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Attribute Conflict and Preference Uncertainty: The RandMAU Model

Author

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  • Gregory W. Fischer

    (The Fuqua School of Business, Duke University, Durham, North Carolina 27708)

  • Jianmin Jia

    (Faculty of Business Administration, Chinese University of Hong Kong, Hong Kong)

  • Mary Frances Luce

    (The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

Abstract

This paper extends the behavioral results reported in Fischer et al. (2000) by developing a model addressing preference uncertainty in multiattribute evaluation. The model is motivated by two hypotheses regarding properties of multiattribute profiles that lead to greater preference uncertainty. Our attribute conflict hypothesis predicts that greater within-alternative conflict (discrepancy among the attributes of an alternative) leads to more preference uncertainty. Our attribute extremity hypothesis predicts that greater attribute extremity (very high or low attribute values) leads to less preference uncertainty. To provide a deeper explanation of attribute conflict and extremity effects, we develop RandMAU, a family of additive (RandAUF) and multiplicative (RandMUF) random weights multiattribute utility models. In RandMAU models, preference uncertainty is represented as random variation in both the weighting parameters governing trade-offs among attributes and the curvature parameters governing single-attribute evaluations. Simulation results show that RandMUF successfully predicts both the attribute conflict and attribute extremity effects exhibited by the experimental participants in Fischer et al. (2000). It also predicts an outcome value effect on error whose form depends on the shape of single-attribute functions and on the type of multiattribute combination rule.

Suggested Citation

  • Gregory W. Fischer & Jianmin Jia & Mary Frances Luce, 2000. "Attribute Conflict and Preference Uncertainty: The RandMAU Model," Management Science, INFORMS, vol. 46(5), pages 669-684, May.
    • Handle: RePEc:inm:ormnsc:v:46:y:2000:i:5:p:669-684
    DOI: 10.1287/mnsc.46.5.669.12051
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

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    8. Philippe Delquié, 2003. "Optimal Conflict in Preference Assessment," Management Science, INFORMS, vol. 49(1), pages 102-115, January.
    9. A Jessop, 2011. "Using imprecise estimates for weights," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1048-1055, June.
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    11. Richard M. Anderson & Benjamin F. Hobbs, 2002. "Using a Bayesian Approach to Quantify Scale Compatibility Bias," Management Science, INFORMS, vol. 48(12), pages 1555-1568, December.
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