This paper is an introduction to a series of papers on sensitivity analysis. It
contains three exploratory exercises demonstrating the effects of various parameter and
initial value changes on system behavior.
The paper assumes that the reader is able to build and understand a multiple-level
model, and has experience with the sensitivity feature in the STELLA software.1 We
encourage the reader to build all the models and to run the simulations described.
1 For a review of the sensitivity feature in STELLA, please refer to your STELLA user manual or to Road
Maps 3: A Guide to Learning System Dynamics (D-4503-3), System Dynamics in Education Project,
System Dynamics Group, Sloan School of Management, Massachusetts Institute of Technology, p. 12-13.
STELLA is a registered trademark of High Performance Systems, Inc.
Sensitivity analysis is used to determine how “sensitive” a model is to changes in
the value of the parameters of the model and to changes in the structure of the model. In
this paper, we focus on parameter sensitivity. Parameter sensitivity is usually performed
as a series of tests in which the modeler sets different parameter values to see how a
change in the parameter causes a change in the dynamic behavior of the stocks. By
showing how the model behavior responds to changes in parameter values, sensitivity
analysis is a useful tool in model building as well as in model evaluation.
Sensitivity analysis helps to build confidence in the model by studying the
uncertainties that are often associated with parameters in models. Many parameters in
system dynamics models represent quantities that are very difficult, or even impossible to
measure to a great deal of accuracy in the real world. Also, some parameter values
change in the real world. Therefore, when building a system dynamics model, the modeler
is usually at least somewhat uncertain about the parameter values he chooses and must use
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