IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v28y1982i2p182-196.html
   My bibliography  Save this article

An Experimental Comparison of Different Approaches to Determining Weights in Additive Utility Models

Author

Listed:
  • Paul J. H. Schoemaker

    (University of Chicago)

  • C. Carter Waid

    (Formerly with St. Edward's University, Austin)

Abstract

Several studies this past decade have examined differences between holistic and decomposed approaches to determining weights in additive utility models. Some have argued that it matters little which procedure is used, whereas others strongly favored particular methods. In this paper we address this controversy experimentally by comparing five conceptually different approaches in terms of their weights and predictive ability. The five methods are (1) multiple linear and non-linear regression analyses of ten and fifteen holistic assessments, (2) direct decomposed tradeoffs as proposed by Keeney and Raiffa (Keeney, R. L., H. Raiffa. 1977. Decisions with Multiple Objectives. Wiley, New York.), (3) a recent eigen-vector technique of Saaty (Saaty, T. L. 1977. A scaling method for priorities in hierarchical structures. J. Math. Psych. 15 (3) 234--281.) involving redundant pairwise comparisons of attributes, (4) a straightforward allocation of hundred importance points, and (5) unit weighting (i.e., equal weighting after standardizing the attributes). The decision task involved college admissions. Subjects were asked to evaluate hypothetical college applicants on the basis of verbal SAT, quantitative SAT, high-school grade point average, and a measure of extra-curricular activity. Linear as well as nonlinear attribute utility functions were used in constructing the additive models. The nonlinear functions were specified graphically by the subjects through selection from five different shapes (i.e., one per attribute). To test the predictive ability of the various models, each subject made twenty separate pairwise comparisons of alternatives (including direction and strength of preference). The prediction criteria were percentage correct predictions as well as correlations (using these twenty pairs). Seventy subjects were tested, using an (order-controlled) within-subject design, in comparing the different methods of weight determination. Monetary incentives were used to enhance motivation. In terms of findings, the methods generally differed systematically concerning the weights given to the various attributes, as well as the variances of the resulting predictions. On average, however, the methods predicted about equally well, except for unit weighting which was clearly inferior. The findings differ in this regard from the general literature. Furthermore, nonlinear models were found to be inferior to linear ones. Finally, subjects judged the methods to differ significantly in difficulty and trustworthiness, which were found to correlate inversely. The overall results raise various applied and theoretical issues, which are discussed.

Suggested Citation

  • Paul J. H. Schoemaker & C. Carter Waid, 1982. "An Experimental Comparison of Different Approaches to Determining Weights in Additive Utility Models," Management Science, INFORMS, vol. 28(2), pages 182-196, February.
  • Handle: RePEc:inm:ormnsc:v:28:y:1982:i:2:p:182-196
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.28.2.182
    Download Restriction: no

    References listed on IDEAS

    as
    1. Ian I. Mitroff, 1972. "The Myth of Objectivity OR Why Science Needs a New Psychology of Science," Management Science, INFORMS, vol. 18(10), pages 613-618, June.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    decision making; additive utility models;

    Statistics

    Access and download statistics

    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:ormnsc:v:28:y:1982:i:2:p:182-196. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Mirko Janc). General contact details of provider: http://edirc.repec.org/data/inforea.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.