the first international transport forum, may 28 - 30 2008, leipzig inducing transport mode choice...

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


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


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


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.


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


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


Table 2. Price Elasticity of Demand for Fuel Consumption


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)


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)


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


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


9 .3 8 .0~10.4

Pr ivate Car 31.4 75% Public Transport


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


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


Thank you.

the first international transport forum, may 28 - 30 2008, leipzig inducing transport mode choice...

Documents

international transport

service elasticity

arc elasticity

policy measures

urban transportation

social costs

effective policies

new policies