5.3 Static and Dynamic Models
Static Analysis
– Single snapshot
Dynamic Analysis
– Dynamic models – Evaluate scenarios that change over
time – Are time dependent
– Show trends and patterns over time – Extended static models
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ
5.4 Treating Certainty,
Uncertainty, and Risk
Certainty Models
Uncertainty
Risk
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ
Graphical representations of a model to assist in model design, development and understanding
Provide visual communication to the model builder or development team
Serve as a framework for expressing the MSS model relationships
Rectangle = a decision variable Circle = uncontrollable or intermediate
variable Oval = result outcome variable:
intermediate or final Variables connected with arrows
Example in Figure 5.1
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ
FIGURE 5.1 An Influence Diagram for the Profit Model.
~ Amount used in advertisement
Profit Income
Expense Unit Price
Units Sold
Unit Cost
Fixed Cost
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ
Spreadsheets
Electronic spreadsheet: most popular end-user modeling tool
Powerful financial, statistical, mathematical, logical, datetime,
string functions
External add-in functions and solvers
Important for analysis, planning, modeling
Programmability macros
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ
What-if analysis
Goal seeking
Seamless integration
Microsoft Excel
Lotus 1-2-3
Figure 5.2: Simple loan calculation model static
Figure 5.3: Dynamic
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ
of Few Alternatives
Decision Tables and Trees
Single Goal Situations
– Decision tables – Decision trees
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ
Decision Tables
Investment Example
One goal: Maximize the yield after one year
Yield depends on the status of the economy
the state of nature
– Solid growth – Stagnation
– Inflation
Decision Support Systems and Intelligent Systems, Efraim Turban and Jay E. Aronson Copyright 1998, Prentice Hall, Upper Saddle River, NJ
1. If there is solid growth in the economy, bonds will yield 12 percent;