Public Bus Data Management Johor Bahru, Malaysia
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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
720105-01-5731_ (NEW IC NO./PASSPORT NO.)
Date
NOTES: *
: 12th November 2008
________________________________ SIGNATURE OF SUPERVISOR
DR.MUHAMMAD ZALY SHAH NAME OF SUPERVISOR
Date
: 12th November 2008
If the project paper is CONFIDENTIAL or RESTRICTED, please attach with the letter from the organisation with period and reasons for confidentially or restriction
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
iii
“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
iv
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.
v
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.
vi
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 lainlain bandaraya di negara-negara membangun.
vii
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 1
PAGE
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
2
TITLE
PAGE
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 2.5.5 2.5.6 2.6
24
ITS case study 1 - Improvement in Denmark Rail Services using ITS
26
ITS case study 2 - Buses Tracked in Denmark
27
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
2.9
2.10
32
Importance of data management to CEO/ Executive and Planners
33
2.9.1
34
Application of EIS
Contribution of data management to public transportation 36 2.10.1 Key benefits of the data management in public Transportation
36
x CHAPTER
3
TITLE
PAGE
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
CHAPTER
43
TITLE
4
PAGE
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
4.1.8 4.1.9
49
Information collects by bus operators from passenger
50
Record keeping
52
4.1.10 Purpose of bus operators collect data on passenger opinion 4.1.11 Activity after collected the passenger data
52 53
4.1.12 Use of collected passenger’s data by bus operators 53
xi 4.1.13 Receiver of the complete passenger’s opinion reports 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
4.2.7
4.3
60
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
Conclusion
67
CHAPTER
TITLE
5
55
PAGE
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. Table 1.1
TITLE
PAGE
Current public bus operators and number of bus routes in Johor Bahru City
Table 1.2
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
xiii 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
8,615
8,976
License Issued
519
361
Complaint
775
724
Warning
204
127
Compound
123
200
Suspension
2
13
Termination
0
1
Total registered stages bus
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
Public transport
per 1000 population
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
Area of study Johor Bahru 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.
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
PROCESS OF DATA MANAGEMENT
Data Collection
Data Analyse
Data Entry
1st Qtr 2nd Qtr
Data Reporting
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).
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. Computerbased 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
Check the raw data and prepare data for analysis
Conduct additional analyses based on initial results
Data analysis
Conduct initial analysis base on the evaluation plan
Integrated and synthesize findings
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.
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-today 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.
21 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.
25 ii.
Better travel information At home, at work, or on the road, travellers have access to real-time, up-todate 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.
26 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.
29
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.
31 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 semimanufactures. 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
Population Respondents (All Public bus operators)
Trip/operational activities Passenger’s opinion
Data management Existing / current practice
Factors effects the data collection
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
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.
Bus Operator Data Management Survey
Part A
Data Collection (Passenger Opinion)
Part B
Data Collection (Operational)
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.
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
Maju
√
Handal Indah
√
S&S
√
GML Line
√
Triton
√
City Bus
No
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
Maju
√
Handal Indah
√
No
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
S&S
Indah Customer complaint form On-line
/website
complaint form Passenger survey
GML
Triton
Line
City Bus
√
√
√
√
√
nd
X
√
X
X
X
nd
√
√
X
X
X
nd
√
X
X
X
nd
Suggestion box 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
Maju
√
Handal Indah
√
S&S
√
GML Line
No
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
S&S
Indah Passenger
don’t
GML
Triton
Line
City Bus
√
√
√
√
√
nd
Limited budget
X
X
X
X
X
nd
Not trained
√
√
X
X
X
nd
Less manpower
√
√
X
X
X
nd
√
√
X
√
√
nd
√
√
√
√
√
nd
give information
Time
limitation
with passenger Others
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
S&S
Indah
GML
Triton
City Bus
Line
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
Nd
nd
nd
City Bus
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
Own use and analysis Market study /
Handal
S&
GML
Indah
S
Line
√
√
√
√
√
nd
√
√
X
√
√
nd
X
X
X
X
X
nd
X
X
X
X
X
nd
new investment For authority (LPKP,MBJB,JPJ) Others
Triton
City Bus
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
S&S
GML
Indah
Triton
City Bus
Line
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
Triton
City Bus
Description
Maju
Handal Indah
GML
S&S
Line
Manual
X
X
√
√
√
nd
Software
√
√
X
X
X
X
Outsource
X
X
X
X
X
X
Others
X
X
X
X
X
X
Triton
City Bus
Note: nd = not done by bus operators, √= yes, X= no
Table 4.11: Use of data collected by public bus operators Maju
Handal
S&S
Indah
GML Line
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
service
√
√
X
X
X
nd
Planning
X
X
X
X
X
nd
Operation manager
X
√
√
√
√
nd
Executive management
√
√
√
√
√
nd
CEO
X
X
X
X
X
nd
Others
√
√
X
√
√
nd
Customer manager Traffic
/
manager
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 Bus operators
Yes
No
Action Plan by company 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
Maju
√
Handal Indah
√
S&S
√
GML Line
No
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
Maju
√
Handal Indah
√
S&S
√
GML Line
No
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
S&S
Indah
GML
Triton
Line
City Bus
√
√
√
nd
√
nd
Limited budget
X
X
X
nd
X
nd
No experience
√
√
X
nd
X
nd
Less manpower
√
√
√
nd
√
nd
Others
√
√
√
nd
√
nd
Passenger don’t give information
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
Maju
√
Handal Indah
√
S&S
√
GML Line
nd
Triton
√
City Bus
nd
Note: nd = not done by bus operators, √= yes, X= no
No
nd nd
62 Table 4.19: Type of data collected from operational activities Description
Maju
Handal S & S
GML
Indah
Line
Passenger load factor
√
√
Passenger per trip
√
√
Passenger volume
√
√
Passenger by route
√
√
Bus fare
√
√
Ticket sold by route
√
No. of trip by route Overall data by
√
nd
Triton
City Bus
√
nd
nd √
nd
nd
√
nd
nd
√
nd
√
nd
√
nd
√
√
nd
√
nd
X
√
X
nd
X
nd
X
X
X
nd
X
nd
Bus breakdown
√
√
√
nd
√
nd
Miss schedule
√
√
X
nd
X
nd
Safety on board
√
√
nd
√
nd
Others
X
X
nd
X
nd
monthly / annually
X
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
S&S
GML
Triton
City Bus
Indah 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
S&S
GML
Triton
City Bus
Indah 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
X
X
X
nd
X
nd
X
X
X
nd
X
nd
Outsource / consultation Others
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
S&S
Indah
GML
Triton
City Bus
Line
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.
66 Table 4.25: Receiver of the operational report Description
Maju
Handal
S&S
Indah Customer service
GML
Triton
City Bus
Line
√
√
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
manager
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
S&S
Indah
GML
Triton
City Bus
Line
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
67 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 Bus operators
Yes
Action Plan by company No
Yes
Maju
√
√
Handal Indah
√
√
S&S
X
GML Line
nd
Triton
√
City Bus
nd
Nd
No
X nd
nd X
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
68 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
71 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.
72
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
REFERENCES
Alexis Morgan. (2006). WWF Standards of Conservation Project and Programme Management. Canada: Foundation of Success. Asuman Dogac, M. Tamer Özsu, Ozgur Ulusoy. (1999). Current Trends in Data Management Technology, Canada: Idea Group Publishing. Bluman, Allan G. (2000). Elementary Statistics: A Step By Step Approach. Statistics, Boston: McGraw-Hill, A Brief version. Cooper, W. W., L. M. Seiford, and J. Zhu. (2004). Handbook on data development analysis, Boston, MA: Kluwer Academic Publishers. Edward Vanden Berghe, National Oceanic and Atmospheric Administration, Annual Conference. September 24-26, 2007, Flanders Marine Institute (VLIZ), Belgium. NOAA. 2006. 45-52 Globe Logo. (2003). ESRI—The World Leader in GIS, issue no: 03 Hassan A. Karimi, Amin Hammad. (2004). Telegeoinformatics: Location-based Computing and Services. California: CRC Press Higgins, J. (2005). Ecoregional Toolbox - Standard 3: Use a consistent data management framework in accordance with internal and partner organization data standards. The Nature Conservancy.
Irwin M. Jarett. (1983). Graphics and Reporting Financial Data. Michigan:Wiley.
76
Jiawei Han, Micheline Kamber. (2006). Data Mining: Concepts and Techniques : Morgan Kaufmann John Sutton. (2005). Advanced GIS Applications in TransitCase Studies of Five Large Transit AgenciesTransportation: Cambridge Systematic Lau Too Kya, Zainuddin Awang. (2002). Statistik asas UiTM. 10th Edition. Malaysia: Fajar Bakti, Sdn. Bhd. Pp 6-15. Malaysia Quality of Life Report (2002), Government of Malaysia. Margoluis, R. and Salafsky, N. (1998). Measures of Success: Designing, Managing, and Monitoring Conservation and Development Projects. Island Press Michael S. Lewis-Beck. (1995). Data Analysis: An Introduction.Ohio: SAGE Ministry of Entrepreneurship and Cooperative Development. (2005 and 2006) Report. Kuala Lumpur: MECD
Annual
Pang-Ning Tan, Michael Steinbach, Vipin Kumar. (2005). Introduction to Data Mining : Pearson Addison Wesley. Partnership for Sustainable Urban Transport in Asia (PSUTA): Asian Development Bank, Clean Air Initiative for Asian Cities, Swedish International Development Cooperation Agency (Sida), Australia : World Resources Institute. Ralph Kimball. (1996). The Data Warehouse Toolkit: Practical Techniques for Building
Dimensional Data Warehouses. Michigan: John Wiley & Sons.
Road Transport Department, Malaysia, 2007. Robert J. Thierauf. (1991). Executive Information Systems: A Guide for Senior Management and MIS Professionals. Michigan: John Wiley & Sons.
77
Rob Mattison, Robert M. Mattison. (1996).Data Warehousing: Strategies, Technologies, and Techniques. McGraw-Hill Robert P. Odenweller. (1998). Data Management Guide. Canada: Idea Press. Susanne Prokscha. (2006). Practical Guide to Clinical Data Management. California: CRC Press. Technical report (2002). Transport Traffic Management Unit, Local Plan Research, Johor Bahru. Jabatan Perancangan Bandar dan Desa Selatan. William H. Inmon. (2005). Building the Data Warehouse, Michigan: John Wiley and Sons.
WEBSITE Matt Lythe. (2005). Succeess Story of New Zealand Post. http://www.nzpost.co.nz/Cultures/en.NZ/ Handal Indah Sendirian Berhad. (2008). Customer feedback form http://www.handalindah.com.my/feedback.php
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 ii.
□ No
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 iv.
□ Annually □ Other, please specify__________
How you collect passenger feedbacks; (Please tick more than one if any)
□ Customer complaint form □ Passenger survey □ SMS / telephone
□ On-line / website complaint form □ Suggestion box in every bus □ Other, please specify___________
79 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 vii.
□ No
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 □ Safety on board □ Punctuality □ Driver attitude □ Noisiness □ Gender and age □ Occupation □ Lost and found item
□ Seat conditions □ Schedule/frequency □ Bus route □ Reliability
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_______________
80 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 □ Submit to authority ii.
□ Kept in the file (for reference only) □ Other, please specify____________
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___________
81 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 ii.
□ No
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
82 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 □ Not trained / experience □ Other, please specify___________
□ Limited budget □ Less manpower
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_______________
83 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 □ Submit to authority ii.
□ Kept in the file (for reference only) □ Others, please specify____________
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) _________
84 7. Company strategies and action plans. i.
ii.
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___________ 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 iv.
□ No
Any action plan taken from findings in the reports?
□ Yes
□ No
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
720105-01-5731_ (NEW IC NO./PASSPORT NO.)
Date
NOTES: *
: 12th November 2008
________________________________ SIGNATURE OF SUPERVISOR
DR.MUHAMMAD ZALY SHAH NAME OF SUPERVISOR
Date
: 12th November 2008
If the project paper is CONFIDENTIAL or RESTRICTED, please attach with the letter from the organisation with period and reasons for confidentially or restriction
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
iii
“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
iv
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.
v
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.
vi
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 lainlain bandaraya di negara-negara membangun.
vii
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 1
PAGE
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
2
TITLE
PAGE
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 2.5.5 2.5.6 2.6
24
ITS case study 1 - Improvement in Denmark Rail Services using ITS
26
ITS case study 2 - Buses Tracked in Denmark
27
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
2.9
2.10
32
Importance of data management to CEO/ Executive and Planners
33
2.9.1
34
Application of EIS
Contribution of data management to public transportation 36 2.10.1 Key benefits of the data management in public Transportation
36
x CHAPTER
3
TITLE
PAGE
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
CHAPTER
43
TITLE
4
PAGE
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
4.1.8 4.1.9
49
Information collects by bus operators from passenger
50
Record keeping
52
4.1.10 Purpose of bus operators collect data on passenger opinion 4.1.11 Activity after collected the passenger data
52 53
4.1.12 Use of collected passenger’s data by bus operators 53
xi 4.1.13 Receiver of the complete passenger’s opinion reports 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
4.2.7
4.3
60
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
Conclusion
67
CHAPTER
TITLE
5
55
PAGE
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. Table 1.1
TITLE
PAGE
Current public bus operators and number of bus routes in Johor Bahru City
Table 1.2
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
xiii 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
8,615
8,976
License Issued
519
361
Complaint
775
724
Warning
204
127
Compound
123
200
Suspension
2
13
Termination
0
1
Total registered stages bus
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
Public transport
per 1000 population
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
Area of study Johor Bahru 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.
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
PROCESS OF DATA MANAGEMENT
Data Collection
Data Analyse
Data Entry
1st Qtr 2nd Qtr
Data Reporting
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).
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. Computerbased 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
Check the raw data and prepare data for analysis
Conduct additional analyses based on initial results
Data analysis
Conduct initial analysis base on the evaluation plan
Integrated and synthesize findings
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.
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-today 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.
21 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.
25 ii.
Better travel information At home, at work, or on the road, travellers have access to real-time, up-todate 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.
26 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.
29
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.
31 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 semimanufactures. 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
Population Respondents (All Public bus operators)
Trip/operational activities Passenger’s opinion
Data management Existing / current practice
Factors effects the data collection
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
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.
Bus Operator Data Management Survey
Part A
Data Collection (Passenger Opinion)
Part B
Data Collection (Operational)
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.
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
Maju
√
Handal Indah
√
S&S
√
GML Line
√
Triton
√
City Bus
No
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
Maju
√
Handal Indah
√
No
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
S&S
Indah Customer complaint form On-line
/website
complaint form Passenger survey
GML
Triton
Line
City Bus
√
√
√
√
√
nd
X
√
X
X
X
nd
√
√
X
X
X
nd
√
X
X
X
nd
Suggestion box 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
Maju
√
Handal Indah
√
S&S
√
GML Line
No
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
S&S
Indah Passenger
don’t
GML
Triton
Line
City Bus
√
√
√
√
√
nd
Limited budget
X
X
X
X
X
nd
Not trained
√
√
X
X
X
nd
Less manpower
√
√
X
X
X
nd
√
√
X
√
√
nd
√
√
√
√
√
nd
give information
Time
limitation
with passenger Others
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
S&S
Indah
GML
Triton
City Bus
Line
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
Nd
nd
nd
City Bus
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
Own use and analysis Market study /
Handal
S&
GML
Indah
S
Line
√
√
√
√
√
nd
√
√
X
√
√
nd
X
X
X
X
X
nd
X
X
X
X
X
nd
new investment For authority (LPKP,MBJB,JPJ) Others
Triton
City Bus
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
S&S
GML
Indah
Triton
City Bus
Line
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
Triton
City Bus
Description
Maju
Handal Indah
GML
S&S
Line
Manual
X
X
√
√
√
nd
Software
√
√
X
X
X
X
Outsource
X
X
X
X
X
X
Others
X
X
X
X
X
X
Triton
City Bus
Note: nd = not done by bus operators, √= yes, X= no
Table 4.11: Use of data collected by public bus operators Maju
Handal
S&S
Indah
GML Line
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
service
√
√
X
X
X
nd
Planning
X
X
X
X
X
nd
Operation manager
X
√
√
√
√
nd
Executive management
√
√
√
√
√
nd
CEO
X
X
X
X
X
nd
Others
√
√
X
√
√
nd
Customer manager Traffic
/
manager
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 Bus operators
Yes
No
Action Plan by company 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
Maju
√
Handal Indah
√
S&S
√
GML Line
No
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
Maju
√
Handal Indah
√
S&S
√
GML Line
No
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
S&S
Indah
GML
Triton
Line
City Bus
√
√
√
nd
√
nd
Limited budget
X
X
X
nd
X
nd
No experience
√
√
X
nd
X
nd
Less manpower
√
√
√
nd
√
nd
Others
√
√
√
nd
√
nd
Passenger don’t give information
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
Maju
√
Handal Indah
√
S&S
√
GML Line
nd
Triton
√
City Bus
nd
Note: nd = not done by bus operators, √= yes, X= no
No
nd nd
62 Table 4.19: Type of data collected from operational activities Description
Maju
Handal S & S
GML
Indah
Line
Passenger load factor
√
√
Passenger per trip
√
√
Passenger volume
√
√
Passenger by route
√
√
Bus fare
√
√
Ticket sold by route
√
No. of trip by route Overall data by
√
nd
Triton
City Bus
√
nd
nd √
nd
nd
√
nd
nd
√
nd
√
nd
√
nd
√
√
nd
√
nd
X
√
X
nd
X
nd
X
X
X
nd
X
nd
Bus breakdown
√
√
√
nd
√
nd
Miss schedule
√
√
X
nd
X
nd
Safety on board
√
√
nd
√
nd
Others
X
X
nd
X
nd
monthly / annually
X
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
S&S
GML
Triton
City Bus
Indah 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
S&S
GML
Triton
City Bus
Indah 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
X
X
X
nd
X
nd
X
X
X
nd
X
nd
Outsource / consultation Others
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
S&S
Indah
GML
Triton
City Bus
Line
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.
66 Table 4.25: Receiver of the operational report Description
Maju
Handal
S&S
Indah Customer service
GML
Triton
City Bus
Line
√
√
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
manager
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
S&S
Indah
GML
Triton
City Bus
Line
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
67 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 Bus operators
Yes
Action Plan by company No
Yes
Maju
√
√
Handal Indah
√
√
S&S
X
GML Line
nd
Triton
√
City Bus
nd
Nd
No
X nd
nd X
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
68 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
71 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.
72
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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WEBSITE Matt Lythe. (2005). Succeess Story of New Zealand Post. http://www.nzpost.co.nz/Cultures/en.NZ/ Handal Indah Sendirian Berhad. (2008). Customer feedback form http://www.handalindah.com.my/feedback.php
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 ii.
□ No
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 iv.
□ Annually □ Other, please specify__________
How you collect passenger feedbacks; (Please tick more than one if any)
□ Customer complaint form □ Passenger survey □ SMS / telephone
□ On-line / website complaint form □ Suggestion box in every bus □ Other, please specify___________
79 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 vii.
□ No
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 □ Safety on board □ Punctuality □ Driver attitude □ Noisiness □ Gender and age □ Occupation □ Lost and found item
□ Seat conditions □ Schedule/frequency □ Bus route □ Reliability
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_______________
80 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 □ Submit to authority ii.
□ Kept in the file (for reference only) □ Other, please specify____________
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___________
81 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 ii.
□ No
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
82 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 □ Not trained / experience □ Other, please specify___________
□ Limited budget □ Less manpower
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_______________
83 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 □ Submit to authority ii.
□ Kept in the file (for reference only) □ Others, please specify____________
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) _________
84 7. Company strategies and action plans. i.
ii.
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___________ 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 iv.
□ No
Any action plan taken from findings in the reports?
□ Yes
□ No
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