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 comparison by shopbots have motivated sellers to use software agents called pricebots to adjust 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 preferences and, therefore, a seller's pro t 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 depending on the buyers' purchase criteria and then charges a dierent price for each segment. Simulation results of our algorithm indicate that sellers' pro ts are improved by charging dierent prices to buyers with different purchase criteria