Factors affecting Passengers’ Decisions to Use the Metropolitan Rapid
Transit Chalong Ratchadham Line (Purple Line)
Krongthong Heebkhoksung
Bansomdejchaopraya Rajabhat University

Abstract
The objectives of this research were to study factors affecting passengers’ decisions to use the Metropolitan
Rapid Transit Chalong Ratchadham Line (Purple Line) and to study whether passengers decided to use MRT
Chalong Ratchadham Line. The setting of this study was area around MRT Chalong Ratchadham Line (Purple
Line). Data were collected in March 2017. The aim of this research was to study predictor factors and
passengers’ behaviors influencing the possibility of using Purple Line MRT. Mathematical models could be
developed to predict the decision to use Purple Line MRT. The predictive results were used to plan transport
management. Logistic Regression Analysis was used to determine the relationship. The results of studying the
relationship showed that predictor factors influencing the possibility of using Purple Line MRT included
available routes, fast, safe, and convenient transport as well as other factors. By comparing Purple Line MRT
usage, the passengers’ decision to use this line was more than their decision not to use the service.
Keywords: Metropolitan Rapid Transit Chalong Ratchadham Line, Purple Line
1. Introduction
The policy of decentralizing the prosperity to local administration areas has been formulated by the
government meanwhile number of population in the metropolitan area is still increasing. The price of typical
residences in Bangkok is expensive. Most people are unable to find a residence in the city and are forced to
live in the metropolitan area. However, most employment sources are still located in Bangkok and are
increasing. The greater number of people living in outer areas needs for staying in Bangkok, resulting in traffic
jam. Metropolitan Rapid Transit system is important to facilitate the public transport without the usage of
private car. Presently, MRT structure is constructed in Bangkok and Metropolitan Area. The Metropolitan
Rapid Transit Chalong Ratchadham Line (Purple Line) contains total distance of 23 km. and 16 stations. The
behaviors of using Purple Line MRT service were studied in this research to analyze basic data and decision
criteria to decide to use the Purple Line MRT towards the development of a Binary Choice Model to predict
the probability of passengers to use the Purple Line MRT.
2. Objectives
1.To study the demographic characteristics affecting the decision to use Purple Line MRT service.

2.To study behaviors of Purple Line passengers affecting possibility of using Purple Line MRT service.
3. To develop a mathematical model for predicting the selection of using Purple Line MRT service when
factors and behaviors affecting passengers’ decision to use Purple Line MRT service.
3. Methodology

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Data analysis in this research could be divided into 4 parts as follows:
Analysis of demographic data
Analysis of factors affecting the usage of Purple Line MRT
Analysis of behaviors of Purple Line MRT passengers
Analysis of data for hypothesis testing and summary.
- Hypothesis 1: The samples with different demographic characteristics emphasize on factors affecting the
decision to use Purple Line MRT.
- Hypothesis 2: Demographic characteristics of Purple Line MRT passengers affect the decision to use or
not use Purple Line MRT.
- Hypothesis 3: Factors affecting the decision to use or not use Purple Line MRT.
- Hypothesis 4: Behaviors of the Purple Line MRT passengers affect the decision to use or not use Purple
Line MRT.
4. Logistic Regression Analysis
Logistic regression analysis or Logit Analysis is the analysis of the predictive equation to study the effect
of a predictor variable on a dichotomous variable or polytomous variable. Logistic Function represents the
relationship between predictor variable and probability of the occurrence of events according to the criterion
variable (Sirichai Kanchanawasee. 2005: 39). In conclusion, there are three concepts of regression analysis in
case that dependent variables are dichotomous variables (Sriridej Sucheewa: 1996: p. 17).


Conditional mean of regression equation shall be converted to be from 0 to 1, which is suitable for
logistic regression analysis.




The distribution of errors must be binomial, which will be the basic statistical distribution for
further analysis.

 Other principles of linear regression analysis can be applied to logistic regression.
Goodness of fit must be validated by the researcher.


If Chi-square is significant, it means that an independent variable or a set of independent variables
is related to the dependent variable.



If -2 Log Likelihood is close to 0, it means that the model has higher goodness-of-fit than other
models (if its value is 0, it is the perfect model.)
The significance of each independent variable in the model was validated with Wald statistic ( t-statistics
were used in Linear Regression). The model’s ability to forecast is considered by % of Classification. When
the goodness-of-fit was validated, the next steps are the analysis and determination of statistics from the
analysis.


The relationship between a set of independent variables and dependent variable was tested by -2
log Likelihood and Chi-square statistics.



The model’s Goodness of fit was tested with Chi-square statistics.




The significance of each independent variable in the model was validated with Wald statistic.

 The model’s predictability was tested by considering % of Classification.
Studying the passengers’ decision to use or not use Purple Line MRT is useful to prepare or manage to plan
the implementation efficiently and effectively. The variables affecting the decision to use the Purple Line MRT
are classified into 3 groups as follows:


Variables related to passengers’ personal characteristics are gender, age and occupation.



Variables related to the factors influencing the use of the Purple Line MRT including Purple Line
MRT service usage, fares, station location, marketing promotion, employee service, service process,
station facilities.

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

Variables related to the behavior of using the Purple Line MRT including weekly usage frequency,
most frequently period of time to use the service, main objective of using the service, reason to use
the service, and reason not to use the service.
Some variables described above had positive impact(this implied that data collected from the questionnaire
were then analyzed through table and Logistic Regression Analysis.
5. Results
The results of data analysis showed that the samples were males(46.76%) and females (53.24%). Most of the

samples were those aged between 21-30 years (33.5%). Most of the samples were employees (33.50%). To study
demographic factors of the samples who have used the Purple Line MRT service, 11-item questionnaire was
used. To study factors affecting the decision to use Purple Line MRT, 24-item questionnaire was used with 5rating scale. If an answer is “5” means “highest” level and “1” means “lowest” level. From evaluating factors
affecting the decision to use Purple Line MRT, data collected were then analyzed to determine the mean and
standard deviation as shown in Table 1.
Table 1: Mean and standard deviation of the samples classified with factors affecting the decision
to use Purple Line MRT service
Items

x

S.D.

3.93

0.737

4.07

0.755

3.97

0.798

3.79

0.886

3.72


0.808

3.75

0.782

easily understood.

3.83

0.916

Station location is near major landmarks such as office,
department store and educational institution.

3.585

0.918

Routes are convenient.

3.76

0.887

Number of stations is enough.

3.78


0.856

3.40

0.884

Purple Line MRT provides fast service without waiting
long time.
Purple Line MRT provides sufficient number of trains to
meet the passengers’ need.
Purple Line MRT provides more convenient transport.
Purple Line MRT provides convenient transport of BTS or
MRT linkage.
Passenger fare is reasonable and based on distance.
Passenger fares are classified by passenger’s age. Children
and students are charged cheaper than general passengers.
A list of fares is clearly displayed on ticketing machine and

Public relations are available through various media.

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Symbol


Items

x

S.D.


Discount is offered for top-up card.

3.59

0.753

Documents are distributed to educate routes.

3.44

0.978

3.73

0.965

3.69

0.911

3.63

0.968

3.97

0.813

passengers is consistent.


3.93

0.723

Queuing is formed to access to the service.

3.82

0.921

MRT provide facilities for disable people such as entranceexit,
toilet for priority, disable people, and Braille signs.

3.74

0.970

MRT station is clean and tidy.

3.74

0.870

Elevator, toilet, telephone box, ATM, and shops are available.

3.23

0.995


Both Thai and English signage are available for the passengers.

3.69

0.979

Ticket is issued easily.

3.67

0.966

MRT officers are polite and friendly.

Symbol

Number of stationed officers in each station is enough to
meet the demand.
MRT officers pay their attention to clients and make them
feel impressive.
Steps of using MRT service are not complicated and
passengers can do self-service.
MRT service is punctual. Period of waiting for the

To study the behaviors of using the Purple Line MRT service, 15-item scale was used as shown in table 2.
Table 2 : Number and percentage of the samples classified by behaviors of using Purple Line MRT service
Items

Frequency


Percentage

1 – 2 times/week

113

28.25

3 – 4 times/week

116

29

5 – 6 times/week

64

16

Over 6 times/week

107

26.75

05.30 – 09.30 hrs.

150


37.5

Items

Frequency

Percentage

184

Symbol

Symbol


09.31 – 12.30 hrs.

53

12.31 – 15.30 hrs.

56

14

15.31 – 18.30 hrs.

85

21.25


18.31 – 22.40 hrs.

56

Routes available meet the passenger’s need.

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45.75

MRT transport is convenient.

140

35

MRT transport is safe and convenient.

71

17.75

Station is not located in the area where a passenger lives.

190

47.50

Number of co-users is large.


34

8.50

143

35.75

Expense is high.

13.25

14

Table 3: Statistics of the model of Purple Line MRT passengers
Omnibus Test
Chi-Square
136.457

Sig.
0.000*

Cox&Snell
R2
0.289

Nakelkerke
R2
0.507


Hosmer and Lemeshow Test
Chi-Square
8.233

Sig.
0.411

Initial -2 Log Likelihood : 338.167
-2LL of Full Model : 201.711
* Reject the hypothesis at a significance level of 0.05.

From Table 3, the Chi-square statistics was 136.457 (sig. = 0.000). This meant that at least one factor
influenced the decision to use Purple Line MRT with -2 log likelihood value approaching zero. This implied
that constructed equation or model had good quality or consistency with data. Cox & Snell R Square value
was 0.289 which was not close to zero. This indicated the model’s consistency in terms of comparing the quality
of the model created with the worst model, a null model with no independent variable. The Nagelkerke R
Square value was 0.507. This meant that independent variables could explain 50.70% of the variation in the
service usage. When Wald Statistic of over 1 was considered and Sig. value was less than 0.05, only variables
as in Table 4 influenced predictive equation of Purple Line MRT usage.

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Table 4: Variables affecting predictive equation of Purple Line MRT service
Variables
Number

of


trains

is
Variables

enough to

meet

β

S.E.

Wald

df

Sig.

Exp (β)

0.857

0.320

7.152

1

0.007*


2.356

β

S.E.

Wald

df

Sig.

Exp (β)

the
1.892

passengers’ needs.
Convenient transport of both
BTS or MRT linkage.

Uncomplicated steps of
using the service and
self-service

0.333

2.955
2.818

Usage frequency of 1 -2
times/week
Usage frequency of 3 -4
time/week
Period of using the service
during
12.31-15.30 hrs.

Constant

0.638
-1.099
1.084
1.036
-1.876
16.633

0.264
0.309
0.489
0.431
0.834
46160.889

5.817
12.645
4.910
5.781
5.064
0.000


1
1
1
1
1
1

0.016*
0.000*
0.027*
0.016*
0.024*
1.000

0.153

16734186.077

Logistic Regression Equation was obtained as follows:

Table 4 shows that factors influencing the decision to use the Purple Line MRT were as follows. Sufficient
number of MRT trains influenced the increase in using Purple Line MRT service by 2.356 times. Convenient
transport of BTS or MRT linkage influenced the increase in using Purple Line MRT service by 1.892 times.
Uncomplicated service usage steps and selfservice influenced the increase in using Purple Line MRT service
by 0.333 times. Queuing of passengers influenced the increase in using Purple Line MRT service by 2.660 times.
The service usage of 1-2 times /week influenced the increase in using Purple Line MRT service by 2.995 times.
The service usage of 3-4 times /week influenced the increase in using Purple Line MRT service by 2.818 times.
The service usage during 12.31-15.30 hrs. influenced the increase in using Purple Line MRT service by 0.153
times.


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6. Discussions
Firstly, the service usage of 1-2 times /week influenced the increase in using Purple Line MRT service by
2.995 times. This implied that number of passengers of Purple Line MRT was 92 and will be increased by 271
in the next five years because of available routes, fast, safe and convenient transport.
Secondly, the service usage of 3-4 times /week influenced the increase in using Purple Line MRT service
by 2.818 times. This implied that number of passengers of Purple Line MRT was 94 and will be increased by
264 in the next five years because of available routes, fast, safe and convenient transport.
Thirdly, queuing of passengers influenced the increase in using Purple Line MRT service by 2.660 times.
This implied that number of passengers of Purple Line MRT was 340 and will be increased by 904 in the next
five years because of available routes, fast, safe and convenient transport.
Fourthly, sufficient number of MRT trains influenced the increase in using Purple Line MRT service by
2.356 times. This implied that number of passengers of Purple Line MRT was 340 and will be increased by 801
in the next five years because of available routes, fast, safe and convenient transport.
Fifthly, convenient transport of BTS or MRT linkage influenced the increase in using Purple Line MRT
service by 1.892 times. This implied that number of passengers of Purple Line MRT was 340 and will be
increased by 643 in the next five years because of available routes, fast, safe and convenient transport.
Sixthly, uncomplicated service usage steps and self-service influenced the increase in using Purple Line
MRT service by 0.333 times. This implied that number of passengers of Purple Line MRT was 340 and will be
increased by in the next five years because of available routes, fast, safe and convenient transport.
Seventhly, the service usage during 12.31-15.30 hrs. influenced the increase in using Purple Line MRT
service by 0.153 times. . This implied that number of passengers of Purple Line MRT was 53 and will be
increased by 8 in next five years 5 because of available routes, fast, safe and convenient transport.
7. Suggestions
More questionnaire examples should be prepared as greater information leads to lower errors. This also
provides benefits to make Purple Line MRT service improvement plan.
The study period was from 08.00-18.00 hrs. from Monday to Friday. Therefore, other periods of time should

be explored to increase data. Additional survey should be conducted during Saturdays and Sundays for data
coverage.
Convenient access to sky train stations should be studied.
-Greater studies on public needs for station locations should be conducted.
-More studies should be conducted to investigate whether the public accepts fare or not.
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