ANNAM. An artificial neural net attraction model to analyze market shares.

Harald Hruschka

Publikation: Working/Discussion PaperWU Working Paper

Abstract

The marketing literature so far only considers attraction models with strict functional forms. Greater exibility can be achieved by the neural net based approach introduced which assesses brands' attraction values by means of a perceptron with one hidden layer. Using log-ratio transformed market shares as dependent variables stochastic gradient descent followed by a quasi-Newton method estimates parameters. For store-level data the neural net model performs better and implies a price response qualitatively different from the well-known MNL attraction model. Price elasticities of these competing models also lead to specific managerial implications. (author's abstract)
OriginalspracheEnglisch
ErscheinungsortVienna
HerausgeberSFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business
PublikationsstatusVeröffentlicht - 1999

Publikationsreihe

NameWorking Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"
Nr.32

WU Working Paper Reihe

  • Working Papers SFB \Adaptive Information Systems and Modelling in Economics and Management Science\

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