A Customer Purchase Incidence Model Applied to Recommender Services

  • Andreas Geyer-Schulz
  • Michael Hahsler
  • Maximillian Jahn
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2356)


In this contribution we transfer a customer purchase incidence model for consumer products which is based on Ehrenberg’s repeat-buying theory to Web-based information products. Ehrenberg’s repeat-buying theory successfully describes regularities on a large number of consumer product markets. We show that these regularities exist in electronic markets for information goods, too, and that purchase incidence models provide a well founded theoretical base for recommender and alert services.

The article consists of two parts. In the first part Ehrenberg’s repeat-buying theory and its assumptions are reviewed and adapted for web-based information markets. Second, we present the empirical validation of the model based on data collected from the information market of the Virtual University of the Vienna University of Economics and Business Administration from September 1999 to May 2001.


Association Rule Recommender System Information Product Recommender Service Market Basket 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Andreas Geyer-Schulz
    • 1
  • Michael Hahsler
    • 2
  • Maximillian Jahn
    • 2
  1. 1.Universität Karlsruhe (TH)KarlsruheGermany
  2. 2.Wirtschaftsuniversität WienWienAustria

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