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Activity Number:
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435
- Contributed Poster Presentations: Section on Statistics in Marketing
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Type:
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Contributed
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Date/Time:
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Wednesday, August 10, 2022 : 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 #322648
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Title:
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Multinomial Logit Parameter Estimation in the Presence of Product Missingness
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Author(s):
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Thilini Saram* and David Hunter and Aydin Alptekinoglu
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Companies:
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Pennsylvania State University and Pennsylvania State University and Pennsylvania State University
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Keywords:
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EM algorithm;
Discrete Choice Models;
Baum-Welch algorithm;
Hidden Markov Model
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Abstract:
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Discrete choice models predict the choices among two or more discrete alternatives. Missingness of product availability is a challenge to choice models. We provide evidence that failing to account for product availability leads to bias in demand estimates and use an illustrative example to demonstrate this. We study a weekly grocery purchase dataset that does not contain availability of products. We propose a new model that introduces product availability as a missing variable. We use a Baum-Welch algorithm as the expectation step of an expectation-maximization (EM) algorithm to estimate parameters in a hidden Markov model (HMM). We use a simulation study to compare the models’ prediction accuracy and fit the new model to the illustrative example.
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Authors who are presenting talks have a * after their name.
