Automated Pricing Rules in Electronic Posted Offer Markets

Internet markets are heralded as enhancing efficiency by providing buyers and sellers with an abundance of information. In these electronic markets, firms have the opportunity to employ “pricebots,” computerized algorithms that automatically adjust prices to prevailing market conditions. This article uses laboratory methods to examine the potential market impact of the endogenous selection of three automated pricing algorithms: undercutting, low‐price matching, and trigger pricing. We find that the undercutting algorithm leads to prices similar to the game‐theoretic prediction. Low‐price matching generates significantly higher prices, and trigger pricing results in market prices below the game‐theoretic prediction.