Modeling toothpaste brand choice: an empirical comparison of artificial neural networks and multinomial probit model
Loading...
Date published
Free to read from
Authors
Kaya, Tolga
Aktas, Emel
Topçu, Ilker
Ulengin, Burç
Supervisor/s
Journal Title
Journal ISSN
Volume Title
Department
Course name
Type
ISSN
1875-6891
Format
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
Software Description
Software Language
Github
Keywords
Brand choice modeling, artificial neural networks, multinomial probit, toothpaste, household panel
DOI
Rights
Attribution-NonCommercial 4.0 International