On the Computational Complexity of Consumer Decision Rules

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...

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Bibliographic Details
Published in:Computational economics Vol. 23; no. 2; pp. 173 - 192
Main Authors: Norman, A., Ahmed, A., Chou, J., Dalal, A., Fortson, K., Jindal, M., Kurz, C., Lee, H., Payne, K., Rando, R., Sheppard, K., Sublett, E., Sussman, J., White, I.
Format: Journal Article
Language:English
Published: Dordrecht Society for Computational Economics 01.03.2004
Springer Nature B.V
Series:Computational Economics
Subjects:
Algorithms
Bookstores
Complexity
Consumer behavior
Consumers
Decision making
Decisions
Economic models
Economics
Grocery stores
Information
Internet
Linear programming
Operators
Optimization techniques
Shopping
Studies
Utility functions
ISSN:0927-7099, 1572-9974
Online Access:Get full text
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Summary: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.
Bibliography:SourceType-Scholarly Journals-1
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ISSN:0927-7099
1572-9974
DOI:10.1023/B:CSEM.0000021676.64701.12