Learning Curve: A Simulation-Based Approach to Dynamic Pricing

By employing dynamic pricing, sellers have the potential to increase their revenue by selling their goods at prices customized to the buyers’ demand, the market environment, and the seller’s supply at the moment of the transaction. As dynamic pricing becomes a necessary competitive maneuver, and as market mechanisms become more complex, there is a growing need for software agents to be used to automate the task of implementing implementation of instantaneous prices changes. But prior to using dynamic pricing agents, sellers need to understand the implications of agent pricing strategies on their marketplaces. The following article presents the Learning Curve Simulator, a market simulator designed for analyzing agent pricing strategies in markets under finite time horizons and fluctuation buyer demand. Through an in-depth description of the simulator’s capabilities and an example of strategy analysis, we demonstrate the strength of a simulation-based approach to understanding agent pricing strategies.