Predicting the use of public transportation: A case study from Putrajaya, Mal...UCSI University
Putrajaya is a new federal administrative capital of Malaysia which has been set to achieve a
70% share of all travels by public transport in the city area. However, the current modal split
between the public transport and private transport is 15:85. In order to understand travelers’
willingness to use the public transport, a conceptual model has been developed to determine
the factors that affect them to use the public transport instead of travelling in their own cars.
The conceptualized relationship model was analyzed and tested using an analytical technique,
known as the structural equation model (SEM). Various variables such as service quality,
environmental impact, attitude and behavior intention were used in the structural model. The
database consisted of a survey of 290 car users in the Putrajaya city and all of them are
workers working in Putrajaya. Results indicate that the service quality and attitude are found
to have positive effects on the behavioral intention of taking the public transport. Other than
this, this study also shows that the service quality and environmental impact have some
positive influences on the attitude in using the public transport. However, environmental
impact has no significant, positive and direct effect on behavioral intention. The results of this
study demonstrate that the model that was developed is useful in predicting the public transport and it could provide a more complete understanding of behavioral intention towards public transport use.
One of the problems in big cities are transportation.They solve this problem by providing mass transportation such bus or train. People use this facility to travel between surrounding cities or within the city. Jakarta recently has a new public transportation called TransJakarta which serving people travelingfrom nearby cities and in the city.In order to move or doing business between places people in Jakarta use TransJakarta This research aims to analyse ticket price, service quality and customer value toward customer satisfaction. We conducted a research by using questionnaires given to thepassangers and developed a model using a multiple regression to process the result from questionnaires. Samples were taken from The number of sample for this reseach was 130 customers taken from one bus stop which passengers traveled from BSD City to Grogol and Slipi. The results from partial testing showed that customer value andservice quality have effect on customer satisfaction while ticket price does not have effect on customer satisfaction.
Identification of Factors to Improve Public Transit Services (A Case Study of...Dr. Amarjeet Singh
This research presents studies on a segment of highway to determine the quantitative factors that inuence transit services. Travel time and delay study is one of the method to determine quantitative factors. Tour time is described as the average period of time required to journey from one region to some other. Total departure time consists of gadgets which include total working time, places and general delay time. The examine section was done in Prithvi chowk to Tal chowk of Prithvi Highway which is turned to be 12.5 km long.
Additionally, it has been found that the principle variables affecting travel time are: postpone time because of forestall selecting and choosing up passengers, bus model and bus size.32 trips public transport carrier and a 10 trips non-public automobile journey have been held during peak hours. Models are developed the use of SPSS software to become aware of the relationship between the causes of delays and the overall-time delays. Travel time and learning delays can help reduce the number of private vehicles operating and increase the number of public vehicles in order to reduce congestion and improve the e efficiency of the public transport system. It turned into determined that there was a full-size distinction in tour time among the use of the public transit services and the car.
Predicting the use of public transportation: A case study from Putrajaya, Mal...UCSI University
Putrajaya is a new federal administrative capital of Malaysia which has been set to achieve a
70% share of all travels by public transport in the city area. However, the current modal split
between the public transport and private transport is 15:85. In order to understand travelers’
willingness to use the public transport, a conceptual model has been developed to determine
the factors that affect them to use the public transport instead of travelling in their own cars.
The conceptualized relationship model was analyzed and tested using an analytical technique,
known as the structural equation model (SEM). Various variables such as service quality,
environmental impact, attitude and behavior intention were used in the structural model. The
database consisted of a survey of 290 car users in the Putrajaya city and all of them are
workers working in Putrajaya. Results indicate that the service quality and attitude are found
to have positive effects on the behavioral intention of taking the public transport. Other than
this, this study also shows that the service quality and environmental impact have some
positive influences on the attitude in using the public transport. However, environmental
impact has no significant, positive and direct effect on behavioral intention. The results of this
study demonstrate that the model that was developed is useful in predicting the public transport and it could provide a more complete understanding of behavioral intention towards public transport use.
One of the problems in big cities are transportation.They solve this problem by providing mass transportation such bus or train. People use this facility to travel between surrounding cities or within the city. Jakarta recently has a new public transportation called TransJakarta which serving people travelingfrom nearby cities and in the city.In order to move or doing business between places people in Jakarta use TransJakarta This research aims to analyse ticket price, service quality and customer value toward customer satisfaction. We conducted a research by using questionnaires given to thepassangers and developed a model using a multiple regression to process the result from questionnaires. Samples were taken from The number of sample for this reseach was 130 customers taken from one bus stop which passengers traveled from BSD City to Grogol and Slipi. The results from partial testing showed that customer value andservice quality have effect on customer satisfaction while ticket price does not have effect on customer satisfaction.
Identification of Factors to Improve Public Transit Services (A Case Study of...Dr. Amarjeet Singh
This research presents studies on a segment of highway to determine the quantitative factors that inuence transit services. Travel time and delay study is one of the method to determine quantitative factors. Tour time is described as the average period of time required to journey from one region to some other. Total departure time consists of gadgets which include total working time, places and general delay time. The examine section was done in Prithvi chowk to Tal chowk of Prithvi Highway which is turned to be 12.5 km long.
Additionally, it has been found that the principle variables affecting travel time are: postpone time because of forestall selecting and choosing up passengers, bus model and bus size.32 trips public transport carrier and a 10 trips non-public automobile journey have been held during peak hours. Models are developed the use of SPSS software to become aware of the relationship between the causes of delays and the overall-time delays. Travel time and learning delays can help reduce the number of private vehicles operating and increase the number of public vehicles in order to reduce congestion and improve the e efficiency of the public transport system. It turned into determined that there was a full-size distinction in tour time among the use of the public transit services and the car.
Service Quality and Passengers Satisfaction of Southern Railways by SERVQUAL ...Selladurai Muthusamy
The economic growth of a country is mostly depends on the infrastructure and construction available in their area. Substructure link the peoples to services, markets and jobs and helps people to live healthy and productive lives. Transport facility is an important aspect of infrastructure facilitating mobility of goods and people from one place to another place. The passengers expect huge services from Indian Railways, but the railways providing few of the service in good quality and many of its services are not good. When the Indian Railways is not fulfil the passenger’s expectation, they are ready to switch over to another mode of transportation service. So, Indian railways to go down passenger business earning, in recent year the railway freight services only to contribute major role in Railway earnings. The railways passenger earnings were not good in past few years. Indian railways has to improve their services to world class. The main aim of the study is to identify the socio economic background of railway passengers and to analyse the gap between passenger’s expectation and perception of service quality.
We are committed to providing 100% Plagiarism free quality academic assignments i.e. thesis, dissertations, Course work assignments, HND Business assignments, Research and Term papers and Oxford Brookes thesis (RAP, SLS and PPT). Pay by milestones. Please visit www.ghostwritingmania.com or reach my inbox at ghostwritingmania@yahoo.com or add me on Skype: ghostwritingmania
The Presentation provides insight of actual implementation of the bus cluster scheme in Delhi. The government launched the scheme in 2008 . However, the project saw the light of the day in May 2011...it is expanding rapidly...please share your feedback at info@valoriserconsultants.com.
A project report on consumer perception towards GSRTC (st gujarat)Sunny Gandhi
gsrtc, st gujarat-consumer perception and attitude (behavior) towards GSRTC of people of sachin area-analysis on various aspects like bus station depots conductors drivers location water sitting arrangement punctuality timing online booking etc....
Bus system reform in India through JnNURMJaspal Singh
As part of Second Economic Stimulus Package by Government of India (announced on 02nd January 2009), the Government launched a scheme to provide one time assistance to States for the purchase of buses for their Urban transport system and identified 61 mission cities in the first phase. The presentation gives a brief overview of the complete scheme and its current status.
How to Make Awesome SlideShares: Tips & TricksSlideShare
Turbocharge your online presence with SlideShare. We provide the best tips and tricks for succeeding on SlideShare. Get ideas for what to upload, tips for designing your deck and more.
Satisfaction with public transport: the case of an university accessIJERA Editor
This study presents the results of a diagnostic survey on the users satisfaction with the public transportation
system which enables access to a higher education institution (HEI), relating it to some socio-bio-demographic
characteristics. The research instrument, based on fuzzy logic, was answered by 184 randomly selected
passengers. The statistical analysis was performed with non-parametric tests (Kruskal-Wallis, Man Whitney,
Friedman and Wilcoxon). The results for the level of satisfaction were considered reasonable and it was
identified that the factors ''terminal/stops'' and ''comfort/service for passengers'' were the worst evaluated. It was
also identified that the age of the passengers, travel time and distance from the terminal/stop to the
origin/destination are associated with the level of satisfaction.
Service Quality and Passengers Satisfaction of Southern Railways by SERVQUAL ...Selladurai Muthusamy
The economic growth of a country is mostly depends on the infrastructure and construction available in their area. Substructure link the peoples to services, markets and jobs and helps people to live healthy and productive lives. Transport facility is an important aspect of infrastructure facilitating mobility of goods and people from one place to another place. The passengers expect huge services from Indian Railways, but the railways providing few of the service in good quality and many of its services are not good. When the Indian Railways is not fulfil the passenger’s expectation, they are ready to switch over to another mode of transportation service. So, Indian railways to go down passenger business earning, in recent year the railway freight services only to contribute major role in Railway earnings. The railways passenger earnings were not good in past few years. Indian railways has to improve their services to world class. The main aim of the study is to identify the socio economic background of railway passengers and to analyse the gap between passenger’s expectation and perception of service quality.
We are committed to providing 100% Plagiarism free quality academic assignments i.e. thesis, dissertations, Course work assignments, HND Business assignments, Research and Term papers and Oxford Brookes thesis (RAP, SLS and PPT). Pay by milestones. Please visit www.ghostwritingmania.com or reach my inbox at ghostwritingmania@yahoo.com or add me on Skype: ghostwritingmania
The Presentation provides insight of actual implementation of the bus cluster scheme in Delhi. The government launched the scheme in 2008 . However, the project saw the light of the day in May 2011...it is expanding rapidly...please share your feedback at info@valoriserconsultants.com.
A project report on consumer perception towards GSRTC (st gujarat)Sunny Gandhi
gsrtc, st gujarat-consumer perception and attitude (behavior) towards GSRTC of people of sachin area-analysis on various aspects like bus station depots conductors drivers location water sitting arrangement punctuality timing online booking etc....
Bus system reform in India through JnNURMJaspal Singh
As part of Second Economic Stimulus Package by Government of India (announced on 02nd January 2009), the Government launched a scheme to provide one time assistance to States for the purchase of buses for their Urban transport system and identified 61 mission cities in the first phase. The presentation gives a brief overview of the complete scheme and its current status.
How to Make Awesome SlideShares: Tips & TricksSlideShare
Turbocharge your online presence with SlideShare. We provide the best tips and tricks for succeeding on SlideShare. Get ideas for what to upload, tips for designing your deck and more.
Satisfaction with public transport: the case of an university accessIJERA Editor
This study presents the results of a diagnostic survey on the users satisfaction with the public transportation
system which enables access to a higher education institution (HEI), relating it to some socio-bio-demographic
characteristics. The research instrument, based on fuzzy logic, was answered by 184 randomly selected
passengers. The statistical analysis was performed with non-parametric tests (Kruskal-Wallis, Man Whitney,
Friedman and Wilcoxon). The results for the level of satisfaction were considered reasonable and it was
identified that the factors ''terminal/stops'' and ''comfort/service for passengers'' were the worst evaluated. It was
also identified that the age of the passengers, travel time and distance from the terminal/stop to the
origin/destination are associated with the level of satisfaction.
Sustainable Urban Transport Development by Applying a Fuzzy-AHP Model: A Case...BME
Sustainable development decisions generally require citizen participation in the decision process to avoid public resistance and objections in the long term. Because of the involvement of non-experts, the uncertainty of the decision is increased, and this must be considered in the decision-making process. This paper aims to introduce a sustainable urban transport development problem in which citizens are involved to allow them to express their preferences for improving certain elements of the public bus system. To mitigate the uncertainty of the non-expert evaluations, a fuzzy-analytic hierarchy process (AHP) model has been created and applied. Since the objective of the research is to provide a suitable framework for transport development tenders, only the criteria weights have to be determined; thus, an alternative level has not been applied. The model has been tested on the urban bus transport system of a large Turkish city: Mersin. Based on the application, citizen preference weights could be associated with certain elements of the supply quality; thus, government development source allocation decisions could be supported. The fuzzy-AHP model ensures that the final development implications will meet public demand for bus system improvement in the city.
Applied research. Optimization of the Shuttle ServicesRAMON RIOS
Application of the queuing theory to find out the root causes of the long waiting times in the company X. The verification of the outcome was with promodel simulation software. Networking using the shortest route to optimize even better. Forecasting to predict increasing in the population and get our life cycle. Gantt chart to calculate the total days and to track the gantt chart for any delays.
The Prediction of Optimal Route of City Transportation Based on Passenger Occ...TELKOMNIKA JOURNAL
Currently, the existence of city transport is increasingly eliminated by private vehicles such as
cars and motorcycles. This situation is further exacerbated by the behavior of city transport drivers who are
less discipline in driving, or in picking up and dropping off their passengers. The bad behavior is partly
caused by the low level of passenger occupancy. The drivers try to search for passengers as much as
possible but often ignore the traffic rules. To overcome this problem, an optimal transport route with high
passenger potential is required. Therefore, this study investigated the optimal route of city transport based
on the passenger occupancy rate in the city of Bandung as the case study. The method employed for
determining the optimal route is Genetic algorithm combined with Ordinary Kriging method used for the
process of passenger prediction and fitness calculation. The optimal routes are those with higher
occupancy rate. The analysis results showed that the use of the Genetic algorithm with a low number of
generations succeed in creating new optimal routes even though the increase is not too high the maximum
only reaches 4%.This result is certainly important enough to be used in making better public transport
routes.
MODE CHOICE ANALYSIS BETWEEN ONLINE RIDE-HAILING AND PARATRANSIT IN BANJARMAS...IAEME Publication
Nowadays, application-based transportation is in great demand by the public. Public transport users began to switch to private-hire transportation. This is influenced by the increasingly sophisticated communication tools, making it’s easier for people to mobilise. Another reason for the large number of private-hire transportation use is due to the disappointment that arises on the insufficient of public transportation facilities. This raises the competition between both transporation modes—providing people with a choice in choosing the most appropriate one to use in supporting their activities. The aim of this research is to get a model that can explain the probability of Banjarmasin people’s preference in choosing between online ride-hailing and paratransit in banjarmasin city. In addition to this, the research also aims to find out about the factors or attributes that affect their preference, analyze the influence of travel costs and other attributes reviewed from different travel distance. This research was analyzed using multinomial logite method in Limdep Nlogit 4.0 software. Further analysis is done by multinomial logic analysis to obtain utility and probability on the transportation preference. After obtaining the best utility model,the data on cost sensitivity, travel time and convenience in choosing between both type of transporation, were obtained. Based on the result, the researcher found that the greater the cost and the travel time are, the greater the probability for the private-hire transportation to be choosen will be. Another aspect that makes people tend to choose private-hire transporation rather then public one is the convenience. The result shows that even if public transporation tries to improve its convenience from what it has now, it won’t cause any significant change on the number. In conclusion, private-hire transportation has the highest probability value compared to others. Based on the sensitivity of convenience, then it can be concluded that if the convenience of public transport is improved from its existing conditions, the probability may increase but the raise in the probability value isn’t going to be significant. Therefore, the largest probability value of the three modes belongs to online taxibike.
IRJET-Impact on Employment via Public Transit System
CTSEM2014 118
1. Colloquium on Transportation Systems Engineering and Management
CTR, CED, NIT Calicut, India, May 12-13, 2014.
Paper Id: 118
MULTINOMIAL LOGISTIC REGRESSION MODELLING FOR
PERCEPTION EVALUATION OF COMMUTERS TO WORK
USING BUS TRANSPORT
Ms Kamini Gupta1
, Dr. Ravindra Kumar2,
, Dr. Neelima Chakrabarty3
, Mr. Satyendra
Tomar4
1
Sr. Technical Officer, CSIR-CRRI, Mathura Road, New Delhi-110025,kgupta.crri@nic.in,
kamini_marut@rediffmail.com
2
Principal Scientist, CSIR-CRRI, Mathura Road, New Delhi-110025, ravinder.crri@nic.in
3
Sr. Principal Scientist, CSIR-CRRI, Mathura Road, New Delhi-110025,neelima.crri@nic.in
4
Project Fellow, CSIR-CRRI, Mathura Road, New Delhi-110025,
satyendra.tomar90@gmail.com
Abstract
Commuting to work by bus is still one of the major transportation system in Delhi.
Delhi government has introduced several reforms in services and it is found that the per
capita trip rate (excluding walk trips) has increased from 0.72 in 1981 to 0.87 in 2001.
It is estimated that per capita trip rate may reach to 1.2 by 2021 in Delhi. There is
always a gap between satisfactions of user due to increase in trip rate and offered
services by Delhi Transport Corporation. The major challenges to provide services are
in terms of quality service indicators such as travel time, comfort, information system,
accessibility, safety, different type of service offered, customer service, environmental
impact etc. to improve overall quality by transport authority. To know the service
performance of bus transportation one of the good method is User Perception Survey.
The users’ perception about services offered by transit system plays a essential role in
its success. It is therefore important to know the parameters which significantly
influence user’s perception regarding bus services, knowing which one will impact
more to improve the quality of transport services, as the public transportation improves
the quality of life across the country by providing safe, economical and efficient
services.
In this paper research work is presented for evaluation of user perception of commuting
passenger coming to CRRI Office in Delhi for official work. The age group of the
passenger is considered adult those who are coming to office from different directions
of Delhi. User Perception data has been collected by face to face interview.
Respondents were asked to give their perception of the quality level across the different
factors as well as satisfaction level toward their Bus services. A variable reduction
technique (PCA) was used to identifyinfluential variables & using these variables a
Multinomial Logistic (MNL) Regression model (using STATA) was formed for
Commuters satisfaction & their Comfort level. The model showed a higher degree of
precision when compared with real-life data.
Keywords
Bus user perception, official commute, Transportation, MNL
2. 1. INTRODUCTION
Public transport should become part of a solution for sustainable transport in the
future. However, in order to keep and attract more passengers, public transport must to have
high service quality to satisfy and fulfil more wide range of different customer’s needs.20, 21
.It is important to summarize knowledge about what drives customer satisfaction and
dissatisfaction in public transport area to design an attractive and marketable public transport.
The focus of this is Delhi Public Transport (bus) where the number of private vehicles is
increasing rapidly.
For a public transport service to function efficiently, it should be operated &
maintained keeping the user perception in focus. The user’s perception about services offered
by transit systems play a pivotal role in its success. It is therefore essential to know the
parameters which significantly influence user’s perception regarding bus services, knowing
which it is easier to improve the quality of transport services. Research on service quality has
been done from various aspects from a very long time; sufficient research has been
contributed in developing the service quality concept. There is a need for conceptual changes
to be built as the present concept of service quality does not fit the multidimensional
situations across nations.1,2,3,6,7
.In the current scenario of globalization, public transportation
services (PTS) need to introspect sensitivity towards the quality of services offered. In this
context, a study was carried out by Kokku18
to examine the commuters’ perception on service
quality offered by the public transport services of twin cities of Hyderabad and
Secunderabad, India.
For this purpose surveys were conducted in CSIR-Central Road Research Institute
(CRRI) Campus & commuters response on questionnaire prepared was collected. A
questionnaire with 30 questions has been prepared and used as opinion survey Performa for
conducting the survey. Data has been generated by face to face interview. Respondents have
been asked to give their perception of the quality level across the different factors as well as
satisfaction level toward their Bus services. The surveys encompass evaluation from CRRI
staff. The limitation of the survey conducted was most of the respondent were from South
Delhi and adult working class commuter.
1.1 Objective of the Research Study
The main objective of our study is to analyze data and modelling of bus user
perception survey and to find the appropriate quality parameter of bus passenger in Delhi
using Principle Component Analysis and Multinomial Logistic Regression technique. The
prior technique is use to reduce the number of variables affecting bus user perception and
later for modelling of the reduced variables in terms of time saving, cost saving, comfort,
environment, safety enhancement and commuter satisfaction.
2. METHODOLOGY
First the User Perception Survey questionnaire was prepared which includes 30
parameters (service quality indicators) like comfort, safety, waiting time, frequency, safety &
security, maintenance & construction, economic /financial viability) etc. More than 400
performance indicators, each assessed based on its performance category and then only 30
chosen 4, 10, 15,16,17,19.
Then the survey was conducted inside CRRI campus. Questions were
asked by face to face interview.
3. Finally analysis done using variable reduction technique (PCA) to identify influential
variables & using these variables a Multinomial Logistic Regression model was carried out
for commuter’s satisfaction & their comfort level.8, 9, 12, 13
2.1 Detailed methodology as follows:
2.1.1 Flow Chart of Methodology
To assess the quality of user perception in this paper, various set of variables were define to
the set indicators and selected to evaluate the current situation and the strategies. A Flow
chart Fig. 1 explains the steps involved like data collection, bus user attributes selected, use
of PCA & multinomial regression and finally satisfaction for Overall rating to DTC buses.
Fig 1. Flow Chart of Methodology
2.1.2 Preparation of Questionnaire
After reviewing of various services quality parameters as mentioned in review of Task
Force Group, the following variable were selected as attributes for user perception in basic
questionnaire design.
1. Gender 2. Age of Respondent 3. Education 4. Availability of personalized mode
5. Monthly income 6. Purpose of trip 7. Frequency of your travel on the routes 8. How do you
reach the bus stop? 9. What is your mode to reach the destination after alighting the bus?
10. General Information 11. How often do you ride the bus? 12. How often is the bus late?
13. How clean are the buses? 14. What is the condition of the buses (windows, seats)? 15.
How crowded are the buses? 16. Does the bus come to a complete stop at bus stops? 17. Does
the bus stop right in front of the bus stops? 18. Is the bus stop sufficient in size? 19. Does the
bus stop enough shade with respect to heat and rain? 20. On average, how long do you have
to walk to get to a bus stop? 21. On an average, how long do you have to wait for a bus?
22. Have you ever been assisted by a conductor to get a seat reserved for you? 23. Do you
have any information regarding the PMPML helpline? 24. If yes, have you ever used the
helpline for filing complaints? 25. If yes, did you receive any favorable response? 26. How
do you find the bus fares? 27. Keeping all the factors in mind, what according to you would
be the overall grade to the DTC service? 28. What are the reason(s) for using the bus?
29. Apart from bus how do you commute? 30. Do you think existing bus transport system is
beneficial to you on this corridor?
3. DATA COLLECTION:-
4. A survey was conducted in CRRI campus for two days on 08/04/2013 and 09/04/2013
from 9:30 AM to 4:30 PM and questions were asked by our team from the CRRI staff
including regular and temporary staff. Around 250 samples were collected from all the
divisions in the campus. In the data collected 52% were male and 48% were female and 58%
were of the age group of 30-59 years and 42% of 20-29 years. Complete User Perception
Survey was filled and obtained from the interviewer.
4. STEPS INVOLVED IN DATA ANALYSIS
4.1 Reducing Variable
First stage of modelling is to reduce the data set. In order to reduce a data set
containing a large number of inter-correlated variables to a data set containing fewer
variables, which represent a large fraction of the variability contained in the original data
Principal Component Analysis, is used. PCA is a variable reduction technique. It is a
multivariate statistical technique which can help t o get a better understanding of the
dependencies existing among a set of inter-correlated variables. PCA is conducted on
centred data or anomalies, and is used to identify patterns of simultaneous variations. These
components are simply linear combinations of the original variables with coefficients given
by the Eigen vectors. A property of component is that each contributes to the total
explained variance of the original variables. The analysis scheme requires that the
component contribution occur in descending order of magnitude, such that the largest amount
of variance of the first component explains the largest amount of variance of the original
variables, the second the next largest, and so on. In PCA, the number of extracted
components is equal to the number of input variables, there are ten sizing variables so ten
components are extracted, but only component with large amount of total variance are
selected for applying to the next step.
4.2 Logistic Regression
Logistic regression is useful for situations in which you want to be able to predict the
presence or absence of a characteristic or outcome based on values of a set of predictor
variables. It is similar to a linear regression model but is suited to models where the
dependent variable is dichotomous. Logistic regression coefficients can be used to estimate
odds ratios for each of the independent variables in the model. Logistic regression is
applicable to a broader range of research situations than discriminant analysis. After
performing and analysis findings from questionnaire are found out 16, 18, 19
.
4.3 User Perception from Questionnaire
Summary and findings of the sample is given below:
a) Condition of Buses: The condition of the buses was rated as Bad, Fairly Good and Very
Good. It was found that 28.84% responded with bad condition, Fairy good with 65.38%
respondent, and 5.76% rated very well to Delhi Transport Corporation buses as shown in
Figure 12.
b) Response on Bus Fare: The fare structure of the buses was rated as cheap, reasonable, and
costly. It was found that 5.76% responded with cheap condition, reasonable with 61.53%
5. respondent, and 32.69% rated costly fare for Delhi Transport Corporation buses as shown in
Figure 14.
c) Frequency of Bus Ride: The frequency of bus ride was classified into Daily, 4-5 time per
week, weekly, occasionally. It was found that 38% respondent for Daily, 27% respondent for
4-5 time per week, 12% respondent for weekly, 23% respondent for Occasionally travel in
Delhi Transport Corporation buses as shown in Figure 7.
d) Waiting time for buses: Waiting time for buses was classified into 1-3 minute/4-6 minute/
7-10 minute/ 10+ minute. It was found that 3.84% respondent wait for 1-3 minute, 26.92%
respondent waits for 4-6 minute, 28.84% respondent wait for 7-10 minute, and 40.38%
respondent waits for more than 10 minute to board the buses of Delhi Transport Corporation
buses a0s shown in Figure 11.
e) Comfort in Buses: Comfort in buses was classified into stand uncomfortably, stand
comfortably, and always get to sit. It was found that 63% respondent said they stand
uncomfortably in DTC buses, 25% respondent said they stand comfortably in buses, 12%
said they always get to sit in DTC buses as shown in Figure 10.
Other findings like age, gender details, availability of vehicles, income, purpose of trip,
frequency of travel, cleaninesscleanliness, comfort, maintenance, information regarding DTC
helpline, Overall grade to DTC services, Reason for using buses etc are shown in (Figure 2 to
Figure 18)
42%
58%
20-29
30-59
Fig 2. Age of Respondents
52%
48%
Male
Female
Fig 3. Gender of Respondents
Formatted: Normal, Left
6. 90%
4%2%2% 2%
Fig 4. Purpose of Trip
Work
Business
Education
Social
Leisure
2%
19%
40%
21%
12%
2%
2%
2%
<5000
5001-15000
15001-30000
30001-50000
50001-75000
75001-1 lakh
1 lakh-1.5 lakh
>1.5 lakh
Fig 5. Income
77%
2%
6%
2% 4%
9%
Fig 6. How do you reach Bus Stop?
Walk
Cycle
Bus
Two Wheeler
Car
Others
38%
27%
12%
23%
Fig 7. Frequency of Travel
Daily
4-5 times a
week
Weekly
Occasional
6%
48%
46%
Fig 8. Cleanliness
Very Dirty
Dirty
Clean
94%
2%
2%
2%
Fig 9. How do you reach Destination
after alighting the bus?
Walk
Bus
Two Wheeler
Others
63%
25%
12%
Fig 10. Comfort
Stand
Uncomfortably
Stand Comfortably
Always get to sit
4%
27%
29%
40%
Fig 11. Waiting Time
1-3 minute
4-6 minute
7-10 minute
10+ minute
7. 5. MULTINOMIAL LOGISTIC REGRESSION MODELLING:-
5.1 Principle Component analysis
Analysis of data is carried out in two steps for this research. First Principle
Component Analysis (PCA) was used to reduce the variables and it is done using the
software XLSTAT. And secondly Multinomial Regression was done on the output of PCA
using STATA.
29%
65%
6%
Fig 12. Condition of Buses
Bad
Fairly Good
Very Good
34%
66%
Fig 13. Size of Bus stop
Yes
No
6%
61%
33%
Fig 14. Fare
Cheap
Reasonable
Costly
25%
41%
17%
17%
Fig 15. How long do you wait for a
bus?
1-5 minute
6-10 minute
11-15 minute
15+ minute
21%
79%
Fig 16. Information regarding DTC
helpline
Yes
No
2%
56%
29%
7% 6%
Fig 17. Overall Grade to DTC
services
Excellent
Good
Average
Poor
Pathetic
90%
10%
Fig 18. DTC system beneficial for
you?
Yes
No
8. 5.2 Findings from PCA
Nine important parameters from thirty parameters were segregated depending on
Eigen value (>/= to 1) and maximum squared cosine values (greater than 0.5). XLSTAT is
software u s ed fo r data analysis. This was a l s o used for computing Principal
Component Analysis (PCA) and obtained nine parameters are:
1) Purpose of Trip: Work / Business / Education / Social / Leisure
2) Education: Below graduate/graduate/PG
3) What is your mode to reach the destination after alighting the Bus? Walk / Cycle /
Bus / Two Wheeler / Car / Others
4) How often do you ride the bus? Never/ 2-3 times per week/ 4-5 times per
week/Everyday
5) How often is the bus late? Never/ 1-2 times per week/3-4 times per week/ Always
6) How clean are the buses? Very Dirty/ Dirty/Clean
7) How crowded are the buses? Stand Uncomfortably/ Stand Comfortably/ Always get
to sit
8) On average, how long do you have to walk to get to a bus stop? 1-5 minute/ 6-10
minute/ 11-15 minute/ 15+ minute
9) On an average, how long do you have to wait for a bus? 1-3 minute/ 4-6 minute/ 7-10
minute/ 10+ minute.
5.3 Reduction of variable
These nine variables as selected from principal component analysis are used as an
input for Multinomial logistic Regression technique. Multinomial Logistic Regression is
useful for situations in which we want to classify subjects based on values of a set of
predictor variables. This type of regression is similar to logistic regression, but it is
more general because the dependent variable is not restricted to two categories. Dependent
variable taken as Overall customer satisfaction for DTC buses and independent variable as
output from PCA. Result obtained from Multinomial logistic Regression technique is shown
in Table (1 to 3) below as: Table 1 shows the model fitting information.
Table 1. Model Fitting Information
In the linear regression model, the coefficient of determination, R2
, summarizes the
proportion of variance in the dependent variable associated with the predictor (independent)
variables, with larger R 2
values indicating that more of the variation is explained by the
model, to a maximum of 1. The following methods are used to estimate the coefficient of
determination.
Cox and Snell's R2
1 is based on the log likelihood for the model compared to the log
likelihood for a baseline model. However, with categorical outcomes, it has a theoretical
maximum value of less than 1, even for a "perfect" model.
Model
Model
Fitting
Criteria Likelihood Ratio Tests
-2 Log
Likelihood Chi-Square df Sig.
Intercept
Only
116.703
Final 25.707 90.996 100 .729
Commented [Ravi1]: Where is the models parameters of MLR
like coefficients, variables /// thast is important part of models
results..
9. Nagelkerke's R2
2 is an adjusted version of the Cox & Snell R-square that adjusts the scale of
the statistic to cover the full range from 0 to 1.
McFadden's R2
3 is another version, based on the log-likelihood kernels for the intercept-
only model and the full estimated model.
From our test all these values are less than 1 as shown in Table 2, which satisfies the result
Table 2. Pseudo R Square
5.4 Chi-Square-Based Fit Statistics
The Table 3 in the output is the Goodness-of-Fit table. This table contains Pearson's
chi-square statistic for the model and another chi-square statistic based on the deviance.
These statistics are intended to test whether the observed data are inconsistent with the fitted
model or not. If they are not-that is, if the significance values are large-then you would
conclude that the data and the model predictions are similar and that you have a good model.
Table 3: Goodness of Fit
5.5 Overall Rating according to MLR Model
Figure 26 shows overall rating obtained from the MLR model and compared with Bus
Passenger Survey. at CRRI office . The results of this models difference shows overall
customer satisfaction in terms of excellent, good, average , poor and pathetic from model and
real world data. For excellent overall grading of Delhi Transport Corporation was found 2%
both in model and real world data. Similarly pathetic overall grading of DT was 6 % in both
model and real passenger survey. Model shows only 7% difference for Good Overall grading
and however for average and poor overall satisfaction grading there was 10% difference in
real data from passenger survey and model. The result of the models shows that model is very
accurate for certain grading like extreme rating (Excellent, poor and pathetic) and also predict
up to 90% correct for good and average satisfaction rating).
Pseudo R-Square
Cox and Snell 0.826
Nagelkerke 0.924
McFadden 0.779
Goodness-of-Fit
Chi-Square df Sig.
Pearson 28.448 100 1
Deviance 25.706 100 1
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10. Figure 19. Comparison of Overall Satisfaction RatingCRRI Survey and MLR result
6. CONCLUSION
Results found that in general condition of DTC buses are satisfactory but comfort
wise stand uncomfortably is 63% and 41% responds waiting time is almost 10 minutes. Bus
conditions are fairly good with 65% respondent, 29% bad and 6% rated very well to Delhi
Transport Corporation buses. Study found that fare for Delhi Transport Corporation buses are
61% responded reasonable, 33% responded costly and only 6% responded cheap. Bus user’s
populations are quite young. But as the age increases bus users decreases. It was found that in
general overall rating of DTC buses lie in terms of good (56%) to average (29%) others are
excellent only 2%, poor 8% and pathetic 6%. From the model overall ratings are almost
similar from good (52%) to average (32%) and excellent, poor & pathetic are exactly same.
The result of the Multinomial Regression model shows that model is very accurate for certain
grading like extreme rating (Excellent, poor and pathetic) and also predict up to 90% correct
for good and average satisfaction rating).
Such a study, will also serve to track the quality of service over time and help
advocacy groups as well as users to press for improvements. Such system can act as a
running performance audit for public transportation system from user perspective point of
view.
Acknowledgement
The authors are thankful to the Director, Central Road Research Institute, New Delhi for
permitting to publish this paper. Authors are thankful to Dr. E. Madhu, Champion of the
SUSTRAN project, 12th
five year plan project, CSIR-CRRI for his kind support. Paper has
been prepared based on data collected in SUSTRANS project and produced.
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