Analyzing Frictions in Generalized Second-Price Auction Markets
Karthik Kannan, Vandith Pamuru, Yaroslav Rosokha
Information Systems Research · 2023 · Volume 34 · Issue 4
Abstract
We investigate the role of frictions in determining the efficiency and bidding behavior in a generalized second-price auction—the most preferred mechanism for sponsored-search advertisements. In particular, we take a twofold approach of Q-learning–based computational simulations in conjunction with human-subject experiments. We find that the lower valued advertisers (who do not win the auction) exhibit highly exploratory behavior. Moreover, we find the presence of market frictions moderates this phenomenon and results in higher allocative efficiency. These results have implications for policymakers and auction-platform managers in designing incentives for more efficient auctions. History: Ahmed Abbasi, Senior Editor; Idris Adjerid, Associate Editor. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1187 .
Keywords
auctions, generalized second-price auctions, human-subject experiments, Q-learning, machine learning, reinforcement learning
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