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Economic Impacts and Motivations of Off-Highway Vehicle Recreationists

Permanent Link: http://ufdc.ufl.edu/UFE0021050/00001

Material Information

Title: Economic Impacts and Motivations of Off-Highway Vehicle Recreationists A Case Study from Florida
Physical Description: 1 online resource (83 p.)
Language: english
Creator: Parent, Gregory D
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: analysis, based, benefits, cluster, consumer, cost, desired, florida, forest, highway, individual, input, least, method, motivations, motorized, nature, off, ordinary, output, pay, recreation, square, state, surplus, to, travel, vehicles, willingness, withlacoochee
Forest Resources and Conservation -- Dissertations, Academic -- UF
Genre: Forest Resources and Conservation thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Off-highway vehicle (OHV) recreation is a popular and fast growing forest-based activity. As such it is necessary to understand the participants involved and their impacts to better manage for this use. While OHV use does generate negative impacts, such as noise pollution, adverse soil effects, and user conflicts, positive impacts also arise from this activity. My thesis reports a study of OHV users who visited the Croom Motorcycle Area (CMA), a single use OHV recreation area in the Withlacoochee State Forest, Florida. Specifically, this study focuses on economic impacts of OHV recreation on local economies. Evaluation of the economic impact was achieved through travel expenditure surveys combined with economic input-output analysis to estimate the direct, indirect, and induced economic impact arising from OHV. The impact is significant to the surrounding communities with a total value estimated at over $21 million. My study goes one step further to evaluate consumer surplus (CS) of CMA users through the application of the individual travel cost method, to quantify this additional societal benefit. Results suggest that participants with more experience in OHV recreation at the CMA will more frequently visit the site reflecting the effect of habit formation. Regression coefficients were used to estimate CS with individual household CS evaluated at over $1,600, while the total annual CS of all households recreating at the CMA was estimated at over $31 million. In addition, the study analyzed the benefits that act as motivations for users involved in OHV recreation. Results indicated that the attainment of family oriented benefits were the main motivation for their participation. The motivations to 'be with friends and family' and to 'strengthen family kinship' had the top two overall mean rank scores out of a list of 19 motivation variable. Furthermore, motivational subgroups exist within the overall population and vary in the benefits that motivate them to ride OHVs. Results revealed three distinct homogenous motivational groups; group one, the Experiencers, riding for the attainment of multiple and diverse benefits; group two, the Familists, riding mainly for the attainment of family based benefits; and group three, the Individualists, riding for the attainment of individual oriented benefits.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Gregory D Parent.
Thesis: Thesis (M.S.)--University of Florida, 2007.
Local: Adviser: Alavalapati, Janaki R.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021050:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021050/00001

Material Information

Title: Economic Impacts and Motivations of Off-Highway Vehicle Recreationists A Case Study from Florida
Physical Description: 1 online resource (83 p.)
Language: english
Creator: Parent, Gregory D
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: analysis, based, benefits, cluster, consumer, cost, desired, florida, forest, highway, individual, input, least, method, motivations, motorized, nature, off, ordinary, output, pay, recreation, square, state, surplus, to, travel, vehicles, willingness, withlacoochee
Forest Resources and Conservation -- Dissertations, Academic -- UF
Genre: Forest Resources and Conservation thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Off-highway vehicle (OHV) recreation is a popular and fast growing forest-based activity. As such it is necessary to understand the participants involved and their impacts to better manage for this use. While OHV use does generate negative impacts, such as noise pollution, adverse soil effects, and user conflicts, positive impacts also arise from this activity. My thesis reports a study of OHV users who visited the Croom Motorcycle Area (CMA), a single use OHV recreation area in the Withlacoochee State Forest, Florida. Specifically, this study focuses on economic impacts of OHV recreation on local economies. Evaluation of the economic impact was achieved through travel expenditure surveys combined with economic input-output analysis to estimate the direct, indirect, and induced economic impact arising from OHV. The impact is significant to the surrounding communities with a total value estimated at over $21 million. My study goes one step further to evaluate consumer surplus (CS) of CMA users through the application of the individual travel cost method, to quantify this additional societal benefit. Results suggest that participants with more experience in OHV recreation at the CMA will more frequently visit the site reflecting the effect of habit formation. Regression coefficients were used to estimate CS with individual household CS evaluated at over $1,600, while the total annual CS of all households recreating at the CMA was estimated at over $31 million. In addition, the study analyzed the benefits that act as motivations for users involved in OHV recreation. Results indicated that the attainment of family oriented benefits were the main motivation for their participation. The motivations to 'be with friends and family' and to 'strengthen family kinship' had the top two overall mean rank scores out of a list of 19 motivation variable. Furthermore, motivational subgroups exist within the overall population and vary in the benefits that motivate them to ride OHVs. Results revealed three distinct homogenous motivational groups; group one, the Experiencers, riding for the attainment of multiple and diverse benefits; group two, the Familists, riding mainly for the attainment of family based benefits; and group three, the Individualists, riding for the attainment of individual oriented benefits.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Gregory D Parent.
Thesis: Thesis (M.S.)--University of Florida, 2007.
Local: Adviser: Alavalapati, Janaki R.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021050:00001


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4516353f6eeca92c6841d5470785e102024cb976







ECONOMIC IMPACTS AND MOTIVATIONS OF OFF-HIGHWAY VEHICLE
RECREATIONISTS: A CASE STUDY FROM FLORIDA




















By

GREGORY D. PARENT


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2007


































O 2007 Gregory D. Parent










ACKNOWLEDGMENTS

Financial support for this study was provided through the T. Mark Schmidt OHV Safety

& Recreation Act Grant Program. The author would like to thank all Division of Forestry

personnel who provided assistance throughout the proj ect. In addition, I would like to thank Jack

Terrell for his technical knowledge, which he generously provided throughout the duration of the

proj ect. I would also like to thank Sara Lumban Tobing for her invaluable assistance in data

collection and for her ongoing moral support. In addition, I thank Rachel Albritton for her help in

providing technical information. I thank all the participants who took the time for filling out the

lengthy mail-back survey; your survey was a critical part of this study. Finally, and most

importantly, I would like to thank my advisor Janaki Alavalapati and my committee members

Taylor Stein, Alan Hodges, and Douglas Carter for all their help and guidance throughout this

study .













TABLE OF CONTENTS


page

ACKNOWLEDGMENTS .............. ...............3.....


LIST OF TABLES .........._.... ...............6.._.._ ......


LIST OF FIGURES .............. ...............7.....


AB S TRAC T ......_ ................. ............_........8


CHAPTER


1 INTRODUCTION ................. ...............10.......... ......


Understanding Off-Highway Vehicle Recreation .............. ...............10....
Off-Highway Vehicle Recreation Policy in Florida ................ ...............11...............
Study Area: The Croom Motorcycle Area ................. ...............13...............
Study Objectives............... ...............1

2 STUDY DESIGN AND IMPLEMENTATION ................. ...............15........... ...


Profie of Respondents............... .............1
Visitor Characteristics .............. ...............16....
Trip Characteristics .............. ...............16....

3 REGIONAL ECONOMIC IMPACT OF OFF-HIGHWAY VEHICLE RECREATION
AT THE CROOM MOTORCYLCE AREA THROUGH INPUT-OUPUT ANALYSIS .....22


Introducti on ................. ...............22._ ___.......
M odel Specif cation............... .............2
Re sults .................. ........__ ... ...............25.....
Total Population Estimate .............. ...............25....
Trip Expenditure............... ..............2
Equipment Expenditure ................. .......__ ...............26.......
Regional Economic Impact Estimation ................. ........__ ........27.........



4 CONSUMER SURPLUS ESTIMATION: AN INDIVIDUAL TRAVEL COST
MET HOD APPROACH ................. ...............3.. 4..............


Introducti on ................... ....... .. ........ .. ......... .... ..........3
Individual Travel Cost Method Model Specifieation ................ ..............................36
Re sults ....___ ................. ......._ .. ..........3












5 MOTIVATIONS OF OFF-HIGHWAY VEHICLE USERS ................. ........................42


Introducti on ........._.___..... ._ __ ...............42.....
Data Analysis............... ...............43
R e sults.........._.... .... ....._._... ..........._. ... ........ .. ..... ..........4
Desired Benefit Profile of Off-Highway Vehicle Recreation Policy in Florida Users
at the Croom Motorcycle Area .............. ...............43....
Benefit Subgroups Identification............... .............4
Benefit Subgroups Description............... ..............4

6 DISCUS SION AND CONCLUSIONS .............. ...............53....


Policy Implications .............. ...............56....
Future Work............... ...............57..


APPENDIX


A MAP OF THE WITHLACO OCHEE S TATE F ORE ST ................. ................ ....__.5 9


B VERBAL CONSENT SCRIPT .............. ...............60....


C ON-SITE SURVEY............... ...............61.


D MAIL-BACK SURVEY ................. ...............62........... ....


E MATHEMATICAL DISCRETION OF INPUT-OUTPUT MODEL ................... ...............71


F DIRECT, INDIRECT, AND INDUCED REGIONAL ECONOMIC IMPACTS OF
OHV RECREATION AT THE CMA BY INDUSTRY GROUP AND IMPACT TYPE.....73


LIST OF REFERENCES ................. ...............78......_._ ....


BIOGRAPHICAL SKETCH .............. ...............83....












LIST OF TABLES


Table page

2-1 Visitor characteristics of respondents ................. ...............18........... ...

2-2 Trip characteristics of respondents. ................ ................ ......... ........ ...._20

2-3 Activities and experiences of Croom visitors .............. ...............21....

3-1 Population estimate of visitors to the Croom Motorcycle Area ................. ................. .28

3-2 Trip expenditure of a typical visitor to the Croom Motorcycle Area and total trip
expenditure for 2006 ................ ...............29........... ....

3-3 Equipment expenditure of a typical visitor to the Croom Motorcycle Area and total
equipment expenditure for 2006 .............. ...............30....

3-4 Regional impact events by IMPLAN sector ................. ...............31........... ..

3-5 Direct, indirect, and induced regional economic impact of off-highway vehicle
recreation at the Croom Motorcycle Area .............. ...............32....

3-6 Total regional economic impact by industry group for off-highway vehicle activity at
the Croom Motorcycle Area .............. ...............33....

4-1 Description of variables used in the Individual Travel Cost Method model ................... ..36

4-2 Descriptive statistics of variables used in the model ................. ................. ..........40

4-3 Regression model results .............. ...............41....

5-1 Results of cluster analysis ............... ...............48....

5-2 Desired benefits of respondents and benefit subgroups. .......................... ...............49

5-3 Desired benefit ranking by cluster membership .............. ...............50....

5-4 Visitor characteristics by cluster membership ................ ...............51...............

5-5 Additional visitor characteristics by cluster membership ................. ................ ...._.51

5-6 Trip characteristics by cluster membership .............. ...............52....

5-7 Additional trip characteristics by cluster membership............... ...............5










LIST OF FIGURES


Figure


page


2-1 Region of residence of CMA visitors ................ ............. ......... ........ .......21









Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

ECONOMIC IMPACTS AND MOTIVATIONS OF OFF-HIGHWAY VEHICLE
RECREATIONISTS: A CASE STUDY FROM FLORIDA

By

Gregory D. Parent

April 2007

Chair: Janaki Alavalapati
Maj or: Forest Resources and Conservation

Off-highway vehicle (OHV) recreation is a popular and fast growing forest-based

activity. As such it is necessary to understand the participants involved and their impacts to

better manage for this use. While OHV use does generate negative impacts, such as noise

pollution, adverse soil effects, and user conflicts, positive impacts also arise from this activity.

My thesis reports a study of OHV users who visited the Croom Motorcycle Area (CMA), a

single use OHV recreation area in the Withlacoochee State Forest, Florida. Specifically, this

study focuses on economic impacts of OHV recreation on local economies. Evaluation of the

economic impact was achieved through travel expenditure surveys combined with economic

input-output analysis to estimate the direct, indirect, and induced economic impact arising from

OHV. The impact is significant to the surrounding communities with a total value estimated at

over $21 million.

My study goes one step further to evaluate consumer surplus (CS) of CMA users through

the application of the individual travel cost method, to quantify this additional societal benefit.

Results suggest that participants with more experience in OHV recreation at the CMA will more

frequently visit the site reflecting the effect of habit formation. Regression coefficients were used









to estimate CS with individual household CS evaluated at over $1,600, while the total annual CS

of all households recreating at the CMA was estimated at over $31 million.

In addition, the study analyzed the benefits that act as motivations for users involved in

OHV recreation. Results indicated that the attainment of family oriented benefits were the main

motivation for their participation. The motivations to "be with friends and family" and to

"strengthen family kinship" had the top two overall mean rank scores out of a list of 19

motivation variable. Furthermore, motivational subgroups exist within the overall population and

vary in the benefits that motivate them to ride OHVs. Results revealed three distinct homogenous

motivational groups; group one, the Experiencers, riding for the attainment of multiple and

diverse benefits; group two, the Familists, riding mainly for the attainment of family based

benefits; and group three, the Individualists, riding for the attainment of individual oriented

benefits .









CHAPTER 1
INTTRODUCTION

Understanding Off-Highway Vehicle Recreation

Nature-based recreational activities on forested lands in the United States attract millions

of participants yearly. Over 200 million people visited US Forest Service managed lands

annually from 2000-2003 to participate in varied forms of recreation such as hiking,

backpacking, skiing and off-highway vehicle (OHV) riding (USDA, 2005). One of the fastest

growing forms of recreation over the last decade has been OHV recreation. Cordell et al., (2005)

estimated that from 1999 to 2004 OHV recreation grew by over 15 million participants in the

United States. This growth has been mirrored in Florida with an estimated 1.78 million

participants as of 2004, ranking it fifth within the US and first within the southern US (Cordell et

al., 2005). The enormous and growing popularity of OHV recreation has spurred many states

into creating new OHV management policies to address the positive and negative externalities

and capitalize on positive externalities that arise from this form of recreation.

To date, the maj ority of the research undertaken on OHV recreation has focused on the

negative environmental and social impacts resulting from OHV recreation. OHV use is a highly

consumptive form of recreation, whose impacts tend to be very visible (Maj or, 1987). Repeated

use of OHVs on trails lead to the reduction in air and organic soil components, reduced levels of

vegetation on trail margins, and increased erosion (Kay, 1981; Webb et al., 1978). A study in

California deserts by Sheridan (1978) found that areas with high OHV use experienced a 60%-

75% decrease in animal life. Similarly, white-tailed deer populations were found to be inversely

proportional to OHV levels along trails in Minnesota (Dorrence, 1975). Sound pollution is also a

maj or problem with OHVs. In a 1974 study, Harrison found that motor noise from OHVs could

be detected from up to 15,000 feet away depending on the engine and OHV type.









These negative environmental impacts in turn generate user conflicts between OHV users

and other stakeholders. Hunters are particularly affected by OHV recreation due to the tendency

of animals to avoid areas with heavy OHV use. Other recreation groups often seek out solitude

or undisturbed environments; these groups can be negatively affected by the aggressive nature of

OHV impacts (Kariel, 1990). A study by Vail & Heldt (2004), on snowmobile recreation in

Sweden and Maine, demonstrated that the conflict between snowmobilers and cross-country

(XC) skiers was largely asymmetrical, with the environmental impacts of snowmobiling

perceived highly by XC skiers, reducing their enj oyment. The same study also illustrated the

conflict that arises between the OHV riders and private landowners due high noise levels and

damage to property. Mountaineers gave OHV noise an aggregate score of 4.98 on a scale of one

to Hyve where Hyve means annoying and indicated that their enj oyment of nature decreased when

unnatural sounds were introduced to the environment (Kariel, 1990). These negative

environmental and social impacts can be minimized through the creation of OHV recreation

areas in which the impacts could be concentrated, and by the formulation of effective

management policies.

OHV Recreation Policy in Florida

Florida' s first attempt at managing OHV recreation came in 1972 when the Division of

Forestry (DOF) established the Croom Motorcycle Area (CMA) within the Withlacoochee State

Forest. The DOF created the CMA in response to the high level of perceived forest-wide

environmental degradation and the increasing conflicts between OHV riders and other

stakeholders (Florida Department of Agriculture and Consumer Services, 2002). By the founding

of this single-use OHV recreation area, it was the DOF's hope to confine all OHV riding to this

2,600 acre area, thus reducing the negative costs throughout the rest of the 133 thousand acres of









the Withlacoochee. DOF personnel have found that this has indeed been the case and the CMA is

now highly visited and liked by OHV riders.

However, the negative externalities that are associated with OHV riding persisted to be

an issue throughout the rest of Florida as OHV recreation continued to grow. The state of Florida

took notice in 2002 when they passed the T. Mark Schmidt Off-Highway Vehicle Safety and

Recreation Act. In formulating this legislation, the legislator recognized that positive

externalities are also present in OHV recreation. In the pursuit of OHV recreation, riders make

substantial travel and equipment expenditure that has a positive impact on the economy (see

chapter 3 for a further discussion on economic impacts). In addition to the positive economic

impacts, society can also gain from the beneficial social effects. As well as the personal benefits

riders get such as stress relief, physical fitness, and the enj oyment of nature, OHV recreation also

tends to be an outlet for socializing, family bonding, and community building (Maine Sunday

Telegram, 2002).

The 2002 OHV Safety and Recreation act was designed to provide opportunities for

people pursuing OHV recreation in a managed and controlled manner, thus reducing the negative

environmental and social impacts of illegal or unmanaged riding. The act explicitly recognizes

that current and future OHV recreation areas are compatible with Florida's overall recreation

plan and underlying goal of multiple use. The act laid the groundwork for the creation of at least

two new OHV riding areas that would be modeled after the CMA. The DOF has considered the

CMA to be a success as is has both reduced illegal riding and continues to attract large numbers

of users. The CMA was the only riding area on state land until 2005 when the DOF created a


1 In stating the need for at least two additional riding area, the legislature recognized that at a
time when OHV is growing in popularity, riding opportunities are decreasing in the State as the
USDA Forest Service further restricts riding on national forest lands though the Access
Designation Process.









new area in northern Florida.2 However the DOF, who manages the CMA and would be

responsible for any future OHV recreation areas, knew little about the population that rides

OHVs at its facilities and has limited information about the associated economic impacts. This

information gap has prompted the DOF to approach the University of Florida to conduct this

study .

Study Area: The Croom Motorcycle Area

The Croom Motorcycle Area (CMA) is located within the Croom tract of the 133

thousand acre Withlacoochee State Forest (Appendix A). It is a 2,600-acre single-use area

dedicated to Off-Highway Vehicle (OHV) recreation with the use of both off-road motorcycles

(ORM) and all-terrain vehicles (ATV) permitted. Forest-wide, the Withlacoochee supports

multiple uses within its borders, from extractive forestry activities to various recreational

pursuits (Florida Department of Agriculture & Consumer Services, 2005). The CMA came into

existence in 1972 as an attempt by the DOF to manage the forest for multiple uses by confining

OHV riding to one area, thereby concentrating the environmental impacts, eliminating conflicts

between OHV riders and other user groups on non-OHV areas (Florida Department of


2 Currently the two main OHV riding areas in Florida are within the State Forests of
Withlacoochee and Tate's Hell. OHV riding also occurs in Big Scrub, however it is substantially
restricted in terms of both numbers allowed and OHV vehicle type. Restricted OHV
opportunities are also available on some Florida Fish and Wildlife Conservation Commission
managed lands.
3 Three types of ORMs are used at the CMA. Endure motorcycles are street legal motorbikes
designed for sport and long travel. Endure motorcycles include a headlight and taillight, quiet
muffler. Motocross motorcycles are similar to enduro motorcycles but lack the refinements, such
as quiet mufflers and lights, to make them street legal. The third main type of ORM is the trial
motorcycle. Trials motorcycles are distinctive and specialized for events known as observed
trials. They are lightweight with a short suspension and have no seat as they are designed to be
ridden standing up.
4 There are two main types of ATVs used at the CMA. Sport quads are small lightweight two
wheel drive vehicles that can attain high speeds. Utility ATVs are larger four wheel drive
vehicles that have a much lower top speed. Utility ATVs have the ability to perform other tasks
such as hauling and towing items and often have lights on the front and rear ends.









Agriculture and Consumer Services, 2002). The popularity and lack of other riding areas makes

the CMA a popular destination with an estimated 71,500 total user-days for the 2005 fiscal year.

Study Objectives

There were four obj ectives of this study. Obj ective one was to describe the visitor of the

CMA in terms of their socio-demographics. The second obj ective was to evaluate the economic

impact arising from visitation to the CMA. As obj ective two does not capture the benefit users

get from their visitation of the CMA, obj ective three was to quantify this benefit through the

estimation of visitor' s consumer surplus. Obj ective four was to identify the specific desired

benefits that riders are attempting to attain as a reason for their use of the CMA and, to identify

and describe definable benefit subgroups.

To fulfill the above obj ectives a number of analytical methods were employed.

Descriptive statistics, such as frequencies and means, were used to identify who the visitors are

in terms of their socio-demographics. The estimate of economic impact to the region required the

utilization input-output to generate this estimated impact. The individual travel cost method was

employed to generate and estimate of visitors consumer surplus. Obj ective four was achieved by

having participants rate 19 individual motivations on a Likert scale to identify the primary

motivations. Cluster analysis was employed









CHAPTER 2
STUDY DESIGN AND IMPLEMENTATION

Researchers designed a comprehensive survey in order to achieve the four study

obj ectives. During the development process, researchers met with DOF personnel, made site

visits, and conducted protests of the survey on participants at the CMA. The survey was

developed using a modified Dillman (2000) method to increase response rate. On-site interviews

(Appendix C) were conducted, asking basic questions such as overall trip satisfaction, OHV type

used at the CMA, region of home residence, etc. The main obj ective of the on-site interviews

was to introduce and familiarize the participants with the more comprehensive mail-back survey.

The mail-back survey (Appendix D) contained the detailed questions that would provide the data

necessary to meet the study objectives. The survey was designed to be filled out on a household

basis, hence one mail-back survey was distributed per household.

Researchers approached potential participants in parking areas of the CMA asking OHV

riders whether they would participate using a verbal consent script (Appendix B). On-site

interviews were conducted from January through April 2006, with surveyors randomly

approaching a total of 342 OHV riders and attaining the verbal consent of 321 participants. At

the conclusion of each on-site interview a mail-back survey was distributed to the participant. An

additional mail-back survey was mailed to the participant if the original survey was not returned

after two weeks. A total of 1 16 out of the 321 mail-back surveys distributed were returned

completed for a response rate of 36. 14%. Surveyors also randomly left 99 surveys, a survey that

combined the on-site questionnaire with the mail-back survey, on parked vehicles throughout the

parking areas of the CMA. Out of the 99 surveys left with vehicles, 34 were returned, a response

rate of 34.34%. The combined response rate for the mail-back survey was 35.71%.









Profile of Respondents


Visitor Characteristics

The mail-back survey contained detailed socio-demographic information (Table 2-1).

Males made up a significant maj ority of the survey respondents (84.5%). For the survey

participants who provided their age, the majority indicated they were 40 or above (60.3%). More

than two thirds of respondents (67.8%) indicated that they were married, and 61.9% reported that

they have at least one child still living at home. Nearly all (91.0%) of the participants identified

themselves as Caucasian with 4.2% and 3.5% identifying themselves as Native American and

Hispanic / Latino respectively. The survey participants were well educated with 91.1% having

graduated from high school and 47.3% holding at least a bachelors degree. Close to 75% (74.5%)

of survey participants had annual household incomes of at least $55,000. Finally, the three main

occupations of survey participants were that of business owner (24.5%), skilled trade (23.8%),

and professional worker (19.0%).

Trip Characteristics

The mail-back and on-site surveys contained questions pertaining to the trip

characteristics of the survey participant (Table 2-2). The maj ority (55.3%) of the survey

participants have been riding OHVs for over 10 years with the mean years of ridding OHVs

being over 16 years (16.3 years). Within the last year, participants indicated that they have taken

numerous OHV recreational trips with over half (51.7%) having taken over 20 trips.

Participants have not been recreating as long at the CMA, with only 27.3% of participants

having recreated at the CMA for over 10 years and a mean of 8.1. Close to 32% of participants

have made over 20 trips to the CMA within the last year, with a mean of 18.6 trips per

participant. Users of the CMA also tend to recreate with family, as 85% recreated with at least









one other family member on their last trip and approximately 20% travel to the CMA with at

least 5 other members of their family. It is important to highlight that 18% of the participants live

in the southeastern or southwestern regions of Florida, indicating substantial travel time to the

CMA for a significant percentage of the participants.

Participants were asked for their zip code in order to evaluate their home region. Survey

results (Figure 2-1) indicate that visitors traveled not only from different parts of Florida but also

from other states and countries (4%) to recreate at the CMA. West-Central Florida was the home

region of the largest percentage (3 5.9%), with the counties surrounding the CMA contributing

close to a quarter (24.9%) of the survey participants.

The on-site and mail back surveys also asked participants questions pertaining to trip

activities and experience while at the CMA (Table 2-3). Participants were asked to indicate what

their primary OHV was at the CMA. Utility ATV, sport quad, motorcross bike, and trail/enduro

bike were cited with about the same frequency. Trials bike was only used by about 2% of the

participants as their primary OHV. In addition, the breakdown of use between two and four

wheeled OHVs, was about equal with 46% saying they ride two wheeled OHVs (utility ATVs

and sport quads) and 56% listing four wheeled OHVs (trail/enduro, motorcross, and trials bikes)

as their primary OHV at the CMA. About 41% of the respondents ride another type of OHV in

addition to their primary type while recreating at the CMA. The maj ority of survey participants

(44.7%) consider themselves of intermediate skill level and 27% consider their skill level to be

advanced. The on-site survey asked the participant to rank their last trip to the CMA on a scale of

1 to 10 with 10 being a perfect trip. Close to 29.3% considered their last trip to be perfect by

indicating a ranking of 10. The vast maj ority also gave high satisfaction scores with 92%

indicating a score of 7 or higher for their last trip to the CMA.










Table 2-1. Visitor characteristics of respondents.
Variable

Gender of Survey Participant (N = 148)
Male
Female

Age (N = 106)
18-29
30-39
40-49
Greater than 50
Marital Status (N = 146)
Single
Married

Separated / Divorced
Widowed
Children under 18 (N = 147)


1 to 2
More than 2
Ethnic Origin (N = 144)
African American

Hispanic / Latino
Caucasian
Native American
Level of Education (N = 146)
Some High School
High School Graduate / GED
Some College
Trade / Vocational School
College Graduate
Some Graduate School
Graduate Degree
N= Number of valid survey responses


Valid Percent


84.5
15.5


17.0
22.6
48.1
12.2


21.9
67.8
9.6
0.7


38.1
50.3
11.6


1.4
3.5
91.0
4.2


8.9
14.4
12.3
17.1
24.7
1.4
21.2










Table 2-1. Continued
Variable Valid Percent

Level of Household Income (N = 141)
Less then $15,000 1.4
$15,000-$24,999 0.7
$25,000-$34,999 2.8
$35,000-$44,999 9.9
$45,000-$54,999 10.6
$55,000-$64,999 9.2
$65,000-$74,999 11.3
$75,000-$84,999 12.1
$85,000-$94,999 7.8
$95,000-$104,999 5.7
$105,000-$124,999 5.7
$125,000 and above 22.7
Employment (N = 147)
Business owner 24.5
Homemaker 2.7

Manager/Executive 12.2
Professional worker 19
Sales worker 3.4
Skilled trade 23.8
Laborer 0.7
Permanently disabled 0.7
Retired 1.4
Service worker 2
Student 2
Other 7.5
N= Number of valid survey responses











Table 2-2. Trip Characteristics of Respondents.
Variable
Number of years riding OHVs for recreational purposes
(N 149)
Less than 3
3 to 10
11 to 20
21 to 30
More than 30
Total OHV recreational trips taken within the last year
(N = 149)
1 to 3
4 to 10
11 to 15
16 to 20
21 or more
Number of years ridding OHVs at the CMA (N = 149)
Less than 3
3 to 10
11 to 20
21 to 30
More than 30
Total number of trips to the CMA within the last year
(N = 147)
1 to 3
4 to 10
11 to 15
16 to 20
21 or more
Total household party size on last trip to the CMA (N = 147)







5 or more

N= Number of valid survey responses


Valid Percent


Mean

16.34


16.0
28.7
22.0
17.3
16.0


27.81


6.0
21.5
13.4
7.4
51.7


41.3
31.3
17.3
6.7
3.3



16.2
29.7
13.5
8.8
31.8


15.0
26.5
25.2
13.6
19.7


8.08


18.63


3.20











Valid Percent
Region (% N345)*

North-West Florida < 1
North Florida 2.3
CMVA area counties 24.9
East-Central Florida 14.5
West-Central Florida 35.9
South-East Florida 8.4

South-West Florida 9.6
Non-Florida 4

IMean one-way travel distance (mi) 115.27
*Information based on zip codes given on on-site
surveys
N= Number of valid survey responses

Figure 2-1i. Region of residence of CMA visitors.


Table 2-3. Activities and experience of Croom Visitors.
Variable

Primary OHV ridden at the CMA (N = 334)
Utility ATV

Sport Quad
Motorcross Bike
Trail / Enduro Bike
Trials Bike

Self Reported Skill Level (N = 329)

Beginner
Novice
Intermediate
Advanced

Expert
1 to 5
Participant rating of last visit to the CMA (N = 355)







10
N= Number of valid survey responses


iirbr


Valid Percent


26.0
27.8
26.0
18.0
1.5


6.1
12.2
44.7
28.6
8.5
3.8


4.0
16.5
28.4
18.0
29.3









CHAPTER 3
REGIONAL ECONOMIC IMPACT OF OFF-HIGHWAY VEHICLE RECREATION AT THE
CROOM MOTORCYCLE AREA THROUGH INPUT-OUTPUT ANALYSIS

Introduction

When studying economic impacts of outdoor recreation a common technique used is that

of input-output analysis. This is achieved by collecting travel expenditure data through surveys

administered to the recreation participants (Donnelly et al., 1998; Briassoulis, 1991; Fletcher,

1989). The direct benefits that the surveys establish can then be used to estimate the indirect and

induced benefits through the implementation oflI-O models (Cordell et al., 1992; Zhou, 1997). I-

O models consider inter-industry relations in a regional economy, as well as their interrelations

with final demanded sectors (households, employees, government, and trade) in order to evaluate

the impact that an industry or, as in the case of this study, an activity can have on the local

economy (Leontief, 1986; Millar & Blair, 1985). I-O analysis has become a popular tool for the

estimation of regional economic impact by an activity and has been applied numerous times

towards this end in recreation studies (Loomis, 1995; Bergstom et al., 1990; Propst; 1985). The

IMpact Analysis for PLANning (IMPLAN) software, a computer based modeling system that

was developed by the USDA and modified to estimate economic impacts, is the most commonly

used I-O model (Donnelly et al., 1998).

Studies using the IMPLAN input-output models to capture the direct, indirect and

induced impacts of OHV recreation to state and local economies have been undertaken on

several occasions. A study in Colorado estimated that OHV recreation contributed $314 to $354

million to the Colorado economy and supported 3,196 to 3,515 full and part-time jobs (Hazen

and Sawyer, 2001). A similar study undertaken in New Hampshire found that OHV recreation

contributed around $318 million to the state' s economy and helped to maintain 2,379 jobs










(Okrant & Gross, 2004). In Maine a study indicated that OHV recreation, not including

snowmobiles, contributed over $200 million and helps to sustain 1,975 jobs (Morris et al., 2005).

As with other forms of nature-based recreation that have garnered the attention from

states as a rural development tool (Che, 2003; Lindberg et al., 1996), OHV recreation has not

gone unnoticed in this regard, as states have recognized its' rural development potential (ATV

Task Force, 2003; Vail & Heldt, 2004). However, investigation of the literature did not reveal

any economic impact study focusing on the impacts from a single riding facility, nor did it find a

study looking at impacts to any region smaller then that of a State.

Model Description

As is often done in establishing recreational economic impacts, the regional economic

impact assessment for this study was achieved by developing an economic model using the

Impact Analysis for Planning (IMPLAN) software for the four county area that surrounds the

Withlacoochee State Forest. IMPLAN is a software package for the construction of I-O models

to simulate the effects on economic activity that results from a change in the demand for goods

and service in a given region.

Before running the model in IMPLAN it is necessary to achieve a reliable expenditure

estimate to be introduced as the direct impact, or shock, into the model. Furthermore, to

adequately evaluate the impact of the CMA to the regional economy, it is necessary to estimate

the separate expenditures for residents and non-residents of this region in order to satisfactorily

calculate the new money introduced to the region. Detailed survey questions on travel and

equipment purchases, county of residence, and purchase location were used to compute the "new

money". This new money (otherwise known as the direct impact) quantity will have a ripple

effect throughout the economy (for a further mathematical description of the I-O model, see










Appendix E). The estimated total user-days of 71,500 for fiscal year 2006 was provided by the

Florida Division of Forestry and used to estimate total number of households visiting the CMA.

This estimated household population was then applied to average household expenditure per trip

and average annual equipment expenditure to establish total expenditure for CMA visitors. For

the purpose of this analysis, economic impact was assessed for the counties of Hernando, Pasco,

Sumter, and Citrus. As such only the percentage of expenditure, as identified by the survey

participants, was used in the establishment of the total economic impact. Expenditure levels were

evaluated for both residents of the four county region and non-residents.

There are three types of economic impacts that input-output modeling will capture:

* Direct impacts- the initial expenditures that OHV participants make. The total expenditure
level, direct impact, as the impetus for additional impacts.

* Indirect impacts- inter-industry change within the economy as they adjust their output
levels to meet the demands of directly affected industries, as these industries will adjust
inputs to the change in final demand. (Type I impacts, sum of direct and indirect impacts)

* Induced impacts- industry sectors that are both directly and indirectly affected will undergo
income changes, further affecting other sectors as employees adjust their expenditures
based on income level. (Type II impacts, sum of type I and induced impacts)

The sum of the direct, indirect, and induced impacts provides the total impacts that an

activity generates. Impact estimates are provided in terms of sales, income, indirect business

taxes, and jobs for the analysis region, and are given as follows:

* Output- total change in sales revenues.

* Value added- change in personal and business net income including property related
income such as rents, dividends and interest.

* Labor income- change in employee wages and salaries.

* Indirect business taxes- the impact to the regional economy from a change in taxes, fees,
licenses, and other payouts to government. (not including federal income taxes)

* Employment- an impact estimate based on a change in full and part-time jobs.












Total Population Estimate

In order to establish the total economic impact of OHV recreation at the CMA, it was

first essential to establish the total population recreating at the CMA. As the survey was designed

on a per household basis, total population would be defined as total households recreating at the

CMA. The Florida Division of Forestry estimates total user-days for fiscal year 2006 to be

71,500. Table 3-1 summarizes the results in establishing total household population for both

resident and non-resident households. Dividing total user-days by mean household size per trip

derived total household user-days. Dividing total household user-days by the mean number of

trips per household provides the total households recreating at the CMA. The total household

day-trip estimates of 6,088 and 16,283 by resident and non-resident households respectively

were applied to mean expenditure per trip to evaluate total annual trip expenditure. The total

population estimates of households recreating at the CMA of 3 13 and 1,347 resident and non-

resident households, respectively, were used to evaluate total annual equipment expenditure.

Trip Expenditure

Trip expenditure levels were evaluated for both residents and non-residents. The

estimated day-use populations of 6,088 and 16,283 respectively (Table 3-1) were multiplied by

mean household trip expenditure (column N, Table 3-2) to achieve total annual household trip

expenditure (column O, Table 3-2) with total resident expenditure estimated at over $1.1 million

and non-resident expenditure at about $5.7 million. As the study is evaluating the regional

economic impact to Hernando, Pasco, Sumter, and Citrus counties ,the total annual trip

expenditure column is multiplied by percentage of expenditure survey participants indicated that

they made within the four-county region, 93.9% and 57.4% for residents and non-residents


Results










respectively (Table 3-1). The resulting total annual trip expenditure (column P, Table 3-2) is

estimated at just over $1 million for residents and over $3.2 million for non-residents. OHV

related purchases (row A, Table 3-2) was the category of greatest expenditure for residents at

$0.5 million. For non-residents, purchases related to transportation (row B, Table 3-2) were the

category of greatest expenditure at almost $1.2 million. Entertainment, gift and souvenir

purchases (row E, Table 3-2) was the category of lowest expenditure for both resident and non-

residents .

Equipment Expenditure

Total annual equipment expenditure was also evaluated for both residents and non-

residents. The population of individual households that travel to the CMA was estimated at 313

resident households and 1,347 non-resident households (Table 3-1). Multiplying household

population estimates by mean annual expenditure per household (column Q, Table 3-3) generates

total household equipment expenditure (column R, Table 3-3). Using only the percentage of

expenditure indicated in Table 3-1 provides the total regional annual equipment expenditure

estimate (column S, Table 3-3). Total regional equipment expenditure is estimated at over $2.1

million for residents and about $7.0 million for non-residents. New OHV purchases (row L,

Table 3-3) was the highest expenditure category for both residents and non-residents, with total

expenditure levels of $1.4 million and 4.0 million respectively. The sum of resident and non-

resident total expenditure for both trip and equipment expenditures is $13.59 million and

represents the direct impact to the region resulting from OHV recreation at the CMA. The direct

expenditure was then distributed across the IMPLAN sectors (Table 3-4) to serve as shocks to

those sectors within the model. This shock, or direct impact, will result in indirect and induced

impacts as are described in the following section.









Regional Economic Impact Estimate

Table 3-5 summarizes the results of the input-output model in determining the economic

impacts of OHV riding at the CMA. Total output impacts were estimated at $21.7 million. Direct

output impacts were estimated at $13.6 million and measure the direct purchases made by OHV

users in the pursuit of their activity. The indirect output impacts, that capture the activity

between industries, were estimated at $1.5 million. Induced output impacts, increased activity

resulting from industry employees, were estimated at $6.6 million. Looking at the value added

portion of the impacts associated with an activity is often more important to policy makers than

focusing only on the output impacts. The value added is an estimate of the additional value

created within the region as a portion of total output. The value added impact was estimated at

$14.7 million, comprised of $9.6 million in direct, $0.8 million in indirect, and $4.3 million in

induced impacts. Total impacts resulting from a change in labor income was $9.4 million,

consisting of $6. 1 million, $0.5 million, $2.8 million in direct, indirect, and induced impacts

respectively. Total indirect business taxes impact was $2. 1 million and comprised of $1.7

million, $0.06 million, and $0.3 million in direct, indirect and induced impacts. Total impacts to

employment of 318 full and part-time jobs were estimated to have resulted from this activity,

with 215 direct, 16.4 indirect, and 86.9 induced job impacts.

Economic impacts from OHV use at the CMA are disaggregated in Table 3-6 to see the

impacts to industry groups within the counties of Hernando, Pasco, Citrus, and Sumter (see

appendix E to view the direct, indirect and induced impacts of each industry group and by impact

type). The largest impacts are within the retail trade industry group with output impacts of $11.6

million, $8.8 million in value added impacts, and 196 job impacts to employment. Other industry

groups with total output impacts of over $0.5 million are government, real estate and rental, other










services, health and social services, accommodation and food service, and construction. In

addition, all of these industry groups had total employment impacts of over eight j obs.


Table 3-1. Population Estimate of visitors to the CMA.

Resident

Estimated total user days, 2006 71,500*

Percent of user population 24.9

Total User-days 17,804

Household members per Trip 2.9

Total household user-days 6,088

Number of trips per household 19.5

Total households riding at the CMA 313
Percent of expenditure made within
93.9%
region
*Total user days estimate provided by the Florida Division of Forestry


Non-Resident



75.1

53,697
3.3

16,283
12.1

1,347

57.4%










Table 3-2. Trip expenditure of a typical visitor to the CMA and total trip expenditure for
2006.


Total estimated
household
expenditure within
region of analysis
(millions of $)
.Non-
Resident.
Resident


Total estimated
household trip
expenditures
(millions of $)
.Non-
Resident .
Resident


Mean Household
expenditure per
trip

.Non-
Resident .
Resident


Expenditure Category


OHV related purchases
(gas, equipment, etc.)
Purchases related to
transportation to the
CMA (gas, tolls, rental
fees, etc.)
Food & beverage
purchases
Lodging (hotel, motel,
campsite, etc.)
Entertainment, gift and
souvenir purchases
Miscellaneous/other
purchases
Total


$72


$0.53 $1.17 $0.50 $0.67


$126 $0.22 $2.04 $0.21 $1.17


$79

$41


$0.27 $1.29 $0.25 $0.74

$0.08 $0.67 $0.07 $0.38

$0.02 $0.20 $0.02 $0.11

$0.05 $0.37 $0.04 $0.21


$3 $12

$8 $23


$191 $352 $1.16 $5.74 $1.10 $3.29










Table 3-3. Equipment expenditure of a typical visitor to the CMA and total equipment


expenditure for 2006.





Expenditure Category


Q

Mean annual
household
equipment
expenditure


Total estimated
household
expenditure
within region of
analysis (millions
of $)
.Non-
Resident.
Resident


Total estimated
household
equipment
expenditures
(millions of $)
.Non-
Resident .
Resident


.Non-
Resident .
Resident


Repairs / routine
maintenance to OHVs
G (gas/oil, lubricants, tools,
air filters, tires, wear
items, etc.)
OHV equipment
modifications and
upgrades (exhaust,
suspension, other
aftermarket accessories,
etc.)
OHV Riding apparel
(helmets, boots, eye
I protection, gloves,
additional protective
clothing)
Equipment or purchase of
rentals related to the
transport of OHVs
(transport vehicle, trailer,
gas/fuel, loading ramp,
tie-downs, etc.)
OHV expenditure related
to permits, fees (day-use
fees, special events fees,
competition entry fees,
etc.), insurance, Titling,
club membership
L New OHV Purchases
Miscellaneous/other
M purchases related to
OHV riding
Total


$661


$746 $0.21 $1.01 $0.19 $0.58


$538 $869 $0.17 $1.17 $0.16 $0.67





$333 $597 $0.10 $0.80 $0.10 $0.46


$721 $1,139 $0.23


$1.53 $0.21 $0.88


$158


$336 $0.05 $0.45 $0.05 $0.26


$4,774 $5,178 $1.49 $6.97 $1.40 $4.00

$196 $237 $0.06 $0.32 $0.06 $0.18

$7,381 $9,105 $2.31 $12.26 $2.17 $7.04












Table 3-4. Regional impact events by IMPLAN sector.
.Non-
Resident*
Resident
Expense Item Implan Sector (millions ..
of $)(millions
off $)


Gas, equipment for OHV

Transportation to the CMA (gas, tolls'
rental fees, etc.)

Food & beverage


Lodging (hotel, motel, campsite, etc.)


Entertainment, gifts and souvenirs


Miscellaneous/other

Repairs / routine maintenance (lubricants
tools, air filters, tires, wear items, etc.)

Equipment modifications and upgrades
(exhaust, suspension, other aftermarket
accessories, etc.)
Riding apparel (helmets, boots, eye
protection, gloves, additional protective
clothing)
Transport equipment purchase or rental
(vehicle, trailer, gas/fuel, loading ramp,
tie-downs, etc.)

New OHV purchase


Permits, fees, insurance, titling, club
membership

Miscellaneous/other purchases related to
OHV riding


407- Gasoline stations


407- Gasoline stations

405- Food and beverage
stores

479- Hotels and motels

478- Other amusement
and recreation
industries
411- Miscellaneous store
retailers

483- Automotive repair
and maintenance

401- Motor vehicle and
parts dealers

408- Clothing and
clothing accessory
stores
432- Automotive
equipment rental and
leasing

401- Motor vehicle and
parts dealers
499- Other state and
local government
enterprises
411- Miscellaneous store
retailers


$0.50


$0.21


$0.25


$0.07


$0.02


$0.04


$0.19



$0.16


$0.67


$1.17


$0.74


$0.38


$0.11


$0.21


$0.58



$0.67


$0.10


$0.21



$1.40


$0.05


$0.06


$0.88



$4.00


$0.26


$0.18


*Participants residing in the counties of Citrus, Sumter, Hemnando, Pasco Counties










Table 3-5. Direct, indirect and induced regional economic impact of OHV recreation at the
CMA.

Output Value Added Labor Income Indirect Business Employm
(millions of $) (millions of $) (millions of $) Taxes (millions of $) ent (Jobs)

Direct $13.59 $9.55 $6.13 $1.75 215

Indirect $1.50 $0.82 $0.50 $0.06 16

Induced $6.57 $4.32 $2.75 $0.33 87

Total $21.66 $14.69 $9.38 $2.14 318










Table 3-6. Total regional economic impact by industry group for OHV activity at the CMA.


Value
Added
(millions
of $)
0.025

0.001

0.224

0.296

0.064

0.121

0.171

8.804

0.094

0.234

0.719

0.196

0.033

0.163

0.020

0.565

0.115

0.499

0.567

1.782

14.689


Labor
Income
(millions
of $)
0.011

0.000

0.068

0.256

0.046

0.068

0.131

5.691

0.048

0.109

0.292

0.167

0.025

0.129

0.019

0.491

0.066

0.305

0.420

1.032

9.376


Indirect
Business Taxes
(millions of $)

0.001

0.000

0.032

0.004

0.001

0.026

0.004

1.723

0.008

0.007

0.065

0.003

0.001

0.005

0.000

0.006

0.014

0.064

0.072

0.104

2.139


Empl oy-
ment
(Jobs)

0.8


Output
(millions
of $)

0.047

0.001

0.311

0.733

0.258

0.159

0.273

11.598

0.261

0.371

1.490

0.381

0.060

0.323

0.037

0.898

0.192

0.827

1.185

2.256

21.661


Industry Group (NAICS)*


Ag, Forestry, Fish &
Hunting
Mining

Utilities

Construction

Manufacturing

Wholesale Trade
Transportation &
Warehousing
Retail trade

Information

Finance & insurance

Real estate & rental
Professional- scientific &
tech svcs

Management of companies
Administrative & waste
services
Educational svcs

Health & social services
Arts- entertainment &
recreation
Accommodation & food
services
Other services

Government & non NAICs

Total


0

0.8

8

1.2

1.7

3.3

195.7

1.3

2.7

12.5

4.9

0.5

5.4

0.9

12.4

3.8

17

20.8

24.2

318


*North American Industry Classification System









CHAPTER 4
CONSUMER SURPLUS ESTIMATION: AN INDIVIDUAL TRAVEL COST METHOD
APPROACH

Introduction

The previous chapter dealt with the economic impact estimation through input-output (I-

O) analysis. I-O analysis is inherently a supply side model as it is designed around regional

production process (Leontief, 1986). While the data that I-O analysis provides is useful to

recreational planners and policy makers, it does not fully capture the impact or benefit of a

recreation area to society as it fails to capture the benefits to consumers. To capture this value of

a resource it is necessary to evaluate consumer surplus (CS). CS can be defined as the total value

that recreational consumers place on the resource minus actual expenditures. The estimation of

consumer surplus is achieved through the quantification of the area under the demand curve of a

user between the choke price and the price actually paid (Dobbs, 1993).

One approach for the calculation of this demand curve is the travel cost method (TCM).

The TCM is derived from revealed preference theory (Ward & Beal, 2000); hence it is based on

real market data as the purchase decisions have already been made by the participant (Oh et al.,

2005). TCM allows one to determine a Marshallian demand curve to calculate the area between

consumers actual price and the maximum price they are willing to pay.

Potential visitors to a site will decide to visit that site only if they achieve some value

from their visit or their costs are not greater than their perceived benefit (Siderelis & Moore,

1995). In accordance with demand theory, as the cost of the trip to a site increases, the visits will

decrease (Fix & Loomis, 1997), allowing one to derive a site demand curve. As such, the value

of this site can then be estimated using a site demand model (Siderelis & Moore, 1995; Hesseln

et al., 2004; Dobbs, 1993).









Within TCM there are two methods, zonal and individual. Zonal TCM is based on census

data and arbitrary geographic areas generated by zip codes leading to zonal bias (Bowker et al.,

1996). Individual TCM (ITCM) is based on survey information gathered from visitors to the site.

In addition to avoiding zonal bias, it is possible to incorporate further explanatory variables

within the demand function through the collection of data on trip and visitor characteristics

(Siderelis & Moore, 1995). Given the above, the ordinary demand function for a user of a

recreation area is t = f(TC, TD, TChar, VChar) where :

* t = number trips per year

* TC = travel cost per trip

* TD = travel distance per trip

* TChar = vector of trip characteristics variables

* VChar = vector of visitor characteristics variables.

The estimation of CS for recreation sites through the use of ITCM has been used

extensively. Siderelis & Moore (1995) concluded that the total consumer surplus from three

different rail-trail sites throughout the United States ranged from $1.9 million to $8.5 million

($9.56-$49.78 individual CS per trip). Shrestha et al. (2002) estimated that CS to be between $35

million and $57 million ($540.45-$869.57 individual CS per trip) for recreational fishing visitors

to the Brazilian Pantanal. Another study undertaken by Oh et al. (2005) on recreational fishers of

the Sam Rayburn Reservoir in Texas evaluated individual CS per trip to be between $249-$414.

Lockwood & Tracy (1995) evaluated the CS of an urban park in Australia to be between $23

million to $33 million. However, with the exception of a study on snowmobiling in Wyoming

where individual CS per trip was estimated at $68 (Coupal et al., 2001), no other study on the

estimation of CS for OHV recreation was found.









ITCM Model Specification

There are several alternative methods for establishing demand models (Dobbs, 1993).

This study uses the continuous ordinary least squared (OLS) model with a logarithmic

transformation of the dependent variable. The semi-log OLS method has been applied many

times for the estimation of consumer surplus (CS) for recreation participants (Balkan & Kahn,

1988; Willis & Garrod, 1991). Alternative models that have been used include OLS without the

logarithmic transformation of the dependent variable and maximum likelihood estimators

(Hesseln et al., 2004; Shrestha et al., 2002). Two studies that have utilized the semi-log OLS

model along with the alternative models have indicated the semi-log OLS CS estimate to be a

median value estimate compared to other models (Smith, 1988; Siderelis & Moore, 1995)


Table 4-1. Description of variables used in the ITCM model.

Variable Description

TRIP S Total number of household trips taken in the last year.

TRVLCOST Household travel cost per trip.

DISTTRVL One-way travel distance to the CMA.

YRSRIDCMA Years riding at the CMA.
FMPRTYSZ Family party size riding at the CMA
Overall rating of last trip to the CMA. (Scale of 1 to 10 where 10 is a
TRPRATING
perfect trip)
Primary OHV type ridden at the CMA.
OHVTYPE
(0 = ORM, 1 = ATV)
Dummy variable for multi-day trips to the CMA.
OVRNGHTDM...
(1 = made at least one overnight trip within the last year)
GENDER Gender of the survey participant. (1 = male, O = female)


In the construction of the semi-logarithmic OLS model to evaluate individual household

and total consumer surplus for this study, explanatory variables were evaluated in addition to the

travel cost variable to further refine the final model, as such various trip and visitor









characteristics variables were included in the model. TRVLCOST, DISTTRVL, and

YRSRIDCMA were included in the several regression models that were constructed

incorporating contrasting groupings of trip and visitor characteristics. Visitor characteristic

variables were never significant predictors in the models, as such all except for GENDER were

not included in the final model, as shown in equation 4-1, which was selected based upon its

goodness of fit to the population as evaluated by the adjusted R2 Statistic and reached its highest

level with the inclusion of these variables in equation 4-1. The description of the variables used

are given in Table 4-1.


EnTRIPS = P, + P,(TRVLCOST) + P,(DISTTRVyL) + P (YRS~RIDCM4 ) + P (GENDER) +
4 (OIHVT/ YPE) + 96 (FMPRT2Y~SZ )+ P (OVR/NG;HTDMI ) + P, ('TRPRATING ) (4-1)


To estimate the individual CS from the resulting model, it is necessary to evaluate the

area under the demand curve generated by the semi-log OLS model. Normally this would be

accomplished by the calculation of the integral of the function. However, since the semi-log form

was used the accepted estimation method, as described by Smith and Devouges (1985), is to

approximate the integral as the negative inverse of the coefficient on the travel cost, -18)

Results

Table 4-2 summarizes the descriptive statistics of the variables used in the regression

model. As a non-response in any variable will result in the entire case be excluded when

conducting linear regression, the sample size for this analysis was 139 out of the initial 150

cases. Survey questions reveled that households in this sample make over 18 (18.68) trips

annually to the CMA and spend over $255 on average per trip on travel related expenses. On

average, households travel over 104 miles one-way and recreate at the CMA with over 3 family

members. Participants tended to be loyal to the CMA through the indication that they have been









riding there for almost 8 (7.92) years and showing an overall enj oyment of their experience,

giving the CMA a mean score of 8.46 out of a maximum of 10. Types of vehicles ridden at the

CMA were almost equally split between off-road motorcycles (ORM) (48.9%) and all-terrain

vehicles (ATV) (51.1%). Over 56. 1 indicated that they made at least one overnight trips within

the last year. The gender results must be interpreted with a bit of caution as the surveys were

designed on a household basis to reduce the complexity and length of the survey. As such the

variable GENDER may under-represent females.

As stated, the final model was selected based on the adjusted R2 value, in this case 0.275

(Table 4-3). The R2 Value is 0.317. But since R2 tends to optimistically estimate the model fit to

the population, the adjusted R2 ValUe WaS used.

As the key property of the ITCM is the inverse relationship between the travel cost

variable and that of the number of annual trips taken, without this relationship it would be

impossible to get a demand function and the corresponding estimate of the CS. As shown in

Table 4-3, an inverse relationship does exist as TRVLCOST has a negative impact on the

number of trips taken and is significant (p=0.03 1).

In looking at the other explanatory variables in the model, for variables are significant at

the P<0.05 level. DISTTRVL has a negative effect on trips taken with a p-value of 0.01. The

negative sign on DISTTRVL was expected, one would expect to observe a decline in trips taken

as the distance needed to travel to an area increases. Another highly significant variable is

YRSRIDCMA (p=0.004) and it exhibits a positive relationship with trips taken. It is also

important to note that this variable was always the most significant and always at the P<0.010 in

every model run. This result is highly suggestive of habit formation of users at the CMA, as the

more users experienced the CMA, the greater the amount of trips they would make in a year.









TRPRATING was significant with a p-value of 0.016 and had a positive relationship with trips

made. Again, this was a result that was anticipated, as one would expect to observe an increase in

trips taken with an increased enj oyment of their experience. The variable FMPRTYSZ was

significant at the P<0. 10 level (p=0.051), with a negative impact on trips taken, hence the greater

the family riding groups is, the fewer the trips taken.

While the remaining three variables are not significant at the P<0.10, it is interesting to

note that visitor characteristics were not significant, nor were the socio-demographic variables

significant in any of the various models created. This result was not expected. Often socio-

demographic such as age, sex and income are significant predictors of the dependent variable,

not in the case of OHV recreation.

Total Consumer Surplus Estimation. By taking the negative inverse of the

TRVLCOST coefficient -(1/-6.232E-04), the resulting individual household CS per trip is

estimated at $1,605. To evaluate total annual CS, it is necessary apply this to total household

trips, 19,455 the number of unique trips of all households to the CMA. As such, the total annual

household CS is estimated at $31.23 million.










Table 4-2. Descriptive statistics of variables used in the model (N = 139).
Variable Mean

Total trips to the CMA 18.68

TRVLCOST ($) $255.01
DISTTRVL 104.31


YRSRIDCMA

FMPRTYSZ

TRPRATING


7.92

3.20

8.46




48.9

51.1


43.9

56.1


16.5

83.5


OHVTYPE

Off-road motorcycles (0)

All-terrain vehicles (1)
OVRNGHTDM

No overnight trips (0)

Made at least one overnight trips(1)
GENDER

Female (0)

Male (1)












Standard. Error
.632

.000

.001

.009

.225

.176

.044

.178

.064


Table 4-3. Regression model results (N = 139).

Variable Coefficient (Beta) P-value

(constant) 1.255 0.049**
TRVLCOST -6.232E-04 0.031**

DISTTRVL -1.389E-03 0.010**

YRSRIDCMA 2.694E-02 0.004**

FMPRTYSZ -8.615E-02 0.051*

TRPRATING 0.155 0.016**

OHYTYPE -0.250 0.158

OVRNGHTDM 0.250 0.163

GENDER 0.238 0.292

R2 0.317

Adjusted R2 0.275

** Significance at p < 0.05

* Significance at p < 0. 10









CHAPTER 5
MOTIVATIONS OF OFF-HIGHWAY VEHICLE USERS

Introduction

Visitors to the CMA have made the decision to participate in OHV recreation at that

facility. Previous results have indicated that their decision has generated economic benefit to the

surrounding communities. In addition, visitors to the CMA receive benefits from their

involvement, captured by the individual household consumer surplus estimate per trip of $1,605.

As CS can be defined as the value of the total experience minus travel expenditures (Huppert,

1983; Dobbs, 1993), the CS can also be considered a value estimate of visitors experience at the

CMA. Driver & Tocher (1970) define a recreationists experience as the desired psychological

result (benefit) that motivates them to participate in a recreation opportunity. They only engage

in a recreation opportunity if their efforts lead to their desired benefit (Haas et al., 1981;

Manfredo et al., 1983; Lawler, 1973). Given this, it is important for planners to understand the

desired benefits of visitors in order to provide the opportunities for the attainment of these

benefits (Graefe & Fedler, 1986; Stein & Lee, 1995; Driver, 1985). By providing these

opportunities, planners can aid in the production of economic, personal, social and

environmental benefits that result from the individual's choice to participate in a recreation

activity (Brown, 1984; Stein & Lee, 1995).

Research on the desired benefits of visitors has been ongoing since the 1970s (Stein et al.,

2003). There has been a profusion of studies done on recreational activities to identify the

desired benefits that motivate the individual to participate in a given activity. Loomis & Ditton

(1987), Wilde et al. (1998) and Fedler & Ditton (1994) investigated the benefits that are

important motivations to recreational anglers. Cross-country skiers were studied by Haas et al.

(1981) to identify their desired benefits. Other studies have looked at and determined the benefits









for backpacking (Brown & Hass, 1980) and hunting (Hautaluoma & Brown, 1978). Studies have

also found that experiences are not homogenous to activity classification, that, in fact, benefit

sub-groups exist within activities (Manfredo et al., 1983; Brown & Haas, 1980; Hautaluoma &

Brown, 1978). Yet, no study could be located that attempted to establish the desired benefits for

recreational OHV users, nor potential subgroups within the activity.

Data Analysis

To identify the desired benefits that motivate visitors to participate in OHV recreation at

the CMA, a 19-item list was given where the participant was asked to rate the importance of each

benefit item as a motivation for their involvement'. Cluster analysis was then undertaken on the

19-item list in order to classify respondents into homogenous subgroups based on their similarity

in motivational responses (Lorr, 1983). This approach has been applied many times in recreation

research as a means of identifying homogenous subgroups (Purnomo et al., 2005; Manfredo et

al., 1983; Oh et al., 2005; Hautaluoma & Brown, 1978; Collins & Hodge, 1984; Stein & Lee,

1995) and undertaken using the K-means cluster procedure using SPSS 11.0 for Mac. A final

solution of three-clusters was accepted based on the size and interpretability of the resulting

groups (Hair et al., 1998; Lorr, 1983).

Results

Desired Benefit Profile of OHV Users at the CMA

The mean responses for each of the 19 benefit variables are listed in descending order in

the first column of Table 5-2. A look at the overall means illustrate the family oriented nature of

the motivations behind OHV recreation. The benefits to "be with friends and family" (mean =

4.47) and "strengthen family kinship" (mean = 4. 17) are the top two ranked benefits.


SFor this purpose a Likert scale was used where 1 = Not at all important, 2 = Not very important,
3 = Important, 4 = Very important, 5 = Extremely important









Additionally, the results indicate that individual oriented benefits are also important to OHV

recreationists. Ranked third and fifth respectively were to "reduce tensions and stress from

everyday life" (mean = 4. 14) and "improve my skills and abilities" (mean = 4.05). The two other

benefits with a mean ranking of over four were to "enj oy nature" (mean = 4.07) and "promote

physical fitness" (mean = 4.03), ranked fourth and sixth respectively. Ranked at the bottom of

the list of motivations and two of only three benefit statements with a mean of below three, are to

"engage in personal / spiritual reflection" (mean = 2.81) and "take risks" (mean = 2.63), ranked

17th and 19th respectively and individualistic in nature. Taken as a whole, the population

participates in OHV recreation at the CMA mainly for the attainment of family based benefits

but, while less important, place some significance on individual benefits.

Benefit Subgroup Identification

Cluster analysis classified the participants into three subgroups based on their

motivations for participating in OHV recreation at the CMA (Table 5-1). To identify the

motivational makeup of the three groups, an analysis of variance (ANOVA) test was undertaken

with the cluster group as the factor and the 19 benefit scale questions as dependent variables. By

examining the post hoc test results of the motivational statements for the groups (Table 5-2) and

the listwise ranking of the motivations for each group, evident difference emerges between the

groups.

Group 1 (n = 70, 52.2%), the Experiencers, indicated that both family and individualistic

benefits as important reasons for their involvement in OHV recreation. Post hoc analysis

revealed that Experiencers mean score on 18 out of the 19 variables was either greater than the

other two groups or at least greater than one group while exhibiting no significant difference

with the other group. The only variable in which the Experiencers had a mean score significantly









smaller than another group was the benefit item to "take risks". As Table 5-2 illustrates,

Experiencers had a mean score of over three for each item except the aforementioned "take

risks" (2.79), an indication of the importance for the attainment of multiple benefits as a

motivation for riding. Table 5-3 gives the top and bottom Hyve ranked benefits for each group

with the ranking of the other two groups in the succeeding two columns. While family-based

motivations are the top two, the fourth and fifth are very much individualistic in nature, "reduce

tension" (M = 4.54) and "promote physical Sitness" (M = 4.39).

Group 2 (n=32, 23.9%), Familists, ranked family oriented benefits as primary reasons for

their involvement in OHV recreation. While Familists may have certain top Hyve benefits in

common with Experiencers, Familists are even more family centric in regards to riding

motivations. Where as Experiencers ranked the statement to "Continue family traditions" 12th, it

was 3rd for Group 2 (M = 3.97). The statement to "be in an area where I feel secure and safe", a

motivation one would expect to be higher for families, is ranked fourth by Familists as apposed

to eighth for Experiencers.

Group 3 (n = 32, 23.9%), the Individualists, rated individualistic oriented benefits at the

top for reasons as to why they participate in OHV recreation. Whereas the other two groups

placed importance on family centered benefits, the results indicated that Individualists rode, as

the name would suggest, primarily for the attainment of individual benefits. The top two benefits

for group 3 were to "improve my skills and abilities" (M = 4.28) and "depend on my skills and

abilities" (M = 4. 16). As table 5-3 shows, with the exception of to "promote physical fitness" for

Experiencers (5th), HOne Of the Individualists' top five benefits were ranked within the top five of

the other two groups. Until now the bottom five benefits as shown in Table 5-1 have not been

mentioned, largely due to the similarity between the first two groups. However, looking at









Individualists' bottom five, further illustrates just how centered Individualists are for the

attainment of individual benefits. To "continue personal or family traditions" ranked 3rd by

Familists and 12th by Experiencers, was ranked 15th by Individualists, with a mean score of

below three (2.59). The benefit to "take risks" was ranked last when looking at the overall

population (M = 2.63), last by Familists (M = 1.56), and last by Individualists (M = 2.79), but

was ranked ninth by Group 3, with a mean of 3.34 and the only mean for which Group one had a

significantly smaller mean than another group.

Benefit Subgroup Description

With the knowledge that homogenous subgroups exist based on their desired benefits for

riding OHVs at the CMA, it is important to understand the differences between the groups in

terms of visitor and trip characteristics. To this end, ANOVA and Chi-squared tests were

undertaken to identify if any significant differences in visitor and trip characteristics existed

between the groups.

Table 5-4 and 5-5 display the results of ANOVA and Chi-Squared test respectively on

visitor characteristics. No significant differences were found between groups for the variables

number of children in the household, age, marital status, education, or income. The groups only

differed significantly (p = 0.021) when it came to gender, where Individualists were significantly

more male at 96.9% versus 82.9% for Experiencers and 71.0% for Familists

Considerably more variation existed between the groups when looking at trip

characteristic variables. While no significant difference was found in total number of annual

OHV recreation trips or annual trips to the CMA, Experiencers were more likely to have made at

least one multi-day trip per year, 68.6%, with 56.3 % of Familists making a multi-day trip.

However only 31.3% of Individualists indicated they made at least multi-day trip within the last









year, indicating their preference for day trips, a deviation that is statistically significant (p =

.002). When at the CMA, the groups differ significantly (p = 0.03 8) in their OHV type

preference. While 62.5% of Individualists indicated their primary OHV at the CMA is an ORM,

only 31.3% of Familists rode ORMs, suggesting families may consider a four wheel OHV a safer

alternative. Not surprisingly there was a significant difference (p = 0.020) in mean party size

between the groups with Individualists having a mean of 2.39 people per trip versus means of

3.56 and 3.55 for Experiencers and Familists. Individualists gave the CMA a significantly lower

mean trip rating (p = 0.050), however it is important to note that while they rated the CMA lower

than the other groups, it was still above 8 (8.03).

When looking at total yearly OHV expenditure excluding new OHV purchases,

Experiencers spend more money ($5,077) than either Familists ($2,665) or Individualists

($2,197) a difference that is highly significant (p =0.000). This result is interesting as there was

no significant difference in OHV trips per year and no difference in one-way travel distance to

the CMA. In fact, Individualists traveled further (146.38 mi) than Experiencers (122.45 mi) to

get to the CMA and made more trips in a year (22.75 versus 17.52). As Experiencers are after the

attainment of multiple benefits, this goal may necessitate the outlay of additional expenditure

towards that end.











Table 5-1. Results of cluster analysis (N = 134).
Cluster N

Group 1 (Experiencers) 70
Group 2 (Familists) 32
Group 3 (Individualists) 32










Table 5-2. Desired benefits of respondents and benefit subgroups.
Means


Tukey HSD
Post Hoc
Mean test
Ordering

1,2>3"

1>2>3"


Overall
Mean

4.47

4.17

4.14

4.07

4.
4.03



3.93


3.88

3.70


3.67

3.64

3.57

3.51

3.27

3.15

3.05


2.81


2.68

2.63


Group 1
(Experiencers)

4.74

4.64


Group 2
(Familhsts)

4.53

4.22


Group 3 .
(Individuahists)

3.75

2.97


Statement


Be with friends and family

Strengthen family kinship

Reduce tensions and stress
from everyday life

Enjoy nature
Improve my skills and
abilities

Promote physical fitness

Be in an area where I feel
secure and safe

Depend on my skills and
abilities
Challenge myself and
achieve personal goals

Explore the area and natural
environment

Feel a sense of independence

Continue family traditions

Test vehicle's performance

Meet new people

Escape noise/crowds

Learn about the natural
environment of the area

Engage in personal/spiritual
reflection
Learn about history and
culture of the area

Take risks


a>,3
1>2,3


1,3>2

1>3>2

1>2>3


1,3>2

1,3>2


1>2,3

1>2,3

1,2>3"

1,3>2

1>2,3

1>2,3

1>2,3


1>2,3

1>2>3"

3>1>2"


4.54

4.60

4.36

4.39

4.34


4.26

4.10


4.37

4.13

3.93

3.69

3.66

3.66

3.70


3.51


3.29

2.79


3.66

3.69

3.23

3.31

3.91


2.81

2.69


3.12

2.88

3.97

2.69

2.84

2.47

2.53


1.84


2.25

1.56


3.63

3.37

4.28

3.97

3.03


4.16

3.81


2.87

3.25

2.59

3.91

2.72

2.56

1.81


2.31


2.12

3.34


Note: Means are based on a scale of 1 to 5, where 1 = not at all important, 2 = not very important, 3 = important, 4 =
very important, and 5 = extremely important. Mean differences between the groups were evaluated using the Tukey
Highest Significant Difference test at the p < 0.05 level. a Indicates that the assumption of equal variance does not
hold and the Games-Howell test was used to evaluate mean difference, where p < 0.05.















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Table 5-5. Additional visitor characteristics by cluster membership (X2)


Table 5-4. Visitor characteristics by cluster membership (ANOVA).


Group
mean
rankings


Variable


Overall Group 1 Group 2 Group 3 F


Number of
Children under
~1.17
18 mn
Household


1.731 0.181 NS


1.20


1.47


0.90


Age 40.59 38.90 42.39 40.61 1.068 0.348
aDifference in group means evaluated using Tukey's HSD post hoc test where p<0.05


Variables


Overall Group 1 Group 2 Group 3 2


P


0.021



0.529




0.356


Gender
Male
Female
Marital Status
Married
Single
Education
High school grad or
less
Trade/voc. School or
some college
College graduate and
above
Household income
Below $35,000
$35,000 to $64,999
$65,000 to $94,999
$95,000 and above


83.5
16.5


67.2
32.8


82.9
17.1


65.7
34.3


71.0
29.0


75.0
25.0


25.0

15.6

59.4


0.0
31.3
31.3
37.5


96.9
3.1


62.5
37.5


15.6

34.4

50.0


6.3
18.8
34.4
40.6


7.694



1.273




4.389


23.1 25.7


27.6

49.3


4.5
29.9
28.4
37.3


30.0

44.3


5.7
34.3
24.3
35.7


4.754


0.576











Table 5-6. Trip characteristics by cluster membership (ANOVA).


Group
mean
F P rankings


Variable


Overall Group 1 Group 2 Group 3


Years of riding
OHV' s
Years of riding OHVs
at the CMA
One-way travel
distance to the
CMA
Party Size while
riding at the CMA

Overall trip rating


16.23 15.89 15.13 17.56 0.324 0.724 NS


7.76


7.96


7.27


7.81


0.119 0.888 NS


121.01 122.45 92.37 146.38 0.527 0.592 NS


3.22 3.56

8.46 8.69


3.55

8.41


2.39

8.03


4.028 0.020 1,2>3

3.009 0.050 1,2>3


Variables where homogeneity of variances cannot be assumed


Group
mean
P ranking


Variable


Statisti
c


Overall Group 1 Group 2 Group 3


Total trips to the
CMA
Total Yearly OHV
tnips
Total Yearly OHV
expenditure


18.53 17.52 12.97 22.75 2.37 0.102 NS

27.81 29.12 18.31 32.97 2.89 0.062 NS

3896.4
5076.66 2665.15 2196.88 10.25 0.000 1>2,3


aDifference in group means evaluated using Tukey's HSD post hoc test where p<0.05. bDifference in
group means evaluated using Games-Howell post hoc test where p<0.05. "Brown-Forsythe statistic
used, Asymptotically F distributed. dExluding new OHV purchases.


Table 5-7. Additional trip characteristics by cluster membership (X2)


Variable


Overall Group 1 Group 2 Group 3 X2


Primary OHV type
Four wheel type
Two wheel type
Made a multi-day trip within
the last year
Yes


50.7
49.3


48.6
51.4


68.8
31.3


37.5
62.5


6.529 0.038


56.7
43.3


68.6
31.4


56.3
43.8


31.3
68.8


12.464 0.002









CHAPTER 6
DISCUSSION AND CONCLUSIONS

While much of the literature and public attention towards OHV recreation has centered

on the negative ecological and social impacts resulting from OHV riding, this study investigates

the potential positive impact. Whereas the negative impacts are especially visible, positive social

and economic externalities looked at in this study are largely veiled from public perception. In

the case of the CMA the total economic impact did not occur in one site nor in a single event, but

resulted from thousands of small purchase decisions, by over 1500 households throughout a

years time, and over a wide geographic area. The sum total of the purchases related to recreating

at the CMA was over $13 million, with a total impact of $21 million and over 318 jobs.

The $21 million economic impact is a benefit to the region but this value does not capture

all the benefits generated by the CMA, as it does not capture the user benefits to the CMA. User

benefits as measured by consumer surplus (CS) were evaluated in Chapter 3 and, at over $31

million with an individual household CS per trip at over $1,600, is substantial. Relative to other

TCM valuation studies (page 34), CS per trip was on the high side. But it is not to far above

other estimates when one accounts for the fact that the $1,605 estimate was household CS. As

such, with an average of 3.2 family members per trip the individual CS is $501, which is in-line

with other CS estimates such as Oh et al. (2005) CS estimate of $249-$414 per trip for

recreational fishing site in Texas. The high CS result is consistent with the concept of

commitment which states that a participant' s level of emotional and equipment investment in an

activity is greater for those who are most committed (Buchanan, 1985; McFarlane, 1996; Oh et

al., 2005). A considerable investment results in a larger CS (willingness-to-pay) as they would

have the most to lose from a loss of recreation areas. OHV recreation necessitates a considerable

outlay of thousands of dollars for equipment required to recreate, necessitating a considerable









commitment. One must also consider the scarcity of riding areas when interpreting these results.

The CMA is one of only five riding facilities in Florida and, located at 30 miles north of Tampa,

the southern most OHV riding area. Visitors travel significant distant (over 100 miles one-way)

and make the journey multiple times a year (18.6 annual trips) to ride at the CMA. Their

commitment and the lack of riding areas results in the appreciably large value they place on the

benefits they attain from the CMA, as there are few other opportunities in Florida for the

attainment of the desired benefits of recreational OHV users.

As such, it is important to understand what these highly valued benefits are that riders

hope to attain through their involvement in OHV recreation in order to better manage for the

opportunities that provide them. Results from Chapter 5 indicate that it is in the attainment of

family oriented benefits that are the top two motivations. However, riders also indicated the

importance of individual benefits such as "reduce tensions and stress from everyday life" and

"improve my skills and abilities" as important motivations. Rounding out the top five was

enjoyingg nature" indicating a riding preference for riding in natural settings. The $1,600

individual household CS is the estimated value that households place on the attainment of these

benefits .

It is important to identify potential motivational subgroups, as groups of visitors may ride

for the attainment of benefits that differ from the general population. Understanding these

subgroups allows managers to incorporate their benefits in the planning process to ensure the

continued visitation of these subgroups. Results from cluster analysis in Chapter 5 reveal the

existence of 3 homogenous benefit subgroups: Experiencers, Familists, and Individualists.

Experiencers and Familists did not differ from the general population, in that their top benefits

were still family oriented. However, results show that Experiencers consider the attainment of a









diversity of benefits as motivations for their involvement. Familists were more oriented toward

the attainment of family based benefits than the general population. The Individualists were the

most unique out of the three subgroups. Individualist rode almost exclusively for the attainment

of individual oriented benefits. None of the top five motivations for the Individualists were

within the top 5 of the other two groups, nor the top Hyve of the general population.

Is the CMA providing the necessary opportunities that allow for the attainment by the

visitors of these diverse benefits? While this study did not specifically address this question,

interpretation of the data leads one to conclude that the CMA is providing the opportunities for

the attainment of diverse benefits. Visitors to the CMA have been riding there for almost eight

years and taking an average of over 18 trips annually. Granted, Florida does have limited riding

areas, but this long-term frequent use would not be expected if visitors were not attaining their

desired benefits. Additionally, when participants were asked to rate their last visit to the CMA,

they gave a mean score of 8.46 out of a possible 10. All three motivational subgroups had similar

results in respect to the variables mentioned. The group with the lowest mean years of riding at

the CMA and number of annual trips taken were the Familists, but who have still been riding at

the CMA 7.27 years with an annual average of 12.97 trips. The lowest mean rating was given by

the individualists, but at 8.03 still considered their experience at the CMA worthwhile.

It is because visitors to the CMA attain the benefits they seek, that they return year after

year. The value they place on their benefits is captured by their CS, and is substantial. The

substantial user valuation of these benefits induces their decisions to make purchases in pursuit

of their desired benefits. Their expenditures, in turn, generates economic benefits to the

surrounding communities, through the addition of new money into the region and the associated

additional economic activity.









Policy Implications

Florida has committed to provide several additional riding areas to meet the increasing

demand and reduce the negative impacts associated with OHV recreation. However, this will

only be possible if the new riding areas provide the opportunities for OHV riders to attain their

desired benefits. If Florida is able to design and manage future areas that incorporate the desired

benefits of the participants, the results could be similar to that of the CMA.

This study has illustrated that for OHV recreationists the prime motivations for riding are

for the attainment of family based benefits. As such, future areas need to design areas that would

provide the facilities and experiences that would attract these riders. However, simply designing

areas to attract family OHV riders would fail to attract the maximum number of people as this

study demonstrated that motivational homogenous subgroups exist. While family oriented

benefits are still important, the group Experiencers indicated the importance of multiple and

diverse benefits in riding OHVs. Another group, Individuals, ride almost exclusively for the

attainment of individual oriented benefits.

Planners need to be aware of and manage for the multiple benefits desired by the OHV

riding population, otherwise future areas may be unsuccessful in drawing OHV riders away from

unmanaged and illegal riding opportunities. The CMA has done just this with DOF personnel

indicating that OHV riding is no longer an issue throughout the rest of the Withlacoochee State

Forest. This is attributable to the CMA providing the benefits that riders are looking for. The

DOF has never integrated this type of information into their management plan for the CMA;

however managers have been successfully achieved satisfied users. But understanding why riders

come to the CMA will improve the management of future areas through the integration of

participant desired benefits into the management process. This integration in future area is









crucial as areas may not be as big or rural, hence the need to specialize. In addition, the fact that

the CMA has done this well, gives further weight to the DOF plan to use the CMA as a model

for the design of future areas.

The results from this study testified to the substantial economic impact that OHV

recreation generates to the surrounding communities. The estimate of $21 million in total output

impacts and over 3 18 jobs is a product of the expenditure of visitors to the CMA. Future OHV

areas in Florida will undoubtedly induce economic impact within their region, but the level of the

impact will be directly tied to the amount of riders attracted to the area. Again, to maximize

economic impact, planners need to provide the opportunities that allow OHV riders to attain their

desired benefits. If this is done, results similar to the CMA could be expected, with communities

seeing both economic impact and a reduction in illegal riding on non-OHV lands.

The economic impacts and the natural setting nature of OHV recreation has already

prompted other states and communities to recognized OHV recreation as a potential rural

development tool. But, like other regions, communities in Florida have not been receptive to

potential future areas. This is not surprising given the visible nature of the environmental and

social impacts of OHV recreation along with the hidden nature of economic impacts. By

illustrating the regional economic impacts, additional information is know available for the

decision making process. As such, communities may be more receptive to a potential OHV

riding area as this information has the possibility of adjusting the cost-benefit analysis and

communities may deem the costs acceptable in light of the economic impacts.

Future Work

Towards the understanding of OHV recreation, the largest gap in the data is that of

resident perceptions of the impacts. While some secondary sources exist, no comprehensive










study could be located that looked at how local residents perceived the economic, social,

environmental impacts. Information of this type could further help managers plan OHV riding

areas that would be more acceptable to residents. To date no information could be found that

illustrated the integration of resident perceptions into any OHV area design.

While establishing economic impact was an element of this study and has been

undertaken in other OHV recreation studies, what has yet to be undertaken is a study into the

potential economic impact that the negative externalities of OHV recreation could have on a

region. A region that allows some form of OHV riding, may experience a reduction in visits from

other potential recreation forms that seek an experience void of urban stimuli that OHV machine

noise would eliminate, such as bikers, hikers, birdwatchers, and hunters. The resulting loss of

these visitors, along with the expenditure they would have brought, would function as a negative

externality. A comprehension of the negative economic impacts would provide further

information to policy makers towards the goal of a more efficient and socially acceptable

allocation of resources devoted to OHV recreation.













APPENDIX A
MAP OF THE WITHLACOOCHEE STATE FOREST


I r

C tJ
r
r
c
r
r
r
Groom ~crtElrcycle Ar~a











APPENDIX B
VERBAL CONSENT SCRIPT







Craoom.15crlorcycle Aren Visitor Sandy'

Verbal Consent Script

Hello. My name is and I work for he: University of Florlds. We're working
with the 1* Iondu L;~ ej-rnenl af Agri culhEECB Cons~umer Servces. Division of I arra~y to better
understand visitor preferences and their economic impact fbr off-highwvay vehicle recreation at
the Croom Motorcycle Area, The information we are collef ully, will help us better manager Ihe'
Area and provide desired OHV recreation orpportuities in the Area.

I have a few questions I would likec to ask you which should, take only about two minutes of yousr
time. First, are you al least, 18 years old? (Ifhe~y answert yes cotr~inu, ifna, Andbr th~ individual
r..- IIr :r .,,n aB~ndtRminate the Convelrsation.) If you have the time to spare now, would you
be willing: to answer some questions? i(Krhes- av.,*~lr~ 1., continued, ifd no. tan t~he in~divi~dua
for Mr.-he tijme and~P~ terinte Lscn~vervaion

Thank your for a our n ingch IIC.ll ~ partic~Ipn. You do not have to answer any question you do
not wlsh to answer, and yiou may discontinue participation or withdraw your answder at any rime
withoutr consequence. There is no anticipated risk or direct benefit to participants.
Unfortunately, I cannot compens~ate you for yoIur time, but your participation is greatly
appreclatd. If you have ans quesrican. regardsng thl. project, you may contact D~r. Alavalapart at
3 52-5146-089 or emaail j 3n;h li) It'-as u11.edu Uui RIonsl or conCernS about research participants"
rights may be directed to the UFIRB Offi~ce at 352-3~92-0433, May I begin Ithe survey?~ (ff
answer 9 An, thdA k~ the inddual and terminated th cnversation.~ ~Jif.se, bein thP on-itei
.Curvey.)

Befl-ri ask~in Questiojn 5:

We are~ interested in leapr~nin more about your ClHV recreationyl experience at the Croorm
Motorcycle Are (CMA)i. To do this, I have a more deralet~d question aillrr that you can take! with
you and fill out whien you have thre time. The ;questionnatre takles approximately 15 minutes and
is a onpl tely confidential. Would you be willing to hielp u s with this survey? (,lfthe amuwap ~Is
yes, givea the participant the snail-haock surVEY and contrinn, ifRn. o, thak t individual fr :in tre
timer and teRminate ike+ conversation.)

Cudd you plm easetl me your name and address, ciry, state, andi zipl code so we can send you a
thank you posteardl Even thoiugh [m taking your name and addrss, your particfpatio will be
kept coulklental Ito the extent provitded by law. (~if thy agree to ive~ youa their nam aInd
addrats, wi~te it in the .spalce r,rs..u~ id nd Coni~nue as wcith~ the srvey. Ifn alt hank th~e
individual for hidAje r ime an trmrinate th~e corPnerwain.)

IOwa~gplt the SrVeyBY~ with~l F..j'e .atiL inant.--

Thank you, for participating. Your time~ is greatly apprcicated and is; exlremely belpful to our
st~udy.






















ilDI

Cmeom Motorcyle Area On-site Visitors Sluvey

(For, the purposes of this surveys Of-H~ighw a hry 1 ekie rdl' ndsb forA bt ATPand of highny
smierncyce.)

t. Wbatl Ltpe: EOHIV do yoreu pauslanl ue tor rde at hth Croar Muaaterccle Area?


2. What~~ othrp- up.OIlV do you uset t ride at the Crown Multm~ycle Are~a?


Begmne Navice Intermactuat A9dvanced ExPre


3. Ek... wo~uld I;s.audl; your last~ visijL bare? (front 1-10 width 01 bcein a pe~frfet trip, pleaseir circle:
approrpriale, number)

1 2 3 41 S CE 8 9r 10b

4. What is your gender? Male or Fernate

5. If urhers within yourT hou1StebuldC are rliding Loda, hoIw R anyre~:


6. WiR] you be P~cparkiplin n any othe Frm fonsofrecrtion during this trip, such as calmping, biking, and
hikjng? If yes, plEase list. (use the back as~ needed)




5. Name: and trddressi:
Name:

Adldress:

City: State: Zp


APPENDIX C
ON-SITE SURVEY


Utility ATV
Tdrt / Endum~L~ Bike
Trials Bllke


Mctuurreme Bike~


Uitilty AT~V
Trail!' Endura ~ike
Trials BL E


Span Q~uad
Mraslracro~s Bike


3. tHow do you rarr your skill lteve in, Oil-V ridr~ng?


Makeb older than Iin
McalEs younger chLan 18


Femaksl older tha I B
Femalex younger than [S












APPENDIX D
MAIL-BACK SURVEY








UN~IVE.RSI~l OF;
FLORIDA

IFAS


4Kg Schoul of Forest Rl~ENGNEE t CUsenation 1i8 Newins-Zlegler Hatl
PO Box 110410
CainesviLle, FL3241-410
r-i;-3;-. ..rr. ,-IT;,[.


Dea Partlcipant.

Tlhe Unil L"T.11 a fi I.'1.1 C~ .1 4; al al^ FoBer INGHEDEs; MId Conservatt.wr and IbE I lorda Da..y-trtrimen of
Agriculrure & CILBConue Servte- Ljl 1:n or 1 OTre~ ato- arec~da.-ring .. survey to Learn mwo re oun your
cri-tigh' .a i hicle .>11 I'rreTift.El15 IIrr.nA*:OR il th ruDm UtOnyl PlrCaE. Only&TK D s lll lme it"T
peopl: havie been abosuen a pariL i;pulai r"; I~d [ L m @ .op* g yaY Fgggg is ggy~ a gypf.

Your participation is voluntary, but we staicnd~y hoper ah t you wilt help us writh iski project. Yan are nutI
rea~uired no ans~wer any question that you do not w~ih to maswerT, and there aire no risks to you limm
partic~ipiaing in this r udl _.E You mawar will Be Arr e-nruels confidmrur s dre erreerpresIdedb~y lw.

Your respons~ei s wl be very helpful in assessinjg the current arid future need~s of v~isiors to the Crnaom
Motorcycle Area. PrO~ldlay ITrL mr aour ..Ur C.5111' knowledge experien~ces, mativatuons, mad expenditures
wilt bcip the Florida Divisirn of Forrstry bette manage the CEDGER MolGE~yteD AniB; lhif 1 FC, We urfgC
voa u1 cornlee this questn~iemar and retur it as. suric- as pa ~;bk~l. 11e rtotl. titan se~dedto uamplete th
survey should be approximately 15 mninttes.

Please be alSsur~ed that aL l Yl ofna responses; witL be coanfidential. We will. not release kafbrmaltron wheb could
Idenllr sr. dl Idul-, Ihdl ni Pumspa in the survey. I be identitication number an the questinnaire will be used
.*no. to ...-il:. the quL*Elia.=00dTO'r 5 DufR. YOu Wil rrCMVB Ro benefit foi ir copil-l~ing 0- of~ the survey will be in~tepreled as consetnt ;~r Fn;pard-; png m thr staudy. If you have any queuirjous about your
rightsi oncerning the study. pl~ea feel free ra contact the I.*1 IN L1 ofias..*~ ba: i 122~51) L nu~ en!I upi c Hond~a,
,;a~rne-.,dle. EL 32611-2250).

When complcted, please put your questjonnamre n the nclosed postage pai~d cnvelaop. IMyou hav'rE aIY
qUEstions about this su~ury, please call (352) 846-0899 or ornail 3mnakit~ifas;.utT.ecl

Yoaur inpurt is unpurterit to the FLorida 1.7ivisiorn of Furnary. It4ir r. p-.n~~ml thal we knar fromn youL by Miar
]gl~so your inp~ut can be added to the study.

rLand- You far your help

Zin~cr-l*.,



Janaki Alaveligpati
Ass-ociate Pml'a~ssr


















We would like to start by asking que~sticars about yo~ur prefenrnces FOT cii ~Way vL' C '


ri or ?he prrp~pos of this sUnvy, Of-Highseen* Vehicle (OH V) ~Rstand for bt AT mPad~ af-hrR~ighw
motrcyde.)

1) Htow many years have you ridden an OHV fo rcrscatioal purpoun
Number of years


1) a. Did Iou ~Irw1. e to ~htV recreaion armsil oter~ then the CMrA within the last yE-ar
YEsi or Na
b. 1f y~c. appro amrrncl y howBP many trip.. did you take? Total 4 of trips raken
c Ho~cw many of dxese trimps wee taken to ride on Prvivae lands (motorross or quad tracks closed
Com~E r~cs, friend or family Jan~ds, tc.)?
"Toctal. 4 alfrips taken to Pnvate lands
d. PleasC indicabtbe thecr abl ohe areaa you ~wen~t t~o most ofen.
1)




4) Perople ~go to particular areats ad parlitipate in nature-based reenrerion activities for anyg nrumber of
masoans. Listed below are s..-me p.: ,*,ibhl reasons youL might have folr taking~ your Iinp. L*-bil Ie .r-nnagC
in OI-V recrrudon. please: indrentl how impposrtant each of the fo[llowing: motaivations re~ as reasont;
for yorur r*i=il > lese ciircle the 8vappropriat uberfo each susremen)

Mo~tiverious Impartance
Not at all Not very Very' Extrremly
unprltant6 ulpolrtantIprat exportarnk japarts
Redu-e tensions and sirrBE him rvcryday lIfe 1 2 3 4 5
5Y.11fgd co iluuy kin3sb~p I 2 3 4 5
Leara abou iLLStolry and culrnue of Lne area I 2 3 4 -5
Promote physical fitness I 2 3 4 5

Eac~apc nisroitrewds I 2 3 4 5
Leamo abolur th navral codr~rromentt af1ib arecs 2 3 5
Be wnh funds and fana ly I 2 3 4 -5
Feel asn ofe aindependecre I 2 3 4 5
Talkes ~riss 1 2 '3 4 5

l"..ault in personralispirijtul~ refecion I 2 3 4 5
EIIPiGc~ the area said Rnsural environment I 2 3 4 -5


2) H-ow many years harve: you ridden at the Quota M~otorbycle .Area (C'MA)?


#of yelrs,























Enjoy untu~re

Chai c-Iga minysuif n choicee pecyurus godsl

Depend ~Ime cy sk:lls and alr-lsins
Be in ir i rcs, wkhce-c 1a Fevlse iuc crJ af

Cdntkru pursan or faily tradilican
'ti:<: newt xicac.1

[mpruse my skII i an biilitiE
Tus: vckicia's prfctriaanec

Others.(p leasehat


$1 w c vxoutd nlowu like~ youra tinklP shour Obl re ana synarrauidesrl~~kC dlst are~ pseded
011 pubt~r ]rladS LjllCut~llut10 drlCCLEYC: res.Fdiretif fo Iddei. PICS rt&& 1110 Ms101Err als ebelow ~ad rrl~dle-at
dIh eCkellU,1 to wkicks y agrat or disan:;-r I'F m:.e circle rise ~3bUpproriat numbe~L7r13. ILe ech s~T~emnrvrerl




OINV recastionl out pakke ladr d-.ac~u'l~lL

Tr~~Ily ZL-angly Saemrb$ 8 a~ l Srrrw-nhat SI-on-a!* Toa';lly Numdl
di~ngree daLter~r diasagt Agrue agru apran don't
knwan


No t O. Very
I~nrstran ir-a-:2-11


Very 1.xbrcinel
isr~rmian'. rnerrliar


]rnpcr~mr


L ?
[ 2


helps ner~srar~ 4--itors
rnd residets awarness


is a lei~bd way~ fo o l-..::13:
l0 primer threduned and
:-id2-qured -suric>

Ls godwsr. f~Iar h sm ~

is done well in IE~u s-alu


prmmolnd in the 5121E
i cr~cf i the ~ccnenmv ad
! -al s:-ncrrrau-siis cr ct


should curm an all publ!c


1 2 31 4 5 5 7


I 2.3


rl 5 6


1 2 3 41 5 Ei 7

I 2.3 5 6 7

1 2 3 4 5 d


I L.3


4r 5 6


1 2 3 4r 5 A 7




















61 ~he: ul~lowar;Cg Clestonf is related eo OJ-IV ridutny Inrefraences Iderase~ ce-,at ils srate~ner~ tK'l.9bel and
LItdicate the exte-b:rt10 I~ldcl gou agate of dslag cc. '.I'e:.rc~ ircL~E. Fh. ~~itegr=r.rpratnmae je.




'.~l'he riding your .1111'r, you prefe r tuting.

Sun~rnwhat. Sarrxcwhat
DirsLagre diare ulsk arcgree

Offi-tchai 1 3 3 4 5

On desiganiEdsrd~s I -1 3
Scrurrh!e area (~ra enidinfg rrs 125
such ar p:Lh)
Tiebt"lisaechach' .u I S
Wlde enaruk.-ing Irinl 1 1 3 4 5~

We"I' mann:? 1rs 1r 2

Events (rut~arer~jus-Cua -r acks hruc
s-menble. endr;Tce, fu-1 runs. purke
e..ns, & atlE~ sanctions oTr lub
Cevents



?) 1c re what extentl ki: ~You ~cl thae rarh ofl thfllew~:l:B condirrin~ is a problems in dice C'roomj
Alutrt;'ve'. ArCa (C.11~A.I

Net~ 5 Minur ModrsI~ a 5cneba Elx-crn
P-oblrshcl Pro-Lern Pfk.L .P-da-s:C. Prov;er

latte I 3 4 3

Oll's ass~:nt..r4l t ax: [ ? 3 4 5

Ou~vercawin I 2` 3 4l 5

1-nau vhicc wkilr eby one-OII d1Yrivers [ : .1 4
lack of proper aFey equr~rneI worn by I 2 3 4
otherT OIlV driver
Naise Irr H? 3 4 "

lack of >aied Bermn I 2 3 4 5;


C:MA (sail, vectntuium, ute >
laL Tck ~ of Iarv nviruramnena r~esk
Note:Imp -oeta usaz:ou23 4 5


Tans many ruins and Treulatinas~ 1 3 3 4 5

Pc.:r enk-cerment of -alus ad ragusi~lat~a 1 2 3 4 5
lack afknrveswidg llridesfr insand r2 3 45
Ergulatira~





















No: a Mvinur ?rwide-c Scrious~ Co.--:me"""""'
I-obZ~ern Fed~lerm Ptob;E Rns P-okrn P-ob~cn
Lack arenarkpld I-tik I Z 3 4 5
Nat enough childrn de faily czling 2 3 4- 5
crPpaCitesiie
Inadequate trail maintenncr~e E 1. 3 4
lakofnasuterrkns o spor 3 4 5

Lack a fudelquute~ campllround sites E 1 3 4 5

Inadeqrute facilities 1 2 3 4

L 2 3 4 5




81ISTh 5..11.~:w~ sy is ]a7 knof posble nagnetre~clrr~ ~i9rto~ rat Coubldl bre raken~ 10 ialprove Clit OFIV riditg
expectanec alt de Croosts .\i...-cl:e~1 Area (IU.1~). Please iadidate the exkltemb t shak you v.*~O~dd
sulpport eacht anola.


$p.*C'::irc Aanagerien A4ctionls. 5:un- Soewat Nutn: mehl5:-.*
Oppose CDp3Kuse Su-r-Le Srrpp:.rl
Ptoride I s:ras uajrainse ad trai rarcties 12 45
indical-ng LrmngIl
Proivide s gns ni trai~hund vand t-.r incton i 2 S
indical-agI Inuc: ac" i Tiv.!La
Pmrovie scrwnble mi-ng aresI 41 5

Llral: russ: OJ16 EV =izig :ad danguatead LeadsZ ] 2 3 4 5
Ptoride enm rmual re system that ldlws the

Zhroughou the state
thos:&c dat lcd rra-c; of te I:1.1 ] 2 4 5

Ptoride nurn range pTosL 1 2 3 -4 5
bnrFeamsr the rairrennce of frac3 I OiV~ arEE. Mi d;
~rilsr
Take r~uE25EE ED prmiBEl Hfi~br impEDVE the
nxtratun cnvr~accREln mn ELEEM
Provuide Rmre purrking sp~acg? TbrDV Cllubpport ] 4 5
vchic~rs
PRovder rian-ttr: currasi at a~Fppropaepae I 34
*ithin thE CMA


Ptoride more aik faci'itics wvithin the CMA~c I r 3

Provide mesrr Oil'v safaty udntia~n ] -1 r S

Provide envrroRmruni al~ h-ctamus I 4 34 5
PRo.:de Bdlil~onal pavilialns arnd pic-nic Ilab:e ] 2 4 5





We would now like to ask you a few questions regarding your expenditlue related
to off'highwaybveicle rereatlon.




9) 1~ How stin day Irjlps did y~ur bUu~Sek.:ld s-nae 10 the C11A uver lle laut 12 mouhlr? -if .varr









l u yo u~r best eS~Ltureme. bbow rituals~ frd~uac wa pent~ Bry ycur ouscbhold in parate tins in~ du~
followiblf vis-9ocgelce1:11..u 'ast day trip tod he CM-A?


Ansulat~a Phirduased




L'


Care-garlv

CGIV rr.aIntd pusetunes (gmu, equipyre~l. wic..
Purchuses reluted t, Lrumspon~alB~an Ito the~ C).5 (gas~W.r rentahl fe, e-.)
Fod & cr~averapurchase
Eric-lu-Irce it, gi* und souvenir purelinscs
Afiscllraneous~ath purcEME5l


faotalkao Ylrtitil Pchsed ?5



a21 Houw rarl:. Olver- algt rps r ad your hoursehold steaks:~ ~L: te CN oree did Lissi 12f IdlaurtiS? !!/ror
ro>.*uk ch.' id as:*/ :al~e an.- eve-mirght try, plea.* e..p re~C qu .*JI:.* L's.I




CMAT
# of preol

























OliV Trbaler-lu3chmesI (gas, equiPment, et.1
P.:rc~hirvs rlated lo~ Ltruspeclalna;B Ihe CM.^. ipe. :c:Is, rents fees. c-r.) i
~FoodJ & bdsverg ~purc8hen S

Ladejpllmgl B:haten::cl. api~nci~ ute.I I
~rveaiarra~~gni 51m d w**i Furchases $
Misce.I:.-Ico.Is~ ate-ueS~e


hleta~~l ArtitinVrdssedr g




I ~ 10~ yval b~eit esiae.boa c lw much nandcy did yol 'aumboldB 9Pnd~ al inefll OwIlnei~g CategotteS overI
Ylses~ rclrusi lwlvelani.It lee 8H IILY ectrat ivastgen:rll


.*1II U u vl bea3 cucn iat, obus araudcl roalltlI s.~Ca spent by yourlt b~Isahlold Iol~~ v ichmlaln. jd dhe
Iolclowring categics of. Irour Las avr~-afdgb lit tIp La::5 I^ rA1


Amsrboun Painastas


Caragefry


Artrnuart S~penrt







(r.


Caregory:
Repairs wardtbi maintenance to OLlYI (man-oi, :id*ricant s.~ In sic
tilic-s, tiCCC, wLdf "'011, Ct ".)
O)ilV equvpenan readificatlions and upnglrus rr:zhamsL sruspenlion.

GifV RYEidnK syrparcl Ihalanets Elclis, eer) PO~Lationadves
add-laci protetive clo-rugh
Lat.Ii-rre~cr* ur -a-..F 2.s*: ofrea~rldu relte to 16r Lrurus~po:- fOl~s (Iranysprl
*.ch-cle. radeir. grufuel. IcadingTrun-.:I downsa, erc.:.
GilV ErpEEEETHE EEbind in pcurath fees (day-u e fee, spcid sea 6tues
carrrpercl oat rry Ene, alc.Xh l~ ~~inszneTin g, clb anernbipesi
M isjellsrul:Qecascubt _xTCh~CI rch~ed :ur Dil' -irhng


Te"Larl Amorunrt Splent



SrlD ~1.[ pou fcift l t th~LIL l Otrical: UfI$ lie1 VA WM. da meI3Bst fitdle: IIIt yd Jcrlirf tts au (sul t~aie1 :Inclt ofl [|10

Yite. or he



' g PI Appoi:ull~el Vujlti pa"Ud~ range ul"The : sLavlChases VI:, :Indei~ inL IbeC COuL~neLmI CIautu.~i
Bermando, Sumeitrce and Pasco?





:31 He. yourr !.ausehold pf6a~~tlamed a ene OEIVris) bs the '.us 12 c.:onsle.:
YesCI or"t (,1*, pe'emrse Ko.* qu~ler .'llII~ I-)

Efyii ves, bo mallay? = of newi 0J131.

Appekratutimly hcw murclr dad yo~u Spenrd is roa~l? Si

'i~nlid fuI SL btyL[dt X~LCLCU~I rha l:e:tne.fs MAhV~ Ba useag 12:ED: 1n youWI dCicSs*.oal to ]PullaIIBS duL
UIti'*,'|>.1vour~d clrcabe Ycs or No


.91 12. you~ r househld pun.-hased a Ined 0141-'.> usltih, lust .2: enltle 'r
Yes5 or 150

lf ve-, bow racy ."~~ = f usedc OHL'8

Approxulnae~ly bowi mucki~ did you rjpend mc Iotl?~- S

\#011 ylu Or ay sbal EllC cxl.[irclte Ofih-:CM f.'iA WMI 8 rln t or tkt Hj yoiu ticriscoiw l LU pe:Chat~ El
OI) V'~ | .).-u ciited abuye YC es1 or No


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pi LI per L,-Car 10( c8th esethe. lsc1bit cVInlikde ~cits .










We would like to end this survey with a few general questions abour you.





rl) cl a* is yourf eip co6de?


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ialre
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sun.*cy.


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525,00-534,99
S555WZ,00 5.5999
555,000-594,99
91~5 5 000 ad abovE










APPENDIX E
MATHEMATICAL DESCRIPTION OF INPUT-OUTPUT MODEL

To aid the reader in understanding I-O analysis, a basic description of a three-sector I-O

model follows, as put forth by Leontief (1986) and Miller & Blair (1985), to illustrate how one

derives the indirect and induced impacts from the initial direct impact.

Figure 1 is a generalized accounting table that

I-O models utilize. An assumption that is key in I-O Fiue1 eea conigtbeInputs
Producing
Final demand sector
models is that total outputs from a sector equals total Outputs sector
H G E Total
S1 S2
inputs. The columns within the table represent inputs
.S1 Zll Zl2 H13 Gl4 E15 X't
that industries require to produce a given level 4s
& 4 S2 Z21 Z22 H23 G24 E25 X'2
output. Reading down the columns gives the level of H(3) H31 H32 T33 T34 T35 X'3
6 G(4) G41 G42 T43 T44 T45 X'4
inputs that each sector receives from others. Industry
P a I?(5) Isi I52 T53 T54 T55 X's
sector S1 purchases Zll from itself, Z21 %Om S2, H31 Totalinputs X, X2 X3 X4 X,

inputs from households and so on for total inputs of X1, the bottom row of table 1. Conversely,

reading across the rows shows the outputs sold by a sector to the other sectors. Hence, sector S1

will sell Zll to itself, Z12 Sector S2, H13 Outputs will be sold to households, and so on for a total

output of X' 1, given the assumption stated above X2 = X'2.

As such:

X' 1= Zii +Z12 + 1

where Y1 is total final demand for S2 outputs, Y1 = H13 + G14 + E15.

Dividing the column entry by gross outputs will provide the trade coefficients, the

amount of input from each sector needed for S2 to produce one unit of output. Duplicating this

for each producing sector results in a series of equations that will form the coefficient matrix A,


Sa 21al a 2 12









where :


Solving for X, the vector of gross output, provides the final equation:

X=(I-A)- *Y

Where (I-A)-1 in the Leontif inverse matrix and Y is the vector of Einal demand.

Households can be treated as either exogenous or endogenous with respect to the model.

When households are treated as exogenous, type I (direct and indirect) multipliers and impacts

are derived. Type II (direct, indirect, and induced) multipliers and impact are obtained by

extending the Leontif inverse matrix to include additional spending of wage income by

households. As such, type II multipliers and the associated impacts are greater due to the

inclusion of this additional sector.

By changing Y, one can derive economic impacts from an I-O model. Essentially an

activity or policy change can affect the Einal demand from various sectors. A change in Y will

result in a corresponding change in total output greater then the initial impact, as the sectors that

experience an increase in Einal demand for their products will increase purchases of inputs from

other sectors, hence causing the direct impact to multiply.











APPENDIX F
DIRECT, INDIRECT, AND INDUCED REGIONAL ECONOMIC IMPACTS OF OHV
RECREATION AT THE CMA BY INDUSTRY GROUP AND IMPACT TYPE



Output Impact ($)

Direct Indirect Induced
Direct Non-
Industry Group (NAICS) Local Non-Local Non-Local Total Impact
Local Res.
Residents Res. Res.

Ag, Forestry, Fish & Hunting 0 0 3,188 43,469 46,656
Mining 0 0 112 1,071 1,183
Utilities 0 0 111,577 199,311 310,888
Construction 0 0 69,285 663,505 732,790
Manufacturing 0 0 74,829 182,983 257,812
Wholesale Trade 0 0 27,064 131,507 158,571
Transportation & Warehousing 0 0 142,040 131,064 273,104
Retail trade 2,719,701 8,118,798 71,093 688,289 11,597,880
Information 0 0 114,365 146,439 260,804
Finance & insurance 0 0 92,742 278,367 371,109
Real estate & rental 211,638 881,019 186,681 210,874 1,490,212
Professional- scientific & tech svcs 0 0 179,506 201,346 380,852
Management of companies 0 0 51,593 8,667 60,260
Administrative & waste services 0 0 189,905 133,465 323,370
Educational svcs 0 0 726 36,731 37,457
Health & social services 0 0 47 897,788 897,835
Arts- entertainment & recreation 16,829 113,902 6,146 55,409 192,286
Accomodation & food services 70,897 383,565 41,005 331,914 827,380
Other services 194,065 577,305 83,206 330,019 1,184,595
Government & non NAICs 46,496 259,772 54,371 1,895,090 2,255,729
Total 3,259,626 10,334,361 1,499,482 6,567,306 21,660,775
*Citrus, Sumter, Hemnando, and Pasco Counties













Total Value Added Impact ($)

Direct Indirect Induced
Direct Non-
Industry Group (NAICS) Local Loa e. Non-Local Non-Local Total Impact
Residents Res. Res.

Ag, Forestry, Fish & Hunting 0 0 1,911 22,615 24,526
Mining 0 0 73 700 774
Utilities 0 0 80,357 143,532 223,889
Construction 0 0 31,054 264,534 295,588
Manufacturing 0 0 23,252 40,604 63,856
Wholesale Trade 0 0 20,585 100,023 120,607
Transportation & Warehousing 0 0 95,983 74,595 170,578
Retail trade 2,084,005 6,151,171 53,261 515,959 8,804,396
Information 0 0 41,580 52,746 94,327
Finance & insurance 0 0 65,930 168,010 233,940
Real estate & rental 87,331 363,548 126,762 140,879 718,520
Professional- scientific & tech svcs 0 0 85,580 110,048 195,627
Management of companies 0 0 28,135 4,726 32,861
Administrative & waste services 0 0 92,959 70,095 163,054
Educational svcs 0 0 353 19,508 19,861
Health & social services 0 0 20 564,622 564,642
Arts- entertainment & recreation 10,175 68,868 3,055 32,569 114,668
Accomodation & food services 50,279 272,020 21,061 155,684 499,044
Other services 93,476 278,073 32,364 162,880 566,793
Government & non NAICs 14,125 78,917 16,389 1,672,369 1,781,800
Total 2,339,392 7,212,596 820,663 4,3 16,699 14,689,351
*Citrus, Sumter, Hemnando, and Pasco Counties












Labor Income Impact ($)

Direct Indirect Induced
Direct Non-
Industry Group (NAICS) Local Non-Local Non-Local Total Impact
Local Res.
Residents Res. Res.

Ag, Forestry, Fish & Hunting 0 0 941 10,501 11,442
Mining 0 0 38 362 400
Utilities 0 0 24,071 43,760 67,831
Construction 0 0 27,482 228,475 255,957
Manufacturing 0 0 17,666 28,393 46,059
Wholesale Trade 0 0 11,529 56,019 67,548
Transportation & Warehousing 0 0 72,899 58,309 131,208
Retail trade 1,352,449 3,981,654 33,435 323,794 5,691,332
Information 0 0 24,764 23,249 48,013
Finance & insurance 0 0 30,178 78,546 108,724
Real estate & rental 42,660 177,589 32,771 39,339 292,360
Professional- scientific & tech svcs 0 0 72,023 94,672 166,696
Management of companies 0 0 21,619 3,632 25,250
Administrative & waste services 0 0 73,756 55,664 129,421
Educational svcs 0 0 342 19,003 19,345
Health & social services 0 0 18 491,184 491,202
Arts- entertainment & recreation 5,669 38,367 2,251 20,078 66,364
Accomodation & food services 28,605 154,758 13,924 107,419 304,706
Other services 67,564 200,990 22,807 128,936 420,297
Government & non NAICs 12,209 68,214 16,059 935,822 1,032,304
Total 1,509,156 4,621,572 498,571 2,747,157 9,376,456
*Citrus, Sumter, Hemnando, and Pasco Counties












Indirect Business Taxes Impact ($)

Direct Indirect Induced
Direct Non-
Industry Group (NAICS) Local Non-Local Non-Local Total Impact
Local Res.
Residents Res. Res.

Ag, Forestry, Fish & Hunting 0 0 47 913 960
Mining 0 0 3 31 34
Utilities 0 0 11,484 20,244 31,728
Construction 0 0 425 3,170 3,594
Manufacturing 0 0 367 842 1,209
Wholesale Trade 0 0 4,453 21,637 26,090
Transportation & Warehousing 0 0 1,715 2,060 3,775
Retail trade 410,337 1,205,791 9,996 96,659 1,722,783
Information 0 0 2,841 5,603 8,444
Finance & insurance 0 0 2,221 4,736 6,957
Real estate & rental 4,325 18,003 20,370 22,069 64,767
Professional- scientific & tech svcs 0 0 1,139 2,005 3,143
Management of companies 0 0 465 78 543
Administrative & waste services 0 0 2,721 2,227 4,949
Educational svcs 0 0 7 343 350
Health & social sen ices 0 0 0 6,076 6,076
Arts- entertainment & recreation 1,249 8,452 218 3,678 13,597
Accomodation & food services 7,045 38,113 2,440 16,694 64,291
Other sen ices 13,913 41,388 3,173 13,060 71,533
Government & non NAICs 8 47 19 104,196 104,271
Total 436,876 1,311,793 64, 104 326,321 2,139,094
*Citrus, Sumter, Hemnando, and Pasco Counties













Employment Impact (Jobs)

Direct Indirect Induced
Direct Non-
Industry Group (NAICS) Local Non-Local Non-Local Total Impact
Local Res.
Residents Res. Res.


Ag, Forestry, Fish & Hunting 0.0 0.0 0.0 0.8 0.8
Mining 0.0 0.0 0.0 0.0 0.0
Utilities 0.0 0.0 0.3 0.5 0.8
Construction 0.0 0.0 0.9 7.2 8.0
Manufacturing 0.0 0.0 0.5 0.8 1.2
Wholesale Trade 0.0 0.0 0.3 1.4 1.7
Transportation & Warehousing 0.0 0.0 1.8 1.5 3.3
Retail trade 46.2 134.6 1.4 13.6 195.7
Information 0.0 0.0 0.7 0.6 1.3
Finance & insurance 0.0 0.0 0.7 2.0 2.7
Real estate & rental 1.8 7.4 1.5 1.8 12.5
Professional- scientific & tech svcs 0.0 0.0 2.2 2.7 4.9
Management of companies 0.0 0.0 0.4 0.1 0.5
Administrative & waste services 0.0 0.0 3.2 2.3 5.4
Educational svcs 0.0 0.0 0.0 0.9 0.9
Health & social services 0.0 0.0 0.0 12.4 12.4
Arts- entertainment & recreation 0.3 2.2 0.1 1.2 3.8
Accomodation & food services 1.3 7.2 0.9 7.5 17.0
Other services 3.0 9.1 1.2 7.5 20.8
Government & non NAICs 0.3 1.4 0.3 22.2 24.2
Total 52.9 161.9 16.4 86.9 318.0
*Citrus, Sumter, Hemnando, and Pasco Counties










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BIOGRAPHICAL SKETCH

Gregory Parent was born in Dover, NH on the 24th of May 1978 and has spent the first

eighteen years of his life living in Rochester, NH. Upon completion of his studies at Saint

Thomas Aquinas High School in 1997, Gregory moved to Montreal, Quebec to pursue his B.A.

degree at McGill University. Gregory graduated in 2001 from McGill with a double maj or in

economics and international development.

In June of 2002 Gregory entered into service as a Peace Corps volunteer in the country of

Togo. Gregory developed and managed proj ects in collaboration with villages that focused on

improving the sustainability of natural resources use. Most of these proj ects centered on the

generation of revenue from non-timber forest products, taking the form of a comprehensive

ecotourism proj ect and agroforestry regime promotion. During those two years in Togo Gregory

gained a level of insight into the relationship between the village social organization and natural

resources that he never could have gained in university studies alone. He developed an

understanding of the prime importance of representing the diversity of interests and resource use

issues of rural village communities in any attempted conservation plan.

Upon completion of his M. S. degree, Gregory will be entering into a PhD program at the

University of Florida, through the auspice of a National Science Foundation fellowship through

the Integrative Graduate Education and Research Traineeship program. His proposed area of

research will be in developing economic models, most likely either computable general

equilibrium (CGE) or econometric models, to analyze the economic structure of local

communities with an emphasis on the regional economic linkages to natural resource use.





PAGE 1

1 ECONOMIC IMPACTS AND MOTIVATIO NS OF OFF-HIGHWAY VEHICLE RECREATIONISTS: A CASE STUDY FROM FLORIDA By GREGORY D. PARENT A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2007

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2 2007 Gregory D. Parent

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3 ACKNOWLEDGMENTS Financial support for this study was provide d through the T. Mark Schmidt OHV Safety & Recreation Act Grant Program. The author wo uld like to thank all Division of Forestry personnel who provided assistance throughout the proj ect. In addition, I would like to thank Jack Terrell for his technical knowledge, which he generously provided throughout the duration of the project. I would also like to thank Sara Lumban Tobing for her invaluab le assistance in data collection and for her ongoing moral support. In addi tion, I thank Rachel Albritton for her help in providing technical information. I thank all the participants who took the time for filling out the lengthy mail-back survey; your survey was a crit ical part of this study. Finally, and most importantly, I would like to thank my advisor Janaki Alavalapati and my committee members Taylor Stein, Alan Hodges, and Douglas Carter for all their help and guidance throughout this study.

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4 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................3 LIST OF TABLES................................................................................................................. ..........6 LIST OF FIGURES................................................................................................................ .........7 ABSTRACT....................................................................................................................... ..............8 CHAPTER 1 INTRODUCTION................................................................................................................. .10 Understanding Off-Highway Vehicle Recreation..................................................................10 Off-Highway Vehicle Recrea tion Policy in Florida...............................................................11 Study Area: The Croom Motorcycle Area..............................................................................13 Study Objectives............................................................................................................... ......14 2 STUDY DESIGN AND IMPLEMENTATION.....................................................................15 Profile of Respondents......................................................................................................... ...16 Visitor Characteristics.....................................................................................................16 Trip Characteristics.........................................................................................................16 3 REGIONAL ECONOMIC IMPACT OF OFF-HIGHWAY VEHICLE RECREATION AT THE CROOM MOTORCYLCE AREA THROUGH INPUT-OUPUT ANALYSIS.....22 Introduction................................................................................................................... ..........22 Model Specification............................................................................................................ ....23 Results........................................................................................................................ .............25 Total Population Estimate...............................................................................................25 Trip Expenditure..............................................................................................................2 5 Equipment Expenditure...................................................................................................26 Regional Economic Im pact Estimation...........................................................................27 4 CONSUMER SURPLUS ESTIMATION: AN INDIVIDUAL TRAVEL COST METHOD APPROACH.........................................................................................................34 Introduction................................................................................................................... ..........34 Individual Travel Cost Method Model Specification.............................................................36 Results........................................................................................................................ .............37

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5 5 MOTIVATIONS OF OFF-HI GHWAY VEHICLE USERS..................................................42 Introduction................................................................................................................... ..........42 Data Analysis.................................................................................................................. ........43 Results........................................................................................................................ .............43 Desired Benefit Profile of Off-Highway Ve hicle Recreation Policy in Florida Users at the Croom Motorcycle Area....................................................................................43 Benefit Subgroups Identification.....................................................................................44 Benefit Subgroups Description........................................................................................46 6 DISCUSSION AND CONCLUSIONS..................................................................................53 Policy Implications............................................................................................................ .....56 Future Work.................................................................................................................... ........57 APPENDIX A MAP OF THE WITHLACO OCHEE STATE FOREST........................................................59 B VERBAL CONSENT SCRIPT..............................................................................................60 C ON-SITE SURVEY............................................................................................................... .61 D MAIL-BACK SURVEY.........................................................................................................62 E MATHMATICAL DISCRITION OF INPUT-OUTPUT MODEL.......................................71 F DIRECT, INDIRECT, AND INDUCED REGIONAL ECONOMIC IMPACTS OF OHV RECREATION AT THE CMA BY INDU STRY GROUP AND IMPACT TYPE.....73 LIST OF REFERENCES............................................................................................................. ..78 BIOGRAPHICAL SKETCH.........................................................................................................83

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6 LIST OF TABLES Table page 2-1 Visitor characterisitcs of respondents................................................................................18 2-2 Trip characteristics of respondents....................................................................................20 2-3 Activities and experien ces of Croom visitors....................................................................21 3-1 Population estimate of visitors to the Croom Motorcycle Area........................................28 3-2 Trip expenditure of a typical visitor to the Croom Motorcycle Area and total trip expenditure for 2006..........................................................................................................2 9 3-3 Equipment expenditure of a typical visito r to the Croom Motorcycle Area and total equipment expenditure for 2006........................................................................................30 3-4 Regional impact events by IMPLAN sector......................................................................31 3-5 Direct, indirect, and in duced regional economic impact of off-highway vehicle recreation at the Croom Motorcycle Area.........................................................................32 3-6 Total regional economic impact by industr y group for off-highwa y vehicle activity at the Croom Motorcycle Area..............................................................................................33 4-1 Description of variables used in th e Individual Travel Cost Method model.....................36 4-2 Descriptive statistics of variables used in the model.........................................................40 4-3 Regression model results................................................................................................... 41 5-1 Results of cluster analysis................................................................................................ ..48 5-2 Desired benefits of resp ondents and benefit subgroups.....................................................49 5-3 Desired benefit ranki ng by cluster membership................................................................50 5-4 Visitor characteristics by cluster membership...................................................................51 5-5 Additional visitor characte ristics by cluster membership..................................................51 5-6 Trip characteristics by cluster membership.......................................................................52 5-7 Additional trip characteri stics by cluster membership.......................................................52

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7 LIST OF FIGURES Figure page 2-1 Region of residence of CMA visitors................................................................................21

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8 Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy ECONOMIC IMPACTS AND MOTIVATIO NS OF OFF-HIGHWAY VEHICLE RECREATIONISTS: A CASE STUDY FROM FLORIDA By Gregory D. Parent April 2007 Chair: Janaki Alavalapati Major: Forest Resources and Conservation Off-highway vehicle (OHV) recreation is a popular and fast growing forest-based activity. As such it is necessary to understand the pa rticipants involved a nd their impacts to better manage for this use. While OHV use doe s generate negative impacts, such as noise pollution, adverse soil effects, and user conflicts positive impacts also arise from this activity. My thesis reports a study of OHV users who visited the Croom Moto rcycle Area (CMA), a single use OHV recreation area in the Withlacooch ee State Forest, Florida. Specifically, this study focuses on economic impacts of OHV recrea tion on local economies. Evaluation of the economic impact was achieved through travel expenditure surveys combined with economic input-output analysis to estimate the direct, indirect, and induced economic impact arising from OHV. The impact is significant to the surroundin g communities with a total value estimated at over $21 million. My study goes one step further to evaluate consumer surplus (CS) of CMA users through the application of the individual travel cost met hod, to quantify this additional societal benefit. Results suggest that participan ts with more experience in OHV recreation at the CMA will more frequently visit the site reflecti ng the effect of habit formation. Re gression coefficients were used

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9 to estimate CS with individual household CS evaluated at over $1,600, while the total annual CS of all households recreating at the CMA was estimated at over $31 million. In addition, the study analyzed th e benefits that act as motiv ations for users involved in OHV recreation. Results indicated that the attainment of family orie nted benefits were the main motivation for their participation. The motivatio ns to be with friends and family and to strengthen family kinship had the top two ove rall mean rank scores out of a list of 19 motivation variable. Furthermore, motivational subgroups exist within the overall population and vary in the benefits that motivat e them to ride OHVs. Results re vealed three distinct homogenous motivational groups; group one, the Experiencers riding for the attainment of multiple and diverse benefits; group two, the Familists, riding mainly for the attainment of family based benefits; and group three, the In dividualists, riding for the attain ment of individual oriented benefits.

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10 CHAPTER 1 INTRODUCTION Understanding Off-Highway Vehicle Recreation Nature-based recreational activities on forested lands in the United States attract millions of participants yearly. Over 200 million peopl e visited US Forest Service managed lands annually from 2000-2003 to participate in vari ed forms of recreation such as hiking, backpacking, skiing and off-highway vehicle (O HV) riding (USDA, 2005). One of the fastest growing forms of recreation over the last decad e has been OHV recreation. Cordell et al., (2005) estimated that from 1999 to 2004 OHV recreation grew by over 15 million participants in the United States. This growth has been mirrore d in Florida with an estimated 1.78 million participants as of 2004, ranking it fi fth within the US and first within the southern US (Cordell et al., 2005). The enormous and growing popularity of OHV recreation has spurred many states into creating new OHV management policies to a ddress the positive and negative externalities and capitalize on positive externalities that arise from this form of recreation. To date, the majority of the research undertaken on OHV recreation has focused on the negative environmental and social impacts resu lting from OHV recreation. OHV use is a highly consumptive form of recreation, whose impacts te nd to be very visible (Major, 1987). Repeated use of OHVs on trails lead to th e reduction in air and organic so il components, reduced levels of vegetation on trail margins, and incr eased erosion (Kay, 1981; Webb et al., 1978). A study in California deserts by Sheridan (1978) found that areas with high OHV use experienced a 60%75% decrease in animal life. Similarly, white-taile d deer populations were found to be inversely proportional to OHV levels along tr ails in Minnesota (Dorrence, 1975). Sound pollution is also a major problem with OHVs. In a 1974 study, Harr ison found that motor noise from OHVs could be detected from up to 15,000 feet away depending on the engine and OHV type.

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11 These negative environmental impacts in turn generate user conflicts between OHV users and other stakeholders. Hunters are particularly affected by OHV recreation due to the tendency of animals to avoid areas with heavy OHV use. Other recreation groups often seek out solitude or undisturbed environments; these groups can be ne gatively affected by the aggressive nature of OHV impacts (Kariel, 1990). A study by Vail & Heldt (2004), on snowm obile recreation in Sweden and Maine, demonstrated that the conf lict between snowmobilers and cross-country (XC) skiers was largely asymmetrical, with the environmental impacts of snowmobiling perceived highly by XC skiers, reducing their en joyment. The same study also illustrated the conflict that arises between the OHV riders a nd private landowners due high noise levels and damage to property. Mountaineers gave OHV noise an aggregate score of 4.98 on a scale of one to five where five means annoying and indicated th at their enjoyment of nature decreased when unnatural sounds were introduced to the e nvironment (Kariel, 1990). These negative environmental and social impacts can be mi nimized through the creation of OHV recreation areas in which the impacts could be concen trated, and by the formulation of effective management policies. OHV Recreation Policy in Florida Florida’s first attempt at managing OHV r ecreation came in 1972 when the Division of Forestry (DOF) established the Croom Motorcyc le Area (CMA) within the Withlacoochee State Forest. The DOF created the CMA in response to the high level of perceived forest-wide environmental degradation and the increasi ng conflicts between OHV riders and other stakeholders (Florida Department of Agricult ure and Consumer Services, 2002). By the founding of this single-use OHV recreati on area, it was the DOF’s hope to confine all OHV riding to this 2,600 acre area, thus reducing the negative costs th roughout the rest of the 133 thousand acres of

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12 the Withlacoochee. DOF personnel have found that th is has indeed been the case and the CMA is now highly visited and liked by OHV riders. However, the negative externalities that ar e associated with OHV riding persisted to be an issue throughout the rest of Fl orida as OHV recreation continued to grow. The state of Florida took notice in 2002 when they passed the T. Ma rk Schmidt Off-Highway Vehicle Safety and Recreation Act. In formulating this legisla tion, the legislator r ecognized that positive externalities are also present in OHV recreation. In the pursuit of OHV recreation, riders make substantial travel and equipmen t expenditure that has a positive impact on the economy (see chapter 3 for a further discussion on economic impacts). In addition to the positive economic impacts, society can also gain from the beneficial social effects. As well as the personal benefits riders get such as stress relief, physical fitness, and the enjoym ent of nature, OHV recreation also tends to be an outlet for socializing, family bonding, and community building (Maine Sunday Telegram, 2002). The 2002 OHV Safety and Recreation act wa s designed to provide opportunities for people pursuing OHV recreation in a managed and controlled manner, thus reducing the negative environmental and social impacts of illegal or unmanaged riding. The act explicitly recognizes that current and future OHV recr eation areas are compatible w ith Florida’s overall recreation plan and underlying goal of multiple use. The act laid the groundwor k for the creation of at least two new OHV riding areas1 that would be modeled after the CMA. The DOF has considered the CMA to be a success as is has bot h reduced illegal riding and con tinues to attract large numbers of users. The CMA was the only riding area on state land until 2005 when the DOF created a 1 In stating the need for at l east two additional riding area, the legislature recognized that at a time when OHV is growing in popularity, riding oppor tunities are decreasing in the State as the USDA Forest Service further restricts ridi ng on national forest lands though the Access Designation Process.

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13 new area in northern Florida.2 However the DOF, who manages the CMA and would be responsible for any future OHV recreation areas knew little about the population that rides OHVs at its facilities and has lim ited information about the associated economic impacts. This information gap has prompted the DOF to approach the University of Florida to conduct this study. Study Area: The Croom Motorcycle Area The Croom Motorcycle Area (CMA) is located within the Croom tract of the 133 thousand acre Withlacoochee State Forest (A ppendix A). It is a 2,600acre single-use area dedicated to Off-Highway Vehicl e (OHV) recreation with the use of both off-road motorcycles3 (ORM) and all-terrain vehicles4 (ATV) permitted. Forest-wide, the Withlacoochee supports multiple uses within its borders, from extractiv e forestry activities to various recreational pursuits (Florida Department of Agriculture & Consumer Services, 2005). The CMA came into existence in 1972 as an attempt by the DOF to ma nage the forest for multiple uses by confining OHV riding to one area, thereby co ncentrating the environmental im pacts, eliminating conflicts between OHV riders and other user groups on non-OHV areas (Florida Department of 2 Currently the two main OHV riding areas in Florida are within the State Forests of Withlacoochee and Tate’s Hell. OHV riding also o ccurs in Big Scrub, however it is substantially restricted in terms of both numbers a llowed and OHV vehicle type. Restricted OHV opportunities are also available on some Florida Fish and Wi ldlife Conservation Commission managed lands. 3 Three types of ORMs are used at the CMA. En duro motorcycles are street legal motorbikes designed for sport and long travel. Enduro motorc ycles include a headlight and taillight, quiet muffler. Motocross motorcycles are similar to enduro motorcycles but lack the refinements, such as quiet mufflers and lights, to make them street legal. The third main type of ORM is the trial motorcycle. Trials motorcycles are distinctive and specialized for events known as observed trials. They are lightweight with a short suspensi on and have no seat as they are designed to be ridden standing up. 4 There are two main types of ATVs used at the CMA. Sport quads are small lightweight two wheel drive vehicles that can attain high speed s. Utility ATVs are larger four wheel drive vehicles that have a much lower top speed. Utilit y ATVs have the ability to perform other tasks such as hauling and towing items and often have lights on the front and rear ends.

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14 Agriculture and Consumer Services, 2002). The popul arity and lack of other riding areas makes the CMA a popular destination with an estimate d 71,500 total user-days for the 2005 fiscal year. Study Objectives There were four objectives of this study. Obj ective one was to descri be the visitor of the CMA in terms of their socio-demographics. Th e second objective was to evaluate the economic impact arising from visitation to the CMA. As objective two does not ca pture the benefit users get from their visitation of the CMA, objective three was to quantify th is benefit through the estimation of visitor’s consumer surplus. Objective four was to identify the specific desired benefits that riders are attempti ng to attain as a reason for their use of the CMA and, to identify and describe definable benefit subgroups. To fulfill the above objectives a number of analytical methods were employed. Descriptive statistics, such as frequencies and mean s, were used to identify who the visitors are in terms of their socio-demographics. The estimat e of economic impact to the region required the utilization input-output to generate this estimated impact. Th e individual travel cost method was employed to generate and estimate of visitors co nsumer surplus. Objective four was achieved by having participants rate 19 indi vidual motivations on a Likert scale to identify the primary motivations. Cluster analysis was employed

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15 CHAPTER 2 STUDY DESIGN AND IMPLEMENTATION Researchers designed a comprehensive surv ey in order to ach ieve the four study objectives. During the development process, rese archers met with DOF personnel, made site visits, and conducted pretests of the survey on participants at the CMA. The survey was developed using a modified Dill man (2000) method to increase res ponse rate. On-site interviews (Appendix C) were conducted, asking basic questions such as overall trip satisfaction, OHV type used at the CMA, region of home residence, etc. The main obj ective of the on-site interviews was to introduce and familiarize the participants with the more comprehensive mail-back survey. The mail-back survey (Appendix D) contained the detailed questions that would provide the data necessary to meet the study obj ectives. The survey was designed to be filled out on a household basis, hence one mail-back surv ey was distributed per household. Researchers approached potential participan ts in parking areas of the CMA asking OHV riders whether they would participate using a verbal consent script (Appendix B). On-site interviews were conducted from January th rough April 2006, with surveyors randomly approaching a total of 342 OHV riders and attaini ng the verbal consent of 321 participants. At the conclusion of each on-site interview a mail-back survey was distributed to the participant. An additional mail-back survey was mailed to the part icipant if the original survey was not returned after two weeks. A total of 116 out of the 321 mail-back survey s distributed were returned completed for a response rate of 36.14%. Surveyors also randomly left 99 surveys, a survey that combined the on-site questionnair e with the mail-back survey, on parked vehicles throughout the parking areas of the CMA. Out of the 99 surveys left with vehicles, 34 were returned, a response rate of 34.34%. The combined response rate for the mail-back survey was 35.71%.

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16 Profile of Respondents Visitor Characteristics The mail-back survey contained detailed so cio-demographic information (Table 2-1). Males made up a significant majority of th e survey respondents (84.5%). For the survey participants who provided their age, the majority indicated they were 40 or above (60.3%). More than two thirds of respondents (67.8%) indicated that they were married, and 61.9% reported that they have at least one child sti ll living at home. Nearly all (91.0 %) of the participants identified themselves as Caucasian with 4.2% and 3.5% id entifying themselves as Native American and Hispanic / Latino respectively. The survey par ticipants were well educated with 91.1% having graduated from high school and 47.3% holding at l east a bachelors degree. Close to 75% (74.5%) of survey participants had annual household in comes of at least $55,000. Finally, the three main occupations of survey participants were that of business owner (24.5%), skilled trade (23.8%), and professional worker (19.0%). Trip Characteristics The mail-back and on-site surveys contai ned questions pertaining to the trip characteristics of the survey participant (Tab le 2-2). The majority (55.3%) of the survey participants have been riding OHVs for over 10 years with the mean years of ridding OHVs being over 16 years (16.3 years). Within the last y ear, participants indicate d that they have taken numerous OHV recreational trips with over ha lf (51.7%) having taken over 20 trips. Participants have not been r ecreating as long at the CMA, w ith only 27.3% of participants having recreated at the CMA for over 10 years and a mean of 8.1. Close to 32% of participants have made over 20 trips to the CMA within th e last year, with a mean of 18.6 trips per participant. Users of the CMA also tend to recrea te with family, as 85% recreated with at least

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17 one other family member on their last trip and approximately 20% travel to the CMA with at least 5 other members of their family. It is importa nt to highlight that 18% of the participants live in the southeastern or southwestern regions of Florida, indicating substantial travel time to the CMA for a significant percentage of the participants. Participants were asked for their zip code in order to evaluate their home region. Survey results (Figure 2-1) indicate that visitors traveled not only from di fferent parts of Florida but also from other states and countries (4%) to recreate at the CMA. West-Central Florida was the home region of the largest percenta ge (35.9%), with the counties surrounding the CMA contributing close to a quarter (24.9%) of the survey participants. The on-site and mail back surveys also asked participants questions pertaining to trip activities and experience while at the CMA (Table 2-3). Participants were asked to indicate what their primary OHV was at the CMA. Utility ATV, sport quad, motorcross bike, and trail/enduro bike were cited with about the same frequency. Trials bike was only used by about 2% of the participants as their primary OHV. In additi on, the breakdown of use between two and four wheeled OHVs, was about equal with 46% saying they ride two wheeled OHVs (utility ATVs and sport quads) and 56% listing four wheeled OHVs (trail/enduro, mo torcross, and trials bikes) as their primary OHV at the CMA. About 41% of the respondents ride another type of OHV in addition to their primary type wh ile recreating at the CMA. The majority of survey participants (44.7%) consider themselves of intermediate skill level and 27% consider their skill level to be advanced. The on-site survey asked the participant to rank their last trip to the CMA on a scale of 1 to 10 with 10 being a perfect trip. Close to 29.3 % considered their last trip to be perfect by indicating a ranking of 10. The vast majority al so gave high satisfac tion scores with 92% indicating a score of 7 or higher fo r their last trip to the CMA.

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18 Table 2-1. Visitor characte ristics of respondents. Variable Valid Percent Gender of Survey Participant (N = 148) Male 84.5 Female 15.5 Age (N = 106) 18-29 17.0 30-39 22.6 40-49 48.1 Greater than 50 12.2 Marital Status (N = 146) Single 21.9 Married 67.8 Separated / Divorced 9.6 Widowed 0.7 Children under 18 (N = 147) 0 38.1 1 to 2 50.3 More than 2 11.6 Ethnic Origin (N =144) African American 1.4 Hispanic / Latino 3.5 Caucasian 91.0 Native American 4.2 Level of Education (N = 146) Some High School 8.9 High School Graduate / GED 14.4 Some College 12.3 Trade / Vocational School 17.1 College Graduate 24.7 Some Graduate School 1.4 Graduate Degree 21.2 N= Number of valid survey responses

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19 Table 2-1. Continued Variable Valid Percent Level of Household Income (N = 141) Less then $15,000 1.4 $15,000-$24,999 0.7 $25,000-$34,999 2.8 $35,000-$44,999 9.9 $45,000-$54,999 10.6 $55,000-$64,999 9.2 $65,000-$74,999 11.3 $75,000-$84,999 12.1 $85,000-$94,999 7.8 $95,000-$104,999 5.7 $105,000-$124,999 5.7 $125,000 and above 22.7 Employment (N = 147) Business owner 24.5 Homemaker 2.7 Manager/Executive 12.2 Professional worker 19 Sales worker 3.4 Skilled trade 23.8 Laborer 0.7 Permanently disabled 0.7 Retired 1.4 Service worker 2 Student 2 Other____________ 7.5 N= Number of valid survey responses

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20 Table 2-2. Trip Characteristics of Respondents. Variable Valid Percent Mean Number of years riding OHVs for recreational purposes (N = 149) 16.34 Less than 3 16.0 3 to 10 28.7 11 to 20 22.0 21 to 30 17.3 More than 30 16.0 Total OHV recreational trips take n within the last year (N = 149) 27.81 1 to 3 6.0 4 to 10 21.5 11 to 15 13.4 16 to 20 7.4 21 or more 51.7 Number of years ridding OHVs at the CMA (N = 149) 8.08 Less than 3 41.3 3 to 10 31.3 11 to 20 17.3 21 to 30 6.7 More than 30 3.3 Total number of trips to the CMA within the last year (N = 147) 18.63 1 to 3 16.2 4 to 10 29.7 11 to 15 13.5 16 to 20 8.8 21 or more 31.8 Total household party size on last trip to the CMA (N = 147) 3.20 1 15.0 2 26.5 3 25.2 4 13.6 5 or more 19.7 N= Number of valid survey responses

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21 Table 2-3. Activities and expe rience of Croom Visitors. Variable Valid Percent Primary OHV ridden at the CMA (N = 334) Utility ATV 26.0 Sport Quad 27.8 Motorcross Bike 26.0 Trail / Enduro Bike 18.0 Trials Bike 1.5 Self Reported Skill Level (N = 329) Beginner 6.1 Novice 12.2 Intermediate 44.7 Advanced 28.6 Expert 8.5 1 to 5 3.8 Participant rating of last visit to the CMA (N = 355) 6 4.0 7 16.5 8 28.4 9 18.0 10 29.3 N= Number of valid survey responses

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22 CHAPTER 3 REGIONAL ECONOMIC IMPACT OF OFFHIGHWAY VEHICLE RECREATION AT THE CROOM MOTORCYCLE AREA THROUGH INPUT-OUTPUT ANALYSIS Introduction When studying economic impacts of outdoor r ecreation a common techni que used is that of input-output analysis. This is achieved by co llecting travel expenditure data through surveys administered to the recreation participants (Donnelly et al., 1998; Bria ssoulis, 1991; Fletcher, 1989). The direct benefits that the surveys establis h can then be used to estimate the indirect and induced benefits through the implementation of I-O models (Cordell et al., 1992; Zhou, 1997). IO models consider inter-industry relations in a regiona l economy, as well as their interrelations with final demanded sectors (households, employees government, and trade) in order to evaluate the impact that an industry or, as in the cas e of this study, an activity can have on the local economy (Leontief, 1986; Millar & Blair, 1985). I-O an alysis has become a popular tool for the estimation of regional economic impact by an ac tivity and has been applied numerous times towards this end in recreation studies (Loomis, 1995; Bergstom et al., 1990; Propst; 1985). The IMpact Analysis for PLANning (IMPLAN) softwa re, a computer based modeling system that was developed by the USDA and modified to estim ate economic impacts, is the most commonly used I-O model (Donnelly et al., 1998). Studies using the IMPLAN input-output models to capture the di rect, indirect and induced impacts of OHV recreation to state and local economies have been undertaken on several occasions. A study in Colorado estimat ed that OHV recreation contributed $314 to $354 million to the Colorado economy and supported 3,196 to 3,515 full and part-time jobs (Hazen and Sawyer, 2001). A similar study undertaken in New Hampshire found that OHV recreation contributed around $318 million to the state’s economy and helped to maintain 2,379 jobs

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23 (Okrant & Gross, 2004). In Maine a study i ndicated that OHV recreation, not including snowmobiles, contributed over $200 million and help s to sustain 1,975 jobs (Morris et al., 2005). As with other forms of nature -based recreation that have garnered the attention from states as a rural development tool (Che, 2003; Lindberg et al., 1996) OHV recreation has not gone unnoticed in this regard, as states have recognized its’ rural de velopment pot ential (ATV Task Force, 2003; Vail & Heldt, 2004). However, investigation of the lit erature did not reveal any economic impact study focusing on the impacts from a single riding facility, nor did it find a study looking at impacts to any region smaller then that of a State. Model Description As is often done in establishing recreationa l economic impacts, the regional economic impact assessment for this study was achieve d by developing an economic model using the Impact Analysis for Planning (IMPLAN) software for the four county area that surrounds the Withlacoochee State Forest. IMPLAN is a software package for the construction of I-O models to simulate the effects on economic activity that results from a change in the demand for goods and service in a given region. Before running the model in IMPLAN it is ne cessary to achieve a reliable expenditure estimate to be introduced as the direct impact or shock, into the model. Furthermore, to adequately evaluate the impact of the CMA to the regional economy, it is necessary to estimate the separate expenditures for residents and non-resi dents of this region in order to satisfactorily calculate the new money introduced to the regi on. Detailed survey questions on travel and equipment purchases, county of residence, and purc hase location were used to compute the “new money”. This new money (otherwise known as th e direct impact) quanti ty will have a ripple effect throughout the economy (for a further ma thematical description of the I-O model, see

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24 Appendix E). The estimated total user-days of 71,500 for fiscal year 2006 was provided by the Florida Division of Forestry and used to estima te total number of households visiting the CMA. This estimated household population was then app lied to average household expenditure per trip and average annual equipment expe nditure to establish total expe nditure for CMA visitors. For the purpose of this analysis, economic impact wa s assessed for the counties of Hernando, Pasco, Sumter, and Citrus. As such onl y the percentage of expenditure as identified by the survey participants, was used in the establishment of the total economic impact. Expenditure levels were evaluated for both residents of the f our county region and non-residents. There are three types of economic impacts that input-output m odeling will capture: Direct impactsthe initial e xpenditures that OHV participants make. The total expenditure level, direct impact, as the impetus for additional impacts. Indirect impactsinter-indus try change within the economy as they adjust their output levels to meet the demands of directly affect ed industries, as these industries will adjust inputs to the change in final demand. (Type I im pacts, sum of direct and indirect impacts) Induced impactsindustry sectors that are both directly and indi rectly affected will undergo income changes, further affecting other sect ors as employees adju st their expenditures based on income level. (Type II impacts, sum of type I and induced impacts) The sum of the direct, indirect, and induced impacts provides the total impacts that an activity generates. Impact estimates are provided in terms of sales, income, indirect business taxes, and jobs for the analysis region, and are given as follows: Outputtotal change in sales revenues. Value addedchange in personal and busin ess net income including property related income such as rents, dividends and interest. Labor incomechange in employee wages and salaries. Indirect business taxesthe impact to the re gional economy from a change in taxes, fees, licenses, and other payouts to government (not including federal income taxes) Employmentan impact estimate based on a change in full and part-time jobs.

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25 Results Total Population Estimate In order to establish the total economic im pact of OHV recreation at the CMA, it was first essential to establish the total population re creating at the CMA. As the survey was designed on a per household basis, total popul ation would be defined as tota l households recreating at the CMA. The Florida Division of Forestry estimates total user-days for fiscal year 2006 to be 71,500. Table 3-1 summarizes the results in es tablishing total household population for both resident and non-resident househol ds. Dividing total user-days by mean household size per trip derived total household user-day s. Dividing total household use r-days by the mean number of trips per household provides th e total households recreating at the CMA. The total household day-trip estimates of 6,088 and 16,283 by reside nt and non-resident households respectively were applied to mean expenditure per trip to evaluate total annual trip expenditure. The total population estimates of households recreating at the CMA of 313 and 1,347 resident and nonresident households, respectively, were used to evaluate total annual equipment expenditure. Trip Expenditure Trip expenditure levels were evaluate d for both residents and non-residents. The estimated day-use populations of 6,088 and 16,283 respectively (Table 3-1) were multiplied by mean household trip expenditure (column N, Tabl e 3-2) to achieve tota l annual household trip expenditure (column O, Table 3-2) with total resident expenditure es timated at over $1.1 million and non-resident expenditure at about $5.7 million. As the study is evaluating the regional economic impact to Hernando, Pasco, Sumter, a nd Citrus counties ,the total annual trip expenditure column is multiplied by percentage of expenditure survey participants indicated that they made within the four-county region, 93.9% and 57.4% for residents and non-residents

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26 respectively (Table 3-1). The resulting total annu al trip expenditure (column P, Table 3-2) is estimated at just over $1 million for resident s and over $3.2 million for non-residents. OHV related purchases (row A, Table 3-2) was the ca tegory of greatest expend iture for residents at $0.5 million. For non-residents, purc hases related to transportation (row B, Table 3-2) were the category of greatest expenditure at almost $1.2 million. Entertainment, gift and souvenir purchases (row E, Table 3-2) was the category of lowest expenditure for both resident and nonresidents. Equipment Expenditure Total annual equipment expenditure was al so evaluated for both residents and nonresidents. The population of individual households that travel to the CMA was estimated at 313 resident households and 1,347 non -resident households (Table 3-1). Multiplying household population estimates by mean annual expenditure pe r household (column Q, Table 3-3) generates total household equipment expendi ture (column R, Table 3-3). Using only the percentage of expenditure indicated in Tabl e 3-1 provides the total regiona l annual equipment expenditure estimate (column S, Table 3-3). Total regional eq uipment expenditure is estimated at over $2.1 million for residents and about $7.0 million for non-residents. New OHV purchases (row L, Table 3-3) was the highest expend iture category for both residents and non-residents, with total expenditure levels of $1.4 million and 4.0 millio n respectively. The sum of resident and nonresident total expenditure for both trip and equipment expenditures is $13.59 million and represents the direct impact to the region resulting from OHV recreation at the CMA. The direct expenditure was then distributed across the IMPLAN sectors (Table 3-4) to serve as shocks to those sectors within the model. This shock, or di rect impact, will result in indirect and induced impacts as are described in the following section.

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27 Regional Economic Impact Estimate Table 3-5 summarizes the results of the input -output model in determining the economic impacts of OHV riding at the CMA. Total output impacts were estimated at $21.7 million. Direct output impacts were estimated at $13.6 million a nd measure the direct purchases made by OHV users in the pursuit of their activity. The indir ect output impacts, that capture the activity between industries, were estimated at $1.5 millio n. Induced output impacts, increased activity resulting from industry employees, were estimated at $6.6 million. Looking at the value added portion of the impacts associated with an activity is often more important to policy makers than focusing only on the output impacts. The value a dded is an estimate of the additional value created within the region as a portion of total output. The valu e added impact was estimated at $14.7 million, comprised of $9.6 million in direct $0.8 million in indirect, and $4.3 million in induced impacts. Total impacts resulting from a change in labor income was $9.4 million, consisting of $6.1 million, $0.5 million, $2.8 million in direct, indirect, and induced impacts respectively. Total indirect business taxe s impact was $2.1 million and comprised of $1.7 million, $0.06 million, and $0.3 million in direct, indir ect and induced impacts. Total impacts to employment of 318 full and part-time jobs were estimated to have resu lted from this activity, with 215 direct, 16.4 indirect, and 86.9 induced job impacts. Economic impacts from OHV use at the CMA ar e disaggregated in Table 3-6 to see the impacts to industry groups with in the counties of Hernando, Pa sco, Citrus, and Sumter (see appendix E to view the direct, indirect and i nduced impacts of each industry group and by impact type). The largest impacts are w ithin the retail trade industry group with output impacts of $11.6 million, $8.8 million in value added impacts, and 196 job impacts to empl oyment. Other industry groups with total output impacts of over $0.5 million ar e government, real estate and rental, other

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28 services, health and social se rvices, accommodation and food se rvice, and construction. In addition, all of these industry groups had tota l employment impacts of over eight jobs. Table 3-1. Population Estimate of visitors to the CMA. Resident Non-Resident Estimated total user days, 2006 71,500* Percent of user population 24.9 75.1 Total User-days 17,804 53,697 Household members per Trip 2.9 3.3 Total household user-days 6,088 16,283 Number of trips per household 19.5 12.1 Total households riding at the CMA 313 1,347 Percent of expend iture made within region 93.9% 57.4% *Total user days estimate provided by the Florida Division of Forestry

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29 Table 3-2. Trip expenditure of a typical visito r to the CMA and total trip expenditure for 2006. N O P Mean Household expenditure per trip Total estimated household trip expenditures (millions of $) Total estimated household expenditure within region of analysis (millions of $) Expenditure Category Resident NonResident Resident NonResident Resident NonResident A OHV related purchases (gas, equipment, etc.) $88 $72 $0.53 $1.17 $0.50 $0.67 B Purchases related to transportation to the CMA (gas, tolls, rental fees, etc.) $36 $126 $0.22 $2.04 $0.21 $1.17 C Food & beverage purchases $44 $79 $0.27 $1.29 $0.25 $0.74 D Lodging (hotel, motel, campsite, etc.) $12 $41 $0.08 $0.67 $0.07 $0.38 E Entertainment, gift and souvenir purchases $3 $12 $0.02 $0.20 $0.02 $0.11 F Miscellaneous/other purchases $8 $23 $0.05 $0.37 $0.04 $0.21 Total $191 $352 $1.16 $5.74 $1.10 $3.29

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30 Table 3-3. Equipment expenditure of a typica l visitor to the CMA and total equipment expenditure for 2006. Q R S Mean annual household equipment expenditure Total estimated household equipment expenditures (millions of $) Total estimated household expenditure within region of analysis (millions of $) Expenditure Category Resident NonResident Resident NonResident Resident NonResident G Repairs / routine maintenance to OHVs (gas/oil, lubricants, tools, air filters, tires, wear items, etc.) $661 $746 $0.21 $1.01 $0.19 $0.58 H OHV equipment modifications and upgrades (exhaust, suspension, other aftermarket accessories, etc.) $538 $869 $0.17 $1.17 $0.16 $0.67 I OHV Riding apparel (helmets, boots, eye protection, gloves, additional protective clothing) $333 $597 $0.10 $0.80 $0.10 $0.46 J Equipment or purchase of rentals related to the transport of OHVs (transport vehicle, trailer, gas/fuel, loading ramp, tie-downs, etc.) $721 $1,139 $0.23 $1.53 $0.21 $0.88 K OHV expenditure related to permits, fees (day-use fees, special events fees, competition entry fees, etc.), insurance, Titling, club membership $158 $336 $0.05 $0.45 $0.05 $0.26 L New OHV Purchases $4,774 $5,178 $1.49 $6.97 $1.40 $4.00 M Miscellaneous/other purchases related to OHV riding $196 $237 $0.06 $0.32 $0.06 $0.18 Total $7,381 $9,105 $2.31 $12.26 $2.17 $7.04

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31 Table 3-4. Regional impact ev ents by IMPLAN sector. Expense Item Implan Sector Resident* (millions of $) NonResident (millions of $) Gas, equipment for OHV 407Gasoline stations $0.50 $0.67 Transportation to the CMA (gas, tolls, rental fees, etc.) 407Gasoline stations $0.21 $1.17 Food & beverage 405Food and beverage stores $0.25 $0.74 Lodging (hotel, motel, campsite, etc.) 479Hotels and motels $0.07 $0.38 Entertainment, gifts and souvenirs 478Other amusement and recreation industries $0.02 $0.11 Miscellaneous/other 411Miscellaneous store retailers $0.04 $0.21 Repairs / routine maintenance (lubricants, tools, air filters, tires, wear items, etc.) 483Automotive repair and maintenance $0.19 $0.58 Equipment modifications and upgrades (exhaust, suspension, other aftermarket accessories, etc.) 401Motor vehicle and parts dealers $0.16 $0.67 Riding apparel (helmets, boots, eye protection, gloves, additional protective clothing) 408Clothing and clothing accessory stores $0.10 $0.46 Transport equipment purchase or rental (vehicle, trailer, gas/fuel, loading ramp, tie-downs, etc.) 432Automotive equipment rental and leasing $0.21 $0.88 New OHV purchase 401Motor vehicle and parts dealers $1.40 $4.00 Permits, fees, insurance, titling, club membership 499Other state and local government enterprises $0.05 $0.26 Miscellaneous/other purchases related to OHV riding 411Miscellaneous store retailers $0.06 $0.18 *Participants residing in the counties of Citrus, Sumter, Hernando, Pasco Counties

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32 Table 3-5. Direct, indirect and induced regiona l economic impact of OHV recreation at the CMA. Output (millions of $) Value Added (millions of $) Labor Income (millions of $) Indirect Business Taxes (millions of $) Employm ent (Jobs) Direct $13.59 $9.55 $6.13 $1.75 215 Indirect $1.50 $0.82 $0.50 $0.06 16 Induced $6.57 $4.32 $2.75 $0.33 87 Total $21.66 $14.69 $9.38 $2.14 318

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33 Table 3-6. Total regional economic impact by industry group for OHV activity at the CMA. Industry Group (NAICS)* Output (millions of $) Value Added (millions of $) Labor Income (millions of $) Indirect Business Taxes (millions of $) Employment (Jobs) Ag, Forestry, Fish & Hunting 0.047 0.025 0.011 0.001 0.8 Mining 0.001 0.001 0.000 0.000 0 Utilities 0.311 0.224 0.068 0.032 0.8 Construction 0.733 0.296 0.256 0.004 8 Manufacturing 0.258 0.064 0.046 0.001 1.2 Wholesale Trade 0.159 0.121 0.068 0.026 1.7 Transportation & Warehousing 0.273 0.171 0.131 0.004 3.3 Retail trade 11.598 8.804 5.691 1.723 195.7 Information 0.261 0.094 0.048 0.008 1.3 Finance & insurance 0.371 0.234 0.109 0.007 2.7 Real estate & rental 1.490 0.719 0.292 0.065 12.5 Professionalscientific & tech svcs 0.381 0.196 0.167 0.003 4.9 Management of companies 0.060 0.033 0.025 0.001 0.5 Administrative & waste services 0.323 0.163 0.129 0.005 5.4 Educational svcs 0.037 0.020 0.019 0.000 0.9 Health & social se rvices 0.898 0.565 0.491 0.006 12.4 Artsentertainment & recreation 0.192 0.115 0.066 0.014 3.8 Accommodation & food services 0.827 0.499 0.305 0.064 17 Other services 1.185 0.567 0.420 0.072 20.8 Government & non NAICs 2.256 1.782 1.032 0.104 24.2 Total 21.661 14.689 9.376 2.139 318 *North American Industry Cl assification System

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34 CHAPTER 4 CONSUMER SURPLUS ESTIMATION: AN INDIVIDUAL TRAVEL COST METHOD APPROACH Introduction The previous chapter dealt with the economic impact estimation through input-output (IO) analysis. I-O analysis is i nherently a supply side model as it is designed around regional production process (Leontief, 1986). While the data that I-O analysis provides is useful to recreational planners and policy makers, it does not fully capture the impact or benefit of a recreation area to society as it fails to capture the benefits to consumers. To capture this value of a resource it is necessary to evaluate consumer su rplus (CS). CS can be defined as the total value that recreational consumers place on the resour ce minus actual expenditures. The estimation of consumer surplus is achieved through the quantif ication of the area under the demand curve of a user between the choke price and th e price actually paid (Dobbs, 1993). One approach for the calculation of this dema nd curve is the travel cost method (TCM). The TCM is derived from revealed preference th eory (Ward & Beal, 2000); hence it is based on real market data as the purchase decisions have already been ma de by the participant (Oh et al., 2005). TCM allows one to determine a Marshallia n demand curve to calculate the area between consumers actual price and the maximum price they are willing to pay. Potential visitors to a site will decide to visi t that site only if they achieve some value from their visit or their costs are not greater than th eir perceived benefit (Siderelis & Moore, 1995). In accordance with demand theory, as the cost of the trip to a site incr eases, the visits will decrease (Fix & Loomis, 1997), al lowing one to derive a site de mand curve. As such, the value of this site can then be estimated using a site demand model (Siderelis & Moore, 1995; Hesseln et al., 2004; Dobbs, 1993).

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35 Within TCM there are two methods, zonal a nd individual. Zonal TCM is based on census data and arbitrary geographic areas generated by zip codes leading to zonal bias (Bowker et al., 1996). Individual TCM (ITCM) is based on survey info rmation gathered from visitors to the site. In addition to avoiding zonal bias, it is possibl e to incorporate further explanatory variables within the demand function thr ough the collection of data on tr ip and visitor characteristics (Siderelis & Moore, 1995). Given the above, th e ordinary demand function for a user of a recreation area is t = f(TC, TD, TChar, VChar) where : t = number trips per year TC = travel cost per trip TD = travel distance per trip TChar = vector of trip characteristics variables VChar = vector of visitor characteristics variables. The estimation of CS for r ecreation sites through the use of ITCM has been used extensively. Siderelis & Moore ( 1995) concluded that the total consumer surplus from three different rail-trail sites throughout the Unite d States ranged from $1.9 million to $8.5 million ($9.56-$49.78 individual CS per trip). Shrestha et al. (2002) estimat ed that CS to be between $35 million and $57 million ($540.45-$869.57 individual CS pe r trip) for recreational fishing visitors to the Brazilian Pantanal. Another study undertaken by Oh et al. (2005) on recreational fishers of the Sam Rayburn Reservoir in Texas evaluated individual CS per trip to be between $249-$414. Lockwood & Tracy (1995) evaluate d the CS of an urban park in Australia to be between $23 million to $33 million. However, with the excep tion of a study on snowmobiling in Wyoming where individual CS per trip was estimated at $68 (Coupal et al., 2001), no other study on the estimation of CS for OHV recreation was found.

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36 ITCM Model Specification There are several alternative methods fo r establishing demand models (Dobbs, 1993). This study uses the continuous ordinary leas t squared (OLS) model with a logarithmic transformation of the dependent variable. Th e semi-log OLS method has been applied many times for the estimation of consumer surplus (C S) for recreation participants (Balkan & Kahn, 1988; Willis & Garrod, 1991). Alternative models that have been used include OLS without the logarithmic transformation of the dependent variable and maximum likelihood estimators (Hesseln et al., 2004; Shrestha et al., 2002). Two studies that have utilized the semi-log OLS model along with the alternative models have indicated the semi-log OLS CS estimate to be a median value estimate compared to other m odels (Smith, 1988; Siderelis & Moore, 1995) In the construction of the semi-logarithmi c OLS model to evalua te individual household and total consumer surplus for this study, explanat ory variables were evaluated in addition to the travel cost variable to further refine the fi nal model, as such various trip and visitor Table 4-1. Description of variab les used in the ITCM model. Variable Description TRIPS Total number of household tr ips taken in the last year. TRVLCOST Household travel cost per trip. DISTTRVL One-way travel distance to the CMA. YRSRIDCMA Years riding at the CMA. FMPRTYSZ Family party size riding at the CMA TRPRATING Overall rating of last trip to the CMA. (Scale of 1 to 10 where 10 is a perfect trip) OHVTYPE Primary OHV type ridden at the CMA. (0 = ORM, 1 = ATV) OVRNGHTDM Dummy variable for multi-day trips to the CMA. (1 = made at least one overnight trip within the last year) GENDER Gender of the survey par ticipant. (1 = male, 0 = female)

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37 characteristics variables were included in the model. TRVLCOST, DISTTRVL, and YRSRIDCMA were included in the several re gression models that were constructed incorporating contrasting groupings of trip and visitor characteri stics. Visitor characteristic variables were never significant predictors in th e models, as such all ex cept for GENDER were not included in the final model, as shown in equation 4-1, which was selected based upon its goodness of fit to the population as evaluated by the adjusted R2 statistic and reached its highest level with the inclusion of these variables in e quation 4-1. The description of the variables used are given in Table 4-1. (4-1) To estimate the individual CS from the resu lting model, it is nece ssary to evaluate the area under the demand curve generated by the semi -log OLS model. Normally this would be accomplished by the calculation of th e integral of the function. However, since the semi-log form was used the accepted estimation method, as desc ribed by Smith and Devouges (1985), is to approximate the integral as the negative inverse of the coefficient on the travel cost, -(1/1). Results Table 4-2 summarizes the descriptive statisti cs of the variables used in the regression model. As a non-response in any variable will result in the entire case be excluded when conducting linear regression, the sample size for this analysis was 139 out of the initial 150 cases. Survey questions reveled that househol ds in this sample make over 18 (18.68) trips annually to the CMA and spend over $255 on averag e per trip on travel related expenses. On average, households travel over 104 miles one-way and recreate at the CMA with over 3 family members. Participants tended to be loyal to th e CMA through the indication that they have been nTRIPS 0 1( TRVLCOS T ) 2( D ISTTRVL ) 3( YRSRIDCMA ) 4( GENDER ) 5( OHVTYPE ) 6( FMPRTYSZ ) 7( OVRNGHTDM ) 8( TRPRATING )

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38 riding there for almost 8 (7.92) years and showing an overall enjoyment of their experience, giving the CMA a mean score of 8.46 out of a maxi mum of 10. Types of vehicles ridden at the CMA were almost equally split between off-ro ad motorcycles (ORM) (48.9%) and all-terrain vehicles (ATV) (51.1%). Over 56.1 i ndicated that they made at le ast one overnight trips within the last year. The gender results must be interp reted with a bit of cauti on as the surveys were designed on a household basis to reduce the comple xity and length of the survey. As such the variable GENDER may under-represent females. As stated, the final model was se lected based on the adjusted R2 value, in this case 0.275 (Table 4-3). The R2 value is 0.317. But since R2 tends to optimistically estimate the model fit to the population, the adjusted R2 value was used. As the key property of the ITCM is the i nverse relationship between the travel cost variable and that of the number of annual tr ips taken, without this relationship it would be impossible to get a demand function and the co rresponding estimate of the CS. As shown in Table 4-3, an inverse relationship does exist as TRVLCOST has a negative impact on the number of trips taken an d is significant (p=0.031). In looking at the other explanat ory variables in the model, fo r variables are significant at the P 0.05 level. DISTTRVL has a negative effect on trips taken with a p-value of 0.01. The negative sign on DISTTRVL was ex pected, one would expect to obs erve a decline in trips taken as the distance needed to travel to an area in creases. Another highly si gnificant variable is YRSRIDCMA (p=0.004) and it exhibits a positive relationship with trips taken. It is also important to note that this variable was alwa ys the most significant and always at the P 0.010 in every model run. This result is highly suggestive of habit formation of users at the CMA, as the more users experienced the CMA, the greater the amount of trips they would make in a year.

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39 TRPRATING was significant with a p-value of 0. 016 and had a positive relationship with trips made. Again, this was a result that was anticipated, as one would expect to observe an increase in trips taken with an increased enjoyment of their experience. The variable FMPRTYSZ was significant at the P 0.10 level (p=0.051), with a negative impact on trips taken, hence the greater the family riding groups is, the fewer the trips taken. While the remaining three variables are not significant at the P 0.10, it is interesting to note that visitor characteristics were not significant, nor were the socio-demographic variables significant in any of the various models creat ed. This result was not expected. Often sociodemographic such as age, sex and income are si gnificant predictors of the dependent variable, not in the case of OHV recreation. Total Consumer Surplus Estimation. By taking the negative inverse of the TRVLCOST coefficient –(1/-6.232E-04), the re sulting individual household CS per trip is estimated at $1,605. To evaluate total annual CS, it is necessary apply this to total household trips, 19,455 the number of unique trips of all hou seholds to the CMA. As such, the total annual household CS is estimated at $31.23 million.

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40 Table 4-2. Descriptive sta tistics of variables used in the model (N = 139). Variable Mean Total trips to the CMA 18.68 TRVLCOST ($) $255.01 DISTTRVL 104.31 YRSRIDCMA 7.92 FMPRTYSZ 3.20 TRPRATING 8.46 % OHVTYPE Off-road motorcycles (0) 48.9 All-terrain vehicles (1) 51.1 OVRNGHTDM No overnight trips (0) 43.9 Made at least one overnight trips(1) 56.1 GENDER Female (0) 16.5 Male (1) 83.5

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41 Table 4-3. Regression model results (N = 139). Variable Coefficient (Beta) P-value Standard. Error (constant) 1.255 0.049** .632 TRVLCOST -6.232E-04 0.031** .000 DISTTRVL -1.389E-03 0.010** .001 YRSRIDCMA 2.694E-02 0.004** .009 FMPRTYSZ -8.615E-02 0.051* .225 TRPRATING 0.155 0.016** .176 OHYTYPE -0.250 0.158 .044 OVRNGHTDM 0.250 0.163 .178 GENDER 0.238 0.292 .064 R2 0.317 Adjusted R2 0.275 **Significance at p 0.05 *Significance at p 0.10

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42 CHAPTER 5 MOTIVATIONS OF OFF-HIGHWAY VECHICLE USERS Introduction Visitors to the CMA have made the decisi on to participate in OHV recreation at that facility. Previous results have indicated that their decision has generated economic benefit to the surrounding communities. In addition, visitors to the CMA receive benefits from their involvement, captured by the individual househol d consumer surplus estimate per trip of $1,605. As CS can be defined as the value of the to tal experience minus travel expenditures (Huppert, 1983; Dobbs, 1993), the CS can also be considered a value estimate of visitors experience at the CMA. Driver & Tocher (1970) define a recreatio nists experience as the desired psychological result (benefit) that motivates them to participate in a recrea tion opportunity. They only engage in a recreation opportunity if their efforts lead to their desired benefit (Haas et al., 1981; Manfredo et al., 1983; Lawler, 1973). Given this, it is important for planners to understand the desired benefits of visitors in order to provi de the opportunities for th e attainment of these benefits (Graefe & Fedler, 1986; Stein & L ee, 1995; Driver, 1985). By providing these opportunities, planners can aid in the produc tion of economic, pe rsonal, social and environmental benefits that result from the indi vidual’s choice to participate in a recreation activity (Brown, 1984; Stein & Lee, 1995). Research on the desired benef its of visitors has been ongoing since the 1970s (Stein et al., 2003). There has been a profusion of studies done on recreational activities to identify the desired benefits that motivate th e individual to participate in a given activity. Loomis & Ditton (1987), Wilde et al. (1998) and Fedler & Ditt on (1994) investigated th e benefits that are important motivations to recreati onal anglers. Cross-country skiers were studied by Haas et al. (1981) to identify their desired be nefits. Other studies have looked at and determined the benefits

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43 for backpacking (Brown & Hass, 1980) and hunt ing (Hautaluoma & Brown, 1978). Studies have also found that experiences are not homogenous to activity classification, that, in fact, benefit sub-groups exist within activit ies (Manfredo et al., 1983; Brown & Haas, 1980; Hautaluoma & Brown, 1978). Yet, no study could be located that attempted to esta blish the desired benefits for recreational OHV users, nor potentia l subgroups within the activity. Data Analysis To identify the desired benefits that motivat e visitors to participate in OHV recreation at the CMA, a 19-item list was given where the partic ipant was asked to rate the importance of each benefit item as a motivation for their involvement5. Cluster analysis was then undertaken on the 19-item list in order to classify respondents in to homogenous subgroups ba sed on their similarity in motivational responses (Lorr, 1983). This approach has been applied many times in recreation research as a means of identifying homogenous subgroups (Purnomo et al., 2005; Manfredo et al., 1983; Oh et al., 2005; Hautaluoma & Brow n, 1978; Collins & Hodge, 1984; Stein & Lee, 1995) and undertaken using the K-means clus ter procedure using SPSS 11.0 for Mac. A final solution of three-clusters was accepted based on the size and interpretability of the resulting groups (Hair et al., 1998; Lorr, 1983). Results Desired Benefit Profile of OHV Users at the CMA The mean responses for each of the 19 benefit variables are listed in descending order in the first column of Table 5-2. A look at the overal l means illustrate the fam ily oriented nature of the motivations behind OHV recreation. The benefits to “be with friends and family” (mean = 4.47) and “strengthen family kinship” (mean = 4.17) are the top two ranked benefits. 5 For this purpose a Likert scale was used where 1 = Not at all important, 2 = Not very important, 3 = Important, 4 = Very important, 5 = Extremely important

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44 Additionally, the resu lts indicate that individu al oriented benefits ar e also important to OHV recreationists. Ranked third and fifth respectively were to “r educe tensions and stress from everyday life” (mean = 4.14) and “improve my sk ills and abilities” (mean = 4.05). The two other benefits with a mean ranking of over four were to “enjoy nature” (mean = 4.07) and “promote physical fitness” (mean = 4.03), ranked fourth and sixth respectively. Ra nked at the bottom of the list of motivations and two of only three benef it statements with a mean of below three, are to “engage in personal / spiritual reflection” (m ean = 2.81) and “take risks” (mean = 2.63), ranked 17th and 19th respectively and individualistic in na ture. Taken as a whole, the population participates in OHV recreation at the CMA mainly for the attainme nt of family based benefits but, while less important, place some si gnificance on individual benefits. Benefit Subgroup Identification Cluster analysis classified the particip ants into three subgr oups based on their motivations for participating in OHV recreati on at the CMA (Table 5-1). To identify the motivational makeup of the three groups, an anal ysis of variance (ANOVA) test was undertaken with the cluster group as the fact or and the 19 benefit scale questi ons as dependent variables. By examining the post hoc test results of the motivat ional statements for the groups (Table 5-2) and the listwise ranking of the motivations for each group, evident difference emerges between the groups. Group 1 (n = 70, 52.2%), the Experiencers, indica ted that both family and individualistic benefits as important reasons for their invol vement in OHV recreation. Post hoc analysis revealed that Experiencers mean score on 18 out of the 19 variables was either greater than the other two groups or at least greater than one group while exhibiting no significant difference with the other group. The only variable in which the Experiencers had a mean score significantly

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45 smaller than another group was the benefit item to “take risks”. As Table 5-2 illustrates, Experiencers had a mean score of over three for each item except the aforementioned “take risks” (2.79), an indication of the importance for the attainment of multiple benefits as a motivation for riding. Table 5-3 gives the top and bottom five ranked benefits for each group with the ranking of the other two groups in the succeeding two columns. While family-based motivations are the top two, the fourth and fifth are very much individualis tic in nature, “reduce tension” (M = 4.54) and “promote physical fitness” (M = 4.39). Group 2 (n=32, 23.9%), Familists, ranked family or iented benefits as primary reasons for their involvement in OHV recreation. While Fam ilists may have certain top five benefits in common with Experiencers, Familists are even more family centric in regards to riding motivations. Where as Experiencers ranked the st atement to “Continue family traditions” 12th, it was 3rd for Group 2 (M = 3.97). The statement to “be in an area where I feel secure and safe”, a motivation one would expect to be higher for fam ilies, is ranked fourth by Familists as apposed to eighth for Experiencers. Group 3 (n = 32, 23.9%), the Individualists, rated individualistic orient ed benefits at the top for reasons as to why they participate in OHV recreation. Whereas the other two groups placed importance on family centered benefits, the results indicated that I ndividualists rode, as the name would suggest, primarily for the attainme nt of individual benefits. The top two benefits for group 3 were to “improve my skills and abil ities” (M = 4.28) and “depend on my skills and abilities” (M = 4.16). As table 5-3 shows, with the excep tion of to “promote physical fitness” for Experiencers (5th), none of the Indivi dualists’ top five benefits were ranked within the top five of the other two groups. Until now the bottom five bene fits as shown in Table 5-1 have not been mentioned, largely due to the similarity betw een the first two groups. However, looking at

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46 Individualists’ bottom five, further illustrates just how centered Individualists are for the attainment of individual benefits. To “contin ue personal or family traditions” ranked 3rd by Familists and 12th by Experiencers, was ranked 15th by Individualists, with a mean score of below three (2.59). The benefit to “take risks” was ranked last when looking at the overall population (M = 2.63), last by Familists (M = 1.56) and last by Individualists (M = 2.79), but was ranked ninth by Group 3, with a mean of 3.3 4 and the only mean for which Group one had a significantly smaller mean than another group. Benefit Subgroup Description With the knowledge that homogenous subgroups exist based on their desired benefits for riding OHVs at the CMA, it is important to unde rstand the differences between the groups in terms of visitor and trip characteristics. To this end, ANOVA and Chi-squared tests were undertaken to identify if any significant differe nces in visitor and trip characteristics existed between the groups. Table 5-4 and 5-5 display th e results of ANOVA and Chi-S quared test respectively on visitor characteristics. No si gnificant differences were found be tween groups for the variables number of children in the household, age, mar ital status, education, or income. The groups only differed significantly (p = 0.021) when it came to gender, where Individua lists were significantly more male at 96.9% versus 82.9% for Experiencers and 71.0% for Familists Considerably more varia tion existed between the gr oups when looking at trip characteristic variables. While no significant difference was found in total number of annual OHV recreation trips or annual trips to the CMA, Experiencers were more likely to have made at least one multi-day trip per year, 68.6%, with 56.3 % of Familists making a multi-day trip. However only 31.3% of Individualists indicated they made at least multi-day trip within the last

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47 year, indicating their preference for day trips, a deviation that is statis tically significant (p = .002). When at the CMA, the groups differ si gnificantly (p = 0.038) in their OHV type preference. While 62.5% of Indivi dualists indicated their primar y OHV at the CMA is an ORM, only 31.3% of Familists rode ORMs, suggesting fa milies may consider a four wheel OHV a safer alternative. Not surprisingly th ere was a significant difference (p = 0.020) in mean party size between the groups with Individu alists having a mean of 2.39 people per trip versus means of 3.56 and 3.55 for Experiencers and Familists. Indivi dualists gave the CMA a significantly lower mean trip rating (p = 0.050), however it is important to note that while they rated the CMA lower than the other groups, it was still above 8 (8.03). When looking at total yearly OHV e xpenditure excluding new OHV purchases, Experiencers spend more money ($5,077) than either Familists ($2,665) or Individualists ($2,197) a difference that is highly significant (p =0.000). This result is interesting as there was no significant difference in OHV trips per year an d no difference in one-way travel distance to the CMA. In fact, Individualists traveled fu rther (146.38 mi) than Experiencers (122.45 mi) to get to the CMA and made more trips in a year (22.75 versus 17.52). As Expe riencers are after the attainment of multiple benefits, this goal may necessitate the outlay of additional expenditure towards that end.

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48 Table 5-1. Results of cluster analysis (N = 134). Cluster N Group 1 (Experiencers) 70 Group 2 (Familists) 32 Group 3 (Individualists) 32

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49 Table 5-2. Desired benefits of re spondents and benefit subgroups. Means Statement Overall Mean Group 1 (Experiencers) Group 2 (Familists) Group 3 (Individualists) Tukey HSD Post Hoc Mean test Ordering Be with friends and family 4.47 4.74 4.53 3.75 1,2>3a Strengthen family kinshi p 4.17 4.64 4.22 2.97 1>2>3a Reduce tensions and stress from everyday life 4.14 4.54 3.66 3.63 1>2,3a Enjoy nature 4.07 4.60 3.69 3.37 1>2,3 Improve my skills and abilities 4.05 4.36 3.25 4.28 1,3>2 Promote physical fitness 4.03 4.39 3.31 3.97 1>3>2 Be in an area where I feel secure and safe 3.93 4.34 3.91 3.03 1>2>3 Depend on my skills and abilities 3.88 4.26 2.81 4.16 1,3>2 Challenge myself and achieve personal goals 3.70 4.10 2.69 3.81 1,3>2 Explore the area and natural environment 3.67 4.37 3.12 2.87 1>2,3 Feel a sense of independence 3.64 4.13 2.88 3.25 1>2,3 Continue family traditions 3.57 3.93 3.97 2.59 1,2>3a Test vehicle’s performance 3.51 3.69 2.69 3.91 1,3>2 Meet new people 3.27 3.66 2.84 2.72 1>2,3 Escape noise/crowds 3.15 3.66 2.47 2.56 1>2,3 Learn about the natural environment of the area 3.05 3.70 2.53 1.81 1>2,3 Engage in personal/spiritual reflection 2.81 3.51 1.84 2.31 1>2,3 Learn about history and culture of the area 2.68 3.29 2.25 2.12 1>2>3a Take risks 2.63 2.79 1.56 3.34 3>1>2a Note: Means are based on a scale of 1 to 5, where 1 = not at all important, 2 = not very important, 3 = important, 4 = very important, and 5 = extremely important. Mean differences between the groups were evaluated using the Tukey Highest Significant Difference test at the p < 0.05 level. a Indicates that the assumption of equal variance does not hold and the Games-Howell test was used to evaluate mean difference, where p < 0.05.

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50

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51 Table 5-4. Visitor characteristic s by cluster membership (ANOVA). Variable Overall Group 1 Group 2 Group 3 F P Group mean rankinga Number of Children under 18 in Household 1.17 1.20 1.47 0.90 1.731 0.181 NS Age 40.59 38.90 42.39 40.61 1.068 0.348 NS aDifference in group means evaluated using Tukey's HSD post hoc test where p<0.05 Table 5-5. Additional visitor charac teristics by cluster membership ( 2). % Variables OverallGroup 1 Group 2 Group 3 2 P Gender Male 83.5 82.9 71.0 96.9 7.694 0.021 Female 16.5 17.1 29.0 3.1 Marital Status Married 67.2 65.7 75.0 62.5 1.273 0.529 Single 32.8 34.3 25.0 37.5 Education High school grad or less 23.1 25.7 25.0 15.6 4.389 0.356 Trade/voc. School or some college 27.6 30.0 15.6 34.4 College graduate and above 49.3 44.3 59.4 50.0 Household income Below $35,000 4.5 5.7 0.0 6.3 4.754 0.576 $35,000 to $64,999 29.9 34.3 31.3 18.8 $65,000 to $94,999 28.4 24.3 31.3 34.4 $95,000 and above 37.3 35.7 37.5 40.6

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52 Table 5-6. Trip characteristic s by cluster membership (ANOVA). Variable Overall Group 1 Group 2 Group 3 F P Group mean rankinga Years of riding OHV's 16.23 15.89 15.13 17.56 0.324 0.724 NS Years of riding OHVs at the CMA 7.76 7.96 7.27 7.81 0.119 0.888 NS One-way travel distance to the CMA 121.01 122.45 92.37 146.38 0.527 0.592 NS Party Size while riding at the CMA 3.22 3.56 3.55 2.39 4.028 0.020 1,2>3 Overall trip rating 8.46 8.69 8.41 8.03 3.009 0.050 1,2>3 Variables where homogeneity of variances cannot be assumed Variable Overall Group 1 Group 2 Group 3 Statisti cc P Group mean rankingb Total trips to the CMA 18.53 17.52 12.97 22.75 2.37 0.102 NS Total Yearly OHV trips 27.81 29.12 18.31 32.97 2.89 0.062 NS Total Yearly OHV expenditured 3896.4 3 5076.66 2665.15 2196.88 10.25 0.000 1>2,3 aDifference in group means evaluated using Tukey's HSD post hoc test where p<0.05. bDifference in group means evaluated using Games-Howell post hoc test where p<0.05. cBrown-Forsythe statistic used, Asymptotically F distributed. dExluding new OHV purchases. Table 5-7. Additional trip characteristics by cluster membership ( 2). % Variable Overall Group 1 Group 2 Group 3 2 P Primary OHV type Four wheel type 50.7 48.6 68.8 37.5 6.529 0.038 Two wheel type 49.3 51.4 31.3 62.5 Made a multi-day trip within the last year Yes 56.7 68.6 56.3 31.3 12.464 0.002 No 43.3 31.4 43.8 68.8

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53 CHAPTER 6 DISCUSSION AND CONCLUSIONS While much of the literature and public attention towards OHV recreation has centered on the negative ecological and social impacts resulting from OHV riding, this study investigates the potential positive impact. Whereas the negative impacts are especially visible, positive social and economic externalities looked at in this study are largely veiled from public perception. In the case of the CMA the total economic impact did not occur in one site nor in a single event, but resulted from thousands of small purchas e decisions, by over 1500 households throughout a years time, and over a wide geographic area. The su m total of the purchases related to recreating at the CMA was over $13 million, with a tota l impact of $21 million and over 318 jobs. The $21 million economic impact is a benefit to the region but this value does not capture all the benefits generated by the CMA, as it does not capture the user benefits to the CMA. User benefits as measured by consumer surplus (CS) were evaluated in Chapter 3 and, at over $31 million with an individual household CS per trip at over $1,600, is substantial. Relative to other TCM valuation studies (page 34), CS per trip wa s on the high side. But it is not to far above other estimates when one accounts for the fact that the $1,605 estimate was household CS. As such, with an average of 3.2 family members per trip the individual CS is $501, which is in-line with other CS estimates such as Oh et al. (2005) CS estimate of $249-$414 per trip for recreational fishing site in Texas. The high CS result is consistent with the concept of commitment which states that a participant’s leve l of emotional and equipment investment in an activity is greater for those who are most co mmitted (Buchanan, 1985; Mc Farlane, 1996; Oh et al., 2005). A considerable investment results in a larger CS (willingness-to-pay) as they would have the most to lose from a loss of recreati on areas. OHV recreation necessitates a considerable outlay of thousands of dollars for equipment re quired to recreate, nece ssitating a considerable

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54 commitment. One must also consider the scarcity of riding areas when inte rpreting these results. The CMA is one of only five riding facilities in Florida and, located at 30 miles north of Tampa, the southern most OHV riding area. Visitors travel si gnificant dist ant (over 100 miles one-way) and make the journey multiple times a year (18.6 annual trips) to ride at the CMA. Their commitment and the lack of riding areas results in the appreciably large value they place on the benefits they attain from the CMA, as ther e are few other opportunities in Florida for the attainment of the desired bene fits of recrea tional OHV users. As such, it is important to understand what these highly valued benefits are that riders hope to attain through their involvement in OHV r ecreation in order to better manage for the opportunities that provide them. Results from Chapter 5 indicate that it is in the attainment of family oriented benefits that are the top two motivations. However, riders also indicated the importance of individual benefits such as “reduce tensions and stress from everyday life” and “improve my skills and abiliti es” as important motivations. Rounding out the top five was “enjoying nature” indicating a riding prefer ence for riding in na tural settings. The $1,600 individual household CS is the estimated value that households place on the attainment of these benefits. It is important to identify potential motiva tional subgroups, as groups of visitors may ride for the attainment of benefits that differ from the general populat ion. Understanding these subgroups allows managers to incorporate their be nefits in the planning process to ensure the continued visitation of these subgr oups. Results from cluster anal ysis in Chapter 5 reveal the existence of 3 homogenous benefit subgroups: Ex periencers, Familists, and Individualists. Experiencers and Familists did not differ from th e general population, in that their top benefits were still family oriented. However, results show that Experiencers consid er the attainment of a

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55 diversity of benefits as motivations for their in volvement. Familists were more oriented toward the attainment of family based benefits than the general population. The Individualists were the most unique out of the three subgr oups. Individualist rode almost exclusively for the attainment of individual oriented benefits. None of the top five motivatio ns for the Individualists were within the top 5 of the othe r two groups, nor the top five of the general population. Is the CMA providing the necessary opportuni ties that allow for the attainment by the visitors of these divers e benefits? While this study did not specifically addr ess this question, interpretation of the data lead s one to conclude that the CMA is providing the opportunities for the attainment of diverse benefits. Visitors to the CMA have been riding there for almost eight years and taking an average of over 18 trips annually. Granted, Fl orida does have limited riding areas, but this long-term frequent use would not be expected if visitors were not attaining their desired benefits. Additionally, when participants we re asked to rate their last visit to the CMA, they gave a mean score of 8.46 out of a possibl e 10. All three motivational subgroups had similar results in respect to the variables mentioned. Th e group with the lowest mean years of riding at the CMA and number of annual trips taken were the Familists, but who have still been riding at the CMA 7.27 years with an annual average of 1 2.97 trips. The lowest mean rating was given by the individualists, but at 8.03 still considered their experi ence at the CMA worthwhile. It is because visitors to the CMA attain the be nefits they seek, that they return year after year. The value they place on th eir benefits is captured by their CS, and is substantial. The substantial user valuatio n of these benefits induces their deci sions to make purchases in pursuit of their desired benefits. Their expenditures, in turn, generates economic benefits to the surrounding communities, through the addition of ne w money into the region and the associated additional economic activity.

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56 Policy Implications Florida has committed to provide several addi tional riding areas to meet the increasing demand and reduce the negative im pacts associated with OHV recr eation. However, this will only be possible if the new ridi ng areas provide the opportunities fo r OHV riders to attain their desired benefits. If Florida is ab le to design and manage future ar eas that incorporate the desired benefits of the participants the results could be similar to that of the CMA. This study has illustrated that for OHV recrea tionists the prime motivations for riding are for the attainment of family base d benefits. As such, future areas need to design areas that would provide the facilities and experi ences that would attract these ri ders. However, simply designing areas to attract family OHV riders would fail to attract the maximum numb er of people as this study demonstrated that motivational homogenous subgroups exist. While family oriented benefits are still important, the group Experiencers indicated the importance of multiple and diverse benefits in riding OHVs. Another group, Individuals, ride almost exclusively for the attainment of individual oriented benefits. Planners need to be aware of and manage for the multiple benefits desired by the OHV riding population, otherwise future areas may be unsuccessful in drawing OHV riders away from unmanaged and illegal riding opportunities. The CMA has done just this with DOF personnel indicating that OHV riding is no lo nger an issue throughout the rest of the Withlacoochee State Forest. This is attributable to the CMA providi ng the benefits that ride rs are looking for. The DOF has never integrated this type of informa tion into their management plan for the CMA; however managers have been successfully achieved satisfied users. But u nderstanding why riders come to the CMA will improve the management of future areas through the integration of participant desired benefits into the management process. This integration in future area is

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57 crucial as areas may not be as big or rural, hence the need to specialize. In addition, the fact that the CMA has done this well, gives further weight to the DOF plan to use the CMA as a model for the design of future areas. The results from this study testified to the substantial economic impact that OHV recreation generates to the surr ounding communities. The estimate of $21 million in total output impacts and over 318 jobs is a product of the e xpenditure of visitors to the CMA. Future OHV areas in Florida will undoubtedly induce economic im pact within their region, but the level of the impact will be directly tied to the amount of riders attrac ted to the area. Again, to maximize economic impact, planners need to provide the opportunities that a llow OHV riders to attain their desired benefits. If this is done, results simila r to the CMA could be expected, with communities seeing both economic impact and a reduc tion in illegal ri ding on non-OHV lands. The economic impacts and the natural setti ng nature of OHV recreation has already prompted other states and communities to re cognized OHV recreation as a potential rural development tool. But, like othe r regions, communities in Florida have not been receptive to potential future areas. This is not surprising gi ven the visible nature of the environmental and social impacts of OHV recreation along with th e hidden nature of economic impacts. By illustrating the regional economic impacts, addi tional information is know available for the decision making process. As such, communitie s may be more receptive to a potential OHV riding area as this information has the possibility of adjusti ng the cost-benefit analysis and communities may deem the costs acceptabl e in light of the economic impacts. Future Work Towards the understanding of OHV recreation, the largest gap in the data is that of resident perceptions of the impacts. While so me secondary sources ex ist, no comprehensive

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58 study could be located that l ooked at how local residents pe rceived the economic, social, environmental impacts. Information of this type could further help managers plan OHV riding areas that would be more acceptable to resident s. To date no information could be found that illustrated the integration of resident perceptions into any OHV area design. While establishing economic impact was an element of this study and has been undertaken in other OHV recreation studies, what ha s yet to be undertaken is a study into the potential economic impact that the negative extern alities of OHV recreation could have on a region. A region that allows some form of OHV riding, may experi ence a reduction in visits from other potential recreation forms that seek an e xperience void of urban stimuli that OHV machine noise would eliminate, such as bikers, hikers, birdwatchers, and hunters. The resulting loss of these visitors, along with the expenditure they would have brought, would function as a negative externality. A comprehension of the negativ e economic impacts would provide further information to policy makers towards the goal of a more efficient and socially acceptable allocation of resources devoted to OHV recreation.

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59 APPENDIX A MAP OF THE WITHLACO OCHEE STATE FOREST

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60 APPENDIX B VERBAL CONSENT SCRIPT

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61 APPENDIX C ON-SITE SURVEY

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62 APPENDIX D MAIL-BACK SURVEY

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71 APPENDIX E MATHMATICAL DISCRIPTION OF INPUT-OUTPUT MODEL To aid the reader in understanding I-O analys is, a basic description of a three-sector I-O model follows, as put forth by Leontief (1986) and Miller & Blair (1985), to illustrate how one derives the indirect and induced impact s from the initial direct impact. Figure 1 is a generali zed accounting table that I-O models utilize. An assumption that is key in I-O models is that total outputs from a sector equals total inputs. The columns within the table represent inputs that industries require to produce a given level output. Reading down the columns gives the level of inputs that each sector r eceives from others. Industry sector S1 purchases Z11 from itself, Z21 from S2, H31 inputs from households and so on for total inputs of X1, the bottom row of table 1. Conversely, reading across the rows shows the outputs sold by a se ctor to the other sector s. Hence, sector S1 will sell Z11 to itself, Z12 sector S2, H13 outputs will be sold to households, and so on for a total output of X’1, given the assumption stated above X2 = X’2. As such: X’1 = Z11 + Z12 + Y1 where Y1 is total final demand for S2 outputs, Y1 = H13 + G14 + E15. Dividing the column entry by gross outputs will provide the trade coefficients, the amount of input from each sector needed for S2 to produce one unit of output. Duplicating this for each producing sector results in a series of eq uations that will form the coefficient matrix A, Figure 1: General accounting table Inputs Producing sector Final demand sector Outputs S1 S2 H (3) G (4) E (5) Total outputs S1 Z11 Z12 H13 G14 E15X’1 Producing Sector S2 Z21 Z22 H23 G24 E25X’2 H(3) H31 H32 T33 T34 T35X’3 G(4) G41 G42 T43 T44 T45X’4 Payments Sector I(5) I51 I52 T53 T54 T55X’5 Total inputs X1 X2 X3 X4 X5 A a11a12a21a22

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72 where: Solving for X, the vector of gross output, provides the final equation: X=(I-A)-1*Y Where (I-A)-1 in the Leontif inverse matrix and Y is the vector of final demand. Households can be treated as either exogenous or endogenous with respect to the model. When households are treated as exogenous, type I (direct and indirect) multipliers and impacts are derived. Type II (direct, indirect, and induced) multip liers and impact are obtained by extending the Leontif inverse matrix to incl ude additional spending of wage income by households. As such, type II multipliers and the associated impacts are greater due to the inclusion of this additional sector. By changing Y, one can derive economic im pacts from an I-O model. Essentially an activity or policy change can affect the final de mand from various sectors. A change in Y will result in a corresponding change in total output gr eater then the initial imp act, as the sectors that experience an increase in final de mand for their products will incr ease purchases of inputs from other sectors, hence causing the direct impact to multiply.

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73 APPENDIX F DIRECT, INDIRECT, AND INDUCED RE GIONAL ECONOMIC IMPACTS OF OHV RECREATION AT THE CMA BY INDUS TRY GROUP AND IMPACT TYPE Output Impact ($) Industry Group (NAICS) Direct Local Residents Direct NonLocal Res. Indirect Non-Local Res. Induced Non-Local Res. Total Impact Ag, Forestry, Fish & Hunting 0 0 3,188 43,469 46,656 Mining 0 0 112 1,071 1,183 Utilities 0 0 111,577 199,311 310,888 Construction 0 0 69,285 663,505 732,790 Manufacturing 0 0 74,829 182,983 257,812 Wholesale Trade 0 0 27,064 131,507 158,571 Transportation & Warehousing 0 0 142,040 131,064 273,104 Retail trade 2,719,701 8,118,798 71,093 688,289 11,597,880 Information 0 0 114,365 146,439 260,804 Finance & insurance 0 0 92,742 278,367 371,109 Real estate & rental 211,638 881,019 186,681 210,874 1,490,212 Professionalscientific & tech svcs 0 0 179,506 201,346 380,852 Management of companies 0 0 51,593 8,667 60,260 Administrative & waste services 0 0 189,905 133,465 323,370 Educational svcs 0 0 726 36,731 37,457 Health & social services 0 0 47 897,788 897,835 Artsentertainment & recreation 16,829 113,902 6,146 55,409 192,286 Accomodation & food services 70,897 383,565 41,005 331,914 827,380 Other services 194,065 577,305 83,206 330,019 1,184,595 Government & non NAICs 46,496 259,772 54,371 1,895,090 2,255,729 Total 3,259,626 10,334,361 1,499,482 6,567,306 21,660,775 *Citrus, Sumter, Hernando, and Pasco Counties

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74 Total Value Added Impact ($) Industry Group (NAICS) Direct Local Residents Direct NonLocal Res. Indirect Non-Local Res. Induced Non-Local Res. Total Impact Ag, Forestry, Fish & Hunting 0 0 1,911 22,615 24,526 Mining 0 0 73 700 774 Utilities 0 0 80,357 143,532 223,889 Construction 0 0 31,054 264,534 295,588 Manufacturing 0 0 23,252 40,604 63,856 Wholesale Trade 0 0 20,585 100,023 120,607 Transportation & Warehousing 0 0 95,983 74,595 170,578 Retail trade 2,084,005 6,151,171 53,261 515,959 8,804,396 Information 0 0 41,580 52,746 94,327 Finance & insurance 0 0 65,930 168,010 233,940 Real estate & rental 87,331 363,548 126,762 140,879 718,520 Professionalscientific & tech svcs 0 0 85,580 110,048 195,627 Management of companies 0 0 28,135 4,726 32,861 Administrative & waste services 0 0 92,959 70,095 163,054 Educational svcs 0 0 353 19,508 19,861 Health & social services 0 0 20 564,622 564,642 Artsentertainment & recreation 10,175 68,868 3,055 32,569 114,668 Accomodation & food services 50,279 272,020 21,061 155,684 499,044 Other services 93,476 278,073 32,364 162,880 566,793 Government & non NAICs 14,125 78,917 16,389 1,672,369 1,781,800 Total 2,339,392 7,212,596 820,663 4,316,699 14,689,351 *Citrus, Sumter, Hernando, and Pasco Counties

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75 Labor Income Impact ($) Industry Group (NAICS) Direct Local Residents Direct NonLocal Res. Indirect Non-Local Res. Induced Non-Local Res. Total Impact Ag, Forestry, Fish & Hunting 0 0 941 10,501 11,442 Mining 0 0 38 362 400 Utilities 0 0 24,071 43,760 67,831 Construction 0 0 27,482 228,475 255,957 Manufacturing 0 0 17,666 28,393 46,059 Wholesale Trade 0 0 11,529 56,019 67,548 Transportation & Warehousing 0 0 72,899 58,309 131,208 Retail trade 1,352,449 3,981,654 33,435 323,794 5,691,332 Information 0 0 24,764 23,249 48,013 Finance & insurance 0 0 30,178 78,546 108,724 Real estate & rental 42,660 177,589 32,771 39,339 292,360 Professionalscientific & tech svcs 0 0 72,023 94,672 166,696 Management of companies 0 0 21,619 3,632 25,250 Administrative & waste services 0 0 73,756 55,664 129,421 Educational svcs 0 0 342 19,003 19,345 Health & social services 0 0 18 491,184 491,202 Artsentertainment & recreation 5,669 38,367 2,251 20,078 66,364 Accomodation & food services 28,605 154,758 13,924 107,419 304,706 Other services 67,564 200,990 22,807 128,936 420,297 Government & non NAICs 12,209 68,214 16,059 935,822 1,032,304 Total 1,509,156 4,621,572 498,571 2,747,157 9,376,456 *Citrus, Sumter, Hernando, and Pasco Counties

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76 Indirect Business Taxes Impact ($) Industry Group (NAICS) Direct Local Residents Direct NonLocal Res. Indirect Non-Local Res. Induced Non-Local Res. Total Impact Ag, Forestry, Fish & Hunting 0 0 47 913 960 Mining 0 0 3 31 34 Utilities 0 0 11,484 20,244 31,728 Construction 0 0 425 3,170 3,594 Manufacturing 0 0 367 842 1,209 Wholesale Trade 0 0 4,453 21,637 26,090 Transportation & Warehousing 0 0 1,715 2,060 3,775 Retail trade 410,337 1,205,791 9,996 96,659 1,722,783 Information 0 0 2,841 5,603 8,444 Finance & insurance 0 0 2,221 4,736 6,957 Real estate & rental 4,325 18,003 20,370 22,069 64,767 Professionalscientific & tech svcs 0 0 1,139 2,005 3,143 Management of companies 0 0 465 78 543 Administrative & waste services 0 0 2,721 2,227 4,949 Educational svcs 0 0 7 343 350 Health & social services 0 0 0 6,076 6,076 Artsentertainment & recreation 1,249 8,452 218 3,678 13,597 Accomodation & food services 7,045 38,113 2,440 16,694 64,291 Other services 13,913 41,388 3,173 13,060 71,533 Government & non NAICs 8 47 19 104,196 104,271 Total 436,876 1,311,793 64,104 326,321 2,139,094 *Citrus, Sumter, Hernando, and Pasco Counties

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77 Employment Impact (Jobs) Industry Group (NAICS) Direct Local Residents Direct NonLocal Res. Indirect Non-Local Res. Induced Non-Local Res. Total Impact Ag, Forestry, Fish & Hunting 0.0 0.0 0.0 0.8 0.8 Mining 0.0 0.0 0.0 0.0 0.0 Utilities 0.0 0.0 0.3 0.5 0.8 Construction 0.0 0.0 0.9 7.2 8.0 Manufacturing 0.0 0.0 0.5 0.8 1.2 Wholesale Trade 0.0 0.0 0.3 1.4 1.7 Transportation & Warehousing 0.0 0.0 1.8 1.5 3.3 Retail trade 46.2 134.6 1.4 13.6 195.7 Information 0.0 0.0 0.7 0.6 1.3 Finance & insurance 0.0 0.0 0.7 2.0 2.7 Real estate & rental 1.8 7.4 1.5 1.8 12.5 Professionalscientific & tech svcs 0.0 0.0 2.2 2.7 4.9 Management of companies 0.0 0.0 0.4 0.1 0.5 Administrative & waste services 0.0 0.0 3.2 2.3 5.4 Educational svcs 0.0 0.0 0.0 0.9 0.9 Health & social services 0.0 0.0 0.0 12.4 12.4 Artsentertainment & recreation 0.3 2.2 0.1 1.2 3.8 Accomodation & food services 1.3 7.2 0.9 7.5 17.0 Other services 3.0 9.1 1.2 7.5 20.8 Government & non NAICs 0.3 1.4 0.3 22.2 24.2 Total 52.9 161.9 16.4 86.9 318.0 *Citrus, Sumter, Hernando, and Pasco Counties

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78 LIST OF REFERENCES ATV Task Force. (2003). ATV Solutions: Recommendations of Gov. John Baldaccis ATV Task Force. http://atvmaine.net/atvtfrecommendations.pdf Accessed 10/10/2005. Balkan, E., and Kahn, J. R. (1988). The value of changes in deer hunting quality: a travel cost approach. Applied Economics 20 533-539. Bowker, J. M., English, B. K., and Donovan, J. A. (1996). Toward a value for guided rafting on southern rivers. Journal of Agricultural and Applied Economics 28 423-432. Briassoulis, H. (1991). Methodological issues: tour ism input-output analysis. Annals of Tourism Research, 18 (3) 485-495. Brown, P. J. (1984). Benefits of outdoor re creation and some ideas for valuing recreation opportunities. In Valuation of Wildland Resource Benefits (G. L. Peterson and A. Randall, eds), pp209-220. Boulder, CO: Westview Press. Brown, P. J. and Haas, G. E. (1980). Wild erness recreation experience: the Rawah case. Journal of Leisure Research 12(3) 229-241. Buchanan, T. (1985). Commitment and leis ure behavior: A theoretical perspective. Leisure Sciences 7 401-420. Che, D. (2003). The new economy and the fore st: rural development in the post-industrial spaces of the rural Alleghenies. Social Science Quarterly, 84 (4) 964-978. Collins, R., and Hodge, I. (1984). Cluste ring visitors for recreation management. Journal of Environmental Management 19(1) 147-158. Cordell, H. K., Bergstrom, J. C., & Wa tson, A. E. (1992). Economic growth and interdependence effects of state park visitation in lo cal and state economies. Journal of Leisure Research, 24 (3) 253-268. Cordell, H. K., Betz, C. J., Green, G., & Owens, M. (2005). Off-highway vehicle recreation in the United States, Regions and States (A national report from the national survey on recreation and the environment). Southern Rese arch Station: United States Department of Agriculture. Coupal, R. H., Bastian, C., May, J., and Taylor D. T. (2001). The economic benefits of snowmobiling to Wyoming residents: a travel cost approach with market segmentation. Journal of Leisure Research 33 492-510. Dillman, D. A. (2000). Mail and Internet Survey: The Tailored Design Method (2nd ed.). New York: John Wiley and Sons.

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79 Dobbs, I. M. (1993). Individual travel cost method: estimation and benefit assessment with a discrete and possible gro uped dependent variable. American Journal of Agricultural Economics 71(1) 84-94. Donnelly, M. P., Vaske, J. J., DeRuiter, D. S., & Loomis, J. B. (1998). Economic impacts of state parks: effect of park visitation, park facilities, and county economic diversification Journal of Park and Recreation Administration, 16 (4) 57-72. Dorrance, M.J. (1975). Effects of snowmobiles on white-tailed deer Journal of Wildlife Management, 39 (3) 563-569. Driver, B. L. (1985). Specifying what is produced by management of wildlife by public agencies. Leisure Sciences 7 281-296. Driver, B. L. and Tocher, S. R. (1970). Towa rds a behavioral interpretation of recreational engagements with implications for planning. In Elements of Outdoor Recreation Planning (B. L. Driver, ed), pp. 303-331. Ann Arbor, MI : University Microfil ms International. Fedler, A. J. and Dittion, R. B. (1994). Understanding angler motivations in fisheries management. Fisheries 19 6-13. Fix, P. and Loomis, J. B. (1997). The economic benefits of mountain biking at one of its meccas: An application of the travel cost method to mountain biking in Moab, Utah. Journal of Leisure Research 29 343-352. Fletcher, J. E. (1989). Input-outpu t analysis and tourism impact studies Annals of Tourism Research, 16 (3) 514-529. Florida Department of Agriculture and Consum er Services, Division of Forestry. (2002) OffHighway Vehicle Safety & Recreation Act Report. Graefe, A. R. and Fedller, A. J. (1986). Situ ational and subjective dete rminants of satisfaction in marine recreational angling. Leisure Sciences 8 275-295. Haas, G. E., Driver, B. L., and Brown, P. J. (1981) Measuring wilderness recreation experiences. In Proceedings of the Wilderness Psychology Group Annual Conference (L. Cannon, ed), pp. 25-30. Durham, NH: Departme nt of Psychology, University of New Hampshire. Hair, J. F. Anderson, R. E., Tatham R. L., and Black, W. C. (1998). Multivariate Data Analysis with Readings. New York: Maxwell Macmillan International. Harrison, R. T. (1974). Off-road Vehicle Noise Effect s on Operators and Bystanders (National Combined Farm, Construction & Industrial Machinery and Powerp lant Meetings). Milwaukee, WI: Society of Automotive Engineers.

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80 Hautaluoma, J. and Brown, P. J. (1978). Attrib utes of the deer hunti ng experience: a cluster analytic study. Journal of Leisure Research 10(4) 271-287. Hazen and Sawyer. (2001). Economic Contribution of Off-Hi ghway Vehicle Use in Colorado Denver: Colorado Off-Highway Vehicle Coalition. Hesseln, H., Loomis, J. B., and Gonzlez-Cabn, A. (2004). The effects of fire on recreation demand in Montana. Western Journal of Applied Forestry 19(1) 47-53. Huppert, D. D. (1983). NMFS Guidelines on Economic Valu ation of Marine Recreational Fishing Technical Memorandum NMFS-WSFC-32. Silver Springs, MD: US Department of Commerce, NOAA. Kariel, H. G. (1990). Factors affecting respons e to noise in outdoor recr eational environments. The Canadian Geographer, 34 (2) 142-149. Kay, J. (1981). Evaluating environmental impacts of off -road vehicles Journal of Geography, 80 (1) 10-18. Lawler, E. E. (1994). Motivation in Work Organizations San Francisco, CA: Jossey-Bass. Leontief, W. (1986). Input-Output Economics (2nd Ed.). New York: Oxford University Press. Lindberg, K., Enriquez, J., & Sproule, K. (1996) Ecotourism questioned: case studies from Belize Journal of Tourism Research, 23 (3) 543-562. Lockwood, M., and Tracy, K. (1995). Nonmarke t economic valuation of an urban recreation park. Journal of Leisure Research 27 155-167. Loomis, D. K. and Ditton, R. B. (1978). Anal ysis of motive and participation differences between saltwater sport and tournament fishermen. North American Journal of Fisheries Management 7 482-487. Lorr, M. (1983). Cluster Analysis for Social Scientists San Francisco, CA: Jossey-Bass. Maine Sunday Telegram (2002). Saturday’s Ricky Craven r un to benefit five charities http://www.travisroyfoundation.org/images/ articles-releases/MESunTel-Craven01-2002.htm Accessed 10/25/2005. Major, M. J. (1987). Managing off-road vehicles Journal of Forestry, 85 (11) 37-41. Manfredo, M. J., Driver, B. L., and Brown, P. J. (1983). A test of concepts inherent in experienced based setting manageme nt for outdoor recreation areas. Journal of Leisure Research 15(3) 263-283.

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81 McFarlane, B. L. (1996). Socialization infl uences of specialization among birdwatchers. Human Dimensions of Wildlife 2(1) 1-18. Miller, R. E., & Blair, P. D. (1985). Input-Output Analysis: F oundations and Extensions. Englewood Cliffs, NJ: Prentice-Hall, Inc. Morris, C. E., Allan, T., Rubin, J., Br onson, B. N., & Bastey, C. S. (2005). Economic Contributions of ATV-Rela ted Activity in Maine. University of Maine, Margret Chase Smith Policy Center. Oh, C., Anderson, D. K., Scott, D., and Stoll, J. R. (2005). Understanding differences in nonmarket valuation by angler specialization level. Leisure Sciences 27 263-277. Okrant, M. J., & Gross L.E. (2004). The Impact of Spending By ATV/ Trailbike Travel Parties on New Hampshire’s Economy During July 2002 to June 2003 Plymouth, NH: Institute for New Hampshire studies. Purnomo, H., Mendoza, G. A., and Prabhu, R. (2005). Analysis of local perspectives on sustainable forest management: An Indonesian case study Journal of Environmental Management 74 111-126. Sheridan, D. (1978). Dirt motorbikes and dune buggies threaten deserts. Smithsonian, 9 (5) 65-75. Shrestha, R. K., Seidl, A. F., and Moreas, A. S. (2002). Value of recr eational fishing in the brazilian pantanal: a travel cost an alysis using count data models. Ecological Economics 42 289-299. Siderelis, C., and Moore, R. (1995). Outdoor recreation net benefits of rail-trails. Journal of Leisure Research 27(4) 344-359. Smith, V. K. (1988). Selection and recreation demand. American Journal of Agricultural Economics 70 29-36. Smith, V. K., & Desvouges. (1985). The genera lized travel cost method and water quality benefits: A reconsideration. Southern Economics Journal 52 371-381. Stein, T. V., and Lee, M. E. (1995). Managi ng recreation resources for positive outcomes: An application of benefits -based management. Journal of Park and Recreation Administration 13(2) 52-70. Stein, T. V., Denny, C. B., and Pennisi, L. A. (2003). Using visitors’ motivations to provide learning opportunities at wate r-based recreation areas. Journal of Sustainable Tourism 11(5) 404-425.

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82 USDA Forest Service. (2005). Recreation Facts http://www.fs.fed.us/recreation/programs/ facts/facts_sheet.shtml Accessed 11/10/2005 Vail, D. & Heldt, T. (2004). Governing s nowmobilers in multiple-use landscapes: Swedish and Maine (USA) cases. Ecological Economics, 48 (4) 469-483. Vail, D. & Heldt, T. (2004). Governing s nowmobilers in multiple-use landscapes: Swedish and Maine (USA) cases. Ecological Economics, 48 (4) 469-483. Ward, F. A. and Beal, D. (2000). Valuing Nature with Travel Cost Models Northampton, MA: Edward Elgar Publishing, Ltd. Webb, R. H., Ragland, H. C., Godwin, W. H., & Jenkins, D. (1978). Environmental effects of soil property changes with off -road vehicle use. Environmental Management, 2 (3) 219233. Wilde, G. R., Reichers, R. K., and Ditton, R. B. (1998). Differences in attitudes, fishing motives, and demographic characteristics be tween tournament and non-tournament black bass anglers in Texas. North American Journal of Fisheries Management 18 422-431. Willis, K., and Garrod, G. (1991). An individu al travel cost method of evaluating forest recreation. Journal of Agricultural Economics 42 33-42. Zhou, D., Yanagida, J. F., Chakravorty, U., & Leung, P. (1997). Estimating economic impacts from tourism. Annals of Tourism Research, 24 (1) 76-89.

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83 BIOGRAPHICAL SKETCH Gregory Parent was born in Dover, NH on th e 24th of May 1978 and has spent the first eighteen years of his life living in Rochester, NH. Upon completion of his studies at Saint Thomas Aquinas High School in 1997, Gregory moved to Montreal Quebec to pursue his B.A. degree at McGill University. Gregory graduate d in 2001 from McGill with a double major in economics and international development. In June of 2002 Gregory entered into service as a Peace Corps voluntee r in the country of Togo. Gregory developed and manage d projects in collaboration w ith villages that focused on improving the sustainability of natural resources use. Most of these projects centered on the generation of revenue from non-timber forest pr oducts, taking the form of a comprehensive ecotourism project and agroforest ry regime promotion. During t hose two years in Togo Gregory gained a level of insight into the relationship be tween the village social organization and natural resources that he never could have gained in university st udies alone. He developed an understanding of the prime importance of represen ting the diversity of in terests and resource use issues of rural village communities in any attempted conservation plan. Upon completion of his M.S. de gree, Gregory will be entering into a PhD program at the University of Florida, through the auspice of a National Science Foundation fellowship through the Integrative Graduate Education and Resear ch Traineeship program. His proposed area of research will be in developing economic mode ls, most likely either computable general equilibrium (CGE) or econometric models, to analyze the economic structure of local communities with an emphasis on the regional economic linkages to natural resource use.