the scientometric, social network and scientographic analysis of

THE SCIENTOMETRIC, SOCIAL NETWORK AND

SCIENTOGRAPHIC ANALYSIS OF AN

INDUSTRIAL ENGINEERING DEPARTMENT

MATHIAS DHARMAWIRYA

WEE KIM WEE

SCHOOL OF COMMUNICATION AND INFORMATION

2007

The Scientometric, Social Network and Scientographic Analysis of an

Industrial Engineering Department

Mathias Dharmawirya

Wee Kim Wee School Of Communication and Information

A thesis submitted to the Nanyang Technological University

in fulfilment of the requirement for the degree of

Master of Science

2007

Abstract

i

ABSTRACT

This dissertation examines the twenty-year publication output (from 1986 to 2005) of the

National University of Singapore Industrial Engineering Department (NUS-ISE) based on three

perspectives namely scientometrics, social network analysis, and multidimensional scaling. The

scientometrics perspective allows the evaluation of the productivity and impact of the NUS-ISE

faculties, as well as the collaboration trend in publishing, while the social network analysis and

multidimensional scaling techniques allow a holistic understanding of the evolutions of the NUS-

ISE co-authorship networks and the disciplinary roots of NUS-ISE.

The raw publication data were retrieved from the Institute of Scientific Information’s

Web of Science® and the NUS-ISE website. The data were analysed on annual basis for

scientometrics perspective, and on four different time windows (1986-1995, 1991-2000, 1996-

2005, and 1986-2005) for social network analysis and multidimensional scaling. The network

parameters and visualisation were done using UCINET, while the bibliographic maps derived

from multidimensional scaling were constructed using SPSS’s ALSCAL.

From the scientometrics point of view, NUS-ISE produced 324 publications in the

twenty-year period with an average 2.54 authors per publication. 212 unique authors were

involved in the 324 publications; however 57% of them published only once. Most of NUS-ISE

publications were produced collaboratively with less than 15% single-authored publications.

These collaborations were mostly done among researchers within the department (35%), but

international collaborations were also favoured (30%). Each NUS-ISE publication received 4.15

citations on average; with the 45% of the publications receiving 2 to 9 citations and 28%

receiving none.

Social network analysis on the co-authorship networks indicate that although most

authors are included in the main component, the network is very loose. This is shown with the

average number of direct connections each node has at 7.8, while the maximum possible

connection is 211. However, the nodes in the network can reach any other node within an average

of 3.2. This indicates the existence of nodes which are very central. An examination of degree

centrality, closeness, and betweenness of the nodes identifies a number of nodes which are the

most central. In reality, these nodes are the people who play important roles in both the NUS-ISE

department as well as the industrial engineering field as a whole. Some roles assumed are head of

department, director of research groups, editor, and associate editors of journals.

Finally, the multidimensional scaling technique allows the mapping of disciplinary root of

the industrial engineering field in NUS-ISE based on journal co-citation analysis. Over the 4

different time windows, five disciplines consistently appear. The five disciplines are (1) statistics

Abstract

ii

and probability; (2) quality reliability; (3) electrical engineering; (4) environmental science and

economics; and (5) operations research and management science. These disciplines closely match

the research interests of the NUS-ISE. The first two disciplines are covered under the Quality

Engineering research group, while the third and fourth discipline under Systems Engineering

research group and finally the fifth discipline are covered under Engineering Management

research group. The consistent appearance of the five disciplines also indicates that industrial

engineering is a maturing discipline or a normal science in Kuhnian sense.

Acknowledgments

iii

ACKNOWLEDGEMENTS

First of all, I would like to thank my supervisor who at the same time has become a kaki,

Mr Lee Chu Keong for his continuous guidance, advices, and suggestions. His insights and ideas

have been essential in the development of this dissertation.

I would also like to thank my family and friends especially my parents for their

continuous support, encouragement, and love not only throughout the dissertation development

but throughout my whole life. For Amri and Francy, thanks for the chats and discussions. For

Linda, thanks for her care, companionship, and understanding.

Finally and ultimately, I would like to express my gratitude to my God and Saviour, Jesus

Christ. Praise and glory be to Him!

Table of Contents

iv

TABLE OF CONTENTS

ABSTRACT ...................................................................................................................................... i

ACKNOWLEDGEMENTS ............................................................................................................iii

TABLE OF CONTENTS ................................................................................................................ iv

LIST OF TABLES .........................................................................................................................vii

LIST OF FIGURES.......................................................................................................................viii

CHAPTER ONE INTRODUCTION ............................................................................................... 1

Introduction to the Department of Industrial and Systems Engineering, ..................................... 4

National University of Singapore................................................................................................. 4

Motivation of the Research .......................................................................................................... 4

Research Objectives.....................................................................................................................5

Organisation of the Dissertation................................................................................................... 6

CHAPTER TWO LITERATURE REVIEW.................................................................................... 7

Scientometrics Review.................................................................................................................7

Scientometrics of the International Journal Scientometrics.....................................................7

Twenty-five years of the Journal of Economic Psychology (1981–2005): A report on the

development of an interdisciplinary field of research.............................................................. 8

Bibliometric Overview of Library and Information Science Research in Spain .....................9

A Bibliometrics Analysis of Physics Publications in Korea, 1994-1998 ..............................10

Who’s Who in Conservation Biology—an Authorship Analysis ..........................................12

Social Network Analysis Review...............................................................................................12

Who is the best connected scientist? A study of scientific co-authorship networks..............13

International Mechanics Collaboration in 30 Countries ........................................................14

The Structure of Scientific Collaboration Networks in Scientometrics.................................15

Collaboration Analysis in Recommender Systems Using Social Networks..........................16

Analyzing and Visualizing Criminal Network Dynamics: A Case Study .............................17

Multidimensional Scaling Review .............................................................................................17

Journal as Markers of Intellectual Space: Journal Co-citation Analysis of Information

Retrieval Area, 1987-1997.....................................................................................................18

Visualizing a Discipline: An Author Co-Citation Analysis of Information Science, 1972–

1995 .......................................................................................................................................19

Research Fronts in Library and Information Science in Spain (1985-1994) .........................20

The Social and Collaborative Nature of Entrepreneurship Scholarship: A Co-Citation and

Perceptual Analysis ...............................................................................................................20

Table of Contents

v

Other Studies .........................................................................................................................21

Summary ....................................................................................................................................21

CHAPTER THREE METHODOLOGY........................................................................................22

Data Sources ..............................................................................................................................22

Bibliographic Records Retrieval Methods .................................................................................22

Scientometrics............................................................................................................................23

Literature Growth ..................................................................................................................23

Degree and extent of collaboration........................................................................................24

Prolific authors.......................................................................................................................25

Reference and Citation Counts ..............................................................................................26

Journal Impact Factor ............................................................................................................26

Social Network Analysis............................................................................................................27

General Parameters................................................................................................................28

Density...................................................................................................................................28

Distance .................................................................................................................................29

Centrality ...............................................................................................................................29

UCINET (Version 6.0) ..........................................................................................................31

Multidimensional Scaling ..........................................................................................................32

Selection of journals and construction of raw co-citation matrices .......................................32

Conversion to correlation matrix ...........................................................................................32

Multidimensional scaling analysis.........................................................................................32

Summary ....................................................................................................................................33

CHAPTER FOUR RESULT AND DISCUSSION........................................................................34

Scientometrics............................................................................................................................34

Publication Growth................................................................................................................34

Co-authorships.......................................................................................................................35

Extent of Collaboration..........................................................................................................40

Prolific Authors .....................................................................................................................42

Reference and Citation Counts ..............................................................................................44

Journal Impact Factor ............................................................................................................47

Social Network Analysis............................................................................................................48

General Parameters................................................................................................................48

Density...................................................................................................................................49

Distance .................................................................................................................................49

Centrality ...............................................................................................................................50

Table of Contents

vi

Visualisation using UCINET (Version 6.0)...........................................................................51

Multidimensional Scaling ..........................................................................................................54

Limitations of the Research .......................................................................................................59

CHAPTER FIVE CONCLUSION AND FUTURE WORK..........................................................60

Future Work and Recommendation ...........................................................................................61

REFERENCES...............................................................................................................................62

APPENDICES..............................................................................................................................A-1

APPENDIX A Publications of NUS-ISE from 1986 to 2005 indexed in Web of Science® ........A-1

APPENDIX B Publications of NUS-ISE from 1986 to 2005 not indexed in Web of Science®.A-25

APPENDIX C Authors List for NUS-ISE Publications.........................................................A-28

APPENDIX D Journal List for NUS-ISE Publications .........................................................A-33

APPENDIX E Authors outside the main component of NUS-ISE co-authorship networks .A-35

APPENDIX F Degree, Closeness, and Betweenness Centralities of Authors .......................A-37

List of Tables

vii

LIST OF TABLES

Table 4.1 Yearly publication growth at NUS-ISE, NUS-ECE, and NTU-EEE ………………….34

Table 4.2 Annual co-authorship levels at NUS-ISE………………….………………….………. 36

Table 4.3 Annual co-authorship levels at NUS-ECE ……………….………………….………... 36

Table 4.4 Annual co-authorship levels at NTU-EEE ………………….………………….……... 37

Table 4.5 Distribution of number of authors per publication at NUS-ISE, NUS-ECE,

and NTU-EEE………………….………………….……….………………….………………… 37

Table 4.6 Average number of authors per publication at NUS-ISE, NUS-ECE, and NTU-EEE.. 38

Table 4.7 Measures of degree of collaborations at NUS-ISE, NUS-ECE, and NTU-EEE ………40

Table 4.8 Extent of collaborations at NUS-ISE, NUS-ECE, and NTU-EEE …………………….40

Table 4.9 International Collaborators of NUS-ISE ……………………………………………… 41

Table 4.10 Local Collaborators of NUS-ISE ……………………………………………………. 41

Table 4.11 Top 10 authors based on whole counting …………………………………………….43

Table 4.12 Top 10 authors based on fractional counting ………………………………………... 43

Table 4.13 Top 10 authors based on first-author counting ……………………………………… 44

Table 4.14 Reference Counts at NUS-ISE, NUS-ECE, and NTU-EEE ………………………… 44

Table 4.15 Annual Reference Counts at NUS-ISE, NUS-ECE, and NTU-EEE …………………45

Table 4.16 Citation counts at NUS-ISE, NUS-ECE, and NTU-EEE …………………………….46

Table 4.17 Top 10 impact articles published by NUS-ISE ……………………………………… 47

Table 4.18 Top 10 popular journals at NUS-ISE ………………………………………………... 48

Table 4.19 General parameters of NUS-ISE co-authorship networks ………………................... 49

Table 4.20 Density of NUS-ISE co-authorship networks ……………………………………….. 49

Table 4.21 Distances in NUS-ISE co-authorship networks ……………………………………... 50

Table 4.22 Average degree centrality of NUS-ISE co-authorship networks ……………………. 50

Table 4.23 Top 10 central authors at NUS-ISE …………………………………………………. 51

Table 4.24 Average closeness centrality of NUS-ISE co-authorship networks ………………… 51

Table 4.25 Average betweenness centrality of NUS-ISE co-authorship networks ………………51

Table 4.26 Top 30 most cited journals – 1986-1995 ………………….………………….………54




List of Figures

viii

LIST OF FIGURES

Figure 1.1 A taxonomy for classes of MDA methods ……………………………………………..3

Figure 2.1 Steps of Author Co-citation Analysis ………………………………………………... 19

Figure 3.1 Density and inclusiveness comparisons ………………………………………………29

Figure 3.2 Paths and distances ……………………………………………………………………29

Figure 3.3 Degree centrality and closeness ……………………………………………………… 31

Figure 4.1 Annual publication counts at NUS-ISE, NUS-ECE, and NTU-EEE …………………35

Figure 4.2 Degree of collaborations at NUS-ISE, NUS-ECE, and NTU-EEE ………………….. 38

Figure 4.3 Comparison of mean numbers of authors per publication …………………………… 39

Figure 4.4 Comparison of extent of collaboration at NUS-ISE, NUS-ECE, and NTU-EEE …… 42

Figure 4.5 Comparison of citations received by NUS-ISE, NUS-ECE, and NTU-EEE………….46

Figure 4.6 NUS-ISE co-authorship networks in the period of 1986-1995 ……………………….52




Figure 4.10 Bibliographic map of NUS-ISE – 1986-1995 ……………………………………….57




Chapter One - Introduction

1

CHAPTER ONE

INTRODUCTION

If science is the constellation of facts, theories and methods collected in current texts,

then scientists are the men who, successfully or not, have striven to contribute one or another

element to that particular constellation (Kuhn, 1970). One of the roles that scientists play in

contributing to the constellation is to act as literary reasoners, or the transformation of laboratory

reason. In other words, scientists produce scientific papers as the end-product of scientific

research (Knorr-Cetina, 1981).

Why do scientists need to assume the role of literary reasoners? Why do scientists publish

scientific papers? Merton (1973) mentioned that the ethos of modern science is consist of

universalism, communism, disinterestedness, and organized scepticism. Communism as one

element of scientific ethos means that scientific knowledge is part of the public domain. Merton

further argued that scientists depend upon a cultural heritage; and scientific advance is a result of

collaboration between past and present generations, echoing Newton’s ‘If I have seen farther it is

by standing on the shoulder of giants’ remark. As a result, it is only imperative for scientists to

communicate their research findings. But, that is not the only reason for scientists to publish

scientific papers. Hagstrom (1965) observed that scientists in scientific communities compete

among themselves for reputation. The determination of the prestige of a scientist is affected

heavily by articles productivity and number of citations received (Hagstrom, 1971). So, scientists

also publish because publishing scientific papers will cause them to be recognised and enable

them to grow their reputation (Jeremy, 2006).

Singapore is a country that is very committed to the development of science and

technology. PM Lee Hsien Loong, in his Budget Speech 2006, stated the intention of developing

Singapore into a knowledge hub. PM Lee further mentioned that R&D is the foundation upon

which Singapore’s competitiveness will be built and a new R&D Trust Fund would be

established. The Singapore Government injected S$500 million into the newly set up R&D Trust

Fund in 2006 and targeted S$5 billion by 2010 and S$30 billion by 2015. While acknowledging

that R&D is about experimentation and taking risks, PM Lee stressed the importance of assessing

the projects where the money is allocated.

Given the need of accomplishing the ‘value for money’ principle, it is clear that scientific

projects must be systematically and continuously evaluated and monitored. The measurement on

science has traditionally been conducted qualitatively by scientists themselves. The information

was provided through qualitative analysis (e.g. the peer review system) by well-informed experts.

However, this approach was considered prone to subjectivity. So, Tijssen (1992) stated that more


2

reliable methods of generating sources of information on science were needed, sources that could

identify, compare, and evaluate relevant aspect of the input, throughput, and output of scientific

work in a more objective (i.e. quantitative) manner.

Tijssen (1992) further discussed three aspects in which quantitative measurements are

concerned about:

• The economic aspects. The amount and distribution of human and financial resources.

• The knowledge, ideas, and research methods. The connection between science and its social

and economic aspects of societies.

• The scientific output in terms of research publications.

The practice of using research publications for quantitative science measurement is called

bibliometric or scientometrics. According to Tijssen (1992), research publications contain the

main aspects of research activity:

• The products. The size of scientific activities reflected in the output of research publications.

• The process. The transfer of knowledge among scientists. This is reflected in the

bibliographic references (the citation process) of an article in which an article’s authors

acknowledge prior scientific work that has contributed to the authors’ research activity.

• The structure. The social and cognitive network of science reflecting the relational aspects of

science (e.g. co-authorship, co-citation journals).

These bibliometric data are further analysed to obtain a more compact description of data

which is characterised by a few quantitative variables. Tijssen (1992) discussed that the analytical

procedure of bibliometric data can be differentiated into univariate, bivariate and multivariate data

analyses. Gross & Gross (1927) applied the univariate data analysis in grading of scientific

journals. They used the number of citations given to a journal as the only variable in determining

the significance of different scientific journals. Garfield (1972) made use of two bibliometric data,

citations and publications, to derive the concept of ‘impact factor’. He formulated a computational

formula involving the two variables to derive the value of a journal impact factor. His procedure

can be described as bivariate data analysis.

Pinski and Narin (1976) introduced the concept of ‘influence weight’ which is derived

from the number of citations received and number of references given out by a particular journal.

This influence of a journal was then derived based on the influence weight and publications. This

analysis which concerns about three or more variables is called multivariate data analysis

(MDA). Tijssen and De Leeuw (1988) explained that the goal of MDA is to simultaneously

represent the relations between multiple variables of each entity. They further noted that there is

not only one MDA method; however, researchers tend to neglect the process of extensive search


3

of the most appropriate MDA method. Figure 1.1 summarises the different classes of MDA

methods. Metric multidimensional scaling is the MDA method used in this dissertation.

Figure 1.1 A taxonomy for classes of MDA methods (adapted from Tijssen, 1992)

The results of univariate, bivariate and multivariate data analyses may not be meaningful

for the people looking at them, hence they need to be visualised so that the data can be interpreted

with as little effort as possible. Representing results of univariate and bivariate data analyses can

be easily done using two-dimensional graphical displays (e.g. bar charts, pie charts, line graphs),

and this practice has been well accepted by both the scientific community as well as the general

public (Tijssen, 1992).

However, the multidimensional character of the outcome of MDA creates representational

problems. Hence, spatial representations (i.e. bibliographic maps) are used to visualise the pattern

of the multivariate data for ease of interpretation (Tijssen, 1992). Vladutz, then ISI’s manager of

basic research, coined the term ‘scientography’ for bibliographic map reflecting the derivation of

mapping from the field of scientometrics and the geographic focus of the map as cited by Garfield

(1986). Small and Garfield (1985) generated disciplinary maps using multidimensional scaling

method based on clusters of co-cited publications derived from the combined use of fractional

citation counting and co-citation frequency.

MDA methods

Dependence MDA methods

Dependence/ Interdependence MDA methods

Interdependence MDA methods

One dependent variable

Multiple dependent variables

One or more dependent variables

Multiple dependent variables

Multiple-Regression, Correlation

Metric

Discriminant analysis,

Probit analysis

Multivariate analysis

of variance

Canonical correlation

analysis

Structural equations models,

Path analysis

Latent structure analysis

Factor analysis, Principal

Components Analysis

Metric Multi-

dimensional scaling

Cluster analysis

Loglinear analysis

Non-metric Multi-

dimensional scaling

Non-metric Principle

Components Analysis

Nonmetric Metric Nonmetric Nonmetric Nonmetric Metric Metric


4

Introduction to the Department of Industrial and Systems Engineering,

National University of Singapore

In 1972, the Department of Industrial & Systems Engineering (ISE) was established as

one of the five departments in the Faculty of Engineering of National University of Singapore.

The department offers an undergraduate degree programme leading to BEng degree and graduate

programmes leading to MSc, MEng and PhD degrees. It produced its 1000th MSc graduate in

2003.

The NUS-ISE consists of three research groups of (1) Engineering Management; (2)

Quality Engineering; and (3) Systems Engineering, within the groups there are 23 faculty

members, 80 PhD students, and 24 MEng students. To facilitate scientific research, the

department provides six research centres and laboratories of (1) Quality and Innovation Research

Centre; (2) Computing Laboratory; (3) Ergonomics Laboratory; (4) Quality and Reliability

Engineering; (5) Simulation Laboratory; and (6) Systems Modelling and Analysis Laboratory. In

addition to academic and research activities, the department also provides series of short courses

for industry practitioners.

A number of faculty members of NUS-ISE have achieved distinctions in their respective

academic fields. Among them are IEEE's Engineering Management Educator of the Year Award,

Best Paper Award for the 19th Asia Quality Symposium, and the most outstanding technical paper

at the 2004 Reliability and Maintainability Symposium (RAMS). In addition, one of its faculty

members is an IEEE Fellow.

Motivation of the Research

Scientometrics studies have been done a couple of Singapore local academic institutions,

such as studies on NUS Department of Economics (Ng, 2004), Nanyang Business School and

INSEAD (Wee, 2006). However, there has been completely no scientometrics study on the NUS

Department of Industrial & Systems Engineering. This dissertation studies the scientific outputs

produced by the NUS-ISE from 1986 to 2005 in comparison with an earlier study by Ang, Lee,

and Tng (2006), in which they retrieved the bibliometric data from the Institute of Scientific

Information’s Web of Science® from 1990 to 2004 to examine the scientific output of two local

academic institutions: (1) NUS Department of Electrical and Computer Engineering; and (2) NTU

School of Electrical and Electronics Engineering.

In every organization, the leader plays a very important role. This dissertation investigates

whether the authorships rank in NUS-ISE reflects the leadership roles in the department. In

addition, this dissertation also investigates whether the leading figures in NUS-ISE also play

significant roles in industrial engineering field as a whole.


5

Finally, NUS-ISE claims on its website (NUS Industrial and Systems Engineering

Department, 2006) that its domain knowledge is derived from combinations of engineering,

mathematics, statistics, computing and social sciences. This dissertation examines this claim and

at the same time finds out the disciplinary roots that construct the scientific community of NUS-

ISE. Hence, a scientographic study based on the scientific outputs of the NUS-ISE would be an

interesting area to study to verify the accuracy of its claim.

Research Objectives

The objective of the dissertation is to study extensively the scientific outputs of NUS-ISE

for a twenty-year time window from 1986 to 2005 and to find out the disciplinary roots of the

industrial engineering field using scientometrics techniques and one of the MDA methods,

namely multidimensional scaling (MDS).

Bibliometric data will be retrieved from the Institute of Scientific Information’s Web of

Science®. The following will be studied using the scientometrics techniques:

a. Literature growth

b. Average number of authors per paper

c. Average number of papers per author

d. The extent of collaboration based on the Collaborative Index (CI), Degree of

Collaboration (DC), and the Collaboration Coefficient (CC)

e. Type of collaboration

f. Most productive authors and the different productivity profile

g. Most popular journals in term of frequency of publications

h. Most prestigious journals in term of Journal Impact Factor

i. Number of references per article

j. Number of citations received per article

Based on the authorships bibliometric data, the co-authorship networks will be

constructed and analysed using social network analysis method. The size of main component,

inclusiveness, and the density of the network will be investigated. In addition, the geodesic

distances among authors and the centrality of each author in the network will be analysed.

Scientographic technique, the multidimensional scaling, will then be used to map the

disciplinary roots of the scientific outputs of NUS-ISE from the perspective of the scholarly

communication media (i.e. journals).

Both the social network analysis and the multidimensional scaling will be applied into

three overlapping time windows of 10 years (1986-1995, 1991-2000, and 1996-2005) and a single


6

overall time window of 20 years (1986-2005). This is to investigate how the co-authorship

networks and the bibliographic maps evolve over the years.

Organisation of the Dissertation

This dissertation is divided into five chapters. Chapter One describes the reasons why

scientists have been continuously publishing their research outputs, why it is imperative to have

proper methods in evaluation research outputs, provides a short summary of two types of analysis,

qualitative and quantitative, that have been used to measure the scientific outputs, and outlines the

motivation and objectives of the dissertation. Chapter Two provides reviews of past researches

that introduced and applied the scientometrics, social network, and scientographic techniques in

analysing bibliometric data. Chapter Three describes the data source and the methods used for

obtaining as well as analysing the bibliographic data using scientometrics, social network, and

scientographic techniques. Chapter Four presents the results and analyses of the data, and finally

conclusions and future research recommendations are presented in Chapter Five.

Chapter Two - Literature Review

7

CHAPTER TWO

LITERATURE REVIEW

This chapter discusses the three perspectives used in this dissertation, namely

scientometrics, social network analysis, and multidimensional scaling. Each perspective’s short

history is presented and how the three perspectives have been applied in prior studies will be

reviewed.

Scientometrics Review

The term scientometrics was first introduced by Vassily V. Nalimov in 1969. The term

was mainly used to address all study related to the literature of science and technology (Hood and

Wilson, 2001). The term became more popular with the foundation of the journal Scientometrics

in 1978 by Tibor Braun. It is now often defined as the quantitative study of science and

technology.

Scientometrics and bibliometrics have some overlapping techniques. However, they are

not the same, bibliometrics focus mainly on the analysis of literary outputs, while scientometrics

is not restricted to analysing the literary outputs. Hood and Wilson (2001) noted practices of

scientists, structures of organisations, research policy and management, the impact of science and

technology in the economy among the topics that can be analysed.

Scientometrics techniques have been applied in different level of aggregations such as

field study in the international, national, or organisational levels, journal study, and even

individual figures level. Prior applications of scientometrics techniques in some of the different

levels of aggregation will be reviewed.

Scientometrics of the International Journal Scientometrics

Dutt, Garg, and Bali (2003), examined 1,317 publications in the first 50 volumes of

Scientometrics from 1978 to 2001. The authors focused on research articles and excluded letters

to the editor, bibliographies, meeting abstracts, news and notes, editorials, obituaries, and

commentary to Derek De Solla Price awards. Data about year and volume of the publication,

author, total number of authors, institutional affiliation, number of institutions, country, number

of countries, type of collaboration, and theme of each research article were collected. All of the

research articles were the classified into seven groups, namely (1) scientometrics assessment; (2)

citation and cluster analysis; (3) scientometrics distribution; (4) history of science; (5) scientific

collaboration; (6) theoretical studies on scientometrics; and (7) others. In their analysis, Dutt,


8

Garg, and Bali divided the research articles into three blocks of time window, 1978-1986, 1987-

1994 and 1994-2001.

Dutt, Garg, and Bali (2003) found that the most common theme in Scientometrics is

scientometrics assessment which constitutes 447 (33.94%) of the 1,317 publications, followed by

theoretical studies and citation and cluster analysis with 186 (14.12%) and 165 (12.52%)

publications respectively.

The authors also found that the United States contributed the most publications in

Scientometrics. There were 233 publications originated from USA, followed with 121 from

Netherlands and 97 from India. However, in the three blocks of time window, publications

originated from USA shows significant decrease with only 49 publications from 1994 to 2001. On

the contrary, publications originated from India had increased significantly from 7 publications in

the earliest time window to 60 in the last time window. Publications originated from Netherlands,

India, France, Spain and Japan were also on the rise.

Next, Dutt, Garg, and Bali also examined the co-authorships pattern in Scientometrics.

They found that 53.4% of the publications were single-authored papers, and 28.6% were two-

authored papers. Although most publications were produced by a single author, multiple-authored

papers are gaining momentum. Domestic and international collaborations were also gaining

momentum, out of the 1317 publications 209 (15.87%) were the result of domestic collaboration

and 77 (5.84%) were the result of international collaboration.

Finally, they noted that scientometrics research had been conducted in over fifty countries

in many publishing institutions. The average number of papers per institution is 0.85. This

indicated that scientometrics research were highly scattered.

Twenty-five years of the Journal of Economic Psychology (1981–2005): A report on the

development of an interdisciplinary field of research

In similar fashion, Kirchler and Hölzl (2006) studied a specific journal. They studied

publications in the first twenty-five years of Journal of Economic Psychology, which is from 1981

to 2005. All the publication data were retrieved using the ISI’s Web of Science®. In the 25 years

period, there were 1,032 publications, however only 854 were analysed. The 854 publications

were exclusively research articles, excluding book review, errata, etc.

Kirchler and Hölzl (2006) divided the research articles into five blocks of time window,

1981-1985, 1986-1990, 1991-1995, 1996-2000, and 2001-2005. They found that the number of

articles published increased from 127 in the earliest time window to 220 in the latest. The number

of references per article also increased over the years, from 23.22 in the earliest time window to


9

38.35 in the latest. They also noted that the number of single-authored articles had decreased

significantly from 52.0% to 34.1% over the time windows. On average, an article was written by

1.77 authors.

The 854 research articles were categorised into 15 topics, namely theory and history;

individual decision making; cooperation and competition; socialization and lay theories; money,

currency and inflation; financial behaviour and investment; consumer attitudes; consumer

behaviour; consumer expectations; firm; marketplace behaviour, marketing and advertising;

labour market; tax; environmental behaviour; government and policy; and others. Over the twenty

five years, four topics, namely consumer behaviour, individual decision making, financial

behaviour and investment, and cooperation and competition constitute 41.2% of the publications.

Having analysed the topics of the research articles, Kirchler and Hölzl (2006) proceeded

in analysing the sources of the publications. The 854 research articles made a total of 28,456

references. However, only 4% of the sources were cited more than three times. 84% of the sources

were cited once, 9% twice and 3% thrice. Kirchler and Hölzl further short listed the 20 most-cited

journals with Journal of Economic Psychology, Journal of Consumer Research, Journal of

Personality and Social Psychology, and American Economic Review as the top 4. The 4 most-

cited journals contributed 11.0% of the references, but Kirchler and Hölzl noted that for every

research article 35.7% of the references were from the 4 most-cited journals. This finding

indicated that the perspectives of social psychology, social economics, and consumer research

dominated the study of economic psychology.

Lastly, Kirchler and Hölzl (2006) also indicated the 20 most-cited articles. The most-cited

article received 132 citations, and on average the 20 most-cited articles received 37.95 citations.

Finally, the self-citation rate of Journal of Economic Psychology was analysed which indicated

3.6% of self-citation rate.

Bibliometric Overview of Library and Information Science Research in Spain

Cano (1999) reviewed the research in Library and Information Science in Spain from

1977 to 1994. Two journals, Revista Espanola De Documentacion Cientifica (RevDoc) and

Documentacion de las Ciencias de la Informacion (Documentacion), which publications were

mostly in Spanish were selected to be analysed. In the 17 years period, the two journals had a total

of 354 articles.

The articles were then categorised into eleven classes, namely (1) the profession and

L&IS education; (2) library history; (3) publishing (book history); (4) education in L&IS; (5)

methodology; (6) analysis of L&IS; (7) L&IS service activities; (8) information storage and


10

retrieval; (9) information seeking; (10) scientific and professional communication; and (11) other

L&IS aspects. The most popular topics were L&IS Services with 19.5% of the total publications,

followed closely by Information Retrieval and Scientific and Professional Communication with

18.9% and 18.6% respectively. He mentioned that the popularity of topics was caused by the

influence of Belgian and French documentalists such as Suzanne Briet, Paul Otlet, and La

Fontaine. Briet emphasised on information retrieval, scientific communication and description of

services, while Otlet and La Fontaine focused on information technology, information retrieval,

search strategies, and scholarly communication networks.

The methodology used each paper was also examined by Cano. The most commonly used

method was the empirical method with 119 articles, followed by discussion, literature review, and

bibliography with 55, 30 and 29 papers respectively. While mathematical methods were only used

in four of the papers.

Cano also investigated the authorship patterns in both journals, and found out that 68% of

the papers studied were single-authored papers. Cano noted that this tendency might be caused by

the need for getting personal recognitions in order to get a permanent employment in Spanish

civil service. A search in LISA database indicated that 77.7% of a total of 205 authors never

published in any of the journals indexed in LISA. According to Cano, this does not mean that the

Spanish L&IS researchers are not productive, but it might be caused by language barriers which

affect the choices of journals.

Interestingly, there were only 7 authors who published in both journals. Cano argued that

this was caused by the existence “gatekeepers” in each editorial board whose task was to maintain

the continuity of their respective invisible colleges. This argument was supported by the fact that

109 out of 119 articles using empirical method were published in RevDoc, where most of the

editors hold PhDs in sciences. While 31 out of 59 articles using literature review and bibliography

methods were published in Documentation, where most of the editors hold PhDs in humanities,

linguistics and literature.

A Bibliometrics Analysis of Physics Publications in Korea, 1994-1998

Kim (2001) conducted a research in the same level of aggregation as Cano (1999), which

was a specific discipline. However, Kim focused more on the research performance of the

authors, which in this case were Korean physicists. Research publications data from 1994 to 1998

produced by Korean physicists were collected from the Science Citation Index CD-ROM

Database.


11

Korean Physical Society and other physical society related in Korea published more than

ten journals in either English or Korean. However, Science Citation Index only included two

Korean-published journals, namely Journal of the Korean Physical Society and Bulletin of the

Korean Chemical Society.

A total of 4,665 publications produced by Korean physicists or researchers affiliated with

physics departments or laboratories were found. These publications were spread over 224 journals

produced by 19 different countries. USA journals accounted for 37.5% while, followed by Korean

and Dutch journals which accounted for 22.0% and 20.1% respectively. There were 33 journals

where more than 30 papers had been published in the journals. These 33 journals accounted for

77% of the total number of publications. The top journal, Journal of the Korean Physical Society,

accounted for 21.6% of publications.

Out of the 4.665 publications, 31.9% were authored collaboratively by Korean physicists

with researchers from other countries. Kim also noted that most Korean-authored papers were

more likely to be published in Korean, Japanese, or UK journals, while internationally

collaborated papers had a tendency to be published in German, Dutch or Swiss journals.

Kim identified the top 15 Korean institutions with more than 100 publications. These top

15 institutions contributed 86.4% of the total publications, with Seoul National University, Korea

Advanced Institute of Science and Technology, and Korea University as the top three institutions.

Kim further investigated the impact of the publications by looking at the Journal Impact

Factor (JIF) of the journals where the papers were published and also at the citation rates of the

papers. First, 62.7% of the total publications appeared in the journals with a JIF (1998) greater

than 1. Both Korean journals, which accounted for 22% of the total number of publications, had a

JIF of less than 1. Secondly, based on the first authors of the publications, 18 authorships

countries were identified. Kim found that USA and French publications tend to get more citations

with an average of 15.9 and 16.4 citations per paper respectively, while Korean publications

averaged 4.0 citations per paper. However, French publications had a significantly higher self-

citations rate in comparison with USA and Korean publications. 24.6% of the total number of

citations received by the French publications was self-citations, whereas for Korea and USA, only

14.1% and 8.2% are self-citations. Among the 18 authorship countries, papers authored by

China’s researchers were the least cited with an average of 2.2 citations per paper and 25% of the

citations received were self-citations.


12

Who’s Who in Conservation Biology—an Authorship Analysis

The four previous papers have illustrated how scientometrics techniques being applied in

the level of journals, fields, as well as countries. Harrison (2006) studied the authorship trends of

a specific journal, Conservation Biology, from its inauguration in 1987 to 2005.

Over the 19-years period, there were more than 5,200 unique authors representing almost

1,500 organisations from 89 countries contributing to 2,060 papers. These data were obtained

from Thomson Scientific™ bibliometric records.

Harrison (2006) first investigated the 25 most cited papers. It was found that 62

individuals were involved in the 25 papers. From the first author perspective, twenty one of them

are men and four are women.

From the total number of authors, 82.6% of them published only a single paper and only

six of them published 10 or more papers, namely Dennis Murphy with 13 papers, Joel Berger 12

papers, each Philip Hedrick and Mac Hunter with 11 papers, and Tim Clark and Kent Redford

with 10 papers. Interestingly, the three most cited papers were not written by any of the six

authors. The three most cited authors were all from Australia, Richard J. Hobbs received 1021

total citations from 5 papers, Chris Margules received 951 citations from 3 papers, and Denis

Saunders received 857 citations from the only paper that he published in Conservation Biology.

82.6% of them published only a single paper.

Harrison (2006) also found that the number of single-authored papers decreased

significantly over the years from 56.7% in 1987 to 17.8% in 2005. While the number of papers

with five or more authors ranged from 0 in 1987 to 23% in 2005. Overall, the average number of

authors per paper increased from 1.6 in 1987 to 3.3 in 2005.

Finally, he investigated the affiliation of the authors. 62% of the total number of

institutions contributed only a single paper. The U.S. Department of Agriculture Forest Service

with its 63 papers was the most productive, while the University of Florida and University of

California, Davis, were the two institutions with the highest number of first authors with 41 and

40 respectively.

Social Network Analysis Review

Social network analysis, sometimes called structural analysis, is a sociological strategy to

investigate social structures (Otte & Rousseau, 2002). This strategy came into being because of

the arising need to analyse the social context of individuals, which can not be accomplished by

using the traditional individualistic social theory and analysis.


13

The focus in social network analysis is investigating the relational and network data. The

network analysis can be distinguished into: (1) ego network analysis, in which the network of a

single person is investigated, and (2) global network analysis, in which all connections among the

members of a network are investigated.

Social network analysis made use of the attributes of graph theory such as components,

density, centrality (degree, closeness, and betweenness), and cliques. These attributes will be

further explained in Chapter Three.

Although social network analysis originated from the field of sociology, it has been also

widely used in other fields. Otte and Rousseau (2002) noted that most publications under the

subject social network analysis were also assigned other subjects . This indicates that the authors

of the publications have either applied the social network analysis to a certain subject, have

applied social network analysis together with that other subject, or have discussed the relation

between social network analysis and the subject.

Some prior studies applying social network analysis will be discussed next, primarily the

application of social network analysis in investigating co-authorship networks.

Who is the best connected scientist? A study of scientific co-authorship networks

Newman (2001) studied the network of scientists based on the publication data retrieved

from four publicly available databases, namely Physics E-print Archive, Medline, SPIRES, and

NCSTRL. The Physics E-print Archive had three subdivisions, which are astrophysics, condensed

matter physics, and high-energy theory. The co-authorship networks of the four databases were

constructed separately.

Newman first evaluated the basic statistics of the four networks, such as their total

authors, papers, number of papers per author, number of authors per paper, number of

collaborators per author, clustering coefficients, and the size of the main component of each

network. In all the four networks, the main components accounted for 80% to 90% of the

network, except for computer science and high-energy theory. Newman argued that this might be

caused by the poor coverage of the disciplines in the databases. This indicated that the majority of

the scientists had channels to other scientists should they need to collaborate in their researches.

Secondly, Newman (2001) examined the networks further by looking into some measures

of the networks, namely geodesics (i.e. the shortest path between two given nodes), betweenness,

and average distances.

The geodesics could be identified by running the algorithm proposed by Newman (2001),

which was a modification of the breadth-first search algorithm:


14

1. Assign vertex s distance zero, to indicate that it is zero steps away from itself, and set d = 0.

2. For each vertex i whose assigned distance is d, follow each attached edge to the vertex j at its

other end and then do one of the following three things:

a. If j has not already been assigned a distance, assign it distance d + 1. Declare i to

be a predecessor of j.

b. If j has already been assigned distance d + 1, then there is no need to do this

again, but i is still declared a predecessor of j.

c. If j has already been assigned a distance less than d + 1, do nothing.

3. Set d � d + 1.

4. Repeat from step (2) until there are no unassigned vertices left.

Betweenness of a certain node A can be defined as the number of all shortest paths

Betweenness of a certain node A can be defined as the number of all shortest paths between pairs

of nodes that go through the node A. In the context of co-authorship networks, the authors with

the highest betweenness will indicate the high influence of the authors. They will be able control

the flow of information among the authors in the network. To calculate the betweenness of each

node, the geodesics which had been explained earlier will be used. The following algorithm was

then proposed by Newman:

1. Find every “leaf” vertex t, i.e., a vertex such that no paths from s to other vertices go though t

and assign it a score of 1=tx .

2. Now, starting with the vertices that are farthest from the source vertex s, work up towards s.

To each vertex i assign a score ∑+=j

jiji wwxx /1 , where the sum is over the neighbours j

immediately below vertex i.

3. Repeat from step 2 until vertex s is reached.

Finally, Newman (2001) proposed to assign weights to the ties to evaluate the strength of

collaborations among the authors. These weights will depend on the number of papers that a given

co-authors have published.

International Mechanics Collaboration in 30 Countries

Chen and Liu (2006) examined the international collaboration in the field of mechanics

among authors in different countries using the social network analysis perspective. 168,689

mechanics-related articles in 106 journals from 1945 to 2003 were collected from the Science

Citation Index-Expanded Database. The authors of the articles were from 150 countries, but only

the collaborations among 30 most productive countries were analysed, which was ranked based

on the number of the first-authors.


15

Based on the publication data of the 30 most productive countries, a non-symmetrical

collaboration matrix was constructed with the rows representing first-author’s countries and the

columns representing non first-author’s countries. The diagonal of the collaboration matrix was

not given any value.

Chen and Liu (2006) identified the six most productive countries, namely USA, UK,

Japan, France, Germany and China. These 6 countries accounted for 66.8% of the 88,891

publications from the top 30 countries, and 58.37% of 18,660 collaborations among the 30

countries. There were 666 different pairs of collaborations among the 900 possible collaborations,

giving a density of 0.74.

The degree centrality, which is the number of direct connections each node has, was also

identified. Only the top 6 countries had a degree centrality of at least seven led by USA with 26,

UK with 18, Germany with 16, France with 14, and both China and Japan with degree centralities

of seven.

Chen and Liu (2006) then divided the 30 countries into 4 regions, namely Europe, North

America, Asia, and other. They found that European countries had a tendency to collaborate with

other European countries, which accounted for more than half of the European countries’

collaborations and 26.7% of total collaborations. The percentage of collaborations by European

countries was the highest compared to other regions’ collaborations. However, they were not the

most productive region; North America was the highest with 39% (35% by USA).

Finally, Chen and Liu (2006) concluded that the United States was the most important

node in the network and European countries led by United Kingdom, Germany, and French

played important roles in the international collaboration in the field of mechanics.

The Structure of Scientific Collaboration Networks in Scientometrics

Hou, Kretschmer, and Liu (2006) conducted a similar research as Newman (2001). They

tried to reveal the microstructure of the collaboration network in Scientometrics journal by

making use of social network analysis, co-occurrence analysis, cluster analysis and frequency

analysis of words. The publication data from 1978-2004 were retrieved from the Science Citation

Index.

A total of 1,927 publications contributed by 3,340 co-authors and 1,630 authors were

found. This translates to 1.18 publications per author and 1.73 authors per paper. Out of the 1,927

publications, only 45.4% were co-authored by 2 or more people, with 59.6% authored by 2

people, 26.6% by 3 people, and the rest by more than 3 people.


16

Hou, Kretschmer, and Liu (2006) constructed the co-authorship network using UCINET

and visualised it using Pajek, but they did not include all the co-authors. Only the authors who

had published at least three articles would be mapped in the social network. As a result, only 163

authors were identified. BibExcel was then used to cluster the authors into 22 clusters. Each of the

two biggest clusters consisted of 15 and 14 authors.

The density and centrality of the co-authorship network was then examined. The three

centrality measures, namely degree, closeness, and betweenness were available in Pajek. The co-

authorship network in Scientometrics was very loose, with a density of 0.03.

Degree centrality refers to the number of co-workers of an author; closeness centrality

refers to the total of distance of an author in the network to every other author, while betweenness

centrality indicates the frequency of an author’s involvement in the shortest paths between

authors. For both three measures of centrality, Glanzel was the most central figure in

Scientometrics journal. Hou, Kretschmer, and Liu (2006) also identified the central figures in the

22 clusters.

Finally, they investigated the fields of each cluster. The two biggest clusters concentrated

on the topics of publication output and citation impact using bibliometrics and scientometrics

techniques. The clusters of similar fields had collaborated with each other except for the four

technology and science-related clusters which had no co-authorships at all among the clusters.

Collaboration Analysis in Recommender Systems Using Social Networks

Social network analysis has been used not only in analysing co-authorship networks, but

also for analysing other networks. Palau, Montaner, Lopez, and de la Rosa (2004) made use of

SNA to analyse the evolution of collaboration in a recommender system, a systems which filter

and present information according the users interests and needs. The recommender system in their

research was GenialChef, a restaurant recommender system, which was simulated in the

university involving 40 users for 60 days.

In order to investigate the networks, Palau, Montaner, Lopez, and de la Rosa (2004) made

use of some network measures, namely size, density, degree centrality, network centrality, clique

membership and factions. Network centrality was calculated based on the in-degree and out-

degree centrality, this means that the networks constructed by Palau, Montaner, Lopez, and de la

Rosa were bi-directional networks. Factions are the loosen-cliques where the nodes which had

certain similarities would be categorised into the same faction.

Palau, Montaner, Lopez, and de la Rosa (2004) constructed two social networks using

UCINET, one at the beginning of the 60-day experiment period and one at the end. As there were


17

40 users in the experiment, the size of the networks remained the same at 40. However out of the

possible maximum connections of 1,560 (derived from permutation of pairs of 40 users), there

were only 150 connections at the 1st network, and 170 connections at the 2nd network. The

numbers of connections translate to the density of 9.6% for network 1 and 10.9% for network 2.

The mean in-degree and out-degree centralities of each node increased over the 60-day

period from 3.72 for both in-degree and out-degree centralities to 4.25 for both too. Finally, Palau,

Montaner, Lopez, and de la Rosa (2004) identified the factions existing in the networks.

Analyzing and Visualizing Criminal Network Dynamics: A Case Study

Palau, Montaner, Lopez, and de la Rosa (2004) had previously used social network

analysis to analyse the evolution of a recommender system, it had also been used to analyse and

visualise the dynamics of criminal networks. The motivation of analysing the dynamics of

criminal networks came from the fact that most previous study on criminal networks had been

done from a static point view, which would not answer many important questions, such as “Do

the relations among the individuals become stronger?”, “Do the individuals move to other

cliques?”, “What do the changes imply?”.

Xu, Marshall, Kaza, and Chen (2004) examined the criminal networks from individual

levels and group levels. The individual levels were analysed based on the 3 centrality measures

introduced by Freeman (1979), namely degree centrality, closeness centrality, and betweenness

centrality. But, since Xu, Marshall, Kaza, and Chen were trying to analyse the networks which

might have different sizes, they used the normalised centralities.

At the group levels, Xu, Marshall, Kaza, and Chen (2004) measured the density,

cohesion, and group stability. While the density showed how well connected were the members in

a component in the network, cohesion measured how strongly connected were the members in a

component as compared to the strength of the connection between the members of the component

with other members from other component. This, Xu, Marshall, Kaza, and Chen argued, would

reflect the loyalty of the members in the component. Group stability measured the ability of a

specific group maintains its members. It could be obtained by calculating the ratio between the

overlapping memberships of a group at two different times, and the total memberships of the

group at the two times:

Multidimensional Scaling Review

Tijssen (1992) classified multivariate data analysis (MDA) into dependence,

dependence/interdependence, and interdependence MDA methods as has been shown in Figure


18

1.1. Three types of MDA methods are often used to represent the object of analysis spatially,

namely hierarchical cluster analysis, factor analysis, and multidimensional scaling.

Multidimensional scaling are usually used to represent objects in two or three-

dimensional maps. The location of each node is derived from the correlation matrix supplied to

multidimensional scaling program such as ALSCAL and MDSCAL. The program will locate the

nodes in the map based on the calculated distances. Kruskal’s Stress formula is commonly used to

ensure the goodness of fit of the nodes between original input matrix distances and the estimated

distances, or in other words the goodness of fit between the calculated distances and the observed

distances (Anegón, Contreras, & Corrochano, 1998).

White and McCain (1997) noted that for co-citation analysis, two-dimensional maps have

been more commonly used. This is because two-dimensional maps provide rich enough

information to interpret, while the three-dimensional maps are more complex while adding only

little explanatory power. The location of the nodes and the clusters they belong are the basis of

interpretation of the maps.

Following are the review of some co-citation analysis studies which used

multidimensional scaling to map the different objects of study, including journals and authors in

different fields such as information retrieval, information science in different countries and

different time periods.

Journal as Markers of Intellectual Space: Journal Co-citation Analysis of Information

Retrieval Area, 1987-1997

Ding, Chowdhury, and Foo (2000) sought to construct the evolution of bibliographic

maps of the Information Retrieval (IR) field based on journal co-citation analysis of publications

in the 1987-1997 periods, which was divided into three time windows of 1987-1991, 1992-1997,

and 1987-1997. A total of 3,325 papers with 78,785 citations from 971 journals were collected

from both the Social Science Citation Index (SSCI) and the Science Citation Index (SCI). Two sets

of 50 highly cited journals were then selected. The first set was based on the overall rank of the

journals, while the second set consisted of only Library and Information Science (LIS) journals

based on the LISA CD-ROM database.

Ding, Chowdhury, and Foo (2000) proceeded to create the 50x50 co-citation matrices of

the 50 journals. The co-citation matrices, however, would need to be converted into correlation

matrices so that they can be analysed using multidimensional scaling. Pearson’s correlation with

pair-wise deletion was the attributes set to convert the raw matrices into correlation matrices.

These correlation matrices became the inputs for the multidimensional scaling program ALSCAL


19

(in SPSS) to generate the bibliographic maps. The attributes set in the program was 0.001 S-stress

convergence, 0.005 minimum S-stress value, and 30 minimum iterations.

From the three bibliographic maps generated based on the journal co-citation analyses of

the 3 time windows, four groups appeared consistently in the maps, namely psychology, LIS &

computer science, physics (optics) & chemistry, and science/nature/neuroscience. These four

groups were clustered based on hierarchical clustering in SPSS. The stability of the 4 groups

appearing in the maps indicated IR as a maturing discipline.

Visualizing a Discipline: An Author Co-Citation Analysis of Information Science, 1972–1995

Prior to Ding, Chowdhury, and Foo (2000) research, White and McCain (1998) had also

tried to analyse the domain of a subject, namely Information Science. The difference between the

two studies was the use of author co-citation analysis rather than journal co-citation analysis by

White and McCain.

McCain (1990) summarised the steps in co-citation analysis involving multidimensional

scaling as shown in Figure 2.1.

Figure 2.1 Steps of Author Co-citation Analysis (adapted from McCain, 1990)

Using Sociological Scisearch via DIALOG, White and McCain retrieved 120 highly cited

authors in 12 key journals from 1972 to 1995. Three maps of three separate periods (1972-1979,

1980-1987, and 1988-1995) were then constructed to show the specialty structure constituting the

Selection of authors

Retrieval of co-citation frequencies

Compilation of raw co-citation matrices

Conversion to correlation matrices

Multivariate analysis of correlation matrices (eg. Principal Component Analysis, Cluster

Analysis, and Multidimensional scaling)

Interpretation & Validation


20

Information Science discipline. Two biggest specialties in the Information Science discipline were

experimental retrieval and citation analysis. Each of the two specialties accounted for 30 and 28

members respectively. The rest of the main specialties were practical retrieval, bibliometrics,

general library systems theory, user theory, and science communication.

White and McCain, based on the 3 maps, also analysed the evolution of the maps,

whereas there were authors who moved from one specialty to another, and also the newcomers in

the specialties. In addition, they also noted 75 authors who appeared in all three maps.

Research Fronts in Library and Information Science in Spain (1985-1994)

Anegón, Contreras, and Corrochano (1998) conducted author co-citation analysis in the

field of Library and Information Science in Spain during the period of 1985-1994, and they also

studied the publication co-citation analysis.

From 1985 to 1994, 1,500 articles with 10,000 references were found. The number of

authors contributing to the references was 2,250. However, Anegón, Contreras, and Corrochano

(1998) only analysed 53 authors who satisfied two restrictions, (1) the authors received more than

15 citations and (2) the authors received more than 60 co-citations.

Anegón, Contreras, and Corrochano (1998) then proceeded to construct the co-citation

matrices and their correlation matrices. These correlation matrices were then analysed statistically

using multivariate analysis, namely Principal Component Analysis, Cluster Analysis, and

Multidimensional Scaling.

As discussed earlier, the purpose of multidimensional scaling is to map objects based on

similarity and dissimilarity matrices (i.e. from correlation matrices). For author co-citation

analysis, the matrices are used to calculate the locations of the authors, which indicate the clusters

and the overall components of the discipline. The cluster analysis is useful to indicate to which

cluster does an author belongs to. Four clusters were identified by Anegón, Contreras, and

Corrochano (1998) with 13, 16, 19, and 4 members respectively.

The Social and Collaborative Nature of Entrepreneurship Scholarship: A Co-Citation and

Perceptual Analysis

Reader and Watkins (2006) sought to answer the question whether the highly co-cited

authors in the field of entrepreneurship reflected only the network of ideas of the citers or there

were actually social and collaborative network among the co-cited authors.


21

The publication data were collected from the entire Social Science Citation Index

database in the 1972 to July 2000 period. 3,003 authors were found, but only the authors with at

least 100 co-citation counts would be analysed. 78 authors were finally identified.

To be able to investigate the existence of the social and collaborative networks, Reader

and Watkins applied the author co-citation analysis using the steps suggested by McCain (1990)

and then proceed with constructing a two-dimensional map using multidimensional scaling and

factor analysis. The multidimensional scaling program used was ALSCAL (in SPSS) with the

stress value set at 0.14 and squared correlation at 0.92.

Reader and Watkins (2006) found that the authors were classified into 9 clusters, each had

different emphasises in their research topics or methodologies.

Other Studies

The integration of multidimensional scaling to co-citation analysis has been done in other

fields as well, such as philosophy (Kreuzman, 2001), human behavioural ecology (Sandstrom,

2001), and chemical engineering (Peters & Vanraan, 1991).

Summary

This chapter presents the short history and literature reviews of three perspectives used in

this dissertation. The first section, scientometrics literature review, presents five studies using

scientometrics techniques in different level of aggregations. The social network analysis review

section presents five co-authorship networks analysed using social network analysis. Finally, the

multidimensional scaling section presents four studies which tried to map the bibliographic maps

of certain disciplines based mainly on either journal or co-citation analyses.

Chapter Three - Methodology

22

CHAPTER THREE

METHODOLOGY

This chapter describes the methods used to obtain the bibliographic records of NUS ISE

Department from 1986 to 2005, including the data sources and search strategies. This is then

followed by discussion on the three different perspectives used in this study. As mentioned in

Chapter One, this study examines the bibliographic records of the publications from three

different perspectives, which are scientometrics, scientographic, and social network analysis

(SNA). The methods of incorporating each of the three perspectives in this study as well as the

different parameters generated by each perspective are then described.

Data Sources

The Institute of Scientific Information’s Web of Science® and Journal Citation Report®

were used to obtain the required data in this study. Web of Science®, a citation database, was used

to retrieve the bibliometric data of the NUS ISE Department, while Journal Citation Report® was

used to retrieve the relevant journals impact factors. The publications list posted in the NUS ISE

Department website were also retrieved for cross checking.

Web of Science® was chosen because of its credibility, extensiveness, and authority. It

consists of Science Citation Index Expanded, Social Sciences Citation Index, and Arts &

Humanities Citation Index; and indexes approximately 9,300 journals with over 21.5 million

records (Thomson, n.d.). The choice of using Web of Science® over the publications list in the

NUS ISE website was due to the fact that the NUS ISE website only listed their publications

starting from the year of 2000.

Bibliographic Records Retrieval Methods

Bibliographic records of the NUS ISE publications from 1986 to 2005 were retrieved by

utilizing two fields in the Web of Science® search option, address and date. The date field was

used to limit the publication year, while the address field was used to ensure that the search results

would only contain bibliographic records of NUS ISE publications. As NUS ISE consists of three

research groups, there were occasions when the authors put only the affiliated research group and

not the NUS ISE. To ensure that every publication would be retrieved, all the research group

names were also included in the query statement.

Address: Natl Univ Singapore SAME (dept ind & syst engn OR ind

engn OR engn management OR quality engn OR syst engn)

Date: 1986-2005


23

The search results including the full bibliographic records and cited references were then

exported to Microsoft Excel. One of the fields retrieved from the Web of Science® was SO (i.e.

the title of journals). The list of the journal titles where the NUS ISE Department members had

published were then used to check and collect each journal’s Journal Impact Factor (JIF) from

Journal Citation Report®. In retrieving the JIF of the journals, there were cases when a journal is

not listed in the Journal Citation Report®. This is because:

(1) The journal has changed its name

(2) The journal has been divided into few journals

(3) The journal is not indexed by Journal Citation Report®.

The journals that are not indexed in the Journal Citation Report® were noted and treated

as journals with a zero impact factor.

Scientometrics

The first perspective used to examine the bibliographic records of NUS ISE Department’s

publications is scientometrics. Scientometrics methods were used to analyze four aspects of the

bibliographic records, namely, the literature growth over 20 years time span indicated by

publication counts; authorships, including both the degree and extent of collaboration and the

most prolific authors; the impact articles measured by the times it is cited; and the quality of

journals where the NUS ISE Department members have published which is measured by the

Journal Impact Factor.

Literature Growth

The number of publications for each year from 1986 to 2005 was first compiled. To

measure the growth of the number of publications, two approaches were used:

(1) Percentage growth compared to a base year publication counts.

Each year number of publications was compared to the number of publications in the base

year 1986. This was calculated based on the following equation:

%1001986

×

p

pn

where,

np = number of publications in year n

1985p = number of publications in 1986


24

(2) Percentage growth compared to previous year publication counts.

Each year number of publications was compared to the number of publications in the

preceding year. This can be represented in the following equation:

%100)1(

)1(×

−

−

−

n

nn

p

pp

where,

np = number of publications in year n

)1( −np = number of publications in year )1( −n

Degree and extent of collaboration

More than half of the NUS ISE Department publications are authored by more than a

single person. To measure and compare the multiple authorships trend and the extent of

collaboration, Lawani’s (1980) Collaborative Index, Subramanyam’s (1983) Degree of

Collaboration, and Ajiferuke, Burell, and Tague’s (1988) Collaborative Coefficient are used.

Lawani (1980) suggested calculating the mean number of authors per paper to measure

the extent collaboration:

N

fj

CI

k

j

j∑=

⋅

=1

where,

jf = number of j-authored publications published in a discipline during a certain

period of time

N = total number of publications published in a discipline during a certain period of

time

k = the greatest number of authors per publication in a discipline

This is the simplest method; however it does not distinguish single-authored from

multiple-authored publications. As a result, the multiple authorships trend can not be examined.

To overcome this, Subramanyam (1983) proposed a method called Degree of Collaboration:

N

fDC 11−=

where,

1f = number of single-authored publications published in a discipline during

a certain period of time

N = number of publications published in a discipline during a certain period of time


25

The value of Degree of Collaboration ranges between 0 and 1. The more multiple-

authored publications, the closer will the value of DC to 1. However, DC does not distinguish the

different levels of multiple authorships. Hence, Ajiferuke, Burell, and Tague’s (1988) came with

Collaborative Coefficient, which considers every multiple-authored publication differently:

N

fj

CC

k

j

j∑=

⋅

−=1

1

1

where,

jf = number of j-authored publications published in a discipline during a certain

period of time

N = total number of publications published in a discipline during a certain period of

time

k = the greatest number of authors per publication in a discipline

The three different measurements allow the comparison among different time and places

collaboration. However, they treat every author regardless of their location. Melin and Persson

(1998) proposed four different collaborative ties that could take place from the perspective of a

given university:

(1) Internal collaboration.

o Intra-departmental. This collaboration takes place with one or more students,

faculties, or researchers in the same department.

o Intra-university. This collaboration takes place with one or more students, faculties,

or researchers across different departments.

(2) National collaboration. This collaboration takes place with one or more different

institutions within the country of the given university.

(3) International collaboration. This collaboration takes place with one or more institutions

outside the country of the given university.

(4) Mixed national and international collaboration. This collaboration takes place with one

or more national institutions and with one or more institutions outside the country of the

given university.

Prolific authors

Next, the number of publications of every author from 1986 to 2005 was compiled to find

out the ten most prolific authors in the NUS ISE Department. The authors were rank based on

three methods of counting:


26

(1) Whole counting. Each author is credited with one count for every publication that bears

his/her name regardless of whether it is a single-authored or multiple-authored

publication.

(2) Fractional Counting. An author is credited with respect to the number of authors for

every publication that bears his or her name. For example, every author of a 5-authored

publication will be credited with a 5

1 count.

(3) First Author Counting. An author is credited with one count only if he or she is the first

author of a publication.

For example, consider the paper below:

Majid, S., Chaudhry, A.S., Foo, S., & Logan, E. (2003). Accreditation of Library and Information

Studies Programmes in Southeast Asia. Singapore Journal of Library & Information

Management, 32, 58−69.

In method (1), Majid, Chaudhry, Foo and Logan will each receive one count. In method (2),

because this is a paper with four authors, each author will receive 4

1 count. If Method (3) was

used, only Majid, the first author will receive a count.

In addition, the numbers generated by the three methods of counting are used to derive

the average number of days required by an author to publish a publication:

nsPublicatio ofNumber

Year)per (Days 25.365 (Years) 20 ×

Reference and Citation Counts

Web of Science® provides data about references of each publication. The total number of

references and the average number of references per publication will be presented. Web of

Science® also provides data about the number of citations received by every publication. The top

10 most-cited publications and their number of self-citation over 20 years from 1986 to 2005 will

be listed.

Journal Impact Factor

The quality of individual publication should be evaluated based on the content of the

publication; however it is also often associated with where it is published. A simple fact of a

researcher’s work got published in a reputable journal indicates that the research should be good

and has a significance.


27

One of the measurements used to rank different journals is Journal Impact Factor. Since

its introduction in 1963 (Whitehouse, 2001), it has been widely used to evaluate the impact of

journals (Garfield, 1996). The Journal Impact Factor, which is derived from dividing the number

of citations received by any publication in a journal of a given year to the total number of

publications of the respective journal in the two preceding years of the given year, is now

published annually by the Journal Citation Report®. The formula to calculate the Journal Impact

Factor is:

)2,1(

)2,1()(

−−

−−

=

XX

XX(X)

P

AC(A)IF

where,

(A)IF(X) = Impact factor for Journal A in Year X

)2,1()(−− XXAC = Number of citations received in year X by publications in year (X-1)

and year (X-2) publications of journal A

)2,1( −− XXP = Total number of publications in year (X-1) and year (X-2)

But, it should be noted that Journal Impact Factor should be used with careful

consideration as mentioned by Garfield (1994) and Seglen (1997). For example, long publications

and articles from reputable journals are generally cited more than shorter articles and articles from

less reputable journals; review and method articles tend to get more citations; and self-citations

are not corrected.

Social Network Analysis

Social network analysis is the second perspective used to examine the bibliographic

records of NUS ISE Department’s publication. The social networks or sociograms were

constructed based on the collaborations among authors. Every author was represented with a node

and the connections among co-authors were represented with a line.

The co-authorship sociograms were constructed based on three 10-years windows and one

20-years window, namely 1986-1995, 1991-2000, 1996-2005, and 1986-2005. The four

sociograms were then examined at three levels by the use of UCINET software:

(1) Whole network level. The main component and its size were identified; the inclusiveness

and the total number of components and isolates were also generated.

(2) Main component level. The density and the geodesic distance were generated.

(3) Individual nodes level. The centrality of the sociograms was generated according to the

degree centrality, closeness and betweenness, and then the five most central authors were

determined.


28

General Parameters

A component in a sociogram means that all its member nodes are reachable from another

node through at least one path. For every network, there could more than one component. This

fact could be used as an indicator of the different research areas, ideas, associations and

communities (Wee, 2006).

The single largest component in a network is called main component. A parameter

associated with main component is inclusiveness, which indicates the number of nodes in the

main component and can be expressed by:

network wholein the nodes ofnumber total

componentmain in the nodes ofnumber essinclusiven =

While main component is the largest component in a sociogram, isolates are a component

which consists of only one node and does not have paths to other nodes. In this study, isolates

simply means the authors who always publish by themselves or never involved in any

collaboration.

Density

The density of a sociogram describes the level of connections among the points in the

sociogram. It expresses the proportion of existing number of lines in a sociogram to the maximum

possible number of lines in the sociogram. The maximum number of lines depends on the number

of nodes in a sociogram. If there are n nodes in a sociogram, the maximum number of nodes is

2/)1( −nn . Hence, the density is formulated as (Scott, 2000):

2/)1( −

=

nn

ldensity

)1(

2

−

=

nn

l

where,

l = number of lines in the sociogram

n = number of nodes in the sociogram

Density is closely related with inclusiveness as can be seen in Figure 3.1. The higher the

inclusiveness, the higher the density will be. In this study, the density indicates the relation among

the members of NUS ISE Department in terms of the cohesiveness of the department.


29

Number of Connected Nodes

4 4 4 3 2 0

Inclusiveness 1.00 1.00 1.00 0.75 0.50 0.00

Number of Lines

6 4 3 2 1 0

Density 1.00 0.67 0.50 0.33 0.17 0.00

Figure 3.1 Density and inclusiveness comparisons (adapted from Scott, 2000)

Distance

Distance is one of the most important elements in a graph or a sociogram in this study.

The distance between two nodes is the length of the geodesic, which connects the two nodes.

Geodesic simply means the shortest path from one node to another node. For example in Figure

3.2, node A can reach node D through three different paths, namely AD, ACD, and ABCD. The

lengths of the paths are 1, 2, and 3 respectively. As can be seen, the shortest path (geodesic) is

AD, hence the distance between nodes A and D is 1.

Figure 3.2 Paths and distances (adapted from Scott, 2000)

Centrality

Centrality is one of the earliest analyses pursued by social networks analysts (Scott,

2000). It originated from efforts to find out the most popular and prominent person in a social

network. There are three measures to evaluate the centrality of the nodes in a sociogram, namely

degree centrality, closeness and betweenness.

Degree centrality

Also known as local centrality, this is the simplest method to measure centrality. It counts

the number of other nodes directly connected to a specific node. The more direct connections the

node has, the more central it is.


30

Because this method only counts the direct connections, meaningful comparisons can

only be done among members of a sociogram or other sociograms with similar size. To encounter

this, relative degree centrality is introduced. It measures the proportion of the direct connections a

node has with the number of nodes in a sociogram, which can be expressed as:

B sociogramin nodes ofnumber

A node of s connectiondirect ofnumber B sociogramin A node of centrality degree relative =

In addition, degree centrality may not show the most central node in a sociogram as it

ignores indirect connections. This leads to the concept of closeness.

Closeness

Freeman (1979) proposed to measure closeness of nodes, also known as global centrality.

Freeman expressed global centrality by measuring the geodesic distances among various nodes,

and the value of a node’s global centrality is the sum of all geodesic distances from the node to

other nodes in the sociogram. It can be expressed as:

∑=

≠=

g

j

jiic jnndnC1

1),,()(

where,

)( ic nC = closeness or global centrality of node in

∑=

g

j

ji nnd1

),( = sum of geodesic distances from in to all other nodes in the sociogram

g = total number of nodes in the sociogram

The smaller the value of the closeness, which means smaller sum of the geodesic

distances from a node to other nodes, the more central the node is in the sociogram. Figure 3.3

illustrates the comparison between degree centrality and closeness of nodes in the sociogram.


31

Centrality A, C B G, M J, K, L All other

points

Local (Absolute)

5 5 2 1 1

Local (Relative)

0.33 0.33 0.13 0.07 0.07

Global 43 33 37 48 57

Figure 3.3 Degree centrality and closeness (adapted from Scott, 2000)

Betweenness

In addition to introducing the concept of closeness, Freeman (1979) also introduced the

concept of betweenness. A node with high betweenness means the node is an important

intermediary point which lies between many other points in a sociogram. This node many not

necessarily have the highest local centrality nor the least global centrality. For example, nodes G

and M in Figure 3.3 are the intermediary points which act as ‘broker’ or ‘gatekeeper’ for many

pair of nodes.

Betweenness is formulated as follows:

∑∑>

=

n

kj

n

ijkiB xbxC )()(

where,

)( iB xC = Betweenness of node ix

)( ijk xb = proportion of geodesics linking jx and kx that contains ix

UCINET (Version 6.0)

UCINET is software for social network analysis, which was used to construct the four

sociograms of co-authorship network of NUS ISE Department’s publications. It was also used to

compute the social network analysis parameters which have been discussed earlier.

UCINET was supplied with .DL extension files. The .DL files consist of the publications

codes as well as abbreviations of the authors’ names. UCINET treats comma and space as a

delimiting character between items, in this case authors. Hence, the spaces and commas in the

abbreviation of authors’ names are replaced by underscore character. For example, “Garfield, E”

was represented as “GARFIELD_E”. The publications are represented based on the time period

they are in. For example, a publication in 1986 was represented as P8695_XX, with XX as the

count number.

UCINET is case-sensitive; “Garfield_E” and “GARFIELD_E” will be treated as two

different items. In this study, all publications codes and abbreviations of authors’ names were

standardized in upper case letters.


32

The sociograms for each time window was then drawn using NetDraw and Pajek, which

are integrated with UCINET.

Multidimensional Scaling

The third perspective used in this study is multidimensional scaling (MDS). Four maps of

different time windows were constructed, in line with the social network analysis time windows,

namely 1986-1995, 1991-2000, 1996-2005, and 1986-2005. The maps of the disciplinary roots of

NUS ISE Department generated using MDS were based on the cited references in its publications

or known as journal co-citation analysis. The steps leading to the construction of the maps

adapted earlier study by Ding, Chowdhury, and Foo (2000), which includes selection of 30 highly

cited journals in each time window, construction of raw co-citation matrix, conversion to

correlation matrix, and finally the multivariate analysis of correlation matrix.

Selection of journals and construction of raw co-citation matrices

Based on the publication data retrieved from Web of Science®, the top 30 highly cited

journals were selected according to the four different time windows. Journal Citation Report® was

then used to obtain the subject areas of the journals.

The frequency of co-citation among journals in the same publication was computed and

tabulated using Microsoft Excel. This step resulted in a one-mode two-way 30-by-30 matrix for

each time window. A one-mode two-way 30-by-30 matrix means that both the rows and columns

of the matrix represent the top 30 highly selected journals.

Conversion to correlation matrix

The diagonals of the raw co-citation matrices, which indicate the co-citation between a

journal and itself, were assigned value of zeroes and treated as missing data. The raw co-citation

matrices were then converted to correlation matrices using Pearson’s correlation coefficients with

pairwise deletion in SPSS. These conversions were necessary as the correlation matrices are the

required inputs for the multidimensional scaling analysis.

Multidimensional scaling analysis

SPSS provided multidimensional scaling in its ALSCAL (Norusis, 2002). The parameters

set to analyse the correlation matrices were 0.001 of S-stress convergence, 0.005 of Minimum S-

stress value, and 30 of minimum iterations. Euclidean distance scaling model was chosen for

plotting the nodes representing the journals. To classify the top 30 highly cited journals, SPSS’s

hierarchical clustering analysis with Ward’s method as the statistics (Ding, Chowdhury, & Foo,


33

2000). Finally, the clusters in the maps were named based on the subject areas of each cluster’s

members.

Summary

This chapter started with the description of data sources, Institute of Scientific

Information’s Web of Science® and Journal Citation Report®, and the retrieval methods. This was

followed by explanations on scientometrics and social network analysis parameters; and also the

use of UCINET to derive the paramaters and to draw the sociograms. Finally, a description on

multidimensional scaling analysis and the preparation required to run the analysis using SPSS’s

ALSCAL was presented.

Chapter Four - Result and Discussion

34

CHAPTER FOUR

RESULTS AND DISCUSSION

The objective of this study is to examine the NUS-ISE Department’s publications from

three different perspectives, namely, scientometrics, social network analysis, and

multidimensional scaling analysis. This chapter is divided into three parts according to the

perspectives used in this study. The first section analyses and discussed the publications from the

scientometrics perspective in comparison with previous study by Ang, Lee, and Tng (2006) on the

electrical engineering department of both NTU and NUS. This is subsequently followed by

analyses and discussions based on the social network analysis and multidimensional scaling

perspectives. Chapter four ends with conclusions and a discussion on the limitation of the study.

Scientometrics

Publication Growth

The NUS-ISE annual publication outputs from 1986 to 2005, together with the both the

publication outputs of NTU Electrical and Electronics Engineering (NTU-EEE) and NUS

Electrical and Computer Engineering (NUS-ECE) are presented in Table 4.1. It should be noted

that the period being studied by Ang, Lee, and Tng (2006) were only from 1990 to 2005.

No. of

Publications

Growth rate

(%)

No. of

Publications

Growth rate

(%)

No. of

Publications

Growth rate

(%)

1986 16 - - - - -

1987 9 -44.00% - - - -

1988 15 67.00% - - - -

1989 16 7.00% - - - -

1990 6 -63.00% 34 - 35 -

1991 4 -33.00% 42 24.00% 38 9.00%

1992 7 75.00% 64 52.00% 40 5.00%

1993 12 71.00% 124 94.00% 76 90.00%

1994 18 50.00% 129 4.00% 98 29.00%

1995 14 -22.00% 141 9.00% 158 61.00%

1996 16 14.00% 136 -4.00% 152 -4.00%

1997 10 -38.00% 173 27.00% 199 31.00%

1998 16 60.00% 205 18.00% 283 42.00%

1999 15 -6.00% 226 10.00% 355 25.00%

2000 17 13.00% 280 24.00% 499 41.00%

2001 20 18.00% 259 -8.00% 490 -2.00%

2002 33 65.00% 293 13.00% 464 -5.00%

2003 31 -6.00% 269 -8.00% 542 17.00%

2004 25 -19.00% 370 38.00% 633 17.00%

2005 25 0.00% - - - -

Total 325 - 2745 - 4062 -

Year

NUS-ECE NTU-EEENUS-ISE

Table 4.1 Yearly publication growth at NUS-ISE, NUS-ECE, and NTU-EEE


35

From both Table 4.1 and Figure 4.1, it can be seen that the number of publication outputs

by NUS-ISE is much smaller compared with both the NTU-EEE and NUS-ECE publication

outputs. This reflects the number of faculties and research fellows in each department. Based on

the data in each school website in 2007, NTU-EEE has over 400 faculties and research fellows;

NUS-ECE has 213, while NUS-ISE is only 23 people strong. However, unlike NUS-ECE and

NTU-EEE publication outputs which had increased more than ten times in 15 years period, the

NUS-ISE publication outputs does not show similar trend.

But, the proportion between the strength of each department and the number of

publication outputs, all departments average approximately 10 publication outputs per person.

Furthermore, there are a significant number of publication outputs by NUS-ISE, which are not

indexed by the Web of Science®. In the period from 2000 to 2005, there are 60 of them as shown

in Appendix B.

0

100

200

300

400

500

600

700

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Year of Publication

Nu

mb

er

of

Pu

blicati

on

s

NUS-ECE

NTU-EEE

NUS-ISE

Figure 4.1 Annual publication counts at NUS-ISE, NUS-ECE, and NTU-EEE

Co-authorships

Table 4.2, 4.3, and 4.4 presents the co-authorships level in each department. The

highlighted cells indicate the most common number of authors collaborating to produce a

publication output for each year. In all three departments, the most common number of authors

collaborating for a publication is between 2 to 4.


36

1 2 3 4 5 6 7

1986 16 4 8 4 0 0 0 0 32 2.00

1987 9 3 4 2 0 0 0 0 17 1.89

1988 15 3 4 5 3 0 0 0 38 2.53

1989 16 2 7 3 2 2 0 0 43 2.69

1990 6 1 0 5 0 0 0 0 16 2.67

1991 4 1 2 1 0 0 0 0 8 2.00

1992 7 0 3 2 1 1 0 0 21 3.00

1993 12 1 7 1 3 0 0 0 30 2.50

1994 18 2 4 10 2 0 0 0 48 2.67

1995 14 2 6 5 1 0 0 0 33 2.36

1996 16 1 5 7 3 0 0 0 44 2.75

1997 10 1 3 2 4 0 0 0 29 2.90

1998 16 0 6 6 3 1 0 0 47 2.94

1999 15 2 5 4 3 1 0 0 41 2.73

2000 17 3 3 9 2 0 0 0 44 2.59

2001 20 4 7 9 0 0 0 0 45 2.25

2002 33 6 10 12 5 0 0 0 82 2.48

2003 31 2 14 11 2 1 0 1 83 2.68

2004 25 6 7 9 2 1 0 0 60 2.40

2005 24 2 8 13 1 0 0 0 61 2.54

Total 324 46 113 120 37 7 0 1 822 2.54

No of Authors Author

Totals

Authors/P

aperYear

No of

Articles

Table 4.2 Annual co-authorship levels at NUS-ISE

1 2 3 4 5 6 7 8 9 10 >10

1986 - - - - - - - - - - - - - -

1987 - - - - - - - - - - - - - -

1988 - - - - - - - - - - - - - -

1989 - - - - - - - - - - - - - -

1990 34 8 10 9 6 1 0 0 0 0 0 0 84 2.47

1991 42 13 15 8 4 2 0 0 0 0 0 0 93 2.21

1992 64 13 18 17 10 3 3 0 0 0 0 0 173 2.70

1993 124 22 37 42 18 4 1 0 0 0 0 0 320 2.58

1994 129 13 38 47 23 7 0 0 1 0 0 0 365 2.83

1995 141 25 31 51 23 7 4 0 0 0 0 0 391 2.77

1996 136 15 39 41 26 10 3 1 1 0 0 0 403 2.96

1997 173 12 54 50 31 13 3 6 3 1 0 0 552 3.19

1998 205 13 50 69 37 18 6 4 3 2 1 2 697 3.40

1999 226 11 58 73 37 22 8 6 7 2 1 1 789 3.49

2000 280 9 58 84 66 33 10 9 6 4 0 1 1025 3.66

2001 259 3 48 79 62 35 9 9 8 2 2 2 1001 3.86

2002 293 10 60 95 52 35 17 10 6 4 2 2 1099 3.75

2003 269 13 57 76 49 26 14 14 9 4 3 4 1047 3.89

2004 370 11 75 101 66 39 34 15 10 6 5 8 1520 4.11

2005 - - - - - - - - - - - - - -

Total 2745 191 648 842 510 255 112 74 54 25 14 20 9559 3.48

Authors/P

aper


TotalsYear

No of

Articles

Table 4.3 Annual co-authorship levels at NUS-ECE


37

1 2 3 4 5 6 7 8 9 10 >10

1986 - - - - - - - - - - - - - -

1987 - - - - - - - - - - - - - -

1988 - - - - - - - - - - - - - -

1989 - - - - - - - - - - - - - -

1990 35 15 16 3 1 0 0 0 0 0 0 0 60 1.71

1991 38 20 14 2 1 1 0 0 0 0 0 0 63 1.66

1992 40 14 14 7 5 0 0 0 0 0 0 0 83 2.08

1993 76 21 20 24 9 1 1 0 0 0 0 0 180 2.37

1994 98 38 27 17 10 4 1 1 0 0 0 0 216 2.2

1995 158 42 52 32 25 3 1 1 1 0 1 0 388 2.46

1996 152 19 60 43 22 5 2 1 0 0 0 0 400 2.63

1997 199 28 73 63 22 4 5 3 1 0 0 0 530 2.66

1998 283 47 80 80 36 22 9 6 2 0 0 1 836 2.95

1999 355 38 101 120 39 20 15 15 3 3 0 1 1113 3.14

2000 499 29 112 159 64 37 35 22 24 7 8 2 1904 3.82

2001 490 16 99 134 93 52 24 30 16 16 8 2 1988 4.06

2002 464 25 115 114 102 52 19 17 10 6 1 3 1691 3.64

2003 542 28 123 153 87 61 41 29 11 4 4 1 2022 3.73

2004 633 29 155 158 112 83 49 25 13 6 2 1 2334 3.69

2005 - - - - - - - - - - - - - -

Total 4062 409 1061 1109 628 345 202 150 81 42 24 11 13808 3.40

Authors/P

aper


TotalsYear

No of

Articles

Table 4.4 Annual co-authorship levels at NTU-EEE

Price (1963) predicted that the single-authored paper would have been extinct by 1980.

Although the single-authored publications still exist in all three departments, the percentages of

single-authored publications keep decreasing. This shows that collaboration is becoming the trend

in writing a publication in all the three departments. The Science and Engineering Indicator 2004

(SEIR 2004) indicated that this trend was caused by at least five factors, namely technological

advances, increasing level of education, falling rate of political barriers, government policies, and

also because of scientific needs.

No. of

Publications

% of

Publications

No. of

Publications

% of

Publications

No. of

Publications

% of

Publications

1 46 14.20% 191 6.96% 409 10.07%

2 113 34.88% 648 23.61% 1061 26.12%

3 120 37.04% 842 30.67% 1109 27.30%

4 37 11.42% 510 18.58% 628 15.46%

5 7 2.16% 255 9.29% 345 8.49%

6 0 0.00% 112 4.08% 202 4.97%

7 1 0.31% 74 2.70% 150 3.69%

>7 0 0.00% 113 4.12% 158 3.89%

Overall 324 100.00% 2745 100.00% 4062 100.00%

No. of

Authors

NUS-ISE NUS-ECE NTU-EEE

Table 4.5 Distribution of number of authors per publication at NUS-ISE, NUS-ECE, and NTU-EEE


38

From Table 4.5, it can be seen that the collaboration of 2 to 4 authors contributes around

70% of the publication outputs, 83.33% for NUS-ISE, 72.86% for NUS-ECE, and 68.89% for

NTU-EEE. The three departments also have similar distributions of the degree of collaboration as

shown in Figure 4.2.

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

1 2 3 4 5 6 7 >7

Level of Co-authorship

% o

f P

ub

licati

on

s

NUS-ISE

NUS-ECE

NTU-EEE

Figure 4.2 Degree of collaborations at NUS-ISE, NUS-ECE, and NTU-EEE

The tendency of collaboration between 2 to 4 authors per publication can also be seen in

Table 4.6, which summarises the mean numbers of authors per publication. It can be seen that in

the three departments the numbers of authors per publication range from 2.54 to 3.48.

1986 2.00 - -

1987 1.89 - -

1988 2.53 - -

1989 2.69 - -

1990 2.67 2.47 1.71

1991 2.00 2.21 1.66

1992 3.00 2.70 2.08

1993 2.50 2.58 2.37

1994 2.67 2.83 2.2

1995 2.36 2.77 2.46

1996 2.75 2.96 2.63

1997 2.90 3.19 2.66

1998 2.94 3.40 2.95

1999 2.73 3.49 3.14

2000 2.59 3.66 3.82

2001 2.25 3.86 4.06

2002 2.48 3.75 3.64

2003 2.68 3.89 3.73

2004 2.40 4.11 3.69

2005 2.54 - -

Overall 2.54 3.48 3.40

NUS-ISE NUS-ECE NTU-EEEYear

Table 4.6 Average number of authors per publication at NUS-ISE, NUS-ECE, and NTU-EEE


39

However, the mean number of authors of NUS-ISE and both NUS-ECE and NTU-EEE

also indicates that the future collaboration trend in the field of industrial engineering and electrical

engineering may not be the same. This is illustrated in Figure 4.3 where the mean number of

authors in NUS-ISE has stabilised in the range of 2.50 authors per publication for the past 10

years, but the mean number of authors in both NUS-ECE and NTU-EEE are still trending up with

increasing number of authors collaborating for a publication.

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Year of Publication

Avera

ge N

um

ber

of

Au

tho

rs p

er

Pu

blicati

on

NUS-ECE

NTU-EEE

NUS-ISE

Figure 4.3 Comparison of mean numbers of authors per publication

The degree of collaboration in each department are further analysed by calculating their

collaborative index (CI), degree of collaboration (DC), and collaborative coefficient (CC) as

discussed in Chapter 3. The CI is the same as the mean number of authors per publication which

has been shown in Table 4.6 and Figure 4.3, while DC and CC indicate how collaborative the

publications in each year are. The higher the DC and CC, the more collaborative were the

publications in the respective year. Table 4.7 presents CI, DC, and CC for NUS-ISE, NUS-ECE,

and NTU-EEE.

The overall DCs of each three schools, which indicate the proportion of non single-

authored publication shows that, range from 0.86 to 0.93. This means that only 14% or fewer

publications in the past 20 years were single-authored publications.


40

CI DC CC CI DC CC CI DC CC

1986 2.00 0.75 0.42 - - - - - -

1987 1.89 0.67 0.37 - - - - - -

1988 2.53 0.80 0.51 - - - - - -

1989 2.69 0.88 0.54 - - - - - -

1990 2.67 0.83 0.56 2.47 0.76 0.48 1.71 0.57 0.31

1991 2.00 0.75 0.42 2.21 0.69 0.42 1.66 0.47 0.26

1992 3.00 1.00 0.63 2.7 0.8 0.51 2.08 0.65 0.39

1993 2.50 0.92 0.53 2.58 0.82 0.52 2.37 0.72 0.45

1994 2.67 0.89 0.56 2.83 0.9 0.57 2.20 0.61 0.38

1995 2.36 0.86 0.51 2.77 0.82 0.54 2.46 0.73 0.46

1996 2.75 0.94 0.59 2.96 0.89 0.58 2.63 0.88 0.54

1997 2.90 0.90 0.58 3.19 0.93 0.61 2.66 0.86 0.53

1998 2.94 1.00 0.63 3.4 0.94 0.63 2.92 0.83 0.54

1999 2.73 0.87 0.55 3.49 0.95 0.64 3.14 0.89 0.58

2000 2.59 0.82 0.53 3.66 0.97 0.67 3.79 0.94 0.65

2001 2.25 0.80 0.48 3.86 0.99 0.69 4.03 0.97 0.68

2002 2.48 0.82 0.51 3.75 0.97 0.67 3.62 0.95 0.65

2003 2.68 0.94 0.56 3.89 0.95 0.66 3.71 0.95 0.65

2004 2.40 0.76 0.47 4.11 0.97 0.68 3.69 0.95 0.66

2005 2.54 0.92 0.56 - - - - - -

Overall 2.54 0.86 0.53 3.48 0.93 0.63 3.39 0.90 0.60

YearNUS-ISE NUS-ECE NTU-EEE

Table 4.7 Measures of degree of collaborations at NUS-ISE, NUS-ECE, and NTU-EEE

Extent of Collaboration

The co-authorships levels of NUS-ISE, NUS-ECE, and NTU-EEE have been discussed

earlier. But, with whom did the authors collaborate? Table 4.8 summarises the different types of

collaboration and their proportion in each of the three departments. However, over 50% of the

publications were the result of collaboration with authors outside the department. Interestingly, as

pointed by Ang, Lee, and Tng (2006), the collaboration between NTU-EEE and NUS-ECE were

non-existent. This is also the case with NUS-ISE; none of the collaboration was with any author

from NTU. The details of the local and international collaborations of NUS-ISE author can be

seen in Tables 4.9 and 4.10.

Number % Number % Number %

Zero Collaboration 46 14.20% 191 6.96% 409 10.07%

Intra-Departmental 113 34.88% 1182 43.06% 1905 46.90%

Intra-University 40 12.35% 304 11.07% 162 3.99%

Local 28 8.64% 397 14.46% 507 12.48%

International 95 29.32% 536 19.53% 980 24.13%

Mixed 2 0.62% 135 4.92% 99 2.44%

Total 324 100.00% 2745 100.00% 4062 100.00%

NTU-EEEType of Collaboration

NUS-ISE NUS-ECE

Table 4.8 Extent of collaborations at NUS-ISE, NUS-ECE, and NTU-EEE


41

Countries Quantity %

USA 31 27.43%

Australia 17 15.04%

New Zealand 14 12.39%

China 13 11.50%

Sweden 8 7.08%

Hong Kong 7 6.19%

South Korea 6 5.31%

Taiwan 6 5.31%

Canada 3 2.65%

France 2 1.77%

South Africa 2 1.77%

England 1 0.88%

Finland 1 0.88%

Israel 1 0.88%

Kuwait 1 0.88%

Table 4.9 International Collaborators of NUS-ISE

Organization Quantity %

Ngee Ann Polytechnic 4 13.33%

Singapore Management University 4 13.33%

Motorola S Pte Ltd, Corp Res & Technol Ctr, Singapore 2 6.67%

Singapore Polytechnic 2 6.67%

Singapore Technol Aerosp 2 6.67%

Hewlett Packard Singapore Privte Ltd 1 3.33%

Gint Inst Mfg Technol, Mfg Planning & Scheduling Grp, Singapore 1 3.33%

Inst High Performance Comp 1 3.33%

Kent Ridge Digital Labs 1 3.33%

Man Drapeau Res Pte Ltd 1 3.33%

Minist Def, Singapore 1 3.33%

Minist Environm, Singapore 1 3.33%

Def Sci Org,Dept Prod Assurance, Singapore 1 3.33%

Motorola Elect Pte Ltd, Singapore Software Ctr, Singapore 1 3.33%

National University Hosp 1 3.33%

Natl Semicond Manufacturer Singapore Pte Ltd, 1 3.33%

Natsteel Chem Ltd, Singapore 1 3.33%

Registry Vehicles, Singapore 1 3.33%

Silicon Syst Singapore Pfc Ltd, Singapore 1 3.33%

Stand Chartered Bank, Card Ctr, Singapore 1 3.33%

Tan Tock Seng Hosp, Dept Neurosurg, Singapore 1 3.33%

Table 4.10 Local Collaborators of NUS-ISE

All three departments have similar pattern of collaboration, with intra-departmental

collaboration as the most common type of collaboration and international collaboration

constitutes around 20% to 30% of the publication. This is in line with the statistics detailed in the

Science and Engineering Indicators 2006 (SEIR 2006) where 20% of all publications have at least

one foreign author.


42

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

45.00%

50.00%

Zero C

ollabora

tion

Intra-D

epartmenta

l

Intra-U

niversity

Local

Intern

ational

Mixed

Type of Collaboration

% o

f P

ub

licati

on

NUS-ISE

NUS-ECE

NTU-EEE

Figure 4.4 Comparison of extent of collaboration at NUS-ISE, NUS-ECE, and NTU-EEE

Prolific Authors

In addition to the pressure to publish articles, Birnholtz (2006) also indicated that

academic faculties and researches publish because of the functions that authorships serve. There

are three functions of authorship, which are (1) attribution of credit for discoveries to a person or

to a group of people (2) assigning ownership to an author or the authors; and (3) enabling the

accrual of reputation. Based on the functions of authorships, it can be concluded that the more

articles an author publishes, the more reputable he/she is. High reputability is very important for

academic faculties and researchers, because it means their articles will get more citations, which

means they are getting more credits (Merton 1968; 1988).

In Tables 4.11 and 4.12, the most prolific authors in NUS-ISE according to whole

counting and fractional counting are presented. It can be seen that the top ten authors based on the

two counting methods are exactly the same except for the top 2 authors. This is because the two

authors, Ang and Xie, have different style of collaboration. Ang wrote 19 (29.69%) single-

authored papers while Xie only wrote 1 (1.03%) single-authored paper. The rest of Ang’s

publications are collaborated with 1 person (32.81%), 2 people (31.25%), and 3 people (3.13%).

While Xie collaborated with 1 person (21.65%), 2 people (48.45%), 3 people (19.59%), and 4

people (6.19%). This fact explains why Ang are more prolific based on fractional counting

method.


43

The average numbers of days per publication by each of the top 10 authors are also

presented in Tables 4.11 and 4.12. Based on the whole counting method, the top 10 authors need

187.31 days to publish a paper. While based on the fractional counting method, 441.42 days are

needed.

Rank NameWhole

counting

Average No. of Days

per Publication

1 XIE, M 97 75.31

2 ANG, BW 64 114.14

3 GOH, TN 60 121.75

4 TANG, LC 39 187.31

5 ONG, HL 29 251.90

6 POH, KL 28 260.89

7 TEO, KL 21 347.86

8 GOH, CJ 19 384.47

9 CHEW, EP 18 405.83

10 LAI, CD 15 487.00

Table 4.11 Top 10 authors based on whole counting

Rank NameFractional

counting

Average No. of Days

per Publication

1 ANG, BW 37.50 194.80

2 XIE, M 34.20 213.60

3 GOH, TN 23.43 311.74

4 TANG, LC 18.48 395.22

5 ONG, HL 10.83 674.31

6 POH, KL 10.51 695.08

7 TEO, KL 9.83 742.88

8 GOH, CJ 8.17 894.49

9 CHEW, EP 7.17 1,019.30

10 LAI, CD 5.37 1,361.18

Table 4.12 Top 10 authors based on fractional counting

Pichini, Pulido, and Garcia-Algar (2005) noted that the first author of a publication had

been allocated to the one who come up with the idea and who contributed the most as a whole.

Based on this assumption, the first author should be given the highest credit of the work. It turns

out that using this counting method, the top 10 authors remain the same with one additional

author as presented in Table 4.13.


44

Rank Name1st Author

counting

Average No. of Days

per Publication

1 ANG, BW 46 158.80

2 XIE, M 27 270.56

3 TANG, LC 22 332.05

4 GOH, TN 12 608.75

5 TEO, KL 11 664.09

6 GOH, CJ 8 913.13

7 CHEW, EP 8 913.13

8 ONG, HL 7 1,043.57

9 POH, KL 7 1,043.57

10 LAI, CD 7 1,043.57

11 CUI, LR 7 1,043.57

Table 4.13 Top 10 authors based on first-author counting

Reference and Citation Counts

Table 4.14 summarises the references cited by the publications of the three departments.

It can be seen that the number of references in all NUS-ISE, NUS-ECE, and NTU-EEE are

similar. Over the years, the numbers of references per publication have increased significantly as

can be seen in Table 4.15. For example, in 1986 each NUS-ISE publication averaged 9.25

references. While in 2005, there were 22.46 references per publication.

NUS-ISE NUS-ECE NTU-EEE

Total No. of

References Cited5,668 42,781 64,296

No. of Publications 324 2,745 4,062

Average No.of References

Per Publication16.72 14.23 13.90

Table 4.14 Reference Counts at NUS-ISE, NUS-ECE, and NTU-EEE

The numbers of publications among NUS-ISE, NUS-ECE, and NTU-EEE differ pretty

significantly. However, the patterns of the impact of the publications are very similar as depicted

in Figure 4.5. In this case, the impact is measured by how frequent the publications are being

cited. Table 4.16 summarises the distribution of impact that each publication has. It can be seen

that around 30% of publications in all the three departments are never cited, while 40% to 45%

are cited between 2 to 9 times.


45

No.of

References

Cited

No. of

Publications

Average No.of

References Per

Publication

No.of

References

Cited

No. of

Publications

Average No.of

References Per

Publication

No.of

References

Cited

No. of

Publications

Average No.of

References Per

Publication

1986 148 16 9.25 - - - - - -

1987 127 9 14.11 - - - - - -

1988 189 15 12.60 - - - - - -

1989 237 16 14.81 - - - - - -

1990 68 6 11.33 335 34 9.85 265 35 7.57

1991 52 4 13.00 316 42 7.52 286 38 7.53

1992 165 7 23.57 815 64 12.73 446 40 11.15

1993 122 12 10.17 1311 124 10.57 1008 76 13.26

1994 215 18 11.94 1759 129 13.64 1339 98 13.66

1995 388 14 27.71 1777 141 12.60 2081 158 13.17

1996 216 16 13.50 2061 136 15.15 2020 152 13.29

1997 139 10 13.90 2640 173 15.26 3047 199 15.31

1998 283 16 17.69 3288 205 16.04 3923 283 13.86

1999 219 15 14.60 3467 226 15.34 5290 355 14.90

2000 414 17 24.35 4203 280 15.01 7832 499 15.70

2001 374 20 18.70 4337 259 16.75 8428 490 17.20

2002 605 33 18.33 5248 293 17.91 7978 464 17.19

2003 574 31 18.52 4612 269 17.14 9651 542 17.81

2004 594 25 23.76 6612 370 17.87 10702 633 16.91

2005 539 24 22.46 - - - - - -

Overall 5668 324 16.72 42781 2745 14.23 64296 4062 13.90

Year


Table 4.15 Annual Reference Counts at NUS-ISE, NUS-ECE, and NTU-EEE


46

In the case of NUS-ISE, a total of 1344 citations were received, this means that on

average each publication received 4.15 citations. The Institute of Scientific Information’s

Essential Science Indicators indicates that over the period of 1996 to 2005, the engineering field

publications average 3.82 citations. In the same period, the NUS-ISE has comparable citation rate,

which is 3.22.

No. of

Publications%

No. of

Publications%

No. of

Publications%

0 (uncited) 93 28.70% 823 29.98% 1287 31.68%

1 52 16.05% 494 18.00% 701 17.26%

2 To 9 147 45.37% 1089 39.67% 1637 40.30%

10 To 19 23 7.10% 238 8.67% 316 7.78%

20 To 49 8 2.47% 89 3.24% 108 2.66%

50 To 99 0 0.00% 11 0.40% 11 0.27%

100 To 149 1 0.31% 1 0.04% 2 0.05%

>150 0 0.00% 0 0.00% 0 0.00%

Total 324 100% 2,745 100% 4,062 100%

No. of Times

Cited


Table 4.16 Citation counts at NUS-ISE, NUS-ECE, and NTU-EEE

0

5

10

15

20

25

30

35

40

45

50

0 (uncit

ed) 1

2 To 9

10 To 1

9

20 To 4

9

50 To 9

9

100 To 1

49>150

Number of Times Cited

% o

f P

ub

licati

on

s

NUS-ECE

NTU-EEE

NUS-ISE

Figure 4.5 Comparison of citations received by NUS-ISE, NUS-ECE, and NTU-EEE publications

The 10 most-cited publications, the frequency of citations and self citations are presented

in Table 4.17. The publication with the highest impact is ‘Control Parametrization – A Unified

Approach to Optimal-Control Problem with General Constraints’ by Goh and Teo (1988) with

102 citations, followed by ‘A Survey of Index Decomposition Analysis in Energy and

Environmental Studies’ by Ang and Zhang (2000) with 49 citations.


47

It should be noted, however, that only one publication has no self-citation. Hyland (2003)

pointed out that self-citation is a strategy to strengthen the author’s knowledge claims, research

credibility, and wider standing in a research area.

The self-citation rate across all disciplines is 9%, with 15% in physical sciences, 6% in

social sciences and 3% in humanities (Snyder and Bonzi, 1998). NUS-ISE has multi-disciplinary

roots of physical and social sciences as will be described in the multidimensional scaling analysis.

Hence, the expected self-citation rate of NUS-ISE publication should be around 10.5%. However,

based on the 13 most-cited articles, it is found that the self citation rate is much higher at 38.2%.

In the 13 most-cited articles, the article with the highest self-citation rate is ‘A Computational

Method For Combined Optimal Parameter Selection And Optimal-Control Problems With

General Constraints’ with 77.78% self-citation rate.

Quantity %

1 Goh, CJ; Teo, KLControl Parametrization - A Unified Approach To Optimal-

Control Problems With General Constraints102 28 27.45%

2 Ang, BW; Zhang, FQA Survey Of Index Decomposition Analysis In Energy And

Environmental Studies49 10 20.41%

3 Ang, BW; Choi, KHDecomposition Of Aggregate Energy And Gas Emission

Intensities For Industry: A Refined Divisia Index Method35 16 45.71%

4 Ang, BWDecomposition Methodology In Industrial Energy Demand

Analysis35 9 25.71%

5 Ang, BW; Lee, SYDecomposition Of Industrial Energy-Consumption - Some

Methodological And Application Issues31 10 32.26%

Cheng, TCE Optimal Due-Date Assignment In A Job Shop 27 8 29.63%

Quaddus, MAA Generalized-Model Of Optimal Due-Date Assignment By

Linear-Programming27 0 0.00%

7 Ang, BWDecomposition Of Industrial Energy-Consumption - The Energy

Intensity Approach22 10 45.45%

8 Teo, KL; Goh, CJA Simple Computational-Procedure For Optimization Problems

With Functional Inequality Constraints20 10 50.00%

Ang, BW; Zhang, FQ;

Choi, KH

Factorizing Changes In Energy And Environmental Indicators

Through Decomposition21 10 47.62%

Goh, CJ; Teo, KLMiser - A Fortran Program For Solving Optimal-Control

Problems19 14 73.68%

Ang, BW; Pandiyan,

G

Decomposition Of Energy-Induced Co2 Emissions In

Manufacturing18 4 22.22%

Teo, KL; Goh, CJ

A Computational Method For Combined Optimal Parameter

Selection And Optimal-Control Problems With General

Constraints

18 14 77.78%

Self Citation

6

9

10

Publication TitleRank AuthorsTimes

Cited

Table 4.17 Top 10 impact articles published by NUS-ISE

Journal Impact Factor

In the period of 20 years, NUS-ISE published 324 papers in 108 unique journals. So, on

average there are 3 publications in each journal. Of the 324 publications, 43.2% were published in

the 11 most popular journals, while 54 out of the 108 journals have only 1 NUS-ISE publications.

Table 4.18 summarises the top 11 journals among the NUS-ISE faculties and researchers with the

respective Journal Impact Factors (JIF).


48

The average JIF of the 11 most popular journals are 0.572, while the most prestigious

among the journals is Energy Policy with a JIF of 0.958. Overall, the average JIF is 0.724, with

Journal of the American Medical Informatics Association as the most prestigious journal with a

JIF of 4.339. The JIF used in this study is the 2005 JIF, which means the JIF indicates the

proportion of number of citations received in year 2005 by publications in year 2003 and 2004

publications of the journals. However, even if only the 2003 and 2004 NUS-ISE publications are

considered, the JIF are still comparable at 0.528.

Quantity JIF (2005)

1 ENERGY 27 0.685

2 QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 16 0.210

3 ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 14 0.333

4 RELIABILITY ENGINEERING & SYSTEM SAFETY 13 0.747

5 COMPUTERS & INDUSTRIAL ENGINEERING 12 0.347

6 ENERGY ECONOMICS 10 0.564

6 ENERGY POLICY 10 0.958

6 EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 10 0.824

6 INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 10 0.481

10 ADVANCES IN ENGINEERING SOFTWARE 9 0.263

10 IIE TRANSACTIONS 9 0.476

Rank Journal TitleNumber of Publications

Table 4.18 Top 10 popular journals at NUS-ISE

Social Network Analysis

General Parameters

Table 4.19 summarises the general network parameters of the NUS-ISE author-to-author

sociograms in 4 different time windows. It can be seen that over the years, the number of nodes

(i.e. authors) increased significantly from 69 authors in 1986-1995 to 164 authors in 1996-2005.

In the 20 years period, there is only one author –Paul, H. – who is not connected to any other

author. According to the data retrieved from Web of Science®, he published his only article is

1986. This, however, is only from the journals indexed by Web of Science®. There is a possibility

that he has authored more articles and collaborated with other authors. But, it is difficult to trace

as Web of Science® only indexes the full name of authors starting from 2006.

There are 4 to 6 components in each time window, and the main component includes

around 74% to 91% of all the authors. This is in contrast with what Wee (2006) found in business

schools where inclusiveness of the networks hover around only 8% to 20%.


49

Time

Window

No. of

Nodes

No. of

ComponentsNo. of Isolates

Average Number of

Nodes per Component

Size of Main

ComponentInclusiveness

1986-1995 69 4 2 16.75 62 0.90

1991-2000 91 6 0 15.17 67 0.74

1996-2005 164 6 0 27.33 146 0.89

1986-2005 212 6 1 35.17 193 0.91

Table 4.19 General parameters of NUS-ISE co-authorship networks

Density

Although the author-to-author sociograms have high degrees of inclusiveness, the density

is pretty low as shown in Table 4.20. In fact, the density is not even 10% of the possible

connections in the networks. One of the reasons is the large number of authors in the networks

who authored only 1 article. These authors –57% of total number of authors– are usually

undergraduate and graduate students, visiting researchers or visiting professors who are only in

the department for a short-term period.

Density Std. Deviation Density Std. Deviation

1986-1995 0.0759 0.445 0.0878 0.4776

1991-2000 0.073 0.4845 0.1131 0.6257

1996-2005 0.0458 0.4745 0.0542 0.5251

1986-2005 0.0353 0.4164 0.0406 0.4521

Whole Network Main ComponentTime Window

Table 4.20 Density of NUS-ISE co-authorship networks

With the high level of inclusiveness but low level of density, this means that there will be

a certain number of authors who become the important links in the networks. One way to evaluate

the importance of authors in their network is by looking at their centrality. However, to measure

the centrality of the authors, the geodesic distance between authors need to be found, which will

be presented next.

Distance

Table 4.21 shows the average distances between authors in the main component. Over the

years, the average geodesic distances did not change much, ranging from 2.941 to 3.226 with the

maximum distance is 7. This further indicates the existence of authors with high level of

connections and as a result become the most “between” authors.

The short average geodesic distances between authors in NUS-ISE are comparable with

the Small World Effect proposed by Milgram (1967). Milgram proposed that the distance between

a person to another in the world is generally short and must be less than six. Although there are

cases where the geodesic distance is 7, the average geodesic distances of authors in NUS-ISE

department are well below the limit (i.e. 6).


50

Time Window Average Distance Max. Distance

1986-1995 3.159 6

1991-2000 2.941 5

1996-2005 3.111 7

1986-2005 3.226 7

Table 4.21 Distances in NUS-ISE co-authorship networks

Centrality

Degree centrality

The average degree centralities and their standard deviations of the sociograms are shown

in Table 4.22. Although the degree centralities look similar, the average levels of connectedness

of the authors are decreasing. This is because the number of possible connections had also

increased as the size of the main components grew, just as has been indicated with the decreasing

level of density in Table 4.20.

Time Window Degree Std. Deviation

1986-1995 5.355 6.599

1991-2000 7.463 11.785

1996-2005 7.863 18.905

1986-2005 7.793 19.118

Table 4.22 Average degree centrality of NUS-ISE co-authorship networks

Over the years, the authors with the highest degree centralities also change. Table 4.19

shows how Xie are the author with the widest network in NUS-ISE in term of the collaboration in

publishing articles, followed by Goh, and Ang. Unsurprisingly, all three authors play important

roles not only in NUS-ISE but also in Industrial Engineering field. Xie is the Program Manager of

NUS-ISE Master of Science and also the Deputy Director of NUS-ISE’s Quality and Innovation

Research Centre. In addition, Xie is also an editor or an associate editor of many different journals

such as International Journal of Reliability, Quality and Safety Engineering, IIE Transactions,

International Journal of Innovation and Technology Management, IEEE Transactions on

Reliability, Asia Pacific Journal of Operational Research, and Computational Statistics and Data

Analysis. Interestingly, many of the journals are also the most popular journals where NUS-ISE

publications were published as shown in Table 4.18. Goh is Director Quality and Innovation

Research Centre under NUS-ISE and has recently been appointed to the Advisory Committee of

the Quality Engineering Journal of the American Society for Quality. While Ang is the Head of

NUS-ISE department and also an Associate Editor of Energy - The International Journal and

Energy Economics, and a member of the editorial boards of Energy Policy, Journal of Urban

Technology, and Energy & Environment.


51

1986-1995 1991-2000 1996-2005 1986-2005

XIE, M 8 1 1 1

GOH, TN 4 2 2 2

ANG, BW 1 3 4 3

POH, KL 9 6 3 4

TANG, LC 6 4 5 5

ONG, HL 5 5 6 6

LAI, CD - 7 7 7

CHEW, EP 10 11 11 8

TEO, KL 2 - - 9

GOH, CJ 3 - - 10

Table 4.23 Top 10 central authors at NUS-ISE

Closeness

The result of closeness centrality also indicates that Xie is the most central figure in NUS-

ISE as shown in Appendix F. The closeness centrality of the network as a whole increase over the

years following the growth of the size of the main component as presented in Table 4.24.

Time Window Closeness Std. Deviation

1986-1995 192.71 33.232

1991-2000 194.09 27.657

1996-2005 451.096 77.013

1986-2005 619.347 106.017

Table 4.24 Average closeness centrality of NUS-ISE co-authorship networks

Betweenness

Table 4.25 shows the average betweenness of the networks as a whole. It can be seen that

although the betweenness increase over the years, the standard deviations also increase

significantly. This indicates that there are certain numbers of authors who are getting more central

in the network, while the authors with few publications are getting less significant to the network.

Xie is still the most central figure according to the betweenness centrality as can be seen

Appendix F.

Time Window Betweenness Std. Deviation

1986-1995 65.855 165.203

1991-2000 64.045 214.708

1996-2005 153.048 617.316

1986-2005 213.674 894.297

Table 4.25 Average betweenness centrality of NUS-ISE co-authorship networks

Visualisation using UCINET (Version 6.0)

Based on the connections among the different authors and the values of betweenness

centrality of each author, the social networks of NUS-ISE in the 4 time windows were generated

using NetDraw. It can be seen how the authors with the biggest sizes of nodes, which indicate the

importance of the authors in the networks remain the same over the 20 years period. The authors

with high betweenness centrality usually also become the cut-points where if they leave the


52

network, its numbers of components will increase significantly and there could be many

unconnected nodes.

The fact that the degree of collaborations increases over the years can also be seen clearly

in Figures 4.6, 4.7, 4.8, and 4.9, which illustrate how the network grows and how the overall

network of 20 years looks like.

Figure 4.6 NUS-ISE co-authorship networks in the period of 1986-1995



53




54

Multidimensional Scaling

Using the top 30 highest cited journals in each time window shown in Tables 4.26, 4.27,

4.28, and 4.29, the 30 journals co-citation rates were recorded in the raw co-citation matrices.

These matrices were then converted into correlation matrices before the multidimensional scaling

analysis was applied using ALSCAL (SPSS).

The 30 highest cited journals in each time window accounted for 34.66% of all references

by NUS-ISE publications in 1986-2005, 40.99% in 1991-2000, 42.08% in 1996-2005, and

38.55% in 1986-2005.

It can be seen that over the years the top 30 highly cited journals only changed slightly.

However, the ranks of the journals change over the years. Notably, in the 1996-2005 time

window, the Journal of Quality Technology and IEEE Transactions on Reliability had become the

two most cited journals after overtaking Energy and Energy Economics which were the two most

cited journals in the earlier time windows. This may indicate the shift of NUS-ISE research focus

more towards Quality Engineering field.

The only significant change of rank happens to Journal of Optimization Theory and

Applications, which was the 3rd highest cited journals in 1986-1995, but was not in top 30 in the

rest of time windows.

Rank Legend Journal TitleTimes

Cited

1 A ENERGY 105

2 B ENERGY ECONOMICS 80

3 C JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 43

4 D IEEE TRANSACTIONS ON AUTOMATIC CONTROL 39

5 E OPERATIONS RESEARCH 36

6 F MANAGEMENT SCIENCE 34

7 G ENERGY POLICY 32

8 H TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE 28

9 I IEEE TRANSACTIONS ON RELIABILITY 19

10 J EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 18

11 K WATER RESOURCES RESEARCH 17

12 L QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 15

13 M AUTOMATICA 14

14 N COMPUTERS & OPERATIONS RESEARCH 14

15 O JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 14

16 P RELIABILITY ENGINEERING & SYSTEM SAFETY 10

17 Q TECHNOMETRICS 10

18 R JOURNAL OF QUALITY TECHNOLOGY 9

19 S JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT-ASCE 9

20 T ANNUAL REVIEW ENERGY 8

21 U JOURNAL OF APPLIED PROBABILITY 6

22 V COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 5

23 W IEEE TRANSACTIONS ON ADVANCED PACKAGING 5

24 X INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 5

25 Y INTERNATIONAL JOURNAL OF QUALITY AND RELIABILITY MANAGEMENT 4

26 Z JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION 4

27 AA NAVAL RESEARCH LOGISTICS 3

28 AB TRANSPORTATION SCIENCE 3

29 AC IIE TRANSACTIONS 2

30 AD JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY 2

Table 4.26 Top 30 most cited journals – 1986-1995


55


Cited

1 A ENERGY 153

2 B ENERGY ECONOMICS 130

3 C JOURNAL OF QUALITY TECHNOLOGY 72

4 D QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 61

5 E IEEE TRANSACTIONS ON RELIABILITY 51

6 F ENERGY POLICY 48

7 G TECHNOMETRICS 44

8 H OPERATIONS RESEARCH 35

9 I EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 27

10 J MANAGEMENT SCIENCE 25

11 K COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 24

12 L INTERNATIONAL JOURNAL OF QUALITY AND RELIABILITY MANAGEMENT 21

13 M TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE 20

14 N RELIABILITY ENGINEERING & SYSTEM SAFETY 17

15 O NAVAL RESEARCH LOGISTICS 16

16 P WATER RESOURCES RESEARCH 14

17 Q IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 14

18 R MICROELECTRONICS RELIABILITY 13

19 S JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 12

20 T IEEE TRANSACTIONS ON ADVANCED PACKAGING 12

21 U JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION 12

22 V BIOMETRIKA 12

23 W ANNUAL REVIEW ENERGY 11

24 X IIE TRANSACTIONS 11

25 Y INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 10

26 Z JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY 10

27 AA IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT 10

28 AB JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT-ASCE 9

29 AC INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 7

30 AD COMPUTERS & OPERATIONS RESEARCH 6



Cited

1 A JOURNAL OF QUALITY TECHNOLOGY 163

2 B IEEE TRANSACTIONS ON RELIABILITY 162

3 C ENERGY 117

4 D QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 101

5 E TECHNOMETRICS 101

6 F MANAGEMENT SCIENCE 101

7 G ENERGY ECONOMICS 94

8 H OPERATIONS RESEARCH 83


10 J INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 63

11 K IIE TRANSACTIONS 60

12 L RELIABILITY ENGINEERING & SYSTEM SAFETY 52

13 M COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 48

14 N IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 45

15 O NAVAL RESEARCH LOGISTICS 38

16 P ENERGY POLICY 37

17 Q JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION 35

18 R INTERNATIONAL JOURNAL OF QUALITY AND RELIABILITY MANAGEMENT 31

19 S BIOMETRIKA 30

20 T COMPUTERS & OPERATIONS RESEARCH 30

21 U JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 24

22 V JOURNAL OF APPLIED PROBABILITY 24

23 W MICROELECTRONICS RELIABILITY 23

24 X INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 23

25 Y IEEE TRANSACTIONS ON ADVANCED PACKAGING 21

26 Z JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY 18

27 AA IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT 18

28 AB INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 18

29 AC TRANSPORTATION SCIENCE 18

30 AD IEEE TRANSACTIONS ON AUTOMATIC CONTROL 10



56


Cited

1 A ENERGY 222

2 B IEEE TRANSACTIONS ON RELIABILITY 181

3 C ENERGY ECONOMICS 174

4 D JOURNAL OF QUALITY TECHNOLOGY 172

5 E MANAGEMENT SCIENCE 135

6 F OPERATIONS RESEARCH 119

7 G QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 116

8 H TECHNOMETRICS 111


10 J ENERGY POLICY 69

11 K INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 68

12 L IIE TRANSACTIONS 62

13 M RELIABILITY ENGINEERING & SYSTEM SAFETY 62

14 N COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 53

15 O JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 52

16 P IEEE TRANSACTIONS ON AUTOMATIC CONTROL 48

17 Q IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 46

18 R COMPUTERS & OPERATIONS RESEARCH 44

19 S NAVAL RESEARCH LOGISTICS 41

20 T JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION 39

21 U JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 38

22 V INTERNATIONAL JOURNAL OF QUALITY AND RELIABILITY MANAGEMENT 35

23 W BIOMETRIKA 31

24 X JOURNAL OF APPLIED PROBABILITY 30

25 Y TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE 28

26 Z IEEE TRANSACTIONS ON ADVANCED PACKAGING 26

27 AA MICROELECTRONICS RELIABILITY 24

28 AB INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 23

29 AC TRANSPORTATION SCIENCE 21

30 AD JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY 20


Journal Citation Report® provides the subject domain classification of each journal. These

subject domains were the ones used to cluster the different journals in the bibliographic maps.

Figures 4.10, 4.11, 4.12, and 4.13 illustrate the subject domains which are most cited in NUS-ISE

publications. Five clusters consistently appear in the four bibliographic, namely (1) Statistics &

Probability; (2) Quality Reliability; (3) Electrical Engineering; (4) Operations Research and

Management Science; and (5) Environmental Science and Economics.

The five clusters can be further mapped into the 3 research groups in NUS-ISE, namely

Engineering Management, Quality Engineering, and Systems Engineering. Based on the

descriptions of each department, Engineering Management includes Operations Research and

Management Science; Quality Engineering includes Quality Reliability and Statistics &

Probability; and Systems Engineering includes Electrical Engineering and Environmental Studies.

The fact that the five clusters representing the subject domains of NUS-ISE have

stabilised over the twenty years period reflect the maturity of Industrial Engineering discipline in

NUS-ISE. In Kuhnian sense, Industrial Engineering can then be called a “normal science”, that is

problem solving and mopping up work guided by a certain paradigm (Kuhn, 1970).


57

Figure 4.10 Bibliographic map of NUS-ISE – 1986-1995



58




59

Limitations of the Research

The limitations of the research can be classified into three groups, all of which related to

the publication data. The first limitation is the fact that Web of Science® is known to have an

English-language bias and is very selective in choosing the journals to be indexed (Ng, 2004;

Wee, 2006). This will immediately eliminate the non-English publications by the NUS-ISE if any.

Less renowned or region-based journals not being indexed by Web of Science® have proven to be

contributing a significant percentage of NUS-ISE publication. In a 6-years period from 2000 to

2005, 60 publications from 46 journals were not indexed by Web of Science®, which only indexed

150 NUS-ISE publications during the same period. Hence, the impact of the publications in the

un-indexed journals could not be determined.

Secondly, the un-indexed journals also cause inability to evaluate the prestige of the

journals which in this research found through the database provided in Journal Citation Report®.

Finally, all scientometrics, social network analysis, and multidimensional scaling analysis

were used to analyse the publication data of NUS-ISE. However, this publication data only

includes the publications in journals. Other methods of scholarly communication such as

monographs, conference papers, and patents were excluded. So, it should be noted that the result

of this research presents only one side of scholarly communications, which is journals.

Chapter Five - Conclusion and Future Work

60

CHAPTER FIVE

CONCLUSION AND FUTURE WORK

This dissertation examines the research publications of the Industrial and Systems

Engineering Department of National University of Singapore (NUS-ISE) for a 20-years period

from 1986 to 2005. Scientometrics techniques, social network analysis, and multidimensional

scaling were applied to analyse the publication data retrieved from the Institute of Scientific

Information’s Web of Science® and Journal Citation Report®. The data were processed and

analysed using Microsoft Excel, UCINET (Version 6.0), and SPSS.

Based on the scientometrics techniques, the NUS-ISE publications over the years were

greatly outnumbered by the NUS-ECE and NUS-EEE publications. Over the 20-years period,

NUS-ISE produced 324 publications, while in 15-years period from 1990 to 2004, NUS-ECE and

NTU-EEE produced 2745 and 4062 publications respectively. This, however, does not show that

the NUS-ISE authors are less productive, but it reflects the different manpower strength in each

department, where NTU-EEE has over 400 faculties and research fellows; NUS-ECE has 213,

while NUS-ISE is only 23 people strong.

In terms of producing the publications, authors in all three departments tend to collaborate

with other authors. More than 85% of the publications in each of the three departments are the

result of collaboration. On average, every NUS-ISE publication is a result of collaboration among

2.54 authors. This is slightly below the average authors per publication in NUS-ECE and NTU-

EEE, which average 3.48 and 3.40 subsequently.

Over the years, the numbers of references per publication have been increasing in all three

departments. The overall averages of references are 16.72 for NUS-ISE, 14.23 for NUS-ECE, and

13.90 for NTU-EEE. The other side of references is the citations received by the publications. The

citations rates in the three departments are also comparable. On average, each NUS-ISE

publication receives 4.15 citations, 3.82 citations for each NUS-ECE publications, and 3.22 for

NTU-EEE. In NUS-ISE, the top 13 publications account for 31.5% of the total citations. It was

also found that 38.2% of the citations received by the top 13 publications are self citations.

From the social network perspective, it was found that the NUS-ISE’s author-to-author

sociograms were not fragmentary with the overall inclusiveness of 0.91, which means that 91% of

the authors are in the main component of the sociogram. But, it was also found that the majority

of the authors are not directly connected to other authors. There were a number of leading figures

who played the role of “connectors” and at the same time became the cut-points of the

sociograms. These figures, unsurprisingly, were also the most prolific authors in the department

and held important roles not only in NUS-ISE but also in the Industrial Engineering discipline.

Chapter Five - Conclusion and Future Work

61

Some of the roles were the head of the department, directors of research group, and also editors or

associate editors of many journals.

The existence of these “connectors” also caused the small world effect in the author-to –

author sociograms, where each author can reach other authors in the sociogram within an average

distance of 3.226.

Finally, the multidimensional scaling analysis of the journal co-citation rates creates

bibliographic maps, which indicate that the industrial engineering discipline in NUS-ISE are

formed by five subject domains, namely (1) Statistics & Probability; (2) Quality Reliability; (3)

Electrical Engineering; (4) Operations Research and Management Science; and (5) Environmental

Science and Economics. The five subject domains reflect the focus of 3 research groups in NUS-

ISE, namely Engineering Management, Quality Engineering, and Systems Engineering. Over the

years, the 5 subject domains consistently appeared in the bibliographic maps. This indicates the

maturity of the Industrial Engineering field, which in Kuhnian sense can be called as “normal

science”.

Future Work and Recommendation

This dissertation made use of the NUS-ISE publication data indexed by the Institute of

Scientific Information’s Web of Science® and Journal Citation Report® and subsequently analysed

them based on three perspectives, namely scientometrics, social network analysis, and

multidimensional scaling.

The first recommendation is to make use of more than one source of publication data,

such as Scopus and Google Scholar to obtain comprehensiveness of the publication data. This will

address the limitations encountered when conducting this research where many of less renowned

and region-based journals are not indexed by Web of Science®. In its database, Web of Science®

also does not index web documents and e-journals, which numbers are increasing significantly in

recent years.

Secondly, other scholarly communication media such as conferences and patents can be

explored to have a more comprehensive evaluation of the scientific outputs of a certain

department or organisation.

Finally, there are many type of multivariate analysis other than multidimensional scaling

such factor analysis and principle component analysis. It will be interesting to see whether the

result of the various multivariate analyses will generate consistent outputs.

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62

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Appendix A

A-1

APPENDICES

APPENDIX A

Publications of NUS-ISE from 1986 to 2005 indexed in Web of Science®.

(This list was retrieved using the Web of Science® database)

No Publication Data PY

1

Ang, BW A Method For Estimating Non-Commercial Energy-Consumption In The Household Sector Of Developing-Countries JOURNAL OF URBAN TECHNOLOGY NR: 38; TC: 9

1986

2

Cheng, TCE Eoq With Limited Backorder Delays IEEE TRANSACTIONS ON RELIABILITY NR: 2; TC: 1

1986

3

Cheng, TCE Optimal Due-Date Assignment For A Single-Machine Sequencing Problem With Random Processing Times QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 12; TC: 7

1986

4

Cheng, TCE Due-Date Determination For A Single-Machine Shop With Spt Dispatching ENERGY NR: 0; TC: 3

1986

5

Cheng, TCE Optimal Due-Date Assignment In A Job Shop JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY NR: 0; TC: 27

1986

6

Goh, TN; Ong, HL; Lee, YO A New Approach To Statistical Forecasting Of Daily Peak Power Demand ENERGY NR: 0; TC: 4

1986

7

Goh, TN; Varaprasad, N A Statistical Methodology For The Analysis Of The Life-Cycle Of Reusable Containers ENERGY NR: 7; TC: 10

1986

8

Loo, EH; Goh, TN; Ong, HL A Heuristic Approach To Scheduling University Timetables QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 11; TC: 1

1986

9

Moore, JB; Teo, KL Smoothing As An Improvement On Filtering In High Noise JOURNAL OF HYDRAULIC ENGINEERING-ASCE NR: 2; TC: 2

1986

10

Paul, H An Application Of Stochastic Geometric-Programming To Heat-Exchanger Design ENERGY ECONOMICS NR: 6; TC: 1

1986

11

Poh, KL; Quaddus, MA A Spread Sheet-Like Input Routine For Optimization Problems QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 2; TC: 2

1986

12

Quaddus, MA On Applying Logistic-Models In Technological-Forecasting JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION NR: 11; TC: 1

1986

Appendix A

A-2


13

Quaddus, MA; Holzman, Ag Imolp - An Interactive Method For Multiple Objective Linear-Programs SCANDINAVIAN JOURNAL OF WORK ENVIRONMENT & HEALTH NR: 26; TC: 2

1986

14

Teo, KL; Wilson, SJ Convergence Of A Feasible Directions Algorithm For A Distributed Optimal-Control Problem Of Parabolic Type With Terminal Inequality Constraints EUROPEAN JOURNAL OF OPERATIONAL RESEARCH NR: 8; TC: 0

1986

15

Teo, KL; Wong, Kh; Wu, Zs An Optimal-Control Problem Involving A Class Of Linear Time-Lag Systems QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 13; TC: 2

1986

16

Wang, CM; Thevendran, V; Teo, KL; Kitipornchai, S Optimal-Design Of Tapered Beams For Maximum Buckling Strength NAVAL RESEARCH LOGISTICS NR: 10; TC: 3

1986

17

Ang, BW A Cross-Sectional Analysis Of Energy Output Correlation INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS NR: 23; TC: 11

1987

18

Ang, BW Energy Output Ratios And Sectoral Energy Use - The Case Of Southeast-Asian Countries QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 24; TC: 5

1987

19

Ang, BW Structural-Changes And Energy-Demand Forecasting In Industry With Applications To 2 Newly Industrialized Countries ENERGY ECONOMICS NR: 26; TC: 11

1987

20

Cheng, TCE; Teo, KL Further Extensions Of A Student-Related Optimal-Control Problem IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS NR: 2; TC: 3

1987

21

Ong, HL; Goh, TN Routing And Scheduling Of Wardens For Public Car Park Inspection COMMUNICATIONS IN STATISTICS-THEORY AND METHODS NR: 4; TC: 1

1987

22

Quaddus, MA A Generalized-Model Of Optimal Due-Date Assignment By Linear-Programming JOURNAL OF APPLIED PROBABILITY NR: 11; TC: 27

1987

23

Teo, KL Convergence Analysis For A Computational Method For Optimal-Control ENERGY ECONOMICS NR: 12; TC: 2

1987

24

Teo, KL; Goh, CJ A Simple Computational-Procedure For Optimization Problems With Functional Inequality Constraints INTERNATIONAL JOURNAL OF VEHICLE DESIGN NR: 7; TC: 20

1987

25

Teo, KL; Jepps, G; Moore, Ej; Hayes, S A Computational Method For Free Time Optimal-Control Problems, With Application To Maximizing The Range Of An Aircraft-Like Projectile MICROELECTRONICS AND RELIABILITY NR: 18; TC: 2

1987

Appendix A

A-3


26

Ang, BW Electricity Output Ratio And Sectoral Electricity Use - The Case Of East And Southeast Asian Developing-Countries INTERNATIONAL JOURNAL OF VEHICLE DESIGN NR: 6; TC: 4

1988

27

Ang, BW; Oh, ST Transport And Traffic Management Schemes And Energy Saving In Singapore JOURNAL OF SYSTEMS AND SOFTWARE NR: 10; TC: 7

1988

28

Ang, BW; Teo, KL; Wang, CM Optimal Shape Of Arches Under Bending And Axial-Compression JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT-ASCE NR: 6; TC: 2

1988

29

Ang, BW; Yap, CM The Use Of Growth-Curves In Forecasting Interfuel Substitution Processes RELIABILITY ENGINEERING & SYSTEM SAFETY NR: 17; TC: 2

1988

30

Goh, CJ; Chew, EP; Fwa, TF Discrete And Continuous Models For Computation Of Optimal Vertical Highway Alignment RELIABILITY ENGINEERING & SYSTEM SAFETY NR: 11; TC: 9

1988

31

Goh, CJ; Teo, KL A Mathematical-Model Of Optimal Drug Administration In The Presence Of Random Noise MICROELECTRONICS AND RELIABILITY NR: 0; TC: 0

1988

32

Goh, CJ; Teo, KL Miser - A Fortran Program For Solving Optimal-Control Problems INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS NR: 13; TC: 19

1988

33

Goh, CJ; Teo, KL On Minimax Eigenvalue Problems Via Constrained Optimization ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 11; TC: 7

1988

34

Goh, CJ; Teo, KL Control Parametrization - A Unified Approach To Optimal-Control Problems With General Constraints TECHNOVATION NR: 47; TC: 101

1988

35

Goh, CJ; Wang, CM Optimization Of Segment-Wise Linear Structures Via Optimal-Control Theory MICROELECTRONICS AND RELIABILITY NR: 8; TC: 2

1988

36

Quaddus, MA; Poh, KL A User-Friendly Program Of Human Judgments In Engineering Decision-Analysis ADVANCES IN ENGINEERING SOFTWARE NR: 7; TC: 0

1988

37

Tang, LC; Goh, CJ; Lim, Sc On The Reliability Of Components Subject To Sliding Wear - A 1St Report STATISTICS & PROBABILITY LETTERS NR: 12; TC: 6

1988

38

Teo, KL; Goh, CJ On Constrained Optimization Problems With Nonsmooth Cost Functionals IEEE TRANSACTIONS ON RELIABILITY NR: 16; TC: 8

1988

39

Teo, KL; Lim, CC Time Optimal-Control Computation With Application To Ship Steering ENERGY NR: 16; TC: 5

1988

Appendix A

A-4


40

Wu, ZS; Teo, KL Convex Optimal-Control Problem Involving A Class Of Linear Hyperbolic Systems With Constraints INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH NR: 9; TC: 0

1988

41

Ang, BW Asean Energy Demand - Current Trends And Future Outlook WATER RESOURCES RESEARCH NR: 14; TC: 0

1989

42

Ang, BW; Fwa, TF A Study On The Fuel-Consumption Characteristics Of Public Buses ENERGY NR: 13; TC: 5

1989

43

Chew, EP; Goh, CJ On Minimum Time Optimal-Control Of Batch Crystallization Of Sugar RELIABILITY ENGINEERING & SYSTEM SAFETY NR: 13; TC: 6

1989

44

Chew, EP; Goh, CJ; Fwa, TF Simultaneous-Optimization Of Horizontal And Vertical Alignments For Highways JOURNAL OF MATERIALS PROCESSING TECHNOLOGY NR: 16; TC: 13

1989

45

Goh, CJ; Tang, LC; Lim, SC Reliability Modeling Of Stochastic Wear-Out Failure JOURNAL OF HYDRAULIC ENGINEERING-ASCE NR: 19; TC: 6

1989

46

Goh, CJ; Teo, KL Species Preservation In An Optimal Harvest Model With Random Prices INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS NR: 16; TC: 2

1989

47

Goh, TN Some Practical Considerations In The Design Of Manufacturing Process Experiments ENERGY NR: 0; TC: 0

1989

48

Huang, HC; Ong, HL Expected Performance Of 2 Lot-Sizing Heuristics In A Finite Planning Horizon ENERGY NR: 11; TC: 0

1989

49

Ong, HL An Algorithm For Solving Certain Large-Scale Sparse Linear-Systems ENERGY NR: 4; TC: 0

1989

50

Ong, HL; Huang, HC Asymptotic Expected Performance Of Some Tsp Heuristics - An Empirical-Evaluation ENERGY NR: 18; TC: 10

1989

51

Tang, LC; Olorunniwo, Fo A Maintenance Model For Repairable Systems ENERGY NR: 11; TC: 0

1989

52

Teo, KL; Goh, CJ A Computational Method For A Class Of Optimal Relaxed Control-Problems ENERGY NR: 19; TC: 5

1989

53

Teo, KL; Goh, CJ A Computational Method For Combined Optimal Parameter Selection And Optimal-Control Problems With General Constraints ENERGY NR: 19; TC: 18

1989

Appendix A

A-5


54

Teo, KL; Goh, CJ; Lim, CC A Computational Method For A Class Of Dynamical Optimization Problems In Which The Terminal Time Is Conditionally Free ENERGY ECONOMICS NR: 19; TC: 2

1989

55

Teo, KL; Wong, Kh; Goh, CJ Optimal Maintenance Of A System Of Machines With Weakest-Link-Dependent Performance ENERGY NR: 30; TC: 0

1989

56

Wang, CM; Goh, CJ; Chew, EP An Energy Approach To Elastic Stability Analysis Of Multiply Braced Monosymmetric I-Beams JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY NR: 15; TC: 0

1989

57

Ang, BW; Deng, CC The Effects Of Maintenance On The Fuel Efficiency Of Public Buses ENERGY NR: 9; TC: 1

1990

58

Ang, BW; Tan, KC Forecasting Of Diesel And Petrol Sales - An Evaluation Of Various Marketing Strategies INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH NR: 5; TC: 0

1990

59

Lim, Sc; Goh, CJ; Tang, LC The Interdependence Of Wear Events During Slow Sliding - A Statistical Viewpoint ADVANCES IN ENGINEERING SOFTWARE AND WORKSTATIONS NR: 10; TC: 0

1990

60

Ong, HL; Goh, TN; Poh, KL; Lim, Cc A Computerized Vehicle-Routing System For Refuse Collection ENERGY POLICY NR: 16; TC: 6

1990

61

Poh, KL; Quaddus, MA A Hybrid Approach To Multiobjective Linear Optimization WEAR NR: 28; TC: 1

1990

62

Wee, EHT; Nee, AYC; Goh, TN Off-Line Adaptive Optimization Of Cnc Lathe Turning MECHANICS OF STRUCTURES AND MACHINES NR: 0; TC: 0

1990

63

Ang, BW Statistical Evaluation Of Fuel Consumption Of Buses With Specific Operational Changes ENERGY NR: 6; TC: 0

1991

64

Ang, BW A Statistical-Analysis Of Energy Coefficients ENERGY NR: 29; TC: 4

1991

65

Ang, BW; Fwa, TF; Poh, CK A Statistical Study On Automobile Fuel Consumption EUROPEAN JOURNAL OF OPERATIONAL RESEARCH NR: 11; TC: 4

1991

66

Ang, BW; Fwa, TF; Poh, CK A Statistical-Analysis Of The Fuel Efficiencies Of Public Buses JOURNAL OF MECHANICAL WORKING TECHNOLOGY NR: 6; TC: 2

1991

67

Ang, BW; Goh, TN; Liu, XQ Residential Electricity Demand In Singapore TRANSPORTATION RESEARCH PART B-METHODOLOGICAL NR: 17; TC: 4

1992

Appendix A

A-6


68

Ang, BW; Liu, XQ; Ong, HL Sector Disaggregation And The Effect Of Structural-Change On Industrial Energy-Consumption ADVANCES IN ENGINEERING SOFTWARE AND WORKSTATIONS NR: 19; TC: 8

1992

69

Ang, BW; Ng, TT The Use Of Growth-Curves In Energy Studies MATHEMATICAL BIOSCIENCES NR: 84; TC: 6

1992

70

Ang, BW; Ng, TT; Fwa, TF A Factorization Analysis Of Automobile Fuel Consumption In Actual Traffic RELIABILITY ENGINEERING & SYSTEM SAFETY NR: 6; TC: 1

1992

71

Goh, TN An Organizational Approach To Product Quality Via Statistical Experiment Design CHEMICAL ENGINEERING COMMUNICATIONS NR: 0; TC: 0

1992

72

Ibrahim, Y; Liong, SY Calibration Strategy For Urban Catchment Parameters ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 14; TC: 6

1992

73

Liu, XQ; Ang, BW; Ong, HL Interfuel Substitution And Decomposition Of Changes In Industrial Energy-Consumption OPTIMAL CONTROL APPLICATIONS & METHODS NR: 25; TC: 13

1992

74

Ang, BW An Energy And Environmentally Sound Urban Transport-System - The Case Of Singapore IMA JOURNAL OF MATHEMATICAL CONTROL AND INFORMATION NR: 0; TC: 1

1993

75

Ang, BW Sector Disaggregation, Structural Effect And Industrial Energy Use - An Approach To Analyze The Interrelationships JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS NR: 15; TC: 9

1993

76

Ang, BW; Fwa, TF; Ng, TT Analysis Of Process Energy Use Of Asphalt-Mixing Plants RELIABILITY ENGINEERING & SYSTEM SAFETY NR: 13; TC: 0

1993

77

Chang, DS; Tang, LC Reliability Bounds And Critical Time For The Birnbaum-Saunders Distribution COMPUTERS & STRUCTURES NR: 12; TC: 13

1993

78

Goh, TN; Rahman, M; Seah, KHW; Lee, CH Influence Of The Substrate Material On The Effectiveness Of Coatings In Metal-Cutting TRANSPORTATION RESEARCH PART B-METHODOLOGICAL NR: 14; TC: 3

1993

79

Huang, HC; Ong, HL; Tan, Hh Construction Of Flight Crew Operating Patterns - A Successful Application Of Heuristic Procedures JOURNAL OF THE AUSTRALIAN MATHEMATICAL SOCIETY SERIES B-APPLIED MATHEMATICS NR: 18; TC: 0

1993

80

Ibrahim, Y; Liong, SY A Method Of Estimating Optimal Catchment Model Parameters CYBERNETICS AND SYSTEMS NR: 20; TC: 2

1993

81

Liong, SY; Ibrahim, Y; Chan, Wt; Law, CL Computer-Aided Catchment-Calibration Model ENERGY NR: 8; TC: 0

1993

Appendix A

A-7


82

Sun, Ys; Xie, M; Goh, TN; Ong, HL Development And Applications Of A 3-Parameter Weibull Distribution With Load-Dependent Location And Scale-Parameters SCRIPTA METALLURGICA NR: 16; TC: 1

1993

83

Tang, LC Limit-Theorems For Markov Random-Walks APPLIED MATHEMATICS AND OPTIMIZATION NR: 6; TC: 0

1993

84

Yap, CM; Souder, We A Filter System For Technology Evaluation And Selection ADVANCES IN ENGINEERING SOFTWARE AND WORKSTATIONS NR: 0; TC: 10

1993

85

Zhuang, L Economic Manufacturing Quantity In A Just-In-Time Delivery System - Discussion ADVANCES IN ENGINEERING SOFTWARE AND WORKSTATIONS NR: 0; TC: 1

1993

86

Ang, BW Decomposition Of Industrial Energy-Consumption - The Energy Intensity Approach JOURNAL OF ENGINEERING MECHANICS-ASCE NR: 24; TC: 21

1994

87

Ang, BW; Lee, Sy Decomposition Of Industrial Energy-Consumption - Some Methodological And Application Issues ENERGY POLICY NR: 27; TC: 31

1994

88

Ang, BW; Neoh, Kg An Energy And Environmental Assessment Of Road Transport Fuels JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS NR: 0; TC: 2

1994

89

Chang, Ds; Tang, LC Percentile Bounds And Tolerance Limits For The Birnbaum-Saunders Distribution ENERGY NR: 7; TC: 8

1994

90

Chang, Ds; Tang, LC Graphical Analysis For Birnbaum-Saunders Distribution INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE NR: 6; TC: 2

1994

91

Goh, TN Taguchi Methods In Practice - An Analysis Of Goh Paradox AUTOMATICA NR: 14; TC: 1

1994

92

Goh, TN Some Practical Issues In The Assessment Of Nonconforming Rates In A Manufacturing Process JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS NR: 0; TC: 1

1994

93

Liong, SY; Ibrahim, Y Estimation Of Peak Flow And Runoff Volume With Response-Surface Method PROBLEMS OF CONTROL AND INFORMATION THEORY-PROBLEMY UPRAVLENIYA I TEORII INFORMATSII NR: 14; TC: 1

1994

94

Poh, KL; Fehling, Mr; Horvitz, Ej Dynamic Construction And Refinement Of Utility-Based Categorization Models ENERGY ECONOMICS NR: 18; TC: 3

1994

95

Prabhu, Nu; Tang, LC Markov-Modulated Single-Server Queuing-Systems IEEE TRANSACTIONS ON AUTOMATIC CONTROL NR: 12; TC: 1

1994

Appendix A

A-8


96

Sun, Ys Revised Miners Rule And Its Application In Calculating Equivalent Loads For Components MATHEMATICAL MODELLING NR: 19; TC: 2

1994

97

Tang, LC; Chang, Ds Tolerance Limits For Inverse Gaussian Distribution COMPUTERS & INDUSTRIAL ENGINEERING NR: 7; TC: 4

1994

98

Tang, LC; Chang, Ds Reliability Bounds And Tolerance Limits Of 2 Inverse Gaussian Models ENERGY POLICY NR: 16; TC: 2

1994

99

Xie, M Untitled JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY NR: 12; TC: 0

1994

100

Zhao, M; Xie, M Em Algorithms For Estimating Software-Reliability Based On Masked Data ENERGY NR: 15; TC: 0

1994

101

Zhao, M; Xie, M A Model Of Storage Reliability With Possible Initial Failures JOURNAL OF THE AUSTRALIAN MATHEMATICAL SOCIETY SERIES B-APPLIED MATHEMATICS NR: 9; TC: 0

1994

102

Zhuang, L Towards A More Economic Production And Just-In-Time Delivery System ENGINEERING STRUCTURES NR: 0; TC: 7

1994

103

Zhuang, Wj; Xie, M Design And Analysis Of Some Fault-Tolerance Configurations Based On A Multipath Principle SYSTEMS & CONTROL LETTERS NR: 15; TC: 0

1994

104

Ang, BW Relieving Urban Traffic Congestion: The Singapore Area Licensing Scheme COMPUTERS & INDUSTRIAL ENGINEERING NR: 17; TC: 0

1995

105

Ang, BW Decomposition Methodology In Industrial Energy Demand Analysis COMPUTERS & OPERATIONS RESEARCH NR: 56; TC: 35

1995

106

Ang, BW Multilevel Decomposition Of Industrial Energy-Consumption SOCIO-ECONOMIC PLANNING SCIENCES NR: 52; TC: 15

1995

107

Chew, EP; Johnson, La Service Levels In Distribution-Systems With Random Customer Order Size ADVANCES IN ENGINEERING SOFTWARE AND WORKSTATIONS NR: 22; TC: 3

1995

108

Chew, EP; Tang, LC Warehouse Retailer System With Stochastic Demands - Nonidentical Retailer Case COMPUTERS & EDUCATION NR: 14; TC: 1

1995

109

Choi, Kh; Ang, BW; Ro, Kk Decomposition Of The Energy-Intensity Index With Application For The Korean Manufacturing-Industry JOURNAL OF THE AUSTRALIAN MATHEMATICAL SOCIETY SERIES B-APPLIED MATHEMATICS NR: 7; TC: 5

1995

Appendix A

A-9


110

Huang, Jp; Poh, KL; Ang, BW Decision-Analysis In Energy And Environmental Modeling JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS NR: 132; TC: 15

1995

111

Liong, SY; Shreeram, J; Ibrahim, Y Catchment Calibration Using Fractional-Factorial And Central-Composite-Designs-Based Response-Surface INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE NR: 14; TC: 2

1995

112

Ong, Cn; Chia, Se; Jeyaratnam, J; Tan, Kc Musculoskeletal Disorders Among Operators Of Visual-Display Terminals IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS NR: 19; TC: 9

1995

113

Seah, Khw; Rahman, M; Lee, Ch Comparing The Effectiveness Of Coatings On Carbide And Cermet Cutting-Tool Inserts ELECTRIC POWER SYSTEMS RESEARCH NR: 13; TC: 0

1995

114

Tang, LC; Chang, Ds Reliability Prediction Using Nondestructive Accelerated-Degradation Data - Case-Study On Power-Supplies ENGINEERING COSTS AND PRODUCTION ECONOMICS NR: 11; TC: 6

1995

115

Xie, W; Xie, M; Goh, TN Control Charts For Processes Subject To Random Shocks INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH NR: 12; TC: 2

1995

116

Xie, W; Xie, M; Goh, TN A Shewhart-Like Charting Technique For High-Yield Processes ENERGY NR: 11; TC: 7

1995

117

Zhao, M; Xie, M; Zhang, Yt A Study Of A Storage Reliability Estimation Problem IIE TRANSACTIONS NR: 8; TC: 0

1995

118

Ang, BW Urban Transportation Management And Energy Savings: The Case Of Singapore QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 13; TC: 2

1996

119

Ang, BW; Lee, PW Decomposition Of Industrial Energy Consumption: The Energy Coefficient Approach INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH NR: 17; TC: 9

1996

120

Chew, EP; Johnson, LA Service Level Approximations For Multiechelon Inventory Systems IEEE TRANSACTIONS ON ELECTRONICS PACKAGING MANUFACTURING NR: 19; TC: 0

1996

121

Fuh, JYH; Wong, YS; Yee, CY; Zhuang, L; Neo, KS Modelling, Analysis And Simulation For The Design Of A Robotic Assembly System JOURNAL OF APPLIED STATISTICS NR: 16; TC: 2

1996

122

Goh, TN Economical Experimentation Via 'Lean Design' INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS NR: 6; TC: 3

1996

123

Mok, YL; Xie, M; Goh, TN Planning Environmental Stress-Screening Based On Dod-Hdbk-344 - A Case Study INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING NR: 14; TC: 0

1996

Appendix A

A-10


124

Ong, HL; Ang, BW; Goh, TN; Deng, CC A Model For Vending Machine Services In The Soft Drink Industry EUROPEAN JOURNAL OF OPERATIONAL RESEARCH NR: 8; TC: 0

1996

125

Rahman, M; Seah, KHW; Goh, TN; Lee, CH Effectiveness Of Various Coatings On Cermet Cutting Tools ADVANCES IN ENGINEERING SOFTWARE NR: 15; TC: 1

1996

126

Tang, LC A Nonparametric Approach For Selecting The Most Reliable Population JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY NR: 11; TC: 0

1996

127

Tang, LC; Sun, YS; Goh, TN; Ong, HL Analysis Of Step-Stress Accelerated-Life-Test Data: A New Approach IIE TRANSACTIONS NR: 12; TC: 10

1996

128

Xie, M; Lai, CD On The Increase Of The Expected Lifetime By Parallel Redundancy INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE NR: 13; TC: 3

1996

129

Xie, M; Lai, CD Exploiting Symmetry In The Reliability Analysis Of Coherent Systems ANNUAL RELIABILITY AND MAINTAINABILITY SYMPOSIUM, 2005 PROCEEDINGS NR: 10; TC: 2

1996

130

Xie, M; Lai, CD Reliability Analysis Using An Additive Weibull Model With Bathtub-Shaped Failure Rate Function JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING NR: 14; TC: 4

1996

131

Xie, M; Zhao, M Reliability Growth Plot - An Underutilized Tool In Reliability Analysis EUROPEAN JOURNAL OF OPERATIONAL RESEARCH NR: 14; TC: 3

1996

132

Xie, W; Xie, M; Goh, TN A Mixed Poisson Model And Its Application To Attribute Testing Data ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 10; TC: 0

1996

133

Zhuang, L Acceptance Instant Distributions In Product-Form Closed Queueing Networks With Blocking IEEE TRANSACTIONS ON RELIABILITY NR: 24; TC: 0

1996

134

Ang, BW; Choi, KH Decomposition Of Aggregate Energy And Gas Emission Intensities For Industry: A Refined Divisia Index Method IEEE TRANSACTIONS ON RELIABILITY NR: 18; TC: 34

1997

135

Ang, BW; Pandiyan, G Decomposition Of Energy-Induced Co2 Emissions In Manufacturing JOURNAL OF STATISTICAL PLANNING AND INFERENCE NR: 13; TC: 18

1997

136

Atienza, OO; Tang, LC; Ang, BW Arl Properties Of A Sample Autocorrelation Chart QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 19; TC: 0

1997

137

Goh, TN Some Strategies For Experimentation Under Operational Constraints JOURNAL OF GLOBAL OPTIMIZATION NR: 12; TC: 1

1997

Appendix A

A-11


138

Hu, XN; Tang, LC; Ong, HL A M/D-X/L Vacation Queue Model For A Signalized Intersection ADVANCES IN ENGINEERING SOFTWARE NR: 9; TC: 1

1997

139

Ong, HL; Ang, BW; Goh, TN; Deng, CC A Vehicle Routing And Scheduling Problem With Time Windows And Stochastic Demand Constraints ENERGY POLICY NR: 10; TC: 2

1997

140

Tang, LC; Chew, EP Order Picking Systems: Batching And Storage Assignment Strategies ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 9; TC: 2

1997

141

Tang, LC; Than, SE; Ang, BW A Graphical Approach To Obtaining Confidence Limits Of C-Pk INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY NR: 10; TC: 9

1997

142

Xie, M; Goh, TN; Xie, W A Study Of Economic Design Of Control Charts For Cumulative Count Of Conforming Items INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE NR: 21; TC: 4

1997

143

Xie, M; Hong, GY; Wohlin, C A Study Of The Exponential Smoothing Technique In Software Reliability Growth Prediction EUROPEAN JOURNAL OF OPERATIONAL RESEARCH NR: 18; TC: 0

1997

144

Ang, BW; Zhang, FQ; Choi, KH Factorizing Changes In Energy And Environmental Indicators Through Decomposition JOURNAL OF SYSTEMS AND SOFTWARE NR: 12; TC: 20

1998

145

Chim, YC; Kassim, AA; Ibrahim, Y Dual Classifier System For Handprinted Alphanumeric Character Recognition NAVAL RESEARCH LOGISTICS NR: 24; TC: 4

1998

146

Goh, TN; Xie, M Prioritizing Processes In Initial Implementation Of Statistical Process Control IIE TRANSACTIONS NR: 18; TC: 0

1998

147

Ho, SL; Xie, M The Use Of Arima Models For Reliability Forecasting And Analysis INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS NR: 7; TC: 5

1998

148

Lai, CD; Govindaraju, K; Xie, M Effects Of Correlation On Fraction Nonconforming Statistical Process Control Procedures ENERGY ECONOMICS NR: 28; TC: 3

1998

149

Lai, YW; Ang, BW; Chew, EP Decomposition Of Aggregate Defective Rate In Batch Production INTERNATIONAL JOURNAL OF MATERIALS & PRODUCT TECHNOLOGY NR: 7; TC: 3

1998

150

Lu, XS; Xie, M; Goh, TN; Lai, CD Control Chart For Multivariate Attribute Processes EUROPEAN JOURNAL OF OPERATIONAL RESEARCH NR: 28; TC: 2

1998

151

Poh, KL A Knowledge-Based Guidance System For Multi-Attribute Decision Making IIE TRANSACTIONS NR: 14; TC: 0

1998

Appendix A

A-12


152

Wang, H; Xie, M; Goh, TN A Comparative Study Of The Prioritization Matrix Method And The Analytic Hierarchy Process Technique In Quality Function Deployment IIE TRANSACTIONS NR: 30; TC: 11

1998

153

Xie, M; Goh, TN; Lu, XS A Comparative Study Of Ccc And Cusum Charts IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT NR: 20; TC: 7

1998

154

Xie, M; Goh, TN; Lu, XS Computer-Aided Statistical Monitoring Of Automated Manufacturing Processes INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE NR: 8; TC: 4

1998

155

Xie, M; Goh, TN; Wang, H A Study Of The Sensitivity Of "Customer Voice" In Qfd Analysis COMPUTING NR: 18; TC: 5

1998

156

Xie, M; Hong, GY A Study Of The Sensitivity Of Software Release Time ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 15; TC: 4

1998

157

Xie, M; Wang, H; Goh, TN Quality Dimensions Of Internet Search Engines IEEE TRANSACTIONS ON RELIABILITY NR: 25; TC: 4

1998

158

Zhao, M; Wohlin, C; Ohlsson, N; Xie, M A Comparison Between Software Design And Code Metrics For The Prediction Of Software Fault Content RELIABILITY ENGINEERING & SYSTEM SAFETY NR: 10; TC: 3

1998

159

Zhuang, L; Wong, YS; Fuh, JYH; Yee, CY On The Role Of A Queueing Network Model In The Design Of A Complex Assembly System ENERGY POLICY NR: 19; TC: 1

1998

160

Ang, BW Is The Energy Intensity A Less Useful Indicator Than The Carbon Factor In The Study Of Climate Change? ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 17; TC: 12

1999

161

Ang, BW; Huang, JP; Poh, KL Break-Even Price Of Distributed Generation Under Uncertainty IIE TRANSACTIONS NR: 14; TC: 1

1999

162

Ang, BW; Zhang, FQ Inter-Regional Comparisons Of Energy-Related Co2 Emissions Using The Decomposition Technique ANNUAL RELIABILITY AND MAINTAINABILITY SYMPOSIUM, 2004 PROCEEDINGS NR: 9; TC: 16

1999

163

Chew, EP; Tang, LC Travel Time Analysis For General Item Location Assignment In A Rectangular Warehouse ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 16; TC: 6

1999

164

Chim, YC; Kassim, AA; Ibrahim, Y Character Recognition Using Statistical Moments COMPUTER SYSTEMS SCIENCE AND ENGINEERING NR: 12; TC: 4

1999

165

Harmanec, D; Leong, TY; Sundaresh, S; Poh, KL; Yeo, TT; Ng, I; Lew, TWK Decision Analytic Approach To Severe Head Injury Management EUROPEAN JOURNAL OF OPERATIONAL RESEARCH NR: 15; TC: 0

1999

Appendix A

A-13


166

Hong, GY; Xie, M; Shanmugan, P A Statistical Method For Controlling Software Defect Detection Process INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE NR: 3; TC: 0

1999

167

Lee, LH; Lau, TWE; Ho, YC Explanation Of Goal Softening In Ordinal Optimization ENERGY POLICY NR: 17; TC: 17

1999

168

Poh, KL; Ang, BW Transportation Fuels And Policy For Singapore: An Ahp Planning Approach COMPUTERS & OPERATIONS RESEARCH NR: 20; TC: 9

1999

169

Shen, XX; Tan, KC; Xie, M; Goh, TN; Wang, H Sensitivity Of The Relationship Matrix In Quality Function Deployment MATHEMATICAL AND COMPUTER MODELLING NR: 23; TC: 2

1999

170

Tan, HK; Ibrahim, Y Design Centering Using Momentum Based Cog INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY NR: 14; TC: 0

1999

171

Tang, LC; Goh, TN; Sun, YS; Ong, HL Planning Accelerated Life Tests For Censored Two-Parameter Exponential Distributions IIE TRANSACTIONS NR: 16; TC: 2

1999

172

Tang, LC; Than, SE Computing Process Capability Indices For Non-Normal Data: A Review And Comparative Study COMPUTERS & MATHEMATICS WITH APPLICATIONS NR: 20; TC: 6

1999

173

Xie, M; Hong, GY Software Release Time Determination Based On Unbounded Nhpp Model ENERGY ECONOMICS NR: 9; TC: 1

1999

174

Xie, M; Hong, GY; Wohlin, C Software Reliability Prediction Incorporating Information From A Similar Project OPERATIONS RESEARCH NR: 14; TC: 2

1999

175

Ang, BW; Zhang, FQ A Survey Of Index Decomposition Analysis In Energy And Environmental Studies TOTAL QUALITY MANAGEMENT & BUSINESS EXCELLENCE NR: 130; TC: 44

2000

176

Ang, BW; Zhang, FQ; Chew, EP A Decomposition Technique For Quantifying Real Process Performance RELIABILITY ENGINEERING & SYSTEM SAFETY NR: 5; TC: 0

2000

177

Atienza, OO; Tang, LC; Ang, BW A Uniformly Most Powerful Cumulative Sum Scheme Based On Symmetry APPLIED ENERGY NR: 19; TC: 1

2000

178

Chan, LY; Xie, M; Goh, TN Cumulative Quantity Control Charts For Monitoring Production Processes IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS NR: 12; TC: 9

2000

179

Chen, HM; Samudra, GS; Chan, DSH; Ibrahim, Y Global Optimization For Digital Mos Circuits Performance IIE TRANSACTIONS NR: 18; TC: 1

2000

Appendix A

A-14


180

Chuan, TK; Soon, LC A Detailed Trends Analysis Of National Quality Awards World-Wide EUROPEAN JOURNAL OF OPERATIONAL RESEARCH NR: 28; TC: 3

2000

181

Lai, CD; Xie, M A New Family Of Positive Quadrant Dependent Bivariate Distributions COMPUTATIONAL STATISTICS & DATA ANALYSIS NR: 12; TC: 7

2000

182

Lai, CD; Xie, M; Govindaraju, K Study Of A Markov Model For A High-Quality Dependent Process INTERNATIONAL JOURNAL OF FLEXIBLE MANUFACTURING SYSTEMS NR: 20; TC: 2

2000

183

Lee, LH; Abernathy, FH; Ho, YC Production Scheduling For Apparel Manufacturing Systems ENERGY POLICY NR: 16; TC: 6

2000

184

Lu, XS; Xie, M; Goh, TN An Investigation Of The Effects Of Inspection Errors On The Run-Length Control Charts SOCIAL CHOICE AND WELFARE NR: 23; TC: 2

2000

185

Sun, JW; Ang, BW Some Properties Of An Exact Energy Decomposition Model JOURNAL OF SYSTEMS AND SOFTWARE NR: 15; TC: 3

2000

186

Tan, KC; Shen, XX Integrating Kano'S Model In The Planning Matrix Of Quality Function Deployment COMMUNICATIONS IN STATISTICS-THEORY AND METHODS NR: 27; TC: 5

2000

187

Wu, X; Poh, KL Decision-Model Construction With Multilevel Influence Diagrams ADVANCES IN ENGINEERING SOFTWARE NR: 35; TC: 0

2000

188

Xie, M; Goh, TN; Tang, XY Data Transformation For Geometrically Distributed Quality Characteristics INTERNATIONAL JOURNAL OF TECHNOLOGY MANAGEMENT NR: 14; TC: 1

2000

189

Xie, M; Yang, ZL; Gaudoin, O More On The Mis-Specification Of The Shape Parameter With Weibull-To-Exponential Transformation IEEE TRANSACTIONS ON SOFTWARE ENGINEERING NR: 6; TC: 3

2000

190

Yang, B; Xie, M A Study Of Operational And Testing Reliability In Software Reliability Analysis JOURNAL OF TRANSPORTATION ENGINEERING-ASCE NR: 20; TC: 9

2000

191

Yang, ZL; Xie, M Process Monitoring Of Exponentially Distributed Characteristics Through An Optimal Normalizing Transformation JOURNAL OF QUALITY TECHNOLOGY NR: 14; TC: 1

2000

192

Ang, BW; Liu, FL A New Energy Decomposition Method: Perfect In Decomposition And Consistent In Aggregation QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 24; TC: 15

2001

193

Cai, DQ; Xie, M; Goh, TN Spc In An Automated Manufacturing Environment COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION NR: 14; TC: 1

2001

Appendix A

A-15


194

Choi, KH; Ang, BW A Time-Series Analysis Of Energy-Related Carbon Emissions In Korea JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION NR: 5; TC: 2

2001

195

Cui, LR; Xie, M Availability Analysis Of Periodically Inspected Systems With Random Walk Model JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION NR: 16; TC: 2

2001

196

Goh, TN A Pragmatic Approach To Experimental Design In Industry IEEE TRANSACTIONS ON RELIABILITY NR: 17; TC: 6

2001

197

Ho, SL; Xie, M; Tang, LC; Xu, K; Goh, TN Neural Network Modeling With Confidence Bounds: A Case Study On The Solder Paste Deposition Process ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 23; TC: 0

2001

198

Kong, H; Xie, M; Goh, TN A Study Of Lifetime Distributions For Regularly Replaced Systems JOURNAL OF MANUFACTURING SYSTEMS NR: 14; TC: 0

2001

199

Lai, CD; Chan, LY; Xie, M Distribution Of Runs In A Two-Stage Process Monitoring Model RELIABILITY ENGINEERING & SYSTEM SAFETY NR: 5; TC: 0

2001

200

Lee, C; Ventura, JA Optimal Dwell Point Location Of Automated Guided Vehicles To Minimize Mean Response Time In A Loop Layout INTERNATIONAL JOURNAL OF ENGINEERING EDUCATION NR: 15; TC: 3

2001

201

Lin, L; Poh, KL; Lim, TK Empirical Treatment Of Chronic Cough - A Cost-Effectiveness Analysis INFORMATION SCIENCES NR: 6; TC: 0

2001

202

Poh, KL; Ang, BW; Bai, F A Comparative Analysis Of R&D Project Evaluation Methods COMPUTERS IN INDUSTRY NR: 46; TC: 7

2001

203

Shen, XX; Tan, KC; Xie, M The Implementation Of Quality Function Deployment Based On Linguistic Data JOURNAL OF QUALITY TECHNOLOGY NR: 27; TC: 10

2001

204

Tan, KC; Lee, LH; Ou, K Artificial Intelligence Heuristics In Solving Vehicle Routing Problems With Time Window Constraints JOURNAL OF QUALITY TECHNOLOGY NR: 52; TC: 7

2001

205

Tan, KC; Lee, LH; Ou, K Hybrid Genetic Algorithms In Solving Vehicle Routing Problems With Time Window Constraints INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS NR: 6; TC: 15

2001

206

Tan, KC; Lee, LH; Zhu, QL; Ou, K Heuristic Methods For Vehicle Routing Problem With Time Windows ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 25; TC: 8

2001

207

Ventura, JA; Lee, CL A Study Of The Tandem Loop With Multiple Vehicles Configuration For Automated Guided Vehicle Systems ENERGY POLICY NR: 17; TC: 4

2001

Appendix A

A-16


208

Xie, M; Del Castillo, E; Goh, TN; Cai, DQ On The Monitoring Of Trended And Regularly Adjusted Processes TOTAL QUALITY MANAGEMENT NR: 12; TC: 2

2001

209

Xie, M; He, B; Goh, TN Zero-Inflated Poisson Model In Statistical Process Control TOTAL QUALITY MANAGEMENT NR: 15; TC: 5

2001

210

Xie, M; Tang, XY; Goh, TN On Economic Design Of Cumulative Count Of Conforming Chart PRODUCTION PLANNING & CONTROL NR: 20; TC: 1

2001

211

Zhang, FQ; Ang, BW Methodological Issues In Cross-Country/Region Decomposition Of Energy And Environment Indicators SOCIAL CHOICE AND WELFARE NR: 15; TC: 7

2001

212

Ang, BW; Choi, KH Boundary Problem In Carbon Emission Decomposition METRIKA NR: 10; TC: 0

2002

213

Atienza, OO; Tang, LC; Ang, BW A Cusum Scheme For Autocorrelated Observations APPLIED ARTIFICIAL INTELLIGENCE NR: 30; TC: 2

2002

214

Cai, DQ; Xie, M; Goh, TN; Tang, XY Economic Design Of Control Chart For Trended Processes IIE TRANSACTIONS NR: 20; TC: 2

2002

215

Chan, LY; Lin, DKJ; Xie, M; Goh, TN Cumulative Probability Control Charts For Geometric And Exponential Process Characteristics RELIABILITY ENGINEERING & SYSTEM SAFETY NR: 16; TC: 2

2002

216

Cheong, YM; Ong, HL; Huang, HC Modeling The Vehicle Routine Problem For A Soft Drink Distribution Company JOURNAL OF MANUFACTURING SYSTEMS NR: 6; TC: 0

2002

217

Chew, EP; Huang, HC; Horiana Performance Measures For Returnable Inventory: A Case Study INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH NR: 6; TC: 0

2002

218

Chew, EP; Ong, CJ; Lim, KH Variable Period Adaptive Genetic Algorithm RELIABILITY ENGINEERING & SYSTEM SAFETY NR: 11; TC: 1

2002

219

Choi, KH; Ang, BW Measuring Thermal Efficiency Improvement In Power Generation: The Divisia Decomposition Approach ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE NR: 12; TC: 0

2002

220

Chua, VCH; Ueng, CH; Huang, HC A Method For Evaluating The Behavior Of Power Indices In Weighted Plurality Games ENGINEERING OPTIMIZATION NR: 9; TC: 1

2002

221

Huang, BQ; Gou, HM; Liu, WH; Li, Y; Xie, M A Framework For Virtual Enterprise Control With The Holonic Manufacturing Paradigm INFORMATION AND SOFTWARE TECHNOLOGY NR: 27; TC: 6

2002

Appendix A

A-17


222

Jayaram, JSR; Ibrahim, Y; Loh, HT; Brombacher, AC A Technique To Achieve Maximal Manufacturing Yield In Engineering Design COMPUTERS & INDUSTRIAL ENGINEERING NR: 16; TC: 0

2002

223

Kuralmani, V; Xie, M; Goh, TN; Gan, FF A Conditional Decision Procedure For High Yield Processes COMPUTERS & INDUSTRIAL ENGINEERING NR: 18; TC: 0

2002

224

Lai, CD; Xie, M; Poh, KL; Dai, YS; Yang, P A Model For Availability Analysis Of Distributed Software/Hardware Systems ENERGY NR: 36; TC: 8

2002

225

Lee, LH; Fan, YL An Adaptive Real-Coded Genetic Algorithm JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS NR: 37; TC: 1

2002

226

Li, D; Lee, LH; Ho, YC Constraint Ordinal Optimization ANNUAL RELIABILITY AND MAINTAINABILITY SYMPOSIUM, 2002 PROCEEDINGS NR: 23; TC: 3

2002

227

Li, YN; Tan, KC; Xie, M Measuring Web-Based Service Quality ANNUAL RELIABILITY AND MAINTAINABILITY SYMPOSIUM, 2002 PROCEEDINGS NR: 44; TC: 7

2002

228

Liu, SQ; Ong, HL A Comparative Study Of Algorithms For The Flowshop Scheduling Problem JOURNAL OF QUALITY TECHNOLOGY NR: 27; TC: 5

2002

229

Loy, C; Goh, TN; Xie, M Retrospective Factorial Fitting And Reverse Design Of Experiments COMPUTERS IN BIOLOGY AND MEDICINE NR: 16; TC: 0

2002

230

Pek, PK; Poh, KL Formulation Of Tutoring Policy For Maximising Student Learning Using A Decision-Theoretical Approach JOURNAL OF APPLIED PROBABILITY NR: 29; TC: 0

2002

231

Tang, LC; Tan, AP; Ong, SH Planning Accelerated Life Tests With Three Constant Stress Levels IEEE TRANSACTIONS ON ELECTRONICS PACKAGING MANUFACTURING NR: 9; TC: 1

2002

232

Tang, LC; Xie, M A Simple Graphical Approach For Comparing Reliability Trends Of Different Units In A Fleet RELIABILITY ENGINEERING & SYSTEM SAFETY NR: 5; TC: 0

2002

233

Tang, LC; Xu, K A Unified Approach For Dual Response Surface Optimization JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY NR: 24; TC: 12

2002

234

Tang, LC; Yang, GY Planning Multiple Levels Constant Stress Accelerated Life Tests INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH NR: 5; TC: 1

2002

235

Tay, FEH; Lee, LH; Wang, LX Production Scheduling Of A Mems Manufacturing System With A Wafer Bonding Process COMPUTATIONAL STATISTICS & DATA ANALYSIS NR: 16; TC: 0

2002

Appendix A

A-18


236

Xiang, YP; Poh, KL Time-Critical Dynamic Decision Modeling In Medicine JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION NR: 28; TC: 2

2002

237

Xiang, YP; Poh, KL Knowledge-Based Time-Critical Dynamic Decision Modelling ARTIFICIAL INTELLIGENCE IN ENGINEERING NR: 14; TC: 1

2002

238

Xie, M; Goh, TN; Ranjan, P Some Effective Control Chart Procedures For Reliability Monitoring INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH NR: 9; TC: 2

2002

239

Xie, M; Tang, Y; Goh, TN A Modified Weibull Extension With Bathtub-Shaped Failure Rate Function INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH NR: 14; TC: 5

2002

240

Xie, M; Tsui, KL; Goh, TN; Cai, DQ Process Capability Indices For A Regularly Adjusted Process ENERGY POLICY NR: 19; TC: 0

2002

241

Xu, K; Tang, LC; Xie, M; Ho, SL; Zhu, ML Fuzzy Assessment Of Fmea For Engine Systems JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION NR: 11; TC: 9

2002

242

Yang, MS; Lee, LH Ordinal Optimization With Subset Selection Rule COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION NR: 12; TC: 1

2002

243

Yang, ZL; See, SP; Xie, M An Investigation Of Transformation-Based Prediction Interval For The Weibull Median Life INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS NR: 21; TC: 0

2002

244

Yang, ZL; Xie, M; Kuralmani, V; Tsui, KL On The Performance Of Geometric Charts With Estimated Control Limits ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 25; TC: 11

2002

245

Ang, BW; Liu, FL; Chew, EP Perfect Decomposition Techniques In Energy And Environmental Analysis ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 17; TC: 8

2003

246

Chai, KH Bridging Islands Of Knowledge: A Framework Of Knowledge Sharing Mechanisms ENERGY NR: 32; TC: 2

2003

247

Chan, LY; Lai, CD; Xie, M; Goh, TN A Two-Stage Decision Procedure For Monitoring Processes With Low Fraction Nonconforming R & D MANAGEMENT NR: 24; TC: 1

2003

248

Chan, LY; Ma, CX; Goh, TN Orthogonal Arrays For Experiments With Lean Designs JOURNAL OF APPLIED STATISTICS NR: 26; TC: 0

2003

249

Cheu, RL; Chew, EP; Wee, CL Estimating Total Distance For Hauling Import And Export Containers JOURNAL OF INTELLIGENT MANUFACTURING NR: 11; TC: 1

2003

250

Choi, KH; Ang, BW Decomposition Of Aggregate Energy Intensity Changes In Two Measures: Ratio And Difference ENERGY ECONOMICS NR: 14; TC: 4

2003

Appendix A

A-19


251

Chua, VCH; Huang, HC The Shapley-Shubik Index, The Donation Paradox And Ternary Games KNOWLEDGE ENGINEERING REVIEW NR: 6; TC: 0

2003

252

Cui, LR; Xie, M Some Normal Approximations For Renewal Function Of Large Weibull Shape Parameter INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING NR: 20; TC: 0

2003

253

Dai, YS; Xie, M; Poh, KL; Liu, GQ A Study Of Service Reliability And Availability For Distributed Systems ENERGY NR: 22; TC: 7

2003

254

Dai, YS; Xie, M; Poh, KL; Yang, B Optimal Testing-Resource Allocation With Genetic Algorithm For Modular Software Systems ENERGY NR: 26; TC: 5

2003

255

Goh, TN; Low, PC; Tsui, KL; Xie, M Impact Of Six Sigma Implementation On Stock Price Performance JOURNAL OF APPLIED STATISTICS NR: 18; TC: 4

2003

256

Ho, SL; Xie, M; Goh, TN A Study Of The Connectionist Models For Software Reliability Prediction TOTAL QUALITY MANAGEMENT NR: 19; TC: 4

2003

257

Ho, SL; Xie, M; Goh, TN Process Monitoring Strategies For Surface Mount Manufacturing Processes TOTAL QUALITY MANAGEMENT NR: 31; TC: 1

2003

258

Kotz, S; Lai, CD; Xie, M On The Effect Of Redundancy For Systems With Dependent Components RELIABILITY ENGINEERING & SYSTEM SAFETY NR: 29; TC: 3

2003

259

Lai, CD; Xie, M Relative Ageing For Two Parallel Systems And Related Problems QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 8; TC: 0

2003

260

Lai, CD; Xie, M; Murthy, DNP A Modified Weibull Distribution ENGINEERING OPTIMIZATION NR: 11; TC: 7

2003

261

Lee, CY; Cetinkaya, S; Jaruphongsa, W A Dynamic Model For Inventory Lot Sizing And Outbound Shipment Scheduling At A Third-Party Warehouse JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES D-THE STATISTICIAN NR: 50; TC: 4

2003

262

Lee, LH; Tan, KC; Ou, K; Chew, YH Vehicle Capacity Planning System: A Case Study On Vehicle Routing Problem With Time Windows PRODUCTION PLANNING & CONTROL NR: 34; TC: 2

2003

263

Levitin, G; Dai, YS; Xie, M; Poh, KL Optimizing Survivability Of Multi-State Systems With Multi-Level Protection By Multi-Processor Genetic Algorithm JOURNAL OF APPLIED STATISTICS NR: 14; TC: 4

2003

264

Liu, FL; Ang, BW Eight Methods For Decomposing The Aggregate Energy-Intensity Of Industry COMPUTERS & INDUSTRIAL ENGINEERING NR: 19; TC: 3

2003

Appendix A

A-20


265

Liu, SB; Ong, HL; Huang, HC Two Bi-Directional Heuristics For The Assembly Line Type Ii Problem PRODUCTION PLANNING & CONTROL NR: 7; TC: 0

2003

266

Ong, HL; Huang, HC; Huin, WM Finding The Exact Volume Of A Polyhedron QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 9; TC: 0

2003

267

Ranjan, P; Xie, M; Goh, TN Optimal Control Limits For Ccc Charts In The Presence Of Inspection Errors COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION NR: 16; TC: 0

2003

268

Tang, LC Failure-Free Life In Reliability Modeling IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS NR: 11; TC: 0

2003

269

Tang, Y; Xie, M; Goh, TN Statistical Analysis Of A Weibull Extension Model ENERGY POLICY NR: 15; TC: 1

2003

270

Teng, SY; Ong, HL; Huang, HC A Comparative Study Of Metaheuristics For Vehicle Routing Problem With Stochastic Demands INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH NR: 17; TC: 2

2003

271

Ventura, JA; Lee, C Optimally Locating Multiple Dwell Points In A Single Loop Guide Path System STATISTICS & PROBABILITY LETTERS NR: 16; TC: 0

2003

272

Xie, M; Preuss, W; Cui, LR Error Analysis Of Some Integration Procedures For Renewal Equation And Convolution Integrals JOURNAL OF SYSTEMS AND SOFTWARE NR: 19; TC: 2

2003

273

Xie, M; Yang, B A Study Of The Effect Of Imperfect Debugging On Software Development Cost PATTERN ANALYSIS AND APPLICATIONS NR: 10; TC: 2

2003

274

Yang, ZL; See, SP; Xie, M Transformation Approaches For The Construction Of Weibull Prediction Interval QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 13; TC: 0

2003

275

Yang, ZL; Xie, M Efficient Estimation Of The Weibull Shape Parameter Based On A Modified Profile Likelihood JOURNAL OF INFORMATION SCIENCE NR: 10; TC: 1

2003

276

Ang, BW Growth Curves For Long-Term Global Co2 Emission Reduction Analysis ENERGY NR: 8; TC: 0

2004

277

Ang, BW Decomposition Analysis For Policymaking In Energy: Which Is The Preferred Method? INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE NR: 30; TC: 9

2004

278

Ang, BW; Liu, FL; Chung, HS A Generalized Fisher Index Approach To Energy Decomposition Analysis COMPUTERS & INDUSTRIAL ENGINEERING NR: 21; TC: 0

2004

Appendix A

A-21


279

Chai, KH; Gregory, MJ; Shi, YS An Exploratory Study Of Intrafirm Process Innovations Transfer In Asia COMPUTERS & INDUSTRIAL ENGINEERING NR: 26; TC: 0

2004

280

Cui, LR; Kuo, W; Loh, HT; Xie, A Optimal Allocation Of Minimal & Perfect Repairs Under Resource Constraints ENERGY NR: 19; TC: 2

2004

281

Cui, LR; Loh, HT; Xie, M Sequential Inspection Strategy For Multiple Systems Under Availability Requirement IMAGE AND VISION COMPUTING NR: 10; TC: 2

2004

282

Cui, LR; Xie, M; Loh, HT Inspection Schemes For General Systems NAVAL RESEARCH LOGISTICS NR: 17; TC: 0

2004

283

Dai, YS; Xie, M; Poh, KL; Ng, SH A Model For Correlated Failures In N-Version Programming INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE NR: 42; TC: 5

2004

284

Jaruphongsa, W; Cetinkaya, S; Lee, CY A Two-Echelon Inventory Optimization Model With Demand Time Window Considerations IEEE TRANSACTIONS ON AUTOMATIC CONTROL NR: 32; TC: 1

2004

285

Jaruphongsa, W; Cetinkaya, S; Lee, CY Warehouse Space Capacity And Delivery Time Window Considerations In Dynamic Lot-Sizing For A Simple Supply Chain INFORMATION AND SOFTWARE TECHNOLOGY NR: 9; TC: 2

2004

286

Jewkes, E; Lee, C; Vickson, R Product Location, Allocation And Server Home Base Location For An Order Picking Line With Multiple Servers EUROPEAN JOURNAL OF OPERATIONAL RESEARCH NR: 37; TC: 2

2004

287

Kuan, SN; Ong, HL; Ng, KM Applying Metaheuristics To Feeder Bus Network Design Problem JOURNAL OF SYSTEMS AND SOFTWARE NR: 20; TC: 1

2004

288

Li, R; Huang, HC On-Line Scheduling For Jobs With Arbitrary Release Times INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH NR: 9; TC: 1

2004

289

Liu, GQ; Xie, M; Dai, YS; Poh, KL On Program And File Assignment For Distributed Systems TOTAL QUALITY MANAGEMENT NR: 23; TC: 5

2004

290

Liu, SQ; Ong, HL Metaheuristics For The Mixed Shop Scheduling Problem QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 22; TC: 4

2004

291

Ng, SH; Chick, SE Design Of Follow-Up Experiments For Improving Model Discrimination And Parameter Estimation JOURNAL OF APPLIED STATISTICS NR: 40; TC: 0

2004

292

Tang, LC Multiple-Steps Step-Stress Accelerated Life Tests: A Model And Its Spreadsheet Analysis COMPUTERS & INDUSTRIAL ENGINEERING NR: 14; TC: 0

2004

Appendix A

A-22


293

Tang, LC; Cheong, WT Cumulative Conformance Count Chart With Sequentially Updated Parameters COMPUTERS & INDUSTRIAL ENGINEERING NR: 18; TC: 2

2004

294

Tang, LC; Yang, GY; Xie, M Planning Of Step-Stress Accelerated Degradation Test ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING NR: 17; TC: 0

2004

295

Teng, SY; Ong, HL; Huang, HC An Integer L-Shaped Algorithm For Time-Constrained Traveling Salesman Problem With Stochastic Travel And Service Times ENERGY NR: 25; TC: 0

2004

296

Xie, M; Dai, YS; Poh, KL; Lai, CD Distributed System Availability In The Case Of Imperfect Debugging Process ARTIFICIAL INTELLIGENCE IN ENGINEERING NR: 25; TC: 1

2004

297

Xie, M; Dai, YS; Poh, KL; Lai, CD Optimal Number Of Hosts In A Distributed System Based On Cost Criteria PRODUCTION PLANNING & CONTROL NR: 30; TC: 1

2004

298

Xie, M; Goh, TN; Tang, Y On Changing Points Of Mean Residual Life And Failure Rate Function For Some Generalized Weibull Distributions IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT NR: 22; TC: 1

2004

299

Xu, K; Lin, DKJ; Tang, LC; Xie, M Multiresponse Systems Optimization Using A Goal Attainment Approach QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 41; TC: 3

2004

300

Zhang, CW; Ong, HL Solving The Biobjective Zero-One Knapsack Problem By An Efficient Lp-Based Heuristic QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 37; TC: 1

2004

301

Ang, BW The Lmdi Approach To Decomposition Analysis: A Practical Guide COMPUTERS & INDUSTRIAL ENGINEERING NR: 9; TC: 1

2005

302

Bai, CG; Hu, QP; Xie, M; Ng, SH Software Failure Prediction Based On A Markov Bayesian Network Model COMPUTERS & INDUSTRIAL ENGINEERING NR: 37; TC: 2

2005

303

Cui, LR; Xie, M On A Generalized K-Out-Of-N System And Its Reliability COMPUTERS & INDUSTRIAL ENGINEERING NR: 20; TC: 0

2005

304

Cui, LR; Xie, M Availability Of A Periodically Inspected System With Random Repair Or Replacement Times ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 15; TC: 0

2005

305

Dai, YS; Xie, M; Poh, KL Modeling And Analysis Of Correlated Software Failures Of Multiple Types QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 21; TC: 3

2005

306

Gao, YF; Tang, LC The Effect Of Correlation On Chain Sampling Plans COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION NR: 22; TC: 0

2005

Appendix A

A-23


307

Ghitany, ME; Kotz, S; Xie, M On Some Reliability Measures And Their Stochastic Orderings For The Topp-Leone Distribution ENERGY JOURNAL NR: 10; TC: 0

2005

308

Huang, HC; Chew, EP; Goh, KH A Two-Echelon Inventory System With Transportation Capacity Constraint ENERGY ECONOMICS NR: 13; TC: 0

2005

309

Jaruphongsa, W; Cetinkaya, S; Lee, CY A Dynamic Lot-Sizing Model With Multi-Mode Replenishments: Polynomial Algorithms For Special Cases With Dual And Multiple Modes QUEUEING SYSTEMS NR: 34; TC: 0

2005

310

Lai, X; Xie, M; Tan, KC Dynamic Programming For Qfd Optimization ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 21; TC: 2

2005

311

Lam, SW; Tang, LC A Graphical Approach To The Dual Response Robust Design Problems ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH NR: 30; TC: 0

2005

312

Lee, LH; Chew, EP A Dynamic Joint Replenishment Policy With Auto-Correlated Demand QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL NR: 28; TC: 0

2005

313

Lee, LH; Chew, EP; Ng, TS Production Planning With Approved Vendor Matrices For A Hard-Disk Drive Manufacturer NAVAL RESEARCH LOGISTICS NR: 7; TC: 1

2005

314

Liu, GQ; Poh, KL; Xie, M Iterative List Scheduling For Heterogeneous Computing JOURNAL OF MATERIALS PROCESSING TECHNOLOGY NR: 32; TC: 4

2005

315

Liu, JH; Cao, LQ; Xie, M; Goh, TN; Tang, Y A General Weibull Model For Reliability Analysis Under Different Failure Criteria - Application On Anisotropic Conductive Adhesive Joining Technology PERFORMANCE EVALUATION NR: 18; TC: 0

2005

316

Liu, SB; Ong, HL; Huang, HC A Bidirectional Heuristic For Stochastic Assembly Line Balancing Type Ii Problem ENERGY ECONOMICS NR: 22; TC: 0

2005

317

Liu, SQ; Ong, HL; Ng, KM A Fast Tabu Search Algorithm For The Group Shop Scheduling Problem EUROPEAN JOURNAL OF OPERATIONAL RESEARCH NR: 21; TC: 0

2005

318

Liu, SQ; Ong, HL; Ng, KM Metaheuristics For Minimizing The Makespan Of The Dynamic Shop Scheduling Problem MICROELECTRONICS AND RELIABILITY NR: 14; TC: 1

2005

319

Pek, PK; Poh, KL Making Decisions In An Intelligent Tutoring System RELIABILITY ENGINEERING & SYSTEM SAFETY NR: 39; TC: 1

2005

320

Poh, KL; Choo, KW; Wong, CG A Heuristic Approach To The Multi-Period Multi-Commodity Transportation Problem IEEE TRANSACTIONS ON RELIABILITY NR: 55; TC: 0

2005

Appendix A

A-24


321

Tang, LC; Lee, LH A Simple Recovery Strategy For Economic Lot Scheduling Problem: A Two-Product Case COMPUTER INTEGRATED MANUFACTURING SYSTEMS NR: 16; TC: 0

2005

322

Tang, LC; Xu, K A Multiple Objective Framework For Planning Accelerated Life Tests INTERNATIONAL JOURNAL OF VEHICLE DESIGN NR: 13; TC: 1

2005

323

Zeng, L; Ong, HL; Ng, KM An Assignment-Based Local Search Method For Solving Vehicle Routing Problems MICROELECTRONICS AND RELIABILITY NR: 17; TC: 0

2005

324

Zhang, CW; Xie, M; Goh, TN Economic Design Of Exponential Charts For Time Between Events Monitoring MICROELECTRONICS AND RELIABILITY NR: 25; TC: 0

2005

Appendix B

A-25

APPENDIX B

Publications of NUS-ISE not indexed in Web of Science®

(This list was retrieved from the NUS-ISE website)


1 Bauly, J.A. New Product Development - Avoiding Typical Management Problems TODAY’S MANAGER - JOURNAL OF THE SINGAPORE INSTITUTE OF MANAGEMENT

2000

2

Bauly, J.A., and Foo, S.W. Doing More for New Product Development in Singapore – A Survey of New Product Development in Singapore TODAY’S MANAGER - JOURNAL OF THE SINGAPORE INSTITUTE OF MANAGEMENT

2000

3 Huang, H.C. and Chua Vincent, C.H. Analytical Representation of Probabilities under the IAC Condition SOCIAL CHOICE AND WELFARE

2000

4 Lim, T.K., Cherian, J., Poh, K.L. and Leong, T.Y. The Rapid Diagnosis of Smear-negative Pulmonary Tuberculosis: A Cost-effectiveness Analysis RESPIROLOGY

2000

5 Pek, P.K., and Poh, K.L. Framework of a Decision-theoretic Tutoring System for Learning of Mechanics JOURNAL OF SCIENCE EDUCATION AND TECHNOLOGY

2000

6 Poh, K.L. An Intelligent Decision Support System for Investment Analysis KNOWLEDGE AND INFORMATION SYSTEMS

2000

7 Shen, X.X., Tan, K.C., and Xie, M. Benchmarking in QFD for Quality Improvement BENCHMARKING: AN INTERNATIONAL JOURNAL

2000

8 Shen, X.X., Tan, K.C., and Xie, M. An Integrated Approach to Innovative Product Development Using Kano's Model and QFD EUROPEAN JOURNAL OF INNOVATION MANAGEMENT

2000

9 Tan, K.C. Ergonomic Developments in Singapore HUMAN QUALITY OF LIFE

2000

10 Tang, X.Y., Goh, T.N., Xie, M., and Wiklund, H. Statistical Control and Monitoring of Tool Wear Processes INTERNATIONAL JOURNAL OF RELIABILITY, QUALITY AND SAFETY ENGINEERING

2000

11 Tang, X.Y., Xie, M., and Goh, T.N. A Note on Economic-Statistical Design of Cumulative Count of Conforming Control Chart ECONOMIC QUALITY CONTROL

2000

12 Wu, X., and Poh, K.L. Decision Model Construction with Multilevel Influence Diagrams THE KNOWLEDGE ENGINEERING REVIEW

2000

13 Xie, M., Goh, T.N. and Kuralmani, V. On Optimal Setting of Control Limits for Geometric Chart INTERNATIONAL JOURNAL OF RELIABILITY, QUALITY AND SAFETY ENGINEERING

2000

14 Xie, M., Kong, H., and Goh, T.N. Exponential Approximation for Maintained Weibull Components INTERNATIONAL JOURNAL OF QUALITY IN MAINTENANCE ENGINEERING

2000

15 Xie, M., Lu, X.S., Goh, T.N., and Lai, C.D. Monitoring of a Serially-Correlated Manufacturing Process INDUSTRIAL ENGINEERING RESEARCH

2000

16 Xie, M., Tan, K.C. and Goh, K.H. Optimum Prioritisation and Resource Allocation based on Fault Tree Analysis INTERNATIONAL JOURNAL OF QUALITY AND RELIABILITY MANAGEMENT

2000

17 Yap, C.M., Buisson, D.H. and Garrett, T.C. The Influence of Culture on Innovative Behaviour and Management in Singapore ASEAN JOURNAL ON SCIENCE AND TECHNOLOGY FOR DEVELOPMENT

2000

Appendix B

A-26


18 Yap, C.M., Chou, S.K., Thybussek, I., Gocht, W., and Pozzolo, V. Comparative Practices of EU and ASEAN Firms in Technology-based Interactions with Universities INDUSTRY & HIGHER EDUCATION

2000

19 Ang, B.W., and Tan, K.C. Why Singapore's Land Transportation Energy Consumption is Relatively Low NATURAL RESOURCES FORUM

2001

20 Bauly, J.A., and Nee, A. New Product Development: Implementing Best Practices INTERNATIONAL JOURNAL OF MANUFACTURING TECHNOLOGY AND MANAGEMENT

2001

21 Cheu, R.L., Agarwal, P., Gautham, B., Chan, W.T., Chew, E.P., and Ong, C.J. Modeling of Traffic Processes using Virtual Objects IES JOURNAL

2001

22 Goh, T.N. Information Transformation Perspective on Experimental Design in Six Sigma QUALITY ENGINEERING

2001

23 Lui, P.C., and Tan, T.S. Building Integrated Large-Scale Urban Infrastructures: Singapore’s Experience JOURNAL OF URBAN TECHNOLOGY

2001

24 Shen, X. X., Tan, K. C., and Xie, M. Listening to the Future Voice of Customer using Fuzzy Trend Analysis in QFD QUALITY ENGINEERING

2001

25 Tan, K.C., and Pawitra, T.A. Integrating SERVQUAL and Kano's Model into QFD for Service Excellence Development MANAGING SERVICE QUALITY

2001

26 Xie, M., and Yang, B. Optimal Testing-time Allocation for Modular Systems INTERNATIONAL JOURNAL OF QUALITY AND RELIABILITY MANAGEMENT

2001

27 Xie, M., Goh, T.N., and Cai, D.Q. An Integrated SPC Approach for Manufacturing Processes INTEGRATED MANUFACTURING SYSTEM

2001

28 Atienza, O.O., Tang, L.C., and Ang, B.W. Simultaneous Monitoring of Sample and Group Autocorrelations QUALITY ENGINEERING

2002

29 Goh, T.N. A Strategic Assessment of Six Sigma QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL

2002

30 Goh, T.N. The Role of Statistical Design of Experiments in Six Sigma: Perspectives of a Practitioner QUALITY ENGINEERING

2002

31 Ho, S.L., Xie, M., and Goh, T.N. A Comparative Study of Neural Network and Box-Jenkins ARIMA Modeling in Time Series Prediction COMPUTERS & INDUSTRIAL ENGINEERING

2002

32 Khoo, H.H., and Tan, K.C. Critical Success Factors for Quality Management Implementation in Russia INDUSTRIAL AND COMMERCIAL TRAINING

2002

33 Khoo, H.H., and Tan, K.C. Gandhian Philosophy and National Quality Awards JOURNAL OF HUMAN VALUES

2002

34 Khoo, H.H., and Tan, K.C. Nine Approaches to Organisational Excellence JOURNAL OF ORGANIZATIONAL EXCELLENCE

2002

35 Li, D., Lee, L.H., and Ho, Y.C. Constraint Ordinal Optimisation INFORMATION SCIENCES: AN INTERNATIONAL JOURNAL

2002

36 Tan, K.C. A Comparative Study of 16 National Quality Awards THE TQM MAGAZINE

2002

Appendix B

A-27


37 Tan, K.C., and Khoo, H.H. The Relevance of Confucianism to National Quality Awards in Southeast Asia INTERNATIONAL JOURNAL OF CROSS CULTURAL MANAGEMENT

2002

38 Tan, K.C., and Khoo, H.H. Indian Society, Total Quality and the Rajiv Gandhi National Quality Award JOURNAL OF MANAGEMENT DEVELOPMENT

2002

39 Xie, M., Gaudoin, O., and Bracquemond, C. Redefining Failure Rate Function for Discrete Distributions INTERNATIONAL JOURNAL OF RELIABILITY QUALITY AND SAFETY ENGINEERING

2002

40 Cheu, R.L., Chew, E.P., and Wee, C.L. Estimating Total Distance for Hauling Import & Export Containers JOURNAL OF TRANSPORTATION ENGINEERING

2003

41 Gaudoin, O., Yang, B., and Xie, M. A Simple Goodness-of-fit Test for the Power-law Process based on the Duane Plot IEEE TRANSACTIONS ON RELIABILITY

2003

42 Goh, T.N., and Xie, M. Statistical Control of a Six Sigma Process QUALITY ENGINEERING

2003

43 He, B., Xie, M., Goh, T.N., and Ranjan, P. On the Estimation Error in Zero-inflated Poisson Model for Process Control INTERNATIONAL JOURNAL OF RELIABILITY QUALITY AND SAFETY ENGINEERING

2003

44 Hong, G.Y., and Goh, T.N. Six Sigma in Software Quality THE TQM MAGAZINE

2003

45 Khoo, H.H., and Tan, K.C. Managing for Quality in the USA and Japan: Differences between the MBNQA, DP and JQA THE TQM MAGAZINE

2003

46 Li, Y.N., Tan, K.C., and Xie, M. Managing Service Quality: Applying Utility Theory in the Prioritisation of Service Attributes INTERNATIONAL JOURNAL OF QUALITY AND RELIABILITY MANAGEMENT

2003

47 Li, Y.N., Tan, K.C., and Xie, M. Factor Analysis of Service Quality Dimension Shifts in the information age MANAGERIAL AUDITING JOURNAL

2003

48 Pawitra, T.A., and Tan, K.C. Tourist Satisfaction in Singapore – A Perspective from Indonesian Tourists MANAGING SERVICE QUALITY

2003

49 Tan, K.C., Xie, M., and Li, Y.N. A Service Quality Framework for Web-based Information Systems THE TQM MAGAZINE

2003

50 Wang, W., and Poh, K.L. Fuzzy MCDM based on Confidence Analysis FUZZY ECONOMICS REVIEW

2003

51 Goh, T.N. Six Sigma Certification - A Stamp of Quality Excellence PRODUCTIVITY DIGEST

2004

52 Ho, Y.K., Xu, Z.Y., and Yap, C.M. R&D Investment and Systematic Risk ACCOUNTING AND FINANCE

2004

53 Ng, K.W., Tan, K.C., and Lim, E. A Cognitive Engineering Analysis of an Equipment Preventive Maintenance Procedure ASIAN JOURNAL OF ERGONOMICS

2004

54 Tan, K.C., and Raghavan, V. Incorporating Concepts of Business Priority into Quality Function Deployment INTERNATIONAL JOURNAL OF INNOVATION MANAGEMENT

2004

55 Tang, L.C., and Paoli, P. A Spreadsheet-based Multiple Criteria Optimisation Framework for Quality Function Deployment INTERNATIONAL JOURNAL OF QUALITY AND RELIABILITY MANAGEMENT

2004

Appendix B

A-28


56 Chai, K.H., Zhang, J. and Tan, K.C. A TRIZ-Based Method for New Service Design JOURNAL OF SERVICE RESEARCH

2005

57 Pek, P.K., and Poh, K.L. A Bayesian Tutoring System for Newtonian Mechanics: Can it Adapt to Different Learners? JOURNAL OF EDUCATIONAL COMPUTING RESEARCH

2005

58 Tang, L.C., and Cheong, W.T. On Establishing CCC Charts INTERNATIONAL JOURNAL OF PERFORMABILITY ENGINEERING

2005

59 Yap, C.M., Chai, K.H. and Lemaire, P. An Empirical Study on Functional Diversity and Innovation in SMEs CREATIVITY AND INNOVATION MANAGEMENT

2005

60 Zhang J., Chai, K.H. and Tan, K.C. Applying TRIZ to Service Conceptual Design: An Exploratory Study CREATIVITY AND INNOVATION MANAGEMENT

2005

Appendix C

A-29

APPENDIX C

Authors List for NUS-ISE Publications

No Name Whole

counting Fractional counting

First Author

Counting

1 ABERNATHY, FH 1 0.33 0

2 ANG, BW 64 37.50 46

3 ATIENZA, OO 3 1.00 3

4 BAI, CG 1 0.25 1

5 BAI, F 1 0.33 0

6 BROMBACHER, AC 1 0.25 0

7 CAI, DQ 4 1.08 2

8 CAO, LQ 1 0.20 0

9 CETINKAYA, S 4 1.33 0

10 CHAI, KH 2 1.33 2

11 CHAN, DSH 1 0.25 0

12 CHAN, LY 5 1.50 4

13 CHAN, WT 1 0.25 0

14 CHANG, DS 6 3.00 3

15 CHEN, HM 1 0.25 1

16 CHENG, TCE 5 4.50 5

17 CHEONG, WT 1 0.50 0

18 CHEONG, YM 1 0.33 1

19 CHEU, RL 1 0.33 1

20 CHEW, EP 18 7.17 8

21 CHEW, YH 1 0.25 0

22 CHIA, SE 1 0.25 0

23 CHICK, SE 1 0.50 0

24 CHIM, YC 2 0.67 2

25 CHOI, KH 7 3.17 4

26 CHOO, KW 1 0.33 0

27 CHUA, VCH 2 0.83 2

28 CHUAN, TK 1 0.50 1

29 CHUNG, HS 1 0.33 0

30 CUI, LR 8 3.25 7

31 DAI, YS 9 2.28 4

32 DEL CASTILLO, E 1 0.25 0

33 DENG, CC 3 1.00 0

34 FAN, YL 1 0.50 0

35 FEHLING, MR 1 0.33 0

36 FUH, JYH 2 0.45 1

37 FWA, TF 7 2.50 0

38 GAN, FF 1 0.25 0

39 GAO, YF 1 0.50 1

40 GAUDOIN, O 1 0.33 0

41 GHITANY, ME 1 0.33 1

42 GOH, CJ 19 8.17 8

43 GOH, KH 1 0.33 0

44 GOH, TN 60 23.43 12

45 GOU, HM 1 0.20 0

46 GOVINDARAJU, K 2 0.67 0

47 GREGORY, MJ 1 0.33 0

48 HARMANEC, D 1 0.14 1

49 HAYES, S 1 0.25 0

50 HE, B 1 0.33 0

51 HO, SL 5 1.57 4

52 HO, YC 3 1.00 0

Appendix C

A-30

No Name Whole


First Author

Counting

53 HOLZMAN, AG 1 0.50 0

54 HONG, GY 5 2.00 1

55 HORIANA 1 0.33 0

56 HORVITZ, EJ 1 0.33 0

57 HU, QP 1 0.25 0

58 HU, XN 1 0.33 1

59 HUANG, BQ 1 0.20 1

60 HUANG, HC 14 5.33 3

61 HUANG, JP 2 0.67 1

62 HUIN, WM 1 0.33 0

63 IBRAHIM, Y 10 3.75 2

64 JARUPHONGSA, W 4 1.33 3

65 JAYARAM, JSR 1 0.25 1

66 JEPPS, G 1 0.25 0

67 JEWKES, E 1 0.33 1

68 JEYARATNAM, J 1 0.25 0

69 JOHNSON, LA 2 1.00 0

70 KASSIM, AA 2 0.67 0

71 KITIPORNCHAI, S 1 0.25 0

72 KONG, H 1 0.33 1

73 KOTZ, S 2 0.67 1

74 KUAN, SN 1 0.33 1

75 KUO, W 1 0.25 0

76 KURALMANI, V 2 0.50 1

77 LAI, CD 15 5.37 7

78 LAI, X 1 0.33 1

79 LAI, YW 1 0.33 1

80 LAM, SW 1 0.50 1

81 LAU, TWE 1 0.33 0

82 LAW, CL 1 0.25 0

83 LEE, C 3 1.33 1

84 LEE, CH 3 0.83 0

85 LEE, CL 1 0.50 0

86 LEE, CY 4 1.33 1

87 LEE, LH 13 4.83 6

88 LEE, PW 1 0.50 0

89 LEE, SY 1 0.50 0

90 LEE, YO 1 0.33 0

91 LEONG, TY 1 0.14 0

92 LEVITIN, G 1 0.25 1

93 LEW, TWK 1 0.14 0

94 LI, D 1 0.33 1

95 LI, R 1 0.50 1

96 LI, Y 1 0.20 0

97 LI, YN 1 0.33 1

98 LIM, CC 3 1.08 0

99 LIM, KH 1 0.33 0

100 LIM, SC 3 1.00 1

101 LIM, TK 1 0.33 0

102 LIN, DKJ 2 0.50 0

103 LIN, L 1 0.33 1

104 LIONG, SY 5 2.08 3

105 LIU, FL 4 1.67 1

106 LIU, GQ 3 0.83 2

107 LIU, JH 1 0.20 1

108 LIU, SB 2 0.67 2

Appendix C

A-31

No Name Whole


First Author

Counting

109 LIU, SQ 4 1.67 4

110 LIU, WH 1 0.20 0

111 LIU, XQ 3 1.00 1

112 LOH, HT 4 1.17 0

113 LOO, EH 1 0.33 1

114 LOW, PC 1 0.25 0

115 LOY, C 1 0.33 1

116 LU, XS 4 1.25 2

117 MA, CX 1 0.33 0

118 MOK, YL 1 0.33 1

119 MOORE, EJ 1 0.25 0

120 MOORE, JB 1 0.50 1

121 MURTHY, DNP 1 0.33 0

122 NEE, AYC 1 0.33 0

123 NEO, KS 1 0.20 0

124 NEOH, KG 1 0.50 0

125 NG, I 1 0.14 0

126 NG, KM 4 1.33 0

127 NG, SH 3 1.00 1

128 NG, TS 1 0.33 0

129 NG, TT 3 1.17 0

130 OH, ST 1 0.50 0

131 OHLSSON, N 1 0.25 0

132 OLORUNNIWO, FO 1 0.50 0

133 ONG, CJ 1 0.33 0

134 ONG, CN 1 0.25 1

135 ONG, HL 29 10.83 7

136 ONG, SH 1 0.33 0

137 OU, K 4 1.17 0

138 PANDIYAN, G 1 0.50 0

139 PAUL, H 1 1.00 1

140 PEK, PK 2 1.00 2

141 POH, CK 2 0.67 0

142 POH, KL 28 10.51 7

143 PRABHU, NU 1 0.50 1

144 PREUSS, W 1 0.33 0

145 QUADDUS, MA 6 4.00 4

146 RAHMAN, M 3 0.83 1

147 RANJAN, P 2 0.67 1

148 RO, KK 1 0.33 0

149 SAMUDRA, GS 1 0.25 0

150 SEAH, KHW 3 0.83 1

151 SEE, SP 2 0.67 0

152 SHANMUGAN, P 1 0.33 0

153 SHEN, XX 3 1.03 2

154 SHI, YS 1 0.33 0

155 SHREERAM, J 1 0.33 0

156 SOON, LC 1 0.50 0

157 SOUDER, WE 1 0.50 0

158 SUN, JW 1 0.50 1

159 SUN, YS 4 1.75 2

160 SUNDARESH, S 1 0.14 0

161 TAN, AP 1 0.33 0

162 TAN, HH 1 0.33 0

163 TAN, HK 1 0.50 1

164 TAN, KC 11 3.62 4

Appendix C

A-32

No Name Whole


First Author

Counting

165 TANG, LC 39 18.48 22

166 TANG, XY 3 0.92 0

167 TANG, Y 4 1.20 1

168 TAY, FEH 1 0.33 1

169 TENG, SY 2 0.67 2

170 TEO, KL 21 9.83 11

171 THAN, SE 2 0.83 0

172 THEVENDRAN, V 1 0.25 0

173 TSUI, KL 3 0.75 0

174 UENG, CH 1 0.33 0

175 VARAPRASAD, N 1 0.50 0

176 VENTURA, JA 3 1.50 2

177 VICKSON, R 1 0.33 0

178 WANG, CM 4 1.42 2

179 WANG, H 4 1.20 1

180 WANG, LX 1 0.33 0

181 WEE, CL 1 0.33 0

182 WEE, EHT 1 0.33 1

183 WILSON, SJ 1 0.50 0

184 WOHLIN, C 3 0.92 0

185 WONG, CG 1 0.33 0

186 WONG, KH 2 0.67 0

187 WONG, YS 2 0.45 0

188 WU, X 1 0.50 1

189 WU, ZS 2 0.83 1

190 XIANG, YP 2 1.00 2

191 XIE, A 1 0.25 0

192 XIE, M 97 34.20 27

193 XIE, W 4 1.33 3

194 XU, K 5 1.65 2

195 YANG, B 3 1.25 1

196 YANG, GY 2 0.83 0

197 YANG, MS 1 0.50 1

198 YANG, P 1 0.20 0

199 YANG, ZL 6 2.25 5

200 YAP, CM 2 1.00 1

201 YEE, CY 2 0.45 0

202 YEO, TT 1 0.14 0

203 ZENG, L 1 0.33 1

204 ZHANG, CW 2 0.83 2

205 ZHANG, FQ 5 2.17 1

206 ZHANG, YT 1 0.33 0

207 ZHAO, M 5 2.08 4

208 ZHU, ML 1 0.20 0

209 ZHU, QL 1 0.25 0

210 ZHUANG, L 5 3.45 4

211 ZHUANG, WJ 1 0.50 1

Appendix D

A-33

APPENDIX D

Journal List for NUS-ISE Publications

No Journal Title Quantity JIF

1 ADVANCES IN ENGINEERING SOFTWARE 9 0.3

2 APPLIED ARTIFICIAL INTELLIGENCE 1 0.6

3 APPLIED ENERGY 1 0.7

4 APPLIED MATHEMATICS AND OPTIMIZATION 1 0.6

5 ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 14 0.3

6 AUTOMATICA 1 1.7

7 CHEMICAL ENGINEERING COMMUNICATIONS 1 0.4

8 COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 4 0.2

9 COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2 0.2

10 COMPUTATIONAL STATISTICS & DATA ANALYSIS 2 0.7

11 COMPUTER SYSTEMS SCIENCE AND ENGINEERING 1 0.1

12 COMPUTERS & EDUCATION 1 1

13 COMPUTERS & INDUSTRIAL ENGINEERING 12 0.3

14 COMPUTERS & MATHEMATICS WITH APPLICATIONS 1 0.4

15 COMPUTERS & OPERATIONS RESEARCH 2 0.7

16 COMPUTERS & STRUCTURES 1 0.6

17 COMPUTERS IN BIOLOGY AND MEDICINE 1 1.4

18 COMPUTERS IN INDUSTRY 1 0.9

19 COMPUTING 1 0.9

20 CYBERNETICS AND SYSTEMS 1 0.7

21 ELECTRIC POWER SYSTEMS RESEARCH 1 0.3

22 ENERGY 27 0.7

23 ENERGY ECONOMICS 10 0.6

24 ENERGY JOURNAL 1 0.7

25 ENERGY POLICY 10 1

26 ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 3 0.7

27 ENGINEERING OPTIMIZATION 2 0.5

28 ENGINEERING STRUCTURES 1 0.6

29 EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 10 0.8

30 IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2 2.2

31 IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS

1 1

32 IEEE TRANSACTIONS ON ELECTRONICS PACKAGING MANUFACTURING 2 0.5

33 IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT 2 0.9

34 IEEE TRANSACTIONS ON RELIABILITY 7 0.7

35 IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 1 2

36 IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS 2 0.9

37 IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS

1 0.8

38 IIE TRANSACTIONS 9 0.5

39 IMA JOURNAL OF MATHEMATICAL CONTROL AND INFORMATION 1 N/A

40 IMAGE AND VISION COMPUTING 1 1.4

41 INFORMATION AND SOFTWARE TECHNOLOGY 2 0.4

42 INFORMATION SCIENCES 1 0.7

43 INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2 0.4

44 INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING 1 0.3

45 INTERNATIONAL JOURNAL OF ENGINEERING EDUCATION 1 0.3

46 INTERNATIONAL JOURNAL OF FLEXIBLE MANUFACTURING SYSTEMS 1 0.2

47 INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING-THEORY APPLICATIONS AND PRACTICE

4 0.1

48 INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 1 N/A

49 INTERNATIONAL JOURNAL OF MATERIALS & PRODUCT TECHNOLOGY 1 0.2

50 INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 8 1

51 INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 10 0.5

Appendix D

A-34

No Journal Title Quantity JIF

52 INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 4 0.2

53 INTERNATIONAL JOURNAL OF TECHNOLOGY MANAGEMENT 1 0.2

54 INTERNATIONAL JOURNAL OF VEHICLE DESIGN 3 0.3

55 JOURNAL OF APPLIED PROBABILITY 2 0.6

56 JOURNAL OF APPLIED STATISTICS 5 0.3

57 JOURNAL OF ENGINEERING MECHANICS-ASCE 1 0.8

58 JOURNAL OF GLOBAL OPTIMIZATION 1 0.7

59 JOURNAL OF HYDRAULIC ENGINEERING-ASCE 2 1.2

60 JOURNAL OF INFORMATION SCIENCE 1 0.7

61 JOURNAL OF INTELLIGENT MANUFACTURING 1 0.3

62 JOURNAL OF MANUFACTURING SYSTEMS 2 0.2

63 JOURNAL OF MATERIALS PROCESSING TECHNOLOGY 2 0.6

64 JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY 1 0.2

65 JOURNAL OF MECHANICAL WORKING TECHNOLOGY 1 N/A

66 JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 5 0.6

67 JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 1 0.9

68 JOURNAL OF QUALITY TECHNOLOGY 4 1.1

69 JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 3 0.3

70 JOURNAL OF STATISTICAL PLANNING AND INFERENCE 1 0.5

71 JOURNAL OF SYSTEMS AND SOFTWARE 5 0.7

72 JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2 4.3

73 JOURNAL OF THE AUSTRALIAN MATHEMATICAL SOCIETY 3 0.3

74 JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 4 0.6

75 JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES D-THE STATISTICIAN 1 0.8

76 JOURNAL OF TRANSPORTATION ENGINEERING-ASCE 1 0.3

77 JOURNAL OF URBAN TECHNOLOGY 1 0.4

78 JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT-ASCE 1 1.2

79 KNOWLEDGE ENGINEERING REVIEW 1 2.2

80 MATHEMATICAL AND COMPUTER MODELLING 2 0.4

81 MATHEMATICAL BIOSCIENCES 1 1.4

82 MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES 1 0.2

83 METRIKA 1 0.5

84 MICROELECTRONICS RELIABILITY 6 0.7

85 NAVAL RESEARCH LOGISTICS 4 0.4

86 OPERATIONS RESEARCH 1 1.2

87 OPTIMAL CONTROL APPLICATIONS & METHODS 1 0.5

88 PATTERN ANALYSIS AND APPLICATIONS 1 0.8

89 PERFORMANCE EVALUATION 1 0.8

90 PROBLEMS OF CONTROL AND INFORMATION THEORY-PROBLEMY UPRAVLENIYA I TEORII INFORMATSII

1 N/A

91 PROCEEDINGS : ANNUAL RELIABILITY AND MAINTAINABILITY SYMPOSIUM 4 0

92 PRODUCTION PLANNING & CONTROL 4 0.4

93 QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 16 0.2

94 QUEUEING SYSTEMS 1 0.9

95 R & D MANAGEMENT 1 0.5

96 RELIABILITY ENGINEERING & SYSTEM SAFETY 13 0.7

97 ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2 0.6

98 SCANDINAVIAN JOURNAL OF WORK ENVIRONMENT & HEALTH 1 1.8

99 SCRIPTA METALLURGICA 1 N/A

100 SOCIAL CHOICE AND WELFARE 2 0.3

101 SOCIO-ECONOMIC PLANNING SCIENCES 1 N/A

102 STATISTICS & PROBABILITY LETTERS 2 0.3

103 SYSTEMS & CONTROL LETTERS 1 1.2

104 TECHNOVATION 1 0.5

105 TOTAL QUALITY MANAGEMENT & BUSINESS EXCELLENCE 6 0.3

106 TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2 1.4

107 WATER RESOURCES RESEARCH 1 1.9

108 WEAR 1 1.4

Appendix E

A-35

APPENDIX E

Authors outside the main component of NUS-ISE co-authorship networks.

1986-1995

1991-2000

Appendix E

A-36

1996-2005

1986-2005

Appendix F

A-37

APPENDIX F

Degree, Closeness, and Betweenness Centralities of Authors

Degree Closeness Betweenness Rank

Name Degree NrmDegree Name Farness nCloseness Name Betweenness nBetweenness

1 XIE_M 203 2.711 XIE_M 388 49.485 XIE_M 8198.333 44.712

2 GOH_TN 126 1.683 GOH_TN 396 48.485 ANG_BW 4680.667 25.527

3 ANG_BW 70 0.935 TANG_LC 419 45.823 POH_KL 3879.032 21.155

4 POH_KL 59 0.788 ONG_HL 419 45.823 GOH_TN 3807.271 20.764

5 TANG_LC 57 0.761 ANG_BW 430 44.651 TANG_LC 3721.256 20.295

6 ONG_HL 56 0.748 POH_KL 433 44.342 ONG_HL 2801.571 15.279

7 LAI_CD 31 0.414 TAN_KC 459 41.83 LOH_HT 2502 13.645

8 CHEW_EP 29 0.387 SUN_YS 490 39.184 IBRAHIM_Y 1856 10.122

9 TEO_KL 28 0.374 XU_K 501 38.323 TAN_KC 1819.95 9.926

10 GOH_CJ 27 0.361 HO_SL 502 38.247 CHEW_EP 1799.849 9.816

11 DAI_YS 27 0.361 LIN_DKJ 502 38.247 LEE_LH 1703.922 9.293

12 TAN_KC 25 0.334 CHEW_EP 504 38.095 TEO_KL 1549.783 8.452

13 HUANG_HC 24 0.321 LIM_CC 509 37.721 HUANG_HC 786.058 4.287

14 LEE_LH 24 0.321 LAI_CD 510 37.647 LIM_CC 528.646 2.883

15 IBRAHIM_Y 19 0.254 ZHU_ML 515 37.282 GOH_CJ 358.796 1.957

16 HO_SL 13 0.174 YANG_GY 517 37.137 WANG_CM 224.838 1.226

17 CUI_LR 13 0.174 SHEN_XX 519 36.994 NG_SH 222.034 1.211

18 FWA_TF 13 0.174 WANG_H 519 36.994 QUADDUS_MA 191 1.042

19 XU_K 13 0.174 ZHANG_CW 520 36.923 YAP_CM 191 1.042

20 CHAN_LY 12 0.16 DAI_YS 522 36.782 CUI_LR 184 1.003

21 CAI_DQ 12 0.16 NG_SH 524 36.641 LAI_CD 101.505 0.554

22 YANG_ZL 11 0.147 YANG_P 527 36.433 FWA_TF 24.356 0.133

23 TANG_Y 10 0.134 LIU_GQ 528 36.364 CHAN_LY 24.25 0.132

24 OU_K 10 0.134 LEVITIN_G 528 36.364 WONG_KH 14.862 0.081

25 WANG_H 10 0.134 YANG_B 528 36.364 TSUI_KL 9.873 0.054

26 LOH_HT 10 0.134 DENG_CC 529 36.295 KURALMANI_V 8.706 0.047

27 SUN_YS 9 0.12 LIU_XQ 529 36.295 LIN_DKJ 8.639 0.047

28 CHOI_KH 9 0.12 LI_YN 533 36.023 LIU_FL 8.25 0.045

29 LU_XS 9 0.12 LAI_X 533 36.023 ZHANG_FQ 8.25 0.045

Appendix F

A-38



30 TSUI_KL 9 0.12 CAI_DQ 533 36.023 DAI_YS 6.333 0.035

31 XIE_W 8 0.107 TSUI_KL 533 36.023 XU_K 3.277 0.018

32 NG_KM 8 0.107 CHAN_LY 534 35.955 HO_SL 2.694 0.015

33 LIU_GQ 8 0.107 KURALMANI_V 534 35.955 YANG_ZL 2.5 0.014

34 SEAH_KHW 8 0.107 CASTILLO_E 535 35.888 CAI_DQ 1.667 0.009

35 LEE_CH 8 0.107 DEL 535 35.888 NG_KM 1.5 0.008

36 HONG_GY 8 0.107 LIU_JH 535 35.888 HO_YC 1.5 0.008

37 WANG_CM 8 0.107 TANG_Y 535 35.888 WOHLIN_C 1 0.005

38 RAHMAN_M 8 0.107 CAO_LQ 535 35.888 LIONG_SY 1 0.005

39 ZHAO_M 8 0.107 LOW_PC 536 35.821 ZHAO_M 1 0.005

40 LIONG_SY 8 0.107 TANG_XY 536 35.821 CHOI_KH 0.5 0.003

41 ZHANG_FQ 7 0.093 LU_XS 536 35.821 HONG_GY 0.5 0.003

42 TANG_XY 7 0.093 GAN_FF 536 35.821 KOTZ_S 0.5 0.003

43 NG_SH 7 0.093 MOK_YL 537 35.754 OU_K 0.333 0.002

44 SHEN_XX 7 0.093 RANJAN_P 537 35.754 CASTILLO_E 0 0

45 WOHLIN_C 7 0.093 XIE_W 537 35.754 CHEU_RL 0 0

46 DENG_CC 7 0.093 LOY_C 537 35.754 FEHLING_MR 0 0

47 LIU_XQ 6 0.08 KONG_H 537 35.754 CHUA_VCH 0 0

48 LEW_TWK 6 0.08 HE_B 537 35.754 GOU_HM 0 0

49 HARMANEC_D 6 0.08 GOH_CJ 545 35.229 CHENG_TCE 0 0

50 LIU_SQ 6 0.08 LOH_HT 548 35.036 HAYES_S 0 0

51 LIU_FL 6 0.08 ATIENZA_OO 555 34.595 HOLZMAN_AG 0 0

52 ATIENZA_OO 6 0.08 HUANG_JP 555 34.595 GAO_YF 0 0

53 LIN_DKJ 6 0.08 THAN_SE 555 34.595 HORVITZ_EJ 0 0

54 LIM_SC 6 0.08 LEE_LH 555 34.595 ATIENZA_OO 0 0

55 HO_YC 6 0.08 BAI_F 555 34.595 BAI_F 0 0

56 YEO_TT 6 0.08 CUI_LR 560 34.286 BROMBACHER_AC 0 0

57 KURALMANI_V 6 0.08 HUANG_HC 560 34.286 CAO_LQ 0 0

58 SUNDARESH_S 6 0.08 LOO_EH 570 33.684 HU_QP 0 0

59 CHANG_DS 6 0.08 LEE_YO 570 33.684 CHAN_DSH 0 0

60 LIM_CC 6 0.08 HU_XN 572 33.566 JAYARAM_JSR 0 0

61 LEONG_TY 6 0.08 YANG_ZL 575 33.391 ABERNATHY_FH 0 0

62 NG_I 6 0.08 LIU_WH 576 33.333 JEYARATNAM_J 0 0

63 NG_TT 5 0.067 LI_Y 576 33.333 CHEN_HM 0 0

Appendix F

A-39



64 YANG_B 5 0.067 WOHLIN_C 576 33.333 CHEONG_WT 0 0

65 GOU_HM 4 0.053 HUANG_BQ 576 33.333 CHEONG_YM 0 0

66 DEL 4 0.053 GOU_HM 576 33.333 KONG_H 0 0

67 CASTILLO_E 4 0.053 PREUSS_W 576 33.333 HORIANA 0 0

68 QUADDUS_MA 4 0.053 HU_QP 576 33.333 HUIN_WM 0 0

69 TENG_SY 4 0.053 BAI_CG 576 33.333 KUO_W 0 0

70 YANG_P 4 0.053 ZHAO_M 576 33.333 CHICK_SE 0 0

71 WONG_KH 4 0.053 OHLSSON_N 577 33.276 CHIM_YC 0 0

72 CAO_LQ 4 0.053 HONG_GY 577 33.276 LAI_X 0 0

73 ZHU_ML 4 0.053 KOTZ_S 577 33.276 CHAN_WT 0 0

74 SEE_SP 4 0.053 GHITANY_ME 578 33.218 LAM_SW 0 0

75 RANJAN_P 4 0.053 SEE_SP 578 33.218 CHUNG_HS 0 0

76 LIU_SB 4 0.053 SHANMUGAN_P 578 33.218 LAW_CL 0 0

77 LIU_WH 4 0.053 GAUDOIN_O 578 33.218 HUANG_BQ 0 0

78 LI_Y 4 0.053 ZHANG_YT 578 33.218 DEL 0 0

79 KASSIM_AA 4 0.053 GOVINDARAJU_K 578 33.218 CHOO_KW 0 0

80 CHIM_YC 4 0.053 MURTHY_DNP 578 33.218 FAN_YL 0 0

81 HUANG_JP 4 0.053 ZHUANG_WJ 579 33.161 LEE_YO 0 0

82 HUANG_BQ 4 0.053 WANG_CM 582 32.99 CHANG_DS 0 0

83 LIU_JH 4 0.053 LEE_CH 585 32.821 LEVITIN_G 0 0

84 GOVINDARAJU_K 4 0.053 RAHMAN_M 585 32.821 LEW_TWK 0 0

85 POH_CK 4 0.053 SEAH_KHW 585 32.821 GAUDOIN_O 0 0

86 KOTZ_S 4 0.053 WEE_EHT 586 32.765 LIM_KH 0 0

87 HU_QP 3 0.04 NEE_AYC 586 32.765 JOHNSON_LA 0 0

88 SAMUDRA_GS 3 0.04 MA_CX 586 32.765 GOH_KH 0 0

89 KUO_W 3 0.04 VARAPRASAD_N 587 32.709 KITIPORNCHAI_S 0 0

90 BROMBACHER_AC 3 0.04 FWA_TF 592 32.432 LIN_L 0 0

91 LOW_PC 3 0.04 LIM_SC 595 32.269 LEE_PW 0 0

92 CHUA_VCH 3 0.04 TEO_KL 595 32.269 KUAN_SN 0 0

93 YANG_GY 3 0.04 LIU_FL 597 32.161 LIU_GQ 0 0

94 MOORE_EJ 3 0.04 HUIN_WM 597 32.161 HE_B 0 0

95 HAYES_S 3 0.04 ZHANG_FQ 597 32.161 LIU_SB 0 0

96 JEYARATNAM_J 3 0.04 TAN_HH 597 32.161 LIU_SQ 0 0

97 JAYARAM_JSR 3 0.04 TENG_SY 597 32.161 LIU_WH 0 0

Appendix F

A-40



98 THAN_SE 3 0.04 LIU_SB 597 32.161 LIU_XQ 0 0

99 CHEN_HM 3 0.04 CHEONG_YM 597 32.161 LI_D 0 0

100 LAW_CL 3 0.04 LAI_YW 598 32.107 BAI_CG 0 0

101 CHEW_YH 3 0.04 NG_KM 607 31.631 LI_Y 0 0

102 OHLSSON_N 3 0.04 ZENG_L 609 31.527 LI_YN 0 0

103 CHAN_WT 3 0.04 LIU_SQ 609 31.527 HUANG_JP 0 0

104 CHAN_DSH 3 0.04 TAN_AP 609 31.527 LOO_EH 0 0

105 CHIA_SE 3 0.04 ONG_SH 609 31.527 LOW_PC 0 0

106 BAI_CG 3 0.04 KUAN_SN 609 31.527 LOY_C 0 0

107 KITIPORNCHAI_S 3 0.04 CHEONG_WT 610 31.475 LU_XS 0 0

108 THEVENDRAN_V 3 0.04 GAO_YF 610 31.475 MA_CX 0 0

109 ZHU_QL 3 0.04 CHANG_DS 610 31.475 MOK_YL 0 0

110 GAN_FF 3 0.04 OLORUNNIWO_FO 610 31.475 MOORE_EJ 0 0

111 ONG_CN 3 0.04 PRABHU_NU 610 31.475 MOORE_JB 0 0

112 WU_ZS 3 0.04 LAM_SW 610 31.475 MURTHY_DNP 0 0

113 JEPPS_G 3 0.04 OU_K 614 31.27 NEE_AYC 0 0

114 LEVITIN_G 3 0.04 ZHU_QL 615 31.22 NEOH_KG 0 0

115 XIE_A 3 0.04 CHEW_YH 615 31.22 GOVINDARAJU_K 0 0

116 ZHANG_CW 3 0.04 CHOI_KH 619 31.018 CHEW_YH 0 0

117 CHEU_RL 2 0.027 LEW_TWK 619 31.018 CHIA_SE 0 0

118 KONG_H 2 0.027 YAP_CM 619 31.018 NG_TS 0 0

119 FEHLING_MR 2 0.027 HARMANEC_D 619 31.018 NG_TT 0 0

120 WONG_CG 2 0.027 POH_CK 619 31.018 OHLSSON_N 0 0

121 LIN_L 2 0.027 NG_TT 619 31.018 OH_ST 0 0

122 HORVITZ_EJ 2 0.027 LEONG_TY 619 31.018 OLORUNNIWO_FO 0 0

123 CHUNG_HS 2 0.027 YEO_TT 619 31.018 ONG_CJ 0 0

124 LIM_TK 2 0.027 SUNDARESH_S 619 31.018 ONG_CN 0 0

125 HUIN_WM 2 0.027 NG_I 619 31.018 LEE_CH 0 0

126 ONG_SH 2 0.027 CHUNG_HS 620 30.968 ONG_SH 0 0

127 MURTHY_DNP 2 0.027 RO_KK 620 30.968 DENG_CC 0 0

128 GHITANY_ME 2 0.027 NEOH_KG 621 30.918 PANDIYAN_G 0 0

129 PEK_PK 2 0.027 SUN_JW 621 30.918 PEK_PK 0 0

130 NG_TS 2 0.027 OH_ST 621 30.918 POH_CK 0 0

131 LOO_EH 2 0.027 PANDIYAN_G 621 30.918 GAN_FF 0 0

Appendix F

A-41



132 MA_CX 2 0.027 LEE_PW 621 30.918 PRABHU_NU 0 0

133 CHOO_KW 2 0.027 LEE_SY 621 30.918 PREUSS_W 0 0

134 LIM_KH 2 0.027 QUADDUS_MA 622 30.868 GHITANY_ME 0 0

135 ONG_CJ 2 0.027 FEHLING_MR 623 30.819 RAHMAN_M 0 0

136 GOH_KH 2 0.027 LIN_L 623 30.819 RANJAN_P 0 0

137 CHEONG_YM 2 0.027 LIM_TK 623 30.819 RO_KK 0 0

138 ZENG_L 2 0.027 CHOO_KW 623 30.819 SAMUDRA_GS 0 0

139 GAUDOIN_O 2 0.027 WONG_CG 623 30.819 SEAH_KHW 0 0

140 TAN_HH 2 0.027 HORVITZ_EJ 623 30.819 HARMANEC_D 0 0

141 SHANMUGAN_P 2 0.027 PEK_PK 624 30.769 SHANMUGAN_P 0 0

142 WEE_CL 2 0.027 XIANG_YP 624 30.769 SHEN_XX 0 0

143 SHREERAM_J 2 0.027 WU_X 624 30.769 SHREERAM_J 0 0

144 LAI_X 2 0.027 CHIA_SE 648 29.63 SOUDER_WE 0 0

145 LAI_YW 2 0.027 ONG_CN 648 29.63 SUNDARESH_S 0 0

146 KUAN_SN 2 0.027 JEYARATNAM_J 648 29.63 SUN_JW 0 0

147 LI_D 2 0.027 NG_TS 675 28.444 SUN_YS 0 0

148 YAP_CM 2 0.027 GOH_KH 678 28.319 LI_R 0 0

149 NEE_AYC 2 0.027 HORIANA 678 28.319 TANG_XY 0 0

150 LI_YN 2 0.027 ONG_CJ 694 27.666 TANG_Y 0 0

151 PREUSS_W 2 0.027 CHEU_RL 694 27.666 TAN_AP 0 0

152 WEE_EHT 2 0.027 LIM_KH 694 27.666 TAN_HH 0 0

153 LEE_YO 2 0.027 WEE_CL 694 27.666 TAN_HK 0 0

154 LOY_C 2 0.027 JOHNSON_LA 695 27.626 HU_XN 0 0

155 UENG_CH 2 0.027 WONG_KH 705 27.234 TAY_FEH 0 0

156 XIANG_YP 2 0.027 CHICK_SE 715 26.853 TENG_SY 0 0

157 HORIANA 2 0.027 IBRAHIM_Y 717 26.778 JEPPS_G 0 0

158 TAY_FEH 2 0.027 JAYARAM_JSR 727 26.41 THAN_SE 0 0

159 JOHNSON_LA 2 0.027 BROMBACHER_AC 727 26.41 THEVENDRAN_V 0 0

160 HE_B 2 0.027 KUO_W 736 26.087 KASSIM_AA 0 0

161 BAI_F 2 0.027 XIE_A 736 26.087 UENG_CH 0 0

162 WANG_LX 2 0.027 HO_YC 743 25.841 VARAPRASAD_N 0 0

163 MOK_YL 2 0.027 TAY_FEH 745 25.772 NG_I 0 0

164 RO_KK 2 0.027 LI_D 745 25.772 WANG_H 0 0

165 LAU_TWE 2 0.027 LAU_TWE 745 25.772 WANG_LX 0 0

Appendix F

A-42



166 HU_XN 2 0.027 WANG_LX 745 25.772 WEE_CL 0 0

167 ZHANG_YT 2 0.027 ABERNATHY_FH 745 25.772 WEE_EHT 0 0

168 ABERNATHY_FH 2 0.027 FAN_YL 746 25.737 WILSON_SJ 0 0

169 TAN_AP 2 0.027 YANG_MS 746 25.737 LAI_YW 0 0

170 OLORUNNIWO_FO 1 0.013 UENG_CH 750 25.6 WONG_CG 0 0

171 SUN_JW 1 0.013 CHUA_VCH 750 25.6 LAU_TWE 0 0

172 GAO_YF 1 0.013 LI_R 751 25.566 WU_X 0 0

173 FAN_YL 1 0.013 KITIPORNCHAI_S 762 25.197 WU_ZS 0 0

174 WILSON_SJ 1 0.013 THEVENDRAN_V 762 25.197 XIANG_YP 0 0

175 LI_R 1 0.013 MOORE_EJ 784 24.49 XIE_A 0 0

176 LAM_SW 1 0.013 HAYES_S 784 24.49 LEE_SY 0 0

177 NEOH_KG 1 0.013 JEPPS_G 784 24.49 XIE_W 0 0

178 WU_X 1 0.013 WU_ZS 785 24.459 LEONG_TY 0 0

179 PANDIYAN_G 1 0.013 MOORE_JB 786 24.427 YANG_B 0 0

180 PRABHU_NU 1 0.013 CHENG_TCE 786 24.427 YANG_GY 0 0

181 YANG_MS 1 0.013 WILSON_SJ 786 24.427 YANG_MS 0 0

182 CHENG_TCE 1 0.013 SOUDER_WE 810 23.704 YANG_P 0 0

183 MOORE_JB 1 0.013 HOLZMAN_AG 813 23.616 LIM_SC 0 0

184 CHEONG_WT 1 0.013 LIONG_SY 905 21.215 LIM_TK 0 0

185 HOLZMAN_AG 1 0.013 CHAN_DSH 906 21.192 YEO_TT 0 0

186 VARAPRASAD_N 1 0.013 CHEN_HM 906 21.192 ZENG_L 0 0

187 LEE_PW 1 0.013 LAW_CL 906 21.192 ZHANG_CW 0 0

188 LEE_SY 1 0.013 SAMUDRA_GS 906 21.192 SEE_SP 0 0

189 TAN_HK 1 0.013 CHAN_WT 906 21.192 ZHANG_YT 0 0

190 CHICK_SE 1 0.013 CHIM_YC 907 21.169 LIU_JH 0 0

191 ZHUANG_WJ 1 0.013 SHREERAM_J 907 21.169 ZHUANG_WJ 0 0

192 SOUDER_WE 1 0.013 KASSIM_AA 907 21.169 ZHU_ML 0 0

193 OH_ST 1 0.013 TAN_HK 908 21.145 ZHU_QL 0 0

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