Ambiguous comparative judgment

Fuzzy set model and data analysis

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Abstract: This paper proposed two types of fuzzy set models for ambiguous comparative judgments, which did not always hold transitivity and comparability properties. The first type of model was a fuzzy theoretical extension of the additive difference model for preference that was used to explain ambiguous preference strength. The second was a fuzzy logic model for explaining ambiguous preference in which preference strength was bounded, such as a probability measure. In both models, multi-attribute weighting parameters and all attribute values were assumed to be asymmetric fuzzy L-R numbers. For each model, a method of parameter estimation using fuzzy regression analysis was proposed. Numerical examples were also provided for comparison. Finally, the theoretical and practical implications of the proposed models were discussed.

Original languageEnglish
Pages (from-to)148-156
Number of pages9
JournalJapanese Psychological Research
Volume49
Issue number2
DOIs
Publication statusPublished - 2007 May

Fingerprint

Fuzzy Logic
Regression Analysis

Keywords

  • Ambiguity
  • Choice
  • Comparative judgment
  • Fuzzy set theories
  • Social judgment

ASJC Scopus subject areas

  • Psychology(all)

Cite this

Ambiguous comparative judgment : Fuzzy set model and data analysis. / Takemura, Kazuhisa.

In: Japanese Psychological Research, Vol. 49, No. 2, 05.2007, p. 148-156.

Research output: Contribution to journalArticle

@article{8ccb4dc2e7f646818ec68f09d0521bac,
title = "Ambiguous comparative judgment: Fuzzy set model and data analysis",
abstract = "Abstract: This paper proposed two types of fuzzy set models for ambiguous comparative judgments, which did not always hold transitivity and comparability properties. The first type of model was a fuzzy theoretical extension of the additive difference model for preference that was used to explain ambiguous preference strength. The second was a fuzzy logic model for explaining ambiguous preference in which preference strength was bounded, such as a probability measure. In both models, multi-attribute weighting parameters and all attribute values were assumed to be asymmetric fuzzy L-R numbers. For each model, a method of parameter estimation using fuzzy regression analysis was proposed. Numerical examples were also provided for comparison. Finally, the theoretical and practical implications of the proposed models were discussed.",
keywords = "Ambiguity, Choice, Comparative judgment, Fuzzy set theories, Social judgment",
author = "Kazuhisa Takemura",
year = "2007",
month = "5",
doi = "10.1111/j.1468-5884.2007.00341.x",
language = "English",
volume = "49",
pages = "148--156",
journal = "Japanese Psychological Research",
issn = "0021-5368",
publisher = "Wiley-Blackwell",
number = "2",

}

TY - JOUR

T1 - Ambiguous comparative judgment

T2 - Fuzzy set model and data analysis

AU - Takemura, Kazuhisa

PY - 2007/5

Y1 - 2007/5

N2 - Abstract: This paper proposed two types of fuzzy set models for ambiguous comparative judgments, which did not always hold transitivity and comparability properties. The first type of model was a fuzzy theoretical extension of the additive difference model for preference that was used to explain ambiguous preference strength. The second was a fuzzy logic model for explaining ambiguous preference in which preference strength was bounded, such as a probability measure. In both models, multi-attribute weighting parameters and all attribute values were assumed to be asymmetric fuzzy L-R numbers. For each model, a method of parameter estimation using fuzzy regression analysis was proposed. Numerical examples were also provided for comparison. Finally, the theoretical and practical implications of the proposed models were discussed.

AB - Abstract: This paper proposed two types of fuzzy set models for ambiguous comparative judgments, which did not always hold transitivity and comparability properties. The first type of model was a fuzzy theoretical extension of the additive difference model for preference that was used to explain ambiguous preference strength. The second was a fuzzy logic model for explaining ambiguous preference in which preference strength was bounded, such as a probability measure. In both models, multi-attribute weighting parameters and all attribute values were assumed to be asymmetric fuzzy L-R numbers. For each model, a method of parameter estimation using fuzzy regression analysis was proposed. Numerical examples were also provided for comparison. Finally, the theoretical and practical implications of the proposed models were discussed.

KW - Ambiguity

KW - Choice

KW - Comparative judgment

KW - Fuzzy set theories

KW - Social judgment

UR - http://www.scopus.com/inward/record.url?scp=34547243059&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34547243059&partnerID=8YFLogxK

U2 - 10.1111/j.1468-5884.2007.00341.x

DO - 10.1111/j.1468-5884.2007.00341.x

M3 - Article

VL - 49

SP - 148

EP - 156

JO - Japanese Psychological Research

JF - Japanese Psychological Research

SN - 0021-5368

IS - 2

ER -