Presented to:
Dr. Jay F. Nunamaker Jr.
University of Arizona
Management Information Systems
MIS696a Research Methodologies
Fall 2001
The MIS Disciplines
Founding Papers, Current Research, and
Future Direction
Averill Cate
Sabah Currim
Fred Keers
Byron Marshall
Daniel McDonald
Jialun Qin
Tiantian Qin
Jochen Reb
Doug Twitchell
Harry Wang
Gang Wang
Yiwen Zhang
Yilu Zhou
Table of Content
INTRODUCTION______________________________________________________ 1
MIS DEFINED ________________________________________________________
A MODEL FOR CLASSIFYING MIS RESEARCH ________________________________
Description ________________________________________________________
A FEW EXAMPLES _____________________________________________________
MIS TIMELINE ________________________________________________________
1
2
2
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8
COLLABORATION / COMMUNICATION________________________________ 9
DATABASE / SYSTEMS ANALYSIS ____________________________________ 12
WATERSHED ________________________________________________________
CURRENT ___________________________________________________________
CURRENT/FUTURE ____________________________________________________
CLOSING THOUGHTS __________________________________________________
KEY REFERENCES ____________________________________________________
12
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ECONOMICS OF IT __________________________________________________ 15
KEY AREA: IT PRODUCTIVITY PARADOX___________________________________
Watershed papers ________________________________________________
Current & Future _________________________________________________
KEY AREA: DIFFERENTIATION OF PRODUCTS AND PRICES ______________________
Watershed papers ________________________________________________
Current & Future _________________________________________________
KEY AREA: STRATEGIC OUTSOURCING ____________________________________
Watershed Papers ________________________________________________
Current & Future _________________________________________________
KEY AREA: SWITCHING COSTS AND LOCK-IN _______________________________
Watershed Paper _________________________________________________
KEY AREA: ECONOMICS OF E-COMMERCE __________________________________
Watershed Paper _________________________________________________
Current & Future _________________________________________________
FUTURE KEY AREA: INFORMATIONAL PROPERTY RIGHTS ______________________
Watershed Papers ________________________________________________
Current & Future _________________________________________________
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HCI / PSYCHOLOGY _________________________________________________ 19
OVERVIEW __________________________________________________________
THEORY ____________________________________________________________
WATERSHED AND CURRENT ____________________________________________
FUTURE ____________________________________________________________
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KM / AI / IR__________________________________________________________ 23
GENERAL INFORMATION ABOUT KM/AI/IR_________________________________ 23
I
CONFERENCES _______________________________________________________
WATERSHED ________________________________________________________
CURRENT ___________________________________________________________
Herbert A. Simon (1916-2001) ______________________________________
Allen Newell (1927-1992) _________________________________________
John McCarty ___________________________________________________
Edward Feigenbaum ______________________________________________
Marvin Minsky __________________________________________________
Dr. Gerard Salton (1927-1995) ______________________________________
PUBLICATIONS/ENCYCLOPEDIAS _________________________________________
FUTURE ____________________________________________________________
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OPERATIONS RESEARCH ____________________________________________ 27
OVERVIEW __________________________________________________________
WATERSHED ________________________________________________________
MAIN THEME ________________________________________________________
FUTURE ____________________________________________________________
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POLICY, ETHICS & SOCIAL ISSUES __________________________________ 29
WATERSHED PAPERS/BOOK _____________________________________________ 30
CURRENT RESEARCH __________________________________________________ 31
FUTURE DIRECTION ___________________________________________________ 33
WORKFLOW ________________________________________________________ 34
WORKFLOW MANAGEMENT DESCRIPTION: _________________________________
WORKFLOW FUTURE RESEARCH DIRECTIONS: ______________________________
Workflow Management Systems Architecture __________________________
Workflow Modeling ______________________________________________
Inter-Organizational Workflows _____________________________________
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APPENDIX __________________________________________________________ 37
ANALYSIS & DESIGN / DATABASE ________________________________________
Peter Pin-Shan Chen ______________________________________________
E.F.Codd _______________________________________________________
Michael Stonebraker ______________________________________________
Kim Won_______________________________________________________
Grady Booch ____________________________________________________
COLLABORATION / COMMUNICATIONS ____________________________________
Dr. Jay F. Nunamaker; University of Arizona __________________________
Dr. Douglas Vogel; City University of Hong Kong ______________________
Dr. Geraldine DeSanctis; Duke University _____________________________
Dr. Starr Roxanne Hiltz; New Jersey Institute of Technology ______________
Dr. Wanda J. Orlikowski; MIT Sloan School of Management______________
Dr. Robert Kraut; Carnegie Mellon University _________________________
Dr. Sarah Kiesler; Carnegie Mellon University _________________________
Dr. Murray Turoff; New Jersey Institute of Technology __________________
Dr. Alain Pinsonneault; McGill University ____________________________
II
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Dr. Brent Gallupe; Queen’s School of Business, Canada __________________
Tim Berners-Lee; previously of CERN _______________________________
ECONOMICS OF IT ____________________________________________________
Lynda M. Applegate, Harvard University _____________________________
Yannis Bakos, New York University _________________________________
Erik Brynjolfsson, MIT ____________________________________________
Eric K. Clemons, University of Pennsylvania __________________________
Thomas W. Malone, MIT __________________________________________
Haim Mendelson, Stanford University ________________________________
Carl Shapiro, University of California at Berkeley ______________________
Hal R. Varian, University of Berkeley ________________________________
Andrew B. Whinston, University of Texas at Austin _____________________
HCI / PSYCHOLOGY ___________________________________________________
Donald Norman __________________________________________________
Ben Shneiderman ________________________________________________
Dr. Jakob Nielsen ________________________________________________
Dr. George Furnas ________________________________________________
Edward Tufte ___________________________________________________
Stuart K. Card ___________________________________________________
Izak Benbasat ___________________________________________________
Daniel P. Siewiorek ______________________________________________
Frank Biocca ____________________________________________________
KM / AI / IR ________________________________________________________
Herbert A. Simon (1916-2001) ______________________________________
Allen Newell (1927-1992) _________________________________________
John McCarty ___________________________________________________
Edward Feigenbaum ______________________________________________
Marvin Minsky__________________________________________________
Dr. Gerard Salton (1927-1995) ______________________________________
OPERATIONS RESEARCH _______________________________________________
Dr. Russell L. Ackoff _____________________________________________
Dr. George Dantzig _______________________________________________
Dr. Ward Whitt __________________________________________________
Dr. Hau Lee _____________________________________________________
Dr. Marshall L. Fisher _____________________________________________
POLICY & SOCIAL ISSUES ______________________________________________
Mary J. Culnan __________________________________________________
Sara Kiesler _____________________________________________________
Robert Kling ____________________________________________________
Lee Sproull _____________________________________________________
Peter G. Neumann ________________________________________________
Seymour E. Goodman _____________________________________________
Eli M. Noam ____________________________________________________
Richard Mason __________________________________________________
Dorothy E. Denning ______________________________________________
Pamela Samuelson _______________________________________________
III
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WORKFLOW _________________________________________________________
Clarence Ellis ___________________________________________________
Professor Sheth __________________________________________________
Dr. Jablonski ____________________________________________________
Dr. Christoph Bussler _____________________________________________
UNIVERSITY OF ARIZONA ______________________________________________
Hsinchun Chen __________________________________________________
Moshe Dror _____________________________________________________
Kurt D. Fenstermacher ____________________________________________
Mark Ginsburg: __________________________________________________
James F. LaSalle _________________________________________________
Therani Madhusudan _____________________________________________
David E. Pingry__________________________________________________
Sudha Ram _____________________________________________________
Olivia Sheng ____________________________________________________
Pamela Slaten ___________________________________________________
Matt Thatcher ___________________________________________________
Sherry Thatcher __________________________________________________
Suzie Weisband__________________________________________________
Daniel Zeng _____________________________________________________
J. Leon Zhao ____________________________________________________
IV
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Table of Figures
Figure 1—Functions…………………………………………………………….….……..4
Figure 2—Model Examples….………………………………………………….….……..5
Table 1----Colors……………………………………………………………..…….……..5
Figure 3— Model Examples…….………………………………………………….……..6
Figure 4— Model Examples……….…………………………………………….………..7
Figure 5— Model Examples……….…………………………………………….………..7
Figure 6— Model Examples…….……………………………………………….………..8
Figure 7—Timeline……………………………………………………………..………..10
Figure 8—Workflow in INSPEC Titles………………………………………..………...34
V
Introduction
In order to provide a comprehensive view of the research field of MIS, we have divided
the field into seven main research categories. The seven categories we chose are as
follows:
1.
2.
3.
4.
5.
6.
7.
8.
Collaboration / Communication
Database / System Analysis
Economics of IT
KM / AI / IR
HCI / Psychology
Operations Research
Policy, Ethics, & Social Issues
Workflow
The main sections of the paper are divided into these seven categories. Within each sub
discipline, we have further divided the research into categories of 1) founding or
watershed papers of events that have defined the sub discipline 2) current research in the
sub discipline and finally 3) the researchers’ views of where the sub discipline is going in
the future. The research papers that we present will be placed within this categorization
scheme.
MIS Defined
MIS is an applied discipline which focuses on how information and information
technology is used by, is managed by and affects organizations. This broad definition
leads to a couple of difficulties in establishing boundaries. One problem involves
relationships to reference disciplines. This definition also does little to clarify the
methodologies used by MIS researchers. Because the pervasive inclusion of computers
in nearly every facet of organizational operations is a relatively new phenomenon, and
because computer technology has affected the operation of organizations so
fundamentally, this problem of scope definition is inevitable, especially for these early
years of the discipline’s development.
MIS overlaps other disciplines on all sides. Since organizations are made up of people
who use information, psychology and education have a stake in our research. Because so
much of what we study and apply is related to computer technology, computer science
issues continually intersect with MIS issues. Because the very nature of information is
cognitive and related to knowledge representation, and because human beings trade
knowledge primarily as language, linguistic research intertwines itself with MIS research
repeatedly. Because nearly every human endeavor is being enhanced (hopefully) by the
interaction of humans and computers, many disciplines are extending their efforts into
areas in the MIS domain. For example, the application of computer technology holds
such promise to increase effectiveness for health practitioners that a new area of study,
1
bio-informatics has sprung up in the medical field. This “discipline” could be considered
a subset of MIS, yet the value of domain knowledge in medicine is so vital to success in
this area that many of those who strive in this area of study are medical-researchers first
and information engineers second. This overlapping does not trouble us. It is simply a
fact, not a reduction in the prestige of the MIS field. Even though others may question
MIS as unique discipline, we are satisfied with MIS as an extremely important and useful
discipline.
The wide reach of MIS study also leads to a wide range of methodologies embraced,
sometimes reluctantly, by the MIS community. Many more traditional fields use specific
methodologies that lend themselves to the nature of the research domain. MIS is going to
have a problem limiting its methodological approaches because it has people,
organizations and computers to deal with and a goal of increasing organizational
effectiveness. People are very different from computers. Computers are precise and
measurable. People are amazingly complex and surprising difficult to predict.
Organizations are formed for so many different purposes that effectiveness can have a
huge range of definitions. For these reasons, MIS researchers will continue to struggle to
achieve empirically provable results whenever possible yet they must branch out into
measures which are less discrete and more subjective if the goals of people and
organizations are to be addressed.
A Model For Classifying MIS Research
Description
The purpose of this model is to help us understand and classify MIS research. We drew
from our own creativity as well as taking elements from MIS Legitimacy and the
Proposition of a New Multi-dimensional Model of MIS by Lowry et al. and Build and
Learn, Evaluate and Learn by Dr. Nunamaker. We chose to model 4 attributes of each
piece of MIS research: function, area of focus, technicality and rigor. We would have
liked to model reference disciplines and methodology, but we decided that those were
less crucial and more difficult to express. We will leave those to some future model.
We have chosen to express the functional attribute with icons and the area of focus by
color. The technicality and rigor dimensions are shown vertically and horizontally.
MIS Research can be described as being either technical or behavioral. Technical
research in MIS attempts to describe how a computer-based system behaves. Examples
of technical research include database design and artificial intelligence algorithms.
Behavioral research in MIS attempts to describe how systems and people interact with
each other. Examples of behavioral research include the Technology Acceptance Model
(TAM) and MIS Policy. We have included the spectrum of technical vs. behavioral as
the vertical axis in our model.
Another axis we use to classify research is rigor vs. descriptive. Rigorous research is
performed using proven methodologies in a controlled environment. Precise statistical
2
1
methods are also employed to ensure accurate hypotheses and conclusions. Rigorous
research is usually performed in the laboratory or other controlled setting. Descriptive
research, on the other hand, usually involves observation and field study. In field studies,
a researcher cannot control all of the variables necessary to make a definitive conclusion;
instead the researcher can make general conclusions about trends.
Previous models, such as the model proposed by Lowry et al, classify research using
Rigor vs. Relevance as a dimension. We decided to use descriptive instead of relevance
for two reasons. First, if we were to use rigor vs. relevance, and we classified a piece of
research as being rigorous, we would be implying that the research is irrelevant. Most
researchers whose research is considered rigorous would probably be offended if their
research was deemed irrelevant. Furthermore, rigorous research need not be irrelevant.
E. F. Codd’s relational model was very mathematically rigorous, yet was relevant enough
to be found in almost every database system used today.
Another research feature we model is the function. Figure 1 shows how we understand
the function icons in our model. We view research as a cyclical process that involves
academia and managed organizations. The target of MIS research is managed
organizations. These organizations, often with the help of academics, apply methods and
techniques in an attempt to accomplish business goals. We place this kind of research in
the domain of managed organizations in the model. We refer to that process as “apply”
and chart this kind or research using a hammer icon. Observation of the organizational
processes leads to new insights into how organizational goals can be better accomplished.
A researcher envisions new ways of looking at issues, methods or techniques. Research
that expresses this kind of contribution is classified with the term “conceptualize”. We
denote conceptualization research with a thought cloud icon. Theories, (formal and
informal) are derived which can lead to new ways of addressing important issues. MIS
theories (as in most all disciplines) can be based on work done in other disciplines. For
example, Kohonen’s Self-Organizing Map was not designed for the visualization of
topics from large bodies of documents. Hypothesizing that its use to cluster documents
would assist in browsing large collections of documents captured a kind of theory which
could be developed and tested. Research which presents this kind of thought is denoted
in our model by a formula (E=MC squared) icon. These theories are developed through
experimentation. Development oriented research shows on our model as a microscope
icon. Of course, many research projects cover one or more area of our functional chart.
Thus, the research space on the model can contain more than one icon.
1
Nunamaker, J. F. (1992). "Build and Learn, Evaluate and Learn." Informatica --- TheJournal of Management Information Systems
Development 1(1): 1--6.
P. B. Lowry, W. H. Anderson, D. C. Wilson, G. Leroy, and L. Lin, ;MIS legitimacy and the proposition of a new, multi-dimensional
model of MIS,; 3rd Annual Conference of the Southern Association for Information Systems, Atlanta, GA, 2000.
3
Needs Identified in
Organizations
ACADEMIA
Conceptualize
Apply
Theorize
Techniques and
Methods
MANAGED
ORGANIZATIONS
Develop
Other Academic Fields
New Technologies
 Figure 1
Dr. Nunamaker’s model as presented in Build and Learn, Evaluate and Learn and shown
in Figure 2 captures several similar ideas to what is in our model. We think that elements
of the “Theory Building” node are similar to notions in our “Theorize” and
“Conceptualize” nodes. His “Observation” node and “Experimentation” nodes have
some comparability to our “develop” notion. Since our model is partially attempting to
describe academic functions apart from organizational functions, we split “apply” apart
as its own functional area. This is somewhat like the Systems Development node in the
Nunamaker model. The pictorial depiction of our model may imply that developed ideas
do not lead to new conceptualizations with out actual implementation in an organizational
setting. But this is not always how it works. In short, our model does not attempt to
replace or improve the other one. It emphasizes the role of academia vs. managed
organizations, it shows some sources of input to the research cycle and it charts the
general flow of the research process.
Another important function in classifying research is to group it together with other
topically-similar research. This can be problematic because much research in MIS is
interrelated. In addition, there are many notions of how to categorize research. We have
chosen to group research by area of focus using a structure with 6 groupings. These
4
 Figure 2
groupings should change with time. The function icon or icons representing a piece of
research are places on a circle in the appropriate place to represent its technical and rigor
characteristics. That circle is color coded to represent the area of focus. Each of the
focus areas are has its own color, as shown in Table 1. Since some research spans topic
areas, the circle can be partitioned into several color segments.
 Table 1
Area of Focus
Economics/Policy
Knowledge Management/AI
HCI
Communication/Collaboration
System Design/Data Base
Operations Management
Workflow
Color
Green
Red
Pink
Orange
Yellow
Blue
Purple
5
A Few Examples
Salton, Wong and Yang’s A Vector Space Model for Automatic Indexing2 paper is quite
technical in that it explores a detailed and complex algorithm which describes a
document based on a set of vectors. It is quite rigorous in that it compares results to
results from previous experiments. The paper proposes a new model for segmenting
documents, this theoretical contribution is marked by a formula icon. It also develops the
model with some experimentation, that function is represented by the microscope. The
circular space is colored red to represent the Knowledge Management/Artificial
Intelligence area of focus.
Technical
Behavioral
Rigorous
Descriptive
 Figure 3
A recent paper by Bruce C. Hartman and Moshe Dror , Cost Allocation in ContinuousReview Inventory Models 3proposes 3 criteria for selection of a cost allocation method in
certain inventory systems. Several methods of allocation are considered and analyzed.
Computational complexity and correctness are considered. This paper is quite technical
and quite rigorous in that allocations are evaluated using mathematical analysis. The
paper suggests theory in that it proposes criteria which have not been used in this context
before. It is in the domain of operations research and so the circle is represented in blue.
2
Salton, Gerald ... et al. A vector space model for automatic indexing. - S. 273-280. - I: Readings in information retrieval / edited by
Karen Sparck Jones and Peter Willett. - San Francisco : Morgan Kaufman, 1997
3
Hartman, Bruce C. and Dror, Moshe 1996. Cost Allocation in Continuous-Review Inventory Models Naval Research Logistics.
Vol. 43. Pp 549-561
6
Technical
Behavioral
Rigorous
Descriptive
 Figure 4
E. F. Codd’s landmark paper A relational model of data for large shared data banks4
proposes the theory now widely used in relational databases could be applied to our
model. His research would appear high on the technical scale and rigorous
(mathematically) on the rigorous vs. descriptive scale. The paper seems to be both
Technical
Behavioral
Rigorous
Descriptive
 Figure 5
conceptualizing and theory building, and, since it is the foundation for relational
databases fits very well in the system design/database category.
DeSanctis and Gallupe laid the foundation of collaboration with their paper titled A
Foundation for the Study of Group Decision Support Systems.5 The paper is very
4
5
Codd, E. F. 1970. A relational model of data for large shared data banks. Communications of the ACM. 13, 6.
DeSanctis, G.; Gallupe, B. – Management Science Vol. 33 No. 5 1987. Pp.589-609.
7
theoretically rigorous and describes the behavior of people using group decision support
systems.
Technical
Behavioral
Rigorous
Descriptive
 Figure 6
MIS Timeline
The following timeline shows some of the important events that have occurred in the last
60 years. These events have made MIS the field it is today.
8
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MIS Timeline
 Figure 7
Collaboration / Communication
Collaboration is the process of individuals working together. Collaborative technologies
and Computer Mediated Communications facilitate this process by providing avenues of
communication between individuals while recognizing the interaction dynamics of the
process. Collaboration can be organized on two primary planes – formal collaboration
and informal collaboration. Formal collaboration occurs within a structured setting with
the objective of problem solving. The process is well defined, in many aspects
formalized and coordinated. Informal collaboration is an ad hoc process often occurring
within an unstructured social environment.
Group Support Systems (GSS) are the backbone of formal collaborative methodologies.
GSS supports the planning, brainstorming, negotiating, problem solving and creative
tasks of a group through the utilization of a multitude of technologies. Some common
characteristics of GSS are: diminished communication barriers between group members,
9
structured group activities, the support of varied intellectual capabilities within the group
and a strong emphasis on the social dynamics of the collaborative process.
A result of the broad reach of GSS, research in this area extends into the social and
technological interaction of the system and the user. GSS research typically encompasses
the relationship among the following components: task, group dynamics, technological
capabilities, decision outcomes and process outcomes.
A Foundation for the Study of Group Decision Support Systems6, authored by Drs.
DeSanctis and Gallupe, establishes taxonomy, incorporating a contingency perspective,
for formal collaboration, specifically GSS. This contingency perspective builds a
research framework based on the GSS design level. Three specific levels are identified:
1) technical GSS – focused on the removal of communication barriers, 2) automated
GDSS – focused on removing uncertainty or noise within the decision making process
and 3) machine induced GDSS – focused on machine created expert advice. Once the
GSS design has been established, the contingency perspective expands the decision
making process to consider support needs of the group depending on group size and
proximity. Finally, Drs. DeSanctis and Gallupe consider the role of task within the group
dynamic.
Dr. Nunamaker, et al, provides the foundation of the formal collaborative methodology in
two groundbreaking research papers: Information Technology to Support Electronic
Meetings 7 and Electronic Meeting Systems to Support Group Work. 8 Dr. Nunamaker, et
al outlined the structure and design of Electronic Meeting Systems – the precursor of
Group Support Systems (GSS). The interplay of technology, the group dynamic and the
environment where technology and people interact is recognized as a cohesive unit
generating its own dynamic. The basis of these interactions is the focus of continued
research in collaboration. Dr. Nunamaker, et al provides research conclusions on varying
GSS structural designs: Local Area Decision Nets and Decision rooms; and the
effectiveness of these designs in comparison to each other, in comparison to noncomputer aided decision rooms and in comparison to differing design configurations.
Finally, Dr. Nunamaker, et al address the group decision making process itself and the
effect Electronic Meeting Systems have on the process: from technology specific setups
to human interaction.
Informal collaborative methodologies are funneled through the World Wide Web.
Although Mr. Tim Berners-Lee is credited with creating the World Wide Web, the
informal collaborative environment is a component of e-mail, ftp, chat-rooms and web
surfing; individual components of the web and the users ability to accept the technology
for the purposes of group interaction. Dr. Fred Davis developed the Technology
Acceptance Model (TAM)9 in his pioneering paper Perceived Usefulness, Perceived Ease
of Use, and User Acceptance of Information Technology, correlating the users initial
exposure to the technology to the transitional integration of the technology. This paper
DeSanctis, G.; Gallupe, B. – Management Science Vol. 33 No. 5 1987. Pp.589-609.
Dennis, A.; George, J; Jessup, L.; Nunamaker, J.; Vogel, D. - MIS Quarterly Vol. 12 No. 4 1988. Pp.591-624.
8
Nunamaker, J.; Dennis, A.; Valacich, J.; Vogel, D.; George, J. - Communications of the ACM Vol. 34 No. 7 1991 pp.40-62.
9
Davis, F. MIS Quarterly Vol. 13 No. 3 1989. Pp.319-340.
6
7
10
establishes how people accept technology and perceive its usefulness – something so
evident with the explosion of the Internet and the World Wide Web.
Having a foundation from which to build, research strengthened the usefulness of
collaborative technologies and further defined the dynamics of computer-mediated
communications. Drs. Pinsonneault and Kraemer have shown that collaborative
technologies, specifically GSS, increases consensus reaching, task orientated
communication, confidence on decision by group, satisfaction with decision process, and
satisfaction with decision and decreases decision time in their paper The Effects of
Electronic Meetings on Group Processes and Outcomes: an Assessment of the Empirical
Research10. Furthermore, Drs. Hiltz and Turnoff showed how computer mediated
communication allows for the group to gain a greater comprehension of the problem (task
definition) and the determination of a range of solutions in their paper Computer Support
for Group versus Individual Decisions.11
Additional studies have been the evaluation of earlier theories through experiments and
observation. Consequently the Technology Transition Model (TTM) has been proposed
in a paper, A Technology Transition Model Derived from Field Investigation of GSS Use
Aboard the U.S.S. Coronado12, by Dr. Briggs, et al. Here, TTM extends TAM by
establishing a theoretical algorithm explaining the user’s self-sustaining acceptance and
level of acceptance regarding the technology. Pertinent considering technologies
influence on current social culture. Moreover, Drs. Galegher and Kraut, Computer
Mediated Communication for Intellectual Teamwork: An Experiment in Group Writing13,
further establish the validity of the contingency theory through experiments on sixtyseven three-person writing groups. These experiments, however, do highlight the limited
predictability of the theory when multiple outcomes and their temporal patterns are
considered.
Initial research established a strong foundation for collaborative technologies and
computer mediated communications. Further research verified the significance of the
technology with the interaction of the users. However, collaborative technologies and
computer-mediated communications are still in their infancy. As these components
extend into the new millennium, new areas of research must be examined – particularly
the GSS and World Wide Web interaction with other MIS areas such as HCI, virtual
environments, knowledge communities and process reengineering.
As Dr. Briggs, et al point out in 1001 Unanswered Research Questions in GSS14, GSS is
branching into various new areas: e-commerce, modeling & simulation, software
architecture, crisis response, virtual workspaces, team interface design and the classroom.
With these extensions, further broadened analysis of the collaboration and computer
mediated framework is needed – analysis of organizational implications, goal
10
Pinsonneault, A; Kraemer, K. European Journal of Operational Research Vol. 46 1990 pp.143-161
Turoff, M.; Hiltz R IEEE Transactions on Communications Vol. Com-30 No. 1 Jan. 82 pp.82-91.
12
Briggs, R.; Adkins, M.; Mittleman, D.; Kruse, J.; Miller, S.; and Nunmaker, J. Journal of Management Information Systems, 1999
Vol. 15, No.3, pp. 151-195
13
Galegher, J; Kraut, R. – Information Systems Research Vol. 5 No. 2 1994. Pp.110-138.
14
Briggs, R.; Nunamaker, J.; Sprague, R. Journal of Management Information Systems. Vol. 14 No. 3 1998. Pp.3-21.
11
11
congruence, process gains & losses, team telework ideologies, cross-cultural issues,
process reengineering, leadership structure issues and the ethics of GSS. Still in its
infancy, – like MIS overall, GSS has just begun to show its potential and GSS research
has just begun to identify and explain its impact.
Finally, Using Technology and Constituting Structures: A Practice Lens for Studying
Technology in Organizations15, authored by Dr. Orlikowski, addresses the issue of
technology-in-practice. Technologies-in-practice are not fixed but comprised of the
practices of workers employing technologies to adhere to their particular circumstances.
Using technologies in this manner results in the emergence, improvisation, and change of
work patterns as people reconfigure their technologies-in-practice to meets their
individual needs or change their habits of use. This, in turn, alters the technology-inpractice. The papers proposes to augment the existing structural perspective of
technology with a practice of orientation focused specifically on people’s recurring use of
technology and how that use alters the technology structure.
Database / Systems Analysis
Database systems have a long history in the realm of MIS. Some may consider databases
and database systems to be a core element in MIS. The database industry generated
approximately $7 billion dollars in revenue in 1994 and is estimated to be growing at the
rate of 35% every year16. In the 1960’s companies began automating their office
bookkeeping by using programming languages like COBOL. COBOL and its recordoriented file model were the primary tools during this time period.
The emergence of the “relational” data model in the 1970’s proved to be a major advance
over COBOL and the record-oriented file model. The relational model unified data and
meta-data and it also spawned a non-procedural data access language. Research later into
the 1970’s lead to the development of the Structured Query Language (SQL) and by the
1990’s almost all relational database systems were standardized on SQL. Research in the
latter half of the 1980’s lead to the development of geographically distributed databases
and parallel data access17.
Watershed
A Relational Model of Data for Large Shared Data Banks18 authored by E.F. Codd in
1970 provided a pivotal moment in database history. Codd’s model was based on two
important points:
15
Orlikowski, W. Using Technology and Constituting Structures: A Practice Lens for Studying Technology in Organizations.
Organization Science. Vol. 11 No. 4 2000. Pp.404-428
16
Gray, Dr. James N., http://www.cs.washington.edu/homes/lazowska/cra/database.html
17
Gray, Dr. James N., http://www.cs.washington.edu/homes/lazowska/cra/database.html
18
E.F. Codd. A Relational Model of Data for Large Shared Data Banks. Communications of the ACM, 13(6):377--387, 1970.
12
It provides a means of describing data with its natural structure only--that is,
without superimposing any additional structure for machine representation
purposes. Accordingly, it provides a basis for a high level data language, which
will yield maximal independence between programs on the one hand and machine
representation on the other.19
At first the model was perceived as too simple and not robust enough to provide adequate
performance. IBM Research decided to take a chance and developed System R based on
Codd’s model. System R eventually evolved in DB2, which is a current DBMS system
used in industry. SQL emerged from Codd’s model and System R.
Peter Pin-Shan Chen’s The Entity-Relationship model---toward a unified view of data.
ACM Transactions on Database provided another important moment in database system
history. The ER model was used to establish a variety of different design methods and
case tools. The ER model also helped establish structured system and database analysis.
Current
Inspired by Codd’s work, several faculty members at UC Berkley began working on a
project called INGRES. In The design and implementation of INGRES Michael
Stonebraker et al. describe the development of a relational database system based on
Codd’s work. The Ingres project was the foundation for the Ingres product which is now
owned by Computer Associates. In the mid-1980’s the Ingres project started research on
a new project called Postgres. Postgres expanded on Ingres by including effective
execution on multiprocessors. Postgres has also become the basis of digital libraries and
scientific database works within the University of California system.
Current/Future
Database systems continue to be key component of computer science and information
systems today. The future issues of database systems include representing knowledge
within a computer. Also, there is also significant interest in indexing data, adding
inference to data search, compiling queries more efficiently, executing queries in parallel,
integrating data from heterogeneous data sources, and analyzing performance. Another
key area is combining object-oriented concepts with the relational model. Kim Won’s
Integrating an object-oriented programming system with a database system. The paper
discusses issues related to integrating a database system with an object oriented
programming language. The two key issues are:
1. An object-oriented programming language must be augmented with semantic data
modeling concepts to provide a robust set of data modeling concepts to allow
modeling of entities for important real-world applications.
19
http://www.nap.edu/readingroom/books/far/ch6.html
13
2. The computational-model issue: application programmers should be able to
access and manipulate objects as though the objects are in an infinite virtual
memory; in other words, they should not have to be aware of the existence of a
database system in their computations with the data structures the programming
language allows.20
Finally, software architecture, engineering, and design could have significant influence
on the future of database systems and MIS. Grady Booch, who is internationally
renowned for his work in software architecture. In his article Developing the Future he
discusses the importance of software development and its relationship to automating
business process, its power for connecting people, and its impact on current and future
business. Also, in his earlier work Object-Oriented Development, Grady Booch
introduces the object-oriented paradigm and systems and application development.
Closing Thoughts
1. Why did we put database together with software system? (The relationship between
database and software system in general):
Database technology and software engineering are related in many ways. First, software
engineering methods and tools have to be used for the construction of software providing
database functionality and for the development of database applications. Second,
database technology can be used to support activities; tools and techniques involved in
software development processes.
2. Current:
Different types of software systems can provide database functionality. Database
management systems (DBMS) are general-purpose software systems specifically
designed to manage large quantities of data in a consistent manner.
While in the past database systems have been large, monolithic software systems, a
research trend has emerged in recent years towards their componentization. This trend is
necessary in order to efficiently provide database functionality within today’s distributed
object and component architectures.
For example, implementations are reaching the limitations of file-based storage and
experiencing the shortcomings of contemporary mainstream database technology.
Various special-purpose systems have been developed to satisfy requirements that were
not covered. For instance, object-relational DBs are designed to better support objectoriented data modeling.
Some other special-purpose software database:
20
ACM SIGPLAN Notices , Conference proceedings on Object-oriented programming systems, languages and applications
January 1988 Volume 23 Issue 11
14
Adele-DB is a structurally object-oriented object management system.( Barkhatir, N.,
Estublier, J., and Melo, W. Adele-Tempo: an environment to support process modeling
and enaction (1994)
GRAS is a graph-based active database management system. (Kiesel,N., Schurr, A., and
Westfechtel, B. Gras: A graph-oriented software Engineering Database system.(1996))
3. Future:
The future and the trend directions included:
Querying heterogeneous data sources;
Support for flexible cooperation schemes and creative work;
Unbundling and re-bundling database components;
(Klaus Dittrich, Dimitrios Tombros & Andreas Geppert: Databases in software
engineering (2000))
Key References
Michael Stonebraker
Stonebraker, M. Operating System Support for Database Management. Commun. ACM 24, (July
1981), pp. 412-418.
E.F. Codd
E.F. Codd. A Relational Model of Data for Large Shared Data Banks. Communications
of the ACM, 13(6):377-387, 1970.
Peter Pin-Shan Chen
Peter Pin-Shan Chen. The Entity-Relationship Model: Toward a unified view of data.
TODS, 1(1):9--36, 1976.
Michael Stonebraker
Michael Stonebraker. The design and implementation of INGRES. ACM, 1(3):189-122,
1976
Kim Won
Kim Won, Integrating an object-oriented programming system with a database system,
ACM Conference Proceedings, 142-152, 1988
Grady Booch
Developing the future, Communications of the ACM, Volume 44, Number 3, March
2001
OBJECT-ORIENTED DEVELOPMENT, IEEE Transactions On Software
Engineering,12 (2): 211-221 Feb 1986
Economics of IT
Under the heading “Economics of Information Technology”, we subsumed research that
takes a perspective on the effects and efficiency of IT from a perspective grounded in
15
economic theory. By this, we don’t mean that the work is necessarily “only” an
application of economic theory to a new field, but can as well be an extension of existing
theory or a new theoretical approach grounded in the economic theory tradition.
As economics is a very wide field, there are also several categories in the area of
economics of IT, and there will probably even more in the future, since the field is
relatively new. In the following, we present several key areas that either have been, are or
are believed to be in the future a major area of research in this field. Under each area, we
give cite the watershed paper(s), key researchers as well as the predicted future
importance and direction of the area.
To write this section we relied on the information of MIS faculty members as well as
published articles. A good overview over current issues is given in the following working
paper: Varian, Hal, R. (2001). Economics of Information Technology. Working Paper:
University of California, Berkeley, revised: Nov 18, 2001.
Key Area: IT Productivity Paradox
The information technology (IT) productivity paradox consists in empirical findings that
suggest that although IT use is increasing, contrary to expectations, productivity is not.
Or as major researchers in the area put it: “The ‘productivity paradox’ of information
systems (IS) is that, despite enormous improvements in the underlying technology, the
benefits of IS spending have not been found in aggregate output statistics.” (Brynjolfsson,
E., & Hitt, L., 1996). Also, the question arises, if it is true that IT doesn’t increase
productivity, why do we see an increase in IT use?
Watershed papers
Brynjolfsson, E. (1993). “The Productivity Paradox of Information Technology.”
Communications of the ACM 35(12): 66-77.
Brynjolfsson, E., & Hitt, L. (1996). Paradox lost? Firm-level evidence on the returns to
information systems spending. Management Science, 42(4), 541-558.
Current & Future
Future importance is considered high. Theory is still evolving and new empirical
evidence is collected. According to one source there is a shift taking place towards a
broadening of the theoretical perspective from an investigation of the relation between IT
use and economic productivity towards the relation between IT and firm-specific profits,
firm productivity, market value, among others.
Key Area: Differentiation of Products and Prices
“Information technology allows for fine-grained observation and analysis of consumer
behavior. This allows for various kinds of marketing strategies that were previously
extremely difficult to carry out, at least on a large scale. For example, a seller can offer
prices and goods that are differentiated by individual behavior and/or characteristics.”
16
(Varian, 2001). Sub areas include for example different forms of price discrimination,
bundling of information goods and versioning.
Watershed papers
Bakos, Y., & Brynjolfsson, E. (1999). “Bundling information goods: Prices, profits, and
efficiency.” Management Science, 45(12).
Shapiro, C., & Varian, H. R. (1998). Versioning: The smart way to sell information.
Harvard Business Review, November-December.
Current & Future
Future importance is considered high. As information gathered on consumers continues
to increase, finer forms of price and product discrimination become possible. Theoretical
research will have to investigate the effects on firm, consumer and social welfare of these
developments.
Key Area: Strategic Outsourcing
The underlying question here is about the optimal boundaries of an organization. What
part of the production process should be internalized and what should be externalized?
And if production is outsourced, what are less and more effective ways to do so?
Watershed Papers
Malone, T. W., Yates, J. and Benjamin, R. I. "Electronic Markets and Electronic
Hierarchies: Effects of Information Technology on Market Structure and Corporate
Strategies." Communications of the ACM, Vol. 30, No. 6, 1987, pp. 484-497.
Clemons, E.K., Reddy, S.P., Row, M.C. (1993). The impact of information technology in
the organization of economic activity: The ‘move to the middle’ hypothesis. Journal of
Management Information Systems, 10(2): 9-35.
Current & Future
Future importance is considered relatively low. The area is not as popular as it was in the
late 80s among researchers.
Key Area: Switching Costs and Lock-In
Switching costs are endemic in high-technology industries and can be so large that
switching suppliers is virtually unthinkable, a situation known as ``lock-in.'' For example,
one study found that the total cost of installing an Enterprise Resource Planning (ERP)
system such as SAP was eleven times greater than the purchase price of the software due
to the cost of infrastructure upgrades, consultants, retraining programs, and the like.
(Varian, 2001).
17
Watershed Paper
Farrell, J., & Shapiro, C. (1988). Dynamic competition with switching costs. Rand
Journal of Economics, 19: 123-137.
Key Area: Economics of E-commerce
One gets a good idea of the importance of electronic commerce from the following
citation: “We are on the brink of changes that are projected to rival in impact the
Industrial Revolution of the 18th and 19th Centuries. Much more than making entirely
new knowledge-based products possible, it is clear that electronic commerce will lead to
a fundamental redefinition of the way business is conducted. All participants in the
business community need to wake up to, understand and adapt to electronic commerce.
They need to redefine their business philosophies and approaches so as to position their
organizations to rise with the tide.” (Applegate et al. 1996).
Watershed Paper
Applegate, L. M., Holsapple, C. W., Kalakota, R., Radermacher, F. J., and Whinston, A.
B. (1996). Electronic commerce: building blocks of new business opportunity. Journal of
Organizational Computing and Electronic Commerce, 6(1), 1-10.
Current & Future
Future importance is considered as very high, as the introductory quotation makes clear.
Future Key Area: Informational Property Rights
Watershed Papers
No watershed paper could be found. For a recent review, see David, P. Economic forces
in the coevolution of information technology and intellectual property institutions.
Technical report, Stanford University, 2001.
Current & Future
A very popular a highly regarded current book on the topic is The Future of Ideas: The
Fate of the Commons in a Connected World by Lawrence Lessig. It has been named one
of Amazon.com’s Best of 2001. Their review describes it in the following way: If The
Future of Ideas is bleak, we have nobody to blame but ourselves. Author Lawrence
Lessig, a Stanford law professor and keen observer of emerging technologies, makes a
strong case that large corporations are staging an innovation-stifling power grab while we
watch idly. The changes in copyright and other forms of intellectual property protection
demanded by the media and software industries have the potential to choke off publicly
held material, which Lessig sees as a kind of intellectual commons. He eloquently and
persuasively decries this lopsided control of ideas and suggests practical solutions that
consider the rights of both creators and consumers, while acknowledging the serious
impact of new technologies on old ways of doing business. His proposals would let
existing companies make money without using the tremendous advantages of
18
incumbency to eliminate new killer apps before they can threaten the status quo. Readers
who want a fair intellectual marketplace would do well to absorb the lessons in The
Future of Ideas. (Rob Lightner)
The future importance is considered high. See, for example the ongoing competition
between Microsoft’s operating system and the open Linux system, and the surrounding
theoretical debate.
HCI / Psychology
Overview
Human Computer Interaction (HCI) research is concerned with the design, evaluation and
implementation of interactive computer systems for human use. Furthermore, HCI
studies the interactivity between the computer system and the user. Consequently, HCI
draws supporting knowledge from the computer science discipline and the social
sciences. Within the computer sciences realm, techniques in computer graphics,
operating systems, programming languages, and development environments are relevant
to HCI. Furthermore, Communication Theory, graphic and industrial design disciplines,
linguistics, social sciences, cognitive psychology, and human performance are relevant to
the study of HCI. Finally, engineering and design methods play a substantial role in HCI
research.
Over the last 15-20 years, HCI has emerged as a focus research area with
specialist organizations:
The ACM Special Interest Group on Computer Human Interaction
The British Computer Society Specialist Group on HCI
The IFIP Technical Committee (TC 13) on Human-Computer Interaction
The Human Factors Society Computer Systems Technical Group
The European Association for Cognitive Ergonomics
specialist journals:
Human-Computer Interaction
International Journal of Man-Machine Studies
Behavior and Information Technology
International Journal of Human-Computer Interaction
Interacting with Computers
specialist conferences:
ACM CHI Human Factors in Computing Systems Conference
ACM User Interface Software Technology Conference
BCS HCI SG Human-Computer Interaction Conference
European Conference on Cognitive Ergonomics
IFIP INTERACT Human Factors in Computing Conference
International Conference on Human-Computer Interaction
19
Theory
Activity Theory provides a broad conceptual framework for describing the structure,
development, and context of computer-supported activities. Developed by the Russian
psychologists Vygotsky, Rubinshtein, Leont'ev and others in the 1920s, there is a thriving
Activity Theory tradition within HCI studies. Activity Theory is a set of basic principles
that constitute a general conceptual system, rather than a highly predictive theory. The
basic principles of Activity Theory include the hierarchical structure of activity, objectorientedness, internalization/externalization, and tool mediation and development.
Other related theory and model include: Computational Theory of Working Memory,
Interactivity Model, The Postrepresentational Model (HCS), Artificial Morality, SIDE
Theory
Watershed and Current
As human computer interaction is a field which the application can provide more strong
support to evaluate the research result. Here are many books which is very important to
popularize the concept and application of HCI as well as research paper. As HCI just has
a history no more than 20 years, we can’t identify watershed here, so to be consistant
with other part, we find the most important paper recommended by the expert in this field
and list them as watershed and current.
Card, Stuart K, Thomas P Moran, and Allen Newell, “The psychology of humancomputer interaction,” Hillsdale, N.J., L. Erlbaum Associates, 1983
This book contains much essential material that is unknown to many practitioners in the
field. Designing human-computer interfaces is still an art, learned best by creating many
interfaces and carefully observing how real users interact with them. However, there are
many tools from cognitive psychology that, if understood and applied, can yeild at least
two benefits. First, by learning what is known about how humans operate, you can avoid
many pitfalls in design. Second, you can make quantitative design decisions. This book
can never go out of date as long as humans use keyboards and mice with their hands and
scan the screen with their eyes.
Norman, D. A., & Draper, S. (Eds.), (1986). User Centered System Design: New
Perspectives on Human-Computer Interaction. Hillsdale, NJ: Lawrence Erlbaum
This is an early set of readings that defined the idea of designing systems for users first.
Associates
Ben Shneiderman. Designing the User Interface: Strategies for Effective HumanComputer Interaction. Addison Wesley, 1986. Published 1987;
Based on 20 years experience, Shneiderman offers practical techniques and guidelines for
interface design. He discusses underlying issues and supports conclusions with empirical
results. This new edition features new chapters on the WWW, information visualization,
and computer-supported cooperative work; expanded coverage of evaluation techniques
and user-interface-building tools; and a discussion of speech input-output, natural-
20
language interaction, anthropomorphic design, virtual environments, and agents. An
associated booksite on the Web additional illustrations and links to useful resources.)
Furnas, G. W. Generalized fisheye views, In Proceedings of CHI '86: ACM Conference
on Human Factors in Software, pages 16-23. Association for Computing Machinery.
In many contexts, humans often represent their own "neighborhood" in great detail, yet
only major landmarks further away. This suggests that such views ("fisheye views")
might be useful for the computer display of large information structures like programs,
data bases, online text, etc. This paper explores fisheye views presenting, in turn,
naturalistic studies, a general formalism, a specific instantiation, a resulting computer
program, example displays and an evaluation.
Norman, D. A. (1988). The Psychology of Everyday Things. New York: Basic Books.
(Reissued in 1989 as The Design of Everyday Things. New York: Doubleday.)
Donald Norman was, when he wrote this book, a professor of cognitive science at UC
San Diego, and The Psychology of Everyday Things nicely does three things at once:
introduce the new knowledge gained by his discipline, document our inability to make
good gadgets, and show how the first can help fix the second.
Frank Biocca, Mark Levy, Communication in the Age of Virtual Reality , Hillsdale, NJ:
Erlbaum, 1995
The book was selected as a Choice Outstanding Academic Book for 1995. It was the first
volume to explore the communication applications and implications of virtual reality.
Stuart K. Card, Jock D. Mackinlay, and Ben Shneiderman, Readings in Information
Visualization: Using Vision to Think, 1999, Morgan Kaufmann Publishers
This groundbreaking book defines the emerging field of information visualization and
offers the first-ever collection of 47 classic papers of the discipline, with introductions
and analytical discussions of each topic and paper. The authors' intention is to present
papers that focus on the use of visualization to discover relationships, using interactive
graphics to amplify thought. This book is intended for research professionals in academia
and industry; new graduate students and professors who want to begin work in this
burgeoning field; professionals involved in financial data analysis, statistics, and
information design; scientific data managers; and professionals involved in medical,
bioinformatics, and other areas.
Future
HCI is, however, fundamentally different simply because of the key role of the human in
the area, a factor that makes predictability and characterization so challenging. Good HCI
research requires understanding how people work just as much, if not more, than how
computers work.
Most important issue in future HCI research will be how to assist people to accessing,
managing, and understanding the vast amount of data and information that is available to
them. The Internet, the Web, and computers in general have helped to facilitate an
information explosion that threatens to inundate us all.
21
Three areas of research will drive future HCI work:
Better interface navigation -- Although GUI and WIMP interfaces are a big step past
line-oriented terminals, they still have a learning curve and they can be awkward to use.
HCI research must develop improved interfaces that are more natural to use and more
simple to learn than current interfaces. Interfaces using voice input (speech recognition)
harbor great potential here. Voice input technology, both hardware and software, is
improving.
Visualization tools for understanding -- Vast amounts of useful information are
becoming available and accessible through electronic means. Providing people with a
way to digest all this information and extract the relevant parts for their individual
objectives is a key challenge facing HCI researchers. Sophisticated information
visualization tools present complex or large quantities of data to people in
comprehensible, accessible ways.
A number of examples of this type of work exist: Ben Shneiderman's information
visualization tools, the SAGE project at CMU, recent work from Xerox PARC, and
hopefully John T. Stasko’s work on software visualization systems, just to name a few. A
dramatic step forward will be frameworks that allow people to easily construct their own
visualizations for information sources unique to a domain of interest to them.
Agents or automated task managers -- This category simply refers to computational
tools that aid people in time-consuming, relatively uninteresting, but important tasks.
Consider the following example. For example, Learner-centered System Design.
Researchers from Vision Technology Group at Microsoft Research recommend
Perceptual user interfaces(PUI) as a fundamental change for HCI from the interaction by
typing, pointing, clicking. PUI is expected to require integration at multiple levels of
technologies such as speech and sound recognition and generation, computer vision,
graphical animation and visualization, language understanding, couch-base sensing and
feedback(haptics), learning, user modeling, and dialogue management.
Reference:
John T. Stasko, Future Research Directions in Human-Computer Interaction, ACM
Computing Surveys 28A(4), December 1996
Mark Guzdial, John B. Carrol, Beneiderman, etc, DIS 95 Ann Arbor MI, ACM 1995,
Learner-centered System Design: HCI Perspective for the future
Matthew Turk, George Robertson, Perceptual user interfaces, communications of the
ACM, march 2000, vol. 43, No.3.
22
KM / AI / IR
General Information about KM/AI/IR
Knowledge management is an audit of "intellectual assets" that highlights unique sources,
critical functions and potential bottlenecks which hinder knowledge flows to the point of
use. It protects intellectual assets from decay, seeks opportunities to enhance decisions,
services and products through adding intelligence, increasing value and providing
flexibility [1].
AI is about natural information processing systems as well as artificial systems, and not
just about how they perceive learn and think, but also about what they want and how they
feel. It has already had a profound impact on the study of human minds.[2]
One of the big questions in science is "What is intelligence?" Artificial intelligence
researchers study intelligence--in machines and, through computers, in people. Much of
the general information listed in this section is concerned with the nature of this science
and the question of whether computers can think.
The applications of AI include: game playing, speech recognition, understanding natural
language, computer vision, expert systems, heuristic classification. [3]
Conferences

AAAI: National Conference of the American Association of Artificial Intelligence
(AAAI). First held at Stanford in 1980.
Watershed







1956. John McCarthy coined the term "artificial intelligence" as the topic of the
Dartmouth Conference, the first conference devoted to the subject [4].
1957. The General Problem Solver (GPS) demonstrated by Newell, Shaw & Simon.
1958. John McCarthy (MIT) invented the Lisp language.
1967. Dendral program (Edward Feigenbaum, Joshua Lederberg, Bruce Buchanan,
Georgia Sutherland at Stanford) demonstrated to interpret mass spectra on organic
chemical compounds. First successful knowledge-based program for scientific
reasoning.
1975. Marvin Minsky published his widely-read and influential article on Frames as a
representation of knowledge, in which many ideas about schemas and semantic links
are brought together.
1978. Herb Simon wins the Nobel Prize in Economics for his theory of bounded
rationality, one of the cornerstones of AI known as "satisficing".
1997. The Deep Blue chess program beats the current world chess champion, Garry
Kasparov, in a widely followed match.
23
Current
Herbert A. Simon (1916-2001)
Richard King Mellon University Professor, Computer Science Department, Psychology
Department, Carnegie-Mellon University. Ph.D.: University of Chicago.
Simon has backed up much of his work with numerous studies on decision-making in
business enterprise. Of notable importance was his 1949 article unveiling the "HawkinsSimon" conditions for non- negative square matrices. Since the 1950s, Simon has focused
much of his attention on the issue of decision-making - and has come up with a
behavioral theory based on "bounded rationality".
Allen Newell (1927-1992)
U.A. and Helen Whitaker University Professor of Computer Science at Carnegie Mellon
University. Ph.D.: Industrial Administration, Carnegie Institute of Technology.
With Herbert Simon, he proposed the Physical Symbol System hypothesis in 1957. His
work has centered on SOAR, an architecture for intelligent problem solving and learning.
He is the winner of 1978 Nobel Laureate in Economics for his pioneering research into
the decision-making process within economic organizations.
John McCarty
John McCarthy. Computer Science Department, Stanford University. One of the founders
of the field of AI. Ph.D. Princeton, 1951.
A pioneer in artificial intelligence, McCarthy invented LISP, the preeminent AI
programming language, and first proposed general-purpose time sharing of computers.
He identifies common-sense rules that determine the consequences of events and codifies
these rules, along with other information, as sentences in the symbolic languages of AI
databases.
Edward Feigenbaum
Edward Feigenbaum. Kumagai, Professor of Computer Science, Stanford University.
Ph.D.: Carnegie-Mellon (1960).
Feigenbaum is currently serving as Chief Scientist of the Air Force. Feigenbaum is
studying the structure, dynamics, and the technology and industry trends in the software
segement of the computer industry, as part of the Stanford computer Industry Project. He
continues his long-term research in the representation of knowledge for use by programs
that reason, and his work on advanced applications of expert systems.
24
Marvin Minsky
Toshiba Professor of Media Arts and Sciences, Professor of E.E. and C.S., M.I.T. Ph.D.:
Princeton Univ.
His research has contributed to advances in artificial intelligence, cognitive psychology,
neural networks (he built the first neural-network simulator in 1951), and the theory of
Turing machines. A pioneer in robotics, he built some of the first mechanical hands with
tactile sensors, visual scanners, and accompanying software and computer interfaces. He
influenced many robotic projects outside MIT and has worked to build into machines the
human capacity for commonsense reasoning. In his The Society of Mind (1987), 270
interconnected one-page ideas reflect the structure of his theory. He has participated in
many studies of advanced technologies for space exploration. He received the Turing
Award in 1969.
Dr. Gerard Salton (1927-1995)
Professor PhD Harvard University, 1958
Salton developed SMART (System for the Mechanical Analysis and Retrieval of Text).
From his evaluations/tests of SMART, he formulated general rules for automatic
language processing (Bellardo & Bourne). According to Bellardo and Bourne, Salton's
retrieval experiments of the 1980's "greatly contributed to the knowledge base of
computerized information indexing, storage and retrieval." He advocated system design
at the 1965 ADI conference. See obituary notice in JASIS, February 1996.
There are other researchers involved in Artificial Intelligence, Knowledge Management
and Information Retrieval area. These people includes Jaime Carbonell (CMU), Raj
Reddy(CMU), Roger C. Schank (Northwestern University), Gary Marchionini (UNCCH) and so forth.
Publications/Encyclopedias
Feigenbaum, Edward, and Julian Feldman. 1995. Computers and Thought.
Cambridge, MA: The MIT Press. (Originally published in 1963 by McGraw Hill.) A
collection of early articles., including many "classics." The general public may be
particularly interested in the section introductions , the introductory article by Turing, and
the summary articles by Minsky and Armer. Articles by Newell and Simon provide an
early articulation of the information processing model of intelligent behavior.
Simon, Herbert. 1996. Sciences of the Artificial. 3rd edition. Cambridge, MA: MIT
Press. A classic book, originally published in 1969, that examines several presuppositions
of AI. Updates throughout the book take into account advances in cognitive science and
the science of design.
Computer Machinery and Intelligence, A. M. Turing
This paper address the question of “Can machine think?” Turing takes a behavioristic
posture relative to the question. The question is to be decided by an unprejudiced
25
comparison of the alleged “thinking behavior” of the machine with normal “think
behavior” of human beings. hw propose an experiment-commonly called “Turing test”-in
which the unprejudiced comparison could be made. Though the test has flaws, it is the
best that has been proposed to date.
Herbert A. Simon. Understanding The Natural and the Artificial Worlds,. The Science
of Artificial Intelligence, 1996, pp 1-24.
Understanding the natural and the artificial worlds, the psychology of thinking:
embedding artifice in nature, The science of design: creating the artificial, The
architecture of complexity. "Artificial" denotes systems that have a given form and
behavior because they adapt to their environment in reference to goals or purposes.
Barr, Avron, Paul R. Cohen, and Edward A. Feigenbaum, editors. 1989. The Handbook
of Artificial Intelligence. IV, Reading, MA: Addison-Wesley Publishing Co., Inc. Other
volumes published separately. (A. Barr and E.A. Feigenbaum, editors, Vol. I, Stanford
and Los Altos, CA.: HeurisTech Press and William Kaufmann, 1981; Vol. II, Barr and
Feigenbaum, 1982; Vol. III, Cohen and Feigenbaum, 1982.)
Gabbay, D. M., C. J. Hogger, and J. A. Robinson, editors. 1993. Handbook of Logic in
Artificial Intelligence and Logic Programming. 5 vols. Volume Oxford: Clarendon Press.
Shapiro, Stuart C., editor. 1992. Encyclopedia of Artificial Intelligence. 2nd ed. New
York: John Wiley & Sons. (1st edition, 1987.) Several hundred entries define and explain
key terms in AI. Many entries are quite technical.
Future
Next ten years, I think the real focus of most AI you'll see is on the Internet, speech
recognition, language translation, better search, and much more. There's also some work
in robotics that you'll be seeing in your kid's toys.
--Dr. James Hendler[4]
As companies continue to initiate new knowledge management projects, new knowledge
manager jobs continue to be advertised, and virtually every major software vendor
(including IBM and Microsoft) continues to offer and advertise knowledge management
technologies. Knowledge management is headed toward becoming a permanent fixture in
the business landscape.
-- Tom Davenport[5]
References:
[1]: "An Open Discussion of Knowledge Management", Brian (Bo) Newman, 1991.
[2]:“What is Artificial Intelligence? ”By Aaron Sloman. Computer Science Department,
University of Birmingham, UK.
[2]: American Association for Artificial Intelligence, www.aaai.org
[3]: “Brief History of Artificial Intelligence,” Bruce G. Buchanan, University of
Pittsburgh
26
[4]: AI's Greatest Trends and Controversies. IEEE Intelligent Systems (January/February
2000)
[5]: Nov.1,1999, Issue of CIO Magazine
Operations Research
Overview
Operations Research (OR) is the science of helping people and organizations make better
decisions. One of the definitions is to provide executive departments with a quantitative
basis for decisions regarding operations under their control. Specifically, it is the
development and application of mathematical models, statistical analysis, simulations,
analytical reasoning and common sense to the understanding and improvement of realworld operations [Giancatarino]. Improvements are usually measured by the cost
reduction, increase of efficiency, or any other measures of optimization on effectiveness.
OR originated during World War II as a solution to tactical problems related to the
optimal operations of military forces. By 1942, it had become common in the British
military to deploy teams of mathematicians, physicists, and officers to test equipment and
study the effectiveness of weapons and radar under operating conditions. Operations
research activities were brought to the U.S. in 1942 to the Naval Ordinance Laboratory.
In 1948, Massachusetts Institute of Technology offered studies in Operations Research,
but it was not until 1950 that industry in the U.S. began to use the techniques. Then, OR
developed along with the growth of computers as a business planning and management
tool [Wayne]. As it evolved, the core of OR moved away from interdisciplinary teams to
a focus on the development of mathematical models used to model, improve, and
optimize real-world systems [Wayne]. Mathematical models in OR include mathematical
programming, network flows like queueing theory, simulation and decision trees.
Basically, OR topics can be divided into two big categories: deterministic topic and
stochastic topic. Deterministic topics include integer programming, linear programming,
nonlinear programming, data envelopment analysis, facility layout and location, graph
theory, inventory control, Just-in-time, production scheduling, MRP, network analysis,
vehicle routing, etc. Stochastic topics include decision trees, forecasting, Markov
processes, quality control, simulation, and stochastic programming.
Major journals for OR are listed below:
Operations Research
Management Science
European Journal of Operational Research
Journal of the Operational Research Society
Mathematical Programming
Networks
Naval Research Logistics
Interfaces
27
Watershed
Dr. Russell Ackoff is a former President of the Operations Research Society of America.
He clarifies the differences between conventional thinking and systems thinking, with
which he gave great impact on the direction where OR developed. In two of his papers
[Ackoff, 1979], Dr. Ackoff argued a comprehensive reconsideration of the OR field, the
methodology, they way it is practiced and the nature of OR education. Ackoff discussed
the increasing inappropriateness of OR's methodology, arguing for decision-making
systems that could learn and adept effectively rather than optimize. These highly detailed
articles have come to be regarded as classic papers which reinforced OR's move from the
hard to the soft approach.
Dr. George Dantzig is a professor in Stanford University. His main contribution to
Operations Research is the introduction of Linear Programming, a simplex method of
optimization invented in 1947. He was awarded Von Neumann Theory Prize in
Operational Research in 1975. Linear programming and its offspring, such as nonlinear
programming and integer programming, have come of age and have demonstrably passed
the test. They are fundamentally affecting the economic practice of organizations and
management. Eugene Lawler from Berkeley commented that, linear programming is used
to allocate resources, plan production, schedule workers, plan investment portfolios and
formulate marketing (and military) strategies. The versatility and economic impact of
linear programming in today’s industrial world is awesome.
Main Theme
Stochastic topic:
Dr. Ward Whitt has been contributing in applied probability, queueing theory,
performance analysis, and stochastic models of telecommunication systems. He has
published over 200 articles in top scientific journals. During the course of his illustrious
career, he has served on the Editorial Boards of such journals as Operations Research,
Management Science, Mathematics of Operations Research, Journal of Applied
Probability, Queueing Systems, not to mention various others. He was also elected to the
National Academy of Engineering in 1996.
Along with Donald Iglehart, Dr. Whitt published a sequence of three pioneering papers in
1970, 1974, and 1980 on the analysis of queuing systems through asymptotic
approximations. Much of the most outstanding research in stochastic OR of the past 25
years was built on the foundation established by Whitt’s groundbreaking work.
Deterministic topic:
Dr. Hau Lee is widely recognized as a leading authority on supply chain integration and
coordination, and has been widely published and quoted on the subject of supply chain
improvements. Currently a professor at Stanford University, Dr. Lee has consulted on
supply chain management and global logistics strategy for companies in the computer,
pharmaceutical, automobile, telecommunications, grocery, and semiconductor industries.
His consulting projects include strategic analysis of worldwide logistic systems,
28
development of inventory control systems for filed service supports, integrated control of
manufacturing and distribution, global manufacturing strategy, and integration of the
product design process with on-line quality control and servicing [Integral].
Dr. Marshall Fisher developed systems for agile supply chains linked to customer
demand that have significantly reduced costs of overproduction and underproduction in
apparel and other industries. One of those is the Accurate Response, an integrated
framework linking operational changes and planning approaches to improve a firm’s
ability to match supply with the demand for new products. Accurate Response was
initially implemented at Sport Obermeyer, a leading fashion skiwear firm that credits the
approach with doubling profits and significantly improving customer service [Integral].
Future
Arthur M. Geoffrion and Ramayya Krishnan, "Introduction: Operations Research in the
e-Business Era," Interfaces, Vol. 30, No. 2
F.J. Rademacher, “Challenges for Operations Research as a Scientific Discipline at the
Beginning of the 21st Century”, International Conference on Operations Research
and annual meeting of GOR, 31 August - 3 September 1998
Reference
Mike Giancatarino, Operations Analysis, http://web.nps.navy.mil/~ofcinst/code360.htm
Industrial and Manufacturing Department, Wayne State University, Operations Research
http://mie.eng.wayne.edu/faculty/chelst/informs/introduction/or.htm
Academic Affiliates, Integral, http://www.integral-inc.com/affiliates/lee_bio.html
Policy, Ethics & Social Issues
As computers and the Internet become more pervasive in society, so does the related
social and policy research. As the development of Internet policy is still in its infancy,
policy, ethics, and social research take on a greater sense of relevance, especially
considering the fast moving Internet adoption. Policy and social issues of MIS are
somewhat diverse. Research can vary from having a behavioral focus, such as in “Social
Psychological-Aspects of Computer-Mediated Communication” [Kiesler, et al] to a very
technical focus as in Cryptography and Data Security [Denning]. The backgrounds of
policy researchers also vary greatly. Dr. Pamela Samuelson has a law degree from
Cornell and Peter Neumann has a background in mathematics. The unifying thread in
policy and social research are the issues. The following issues are salient in MIS social
& policy research today:
1. Privacy and Information Security Issues
1. Encryption and Cryptography
29
2.
3.
4.
5.
6.
E-Government, e-voting, and teledemocracy
Intellectual property and patents
Free Speech vs. regulating Internet content
Social and Psychological issues of computer-mediated communication
The Digital Divide
Watershed Papers/Book
There are not really any two or three papers that have defined the policy and social
research as they relate to MIS. Each policy or social issue involves its own set of
considerations and research approaches. However, there are some papers that standout
by how many times they have been cited. These papers largely are from the early to mid
1980s as the MIS discipline was being formed. For lack of a better guide, we use the
number of times a paper has been cited to define our watershed papers.
Watershed Papers
1. Kiesler, Sara Siegel J, McGuire TW. “Social Psychological Aspects of Computer
Mediated Communication” American Psychologist 39 (10): 1123-1134 1984
(cited 271 times on Web of Science)
2. Kiesler, Sara & Sproull, Lee. “Reducing Social-Context Cues-Electronic Mail in
Organizational Communication” Management Science 32 (11): 492-1512 NOV
1986 (cited 225 times on Web of Science)
Studies electronic mail in an organizational setting. Using ideas about how social
context cues within a communication setting affect information exchange, the
paper argues that electronic mail does not simply speed up the exchange of
information but leads to the exchange of new information as well. The authors
explored effects of electronic communication related to self-absorption, status
equalization, and uninhibited behaviour. Consistent with experimental studies, it
was found that decreasing social context cues has a deregulating effects on
communication, and that more information was share via the electronic medium
than would have been in a face to face conversation.
3. Kling, Robert. “Social Analyses of Computing-Theoretical Perspectives in recent
Empirical Research” 1980 Computing Surveys (cited 179 times on Web of
Science)
Kling examines the use of computers in organizations and public life. “The roles
of computer technologies in the workplace, in decision making, in altering power
relationships, and in influencing personal privacy are examined.” (INSPEC) Kling
also studies the social accountability of systems.. The studies make use of
assumptions about the world in which the computers operate. Two main
perspectives are contrasted. “Systems rationalism, a collection of approaches
including management science, managerial rationalism, and the systems
approach, is found to be most helpful in stable settings, when there is considerable
30
consensus over important social values. Segmented-institutionalist analyses,
which assume social conflict rather than consensus, are particularly powerful as
the social world of computing use becomes more dynamic and as a wider variety
of groups is involved.” (INSPEC)
4. Denning, Dorothy. Cryptography and Data Security. 1982 Addison-Wesley (cited
170 times on Web of Science)
Summary:
One of the first books on the topic of cryptography in the field, it is heavily cited.
The book deals with cryptography from an algorithms approach. Data security is
also covered, especially for secure operating systems. Reviews on Amazon list
the book as essential introduction into cryptopgraphy.
Current Research
Because there is so much breadth to the research area of policy and social issues, listing
only a few papers is hard to do and still show research on the salient issues. We have
included well-cited papers from long-standing researchers in the policy and social issues
field. The papers represent discussion on issues including ethics, women in technology,
global adoption of the Internet, information privacy, cryptography, fair use of copyrights,
and social perspective of technology.
1. Mason, Richard. “4 Ethical Issues of The Information Age” MIS Quarterly 10 (1):
5-12 MAR 1986 (Web of Science 21)
Summary:
The nature of information itself has inherent ethical issues. These issues are
especially relevant considering growth in the use of information today. Four
ethical issues are summarized using the acronym PAPA, standing for privacy,
accuracy, property, and accessibility. Privacy deals with what information must
be revealed about oneself or others and the circumstances in which the
information is revealed. Accuracy deals with who is accountable for maintaining
accurate information. Property addresses the issue of information ownership and
accessibility who should have access to information.
2. Sproull, Lee. “Pool Halls, Chips, War Games Women in the Culture of
Computing” Psychology of Women Quarterly. 1986 (Web of Science 39)
3. Goodman SE, Press LI, Ruth SR, Rutkowski AM The Global Diffusion of the
Internet – Patterns and Problems Communications of the ACM 37 (8): 27-31 AUG
1994 (Web of Science 14)
Summary:
31
The Internet has been growing at an incredible pace. Internet use, however, is
varied greatly between countries and even within countries. Academic campuses
in the United States, where the Internet is free, have some professors that do not
use it at all. Four models are presented to explain Internet diffusion. The
categories are 1) Building National Backbones 2) International and Regional
Initiatives 3) Grass Root Nets and 4) Commercial Carriers and Resellers.
Impediments to network diffusion are placed in three categories. The
impediments include 1) government policies 2) technical impediments; and 3)
local and cultural factors.
4. Noam, Eli. “Electronics and The Dim Future of the University” Science (234):
247-249 OCT 13 1995 (Web of Science 30)
Summary:
The advances in computer networks have created the potential for great progress
in our improved ability to communicate with researchers around the world.
However, as new “communications technologies are likely to strengthen research,
they will also weaken the traditional major institutions of learning, the
universities.” Scholarly activity is made up of three primary activities, which
include 1) the creation of knowledge and its evaluation 2) the preservation of
information and 3) the sharing of this information to others. Noam’s argument is
not that technology would provide better education, but that it would provide
more affordable education by more efficiently fulfilling the three main scholarly
activities.
5. Culnan, Mary. “The Dimensions of Accessibility to Online Information –
Implications for Implementing Office Information Systems” ACM Transactions
On Office Information Systems 2 (2): 141-150 1984 (Web of Science 43)
Presents studies that suggest that “(1) physical access to a terminal and access to
the actual information system are independent dimensions; (2) that accessibility is
a multidimensional concept encompassing physical access to a terminal and the
system, the command language and the ability to retrieve the desired information
successfully; and (3) that perceptions of accessibility are a function of prior user
experience with online systems. In order to facilitate the acceptance of office
information systems, organizations need to provide extensive support and training
when the system is introduced, as well as ready physical access to the system over
the course of its useful life.” (INSPEC)
6. Landau S, Kent S, Brooks C, Charney S, Denning D, Diffie W, Lauck A, Miller
D, Neumann P, Sobel D “Crypto Policy Perspectives” Communications of the
ACM 37 (8): 115-121 AUG 1994 (Web of Science 4)
The following abstract comes from INSPEC, “Discusses the Escrowed Encryption
Initiative announced by the White House on April 16, (1993). The initiative
included a chip for encryption (Clipper), to be incorporated into
32
telecommunications equipment, and a scheme under which secret encryption keys
are escrowed with the government; keys will be available to law enforcement
officers with legal authorization. The National Security Agency designed the
system and the underlying cryptographic algorithm SKIPJACK, which is
classified.”
7. Samuelson, Pamela. “Copyright’s Fair use Doctrine and Digital Data”
Communications of the ACM 1994 (Web of Science 17)
Summary:
Applies copyright’s fair use doctrine to digital media such as electronic messages or
newsletters and digital images or sounds. There are four factors that are considered
when determining whether a copyright infringement has taken place, “1) the purpose
of the defendant’s use … 2) the nature of the copyrighted work … 3) the substantiality
of the taking … and 4) the harm or potential for harm to the market for the
copyrighted work arising from the defendant’s activities”. Precedents such as Sony’s
creation of beta max recorders have set a precedent for copyright legal hearings. Also,
publishing a work without notice of a copyright does not place the work in the public
domain.
8. Kling, Robert, Sacchi W “The Web of Computing: Computing Technology as
Social Organization” Advances in Computers 21: 1-90 1982 (Web of Science 54)
9. Sproull, Lee & Kiesler, Sara. “Managerial Response to Changing Environments:
Perspectives on Problem Sensing From Social Cognition” Administrative Science
Quarterly 27 (4): 548-570 1982 (Web of Science 209)
Future Direction
The future certainly does not lack for policy and social issues to research. In fact
information-related policy and social research will only grow as technology becomes
more pervasive in our society. The following papers address future policy concerns.
1. Rezmierski, Virginia, Pinkerton, Tad, Stager, Susan. “’Heads Up’ For
Information Technology Policies: Emerging Policy Issues for Universities and K12”, ACM Special Interest Group on University and College Computing Services
pg 21-24 1994
Future policies must clarify copyright issues, examine the monitoring and
surveillance of electronic mail, and establish rights and responsibilities.
2. Grönlund, Åke “Democracy in an IT-Framed Society” Communications of the
ACM Vol. 44, No. 1 (January 2001), Pages 22-26
33
“We predict many important changes in the functioning of the democratic systems
due to the ongoing transformation of processes into the framework of the
electronic medium.”
3. Armstrong, B. “The social impact of a national information superhighway”
Computers & Society. Vol.25, no.3; Sept. 1995; p.10-14.
In this article, Armstrong makes an assessment of future social impact of broadband
communication. Social problems considered include allowing equal access to rich and
poor people, the linking of geographically separated people and organizations, and the
issues of privacy and censorship. While these issues have existed since the inception
of the World Wide Web, the growing adoption of the Internet makes them relevant.
Workflow
The Number of Papers with "Workflow" in Title
(Data Source: INSPEC )
250
225
200
185
184
Paper Number
157
145
150
118
100
78
47
50
33
20
14
4
4
0
19701980
19801990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
Time Period
Figure 8
Figure 8 shows how Workflow researched has emerged in the 1990s. Workflow
management is defined by the Workflow Management Coalition (WfMC) as follows:
34
The automation of a business process, in whole or in part, during which documents,
information, or tasks are passed from one participant to another for action, according to
a set of procedural rules.
(The WfMC, which was founded in August 1993 and currently has 200 members, is an
international coalition of workflow vendors, users, and industry groups. The coalition's
goal is to promote the use of workflow and establish workflow management standards by
establishing common terminology, reference models, and interoperability between
workflow management products.)
Workflow Management Description:
Workflow management deals with the specification and execution of business processes.
Business process reengineering is often used synonymously to the specification of
workflows. Workflow management systems execute business processes.
General workflow specifications include the actions to be performed, statements on
control and data flow among these actions, agents allowed to execute actions, and
policies that describe the organizational environment. New formal languages are required
to capture all facets of business processes. Graphical user interfaces may alleviate the
specification work.
Workflow Future Research Directions:
Workflow Management Systems Architecture
1. How can WfMS be designed to serve as a component in a distributed system?
2. Is workflow management an essential part of every distributed system, i.e. should
it be in its "kernel"?
3. Which parts of current WfMS can be stripped because they re-implement
common distributed system functionality ?
4. What makes WfMS "special" by the fact that humans are among the performers of
a workflow?
Workflow Modeling
1.
2.
3.
4.
5.
How to provide different views of workflow models for different users?
How to effectively describe exception behavior of processes?
How can the modeling effort be reduced by using workflow patterns?
Can workflow models be deduced from given process execution information?
How to validate workflow models?
Inter-Organizational Workflows
1. How to describe work-to-do in a way that is understood by parties, service
providers and requesters? Does this entail modifications of the existing process
definition languages?
35
2. How to find appropriate performers / prospective service customers?
3. How to manage that all necessary data is moved across to the service provider or
made available on request by the service requester?
4. How to monitor across the organizational boundary?
5. How to manage internal changes in one organization without impacting on the
other?
6. How to manage internal changes in one organization that impact on the
relationships to the others?
36
Appendix
Analysis & Design / Database
Peter Pin-Shan Chen
Dr. Peter Chen's original paper on the Entity-Relationship model (ER model) is one of
the most cited papers in the computer software field. Dr. Peter Chen is also the Editor-inChief of Data & Knowledge Engineering, the Associate Editor for the Journal of
Intelligent Robotic Systems and other journals. In the past, he was the Associate Editor
for IEEE Computer, Information Sciences and other journals. He is a member of the
Airlie Software Council. He received the Data Resource Management Technology Award
from the Data Administration Management Association (NYC) in 1990. Dr. Chen is a
Fellow of the IEEE, the ACM, and the AAAS. Since 1994, Dr. Chen started to teach
graduate seminars focusing on Internet/Web, Java, XML, and E-commerce (B2B and
B2C). He is also doing research in Information warfare, Information Assurance, Internet
security, and Forensics Informatics. Dr. Chen was the recipient of Year 2000 Individual
Achievement Award from DAMA International, an international professional
organization of data management professionals, managers, and Chief Information
Officers (CIO's). He was also inducted into the Data Management Hall of Fame in 2000.
He is the recipient of Stevens Award in Software Method Innovation in 2001.
E.F.Codd
From 1970s to 1980s, as an Oxford trained mathematician, Ted Codd first joined IBM in
1949. The first ideas on using a ‘Relational’ model of data were developed by Dr. Codd,
while working for the IBM Research Laboratory in San Jose, California. He published
the seminal work on relational database systems in an article entitled ‘A Relational
Model of Data for Large Shared Data Banks’ in the Communications of the ACM
(Volume 13 / Number 6 / June 1970). The article provides a mathematical underpinning
37
for relational systems based on set theory. His original work and theories included the
fundamental concepts of all future RDMS systems including Relational Integrity,
Functional Dependency, and Normalization.
He developed the first relational language called ALPHA, which formed the basis for the
subsequent development of SQL (originally SEQUEL) based on the relational calculus
that Dr. Codd had developed. Other relational query languages, such as QBE, were based
on the relational algebra that Dr. Codd defined.
In 1985, He Redefined the world of transaction processing by writing his "12 Laws" of
relational database management. In 1993, He Redefined the world of decision support
systems by publishing his "12 Laws" for Online Analytical Processing and coining the
term "Online Analytical Processing (OLAP)".
Michael Stonebraker
Dr. Stonebraker is Professor of Electrical Engineering and Computer Sciences at the
University of California at Berkeley, where he joined the faculty in 1971. He is widely
recognized as one of the world's foremost experts in database technology and is noted for
his insight in operating systems and expert systems.
He received a Bachelor of Science degree from Princeton University and Master of
Science and Doctor of Philosophy degrees from the University of Michigan. Dr.
Stonebraker has held visiting professorships at the Pontifico Universitade Catholique
(PUC), Rio de Janeiro, Brazil; the University of California, Santa Cruz; and the
University of Grenoble, France.
Dr. Stonebraker founded Ingres Corp. in 1980 and served on the company's board of
directors until 1993. (Ingres Corp. was purchased by Computer Associates in 1994.)
INGRES, the company's primary product, was a commercialization of Dr. Stonebraker's
INGRES research project into relational database management systems (RDBMS) at
Berkeley. Ingres Corp. has been widely recognized as a leader in RDBMS technology.
More recently, Dr. Stonebraker has managed another research project known as
POSTGRES, one of the most advanced such projects ever undertaken on the Berkeley
campus. In August 1992, Dr. Stonebraker co-founded Illustra Information Technologies,
Inc. in order to commercialize his research in object-relational database technology. He is
a member of the company's board of directors and serves as its Chief Technology Officer.
38
Dr. Stonebraker is currently focusing on DBMS support for visualization environments
and on next-generation distributed DBMSs. In addition, he leads a project, which is
developing alternative data management strategies for NASA's Earth Observing System
(EOS).
Kim Won
Dr. Won got his Ph.D form Dept. of Computer Science of University of Illinois; Master
degree on Dept. of Physics in MIT and B.S. on Physics of MIT.
Currently he is the president and CEO of Cyber Database Solutions, Inc.
Dr. Kim’s research interests lie in object-oriented databases and modern database
systems. He is a founder of UniSQL and recently published a white paper describing a
framework with which to evaluate the completeness of a product's compliance with seven
major categories of capabilities of object relational databases.
Grady Booch
Contact Information:
Rational Software Corporation
18880 Homestead Rd
Cupertino, CA 95014
Grady Booch received his BS in Engineering in United States Air Force Academy in
1977 and MS of EE in University of California, Santa Barbara in 1979.
Grady Booch is one of the leading software development methodologists in the world.
Along with Rational colleagues Ivar Jacobson and Jim Rumbaugh, Grady developed the
Unified Modeling Language (UML), the industry-standard language for specifying,
visualizing, constructing, and documenting the artifacts of software systems. The UML
was officially adopted as a standard by the Object Management Group (OMG) in 1997.
His work centers primarily around complex software systems. Booch is the author of four
books, including "Object-Oriented Analysis and Design," and "Object Solutions:
Managing the Object-Oriented Project." He is a member of AAAS, IEEE, and CPSR, and
is both an ACM Fellow and Rational Fellow. Currently he is the chief scientist at
Rational Software.
39
Collaboration / Communications
Dr. Jay F. Nunamaker; University of Arizona
Dr. Jay F. Nunamaker is Regents Professor and Director of the Center for Management of
Information at the University of Arizona. In 1996, Dr. Nunamaker received the DPMA
EDSIG Distinguished IS Educator Award. Dr. Nunamaker received his Ph.D. in systems
engineering and operations research from Case Institute of Technology, a M.S. and B.S.
from the University of Pittsburgh, and a B.S. from Carnegie Mellon University.
RESEARCH: Current research centers on computer supported collaboration and
decision support that is directed toward improving productivity through the use of
information technology. This approach to computer supported collaboration supports a
new way of enabling individuals to work together, to communicate, share information,
collaborate on writing, generate ideas, organize ideas, draft policies, share visions, build
consensus and make decisions at anytime and any-place.
Key Publications
 Electronic Meeting Systems to Support Group Work. Communications of the
ACM Vol. 34 No. 7 1991 pp.40-62.
 Information Technology to Support Electronic Meetings. MIS Quarterly Vol. 12
 No. 4 1988. Pp.591-624.
 1001 Unanswered Research Questions in GSS. Journal of Management
Information Systems. Vol. 14 No. 3 1998. Pp.3-21
Dr. Douglas Vogel; City University of Hong Kong
Dr. Douglas Vogel is a professor at City University of Hong Kong. Dr. Vogel earned his
Ph.D. in Business Administration/MIS from the University of Minnesota and a M.S. in
Computer Science from U.C.L.A.
RESEARCH: Dr. Vogel’s current research interests include group support systems,
business process improvement, executive support systems, technology support for
learning environments, e-Commerce and virtual organizations. His research continues to
build on the established platform of software development and empirical evaluation while
extending out with an increasingly international emphasis. Specific research projects
40
include: process re-engineering through enterprise analysis for government, military, and
industry groups; design and development of multi-media distributed support for groups;
and research on effective facilitation and session leadership as a function of group, task,
and technology characteristics crossing face-to-face and distributed group support.
Dr. Geraldine DeSanctis; Duke University
Dr. Gerry DeSanctis is Professor of Management in the Fuqua School. In 1998, Dr.
DeSanctis received the NationsBank Award, which is an annual award given to a Fuqua
faculty member for outstanding contributions to teaching, research, and service. Dr.
DeSanctis received her Ph. D. in 1982 from Texas Tech University, College of Business
Administration, Lubbock, Texas, M.A. from Fairleigh Dickinson University and B.A.
from Villanova University.
RESEARCH: Her research focuses on the impacts of electronic communication systems
and groupware on global teams and organizations. She has a particular interest in virtual
organizations and recently published a Special Issue in the Journal of ComputerMediated Communication on the topic of virtual teams and organizations. Her recent
book, Shaping Organization Form: Communication, Connection, and Community
(Newbury Park, CA: Sage), with co-author Janet Fulk of the University of Southern
California, concerns the design and impacts of electronic communication systems within
the dynamics of corporate life.
Key Publications
A Foundation for the Study of Group Decision Support Systems. Management Science
Vol. 33 No. 5 1987 pp.589-609.
Dr. Starr Roxanne Hiltz; New Jersey Institute of Technology
Dr. Starr Roxanne Hiltz is a professor at New Jersey Institute of Technology. Dr. Hiltz
was named one of “New Jersey’s Women of the Millennium” by the Easter Seals
41
Foundation for “creating solutions and changing lives, in the field of educational
Technology.” Dr. Hiltz earned a Ph. D. and M.A. in Sociology from Columbia U.
RESEARCH: Current research interests include WebCenter for learning networks
effectiveness research, studies of distributed multimedia support for Group Collaboration
via the Web, virtual classroom to virtual university and coordination in distributed group
support systems.
Key Publications
 Computer Support for Group versus Individual Decisions. IEEE Transactions on
Communications Vol. Com-30 No. 1 Jan. 82 pp.82-91.
 An assessment of Group Support Systems Experimental Research: Methodology
and Results. Journal of Management Information Systems, Vol. 15 No. 3, 1999 7150
Dr. Wanda J. Orlikowski; MIT Sloan School of Management
Dr. Wanda Orlikowski is an Associate Professor of Information Technologies and
Organization Studies at MIT Sloan School of Management. She currently holds the
Eaton-Peabody Chair of Communication Sciences at MIT. She received a Ph.D. from the
Stern School of Business at New York University.
RESEARCH: Her primary research interests focus on the recursive interaction of
organizations and information technology, with particular emphasis on structures,
cultures, work practices, and change. She is currently exploring the organizational and
technological aspects of working virtually.
Key Publications
 Genres of Organizational Communication – A Structural Approach to Studying
Communication and Media. Academy of Management Review. Vol. 17 No. 2
1992 Pp. 299-326
 Using Technology and Constituting Structures: A Practice Lens for Studying
Technology in Organizations. Organization Science. Vol. 11 No. 4 2000.
Pp.404-428.
42
Dr. Robert Kraut; Carnegie Mellon University
Dr. Robert Kraut is the Herbert A. Simon Professor of Human Computer Interaction at
Carnegie Mellon University, with joint appointments in the Human Computer Interaction
Institute and the Graduate School of Industrial Administration.
RESEARCH: His current research interests include examining the challenges that
groups face in performing intellectual tasks, designs new technology to meet some of
these challenges and evaluates the usefulness of the new technology. Further research
interests include examining the impact of the Internet on the average US family and
understanding the role that nationwide computer networks have on the interrelationships
among firms.
Key Publications
 Computer-Mediated Communication for Intellectual Teamwork: an Experiment in
Group Writing. Information Systems Research Vol.5 No. 2 Jun. 94 pp.110-137.
Dr. Sarah Kiesler; Carnegie Mellon University
Dr. Sarah Kiesler is currently a professor at Carnegie Mellon University’s Computer
Human Interaction Institute. She earned her PhD in Psychology from Ohio State
University, MA in Psychology from Stamford and BS in Social Sciences from Simmons
College.
RESEARCH: Social and behavioral aspects of computers and computer-based
communication technologies. Specific projects include: Robotic Assistants for the
Elderly, Multidisciplinary Collaboration (w/Dr. Weisband) and HomeNet.
43
Dr. Murray Turoff; New Jersey Institute of Technology
Dr. Murray Turoff is a professor at New Jersey Institute of Technology. Dr. Turoff
introduced the concept of Computerized Conferencing and is responsible for the
implementation, utilization and early evaluation work on this information and
communication system. Dr. Turoff earned his Ph.D. in Physics from Brandies University
and B.A. from the University of California at Berkeley.
RESEARCH: Current research interests include the development of CMC systems with
the Danish Institute of Technology, development of a CMC network for computer
integrated manufacturing education, development and evaluation of CMC systems and
design of a Collaborative System for the Standard Setting Process.
Key Publications
 Computer Support for Group versus Individual Decisions. IEEE Transactions on
Communications Vol. Com-30 No. 1 Jan. 82 pp.82-91.
Dr. Alain Pinsonneault; McGill University
Dr. Pinsonneault is the Imasco Professor of Information Systems in the Faculty of
Management at McGill University. In 1997, he was awarded the CDROM-SNI Award for
the best pedagogical material that used information technology at HEC. Dr. Pinsonneault
earned his Ph.D from University of California, Irvine.
RESEARCH: His current research interests include the organizational and individual
impacts of information technology, electronic commerce, the strategic alignment of
information technology, group support systems and IT department management.
44
Dr. Brent Gallupe; Queen’s School of Business, Canada
Dr. Brent Gallupe is the founding Director of Canada's first electronic group-decision
support laboratory at the Queen's Executive Decision Center. Dr. Brent Gallupe earned a
Ph.D. in Business Administration at the University of Minnesota and an MBA at York
University.
Tim Berners-Lee; previously of CERN
Mr. Tim Berners-Lee is currently working at the Laboratory for Computer Science (LCS)
at the Massachusetts Institute of Technology (MIT). In 1999, he became the first holder
of the 3Com Founders chair. He is Director of the World Wide Web Consortium, which
coordinates Web development worldwide, with teams at MIT, at INRIA in France, and at
Keio University in Japan. Mr. Berners-Lee earned his undergraduate degree from the
Queen’s College at Oxford University.
Economics of IT
Lynda M. Applegate, Harvard University
Linda Applegate is at the Graduate School of Business Administration, Harvard
University.
Research
Her research focuses on the influence of information technology on markets and
organizations. Her findings on the evolution of electronic commerce and on the role of
information technology as an enabler of flexible and adaptive organizational designs and
innovative management control systems have been widely published.
Key Publications
Applegate, L. M., Holsapple, C. W., Kalakota, R., Radermacher, F. J., and Whinston, A.
B. (1996). Electronic commerce: building blocks of new business opportunity. Journal of
Organizational Computing and Electronic Commerce, 6(1), 1-10.
45
Yannis Bakos, New York University
Yannis Bakos is Associate Professor of Management at the Leonard N.
Stern School of Business at New York University. He holds a Ph.D. from
the Sloan School of Management at the Massachusetts Institute of
Technology. He also received a Masters in Management (Finance) from the
MIT Sloan School, and a B.S. in Computer Engineering and a Masters in
Electrical Engineering and Computer Science from MIT.
Research
He conducts research on the business impacts of information technology, and the Internet
in particular. Professor Bakos pioneered research on the impact of information
technology on markets, and in particular on how internet-based electronic marketplaces
will affect pricing and competition. He is also currently studying pricing strategies for
information goods.
Key Publications
Bakos, Y., & Brynjolfsson, E. (1999). “Bundling information goods: Prices, profits, and
efficiency.” Management Science, 45(12).
Erik Brynjolfsson, MIT
Erik Brynjolfsson is the George and Sandi Schussel Professor of
Management, MIT Sloan School of Management, the Co-director of the
Center for eBusiness@MIT, and the Co-editor of the Ecommerce
Research Forum.
Research
His research focuses on how businesses can effectively use information technology (IT)
in general and the Internet in particular.
Key Publications
Brynjolfsson, E. (1993). “The Productivity Paradox of Information Technology.”
Communications of the ACM 35(12): 66-77.
Brynjolfsson, E., & Hitt, L. (1996). Paradox lost? Firm-level evidence on the returns to
information systems spending. Management Science, 42(4), 541-558.
Bakos, Y., & Brynjolfsson, E. (1999). “Bundling information goods: Prices, profits, and
efficiency.” Management Science, 45(12).
46
Eric K. Clemons, University of Pennsylvania
Eric K. Clemons is Professor of Operations and Information Management
and Management, Wharton School, University of Pennsylvania. He
received his PhD and MS from Cornell University in 1976 (1974), and his
SB from the Massachusetts Institute of Technology in 1970.
Research
Information technology and business strategy; information technology and financial
markets; making the decision to invest in strategic information technology ventures;
managing the risk of strategic information technology implementations; strategic
implications of electronic commerce for channel power and profitability
Key Publications
Clemons, E.K., Reddy, S.P., Row, M.C. (1993). The impact of information technology in
the organization of economic activity: The ‘move to the middle’ hypothesis. Journal of
Management Information Systems, 10(2): 9-35.
Thomas W. Malone, MIT
Thomas W. Malone is the Patrick J. McGovern Professor of Information
Systems at the MIT Sloan School of Management. His background
includes a Ph.D. from Stanford University and degrees in applied
mathematics, engineering, and psychology. He is also the founder and
director of the MIT Center for Coordination Science and was one of two
founding co-directors of the MIT Initiative on "Inventing the
Organizations of the 21st Century".
Research
Professor Malone's research focuses on how new organizations can be designed to take
advantage of the possibilities provided by information technology.
Key Publications
Malone, T. W., Yates, J. and Benjamin, R. I. "Electronic Markets and Electronic
Hierarchies: Effects of Information Technology on Market Structure and Corporate
Strategies." Communications of the ACM, Vol. 30, No. 6, 1987, pp. 484-497.
Haim Mendelson, Stanford University
Haim Mendelson is Codirector, Center for electronic business and
commerce, Stanford University.
47
Research
IT and Time-Based Competition in Financial Markets, Information and Organization for
Horizontal Multi-market Coordination, A New Approach to the Regulation of Trading
Across Securities Markets, Information and Organization for Horizontal Multi-market
Coordination, among others.
Carl Shapiro, University of California at Berkeley
Carl Shapiro is the Transamerica Professor of Business Strategy at the Haas
School of Business at the University of California at Berkeley. He also is
Director of the Institute of Business and Economic Research, and Professor
of Economics in the Economics Department, at UC Berkeley. He earned his
Ph.D. in Economics at M.I.T. in 1981, taught at Princeton University during
the 1980s, and has been at Berkeley since 1990. He has been Editor of the
Journal of Economic Perspectives and a Fellow at the Center for Advanced
Study in the Behavioral Sciences, among other honors.
Research
Professor Shapiro has published extensively in the areas of industrial organization,
competition policy, the economics of innovation, and competitive strategy. His current
research interests include antitrust economics, intellectual property and licensing, product
standards and compatibility, and the economics of networks and interconnection.
Key Publications
Shapiro, C., & Varian, H. R. (1998). Versioning: The smart way to sell information.
Harvard Business Review, November-December.
Farrell, J., & Shapiro, C. (1988). Dynamic competition with switching costs. Rand
Journal of Economics, 19: 123-137.
Hal R. Varian, University of Berkeley
Hal R. Varian is the Dean of the School of Information Management and
Systems at the University of California, Berkeley. He is also a Professor in
the Haas School of Business, a Professor in the Department of Economics,
and holds the Class of 1944 Professorship. He received his S.B. degree
from MIT in 1969 and his MA (mathematics) and Ph.D. (economics) from
UC Berkeley in 1973. He has taught at MIT, Stanford, Oxford, Michigan
and other universities around the world. Professor Varian is fellow of the
Guggenheim Foundation, the Econometric Society, and the American Academy of Arts
and Sciences. He has served as Co-Editor of the American Economic Review and is on
the editorial boards of several journals.
48
Research
Professor Varian is currently interested in various issues of the economics of information
technology.
Key Publications
Shapiro, C., & Varian, H. R. (1998). Versioning: The smart way to sell information.
Harvard Business Review, November-December.
Andrew B. Whinston, University of Texas at Austin
Andrew B. Whinston is at the Center for Research in Electronic Commerce,
College and the Hugh Roy Cullen Centennial Chair Professor in
Information Systems at the Graduate School of Business in the University
of Texas at Austin. He is a Professor in the departments of Economics and
Computer Science as well.
Research
The hallmark of research under his guidance has been an integrated vision spanning
cross- disciplinary efforts, thus bringing technological, business, economic, public policy,
sociological, cryptographic and political concerns together in laying the theoretical and
practical foundations of a digital economy. His current research spans various realms of
Electronic Commerce, its impact on business protocols and processes, on organizational
structure and corporate networks, electronic publishing, electronic education,
complementarity of convergent computational paradigms and business value of IT.
Through diverse initiatives, various aspects and consequences of the emergent economies
over the Internet and corporate Intranets are studied.
Key Publications
Whinston, A. B. The Design and Development of a Financial Cybermarket with a Bundle
Trading Mechanism (with Jan Stallaert and Ming Fan), International Journal of
Electronic Commerce, 1999.
Whinston, A. B. Frontiers of Electronic Commerce (with Ravi Kalakota) , AddisonWesley , 1998.
Whinston, A. B. Creating Electronic Markets (with Ming Fan and Jan Stallaert), Dr.
Dobb's Journal, 1998.
Applegate, L. M., Holsapple, C. W., Kalakota, R., Radermacher, F. J., and Whinston, A.
B. (1996). Electronic commerce: building blocks of new business opportunity. Journal of
Organizational Computing and Electronic Commerce, 6(1), 1-10.
49
HCI / Psychology
Donald Norman
Prof. of Computer Science.
Northwestern University. Evanston
Phone: 408 862-5515
Fax: 408 255-7045
Email: dnorman@apple.com
Web Site: http://www.jnd.org/
Professional Background
Dr. Norman is Professor of Computer Science at Northwestern University and cofounder
of the Nielsen Norman Group, an executive consulting firm that helps companies produce
human-centered products and services. Norman serves as advisor and board member to
numerous companies in high technology and consumer products and to non-profit
organizations in the area of policy and education
Norman received a B.S. degree from MIT and an MS degree from the University of
Pennsylvania, both in Electrical Engineering. His doctorate, from the University of
Pennsylvania, is in Psychology.
He has been a faculty member at Harvard University, Professor Emeritus at the
University of California, San Diego where he was founding chair of the Department of
Cognitive Science and chair of the Department of Psychology. He was one of the
founders of the Cognitive Science Society and has been chair of the society and editor of
its journal, Cognitive Science. He is a fellow of the Human Factors & Ergonomics
Society, the American Psychological Society, and the American Academy of Arts and
Sciences, and has been appointed to the CHI Academy of ACM's SIGCHI, the
professional organization for Computer-Human Interaction. He has been a Fellow at the
Center for Advanced Studies in the Behavioral Sciences (Stanford).
Important Publications
Norman, D. A., & Draper, S. (Eds.), (1986). User Centered System Design: New
Perspectives on Human-Computer Interaction. Hillsdale, NJ: Lawrence Erlbaum
Associates
Norman, D. A. (1990). The design of everyday things. New York: Doubleday. (Paperback
version of The psychology of everyday things, unchanged except for title.)
50
Ben Shneiderman
Department of Computer Science
University of Maryland
College Park, MD 20742
Phone: (301) 405-2680
Fax: (301) 405-6707
(http://www.cs.umd.edu/~ben/)
Professional Background
Ben Shneiderman is a Professor in the Department of Computer Science, Founding
Director (1983-2000) of the Human-Computer Interaction Laboratory, and Member of
the Institute for Advanced Computer Studies and the Institute for Systems Research, all at
the University of Maryland at College Park. He got his Ph.D., at State University of New
York State University at Stony Brook, 1973.
He has taught previously at the State University of New York and at Indiana University.
Dr. Shneiderman teaches popular short courses and organized an annual satellite
television presentation on User Interface Strategies seen by thousands of professionals
from 1987 to 1997. He was made a Fellow of the ACM in 1997, elected a Fellow of the
American Association for the Advancement of Science in 2001, and received the ACM
CHI (Computer Human Interaction) Lifetime Achievement Award in 2001. He was the
Co-Chair of the ACM Policy 98 Conference, May 1998 and is the Founding Chair of the
ACM Conference on Universal Usability, November 16-17, 2000.
Important Publication:
Ben Shneiderman. Direct manipulation: a step beyond programming languages.
Computer, 16(8):57-69, August 1983.
Ben Shneiderman. Designing the User Interface: Strategies for Effective HumanComputer Interaction. Addison Wesley, 1986. Published 1987;
Dr. Jakob Nielsen
Nielsen Norman Group
48921 Warm Springs Blvd.
Fremont, CA 94539-7767
USA
Email: Nielsen@nngroup.com
Office: Luice Hwang,
hwang@nngroup.com, tel. (650) 938-9188
(http://www.useit.com)
Professional Background
51
Dr. Nielsen was usability lead for several design and redesign rounds of Sun’s website
and intranet (SunWeb), including the original SunWeb design in 1994.
His earlier affiliations include Bellcore (Bell Communications Research), the Technical
University of Denmark, and the IBM User Interface Institute at the T.J. Watson Research
Center. He holds a Ph.D. in user interface design/computer science from the Technical
University of Denmark.
Professional journal editorial board memberships: ACM interactions magazine,
Behaviour & Information Technology, Interacting with Computers, International Journal
of Human-Computer Interaction, The New Review of Hypermedia and Multimedia,
Personal and Ubiquitous Computing, World Wide Web.
In June 2000, Dr. Nielsen was inducted into the Scandinavian Interactive Media Hall of
Fame.
Important Publication:
Jakob Nielsen. Hypertext and hypermedia. Academic Press, Inc., 1990(citation 74)
Jakob Nielsen, Usability Engineering, Academic Press, San Diego, CA, 1993.
Dr. George Furnas
School of Information
University of Michigan
310 West Hall
550 East University Ave.
Ann Arbor, MI 48109-1092
313/763-0076
313/764-2475(fax)
furnas@umich.edu
http://www.si.umich.edu/~furnas/
Professional Backgroud
George Furnas joined the faculty of the University of Michigan in 1995, as a Professor in
the School of Information, with additional appointments in Comptuer Science and
Psychology. He came to Michigan from 15 years in research at Bell Labs and Bell
Communications Research (Bellcore), where he was most recently Director of Computer
Graphics and Interactive Media research in the Computer Science Research Department.
He got his AB degree from Harvard ('74 summa) and his PhD from Stanford ('80), both
in Cognitive Psychology. A principal focus of his research has been in human computer
interaction, specializing in areas related to information access and visualization, but he
has also published work in multivariate statistics and graphical reasoning. Some of his
specific contributions include work on statistical semantics, adaptive indexing, latent
semantic indexing, generalized fisheye views, purely graphical deduction systems, the
52
prosection method for high dimensional visualization, multitrees, space-scale diagrams
and information navigation.
Important Publications
Furnas, G. W. Generalized fisheye views, In Proceedings of CHI '86: ACM Conference
on Human Factors in Software, pages 16-23. Association for Computing Machinery.
Furnas, G. W. Furnas, Effective view navigation, In Proceedings of CHI '97: Human
Factors in Computing Systems, Atlanta, Georgia. Association for Computing Machinery.
Edward Tufte
Graphics Press at 203 272-9187,
Fax: 203 272-8600
Email: tufte@graphicspress.com
http://www.edwardtufte.com/1576494545/tufte/
Edward Tufte has written seven books, including Visual Explanations, Envisioning
Information, The Visual Display of Quantitative Information, and Data Analysis for
Politics and Policy. He writes, designs, and self-publishes his books on information
design, which have received more than 40 awards for content and design. He is Professor
Emeritus at Yale University, where he taught courses in statistical evidence, information
design, and interface design. His current work includes digital video, sculpture,
printmaking, and a new book called Beautiful Evidence.
Important Publication
Tufte, Edward. (1983) The Visual Display of Quantitative Information, Graphics
Press. (206citation in citeseer)
Tufte, Edward R. 1990. Envisioning Information. Cheshire, CT: Graphics Press.(144
citation in citeseer)
Stuart K. Card
No photo
Xerox Palo Alto Research Center
USA
Professional Background:
Stuart K. Card is a Xerox Research Fellow and manager of the User Interface Research
Group at Xerox PARC. He received his A.B. in physics from Oberlin College in 1966
and his Ph.D. in psychology from Carnegie- Mellon University in 1978, where he
53
pursued an interdisciplinary program in psychology, artificial intelligence, and computer
science.
Important Publication
Card, Stuart K, Thomas P Moran, and Allen Newell, “The psychology of humancomputer interaction,” Hillsdale, N.J., L. Erlbaum Associates, 1983( citation 211)
Stuart K. Card, Jock D. Mackinlay, and Ben Shneiderman, Readings in Information
Visualization: Using Vision to Think, 1999, Morgan Kaufmann Publishers
Izak Benbasat
CANADA Research Chair in Information Technology Management
Faculty of Commerce and Business Administration
University of British Columbia
Vancouver, B.C. V6T 1Z2
E-Mail: izak.benbasat@ubc.ca
Phone: (604) 822-8396
Fax: (604) 822-0045
http://mis.commerce.ubc.ca/members/benbasat/home.htm
Professional Backgroud
Izak Benbasat is CANADA Research Chair in Information Technology Management, and
he has published above 80 paper in top MIS journal since early 80th. He got Ph.D. in
MIS, University of Minnesota, 1974.
His research interest includes: Evaluating human-computer interfaces, specifically how to
design web-based interfaces to facilitate business-to-consumer electronic commerce;
Investigating the role of explanations in intelligent support systems in improving user
productivity and knowledge transfer to users; and measuring IT-related competencies,
namely, IT knowledge in line managers and business competence in IT professionals, and
their impact on the effective deployment of IT.
Important Publication
I. Benbasat and Lim, Lai-Huat, "Information technology Support for Debiasing Group
Judgments: An Empirical Evaluation," Organizational Behavior and Human Decision
Processes, Volume 83, No. 1, September 2000, pp. 167-183.
54
Daniel P. Siewiorek
Buhl University Professor of Electrical and Computer
Engineering and Computer Science, CMU;
Director of Human-Computer Interaction Institute
Phone: 412-268-2570
Fax NSH: 412-268-1266
Fax WeH: 412-268-5576
Office: 3519 Newell-Simon Hall
http://www.ece.cmu.edu/people/faculty/dps.shtml
Dr. Daniel P. Siewiorek is Buhl University Professor of Electrical and Computer
Engineering and Computer Science; Director of Human-Computer Interaction Institute.
He got his B.S. 1968, University of Michigan at Ann Arbor; M.S. 1969 and Ph.D. 1972,
Stanford University. From 1972, he joined Carnegie Mellon Univerisy.
His research interests include: Design Automation, reliable computing, mobile computing
Important Publication
Siewiorek, Daniel P.; and Swarz, Robert S. 1982: The Theory and Practice of Reliable
System Design. Digital Press.
A. Smailagic and D.P. Siewiorek, "Modalities of Interaction with CMU Wearable
Computers," IEEE Personal Communications, vol. 3, no. 1, pp. 14-25, February 1996.
Frank Biocca
Ameritech Professor
404 Comm Arts Bldg.
East Lansing, MI 48824-1212
Tel: 517.355.5073
Fax: 517.355.1292
biocca@tcimet.net
(http://tc.msu.edu/people/dept/biocca.html)
Professional Background
Dr. Biocca is the Ameritech Professor of Telecommunication and Director of the Media
Interface and Network Design (M.I.N.D.) Lab. He got his Ph.D. in Mass
Communication,University of Wisconsin-Madison.
Dr. Biocca has lectured or been a researcher at Stanford University, the University of
California-Berkeley, Duke University, the University of Wisconsin-Madison, the
University of North Carolina at Chapel Hill, and other universities. His research explores
human-computer interaction in virtual environments.
55
Important Publication
Frank Biocca, Mark Levy, Communication in the Age of Virtual Reality , Hillsdale, NJ:
Erlbaum, 1995
KM / AI / IR
Herbert A. Simon (1916-2001)
Richard King Mellon University Professor, Computer Science
Department, Psychology Department, Carnegie-Mellon University.
Ph.D.: University of Chicago.
Simon has backed up much of his work with numerous studies on
decision-making in business enterprise. Of notable importance was his
1949 article unveiling the "Hawkins-Simon" conditions for non- negative
square matrices. Since the 1950s, Simon has focused much of his
attention on the issue of decision-making - and has come up with a
behavioral theory based on "bounded rationality".
Key Publications
Simon, H.A. (1977) "Models of discovery: and other topics in the methods of science". Boston,
MA: D. Reidel Publishing Company
Newell, A., & Simon, H.A. (1961). GPS: A program that simulates human thought. In H.
Billings (Ed.), Lernende automaten (pp. 109-124). Munchen: R. Oldenbourg
Newell, A., & Simon, H.A. (1956). The logic theory machine. IRE Transactions on Information
Theory, IT-2(3), 61-79
Allen Newell (1927-1992)
U.A. and Helen Whitaker University Professor of Computer Science at
Carnegie Mellon University. Ph.D.: Industrial Administration, Carnegie
Institute of Technology.
With Herbert Simon, he proposed the Physical Symbol System hypothesis
in 1957. His work has centered on SOAR, an architecture for intelligent
problem solving and learning.
He is the winner of 1978 Nobel Laureate in Economics for his pioneering
research into the decision-making process within economic organizations.
Key Publications
Newell, A., and H. A. Simon. 1972. Human Problem Solving. Englewood Cliffs, N.J.: PrenticeHall
Newell, A., and H. A. Simon. 1956. The logic theory machine: A complex information
processing system. IRE Trans. Inf. Theory IT-2:61-79
56
John McCarty
John McCarthy. Computer Science Department, Stanford University. One of the founders of the
field of AI. Ph.D. Princeton, 1951.
A pioneer in artificial intelligence, McCarthy invented LISP, the
preeminent AI programming language, and first proposed general-purpose
time sharing of computers. He identifies common-sense rules that
determine the consequences of events and codifies these rules, along with
other information, as sentences in the symbolic languages of AI databases.
Key Publications
Inversion of Functions Defined by Turing Machines was included in
Automata Studies edited by Claude Shannon and myself and published by
Princeton University Press in 1956
Programs with Common Sense was probably the first paper on logical AI, i.e. AI in which logic
is the method of representing information in computer memory and not just the subject matter of
the program.
Some Philosophical Problems from the Standpoint of Artificial Intelligence by John McCarthy
and Pat Hayes was published in 1969 in Machine Intelligence 4. It is the basic paper on situation
calculus.
Edward Feigenbaum
Edward Feigenbaum. Kumagai, Professor of Computer Science, Stanford
University. Ph.D.: Carnegie-Mellon (1960).
Feigenbaum is currently serving as Chief Scientist of the Air Force.
Feigenbaum is studying the structure, dynamics, and the technology and
industry trends in the software segement of the computer industry, as part
of the Stanford computer Industry Project. He continues his long-term
research in the representation of knowledge for use by programs that
reason, and his work on advanced applications of expert systems.
Key Publications
Feigenbaum, Edward, and Julian Feldman. 1995. Computers and
Thought. Cambridge, MA: The MIT Press. (Originally published in 1963 by McGraw Hill.) A
collection of early articles., including many "classics."
Marvin Minsky
Toshiba Professor of Media Arts and Sciences, Professor of E.E. and C.S.,
M.I.T. Ph.D.: Princeton Univ.
His research has contributed to advances in artificial intelligence, cognitive
psychology, neural networks (he built the first neural-network simulator in
1951), and the theory of Turing machines. A pioneer in robotics, he built
some of the first mechanical hands with tactile sensors, visual scanners,
and accompanying software and computer interfaces. He influenced many robotic projects
outside MIT and has worked to build into machines the human capacity for commonsense
reasoning. In his The Society of Mind (1987), 270 interconnected one-page ideas reflect the
57
structure of his theory. He has participated in many studies of advanced technologies for space
exploration. He received the Turing Award in 1969.
Key Publications
WHY PEOPLE THINK COMPUTERS CAN'T first published in AI Magazine, vol. 3 no. 4, Fall
1982
STEPS TOWARD ARTIFICIAL INTELLIGENCE received by the IRE, October 24, 1960
Dr. Gerard Salton (1927-1995)
Professor PhD Harvard University, 1958
Salton developed SMART (System for the Mechanical Analysis and
Retrieval of Text). From his evaluations/tests of SMART, he formulated
general rules for automatic language processing (Bellardo & Bourne).
According to Bellardo and Bourne, Salton's retrieval experiments of the
1980's "greatly contributed to the knowledge base of computerized
information indexing, storage and retrieval." He advocated system design at
the 1965 ADI conference. See obituary notice in JASIS, February 1996.
Key Publications
Automatic analysis, theme generation and summarization of machine-readable texts. Science,
264, 3 (June 1994), 1421-1426 (with J. Allan, C. Buckley, and A. Singhal). (?)
Operations Research
Dr. Russell L. Ackoff
Professor Emeritus of Management Science at The Wharton School
Between 1964 and 1986, Dr. Ackoff chaired the Wharton School’s Departments of Statistics and
Operations Research and Social Systems Sciences, and directed its Management Science Center
and the Busch Center. Over the years, Dr. Ackoff’s dynamic and innovative techniques have
helped numerous organizations and government agencies meet their strategic planning and
systems design challenges. His work in research, consulting and education has involved more
58
than 250 corporations and 50 governmental agencies in the U.S. and abroad. He has authored or
co-authored 20 books and published over 200 articles in a wide variety of journals.
Key publications:
Russell L. Ackoff, The future of OR is past, Journal of Operational Research Society, 1979, v30:
93-103. (Times cited: 199)
Russell L. Ackoff, Resurrecting the future of OR, Journal of Operational Research Society,
1979, v30: 189-199. (Times cited: 125)
Dr. George Dantzig
Professor of Operations Research and Computer Science, Stanford University
George Dantzig received his doctorate in mathematics from Berkeley in 1946. He worked for the
US Bureau of Labor Statistics, served as Chief of the Combat Analysis Branch for USAF
Headquarters Statistical Control and as Mathematical Advisor for USAF Headquarters, Research
Mathematician for RAND Corporation, and Professor of Operations Research and Chairman of
the Operations Research Center at the University of California, Berkeley.
Key Publications
George Dantzig, P. Wolfe, Decomposition Principle for Linear-programs, Operations Research,
8 (1): 101-111, 1960 (Times cited: 354)
George Dantzig, Discrete-Variable Extremum Problems, Operations Research, 5 (2): 266-277,
1957. (Times cited: 101)
Dr. Ward Whitt
AT&T Shannon Laboratory, Room A117
180 Park Avenue
59
Florham Park, NJ 07932-0971
Dr. Whitt received an A.B. in mathematics from Dartmouth College in 1964 and a Ph.D. in
operations research from Cornell University in 1969. On the faculty of the Department of
Operations Research (now the Department of Management Science and Engineering) at Stanford
University in 1968-69 and then on the faculty of the Department of Administrative Sciences,
with a joint appointment in the Department of Statistics, at Yale University from 1969 through
1977. Since 1977 at Bell, he started to work in the Operations Research Center in the Research
Area (Center 171) in Holmdel, NJ, where the principal project was developing and applying the
Queueing Network Analyzer (QNA) software tool. From 1987 through 1996, he worked in the
Mathematical Sciences Research Center (Center 121) in Murray Hill, NJ (now part of Bell Labs,
Lucent technologies). Since 1996 till now, he has been working in AT&T Labs - Research in
Florham Park, NJ. His research topics concentrate on queuing theory, performance analysis,
stochastic.
Key publications
Ward Whitt, Donald Iglehart, Multiple Channel Queues in Heavy Traffic, Advances in Applied
Probability, vol.2 No.1:150-177, vol. 2, No. 2:355-369, vol.2, No. 2:370-375, 1970.
K Sriram, Ward Whitt, Characterizing Superposition Arrival Processes in Packet Multiplexers
for Voice and Data, IEEE Journal on Selected Areas in Communications, 4(6):833-846, Sep
1986. (Times cited: 161)
Dr. Hau Lee
Professor of Operations, Information, and Technology,
School of Engineering, Stanford University
Director of the Stanford Global Supply Chain Management Forum
Dr. Lee is a professor of Operations, Information, and Technology; Kleiner, Perkins, Mayfield,
Sequoia Capital Professor of Engineering, School of Engineering; Director of The Stanford
Global Supply Chain Management Forum; Director of Managing Your Supply Chain for Global
Competitiveness Executive Program.
He received BS degree in Univ. of Hong Kong, 1974; MSc in London School of Economics,
1975; MIS in the Institute of Statisticians, 1976; MS in the Univ. of Pennsylvania, 1979, PhD,
1983. He was a lecturer, Univ. of Hong Kong during 1975-77. He taught as a lecturer in the
Univ. of Pennsylvania during 1982-83. He has served as an Asst. Prof.-Prof. in Stanford Univ.
since 1983. He also worked as a Project Engineer in Hewlett-Packard Company during 1989-90.
60
His Research Interests includes Supply chain management, global logistic system design and
control, multi-echelon inventory systems, manufacturing and distribution strategy, design for
supply chain management
Key Publications
Material Management in Decentralized Supply Chains, Operations Research, vol. 41 1993
Hewlett-Packard Gains Control of Inventory and Service Through Design for Localization,
Interfaces, vol. 23 1993
Supply Chain Inventory Management: Pitfalls and Opportunities, Sloan Management Review,
vol. 33 1992
Dr. Marshall L. Fisher
Stephen J. Heyman Professor of Operations and Information Management,
Co-Director of Fishman-Davidson Center for Service and Operations Management,
The Wharton School,
University of Pennsylvania
Dr. Fisher holds the UPS Transportation for the Public Sector Professorship (2001) and
previously held the Stephen J. Heyman Professorship in Manufacturing and Logistics (19862001) at the Wharton School of the University of Pennsylvania. He has three degrees from the
Massachusetts Institute of Technology: a S.B. in Electrical Engineering, S.M. in Management,
and a Ph.D. in Operations Research. He served as President of the Institute of Management
Sciences during 1988-89 and as Departmental Editor of the journal Management Science during
1979-83. He is a recipient of the 1977 Lanchester Prize for outstanding published work in the
field of operations research, the 1983 Institute of Management Science Practice Prize for his
work in implementing a very large model used to schedule deliveries for an industrial gas firm,
and the 1984 Council of Logistics Management E. Grosvenor Plowman award. In 1994 he was
elected a member of the National Academy of Engineering. He has published widely in the
professional literature on both practical and theoretical aspects of operations management and
management science, and has been a consultant to many Fortune 500 companies.
Dr. Fisher has devoted his recent research to studying supply chain coordination, focusing
particularly on environments with rapid introduction of new products and a high degree of
demand uncertainty.
61
Key publications
Marshall L. Fisher, The Lagrangian-Relaxation Method for Solving Integer Programming
Problems, Manage Science, 27 (1):1-18 1981 (Times cited: 427)
Marshall L. Fisher, R. Jaikumar, A Generalized Assignment Heuristic for Vehicle-Routing,
Networks, 11 (2): 109-124, 1981 (Times cited: 160)
Gerard Cornuejols, Marshall L. Fisher, George L. Nemhauser, Location of Bank Accounts to
Optimize Float: An Analytic Study of Exact and Approximate Algorithms, Management Science,
April 1977.
Policy & Social Issues
Mary J. Culnan
Contact Information
The McDonough School of Business, Georgetown University
Washington D.C., 20057-1008
(202) 687-3802;
E-mail: culnanm@msb.edu
Research areas
“Professor Culnan specializes in the social and public policy impacts of information technology. Her
research focuses on information privacy. She is currently addressing consumer attitudes toward privacy
and electronic marketing. She teaches courses on information systems, the impact of information
technology on business strategy, and electronic commerce.”
(http://www.gsb.georgetown.edu/faculty/culnanm/)
Sara Kiesler
Contact Information
3513 Newell-Simon Hall
Carnegie Mellon University
5000 Forbes Ave.
Pittsburgh, PA 15213-3891
(412) 268-2888;
E-mail: kiesler@andrew.cmu.ecu
Research Areas
Professor Kiesler’s research interests include the social and behavioral aspects of computers and
computer-based communication technologies. (http://www.hcii.cmu.edu/0_People/faculty.html)
Robert Kling
Contact Information
School of Library and Information Science
Indiana University at Bloomington
107 S. Indiana Avenue
Bloomington, IN 47405-7000
62
(812) 855-9763,
E-mail: kling@indiana.edu
Research areas
“My research focuses upon the social consequences of computerization and the social choices
that are available to people. … I believe that we have to understand information technologies in
terms of their associated social structures and politics, and in meaningful social contexts -- not
just as ‘information tools’…Currently, I'm focusing on electronic publishing and people's use of
digital libraries as a set of applications and social spaces for understanding IT and social change,
and the possibilities of new technologies facilitating the restructuring of social life.”
(http://www.slis.indiana.edu/kling/scholarly.html)
Lee Sproull
Contact Information
Leonard N. Stern School of Business
New York University
New York, New York
Research areas
Prof. Sproull “has published more than fifty books and articles on the social and organizational
implications of computing technology and is a member of the National Research Council
Computer Science and Telecommunications Board. Her current research focuses on the
dynamics and consequences of electronic groups and communities.” (
http://www.mentornet.net/Documents/Other/Bios/sproull.html)
Peter G. Neumann
Contact Information
Principal Scientist at SRI International Computer Science Laboratory
http://www.csl.sri.com/neumann/neumann.html
E-mail: Neumann@csl.sri.com
Education
He spent eight years at Harvard (1950-58, with his A.B. in Math in 1954, S.M. in Applied Math
in 1955, and PhD in 1961 after returning from his two-year Fulbright in Germany (1958-60),
where he received the German Dr rerum naturarum in 1960.
Research areas
Dr. Neumann’s “main research interests continue to involve security, crypto applications, overall
system survivability, reliability, fault tolerance, safety, software-engineering methodology,
systems in the large, applications of formal methods, and risk avoidance.”
(http://www.csl.sri.com/users/neumann/neumann.html).
Seymour E. Goodman
Seymour (Sy) E. Goodman has been Professor of MIS (1981) and a member of the
Center for Middle Eastern Studies at the University of Arizona, and Carnegie
63
Science Fellow (1994) and head of the Program on the Information Technologies and
International Security at the Center for International Security and Arms Control, Stanford
University. Earlier tenured and visiting appointments have been at the University of Virginia
(Applied Mathematics and Computer Science), Princeton University (Mathematics and the
Woodrow Wilson School of Public and International Affairs), and the University of Chicago
(Economics).
Email: goodman@cc.gatech.edu
Education
He did his undergraduate work at Columbia University, and obtained his Ph.D. from the
California Institute of Technology.
Research Areas
“Professor Goodman's research interests include international developments in the information
technologies (IT), technology diffusion, IT and national security, and related public policy
issues. His areas of geographic interest include the former Soviet Union and Eastern Europe,
Latin America, the Middle East, South and Southeast Asia, and parts of Africa.”
(http://www.inta.gatech.edu/cistp/people/goodman.htm)
Eli M. Noam
http://www.citi.columbia.edu/elinoam
Director, Columbia University Institute for Tele-Information; 1983-1987, 1991present
Professor of Finance and Economics, Columbia Business School; 1976-present
Email: noam@columbia.edu
Education
Harvard: A.B. 1970 (Phi Beta Kappa); A.M. 1972; J.D. 1975; Ph.D. Economics, 1975,
Dissertation adviser: Martin Feldstein.
Research Areas
“Eli M. Noam is Professor of Finance and Economics at the Columbia University Graduate
School of Business and Director of the Columbia Institute for Tele-Information…His
publications include over a dozen books and about 200 articles on domestic and international
telecommunications, television, information and regulation subjects.”
(http://www.cpi.seas.gwu.edu/library/seminar_archive/95-96/feb96/noam.html)
Richard Mason
Contact Information:
Carr P. Collins Distinguished Professor of ISOM
Director, Maguire Center for Ethics and Public Responsibility
Edwin L Cox School Of Business
Southern Methodist University
Dallas, Texas 75275
E-mail: rmason@mail.cox.smu.edu
64
Awards:
Named among the top 35 MIS Consultants in Information Week's survey of the top 50 MIS
Consultants (1988).
Elected as a foreign member of the Russian Academy of Natural Sciences in the Information and
Cybernetics section.
Awarded a Fulbright Fellowship in 1993 to do research at Umea University in Sweden.
Research Areas:
Dr. Mason has many areas of expertise, including the following: Business Ethics and Philosophy,
Management Information Systems, Strategy and Policy, Organization Theory, Digital Economy,
Electronic Commerce, Information Management, IS Ethics, and Internet and Culture.”
(http://faculty.cox.smu.edu/rmason.html)
Dorothy E. Denning
Professor of Computer Science at Georgetown University
Director of the Georgetown Institute for Information Assurance.
Also affiliated with the Communication, Culture and Technology program and the
Science and Technology in International Affairs program.
Email denning@georgetown.edu
http://www.cs.georgetown.edu/~denning/
Education
B.A. and M.A. degrees in mathematics from the University of Michigan, Ph.D. degree in
computer science from Purdue University
Research Areas
Dr. Denning’s “current work encompasses the areas of cyber crime and cyber terrorism,
information warfare and security, and the impact of technology on society. She has published
120 articles and four books, her most recent being Information Warfare and Security.”
(http://www.cs.georgetown.edu/~denning/bio.html)
Pamela Samuelson
Professor at the University of California at Berkeley
Joint appointment in the School of Information Management and Systems and
the School of Law.
Co-Director of the Berkeley Center for Law and Technology.
Website: http://www.sims.berkeley.edu/~pam/
Email: pam@sims.berkeley.edu
Education
Yale Law School: J. D. 1976, University of Hawaii at Honolulu: M. A. 1972, Political Science,
B. A. 1971, History
Research Areas
Prof Samuelson’s “principal area of expertise is intellectual property law. She has written and
spoken extensively about the challenges that new information technologies are posing for public
65
policy and traditional legal regimes and is an advisor for the Samuelson Law, Technology and
Public Policy Clinic.” (http://www.sims.berkeley.edu/~pam/)
Workflow
Clarence Ellis
Clarence (Skip) Ellis, Professor
Contact Information:
Office: ECOT 747
Dept of Computer Science
University of Colorado, Boulder
CO 80309-0430
Clarence Ellis is the first African American to receive a Ph.D. in Computer Science. During
1991, he was chief architect of the FlowPath workflow product of Bull S.A.
He has published several books, and over 100 technical papers and reports, lectured in more than
a dozen countries, and was an invited speaker on object oriented systems at the most recent IFIP
World Computer Conference.
Education:
BS degree, double major in math and Physics, Beloit College in Wisconsin
Ph.D. Degree in Computer Science, the University of Illinois (1969)
Current Projects:
Studies of Next Generation Workflow Systems
Study of Architectures for Large Scale Workflow
Key Publication:
A Workflow Architecture to Support Dynamic Change. Workshop on Distributed Systems,
Multimedia, and Infrastructure, March 1995. 23-30.
Goal Based Workflow Systems. International Journal of Collaborative Computing, 1,no.1, 1994.
pp.61-86.
66
Professor Sheth
Amit P. Sheth, Professor
Department of Computer Science
University of Georgia
415 Graduate Studies Research Center
Athens GA 30602-7404
Professor Sheth is one of the leaders in Workflow Coordination. He served in R&D groups at
Bellcore (now Telcordia Technologies), Unisys, and Honeywell. There he led projects on
transactional workflows (METEOR). Prof. Sheth has given nine keynote talks at international
conferences and meetings, over 100 invited talks, tutorials and professional courses. He has over
100 publications, including two outstanding conference papers, and some of the most cited
papers in federated databases, workflow management and semantic interoperability.
Education:
B.E. B.I.T.S., Pilani, India,1981
M.S.(1983) and Ph.D.(1985) ,Ohio State University
Key Publication:
Webwork: Meteor2's web-based workflow management system. Journal of Intelligent
Information Systems, 10(2):185--215, 1998. J. A. Miller, D. Palaniswami, K. J. Sheth, Amit P.
Kochut, and H. Singh.
Workflow Management Systems and Interoperability, Dogac, Kalinichenko,Ozsu and Sheth,
Eds., 1998. (Book)
"Workflow Process management and Enterprise Application Integration in Healthcare," Keynote
Address, IEEE Workshop on Enterprise Networking and Computing in Healthcare Industry
(Healthcom 99), Sydney Australia, January 11, 1999
Dr. Jablonski
Stefan Jablonski, Professor
Dr. Jablonski is a leading
researcher
in the usage
and development
of workflow management
Dept.
of Computer
SciencesVI
(Database Systems)
systems. He published hundreds
of
papers
about
workflow
management
systems. His papers and
Friedrich-Alexander Universitaet Erlangen-Nuernberg
books are widely cited by
other researchers.
Martensstr.
3
Key Publication:
D-91058 Erlangen
Workflow Management---Modeling Concepts, Architecture and Implementation. International
Tompson Computer Press, 1996, Stefan Jablonski and Christoph Bussler.
67
A Comprehensive Approach to Flexibility in Workflow Management Systems. In Proceedings of
the International Joint Conference on Work Activities Coordination and Collaboration
(WACC'99), Feb. 1999, San Francisco, Petra Heinl, Stefan Horn, Stefan Jablonski, Jens Neeb,
Katrin Stein, and Michael Teschke.
"An Approach to Dynamic Instance Adaption in Workflow Management Applications". 1998.
Stefan Horn, Stefan Jablonski
Dr. Christoph Bussler
Christoph Bussler
Advanced Computing Technologist at The Boeing
Company's Applied Research and Technology group,
Dr. Christoph Bussler is anSeattle,
Advanced
Technologist at The Boeing Company's
WA,Computing
USA.
Applied Research and Technology group based in Seattle, WA, USA. As project manager of the
Workflow Management project he is responsible for conducting workflow research as well as
transferring workflow technology into The Boeing Company. Previous to his current position he
was faculty member at the Database Chair of the University of Erlangen-Nuremberg, Germany,
where he earned his Ph. D. degree in the area of workflow management.
Key Publications:
Workflow Management---Modeling Concepts, Architecture and Implementation. International
Tompson Computer Press, 1996. Stefan Jablonski and Christoph Bussler.
An approach to integrate workflow modeling and organizational modeling in an enterprise.
Proceedings of the Third IEEE International Workshop on Enabling Technologies: Infrastructure
for Collaborative Enterprises (WETICE) , MorganTown, West Virginia, USA, April 1994.
Stefan Jablonski Christoph Bussler.
Analysis of the Organization Modeling Capability of Workflow Management -Systems. In:
Proceedings of the PRIISM '96 Conference, Maui, Hawaii, and January 1996. Bussler,
Christoph
Education:
Ph.D., Computer Science, University of Erlangen-Nuernberg, Erlangen, Germany, 1997
M.S., Computer Science, University of Munich, Munich, Germany, 1990
B.A., Computer Science, University of Munich, Munich, Germany, 1987
68
University of Arizona
Hsinchun Chen
Background
Professor, MIS Department. University of Arizona
He received the Ph.D. degree in Information Systems from New York
University in 1989.
Research Interests
He is interested in: Digital Libraries, Knowledge Management, Multi-lingual
and Distributed Information Retrieval
Key Paper(s)
Chen H., Shankaranarayanan G., Iyer A., and She L. “A Machine Learning
Approach to Inductive Query by Examples: An Experiment Using Relevance Feedback, ID3,
Genetic Algorithms, and Simulated Annealing,” Journal of the American Society for Information
Science, Volume 49, Number 8, Pages 693-705, June 1998.
Moshe Dror
Background
Professor, MIS Department, The University of Arizona
He received his Ph.D. degree from University of Maryland College Park
Campus in 1983
Research Interests
He is interested in: Combinatorial Optimization In Logistics And
Manufacturing Systems; Cooperative Game Theory And Cost Allocation In
Inventory And Combinatorial Problems; Agent Theory And Applications In
Operations Management.
Key Paper(s)
Dror, M. and Trudeau P. “Inventory Routing: Operational Design”. Journa; of Business Logistics
9(2); 165-183
Knotts, G., Dror, M. and Hartman, B. “Agent-based project scheduling”. IIE Transactions 32;
387-401; 2000.
Kurt D. Fenstermacher
Background
Assistant Professor, MIS Department, The University of Arizona
He received his Ph.D. degree in Artificial Intelligence from University of Chicago in 1999
Research Interests
69
He is interested in: Construction of scaleable tools for managing knowledge in organizations;
Impact of information technology on organizational structure; Role of information technology in
corporate strategy; Societal impact of computerization
Key paper(s)
Fenstermacher, K. and Marlow, C. “Supporting Consultants with Task-Specific Information
Retrieval”. Presented at the AAAI 1999 Workshop on Intelligent Information Retrieval. July 2223, 1999. Orlando, Florida
Mark Ginsburg:
Background
Assistant Professor, MIS Department. University of Arizona
He received the Ph.D. degree in Information Systems from New York
University in 1998.
Research Interests
He is interested in the following Internet issues: evolution of
standards, collaborative software, and the roles of data and metadata in
search and retrieval
Key paper(s)
1. Kambil, A. and Ginsburg, M. "Public Access Web Information Systems: Lessons from
the Internet EDGAR Project", Communications of the ACM, July 1998, Vol. 41, No. 7,
pp. 91-97.
James F. LaSalle
Background
University Distinguished Professor, MIS Department, The University
of
Arizona.
He received the Ph.D. degree in Business Administration from
Pennsylvania State University in 1963.
Research Interests:
Application of decision-making techniques to strategy development and executive simulation.
Therani Madhusudan
Background
Assistant Professor, MIS Department, The University of Arizona
He received his Ph.D. degree in GSIA and Robotics from CarnegieMellon in 1998
70
Research Interests
His area of interest is the study of properties of complex, socio-technical systems to enable their
analysis, design and management.
Key paper(s)
Madhusudan, T.N, Sycara, Katia and D Navinchandra " On Synthesis of Electromechanical
Assemblies”, ASME, Design Engineering Technical Conference, August 1996, UC Irvine, CA.
David E. Pingry
Background
Professor, MIS Department; Professor, Economics, The University of
Arizona
He received his Ph.D. degree in Economics from Purdue University in
1971.
Research Interests
Research interests include the economics of the design process, production
theory and water resource economics.
Key paper(s)
Issac, M. and Pingry, D. “Managing J. Pierrepont Finch: Should he be
given a PC?”, Information and Management, Volume 21, Pages 269-277, 1991
Pingry D. “Theory of Decision Support Systems portfolio evaluation”
Sudha Ram
Background
Professor, MIS Department, The University of Arizona
She received his Ph.D. degree in Computer Science from University of
Illinois at Urbana-Champaign
Research Areas
Her research deals with modeling and analysis of database and knowledge
based systems for manufacturing, scientific and business applications.
Specifically, the research deals with interoperability among distributed and
heterogeneous database systems, semantic modeling, data allocation,
schema and view integration, intelligent agents and digital libraries for data
management, and automated tools for database design. E-Business infrastructure and strategy is
also one of her favored areas.
Key paper(s):
Ram, S. (1991). Heterogeneous Distributed Database Systems. IEEE Computer, 24(12), 7-11.
Olivia Sheng
Background
Department Head and McCoy-Rogers Professor, MIS Department.
University of Arizona
71
She received the Ph.D. degree in Computers and Information Systems from University of
Rochester in 1986.
Research interests:
Her Research interest fields include global information technology and management for
telemedicine, electronic commerce, manufacturing and service industries, telework and learning.
Key paper(s)
Zeng D., Sheng O., and Wilson. B. “The Design and Experimentation of Agent-based
Procurement Systems”, Proceedings of the Third International Conference on
Telecommunications and Electronic Commerce, November, 2000.
Pamela Slaten
Background
Assistant Department Head, MIS Department. University of Arizona. She
received the Ph.D. degree in Operations Management from University of
Texas at Austin.
Research interests
Her interests include the design of manufacturing systems, Japanese
manufacturing systems, management of service operations.
Matt Thatcher
Background
Assistant Professor, MIS Department. University of Arizona.
He received his Ph.D. in Managerial Science and Applied Economics from
University of Pennsylvania in 1998.
Research interests
His research interests include the economics of international privacy, IT
design and implementation and strategic planning under uncertainty.
Key paper(s)
Thatcher, M. and Clemons, E. “Managing the Costs of Informational Privacy: Bundling as a
Strategy in the Individual Health Insurance Market”. HICSS 2000
Thatcher, M. and Oliver J. “The Impact of Information Technology on Quality Improvement,
Productivity, and Profits: An Analytical Model of a Monopolist”. HICSS 2001
Sherry Thatcher
Background
Assistant Professor, MIS Department. University of Arizona.
She received her Ph.D. from University of Pennsylvania in 2000
Research areas
Her research interests include effects of diversity on the working environment
and the social impacts of technology on different
groups and cultures.
72
Key paper(s)
Thatcher, S. and Foster, W. “Cracks in Diversity Research: The Effects of Diversity Faultliness
on Conflict and Performance”
Thatcher, S., Jehn, K. and Zanutto, E. “B2B e-commerce adoption decisions in Taiwan: The role
of industry, government and culture”
Suzie Weisband
Background
Associate Professor, MIS Department. University of Arizona.
She received the Ph.D. degree in Social and Decision Sciences from
Carnegie Mellon University in 1989.
Research areas
Dr. Weisband’s research includes social and behavioral impacts of
technology on group decision making, and in organizational issues related to
computer use. She has participated in research involving communication
among groups using various technological platforms and interactivity. Dr.
Weisband has also been involved in GSS research, F-t-F interactions, and melding disciplines
such as MIS, Communication, Sociology, and Psychology into her research.
Daniel Zeng
Background
Assistant Professor, MIS Department. University of Arizona.
He received the Ph.D. degree in Industrial Administration from Carnegie
Mellon University in 1998
Research interests:
Software Agents and Multi-Agent Systems, Collaborative Information and
Knowledge Management; Digital Economic Institutions, Automated
Negotiation and Auction Contracting, Process Management and Learning;
Distributed Transaction Management, Web Caching; Supply Chain
Network Configuration, Distributed Optimization
Key paper(s)
Zeng, D. “ Managing Flexibility for Inter-organizational Electronic Commerce”, Electronic
Commerce Research Journal, Vol 1, No. 2, pp. 33-51, 2001.
Zeng, D. and Sycara, K. “Benefits of Learning in Negotiation”, International Journal of Human
Computer Systems, Vol. 48, pp. 125-141, 1998.
Zeng, D. and Sycara, K. “Coordination of Multiple Intelligent Software Agents”, International
Journal of Cooperative Information Systems, Vol. 5, No. 2, pp. 181-211; 1996
73
J. Leon Zhao
Background
Associate Professor, MIS Department. University of Arizona.
He received the Ph.D. degree in Business Administration from University of
California, Berkeley in 1992
Research areas
He is interested in: Development of database and workflow technologies
and their applications in electronic commerce, knowledge management, and
organizational process automation.
Key paper(s)
Stohr, E. and Zhao, L. "Workflow Automation: Overview and Research Issues", Information
Systems Frontiers: Special Issue on Workflow Automation and Business Process Integration,
Volume 3, Issue 3, September 2001.
Kumar, A. and Zhao, A. "Dynamic Routing and Operational Controls in Workflow Management
Systems", Management Science, Volume 45, No. 2, February 1999, pp 253-272.
74