Using fuzzy set theoretic techniques to identify preference rules from interactions in the linear model: an empirical study
Journal Article (Journal Article)
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. We 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 xor) 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. © 1995.
Full Text
Duke Authors
Cited Authors
- Mela, CF; Lehmann, DR
Published Date
- April 28, 1995
Published In
Volume / Issue
- 71 / 2
Start / End Page
- 165 - 181
International Standard Serial Number (ISSN)
- 0165-0114
Digital Object Identifier (DOI)
- 10.1016/0165-0114(94)00266-A
Citation Source
- Scopus