Using fuzzy set theoretic techniques to identify preference rules from interactions in the linear model: An empirical study

Using fuzzy set theoretic techniques to identify preference rules from interactions in the linear model: An empirical study

0.00 Avg rating0 Votes
Article ID: iaor1996989
Country: Netherlands
Volume: 71
Issue: 2
Start Page Number: 165
End Page Number: 181
Publication Date: Apr 1995
Journal: Fuzzy Sets and Systems
Authors: ,
Keywords: decision theory
Abstract:

This paper seeks to establish a parametric linkage between fuzzy set theoretic techniques and commonly used preference formation rules in psychology and marketing. Such a linkage helps to benefit both fields. The authors accomplish this objective by using a linear model with interaction term which nests many common preference protocols; conjunction (fuzzy and), disjunction (fuzzy or), counterbalance (fuzzy or) and linear compensatory. The resulting linear model with interactions can be employed when one has no a priori hypothesis about the individual’s preference formation rule involved to determine the most likely preference rule or to test more formally the adequacy of a given rule. One illustrative application studies two-attribute decisions in six product categories and demonstrates differences in preference formation processes by product category. A second application demonstrates how fuzzy logical operators can be applied to situations involving more than two attributes.

Reviews

Required fields are marked *. Your email address will not be published.