UNIVERSITI TEKNOLOGI MALAYSIA

DECLARATION OF PROJECT REPORT AND COPYRIGHT

Author’s full name : Vasuthevan A/L Annamalai

Date of birth : 05th January 1972

Title : Data Management of Public Bus Operators in Johor Bahru

Academic Session : 2008/2009

I declare that this project report is classified as:

CONFIDENTAL (Contains confidential information under the Official Secret

Act 1972)*

RESTRICTED (Contains restricted information as specified by the

organisation where research was done)*

√ OPEN ACCESS I agree that my project paper to be published as online open

access (full text)

I acknowledge that Universiti Teknologi Malaysia reserves the right as follows:

1. The project report is property of Universiti Teknologi Malaysia

2. The Library of Universiti Teknologi Malaysia has the right to make copies for the

purpose of research only.

3. The Library has the right to make copies of the thesis for academic exchange.

Certified by :

___________________________ ________________________________

SIGNATURE SIGNATURE OF SUPERVISOR

720105-01-5731_ DR.MUHAMMAD ZALY SHAH

(NEW IC NO./PASSPORT NO.) NAME OF SUPERVISOR

Date : 12th November 2008 Date : 12th November 2008

NOTES: * If the project paper is CONFIDENTIAL or RESTRICTED, please attach with the letter from

the organisation with period and reasons for confidentially or restriction

PSZ 19:16 (Pind. 1/97)

DATA MANAGEMENT OF PUBLIC BUS OPERATORS IN JOHOR BAHRU

VASUTHEVAN A/L ANNAMALAI

A project report submitted

in fulfilment of the partial requirement

for the award of the Master of Science (Transport Planning)

Faculty of Built Environment

UNIVERSITI TEKNOLOGI MALAYSIA

NOVEMBER 2008

ii

“We hereby declare that we have read this thesis and in our opinion this project

report is sufficient in terms of scope and quality for the award of the degree of

Master of Science (Transport Planning)”

Signature : ............................................................................

Name of Supervisor : Dr. Muhammad Zaly Shah B. Muhammad Hussein

Date : 12th November 2008

Signature : ............................................................................

Name of Examiner : Associate Professor Dr. Othman Che Puan

Date : 12th November 2008

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“I declare that this project report entitled “Data Management Of Public Bus

Operators in Johor Bahru” is the result of my own research except where I have cited

in the references. The project report has not been accepted for award of any degree

and is not currently submitted in candidature of any degree.”

Signature : ............................................................................

Name of Candidate : Vasuthevan A/L Annamalai

Date : 12th November 2008

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DEDICATION

This thesis is dedicated to my late father Mr.Annamalai, loving mum

Mrs. Theivanai, my lovely wife Parameshwari and dearest daughter

Saranyaa who taught me that the best kind of knowledge to have is that

which is learned for its own sake.

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ACKNOWLEDGEMENT

In all my humbleness and respect, I wish to dedicate this piece of work

including the many endeavour’s undertaken, to my loving mother Mrs.Theivanai. I

also pray for the blessings of my forefathers. My pursuit of Masters (M Sc. Transport

Planning) has been possible due to the moral support of my lovely wife

Parameshwari and my dearest daughter Saranyaa who has constantly assisted me in

continuing my further studies at UTM. It would be incomplete if I did not mention

Dr. Muhammad Zaly Shah my project supervisor, who at all times, guided and

counseled me through the completion of project. Many thanks to my colleagues

Asogan, Captain V and Nizam who were with me during my M. Sc. (Transport

Planning) studies at UTM, Skudai. Special thanks to my lovely wife for her support

in my studies.

Finally, above all, I am grateful to Lord Shiva – Anbe Sivam.

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ABSTRAK

Di dalam era logistik dan ekonomi yang baru, pengurusan data bas yang

sistematik adalah merupakan salah satu aset kritikal bagi mana-mana pengusaha bas.

Johor Bahru antaranya merupakan sebuah bandaraya di dunia ini yang menghadapi

masalah peningkatan permintaan pengangkutan awam dan juga masalah

pengangkutan yang disebabkan oleh pembangunan yang pesat. Kajian ini mengkaji

sistem pengurusan data yang dilaksanakan oleh pengusaha bas awam di bandaraya

Johor Bahru, Johor. Kajian ini memfokuskan kepada cara pengurusan data terkini

yang dilaksanakan oleh pengusaha-pengusaha bas awam di Johor Bahru. Kesemua

enam syarikat pengusaha bas di Johor Bahru telah ditemubual dalam menjayakan

objektif kajian ini. Matlamat pengkajian ini adalah bertujuan untuk mengetahui

pola/corak pengurusan data sedia ada yang dilaksanakan oleh pengusaha-pengusaha

bas awam di Johor Bahru di samping ingin mengetahui apakah faktor-faktor yang

memberikan kesan kepada pengusaha bas samada daripada pengumpulan, penilaian

dan menganalisa data. Borang soal selidik ( pengurusan data bas) untuk kajian ini

telah direka dan dianalisa dengan menggunakan program perisian Excel, di mana

dua dimensi yang berbeza iaitu data pendapat penumpang dan data operasi telah

digunakan dan dianalisa. Data-data diperolehi daripada semua pengusaha bas awam

dianalisa secara terperinci dan hasilnya menunjukkan bahawa tiada pendekatan yang

sistematik digunakan untuk mengumpul data daripada penumpang dan aktiviti

operasi. Hasil kajian ini juga menunjukkan bahawa pengurusan data bas sedia ada

tidak mempunyai satu pengumpulan data yang lengkap dan ianya lebih kepada

bentuk pemasaran dan route impact analysis. Pada masa yang sama, kajian ini

menunjukkan bahawa polisi syarikat memainkan peranan yang jelas dari segi

pengumpulan, penilaian dan analisa data. Kajian ini juga menunjukkan bahawa

pengurusan data bas di Johor Bahru jauh ketinggalan jika dibandingkan dengan lain-

lain bandaraya di negara-negara membangun.

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ABSRACT

In the new logistic and economy era, a systematic bus data management is

one of the critical assets for any bus operator. Johor Bahru like other cities in the

world is facing increased public transportation demands and transportation problems

caused by rapid urbanization. This research project investigates the data management

of public bus provider in Johor Bahru City, Johor. The research is focus on the

current practice of data management by public bus operator in Johor Bahru city. All

six public bus operators were interviewed for the purpose of this research. The aim of

this research attempts to know the pattern of existing data management practiced by

public bus operators in Johor Bahru and to know what are the factors affects the bus

operators from collecting, evaluating and analyzing the data. The questionnaire (bus

data management survey) of the research were designed and analyzed with

application of simple Microsoft Excel where two distinct dimensions namely,

passengers opinion data and operational data were analyzed. The data obtained from

all six public bus operator were descriptively analyzed and the finding indicate that

there is no systematic approach to collect data from passengers and operational

activities. The finding also indicates that the existing bus data management is not a

complete data collection and it is more on market trend and route impact analysis. At

the same time this research indicates that company policy play a significant role in

affects the bus operator from collecting, evaluating and analyzing the data. This

research indicating that the bus data management in Johor Bahru far less than

compare to other cities in developed countries.

viii

TABLE OF CONTENTS

CHAPTER TITLE PAGE

TITLE i

SUPERVISOR DECLARATION ii

STUDENT DECLARATION iii

DEDICATION iv

ACKNOWLEDGEMENT v

ABSTRAK vi

ABSTRACT vii

TABLE OF CONTENTS viii

LIST OF TABLES xii

LIST OF FIGURE xiv

TITLE PAGE

1 INTRODUCTION

1.1 Introduction 1

1.2 Current public bus scenario in Johor Bahru 1

1.3 Problem statement 4

1.4 Research question 5

1.5 Objective of study 5

1.6 Area of study 6

1.7 Contribution 7

1.8 Scope and limitation of study 8

ix

CHAPTER TITLE PAGE

2 LITERATURE REVIEW

2.1 Introduction 9

2.2 Basic element of data management 11

2.2.1 Data collection 11

2.2.2 Data entry 12

2.2.3 Data analysis 16

2.2.4 Data reporting 17

2.3 Data warehousing 18

2.4 Data mining 20

2.5 Application of data management 21

2.5.1 Marine data management 21

2.5.2 Transport data management 23

2.5.3 What is intelligent transport system 23

2.5.4 ITS and transportation 24

2.5.4.1 Benefits of ITS 24

2.5.5 ITS case study 1 - Improvement in Denmark

Rail Services using ITS 26

2.5.6 ITS case study 2 - Buses Tracked in Denmark 27

2.6 Importance of data management 28

2.6.1 Success story of New Zealand Post 28

2.6.2 Challenges 28

2.6.3 Action plan 29

2.6.4 Result 31

2.7 Failure of data management - Failure in predicting El-Nino 31

2.8 Transport data management - Failure in sustainable

data collection 32

2.9 Importance of data management to CEO/ Executive

and Planners 33

2.9.1 Application of EIS 34

2.10 Contribution of data management to public transportation 36

2.10.1 Key benefits of the data management in public

Transportation 36

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CHAPTER TITLE PAGE

3 RESEARCH METHODOLOGY

3.1 Introduction 38

3.2 Conceptual model 38

3.3 Data collection method 39

3.3.1 Primary data 39

3.3.2 Secondary data 40

3.3.3 Bus operator data management survey 40

3.4 Population and sampling method 42

3.5 Data analysis 42

3.5.1 Quantitative method 42

3.5.2 Qualitative analysis 43

3.6 Conclusion 43

CHAPTER TITLE PAGE

4 DATA ANALYSIS

4.1 Introduction 44

4.1.1 Data collection – passenger opinion 44

4.1.2 Passenger bus survey 46

4.1.3 Frequent of passenger bus surveys 47

4.1.4 Source of passenger’s feedback 47

4.1.5 Budget allocated for bus survey 48

4.1.6 Appointed personnel or department 48

4.1.7 Difficulties faced by bus operators during

data collection from passenger 49

4.1.8 Information collects by bus operators from

passenger 50

4.1.9 Record keeping 52

4.1.10 Purpose of bus operators collect data on passenger

opinion 52

4.1.11 Activity after collected the passenger data 53

4.1.12 Use of collected passenger’s data by bus operators 53

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4.1.13 Receiver of the complete passenger’s

opinion reports 55

4.2 Operational data collection 56

4.2.1 Company policy 56

4.2.2 Frequent of operational data 57

4.2.3 Source of operational data 58

4.2.4 Budget allocated for operational data 59

4.2.5 Appointed personnel or department 59

4.2.6 Difficulties faced by bus operators during

operational data collection 60

4.2.7 Type of data collected from operational

activities 61

4.2.8 Record keeping of operational data 63

4.2.9 Purpose of collecting operational data 63

4.2.10 Activity after collect the operational data 63

4.2.11 Use of collected operational data 64

4.2.12 Receiver of complete operational data reports 65

4.2.13 Types and formats of reports 66

4.2.14 Review and action plan 67

4.3 Conclusion 67

CHAPTER TITLE PAGE

5 CONCLUSION

5.1 Introduction 69

5.2 Summary of the research findings 69

5.3 Discussion 70

5.4 Future studies 72

5.5 Recommendation for public bus operators in Johor Bahru 72

5.6 Conclusion 73

REFERENCES 75

APPENDIX 78

xii

LIST OF TABLE

TABLE NO. TITLE PAGE

Table 1.1 Current public bus operators and

number of bus routes in Johor Bahru City 2

Table 1.2 Total registered stages bus, number of complaint and type of

disciplinary action taken by CVLB Peninsular Malaysia

for 2005 and 2006 3

Table 1.3 Transport & Communication Indicator by City, 1990 and 2000 3

Table 1.4 Traffic Compositions (%) By Bus JB-Air Hitam and JB – Endau 4

Table 4.1 Passenger opinion data collection by Johor Bahru bus operators 45

Table 4.2 Public bus passenger bus survey in Johor Bahru 46

Table 4.3 Frequent of public bus passenger survey 47

Table 4.4 Source of passenger’s feedback by bus operators 48

Table 4.5 Department for data management 49

Table 4.6 Difficulties during data collection for passenger opinion 50

Table 4.7 Passengers information collects by bus operators 51

Table 4.8 Records keeping of passenger opinion data by bus operators 52

Table 4.9 Purpose of data collection 53

Table 4.10 Activities after collect the data from passenger and method

of analysis 54

Table 4.11 Use of passenger’s data collected by public bus operators 54

Table 4.12 Receiver of the passenger opinion report 55

Table 4.13 Review of reports and action plan by bus operators on

final report 56

Table 4.14 Company policy on operational data collection 57

Table 4.15 Frequent of operational data collection 58

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Table 4.16 Source of operational data collection 58

Table 4.17 Department for operational data management 59

Table 4.18 Difficulties faces by bus operators during collect

operational data 60

Table 4.19 Type of data collected from operational activities 62

Table 4.20 Data collection on peak time and peak season 61

Table 4.21 Record keeping of operational data 62

Table 4.22 Purpose of bus company collect operational data 64

Table 4.23 Method of use to analyze the operational data 64

Table 4.24 Use of operational data 65

Table 4.25 Receiver of the operational report 66

Table 4.26 Type and format of the report 66

Table 4.27 Review of operational data collection reports and action plan 67

xiv

LIST OF FIGURES

NO. TITLE PAGE

Figure 1.1 Area of Study, Map of Johor Bahru City 7

Figure 2.1 Simple process of data management 11

Figure 2.2 Chicago transit authority bus tracker 15

Figure 2.3 Chicago transit authority bus location map 16

Figure 2.4 Data analysis 17

Figure 2.5 New Zealand Post 30

Figure 3.1 Conceptual model 39

Figure 3.2 Sections in Bus Operator Data Management Survey 41

Figure 4.1 Handal Indah, online customer feedback form 45

CHAPTER 1

INTRODUCTION

1. 1 Introduction1

Data Management is one of the strategically significant resources that any

organization can possess. Data management has traditionally been viewed as part of

the information technology cost centre. But this view is changing, both in business

and in general, as organizations recognize data as a critical asset that, when properly

managed and with a view to addressing specific business challenges, provides

significant competitive advantages. Data management has become an important

source of better performance and competitive advantage for any organization. Data

Management studies in Malaysia mostly focus on Hi-Tech industry, public sector

administration and educational institutes, rarely on transportation. This study takes

how public bus operator in Johor Bahru manage the data their data as a performance

index to improve services and sustain in the industry.

1.2 Current public bus scenario in Johor Bahru

Johor Bahru, like many Asian cities, is facing increased demand in better and

quality public bus transportation due to rapid urbanisation. The current public bus

services in Johor Bahru comprise of 6 bus companies with almost 600 buses which

operating on 117 routes (refer Table 1.1). Even though, current combination of land-

2

use and transport planning, public transport is accessible to a large part of the Johor

Bahru population the modal split is not in favors of public transport (bus, train and

taxi) 30:70 to private vehicles. (Technical report Transport Traffic Management Unit,

Local Plan Research, Johor Bahru , 2002).

Public bus transport system provide most efficient meant of moving large

numbers of people in Johor Bahru, especially in connecting surroundings residential

townships and rural areas to Johor Bahru City. Even though these public bus

transports not considerable flexibility in meeting demand for urban population,

public bus transport is the only choice of majority of the urban poor population in

Johor Bahru.

Table 1.1: Current public bus operators number of bus routes in Johor Bahru City

PUBLIC BUS OPERATOR NUMBER OF BUS ROUTES

MAJU 16 Routes

HANDAL INDAH - CERIA / CAUSEWAY LINK 23 Routes

S & S 3 Routes

GML LINE 5 Routes

TRITON 10 Routes

CITY BUS / TRANSIT LINK 36 Routes

Source: www.wikitravel.com

Statistics from CVLB Commercial Vehicles License Board (CVLB) showed

that even though complaint about stages bus in year 2006 is decreased about 0.9 but

seriousness of disciplinary action taken against stages bus is getting worst in 2006

compare to year 2005 (refer Table 1.2). Number of suspension is increased from 2

cases to 13 cases and one termination in year 2006. Above data clearly indicated that

public bus passenger are not satisfied with the service and poor bus management and

data management of bus resulted in serious disciplinary action taken against bus

operators.

3

Table 1.2: Total registered stages bus, number of complaint and type of disciplinary

action taken by CVLB Peninsular Malaysia for 2005 and 2006

Year 2005 Year 2006

Total registered stages bus 8,615 8,976

License Issued 519 361

Complaint 775 724

Warning 204 127

Compound 123 200

Suspension 2 13

Termination 0 1

Source: MECD Annual Report 2005 and 2006

A study on Malaysian Quality life in year 1990 - 2000 completed in 2002 by

Ministry of Entrepreneurial and Cooperative Development indicated that there are

838 cars and motorcycles per 1000 people in Johor Bahru in year 1990 were

increased to 1271 cars and motorcycles in year 2000. This is contrast with statistic

for public transport per 1000 population was 13.9 in year 1990 were only increased

to 15.8 in year 2000 (refer Table 1.3). This clearly indicated that declined in public

transport, especially public bus transport from year 1990 to 2000 in Johor Bahru and

registered the second highest of private vehicle user after Kuala Lumpur

(Malaysia Quality Life, Year 2002).

Table 1.3: Transport & Communication Indicator by City, 1990 and 2000

City Private vehicles

per 1000 population

Public transport

per 1000 population

City 1990 2000 1990 2000

Ipoh 485.1 825.4 4.8 6.3

Johor Bahru 838.1 1271.1 13.3 15.8

Kuala Lumpur 591.1 1418.5 10.5 21.6

Kuching 1549.0 1882.8 15.5 12.9

Source: Malaysian Quality Life, Year 2000

4

Table 1.4: Traffic Compositions (%) By Bus JB-Air Hitam and JB – Endau

Route / location 2004 2005 2006 2007

JR203 JB-Air Hitam 2.7 2.2 1.9 1.7

JR501 JB-Endau 0.9 0.8 1.9 1.2

Source: Road Transport Department, Malaysia, 2007

Another statistics from Ministry of Transport support above claims that the

traffic Compositions (%) by bus in selected JB-Air Hitam and JB – Endau showed

that compositions of bus on the road reduce from 2.7% in year 2004 to 1.7% in year

2007(refer Table 1.4). This is very obvious in JB-Air Hitam location whereby the

density of population along this route is higher compare to JB-Endau location. Above

two data clearly indicated that poor bus management and data management of bus

result in decreased of buses on the road specifically public bus passenger whom shift

to use private vehicles.

In Johor Bahru only one bus operator provide information and collect

customer’s feedback by online website. It is very surprised to know that two

prominent public us operators Syarikat Pengangkutan Maju (MAJU) and Alec Bus

Sdn. Bhd (City Bus) in Johor Bahru which in this industry more than 25 years still

using traditional method to collect passenger feedback. This study will highlight the

status of intra-city bus data management in Johor Bahru and how these bus operators

use the collected data and the effectiveness of the existing data management.

1.3 Problem statement

Johor Bahru like other cities in the world is facing increased transportation

demands and transportation problems caused by rapid urbanization. Even though

there are six public bus providers in Johor Bahru; intra-city bus industry is still

considered a traditional industry although it is one of indispensable transportation in

Johor Bahru. The management strategy of these public bus providers has no

systematic approach for collecting, record keeping, evaluate and analyze (bus data

management) the bus data’s among public bus operator in Johor Bahru. Most of the

5

bus companies have customer complaints form only and no adequate and well

planned complete bus survey. Basically the bus data management of intra-city bus

industry in Johor Bahru is far less than compare to other cities in developed countries.

Therefore, it is highly desirable to assess the status of intercity bus data management

in Johor Bahru to evaluate the effectiveness of the existing data management and

analyze the factors which affects the bus operators from collecting, evaluating and

analyzing the data’s practiced by bus companies in Johor Bahru.

1.4 Research Question

Research question for this study is based on above scenario of problem

statement and below are the research questions for this study.

i. What is the existing company policy on data management?

ii. What are data / information Johor Bahru bus operator collect?

iii. How these bus operators collect the data?

iv. How do these bus operators keep the collected data or archive the data?

v. Why these bus operators collect data?

vi. What these bus operators do after collected the data?

vii. How do these bus operators use the collected data?

viii. Company strategies and action plan after analyze the data /results?

1.5 Objective of study

The objectives of the study are:

i. To know the pattern of existing data management practiced by bus operators

in Johor Bahru.

6

ii. To know and analyze the factor which affects the bus operator from

collecting, evaluating and analyzing the data.

iii. To suggest and recommend solutions that will help improve the bus

operators data management.

1.6 Area of study

Johor Bahru is physically located at the southern part of the Malaysian

Peninsular which 350 Kilometres south of Kuala Lumpur and proclaimed as a City

Council in 1994. Population of Johor Bahru city is nearly 1.5 million (year 2006).

Land Area is 186 sq. km. Johor Bahru, (refer figure: 1.1) like many Asian cities, is

facing increased demand in better and quality public bus transportation due to rapid

urbanisation. Currently, 6 bus companies providing public bus services in Johor

Bahru city and its metropolitan area (refer table 1.1) This study covers the entire 6

public bus provider in Johor Bahru which covers 112 routes.

7

Figure 1.1: Area of Study, Map of Johor Bahru City

Source: Jabatan Kerja Raya, Negeri Johor, 2007

1.7 Contribution

This study could give us the existing pattern and effectiveness of data

management by bus companies in Johor Bahru.

Area of study Johor Bahru

8

Analyze the factors which affect the data management could help existing bus

service provider to think seriously about bus management and future and sustainable

public bus service in Johor Bahru.

Suggestion and recommendation based on result of study to improve the

Johor Bahru bus companies’ data management.

1.8 Scope and limitation of study

Involving public bus operator associated with competition in Johor Bahru

only. Any cross border bus service from JB-Singapore, Singapore – JB and intercity /

major town not included in this study. Any direct and indirect implications from

congestion, pollution and accidents involving other vehicles not covered in this study.

CHAPTER 2

LITERATURE REVIEW

2.1 Introduction

Data management began as a discipline in the early 1960s. Data

management is the name of a concept in which an organisation continuously and

comprehensively gathers, organizes, shares, and analyzes its collected data or

information in terms of resources, documents, and people skills to produce statistical

evidence reports. It is defined in several places, in ways that depict clearly how data

management has evolved to support time and needs. The definitions of data

management vary according to the understanding and use of it within various

communities of practice.

Data Management also define as the comprehensive series of procedures to

be followed and have developed and maintained the quality data, using the

technology and available resources. It can also be defined that it is the execution of

architectures under certain predefined policies and procedures to manage the full data

lifecycle of a company or organization data managements is the series of procedures

which is used to extract required information, analyze and produce conclusion

reports. This data and conclusion report become ‘evidence’ about the empirical

world (William, 2005).

Alexis Morgan, (2006) from World Wild Life Federation define data

management as a process to ensure that diverse data sets can be efficiently collected,

10

integrated/processed, labeled/stored, and then easily retrieved through time by people

who want to use them. In simple terms it could be taken to mean “a place for

everything and everything in its place”.

Some data management experts define it is a system related to organizing

data as a valuable resource and its primary stage is the consolidation of information

in such a way that data is easily retrieved and preserved. Companies or organisation

manage their data with a comprehensive data management plan, which includes

human as well technology converging to obtain basic company goal and to maintain

the data without any fuss and to be retrieved with ease which is usually done at data

warehouse of the companies.

In the military environment where data management had its roots, the

definition of data management as cited below:

"The process of applying policies, systems, and procedures for identification

and control of data requirements; for the timely and economical acquisition of such

data; for assuring the adequacy of data for its intended use; for the distribution or

communication of the data to the point of use; and for use analysis." (William, 2005)

In the information technology arena, data management is defined as a type of

client or server computing where some portion of the application data is executed on

two or more computers. It is also described in its IT application as control of data

handling operations such as acquisition, analysis, translation, coding, storage,

retrieval, and distribution of data but not necessarily the generation and use of data.

In order to give its various definitions and uses context, data management

should be viewed as objectives centered around life cycle functions and events, with

activities along a timeline that comprise good data management practices.

11

2.2 Basic elements of data management

Data management consists of data collection, data entry, data analyse and

data reporting. The process of data management used these four basic elements to

obtain information which needed for business objective and goals. The simple

process of data management respectively as shown in Figure 2.1

1st Qtr

2nd Qtr

3rd Qtr

4th Qtr

Figure 2.1: Simple process of data management

2.2.1 Data collection

Data are collected for enabling objectives of any organisation. The data are

collected to provide the most accurate information for the desired results. Data is

information and this could be in many forms or types. Data management institute in

US categorized there are major five types of the data usually collected during the

process of data collection (Cooper et al. 2004).

Data Collection

PROCESS OF DATA MANAGEMENT

Data Entry

Data Analyse

Data Reporting

12

i. Quantitative

Quantitative that data that can be represented as numbers including both

continuous data measured along a scale & categorical data recorded in

intervals or by groups such as number of tourist visits through Johor Bahru

Causeway during school holidays.

ii. Qualitative

Normally it is from interview, observation and written documents which not

easily represented in numerical form.

iii. Spatial

Spatial data that are linked to specific geographic coordinates (typically

quantitative, but could be qualitative) such as how transporters locate the

truck on a Global Positioning System.

iv. Financial

A special form of quantitative data that contain financial information such as

company annual report, business records, ledger etc.

v. Pictures, images, video clips and audio clips

This type of data contains photos, drawings, and other images collected on

specific site, area, and event before and after certain period

2.2.2 Data entry

Data entry is the act of transfer some form of data into another form, usually

a computer program. Forms of data that people might transfer include handwritten

documents, information off spreadsheets from another computer program, sequences

of numbers, letters and symbols that build a program, or simple data like names and

13

addresses. Some people perform jobs that are exclusively data entry, while others,

like programmers, might have to occasionally enter data (Cooper et al. 2004).

Generally, three methods currently used for entering data into the database:

i. Fully automated data entry

The fully automated system is one in which data are collected and input into

the database directly via a computer with little to no human intervention

during the collection/input process.

Example, Enabling Objective system in American primary school used to

collect automatic data collection via computer based training. Computer-

based training and testing terminals can collect a variety of information

automatically, such as lesson completion times, test scores, answers to

questions, time required to answer each question, etc. When the session is

over, the computer can tally up the score and record the results. The results

can be printed on paper for the examinee, to a file for the examiner, or

directly to a database.

ii. Manual data entry

Manual methods required data collector to observe performance or test

knowledge of measured items, render a judgment on the observation, and

record the judgment the results on paper media. The data entry operator then

manually keys the paper record into a computer. Good example of manual

data entry is Sijil Pelajaran Malaysia exam in Malaysia judging performance

of a candidate during a simulator session and testing for knowledge during an

oral exam, then recording the results on paper media. The instructor or

separate data entry operator then manually keys the paper record into a

computer

14

iii. Semi automated data entry

The semi-automated method of data entry is a combination of the automated

and manual methods and is the most widely used by companies for collecting

performance data. This method is combination of manual data collection,

then automated input into a computer.

iv. Internet /Web/Satellite based data entry

Data entry and communication via internet based website and GIS

(Geographical Information Systems) is a way of using maps to display

relevant data visually (refer Figure 2.2), making it easy to view, understand

and communicated. Internet /Web/Satellite based data entry become a

powerful tool which applied in today business such as satellite based traffic

management is used by Chicago City Council to control and ease traffic jam

in the city (refer Figure 2.3).

15

Figure 2.2: Chicago transit authority bus tracker

Source: Chicago Transport Authority

16

Figure 2.3: Chicago transit authority bus location map

Source: Chicago Transport Authority

2.2.3 Data analysis

Once the data are collected they must be analyzed and interpreted. The process of

conversion data define as data analysis. It is also define as the process of sorting

data with describes facts, and detect patterns intent to extract useful business

information and develop conclusion to meet short and long term business objectives

(refer Figure 2.4). Analysis of data includes several steps as per below:

17

Figure 2.4: Data analysis

2.2.4 Data reporting

Reporting of data is based on the computer or software analysis of the

performance database to provide information or result on the business objectives and

goals. Generally, three basic types of report formats are available, each with has its

own advantages and disadvantages (Irwin, 1983).

i. Written report

Written reports have some written text only and information that needs to be

brought to the reader / user attention should be presented in form of textual

report. Any tabular or graphical data presented in the report should be used

only to support the written text.

Check the raw data and prepare data for analysis

Conduct initial analysis base on the evaluation

plan

Conduct additional analyses based on initial

results

Integrated and synthesize findings

Da

ta a

na

lysis

18

ii. Tables

Tables are an effective way to present a large amount of data in a compact

space and are ideal for spreadsheets and other numerical analysis techniques.

The tabular format also permits the display of some intermediate results to

help give a sequence of important changes to the business needs.

iii. Graphs & Charts

Graphs and charts are used to present data visually. The relationships

between data values are expressed in visual such as pie charts, bar charts, line

charts, etc. Pictorial data make relationships stand out and conclusions

intuitively obvious. Graphs and charts are very effective when their business

objective and goals such as sales revenue, sales report, production report, etc,

can be presented in a simple diagram.

2.3 Data Warehousing

A data warehouse is a repository of an organization's electronically stored

data. It is specially designed to facilitate reporting and analysis. Data warehousing

focuses on data storage which means to retrieve and analyze data, to extract,

transform and load data, and to manage the data dictionary are also considered

essential components of a data warehousing system (William, 2005).

Many references to data warehousing use this broader context. Thus, an

expanded definition for data warehousing includes business intelligence tools, tools

to extract, transform, and load data into the repository, and tools to manage and

retrieve data. A data warehouse can be a relational database, multidimensional

database, flat file, hierarchical database, object database, etc. Data warehouse data

often gets changed and data warehouses often focus on a specific activity or entity

(Ralph, 1996).

19

Data warehousing is commonly used by companies to analyze trends over

time. In other words, companies may very well use data warehousing to view day-to-

day operations, but its primary function is facilitating strategic planning resulting

from long-term data overviews. From such overviews, business models, forecasts,

and other reports and projections can be made. Routinely, because the data stored in

data warehouses is intended to provide more overview-like reporting, the data is for

read only. Data warehouses could be updated all the time as per needs and necessary.

Robert P. (1998) states that data warehouse as a consolidated view of

business data, optimized for reporting and analysis. Basically it's an aggregated,

sometimes summarized copy of transaction and non-transaction data specifically

structured for dynamic queries and analytics. In data warehousing, data and

information are extracted from data sources as they are generated, or in periodic

stages, making it simpler and more efficient to run queries over data that originally

came from different sources. Data is turned into high quality information to meet all

business reporting requirements for all levels of users including company, customers,

partners, employees, managers, and executives at anytime.

Benefits of the data warehouse notably in customer relationship system. A

data warehouse provides a common data model for all data of collected regardless of

the data's source. This makes it easier to report and information such as sales

invoices, order receipts, general ledger charges, etc. Information in the data

warehouse is under the control of data warehouse users so that, even if the source

system data is purged over time, the information in the warehouse can be stored

safely for extended periods of time.

Because they are separate from operational systems, data warehouses provide

retrieval of data without slowing down operational systems. Data warehouses can

work in conjunction with and enhance the value of operational business applications,

notably customer relationship management (CRM) systems. Data warehouses

facilitate decision support system applications such as trend reports example the

items with the most sales in a particular area within the last two years, exception

reports, and reports that show actual performance versus goals (William, 2005).

20

2.4 Data mining

Jiawei and Micheline (2006) define data mining is the process of analyzing

data from different perspectives and summarizing it into useful information. This is

including information that can be used to increase revenue, cuts costs, or both. Data

mining allows users to analyze data from many different dimensions or angles,

categorize it, and summarize the relationships identified. Technically, data mining is

the process of finding correlations or patterns among dozens of fields in large

relational databases.

Data mining also define as a process whereby the data is extracted based on

the certain requisite parameters from the database. Data mining is an automated

process, using statistical analysis, modeling technique and database technology. Data

mining locate the patterns and relations in data and give us the outcome we desired

(Jiawei and Micheline, 2006).

Data mining consists of five major elements:

i. Extract, transform, and load transaction data into the data warehouse

system.

ii. Store and manage the data in a multidimensional database system.

iii. Provide data access to business analysts and information technology

professionals.

iv. Analyze the data by application software.

v. Present the data in a useful format, such as a graph or table

Jiawei and Micheline (2006) states that data mining is mainly used today by

companies with a strong consumer focus such as retail, financial, communication,

and marketing organizations. It enables these companies to determine relationships

among "internal" factors such as price, product positioning, or staff skills, and

"external" factors such as economic indicators, competition, and customer

demographics. It is enables them to determine the impact on sales, customer

satisfaction, and corporate profits. Finally, it enables them to "drill down" into

summary information to view detail transactional data.

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2.5 Application of data management

Data management has traditionally been viewed as part of the information

technology cost centre but this view is changing in business. Organizations recognize

data as a critical asset, when it is properly managed and with a view to addressing

specific business challenges, provides significant competitive advantages. Business

experts applied data management in various disciplinary of industries such as health,

sports, transportation, etc and good data management resulted success of most of the

business units (William, 1984).

2.5.1 Marine data management

Data management plays an important role in International Oceanographic

Data and Information Exchange (IODE) under spear head of UNESCO. The IOC’s

International Oceanographic Data and Information Exchange (IODE) was

established in 1961 to enhance marine research, exploitation and development by

facilitating the exchange of oceanographic data and information between

participating member states and by meeting the needs of users for data and

information products (Edward, 2007).

Edward (2007) states that the IODE system forms a worldwide service

oriented network consisting of DNAs (Designated National Agencies), NODCs

(National Oceanographic Data Centres), RNODCs (Responsible National

Oceanographic Data Centres) and WDCs (World Data Centres – Oceanography).

During the past 40 years, IOC Member States have established over 60

oceanographic data centres in as many countries. This network has been able to

collect, control the quality of, and archive millions of ocean observations, and makes

these available to member states. These marine data’s very useful those related to

marine activities such as climate and weather, safety at sea and along the coast,

fisheries, offshore activities, management of the seas, etc.

22

Data management of Oceanographic Data and Information Exchange (IODE) focus

on below;

i. Meteorology and coastal management

The weather has a tremendous impact on our lives. To a large extent, weather

is ‘produced’ at sea, and the heat stored in the upper layers of the ocean is of

great importance for both long-term and daily weather patterns. IODE

collecting and managing a good data management of meteorological

conditions and of how they are developing above the oceans, therefore IODE

makes a substantial contribution to timely prediction of storms and other

unfavourable weather to its member. These critical data through good

measuring networks, and systems for making data available swiftly (in

real-time or near real-time) is possible to avoid a great deal of human

suffering.

IODE also collecting and managing data of sea level which important to

monitor sea level changes. It is expected that by 2100 sea-level will have

risen about 38- 55 cm as a result of the greenhouse effect and the predicted

rise of 1.5-6.6°C in the Earth’s temperature. IODE updated and archive data’s

with quality control and fast data availability will estimate the change in sea

level that will occur as a result of wind, atmospheric pressure patterns, rise

and fall of land masses, and changes in ocean current patterns (Edward,

2007).

ii. Predictions needed for the safety of shipping

Tides, storms and currents are among the factors that determine the safety of

shipping and other activities at sea. Predictions of these, by means of

calculations with mathematical models and measurements made from

satellites, buoys and other measuring platforms, have become commonplace

in the context of shipping. These ordinary events can also be explained

through oceanographic databases (Edward, 2007).

23

iii. Management of living and non-living resources

Management of living as well as non-living resources requires good

knowledge and professional data management. Since the UN Conference on

Environment and Development, held in Rio de Janeiro in 1992,

monitoring of biodiversity has been considered necessary for assessing the

health of ecosystems. Many new initiatives have been taken, especially in

oceans and seas, to fill knowledge gaps with regard to living organisms.

IODE with cooperation with the European Fisheries Board managing of

fishing resources in Europe based the data available. Exploitation of

non-living resources, such as sand, gravel, oil, gas and manganese nodules,

is also well documented in databases, which in turn are of great value for

managing future use of these resources (Edward, 2007).

2.5.2 Transport data management

Transport is another industry where data management play an important role.

Emerging and evolving technologies known as intelligent transportation systems

(ITS) is meet the many challenges and demands placed on transportation systems.

2.5.3 What is Intelligent Transport Systems?

John (2005) define Intelligent Transport System (ITS) is about adaptive,

intelligent integration of vehicles, drivers and the transportation system. Integration,

through advanced information processing (computers), of communications and

sensory technologies and management strategies, can improve the safety, capacity

and efficiency of the transportation system. Communications and information

processing technologies allow information on the transportation system both vehicles

and infrastructure and real time road and environmental conditions, to be collected,

processed and disseminated for better decision-making.

24

Examples of ITS applications include traffic signal coordination, smart card

transit fare payment or dynamic route guidance changeable message signs that can

display real time information collected by sensors and warn motorists of collisions,

road and weather conditions; and automated vehicle inspection stations that can

electronically identify and provide expeditious clearance to commercial vehicles

(John, 2005).

2.5.4 ITS and transportation

When ITS integrated into the transportation system's infrastructure, and in

vehicles itself, these technologies monitor and manage traffic flow, relieve

congestion, improve safety and enhance productivity. In short, ITS helps save lives,

time, and money (Hassan and Amin, 2004).

2.5.4.1 Benefits of ITS

Through the use of ITS, public agencies and private corporations, both alone and

in partnership, are able to provide for safer, quicker, and more efficient travel.

Benefits of ITS include:

i. Increase Productivity

Automatic vehicle identification, screening of safety records and vehicle

weights, can provide a seamless commercial vehicle system, increase the

efficiency of the inspections services, and provide preclearance opportunities

for commercial vehicles. Real-time integrated transportation system data

collection can improve the efficiency of the data collection process and

facilitate traffic forecasting and planning. ITS can provide information about

transportation trends and the performance of the transportation system, which

can lead to better management and operations, more efficient allocation of

resources, and improved system performance.

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ii. Better travel information

At home, at work, or on the road, travellers have access to real-time, up-to-

date information about transit and train schedules, schedule adherence,

roadway conditions, and other travel information.

iii. Improve Safety

Pre-trip and en-route road and weather information systems can advise

motorists of traffic, road, environmental and emergency conditions. Real-time

information can assist route planning, ease frustration and reduce road rage.

Congestion reduction measures can reduce travel time and collisions. The end

result of these applications is the reduction in loss of life, injuries and costs,

which benefits society as a whole.

iv. Quicker emergency response

Electronic accident detection allows trained operators to locate then judge the

nature of a crash so they can quickly dispatch and guide the right emergency

personnel and equipment to the site.

v. Easier travel

In-vehicle navigation systems tell car, truck, and transit drivers how to best

reach their destination and will provide alternate routing during congestion,

emergencies or other events.

vi. Improved travel flow

A driver with a toll debit card (EZ Pass) attached to his vehicle can travel

through toll plazas without stopping. His toll charges are deducted

automatically from a prepaid account. Other travel fare collection systems,

like SMART CARDS, allow subway fares, transfers and other fees to be

charged to one card.

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vii. Fewer traffic jams

Traffic management centres reduce traffic jams and speed travel by

continuously monitoring current conditions, freeway operations, and traffic

signal operation, and responding quickly to incidents.

viii. Improved fleet management

Bus, freight and emergency vehicle tracking systems allow supervisors to

track vehicles and to communicate directly with drivers.

ix. Faster freight deliveries

Intelligent Transportation Systems provide for electronic weighing and

inspection of commercial vehicles while in motion, electronic issuing and

monitoring of transportation permits and automatic tracking of containers.

x. Reduced costs

The use of intelligent transportation technologies allows owners and

operators to make more efficient use of existing resources by automating

functions, sharing real-time information, and improving safety.

2.5.5 ITS Case study 1: Improvement in Denmark Rail Services using ITS

Denmark Railways generate multiple databases filled with literally miles of

spatial information. So proper coordination and manage of internet based ITS will be

a advantage in Denmark rail system. In Denmark, the Danish National Railway

Agency (DNRA) has a GIS that is interoperable with its primary user, the privately

owned Danish State Railways (DSB). Two agencies, each having multiple databases

and needing access by many users, require an interoperable GIS. The DSB database

is in itself large because of its ownership of 800 areas and 3,000 buildings. Different

users have many purposes for using the information. The GIS meets their needs on

all levels by organizing data, disseminating information on a GIS-enabled Internet

27

infrastructure, and applying GIS tools and solutions to many types of tasks and

analytical challenges.

DSB and DNRA coordinated their databases. Together they produced a base

map at 1:1,000 scales that covers all the country’s railway lines and stations. The

base map contains information on the railway infrastructure (e.g., tracks,

electrification, and cable signals), buildings, access roads, bridges, property

boundaries, and so forth. Users can query this map to extract various thematic map

layers such as level crossings, cables, and even building outlines (Globe, 2003).

2.5.6 ITS case study 2: Buses Tracked in Denmark

In 1996 the Copenhagen Transportation Company implemented a project

called Priobus involving the real-time tracking of buses throughout the metropolitan

area. The system, which was developed and implemented by the Dutch company

Peek Traffic B.V., helps dispatchers prioritize buses moving about the city and track

arrival information via dynamic displays to passengers waiting at bus stops.

Implementing the Priobus project included continuous accurate real-time localization

calculated with on-board computers in the vehicles using a digital global positioning

system (DGPS). The information is communicated using radio transmission to the

central system. Due to its complexity, the system required more than two years to

implement. All configuration and real-time information is stored in an Oracle

database. The database is used to import new schedules that are automatically

downloaded to the vehicles. The database is also used to create reports with

statistical information. In order to provide intuitive control over the system, a

geographical interface was implemented using another data base - MapObjects.

The mass transportation cornerstone in most cities remains the ubiquitous

public bus. Blending into the urban landscape, buses move about their business with

daily efficiency. This should not imply, however, that the bus system is in any way

static. Managers must be alert to changes within service areas, such as shifting

demographics or an increase in automobile traffic that would require adjustments to

28

routes or the implementation of addition al services to better meet the needs and

expectations of the agency’s ridership (Globe, 2003).

2.6 Importance of data management

Data management has traditionally been viewed as part of the information

technology cost centre but this view is changing in business. Organizations recognize

data as a critical asset, when it is properly managed and with a view to addressing

specific business challenges, provides significant competitive advantages.

2.6.1 Success Story of New Zealand Post (NZ Post)

New Zealand Post (NZ Post) is internationally recognized as providing one of

the most efficient and inexpensive postal services in the world. Every year, NZ Post

delivers more than one billion items of mail to approximately two million delivery

points in New Zealand. While it continues the tradition of carrying and delivering

letters and parcels through its postal services and international and express couriers,

NZ Post has responded to customers’ growing needs by expanding its business

activities to include business and personal communications, physical goods

distribution, banking and payments, and document and information management. NZ

Post is the largest employer in New Zealand.

2.6.2 Challenges

Like most postal authorities the world over, NZ Post has traditionally

captured address data directly from a widely distributed delivery manual records and

maps only.

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As a result NZ post which facing below problems,

i. Lack of ability to achieve maximum processing and delivery efficiencies

ii. The lack of quality and inconsistent address data

iii. Heavily depend on manual mail sorting to meet delivery target

2.6.3 Action plan

To meet this challenge, NZ Post established a program to scope, design, and

build a robust data management system using spatial data and analysis tools to

capture and maintain address data.

i. To capture and manage address data, an easy to use map-based application

was developed by Eagle Technology integrating Oracle®9i™, ESRI®

ArcSDE®, and ESRI ArcGIS® Server.

ii. This data base enabled NZ Post to develop an interactive client map based

application for the capture and maintenance of postal address data datasets

such as postal sort zone, postcode, and suburb/township for the entire

network and it was integrated with existing delivery systems.

The key goal of the new postal data management was to introduce implicit quality

improvement processes including spatial capture and the assigning of quality codes

on all address data.

30

Figure 2.5: New Zealand Post website

Source: www.nzpost.co.nz

The system is now accessible during business hours on the NZ Post intranet.

NZ Post employees use the mouse based application for searching, display, and

reporting. The interface was designed to be easy to use and focuses on completing

routine business processes quickly and accurately. To do this, the application allows

NZ Post employees to use a map view of all address data. They are able to see the

address in question and the surrounding environment such as street parcels, land

parcels, and topography. Addresses can then be added, modified, or deleted, and

reports that include the current map display and relevant details even can be

generated in PDF format.

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2.6.4 Results

NZ Post has found that ArcGIS data base provides centralized addressing

information with consistent high quality, reliability and an architecture that allows

scalability while keeping the core addressing information robust and definitive. This

approach to address data management has given NZ Post a reliable tool to maintain

the address database (a core asset) in a consistent, measurable, and known level of

quality.

2.7 Failure of data management - Failure in predicting El-Nino

Failure of data management caused human health, safety and property; it is

though lesson to IODE in early 1980’as where not aware of impact of El Nino. IODE

do not collect or do not have any data on El Nino which similar to monsoon climate

change. IODE which failure to warn about El Nino its member caused

approximately 125 million people were affected by the 1982-1983 El Nino event and

the material damage amounted to approximately US$ 30 billion (Edward, 2006).

Particularly destructive were the forest fires in Indonesia, the powerful

cyclones that struck the west coast of Mexico, and the floods that destroyed harvests

in East Africa. El Nino events affect fisheries, agriculture, ecosystems and weather

patterns far beyond the tropical Pacific.

The damage could have been even worse, if El Nino not has been predicted

six months in advance. IODE collaboration with United Nation had floating 72

measuring buoys that became operational in the tropical Pacific Ocean in 1987-1988.

These buoys register meteorological and oceanographic data at the surface, and water

temperature to a depth of 500 meter which have sign of El Nino type to IODE data

centre.

Between 1988 and 2002, this mega-project, with its 300 floating buoys and

numerous basin-wide hydro graphic sections, collected thousands of data related to

32

temperature and salinity measurements for the prediction of El Nino. Currently

IODE collect and distribute information about El Nino to its members timely and

efficiently to avoid any disaster in 3 to 6 months in advance (Edward, 2006).

2.8 Transport data management- Failure in sustainable transportation data

collection

A study by The Partnership for Sustainable Urban Transport in Asia

(PSUTA) indicated that information and data for that aids sustainable transport

development is still currently missing or fragmented in many Asia countries. Data

management play a key role in disseminating information on sustainable transport in

Asia in order to improve sustainable transport policy processes and outcomes. The

review of existing related documents is one of the project’s key outputs. Since

sustainable urban transport is a relatively new field, there has to be a systematic

overview of the kind of information that is available.

This study also indicates that decision makers need to have easy access to

such information, which is important and relevant to the formation of good transport

policies. Unfortunately, poor data management made the goal is to contribute toward

enhancing environmental sustainability of transport is unsuccessful in Asian cities.

Example Road facilities and their statistics for non-motorized transport (NMT) are

minimal, if not completely nil for Asian cities such as Hanoi, Delhi, Pune, and Xian,

China (Partnership for Sustainable Urban Transport in Asia, 2005).

PSUTA in its report 2005 found that emissions data for Asian bio fuels are

still minimal, and biodiesel information is variants from other regions outside Asia.

According to PSUTA Asian emission data are mostly outdated by at least 10 years,

which would affect subsequent studies that use these data. A recent informal survey

by PSUTA in 2004 on vehicle statistics and fuel usage shows that this information is

not usually monitored. This report also showed that only the Philippines, Singapore,

and Sri Lanka have this information and carry information on conventional fuels

only.

33

PSUTA in its report 2005 also highlighted that statistics on cleaner vehicle

technology and alternative fuel usage are minimal and are usually not reflected on

motor vehicle registrations, which are segregated by type of motor vehicle.

Substantial information gathered on economic and financial aspects is generally

weak for Asia; most are in the form of news items.

For developed countries such as Singapore and other westernized regions,

data on road pricing and congestion charges is available. Data on the costs of

different mass transit systems is also available. Information is likewise available on

the use of economic incentives for the introduction of cleaner fuels, and vehicles for

both Asian and non-Asian countries. There is limited data on the financial costs of

public transport systems in Asia, which are often operating partly or entirely in the

informal sector. This report also reveals that the size and impact of public transport

subsidies and fuel subsidies are not entirely clear. There is also no data on the costs

of congestion in Asian cities (Partnership for Sustainable Urban Transport in Asia,

2005).

2.9 Importance of data management to CEO / Executives and Planners

One of the most common sets of activities in the business is planning and

decision making. Only good data management could give confidence to CEO,

executives and planners to make decision on company objective, policy, strategic

goals, future plan to develop and sustain in the industries. Another type of data

management used in planning and decision making by senior level personnel in a

companies described as Executive Information System (EIS) (Robert, 1991).

An Executive Information System (EIS) is a type of management information

system intended to facilitate and support the information and decision making needs

of senior executives by providing easy access to both internal and external

information relevant to meeting the strategic goals of the organization.

Traditionally, the purpose is to illustrate a company’s data and to provide

sales performance or market research statistics for decision makers, as such financial

34

officers, marketing directors, and chief executive officers, who were not necessarily

well acquainted with computers. The objective was to develop computer applications

that would highlight information to satisfy senior executives’ needs. An EIS provides

data that would only need to support executive level decisions instead of the data for

all the company. Nowadays, EIS applied in many areas, especially, in manufacturing,

marketing, and finance areas (Robert, 1991).

2.9.1 Applications of EIS

After realizing its advantages, people have applied EIS in many areas, especially,

in manufacturing, marketing, and finance areas (Robert, 1991).

i. Manufacturing

Manufacturing is the transformation of raw materials into finished goods for

sale, or intermediate processes involving the production or finishing of semi-

manufactures. It is a large branch of industry and of secondary production.

Manufacturing operational control focuses on day-to-day operations, and the

central idea of this process is effectiveness and efficiency. To produce

meaningful managerial and operational information for controlling

manufacturing operations, the executive has to make changes in the decision

processes. EIS provides the evaluation of vendors and buyers, the evaluation

of purchased materials and parts, and analysis of critical purchasing areas.

Therefore, the executive can oversee and review purchasing operations

effectively with EIS. In addition, because production planning and control

depends heavily on the plant’s data base and its communications with all

manufacturing work centers, EIS also provides an approach to improve

production planning and control.

35

ii. Marketing

In an organization, marketing executives’ role is to create the future.

Marketing main duty is managing available marketing resources to create a

more effective future. For this, they need make judgments about risk and

uncertainty of a project and its impact on company in short term and long

term. To assist marketing executives in making effective marketing decisions,

an EIS can be applied. EIS provides an approach to sales forecasting, which

can allow the market executive to compare sales forecast with past sales. EIS

also offers an approach to product price, which is found in venture analysis.

The market executive can evaluate pricing as related to competition along

with the relationship of product quality with price charged. In summary, EIS

software package enables marketing executives to manipulate the data by

looking for trends, performing audits of the sales data, and calculating totals,

averages, changes, variances, or ratios. All of these sales analysis functions

help marketing executives to make final decisions.

iii. Financial

A financial analysis is one of the most important steps to companies today.

The executive needs to use financial ratios and cash flow analysis to estimate

the trends and make capital investment decisions. An EIS is a responsibility

oriented approach that integrated planning or budgeting with control of

performance reporting, and it can be extremely helpful to finance executives.

Basically, EIS focuses on accountability of financial performance and it

recognizes the importance of cost standards and flexible budgeting in

developing the quality of information provided for all executive levels. EIS

enables executives to focus more on the long-term basis of current year and

beyond, which means that the executive not only can manage a sufficient

flow to maintain current operations but also can figure out how to expand

operations that are contemplated over the coming years. EIS also can help

cash managers to review the company’s financial structure so that the best

method of financing for an accepted capital project can be concluded. In

addition, the EIS is a good tool to help the executive to review financial ratios,

36

highlight financial trends and analyze a company’s performance and its

competitors.

2.10 Contribution of data management to public transport

After realizing the advantages of data management, business community has

applied this practice in many areas, especially in public transportation. With

improved technology and internet/web/satellite based data management contribute

better fleet management to meet company objectives and goals.

With internet/web/satellite based data management public transport can

reduce their operating costs and increase productivity by having near real time

information on the location and status of all available bus. In addition, this ITS

management may directly communicate with the bus drivers to efficiently adjust

routes, schedule additional pick-ups when carrying less than full loads and be alerted

to emergency situations.

2.10.1 Key Benefits of data management in public transportation

With proper and good data management, any public transport companies can

go beyond simple vehicle tracking by providing the information they need to run the

business more profitably. Below are the key benefits of data management.

i. Increased employee productivity

ii. Increased driver safety

iii. Improved utilization of the fleet

iv. Better customer service

v. Reduced overtime and billing errors

37

vi. Reduced paperwork and reporting

vii. Lower fuel bills

viii. Stop unauthorized vehicle use

ix. Expedite stolen vehicle recovery

CHAPTER 3

RESEARCH METHODLOGY

3.1 Introduction

This chapter outlines the method and procedures engaged in carrying out the

research. It is a method where plays a very important role in ensuring to provide

accurate, or appropriate outputs if the research objectives are immeasurable. This

chapter also will discuss about conceptual model, research flow chart, method of data

collection and method of data analysis.

3.2 Conceptual Model

The conceptual model of this research is as in Figure 3.1. This research focuses

on the current pattern of data management practiced by public bus operators in Johor

Bahru, Johor. This research is to know the pattern of existing data management

practiced and analyze the factors which affects the bus operators from collecting,

evaluating and analyzing the data’s practiced by public bus companies in Johor

Bahru.

39

Figure 3.1: Conceptual model

3.3 Data Collection Method

Data for this study collected from primary data and secondary data. The data

collection method used in this study is discussed in the subsequent sections. The

information collected from this both data is very important to ensure the objectives of

this research are achieved.

3.3.1 Primary Data

According to Lau and Zainudin (2002), primary data is a raw data that has

been collected by the researcher itself who want to use the information. Primary data

can be collected through questionnaires, interviews, and observations among the

respondents related. As for this research, questionnaire has been choosing for the

Population Respondents (All Public bus operators)

Data management

Passenger’s opinion

Trip/operational activities

Existing / current practice

Factors effects the data collection

40

purpose of data collection, where it is depends on the bus operator’s response

regarding the data management of public bus service in Johor Bahru. Questionnaire

is chosen as a primary data collection method in this research because the

information can be gained from a bus operator’s by “face to face” interview and

meetings. The questionnaires used in the study are discussed in section 3.3.3

3.3.2 Secondary data

Secondary data is information gained from the second party or researches of

certain body. This information is very important in giving a deeper knowledge for

the researcher about factors regarding the research. As for this research, secondary

data collected from bus operator’s passenger survey, market study, reports, books,

files and annual report.

3.3.3 Bus Operator Data Management Survey

According to Lau and Zainudin (2002), survey is a list of questions printed

and the purpose is to get information regarding the research objectives. This method

is adopted as the main instrument to acquire the primary data of the research. The

questions were set to enable the researcher to study the concerned aspects. The

respondents of the survey are the Public bus operators in Johor Bahru, Johor.

The survey consisted of 14 questions to obtain data indicate approach used by

bus operators to collect and manage the bus data. Several questions are pertaining to

collect the passenger opinion, trip/operational data, reasons and purpose of collecting

data, analyzing data, companies’ strategies and action plan were included in the bus

operator data management survey. Bus operator data management survey divided in

two Part A and Part B. (refer Figure 3.2)

41

The bus operator data management survey is prepared in English and the

questionnaire is categorized into two sections which are Part A and Part B. Each section

has different questions according to the category respectively as shown in Figure 3.1.

The questionnaire designed is as in Appendix A.

Figure 3.2: Sections in Bus Operator Data Management Survey

i. Part A:

Part A consists of questions related to company policy and passenger

opinions. Questions related to company policy are to measure companies’

commitment towards collect passengers opinions, suggestion, and complaints

on service which rendered by Johor Bahru public bus operators.

ii. Part B:

Part B consists of questions related company policy to operational / trip data.

Questions related to company policy are generally to measure their own

commitment to collect trip or operational data which rendered to public.

Questions related to data trip or operational are used to measure bus

operator’s performance including financially and operationally.

Bus Operator Data Management Survey

Part B Part A

Data Collection

(Passenger Opinion)

Data Collection

(Operational)

42

3.4 Population and sampling methods

Population is collection of a group of individuals, objects, or size or quantity

which the attribute will be studied (Bluman, 2000). Population in this research is the

public bus operators in Johor Bahru, Johor. Johor Bahru City was selected because it

is one of a busiest and development area in Johor state as well as in Peninsular

Malaysia. In this research, the research population for this study is all six bus

operators in Johor Bahru. There is no sampling and all the six bus operators will be

interviewed to obtain information and data collection. The list public bus operators in

Johor Bahru are displayed in Table 1.1.

3.5 Data Analysis

The raw data acquired are generally discreet and in huge amount. In order to

present it in summarized and meaningful form, the statistical analysis in required.

Both primary data and secondary data will be analyzed using quantitative method

and qualitative method.

3.5.1 Quantitative Method

The quantitative method is applied onto the closed ended questions in the

questionnaire form which are from Part A and Part B. Quantitative method employed

in this research is descriptive analysis. Since the amount of data involve is not huge,

the analysis works will be done by using simple computer program called Microsoft

Excel.

The descriptive analysis is used to describe the data’s collected from bus

operators. These description give the most basic and comprehensive statistical

description. The descriptive analysis will be applied in the equation in Part A

(passenger opinion) and B (trip/operational data collection) of the questionnaire. This

43

method will contribute objectives of the research which is to know the pattern of

existing data management practiced and analyze the factors which affects the bus

operators from collecting, evaluating and analyzing the data’s practiced by bus

companies in Johor Bahru.

3.5.2 Qualitative Analysis

Qualitative methods are commonly used in conjunction with quantitative

method. Using qualitative methods it is often possible to understand the meaning of

the number produced by quantitative methods. The approach in the research is

merely focus the bus operator’s company policy on data collection which asked

about, budget and manpower allocation for passenger and operational/trip survey.

All opened question in Part A and B of bus operator data management survey will be

analyzed with using this technique.

3.6 Conclusion

It is through the above procedures that the data of this research are analyzed

and conclusions are drawn from them. The methodology as presented in this chapter

is proposed for achieving the aims and objectives of the research. The result of these

methods will be brought into analysis, comment and conclusion in the next chapter.

CHAPTER 4

DATA ANALYSIS

4.1 Introduction

This chapter will present the findings and the discussions of the research which

were based on in-depth interviews and discussion conducted throughout the study.

The responses of the six bus operators in Johor Bahru will be described in terms of

i. Passenger opinion data collection by bus operators

ii. Operational data collection by bus operators

4.1.1 Data collection by bus operator on passenger opinion

Company policy on data collection from passenger opinion plays a key role

on entire data management of any bus operators. It is one of the critical success

factors of the bus operator to achieve their business objective and goals. In Johor

Bahru only five bus operator collect data on passenger’s opinions (refer Table 5.1). It

is surprised to know that City Bus (previously known as Alec bus, South Johore or

Transit link) which operate in this industry more than 30 years not collecting

passengers opinion. Even though other five operators collecting data on passenger

opinion it is not a complete data collection which cover all aspects of passenger’s

opinions.

45

Table 4.1: Passenger opinion data collection by Johor Bahru bus operators

Bus operators Yes No

Maju √

Handal Indah √

S & S √

GML Line √

Triton √

City Bus X

Note: √= yes, X= no

S & S, GML Line, Maju and Triton just received passenger’s complaints in

form of telephone calls, sms but hardly in letters. Handal Indah takes the initiative to

collect some important passenger’s opinion to improve service by collect passengers

opinion by on line customer’s feedback form in its website (refer figure4.1) It is

showed that public bus passenger opinions are not taken seriously by Johor Bahru

bus operators.

Figure 4.1: Handal Indah, online customer feedback form

Source: www.handalindah.com.my/feedback.php

46

4.1.2 Passenger bus survey

Bus survey is one of the important activities in the public transport industries.

It gives priority to passenger express their view on the service which provide by bus

operators. The nature of bus survey is give full range of important information’s

from passengers to service providers. In the case of Johor Bahru, only Maju and

Handal Indah conducted bus survey so far and other service provider just did a

simple market research before enter into this business (refer Table 4.2). According to

City Bus operation personnel, bus survey is costly and it is impossible for the

company to conduct passenger or bus surveys every year.

Triton, S & S and GML Line not had done complete bus survey due to no

budget and no commitment from their management. This three bus operators depend

on outsource and market trend to get information of passengers. Handal Indah carry

out yearly passenger survey but it is not cover entire bus survey. Handal Indah and

Maju mainly concentrate in certain elements which passenger opinion carries more

value such as driver attitude, passenger’s safety, frequency of trip, schedule and seat

conditions.

Table 4.2: Public bus operator conduct passenger bus survey in Johor Bahru

Bus operator Yes No

Maju √

Handal Indah √

S & S X

GML Line X

Triton X

City Bus nd

Note: nd = not done by bus operators, √= yes, X= no

47

4.1.3 Frequent of passenger bus survey

Table 4.3 clearly showed that how often the public bus survey conducted in

Johor Bahru which consists of six operators. Except Handal Indah all other 5 bus

operators not carry out the bus survey annually or not done yet. Handal Indah

conduct bus survey annually had archive of 3 years record for their analysis. Maju, S

& S and GML Line and Triton bus operators argued that passenger survey or bus

survey is not vary from year before unless drastic changes in fuels price, government

policies, special events or any natural disaster such as flood.

Table 4.3: Frequent of Public bus passenger survey

Bus operators Monthly Annually Others

Maju √

Handal Indah √

S & S √

GML Line √

Triton √

City Bus nd

Note: nd = not done by bus operators, √= yes, X= no

4.1.4 Source of passengers feedback

This survey determines six important source of information’s from

passengers which feedback to bus operators (Refer Table 4.4). On-line customer

complaint form and suggestion box in every bus is provided by Handal Indah and

other four operators not so keen in this method. City bus not even offered basic

customer complaints form to passengers to express their opinions but this company

only receive complaints through short message service (SMS) and phone calls.

Except City Bus the entire bus service providers have customer complaint form to

collect feedback from passengers and result showed that SMS and phone calls are the

popular choice of passengers to feedback. Only Maju and Handal Indah collect

48

passenger feedback from passenger survey which conducted periodically by these

bus operators.

Table 4.4: Source of passenger’s feedback by bus operators

Statement Maju Handal

Indah

S & S GML

Line

Triton City

Bus

Customer

complaint form √ √ √ √ √ nd

On-line /website

complaint form X √ X X X nd

Passenger survey √ √ X X X nd

Suggestion box √ X X X nd

SMS / telephone √ √ √ √ √ √

Others X X X X X X

Note: nd = not done by bus operators, √= yes, X= no

4.1.5 Budget allocated for bus survey

This bus operator’s data management survey revealed that all the bus

operators in Johor Bahru are do not have or do not know about their budged

allocations. Handal Indah do not want to share the amount budgeted for passenger

survey and other operation personnel’s whom interviewed said that they do not know

about the budget for survey. City bus not allocates any budget to passenger or bus

survey.

4.1.6 Appointed personnel or department for data management.

Except GML Line and City bus other four operators has dedicated

personnel’s or department to collect and manage the information’s from passengers

49

(Refer Table 4.5). Maju and Handal Indah have full time customer service

personnel’s to managing the data from passengers. Meanwhile Triton and S & S do

not have any full time personnel or dedicated department to manage the

information’s from passengers.

Table 4.5: Department for data management

Bus operator Yes No

Maju √

Handal Indah √

S & S √

GML Line X

Triton √

City Bus X

Note: √= yes, X= no

Managing data is one of the important activities in bus industries which these

information’s are could be use in business development. The result showed that

Johor Bahru public bus operators do not serious in managing passenger information

to utilized in upgrade passenger needs.

4.1.7 Difficulties faced by bus operators during data collection from

passengers

All the bus operators in Johor Bahru face same type of difficulties during

collect customer’s opinion. This survey determines six type close ended questions to

bus operators to select the difficulties during collects feedback from passengers

(refer Table 4.6). All the public bus operators except City Bus said that toughest

challenge during data collection is passengers don’t give information or passengers

do not give their cooperation. Passenger whom alighting from bus refused to give

their opinion with below reasons;

50

i. rushing for transit another bus

ii. reached their destination

Time limitation also one of the difficulties facing by public bus operators

during collect passengers opinions. Maju and Handal Indah experience with less / not

trained staff in passenger survey. According to Maju and Handal Indah, surveyor

with lake of experience resulted in some poor data collection from passengers. Maju

and Handal Indah which conduct bus survey faced less manpower during passenger’s

survey even though have dedicated personnel and department (refer Table 4.6).

Table 4.6: Difficulties faced by bus operators during data collection

Statement Maju Handal

Indah

S & S GML

Line

Triton City

Bus

Passenger don’t

give information √ √ √ √ √ nd

Limited budget X X X X X nd

Not trained √ √ X X X nd

Less manpower √ √ X X X nd

Time limitation with passenger

√ √ X √ √ nd

Others √ √ √ √ √ nd

Note: nd = not done by bus operators, √= yes, X= no

The interesting information from this survey is all the operators gave

same answer for other difficulties as weather condition is one of the most important

factors should be consider during data collection especially; during raining season.

4.1.8 Information’s collects by bus operators from passenger

Passengers opinion play a key role in data collection and nevertheless what is

the information collect is also very important. This bus operator data management

51

survey question determines 13 elements to be answer by public bus operators in

Johor Bahru (refer Table 4.7) Result showed that all bus operators very concerned

about their bus driver’s attitude, bus fare, safety on board, bus schedule and bus

routes. This result indicated that bus operators more concerned about passenger’s

safety and financial elements rather than other factors such as noisiness, gender,

occupation and seat conditions. All the bus operators not collected information about

lost and found items in the bus. This information is direct link to reliability of bus

service and important element to measure passenger’s satisfaction which totally

ignored by these bus companies which carry higher weightage in this industries.

Table 4.7: Passengers information collects by bus operators.

Description Maju Handal

Indah

S & S GML

Line

Triton City Bus

Cleanliness √ √ X X X Nd

Bus fare √ √ √ √ √ Nd

Seat conditions X √ X X X Nd

Safety on board √ √ √ √ √ Nd

Punctuality X √ X X X Nd

Schedule √ √ √ √ √ Nd

Driver attitude √ √ √ √ √ Nd

Noisiness X X X X X Nd

Bus route √ √ √ √ √ Nd

Gender & age X X X X X Nd

Occupation X X X X X Nd

Lost and found X X X X X Nd

Note: nd = not done by bus operators, √= yes, X= no

4.1.9 Record keeping

Record keeping of bus data management in Johor Bahru is still practiced as

conventional method and latest technology and improvement in information

52

technologies not fully utilized. Table 4.8 showed that only Handal Indah and Maju

use simple software or spread sheet to kept data. Other three companies Triton,

S & S and GML Line still kept their passengers information record in the files. Even

though Handal Indah and Maju using software for kept the records, it is a very

simple spread sheet such as excel format used to analyze and print reports. Intelligent

transport System is not applied in Johor Bahru by any of the public bus company.

This mean that data which kept by all the bus operators is not updated or at least one

to two years old data.

Since there is no proper records keeping of data and not easily retrieve or

easily transfer to others will creates some administrative problems for authority such

as Road Transport Department, Johor Bahru City Council and Commercial Vehicles

License Board to format good transport policies for city of Johor Bahru.

Table 4.8: Records keeping of passenger opinion data by bus operators

Bus operator Paper report / files Software Others

Maju √ √ X

Handal Indah √ √ X

S & S √ X X

GML Line √ X X

Triton √ X X

City Bus Nd nd nd

Note: nd = not done by bus operators, √= yes, X= no

4.1.10 Purpose of bus company collect data on passenger opinions

All the bus companies in Johor Bahru except City Bus collect data on

passenger opinion for below reason (refer Table 4.9). All the bus operators collect

passenger opinion for their own analysis and for future investment. None of the

companies collect data for authority such as Road Transport Department, Johor

Bahru City Council and Commercial Vehicles License Board.

53

Table 4.9: Purpose of data collection

Maju Handal

Indah

S &

S

GML

Line

Triton City

Bus

Own use and analysis √ √ √ √ √ nd

Market study /

new investment √ √ X √ √ nd

For authority

(LPKP,MBJB,JPJ) X X X X X nd

Others X X X X X nd

Note: nd = not done by bus operators, √= yes, X= no

4.1.11 Activity after collecting the passenger data

All the bus operators except City Bus analyze the passenger’s data by its own

for further action (refer table 4.10). None of the companies submit data for authority

such as Road Transport Department, Johor Bahru City Council and Commercial

Vehicles License Board. On the other hand S & S, GML Line, Triton manually

analyze data’s which collected from passengers. Meanwhile Handal Indah and Maju

use software to analyze data (refer Table 4.10).

4.1.12 Use of collected passenger data by bus operators

The survey result showed that more emphasize given by bus operator in

public bus planning and safety analysis. (Please see table 4.11) According to Handal

Indah and Maju operation personal whom interviewed said that both companies use

data to analyze route impact which it could identify profitable routes and poor

collection routes. Maju and Handal Indah said that this will give some information to

the top management to decide priority route for their bus operation.

54

Table 4.10 Activities after collect the data from passenger and method of analysis

Decsription Maju Handal

Indah

S & S GML

Line

Triton City Bus

Analyse √ √ √ √ √ nd

Kept in file X X X X X nd

Submit to authority X X X X X nd

Others X X X X X nd

Description Maju

Handal

Indah S & S

GML

Line Triton City Bus

Manual X X √ √ √ nd

Software √ √ X X X X

Outsource X X X X X X

Others X X X X X X

Note: nd = not done by bus operators, √= yes, X= no

Table 4.11: Use of data collected by public bus operators

Maju Handal

Indah

S & S GML

Line

Triton City Bus

Traffic analysis X X X X X nd

Planning √ √ √ √ √ nd

Route impact analysis √ √ X X X nd

Monitor performance X X X X X nd

Safety analysis √ √ √ √ √ nd

Do not know X X X X X nd

Others X X X X X nd

Note: nd = not done by bus operators, √= yes, X= no

55

4.1.13 Receive the complete passenger’s opinion reports

This survey determines five important designations in the bus companies and

one others for any other department or any important personnel in the company

which final report of passenger opinions will be given for their perusal and action

plan (refer Table 4.12). This study indicated that operation manager and executive

management is the important personnel or group receiving the final reports of the

passenger opinion survey.

Triton and S & S explained that executive management is the decision maker

of the company and any changes is subject to executive management decisions. Any

way all the companies give the reports to other department such as accounts,

planning and customer service for their reference.

Table 4.12: Receiver the passenger opinion report

Statement Maju Handal

Indah S & S

GML

Line Triton City Bus

Customer service

manager

√ √ X X X nd

Traffic / Planning

manager

X X X X X nd

Operation manager X √ √ √ √ nd

Executive management √ √ √ √ √ nd

CEO X X X X X nd

Others √ √ X √ √ nd

Note: nd = not done by bus operators, √= yes, X= no

Table 4.13 showed that review of the reports by respective personnel in the

companies for further action. All bus operators except City Bus review the final

reports of the passenger opinion survey. This reports which consists important data

of passenger opinion give some important information’s to the management for

derive some action plan for the immediate or future actions.

56

Table 4.13 Review of reports and action plan by bus operators on final report

Review the report Action Plan by company

Bus operators Yes No Yes No

Maju √ √

Handal Indah √ √

S & S √ X

GML Line √ X

Triton √ X

City Bus nd nd nd nd

Note: nd = not done by bus operators, √= yes, X= no

Unfortunately, only Handal Indah and Maju take action plan after review the

final reports. According to Maju customer service assistant manager, management

stop servicing of few poor collection routes and increased the bus trip in the most

profitable routes after review the report. Some safety improvement was implemented

by Handal Indah with improved version of training module was conducted for the

company bus driver.

4.2 Operational data collection

Bus operation data play a key role in public bus data management.

Operational data collection was collected by interviewed all the six public bus

operators in Johor Bahru.

4.2.1 Company policy

Company policy on operational data collection plays a key role on entire data

management of any bus operators. It is one of the critical success factors of the bus

operator to achieve their business objective and goals. In Johor Bahru only four bus

57

operators collect operational data (refer Table 4.14). As per discussed in section 4.1.1

it is surprised to know that City Bus (previously known as Alec bus, South Johore or

Transit Link) which operate in this industry more than 30 years not collecting

operational data.

Table 4.14: Company policy on operational data collection

Bus operator Yes No

Maju √

Handal Indah √

S & S √

GML Line X

Triton √

City Bus X

Note: √= yes, X= no

Another bus company which not collects trip data is GML Line. Even though,

other four operators collecting operational data, it is not a complete data collection

which covers all aspects of bus operations. GML line and City bus depend on market

trend and other sources to obtain information about operational data.

4.2.2 Frequent of operational data

Table 4.15 clearly showed that how often the public bus survey conducted in

Johor Bahru which consists of six operators. Except Handal Indah all other 5 bus

operators not carry out the bus survey regularly or not done yet. Handal Indah

conduct bus survey annually and had archive of three years record for their analysis.

Maju, Triton, and S& S bus operator’s personnel’s argued that operation data

collection is not vary from year before unless drastic changes in fuels price,

government policies, special events or any natural disaster such as flood.

58

Table 4.15 Frequent of operational data collection

Bus Operator Monthly Annually Others

Maju X X √

Handal Indah X √ X

S & S X X √

GML Line Nd nd nd

Triton X X √

City Bus Nd nd nd

Note: nd = not done by bus operators, √= yes, X= no

4.2.3 Source of operational data

This survey determines six important operational data element as source of

information to be collected by bus operators (refer Table 4.16). Passenger feedback

form and ticket sold are the two elements which trip data collected by bus operators

in Johor Bahru. All four bus operators which collect operational data obtained

complaints in form of telephone call and sms from passenger Maju and Handal Indah

collect operational data from passenger’s survey which conducted periodically. None

of the bus companies use intelligent transport system to collect operational data.

Table 4.16 Source of operational data collection

Statement Maju Handal Indah S & S GML Triton City Bus

Ticket sold √ √ √ nd √ nd

Passenger survey √ √ X nd X nd

ITS X X X nd X nd

Feedback form √ √ √ nd √ nd

SMS / telephone √ √ √ nd √ nd

Others X X X nd X nd

Note: nd = not done by bus operators, √= yes, X= no

59

4.2.4 Budget allocated for operational data

This bus operator’s data management survey revealed that all the bus

operators in Johor Bahru are do not have or do not want to share their budged

allocations. Handal Indah do not want to share the amount budgeted for operational

data collection and other operation personnel’s whom interviewed said that they do

not know about the budget for survey. City Bus and GML Line not allocate any

budget to this operational data collection.

4.2.5 Appointed personnel or department

Except GML Line and City bus other four operators has dedicated

personnel’s or department to collect and manage operational data (refer table 4.17).

Maju and Handal Indah have full time customer service personnel’s to managing the

data from passengers. Meanwhile Triton and S & S do not have any full time

personnel or dedicated department to manage the operational data.

Table 4.17 Department for operational data management

Bus operator Yes No

Maju √

Handal Indah √

S & S √

GML Line X

Triton √

City Bus X

Note: √= yes, X= no

Managing data is one of the important activities in bus industries which these

information’s are could be use in business development. The result showed that

Johor Bahru public bus operators do not serious in managing operational data to

utilized in upgrade bus service.

60

4.2.6 Difficulties faced by bus operators during collect operational data

All the bus operators in Johor Bahru face same type of difficulties during

collect operational data. This survey determines six type close ended questions to bus

operators to select the difficulties during collects feedback from passengers (refer

Table 4.18). All public bus operators said that toughest challenge during data

collection is passengers don’t give information or passengers do not give their

cooperation.

Table 4.18 Difficulties faces by bus operators during collect operational data

Statement Maju Handal

Indah

S & S GML

Line

Triton City

Bus

Passenger don’t give

information

√ √ √ nd √ nd

Limited budget X X X nd X nd

No experience √ √ X nd X nd

Less manpower √ √ √ nd √ nd

Others √ √ √ nd √ nd

Note: nd = not done by bus operators, √= yes, X= no

Time limitation also one of the difficulties facing by public bus operators

during collect operational data. Maju and Handal Indah experience with not trained

staff in passenger survey. According to Maju and Handal Indah, surveyor with lake

of experience resulted in some poor data collection. Maju and Handal Indah which

conduct bus survey faced less manpower during data collection even though have

dedicated personnel’s and department.

The interesting information from this survey is all the operators gave same

answer for other difficulties as weather condition is one of the most important factors

should be consider during data collection especially; during raining season.

61

4.2.7 Type of data collected from operational activities

Operational data play a key role in data collection and nevertheless what are

the information collect is also very important. This bus operator data management

survey question determines 12 elements to be answer by public bus operators in

Johor Bahru (refer table 4.19) Result showed that bus operators are very concerned

about their financial element such as, passenger load factor, passenger volume, bus

fare and number of ticket sold by route. On the other hand, result showed that bus

break own and safety of passengers on board also given importance by bus operator

during operational data collection.

This result indicated that bus operators are more concerned about passenger’s

safety and financial elements rather than other factors such as passenger per trip,

number of trip by route and miss or jump schedule. Except City Bus and GML Line

all other fours bus operators in Johor Bahru collect the peak time and peak season

data collection for their own analysis (refer table 4.20) This information might useful

to these bus companies to plan their bus operation in especially in the peak hours.

Table 4.20: Data collection on peak time and peak season

Bus operator Yes No

Maju √

Handal Indah √

S & S √

GML Line nd nd

Triton √

City Bus nd nd

Note: nd = not done by bus operators, √= yes, X= no

62

Table 4.19: Type of data collected from operational activities

Description Maju Handal

Indah

S & S GML

Line

Triton City Bus

Passenger load factor √ √ √ nd √ nd

Passenger per trip √ √ nd nd

Passenger volume √ √ √ nd √ nd

Passenger by route √ √ nd √ nd

Bus fare √ √ √ nd √ nd

Ticket sold by route √ √ √ nd √ nd

No. of trip by route X √ X nd X nd

Overall data by

monthly / annually

X X X nd X nd

Bus breakdown √ √ √ nd √ nd

Miss schedule √ √ X nd X nd

Safety on board √ √ nd √ nd

Others X X X nd X nd

Note: nd = not done by bus operators, √= yes, X= no

Table 4.21: Record keeping of operational data

Paper / files Software Others

Maju √ √ X

Handal Indah √ √ X

S & S √ X X

GML Line nd nd nd

Triton √ X X

City Bus nd nd nd

Note: nd = not done by bus operators, √= yes, X= no

63

4.2.8 Record keeping of operational data

Since there is no proper records keeping of data and not easily retrieve or

easily transfer to others will creates some administrative problems for authority such

as Road Transport Department, Johor Bahru City Council and Commercial Vehicles

License Board to format and implement some good transport policies for city of

Johor Bahru (refer table 4.21).

4.2.9 Purpose of bus company collects operational data

All the four bus companies in Johor Bahru collect operational data their own

analysis and for future investment (refer Table 4.22). None of the companies collect

data for authority such as Road Transport Department, Johor Bahru City Council and

Commercial Vehicles License Board.

4.2.10 Activity after collect the operational data

All the bus operators except City Bus and GML Line analyze the

trip/operational data for own use, to know the market trend and future investment

(refer Table 4.22). None of the companies submit data for authority such as Road

Transport Department, Johor Bahru City Council and Commercial Vehicles License

Board. On the other hand S & S and Triton manually analyze data’s which collected

from passengers. Meanwhile Handal Indah and Maju use software to analyze data’s

(refer Table 4.23).

64

Table 4.22: Purpose of bus company collect operational data

Description Maju Handal

Indah

S & S GML Triton City Bus

Own use and analyse √ √ √ nd √ nd

Market study √ √ √ nd √ nd

For to authority X X X nd X nd

Others X X X nd X nd

Description Maju Handal

Indah

S & S GML Triton City Bus

Analyse √ √ √ nd √ nd

Kept in file X X X nd X nd

Submit to authority X X X nd X nd

Others X X X nd X nd

Note: nd = not done by bus operators, √= yes, X= no

Table 4.23: Method of use analyze the operational data

Statement Maju Handal Indah S & S GML Triton City Bus

Manual X X √ nd √ nd

Software √ √ X nd X nd

Outsource /

consultation X X X nd X nd

Others X X X nd X nd

Note: nd = not done by bus operators, √= yes, X= no

4.2.11 Use of collected operational data

More emphasize given by bus operator in public bus route impact analysis,

planning and safety analysis (refer Table 4.24). Handal Indah and Maju use data to

analyze route impact which it could identify profitable routes and poor collection

routes. Maju and Handal Indah said that this will give some information to their top

65

management to decide priority route and improved version safety measures for their

bus operation.

Table 4.24: Used of operational data

Description Maju Handal

Indah

S & S GML

Line

Triton City Bus

Traffic analysis X X X nd X nd

Planning √ √ X nd X nd

Route impact analysis √ √ X nd X nd

Monitor performance X X X nd X nd

Safety analysis √ √ X nd √ nd

Do not know X X √ nd X nd

Others X X X nd X nd

Note: nd = not done by bus operators, √= yes, X= no

4.2.12 Receiver of complete operational data reports

This survey determines five important designations and one is others for any

other department or any important personnel in the company which final report of

passenger opinions will be given for their perusal and action plan (refer Table 4.25).

This study indicated that executive management is most important personnel or

group receiving the final reports of the operational data collection reports.

All four operator which conducts operational data collection explained that

executive management is the decision maker of the company and any changes is

subject to executive management decisions. All the companies give the reports to

other department such as accounts, planning and customer service for their reference.

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Table 4.25: Receiver of the operational report

Description Maju Handal

Indah

S & S GML

Line

Triton City Bus

Customer service

manager √ √ X nd X nd

Planning manager X X X nd X nd

Operation manager X X X nd √ nd

Executive management √ √ √ nd √ nd

CEO X X X nd X nd

Others √ √ X nd X nd

Note: nd = not done by bus operators, √= yes, X= no

4.2.13 Types and format of report

The four public bus operators which conducted trip / operational data prepare

written reports with some tabular or graphical data brought forward to the company

management for further action. None of the bus operators give maps to support their

findings (refer Table 4.26).

Table 4.26: Type and format of the report

Describtion Maju Handal

Indah

S & S GML

Line

Triton City Bus

Tables √ √ √ nd √ nd

Graphic / charts √ √ X nd √ nd

Maps X X X nd X nd

Text √ √ √ nd √ nd

Others X X X nd X nd

Note: nd = not done by bus operators, √= yes, X= no

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4.2.14 Review and action plan

Table 4.27 showed that review of the reports by respective personnel in the

companies for further action. All bus operators except City Bus and GML Line

review the final reports of the passenger opinion survey. This reports which consists

important operational data could give some important information’s to the

management for derive some action plan for the immediate or future actions.

As per discussed in section 4.1.13 unfortunately, only Handal Indah and Maju

take action plan after review the final reports. According to Maju customer service

assistant manager, management stop servicing few poor collection routes and

increased the bus trip in the most profitable routes. Handal Indah with improved

version of preventive maintenance carry out to implement good conditions of bus.

Table 4.27 Review of operational data collection reports and action plan

Review the report Action Plan by company

Bus operators Yes No Yes No

Maju √ √

Handal Indah √ √

S & S X X

GML Line nd Nd nd nd

Triton √ X

City Bus nd Nd nd nd

Note: nd = not done by bus operators, √= yes, X= no

4.3 Conclusion

This analysis showed that bus operator management survey which interviewed all six

public operators gives existing approach and pattern of data management currently

practiced by Johor Bahru public bus operators. This research indicating that the bus

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data management in Johor Bahru far less than compare to other cities in developed

countries.

The existing approach is still using conventional method and far behind if compare to

other cities such as Singapore, Seoul and Tokyo in Asia. So, changes in bus data

management in Johor Bahru public bus operators is a must and action plan should be

carry out to improve the situation.

CHAPTER 5

CONCLUSION AND RECOMMENDATION

5.1 Introduction

This chapter will future discuss on the outcomes of this research according to

means of analysis that have been implement in previous chapter. It will consist of

summary, discussions of research result and some suggestions.

5.2 Summary of the research findings

This research attempts to explore existing pattern of the data management

which practiced by public bus companies in Johor Bahru. The purpose of this

research is to collect and compile existing pattern and effectiveness of data

management by bus operator in Johor Bahru. This research is to know about factors

which affect the bus operator from collecting, evaluating and analyzing the data.

Based on the data analyses that has been conducted, it has concluded that this

research has fulfilled its objectives, which are as per below;

i. To know the pattern of existing data management practiced by bus operators

in Johor Bahru.

70

ii. To know the factor which affects the bus operator from collecting, evaluating

and analyzing the data.

iii. To suggest and recommend solutions that will help improve the bus

operators data management

The findings of the research not only answered the questions related to the

public bus data management in Johor but it also helps the researcher to suggest and

recommendation take in the future.

5.3 Discussion

This section will discuss the objectives of this research and how it was met. It

also will discuss the findings for the each objectives and the result as well.

Based on the first objective, which is to know the pattern of existing data

management practiced by bus operators in Johor Bahru, finding showed that except

Maju other operator S & S, GML Line and Triton and City Bus do not have ISO

standard policy or any other similar policy. This study also found that there was not a

systematic approach of data management which defines how to conduct a proper

passenger and bus survey to achieve company objective including allocation of

budget, responsible department and their functions which met the second objective to

know the factor which affects the bus operator from collecting, evaluating and

analyzing the data.

These data gained from Part A and Part B of the Bus data management

survey. The analysis was analyzed through company policy on feedback of passenger,

frequency of bus survey, and budget and manpower allocation for bus survey.

This study showed that data collection for passenger opinion and operational

not conducted completely. City Bus totally never conducts any survey to gather

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information’s. Rest of the bus operators also not covers entire aspects of the

passenger or operational elements.

Another finding in this study which related to first objective is all the bus

operators kept the collected data or archive the data in files and simple spread sheet.

Latest technologies such as GPRS and satellite website to collect and keep the data

automatic in the systems for analysis not consider by any of the bus operators.

Based on the first objective this study also finds that main purpose of data

collection by these bus operators is to know current market trend and for future

investment only. Since these data not extend to authority, it is make some

administrative implications for authority such as Road Transport Department, Johor

Bahru City Council and Commercial Vehicles License Board not easy to format

good transport policies for city of Johor Bahru.

All the bus operators use the bus data for their daily bus operations which

achieved the bus operator’s objective which give more emphasis on route impact

analysis which benefits for the company.

The finding also showed that it is very minimal action plan by these public

bus companies which took some action plan was intently to improve internal

performance rather than direct benefits to passengers.

This study also found that there was not a systematic approach of data

management which defines how to conduct a proper passenger and bus survey to

achieve company objective including allocation of budget, responsible department

and their functions which met the second objective to know the factor which affects

the bus operator from collecting, evaluating and analyzing the data.

Another finding which met the second objective is difficulties during

collection of data. Factors such as passengers whom don’t want to give information,

time limitation with passengers, less manpower during bus survey and weather

condition during data collection are really affects the bus operator from collecting,

evaluating and analyzing the data.

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Based on second objective this study also find that collecting, evaluating and

analyzing the data not properly maintained and update due to no dedicated

department or manpower in public bus companies in Johor Bahru.

5.4 Future studies

The scope research done by me is limited because of some factors like time and

limited cost. From the research and findings obtained, a few suggestions are

suggested to improve the research result. Thus, there are few suggestions for the

future research, that is:

a) Further researches can help to gain more information with full detail by

accumulating the information from Road Transport Department, Johor Bahru

City Council and Commercial Vehicles License Board through interviews

and questionnaire.

b) The next research can be developed by designing a data management model

that can be used to evaluate the discussed elements.

5.5 Recommendation for public bus operators in Johor Bahru

Based on this research and findings the following recommendations are

suggested by researcher to improve current practice of data management among

public bus operators in Johor Bahru.

Study indicating that there is no systematic approach in data management; it

is a suggestion that a manual which gives complete guideline based on best practice

in the region to public bus operators in Johor Bahru. This manual will become basic

tools to manage the bus data. This practice could be integrated in to their current

management system as an improved version to enhance the bus data management.

73

Since current policy on passenger and operational data collection is not clear

or not well define, it is a necessary to introduce new system to improve the current

policy to achieve the company goals. System such as ISO standard or any other

similar transport standards is sufficient to revamp the existing bus data management

into dynamic public bus transport data control.

It is a suggestion that to form of a working committee on public bus data

management to format systematic approach to manage the data. This committee can

be initiate by Malaysian Road Transport Department and create an ad-hoc committee

which consists of all public bus operator in Johor Bahru, Johor Bahru City Council

and NGO‘s which represent bus passengers to organize the proper data collection.

The report and finding should submit to authorities to design new version of

transport policies and setting of the quality of service standard in Johor Bahru City.

Intelligent Transport System (ITS) is one the tools which could improve data

management in Johor Bahru city. Investment in latest transport software and

technologies would be the best ways to record keeping. Latest technologies such as

GPRS and satellite website collect and keep the data automatic in the systems for

analysis.

5.6 Conclusion

Last but not least, it is now clear that the study shows that pattern of existing

data management practiced by bus operators in Johor Bahru and the factor which

affects the bus operator from collecting, evaluating and analyzing the data. This

research has answered the questions that arise in the early chapter. The finding of this

research clearly shows management strategy of these public bus providers has no

systematic approach for collecting, record keeping, evaluate and analyze bus data

management.

74

Existing bus data management is not a complete data collection and it is more

on market trend and route impact analysis. This research as revealed that new

transports technologies and tools not utilized by the bus companies in Johor Bahru.

This study answered that public bus data management in Johor Bahru facing great

challenge in managing passenger and operational data as a performance index to

improve services and sustain in the industry.

As a researcher, it is hoped that whatever information and the finding of this

research can contribute some meaningful information to public bus operators in

Johor Bahru as well as useful for the relevant authorities especially for as Road

Transport Department, Johor Bahru City Council and Commercial Vehicles License

Board to design new version of transport policies and implementation for Johor

Bahru City. The information and this research also can be use as a reference for the

future researcher that wants to explore and do the research more in depth that relates

to the formulation of service quality.

75

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Appendix A

Bus Operator Data Management Survey

Company profile

Bus operator name : ___________________________________________ Date : ___________________________________________ Interviewee : ___________________________________________ Position : ___________________________________________

PART A: PASSENGER OPINION

1. Company Policy

i. Does your company collect data on passenger opinion?

If you answer ‘yes’ proceed to part iii, if your answer is ‘no’ please

answer part (ii) only and go straight to PART B.

□ Yes □ No

ii. Why your company not collect the data? (Please tick more than one if any)

□ No budget □ No manpower □ No legal requirement

□ Not important □ Depend on other sources □ Don’t know

iii. How often your company conducts passenger survey?

□ Monthly □ Annually □ Other, please specify__________

iv. How you collect passenger feedbacks; (Please tick more than one if any)

□ Customer complaint form □ On-line / website complaint form

□ Passenger survey □ Suggestion box in every bus

□ SMS / telephone □ Other, please specify___________

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v. How much budget allocated annually for bus survey or collection of data?

______________________________________________________________

vi. Any appointed personnel to manage data collected in your company?

□ Yes □ No

vii. How many manpower / man hours involve in the data collection?

______________________________________________________________

viii. Please list down the difficulties faced during collection of the data?

□ Passenger don’t give information □ Limited budget

□ Not trained /experience □ Less manpower

□ Time limitation with passenger □ Other, please specify_________

2. What are the information your bus company collect from passenger?

i. Passenger opinion on: (Please tick more than one if any)

□ Cleanliness □ Bus fare □ Seat conditions

□ Safety on board □ Punctuality □ Schedule/frequency

□ Driver attitude □ Noisiness □ Bus route

□ Gender and age □ Occupation □ Reliability □ Lost and found item

3. How do you keep the record of data?

i. How does your company record and archive the data have collected from various sources? (Please tick more than one if any)

□ Paper reports / files □ Software (e.g. spreadsheet, database, etc)

□ Other, please specify_______________

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4. Why your company collect passenger opinion data’s?

i. Can you specify why your company collect these data?

(Please tick more than one if any)

□ For own use / analysis □ For market study / investment

□ For others purpose, please specify_____________________

For authority, (Please tick more than one if any)

□ JPJ □ Police □ CVLB/LPKP □ Local authority

5. What your company do after collected the passenger opinion data?

i. List the activities after you collected the data? (Please tick more than one if any)

□ Analysis □ Kept in the file (for reference only)

□ Submit to authority □ Other, please specify____________

ii. How do you analyse the data? (Please tick more than one if any)

□ Manually □ Software (e.g. spreadsheet, database, etc)

□ Outsource / consultation □ Other, please specify____________

6. How does your company use the data collected?

i. How does your company use the data collected? (Please tick more than one if any)

□ Traffic analysis / control □ Planning

□ Route impact analysis □ Monitor system performance

□ Safety analysis □ Don’t know

□ Others (please specify) _________

7. Company strategies and action plans.

i. Who receives this performance report? (Please tick more than one if any)

□ Customer service Manager □ Planning Manager

□ Traffic / Operation Manager □ Executive Management

□ CEO □ Other, please specify___________

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PART B: OPERATIONAL DATA 1. Company Policy

i. Do you collect data on operational activities?

If your answer is ‘yes’ proceed to part iii, if your answer is ‘no’ please

answer part (ii) only.

□ Yes □ No

ii. Why your company not collect the operational data?

(Please tick more than one if any)

□ No budget □No manpower □ No legal requirement

□ Not important □ Depend on other sources □ Don’t know

iii. How often your company collect operation data?

□ Monthly □ Annually

□ Other, please specify____________________

iv. How you collect operation data? (Please tick more than one if any)

□ Ticket sold / bus pass □ Passenger / bus survey

□ Intelligent transport system (ITS) e.g. GPRS & satellite website

□ Passenger feedback form □ Telephone / sms

□ Other, please specify___________

v. How much budget allocated annually for bus survey or collection of data?

______________________________________________________________

vi. Any appointed personnel to manage operational data collected in your

company?

□ Yes □ No

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vii. How many manpower / man hours involve in the trip / operation data

collection?

______________________________________________________________

viii. Please list down the difficulties faced during collection of the data?

□ Passenger don’t give information □ Limited budget

□ Not trained / experience □ Less manpower

□ Other, please specify___________

2. What are the operation information your bus company collect?

i. Operational data on: (Please tick more than one if any)

□ Passenger load factor □ Passenger per trip

□ Passenger volume, □ Passenger per bus / route

□ Bus fare □ Number of tickets sold by route

□ Number of trip by route □ Overall trip data by monthly / annually

□ Bus breakdown □ Miss / jump of schedule

□ Safety on board □ Other, please specify______________

ii. Do you have operational data during peak time and peak season?

□ Yes □ No

3. How do you keep the record operational the data?

i. How do your company record and archive the trip / operation data have collected from various sources? (Please tick more than one if any)

□ Paper reports / files □ Software (e.g. spreadsheet, database, etc)

□ Other, please specify_______________

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4. Why your company collect operational data’s?

i. Can you specify why your company collect these data?

(Please tick more than one if any)

□ For own use / analysis □ For market study / investment

□ For others purpose, please specify______________________

For authority, (Please tick more than one if any)

□JPJ □Police □CVLB □Local authority

5. What your company do after collected the data?

i. List the activities after you collected the data? (Please tick more than one if any)

□ Analysis □ Kept in the file (for reference only)

□ Submit to authority □ Others, please specify____________

ii. How do you analyse the operational data? (Please tick more than one if any)

□ Manually □ Software (e.g. spreadsheet, database, etc)

□ Outsource / consultation □ Other, please specify___________

6. How does your company use the operational data collected?

i. How does your company use the data collected? (Please tick more than one if any)

□ Traffic analysis / control □ Planning

□ Route impact analysis □ Monitor system performance

□ Safety analysis □ Don’t know

□ Other (please specify) _________

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7. Company strategies and action plans.

i. Who receives this performance report? (Please tick more than one if any)

□ Customer service Manager □ Planning Manager

□ Traffic / Operation Manager □ Executive Management

□ CEO □ Other, please specify___________

ii. What is the format used to present these measures?

(Please tick more than one if any)

□ Tables □ Graphics/Charts

□ Maps □ Text

□ Other, please specify__________________

iii. Does your company review or assess the reports from data collected?

□ Yes □ No

iv. Any action plan taken from findings in the reports?

□ Yes □ No