Learning Curve: Analysis of an Agent Pricing Strategy Under Varying Conditions

By employing dynamic pricing, the act of changing prices over time within a marketplace, sellers have the potential to increase their revenue by selling goods to buyers “at the right time, at the right price.” As dynamic pricing systems become necessary as a competitive maneuver and as market mechanisms become more complex, there is a greater need for pricing agents to be used, and also a greater challenge for sellers to understand what is the best agent pricing strategy for their marketplaces. This paper addresses these issues by presenting a market simulator designed for analyzing agent pricing strategies for a market in which a seller has a finite amount of time to sell a finite number of goods. Through an in-depth analysis of our ‘Goal-Directed’ pricing strategy, we demonstrate the use of our market simulator as a means for understanding the relevant factors in determining an effective dynamic pricing strategy.