IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v7y1996i3p328-341.html
   My bibliography  Save this article

Inductive Model Analysis Systems: Enhancing Model Analysis in Decision Support Systems

Author

Listed:
  • Ramesh Sharda

    (College of Business Administration, Oklahoma State University, Stillwater, Oklahoma 74078)

  • David M. Steiger

    (Bryan School of Business and Economics, University of North Carolina at Greensboro, Greensboro, North Carolina 27412)

Abstract

After building and validating a decision support model, the decision maker frequently solves (often many times) different instances of the model. That is, by changing various input parameters and rerunning different model instances, the decision maker develops insight(s) into the workings and tradeoffs of the complex system represented by the model.The purpose of this paper is to explore inductive model analysis as a means of enhancing the decision maker's capabilities to develop insight(s) into the business environment represented by the model. The justification and foundation for inductive model analysis is based on three distinct literatures: 1) the cognitive science (theory of learning) literature, 2) the decision support system literature, and 3) the model management system literature. We also propose the integration of several technologies that might help the modeler gain insight(s) from the analysis of multiple model instances. Then we report on preliminary tests of a prototype built using the architecture proposed in this paper. The paper concludes with a discussion of several research questions.Much of the previous MIS/DSS and management science research has focused on model formulation and solution. This paper posits that it is time to give more attention to enhancing model analysis.

Suggested Citation

  • Ramesh Sharda & David M. Steiger, 1996. "Inductive Model Analysis Systems: Enhancing Model Analysis in Decision Support Systems," Information Systems Research, INFORMS, vol. 7(3), pages 328-341, September.
  • Handle: RePEc:inm:orisre:v:7:y:1996:i:3:p:328-341
    DOI: 10.1287/isre.7.3.328
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/isre.7.3.328
    Download Restriction: no

    File URL: https://libkey.io/10.1287/isre.7.3.328?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dawn G. Gregg & Uday R. Kulkarni & Ajay S. Vinzé, 2001. "Understanding the Philosophical Underpinnings of Software Engineering Research in Information Systems," Information Systems Frontiers, Springer, vol. 3(2), pages 169-183, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orisre:v:7:y:1996:i:3:p:328-341. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.