Budget-Management Strategies in Repeated Auctions
成果类型:
Article
署名作者:
Balseiro, Santiago; Kim, Anthony; Mahdian, Mohammad; Mirrokni, Vahab
署名单位:
Columbia University; Amazon.com; Alphabet Inc.; Google Incorporated
刊物名称:
OPERATIONS RESEARCH
ISSN/ISSBN:
0030-364X
DOI:
10.1287/opre.2020.2073
发表日期:
2021
页码:
859-876
关键词:
Online advertising
repeated auctions
budget constraints
throttling
thresholding
bid shading
reserve pricing
multiplicative boosting
mechanism design
incentives
摘要:
In online advertising, advertisers purchase ad placements by participating in a long sequence of repeated auctions. One of the most important features that advertising platforms often provide and advertisers often use is budget management, which allows advertisers to control their cumulative expenditures. Advertisers typically declare the maximum daily amount they are willing to pay, and the platform adjusts allocations and payments to guarantee that cumulative expenditures do not exceed budgets. There are multiple ways to achieve this goal, and each one, when applied to all budget-constrained advertisers simultaneously, drives the system toward a different equilibrium. Our goal is to compare the system equilibria of a range of budget-management strategies. In particular, we consider six different budget-management strategies, including probabilistic throttling, thresholding, bid shading, reserve pricing, and two versions of multiplicative boosting. We show that these methods admit a system equilibrium, study their incentive properties, prove dominance relations among them in a simplified setting, and confirm our theoretical findings using real ad auction data from a sponsored search. Our study sheds light on the impact of budget-management strategies on the trade-off between the seller's profit and buyers' utility and may be of practical relevance for advertising platforms.
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