Determining factors of online auction prices analysis with data mining algorithms on the basis of decision trees

Abstract

The impressive scale of online auctions sales and the economic eco-system of private and commercial providers, made eBay & Co. interesting for science. As part of this work determinants will be identified which affect the outcome of online auctions to a large extent. We observed that for identical (new) products often different prices were charged and that the price volatility is bound to the auction characteristics. By evaluating a large number of online auctions using the decision tree method we derive significant rules that determine the auction success. This gives the market participants, but also the platform operator, additional insights they can take into account with regard to their market activities. © 2011 Springer-Verlag Berlin Heidelberg.