Abstract Details
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Activity Number:
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192
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Type:
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Contributed
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Date/Time:
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Monday, August 5, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Marketing
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| Abstract - #308001 |
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Title:
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Clustering of Respondents and Diagnostics for Choice-Based Conjoint
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Author(s):
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Robert Mee*+ and Wenjun Zhou
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Companies:
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University of Tennessee and University of Tennessee
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Keywords:
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Hierarchical Bayes ;
Multinomial logit ;
Segmentation ;
Clustering
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Abstract:
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Aggregate estimates from the multinomial logit (MNL) model are often not representative of the preferences of individual respondents. Hierarchical Bayes (HB) estimation provides the most popular means for estimating individual preferences. However, HB can be computationally intensive. We contrast use of individual HB estimates with a simpler approach that clusters respondents into homogeneous groups and then uses aggregate estimates of the MNL model parameters for each cluster. We also present a diagnostic for identifying respondents giving suspect responses.
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Authors who are presenting talks have a * after their name.
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