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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Vydané v:Computational economics Ročník 23; číslo 2; s. 173 - 192
Hlavní autori: 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.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Dordrecht Society for Computational Economics 01.03.2004
Springer Nature B.V
Edícia:Computational Economics
Predmet:
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
On-line prístup:Získať plný text
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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.
AbstractList 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.
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. [PUBLICATION ABSTRACT]
Author White, I.
Fortson, K.
Chou, J.
Norman, A.
Payne, K.
Lee, H.
Sublett, E.
Sheppard, K.
Kurz, C.
Ahmed, A.
Dalal, A.
Rando, R.
Sussman, J.
Jindal, M.
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CitedBy_id crossref_primary_10_1016_j_respol_2010_05_006
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Cites_doi 10.2307/1884852
10.1037/h0026750
10.1016/0167-2681(87)90006-0
10.1093/0198295278.001.0001
10.1016/0001-6918(80)90031-1
10.1037/h0032955
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Snippet A consumer entering a new bookstore can face more than 250,000 alternatives. The efficiency of compensatory and noncompensatory decision rules for finding a...
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StartPage 173
SubjectTerms 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
Title On the Computational Complexity of Consumer Decision Rules
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