% X2 = 3.49 0.062
Visit state or national park 31.2% 30.3% 36.2% X2 = 3.00 0.083
Visit an historic site 28.6% 27.6% 33.9% x2 = 3.66 0.056
Attend a festival or event 23.3% 24.2% 18.5% x2 = 3.08 0.079
Visit museum or hall of fame 15.0% 13.9% 21.0% X2 = 7.37 0.007
Fall color touring 9.4% 9.1% 11.1% x2 = 0.83 0.363
Casino gaming 11.1% 11.6% 8.5% x2 = 1.57 0.210
MW = 4 = 0 n_2_1_6= t=2.50 0.013
Worm/g.) 4.8 4.8 5.2
n=1250 011010 = 4 x2 = 28.52 0.000
Hotel/motel/lodge 42.6% 40.0% 57.2%
Friend's/relative's home 27.4% 29.4% 17.0%
Owned cabin/cottage/condominium 7.1% 7.6% 4.6%
Rented cabin/cottage/condominium 7.2% 7.4% 6.2%
Commercial campground 4.9% 4.8% 5.2%
Public campground 4.2% 4.2% 4.1%
Bed & Breakfast 1.7% 1.7% 1.7%
Boat/ship 0.6% 0.4% 1.5%
Other 4.3% 4.6% 2.6%

 

77

Table 15. Trip characteristics and behaviors of instant and hesitant decision-makers,

 

 

continued.
All Instant Hesitant
Pleasure Decision- Decision- Test
Variable Travelers Makers Makers Statistic Significance
1 11:1369 11:12“ 11:212 --- --..
Car/ truck without camping 90.6% 90.7% 90.5%
equipment
Car/ truck with camping 3.0% 2.7% 4.4%
equipment
Motorcoach 2.0% 2.2% 0.7%
Airplane 2.4% 2.2% 3.0%
Ship/boat 1 .4°/o 1.2% 2.4%
Self-contained recreation vehicle 1.5% 1.4% 1.8%
Rental car 0.8% 0.8% 0.8%
Motorcycle 0.4% 0.4% 0.0%
Train 0.2% 0.2% 0.0%
Bicycle 0.2% 0.2% 0.0%
Other 0.9% 0.8% 1.4%
Iraxelhrtx
= 4 11:12.39 n=2|2 t = 0.55 0.583
Average party size 3.3 3.2 3.3
n=|32§ n=119l = 7 t=0.21 0.834
Average age of all persons in 38.0 38.1 37.8
party
Included person(s) aged. . .' n= | 328 n=l [2| 11:25)] --- ---
Less than 10 33.9% 34.8% 28.6%
11 to 20 36.0% 35.9% 36.7%
21 to 30 53.2% 53.0% 54.2%
31 to 40 64.6% 65.0% 62.4%
41 to 50 61.0% 60.2% 65.3%
51 to 60 34.5% 34.5% 34.5%
61 to 70 17.5% 18.4% 12.3%
Above 71 8.2% 8.5% 6.6%
WM n_12i4.= n_l_Qél= L121= X2 = 12.38 0.000
Spent night at 1 place in MI 91.0% 92.2% 84.3%
Spent night more than 1 place in 9.0% 7.8% 15.7%
M1
= 44 n=1 11:12] t=2.37 0.018
WM 1.1 1.1 1.1
(£1an

78

Table 15. Trip characteristics and behaviors of instant and hesitant decision-makers,

 

 

continued.
All Instant
Pleasure Decision- Hesitant Test
Variable Travelers Makers Decision-Makers Statistic Significance
Wm“ ‘1 2' ' l ' = 4 LBJ—8: n.212= X2=6.81 0.235
. .
Upper Peninsula 16.6% 15.8% 20.7%
Northwest Lower Peninsula 18.0% 17.9% 18.3%
Northeast Lower Peninsula 16.0% 16.0% 16.0%
Southwest Lower Peninsula 17.4% 18.2% 12.7%
Southeast Lower Peninsula 18.5% 18.8% 16.9%
without Detroit area
Detroit area (Wayne, Oakland, 13.6% 13.2% 15.5%
and Macomb Counties)
112W 11:15.6 = 7 n=212 t=0.50 0.615
inMichiaaMAan 4.4 4.4 4.6
mm
Overnight trip = 4 n=1245 n=219 x2 = 1.27 0.260
% of Yes 85.2% 84.7% 87.7%
Vacation Trip n= [470 n= | 242 E221 X2 = 6.45 0.01 1
% of Yes 67 8% 66.5% 75 1%
Family Trip =144 151232 n=211 x2 = 0.00 0.973
% of Yes 72.3% 72.2% 72.4%
Arranged by Travel Agent n=| 73 115L253 [13220 X2 = 0.29 0.591
% of Yes 3.3% 3.4% 2.7%
Package Tour with Lodging n=1474 11:12.53 n=198 x2 = 8.04 0.005
% of Yes 6.2% 5.4% 10.4%

79

Table 15. Trip characteristics and behaviors of instant and hesitant decision-makers,

 

 

continued.
All Instant
Pleasure Decision- Hesitant Test
Variable Travelers Makers Decision-Makers Statistics Significance
I . E . C 1 v I
11:12.48 121.1155 11:12.4. t= 1.77 0.079
No. nights away from home 3.8 3.7 4.6
11:12:16 0511123 11323 t= 1.54 0.125
No. nights spent in MI 3.6 3.5 4.2
v E 1 . l l' l .
= 4 n=| l 22 113208 t= 0.25 0.803
Total spending per trip $539.75 $535.24 $565.30

 

' Percentages add to more than 100% due to multiple responses.

2 Definitions of regions:

Upper

    
 

SE wfo
Detrort Area

Detroit
Area

80

Table 16. Demographic and socioeconomic characteristics of instant and hesitant

decision-makers.

 

 

All Instant Hesitant
Pleasure Decision- Decision- Test

Variable Travelers Makers Makers Statistics Significance
Summon = 47 n.1256= =7 x2 = 7.57 0.272
Residenee

Illinois 14.5% 13.7% 18.8%

Indiana 8.6% 9.2% 5.4%

Michigan 47.4% 47.5% 47.1%

Minnesota 2.3% 2.2% 2.7%

Ohio 13.5% 13.5% 13.5%

Wisconsin 6.0% 6.0% 6.3%

Ontario 7.8% 8.0% 6.3%
Hemeheldiemainesl...

Pre-school child(ren) 14.8% 14.8% 14.7% X2 = 0.00 0.962

School age child(ren) 34.6% 34.8% 33.6% x2 = 0.11 0.744

Senior citizen(s) 17.5% 17.1% 19.3% x2 = 0.58 0.448

Handicapped person(s) 4.5% 4.2% 6.0% x2 = 1.38 0.241
QLQSLAnnuaLHelueheldJneeme n_134_Z= = 4 1122.00 >12 = 1.57 0457

Below $31,000 19.2% 19.4% 18.0%

$31,001 - $50,000 28.8% 28.2% 32.5%

Above $50,000 52.0% 52.5% 49.5%
Baeeifithnieim = 4 1131065 11:18: x3= 15.28 0.018

White 93.4% 93.7% 91.8%

African American 4.1% 3.9% 4.9%

Hispanic 0.6% 0.4% 1.6%

Native American 0.9% 1.0% 0.0%

Asian American 0.6% 0.7% 0.0%

Multiracial 0.2% 0.2% 0.5%

Other ‘ 0.2% 0.1% 1.1%

' 11.14.52= 11:42:15 11:219

Employed full-time 66.7% 66.6% 67.0%

Retired 12.0% 12.3% 10.3%

Employed part-time 9.3% 8.6% 13.0%

Homemaker 7.4% 7.4% 7.6%

Student 5.6% 5.8% 4.8%

Other type(s) employment 1.9% 1.8% 2.2%

Not employed 2.3% 2.4% 1 9%
Numhemffullztimeflaee: 11_l_5.= 4 7 11:12.32 11_.1.=7 9 t= 0.25 0.805
EameranfleueeheldiAer 1-5 1-5 1-5

 

' Percentages add to more than 100% due to multiple responses.

81

0 ‘ 1 1011110121! U"! 111. 0 11.1110 1‘ '11 D‘ '01111.‘

AS can be seen in Table 14, instant and hesitant decision makers generally rely on
the same information sources and use them with a similar level of frequency. Noteworthy
exceptions include: (1) instant decision makers are more prone to use a travel agency and
(2) hesitant decision makers rely more on information from word-of-mouth. The only
other observed differences in Table 14 of any significance are that instant decision
makers tend to rely more on television while hesitant decision makers use newspapers

more frequently.

11 1.. 11' 1113111111 11.1.11 1' '11 I: '11u1,.-

In comparison to hesitant decision makers, the primary purpose of trip for instant
decision-makers is more likely to be visiting friends or relatives (30.2% vs. 23.7%) and is
less likely to be outdoor recreation (14.2% vs. 17.8%) (See Table 15).

Instant decision-makers are not as action-oriented as are hesitant decision makers.
Instant decision makers participate in 4.8 activities versus 5.2 activities for hesitant
decision makers. Instant decision makers are less likely to participate in general touring
or driving for pleasure (57.2% vs. 67.4%) and visiting a museum or hall of fame (13.9%
vs. 21.0%) than are hesitant decision makers.

Instant decision-makers are more likely to use a friend's or relative's home as their
main type of lodging (29.4% vs. 17.0%) during their pleasure trips than are hesitant
decision makers. They are also less likely to use hotel/motel/lodge as their main type of
lodging (40.0% vs. 57.2%). Hesitant decision makers tend to spend nights at more than

one destination which in part explains their tendency to devote more time to the

82

information processing interval. Finally, a couple of trip type differences can be noted in
Table 15. Hesitant decision makers are more likely than their counterparts to purchase a

package including lodging (10.4% vs. 5.4%) and to consider their trips to be a vacation

(75.1% vs. 66.5%).

.‘IIDHeDI -.1I I 1- MIN 1-. ._ ‘1' I-1 1.1-.1I1'11D‘i'Il-

Makers.
Few statistically Significant differences were observed in the variables of
state/province of principal residence, household composition, household income,

employment Situation, and number of full-time wage-eamers in household that are

presented in Table 16.

V aI‘. J: 11-‘1‘D-r-_I1I 1' 1._ I'-.111° ‘ 0.. 01' 'v

Findings presented in the previous section suggest "how" total trip planning, post
decision, and information processing intervals fluctuate across Michigan pleasure
travelers. In this section, "what variables" are likely to influence the length of planning
intervals will be examined.

From the data provided in Table 9, it can be seen that the trip planning behavior
clearly varies widely across the responding population. A key question addressed in this
study is: why do the planning intervals vary across pleasure travelers? In other words,
what factors are significant in explaining variations in observed planning intervals? This

question was stated in the form of a hypothesis in Chapter I and is repeated below:

83

Hypothesis 3. Selected socioeconomic characteristics, travel party composition, trip
characteristics and behavior, and expenditure variables have no effect on the duration
of the total trip planning interval.

Note that the total trip planning interval was selected as the best dependent

variable for testing this hypothesis (See footnote 4 in Chapter III).

W91
The multiple regression model Specified to investigate the relationship between
the total trip planning interval and selected socioeconomic and trip related variables is

presented below.

Y, = flo +fl, (PI‘.'141KSEAS,.)+,6'2 (PUR_ VFR, )+fl3(PARTYSIZ,)+fl4(ACT_ NITE,)+
fl5(ACT_PARK,)+fl6(ACT_MUSE,.)+fl7(ACT_HIST,)+,6’8(ACT_0TH,.)+
,69(ACT_FALL,)+,6’IO(ACT_GEN,)+fl”(ACT_OR,)+,6’,2(ACT_SH0P,)+
,6,3(ACT_EVNT,.)+,6,4(ACT_CASI,)+fllS(LOG_ FR,)+,6’,6(N0PTMI,)+
fl,,(TRP_ FAM,)+,6,3(TRP_OVER, )+fl,9(TRP_ VACA, )+fl20(DURAT10N,.)+
,6‘2, (EXPENDIT, ) + ,6’22 (MIRESIDE, ) + ,623 (MEDINCOM, ) + flu (HHS _ PRE, ) +
,625(HHS_SCH,)+£,
where, 1’,- = the total trip planning interval for individual i; £1-35 = coefficients of

independent variables 1-25, and a,- = the error term.
The variables in parenthesis are independent variables that were defined and described in
Table 8, Chapter III.
The estimation results using OLS regression are reported and then the ideal
conditions for using OLS are tested. The double bounded tobit model was used to test the
effect of the double censoring problem in the dependent variable, the total trip planning

interval.

84

E . . E 1
Using the survey data for the period 1996-98, the multiple regression model was
estimated. The parameter estimates are presented in Table 17.

Table 17. Estimated influence of selected variables on total trip planning
interval-OLS regression results.

 

 

Variable Coefficient Beta Standard t-statistic p-value Mean of X
Coefficient Error

CONSTANT -22.651 1 67.85766 0334 0.7385

PEAKSEAS 24.46959 0.1096 7.696926 3.179b 0.0015 0.455978
PUR_VFR -2.86048 -0.0270 9.177873 -0.312 0.7553 0.286376
PARTYSIZ 4.265976 0.1255 1.014099 4.207b 0.0000 3.515292
ACT_NITE -15.0428 -0.0225 7.764815 -1.937 0.0527 0.360519
ACT_PARK -3.53504 0.0412 8.760932 -0.404 0.6866 0.355885
ACT_MUSE -17.3786 -0.0418 10.5181 -l.652 0.0985 0.164968
ACT_HIST -6.15281 -0.0555 9.224168 -0.667 0.5048 0.320667
ACT_OTH 8.395163 0.0074 7.650179 1.097 0.2725 0.466172
ACT_FALL 15.6012 0.0495 13.10005 1.191 0.2337 8.34E-02
ACT_GEN -7.25737 -0.0310 7.984626 -0.909 0.3634 0.610751
ACT_OR 18.58603 0.0710 8.260282 2.25a 0.0244 0.613531
ACT_SHOP 3.775085 0.0073 7.606846 0.496 0.6197 0.551437
ACT_EVNT 32.87272 0.0929 8.453 3.889b 0.0001 0.23633
ACT_CASI 6.108705 0.0221 11.12391 0.549 0.5829 0.125116
LOG_FRH -19.3236 -0.0582 9.408284 -2.054“ 0.0400 0.26228
NOPTMI -0.78658 -0.0408 0.594496 -1.323 0.1858 4.466172
TRP_FAM 1.680766 0.0032 8.335305 0.202 0.8402 0.722892
TRP_OVER 41.64061 0.0193 66.07576 0.63 0.5286 0.99722
TRP_VACA 32.86776 0.1187 8.463422 3.884b 0.0001 0.73494
DURATION 1.97619 0.1118 0.85153 2.3218 0.0203 3.621872
EXPENDIT 0.0153 0.0679 5.83E-03 2.63b 0.0085 541.0028
MIRESIDE -7.37352 -0.0116 7.390944 -0.998 0.3185 0.52456
MEDINCOM -4.32036 -0.0185 9.368547 -0.461 0.6447 0.826691
HHS_PRE -l7.0186 -0.0534 9.706769 -1.753 0.0796 0.163114
HHS_SCH 5.396713 0.0234 7.612915 0.709 0.4784 0.363299

 

110182

a indicates that a coefficient is significantly different from zero at 95% level for two way test.
b indicates that a coefficient is significantly different from zero at 99% level for two way test.

85

In Table 17, the column labeled "Coefficient" provides the estimate for the
parameter associated with the variable named in the first column. These are estimates of
the parameters and sometimes called unstandardized coefficients. The column labeled
"Beta Coefficients" are used to facilitate comparisons between regression coefficients
(Nester & Wasserman, I974). The beta coefficient (or standardized coefficient) reflects
the changes in the mean response (in units of standard deviations of the dependent
variable) per unit change in the independent variable (in units of standard deviations of
the independent variable), when all other independent variables are held constant (Nester
& Wasserman, 1974). Ordinarily, it is difficult to compare regression coefficients
because of differences in the units involved. The values of beta coefficients can be
interpreted as the degree each independent variable impacts on the dependent variable.
The column labeled "t-statistic," which is each coefficient divided by its associated
standard error, serves as a statistical test of whether the coefficient is significantly
different from zero (significance in the statistical sense, not an "importance" sense).7 The
larger the value of the t-statistic, the more statistically significant is the associated
estimated coefficient. Generally, a t-test greater than 2 indicates significance.8

The regression analysis results presented in Table 17 indicate that several

independent variables, eight of the 25 independent variables, are significant at the 95%

 

7 This is an asymptotic t-value on a two tailed test of the null hypothesis that the coefficient is equal to zero.
This is a test of the population mean of a normally distributed variable with unknown variance. It is
asymptotic in that the parameter estimates will be exactly normally distributed only as the sample size
becomes infinitely large, but the approximation is good in large samples.

8 The significance level gives the probability of erroneously deciding the parameter is not zero, when in fact

it is. The 20% significance level falls at t equals 1.28, 10% at t equal 1.65, 5% at t equals 1.96, and 1% at t
equals 2.58.

86

level of significance using the two-tailed t-test. The variable whether a pleasure traveler
begins to take a trip during peak season or non-peak season is significant. The peak
season includes the three summer months (June, July, and August), and the non-peak
season includes the rest of the year. Pleasure travelers who take trips during the summer
months have a significantly longer total trip planning interval. In other words, peak
season pleasure travelers in comparison to the non-peak season pleasure travelers are
likely to begin to plan trips earlier.

The variable party size is significant in explaining variation in total trip planning
interval. As party size increases, the total trip planning interval increases. Respondents
who participate in outdoor recreation are likely to take more time to plan than those who
do not participate in outdoor recreation. Pleasure travelers who attend a festival or event
begin to plan significantly earlier than those who do not. Type of lodging is also
significant for Michigan pleasure travelers. Those who stay at friends' or relatives' homes
have a shorter total trip planning interval. The variable whether or not pleasure travelers
consider their trips to be a vacation trip is also significant. Trips considered to be
vacations involve longer planning horizons. Duration of trip is also a significant
explanatory variable. As length of trip increases, the total trip planning interval increases.
Finally, estimated total trip expenditures in Michigan is significant. As spending

increases, the total trip planning interval increases.

9.025111251521131
Regression analysis is primarily used for two purposes: (1) for estimating

coefficients of interest and testing hypotheses about them and (2) for forecasting (Greene,

87

1994). For the second, how well the regression model predicts movements in the
dependent variable is crucial. The coefficient of determination, R2, is a measure of the fit
of the model. The R2 for the regression model used in this study is 17.2%, which implies
that the independent variables only explain about 17% of the variation in the dependent
variable, the duration of the total trip planning interval. In social science study, the R2
lower than 20% was often found as an meaningful model to estimate coefficients of
interest and testing hypotheses. However, R2 is somewhat low. Therefore, bivariate
analyses are presented in Appendix C with statistic tests as an alternative method to

estimate individual coefficients of variables.

MW

Eight of 25 independent variables were found to be significant in explaining the
duration of the total trip planning interval. As explained in the previous section, the
standardized or beta coefficients allows one to compare the relative impacts of these
significant independent variables. The values of beta coefficients are reported in Table
17. Party size has the strongest impact on the duration of the total trip planning interval
followed by the trip was considered to be a vacation (TRP_VACA), the number of nights
spent in Michigan (DURATION), trip was taken during peak season (PEAKSEAS),
attended a festival or event during the pleasure trip (ACT_EVNT), participated in
outdoor recreation (ACT_OR), and the amount of money spent during pleasure trips to
Michigan (EXPENDIT). The variable, stayed at a friend's or relative's home

(LOG_FRH), was significant, but has the weakest impact on the duration of total trip

88

planning interval. It is also the only statistically significant variable with a negative

impact on the dependent variable.

IlIlI°El‘I III 11
While it would have been desirable to include Internet use behavior in the
regression model, data were not available for the total time period covered in this study.
The Internet use behavior variable was included in the questionnaire one and half years
after the beginning of the survey while other independent variables were included from
the beginning of the survey. However, the influence of the Internet on the tourism
industry is significant. Thus, the influence of the Internet variable on the duration of the
total trip planning interval was investigated by descriptive analysis and statistical
significance was evaluated using the independent sample t-test or one way ANOVA test.
Three Internet variables were investigated: whether or not any member of the household
has accessed to the Internet, have used the Internet to obtain travel information, and used
the Travel Michigan (formerly Michigan Travel Bureau) site on the World Wide Web to
obtain travel information. The mean values of these variable and t-statistics are reported
in Tables 18-20.
Table 18. Total planning interval by: Do you or

any member of your household have
access to the Internet?

 

Case Mean value of total trip
planning interval (Days)

 

Yes 628 66.5
No 565 77.6

 

t-value = 1.83, significance = 0.068

89

Table 19. Total planning interval by: During the
past 12 months, have you or any member
of your household used the Internet to
obtain travel information?

Case Mean value of total trip
planning interval (Days)

 

Yes 359 67.5
No 265 64.6

 

t-value = 0.38, significance = 0.707

Table 20. Total planning interval by: During the
past 12 months, have you or any member
of your household used the Michigan
Travel Bureau's site on the World Wide
Web to obtain travel information?

Case Mean value of total trip

_ planning interval (Days)

Yes 53 70.2
No 300 66.6

 

j-value = 0.24, significance = 0.807

None of the differences were found to be statistically significant using the two-tailed t-
test at 95% confidence interval.

Four segments of Internet users were created from the Internet variables: (1) never
accessed Internet, (2) accessed Internet, (3) accessed Internet and obtained travel
information, and (4) accessed Internet, obtained travel information, and accessed the
Travel Michigan's web site to obtain travel information. The first segment includes those
who answered "no" to the all questions listed in Tables 18-20. The second segment
includes those who answered "yes" to the question in Table 18 and "no" to the questions

in Tables 19-20. The third segment includes those who answered "yes" to the questions in

90

Tables 18-19 and "no" to the question in Table 20. The last segment includes those who
answered "yes" to the questions in Tables 18-20. The degree of Internet involvement
increases from the first segment through the fourth segment. These four groups were
compared in terms of the mean value of the total trip planning interval and statistical
significance was tested using one way ANOVA. This analysis was performed to
investigate how the degree of Internet involvement influences the duration of the total
trip planning interval. The mean and median values of the four segments are reported in
Table 21. The F-value is also reported. No statistically significant relation between the
degree of Internet involvement was found.

Table 21. Total planning interval by the degree of Internet involvement.

Mean value of

total trip Median value of total
planning interval trip planning interval

 

Internet Users Cases (Days) (Days)
Access to Internet & Information & TM1 53 70.2 30.0
Access to Internet & Information 298 66.8 30.0
Access to Internet 264 64.7 30.0
No access to Internet 565 77.6 30.0
Total 1 180 71.6 30.0

 

I TM stands for Travel Michigan's web site

Test results : F -value=1.227 Significance=0.298

W
"2

The assumption of normality can refer either to the variables themselves or to 2 (“of -
\ .

sampling distributions of statistics calculated from samples. Tabachnic and Fidell

(1983) state that, with sampling distributions, the central limit theorem protects against

failure of normality when the sample size is large and there are roughly the same number

91

of cases in all groups. However, testing the normality of the dependent variable, the total
trip planning interval, adds robustness to the estimates derived.

First, the visual method for examining the distribution was employed. The

M ”‘1 .DW 'V.‘ «‘1": .1):ka “‘- “ \‘fl-V/‘QJ-mgv‘At - - 1‘“ “V9“ 1.. ”‘

histogram of standardized residuals are ”plotted in Figure 8. The visual check concerning

” M"“"""‘h'vm.~uwx wu- "“""~ “‘Wm"

 

 

 

 

the distribution of error terms appears to be normal in this histogram. Although
histograms provide a visual basis for assessing normality in residuals, this visual check is

purely subjective in interpretation. It is often desirable to statistically test the error term‘s

my- “mo-M
a..-

 

M

 

distribution. The Kolomogorov-Sflmq: (K- S) one “sample tesiwas used {9113539.ng
normality of the error termsby analyzing the residuals. The K-S test compares the
cumulative distribution function for a variable with a specified distribution, which may
be uniform, normal, or Poisson. The K-S Z is computed from the largest difference (in

absolute value) between the observed and theoretical distribution functions (Neter &

Wasserman, 1974).

92

 

200

 

 

 

100 1
>
o
8 Std. Dev = .99
§ Mean = 0.00
L: o J N = 977.00

“‘/‘/‘.0.'6".".‘~'?"?‘-?‘?
€%€00.%.006~0000 00%00*’ooo°‘0

Regression Standardized Residual

Figure 8. Histogram of regression standardized residuals of the total trip
planning interval.

The null hypothesis that the distribution of the residuals was not a normal
distribution was tested and the test statistics are reported in Table 22. The test results
reveal that the distribution of the residuals is normal. The one-sample chi-square test
statistic is 11.695 and is significant at 0.000 level. Thus, the assumption that error terms

are normally distributed is met in this analysis.

93

.x’” W“ ' "Mg...

Table 22. One-sample Kolmogorov-Smimov Test for normal
distribution of residuals.

 

 

 

Total Trip

Planning Interval

Normal parameters Mean 70.659

Standard deviation 105.281

Most extreme differences Absolute 0.296

Positive 0.296

Negative -0.25 1

Kolmogorov-Smimov Z 11.695

Significance (two-tailed) 0.000
“1.". . 15' l.

I There are two different conditions within correlation matrices that can suggest

3 termination of an analysis or render portions of it unstable; they are multicollinearity and

singularity. These assumptions are not so much assumptions, but a restriction, and if

 

[R these conditions are violated, it can render analyses meaningless.

Multicollinearity occurs when two variables in a matrix are perfectly, or near
perfectly, correlated and when they show a similar pattern of correlation with the other
variables. Singularity occurs when one variable is a linear combination of others.
Detection of these conditions is often found with the use of tolerance measures. Again,
tolerance is a statistic used to determine how much the independent variables are linearly
related to one another (multicollinearity). Although multicollinearity and singularity are

different, they cause similar problems in multivariate analyses, specifically by prohibiting

or rendering an unstable matrix inversion (Tabachnick & Fidell, 1982).

94

Multicollinearity and singularity issues in the study were evaluated by the
tolerance values calculated during the regression analysis. These values are also a
measure of independence among the variables. The test results were reported in Table 23.

Table 23. Multicollinearity test
‘ statistics -Tolerance test.

 

 

Independent Tolerance
Variables

PEAKSEAS 0.803085
PUR_VFR 0.706585
Q5795MIR 0.766757
ACT_NITE 0.855547
ACT_PARK 0.671 167
ACT_MUSE 0.778931
ACT_HIST 0.635854
ACT_OTH 0.813853
ACT_FALL 0.900757
ACT_GEN 0.781571
ACT_OR 0.739355
ACT_SHOP 0.828457
ACT_EVNT 0.930746
ACT_CASI 0.886719
LOG_F RH 0.71 1804
MIVSTNUM 0.787135
TRP_FAM 0.833788
TRP_OVER 0.979740
TRP_VACA 0.843086
Nights spent in MI 0.783954
Spending in MI 0.745127
MIRESIDE 0.873784
MEDINCOM 0.938983
HHS_PRE 0.927813
HHS_SCH 0.8301 17

 

The tolerance of a variable is a commonly used measure of multicollinearity. The
tolerance of variable i is defined as l-R,‘2 , where R, is the multiple correlation coefficient
when the ith independent variable is predicted from the other independent variables

(SPSS Inc.,)1993). If the tolerance of a variable is small, it is almost a linear combination

...... ._ ‘ “

, 9“ i
l ’4 fi -_ ( .

5”.“ <\
‘11.. l? ‘(‘>g’-'.i ..-.. " 'C
\l 95

of the other independent variables (SPSS Inc., 1993). The findings revealed that the
tolerance values were high enough (all over .6 and most of them are over .8). These high
tolerance values indicate that multicollinearity was not a significant limitation on the

reported regression results.

Doubly Censored Normal Distribution

A very common problem in consumer behavior data is censoring of the dependent
variable (Green, 1994). For example, Tobin (1958) analyzed household expenditure on
durable goods using a regression model which specifically took account of the fact that
the expenditure (the dependent variable of his regression model) cannot be negative.
Tobin called his model "the model of limited dependent variable". Some other examples
of this type of dependent variable include: the number of tickets sold (Amemiya , 1984;
Maddala, 1983), the number of extramarital affairs (Fair, 1978), the number of arrests
after release from prison (Quester & Greene, 1982), and household expenditures on
various commodity groups (Jarque, 1987). Using OLS regression for this type of
dependent variable (censored) may cause instability of parameters (Nakamura &
Nakamura, 1983).

Like Tobin's dependent variable, the total trip planning interval cannot be
negative. Recall that the total trip planning interval is the length of time from the date the
trip planning begins to the date the trip is taken. A negative total trip planning interval
would require the date the trip planning begins to follow the date the trip is taken.
Logically, this sequence cannot occur. Therefore, there would be no negative values for

the total trip planning interval. The distribution of the total trip planning interval is also

96

censored at the upper level. Virtually no cases were observed with a total trip planning
interval of longer than one year. 9

It was desirable to test whether or not the dependent variable of this study, the
total trip planning interval, has an associated double censoring problem. The most
familiar regression model used for censored dependent variables is tobit or standard
censored regression. Because the dependent variable in this study was assumed to be
doubly bounded, the double bounded tobit model was used to test the robustness of the
OLS regression method used.

The coefficients and test values of each model were compared to test the
robustness of the OLS model. The results of these two regression estimates are presented
in Table 24. The OLS estimates used for hypotheses testing are presented in the first two
columns in Table 24. The estimates for the double bounded tobit regressions are given in
the third and fourth columns. Three different significant levels are used to compare the
test values of the three estimates of the regression parameters: at 90%, 95%, and 99%
level of significance for two tailed t-test.

With only a few exceptions, the OLS and the double bounded tobit regression
analyses results are quite similar across the full set of independent variables. In
comparing the signs across estimated coefficients, two differences are apparent between
the OLS and the double bounded tobit estimates (i.e. visit state or national park and

family trip). The numeric values of the estimated coefficients from both the OLS and the

double bounded tobit regressions are relatively similar with the exception of the

 

9 As explained in methodology chapter, there were two cases of extreme values, 730 days and 1825 days.
These two cases were deleted from the data set to mitigate outlier problems in these analyses. Therefore,
one year, or 365 days, is the longest interval in the data set.

97

Table 24. Estimated influence 0f selected variables on total trip
planning interval-OLS, negative binomial, and double
bounded tobit regression results.

 

 

OLS Double bounded tobit

Coefficient t-statistics Coefficient t-statistics

CONSTANT -22.651 1 -0334 -244991 -0373
PEAKSEAS 24.46959 3.179c 24.73347 3.293c
PUR_VFR -2.86048 -0312 4.05137 -0453
PARTYSIZ 4.265976 4.207c 4.690777 4.691c
ACT_NITE -15.0428 -1937“ -12.8031 -1688“
ACT_PARK -3.53504 -0404 3.256491 0.381
ACT_MUSE -l7.3786 -1.652 -1194 -1.165
ACT_HIST -6.15281 0667 -151443 4.6843
ACT_OTH 8.395163 1.097 7.105128 0.952
ACT_FALL 15.6012 1.191 18.97758 1.483
ACT_GEN -725737 -0909 -8.78072 -1.128
ACT_OR 18.58603 2.25b 16.59165 2.061b
ACT_SHOP 3.775085 0.496 2.398786 0.323
ACT_EVNT 32.87272 3.889° 29.35669 3.55c
ACT_CASI 6.108705 0.549 6.996827 0.643
LOG_VFR -l9.3236 -2054" -l7.889 -1953
NOPTMI -0.78658 -1323 -0.87312 -1507
TRP_FAM 1.680766 0.202 -2.31784 -O.285
TRP_OVER 41.64061 0.63 39.19948 0.613
TRP_VACA 32.86776 3.884c 36.54552 4.424c
DURATION 1.97619 2.321b 2.635041 3.13c
EXPENDIT 15312-02 263° 14213-02 2.501b
MIRESIDE 737352 -0.998 .3.74347 -0519
MEDINCOM -4.32036 -O.461 -1.92917 .0.21
HHS_PRE -17.0186 -1753“ -16.9793 4.795“
HHS_SCH 5.396713 0.709 7.518106 1.011

 

note:

a

90% level of significance for the two tailed t-test.
b indicates that a coefficient is significantly different from zero at the
95% level of significance for the two tailed t-test.
° indicates that a coefficient is significantly different from zero at the
99% level of significance for the two tailed t-test.

98

indicates that a coefficient is significantly different from zero at the

two previously noted variables with opposite signs and two additional variables (i.e. visit
museum or hall of fame and visit a historic site). Importantly, in the sense of testing the
robustness of the OLS regression in evaluating which among this set of independent
variables may play a significant role in explaining variation in total trip planning interval,
the double bounded tobit regression result identifies the same ten variables as being
statistically significant as were identified from the OLS regression results. However, the
tobit model suggests another variable as being significant (i.e. visit an historic site). On
balance, it would appear that the OLS regression model in this application is not
influenced by the doubly censoring problem. Therefore, the OLS regression as an

instrument for testing this hypothesis is deemed to be adequately robust.

The results of the planning intervals that have been detailed thus far provide
insights into the length of time people employ in planning their pleasure trips. This
information is, of course, useful in timing tourism destination promotion across travel
seasons of the year, but it does not fiilly exploit the information content of the available
data base. Specifically, the three dates—when planning began, when destination was
selected, when trip began—have not been explored for any potentially useful information
they might contain to further refine a destination's travel advertising strategy. The date-
based analyses and results are reported below.

The distributions of planning and decision making dates were investigated using

the following three time segmentations: (1) three parts of a month--early (the first day of

99

the month through 10‘"), mid (11‘h to 20‘"), and end of a month (21St to the end of month),

(2) month, and (3) season.

WWII:

The frequency distributions derived from segmenting each month into three parts
are provided in Table 25 for the three dates of interest: (1) when planning began, (2)
when destination was selected, and (3) when trip began. As was found to be the case for
the frequency distributions of the total trip planning and post decision intervals, the
frequency distribution for the date planning began and the date a trip destination was
selected here again are quite similar. This similarity comes as no surprise since, as has
been discussed previously, the information processing interval plays only a very limited
role in overall trip planning behavior among this group of respondents.

An examination of detailed plots of frequencies of these dates reveals a clustering
of frequencies in the early and middle of each month. Relatively low frequencies for
dates of interest are evident for the end of most months. This pattern is more evident in
Table 26 which was derived by adding the frequencies for each monthly segment across
the full year. The one-sample chi-square test was employed to test the differences among

the frequencies of each variable.

100

Table 25. Relative frequencies of three different dates related to trip planning by three

 

 

 

 

 

 

 

 

 

 

 

 

 

 

segments of the month.
Segment of Month Date trip Date planning Date destination
began (%) began (%) selected (%)
(n=1266) (n=1266) (n=1266)
Janl through Jan 10 1.7 3.0 2.9
Janll through Jan 20 1.6 2.8 3.0
Jan21 through Jan 31 0.8 2.2 2.1
Febl through Feb 10 1.6 2.3 2.2
Feb 11 through Feb 20 2.4 2.0 1.9
Feb 21 through Feb 28 0.8 ~ 1.1 0.9
Mar 1 through Mar 10 1.1 2.3 2.2
Mar 11 through Mar 20 1.3 2.2 2.3
Mar 21 through Mar 31 0.7 1.4 1.5
Apr 1 through Apr 10 1.5 2.0 1.9
Apr 11 through Apr 20 1.3 2.1 2.3
Apr 21 through Apr 30 1.0 1.9 1.4
May 1 through May 10 2.2 4.0 4.0
May 11 through May 20 2.1 3.3 2.9
May 21 through May 31 2.4 2.6 2.8
Jun 1 through Jun 10 3.2 4.4 4.3
Jun 11 through Jun 20 3.8 3.9 3.7
Jun 21 through Jun 30 3.1 4.0 3.6
Jul 1 through Jul 10 7.2 5.0 5.2
Jul 11 through Jul 20 6.1 4.5 4.6
Jul 21 through Jul 31 2.9 3.1 3.4
Aug 1 through Aug 10 6.5 5.6 5.6
Aug 11 through Aug 20 7.5 4.9 4.6
Aug 21 through Aug 30 4.2 3.7 3.9
Sepl through Sep 10 5.8 3.7 3.7
Sep 11 through Sep 20 3.3 2.8 2.9
Sep 21 through Sep 31 2.3 3.8 3.8
Oct 1 through Oct 10 3.4 2.1 2.3
Oct 11 through Oct 20 4.0 ~ 2.2 3.0
Oct 21 through Oct 31 1.3 2.1 ‘ 1.8
Nov 1 through Nov 10 2.0 2.3 2.3
Nov 11 through Nov 20 2.4 1.7 1.6
Nov 21 through Nov 30 3.0 2.3 2.3
Dec 1 through Dec 10 1.8 1.0 1.0
Dec 11 through Dec 20 1.1 0.7 0.8
Dec 21 through Dec 31 2.8 0.9 1.1
Total 100.0 100.0 100.0

 

101

Table 26. Significance test of relative frequencies of trip
related dates by segment of month in which they
occur.

Segment of Date trip Date planning Date destination
month began (%) began (%) selected (%)

 

(n=1266) (n=1266) (n=1266)
Early (1-10) 38.0 37.7 37.6
Mid (1 1-20) 36.9 33.1 33.6
End (21-end) 25.3 29.1 28.6
Chi-square 43.1 18.5 21.9
Significance 0.000 0.000 0.000

 

During the early and mid segments of each month, 38% and 37% respectively of
all trips begin while only 25% begins during the end of month segment. Likewise, 38%
and 33% of trip planning begins during the early and mid-month segments while 29%
begins during the end of the month. Michigan pleasure travelers are also more likely to
make a final decision on trip destination during the early and mid-month periods (37.6%
and 33.6%) than they are at the end of the month (28.6%). The one-sample chi-square test
results reveal that the frequency distributions across the three segments of the month are
significantly different.

A possible explanation for these results may be the monthly cycle over which a
significant portion of the US. population receives income and distributes it to pay
monthly bills. A typical household, paid monthly, has more discretionary earnings
available early rather than late in the month and may be more inclined to take pleasure
trips as well as plan pleasure trips early in the month after the bills are paid and while the
checking account is near its monthly high. Another possible explanation is the fact that
two very popular holidays during which people take pleasure trips—the Fourth of July

and Labor Day— both occur during the beginning of the month.

102

Of these three possible explanations, it is possible to assess only the third with the
data set available. To determine if the Fourth of July and Labor Day holidays exert undue
influence on the observed results, the months of July and September were excluded and
the frequency distributions for all three study relevant dates (the date the trip began, trip
planning began, and trip destination was selected) were recalculated. The revised
frequency distributions for the three dates are reported in Table 27. The one-sample chi-
square test was again employed to test the differences among the frequencies for each
variable.

A clustering of frequencies early and in the middle of each month still exists in
the detailed plots of frequencies of the three dates which excluded the two holiday
months (July and September). And, relatively low frequencies for dates of interest are
still evident for the end of most months. This pattern is more evident in Table 28 which
was derived by adding the frequencies for each monthly segment across the full year.

The high frequencies at the early and middle segments of each month still exist
for the frequency distributions for the three dates when the July and September data are
excluded. The results of the one-sample chi-square test reveal that these differences are

statistically significant for each date.

103

Table 27. Relative frequencies of three different dates related to trip
planning by three segments of the month excluding July and

 

 

 

 

 

 

 

 

 

 

 

 

September.
Segment of Month Date trip Date planning Date destination
began (%) began (%) selected (%)
(n=966) (n=966) (n=966)

Janl through Jan 10 2.3 3.9 3.8
Janll through Jan 20 2.2 3.6 4.0
Jan21 through Jan 31 1.1 2.9 2.8
Febl through Feb 10 2.1 2.9 2.9
Feb 11 through Feb 20 3.4 2.6 2.5
Feb 21 through Feb 28 1.1 1.4 1.2
Mar 1 through Mar 10 1.5 2.9 2.8
Mar 11 through Mar 20 1.7 2.9 3.0
Mar 21 through Mar 31 1.0 1.8 1.9
Apr 1 through Apr 10 2.1 2.6 2.5
Apr 11 through Apr 20 1.7 2.8 3.0
Apr 21 through Apr 30 1.4 2.5 1.8
May 1 through May 10 3.0 5.2 5.2
May 11 through May 20 2.9 4.3 3.8
May 21 through May 31 3.4 3.3 3.6
Jun 1 through Jun 10 4.4 5.8 5.7
Jun 11 through Jun 20 5.3 5.1 4.9
Jun 21 through Jun 30 4.2 5.2 4.7
Aug 1 through Aug 10 8.9 7.2 7.3
Aug 11 through Aug 20 10.4 6.3 6.1
Aug 21 through Aug 31 5.7 4.8 5.1
Oct 1 through Oct 10 4.8 2.7 3.0
Oct 11 through Oct 20 5.5 2.9 3.9
Oct 21 through Oct 31 1.8 2.8 2.4
Nov 1 through Nov 10 2.7 3.0 3.0
Nov 11 through Nov 20 3.3 2.2 2.1
Nov 21 through Nov 30 4.1 3.0 3.0
Dec 1 through Dec 10 2.5 1.2 1.4
Dec 11 through Dec 20 1.6 0.9 1.1
Dec 21 through Dec 31 3.9 1.2 1.4
Total 100.0 100.0 100.0

 

104

Table 28. Significance test of relative frequencies of trip
related dates by segment of month that they occur-
excluding two months: July and September.

Segment of Date trip Date planning Date destination
month began (%) began (%) selected (%)

 

An=966) (n=966) (n=966)
Early (1-10) 34.3 37.4 37.6
Mid (1 1-20) 37.9 33.6 34.3
End (21-end) 27.7 29.0 28.0
Chi-square 9.62 13.83 15.98
Significance 0.008 0.001 0.000

 

The frequency distributions and one-sample chi-square test results are similar for
both cases: when including and excluding the two holiday months (July and September).
This finding suggests that these two very popular holidays are not dominant factors in
explaining the clustering at the early and middle segments of the month for the three
dates (the date the trip began, trip planning began, and trip destination was selected).

The other explanation—monthly patterns of financial income and outgo—might
influence the high frequencies at the early and the middle segments of the month. Or,
there may be other possible reasons that explain the high frequencies during the early and
middle segments of the month. However, exploring them is beyond the scope of this
study.

The differences of frequency percentages for both cases were compared by subtracting
the frequency percentages in Table 26 from Table 28. The differences are reported in
Table 29. The differences between the results with and without the two holiday months

(July and September) included are minimal.

105

Table 29. The differences of relative frequencies of trip
related dates by segments of month between the
data sets including and excluding the July and
September.

Segment of Date trip Date planning Date destination
month began (%) began (%) selected (%)

 

 

Early (1-10) -3.7 -0.3 0.0
Mid (1 1-20) 1.0 0.5 0.7
End (21-6116) 2.4 -0.1 -O.6

 

Monthly Analysis of Trip Related Planning Dates

The frequency distributions for the three relevant trip dates are plotted in Figure 9

and reported numerically in Table 30. The most frequently reported month in which trips

begin is August (18.1%) followed by July (16.2%), September (11.4%), and June

(10.2%). These are also the four most frequently reported months for beginning to plan

and to select a destination although in both cases June replaces September in the third

ranking position. Finally, as one might expect, trip planning is a more frequent activity

than is actual trip taking during the first six months of the year.

106

 

 

 

 

20% l
13°41 1
16% ‘
l4o/o "
o 12°/o d
to
53
c 10% 1
v
o
5 8%
C-
6%
4%
2°/o '1
00/3 I r I i r T j I r m f
Jan Feb Mar Apr May Jun July Aug Sept Oct Nov Dec
Months
[ +Date Trip Began +Date Planning Began “ Date Destination Selected

 

Figure 9. Frequency distribution plots for three trip related dates by month.

Table 30. Frequency distiibutions for three trip related dates by month.

 

 

Month Date trip Date planning Date destination
began (%) began (%) selected (%)
(n=1266) (n=1266) (n=1266)

Jan 4.1 8.0 8.1

Feb 4.8 5.4 5.1

Mar 3.0 5.9 5.9

Apr 3.7 6.1 5.6

May 6.7 9.9 9.7

Jun 10.1 12.4 11.6

July 16.2 12.5 13.3

Aug 18.1 14.1 14.2

Sept 11.4 10.3 10.4

Oct 8.8 6.4 7.0

Nov 7.3 6.4 6.2

Dec 5.7 2.6 3.0

Total 100.0 100.0 100.0

 

107

E lll'EI'EllEl'E

The frequency distributions for the relevant trip related dates are presented by
season in Figure 10 and Table 31. Based on the definitions of seasons used by the US.
Travel Data Center, the four seasons are as follows: December through February equal to
Winter, March through May equal to Spring, June through August equal to Summer, and
September through November equal to Fall.

Michigan pleasure travelers are more likely to begin to plan trips, make final
decisions on trip destinations, and begin to take trips during the summer season. Planning
begins and destinations are selected for 39% of all trips during the summer season, which
is also the season that 44.5% of trips begin. Fall is the second most popular season for all

of these activities.

108

50°/o T

45% ‘

40% ‘

35% "

30% '

25°10 "

 

A

20°11, ~

 

Percentage

.11.,

 

 

Winter Spring Summer Fall

Season

 

L +Date Trip Began +Date Planning Began . ~‘ Date Destination Selected ]

 

Figure 10. Frequency distribution plots for three travel related dates by season.

Table 31. Frequency distributions for three travel related dates by season.

 

 

Season Date trip Date planning Date destination
began (%) began (%) selected (%)
(n=1266) (n=1 266) (n=1 266)

Winter (Dec-Feb.) 14.1 16.0 16.2

Spring (Man-May) 13.9 21.8 21.2

Summer (Jun-Aug.) 44.5 39.0 39.0

Fall (Sept.-Nov.) 27.5 23.2 23.6

 

109

1‘ _ IqICW10_O' u'ic ini'qv: { i -1".

As discussed earlier, there have been arguments about whether or not to include
the VFR travel market in a destination's marketing strategy. Two data sets were used in
this study: the data set including the VFR market and the data set excluding the VF R
market. The same analyses were conducted for both data sets. The analyses included: the
duration and frequency distributions of trip planning intervals, two different decision
making approaches, and frequency distributions for study relevant dates. Separate
regression analyses were not performed because the VFR market was included as an
independent variable in the regression model fitted to the full data set. The results from
analyses of the data sets without and with the VFR market are presented in Appendix B.
The independent samples t-test and chi-square test were used to test for differences in
selected variables between the data sets with and without VFR market.

The summary of statistics for the three trip planning intervals (the total planning,
the post decision, and the information processing intervals) for the data sets without and
with the VFR market included are presented in Table B1 and B1-1 respectively. The
minimum, maximum, range, and median values of the trip planning intervals are identical
for the data sets with and without the VFR market.

The reported frequencies by six selected time intervals (0 days to 7 days, 8 days to
15 days, 16 days to 30 days, 31 days to 60 days, 60 days to 90 days, and over 90 days) for
the total trip planning and the post decision intervals for the two data sets are presented in
Table B4, and B4-1. The frequencies for the two data sets appears to be almost identical

across the six selected time intervals.

110

The frequency distributions for the information processing interval for the two
data sets (data sets without and with the VFR market included) are presented in Table BS
and B5-1. The frequency distributions of this interval for both data sets appears to be
almost identical across the information processing interval days. Comparing the
frequencies in zero information processing interval days, both data sets have very similar
frequencies. Almost 83% of respondents in the data set without the VFR market reported
, that they devoted zero days to the information processing interval, and almost 85% of
those in the data set with the VFR market included reported a zero information
processing interval.

The relative frequencies of trip related dates by three segments of the month (the
early, mid, and end of the month) for the data sets without and with the VF R market are
presented in Table B10 and 810-1, respectively. The frequencies for both data sets reveal

a clustering of frequencies in the early and middle parts of the month.

111

CHAPTER V

SUMMARY AND CONCLUSIONS

This final chapter summarizes and discusses the findings, implications of the
findings, some limitations of the study, and suggestions for further research. The

summary of the findings follows the order in which objectives are listed in Chapter I.

Summamfliesmts

Three planning intervals and three dates were defined based on the planning
behaviors of pleasure travelers. Recall that the total trip planning interval is the number
of days between the dates the trip planning began and the trip began; the post decision
making interval is the number of days between the dates trip destination was selected and
the trip began; and the information processing interval is the number of days between the
dates the trip planning began and the trip destination was selected. This study used these
study relevant time frames to explore the trip planning behaviors of Michigan pleasure

travelers. The summary of the findings of this study are as follows.

D .- .” 1” 1“] . 11".-” . r h” h .1 {1° ’_ ._ 0.'-

Michigan pleasure travelers, on the average, begin to plan about 70 days and
make final decisions on their trip destinations about 63 days prior to travelling. They
decide on their trip destinations, on average, only 7 days afier the beginning of trip

planning.

112

The most frequently reported total trip planning interval was one month (17.6%)
followed by one week (13.9%), two weeks (12.2%), two months (10.4%), one year
(8.8%), and three months (5.6%). The detailed intervals were grouped into six
meaningful segments based on the following frequently stated total trip planning
intervals: within one week, 8-15 days, 16-30 days, 31-60 days, 61-90 days, and over 90
days. Almost 29% of Michigan pleasure travelers begin to plan within one week of taking
their trip, and 64% begin to plan 30 days or less in advance of their trips. The higher
frequency of the total trip planning interval within one month of travel has been
confirmed by Gitelson and Crompton (1983). They found that the most frequently
reported total trip planning interval was one month (43.4%) followed by one to three
months (28.5%) and over three months (28.2%).

While a few studies were found which included the total trip planning interval,
very few studies were found which included the post decision interval. Perdue (1985)
included the timing of the destination decision in his inquiry-conversion study in
Nebraska and examined the relationship between the destination decision and the timing
of decisions (before or after receiving the information packet of Nebraska). However, he
did not provide information about when pleasure travelers make final decisions on their
trip destinations. The findings of this Michigan traveler study reveal when pleasure
travelers finally select their trip destinations. The most frequently reported length of the
post decision interval was also one month (16.7%) followed by one week (14.3%), two
weeks (11.8%), two months (9.0%), one year (7.7%), and one day (7.3%). Based on some
grouping of these intervals, almost 34% of respondents make final decisions on their trip

destinations within one week, and almost 68% of them do so within one month.

113

The information processing interval was found to be a surprisingly short—seven
days long—with a strongly skewed distribution toward zero. In fact, 85% of respondents
reported that the number of days between the date their trip planning began and the date
on which they selected their trip destinations was zero. The interval between when the
trip destination was selected and when the trip began was found to be about 63 days.
Thus, the total trip planning interval equal 70 days. The distributions for both of these
intervals along a 0-365 day axis is strongly skewed toward the zero pole with medians in

both cases of only 30 days.

The data set was divided into two groups of respondents: those who made the
final decision on their trip destinations on the same day as they began to plan their trips
(instant decision-makers) and those who made final decisions on trip destinations from
one day to several months after they began to plan their trips (hesitant decision-makers).
These two groups were profiled in terms of information sources and media habits, trip
characteristics, and socioeconomic characteristics. Instant decision-makers were found to
be more likely to rely on a travel agency as a source of information and to report
television as the most helpful media in selecting their pleasure trip destinations.

The primary purpose of travel for instant decision-makers was more likely to be
visiting friends or relatives and less likely to be outdoor recreation. Instant decision-
makers were not as action-oriented but were more likely to use a friend's or relative's
home as their main type of lodging during their pleasure trips. They were also more likely

to spend all nights at one place during trips.

114

Hesitant decision makers were more likely to consider their trips as vacation trips
and purchase a package, for which they paid one price, that included at least one night of

lodging.

'...111-i:11._..1c,-‘ _. . .r ”m. ... h t _. ”.1“ ”a 'v

A total of 25 independent variables were analyzed using OLS regression to assess
their significance in explaining variation in the dependent variable, the duration of the
total trip planning interval. Eight of the 25 were found to be statistically significant at the
95% level of confidence using a two-tailed t-test. The results show that the Michigan
pleasure travelers are likely to spend more time planning their trips when trips occur
during summer (June, July, and August), the trip party involves a larger number of
pleasure travelers, they participate in outdoor recreation, they attend a festival or event,
they consider their trips to be a vacation, they stay at a friend's or relative's home, or they
spend more nights and more money during their pleasure trip. Some of these significant
variables in explaining the variation of the total trip planning interval have been
confirmed in several previous studies. Rao et a1. (1992) found that the length of the total
trip planning interval was longer as pleasure travelers spend more money on their trips.
Fodness and Murray (1997) found that pleasure travelers are more likely to take a longer
total trip planning interval: for vacation trips, as length of stay increases, when they
visited more destinations, or when their trip expenditures are higher. They also found that
the length of the total trip planning interval decreases if pleasure travelers stay at the

unpaid lodging such as a friend's or relative's home.

115

While several previous studies have investigated variables that influence the
duration of the total trip planning interval, the impacts of these variables on variation in
the total trip planning interval have not been examined. The impacts of selected variables
on variation in total trip planning interval was examined in this study. The impacts of
independent variables on the duration of the dependent variable were compared using
standard coefficients (or beta coefficients). Party size was found to have the strongest
impact on the duration of the total trip planning interval followed by: trip was considered
a vacation, the number of nights spent in Michigan, trip was taken during peak season,
attended a festival or event, participated in outdoor recreation, and the amount of money
spent during the pleasure trip to Michigan.

The assumption of normality was tested using the Kolomogorov-Smirov test. Test
results revealed that the normality assumption was met. Multicolloinearity and singularity
were tested using the tolerance level test. High values of tolerance were found across all
independent variables, and this result suggests that multicollinearity was not problematic.

Using the OLS regression method in this study was questionable because the
dependent variable appears to be censored both at the lower and upper levels. Whether or
not this was indeed problematic was tested using the double bounded tobit model. The
double bounded tobit regression was applied to the same set of 25 variables and yielded
nearly identical results, which implies that the double censored nature of the dependent
variable had little, if any, impact on reported results. This is further evidence of the
robustness of OLS regression in estimating coefficients and testing hypotheses.

Internet use behavior was not included in the model because of the previously

discussed discrepancy in sampling time frames. Instead, the significance of these

116

variables in explaining the variation in the dependent variable was tested using the
independent sample t-test and one way ANOVA. Four variables were tested: whether or
not access to the Internet, whether or not use the Internet to obtain travel information,
whether or not access Travel Michigan's web site to obtain travel information, and the
degree of the Internet involvement. None of these variables were found to be statistically

significant.

An examination of detailed plots of the frequencies of the date: the trip planning
began, the trip destination was selected, and the trip began revealed a clustering of
frequencies early in the month. This was confirmed by tallying reported frequencies into
the following three segments of the month: early-day 1 to 10, mid-day 11 to 20, and late-
day 21 to end of month. Only 25% of respondents reported beginning trips in the late
segment of the months, whereas 38% and 37% began trips in the early and middle
segments, respectively. Only 29% of respondents made a destination decision or began to
plan a trip late in the month. The one-sample chi-square test was used to test results and
revealed that the frequencies of the three segments of the month were significantly
different for all of the three study relevant dates.

A possible explanation for these results may be the monthly cycle over which a
significant portion of the US. population receives income and distributes it to pay
monthly bills. A typical household, paid monthly, has more discretionary earnings
available early rather than late in the month and may be more inclined to travel as well as

plan travel early in the month after the bills are paid and while the checking account is

117

near its monthly high. Another possible explanation is the fact that two very popular
holidays during which people take pleasure trips—the Fourth of July and Labor Day—
both occur during the beginning of the month.

The popular holiday possible explanation was investigated. The two holiday
months (July and September) were excluded from the data set. Frequency distributions
and the one-sample chi-square were again calculated. The results were found to be quite
similar for both the data set with and without the holiday months included. Thus, holidays

do not explain the early to mid-month clustering observed in this data set.

R .1W'igi- W' it- V. "1 r10 a" {12V 1 1 .0'0,

As discussed earlier, DMOs vary in how they deal with the VFR market segment.
Many choose to ignore it under the assumption that targeting it in promotions is not cost
effective, while others develop specific strategies to attract VFR travelers. In any case,
the question as to how including VFR respondents in the analyses performed in this study
may have influenced results and related conclusions is both interesting and legitimate. In
order to resolve the VFR question and to report results relevant to DMOs who target or
ignore the VFR market, the full set of analyses was performed for both the with and
without VFR respondents data sets.

The same analyses were conducted for the two data sets (the data sets with and
without the VFR market). The analyses included: the duration and frequency distributions
of trip planning intervals, two different decision making approaches, and the frequency

distributions for study relevant dates.

118

The results from analyses of the data sets with and without the VFR market
included were found to be almost identical.

Differences between the two groups were minimal suggesting that either set of
results might be utilized by DMOs; however, the data set with VF R respondents is larger
and, therefore, results can be applied with slightly more confidence than those from the

smaller data set without VFR respondents included.

I 1 . [E l

The results were at considerable variance from the expectations and from those of
many if not most DMOs, based upon observations of the latter's advertising timing and
general marketing strategies. A couple of particularly noteworthy examples of variances
between current practice and what the results would appear to suggest as preferable

strategies are discussed in the following sections.

11"11 'I"

The time frames defined in this study provide information about when marketers
should distribute promotion programs or travel information. The planning intervals
provide information about the lengths of time periods underlying pleasure travelers'
decision making process. The lengths of the total trip planning, the post decision, and the
information processing intervals are especially useful for marketers who try to attract
pleasure travelers during specific time periods such as summer season travelers.
Marketers seeking to attract more pleasure travelers during non-peak seasons or event

managers seeking to attract more visitors are additional examples of applications of these

119

planning intervals. Suppose, for example, that the majority of the target market, say two
thirds, begins to plan within 30 days prior to travelling to attend an event. The event
manager should begin to distribute promotion programs or travel information about one
month prior to the event. Too early distribution, for example six months before the event,
may capture the attention of the portion of the target market that begins to plan six
months prior to travelling, but it will miss the majority of the target market. Or, too late
distribution, for example one week in advance, might again miss the majority of the
target market.

DMOs commonly schedule promotions to appear several months before a tourism
season begins and to end at the beginning of that season. For example, summer season
promotion in Michigan begins in March and ends in May. Given that the median total trip
planning interval is only 30 days, based upon the results of this study, promotional
messages placed to appear well into the summer season rather than in spring will reach a
greater percentage of people when they are most receptive to summer tourism promotion
messages.

While the planning interval results provide information to the marketers who try
to promote during specific time periods, other results will be of particular interest to
DMOs who promote on a year round basis. Marketers who promote such activities as
general touring, shopping, or casino gaming, which have little seasonal variation or time
limitations, are examples of year round promotion organizations. Such organizations will
find the planning behavior findings across the month of potential interest in timing their
monthly promotion strategies. For example, the findings that indicate pleasure travelers

tend to plan and take trips earlier in the month rather than at the end of the month

120

 

suggests following a similar pattern in releasing of promotion messages. Thus, the
findings of this study suggest that timing tourism promotional messages to appear early

rather the later in the month is likely to deliver a greater return on investment.

11"ElE'E"l'I"

Many DMOs devote a high proportion of their promotion budgets to generating
and fulfilling inquiries from prospective visitors engaged in what we have defined as the
information processing interval. Results from this study suggest that this interval is
nonexistent for the majority of travelers (85%), and more than half of the remaining small
minority select a destination within 21 days of requesting information. Clearly, prompt
response to inquiries is implied by these results. DMOs would also be advised to
reconsider how they allocate their promotion budgets between inquiry generating and

processing and their other promotion options.

SlI"'

The following were identified as. possible limitation for this study: (1)
nonresponse and refusal rates, (2) secondary nature of the data, (3) recall bias, and (4)

generalizability. Each is discussed below.

Nonresponseandkeflisalfiates

The response rate in this study, including partially-completed interviews, was
44%. The response rate, including only fully-completed interviews, was 35%. About 29%

of eligible potential respondents refused the interview. Although these are similar to

121

those achieved in most other telephone surveys conducted (Groves & Kahn, 1979; Steeh,
1981; and Wiseman & McDonald, 1979), they are nonetheless cause for concern since
one can not be assured that the sample population is necessarily representative of the
overall population of Michigan travelers. Nonresponse bias was assessed, and the results
indicate that differences between respondents and non-respondents is minimal. However,

there is no practical way to assess the potential of refusal bias.

W13

This study used survey data collected by the Travel, Tourism, and Recreation
Resources Center (TTRRC) at Michigan State University. The goal of the survey was to
estimate the effectiveness of Travel Michigan's advertising programs and the
characteristics and behavior of travelers in Travel Michigan's prime market area. The
questionnaire was designed for these survey goals not for the purpose of this study, which
was to provide information about the trip planning and decision making behaviors of
Michigan pleasure travelers. The data set collected via this questionnaire provide very
general information about trip planning and decision behaviors such as the time frames of
the trip planning and decision making behaviors. More specific information was not
obtained that could have contributed to fiilfilling the purposes of this study. More specific
information about trip planning and decision behaviors might have been collected which
would have yielded a richer and potentially higher quality data base than was available to
pursue the objectives of this study. The data available from the survey were extracted and

extrapolated from a selected few questions in a rather lengthy research instrument. A

122

more focused instrument would have offered the opportunity to pursue other aspects of

trip planning behavior in more depth and more directly.

ReealLBias

Respondents were asked to answer three study relevant questions: the number of
days they had taken to plan their pleasure trips and to make final decisions on their trip
destinations and the month and date when they began their trips. Their responses may
contain recall biases because it is hard for most respondents to recall the exact number of
days they actually devoted to trip planning and selecting the trip destinations or when
they travel. Although respondents may recall the number of days requested, they
probably provided approximations rather their specifics. For example, a respondent who
had taken 33 days for trip planning may answer one month.

Recall bias and the tendency to approximate to some unknown degree negatively

influenced the quality of reported results.

3 1’ 11'

The results from this study are based on subsamples drawn from the study region.
The study region was limited to the six states of Illinois, Indiana, Michigan, Minnesota,
Ohio, and Wisconsin and the province of Ontario in Canada. Further, the analyses of this
study were based on the pleasure travelers from the study region who visited Michigan
during the past 12 months. Therefore, the results of this study may not be universally
generalizable to the all pleasure travelers from all origins nor to all destinations. Other

origins or destinations may possess a degree of uniqueness with respect to the

123

distributions of their associated the trip planning intervals and dates. For example,
pleasure travelers who visit Florida may have longer trip planning intervals and different
distributions across time of year than those who visit Michigan. This in turn suggests that
the findings pertaining to any one destination state may not be generalizable to other
destination states. The limited study region, thus, is a limitation to generalizability of this

study's results.

WW

Based on the limitations of this study described previously, several further studies
are recommended. First, it is recommended to conduct similar studies using other survey
methods (e.g., mail survey) and survey instruments. As described previously, the quality
of the data set used for this study may have suffered due to a low response rate and a high
refusal rate. These problems may be due to the telephone survey method employed to
collect data and a long questionnaire. The telephone survey problems are being
exacerbated by: the proliferation of answering machines, fax machines, caller ID, and
telemarketing. These factors collectively appear to be lowering average response rates to
telephone surveys. Similar studies using other survey methods should be assessed for
their potential to mitigate response rate problems.

The questionnaire used for this study is too long for the purpose of the study
reported herein. The questionnaire contains 164 questions. Although no respondents were
asked all questions, the length of the questionnaire was still long. The length of interview
ranged from few seconds to twenty minutes, with an average length of twelve minutes.

The long questionnaire probably caused negative impacts on participation rates. Also, as

124

described previously, the questionnaire was not designed for this study. Therefore, a
considerable portion of the questionnaire were not directly related to this study. To
provide more specific information as well as to reduce the negative impact on the
participation rates, it is recommended to conduct surveys with shorter and well specified
questionnaire. Possible specific variables to be included in the further study are the time
frames of the trip planning and decision making behaviors on their types of
transportation, accommodation, and arrangement of travel. Including these variables in
further studies may provide information to the other tourism related marketers such as
airline agents, hotel/motel industries, and travel agents.

Second, it is recommended to conduct similar studies for other origins and
destinations. As described previous section, the limitations both on the origins and
destinations may cause some limitations in generalizability of this study. The origins
included in this study were limited as the six states (Illinois, Indiana, Michigan,
Minnesota, Ohio, and Wisconsin) and the province of Ontario, Canada. Also, the
destination was limited as Michigan. Therefore, the results of this study may not be
universally generalized to the all pleasure travelers. Comparing the results from analyses
of other origins and destinations with the results of this study may test the generalizability
of this study.

Although not described in the limitations of this study, the analyses of this study
were for the aggregate general pleasure travelers to Michigan. They did not focus on
specific submarkets such as summer season travelers, festival or event attendants, or
casino gamers. Often, marketers need to promote specific submarkets, however, an

overall average approach of this study may not fit these specific situations. Further

125

studies are recommended to provide the information about the trip planning behaviors of
these specific submarkets. For example, comparisons of trip planning and decision
making behaviors between festival or event attendants and other pleasure travelers may
provide useful promotion information to the marketers seeking effective promotion
program distribution schedule for attracting that submarket.

This study found a clustering of frequencies early in the month and presented
possible explanations for this phenomenon. However, these possible explanations are
based on the author's intuition. Further study should be done for investing the possible
reasons why people are likely to begin to take and plan their pleasure trips and decide trip
destination during the early and mid segments of month. Focus group study is one
example. The participants of focus group are to answer the reason why they are likely to

plan and travel during the early and mid segments of month.

126

APPENDIX A.

QUESTIONNAIRE

127

FINAL YEAR 3 CERTEC/SAPMINR PHONE SURVEY QUESTIONNAIRE 9/19/97
[ENTER INTERVIEWER CODE NUMBER] > _

[ENTER CODE NUMBER] >

[ENTER AREA CODE] > _

Hello, my name is .......... I'm calling from Michigan State University.

We're conducting a study on travel and tourism. We'd greatly appreciate your

help in answering a few questions about trips you've made. May I speak to the

adult over 17 years old who will have the next birthday? [IF THIS PERSON IS

NOT AT HOME, ASK TO SPEAK TO THE ADULT AT HOME WHO WILL HAVE
THE NEXT BIRTHDAY]

We're defining a "trip" as any overnight or day trip to a place at least 50
miles from your home, unless it was taken in commuting to work or school.

[ENTER GENDER OF RESPONDENT] > _
M=Male F=Female -99=Can't determine

[DOUBLE ENTRY REQUIRED]
1. Have you taken any kind of trip in the past 12 months? > _

1=Yes
2=No ----> GO TO QUESTION 149
-99=DK/NR ----> GO TO QUESTION 149

BEGIN INTRODUCTORY BLOCK

[READ OPTIONS 1-4; IF NECESSARY, PROBE FOR PRIMARY PURPOSE OF
TRIP]
2. Was your most recent trip primarily for the purpose of... > __

1=Visiting friends or relatives;

2=Recreation;

3=Business; or

4=Some other purpose? ----> ASK QUESTION 3
-99=DK/NR

3. And what would that purpose be?
>

 

128

We're defining a "pleasure trip" as any overnight or day trip to a place at
least 50 miles from your home that was made for your enjoyment, including
vacations, weekend getaways, shopping trips, and trips to visit fiiends or
relatives.

4. Have you taken a pleasure trip to Illinois in the past 3 years?
[CONTINUE FOR EACH STATE/PROVINCE: "How about ?]
1=Yes 2=No -99=DK/NR

 

Illinois > Ohio > _
Indiana > _ Wisconsin > _
Michigan > _ Ontario > _
Minnesota > _

[DO NOT READ LIST]

5. During the next 12 months, do you expect to take more, fewer, or about the
same number of pleasure trips as you did during the previous 12 months?
>

—1=More 2=Fewer 3=Same -99=DK/NR

[DO NOT READ LIST; ACCEPT UP TO 3 RESPONSES]
6. Where do you turn most often when you need information to help plan a
pleasure trip? >

 

ORGANIZATIONS OTHER _
1=Chamber of commerce 10=Friends/relatives/co-workers
2=Convention/visitors bureau 1 1=CD-ROM
3=State travel office/ 12=Highway welcome centers

call state 800 number l3=Internet/on-line service
4=Travel agency 14=Travel show

PUBLICATIONS
5=Magazine(s) 15=Other source
6=Travel section of newspaper l6=No source(s)
7=Mobil Travel Guide -99=DK/N R

8=AAA/CAA/auto club

publications
9=Other travel guide

129

[READ OPTIONS 1-4]
7. Which one of the following media has been most helpfiil to you in selecting
the destinations you have visited on pleasure trips? > __
1=Magazines;
2=Newspapers;
3=Television; or
4=Radio?
-99=DK/N R

8. How would you rate the desirability of Illinois as a pleasure trip
destination on a scale from 1 to 10, where 1 means "not at all desirable"
and 10 means "very desirable?"

[REPEAT FOR EACH REMAINING STATE/PROVINCE:

 

"How about ?"]
STATE/ RATING STATE/ RATING -99=DK/N R
PROVINCE [1-10] PROVINCE [1-10]
Illinois > _ Ohio > _
Indiana > _ Wisconsin >
Florida > _ Ontario > _
Michigan > _ Colorado >
Minnesota > _
END INTRODUCTORY BLOCK

BEGIN PROMOTIONAL AWARENESS AND RESPONSE BLOCK

9. In the past 12 months, have you seen or heard any advertisements promoting
travel to any destinations? > _

1=Yes
2=No ----> GO TO QUESTION 15
-99=DK/NR ----> GO TO QUESTION 15

[ENTER UP TO 5 PLACES; PROBE FOR STATES ASSOCIATED WITH
UNCOMMON PLACES; PROBE: Any other places?]

10. What places have you seen or heard ads for?

>

 

 

 

 

 

VVVV

 

130

[DON'T READ]

1=Michigan or a place in Michigan mentioned

2=Only non-Michigan places mentioned ----> GO TO QUESTION 15
-99=DK/NR ----> GO TO QUESTION 15

>

(ACCEPT 1-99)

11. About how many days ago did you last see or hear a Michigan travel ad?
> _ -99=DK/NR

12. On a scale from 1 to 10, where 1 means "poor" and 10 means "excellent,"

how would you rate the quality of the Michigan ads you've seen or heard?
> -99=DK/NR

[DO NOT READ LIST; PROBE TO FIT A CATEGORY]
13/ 14. Where did you most recently see or hear an ad promoting travel to

Michigan? > __ -99=DK/NR

1=TV 9=Direct mail advertisement

2=Radio lO=Intemet/on-line service

3=Newspaper 1 1=CD-ROM

4=Magazine 12=Chamber of commerce

5=Billboard/outdoors 13=Convention and visitors bureau
=Travel agent 14=Highway welcome center

7=Travel show 15=At the destination

8=Travel guide 16=Other

15. During the past 12 months, have you called any state or province's
toll-free number to request travel information? > _

1=Yes
2=No ----> GO TO QUESTION 17
-99=DK/NR ----> GO TO QUESTION 17

[ENTER ALL STATES/PROVINCES MENTIONED; PROBE: Any others?]

16. What states' or provinces' toll-free numbers have you called?
>

 

END PROMOTIONAL AWARENESS AND RESPONSE BLOCK
BEGIN MICHIGAN IMAGE BLOCK

131

[PROBE: What others come to mind?; ACCEPT UP TO 3 RESPONSES]

17. When you think of Michigan as a pleasure trip destination, what positive
impressions, if any, come to mind?

>

 

>

 

>

 

[PROBE: What others come to mind?; ACCEPT UP TO 3 RESPONSES]
18. And what negative impressions, if any, come to mind?
>

 

>

 

>

 

[ACCEPT UP TO 3 RESPONSES]

19. What, if any, tourism-related facilities, services, or opportunities do
you feel are missing in Michigan?

>

 

>

 

>

 

[ACCEPT UP TO 3 RESPONSES]
20. What types of winter recreation opportunities do you feel Michigan is

known for?
>

 

>

 

>

 

132

We'd like to know how much you agree or disagree with some statements about
Michigan. Please use a scale from 1 to 10, where 1 means you "do not agree
at all" and 10 means you "agree completely."

 

Michigan. . . -99=DK/NR

(ACCEPT 1-10 OR -99)
21. Is close enough for a weekend getaway ................................... > __
22. Has many interesting museums ............................................... > _
23. Is great for summer outdoor recreation activities.............. . . . . . ..> _
24. Is an exciting place to Visit> _
25. Has a lot of high quality lodging... ...> _
26. Offers much scenic appeal.... ...> _
27. Is great for winter outdoor reCreation activmifies... ...> _
28. Is a good place to meet friendly people... .. ....> _
29. Is a place everyone should visit at least once in their lifetime” ..>
30. Isasafe placeto visit... >_
31. Offers exciting nightlife and entertainment .............................. > __
32. Is a great place for a family vacation... ..> __
33. Is a popular destination with vacationers ..> _
34. Has many interesting historic sites... .. . . . . . . . . . .. > _
35. Offers an excellent vacation value fOr the money ...................... >

END MICHIGAN IMAGE BLOCK

Now we'd like to ask you about pleasure trips that you may have taken. Again,
we're defining "pleasure trips" as any overnight or day trips to places at

least 50 miles from your home that were made for your enjoyment, including
vacations, weekend getaways, shopping trips, and trips to visit friends or
relatives.

[DOUBLE ENTRY REQUIRED]
36. In the past 12 months, have you taken any pleasure trips to any
destination? > _

1=Yes

2=No ----> GO TO QUESTION 88
-99=DK/NR ----> GO TO QUESTION 88

133

(ACCEPT 1-999)
37. About how many pleasure trips have you taken in the past 12 months?
> __ pleasure trips

[IF RESPONDENT IS UNABLE TO GIVE A SPECIFIC NUMBER, PROBE2]
In the past 12 months, would you say you've taken. . .
2=1 to 3 pleasure trips?
5=4 to 6 pleasure trips?
8=7 to 9 pleasure trips?
15=10 to 20 pleasure trips?
25=More than 20 pleasure trips?
-99=DK/NR

[NOTE: USE CODES ONLY IF RESPONDENT DOESN'T GIVE A SPECIFIC
RESPONSE]

BEGIN ATTRACTIONS BLOCK

How interested would you be in the following tourism opportunities proposed
for development in Michigan, on a scale from 1 to 10, where 1 means you would

have "no interest at all," and 10 means you would be "extremely interested"?

(ACCEPT 1-10 OR -99)

38. Visiting a major amusement park like Cedar Point... . . . . . . . ..> _
39. Living and working on a working farm or orchard... .......> ____
40. Visiting a park on the Great Lakes with a submarine that would

take you to see shipwrecks dating back to the 18005.. .........> _
41. Taking a guided trip that would enable you to see wildlife in a

natural setting... ...>___
42. Learning to grow grapes and make wine on a wOrking vineyard....... . .> _
43. Visiting a major shopping, dining, and entertainment mall like

theMallofAmerica... >_
44. Learning country arts and Crafts on a working farm... . . . . . . . ...> _
45. Visiting a resort state park with lodging, dining, golfing,

swimming, boating, and hiking facilities... > _
46. Working with an archaeologist at an archaeolOgical dig ...> __
47. Hiking on a trail from one farm Bed & Breakfast to another

each of which would provide you with lodging and meals...... . . . . . . . ..> __

134

48. Have you attended any special events during the past 12 months while on
pleasure trips to places at least 50 miles from your home? These would be
any scheduled events that were open to the public, such as festivals,
fairs, shows, exhibitions, celebrations, sports events, performances,
competitions, and so on.

During the past 12 months, did you attend any special events while on
pleasure trips? > _

1=Yes
2=No ----> GO TO QUESTION 52
~99=DK/NR ----> GO TO QUESTION 52

[ACCEPT UP TO 5 RESPONSES]
49. Which types of special events did you attend while on these pleasure
trips?

 

 

 

 

VVVVV

 

50. Were any of these special events in Michigan? > _

1=Yes
2=No ----> GO TO QUESTION 52
-99=DK/NR ----> GO TO QUESTION 52

[ACCEPT UP TO 5 RESPONSES]

51. Which types of special events did you attend in Michigan?
>

 

 

 

 

VVVV

 

END ATTRACTIONS BLOCK
BEGIN MOST RECENT PLEASURE TRIP PROFILE BLOCK

Now I'd like to ask you about your most recent pleasure trip.

[PROBE FOR MONTH AND DAY; ENTER NUMERICAL VALUES FOR MONTH
AND DAY; IF NECESSARY, PROBE FOR BEST GUESS OF DAY]

135

52. Approximately when did this trip begin -- the month and day?

MONTH CODES
1=January 4=April 7=July 10=October
2=February 5=May 8=August 1 1=November
3=March =June 9=September 12=December
MONTH > __ DAY > _ -99=DK/NR

[ACCEPT UP TO 3 RESPONSES; PROBE FOR SPECIFIC PURPOSE(S),
ESPECIALLY IF RESPONDENT SAYS "VACATION"]

53. What was the purpose or purposes of this trip?
>

 

>

 

>

 

[ASK IF MORE THAN 1 PURPOSE MENTIONED; PROBE FOR SPECIFIC
PURPOSE, ESPECIALLY IF RESPONDENT SAYS "VACATION"]

54. What would you say was the primary purpose of this trip?

>

 

[DO NOT READ LIST; ACCEPT UP TO 3 RESPONSES]
55. What types of transportation did you use? > _ _ __

1=Car/truck without camping equipment
2=Car/truck with camping equipment
3=Self-contained recreation vehicle
4=Rental car
5=Airplane
6=Train
7=Ship/boat
8=Motorcyc1e
9=Bicycle
l 0=Motorcoach/Bus
l 1=Other
-99=DK/NR

56. Other

>

 

136

[IF RESPONDENT WAS ON A GROUP TOUR, PROBE FOR SIZE OF IMMEDIATE
TRAVEL PARTY AS OPPOSED TO SIZE OF ENTIRE GROUP]

(ACCEPT 1-99 OR -99)

57. How many persons, including yourself, were in your immediate travel

party? > __

[IF NECESSARY, PROBE FOR RESPONDENT'S BEST GUESS OF AGE]
(ACCEPT 1-130 FOR AGE VARIABLES)
58. Beginning with yourself, please give me the gender and age of each person

who went on this trip:

M=MALE F=FEMALE -55=REFUSED -99=DK/NR

GENDER AGE GENDER AGE

RESPONDENT > _ > _ PERSON #2 > _ > __

PERSON #3 > _ > _ PERSON #4 > _ > __

PERSON #5 > _ > _ PERSON #6 > _ > __

PERSON #7 > > __ PERSON #8 > > __
PERSON #9 > > PERSON #10 > >

59. Did your immediate travel party consist of family members only? > __

1=Yes 2=No -99=DK/NR

60. Was this an overnight or day trip? > _

1=Ovemight
2=Day trip ----> GO TO QUESTION 66
-99=DK/NR ----> GO TO QUESTION 66

(ACCEPT 1-999)

61. How many nights were you away from home? > __ -99=DK/NR
(ACCEPT 0-999; IF 0, SKIP NEXT 2 QUESTIONS)

62. How many nights did you spend in the state or province containing the
main destination of this trip? > _ -99=DK/NR

[ACCEPT UP TO 5 LOCATIONS]

63. In which locations did you spend these nights?
>

 

 

 

 

VVVV

 

137

(ACCEPT 0-999)

64. While you were in the state or province containing the main destination
of this trip, about how much, if anything, did you spend per night on
lodging in hotels, motels, Bed & Breakfasts, or rental cabins?
> $__ -99=DK/NR

[DO NOT READ LIST UNLESS NECESSARY TO STIMULATE RESPONSES]
65. What was the main type of lodging you used? > _ -99=DK/NR

l=Friend or relative's home

2=Hotel, motel, or lodge

3=Bed & Breakfast

4=Rented cabin, cottage, or condominium
5=Owned cabin, cottage, or condominium
6=County, state, or federal campground
7=Commercial campground (e.g., KOA)
8=Boat/ship

9=Other

[READ LIST]
66. Which, if any, of the following activities did you participate in?

1=Yes 2=No -99=DK/NR

Nightlife? ................................................. > _
Visit a state or national park? ..................... > __
Visit a museum or ball of fame? ................. > _
Visit an historic site? ................................. > _
Visit some other type of attraction? ............. > _
Explore a small city or town? ...................... > _
Dine at a unique restaurant? ........................ > _
Fall color touring outside of traveling to and from
your destination? .................................... >

General touring or driving for pleasure? ..... >
Visit a farmer's market or pick-your—own farm
or orchard? .............................................. >

Outdoor recreation? .................................... .>

138

[ACCEPT UP TO 5 RESPONSES]
(ASK IF OUTDOOR RECREATION AFFIRMED ABOVE)

67. What outdoor recreation activities did you participate in?
>

 

 

 

 

VVVV

 

68. Did you do any shopping on this trip? > __

1=Yes
2=No ----> GO TO QUESTION 72
-99=DK/N R ----> GO TO QUESTION 72

[ACCEPT UP TO 5 RESPONSES]

69. What types of places did you shop at?
>

 

 

 

 

VVVV

 

70. Did you plan to do any shopping before you left home on this trip? > __

1=Yes
2=No ----> GO TO QUESTION 72
-99=DK/NR ----> GO TO QUESTION 72

71. Was shopping the only reason for this trip, a primary reason for this
trip, or a secondary reason for this trip? >_

l=On1y 2=Primary 3=Secondary -99=DK/NR
72. Did you attend a festival or event on this trip? > __
1=Yes

2=No ----> GO TO QUESTION 75
-99=DK/NR "--> GO TO QUESTION 75

139

73. Did you plan to attend a festival or event before you left home on this
trip? > __

1=Yes
2=No ----> GO TO QUESTION 75
-99=DK/N R ----> GO TO QUESTION 75

74. Was attending a festival or event the only reason for this trip, a
primary reason for this trip, or a secondary reason for this trip? > _

l =Only 2=Primary 3=Secondary -99=DK/NR
75. Did you do any casino gaming on this trip? > _

1=Yes
2=No ----> GO TO QUESTION 78
-99=DK/NR ----> GO TO QUESTION 78

76. Did you plan to participate in casino gaming before you left home on this
trip? > __
1=Yes
2=No ----> GO TO QUESTION 78
-99=DK/NR ----> GO TO QUESTION 78

77. Was casino gaming the only reason for this trip, a primary reason for
this trip, or a secondary reason for this trip? > _

l=Only 2=Primary 3=Secondary -99=DK/NR

(ACCEPT 0-999999 OR -99)

78. What would be your best estimate of how much your immediate travel party
spent altogether while in the state or province containing the main
destination of this trip? > S -99=DK/NR

79. Was this a vacation trip? > __
1=Yes 2=No -99=DK/NR
[ENTER RESPONSE, E.G., 90 DAYS, 2 WEEKS, 3 MONTHS]

80. About how far in advance of this trip did you begin to make plans for it?
>

 

140

[ENTER RESPONSE, E.G., 90 DAYS, 2 WEEKS, 3 MONTHS]
81. About how far in advance of this trip did you make a final decision about
where to go? >

 

82. Were any of the travel arrangements for this trip made by a travel agent?
>

1=Yes 2=No -99=DK/N R

83. For this trip, did you purchase a package, for which you paid one price,
that included at least one night of lodging? > __

1=Yes 2=No -99=DK/NR

84. What did you least enjoy about this trip?
>

 

85. And what did you most enjoy about this trip?
>

 

END MOST RECENT PLEASURE TRIP PROFILE BLOCK
[IF NECESSARY, PROBE FOR CITY/PLACE FARTHEST FROM HOME]
86. What was the main destination of this trip?

City/Place: >

 

State/Province/Country: >

 

[DON'T READ; DOUBLE ENTRY REQUIRED]
1=Michigan destination ----> GO TO QUESTION 125

2=Non-Michigan destination
>

[DOUBLE ENTRY REQUIRED]
87. Was a place in Michigan the main destination of any of the pleasure trips
you've taken in the past 12 months? > _

1=Yes ----> GO TO QUESTION 90

2=No
-99=DK/NR

141

88. Have you ever taken a pleasure trip to a place in Michigan? > __

1=Yes
2=No ----> GO TO QUESTION 140
[PROBE FOR YEAR; ENTER LAST TWO DIGITS OF YEAR]

89. When was the last time you took a pleasure trip to a place in Michigan?
> 19__ -99=DK/NR

GO TO QUESTION 140
BEGIN GENERAL MICHIGAN PLEASURE TRIP PROFILE BLOCK

90. Now I'd like to ask you about your most recent pleasure trip in Michigan.

[IF NECESSARY, EXPLAIN THAT WE NEED A PROFILE OF THEIR MOST
RECENT PLEASURE TRIP IN MICHIGAN AS WELL AS THEIR MOST RECENT
PLEASURE TRIP IN GENERAL]

[PROBE FOR MONTH AND DAY; ENTER NUMERICAL VALUES FOR MONTH
AND DAY; IF NECESSARY, PROBE FOR BEST GUESS OF DAY]
Approximately when did this trip begin -- the month and day?

MONTH CODES
1=January 4=April 7=July 10=October
2=February 5=May 8=August 11=November
3=March 6=June 9=September 12=December

MONTH > _ DAY > _ -99==DK/NR

[ACCEPT UP TO 3 RESPONSES; PROBE FOR SPECIFIC PURPOSE(S),
ESPECIALLY IF RESPONDENT SAYS "VACATION"]
91. What was the purpose or purposes of this trip?

>

 

>

 

>

 

[ASK IF MORE THAN 1 PURPOSE MENTIONED; PROBE FOR SPECIFIC
PURPOSE, ESPECIALLY IF RESPONDENT SAYS "VACATION"]

92. What would you say was the primary purpose of this trip?
>

 

142

[DO NOT READ LIST; ACCEPT UP TO 3 RESPONSES]
93. What types of transportation did you use? > _ __ _

1=Car/truck without camping equipment

2=Car/truck with camping equipment

3=Self-contained recreation vehicle

4=Rental car

5=Airplane

6=Train

7=Ship or boat

8=Motorcycle

9=Bicycle

1 0=Motorcoach/Bus

11=Other ----> ENTER UNDER QUESTION 94
-99=DK/NR

94. Other
>

 

[IF RESPONDENT WAS ON A GROUP TOUR, PROBE FOR SIZE OF IMMEDIATE
TRAVEL PARTY AS OPPOSED TO SIZE OF ENTIRE GROUP]

(ACCEPT 1-99)

95. How many persons, including yourself, were in your immediate travel

party? > _

[IF NECESSARY, PROBE FOR RESPONDENT'S BEST GUESS OF AGE]
96. Beginning with yourself, please give me the gender and age of each person
who went on this trip:

M=MALE F=FEMALE -55=REFUSED -99=DK/NR

GENDER AGE GENDER AGE
RESPONDENT > _ > __ PERSON #2 > _ > _
PERSON #3 > __ > _ PERSON #4 > __ > _
PERSON #5 > _ > _ PERSON #6 > _ > _
PERSON #7 > > _ PERSON #8 > _ > __
PERSON #9 > > PERSON #10 > _ >

97. Did your immediate travel party consist of family members only? > _

1=Yes 2=No -99=DK/NR

143

98. Was this an overnight or day trip? > _ ‘

1=Overnight
2=Day trip ----> GO TO QUESTION 104
-99=DK/NR ----> GO TO QUESTION 104

(ACCEPT 1-999)
99. How many nights were you away from home? > _ -99=DK/N R

(ACCEPT 0-999; IF 0, SKIP NEXT 2 QUESTIONS)
100. How many nights were spent in Michigan? > _ -99=DK/NR

[ACCEPT UP TO 5 LOCATIONS]

101. In which locations in Michigan did you spend these nights?
>

 

 

 

 

VVVV

 

(ACCEPT 0-999)

102. While in Michigan, about how much, if anything, did you spend per night
on lodging in hotels, motels, Bed & Breakfasts, or rental cabins?
> $__ -99=DK/NR

[DO NOT READ LIST UNLESS NECESSARY TO STIMULATE RESPONSES]
103. What was the main type of lodging you used? > _

1=Friend's or relative's home
2=Hotel, motel, or lodge
3=Bed & Breakfast
4=Rented cabin, cottage, or condominium
5=Owned cabin, cottage, or condominium
6=County, state, or federal campground
7=Commercial campground (e.g., KOA)
8=Boat/ship
9=Other

-99=DK/NR

144

[READ LIST]
104. Which, if any, of the following activities did you participate in?

1=Yes 2=No -99=DK/NR

Nightlife?... >_
Visit a state or mnational park? ............> _
Visit a museum or hall of fame? ..................... > _
Visit an historic site?" . . . . . . . ..> _
Visit some other type of attraction? ................ > __
Explore a small city or town? ......................... > __
Dine at a unique restaurant? ........................... >
Fall color touring outside of traveling to and from

your destination?" ... .......> ____
General touring or driving fOr pleaSure? ......... > _
Visit a farmer's market or pick-your-own farm

or orchard? > _
Outdoor recreation? ....................................... >

[ACCEPT UP TO 5 RESPONSES]
(ASK IF OUTDOOR RECREATION AFFIRMED ABOVE)
105. What outdoor recreation activities did you participate in while you were

VVVVV

in Michigan?

 

 

 

 

 

106. Did you do any shopping on this trip? > _

1=Yes
2=No ----> GO TO QUESTION 110

-99=DK/NR ----> GO TO QUESTION 110

[ACCEPT UP TO 5 RESPONSES]

107. What types of places did you shop at?

>

VVVV

 

 

 

 

 

145

108. Did you plan to do any shopping before you left home on this trip? > _

1=Yes
2=No ----> GO TO QUESTION 110
-99=DK/NR ----> GO TO QUESTION 110

109. Was shopping the only reason for this trip, a primary reason for this
trip, or a secondary reason for this trip? >_

l=Only 2=Primary 3=Secondary -99=DK/NR
1 10. Did you attend a festival or event on this trip? > _

1=Yes
2=No ----> GO TO QUESTION 113
-99=DK/NR ----> GO TO QUESTION 113

1 11. Did you plan to attend a festival or event before you lefi home on this
trip? > _
1=Yes
2=No ----> GO TO QUESTION 113
-99=DK/NR ----> GO TO QUESTION 113

112. Was attending a festival or event the only reason for this trip, a
primary reason for this trip, or a secondary reason for this trip? > _

1=Only 2=Primary 3=Secondary -99=DK/NR
1 13. Did you do any casino gaming on this trip? > _

1=Yes
2=No ----> GO TO QUESTION 116
-99=DK/NR ----> GO TO QUESTION 116

1 14. Did you plan to participate in casino gaming before you left home on
this trip? > ______
1=Yes
2=No ----> GO TO QUESTION 116
-99=DK/NR ----> GO TO QUESTION 116

115. Was casino gaming the only reason for this trip, a primary reason for
this trip, or a secondary reason for this trip? > _

1 =Only 2=Primary 3=Secondary -99=DK/N R

146

(ACCEPT 0-999999)
116. What would be your best estimate of how much your immediate travel party
spent altogether on this trip while in Michigan? > $ -99=DK/NR

117. Was this a vacation trip? > __
1=Yes 2=No -99=DK/NR
[ENTER RESPONSE, E.G., 90 DAYS, 2 WEEKS, 3 MONTHS]

1 18. About how far in advance of this trip did you begin to make plans for
it? >

 

[ENTER RESPONSE, E.G., 90 DAYS, 2 WEEKS, 3 MONTHS]
119. About how far in advance of this trip did you make a final decision
about where to go? >

 

120. Were any of the travel arrangements for this trip made by a travel
agent? > _

1=Yes 2=No -99=DK/NR

121. For this trip, did you purchase a package, for which you paid one price,
that included at least one night of lodging? > _

1=Yes 2=No -99=DK/NR

122. What did you least enjoy about this trip?
>

 

123. And what did you most enjoy about this trip?
>

 

[IF NECESSARY, PROBE FOR CITY/PLACE FARTHEST FROM HOME]
124. What was the main destination of this trip?

City/Place in Michigan: >

 

END GENERAL MICHIGAN PLEASURE TRIP PROFILE BLOCK
BEGIN INFLUENCE BLOCK

147

125. Before you left home for this most recent pleasure trip in Michigan, did
you see or hear any advertisements about travel in Michigan? > __

1=Yes
2=No ----> GO TO QUESTION 136
-99=DK/NR ----> GO TO QUESTION 136
126. Did you see or hear 1 ad or more than 1 ad about travel in Michigan? > _

1=1 ad
2=More than 1 ad ----> [USE THE PHRASE "THESE ADS" RATHER THAN
-99=DK/NR "THIS AD" IN QUESTIONS IN THIS SECTION]

[DO NOT READ LIST; ACCEPT UP TO 3 RESPONSES; PROBE FOR ANSWERS]
127. Where did you see or hear this (these) ad(s) about travel in Michigan?

 

> -99=DK/NR
1=TV 8=Direct mail advertisement
2=Radio 9=Internet/on-line service
3=Newspaper 10=CD-ROM
4=Magazine 1 1=Chamber of commerce
5=Billboard/outdoors 12=Convention and visitors bureau
6=Travel agent 13=Highway welcome center
7=Travel show 14=State of Michigan publication

15=Other

128. Did this (these) ad(s) have no influence, a partial influence, or a
primary influence on your decision to travel in Michigan? > _

1=No influence 3=Primary influence
2=Partial influence -99=DK/NR

129. Did this (these) ad(s) promote travel to a specific destination in
Michigan or travel to Michigan in general? > _

1=Trave1 to a specific destination in Michigan
2=Travel to Michigan in general ----> GO TO QUESTION 131
-99=DK/NR ----> GO TO QUESTION 131

130. Which destination in Michigan?
>

 

148

131. Did you contact the organization that sponsored this (these) ad(s) to
request additional travel information? > _

1=Yes ---—> GO TO QUESTION 134
2=No
-99=DK/NR
132. Did you contact any other organization to obtain travel information
about Michigan? > _

1=Yes
2=No ----> GO TO QUESTION 136
-99=DK/NR ----> GO TO QUESTION 136

133. What organization did you contact?
>

 

134. Did you receive the information you requested before you left home for
your trip? > _

1=Yes
2=No ----> GO TO QUESTION 136
-99=DK/NR ----> GO TO QUESTION 136

135. Did the information on Michigan you received have no influence, a
partial influence, or a primary influence on your decision to travel in
Michigan? > _

1=No influence 3=Primary influence
2=Partial influence -99=DK/NR

END INFLUENCE BLOCK
BEGIN MICHIGAN PLEASURE TRIP HISTORY BLOCK

136. Was this most recent pleasure trip in Michigan the first pleasure trip
you've ever taken in this state? > _ .

1=Yes ----> GO TO QUESTION 140

2=No
-99=DK/NR

149

(ACCEPT 1-200; IF 1, GO TO QUESTION 140)
137. About how many pleasure trips to places in Michigan have you taken in
the past 12 months? > _ pleasure trips

[IF RESPONDENT IS UNABLE TO GIVE A SPECIFIC NUMBER, PROBE:]
In the past 12 months, would you say that you've taken. . .
2=1 to 3 pleasure trips?
5=4 to 6 pleasure trips?
8=7 to 9 pleasure trips?
15=10 to 20 pleasure trips?
25=More than 20 pleasure trips?
-99=DK/NR
[NOTE: USE CODES ONLY IF RESPONDENT DOESN'T GIVE A SPECIFIC
RESPONSE]

138. Did any of these pleasure trips in Michigan take place on holidays?
>
1=Yes
2=No ----> GO TO QUESTION 140
-99=DK/NR ----> GO TO QUESTION 140

[DO NOT READ LIST]

139. On which holidays did these pleasure trips in Michigan occur?
>

 

1=Martin Luther King Day 8=Labor Day

2=Washington's Birthday =Yom Kippur
3=Easter/Good Friday 10=Thanksgiving
4=Mother's Day 11=Christmas/New Years
5=Memorial Day 12=Other holiday(s)
6=Father's Day -99=DK/NR

7=Fourth of July

END MICHIGAN PLEASURE TRIP HISTORY BLOCK
BEGIN MICHIGAN TRAVEL EXPECTATIONS BLOCK

140. During the next 12 months, do you plan to take any pleasure trips to
places in Michigan? > _

1=Yes

2=No ----> GO TO QUESTION 143
-99=DK/NR

150

[DO NOT READ LIST]

141. Compared to the preceding 12 months, during the next 12 months do
you expect to take more, fewer, or about the same number of pleasure
trips in Michigan? > _

1=More 2=Fewer 3=Same -99=DK/NR
142. Do you plan to take any pleasure trips in Michigan. . .
1=Yes 2=No -99=DK/NR

This fall? > _
How about this Thanksgiving? > _
How about this Christmas or New Years? > __

END MICHIGAN TRAVEL EXPECTATIONS BLOCK
BEGIN MICHIGAN TRIP VOLUME BLOCK

143. Now we'd like to find out how many trips you may have recently taken in
Michigan. Here we'd like to get information on any kind of trips you may
have taken in Michigan, including business trips.

[RESPONSE SHOULD INCLUDE ANY TRIPS RESPONDENT MAY HAVE
ALREADY TOLD YOU ABOUT]
(ACCEPT 0-100; IF 0 OR -99, GO TO QUESTION 149)
How many trips of any kind to places in Michigan have you taken that
occurred wholly or partially during [MONTH PRECEDING CURRENT MONTH]?
> trips -99=DK/NR

 

[IF MORE THAN 1 TRIP WAS TAKEN, SAY: I'd like to ask you about the most
recent trip that occurred wholly or partially during [MONTH PRECEDING
CURRENT MONTH]

144. Was this trip primarily for the purpose of conducting business or
attending a convention, seminar, or meeting? >

1=Yes ----> GO TO QUESTION 146

2=No
-99=DK/NR

151

145. Was this trip primarily for some purpose other than business or
pleasure, such as moving a household, or going to a funeral or wedding
in another city? > _

1=Yes
2=No ----> GO TO QUESTION 149
-99=DK/NR ----> GO TO QUESTION 149

146. Was this an overnight or day trip? > _

1=Ovemight
2=Day trip ----> GO TO QUESTION 149
-99=DK/NR ----> GO TO QUESTION 149

(ACCEPT 0-999)
147. How many nights were spent in Michigan? > _ -99=DK/NR

[DO NOT READ LIST UNLESS NECESSARY TO STIMULATE RESPONSES]
148. What was the main type of lodging you used? > _

l=Friend or relative's home

2=Hotel, motel, or lodge

3=Bed & Breakfast

4=Rented cabin, cottage, or condominium

5=Owned cabin, cottage, or condominium
=County, state, or federal campground
=Commercial campground (e.g., KOA)

‘ 8=Boat/ship
9=Other
-99=DK/NR

END MICHIGAN TRIP VOLUME BLOCK
BEGIN PERSONAL/HOUSEHOLD CHARACTERISTICS BLOCK

149. To conclude, we'd like to ask just a few questions to help us classify
your answers.

In what city do you live? >

 

150. And your state or province? >

 

151. And your zip or postal code? >

 

152. In what county do you live? >

 

152

[READ LIST]
153. Do any of the following types of persons live in your household?

1=Yes 2=No -55=Refused -99=DK/NR

Pre-school child? > _

School-age child under age 18? > __
Senior citizen? > _

Handicapped person? > __

(ACCEPT 1-99 OR -99)
154. How many persons, including yourself, live in your household? > _

(ACCEPT 1-99 OR -99)

155. How many adults over age 17, including yourself, live in this household?
>

(ACCEPT 0-99)
156. How many full-time wage-eamers live in your household? > _
-55=Refused -99=DK/NR

[READ LIST; ACCEPT UP TO 2 RESPONSES]
157. Are you ...... >

1=Employed fiIll-time; 5=A homemaker;
2=Employed part-time; 6=A student; or
3=Retired; =In some other employment situation?
4=Not employed; -55=Refused
-99=DK/NR

158. What racial or ethnic group do you belong to?

> .

 

-55=Refused -99=DK/N R

159. The median household income is $31,000. Would you say your total

household income before taxes in 1996 was above or below the median?
>

1=Above the median

2=Below the median ----> GO TO QUESTION 161
-55=Refiised [DO NOT READ] ----> GO TO QUESTION 161
-99=DK/NR ----> GO TO QUESTION 161

153

160. Was your total household income above $50,000? > _

1=Yes 2=No -55=Refused -99=DK/NR

161. Do you or any member of your household have access to the Internet?
>

1=Yes

2=No ----> GO TO QUESTION 164
~55=Refused ----> GO TO QUESTION 164
-99=DK/NR ----> GO TO QUESTION 164

162. During the past 12 months, have you or any member of your household used
the Internet to obtain travel information? > _

1=Yes

2=No ----> GO TO QUESTION 164
-55=Refused ----> GO TO QUESTION 164
-99=DK/NR ----> GO TO QUESTION 164

163. During the past 12 months, have you or any member of your household used
the Michigan Travel Bureau's site on the World Wide Web to obtain travel
information? > _

1=Yes 2=No -55=Refused -99=DK/NR
END PERSONAL/HOUSEHOLD CHARACTERISTICS BLOCK
164. That's all the questions I have. Thank you very much for your time! Have

a good evening!

[TERMINATE]

154

APPENDIX B

RESULTS EXCLUDING THE VISITING FRIENDS AND RELATIVES (VFR)
MARKET

155

Table B 1. Summary of statistics for the three planning

 

intervals (VFR excluded).
Total trip Post Information
planning decision processing
interval interval interval

(n=1034) (n=1034) (n=1034)

Minimum 0.0 0.0 0.0
Maximum 365 365 363
Range 365 365 363
Mean 76.5 68.4 8.2
Median 30.0 30.0 0.0
Standard
deviation 109.1 104.3 34.9

 

Table Bl-l. Summary of statistics for the three
planning intervals (VFR included).

 

Total trip Post Information
planning decision processing
interval interval interval

(n=1476) (n=1476) (n=1476)

Minimum 0.0 0.0 0.0
Maximum 365 365 363
Range 365 365 363
Mean 70.1 63.3 6.9
Median 30.0 30.0 0.0
Standard
deviation 104.4 100.3 3 l . 1

 

156

Table B2. Frequency distributions for total trip
planning interval (VFR excluded).

 

 

Length of Percent of Cumulative
planning interval respondents Percent
(Days) (n=1034) Q1=1034)
less than 24 hours 2.6 2.6
1 5.0 7.6
2 3.7 11.3
3 2.0 13.3
4 0.5 13.8
5 0.4 14.2
7 13.5 27.7
10 0.1 27.8
11 0.1 27.9
14 10.9 38.8
21 3.9 42.7
28 0.2 42.9
30 17.6 60.5
35 0.1 60.6
42 1.3 61.9
45 0.3 62.3
56 0.1 62.4
60 10.1 72.5
70 0.2 72.7
75 0.1 72.8
90 6.1 78.9
120 3.5 82.4
150 0.9 83.4
180 5.2 88.6
210 0.3 88.9
240 0.5 89.4
270 0.4 89.8
300 0.1 90.0
360 0.1 90.0
364 0.1 90.1
365 9.9 100.0
Total 100.0

 

157

‘-

Table B3. Frequency distributions for post
decision interval (VFR excluded).
Length of post Percent of Cumulative
decision interval respondents Percent

 

 

(Days) (n=1034) (n=1034)
less than 24 hours 3.6 3.6
l 7.5 11.1
2 4.3 15.3
3 2.2 17.6
4 0.7 18.3
5 0.7 18.9
7 13.9 32.9
10 0.2 33.0
11 0.1 33.2
14 10.8 44.0
21 3.8 47.9
28 0.2 48.1
30 17.2 65.3
35 0.1 65.4
42 1.2 66.6
45 0.3 67.0
56 0.1 67.1
60 8.5 75.6
70 0.2 75.8
90 5.2 81.0
120 3.3 84.3
150 0.7 85.0
180 5.0 90.0
210 0.3 90.4
240 0.5 90.8
270 0.3 91.1
300 0.3 91.4
360 0.1 91.5
364 0.1 91.6
365 8.4 100.0

Total 100.0

 

158

Table B4. Reported frequencies by selected time
intervals for the total trip planning and post
decision interval (VFR excluded).

Time interval Total trip planning Post decision

 

(Days) interval interval
(n=1034) @1034)

0-7 27.7% 32.9%
8-15 11.1% 11.1%
16-30 21.7% 21.3%
31-60 12.0% 10.3%
61-90 6.4% 5.4%
Over 90 21.1% 19.0%

 

Table B4-1. Reported frequencies by selected time
intervals for the total trip planning and
post decision interval (VFR included).

Time interval

Total trip planning Post decision

 

(Days) interval interval
(n=1476) (n=1476)

0-7 28.9% 33.9%
8-15 12.4% 12.1%
16-30 22.2% 21 .5%
31-60 12.0% 10.6%
61 -90 5.9% 5.0%
Over 90 ' 18.7% 16.9%

 

159

Table B5. FrecLency distributions for information processing interval (VFR excluded).

 

 

 

160

 

Length of Percent of Cumulative Length of Percent of Cumulative
information respondents Percent information respondents Percent
processing processing

interval (Days) (n=1034) (n=1034) interval (n=1034) (n=1034)
(Dar/S)

0 83.91761 83.91761 65 0.136516 96.61701
1 0.5122 84.42981 69 0.202987 96.82
2 0.574168 85.00398 76 0.129692 96.94969
3 0.422375 85.42636 83 0.049714 96.9994
4 0.152356 85.57871 89 0.210964 97.21037
5 0.076666 85.65538 90 0.406068 97.61644
6 1.123014 86.77839 95 0.154837 97.77127
7 1.880661 88.65905 99 0.098406 97.86968
9 0.299179 88.95823 1 19 0.126292 97.99597

11 0.083518 89.04175 120 0.409612 98.40558

12 0.541179 89.58293 150 0.398832 98.80442

13 0.216503 89.79943 180 0.055438 98.85985

14 0.348338 90.14777 185 0.552083 99.41 194

15 0.158207 90.30598 335 0.15758 99.56952

16 0.801957 91.10793 351 0.263914 99.83343

18 0.086981 91.19491 362 0.082491 99.91592

19 0.139807 91.33472 363 0.084078 100

20 0.078213 91.41293 Total 100

21 0.156545 91.56948

23 0.370921 91.9404

27 0.054553 91.99495

28 0.117026 92.11198

29 0.630779 92.74276

30 1.561171 94.30393

37 0.083518 94.38745

39 0.2973 94.68475

40 0.0539 94.73865

46 0.567771 95.30642

53 0.404943 95.71136

57 0.087098 95.79846

58 0.062226 95.86069

 

Table B5-1. Frequency distributions for information processing interval (VFR included).

 

 

 

 

 

Length of Percent of Cumulative Length of Percent of Cumulative
information respondents percent information respondents percent
processing processing

interval (Days) (n=1476) (n=1476) interval (Days) (n=1476) (n=1476)

0 85.1 85.1 65 0.1 97.7
1 0.5 85.6 69 0.2 97.9
2 0.7 86.3 76 0.1 98.0
3 0.4 86.7 83 0.0 98.0
4 0.2 86.9 89 0.1 98.1
5 0.2 87.1 90 0.4 98.5
6 0.9 88.0 95 0.1 98.6
7 1.7 89.7 99 0.1 98.6
9 0.3 90.0 106 0.1 98.6

11 0.1 90.1 119 0.1 98.6

12 0.6 90.7 120 0.4 99.0

13 0.3 91.0 150 0.3 99.3

14 0.3 91.3 155 0.1 99.4

15 0.1 91.4 180 0.0 99.4

16 0.7 92.1 185 0.4 99.7

18 0.1 92.2 305 0.0 99.7

19 0.2 92.4 335 0.1 99.8

20 0.1 92.5 351 0.2 99.9

21 0.1 92.6 362 0.1 99.9

23 0.4 93.0 363 0.1 100.0

25 0.1 93.1

27 0.2 93.3

28 0.2 93.5

29 0.4 93.9

30 1.6 95.5

35 0.1 95.6

37 0.1 95.7

39 0.3 96.0

40 0.0 96.0

42 0.1 96.1

46 0.4 96.5

53 0.4 96.9

57 0.1 97.0

58 0.2 97.2

60 0.4 97.6

161

Table B6. Sources of information and media habits of instant and hesitant decision-

 

 

makers (VFR excluded).
All Instant Hesitant
Pleasure Decision- Decision- Test
Variable Travelers Makers Makers Statistic Significance
InfonmtiIInSIImMQst
Emmi]! 1
WWII. 021.1882 11.832= n__1.62=
AAA/CAA 25.9% 26.3% 23.9%
Travel agency 1 7.7% 18. 1% 15.7%
F riends/relatives/co-workers 18.8% 1 7. 1% 27.5%
Chamber of commerce 5.0% 5.0% 4.8%
Other travel guide 5.4% 5.3% 5.8%
Magazine 4.2% 4.1% 5.0%
Intemet/online service 8.2% 7.9% 9.5%
State travel office 3.5% 3.3% 4.6%
Travel section of newspaper 2.4% 2.4% 2.3%
Convention/visitors bureau 1.3% 1.1% 2.4%
Mobil Travel Guide 1.8% 2.0% 1.1%
Highway welcome centers 0.5% 0.5% 0.5%
Travel show 0.2% 0.2% 0.6%
CD-ROM 0.1% 0.1% 0.0%
Other source 10.2% 10.2% 10.3%
No source 12.9% 13.5% 9.7%
”1.: .1 111 11151
WWW 1128119 n26812 112121 x2 = 10.54 0.014
Magazine 55.3% 55.7% 53.2%
Newspaper 22.9% 2 1 .2% 3 1.5%
Television 18.6% 20.0% 1 1.3%
Radio 3.3% 3.0% 4.3%
WSW 0283.8 11211.0 112128 X2 = 3.27 0.071
% of Yes 52.0% 50.7% 59.4%
WWII
Immljnfenmtign 1133.1 112322 0216 X2 = 0.76 0.385
% of Yes 58.7% 57.7% 63.2%
WW
Information [1:249 113202 11211 x2 = 0.65 0.420
% of Yes 17.3% 16.3% 21.3%
W
v' ' -
Beguestlmeflnfennatinn 1121032 1128.65 n.1.61= x2 = 0.38 0.536
% of Yes 36.2% 36.6% 34.1%

 

' Percentages add to more than 100% due to multiple responses.

162

Table B7. Trip characteristics and behaviors of instant and hesitant decision-makers

 

 

(VFR excluded).
All Instant Hesitant
Pleasure Decision- Decision- Test
Variable Travelers Makers Makers Statistic Sijnificance
1121925 112812 112161 x2 = 1.84 0.606
Winter (December - February) 15.3% 15.9% 12.6%
Spring (March - May) 12.7% 13.0% 11.4%
Summer (June - August) 46.1% 45.4% 49.7%
Fall (September - November) 25.9% 25.8% 26.3%
Etimanthmmflnn le= 028.68 n.1.61= x2 = 10.91 0.053
Outdoor recreation 20.8% 20.3% 23.4%
Entertainment 19.5% 20.5% 14.4%
Relaxation 14.9% 15.0% 14.4%
General touring 5.1% 5.1% 5.4%
Vacation/holiday/recreation/
amusement/pleasure 32.8% 33.2% 30.5
Other 7.0% 6.0% 12.0
General touring or driving for 61.0% 59.6% 68.7% x2 = 4.84 0.028
pleasure '
Shopping 54.7% 54.6% 55.4% x2 = 0.03 0.849
Outdoor recreation 61.6% 60.1% 69.3% x2 = 4.97 0.026
Explore small city or town 56.3% 55.1% 62.7% X2 = 3.20 0.074
Dine at unique restaurant 51.0% 50.8% 51.8% X2 = 0.05 0.814
Visit other attraction 47.9% 47.5% 50.0% X2 = 0.36 0.548
Nightlife 32.8% 32.1% 36.1% x2 = 1.03 0.309
Visit state or national park 34.2% 33.0% 40.6% X2 = 3.54 0.060
Visit an historic site 31.1% 30.0% 36.5% x2 = 2.77 0.096
Attend a festival or event 24.7% 25.7% 19.5% x2 = 2.62 0.106
Visit museum or hall of fame 15.6% 14.4% 21.7% x2 = 5.60 0.018
Fall color touring 9.7% 9.2% 12.1% X2 = 1.30 0.253
Casino gaming 12.2% 12.6% 10.1% x2 = 0.76 0.384
Numhemmctixitiemmcinatemn 1121012 11285.4 1121.60 F1 .61 0205
MW.) 50 5-0 5-4
n=813 n=723 n=150 x2 = 15.15 0.056
Hotel/motel/lodge 49.0% 46.5% 61.3%
Friend's/relative's home 12.6% 13.7% 7.3%
Owned cabin/cottage/condominium 9.5% 10.2% 6.0%
Rented cabin/cottage/condominium 9.3% 9.5% 8.0%
Commercial campground 6.4% 6.5% 6.0%
Public campground 5.3% 5.3% 5.3%
Bed & Breakfast 1.6% 1.7% 1.3%
Boat/ship 0.7% 0.6% l .3%
Other 5.6% 6.1% 3.3%

 

163

 

Table B7. Trip characteristics and behaviors of instant and hesitant decision-makers
(VFR excluded), continued.

 

 

164

All Instant Hesitant
Pleasure Decision- Decision- Test
Variable Travelers Makers Makers Statistic Significance
' 1121030 286.4. 12166
Car/ truck without camping 89.7% 89.5% 90.5%
equipment
Car/ truck with camping 3.6% 3.3% 5.3%
equipment
Motorcoach 2.4% 2.8% 0.3%
Airplane 2.0% 2.0% 1.7%
Ship/boat 1.6% 1.5% 2.3%
Self-contained recreation vehicle 1.8% 1.8% 1.9%
Rental car 0.9% 0.9% 1.1%
Motorcycle 0.2% 0.2% 0.0%
Train 0.2% 0.3% 0.0%
Bicycle 0.2% 0.3% 0.0%
Other 1.1% 0.9% 1.9%
Itaxelflnx
1131021 n=855 [13166 t = 0.14 0.892
Average party size 3.4 3.4 3.4
11.281= 1128.12 11215.5 t= 0.61 0.952
Average age of all persons in 37.7 37.7 37.8
party
Included person(s) aged. . .' n= | 328 n=1 [2] n=ZQjZ --- «-
Less than 10 31.6% 33.5% 21.8%
11 to 20 36.4% 36.4% 36.0%
21 to 30 56.0% 56.5% 53.5%
31 to40 71.3% 72.1% 67.1%
41 to 50 62.8% 62.0% 67.0%
51 to 60 36.8% 36.6% 37.4%
61 to 70 16.7% 17.6% 11.9%
Above 71 6.4% 6.9% 3.9%
11:81] 112122 112138 x2 = 7.85 0.005
Spent night at 1 place in MI 90.6% 91.8% 84.5%
Spent night more than 1 place in 9.4% 8.2% 15.5%
MI
11:8 20 n=223 n=142 t = 2.11 0.037
W 1.2 1.1 1.3
(Axed

Table B7. Trip characteristics and behaviors of instant and hesitant decision-makers
(VFR excluded), continued.

 

 

All Instant
Pleasure Decision- Hesitant Test
Variable Travelers Makers Decision-Makers Statistic Significance
Melanesnnatmneglmm n2228 11210 1121.62 x2 = 8.08 0.152
111121112303
Upper Peninsula 16.7% 15.7% 22.2%
Northwest Lower Peninsula 19.9% 19.6% 21.6%
Northeast Lower Peninsula 18.4% 18.4% 18.5%
Southwest Lower Peninsula 15.3% 16.1% 1 1.1%
Southeast Lower Peninsula 19.0% 19.9% 14.8%
without Detroit area
Detroit area (Wayne, Oakland, 10.5% 10.3% 1 1.7
and Macomb Counties)
MW 1121011 11285.2 021.05 I = 0.64 0.520
momentum.) 4.4 4.3 4.7
Immune
Overnight trip £1034. E868 n21§.6 x2 = 5.29 0.021
% of Yes 84.4% 83.3% 90.4%
Vacation Trip = 2 112861 112161 X2 = 3.67 0.055
% of Yes 72.4% 71.2% 78.4%
Family Trip 1121925 112881 n216A x2 = 0.20 0.657
% of Yes 67.4% 67. 1% 68.9%
Arranged by Travel Agent E1031 [1:865 [13166 X2 = 1.24 0.265
% of Yes 3.2% 3.5% 1.8%
Package Tour with Lodging 1121032 112805 02182 x2 = 9.17 0.002
% of Yes 7.1% 6.0% 12.6%

165

Table B7. Trip characteristics and behaviors of instant and hesitant decision-makers

 

 

Q/F R excluded), continued.
All Instant
Pleasure Decision- Hesitant Test
Variable Travelers Makers Decision-Makers Statistics Significance
I . E . C E I
112814 11222.4 112110 t= 1.57 0.118
No. nights away from home 4.1 3.9 5.0
n2812 n2723 1121.42 t= 1.39 0.167
3.8 3.7 4.6

No. nights spent in MI

5 E l. . I I. I .
115116 t=0.04 0.968

nfllfl 1128.15
$617.32 $616.74 $620.34

Total spending per trip
' Percentages add to more than 100% due to multiple responses.

2 Definitions of regions:

4’ U

...]
0.1.9

 
 

NE

 

SEwb
DumuAma

Damn
Ann

166

Table B8. Demographic and socioeconomic characteristics of instant and hesitant
decision-makers (VFR excluded).

 

 

All Instant Hesitant
Pleasure Decision- Decision- Test
Variable Travelers Makers Makers Statistics Significance
Statemtmmtnnnsinai 1211135 112862 n2l_6_(z x2 = 10.86 0.093
Residence
Illinois 12. 1% 1 1.0% 17.5%
Indiana 8.8% 9.7% 4.2%
Michigan 51.5% 52.1% 48.2%
Minnesota 2.2% 2.2% 2.4%
Ohio 12.9% 12.5% 15.1%
Wisconsin 5.3% 5.2% 6.0%
Ontario 7.1% 7.2% 6.6%
Householdfiomainedm
Pre-school child(ren) 15.2% 15.2% 14.7% x2 = 0.03 0.868
School age child(ren) 35.5% 35.7% 34.4% x2 = 0.1 1 0743
Senior citizen(s) 16.4% 16.2% 17.8% x2 = 0.27 0.607
Handicapped person(s) 4.3% 4.3% 4.3% X2 = 0.00 0.999
GrosaAnnuaLHouscholdJncome n221§ n.125= nfl X2 = 0.16 0922
Below $31,000 19.0% 19.2% 18.0%
$31,001 - $50,000 28.4% 28.2% 29.3%
Above $50,000 52.6% 52.6% 52.7%
W211! n2816 1127.411 n_13.6= x2 = 11.75 0.068
White 93.8% 93.9% 93.4%
African American 3.4% 3.5% 2.9%
Hispanic 0.7% 0.5% 1.5%
Native American 0.7% 0.8% 0.0%
Asian American 0.8% 0.9% 0.0%
Multiracial 0.2% 0.1% 0.7%
Other 0.3% 0.1% 1.5%
' n21.012 n.855= n21fi
Employed full-time 67.1% 66.6% 69.8%
Retired 1 1.4% l 1.7% 9.5%
Employed part-time 9.9% 9.5% 12.3%
Homemaker 7.2% 7.3% 6.7%
Student 5.4% 5.4% 5.3%
Other type(s) employment 2.0% 2.0% 1.8%
Not employed 2.3% 2.3% 2.5%
mm 1121.020 n2816 1121M t = 0.58 0.564
Eamerflnflnusshnldm.) 1-5 1-5 1-5

 

' Percentages add to more than 100% due to multiple responses.

167

 

Table B9. Relative frequencies of three different dates related to trip planning by three
parts of months of the month (VFR excluded).

Segment of Month Date trip began (%) Date planning Date destination

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

(n=883) began (%) selected (%)
(n=883) (n=883)
Janl through Jan 10 2.9 2.9 1.9
Janll through Jan 20 3.3 3.8 1.9
Jan21 through Jan 31 2.3 2.2 0.9
Febl through Feb 10 2.4 2.3 1.6
Feb 11 through Feb 20 2.6 2.5 2.9
Feb 21 through Feb 28 1.3 1.0 1.0
Mar 1 through Mar 10 2.4 2.4 1.3
Mar 11 through Mar 20 2.1 2.2 1.4
Mar 21 through Mar 31 1.1 1.2 0.9
Apr 1 through Apr 10 1.6 1.4 1.]
Apr 11 through Apr 20 1.8 1.9 0.9
Apr 21 through Apr 30 1.5 1.1 0.6
May 1 through May 10 4.0 4.0 2.1
May 11 through May 20 3.6 3.1 2.1
May 21 through May 31 2.0 2.1 2.0
Jun 1 through Jun 10 4.9 4.5 2.6
Jun 11 through Jun 20 4.1 4.0 3.5 1
Jun 21 through Jun 30 3.7 3.1 3.0 ‘
Jul 1 through Jul 10 5.2 5.6 7.6
Jul 11 through Jul 20 5.1 5.3 7.1
Jul 21 through Jul 31 3.4 3.7 3.1
Aug 1 through Aug 10 5.3 5.1 6.5
Aug 11 through Aug 20 5.4 5.0 8.2
Aug 21 through Aug 31 3.9 4.4 4.5
Sepl through Sep 10 3.8 3.9 6.5
Sep 11 through Sep 20 2.0 2.3 2.6
Sep 21 through Sep 30 3.6 3.6 2.1
Oct 1 through Oct 10 2.2 2.0 3.0
Oct 11 through Oct 20 1.9 2.8 3.9
Oct 21 through Oct 31 1.7 1.3 1.3
Nov 1 through Nov 10 2.4 2.5 1.1
Nov 11 through Nov 20 2.0 1.8 2.7
Nov 21 through Nov 30 2.2 2.3 2.2
Dec 1 through Dec 10 0.9 1.1 2.3
Dec 11 through Dec 20 0.3 0.4 1.2
Dec 21 through Dec 31 1.1 1.2 2.4
Total 100.0 100.0 100.0

 

168

Table B9-1 Relative frequencies of three difl‘erent dates related to trip planning by three
parts of months of the month (VFR included).

 

 

 

 

 

 

 

 

 

 

 

 

 

Segment of Month Date trip Date planning Date destination
began (%) began (%) selected (%)
(n=1266) (n=1266) (n=1266)
Janl through Jan 10 1.7 3.0 2.9
Janll through Jan 20 1.6 2.8 3.0
Jan21 through Jan 31 0.8 2.2 2.1
Febl through Feb 10 1.6 2.3 2.2
Feb 11 through Feb 20 2.4 2.0 1.9
Feb 21 through Feb 28 0.8 1.1 0.9
Mar 1 through Mar 10 1.1 2.3 2.2
Mar 11 through Mar 20 1.3 2.2 2.3
Mar 21 through Mar 31 0.7 1.4 1.5
Apr 1 through Apr 10 1.5 2.0 1.9
Apr 11 through Apr 20 1.3 2.1 2.3
Apr 21 through Apr 30 1.0 1.9 1.4
May 1 through May 10 2.2 4.0 4.0
May 11 through May 20 2.1 3.3 2.9
May 21 through May 31 2.4 2.6 2.8
Jun 1 through Jun 10 3.2 4.4 4.3
Jun 11 through Jun 20 3.8 3.9 3.7
Jun 21 through Jun 30 3.1 4.0 3.6
Jul 1 through Jul 10 7.2 5.0 5.2
Jul 11 through Jul 20 6.1 4.5 4.6
Jul 21 through Jul 31 2.9 3.1 3.4
Aug 1 through Aug 10 6.5 5.6 5.6
Aug 11 through Aug 20 7.5 4.9 4.6
Aug 21 through AuL31 4.2 3.7 3.9
Sepl through Sep 10 5.8 3.7 3.7
Sep 11 through Sep 20 3.3 2.8 2.9
Sgp 21 through Sep30 2.3 3.8 3.8
Oct 1 through Oct 10 3.4 2.1 2.3
Oct 11 through Oct 20 4.0 2.2 3.0
Oct 21 through Oct 31 1.3 2.1 1.8
Nov 1 through Nov 10 2.0 2.3 2.3
Nov 11 through Nov 20 2.4 1.7 1.6
Nov 21 through Nov 30 3.0 2.3 2.3
Dec 1 through Dec 10 1.8 1.0 1.0
Dec 11 through Dec 20 1.1 0.7 0.8
Dec 21 through Dec 31 2.8 0.9 1.1

 

Total 100.0 100.0 100.0

 

169

Table BIO. Significance test of relative frequencies of trip
related dates by segment of month that they occur
(VFR excludedL

 

Segment of Date trip Date planning Date destination
month began (%) began (%) selected (%)

 

(n=883) (n=883) (n=883)
Early (1-10) 38.2 37.6 37.7
Mid (1 1-20) 34.0 35.2 38.4
End (21-end) 27.8 27.2 23.9
Chi-square 35.1 16.3 20.9
Significant 0.000 0.000 0.000

 

Table BIO-1. Significance test of relative frequencies of trip
related dates by segment of month that they
occur (VFR included).

Segment of Date trip Date planning Date destination
month began (%) began (%) selected (%)

 

(n=1266) (n=1266) (n=1266)
Early (1-10) 38.0 37.7 37.6
Mid (1120) 36.9 33.1 33.6
End (21-end) 25.3 29.1 28.6
Chi-square 43.1 18.5 21.9
Significance 0.000 0.000 0.000

 

170

Table Bl 1. Relative frequencies of three different dates related to trip
planning by three parts of the month excluding July and
September (VFR excluded).

Segment of Month Date trip began Date planning Date destination

 

 

 

 

 

 

 

 

 

 

 

 

(%) began (%) selected (%)
(n=1266) (n=1266) (n=1266)
Janl through Jan 10 2.7 3.8 3.9
Janll through Jan 20 2.6 4.3 5.1
Jan21 through Jan 31 1.2 3.0 2.9
Febl through Feb 10 2.3 3.1 3.0
Feb 11 through Feb 20 4.1 3.4 3.3
Feb 21 through Feb 28 1.4 1.7 1.4
Mar 1 through Mar 10 1.8 3.2 3.2
Mar 11 through Mar 20 2.0 2.7 2.8
Mar 21 through Mar 31 . 1.2 1.4 1.6
Apr 1 through Apr 10 1.6 2.1 1.8
Apr 11 through Apr 20 1.3 2.3 2.6
Apr 21 through Apr 30 0.8 1.9 1.5
May 1 through May 10 2.9 5.1 5.3
May 11 through May 20 3.0 4.7 4.1
May 21 through May 31 2.9 2.5 2.8
Jun 1 through Jun 10 3.6 6.4 5.9
Jun 11 through Jun 20 5.0 5.4 5.3
Jun 21 through Jun 30 4.3 4.8 4.1
Aug 1 through Aug 10 9.1 6.9 6.8
Aug 11 through Aug 20 11.6 7.0 6.7
Aug 21 through Aug 31 6.3 5.1 5.8
Oct 1 through Oct 10 4.3 2.8 2.6
Oct 11 through Oct 20 5.5 2.4 3.7
Oct 21 through Oct 31 1.9 2.3 1.7
Nov 1 through Nov 10 1.6 3.2 3.3
Nov 11 through Nov 20 3.8 2.6 2.4
Nov 21 through Nov 30 3.1 2.9 - 3.0
Dec 1 through Dec 10 3.2 1.2 1.5
Dec 11 through Dec 20 1.6 0.3 0.5
Dec 21 through Dec 31 3.4 1.4 1.5
Total 100.0 100.0 100.0

 

 

171

Table Bl l-l. Relative frequencies of three different dates related to trip
planning by three parts of month excluding July and
September (VFR included).
Segment of Month Date trip Date planning Date destination
began (%) began (%) selected (%)

 

 

 

 

 

 

 

 

 

 

 

(n=966) (n=966) (n=966)
Janl through Jan 10 2.3 3.9 3.8
Janll through Jan 20 2.2 3.6 4.0
Jan21 through Jan 31 1.1 2.9 2.8
Febl through Feb 10 2.1 2.9 2.9
Feb 11 through Feb 20 3.4 2.6 2.5
Feb 21 through Feb 28 1.1 1.4 1.2
Mar 1 through Mar 10 1.5 2.9 2.8
Mar 11 through Mar 20 1.7 2.9 3.0
Mar 21 through Mar 31 1.0 1.8 1.9
Apr 1 through Apr 10 2.1 2.6 2.5
Apr 11 through Apr 20 1.7 2.8 3.0
Apr 21 through Apr 30 1.4 2.5 1.8
May 1 through May 10 3.0 5.2 5.2
May 11 through May 20 2.9 4.3 3.8
May 21 through May 31 3.4 3.3 3.6
Jun 1 through Jun 10 4.4 5.8 5.7
Jun 11 through Jun 20 5.3 5.1 4.9
Jun 21 through Jun 30 4.2 5.2 4.7
Aug 1 through Aug 10 8.9 7.2 7.3
Aug 11 through Aug 20 10.4 6.3 6.1
Aug 21 through Aug 31 5.7 4.8 5.1
Oct 1 through Oct 10 4.8 2.7 3.0
Oct 11 through Oct 20 5.5 2.9 3.9
Oct 21 through Oct 31 1.8 2.8 2.4
Nov 1 through Nov 10 2.7 3.0 3.0
Nov 11 through Nov 20 3.3 2.2 2.1
Nov 21 through Nov 30 4.1 3.0 3.0
Dec 1 through Dec 10 2.5 1.2 1.4
Dec 11 through Dec 20 1.6 0.9 1.1
Dec 21 through Dec 31 3.9 1.2 1.4
Total 100.0 100.0 100.0

 

172

Table BIZ. Significance test of relative frequencies of trip
related dates by segment of month that they occur
excluding July and September (VFR excluded).

 

 

Segment of Date trip Date planning Date destination
month began (%) began (%) selected (%)
(n=966) (n=966) (n=966)
Early (1-10) 33.2 37.9 37.3
Mid (11-20) 40.5 35.1 36.5
End (21-end) 26.3 27.0 26.3
Chi-square 20.2 16.0 13.6
Significance 0.000 0.000 0.000

 

Table B12-1. Significance test of relative frequencies of trip
related dates by segment of month that they
occur excluding July and September (VFR

 

 

included).
Segment of Date trip Date planning Date destination
month began (%) began (%) selected (%)
(n=966) (n=966) (n=966)
Early (1-10) 34.3 37.4 37.6
Mid (1 1-20) 37.9 33.6 34.3
End (21-end) 27.7 29.0 28.0
Chi-square 9.62 13.83 15.98
Significance 0.008 0.001 0.000

 

173

 

 

Table B 13. Frequency distributions for three trip related dates by

 

 

month (VFR excluded).

Month Date trip Date planning Date destination
began (%) began (%) selected (%)

(n=883) (n=883) (n=883)
Jan 4.6 8.5 8.9
Feb 5.5 6.3 5.8
Mar 3.5 5.6 5.8
Apr 2.6 4.9 4.4
May 6.2 9.5 9.2
Jun 9.1 12.7 11.6
July 17.8 13.7 14.6
Aug 19.2 14.6 14.6
Sept 11.3 9.5 9.8
Oct 8.3 5.8 6.1
Nov 6.0 6.7 6.6
Dec 5.9 2.3 2.6
Total 100.0 100.0 100.0

 

Table B13-1. Frequency distributions for three trip related dates by

 

 

month (VFR included).
Month Date trip Date planning Date destination
began (%) began (%) selected (%)
(n=1266) (n=1266) (n=1266)
Jan 4.1 8.0 8.1
Feb 4.8 5.4 5.1
Mar 3.0 5.9 5.9
Apr 3.7 6.1 5.6
May 6.7 9.9 9.7
Jun 10.1 12.4 11.6
July 16.2 12.5 13.3
Aug 18.1 14.1 14.2
Sept 11.4 10.3 10.4
Oct 8.8 6.4 7.0
Nov 7.3 6.4 6.2
Dec 5.7 2.6 3.0
Total 100.0 100.0 100.0

 

174

 

 

Table B14. Frequency distribution for three travel related dates by season (VF R

 

 

excluded).
Season Date trip Date planning Date destination
began (%) began (%) selected (%)
(n=883) (n=883) (n=883)
Winter (Dec-Feb.) 16.0 17.1 17.4
Spring (Man-May) 12.3 20.0 19.4
Summer (Jun-Aug.) 46.0 41.0 40.8
Fall (Sept-Nov.) 25.6 22.0 22.4

 

Table B 14-1. Frequency distribution for three travel related dates by season (VFR

 

 

included).
Season Date trip Date planning . Date destination
began (%) began (%) selected (%)
(n=1266) (n=1266) (n=1266)
Winter (Dee-Feb.) 14.1 16.0 16.2
Spring (Man-May) 13.9 21.8 21.2
Summer (Jun-Aug.) 44.5 39.0 39.0
Fall (Sept-Nov.) 27.5 23.2 23.6

 

175

APPENDIX C

DURATION OF TOTAL TRIP PLANNING INVERVAL FOR SELECTED
VARIABLES

176

Table C1. Duration of the total trip planning interval for selected variables.

 

 

177

Average Test
Variable No. Days Correlation Statistics Sigflcmce
Seasonflhcnltinflcgan n215A5 F599 0000
Nonpeak season 55.7
Peak Season 89.4
All 70.7
Enmmfiumnmfldn 112156.12 F418 0000
Other purpose 76.5
Visiting friends or relatives 53.7
All 69.9
IrmLBam
1121.410 0.000
Average party size 0.119
5 'v' . E . . l I
General touring or driving for pleasure 115L460 t=0.99 0.324
Yes 72.5
No 67.0
All 70.2
Shopping 11:15.69 t=1.47 0.141
Yes 73.9
No 65.8
All 70.2
Outdoor recreation 1121460 F669 0.000
Yes 86.0
No 49.7
All 70.2
Visit other attraction 1131560 t=2.38 0.018
Yes 77.3
No 64.3
All 70.1
Nightlife 11213.22 t=0.06 0.951
Yes 70.5
No 70.2
All 70.3
Visit an historic site n=|45§ t=2.98 0.003
Yes 83.7
No 65.1
All 70.4
Visit state or national park 11213.16 F365 0.000
Yes 85.9
No 63.1
All 70.3

Table C 1. Duration of the total 113 planning interval for selected variables, continued.

 

 

Average Test
Variable No. Days Correlation Statistics Significance
Visit museum or ball of fame 11213.61 F232 0.021
Yes 85.3
No 67.5
All 70.2
Casino gaming n=1332 F1.ll 0.268
Yes 80.7
No 69.5
All 70.7
Attend a festival or event n=1332 F3.60 0.000
Yes 91.1
No 64.5
All 70.7
Fall color touring 1131512 F0.l l 0.91 1
Yes 71.2
No 70.2
All 70.3
MaiancnetchflLodginallscd n2125§ t=7.43 0.000
Others 88.3
Friend's/relative's home 46.]
All 76.7
n21316
WW 0069 0.008
13191101211112
1121551 Fl .68 0.094
Non-Family Trip 77.6
Family Trip 66.8
All 69.8
11315151 F8.18 0.000
Day Trip 31.5
Overnight Trip 76.9
All 70.1
11311168 F9.89 0.000
Non-Vacation Trip 37.5
Vacation Trip 85.5
All 70.0
I . I; .
0:1326
No. nights spent in MI 0.195 0.000

178

Table Cl. Duration of the total trip planning interval for selected variables, continued.

 

 

Average Test
Variable No. Days Correlation Statistics Significance
n211116 0.006
Esfimammmxmndimmm 0.074
Statczrzrcmcecrzrincinalncaidence n_IAl§= t=o.33 0745
Other states 71.0
Michigan 69.2
All 70.1
mssAnnuaLHQussholdJnmmc 1121.351 F123 0220
Below $31,000 62.7
Above $31,000 71.5
All 69.8
Householdficmained...
Pre-school 1131552 F3.18 0.750
No 70.3
Yes 67.8
All 69.9
School age 11=|4§8 F1.89 0.059
No 66.2
Yes 77.0
All 70.0

 

179

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