Article ID: | iaor20173083 |
Volume: | 65 |
Issue: | 4 |
Start Page Number: | 897 |
End Page Number: | 913 |
Publication Date: | Aug 2017 |
Journal: | Operations Research |
Authors: | Chen Ying-Ju |
Keywords: | advertising, optimization, combinatorial optimization, programming: dynamic, scheduling, allocation: resources |
In this paper, we investigate the optimal dynamic auction design for the display advertising industry. Currently, display advertising is sold through two markets side by side. In the traditional guaranteed market, the publisher commits to deliver a prespecified number of impressions within a fixed time frame through a guaranteed contract. In the spot market, the publisher runs an auction to allocate the impressions every period, and the supply of heterogeneous impressions is highly uncertain and nonstorable. Thus, the publisher must solve a dynamic capacity allocation problem of heterogeneous impressions across different contracts and markets, taking into account the uncertainties from both the demand and supply sides. We characterize the precise trade‐offs between extracting the revenue from the spot markets, materializing the instantaneous benefit shared with the guaranteed advertisers, and releasing the pressure of paying the penalty related to guaranteed contracts. Furthermore, we identify the dual role of the publisher as a system designer and as a bidder on behalf of the guaranteed advertisers. With heterogeneous due dates of guaranteed contracts, we demonstrate the inherent scheduling issue embedded in this dynamic revenue management problem, and completely solve the joint scheduling and capacity allocation problem for some special cases. The online appendix is available at https://doi.org/10.1287/opre.2017.1592.