Representation and Inference of Lexicographic Preference Models and Their Variants
AbstractThe authors propose two variants of lexicographic preference rules. They obtain the necessary and sufficient conditions under which a linear utility function represents a standard lexicographic rule, and each of the proposed variants, over a set of discrete attributes. They then: (i) characterize the measurement properties of the parameters in the representations; (ii) propose a nonmetric procedure for inferring each lexicographic rule from pairwise comparisons of multiattribute alternatives; (iii) describe a method for distinguishing among different lexicographic rules, and between lexicographic and linear preference models; and (iv) suggest how individual lexicographic rules can be combined to describe hierarchical market structures. The authors illustrate each of these aspects using data on personal-computer preferences. They find that two-thirds of the subjects in the sample use some kind of lexicographic rule. In contrast, only one in five subjects use a standard lexicographic rule. This suggests that lexicographic rules are more widely used by consumers than one might have thought in the absence of the lexicographic variants described in the paper. The authors report a simulation assessing the ability of the proposed inference procedure to distinguish among alternative lexicographic models, and between linear-compensatory and lexicographic models.
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Bibliographic InfoArticle provided by INFORMS in its journal Marketing Science.
Volume (Year): 26 (2007)
Issue (Month): 3 (05-06)
lexicographic preferences; noncompensatory preference models; linear models; optimization techniques; greedy algorithm; approximation algorithms; utility theory; conjoint analysis; hierarchical clustering; market segmentation; hierarchical market structures;
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