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An Artificial Neural Net Attraction Model (ANNAM) to analyze market share effects of marketing instruments

Hruschka, Harald (2000) An Artificial Neural Net Attraction Model (ANNAM) to analyze market share effects of marketing instruments. Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science", 48. SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, Vienna.

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Abstract

Attraction models are very popular in marketing research for studying the effects of marketing instruments on market shares. However, so far the marketing literature only considers attraction models with certain functional forms that exclude threshold or saturation effects on attraction values. We can achieve greater exibility by using the neural net based approach introduced here. This approach assesses brands' attraction values by means of a perceptron with one hidden layer. The approach uses log-ratio transformed market shares as dependent variables. Stochastic gradient descent followed by a quasi Newton method estimates parameters. For store-level data, neural net models perform better and imply a price response that is qualitatively different from the well-known multinomial logit attraction model. Price elasticities of neural net attraction models also lead to specific managerial implications in terms of optimal prices. (author's abstract)

Item Type: Paper
Keywords: Marketinginstrument / Marktanteil / neuronales Netz / Modell
Divisions: Departments > Informationsverarbeitung u Prozessmanag. > Produktionsmanagement > Taudes
Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Departments > Marketing > Service Marketing und Tourismus
Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft
Depositing User: Repository Administrator
Date Deposited: 08 Mar 2002 12:08
Last Modified: 25 Nov 2014 23:21
URI: http://epub.wu.ac.at/id/eprint/940

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