Modeling Consideration Sets and Brand Choice Using Artificial Neural Networks
The concept of consideration sets makes brand choice a two-step process. House-holds first construct a consideration set which not necessarily includes all available brands and conditional on this set they make a final choice. In this paper we put forward a parametric econometric model for this two-step process, where we take into account that consideration sets usually are not observed. It turns out that our model is an artificial neural network, where the consideration set corresponds with the hidden layer. We discuss representation, parameter estimation and inference. We illustrate our model for the choice between six detergent brands and show that the model improves upon a one-step multinomial logit model, in terms of fit and out-of-sample forecasting.
|Keywords||artificial neural network, brand choice, consideration set|
|JEL||Statistical Decision Theory; Operations Research (jel C44), Neural Networks and Related Topics (jel C45), Business Administration and Business Economics; Marketing; Accounting (jel M), Marketing (jel M31)|
|Publisher||Erasmus Research Institute of Management|
|Series||ERIM Report Series Research in Management|
|Rights||Copyright 2001, B. Vroomen, P.H.B.F. Franses, E. van Nierop, This report in the ERIM Report Series Research in Management is intended as a means to communicate the results of recent research to academic colleagues and other interested parties. All reports are considered as preliminary and subject to possibly major revisions. This applies equally to opinions expressed, theories developed, and data used. Therefore, comments and suggestions are welcome and should be directed to the authors.|
Vroomen, B.L.K, Franses, Ph.H.B.F, & van Nierop, J.E.M. (2001). Modeling Consideration Sets and Brand Choice Using Artificial Neural Networks (No. ERS-2001-10-MKT). ERIM Report Series Research in Management. Erasmus Research Institute of Management. Retrieved from http://hdl.handle.net/1765/79