Dynamic Tiered Pricing in a Multi-Agent Economy

Abstract Shopbots or software agents that enable comparison shopping of items from dierent online sellers have become popular for quick and easy shopping among online buyers. Rapid searches and price compar-ison by shopbots have motivated sellers to use software agents called pricebots to ad-just their prices dynamically so that they can maintain a competitive edge in the market. Existing pricebots charge the same price for an item from all of their customers. Online consumers dier in their purchasing pref-erences and, therefore, a seller's prot can be increased by charging two dierent prices for the same good from price-insensitive and price-sensitive consumers. In this paper, we present an algorithm that partitions the buyer population into dierent segments de-pending on the buyers ' purchase criteria and then charges a dierent price for each seg-ment. Simulation results of our algorithm indicate that sellers ' prots are improved by charging dierent prices to buyers with dif-ferent purchase criteria