Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/5544
Title: Modeling toothpaste brand choice: An empirical comparison of artificial neural networks and multinomial probit model
Authors: Kaya, T
Aktas, E
Topcu, YI
Ulengin, B
Keywords: Brand choice modeling;Artificial neural networks;Multinomial probit;Toothpaste;Household panel
Issue Date: 2010
Publisher: Atlantis Press
Citation: International Journal of Computational Intelligence Systems, Vol 3-5: 674 - 687, Oct 2010
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: Copyright @ 2010 Atlantis Press
URI: http://bura.brunel.ac.uk/handle/2438/5544
DOI: http://dx.doi.org/10.2991/ijcis.2010.3.5.15
ISSN: 1875-6891
Appears in Collections:Business and Management
Brunel Business School Research Papers

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