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The Analysis of Assumptions in Model Bases Using Metagraphs

Author

Listed:
  • Amit Basu

    (Owen Graduate School of Management, Vanderbilt University, Nashville, Tennessee 37203)

  • Robert W. Blanning

    (Owen Graduate School of Management, Vanderbilt University, Nashville, Tennessee 37203)

Abstract

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.

Suggested Citation

  • Amit Basu & Robert W. Blanning, 1998. "The Analysis of Assumptions in Model Bases Using Metagraphs," Management Science, INFORMS, vol. 44(7), pages 982-995, July.
    • Handle: RePEc:inm:ormnsc:v:44:y:1998:i:7:p:982-995
    DOI: 10.1287/mnsc.44.7.982
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    References listed on IDEAS

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    1. Amit Basu & Robert W. Blanning, 1994. "Metagraphs: A Tool for Modeling Decision Support Systems," Management Science, INFORMS, vol. 40(12), pages 1579-1600, December.
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    Cited by:

    1. Amit Basu & Robert W. Blanning, 2003. "Synthesis and Decomposition of Processes in Organizations," Information Systems Research, INFORMS, vol. 14(4), pages 337-355, December.
    2. Amit Basu & Robert W. Blanning, 2000. "A Formal Approach to Workflow Analysis," Information Systems Research, INFORMS, vol. 11(1), pages 17-36, March.
    3. Kaushal Chari, 2002. "Model Composition Using Filter Spaces," Information Systems Research, INFORMS, vol. 13(1), pages 15-35, March.
    4. Chaturvedi, Alok & Mehta, Shailendra & Dolk, Daniel & Ayer, Rick, 2005. "Agent-based simulation for computational experimentation: Developing an artificial labor market," European Journal of Operational Research, Elsevier, vol. 166(3), pages 694-716, November.
    5. Rajiv D. Banker & Robert J. Kauffman, 2004. "50th Anniversary Article: The Evolution of Research on Information Systems: A Fiftieth-Year Survey of the Literature in Management Science," Management Science, INFORMS, vol. 50(3), pages 281-298, March.
    6. Therani Madhusudan, 2007. "A web services framework for distributed model management," Information Systems Frontiers, Springer, vol. 9(1), pages 9-27, March.

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