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.
Mela, Carl, and Donald Lehmann. "Using Fuzzy Set Theoretic Techniques to Identify Preference Rules from Interactions in the Linear Model: An Empirical Study." Fuzzy Sets and Systems 71, no. 2 (April 28, 1995): 165-81.
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