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Tight upper bounds for the expected loss of lexicographic heuristics in binary multi-attribute choice

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  • Carrasco, Juan A.
  • Baucells, Manel

Abstract

Tight upper bounds for the expected loss of the DEBA (Deterministic-Elimination-By-Aspects) lexicographic selection heuristic are obtained for the case of an additive separable utility function with unknown non-negative, non-increasing attribute weights for numbers of alternatives and attributes as large as 10 under two probabilistic models: one in which attributes are assumed to be independent Bernouilli random variables and another one with positive inter-attribute correlation. The upper bounds improve substantially previous bounds and extend significantly the cases in which a good performance of DEBA can be guaranteed under the assumed cognitive limitations.

Suggested Citation

  • Carrasco, Juan A. & Baucells, Manel, 2008. "Tight upper bounds for the expected loss of lexicographic heuristics in binary multi-attribute choice," Mathematical Social Sciences, Elsevier, vol. 55(2), pages 156-189, March.
    • Handle: RePEc:eee:matsoc:v:55:y:2008:i:2:p:156-189
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    Cited by:

    1. Manel Baucells & Juan A. Carrasco & Robin M. Hogarth, 2008. "Cumulative Dominance and Heuristic Performance in Binary Multiattribute Choice," Operations Research, INFORMS, vol. 56(5), pages 1289-1304, October.
    2. Konstantinos V. Katsikopoulos, 2013. "Why Do Simple Heuristics Perform Well in Choices with Binary Attributes?," Decision Analysis, INFORMS, vol. 10(4), pages 327-340, December.
    3. Konstantinos V. Katsikopoulos, 2011. "Psychological Heuristics for Making Inferences: Definition, Performance, and the Emerging Theory and Practice," Decision Analysis, INFORMS, vol. 8(1), pages 10-29, March.

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