Modeling Toothpaste Brand Choice: An Empirical Comparison of Artificial Neural Networks and Multinomial Probit Model

Tolga Kaya; Emel Aktaş; İlker Topçu; Burç Ülengin

doi:10.2991/ijcis.2010.3.5.15

Modeling Toothpaste Brand Choice: An Empirical Comparison of Artificial Neural Networks and Multinomial Probit Model

Tolga Kaya^*, Emel Aktaş, İlker Topçu, Burç Ülengin

^*Bu çalışma için yazışmadan sorumlu yazar

İşletme Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: Dergiye katkı › Makale › bilirkişi

1 Atıf (Scopus)

Özet

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.

Orijinal dil	İngilizce
Sayfa (başlangıç-bitiş)	674-687
Sayfa sayısı	14
Dergi	International Journal of Computational Intelligence Systems
Hacim	3
Basın numarası	5
DOI'lar	https://doi.org/10.2991/ijcis.2010.3.5.15
Yayın durumu	Yayınlandı - Eki 2010

Bibliyografik not

Publisher Copyright:
© 2010, the authors.

Belgeye Erişim

10.2991/ijcis.2010.3.5.15

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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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{\textquoteright}s predictions are better while MNP is useful in providing marketing insight.",

keywords = "Brand choice modeling, artificial neural networks, household panel, multinomial probit, toothpaste",

author = "Tolga Kaya and Emel Akta{\c s} and İlker Top{\c c}u and Bur{\c c} {\"U}lengin",

note = "Publisher Copyright: {\textcopyright} 2010, the authors.",

year = "2010",

month = oct,

doi = "10.2991/ijcis.2010.3.5.15",

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T2 - An Empirical Comparison of Artificial Neural Networks and Multinomial Probit Model

AU - Kaya, Tolga

AU - Aktaş, Emel

AU - Topçu, İlker

AU - Ülengin, Burç

PY - 2010/10

Y1 - 2010/10

N2 - 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.

AB - 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.

KW - Brand choice modeling

KW - artificial neural networks

KW - household panel

KW - multinomial probit

KW - toothpaste

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U2 - 10.2991/ijcis.2010.3.5.15

DO - 10.2991/ijcis.2010.3.5.15

M3 - Article

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JO - International Journal of Computational Intelligence Systems

JF - International Journal of Computational Intelligence Systems

IS - 5

ER -

Modeling Toothpaste Brand Choice: An Empirical Comparison of Artificial Neural Networks and Multinomial Probit Model

Özet

Bibliyografik not

Belgeye Erişim

Diğer Dosyalar ve Linkler

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