Probabilistic models of set-dependent and attribute-level best–worst choice

AAJ Marley, TN Flynn, JJ Louviere

    Research output: Contribution to journalArticle (Academic Journal)peer-review

    88 Citations (Scopus)


    We characterize a class of probabilistic choice models where the choice probabilities depend on two scales, one with a value for each available option and the other with a value for the set of available options. Then, we develop similar results for a task in which a person is presented with a profile of attributes, each at a pre-specified level, and chooses the best or the best and the worst of those attribute-levels. The latter design is an important variant on previous designs using best-worst choice to elicit preference information, and there is various evidence that it yields reliable interpretable data. Nonetheless, the data from a single such task cannot yield separate measures of the "importance" of an attribute and the "utility" of an attribute-level. We discuss various empirical designs, involving more than one task of the above general type, that may allow such separation of importance and utility.
    Translated title of the contributionProbabilistic models of set-dependent and attribute-level best–worst choice
    Original languageEnglish
    Pages (from-to)281 - 296
    Number of pages16
    JournalJournal of Mathematical Psychology
    Publication statusPublished - 2008

    Bibliographical note

    Publisher: Elsevier


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