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Related papers: Platform Competition in the Autobidding World

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When online sellers use AI learning algorithms to automatically compete on e-commerce platforms, there is concern that they will learn to coordinate on higher than competitive prices. However, this concern was primarily raised in…

General Economics · Economics 2025-11-03 Hangcheng Zhao , Ron Berman

This note pursues two primary objectives. First, we analyze the outcomes of an all-pay auction within a store where buyers with and without financial constraints arrive at varying rates, and where buyer types are private information.…

Theoretical Economics · Economics 2024-04-16 Cemil Selcuk

We analyze the problem of how to optimally bid for ad spaces in online ad auctions. For this we consider the general case of multiple ad campaigns with overlapping targeting criteria. In our analysis we first characterize the structure of…

Optimization and Control · Mathematics 2020-04-16 Erik Tillberg , Peter Marbach , Ravi Mazumdar

In online ad markets, a rising number of advertisers are employing bidding agencies to participate in ad auctions. These agencies are specialized in designing online algorithms and bidding on behalf of their clients. Typically, an agency…

Computer Science and Game Theory · Computer Science 2023-06-14 Yurong Chen , Qian Wang , Zhijian Duan , Haoran Sun , Zhaohua Chen , Xiang Yan , Xiaotie Deng

Internet advertisers (buyers) repeatedly procure ad impressions from ad platforms (sellers) with the aim to maximize total conversion (i.e. ad value) while respecting both budget and return-on-investment (ROI) constraints for efficient…

Computer Science and Game Theory · Computer Science 2023-02-08 Negin Golrezaei , Patrick Jaillet , Jason Cheuk Nam Liang , Vahab Mirrokni

In this paper, we study the problem of learning to bid in repeated first-price auctions with budget constraints. In each period, the decision maker needs to submit a bid to win the auction and maximize the total collected reward, subject to…

Optimization and Control · Mathematics 2026-03-10 Zeng Fu , Jiashuo Jiang , Yuan Zhou

This paper explores the integration of strategic optimization methods in search advertising, focusing on ad ranking and bidding mechanisms within E-commerce platforms. By employing a combination of reinforcement learning and evolutionary…

Machine Learning · Computer Science 2024-05-30 Chang Zhou , Yang Zhao , Jin Cao , Yi Shen , Xiaoling Cui , Chiyu Cheng

Online bidding serves as a fundamental information system in mobile ecosystems, facilitating real-time ad allocation across billions of devices while optimizing both platform performance and user experience through data-driven decision…

Computer Science and Game Theory · Computer Science 2026-01-07 Huanyu Yan , Yu Huo , Min Lu , Weitong Ou , Xingyan Shi , Ruihe Shi , Xiaoying Tang

Budget management strategies in repeated auctions have received growing attention in online advertising markets. However, previous work on budget management in online bidding mainly focused on second-price auctions. The rapid shift from…

Computer Science and Game Theory · Computer Science 2023-04-27 Qian Wang , Zongjun Yang , Xiaotie Deng , Yuqing Kong

We consider a setting in which bidders participate in multiple auctions run by different sellers, and optimize their bids for the \emph{aggregate} auction. We analyze this setting by formulating a game between sellers, where a seller's…

Computer Science and Game Theory · Computer Science 2020-01-20 Renato Paes Leme , Balasubramanian Sivan , Yifeng Teng

We consider an online ad network problem in which an ad exchange auctions ad slots and intermediaries called demand side platforms (DSPs) buy these ad slots for their clients (advertisers). An intermediary represents multiple advertisers.…

Computer Science and Game Theory · Computer Science 2019-10-07 Rahul Meshram , Kesav Kaza

As commerce shifts to digital marketplaces, platforms increasingly monetize traffic through Sponsored Shopping auctions. Unlike classic ``Sponsored Search", where an advertiser typically bids for a single link, these settings involve…

Computer Science and Game Theory · Computer Science 2026-02-27 Paul Dütting , Yuhao Li , Renato Paes Leme , Kelly Spendlove , Yifeng Teng

Real-Time Bidding is a new Internet advertising system that has become very popular in recent years. This system works like a global auction where advertisers bid to display their impressions in the publishers' ad slots. The most popular…

Computer Science and Game Theory · Computer Science 2020-10-26 Luis Miralles-Pechuán , Fernando Jiménez , José Manuel García

We present a model of digital advertising with three key features: (i) advertisers can reach consumers on and off a platform, (ii) additional data enhances the value of advertiser-consumer matches, and (iii) bidding follows auction-like…

Theoretical Economics · Economics 2024-04-25 Dirk Bergemann , Alessandro Bonatti , Nicholas Wu

With the emergence of new online channels and information technology, digital advertising tends to substitute more and more to traditional advertising by offering the opportunity to companies to target the consumers/users that are really…

Optimization and Control · Mathematics 2021-11-17 Médéric Motte , Huyên Pham

We examine trade-offs among stakeholders in ad auctions. Our metrics are the revenue for the utility of the auctioneer, the number of clicks for the utility of the users and the welfare for the utility of the advertisers. We show how to…

Computer Science and Game Theory · Computer Science 2014-04-22 Yoram Bachrach , Sofia Ceppi , Ian A. Kash , Peter Key , David Kurokawa

Advertisement auctions play a crucial role in revenue generation for e-commerce companies. To make the bidding procedure scalable to thousands of auctions, the automatic bidding (autobidding) algorithms are actively developed in the…

Computer Science and Game Theory · Computer Science 2025-10-23 Andrey Pudovikov , Alexandra Khirianova , Ekaterina Solodneva , Aleksandr Katrutsa , Egor Samosvat , Yuriy Dorn

Contemporary real-world online ad auctions differ from canonical models [Edelman et al., 2007; Varian, 2009] in at least four ways: (1) values and click-through rates can depend upon users' search queries, but advertisers can only partially…

Machine Learning · Computer Science 2024-04-11 Ming Chen , Sareh Nabi , Marciano Siniscalchi

In digital advertising, online platforms allocate ad impressions through real-time auctions, where advertisers typically rely on autobidding agents to optimize bids on their behalf. Unlike traditional auctions for physical goods, the value…

Computer Science and Game Theory · Computer Science 2025-09-03 Zhicheng Du , Wei Tang , Zihe Wang , Shuo Zhang

We consider the problem of bidding in online advertising, where an advertiser aims to maximize value while adhering to budget and Return-on-Spend (RoS) constraints. Unlike prior work that assumes knowledge of the value generated by winning…

Machine Learning · Computer Science 2025-03-06 Sushant Vijayan , Zhe Feng , Swati Padmanabhan , Karthikeyan Shanmugam , Arun Suggala , Di Wang