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On the Computational Complexity of Consumer Decision Rules

Author

Listed:
  • 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

Abstract

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.

Suggested Citation

  • 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, 2004. "On the Computational Complexity of Consumer Decision Rules," Computational Economics, Springer;Society for Computational Economics, vol. 23(2), pages 173-192, March.
    • Handle: RePEc:kap:compec:v:23:y:2004:i:2:p:173-192
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    Cited by:

    1. Peter Earl & Jason Potts, 2013. "The creative instability hypothesis," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 37(2), pages 153-173, May.
    2. Earl, Peter E. & Wakeley, Tim, 2010. "Economic perspectives on the development of complex products for increasingly demanding customers," Research Policy, Elsevier, vol. 39(8), pages 1122-1132, October.
    3. repec:ebl:ecbull:v:6:y:2008:i:30:p:1-12 is not listed on IDEAS
    4. A. Norman & M. Aberty & K. Brehm & M. Drake & S. Gour & C. Govil & B. Gu & J. Hart & G. Kadiri & J. Ke & S. Keyburn & M. Kulkarni & N. Mehta & A. Robertson & J. Sanghai & V. Shah & J. Schieck & Y. Siv, 2008. "Can Consumer Software Selection Code for Digital Cameras Improve Consumer Performance?," Computational Economics, Springer;Society for Computational Economics, vol. 31(4), pages 363-380, May.

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