Title: Understanding Decision Support Systems and Expert Systems

Author: E. Mallach

  1. Introduction to Decision Support systems
    1. Evolution of Information Systems
    2. What is DSS?
    3. DSS in the Information Systems Picture
      1. Types of information
      2. Information systems and decision support
      3. Using computers for decision support
    4. Specific DSS benefits
      1. Improving personal efficiency
      2. Expediting problem solving
      3. Facilitating interpersonal communication
      4. Promoting learning or training
      5. Increasing organizational control
    5. Why study DSS?
    6. The plan of This Book
  2. Human Decision Making Processes
    1. What is a decision?
    2. The decision process
      1. The intelligence phase
      2. The design phase
      3. The choice phase
    3. Types of decisions
    4. How mangers make decisions
      1. The rational manger
      2. Subjective utility
      3. Systematic decision making
      4. Satisficing
      5. Organizational and political decision making
    5. The impact of psychological type on decision making
    6. The Kepner-Tregoe decision making method
      1. State the purpose of the decisions
      2. Establish objectives
      3. Classify according to importance
      4. Generate alternatives
      5. Evaluate alternatives against objectives
      6. Tentatively, choose the best alternative
      7. Assess adverse consequences
      8. Make a final choice
  3. Systems and Models
    1. About systems
    2. Information systems
    3. Data flow diagrams
    4. DSS as information systems
    5. Models
      1. Types of models
      2. Simplification
  4. Types of decision support systems
    1. The DSS types
      1. The seven DSS types
      2. Applying the DSS to the types to airline yield management
    2. Generalizing the DSS categories
    3. Matching DSS to the Decision Type
    4. Individual and group DSS
    5. Matching benefits to DSS user community
    6. Matching DSS to the decision maker’s psychological type
      1. Introversion/Extroversion
      2. Sensing/Intuition
      3. Thinking/Feeling
      4. Judgement/Perception
      5. Combinations of preferences
    7. Usage modes
    8. Institutional versus Ad Hoc DSS
  5. Building a Decision Support System
    1. Defining the DSS architecture
    2. DSS development project participants
    3. The DSS development process
      1. The SDLC approach
      2. Prototyping
      3. End User Development
    4. DSS user interfaces styles
      1. Factors to consider in use-interface design
      2. User-interface styles
      3. Hypertext/ Hypermedia
  6. DSS software tools
    1. DSS software categories
    2. Standard packages
    3. Specialized Tools and Generations
      1. Database Management
      2. Information retrieval packages
      3. Specialized modeling languages
      4. Statistical data analysis packages
      5. Forecasting packages
      6. Graphing packages
    4. Programming languages for DSS
      1. Third generation programming languages
      2. Fourth generation programming languages
  7. DSS Hardware and operating system platforms
    1. The major options
    2. DSS on the central corporate system
    3. DSS with an information base on a separate system
    4. DSS and Client/Server Computing
    5. DSS on a stand-alone system
    6. Open systems and DSS
    7. Choosing a DSS hardware environment
  8. Implementing DSS
    1. The implementing stage
    2. System conversion
    3. Overcoming resistance to Change
      1. Unfreezing
      2. Moving
      3. Refreezing
    4. DSS implementing issues
      1. Technical DSS implementation issues
      2. User related implementation issues
      3. Using the lists of issues
    5. Ethical issues in DSS implementation
  9. Representation Models
    1. Discrete-event simulation models
      1. The concept of discrete-event simulation
      2. A discrete-event simulation example
      3. Designing discrete-event simulation
      4. Another simulation example
      5. Complete simulation studies
      6. Random and Pseudo random numbers
      7. Statistic Simulation models
    2. Queuing Models
      1. Queuing theory concepts
      2. A Queuing theory example
      3. Generalizing the solution
      4. Arrival and departure time distributor
    3. Markov process models
      1. The Markov process model concept
      2. Computer calculations for Markov processes
    4. Simulation, Queuing theory, and Markov process compared
  10. Optimization
    1. Testing Alternatives
      1. Complete Enumeration
      2. Random Search
    2. The calculus approach
    3. Linear programming
    4. Numerical method
      1. Hill Climbing
      2. Box’s Method
  11. Group DSS
    1. What are group DSS?
    2. Why are group DSS now?
      1. Organizational reasons for group DSS growth
      2. Technical reasons for group DSS growth
      3. Putting the factors together
    3. Group vs. Individual activities
    4. Types of group DSS
    5. GroupWare
    6. Group DSS in use today
      1. Electronic meeting systems
      2. Work flow systems
    7. Four group DSS products
      1. Access technologies’s for comment
      2. ON technology’s instant update
      3. Lotus notes
      4. Groupe Bull Flow PATH
  12. Executive Information Systems
    1. Who are the executives?
    2. What is an executive information systems?
    3. EIS characteristics
      1. Genral Features
      2. EIS Sponsor
    4. EIS issues
      1. Who is the user?
      2. The EIS sponsor
      3. Cost of the EIS
      4. Management Resistance to the EIS
      5. Employee Resistance to the EIS
    5. From the EIS to ESS
    6. Implementing EIS/ ESS
  13. DSS Cases
    1. MBTA passenger waiting time system
    2. MediQual
    3. JOCK
    4. Options pricing with Black-Scholes
    5. Geographic Information Systems
      1. GIS example1: Yellow Freight
      2. GIS example2: Metropolitan Life Insurance
  14. Artificial Intelligence, Expert Systems, and DSS
    1. About Artificial Intelligence
      1. History of AI
      2. The Turing Test
    2. Artificial Intelligence today
      1. Robotics
      2. Machine vision
      3. Natural language interpretation
      4. Neutral Nets
    3. Expert Systems
      1. The basic idea
      2. A simple expert system
    4. Expert systems and DSS
    5. Expert systems and Neutral Networks
  15. Expert systems from the Outside
    1. Pros and Cons of expert systems
      1. Advantages of expert systems
      2. Drawbacks of expert systems
    2. Choosing a good expert system application
      1. Problem related criteria
      2. Expert related criteria
      3. Keeping the criteria in perspective
    3. The expert system human interface
      1. Interface of an expert system
      2. The user control and input interfaces
      3. The user output interface
      4. The explanation interface
  16. Expert Systems from the inside
    1. Variables
    2. Production rules
      1. Combining rules into knowledge based system
      2. Inferencing methods
      3. Strength and weaknesses of production rules
    3. Frames
      1. Semantic networks
      2. Object oriented programming
      3. Frame concepts
      4. Reasoning within the frames
      5. Beyond the individual frames
    4. Predicate Calculus
    5. Databases
    6. Confidence factors
      1. Where confidence factors come from?
      2. Alternative approaches to confidential factors
    7. Fuzzy Logic
  17. Building an expert system
    1. Hardware platforms for expert systems
      1. Expert systems and microcomputers
      2. Expert systems and minicomputers
      3. Expert systems and mainframes
    2. Software tools for expert systems
      1. Packages
      2. Shells
      3. Languages
    3. Knowledge Acquisition
      1. What is Knowledge Acquisition
      2. Finding the experts
      3. Characteristics of the knowledge engineer
      4. Starting the knowledge acquisition process
      5. Working with the expert
      6. From the expert to the computer
      7. Introduction: An alternative to knowledge elicitation
    4. Beyond the knowledge engineer
    5. Combining expert systems and DSS
  18. Expert System Cases
    1. XCON
      1. How XCON works
      2. XCON performance
      3. XCON benefits
      4. Key roles in XCON
      5. Lessons learned from XCON
    2. Expert system calculates space shuttle payload configuration
    3. Truck brake balancing
  19. Pulling it together: Systems integration and the future of DSS
    1. Combining the pieces
    2. What is Systems Integration?
    3. A Systems integration example
    4. Types of integrated systems
      1. Single System Visibility vs. Multiple Visibility
      2. One hardware vs. Multiple hardware
      3. One location vs. multiple locations
    5. Trends in systems integration
    6. The future of DSS