MIS 696a and 797a
Group Project
College of Business and Public Administration
Conan Albrecht
Wayne Anderson
Irit Askira
Michael Chau
Faiz Currim
Craig Erwin
Xiao Fang
Rosie Viprakasit Hauck
Vijay Khatri
Dongwon Lee
Greg Lousignont
Gary Mahon
Jeff Perry
Yi Shan
Poh-Kim Tay
Karl Wiers
Huimin Zhao
Dongsong Zhang
Bin Zhu
December 15, 1998
TABLE OF CONTENTS
Introduction …………………………………………………………………………………2
Overall MIS papers …………………………………………………………………………3
Science & Scientific Practice
Theoretical Background
Methodologies
Database Technology ……………………………………………………………………….8
Data mining
Data warehousing
Design/Maintenance
Modeling
OLAP
KM
Software development and engineering ………………………………………………......13
Models
System engineering
Process/work flow
Reengineering
CASE tools
Technology ………………………………………………………………………………….19
AI
Algorithms & Data structures
GSS
OS
Human-computer interaction ……………………………………………………………...24
Visualization techniques
Interface design
I/O: speech, mouse, keyboard
Organizational/Behavioral ………………………………………………………………....27
Individual judgement and decision making
Group judgement and decision making (non-GSS)
Organizational change
Ethics, Legal, International, and Social Issues
Decision Sciences ……………………………………………………………………………33
OR/OM
Project Management
DSS/ESS
Economics of IS
1
Introduction
This collection of key papers and influential people is organized into seven areas, representing
the major divisions of research within Management Information Systems and the related field of
Management. The citations of key papers conform to the most recently published guidelines
from American Psychological Association (APA). For each of the key people identified, a short
biographical sketch has been prepared, highlighting their significant contributions, research
interests, and current university affiliation, if applicable.
It was decided that the management papers would begin chronologically with the introduction of
game theory in the late 1940’s. This was not intended to downplay the contributions of
Bernoulli, Gauss, Pascal, and others in the development of probability theory, but rather to place
a realistic boundary on the time frame for key papers and people.
To facilitate the distribution and use of this compilation, a version will be placed on the web to
enable access by all interested parties. Regular updates will be performed as necessary to keep
the information current and accurate.
The task of narrowing down the list of key papers was not an easy one, however the group
attempted to find the right balance between quality and quantity. Key papers were selected using
one of two methods, either a subjective assessment from one or more faculty or objectively, by
counting the number of citations in the Social Sciences Citation Index (SSCI). Key people were
determined primarily by subjective methods, taking into consideration a person’s publications,
graduate student sponsorship, and notoriety within the field.
2
Overall MIS Papers
Science and Scientific Practice
Nature of Science
Kuhn, T. (1996). The Structure of Scientific Revolutions (3rd edition). Chicago, IL: University of
Chicago Press.
Academic Ethics
Culliton, B. J. (1988, November 4). Authorship, Data Ownership Examined. Science, 242, 658.
Schachman, H. K. (1993, July 9). What is Misconduct in Science. Science, 261, 148-149, 183.
Smith, R. (1997). Authorship, Data Ownership Examined. British Medical Journal, 314(7086),
992.
Methodology
Quantitative Research Methodologies in MIS
1. Optimization Modeling
Ram, S., & Narasimhan, S. (1994). Database Allocation in a Distributed Environment:
Incorporating Concurrency Control Mechanism and Queuing Costs. Management Science, 40(8),
969-983.
Ram, S., & Narasimhan, S. (1995). Incorporating the Majority Consensus Concurrency Control
Algorithm into the Database Allocation Problem. ORSA Journal on Computing, 7(3), 244-258.
Fisher, M. L. (1985). An Application-Oriented Guide to Lagrangian Relaxation. Interfaces, 15,
10-21.
Jain, H. K., Tanniru, M. R., & Fazlollahi, B. (1991). MCDM Approach for generating
Alternatives in Requirements Analysis. Information Systems Research, 2(3), 223-239.
March, S., & Rho, S. (1995). Allocating Data and Operations to Nodes in Distributed Database
Design. IEEE Transactions on Knowledge and Data engineering, 7(2), 305-317.
2. Grammars
Tremblay, J. P., & Sorenson, P. G. (1984). Grammars. Data Structures with Applications, (pp.
101-114). New York: McGraw-Hill.
3
Choobineh, J. (1991). SQLMP: A Data Sublanguage for Representation and Formulation of
Linear Mathematical Models. ORSA Journal on Computing, 3(4), 358-375.
Mohan, L. & Kashyap, R. L. (1993). A Visual Query Language for Graphical Interaction with
Schema Intensive Databases. IEEE Transactions on Knowledge and Data engineering, 5(5),
843-858.
3. Set Theory and Formal Modeling
Lin, Y. F., & Lin, S. Y. (1984). The Concept of Sets. Set Theory with Applications, (pp. 33-58).
Tampa, Florida: Mariner Publishing Co.
Kainz, W., Egenhofer, M. J., & Greasley, I. (1993). Modeling Spatial Relations and Operations
with Partially Ordered Sets. International Journal of Geographic Inforamtion Systems, 7(3), 215229.
Rudensteiner, E., & Bic. L. (1992). Set Operations in Object-based Data Models. IEEE
Transactions on Data and Knowledge Engineering, 4(3), 382-398.
Parsons, J. (1996). An Information Model based on Classification Theory. Management Science,
42(10), 1437-1453.
4. Simulation
Law, A. H., & Kelton, W. D. (1992). Basic Simulation Modeling. Simulation Modeling and
Analysis (pp. 1-132). New York: McGraw-Hill.
Kelton, W. D. (1994). Perspectives on Simulation Research and Practice. ORSA Journal on
Computing, 6(4), 318-328.
Agarwal, R., Carey, M. J., & Livney, M. (1987). Concurrency Control Performance Modeling:
Alternatives and Implications. ACM Transactions on Database Systems, 12(4), 609-654.
Kumar, A., Ow, P. S., & Prietula, M. (1993). Organizational simulation and Information Systems
Design: An Operations Level Example. Management Science, 39(2), 218-240.
5. Econometric Modeling
Simon, H. (1987). Models of Man Social and Rational (pp. 1-61). New York: John Wiley and
Sons.
Zellner, A. (1988). Causality and Causal Laws in Economics. Journal of Econometrics, 39, 7-21
Holland, P. W. (1986), Statistics and Causal Inference. Journal of the American Statistical
Association, 81(396), 945-970.
4
Gurbaxani, V., & Mendelson, H. (1992), An Empirical Analysis of Software and Hardware
Spending. Decision Support Systems, 8, 1-16.
Ein-Dor, P. (1985). Grosch’s Law Re-Revisited: CPU Power and the Cost of Computation.
Communications of the ACM, 28(2), 141-151.
Behavioral Research Methodologies in MIS
1. Nature of Theory
Markus, M. L., & Robey, D. (1988). Information Technology and Organizational Change:
Causal Structure in Theory and Research. Management Science 34(5), 583-598.
Wallace, W. L. (1971). The Logic of Science in Sociology (Chapter 1). Chicago: AldineAtherton.
2. Research Approaches in MIS
Orlikowski, W. J., & Baroudi, J. J. (1991). Studying Information Technology in Organizations:
Research Approaches and Assumptions. Information Systems Research 2(1), 1-28.
3. Research Validity
Cook, T. D., & Campbell, D. T. (1979). Quasi-experimentation : Design & Analysis Issues for
Field Settings (Chapter 1). Chicago : Rand McNally College Publishing Company.
Mitchell, T. R., (1985). An Evaluation of the Validity of Correlational Research Conducted in
Organizations. Academy of Management Review 13(4), 627-638.
4. Survey Research
Fowler, F. J. (1993). Survey research methods (2nd edition). Newbury Park: Sage Publications
Kirsch, L. (1996). The Management of Complex Tasks in Organizations: Controlling the
Systems Development Process, Information Systems Research, 7(1), 1-21.
Nidumolu, S. R. (1995). The Effect of Coordination and Uncertainty on Software Project
Performance: Residual Performance Risk as an Intervening Variable. Information Systems
Research, 6(3), 191-219.
Pinsonneault, A., & Kraemer, K. L. (1993). Survey Research Methodology in Management
Information Systems: An Assessment. Journal of Management Information Systems 10(2), 75105..
5
Straub, D. W. (1989). Validating Instruments in MIS Research. MIS Quarterly, 13(2), 147-166.
5. Intensive Research
Case Studies
Yin, R. K. (1994). Case study research: design and methods (2nd edition). Thousand Oaks: Sage
Publications.
Lee, A. S. (1989). A Scientific Methodology for MIS Case Studies. MIS Quarterly 13(1), 33-50.
Eisenhardt, K. M. (1989). Building Theories from Case Study Research. Academy of
Management Review, 14(4), 532-550.
Ethnography
Barley, S. R. (1986). Technology as an Occasion for Structuring: Evidence from Observations of
CT Scanners and the Social Order of Radiology Departments. Administrative Science Quarterly,
31(1), 78-108.
Grounded Theory Research
Orlikowski, W. J. (1993). CASE Tools as Organizational Change: Investigating Incremental and
Radical Changes in Systems Development. Management Information Systems Quarterly, 17(3),
309-340.
Hermeneutics
Lee, A. S. (1994). Electronic Mail as a Medium for Rich Communication: An Empirical
Investigation Using Hermeneutic Interpretation. MIS Quarterly, 18(2), 143-157.
Action Research
Baskerville, R. L. & Wood-Harper, A. T. (1996). A Critical Perspective on Action Research as a
Method for Information Systems Research. Journal of Information Technology, 11, 235-246.
Network Analysis
Barley, S. R. (1990). The alignment of technology and structure through roles and networks.
Administrative Science Quarterly, 35 (1), 61-104.
Krackhardt, D. & Stern, R. N. (1988). Informal networks and organizational crises: An
experimental simulation. Social Psychology Quarterly, 51(2), 123-140.
6
Other References
1. Research Methods: Under ISWORLD Net Research and Scholarship
http://www.umich.edu/~isworld/reshome.html: extensive references for Qualitative
(Intensive) Research, and MIS Survey Research.
2. Information Systems Ethics: Under ISWORLD Teaching and Learning, Information Systems
Ethics http://www.siu.edu/departments/coba/mgmt/iswnet/isethics/
7
Database Technology
Apers, P. M. G. (1988, September). Data Allocation in Distributed Database Systems. ACM
TODS, 13 (3), 263-304.
Batini, C., Lenzerini, M. & Navathe, S.B. (1986, December). A Comparative Analysis of
Methodologies for Database Schema Integration. ACM Computer Surveys, 18 (4), 323-364.
Chen, P. (1976, March). The Entity-Relationship Model: Toward a Unified View of Data. ACM
Transactions on Database Systems, 1 (1), 9-36.
Frawley, W. J., Pietesky-Shapiro, G., & Mathetheus, C. J. (1991) Knowledge Discovery in
Databases: An Overview. In Piatetsky-Sharpiro, G. & Frawley, W. J. (Eds.), Knowledge
Discovery in Databases (pp. 1-30), Cambridge, MA: MIT Press.
Hull, R. & King, R. (1987, September). Semantic Database Modeling: Survey, Applications, and
Research Issues. ACM Computing Survey 19 (3), 201 – 260.
Lewandowski, S. M. (1998, March). Frameworks for Component-Based Client/Server
Computing. ACM Computing Surveys, 30 (1), 3-27.
Sheth, A. P. & Larson, J. A. (1990, September). Federated Database Systems for Managing
Distributed, Heterogeneous, and Autonomous Databases. ACM Computing Surveys, 22 (3),
183-236.
The List of Key People in MIS - Database Technology
Name
Research Area
E-mail
School
Jay
Nunamak
er
Arie
Segev
Bezalel
Gavish
Univ. of
Arizona
Group decision support systems
Systems analysis and design
Software for eliciting requirements
UC
Information management
Berkeley Electronic Commerce
Distributed Object Technologies &
Applications
Vanderbilt Management and application of
University technology in business
Latest developments in computers,
telecommunications, and other hightechnology instruments
8
NUNAMAKER@BPA.ARIZONA.E
DU
http
edu
SEGEV@HAAS.BERKELEY.EDU
http
~seg
gavishb@ctrvax.Vanderbilt.Edu
Name
Research Area
E-mail
School
Amit
Basu
Lynda
Applegat
e
Izak
Benbasat
Bob
Zmud
Haim
Mendelso
n
Charles
H.
Kriebel
Erik
Brynjolfs
son
Andrew
B.
Vanderbilt Knowledge based systems
University Decision support systems
Database management systems
Workflow Management
Electronic Commerce
Harvard IT and business transformation
Business Computer supported cooperative work
School
IT and globalization
University Analysis of human-computer
of British interaction
Columbia Augmenting decision making with
computerized support
Research methodologies for IS studies
Explanations in Expert systems
It-Business Linkage
University Information technology (IT)
of
management
Oklahoma The diffusion (and infusion) of
technological and managerial
innovations
The effects of computer- mediated
communication systems on
organizational design and performance.
Stanford Information systems economics
University Securities markets
The computer industry
Carnegie- Economics of information systems and
Mellon
technology
University Evaluation of IT and impact on
business value
Software engineering and process
development
MIT
Information technologies and
productivity
Internet applications for pricing,
organizational change
University Decision support systems
of Texas, Electronic commerce
Austin
Economics of information systems
Whinston
Ted
Stuart
9
BASUA@CTRVAX.VANDERBILT.
EDU
http
du/O
lapplegate@hbs.edu
http
ega
IZAK.BENBASAT@COMMERCE.U http
BC.CA
.ca/
enb
rzmud@ou.edu
HAIM@HAIM.STANFORD.EDU
ck04@andrew.cmu.edu
erikb@mit.edu
http
ABW@UTS.CC.UTEXAS.EDU
http
abw
Name
Research Area
E-mail
School
Salvatore
T.
March
Stuart E.
Madnick
Sirkka
Jarvenpaa
Al
Havner
Peter
Chen
Hasan
Pirkul
Omar A.
El Sawy
Wanda
Orlikows
ki
Les
Brown
M. Lynne
Markus
University Automated tools for the design of
of
databases
Minnesota Data modeling and system
development interface
Computer support for groups
MIT
Intelligent interpretation of information
Systematic design
methodology/software project
management
Composite information systems
University
of Texas,
Austin
University
of South
Florida
Louisiana Models of Data Representation for
State
Databases
University Office Automation
Knowledge-based Systems
University Distributed computer systems
of Texas Physical database design
at Dallas Location and allocation problems and
heuristics
University Knowledge sharing and business
of
process redesign
Southern Electronic value chains
California IS for managerial scanning in messy
environments
MIT
Information technology and
organizational change
Social and cultural implications of
information technology
Systems development and CASE tools
SMARCH@CSOM.UMN.EDU
Claremont Information technology, organizational
Graduate change, and reengineering
University Systems policy and administration
Cooperative work and communication
Enterprise software
M.Lynne.Markus@cgu.edu
10
SMADNICK@MIT.EDU
sjarvenpaa@mail.utexas.edu
ahevner@coba.usf.edu
chen@bit.csc.lsu.edu
http
epar
vne
http
y/pc
hpirkul@utdallas.edu
elsawy@bus.usc.edu
WANDA@MIT.EDU
http
y/m
Name
Research Area
E-mail
School
Starr
Roxanne
Hiltz
New
Jersey
Institute
of
Technolog
y
Christine
L.
Borgman
UCLA
Computer-Mediated Communication
Computer-Supported Cooperative
Work
Group Decision Support Systems
Human-Computer Interaction
Technology and Society \ Computers
and Education
Information Systems Evaluation
Methodologies
Digital libraries and technology and
policy issues in the development of
computing networks
Automated library services in Central
and Eastern Europe.
roxanne@eies.njit.edu
http
cborgman@ucla.edu
http
lis.g
lty/c
Process Modeling
1. Booch, G. “Object-Oriented Development” IEEE Transactions on Software Engineering, 12,
2, 1986, pp. 211-220.
2. Chen, P. P. S. “The Entity-relationship Model – Toward a Unified View of Data”
ACM Transactions on Database System, 1, 1, pp. 9-36.
3. Curtis, B., Kellner, M., Over, J., “Process Modeling” Communications of The ACM, 35, 9,
1992.
4. Malone, T. W. et al., “Toward a Handbook of Organizational Processes” Sloan School of
Management Working Paper, 1997.
5. Rumbaugh, J., Blaha, M., Premerlani, W., Eddy, F., Lorensen, W. Object-oriented Modeling
and Design, Prentice Hall, 1990.
6. Scheer, A. W. Business Processes Engineering. Springer-Verlag, 1994.
Key People:
Booch and Rumbaugh are key people in object-oriented modeling. They are now at Rational
Software Corporation. In 1995 they proposed the Unified Modeling Language (UML).
Chen is the person who introduced Entity-Relationship model. This modeling method is very
popular in data modeling area.
Curtis is a professor who is now at CMU’s Software Engineering Institute.
11
Malone is a professor at MIT’s Sloan School of Management.
Scheer is German professor who is famous for modeling ERP system, such as SAP/R3.
Business Process Reengineering
1. Davenport, T. H., Process Innovation: Reengineering Work through Information Technology,
Harvard Business School Press, Boston, Massachusetts, 1993.
2. Davenport, T. H., Beers, M. C. “Managing Information about Processes” Journal of
Management Information Systems, 1995, pp. 57-80.
3. Davenport, T. H., Short, J. E. “The New Industrial Engineering: Information Technology and
Business Process Redesign” Sloan Management Review, Summer 1990, pp. 11-27.
4. Davenport, T. H., Stoddard, D. B. “Reengineering: Business Change of Mythic Proportions?”
MIS Quarterly, June 1994, pp. 121-127.
5. Hammer, M., Champy, J. Reengineering the Corporation, HarperCollins Publishers, New
York, 1993.
Key People:
Hammer and Champy are among the first persons who introduce the concepts and theories of
Business Process Reengineering.
Davernprot is partner at Ernst & Young’s Center for Information Technology and Strategy in
Boston, and teaches at Boston University’s School of Management.
12
Software Development and Engineering
Key Papers
Alonso, G., Agrawal, D., El Abbadi, A., Kamath, M., & et al.
Advanced Transaction Models In Workflow Contexts.
Proceedings of the 12th International Conference on Data
Engineering .
Alonso, G., Gunthor, R., Kamath, M., Agrawal, D., & et al.
(1996). Exotica/FMDC: A Workflow Management System For
Mobile and Disconnected Clients. Distributed and Parallel
Databases, 4(3), 229-247.
Berman, O., Larson, R. C., & Pinker, E. (1997). Scheduling
Workforce And Workflow In a High Volume Factory. Management
Science, 43(2), 158-172.
Bussler, C. J. (1996). Specifying Enterprise Processes With
Workflow Modeling Languages. Concurrent Engineering:
Research and Applications, 4.
Bussler, C. J., & Jablonski, S. An Approach to Integrate
Workflow Modeling and Organization Modeling In an
Enterprise. Proceedings of the 3rd IEEE Workshop on Enabling
Technologies: Infrastructure for Collaborative Enterprises
.
DeMarco, T. (1979). Structured Analysis and System
Specification. Prentice-Hall.
Ellis, C. A., & Nutt, G. J. (1980). Office Information Systems
and Computer Science. ACM Computing Surveys, 12(1).
Fagan, M. E. (1976). Design and code inspections to reduce
errors in program development. IBM Systems Journal.
Georgakopoulos, D., Hornick, M., & Sheth, A. (1995). An Overview
of Workflow Management: From Process Modeling To Workflow
Automation Infrastructure. Distributed and Parallel
Databases, 3(2), 119-153.
Humphrey, W. S. (1995). A Discipline For Software Engineering.
Reading, Massachusetts: Addison-Wesley Publishing Company.
Jablonski, S. (1995). On the Complementarity of Workflow
Management and Business Process Modeling. SIGOIS Bulletin,
16(1), 33-38.
13
Jaeger, T., & Prakash, A. Management and Utilization of
Knowledge for The Automatic Improvement of Workflow
Performance. Conference on Organizational Computing Systems
.
Koksal, P., Arpinar, S. N., & Dogac, A. (1998). Workflow History
Management. SIGMOD Record, 27(1), 67-75.
Kumar, A., & Zhao, J. L. (1998). Dynamic Routing and Operational
Controls in Workflow Management Systems. Management
Science.
Leymnn, F., & Roller, D. Building a Robust Workflow Management
System with Persistent Queues and Stored Procedures. 14th
International Conference on Data Engineering .
Liu, L., & Pu, C. Methodical Restructuring of Complex Workflow
Activities. Proceedings of the 14th International Conference
on Data Engineering .
Lochovsky, F. H. (1983). Improving Office Productivity: A
Technology Perspective. Proceedings of the IEEE, 71(4),
512-519.
Mahling, D. E., Craven, N., & Croft, W. B. (1995). From Office
Automation to Intelligent Workflow Systems. IEEE Expert,
10(3), 41-47.
Mohan, C., Agrawal, D., Alonso, G., El Abbadi, A., & et al.
(1995). Exotica: A Project on Advanced Transaction
Management and Workflow Systems. SIGOIS Bulletin, 16(1),
45-50.
Nutt, G. J. (1996). The Evolution Towards Flexible Workflow
Systems. Distributed Systems Engineering, 3(4), 276-294.
Paulk, M. C., B. Curtis, & et al. (July, 1993). Capability
maturity model, version 1.1. IEEE Software, 18-27.
Pressman, R. S. (1997). Software Engineering: A Practitioner's
Approach. McGraw-Hill. (Chapter 2: Software Engineering
Methods)
Swenson, K. D., & Irwin, K. Workflow Technology: Tradeoffs for
Business Process Re-Engineering. Conference on
Organizational Computing Systems .
Wodtke, D., Weissenfels, J., Weikum, G., Dittrich, K., & et al.
The MENTOR Workbench For Enterprise-Wide Workflow
14
Management. ACM SIGMOD International Conference on
Management of Data.
Yourdon, E., & Constantine, L. (1979). Structured Design.
Prentice-Hall.
Key People
Amit Sheth - Research interests include Interoperable
Information Systems (esp. Transactional Workflow Management),
Global Information Evolving collaboration technologies,
Electronic/Information Commerce, Ontology/Context/Semantics,
Schematic Heterogeneity, Federated Database Systems, Multidatabase Consistency/Interdependent Data, Data Quality, Schema
Integration. He is currently director of the Large Scale
Distributed Research Lab and associate professor of Computer
Science at UGA, as well as an adjunct associate professor in the
College of Computing at the Georgia Tech.
Dimitrios Georgakopoulos - He was a Principal Member of
Technical Staff at GTE Laboratories and the initiator of the
Workflow Management Infrastructure project. He led the
development of the Word Wide Workflow system for enterprise-wide
and multi-organizational business process management. He played
a principal role in introducing workflow and distributed object
technologies to GTE business units, and received an Excellence
award for his work. He is Currently a Senior Member of Technical
Staff and the technical leader of the Collaboration Management
Infrastructure Project (CMI) at MCC.
Gerhard Weikum - Research interests include parallel and
distributed information systems database optimization and
performance evaluation, workflow management, transaction
processing and multimedia information management. He is
currently the head of the Database and Information Systems Group
and a professor at the University of the Saarland, Germany
Christoph Bussler - Research interests include Organizational
Policy Management in Workflow Management Systems, Generic
Workflow Models, Architecture of High Performance Workflow
Management Systems and Mobility Aspects of Workflow Management.
He is currently a researcher at Boeing, USA.
Gustavo Alonso - Research interests include distributed and
parallel data management systems: transaction processing,
database applications, workflow management systems, and Ecommerce issues such as system architecture, scalability, high
performance processing, reliability, availability, fault
15
tolerance, and new applications. He is currently the head of
the Information and Communication Systems Research Group and a
professor at ETH in Zurich, Switzerland.
C. Mohan - Research interests include all aspects of
transaction, database and workflow management. He works for
IBM, but is presently on a 1 year sabbatical at the French
government's computer science research institute called INRIA at
Rocquencourt outside Paris
Gary Nutt - Research interests include distributed systems,
supporting group work with multimedia and distributed systems,
highly responsive operating systems, modeling and performance,
performance visualization, collaboration technology and group
workflow models and systems. He is currently a professor at the
University of Colorado.
Clarence (Skip) Ellis - Research interests include Workflow
Technology, Groupware, Cognitive Science (Group cognition),
Computer Supported Cooperative Work, Object Oriented Systems,
Systems Modeling, Databases, Group User Interfaces and
Distributed Systems. He is currently a professor at the
University of Colorado.
W. Bruce Croft - Research interests include formal models of
retrieval for complex, text-based objects, text representation
techniques, the design and implementation of text retrieval and
routing systems, and user interfaces. He is currently Director
of the Center for Intelligent Information Retrieval and a
professor at the University of Massachusetts.
Tom DeMarco - Has made outstanding contributions to the theory
and practice of software development, through his writing,
lecturing, and consulting. From his early seminal work on
structured analysis, to his later contributions in the areas of
software metrics and team building, Mr. DeMarco has established
himself as a pioneer and leader in the software profession. In
1986, Mr. DeMarco was awarded the J.D. Warner Prize for
"lifetime contribution to the information sciences." His most
recent publications are The Deadline: A Novel About Project
Management, Why Does Software Cost So Much? (and other puzzles
of the information age) and PEOPLEWARE: Productive Projects and
Teams (the latter with co-author Tim Lister), all published by
Dorset House. He also wrote the ground-breaking text Structured
Analysis and System Specification, the popular Controlling
Software Projects: Management, Measurement and Estimation and
more than 100 articles and papers. He is a member of the IEEE
16
Software Editorial Board, and was chosen (along with Dr. Barry
Boehm) to serve as guest editor for that journal's May, 1997
Special Issue on Risk Management. Mr. DeMarco is a Principal
Member of The Atlantic Systems Guild, a systems think tank and
consulting firm with offices in New York and London. He makes
his home and headquarters in Camden, Maine.
Grady Booch - Chief Scientist at Rational. He has been with the
company since its foundation in 1980. Booch has pioneered the
development of object-oriented analysis and design methods. His
work centers primarily around complex software systems. Booch is
the author of four books, ncluding "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.
Michael Fagan has had 20 years of experience as a line manager
of software development, engineering development, and
manufacturing. In addition, he was: manager of programming
methodology for IBM's DP Product Group (Worldwide); the first
software senior technical staff member in IBM's T.J. Watson
Research Laboratory; a member of the Corporate Technology Staff;
and, one of the founder members of the IBM Quality Institute.
After creating the Inspection Process in 1972, he continued
refining the methodology, incorporating Formal Process
Definition, and reinforcing the Continuous Process Improvement
aspect of the Fagan Inspection Process. In 1979, IBM awarded him
the largest individual Corporate Achievement Award for creating
the INSPECTION PROCESS and promoting its implementation in IBM's
laboratories around the world and in industry. Since 1989, when
he formed Michael Fagan Associates, he has continued to refine
the methodology and has also found ways to help facilitate its
very rapid implementation in more than 60 organizations. In
fact, most of these organizations have produced impressive
results in the product or release on which they were working
starting the day after completing training. (The products they
developed spanned a range that included systems programs,
database programs, applications, hardware designs, systems and
applications requirements, 4GL and Object Oriented Tools.) The
methodology developed by Michael Fagan is credited with
dramatically reducing the number of defects in software and
hardware products, increasing the feature content per release,
shortening cycle time, increasing customer satisfaction,
improving development processes, accelerating SEI/CMM maturity
in organizations, and significantly reducing costs!
17
Dr. Pressman specializes in helping companies establish
effective software engineering practices. He is the developer of
Process Advisor, the industy's first self-directed software
process improvement product and Essential Software Engineering,
a comprehensive video curriculum. Dr. Pressman is the author of
six books and many technical and management articles. His book,
Software Engineering: A Practitioner's Approach (McGraw-Hill ,
4th ed., 1997), is the world's most widely used software
engineering textbook. He is on the Editorial Boards of American
Programmer and IEEE Software and is Series Advisor for the
McGraw-Hill Systems Design and Implementation Series. He is a
member of the IEEE, ACM and Tau Beta Pi.
Watts S. Humphrey – Employed by the Software Engineering
Institute (SEI) at Carnegie Mellon University. Formerly
Director of the Software Process Program at the SEI, Humphrey
was responsible for developing improved software engineering
process methods. He has continued to work closely with software
engineers in industry and government, helping them to implement
these improved methods. Before joining the SEI, Humphrey was
with IBM for 27 years in various technical and management
positions. He is a Fellow of the SEI and the IEEE, a member of
the ACM, a past member of the Malcolm Baldridge national Quality
Award Board of Examiners, and a holder of five issued U.S.
patents. He lives in Sarasota Florida.
Mark Paulk – A longtime member of the Software Engineering
Institute (SEI) at Carnegie Mellon University. Paulk was one of
the major contributors to the development of the Capability
Maturity Model (CMM).
18
Technology
Dan O'Leary University of Southern California
Tom Malone Massachusetts Institute of Technology
Tom Davenport Boston University
V. Dhar
New York University
Chen, H., Titkova, Orwig, O. R., & Nunamaker, J. F. (1998).
`Information Visualization for Collaborative Computing, IEEE Computer,
forthcoming.
Nii. H. P. (1986). Blackboard systems: Blackboard applications systems,
blackboard systems from a knowledge engineering perspective. AI Magazine,
7(3): 38-53.
Tversky, A. & Kahneman, D. (1974). Judgment under uncertainty:
Heuristics and biases. Science, 1124-1131.
Quinlan, J. D. (1983) Learning efficient classification procedures
and their applications to chess end games. In Michalshi, R. S.,
Carbonell,J. G., & Mitchell, T. M., Machine Learning, An
Artificial Intelligence Approach, 463-482, Tioga, Palo Alto, CA, 1983.
Lippmann, R. P. (1987) An introduction to computing with neural
networks. IEEE Acoustics Speech and Signal Processing Magazine.
4(2):4-22.
Frawley, W. J., Pietesky-Shapiro, G., & Mathetheus, C. J. (1991).
Knowledge discovery in databases: an overview. In Piatetsky-Sharpiro, G. and
Frawley W. J., Knowledge Discovery in Databases, 1-30, MIT Press, Cambridge, MA, 1991.
Maes, P. (1994). Agents that reduce work and information
overload. CACM, 37(7):30-40.
Bowman, C. M., Danzig, P B., Manber, U., & Schwatrz., F. (1994)
Scalable Internet resource discovery: research problems and approaches.
CACM, 37(8): 98-107, August, 1994.
Group Support Systems
Researchers
Jay F. Nunamaker, Jr.
 The University of Arizona
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Regents Professor of MIS and Computer Science, 1994 - Present.
Director (1985 to Present) and founder of the Center for Management of Information (CMI),
a research center to study collaboration technology and decision support
Current research interests include computer supported collaboration and decision support to
improve productivity and communication.
jnunamaker@cmi.arizona.edu
Center for the Management of Information
University of Arizona
McClelland Hall, Room 430GG
Tucson, Arizona 85721
(520) 621-4105 Voice
(520) 621-3918 Fax
Douglas R. Vogel
 The University of Arizona
 Associate Professor, Dept. of MIS, 1992-Present.
 Current research interests include integrating technology into distributed educational
contexts. He has additionally been particularly active in the development, facilitation, and
evaluation of University of Arizona GroupSystems.
 dvogel@cmi.arizona.edu
 Center for the Management of Information
University of Arizona
McClelland Hall, Room 114
Tucson, Arizona 85721
(520) 626-2644 Voice
(520) 621-2641 Fax
Robert O. Briggs
 The University of Arizona
 Research Fellow, The Center for the Management of Information
 Current esearch interests include technology-supported learning, and technology for group
productivity
 bob@cmi.arizona.edu
 Center for the Management of Information
University of Arizona
McClelland Hall, Room 429
Tucson, Arizona 85721
(520) 621-2133 Voice
(520) 621-2433 Fax
Alan R. Dennis
 The University of Georgia
 Associate Professor, Department of Management
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
Current research interests include computer-supported group brainstorming and decision
making, the design of web-based technologies to support collaborative work, and business
process reengineering.
adennis@uga.cc.uga.edu
Department of Management
Terry College of Business
The University of Georgia
Athens GA 30602
(706) 542-3902 Voice
(706) 542-3743 Fax
Joseph S. Valacich
 Washington State University
 The George and Carolyn Hubman Distinguished Professor in Information Systems and
Associate Professor of Information Systems, College of Business and Economics
 Current research interest include group support systems, organizational impacts of
information systems, systems analysis and design, and distance Learning
 jsv@wsu.edu
 College of Business and Economics
Todd Hall 240D
Washington State University
Pullman, WA 99164-4736
 (509) 335-1112 Voice
 (509) 335-7736 Fax
Gerardine DeSanctis
 Duke University
 Professor of Management
 Current research interests include the design of systems to support managerial decision
making and the effects of information systems use on individuals, groups and organizations
 gd@mail.duke.edu
 Duke University
Box 90120
Durham, NC 27708-0120
 (919) 660-7848 Voice
 (919) 681-6245 Fax
R. Brent Gallupe
 Queens University
 Professor of Management Information Systems
 Director of the Queen's Executive Decision Centre
 Current research interests include electronic brainstorming, the history of information
systems, information technology, and management information systems.
 gallupeb@qucdn.queensu.ca
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School of Business
Queen's University
Kingston, Ontario
K7L 3N6
(613) 545-2361 Voice
(613) 545-6589 Fax
Papers
Briggs, R. O. (1993). Focus Theory: An Explanation of Group Productivity For Developers and
Users of Electronic Meeting Systems. , University of Arizona, Tucson, AZ.
Briggs, R. O., Ramesh, V., Romano, N. C., & Latimer, J. (1995). The Exemplar Project: Using
Group Support Systems to Improve the Learning Enviroment. Journal of Educational
Technology Systems, 23(3), 277-291.
Clawson, V. K., Bostrom, R. P., & Anson, R. (1993). The Role of the Facilitator in ComputerSupported Meetings. Small Group Research, 24(4), 547-565.
Connolly, T., Jessup, L. M., & Valacich, J. S. (1990). Effects of Anonimity and Evaluative Tone
on Idea Generation in Computer-Mediated Groups. Management Science, 36(6), 689703.
Dennis, A. R., George, J. F., Jessup, L. M., Nunamaker, J. F., & Vogel, D. R. (1988).
Information Technology to Support Electronic Meetings. MIS Quarterly, 12(4), 591-624.
Dennis, A. R., Heminger, A. R., Nunamaker, J. F., & Vogel, D. R. (1990a). Bringing Automated
Support to Large Groups: The Burr-Brown Experience. Information & Management, 18,
111-121.
Dennis, A. R., Nunamaker, J. F., & Vogel, D. R. (1991). A Comparison of Laboratory and Field
Research in the Study of Electronic Meeting Systems. Journal of Managment
Information Systems, 7(3), 107-135.
Dennis, A. R., Valacich, J. S., & Nunamaker, J. F. (1990b). An Experimental Investigation of the
Effects of Group Size in an Electronic Meeting Environment. IEEE Transactions on
Systems, Man, and Cybernetics, 20(5), 1049-1057.
DeSanctis, G., & Gallupe, R. B. (1987). A Foundation for the Study of Group Decision Support
Systems. Management Science, 33(5), 589-609.
Gallupe, R. B., Dennis, A. R., Cooper, W. H., Valacich, J. S., Bastianutti, L. M., & Nunamaker,
J. F. (1992). Electronic Brainstorming and Group Size. Academy of Management Journal,
35(2), 350-369.
Grohowski, R., McGoff, C., Vogel, D., Martz, B., & Nunamaker, J. (1990). Implementing
Electronic Meeting Systems at IBM: Lessons Learned and Success Factors. MIS
Quarterly, 14(4), 369-383.
King, W. R., & King, T. S. H. (1996). Key Dimensions of Facilitators and Inhibitors for the
Strategic Use of Information Technology. Journal of Management Information Systems,
12(4), 35-53.
Nunamaker, J., Vogel, D., Heminger, A., Martz, B., Grohowski, R., & McGoff, C. (1989).
Experiences at IBM with Group Support Systems: A Field Study. Decision Support
Systems, 5(2), 183-196.
Nunamaker, J. F. (1992). Articles from Workgroup Computing, Reprinted from Corporate
Computing : Ziff-Davis.
22
Nunamaker, J. F., Briggs, R. O., Mittleman, D. D., Vogel, D. R., & Balthazard, P. A. (1997).
Lessons from a Dozen Years of Group Support Systems Research: A Discussion of Lab
and Field Findings. Journal of Management Information Systems, 13(3), 163-207.
Nunamaker, J. F., Chen, M., & Purdin, T. D. M. (1991a). Systems Development in Information
Systems Research. Journal of Management Information Systems, 7(3), 89-106.
Nunamaker, J. F., Dennis, A. R., Valacich, J. S., & Vogel, D. R. (1991b). Information
Technology for Negotiating Groups: Generating Options for Mutual Gain. Management
Science, 37(10), 1325-1346.
Nunamaker, J. F., Dennis, A. R., Valacich, J. S., Vogel, D. R., & George, J. F. (1991c).
Electronic Meeting Systems to Support Group Work. Communications of the ACM,
34(7), 40-61.
Post, B. Q. (1992). Building the Business Case for Group Support Technology. Paper presented
at the Twenty-Fifth International Conference on System Sciences, Kauai, HI.
Saffo, P. (1990). Same-Time Same-Place Groupware. Personal Computing.
Shepherd, M. M., Briggs, R. O., Reinig, B. A., Yen, J., & Nunamaker, J. F. (1996). Invoking
Social Comparison to Improve Electronic Brainstorming: Beyond Anonymity. Journal of
Management Information Systems, 12(3), 155-170.
Valacich, J. S., Mennecke, B. E., Wachter, R., & Wheeler, B. C. (1993). Computer-Mediated
Idea Genteration: The Effects of Group Size and Group Heterogeneity. Paper presented
at the Twenty-Sixth International Conference on System Sciences, Wailea, HI.
Zigurs, I., Poole, M. S., & DeSanctis, G. L. (1988). A Study of Influence in Computer-Mediated
Group Decision Making. MIS Quarterly, 12(4), 625-643.
23
Human Computer Interaction
Key People in HCI
Dan R. Olsen Jr. (CMU) Director of Human Computer Interaction Institute
Interests include software architectures for user interfaces. In particular, studying how to
structure user interface software so that pervasive capabilities are supported.
John R. Anderson (CMU) Professor of Computer Science
Research is to understand how people organize knowledge that they acquire from their diverse
experiences to produce intelligent behavior. The concern is very much with how it is all put
together and this has led to the focus on what are called "unified theories of cognition." A unified
theory is a cognitive architecture that can perform in detail a full range of cognitive tasks.
Gary Marchionini (UNC) Professor of School of Information and Library Science.
Research interests: Information seeking, human-computer interaction, digital libraries,
information design, information policy
Ben Shneiderman (UMD) Professor of Computer Science and Head of the Human-Computer
Interaction Laboratory
Research Interests: Human-computer interaction, user interface design.
Dr. Kent L. Norman (UMD) Professor of Psychology
Interests include cognitive psychology, human/computer interaction, and the design of electronic
educational environments. Additionally, interested in models of judgment and decision making
and have applied these to the behavior of computer interfaces.
Thomas P. Moran (Xerox Parc)
Research includes early work on the theoretical foundations of human-computer interaction,
development of several HCI analysis tools and theoretical frameworks, and development of
several innovative interactive systems.
Marti Hearst (UC-Berkeley) Professor of School of Information Management & Systems
Current research interests focus on user interfaces and robust language analysis to build
information access systems, and on furthering our understanding of how people use and
understand such systems. The field of Information Access concerns helping people find, use,
understand, and create the information they need, often using computer systems as tools. Text
analysis and user interface technology should be combined with an understanding of how users
work with information and computer tools when building systems to support information access.
I also plan to begin studying the interdependence of the social and the technical in information
systems.
Jakob Nielsen
Until July 1998 he was a Sun Microsystems Distinguished Engineer and the company's Web
usability guru. Dr. Nielsen coined the term "discount usability engineering" and has invented
several usability techniques for fast and cheap improvements of user interfaces, including
24
heuristic evaluation. 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.
Jock D. Mackinlay (Xerox Parc) Information Sciences and Technologies Laboratory (ISTL)
User interface research in the areas of: Information Visualization, 3D User Interfaces, Automatic
Presentation
Gary Perlman
Research interests include several information sciences and their applications: information
management (hypermedia and information retrieval), computer science (software engineering
and user interfaces), experimental psychology (cognitive engineering and human factors),
statistics (measurement and statistical computing).
William Buxton (Alias | Wavefront Inc.) Chief Scientist
Bill Buxton is a designer and researcher specializing in human aspects of technology, humancomputer interaction, and technology mediated collaborative work (Telepresence). He is Chief
Scientist at Alias | Wavefront Inc., as well as its parent compny, Silicon Graphics Inc. (SGI), ,
and an Associate Professor in the Department of Computer Science at the University of Toronto,
where his research is mainly sponsored by the Information Technology Researh Institute of
Ontario (ITRC) and British Telecom Laboratories. While "full-time" at Alias |Wavefront and
SGI, Buxton maintains an office at the University and continues to supervises graduate students.
Terry Winograd (Stanford) Professor of Computer Science
Professor Winograd's focus is on developing the theoretical background and conceptual models
for designing human-computer interaction. He is a principal investigator on the Stanford Digital
Libraries Project, developing models that can provide information collections and services in an
integrated framework from a wide base of heterogeneous distributed materials. He directs the
Project on People, Computers, and Design and is developing teaching programs in HumanComputer Interaction Design.
Judy S. Olson (University of Michigan) Professor of Information Systems and Professor of
Psychology
Prior to joining the Michigan Business School, she was on the faculty of the Department of
Psychology at Michigan and served as a technical supervisor for human factors in systems
engineering at Bell Laboratories. Her research interests are human-computer interaction relating
to the design and evaluation of software for human problem solving in business, both in
individual settings and group work.
Gary M. Olson (University of Michigan) Interim Dean and Professor
His current research interests are in the areas of applied cognitive science, particularly humancomputer interaction and computer-supported cooperative work. Specifically, he is working on
topics in the area of computer support for collaborative activities, particularly when conducted at
a distance. He has conducted both laboratory and field studies of teams carrying out various
25
forms of complex intellectual activities. A major current interest is the design and evaluation of
collaboratories to support distributed science and engineering.
George Furnas (University of Michigan)
Came to Michigan after 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. 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.
Readings
Baecker, R., Grudin, J., Buxton, W., Greenburg, S. (Eds). Readings in human-computer
interaction: Towards the year 2000. 2nd Ed. San Francisco, Morgan Kaufmann. Contains many
great articles pulled from books and journals.
Card, S. K. (1996). Visualizing retrieved information: A survey. Computer Graphics &
Applications, 63-67.
Card, S., Moran, T., & Newell, A. (1983). The psychology of human-computer
interaction. Hillsdale, NJ: Lawrence Erlbaum. Chapters 2 and 5 discuss the Model Human
Processor and the GOMS model.
Carroll, J. M. (1982). The adventure of getting to know a computer. IEEE Computer,
15(11), 49-58.
Daft, R. L. & Lengel, R. H. (1986). Organiztional information requirements, media
richness and structural design, Management Science, 32(5), 554-571.
Furnas, G. W., Landauer, T. K. Gomez, L. M. & Dumais, S. T. (1987). The vocabulary
problem in human-system communication. Communications of the ACM, 30(11), 964-971.
Laudauer, T. K. (1995). The troubles with computers: Usefulness, usability, and
productivity. MIT Press, Cambridge, MA.
Pirolli, P. & Card, S. (1995). Information foraging in formation access environments.
CHI ’95: ACM Conference on Human Factors in Software. ACM: NY pp 51-58.
Nielsen, J. (1992). The usability engineering life cycle. IEEE Computer, 25(3), 12-22.
Shneiderman, B. (1993). Direct manipultation: A step beyong programming language.
IEEE Computer, 57-69.
Winograd, T. (1988). A language/action perspective on the design of cooperative work.
Human-Computer Interaction, 3(1) 3-30.
26
Organization Behavior
Individual Judgement and Decision Making
Anthologies
Bazerman, M. (1994). Judgement in managerial decision making. Third edition. New York:
Wiley.
Plous, S. (1993). The Psychology of Judgment and Decision Making. New York: McGraw-Hill.
Simon, H.A. (1957). Models of man. New York: Wiley.
Simon, H.A. (1982), "Models of Bounded Rationality, Vols. 1 and 2." The MIT Press, London.
Theory Papers and Books
Brockner, J. (1992). The escalation of commitment to a failing course of action: Toward
theoretical progress. Academy of Management Review, 17: 39-61.
Dawes. R. (1988). Rational choice in an uncertain world. New York: Harcourt, Brace,
Jovanovich.
Fischoff, B. (1982). Debiasing. In D. Kahneman, P. Slovic, and A. Tversky (Eds.), Judgement
under uncertainty: Heuristics and Biases. Cambridge, Mass.: Cambridge University Press.
Hardin, G. (1968). The tragedy of the commons. Science 162, 1243-1248.
Kahneman, D. & Tversky, A. (1979). Prospect theory: An analysis of decisions under risk.
Econometrica. 47:263-291.
March, J. & Simon, H. (1958). Organizations. New York: Wiley.
Mintzberg, H. (1975). The nature of managerial work. New York: Harper and Row.
Raiffa, H. (1982). The art and science of negotiation. Cambridge, Mass.: Harvard University
Press.
Slovic, P. (1987). Perception of risk. Science, 236, 280-285.
Staw, B. (1981). The escalation of commitment to a course of action. Academy of Management
Review 6, 577-587.
Thaler, R (1980). Toward a positive theory of consumer choice. Journal of Economic Behavior
and Organization, 1:39-60.
27
Empirical Papers
Arkes, H. & Blumer, C. (1985). The psychology of sunk costs. Organizational Behavior and
Human Decision Processes, 35:124-140.
Bar-Hillel, M. (1973). On the subjective probability of compound events. Organizational
Behavior and Human Performance, 9:396-406.
Kahneman, D. & Tversky, A. (1984). Choices, values, and frames. American Psychologist.
39:341-350.
Laughhunn, D. & Payne, J. (1984). The impact of sunk outcomes on risky choice behavior.
INFOR Canadian Journal of Operations Research and Information Processing, 22:151-181.
Slovic, P. & Lichtenstein, S. (1971). Comparison of Bayesian and regression approaches in the
study of information processing in judgement. Organizational Behavior and Human
Performance, 6:649-744.
Staw, B.M. (1976). Knee-deep in the big muddy: A study of escalating commitment to a chosen
alternative. Organizational Behavior and Human Performance, 16:27-44.
Thaler, R. (1985). Using mental accounting in a theory of purchasing behavior. Marketing
Science 4, 199-214.
Thaler, R. & Johnson, E. (1990). Gambling with the house money and trying to break even: The
effects of prior outcomes on risky choice. Management Science, 36:643-660.
Tversky, A. & Kahneman, D. (1974). Judgement under uncertainty: Heuristics and biases.
Science 185, 1124-1131.
Tversky, A. & Kahneman, D. (1981). The framing of decisions and the psychology of choice.
Science 211: 453-463.
Key People in Individual Judgement and Decision Making
Hal Arkes – Research interests are medical decision making, "colloquial economics", sunk costs,
windfall gains, and the hindsight effect. Currently, Program Director, National Science
Foundation - Decision, Risk, and Management Science.
Jonathan Baron - Research interests include the maximization of utility (good), how to measure
utility for purposes of cost-effectiveness analysis, and in everyday intuitions that stand in the
way of utility maximization, particularly moral intuitions. Currently at the University of
Pennsylvania.
Egon Brunswik - (1903-1955)
28
One of several outstanding psychologists who came to the United States from Europe shortly
before World War II. Developed Social Judgment Theory and the Lens Model.
Robin Dawes - Current research spans five areas: intuitive expertise, human cooperation,
retrospective memory, methodology and United States AIDS policy. Currently at CarnegieMellon University.
Ward Edwards - Director of the Social Science Research Institute and Professor of Psychology
and of Industrial and Systems Engineering at the University of Southern California. Prior to
going to USC in 1973, he spent 15 years at the University of Michigan as Professor of
Psychology, Head of the Engineering Psychology Laboratory, and Associate Director of the
Highway Safety Research Institute. Research interests have been in the fields of behavioral
decision theory, decision analysis, and the subjective expected utility maximization model.
Baruch Fischoff - Best known for his publication entitled “Behavioral Research Approaches to
Reducing Product Liability Risks”. A cognitive psychologist and currently at Carnegie-Mellon
University.
Ken Hammond - Fields of interest include expert judgment, effects of stress on cognition, and
conflict resolution in public policy making. He has done basic and applied research in these areas
and has consulted for federal, state, and local governments and for multinational corporations.
His most recent articles have been on dynamic tasks, conflict resolution, and modes of cognition.
Professor Emeritus at the University of Colorado.
Daniel Kahneman – Developed Prospect Theory along with Amos Tversky. Awards include:
Distinguished Scientific Contribution Award of the American Psychological Association (1982)
and the Warren Medal of the Society of Experimental Psychologists (1995), and the Hilgard
Award for Career Contributions to General Psychology (1995). Currently at Princeton
University.
Oskar Morgenstern - (1902 - 1977) Best known for his work with John von Neumann on the
theory of games. He provided much of the economic analysis on the greater generality of
"strategic behavior" over "Robinson-Crusoe" behavior.
John W. Payne - His research has focused on how people adapt their strategies for solving
decision problems to the demands of the tasks they face. His research has included studies of
consumer choice, managerial risk taking, environmental valuation, and jury decisions. He is an
Associate Editor of Management Science, the Journal of Behavioral Decision Making, Journal of
Risk and Uncertainty, and the Journal of Forecasting. Currently at Duke University.
Richard Thaler - Research activities include behavioral economics and finance, the psychology
of decision making. His most notable contribution is the concept of mental accounting and loss
aversion research. Currently at the University of Chicago.
Amos Tversky - (1937 - 1996) A cognitive psychologist who changed the way experts in many
fields think about how people make decisions about risks, benefits and probabilities. He
29
developed Prospect Theory along with Dan Kahneman. He also influenced statisticians and
other researchers interested in how decisions involving risk are made in fields like medicine and
public policy.
John Louis von Neumann - (1903 - 1957) Brilliant mathematician, synthesizer, and promoter of
the stored program concept, whose logical design of the Institute for Advanced Studies (IAS)
became the prototype of most of its successors - the von Neumann Architecture. Developed the
synergism between computer’s capabilities and the needs for computational solutions to nuclear
problems related to the hydrogen bomb.
KEY PEOPLE IN THE FIELD OF ETHICAL, SOCIAL AND LEGAL ISSUES OF MIS
Sara Kiesler - Research interests are group dynamics, communication, decision making and
computer-mediated communication. Currently a Professor at Carnegie Mellon University.
Rob Kling - Research interests are the social effects of computers, privacy in the electronic age,
and the effects of computers on group and individual behavior. Currently a Professor at the
Indiana University School of Library and Information Science.
Lee Sproull - Research interests are group dynamics, communication, decision making, and in
how computer-based communication affects human behavior. Currently a Professor of
Management at Boston University School of Management.
ETHICAL, SOCIAL AND LEGAL ISSUES OF MIS KEY PAPERS
Branscomb, L. (1979). Information: The ultimate frontier. Science, 248, 143-147.
Conger, S., Loch, K. & Helft, B. (1995). Ethics and information technology use: A factor
analysis of attitudes to computer use. Information Systems Journal, 5(3), 161-183.
Culnan, M. (1993). How did you get my name? An exploratory investigation of consumer
attitudes toward secondary information use. MIS Quarterly, 17, 341-363.
Kling, R. (1980). Social Analyses of computing: Theoretical perspectives in recent empirical
research. Computing Surveys, 12, 62-89.
Kling, R. (1991). Computerization and Social Transformations. Science, Technology and Human
Values, 16(3), 342-367.
Mowshowitz, A. (1994). Virtual Organization: A vision of management in the information age.
The Information Society, 10, 267-288.
Olson, M. (1982). New information technology and organization culture. Management
Information Systems Quarterly, 6(5), 71-92.
Sipior, J., & Ward, B. (1995). The ethical and legal quandary of e-mail privacy. Communications
of the ACM, 22, pp. 48-54.
30
Sproull, L. & Kiesler, S. (1991). Computers, networks and work. Scientific American, 265(3),
116-123.
Sproull, L., Kiesler, S., & Zubrow, D. (1984). Encountering an alien culture. Journal of social
issues, 40(3), 31-48.
Ware, W. (1993). The new faces of privacy. The Information Society, 9, 195-211.
KEY PEOPLE IN THE FIELD OF GROUP DECISION MAKING (NON-GSS)
Andre Delbecq - Research interests are executive decision-making processes, organization
structure and design and managing innovation in rapid change environments. Currently a
Professor of Management in the Leavey School of Business and Administration at Santa Clara
University.
Sara Kiesler - Research interests are group dynamics, communication, decision making and
computer-mediated communication. Currently a Professor at Carnegie Mellon University.
Lee Sproull - Research interests are group dynamics, communication, decision making, and in
how computer-based communication affects human behavior. Currently a Professor of
Management at Boston University School of Management.
Andrew Van de Ven - Research interests are group decision making, organizational innovation
and change, organization theory, and innovation. Currently a Professor at the University of
Minnesota.
Victor Vroom - Research interests are motivation, the psychological analysis of behavior in
organizations, leadership, and decision making. Currently a Professor of Organization and
Management and Professor of Psychology at Yale School of Management.
GROUP DECISION MAKING (OTHER THAN GSS) KEY PAPERS
Bond, Jr., C. & Titus, L. (1983). Social facilitation: A meta-Analysis of 241 studies.
Psychological Bulletin, 29, 265-92.
Cotton, J., Vollrath, D., Froggatt, K., Lengnick-Hall, M., & Jennings, K. (1988). Employee
participation: Diverse forms and different outcomes. Academy of Management Review, 13, 8-22.
Delbecq, A., & Van De Ven, A. (1971). A group process model for problem identification and
program planning. The Journal of Applied Behavioral Science, 7, 466-492.
Doise, W. (1969). Intergroup relations and polarization in individual and collective judgments.
Journal of Personality and Social Psychology, 12, 136-143.
Kiesler, S. & Sproull, L. (1992). Group decision making and communication technology.
Organizational Behavior and Human Decision Processes. 52 (1), 96-123.
31
Lowin, A., (1968). Participative decision making: A model, literature critique, and prescriptions
for research. Organizational Behavior and Human Performance, 3, 68-106.
Park, W. (1990). A review of research on groupthink. Journal of Behavioral Decision Making, 3,
229-245.
Schweiger, D., Sandberg, W., & Ragan, J. (1986). Group approaches for improving strategic
decision making:
A comparative analysis of dialectical inquiry, devil’s advocacy, and
consensus. Academy of Management Journal, 29, 51-71.
Siegel, J., Dubrovski, V., Keisler, S., & McGuire, T. (1986). Group processes in computer
mediated communication. Organizational Behavior and Human Decision Processes, 37, 157187.
Sniezek, J. & Henry, R. (1989). Accuracy and confidence in group judgment. Organizational
Behavior and Human Decision Processes, 43, 1-28.
Stoner, J.A. (1961). A comparison of individual and group decisions involving risk. Unpublished
master’s thesis, Massachusetts Institute of Technology, Cambridge, Massachusetts.
Van De Ven, A., & Delbecq, A. (1971). Nominal versus Interacting Group Process for
committee decision making effectiveness. Academy of Management Journal, 14, 203-212.
Van De Ven, A., & Debecq, A. (1974). The effectiveness of Nominal, Delphi, and Interacting
Group decision
making processes. The Academy of Management Journal, 17(4), 605-21.
Vroom, V. & Jago, A. (1974). Decision making as a social process: Normative and descriptive
models of leader behavior. Decision Sciences, 14, 750-773.
Wagner, J. & Gooding, R. (1987). Shared influence and organizational behavior: A metaanalysis of situational variables expected to moderate participation-outcome relationships.
Academy of Managment Journal, 30, 524-541.
32
Decision Sciences
Operations Management Reading List
Capacity Planning
Bowman, E. H. Scale of Operations – An Empirical Study. Operations Research. June 1958,
320-328.
Carroll, T. M., and Dean, R. D. A Baynesian Approach to Plant Location Decisions. Decision
Sciences, vol. 11, no. 1, Jan. 1980.
Drayer, and Seabury. Facilities Expansion Models. Interfaces, vol. 5, no. 2, 174-184.
Erlenkotter, D. Capacity Planning for Large Multi-location Systems: Approximate and
Incomplete Dynamic Programming Approaches. Management Science, vol. 22, no. 3, 274-285.
Erlenkotter, D. Sequencing Expansion Projects. Operations Research, vol. 21. (1973) 542-553.
Fetter, R. B. A Linear Programming Model for Long Range Capacity Planning. Management
Science, vol. 7, 372-278.
Giglio, R. J. Stochastic Capacity Models. Management Science, vol. 17, no. 3, 174-184.
Groff, G. K., and Muth, J. F. Operations Management: Analysis for Decisions. Irwin Series in
Quantitative Analysis for Business, R. D. Irwin, Inc., 1972.
Gunn, W. Airline System Simulation. Operations Research, vol. 12, no. 2, 206-229.
Hertz, D. B. Risk Analysis in Capital Investment. Harvard Business Review. Jan.-Feb. 1961, 5570.
Hinomoto, H. Capacity Expansion with Facilities under Technological Improvement.
Management Science, vol. 11, no. 5, 581-592.
Howard, G., and Nemhauser, G. Optimal Capacity. Naval Logistics Review Quarterly, vol. 15,
no. 4, Dec. 1968.
Jen, F. C., Pegels, C. C., and DuBois, T. M. Optimal Capacities of Production Facilities.
Management Science, vol. 14, no. 10.
Manne, A. S. Plant Location under Economics of Scale – Decentralization and Computations.
Management Science, November 1964.
McClain, J. O. Bed Planning Using Queuing Theory Models of Hospital Occupancy: A
Sensitivity Analysis. Inquiry, vol. 13, 167-176.
Stochastic Assembly Line Design
Anderson, D. R., and Moodie, C. L. Optimal Buffer Storage Capacity in Production Line
Systems. International Journal of Production Research, 7, 3, 233-240.
Barten, K. A Queuing Simulator for Determining Optimum Inventory Levels in a Sequential
Process. Journal of Industrial Engineering, 13, 4, 245-252.
Carnall, C. A., and Wild, R. The Location of Variable Workstations and the Performance of
Production Flow Lines. International Journal of Production Research.
33
Davis, L. E. Pacing Effects on Manned Assembly Lines. International Journal of Production
Research, 4, 3, 171-184.
De La Wyche, P., and Wild, R. The Design of Imbalance Series Queue Flow Lines. Operational
Research Quarterly, 28, 3, 695-702.
Dudley, N. A. Work Time Distributions. International Journal Operations Research, 2, 2, 137144.
Duncan, A. J. Quality Control and Industrial Statistics. Richard D. Irwin, Inc., Homewood,
Illinois, 1974, 700-706.
El-Rayah, T. E. The Efficiency of Balanced and Unbalanced Production Lines. International
Journal of Operations Research, 17, 1, 61-75.
El Rayah, T. E. The Effect of Inequality of Interstage Buffer Capacities and Operation Time
Variability on the Efficiency of Production Lines Systems. International Journal of Production
Research, 17, 1, 77-89.
Hatcher, J. M. The Effect of International Storage on the Production Rate of a Series of Stages
Having Exponential Service Times. AIIE Transactions, 1, 2, 150-156.
Hillier, F. S., and Boling, R. W. The Effect of Some Design Factors on the Efficiency of
Production Lines with Variable Operation Times. Journal of Industrial Engineering, 17, 12, 651658.
Hillier, F. S., and Boling, R. W. On the Optimal Allocation of Work in Symmetrical Unbalanced
Production Line Systems with Variable Operation Times. Management Science, 25, 8, 721-728.
Kala, R., and Hitchings, G. G. The Effects of Performance Time Variance on a Balanced, Fourstation Manual Assembly Line. International Journal of Production Research, 11, 4, 341-353.
Kottas, J. F., and Lau, H. A Cost-Oriented Approach to Stochastic Line Balancing. AIIE
Transactions, 5, 2, 164-171.
Layout
Books
Francis, R. L., and White, J. A. Facility Layout and Location: An Analytical Approach. PrenticeHall. 1974.
Tompkins, J. A., and Moore, J. M. Computer Aided Layout: A User’s Guide. Facilities Planning
and Design Division, Monograph Series No. 1, AIIE, 1978.
Tompkins, J. A., and White, J. A. Facilities Planning. John Wiley and Sons, 1984.
Muther, R. Systematic Layout Planning. Boston, MA: Industrial Education Institute, 1961.
Mirchandani, P., and Francis, R. L. (Editors) Discrete Location Theory, Wiley, 1990.
Survey Papers
Foulds, L. R. Techniques for Facilities Layout: Deciding Which Pairs of Activities Should Be
Adjacent. Management Science, vol. 9, no. 12, 1414-1426.
Heragu, S. S., and Kusiak, A. Machine Layout Problem in Flexible Manufacturing Systems.
Operations Research, 36, 258-268.
34
Kusiak, A., Heragu, S. S. The Facility Layout Problem. European Journal Operations Research,
29, 229-251.
Application Papers
Pfefferkorn, C. E. A Heuristic Problem Solving Design for Equipment or Furniture Layouts.
Comm. Of ACM, vol. 18, no. 5, 286-297.
Ratliff, D. H. Order Picking in an Aisle. IIE Transactions, 20, 53-62.
Ravindran, A. et al. An Application of Simulation and Network Analysis to Capacity Planning
and Material Handling System at Tinker Air Force Base. Interfaces, 19, 102-115.
Singh, M. G., Roderick, C., and Marcel, C. A Hybrid Knowledge-based System for Allocating
Retail Space and for Other Allocation Problems. Interfaces, 18, 13-22.
Abernathy, W. J. Production Process Structure and Technological Change. Decision Science,
vol. 7, 607-619.
Abernathy, W. J., Clark, K. B., and Kantrow, A. M. the New Industrial Competition. Harvard
Business Review, vol. 59, no. 5, 68-81.
Abruzi, A. The Production Process: Operating Characteristics. Management Science, vol. 11, no.
6, 98-118.
Arcalay, J. A., and Buffa, E. S. A Proposal for a General Model of a Production System.
International Journal of Production Research, March 1963.
Banks, R. L., and Wheelright, S. C. Operations vs. Strategy: Trading Tomorrow for Today.
Harvard Business Review. vol. 57, no. 3, 112-120.
Bowman, E. H. Consistency and Optimality in Managerial Decision Making, Management
Science, January 1963.
Buffa, E. S. Research in Operations Management. Journal of Operations Management, vol. 1, no.
1, 1-7.
Chase, R. B. A Classification of and Evaluation of Research in Operations Management. Journal
of Operations Management, vol. 1, no. 1, 9-14.
Drucker, P. R. Behind Japan’s Success. Harvard Business Review, vol. 59, no. 1, 83-90.
Hayes, R. H., Schenner, R. W. How Should You Organize Manufacturing, Harvard Business
Review, vol. 56, no. 1, 105-118.
Hayes, R. H., and Wheelright, S. C. Link Manufacturing and Product Life Cycles. Harvard
Business Review, vol. 57, no. 1, 133-140.
Hobbs, J. M., and Henry, D. F. Coupling Strategy to Operating Plans. Harvard Business Review,
vol. 55, no. 3, 119-126.
Huge, E. C. Managing Manufacturing Lead Times. Harvard Business Review, vol. 57, no. 5,
116-123.
Kantrow, A. M. The Strategy-Technology Connection. Harvard Business Review, July-August
1980.
35
Work Measurement and Learning Curves
Abernathy, W. J., and Wayne. Limits of the Learning Curve. Harvard Business Review, Sept.Oct. 1974.
Adams, S. K., and McGrath, T. J. Procedure for and Economic Comparison of Work
Measurement Techniques, I Model, II Application. AIIE Transactions, vol. 11, no. 3.
Andress, F. J. The Learning Curve as a Production Tool. Harvard Business Review, JanuaryFebruary 1954.
Baloff. Estimating the Parameters of the Start-up Model – An Empirical Approach. Journal of
Industrial Engineering, April 1967.
Conway, R. W., and Schwartz, A., Jr. The Manufacturing Progress Function. Journal of
Industrial Engineering vol. 10, no. 1, 39-54.
Globerson, S. The Influence of Job-related Variables on the Predictability Power of Three
Learning Curve Models. AIIE Transactions, vol. 12, no. 1 (1980).
Globerson, S. Introducing the Repetition Pattern of a Task into its Learning Curve. International
Journal of Production Research, vol. 18, no. 2, (1980).
Hirsch, W. Z. Manufacturing Progress Functions. Harvard Business Review, vol. 34, May 1952.
Hirschman, W. Profit from the Learning Curve. Harvard Business Review, January-February
1964.
Paul, R. P., and Nof, S. Y. Work Methods Measurement – Comparison between Robot and
Human Task Performance. International Journal of Production Research, vol. 17, no. 3, 1975.
Pegels, C. Start-up on Learning Curves – Some New Approaches. Decision Sciences, vol. 7,
1976.
Raouf, A., and Manney, W. Variations in Cycle Time and Certain Physiological Measures of
Workers Performing a Paced Assembly Task. International Journal of Production Research, vol.
16, no. 5, 1978.
Womer, N. K. Learning Curves, Production Rate and Program Costs. Management Science,
April 1979.
Service Process Design
Chase, R. B. The Customer Contact Approach to Services: Theoretical Bases and Practical
Extensions. Operations Research, v. 29, n. 4, 698-706.
Chase, R. B., Northcraft, G. B., and Wolf, G. Designing High Contact Services Systems:
Application to Branches of a Savings and Loan. Decision Sciences, 15, 4, 1984.
Chase, R. B., and Tansik, D. A. The Customer Contact Model Organization Design.
Management Science, 29, 9, 1037-1050.
Fitzsimmons, J. A. Consumer Participation and Productivity in Service Operations. Interfaces,
15, 3, 60-67.
Johnston, B., and Morris, B. Monitoring and Control in Service Operations. International Journal
of Operations and Production Management, 5, 1, 32-38.
36
Lovelock and Young. Look to Customers to Increase Productivity. Harvard Business Review,
May-June 1979.
Schmenner, R. How Can Service Business Survive and Prosper? Sloan Management Review,
Spring 1986, 21-32.
Shostack, G. L. Designing Services that Deliver. Harvard Business Review, January-February
1984.
Aggregate Planning
Bowman, E. H. Consistency and Optimality in Managerial Decision Making. Management
Science, 9, 2, 310-321.
Eilon, S. Five Approaches to Aggregate Production Planning. AIIE Transactions, 7, 2, 118-131.
Holt, C. C., Modigliani, F., and Simon, H. A. A Linear Decision Rule for Production and
Employment Scheduling. Management Science, 2, 2, 10-30.
Johnson, L. A., and Montgomery, D. C. Operations Research in Production Planning,
Scheduling, and Inventory Control. New York: John Wiley and Sons, 1974.
Jones, C. H. Parametric Production Planning. Management Science, 13, 11, 843-866.
Khoshnevis, B., and Wolfe, P. M. An Aggregate Production Planning Model Incorporating
Dynamic Productivity: Part I, Model Development. AIIE Transactions, 15, 4, 283-291.
Lee, W. B., and Khumawala, B. M. Simulation Testing of Aggregate Production Planning
Models in an Implementation Methodology. Management Science, 20, 6, 903-911.
Schwarz, L. B., and Johnson, R. E. An Appraisal of the Empirical Performance if the Linear
Decision Rule for Aggregate Planning, Management Science, 24, 8, 844-849.
Silver, E. A. A Tutorial on Production Smoothing and Work Force Balancing. Operations
Research, 15, 6, 985-1010.
Taubert, W. H. A Search Decision Rule for the Aggregate Scheduling Problem. Management
Science, 14, 6, 343-359.
Wagner. The Design of Production and Inventory Systems for Multi-Facility and MultiWarehouse Companies. Operations Research, vol. 22, March-April 1974.
Hierarchical Planning Systems
Abernathy, W. J., Baloff, J., Hershey, J. C., and Wandel, S. Three-Stage Manpower Planning and
Scheduling Model: A Service Sector Example. Operations Research, 21, 3, 693-711.
Bitran, G. R., and Hax, A. C. Disaggregation and Resource Allocation Using Convex Knapsack
Problems with Bounded Variables. Management Science, 27, 4, 431-441.
Gaalman, G. Optimal Aggregation of Multi-item Production Smoothing Models. Management
Science, 24, 1733-1739.
Ritzman, L. P., Krajewski, L. J., and Showalter, M. J. The Disaggregation of Aggregate
Manpower Plans. Management Science, 22, 11.
Zipkin, P. Exact and Approximation Cost Functions for Product Aggregates. Management
Science, 28, 9, 1002-1012.
37
Zoller, K. Optimal Disaggregation of Aggregate Production Plans. Management Science, 17, 8,
533-549.
Manufacturing Planning and Control
Books
Hall, R. W. (1983) Zero Inventories, Irwin, Homewood, IL.
Wight, O. W. (1981) MRP II Unlocking America’s Productivity Potential, The Book Press,
Brattleboro, VT.
Workforce Scheduling
Baker, K. R. Scheduling a Full-Time Workforce to Meet Cyclic Staffing Requirements.
Management Science, 20, 12, 1561-1568.
Bechtold, S. E. Workforce Scheduling for Arbitrary Cyclic Demands. Journal of Operations
Management, 1, 4, 205-241.
Buffa, E. S., Cosgrove, M. J., and Luce, B. J. An Integrated Work Shift Scheduling System.
Decision Sciences, 7, 4, 1030-1047.
Chaiken, J. M., and Bennett, H. S. A Patrol Car Allocation Model: Capabilities and Algorithms.
Management Science, 24, 12, 1291-1300.
Chaiken, J. M., and Larson, R. C. Methods of Allocating Urban Emergency Units: A Survey.
Management Science, 19 (Dec. 1972), 110-130.
Fitzsimmons, J. A., and Sullivan, R. S. Service Operations Management. New York: McGrawHill Book Company, 1982.
Glover, F., McMillan, C., and Glover, R. A Heuristic Programming Approach to the Employee
Scheduling Problem and Some Thoughts on “Managerial Robots”. Journal of Operations
Management, 4, 2, 113-128.
Hill, A. D., Naumann, J. D., and Chervany, N. L. SCAT and SPAT: Large Scale Computer-based
Optimization Systems for the Personnel Assignment Problem. Decision Sciences, 14, 2, 207-220.
Ingall, E., Kolesar, P., and Walker, W. Linear Programming of Crew Assignments for Refuse
Collections. IEEE Transactions on Systems, Man, and Cybernatics, 2, 5 (Nov. 1972).
Kolesar, P., and Walker, W. E. An Algorithm for the Dynamic Relocation of Fire Companies.
Operations Research, 22, 2, 249-274.
Krajewski, L. J., Ritzman, L. P., and McKenzie, P. Shift Scheduling in Banking Operations: A
Case Application. Interfaces, 10, 2, 1-8.
Mabert, V. A., and Raedels, A. R. The Detailed Scheduling of a Part-Time Workforce: A Case
Study of Teller Staffing. Decision Sciences, 8, 1, 109-120.
Marsten, R. E., Muller, M. R., and Killon, C. L. Crew Planning at Flying Tiger: A Successful
Application ogf Integer Programming. Management Science, 25, 12, 1175-1196.
Johnson, R. V. Optimally Balancing Large Assembly Lines with FABLE. Management Science,
34 (1988), 240-253.
38
Kao, E. P. C., and Queyranne. On Dynamic Programming Methods for Assembly Line
Balancing. Operations Research, 30, 1982.
Kottas, J. F., and Lau, H. S. Some Problems with Transien Phenomena when Simulating
Unpaced Lines. Journal of Operations Management, 1, 155-164.
MacAskill, J. L. C. Production Line Balances for Mixed Model Lines. Management Science, 19
(1972), 423-434.
Patterson, J. H., and Albrecht, J. J. Assembly Line Balancing: Zero-One Programming with
Fibonacci Search. Operations Research, v. 23, 166-174.
Rosenblatt, M. J., and Carlson, R. C. Designing a Production Line to Maximize Profit. IEE
Transactions, v. 17.
Smunt, T. L., and Perkins, W. C. Stochastic Unpaced Line Design: Review and Further
Experimental Results. Journal of Operations Management, v. 5, 351-373.
Talbot, F. B., and Patterson, J. H. An Integer Programming Algorithm with Network Cuts for
Solving the Assembly Line Problem. Management Science, v. 30, 85-99.
Talbot, F. B., Patterson, J.H., and Gehrlein, W. V. A Comparative Evaluation of Heuristic Line
Balancing Techniques. Management Science, V. 32, 430-454.
Thomopolous, N. T. Mixed Model Line Balancing with Smoothed Station Assignments.
Management Science, v. 16, 593-603.
Wee, T. S., and Magazine, M. J. Assembly Balancing as Generalized Bin Packing. Operations
Research Letters, v. 1, 56-58.
Project Management
Books
Baker, K. R. Introduction to Sequencing and Scheduling. Wiley, New York, 1974.
Johnson, L. A., and Montgomery, D. C. Operations Research in Production Planning,
Scheduling, and Inventory Control. Wiley, New York, 1974.
Hax, A. C., and Candea, D. Production and Inventory Management. Prentice-Hall, Englewood
Cliffs, NJ, 1984.
Elmaghraby, S. E. Activity Networks: Project Planning and Control Network Models, John
Wiley, New York, 1977.
Survey Papers
Adlakha, V. G., and Kulkarni, V. G. A Classified Bibliography of Research on Stochastic PERT
Networks. INFOR, v. 27, 272-296.
Davis, E. W. Resource Allocation in Project Network Models – A Survey. Journal of Industrial
Engineering, v. 17, 177-188.
Davis, E. W. Project Scheduling Under Resource Constraints – Historical Review and
Categorization of Procedures. AIIE Transactions, v. 5, 297-313.
Theory Papers
39
Cooper, D. F. Heuristic for Scheduling Resource Constrained Projects: An Experimental
Investigation. Management Science, v. 22, 1186-1194.
Davis, E. W., and Patterson, J. H. A Comparison of Heuristic and Optimum Solutions in
Resource-Constrained Project Scheduling. Management Science, v. 21, 944-955.
Doersch, R. H., and Patterson, J. H. Scheduling a Project to Maximize Its Present Value: A ZeroOne Programming Approach. Management Science, v. 23, 882-889.
Single-Echelon Systems
Books
Hadley, G., and Whitin, T. M. Analysis of Inventory Systems. Prentice-Hall, Englewood Cliffs,
1963.
Hax, A. C., and Candea, D. Production and Inventory Management, Englewood, NJ, 1984.
Johnson, L. A., and Montgomery, D. C. Operations Research in Production Planning,
Scheduling, and Inventory Control. John Wiley, New York, 1974.
Schwarz, L. B. (Editor) Multi-Level Production/Inventory Control Systems: Theory and Practice.
North Holland, Amsterdam, Netherlands, 1981.
Silver, E. A., and Patterson, R. Decision Systems for Inventory Management and Production
Planning, John Wiley, New York, 1985.
Tersine, R. J. Principles of Inventory and Materials Management. North Holland, New York,
1988.
Survey Papers
Aggarwal, S. C. A Review of Current Inventory Theory and Its Applications. International
Journal of Production Research, v. 12, 443-472.
Elmaghraby, S. E. The Economic Lot Sizing Problem (ELSP): Review and Extensions.
Management Science, v. 24, 587-598.
Graves, S. C. A Review of Production Scheduling. Operations Research, v. 29, 646-675.
Nahmias, S. Perishable Inventory Theory: A Review. Operations Research. v. 30, 680-708.
Silver, E. A. Operations Research in Inventory Management: A Review and Critique. Operations
Research, v. 29, 628-644.
Wagner, H. M. Research Portfolio for Inventory Management and Production Planning Systems.
Operations Research, V. 28, 445-475.
Theory Papers
Arrow, K. J., Harris, T., and Marschak, J. Optimal Inventory Policy. Econometrica, v. 19, 250272.
Berry, W. L., and Bliemel, F. W. Selecting Exponential Smoothing Constraints: An Application
of Pattern Search. International Journal Operations Research, v. 12, n. 4, 483-499.
Bretchneider, S. I., and Gorr, W. P. On the Relationship of Adaptive Filtering Forecasting
Models to Simple Brown Smoothin. Management Science, v. 27, n. 8, 965-969.
40
Bretchneider, S. I., Carbone, R., and Longini, R. L. An Adaptive Approach to Time Series
Forecasting. Decision Sciences, v. 10, n. 2, 232-244.
Brown, R. G., ad Meyer, R. F. The Fundamental Theorem of Exponential Smoothing. Operations
Research, v. 9, 673-685.
Gardner, E. S. The Strange Case of Lagging Forecasts. Interfaces, v. 14, n. 3, 47-50.
Geoffrion. A Summary of Exponential Smoothing. Journal of Industrial Engineering, v. 13, n. 4.
Groff, G. K. Empirical Comparison of Models for Short-Range Forecasting. Management
Science, v. 20, n. 1, 22-31.
Lee, T. S., and Adam, E. E., Jr. Forecasting Error Evaluation in Material Requirements Planning
(MRP) Production Inventory Systems. Management Science, v. 32, n. 9, 1186-1205.
Mabert, V. A. Forecast Modification Based Upon Residual Analysis: A Case Study of Check
Volume Estimation. Decision Sciences, v. 9, 1978.
Mabert, V. A. An Introduction to Short-Term Forecasting Using the Box Jenkins Methodology.
AIIE Monograph, 1975.
Makridakis, S., and Winkler, R. Averages of Forecasts: Some Empirical Results. Management
Science, v. 29, n. 9, 987-996.
McClain, J. O. Restarting a Forecasting System When Demand Suddenly Changes. Journal of
Operations Management, v. 2, n. 1, 53-61.
Muth, J. F. Optimal Properties of Exponential Weighted Forecasts. Journal of American Stat.
Association, v. 55, 299-306.
Investing in Technology/FMS
Buzacott, J. A., and David, D. Y. Flexible Manufacturing Systems: A Review of Analytical
Models. Management Science, v. 32, n. 7, 890-905.
Migrom, P., and Roberts, J. The Economics of Modern Manufacturing: Technology, Strategy,
and Organization. The American Economic Review, v. 80, n. 3, 511-528.
Roller, L., and Tombak, M. Competition and Investment in Flexible Technologies. Management
Science, v. 39, n. 1, 107-114.
Stochastic Assembly Line Design
Baker, K. B., Powell, S., and Pyke, D. Optimal Allocation of Work in Assembly Systems.
Management Science, v. 39, n. 1, 101-106.
Berkley, B. J. A Review of the Kanban Production Control Research Literature. Prodcution and
Operations Management, v. 1, n. 4, 393-411.
Conway, R., Maxwell, W., McClain, J., and Thomas, L. The Role of Work-In-Process Inventory
in Serial Prodcution Lines. Operations Research, v. 36, n. 2, 229-241.
Deleersnyder, J., Hodgson, T., Mulller, H., and O'Grady, P. Kanban Controlled Pull Systems: An
Analytic Approach. Management Science, v. 35, n. 9, 1079-1091.
Duenyas, I., Hopp, W., and Spearman, M. Characterizing the Output Process of a CONWIP Line
with Deterministic Processing and Random Outages. Management Science, v. 39, n. 8, 975-988.
41
Hendricks, K., and McClain, J. The Output Processes of Serial Production Lines of General
Machines with Finite Buffers. Management Science, v. 39, n. 10, 1194-1201.
Muth, E. The Reversibility of Production Lines. Management Science, v. 25, n. 2, 152-158.
Tayur, S. Structural Properties and a Heuristic for Kanban-Controlled Serial Lines. Management
Science, v. 39, n. 11, 1347-1368.
Process Control
Fine, C. Quality Improvement and Learning in Productive Systems. Management Science, v. 32,
n. 10, 1301-1315.
Lee, H. Lot Sizing to Reduce Capacity Utilization in Production Process with Defective Items,
Process Corrections, and Rework. Management Science, v. 38, n. 9, 1314-1328.
Marcellus, R., and Dada, M. Interactive Process Quality Improvement. Management Science, v.
37, n. 11, 137-144.
Multi-Echelon Systems
Atkins, D., and Iyogun, P. A Lower Bound on a Class of Coordinated Invenrory/Production
Problems. Operations Research Letters, v. 6, n. 2, 63-67.
Jackson, P., Maxwell, W., and Mukstadt, J. The Joint Replenishment Problem with a Powers-ofTwo Restriction. IEE Transactions, March 1985, 25-32.
Roundy, R. 98%-Effective Integer-Ratio Lot-Sizing for One-Warehouse Multi-Retailer System.
Management Science, v. 31, n. 11, 1416-1430.
Schwarz, L. A Simple Continuous Review Deterministic One-Warehouse N-Retailer Inventory
Problem. Management Science, v. 19, n. 5, 555-566.
Miscellaneous
Gerwin, D. Control and Evaluation in the Innovation Process: The Case of Flexible
Manufacturing Systems. IEEE Transactions on Engineering Management, Vol. EM-28, No. 3
(August 1981).
Gerwin, D. Do’s and Don’ts of Computerized Manufacturing. Harvard Business Review, MarchApril 1982, 107-116.
Gold, B. CAM Sets New Rules for Production. Harvard Business Review, November-December
1982.
Goldhar, J. D., and Jelinek, M. Plan for Economies of Scope. Harvard Business Review,
November-December 1983, 141-148.
Gruber and Niles. The Science Technology-Utilization Relationship in Management.
Management Science, vol. 21, no. 8, 956-963.
Huang, P.Y., and Chen, C. Flexible Manufacturing Systems: An Overview and Bibliography.
Production and Inventory Management, 3rd Quarter 1986.
Huete, L. M. A Matrix for Linking Service Contents with Delivery Options. Decision Sciences
Institute Proceedings, 1987.
42
Jenkins, K. M., and Raedels, A. R. The Robot Revolution: Strategic Considerations for
Managers. Production and Inventory Management, 3rd Quarter 1982, 107-116.
Kaplan, R. Must CIM be Justified by Faith Alone? Harvard Business Review, March-April 1986.
Kilbridge, M., and Wester, L. An Economic Model for the Division of Labor. Management
Science, vol. 12, no. 6, 255-269.
Kusiak, A. Application of Operational Research Models and Techniques in FMS. European
Journal of Operational Research, vol. 24, 1986.
Malkiel, B. C. Productivity – the Problem Behind the Headline. Harvard Business Review, MayJune 1979.
Monahan, G., and Smunt, t. A Multi-level DSS for the Financial Justification of Automated
Flexible Manufacturing Systems. Interfaces, Nov.-Dec. 1987.
Nof, S. Y., and Whinston, A. B., and Bullers, W. I. Control and Decision Support in Automatic
Manufacturing Systems. AIIE Transactions, vol. 12, no. 2, June 1980.
Quinn, J. B. Technological Forecasting. Harvard Business Review, no. 2, March-April 1967.
43