Efficient Bid Pricing Based on Costing Methods for Internet Bid Systems

Internet bid systems are being widely used of late. In these systems, the seller sets the bid price. When the bid price is set too high compared with the normal price, chances of a successful bid may decrease. When it is set too low, however, based on inaccurate information, it can result in a successful bid yet one with no profit at all. To resolve this problem, an agent is proposed that automatically generates bid prices for sellers based on the similarity of the bidding parameters using past bidding information as well as on various costing methods such as the high-low point method, the scatter diagram method, and the learning curve method. Performance experiments have shown that the number of successful bids with appropriate profits can be increased using the bid pricing agent. Among the costing methods, the learning curve method has shown the best performance. The manner of designing and implementing the bid pricing agent is also discussed.