Full-information maximum likelihood estimation of brand positioning maps using supermarket scanning data

Eric Waarts, Martin Carree, Berend Wierenga

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    The authors build on the idea put forward by Shugan to infer product maps from scanning data. They demonstrate that the actual estimation procedure used by Shugan has several methodological problems and may yield unstable estimates. They propose an alternative estimation procedure, full-information maximum likelihood (FIML), which addresses the problems and yields significantly improved results. An important additional advantage of the procedure is that the parameters of the preference distribution can be estimated simultaneously with the brand coordinates. Hence, it is not necessary to assume a fixed (uniform) distribution of preferences. An empirical application is presented in which the outcomes obtained from Shugan's procedure are compared with those from the proposed procedure.
    Original languageEnglish
    Pages (from-to)483-490
    Number of pages8
    JournalJournal of Marketing Research
    Issue number4
    Publication statusPublished - Nov 1991

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