• DocumentCode
    3238904
  • 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
  • fYear
    2010
  • fDate
    2-4 Nov. 2010
  • Firstpage
    250
  • Lastpage
    254
  • 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;
  • fLanguage
    English
  • Publisher
    ieee
  • 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
  • Type

    conf

  • DOI
    10.1109/ICCTD.2010.5645877
  • Filename
    5645877