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...
Váldodahkkit: | , , , , , , , , , , , , , |
---|---|
Materiálatiipa: | Journal article |
Giella: | English |
Almmustuhtton: |
Springer
2004
|
_version_ | 1826293111958011904 |
---|---|
author | Norman, A Ahmed, A Chou, J Dalal, A Fortson, K Jindal, C Kurz, C Lee, H Payne, J Rando, R Sheppard, K Sublett, E Sussman, J White, I |
author_facet | Norman, A Ahmed, A Chou, J Dalal, A Fortson, K Jindal, C Kurz, C Lee, H Payne, J Rando, R Sheppard, K Sublett, E Sussman, J White, I |
author_sort | Norman, A |
collection | OXFORD |
description | 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. |
first_indexed | 2024-03-07T03:25:03Z |
format | Journal article |
id | oxford-uuid:b8c18800-89e4-4ccd-a5c6-bc718dc0df12 |
institution | University of Oxford |
language | English |
last_indexed | 2024-03-07T03:25:03Z |
publishDate | 2004 |
publisher | Springer |
record_format | dspace |
spelling | oxford-uuid:b8c18800-89e4-4ccd-a5c6-bc718dc0df122022-03-27T04:58:07ZOn the Computational Complexity of Consumer Decision Rules.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:b8c18800-89e4-4ccd-a5c6-bc718dc0df12EnglishDepartment of Economics - ePrintsSpringer2004Norman, AAhmed, AChou, JDalal, AFortson, KJindal, CKurz, CLee, HPayne, JRando, RSheppard, KSublett, ESussman, JWhite, IA 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. |
spellingShingle | Norman, A Ahmed, A Chou, J Dalal, A Fortson, K Jindal, C Kurz, C Lee, H Payne, J Rando, R Sheppard, K Sublett, E Sussman, J White, I On the Computational Complexity of Consumer Decision Rules. |
title | On the Computational Complexity of Consumer Decision Rules. |
title_full | On the Computational Complexity of Consumer Decision Rules. |
title_fullStr | On the Computational Complexity of Consumer Decision Rules. |
title_full_unstemmed | On the Computational Complexity of Consumer Decision Rules. |
title_short | On the Computational Complexity of Consumer Decision Rules. |
title_sort | on the computational complexity of consumer decision rules |
work_keys_str_mv | AT normana onthecomputationalcomplexityofconsumerdecisionrules AT ahmeda onthecomputationalcomplexityofconsumerdecisionrules AT chouj onthecomputationalcomplexityofconsumerdecisionrules AT dalala onthecomputationalcomplexityofconsumerdecisionrules AT fortsonk onthecomputationalcomplexityofconsumerdecisionrules AT jindalc onthecomputationalcomplexityofconsumerdecisionrules AT kurzc onthecomputationalcomplexityofconsumerdecisionrules AT leeh onthecomputationalcomplexityofconsumerdecisionrules AT paynej onthecomputationalcomplexityofconsumerdecisionrules AT randor onthecomputationalcomplexityofconsumerdecisionrules AT sheppardk onthecomputationalcomplexityofconsumerdecisionrules AT sublette onthecomputationalcomplexityofconsumerdecisionrules AT sussmanj onthecomputationalcomplexityofconsumerdecisionrules AT whitei onthecomputationalcomplexityofconsumerdecisionrules |