Top Gear Race : The Estimation Of Society's Choice On Transportation Mode Using Multinomial Logit Model.

Top Gear Race : The Estimation of Society’s Choice on Transpor tation Mode
using a Multinomial Logit Model
I Wayan Sukadana1
Amr it a Nugraheni Sarasw aty 2
I Gusti Ayu Putr i Anggara Indr asw ar i 3
1,2,3 Depar tment

of Development Economics, Faculty of Economics and
Business, Udayana University
Email : wayan.sukadana@gmail.com
amritasaraswaty@gmail.com

Abstract
Bali as par t of Indonesi an gr owing economy is facing an incr easi ng demand of t r anspor tati on
infr ast ructur es. In or der to r esponse high demand of tr anspor tation infr astr uctur e, and to
pr event the thr eat of tr affic congesti on, the gover nment of Bali pr ovides the soci et y with a publ ic
tr anspor t ati on and a br and new tol l r oad. These i nfr astructur es give an oppor tuni ty to society to
decide bet w een tr avel by their own car / motor cycl e or public t r anspor t. For the gover nment, it is
impor tant to set efficient tr anspor tation infr astr uct ur es to escape fr om hi gh cost economy which
appear fr om tr affic congestion. Thi s paper investi gates society’s choi ce on tr anspor tation mode
in Denpasar City. We esti mate the passenger ’s choice data using a Multi nomial Logit model, with

income and number of congestion spot as i ndependent var iables. The r esul t shows that
passenger who has hi gh value of time pr efer t o tr avel by thei r own vehicl e compar e t o publ ic
tr anspor t. The r esult i s analogue t o the Top Gear Race, w her e the car s most of the time win the
r ace agai nst the publi c tr ansport . Finally, fr om the society’s point of view, we can say t hat the
devel opment of infr astr uctur es of public tr anspor tati on, whi ch has been done by the
gover nment , st ill less attr acti ve compar e to the pr i vate tr anspor t ati on.
Key words: pr efer ence, tr anspor t ati on i nfr astr uctur e, l ost minimization, multi nomial logit.

Abstrak
Bali sebagai bagian dar i per t umbuhan ekonomi Indonesia menghadapi peni ngkat an per mint aan
infr ast ruktur tr anspor t asi. Untuk mer espon ti ngginya per mintaan infr ast r uktur tr anspor tasi, dan
untuk mencegah ancaman kemacetan l al u li ntas, pemer intah Bali menyediakan tr anspor tasi
umum dan jalan t ol bar u bagi masyar akat. Infr astr ukt ur ini member ikan kesempat an kepada
masyar akat unt uk memutuskan apakah melakukan per jalanan dengan mobil mer eka sendi r i /
sepeda motor atau angkutan umum. Bagi pemer intah, penting untuk mengatur infr astr uktur
tr anspor t asi yang efisi en untuk t er hindar dar i ekonomi bi aya ti nggi yang muncul dar i kemacet an
lalu lintas. Makalah ini mengkaji pilihan masyar akat pada moda tr anspor tasi di Kot a Denpasar .
Data pil ihan penumpang diper ki r akan menggunakan model Mul tinomial Logit, dengan
pendapat an dan juml ah lokasi kemacet an sebagai var iabel independen. Hasil penel itian
menunjukkan bahwa penumpang yang memili ki nilai waktu ti nggi lebi h memi lih untuk

beper gian dengan kendar aan sendir i dibandingkan dengan angkutan umum. Hasil i ni sesuai
analog Top Gear Race, di mana mobil -mobil pr ibadi sebagian besar waktu memenangkan
per lombaan melawan angkutan umum. Akhir nya, dar i sudut pandang masyar akat, dapat
dikatakan bahwa pembangunan infr astr uktur tr anspor t asi publ ik, yang telah dilakukan oleh
pemer intah, masih kur ang menar ik dibandingkan dengan kendar aan pr i badi.

Kata kunci : pr efer ensi, infr astr uktur t r anspor tasi, lost minimization, mult inomial logi t .

INTRODUCTION
Since the new economic order in the late 1960s, economic development has been
increasing r apidly and so has the demand for tr anspor t. A decade later , it became
obvious that tr ansportation on the w hole needed a lot of attention. Lending
agencies, as w ell as the cent r al gover nment made funds available for highw ay
and tr anspor tation pr ojects to impr ove its r ole in developing the nation. (Sutomo
et.al, 1993). It then tur ned out that the supply of public tr anspor t failed to fulfill
the market demand, so people began to collectively opt for pr ivate vehicles over
public tr anspor tation.Now , for over the last decade, the aver age number of
public tr anspor tation user s has decr eased r apidly, partly due to the over al l
gr ow th of the Indonesian economy, w hich has increased the number of middleincome earner s and the mar ket’s vehicle affor dability (Setiaw an, 2013)
On 2003, public tr anspor t user s accounted for 45 per cent of total tr ansportation

user s, and it r emained so until 2012. Fr om that point, motor cycles became mor e
ubiquitous as a r esult of their almost 60 per cent market share, as few er and
few er people took to public tr anspor tation. It is also wor th nothing that over the
same per iod, public tr anspor t only accounted for 1 per cent of total vehicles on
the r oad.
In the fast and moder n economy, demand of t r anspor t ation infr ast r uctur es ar e
getting higher and higher . Unfor tunately, this gr ow th was and still is not
concur r ently car r ied out w ith enough r esponsibility from the citizens. Vehicle
ow ner ship symbolizes pr estige and r elat es to socioeconomic status, w hile
quantity is valued over quality: the mor e vehicles one ow ns the better their
per ceived economic status. Gridlock and inconvenient public tr anspor t systems
ar e becoming a hindr ance to pr oductivity and a w inning st r ategy to incr ease
citizens’ str ess levels. The cities that wer e initially developed for human
pur poses, ar e now tr ansfor ming into a container of vehicles, gr ow ing at a 12
per cent r at e annually (Setiaw an, 2013)
Bali as par t of Indonesian gr ow ing economy is also facing an incr easing demand
of tr anspor tation infr astr uctures. In or der to response high demand of
transport ation infrastructur e, and to pr event t he thr eat of tr affic congestion, the
gover nment of Bali provides the society w ith a public transportation and a br and

new toll r oad. These infr astr uctur es give an oppor tunity to society to decide
betw een t ravel by their own car / motor cycle or public tr anspor t. For the
gover nment, it is impor tant to set efficient t r anspor t ation infr astr uctur es to
escape fr om high cost economy w hich appear fr om tr affic congestion.

Liter atur e Review
To make an adequate measur es on this ar ea of study, it is important to have an
enough understanding of tr avel behavior and modal choice. Tr avel behaviour is
complex and in the other side modal choices ar e deter mined by several factor s.
Some studies have been done for analyzing the tr anspor t ation mode choice.
Studies that explored the deter minants of the public transport demand
conducted by Paulley et al. (2006) analysed differ ent type of elasticities. They
show that far es, quality of ser vice and car ow ner ship ar e the most significant
variables w hich influence public transpor t demand. Meanw hile, Alpizar and
Car lsson (2001) studied a gr oup of policies aimed at discouraging the use of
pr ivate transportation during peak hours, both directly and indirectly, by
increasing the att r activeness of the only available substitute, the bus. This is
done using a choice exper iment constr ucted to find the answ er to the follow ing
basic question: Given fixed house-to-wor k str uctur es and no w or king hour
flexibility, by how much is the choice of tr avel mode for commuter s to work

sensitive to changes in t r avel time, changes i n costs for each mode and other
ser vice attr ibutes?. The results show that in gener al, indicate that model
substitution is sensitive to the char acter istics and per formance of each mode. In
par ticular , tr avel time for both modes and t ravel cost for car ar e the most
impor tant deter minants of mode choice. They also conclude that a pr ogr am
aimed at r educing congestion and pollution dur ing peak hour s should focus on
increasing the cost of private t r anspor t and pr oviding faster and mor e reliable
public tr anspor t.

The opposition betw een car and public tr anspor t use and ways to encour age
people to take public tr anspor t that provided by the goverment can be found in
many empirical researchs such as; Hensher (1998) and Meyer (1999)
demonstr ate that, in term of tr anspor t demand management (TDM), the best

action is to increase the pr ice of car for individual use and to r educe the over all
attr activeness of the car . Nakamura and Hayashi (2013) define thr ee st r ategies
for low -car bon ur ban tr anspor t: ‘avoid’ (i.e. r educing unnecessar y tr avel
demand), ‘shift’ (i.e. encour aging modal shift in favor of public transpor t use) and
‘impr ove’ (i.e. impr oving fuel economy and emission intensity).
The method that usually uses to estimate tr anspor tation mode choice is the logit

model (McCar thy (2001) and also Gebeyehu and Takano (2007). Depar t fr om
those studies, w e also t r y to estimate the society’s pr efer ence tow ar d the
transport ation mode. This study estimates the impact of monetary expense and
value of time on the society’s choices.

METHODOLOGY
Model of Society’s Choice
In this paper w e assume the society is facing a lost minimization pr oblem of two
alter natives to tr avel, which are their ow n car / motor cycle or the public
transport ation. Before w e ar r ive at the lost minimization pr oblem, let we
consider a simple model of society’s choice, which adapt fr om Shy (1995) w ith a
slight modification. We assume that the passengers, who tr avel fr om Denpasar to
Bukit Jimbar an Campus, have tw o possible alter natives for getting ther e; each
passenger can use either to t r avel by their ow n vehicle or choose to use the
public tr ansportation. For the passenger s w ho tr avel by their ow n vehicle, we
assume deal w ith tC tr avel time. This tr avel time depends on the tr affic
(congestion) and ther efore depends on the number of all passenger s who decide
to tr avel w ith their ow n vehicle. For mally, w e can w r ite this tr avel time as;

tC  α  βnC , w her e 0  α 1 and β  0

(1)

The parameter α measur es the time that spend by passenger , which is
independent from congestion, such as the time it takes to star t and heat a car , to
check the oil, dust, and so on. The par ameter β measur es the effect of congestion
on tr avel time, w hich depends on the quality of r oad, number of lanes, and tr affic
lights. Similar to travel time by using pr ivate vehicle, let w e consider a tP for the
travel time by using public tr anspor tation, and w e can w r ite for mally as follows;

tP  φ ϕnC , wher e 0  φ 1 and ϕ  0

(2)

The paramet er φ measur es the time that spend by passenger , which is
independent fr om congestion, such as the time it takes to get to the bus station
or stop. The par ameter ϕ measur es the effect of congestion on tr avel time, which
depends on the quality of r oad, number of lanes, and tr affic lights. The
interpr etation of par ameter ϕ almost identic w ith β , because public
transport ation has almost same r oute with private tr anspor tation.

We assume N passenger s w ill fall into nC passenger s w ho chose to tr avel with
pr ivate vehicle and nP passenger s w ho chose t o tr avel by public tr anspor tation,

so nC  nP  N . Than, w e denote v as the value of time and define the lost function
for the passenger s w ho use the private vehicle as;

LC ≡ v(α  βnC ) γ

(3)
Meanwhile the lost function for passenger s who use public tr anspor t is as
follows;

LP ≡ v(φ ϕnC )  λ
(4)
The lost-minimization functions of the tw o alter natives ar e functions of both
value of time and a monetar y expense.
We assume that ther e are a lar ge number of passenger s w ishing to go Udayana
Univer sity on Jimbar an, so each passenger ignor es their mar ginal effect on
congestion. Hence, each passenger take nC as given and minimizes;

min L ≡ min L , L
C

P

(5)

C,P

Therefor e, if in equilibr ium passenger s use both tr anspor t ation methods, then nC
must satisfy;

v(α  βnC ) γ  v(φ ϕnC )  λ
(6)
Assuming that N is sufficiency lar ge, so that not all passenger s use the same
transport ation mode, the equilibr ium allocation of passenger s betw een the two
transport ation methods is given by;

nCe 

(λ −γ )  v(φ −α)
v(β −ϕ)

(7)
The equilibr ium number of passenger s w ho use pr ivate vehicle nC increases with
the cost of public tr anspor tation (the ticket) λ and decrease with an incr ease in
toll-r oad ticket, γ . For a given value of time, v , the nC incr ease w ith time it takes
to get to the bus station or stop, intuitively we can assume the α , is ver y small.
The equation (7) also give an interesting int er pr etation, the number of pr ivate
vehicle’s driver is decr ease w ith the decr ease of the travel time using public
transport ation ϕ .

RESULT AND DISCUSSION
Sample and Sur vey Result
The samples are the students and employee of Udayana Univer sity w ho tr avel
for study or wor k in Bukit Jimbar an Campus fr om Denpasar gr eater ar ea
(Sar bagit a). We classified the mode of tr anspor tation into three categor y;
“public” for the tr ans-sarbagita, “motor ” for motorcycle, and “car ” for car . We
select the samples r andomly fr om the student and employee who have an

experience in using those thr ee t r anspor tati on modes. This setting is very
impor tant in gaining gr eater dat a sets that wil l use in Multinomial Logit Model
later on. We classified the per son w ho usually uses the public tr anspor t ation into
samples that chose public tr anspor tation and, w e coded it w ith 1 and 0 for

other s. We also applied the same method for other s mode.

To collect the data, w e have distr ibuted 100 questionnaires, but ther e are 8
retur n questionnair es that not give clear infor mation, and w e decide to dr op it.
Table 1. show the fr equencies and per centages of the mode chosen by
respondent.

Table 1. Fr equencies and Per centages of the Chosen Mode
mode

Freq.

Percent

Cum.

public
car

30
27

32.61
29.35

32.61
61.96

motor

35

38.04

100.00

Total

92

100.00

The data on Table 1, show that r espondents ar e dist r ibuted almost equally
among the alter natives. Motor cycle appear s to be the most popular mode,
compar e to car or public mode. This popular ity may because of motor cycle have
the shor test tr avel time among the alter natives as show n in Table 2.

Table 2. Mean of Tr avel Time by Mode
mode

mean(tmotor)

public
car
motor

32
29
29

mean(tcar)
48
44
44

mean(tpublic)
120
107
105

Respondent tend to choose motor cycle to tr avel w hen they face mor e congestion
spot. Table 3, show us that the average number of congestion spot that face by
respondent who choose car and public tr ansportation does not differ so much.
This figur e t ell us that people tend to indiffer ent in choosing betw een car or
public tr anspor tation when they face less congestion spot.

Table 3. Mean of Congestion Spot by Mode

mode

N(scong)

mean(scong)

sd(scong)

public
car
motor

30
27
35

2.5
2.22222
3.51429

.5085476
.4236593
.8178677

Fr om Table 4, w e can see that r espondent who has low er income choose public
mode. Meanw hile, for the highest income tend to choose car .

Table 4. Mean of Respondent by Mode in Thousand Rupiah
mode

N(income)

mean(income)

sd(income)

public
car
motor

30
27
35

1420
3814.81
1728.57

99.65458
845.6694
388.4899

Econometric Approach and Multinomial Logit Estimation
We estimate the passenger’s choice data using a Multinomial Logit model, with
income and number of congestion spot as independent variables. Fir st, we
estimate the i mpact of income on mode choice. This setting t r y to analyze
monetar y expense impact on society’s choice tow ar d the transpor tation mode.

Table 5. Multinomial Logit Estimation; Monetary Expense Impact
Multinomial logistic regression

Number of obs
LR chi2(2)
Prob > chi2

=
=
=

92
122.38
0.0000

Log likelihood = -39.354221

Pseudo R2

=

0.6086

mode

Coef.

Std. Err.

z

P>|z|

[95%

Conf. Interval]

inc

73.23428

41.03145

1.78

0.074

-7.185889

153.6545

-569.214

321.6897

-1.77

0.077

-1199.714

61.28633

9.903107
-72.32705

3.05575
22.29542

3.24
-3.24

0.001
0.001

3.913946
-116.0253

15.89227
-28.62883

Car
_cons
Motor
inc
_cons
(mode==public

is the base

outcome)

Table 5, tell us that the incr ease in income w ill induce the society to leave the
public tr anspor tation. When society’s income incr eases they w ill pr efer
motor cycle compar e to public tr anspor tation. This phenomenon is causes by the
travel time using motor cycle is shor ter compar e to public tr anspor tation. When,

their income incr eases more, and then they pr efer car compar e to motor cycle.
Although the tr avel time using motor cycle is shor ter than car, using car gives
people mor e comfor t, mor e over if the congesti on spot is less.
The income affect society’s choice of tr anspor tation mode. It is in line with
Mukala’s and Chunchu’s r esear ch (2011). They developed var ious choice models
based on the stated prefer ence dat a for modeling the inter city mode choice
behavior in India. The r esult found that the income and total tr avel cost play an
impor tant r ole in the mode choice decision for the inter city tr anspor t.
On the other hand, car availability gives people mor e comfor t compar e to
motor cycle or public tr anspor t. This r esult in line w ith Nur deen, et.al (2007).
They found car availability is ther efor e a major factor that deter mines the choice
of inter city transport mode. Resistance to sw itching w as obser ved among
respondents w ho have one vehicle available, while r espondents w ho have tw o or
mor e vehicles w er e less r esi stant to mode change.

The second estimation is dedicated to test the value of time tow ar d society’s the
number of congestion spot as the pr oxy of value of time. The estimation r esult is
as shown in Table 6.

Table 6. Estimation Result

Multinomial logistic regression
Table 6. Mult i nomi al Logit Est imat ion;

Log likelihood

=

-70.34808

mode

Coef.

Std. Err.

z

Number of obs
LR chi2(2)
Prob > chi2

=
=
=

92
60.39
0.0000

Pseudo R2

=

0.3003

P>|z|

[95%

Conf. Interval]

Car
scong

-1.215637

.5816799

-2.09

0.037

-2.355709

-.0755658

_cons

2.753292

1.380804

1.99

0.046

.0469648

5.459619

scong
_cons

3.381636
-9.798706

1.032338
3.063051

3.28
-3.20

0.001
0.001

1.358291
-15.80218

5.404982
-3.795235

Motor

(mode==public

is

the base

outcome)

Table 6, tell us that an increase in the number of congestion spot faced by society
will causes people to use motor cycle. Inter estingly, the incr ease in the number of
congestion spot makes people to sw itch fr om using car to public tr anspor tation.
This r esult suggest us that if the gover nment w ant to incr ease the number of

public tr anspor tation costumer, the gover nment have to decr ease the time tr avel
of this public tr anspor tation so can compete w ith motor cycle. It is in line with
other r esear ch that conducted by Alpizar and Car lsson (2001) for r educing tr avel
time.

CONCLUSION
The Multinomial logit estimation shows that passenger w ho has high value of
time prefer to chose tr avel by their own vehicle, w hich is their motor cycle,
compar e to car or public tr ansport. The r eason is, because it mor e pr acticable
and no w aiting time. The result is analogue to the Top Gear Race, w her e the car s
or motor cycle most of the time w in the r ace against the public transpor t. Finally,
from the society’s point of view, w e can say that the development of
infr ast r uctur es of public tr anspor tation, w hich has been done by the
gover nment, still less att r active compar e to the pr ivate tr anspor tation. How ever,
the government still has an oppor tunity to w in the hear t of society by incr easing
the number of bus to r educe the w aiting time. Although it is hard to compet e
with the motor cycle tr avel time and simplicity, the public transportation still
may w in in comfor t aspect.

RECOMMENDATION
The possibility of separ ating public transpor t by cr eating a parallel ser vice that
pr ovides a faster service and mor e comfor t vehicle, is one potential alter native to
detr act society’s fr om pr ivate tr ansportation. It is alr eady conduct with
Sarbagit a’s Pr ogr amme but it still need mor e effort to satisfy the society’s. Our
study sheds light on the featur es r equir ed by that system if it is to attr act
traveler s fr om private modes. Specifically, special emphasis has to be put on
redesigning r outes and exclusive bus lanes, and pr oviding tr affic pr ior ity for
buses, faster connections betw een routes, and mor e fr equent and r eliable
depar tur es, among other measur es intended t o r educe t r avel time with public
transport.

REFERENCES

Alpizar, F., and Carlsson, F. 2001. Policy Implications and Analysis of the
Deter minants of Tr avel Mode Choice: An Application of Choice Exper iment s
to Met r opolitan Costa Rica. Wor king Paper s in Economics no. 56.
Depar t ment of Economics, Götebor g Univer sity. Sweden.

Gebeyehu,M and Takano, S. 2007. Diagnostic Evaluation of Public Tr ansportation
Mode Choice in Addis Ababa. Journal of Public Transpor t at ion, Vol. 10, No. 4,
2007.pp 27-50
Hensher , D.A. 1998. The imbalance between car and public transport use in
ur ban Australia: w hy does it exist?. Transpor t Policy, 5, pp. 193-204
McCarthy. P. S. 2001. Tr anspor tat ion Economics, Theory and Pract ice; A Case
St udy Appr oach. Massachusett s: Blackw ellpublisher s Inc.
Meyer, M.D. 1999. Demand management as an element of t r anspor tation policy:
using car r ots and stickts to influence t r avel behavior. Tr anspor t ation
Resear ch Par t A, 33, pp. 575-599
Mukala, P. K. and M. Chunchu. 2011. Mode choice modelling for inter city
tr anspor t ation in India: A case of Guwahati to five met r o cities.
Int er nat i onal Jour nal of Ear t h Sciences and Engineeri ng, vol. 04, no. 06 SPL,
pp. 364-374
Nakamur a, K. and Hayashi, Y. 2013. Str ategies and instr uments for low-car bon
ur ban tr anspor t: an inter nation r eview on tr ends and effect s. Transpor t
Policy, 29, pp. 264-274
Nur deen. A., R. A. O. Rahmat, and A. Ismail. 2007. Modeling of t ransportation
behavior for coer cive measur es for car driving in Kuala Lumpur . ARPN
Jour nal of Engineer ing and Applied Sciences, Vol. 2, no.2, pp.18-24
Paulley, N., Balcombe, R., Mackett, R., Tither idge, H., Pr eston, J., War dman, M.,
Shir es, J., White, P. 2006, The demand for public tr anspor t: the effects of
far es, quality of ser vice, income and car ow ner ship. Transpor t Policy, 13, pp.
295-306
Setiaw an, R. 2013. Fixing Indonesia’s Public Transport Woes. Comment ar y
Ar t icle on The Jakar t a Globe. Nov. 4 th. 2013. Retr ieved July 27 2014 fr om
http:/ / w w w .thejakartaglobe.com/ opinion/ commentary/ fixing-indonesiaspublic-tr anspor t-woes/
Shy, Oz. 1995. Indust r ial Or ganizat ion Theory and Applicat ions. Cambr idge: MIT
Pr ess.
Sutomo, H., Dikun, S., Tumew u, W., 1993. Tr anspor t Problems, Policies and
Cur r ent Resear ch and Education in Indonesia : An Over view . IATSS
Resear ch. Vol. 17 No. 1.pp 43-51