Reputation Tracking Procurement Auctions

  • Ana Petric
  • Gordan Jezic
Conference paper

DOI: 10.1007/978-3-642-04441-0_72

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5796)
Cite this paper as:
Petric A., Jezic G. (2009) Reputation Tracking Procurement Auctions. In: Nguyen N.T., Kowalczyk R., Chen SM. (eds) Computational Collective Intelligence. Semantic Web, Social Networks and Multiagent Systems. ICCCI 2009. Lecture Notes in Computer Science, vol 5796. Springer, Berlin, Heidelberg

Abstract

The introduction of e-markets has created great challenges for both buyers and suppliers. Buyers have to decide how to take advantage of the possibilities offered on e-markets (i.e., higher savings, expanding the supplier base) but at the same time they should preserve values that are associated with their long-term relationships. As the use of reverse auctions in the industry grows,involved parties are increasingly concerned with how these auctions influence their previously established business relationships. Due to those existing relationships, reverse auctions should not be analyzed as stand-alone auctions. If the relationship is specified as a value-generating asset in the procurement process, then neither business party should expect relationships to be harmed. We propose a reputation tracking reverse auction model that exploits the advantages reverse auctions bring to buyers, while decreasing the disadvantages they bring to sellers. Several experiments were conducted and the analysis was focused on auctions that have different outcomes depending on whether they took reputation into account or not.

Keywords

reputation reverse auctions procurement multi-attribute auctions B2B e-market 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ana Petric
    • 1
  • Gordan Jezic
    • 1
  1. 1.Faculty of Electrical Engineering and ComputingUniversity of ZagrebZagrebCroatia

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