Intelligent Personalized Trading Agents that facilitate Real-time Decisionmaking for Auctioneers and Buyers in the Dutch Flower Auctions

Wolfgang Ketter, Eric van Heck and Rob Zuidwijk

ERIM Report Series Research in Management from Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam

Abstract: In this case the Dutch Flower Auctions (DFA) are discussed. The DFA are part of the supply network in which flowers are produced, stocked, and then sold through either mediation or auctioning. This case focuses on the buyers’ and auctioneers’ positions when flowers are traded through auctions. This case deals with the application of personalized agents as part of a Decision Support System which empowers the decision maker. The decision makers discussed in this case are the auctioneers who control the auction process, and the buyers who bid at the clock auction. Agents are defined as software programs that sense their environment and react autonomously on their environment in order to maximize a certain outcome. The agents, as envisioned in this case, are able to determine users’ preferences and based on these preferences agents can proactively make recommendations. Agents as applied to the auction process could empower the auctioneers in their decisions. Another type of agent could empower the buyer, since buyers have the high-pressure task of buying at the clock auction.

Keywords: business intelligence; decision support systems; dutch flower auctions (dfa); learning agents; smart business networks; teaching case (search for similar items in EconPapers)
JEL-codes: L15 M O32 (search for similar items in EconPapers)
Date: 2010-05-02
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