by David L. Olson and James F. Courtney, Jr. 1997
This book discusses the application of computer systems to aid business decision making. Included are a variety of systems that have been developed over the past three decades, spanning a wide range of decision types. The systems addressed in this book include decision support systems, group decision support systems, executive information systems, and expert systems. These kinds of computer systems have revolutionizing the way business is conducted. Computers provide the means to give managers far more information than could have been imagined a few decades ago. Systems are available that go beyond providing information, adding the potential to conduct more thorough analyses of business problems. Other systems extend support to emulating experts. The concept of computers running manufacturing operations has been a reality for a number of years. The potential to apply expert systems to develop knowledge about business operations is a developing application.
Computer systems have limits. They are not going to replace all human functions of management. But the competitive advantage due to computerization is going to make it mandatory to understand the things computers can do for business. It is an uncomfortable subject, because the subject matter is constantly changing. People think of new and better things to do with computers each day. New and exciting software products are developed each year. This environment is further complicated because new hardware systems are developed (and become popular) every few years.
Computer support to business decision making is presented. This is done by first focusing on an overview of computer support to business decision making (chapter 1). Chapters 2 and 3 discuss decision support systems in general, with chapter 2 discussing DSS concepts, and chapter 3 demonstrating these concepts through real examples.
A major change in the way business is conducted is the trend toward more participative decision making. Computers have provided a means to communicate much more rapidly, along with a variety of tools that hopefully can make groups better understand the complexities of decisions, as well as the positions of other people. Current group decision support systems are reviewed in Chapter 4, along with actual applications, and problem areas that have yet to be resolved. We feel that this chapter provides a view of a highly important topic, given that we expect a much higher degree of group decision making in future business operations.
Executive information systems are a relatively new class of computer support focusing upon giving decision makers important information in real time, tapping the potential of computer capabilities much more than has been traditional in the past. Chapter 5 discusses some of the benefits and capabilities currently available. It concludes with the idea that while currently such systems are very expensive (and therefore tend to be found at top levels of the organization), the ideas and developments in pursuing the goal of providing decision making information as quickly as possible will soon find its way throughout the organization.
The next section of the book focuses on decision making in general. Chapter 6 discusses individual decision making, to include identification of individual preference. Chapter 7 discusses organizational factors of decision making.
The third second discusses DSS tools. The object-oriented paradigm is useful in organizing systems to aid decision making, and is presented in Chapter 8. Chapter 9 discusses quantitative modeling of real decisions. Chapter 10 presents simple models of decision maker preference. Spreadsheet modeling is covered in Chapter 11. Chapter 12 discusses the importance of data, and how current technology can be used to access a variety of data types and forms. Chapter 13 discusses databases, using the structured query language (SQL) to demonstrate database concepts.
Probably no topic involving computer systems is more popular than that o f expert systems. Chapter 14 presents a general discussion of expert systems, followed by a chapter focusing on the use of an expert systems shell, with example applications. Chapter 16 presents concepts used in neural networks, and presents applications of their use to support business decision making. Chapter 17 presents three advanced applications of computer technology to aid humans in making decisions.
Three supplemental chapters at the end of the text provide exposure to analytic tools available for DSSs. Supplemental chapter 1 discusses forecasting models, supplemental chapter 2 linear programming, and supplemental chapter 3 simulation. Note that the rest of the book can be used without coverage of these three modeling chapters.
Each chapter presenting a technique includes some example material. There are also optional project assignments in most chapters. The intent of the book is to provide a broad overview of what is available, and to see the value of such approaches in decision support systems. Using the project approach, there is more material than one semester of classes can cover. The content can be used flexibly, and those topics not covered in class could be used as independent project alternatives.
Our philosophy is that knowledge is gained through observation. We have sought to emphasize applications, with the text intended to provide a framework presenting the most important concepts involved in a topic. Applications are presented in short form, focusing on the content of the chapter, seeking to demonstrate important concepts related to computer support to business decision making.
The book is organized with the intention of providing a framework for a variety of pedagogical approaches. A large number of references are provided for courses focusing upon readings. The book includes a large dose of applications from the literature, along with our interpretation of these articles in light of topic material. Student reading of the articles themselves is encouraged, providing them deeper understanding of the applications, as well as other factors discussed in greater detail by the original authors. Further, reports of more current applications could be reviewed, and thought given to the implications of what is found in these new applications.
Another approach is to involve students in hands-on activities. Knowled ge is reinforced by doing. Project suggestions are available in many of the chapters, but we would emphasize that a number of other options are available. Expert system applications would probably involve the need for some shell. Chapter 14 presents some ideas. Data collection is an activity that can be pursued through a variety of assignments. Spreadsheets are widely available, with many productive student activities. Supplemental chapters 1 through 3 involve management science material, with many assignment possibilities available from many sources. (Management science material could be omitted.)
Our experience is that use of computer systems is a highly effective means of reinforcing concept understanding. There are many useful computer packages available that can provide needed support. Decision support systems can consist of a wide variety of configurations. This is especially true for model support. Generally available software could support specific chapters. Regression analysis is supported by many packages, both mainframe and microcomputer. There are many spreadsheet packages available. There are many spreadsheet packages available. IFPS is a little different than most, as is discussed in Chapter 11. AHP is supported by Expert Choice, as well as by a number of other products, including some accessible on the internet. Linear programming packages are widely available. LINDO has been found useful by the authors, although many new microcomputer packages look even better. EXCEL is a very good spreadsheet package that includes SOLVER, a means to solve linear programming models.
We have included short "quick and dirty" guides intended to get students started using some specific packages. Spreadsheets are the basis for many effective decision support systems. At the end of chapter 7, a guide for IFPS use is included. Statistical analysis is common in DSS, even when other models such as linear programming or simulation are used. At the end of supplemental chapter 1, guides for SAS, MINITAB, and IDA are provided. LINDO is a widely used linear programming package. At the end of supplemental chapter 2, a guide for LINDO's use is included. Simulation analysis is less structured. Our experience is that EXCEL is best for most simulations, and BASIC is suitable for complex waiting line models. The last computer support considered is for expert systems. There are many useful shells currently on the market for rule based systems. One of these, EXSYS, is the focus of chapter 12.
Discussion of computer systems inevitably involves strange phrases. Discussion of modeling techniques involves additional jargon. A glossary of terms is provided at the end of the book.
Chapter 1 INTRODUCTION
Decision Making
The History of Computer Support to Business
Clerical Applications or Electronic Data Processing Systems
Management Information Systems
Database Management Systems
Decision Support Systems
Group Decision Support Systems
Executive Information Systems
Expert Systems
The Relationship of Systems to Levels of Decision Making
Scientific Approaches to Business
The "Rational" Decision Process
Decision Modeling
Example Uses of Management Science Models
Airline Ticket Yield Management - Smith, et al.
Summary
References
Chapter 2 THE CONCEPT OF DECISION SUPPORT SYSTEMS
DSS Concepts
Issues of DSS Implementation
Systems Development Practice
Cost Justification
Institutionalization of DSS in the Egyptian Government -El Sherif
Conclusions
References
Project Ideas
Chapter 3 REAL DSS EXAMPLES
Statistical Quality Control in Auto Loans - Mehring
Selection of R&D Projects - Islei, et al.
Spreadsheet Model DSS for Resource Planning - Rizakou, et al.
Use of Heuristics to Generate Better Solutions - Bowers and Agarwal
Fisheries in Iceland - Randhawa and Bjarnason
Optimization of a Distribution System - Robinson, et al.
Intelligent DSS for Patient Illness Assessment - Sharkey, et al.
Discussion
References
Project Idea
Chapter 4 GROUP DECISION SUPPORT SYSTEMS
Group Decision Making
Levels of Group Decision Support
Types of Group Decision Support Systems
Business Climate Forecasting - Vickers
When GDSSs Perform Effectively
Commercially Available GDSSs
Decision Conferencing in Hungary - V=E1ri and Vecsenyi
A Negotiation Support System: MEDIATOR
Airplane Buyout Negotiations - Shakun
Multiple Objective GDSS
Strategies to Break Deadlocks
Nemawashi Group Decision Support - Watabe, et al.
Summary
References
Project Ideas
Chapter 5 EXECUTIVE INFORMATION SYSTEMS
Definition of EIS
Executive Use of Computer Systems
Historical Development of EIS
Critical Success Factors
Sources of Critical Success Factors
Measuring Critical Success Factors
Views of EIS
Selection of EIS Software at Georgia Power - Frolick andJennings
EIS for NASA - Moynihan
Conoco's EIS Evaluation - Belcher and Watson
Commercially Available Products
Differences Between EIS and Other Systems
Future Prospects
Strategic Options Generator - Wiseman and MacMillan
Summary
References
Project Ideas
Chapter 6 INDIVIDUAL DECISION MAKING
Rational Decision Models
Risk
Modeling Decision Making Risk
Studies of Real Decision Making
Utility Functions
Empirical Study of Executive Approaches to Risk
Individual Decision Styles
Problem Finding
Decision-Making Systems
Human Information Processing
The Computer Information Processor (DSS)
Summary
References
Chapter 7 ORGANIZATIONAL DECISION MAKING
Organizational Decision Processes - Mintzberg, et al.
Elements of the Strategic Decision Process
Dynamic Factors
Mental Models Applied to Aid Decision Making
Model Aid in the Problem Identification Phase
Problem Identification - Pounds
Model Aid in the Development Phase
Model Aid in the Selection Phase
Representing Mental Models with Cognitive Maps
Summary
References
Project Ideas
Chapter 8 OBJECT-ORIENTED SYSTEMS
Basic Object Concepts and Object Modeling
Relationships Between Object Classes
Methods, Polymorphism and Encapsulation
Example Object Model
Application of Object Orientation to DSS Development
DSS for Management of Fixed-Income Securities - Sodhi
Object-Oriented Programming
Summary
References
Project Ideas
Chapter 9 DECISION MODELING
What is a Model?
Modeling
Model Structure
Relationships Within the Model
Decision-Making Environments
Decision Making Under Certainty
Real-Time DSS for Airline Management - Rakshit, et al.
Decision Making Under Risk
Simulation of the Postal Service System - Cebry, et al.
Decision Making Under Certainty
Real Treasure Hunting - Stone
Decision Making Under Conflict
Finnish Agricultural Income Policy - Teich, et al.
The Process of Modeling
Formulation of the Problem
Development of the Model
Model Validation and Data Collection
Solution of the Model
Implementation of the Solution
Summary
References
Chapter 10 MODELING SELECTION DECISIONS
Multiple Objectives
Conflicts
Selecting a Nuclear Repository - Keeney
SMART
Job Selection Problem
Analytic Hierarchy Process
Description of AHP
Alternate AHP Calculation
Finnish Energy Policy Evaluation - H=E4m=E4l=E4inen
Summary
References
Project Ideas
Appendix: Eigen Value Calculation
Chapter 11 MODELING SUPPORT
Banking Decision Support System - Cale and Eriksen
IFPS (Interactive Financial Planning System)
IFPS Modeling
Sample Model
Functions and Subroutines
Functions
Subroutines
Reports
Solve Options
What-If Analysis
Goal Seeking
Explain
Lotus 1-2-3
Functions
EXCEL
Functions
Garbage Recycling Problem
IFPS Model
EXCEL Model
What-If Analysis
Summary
References
Project Ideas
Chapter 12 DATA COLLECTION AND DATA ACCESS
Business Intelligence
Jamaican Bauxite Institute - Ventura
Grain Traders - Blanc
Sources
Management Information Systems
Time Study
Surveys
Publications
Commercial Databases
The Internet
Summary
References
Project Ideas
Appendix: Data Sources
Chapter 13 DATABASE MANAGEMENT
Types of Databases
The Objectives of Database Systems
Network and Hierarchical Databases
Relational Databases
The Structured Query Language
Updating SQL Databases
Different People, Different Perspectives: Views and Security
Summary
References
Chapter 13 EXPERT SYSTEMS
An Overview of Expert Systems
Example of a Production Rule System
Strategic Marketing System - Moutinho, et al.
Example Applications in Finance
Insurance
Consumer Credit Services
Banking
Portfolio Management
Trading
The Role of Expert Systems in the Decision Process
EXSYS
Summary
References
Project Ideas
Appendix: EXSYS Variables and Rule Base for Bank of Aberdeen
Chapter 15 EXPERT SYSTEMS WITH EXSYS
Creation of a Knowledge Base in EXSYS
Economic Advisor Expert System
A Marketing Advisor System
Use of Confidence Factors
Auditor Expert System
Doctor Mother
Summary
References
Appendix 1: Rule Base for Marketing Advisor System
Appendix 2: Rule Base for Expert Auditor
Appendix 3: Rule Base for Doctor Mother
Chapter 16 NEURAL NETWORKS
Definition of Neural Networks
Example Neural Network Application
Business Applications of Neural Networks
Statistical Methods
Optimization
Neural Network Applications in Marketing
Neural Networks to Predict Bankruptcy - Wilson and Sharda
Use of Neural Networks for Ranking - Wilson
Available Neural Network Systems
Summary
References
Project Ideas
Chapter 17 FUTURE EXPECTATIONS
LearningSpace
Contemporary Systems
Decision Support System for Fiber-Optic Network Architecure Design
Cosares, et al.
Application of Technology to Cardiovascular Diagnosis - Bordetsky, et al.
Decision Support System Combining Optimization with Expert Systems -
Yang and Mou
DSS Product Availability
Summary
References
Supplemental Chapter 1 FORECASTING
Forecasting the Alaskan Economy - Eschenbach and Geistauts
Classes of Forecasting Techniques
Qualititative Methods
Time Series Forecasts
Causal Methods
Forecasting Models
Regression Models
Box-Jenkins Models
Index of Leading Indicators
Summary
References
Project Ideas
Appendix A: Components of the Index of Leading Indicators
Appendix B: Selected Classification of Cyclical Indicators
Appendix C: Durbin-Watson Table
Appendix D: OLS Regression
Supplemental Chapter 2 LINEAR PROGRAMMING
Applications of Linear Programming
LP Model for Credit Card Debt Collection - Makuch, et al.
Model Components and Assumptions
Components
Sensitivity Analysis
Integer and Zero-One Models
Summary
References
Project Ideas
Appendix: Demonstration Problem
Supplemental Chapter 3 SIMULATION
Definition of Simulation
Monte Carlo Simulation
Simulation Procedure
Analysis of Bloodmobile Organization - Brennan, et al.
Random Numbers
Test for Uniformity
Controlling Random Numbers
Transforming Random Numbers
Simulation Sequence
Summary
References
Project Ideas
GLOSSARY
AUTHOR INDEX
SUBJECT INDEX
provided by
James F. Courtney
Tenneco Professor of Business Administration
Business Analysis and Research Department (MS 4217)
322 Wehner Building
Mays College of Business Administration and Graduate School of Business
Texas A&M University
College Station, Texas 77843-4217
Phone: 409-845-9541
Fax: 409-845-5653
e-mail: j-courtney@tamu.edu
homepage: http://cmis.tamu.edu/faculty/courtney/