Modeling toothpaste brand choice: an empirical comparison of artificial neural networks and multinomial probit model
Date published
2010-10-01
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Volume Title
Publisher
Atlantis Press: Part of Springer Nature
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Article
ISSN
1875-6891
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Citation
Kaya T, Aktas E, Topcu I, Ulengin B. (2010) Modeling toothpaste brand choice: an empirical comparison of artificial neural networks and multinomial probit model. International Journal of Computational Intelligence Systems, Volume 3, Issue 5, October 2010, pp. 674-687
Abstract
The purpose of this study is to compare the performances of Artificial Neural Networks (ANN) and Multinomial Probit (MNP) approaches in modeling the choice decision within fast moving consumer goods sector. To do this, based on 2597 toothpaste purchases of a panel sample of 404 households, choice models are built and their performances are compared on the 861 purchases of a test sample of 135 households. Results show that ANN's predictions are better while MNP is useful in providing marketing insight.
Description
Change of publisher from Taylor & Francis to Atlantis Press: Part of Springer Nature
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Github
Keywords
Brand choice modeling, artificial neural networks, multinomial probit, toothpaste, household panel
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Attribution-NonCommercial 4.0 International