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On the Computational Complexity of Consumer Decision Rules

Listed author(s):
  • A. Norman


  • A. Ahmed
  • J. Chou
  • A. Dalal
  • K. Fortson
  • M. Jindal
  • C. Kurz
  • H. Lee
  • K. Payne
  • R. Rando
  • K. Sheppard
  • E. Sublett
  • J. Sussman
  • I. White

A consumer entering a new bookstore can face more than 250,000 alternatives. The efficiency of compensatory and noncompensatory decision rules for finding a preferred item depends on the efficiency of their associated information operators. At best, item-by-item information operators lead to linear computational complexity; set information operators, on the other hand, can lead to constant complexity. We perform an experiment demonstrating that subjects are approximately rational in selecting between sublinear and linear rules. Many markets are organized by attributes that enable consumers to employ a set-selection-by-aspect rule using set information operations. In cyberspace decision rules are encoded as decision aids.

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Article provided by Springer & Society for Computational Economics in its journal Computational Economics.

Volume (Year): 23 (2004)
Issue (Month): 2 (03)
Pages: 173-192

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Handle: RePEc:kap:compec:v:23:y:2004:i:2:p:173-192
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