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INDUCING TRANSPORT MODE CHOICE BEHAVIORIAL CHANGES IN KOREA: A Quantitative Analysis of Hypothetical TDM Measures. Ma y 28 , 200 8 Sungwon Lee , Ph.D. Director, Center for Sustainable Transportation The Korea Transport Institute. Outline. Introduction - PowerPoint PPT Presentation
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The First International Transport Forum, May 28 - 30 2008, Leipzig
INDUCING TRANSPORT MODE CHOICE BEHAVIORIAL CHANGES IN KOREA:
A Quantitative Analysis of Hypothetical TDM Measures
May 28, 2008May 28, 2008
Sungwon Lee, Ph.D.Sungwon Lee, Ph.D.
Director, Center for Sustainable TransportationDirector, Center for Sustainable TransportationThe Korea Transport InstituteThe Korea Transport Institute
The First International Transport Forum, May 28 - 30 2008, Leipzig
Outline IntroductionIntroduction Literature Review and Comparison with Other Literature Review and Comparison with Other
ResearchResearch SP Survey and Estimation ResultsSP Survey and Estimation Results Price Elasticities of Demand for Urban Price Elasticities of Demand for Urban
Transportation and Policy EffectsTransportation and Policy Effects Time Elasticities, Response to Service Variable, Time Elasticities, Response to Service Variable,
and Policy Effectsand Policy Effects Public Transit User Subsidy and the Policy Public Transit User Subsidy and the Policy
EffectivenessEffectiveness ConclusionConclusion
The First International Transport Forum, May 28 - 30 2008, Leipzig
1. Introduction
Increasing social costs due to transportationIncreasing social costs due to transportation Traffic congestion cost has reached to US $ 24 Traffic congestion cost has reached to US $ 24
billion per annum in Koreabillion per annum in Korea Numerous other social costs such as urban air Numerous other social costs such as urban air
pollution, noise pollution and traffic accidentspollution, noise pollution and traffic accidents Needs for controlling vehicle useNeeds for controlling vehicle use Needs for having precise estimates of transport Needs for having precise estimates of transport
users’ behavioral responses to policy measuresusers’ behavioral responses to policy measures
The First International Transport Forum, May 28 - 30 2008, Leipzig
PurposePurpose find effective policies to reduce travel of passenger cars find effective policies to reduce travel of passenger cars
and to encourage use of public transportand to encourage use of public transport TDM policiesTDM policies Estimate price and service elasticity with survey data in Estimate price and service elasticity with survey data in
Seoul, Korea.Seoul, Korea. Use SP(stated preference) and sample enumeration Use SP(stated preference) and sample enumeration
methodologymethodology SP is based on hypothetical situationSP is based on hypothetical situation Good for implementing new policies and obtaining arc Good for implementing new policies and obtaining arc
elasticity.elasticity.
The First International Transport Forum, May 28 - 30 2008, Leipzig
2. Literature Review and Comparison with Other Research
Fuel price elasticity of demand for car useFuel price elasticity of demand for car use -0.33 ~ -0.39 in UK DOT(1994)-0.33 ~ -0.39 in UK DOT(1994) -0.16 ~ -0.84 in Goodwin(1992)-0.16 ~ -0.84 in Goodwin(1992) Price elasticity of fuel consumptionPrice elasticity of fuel consumption -0.092 ~ -0.54 in Korea(1998)-0.092 ~ -0.54 in Korea(1998) -0.27 ~ -0.73 in UK DOT(1994)-0.27 ~ -0.73 in UK DOT(1994) -0.18 ~ -0.84 in Goodwin(1992)-0.18 ~ -0.84 in Goodwin(1992) Fare elasticity of demand for public transportFare elasticity of demand for public transport -0.20 ~ -1.10 in UK DOT(1994)-0.20 ~ -1.10 in UK DOT(1994) Mostly inelastic to pricesMostly inelastic to prices
The First International Transport Forum, May 28 - 30 2008, Leipzig
Table 1. Elasticities of Demand for Urban Transportation
DemandDemand AttributesAttributesElasticitiesElasticities
Short runShort run Long runLong run OverallOverall
Fuel consumptionFuel consumption Fuel priceFuel price -0.27-0.27 -0.73-0.73 -0.48-0.48
Car useCar use Fuel priceFuel price -0.33-0.33 -0.30-0.30 -0.39-0.39
Car ownershipCar ownership Fuel priceFuel price ** ** -0.21-0.21
Car ownershipCar ownership Car priceCar price ** ** -0.87-0.87
TrafficTraffic Toll feeToll fee ** ** -0.45-0.45
Demand for busDemand for bus Bus fareBus fare -0.30-0.30 -0.65-0.65 -0.41-0.41
Demand for Demand for subwaysubway
Subway fareSubway fare -0.20-0.20 -0.40-0.40 -0.20-0.20
Demand for railDemand for railRailway Railway
farefare-0.70-0.70 -1.10-1.10 -0.65-0.65
Mass transitMass transit Fuel priceFuel price ** ** +0.34+0.34
Car ownershipCar ownership Transit fareTransit fare ** ** +0.10+0.10Note: Short run means usually within a year, and long run means 5 to 10 years.Source: UK Department of Transport
The First International Transport Forum, May 28 - 30 2008, Leipzig
Table 2. Price Elasticity of Demand for Fuel Consumption
Short runShort run Long runLong run OverallOverall
Time-seriesTime-series -0.27-0.27 -0.71-0.71 -0.53-0.53
Cross-sectionCross-section -0.28-0.28 -0.84-0.84 -0.18-0.18
Source: Goodwin (1992)
Short runShort run Long runLong run OverallOverall
Time-seriesTime-series -0.16-0.16 -0.33-0.33 -0.46-0.46
Cross-sectionCross-section ** -0.84-0.84 -0.18-0.18
Table 3. Fuel Price Elasticity of Demand for Car UseTable 3. Fuel Price Elasticity of Demand for Car Use
Source: Goodwin (1992)
The First International Transport Forum, May 28 - 30 2008, Leipzig
3. SP Survey and Estimation Results
If variables are too numerous and too widely variedIf variables are too numerous and too widely varied
impossible to create all the possible sets of SP impossible to create all the possible sets of SP questionnairesquestionnaires
Use fractional factorial plan which analyzes only main Use fractional factorial plan which analyzes only main effects and guarantee the orthogonality of variables effects and guarantee the orthogonality of variables following Kocur et al.(1982) and Hensher(1994)following Kocur et al.(1982) and Hensher(1994)
SP design of mode choice between passenger cars and SP design of mode choice between passenger cars and alternative modes of bus and subway (Table 4)alternative modes of bus and subway (Table 4)
Explanatory variablesExplanatory variables
travel expense, travel time, and service levelstravel expense, travel time, and service levels
The First International Transport Forum, May 28 - 30 2008, Leipzig
Table 4. SP Design of Mode Choice between the Alternative Modes
ModesModesExplanatoryExplanatory
variablesvariables# of# of
LevelsLevels
LevelsLevels
Level 1Level 1 Level 2Level 2 Level 3Level 3
Basic modeBasic mode(private(private
automobile)automobile)
Fuel priceFuel price (per litter)(per litter)
33Current levelCurrent level(1,200 won)(1,200 won)
Increase toIncrease to 1,500 won1,500 won
Increase to Increase to 1,800 won1,800 won
In-vehicle timeIn-vehicle time 33 Current levelCurrent level 20% higher20% higher 40% higher40% higher
MonthlyMonthly parking feeparking fee
33Current levelCurrent level(150,000 won)(150,000 won)
40,000 won40,000 won higherhigher
80,000 won 80,000 won higherhigher
AlternativeAlternative modemode
(bus and(bus and subway)subway)
farefare 33 400 won lower400 won lower 200 won lower200 won lowerCurrent levelCurrent level
(500~1,000won)(500~1,000won)
In-vehicle timeIn-vehicle time 33 40% lower40% lower 20% lower20% lower Current levelCurrent level
Out-vehicle Out-vehicle timetime
33 50% lower50% lower 25% lower25% lower Current levelCurrent level
CongestionCongestion(comfortable)(comfortable)
33 No congestionNo congestionMedium Medium
congestioncongestionHigh congestionHigh congestion
Note: US $ 1.00 is equivalent to 1,200 Korean Won as of Jan 1, 2003
The First International Transport Forum, May 28 - 30 2008, Leipzig
where where altmode = bus, subway, bus + subwayaltmode = bus, subway, bus + subway
Surveyed on 662 car users Surveyed on 662 car users binary choice with multiple binary choice with multiple levels of attributes levels of attributes 4,228 effective data sets 4,228 effective data sets
Main purpose of using passenger cars (Table 5)Main purpose of using passenger cars (Table 5) Commuting (71.5%)Commuting (71.5%) Business trips (16.4%)Business trips (16.4%)
ParkIvtFuelUoricar 531
CrowdOvtIvtFareU 6432 altmode
Utility functions
The First International Transport Forum, May 28 - 30 2008, Leipzig
Table 5. Trip Purpose of Passenger Car Users
commutingcommuting businessbusiness shoppingshopping leisureleisureAttendingAttending
schoolschoolothersothers totaltotal
# of# ofPeoplePeople
445445 102102 1313 2424 2222 1616 622622
ShareShare(%)(%)
71.571.5 16.416.4 2.12.1 3.93.9 3.53.5 2.62.6 100.0100.0
Estimation results (Table 6)
Coefficients of travel expense and travel time
negative value
The First International Transport Forum, May 28 - 30 2008, Leipzig
Although most variables were statistically significant, Although most variables were statistically significant, fare of mass transit was statistically insignificantfare of mass transit was statistically insignificant
car users do not consider fare level as significant car users do not consider fare level as significant since fare is significantly smaller than user expense of a since fare is significantly smaller than user expense of a carcar
Positive car dummy Positive car dummy prefer car to mass transit prefer car to mass transit Demand elasticity of fuel price is much higher than that Demand elasticity of fuel price is much higher than that
of fare level, as fuel expense is far more significant than of fare level, as fuel expense is far more significant than farefare
Car users respond to bus fare changes more than subway Car users respond to bus fare changes more than subway fare changesfare changes
The First International Transport Forum, May 28 - 30 2008, Leipzig
Bigger coefficient of out-vehicle time than that of in-Bigger coefficient of out-vehicle time than that of in-vehicle time vehicle time bigger disutility of waiting than riding bigger disutility of waiting than riding
Bus users are more sensitive to in-vehicle time than Bus users are more sensitive to in-vehicle time than other modes other modes recommend express bus or HOV lanes recommend express bus or HOV lanes
Estimated coefficient of parking fees is more than two Estimated coefficient of parking fees is more than two times bigger than that of fuel pricestimes bigger than that of fuel prices
perceived cost of parking is much greater than perceived cost of parking is much greater than fueling and car users are very sensitive to parking feesfueling and car users are very sensitive to parking fees
Positive and bigger coefficient of Crowdedness of bus Positive and bigger coefficient of Crowdedness of bus than that of subway than that of subway very sensitive to crowded bus very sensitive to crowded bus
The First International Transport Forum, May 28 - 30 2008, Leipzig
Table 6. Estimation Results of Mode Choice Behavior of Car Users
VariablesVariablescar car bus bus car car bus + subway bus + subway car car subway subway
coefficientcoefficient t-valuet-value coefficientcoefficient t-valuet-value coefficientcoefficient t-valuet-value
Car dummyCar dummy 1.63621.6362 5.5055.505 0.997520.99752 5.2075.207 0.506050.50605 2.292.29
Fuel priceFuel price -1.01E-04-1.01E-04 -3.067-3.067 -1.17E-04-1.17E-04 -5.241-5.241 -6.10E-05-6.10E-05 -2.848-2.848
Fare of bus or Fare of bus or subwaysubway
-2.00E-04-2.00E-04 -1.456-1.456 -1.41E-04-1.41E-04 -2.862-2.862 -5.40E-05-5.40E-05 -0.637-0.637
In-vehicle timeIn-vehicle time -4.21E-02-4.21E-02 -8.106-8.106 -2.76E-02-2.76E-02 -9.376-9.376 -3.80E-02-3.80E-02
--10.10.717177
Out-vehicle timeOut-vehicle time -4.41E-02-4.41E-02 -3.486-3.486 -2.81E-02-2.81E-02 -5.053-5.053 -6.49E-02-6.49E-02 -7.089-7.089
Parking feeParking fee -3.63E-04-3.63E-04 -6.36-6.36 -2.49E-04-2.49E-04 -6.188-6.188 -2.61E-04-2.61E-04 -6.018-6.018
CrowdednessCrowdedness 0.830810.83081 8.388.38 0.644310.64431 9.3069.306 0.580230.58023 7.5087.508
2 2 (Rho square)(Rho square) 0.190.19 0.200.20 0.220.22
No. of responsesNo. of responses 943943 1,7831,783 1,5021,502
The First International Transport Forum, May 28 - 30 2008, Leipzig
4. Price Elasticities of Demand for Urban
Transportation and Policy Effects
Estimate price elasticities through Sample Enumeration Estimate price elasticities through Sample Enumeration methodmethod
obtain arc elasticity rather than point elasticityobtain arc elasticity rather than point elasticity Fuel price elasticity of demand for passenger car useFuel price elasticity of demand for passenger car use -0.078~-0.171(inelastic)-0.078~-0.171(inelastic) With 50% increase in fuel price, modal change from car to With 50% increase in fuel price, modal change from car to
bus or subway is expected at minimum 3.9% to maximum bus or subway is expected at minimum 3.9% to maximum 8.5%8.5%
Dual users of bus and subway show higher price elasticity Dual users of bus and subway show higher price elasticity than single users than single users more sensitive to fuel price as they are more sensitive to fuel price as they are relatively longer-distance commutersrelatively longer-distance commuters
The First International Transport Forum, May 28 - 30 2008, Leipzig
Table 7. Fuel Price Elasticities of Demand for Car Use and Change of Modal Share
Fuel Price ElasticitiesFuel Price Elasticities Modal change from carModal change from car
to transit modes (%)to transit modes (%)
Car-busCar-bus
10% price increase10% price increase -0.086-0.086 0.860.86
20% ”20% ” -0.086-0.086 1.721.72
30% ”30% ” -0.086-0.086 2.592.59
40% ”40% ” -0.086-0.086 3.453.45
50% ”50% ” -0.086-0.086 4.324.32
Car-subwayCar-subway
10% ”10% ” -0.078-0.078 0.780.78
20% ”20% ” -0.078-0.078 1.551.55
30% ”30% ” -0.078-0.078 2.332.33
40% ”40% ” -0.078-0.078 3.113.11
50% ”50% ” -0.078-0.078 3.883.88
Car-Car-bus+subwbus+subw
ayay
10% ”10% ” -0.171-0.171 1.711.71
20% ”20% ” -0.171-0.171 3.413.41
30% ”30% ” -0.171-0.171 5.115.11
40% ”40% ” -0.171-0.171 6.796.79
50% ”50% ” -0.169-0.169 8.478.47
The First International Transport Forum, May 28 - 30 2008, Leipzig
Estimate cross price elasticity of demand for passenger Estimate cross price elasticity of demand for passenger car use through sample enumeration techniquecar use through sample enumeration technique
0.016~0.087 (inelastic) in Table 80.016~0.087 (inelastic) in Table 8 Modal change from car to mass transit with 50% fare Modal change from car to mass transit with 50% fare
decrease decrease 4.35% at most 4.35% at most
policy of subsidizing transit fare is not expected to policy of subsidizing transit fare is not expected to reduce car usereduce car use
The First International Transport Forum, May 28 - 30 2008, Leipzig
Table 8. Fare Elasticities of Demand for Car Use and Change of Modal Share
Fare (cross price) Fare (cross price) elasticityelasticity
Modal change from car to Modal change from car to transit modes (%)transit modes (%)
Car-busCar-bus
10% fare decrease10% fare decrease 0.0580.058 0.580.58
20% ”20% ” 0.0580.058 1.161.16
30% ”30% ” 0.0580.058 1.751.75
40% ”40% ” 0.0580.058 2.332.33
50% ”50% ” 0.0580.058 2.922.92
Car-subwayCar-subway
10% ”10% ” 0.0160.016 0.160.16
20% ”20% ” 0.0160.016 0.330.33
30% ”30% ” 0.0160.016 0.490.49
40% ”40% ” 0.0160.016 0.660.66
50% ”50% ” 0.0160.016 0.820.82
Car-Car-bus+subwbus+subw
ayay
10% ”10% ” 0.0860.086 0.860.86
20% ”20% ” 0.0860.086 1.731.73
30% ”30% ” 0.0870.087 2.602.60
40% ”40% ” 0.0870.087 3.473.47
50% ”50% ” 0.0870.087 4.354.35
The First International Transport Forum, May 28 - 30 2008, Leipzig
Test whether “car users consciously perceive parking Test whether “car users consciously perceive parking costs more than fuel costs (Button, 1993)”costs more than fuel costs (Button, 1993)”
whether the estimates of the coefficients of fuel price whether the estimates of the coefficients of fuel price and parking fees are the sameand parking fees are the same
Asymptotic t-testAsymptotic t-test Reject at 5% significance levelReject at 5% significance level
ji
ji
ˆˆvar
ˆˆ
The First International Transport Forum, May 28 - 30 2008, Leipzig
Table 9. Results of Asymptotic t Test for Indifference between Variables
ModesModesAsymptotic t Test Asymptotic t Test
StatisticStatisticResultsResults
Car-busCar-bus 4.084.08 Reject nullReject null
Car-subwayCar-subway 4.224.22 Reject nullReject null
Car-bus+subwayCar-bus+subway 2.952.95 Reject nullReject null
The First International Transport Forum, May 28 - 30 2008, Leipzig
Increase of monthly parking fee by US $33.00Increase of monthly parking fee by US $33.00
decrease car use by 13~15%decrease car use by 13~15% Increase of monthly parking fee by US $66.00Increase of monthly parking fee by US $66.00
decrease car use by 25~30%decrease car use by 25~30% Each current individual level of parking fee is not Each current individual level of parking fee is not
the same the same cross price elasticity of parking fee cross price elasticity of parking fee cannot be estimatedcannot be estimated
The First International Transport Forum, May 28 - 30 2008, Leipzig
Table 10. Change of Modal Share due to Increasing Parking Fee
Modal change due to the Modal change due to the change of parking feechange of parking fee
ModalModal Change (%)Change (%)
+40,000+40,000 wonwon per per
MonthMonth
Car-busCar-busCarCar 0.660 0.660 0.562 0.562 -15-15
BusBus 0.340 0.340 0.438 0.438 2929
Car-subwayCar-subwayCarCar 0.576 0.576 0.502 0.502 -13-13
SubwaySubway 0.424 0.424 0.498 0.498 1818
Car-Car-bus+subwaybus+subway
CarCar 0.567 0.567 0.495 0.495 -13-13
Bus+subwayBus+subway 0.433 0.433 0.505 0.505 1717
+80,000 +80,000 wonwon perper
monthmonth
Car-busCar-busCarCar 0.660 0.660 0.460 0.460 -30-30
BusBus 0.340 0.340 0.540 0.540 5959
Car-subwayCar-subwayCarCar 0.576 0.576 0.428 0.428 -26-26
SubwaySubway 0.424 0.424 0.572 0.572 3535
Car-Car-bus+subwaybus+subway
CarCar 0.567 0.567 0.423 0.423 -25-25
Bus+subwayBus+subway 0.433 0.433 0.577 0.577 3333
The First International Transport Forum, May 28 - 30 2008, Leipzig
5. Time Elasticities, Response to Service Variable, and Policy Effects
Estimate cross elasticity of in-vehicle time of transit for Estimate cross elasticity of in-vehicle time of transit for demand for car use using sample enumeration techniquedemand for car use using sample enumeration technique
Decrease in-vehicle time of transit by 10~50%Decrease in-vehicle time of transit by 10~50%
cross elasticity 0.46 ~0.57 (Table 11)cross elasticity 0.46 ~0.57 (Table 11) Speed of subway improves two foldsSpeed of subway improves two folds
29% of car users transfer to subway29% of car users transfer to subway Introducing either express subway transit system or Introducing either express subway transit system or
express bus will be an effective policy in reducing car express bus will be an effective policy in reducing car use and traffic congestion in Seouluse and traffic congestion in Seoul
The First International Transport Forum, May 28 - 30 2008, Leipzig
Table 11. In-vehicle Time Elasticities of Demand for Car Use and Modal Share
In-vehicle (cross)In-vehicle (cross) time elasticity time elasticity
Modal change from car to Modal change from car to transit modes (%)transit modes (%)
Car-busCar-bus
10% decrease10% decrease 0.4590.459 4.594.59
20% ”20% ” 0.4710.471 9.429.42
30% ”30% ” 0.4810.481 14.4314.43
40% ”40% ” 0.4890.489 19.5719.57
50% ”50% ” 0.4950.495 24.7724.77
Car-subwayCar-subway
10% ”10% ” 0.5490.549 5.495.49
20% ”20% ” 0.5590.559 11.1811.18
30% ”30% ” 0.5670.567 17.0117.01
40% ”40% ” 0.5720.572 22.8922.89
50% ”50% ” 0.5750.575 28.7328.73
Car – bus + Car – bus + subwaysubway
10% ”10% ” 0.5120.512 5.125.12
20% ”20% ” 0.5170.517 10.3510.35
30% ”30% ” 0.5200.520 15.6115.61
40% ”40% ” 0.5210.521 20.8420.84
50% ”50% ” 0.5200.520 25.9925.99
The First International Transport Forum, May 28 - 30 2008, Leipzig
Estimate cross elasticity of out-vehicle time of transit Estimate cross elasticity of out-vehicle time of transit for demand of car use with sample enumeration for demand of car use with sample enumeration technique technique smaller than that of in-vehicle time smaller than that of in-vehicle time
Decrease out-vehicle time of transit by 10~50%Decrease out-vehicle time of transit by 10~50%
cross elasticity 0.19 ~0.38cross elasticity 0.19 ~0.38
modal change up to 19%modal change up to 19% Policy of increasing frequency of bus and subwayPolicy of increasing frequency of bus and subway
very effective for promoting use of transit modes very effective for promoting use of transit modes and reducing traffic congestion in Koreaand reducing traffic congestion in Korea
The First International Transport Forum, May 28 - 30 2008, Leipzig
Table 12. Out-vehicle Time Elasticities of Demand for Car Use and Modal Share
Out-vehicle (cross) Out-vehicle (cross) time elasticitytime elasticity
Modal change from Modal change from car to transit modes (%)car to transit modes (%)
Car-busCar-bus
10% decrease10% decrease 0.1970.197 1.971.97
20% ”20% ” 0.2000.200 3.993.99
30% ”30% ” 0.2020.202 6.056.05
40% ”40% ” 0.2040.204 8.158.15
50% ”50% ” 0.2060.206 10.2810.28
Car-Car-subwaysubway
10% ”10% ” 0.3640.364 3.643.64
20% ”20% ” 0.3690.369 7.387.38
30% ”30% ” 0.3730.373 11.2011.20
40% ”40% ” 0.3770.377 15.0815.08
50% ”50% ” 0.3800.380 18.9918.99
Car – busCar – bus + subway+ subway
10% ”10% ” 0.2080.208 2.082.08
20% ”20% ” 0.2100.210 4.194.19
30% ”30% ” 0.2110.211 6.336.33
40% ”40% ” 0.2120.212 8.488.48
50% ”50% ” 0.2130.213 10.6510.65
The First International Transport Forum, May 28 - 30 2008, Leipzig
Level of service in transit modes is defined as the Level of service in transit modes is defined as the level of crowdedness in this studylevel of crowdedness in this study
Decrease congestion of transit modes by one stepDecrease congestion of transit modes by one step
18~25% of car users transfer to alternative modes18~25% of car users transfer to alternative modes
improving in-vehicle congestion is very important improving in-vehicle congestion is very important for promoting the use of transit modes and reducing for promoting the use of transit modes and reducing traffic congestion in Seoultraffic congestion in Seoul
The First International Transport Forum, May 28 - 30 2008, Leipzig
Table 13. Car Users’ Response to Service Variable of In-vehicle Congestion
Change of modal shareChange of modal share
Car-busCar-busImproving one stepImproving one step 25.05 % from car to bus25.05 % from car to bus
Worsening one stepWorsening one step 21.92 % from bus to car21.92 % from bus to car
Car-subwayCar-subwayImproving one stepImproving one step 17.85 % from car to subway17.85 % from car to subway
Worsening one stepWorsening one step 17.47 % from subway to car17.47 % from subway to car
Car – busCar – bus + subway+ subway
Improving one stepImproving one step 20.71 % from car to bus + subway20.71 % from car to bus + subway
Worsening one stepWorsening one step 20.46 % from bus + subway to car20.46 % from bus + subway to car
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If 100% public transit user subsidy is If 100% public transit user subsidy is implemented, 18% of current private implemented, 18% of current private vehicle user will switch over to public vehicle user will switch over to public transporttransport
If this policy is supplemented by commuter If this policy is supplemented by commuter parking fee increase ($ 100/month), the parking fee increase ($ 100/month), the modal share change is estimated at 28%.modal share change is estimated at 28%.
6. Public Transit User Subsidy and the Policy Effectiveness
The First International Transport Forum, May 28 - 30 2008, Leipzig
Policy Scenarios Commuting Mode Modal Share Conversion Rate to Public Transport
90% Confidence Interval
Private Car 39.6 Baseline
Public Transport 60.4 N.A N.A
Private Car 36.8 25% Public Transport
Subsidy Public Transport 63.2
4 .7 3 .1~6.2
Pr ivate Car 34.0 50% Public Transport
Subsidy Public Transport 66.0
9 .3 8 .0~10.4
Pr ivate Car 31.4 75% Public Transport
Subsidy Public Transport 68.6
13.6 12.4~14.8
Pr ivate Car 29.0 100% Public
Transport Subsidy Public Transport 71.0
17.7 16.1~19.2
Table 14. Car Users’ Response to Public Transit User Subsidy
The First International Transport Forum, May 28 - 30 2008, Leipzig
7. Conclusion Could analyze the effects of hypothetical TDM Could analyze the effects of hypothetical TDM
policies in terms of modal changes utilizing policies in terms of modal changes utilizing elasticity estimateselasticity estimates
Ineffective policy measuresIneffective policy measures Small effect of fuel price policySmall effect of fuel price policy Fare related policy (Excluding user subsidy)Fare related policy (Excluding user subsidy) Effective policy measuresEffective policy measures Parking regulation or pricing policyParking regulation or pricing policy Express bus, express urban trains, and HOV lanesExpress bus, express urban trains, and HOV lanes Reducing crowdedness in bus and subway through Reducing crowdedness in bus and subway through
increasing frequencyincreasing frequency Public transit user subsidyPublic transit user subsidy
The First International Transport Forum, May 28 - 30 2008, Leipzig
Thank you.