Title :
Determining factors of online auction prices analysis with data mining algorithms on the basis of decision trees
Author :
Lackes, Richard ; Börgermann, Chris ; Frank, Erik
Author_Institution :
Dept. of Bus. Inf. Manage., Tech. Univ. Dortmund, Dortmund, Germany
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.
Keywords :
data mining; decision trees; electronic commerce; pricing; data mining algorithm; decision trees; eBay; online auction price analysis; Biological system modeling; Color; Economics; Marketing and sales; data mining; decision tree; internet auction; online auction; price determinants; price prediction;
Conference_Titel :
Computer Technology and Development (ICCTD), 2010 2nd International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-8844-5
Electronic_ISBN :
978-1-4244-8845-2
DOI :
10.1109/ICCTD.2010.5645877