Dynamic Auctions with Buy-It-Now Pricing: A Practical Design Model and Experimental Evaluation

Abstract

Several studies have shown that Consumer-to-consumer (C2C) auctions operate below their revenue and efficiency potential. From a theoretical perspective, most auction researchers agree that dynamic prices should improve the performance of these auctions, but it is still unclear whether dynamic prices can achieve significant benefits in practice. This paper uses experiments with economically motivated human subjects to test the benefits of using dynamic prices. Subjects represent buyers or sellers in a simulated trading environment. They are randomly assigned costs and values for. During the experiment subjects trade five virtual products through computer terminals in auctions similar to those held on eBay and generate profits, which subjects receive at the end of the experiment. Our results demonstrate that our specific implementation of a dynamic auction design, using a dynamic buy-it-now pricing strategy, increases seller surplus as well as overall operational efficiency. We also suggest using the method of dynamic programming for discrete stochastic systems to identify better dynamic auction designs in simple settings.

Keywords: auction design, auction performance, buyout price, dynamic auctions, online auctions, experimental economics