Article ID: | iaor2000356 |
Country: | United States |
Volume: | 44 |
Issue: | 7 |
Start Page Number: | 982 |
End Page Number: | 995 |
Publication Date: | Jul 1998 |
Journal: | Management Science |
Authors: | Blanning Robert W., Basu Amit |
Keywords: | information, decision: studies, networks |
Decision models are often based on certain assumptions as to their validity. Relevant assumptions may include value-based assumptions, such as limitations on the range or values of some input variables or exogenous factors, as well as assumptions about model structure (e.g., linearity). In a model base consisting of many models, there may be several models (or collections of models) that can be used to solve a particular problem. We may wish to know what the applicable models are, what assumptions are associated with these models, and whether a given set of assumptions is necessary and/or sufficient for solving the problem. We describe an analytical approach, based on a graph-theoretic construct called a metagraph, and show how it can be used to represent and analyze assumptions in model bases.