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Activity Number:
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314
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Type:
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Invited
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Date/Time:
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Tuesday, July 31, 2007 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics and Marketing
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| Abstract - #307873 |
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Title:
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Market Share Constraints and the Loss Function in Choice-Based Conjoint Analysis
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Author(s):
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Timothy Gilbride*+ and Peter Lenk and Jeff Brazell
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Companies:
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University of Notre Dame and The University of Michigan and The Modellers, LLC
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Address:
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315 Mendoza College of Business, Notre Dame, IN, 46530,
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Keywords:
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Hierarchical Bayes ; Loss Function ; Bayesian Decision Theory ; Conjoint Analysis
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Abstract:
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Choice-based conjoint analysis is a popular marketing research technique to learn about consumers' preferences and to make market share forecasts. Managers expect these forecasts to be "realistic" in terms of being able to replicate market shares at some pre-specified or "base case" scenario. Frequently, there is a discrepancy between the forecasted and base case market share. This paper presents a Bayesian decision theoretic approach to incorporating base case market shares into conjoint analysis via the loss function. We specify an appropriate loss function and all estimates are formally derived via minimizing the posterior expected loss. We contrast this approach to using informative priors. MCMC methods for performing the analysis are presented. The approach is demonstrated with simulated data and actual market research studies using both multinomial logit and probit models.
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