micro-simulation modelling of domestic tourism in sweden
DESCRIPTION
Micro-Simulation Modelling of Domestic Tourism in Sweden. KIRUNA. Anders Lundgren Dep. Geography, Umeå University. SVERIGE. S ystem for V isualizing E conomic and R egional I nfluences G overning the E nvironment - PowerPoint PPT PresentationTRANSCRIPT
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Micro-Simulation Modelling of Micro-Simulation Modelling of Domestic Tourism Domestic Tourism in in SwedenSweden
Anders Lundgren
Dep. Geography, Umeå University
KIRUNA
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SVERIGE
System for Visualizing Economic and Regional
Influences Governing the Environment
SVERIGE is a MicrosimulationMicrosimulation model based on microdata on the Swedish population
Socioeconomic data for ALL individuals
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Current ModulesFertility Education
Cohabitation and marriage
Employment and earnings
Mortality Immigration
Divorce Emigration
Leaving home
Migration
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What is microsimulation?• Micro = individual level• Microsimulation model - Simulation
model that describes the behaviour of individual micro units and permits analysis of the impacts of the environment
• Laboratory ”world” for testing policies• SVERIGE is dynamic dynamic and and spatialspatial
- What happens if we increase immigration?
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Experiment
Base case – 60 000 immigrants
80 000 immigrants
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”National” Tourism module
• How many trips are done?
• What do they do?
• Where do people go?
• Exchange of tourists between LA- regions
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Swedish Tourist Database
• Managed by Åre marknadsfakta
• 14 years
• 24 000 interviews every year
• Using 10 years
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Number of cases
• Randomly collected
• Densely populated areas are well represented
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Different categories of tourism
Domestic travel with at least one night away from home done at
leisure time
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Limitations in data
To few observations to perform regressions analyses IF
you look at municipalities and each activity in TDB
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LA-regions
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Activity/purpose in TDB
•Meeting friends and relatives•Visit second home•Piece and quiet/relaxation (Experience)•Pleasure and entertainment (Experience)•Community with others (Experience)•Skiing (Participate/be active in)•Sun&swimming (Participate/be active in)•Events (away 00-01)•Outdoor life (Participate/be active in)•Sports (Participate/be active in)•Course & meeting as leisure assignment•Cultural activity (Participate/be active in)•Cultural environment (Experience)•Rush and speed (Experience)•Seclusion (Experience)•Prophylaxis, health care (Participate/be active in)
•Natural environment (Experience)•Fishing (Participate/be active in)•Other activity (Participate/be active in)•Private matters/look for job (Experience)•See the country (Experience)•Buy things•Attraction (Visit, watch, listen to)•Stimulation (Experience)•Education/studies (Participate/be active in)•Urban environment (Experience)•Parks (Visit, watch, listen to)•Hunting (Participate/be active in)•Golf (Participate/be active in)•Adventure and excitement (Experience)•School trip (Experience)
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Activity Freq. Valid Percent
5 Fishing 1056 1,1
1 Visit friends and relatives 43380 43,9 Hunting 323 0,3
Great Events 1875 1,9 Total Fish/Hunt 1379 1,4
Shopping 898 0,9
Private matters/look for job 778 0,8 6 Outdoor life 1993 2,0
Community with others 2586 2,6
Course and meeting – as leisure assignment 1493 1,5
7 Natural environment 1307 1,3
Visit attraction 776 0,8 Cultural environment 277 0,3
Visit parks 593 0,6 Adventure/excitement 188 0,2
Education/studies 467 0,5 Stimulation 616 0,6
Big City Environment 441 0,4 Total nature/culture 1772 2,4
Health service 236 0,2
See the country 875 0,9 8 Pleasure/Entertainment 5989 6,1
Cultural activity 411 0,4 Get some action 307 0,3
Total Social bonds activities (SBA) 54809 55.,5
School trip 253 0,3
Total Pleasure/entertainment 6549 6,7
2 Visit second home 13608 13,8
Piece and quiet 7381 7,5 9 Sports 2433 2,5
Total Visit second home (VSH) 21214 21,3 Golf 168 0,2
Total Sports/Golf 2601 2,7
3 Sun & bath 2613 2,6
10 Others 1523 1,5
4 Skiing 2762 2,8 Otheractivity 1097 1,1
Total Others 2620 2,6
Aggregated activities
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A model for number of trips
The two key factors that make tourism possible is access to
money and leisure time Age group– divided into 5 groups
Income – household income
Gender
Education – university degree or not
If the individual has children at home or not
If the individual is single or not
Size of place of residence
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A model for choice of activities
Age, gender, income and lifecycle are key factors that affect activity choice
Age group– divided into 5 groups
Income – household income
Gender
Education – university degree or not
If the individual has children at home or not
If the individual is single or not
Main residential region
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Regression analysis
Poisson regression for the number of trips – most people make 1 trip per
month - 98% within 5 trips.
Multinomial logit regression for the choice between 10 activities
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Choice of destination • Interaction model used for
destination choice
• Compare calculated and observed number of trips from TDB
• Interaction model estimated by using iteration and minimising misplaced flows
bij
ckj
bij
ckjki
kij DA
DAPM
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Results
• Distance is important for the activities VSH and sun/bath – people prefer to do that close to home.
• Skiers and people who visits friends and relatives are less concerned about distance.
Number of trips
SBA VSH Sun bath Ski
Hunt fish
Out door
Nature env
Pleasure/Entertain
Sport golf Other Total
Sample 721 196 28 36 12 16 24 124 29 58 1 243 Sweden 23 358 6 364 920 1 151 373 519 762 4 005 940 1 895 40 288
X 1000
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Tourism Flows
Misplaced flows
SBA VSH SUN&BATH SKI Percentage misplaced flows
18,81 31,91 34,46 26,71
Number of cases in TDB 37 100 10 124 1 818 2 067
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Percentageof trips - VFR
0 - 11 - 2.52.5 - 44 - 99 - 18
Percentageof trips - VFR
0 - 11 - 2.52.5 - 44 - 99 - 18
ObservedCalculated
SBA SBA
Social Bond Activity
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Visit Second Home
Percentageof trips - VSH
0 - 0.50.5 - 11 - 22 - 33 - 8
Percentageof trips - VSH
0 - 0.50.5 - 11 - 22 - 33 - 8
ObservedCalculated
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Sun and Bath
Percentageof trips - sun&bath
0 - 0.50.5 - 1.51.5 - 44 - 1211 - 25
Percentageof trips - sun&bath
0 - 0.50.5 - 1.51.5 - 44 - 1212 - 25
ObservedCalculated
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Skiing
Percentageof trips - ski
0 - 0.50.5 - 1.51.5 - 2.52.5 - 1515 - 55
Percentageof trips - ski
0 - 0.50.5 - 1.51.5 - 2.54 - 915 - 55
ObservedCalculated
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Problems
• Multinomial logit regression for destination choice failed
• ”Empty” LA-regions – no observations
• ”Holes” in the data – system missing
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Data needs• More observations for individuals in
sparsely populated areas• Purpose NOT mixed with activity• ”Clean” the array of variables with
respect to desired information• What about immigrants?• Improve ”visit second home” and
”social bond” activities by using SCB-data
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Future experiments
• Change in demand by running ”SVERIGE”– 50 years forward– divorce, labour market, migration
• Change supply – move central point of attraction
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Summary
• We model the flow of tourists between LA-regions
• TDB explain choice of activities
• An interaction model calculates the choice of place
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END
Questions?