Modeling toothpaste brand choice: an empirical comparison of artificial neural networks and multinomial probit model

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dc.contributor.authorKaya, Tolga
dc.contributor.authorAktas, Emel
dc.contributor.authorTopçu, Ilker
dc.contributor.authorUlengin, Burç
dc.date.accessioned2022-11-03T14:44:46Z
dc.date.available2022-11-03T14:44:46Z
dc.date.issued2010-10-01
dc.descriptionChange of publisher from Taylor & Francis to Atlantis Press: Part of Springer Nature
dc.description.abstractThe 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.en_UK
dc.identifier.citationKaya 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. 674-687en_UK
dc.identifier.issn1875-6891
dc.identifier.urihttps://doi.org/10.2991/ijcis.2010.3.5.15
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/18652
dc.language.isoenen_UK
dc.publisherAtlantis Press: Part of Springer Natureen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectBrand choice modelingen_UK
dc.subjectartificial neural networksen_UK
dc.subjectmultinomial probiten_UK
dc.subjecttoothpasteen_UK
dc.subjecthousehold panelen_UK
dc.titleModeling toothpaste brand choice: an empirical comparison of artificial neural networks and multinomial probit modelen_UK
dc.typeArticleen_UK

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