An empirical comparison of the validity of a neural net based multinomial logit choice model to alternative model specifications

DOI10.1016/S0377-2217(03)00410-7zbMath1065.90051OpenAlexW1996941263MaRDI QIDQ1876168

Werner Fettes, Markus Probst, Harald Hruschka

Publication date: 16 August 2004

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0377-2217(03)00410-7

zbMATH Keywords

Neural networksBrand choiceMarketingMultilayer perceptronChoice model

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Marketing, advertising (90B60)

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Accommodating heterogeneity and nonlinearity in price effects for predicting brand sales and profits ⋮ A Stackelberg-Nash model for new product design

Cites Work

• Estimating the dimension of a model
• Neural networks: A review from a statistical perspective. With comments and a rejoinder by the authors
• Multilayer feedforward networks are universal approximators
• Partial BFGS Update and Efficient Step-Length Calculation for Three-Layer Neural Networks
• Universal approximation bounds for superpositions of a sigmoidal function
• Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their Derivatives
• Approximation by superpositions of a sigmoidal function
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