2nd Annual Pileus Project2nd Annual Pileus Project

General Stakeholder General Stakeholder Advisory Group MeetingAdvisory Group Meeting

March 9, 2004 – 4:00-6:00 PMMarch 9, 2004 – 4:00-6:00 PM

WELCOME! & Introductions WELCOME! & Introductions – Lori Martin– Lori Martin

News & Comments from the News & Comments from the EPA – Jeanne BisanzEPA – Jeanne Bisanz

Review of the Agriculture & Review of the Agriculture & Climate Team’s Progress Climate Team’s Progress

To Date – Dr. Julie WinklerTo Date – Dr. Julie Winkler

Pileus Project Tourism TeamPileus Project Tourism Team

Dr. Don HolecekDr. Don Holecek

Lori A. MartinLori A. Martin

Charles ShihCharles ShihJeonghee NohJeonghee Noh

Dr. Sarah NichollsDr. Sarah Nicholls

Coordination, Coordination, communications and communications and marketing; develop and marketing; develop and maintain stakeholder maintain stakeholder relations; report relations; report production.production.

PI and leads Tourism PI and leads Tourism Team; identify and Team; identify and communicates with key communicates with key stakeholders; oversees stakeholders; oversees advisory groups; web advisory groups; web site tools and all site tools and all aspects of the Tourism aspects of the Tourism Team.Team.

Literature review; Literature review; lead development of lead development of camping model; camping model; stakeholder stakeholder relations.relations.

Data management Data management and demand analysis; and demand analysis; development of the development of the tourism/economic tourism/economic model.model.

To develop tools that tourism and To develop tools that tourism and outdoor recreation businesses in outdoor recreation businesses in Michigan can use to incorporate Michigan can use to incorporate

climate variability and changeclimate variability and change into into their planning activitiestheir planning activities

Primary ObjectivePrimary Objective

Rationale for Current StudyRationale for Current Study

There is a need for studies that …There is a need for studies that …

• Are more location (site) specificAre more location (site) specific• Focus on the shorter termFocus on the shorter term• Focus on the bottom-line Focus on the bottom-line

• Assessment revealed that data needs to be in more useable form for stakeholders to use – short term time frame

• Tourism businesses operate with relatively narrow profit margins

• Weather dependent

• Profitability is often very reliant on seasonality

Why Research Tourism?Why Research Tourism?

Tourism & Outdoor Recreation in Tourism & Outdoor Recreation in MichiganMichigan

• Are vital to Michigan’s economy & societyAre vital to Michigan’s economy & society• Are extremely weather-dependent Are extremely weather-dependent • Are very sensitive to climate variability & Are very sensitive to climate variability &

changechange• Yet, are also subject to a multitude of Yet, are also subject to a multitude of

other influencesother influences

Other Influences on TourismOther Influences on Tourism • Leisure timeLeisure time• DemographicsDemographics• Socioeconomics Socioeconomics • Economic factors Economic factors

– Consumer confidence, interest rates, gas pricesConsumer confidence, interest rates, gas prices– Prices: entrance fees, equipment, etc.Prices: entrance fees, equipment, etc.

• Competition (from local to international)Competition (from local to international)• Technological innovationsTechnological innovations

Literature ReviewLiterature Review

General Stakeholder General Stakeholder Advisory GroupAdvisory Group

Technical Stakeholder Technical Stakeholder Advisory GroupsAdvisory Groups

Database(s) DevelopmentDatabase(s) Development

Overview of Research StrategyOverview of Research Strategy

Conceptual Model(s), Data Conceptual Model(s), Data Needs, Identify CooperatorsNeeds, Identify Cooperators

Empirical Model(s), Add Empirical Model(s), Add CooperatorsCooperators

Identify Sources of Identify Sources of Relevant Secondary Data, Relevant Secondary Data,

Access & “Refine” Available Access & “Refine” Available DataData

Develop “Pilot Empirical Develop “Pilot Empirical Model(s)Model(s)

Collect Primary DataCollect Primary Data

Develop “Refined” Develop “Refined” Empirical Model(s)Empirical Model(s)

““Field Test” “Refined” Field Test” “Refined” Empirical Model(s)Empirical Model(s)

Assess Exploratory Power of Assess Exploratory Power of Conceptual Variables, Identify Conceptual Variables, Identify

Probable Missing VariablesProbable Missing Variables

Mitigate Missing Mitigate Missing Variable(s) ProblemVariable(s) Problem

Critical Review By Critical Review By StakeholdersStakeholders

Operational Model(s) for Operational Model(s) for Stakeholder ApplicationStakeholder Application

EvaluateEvaluate

Literature ReviewLiterature Review

• The likely impacts of climate variability & The likely impacts of climate variability & change on outdoor recreation & tourism change on outdoor recreation & tourism have been “seriously understudied” have been “seriously understudied” (Morehouse, 2001)(Morehouse, 2001)

• Studies to date have …Studies to date have …– Been scattered (in area & activity)Been scattered (in area & activity)– Been broad (in areas & time frames)Been broad (in areas & time frames)– Been conducted mostly by physical Been conducted mostly by physical

geographers & climatologistsgeographers & climatologists– Paid little attention to economic issuesPaid little attention to economic issues

Key Research Groups & ContactsKey Research Groups & Contacts

• Climatic Research Unit, University of Climatic Research Unit, University of East Anglia, UK East Anglia, UK (Viner, Agnew)(Viner, Agnew)

• Adaptation & Impacts Research Group Adaptation & Impacts Research Group of Environment Canada/Faculty of of Environment Canada/Faculty of Environmental Studies, University of Environmental Studies, University of Waterloo, Canada Waterloo, Canada (Scott, Wall, (Scott, Wall, McBoyle, Mills) McBoyle, Mills)

Stakeholder Involvement & Stakeholder Involvement & Introduction of ProjectIntroduction of Project

• 1st General Stakeholder Advisory Group 1st General Stakeholder Advisory Group Meeting, March 2003Meeting, March 2003

• Michigan Tourism Outlook Conference, Michigan Tourism Outlook Conference, March 2003 - March 2003 - Presentation, AndresenPresentation, Andresen

• Midwest Ski Area Association Conference, Midwest Ski Area Association Conference, August 2003 - August 2003 - Attended, MartinAttended, Martin

• TTRA CenStates Conference, Sept 2003 - TTRA CenStates Conference, Sept 2003 - Presentation, MartinPresentation, Martin

• Tourism Industry Coalition of Michigan, Tourism Industry Coalition of Michigan, October & December 2003 -October & December 2003 - Presentations, Presentations, Martin, Holecek & AndresenMartin, Holecek & Andresen

• Michigan Association of Convention & Michigan Association of Convention & Visitor Bureaus, December 2003 -Visitor Bureaus, December 2003 - Presentation, Martin & HolecekPresentation, Martin & Holecek

• 2nd General Tourism Stakeholder Advisory 2nd General Tourism Stakeholder Advisory Group Meeting, March 2004Group Meeting, March 2004

Related ActivitiesRelated Activities

• First International Conference on Climate First International Conference on Climate Change & Tourism, April 2003 -Change & Tourism, April 2003 - Attended, Attended, conference report in Annals of Tourism Research, conference report in Annals of Tourism Research, NichollsNicholls

• European Science Foundation Exploratory European Science Foundation Exploratory Workshop on Climate Change, Environment Workshop on Climate Change, Environment

& Tourism, June 2003 -& Tourism, June 2003 - Attended, NichollsAttended, Nicholls

Outreach to DateOutreach to Date

• East Lakes-West Lakes Meeting of East Lakes-West Lakes Meeting of Association of American Geographers, Association of American Geographers, October 2003 - October 2003 - Presentation, Nicholls & ShihPresentation, Nicholls & Shih

• NATO Advanced Research Workshop, NATO Advanced Research Workshop, NATO Science Series - NATO Science Series - Chapter, NichollsChapter, Nicholls

• Preparation of articles for, e.g., Preparation of articles for, e.g., Journal of Journal of Leisure ResearchLeisure Research

Future OutreachFuture Outreach

• Annual Meeting of AAG, March 2004 - Annual Meeting of AAG, March 2004 - Presentation, NichollsPresentation, Nicholls

• Second International Workshop on Climate, Second International Workshop on Climate, Tourism & Recreation, June 2004 -Tourism & Recreation, June 2004 - Presentation, NichollsPresentation, Nicholls

• Annual Michigan Tourism Conference, Annual Michigan Tourism Conference, October 2004 - October 2004 - Presentation and/or exhibit, Presentation and/or exhibit, Holecek & MartinHolecek & Martin

• ““Comprehensive” – based on traffic Comprehensive” – based on traffic countscounts

• Downhill Skiing & SnowboardingDownhill Skiing & Snowboarding

• Camping Camping

Three Tourism & Outdoor Three Tourism & Outdoor Recreation ModelsRecreation Models

# 1# 1Comprehensive ModelComprehensive Model

Conceptual Comprehensive Conceptual Comprehensive ModelModel

Traffic = fTraffic = f (weather conditions, (weather conditions, economy, season, day of week, economy, season, day of week, population, etc.)population, etc.)

Traffic Trends 1991-2000 Traffic Trends 1991-2000 (US 127 Clare)(US 127 Clare)

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

year

1 2 3 4 5 6 7 8 9 10 11 12

Month

2000

4000

6000

8000

Traffic

Traffic Trends 1991-2000 Traffic Trends 1991-2000 (US 127 Clare)(US 127 Clare)

YEAR

200019991997199619951994199319921991

Average July Traffic

10000

9000

8000

7000

6000

Comprehensive Tourism ModelComprehensive Tourism Model

Regarding Regarding Traffic CountsTraffic Counts• Traffic: Daily traffic volume of Station #4129 between 1991Traffic: Daily traffic volume of Station #4129 between 1991 & 2000, provided by MDOT & 2000, provided by MDOT• Counts are bi-directional (Northbound & Southbound)Counts are bi-directional (Northbound & Southbound)• New set of traffic counts were generated to New set of traffic counts were generated to better represent the flow of touristsbetter represent the flow of tourists Monday–Thursday Traffic = (NB+SB)/2Monday–Thursday Traffic = (NB+SB)/2 SaturdaySaturday Friday Traffic = NBFriday Traffic = NB Sunday Traffic = SB Sunday Traffic = SB

41294129

Lake CityLake City

Comprehensive Tourism ModelComprehensive Tourism ModelVariable Definition and Data SourcesVariable Definition and Data Sources

• Daily high Daily high temperaturestemperatures and and precipitationprecipitation: Daily observations : Daily observations from the Lake City weather station provided by the Climate from the Lake City weather station provided by the Climate TeamTeam

• CCICCI: Consumer Confidence Index for the East North Central : Consumer Confidence Index for the East North Central Region (MI, OH, WI, IN, IL) (Conference Board)Region (MI, OH, WI, IN, IL) (Conference Board)

• Seasons: Seasons: SpringSpring (March, April, May), (March, April, May), SummerSummer (June, July, (June, July, August), August), FallFall (September, October, November), and (September, October, November), and WinterWinter (December, January, February)(December, January, February)

• Days of the week: Days of the week: Friday and SundayFriday and Sunday, , SaturdaySaturday and and WeekdaysWeekdays (Monday through Thursday) (Monday through Thursday)

• HolidayHoliday: New Year’s Day, Memorial Day, Independence Day, : New Year’s Day, Memorial Day, Independence Day, Labor Day, Thanksgiving, and ChristmasLabor Day, Thanksgiving, and Christmas

Comprehensive Tourism Model:Comprehensive Tourism Model:Regression AnalysisRegression Analysis

*Dependent variable is the logarithm of traffic volume*Dependent variable is the logarithm of traffic volume*Overall R-Square=0.820*Overall R-Square=0.820*Winter dummy variable & gas prices were not significant &*Winter dummy variable & gas prices were not significant & dropped from the modeldropped from the model

Unstandardized Coefficients Standardized Coefficients Sig. Collinearity StatisticsVariables B Std. Error Beta Tolerance VIF

(Constant) -74.621 7.70 0.00Temperature 0.013 0.00 0.296 0.00 0.51 1.98Precipitation -0.003 0.00 -0.029 0.00 0.99 1.01CCI -0.001 0.00 -0.045 0.05 0.12 8.41Summer 0.397 0.01 0.327 0.00 0.46 2.17Fall 0.204 0.01 0.166 0.00 0.78 1.29Fri_Sun 0.821 0.01 0.709 0.00 0.93 1.07Sat 0.319 0.01 0.214 0.00 0.93 1.07Holiday 0.602 0.03 0.135 0.00 0.99 1.01Year 0.041 0.00 0.239 0.00 0.12 8.38

Comprehensive Tourism Model:Comprehensive Tourism Model:Regression AnalysisRegression Analysis

Residuals Plot

Dependent Variable: Traffic

Regression Standardized Predicted Value

3210-1-2

Regression Standardized Residual

6

4

2

0

-2

-4

-6

Durbin-Watson Stat = 1.192Durbin-Watson Stat = 1.192

Comprehensive Model – Forecasting ExampleComprehensive Model – Forecasting Example

• # of Vehicles = # of Vehicles = Constant+B1*Temp+B2*Precip+B3*CCI+B4*Constant+B1*Temp+B2*Precip+B3*CCI+B4*Summer+B5*Fall+B6*FriSun+B7*Sat+B8*HolidaySummer+B5*Fall+B6*FriSun+B7*Sat+B8*Holiday+B9*Year +B9*Year

• Scenario: Friday of July, 2005 (non-holiday)Scenario: Friday of July, 2005 (non-holiday)

• Temperature: Average (mean), warmer (1 std Temperature: Average (mean), warmer (1 std deviation above mean), cooler (1 std deviation deviation above mean), cooler (1 std deviation below mean)below mean)

• # of Vehicles: Average – 13,552# of Vehicles: Average – 13,552

Warmer – 14,296Warmer – 14,296

Cooler – 12,845Cooler – 12,845

1,5001,500

# 2# 2Downhill Skiing & Downhill Skiing &

Snowboarding ModelSnowboarding Model

Crystal Mountain ResortCrystal Mountain Resort®® & & Weather StationsWeather Stations

Crystal Mountain ResortCrystal Mountain Resort®®

GreenvilleGreenville

Lake CityLake City

PontiacPontiac

Weather StationWeather Station

Downhill Skiing & Snowboarding ModelDownhill Skiing & Snowboarding ModelVariable Definition & Data Sources• Skier: number of daily tickets sold at Crystal Mountain Ski

Resort between 1996 & 2002• Weather: daily minimum temperatures & daily snow depth

for the “Lake City” station provided by the Climate Team Snow depths of two other stations: Greenville & Pontiac also included

• Regional CCI• Weekend: Friday, Saturday, Sunday• Holiday: Christmas break through New Year’s day,

excluding weekends• Peakseason: December, January, & February

Downhill Skiing & Snowboarding ModelDownhill Skiing & Snowboarding Model

Regression Analysis of Crystal Mt. Skiers (1996-2002)Regression Analysis of Crystal Mt. Skiers (1996-2002)

*R-square = 0.543*R-square = 0.543*Gas prices & snow fall were dropped due to insignificance*Gas prices & snow fall were dropped due to insignificance*Durbin-Watson Stat = 1.318*Durbin-Watson Stat = 1.318

Unstandardized Coefficients Standardized Coefficients Sig. Collinearity StatisticsB Std. Error Beta Tolerance VIF

(Constant) -103752.32 26390.50 0.00Temperature -8.86 3.01 -0.09 0.00 0.79 1.27Snowdepth 0.82 0.22 0.13 0.00 0.60 1.66CCI 3.21 1.19 0.10 0.01 0.52 1.94GVsnowdepth -0.03 0.22 0.00 0.90 0.47 2.12POsnowdepth 0.27 0.16 0.06 0.09 0.60 1.66Holiday 1287.09 73.36 0.47 0.00 0.93 1.08Weekend 635.12 35.98 0.46 0.00 1.00 1.00Peakseason 323.05 42.78 0.21 0.00 0.84 1.19Year 51.61 13.15 0.14 0.00 0.53 1.88

Skiing Model – ForecastingSkiing Model – Forecasting Example Example

• # of Skiers = # of Skiers = Constant+B1*Temp+B2*Snowdepth+B3*CCI+B4*Constant+B1*Temp+B2*Snowdepth+B3*CCI+B4*PontiacSnowdepth+B5*Weekend+B6*PeakseasonPontiacSnowdepth+B5*Weekend+B6*Peakseason+B8*Holiday+B9*Year +B8*Holiday+B9*Year

• Scenario: Saturday of February, 2005Scenario: Saturday of February, 2005

• Snow depth: Average (mean), more snow (1 std Snow depth: Average (mean), more snow (1 std deviation above mean), less snow (1 std deviation deviation above mean), less snow (1 std deviation below mean)below mean)

• # of Skiers: Average – 1,301# of Skiers: Average – 1,301

More Snow – 1,402More Snow – 1,402

Less Snow – 1,201Less Snow – 1,201

200200

# 3# 3Camping ModelCamping Model

Camping ModelCamping Model

Camping = f (weather conditions (rain, Camping = f (weather conditions (rain, excess heat, humidity), bugs, economy, excess heat, humidity), bugs, economy, season, day of week, population, etc.)season, day of week, population, etc.)

Work Plan for Years 2 & 3Work Plan for Years 2 & 3

Year 2Year 2• Refine & extend the Comprehensive & Downhill Refine & extend the Comprehensive & Downhill

Skiing & Snowboarding ModelsSkiing & Snowboarding Models• Develop preliminary campground modelDevelop preliminary campground model• Define user-friendly interface for decision support Define user-friendly interface for decision support

toolstools

Year 3Year 3• Refine Campground ModelRefine Campground Model• Outreach with decision support tools for all modelsOutreach with decision support tools for all models