Design Information Disclosure under Bidder Heterogeneity in Online Advertising Auctions: Implications of Bid-Adherence Behavior
Zhu Mingxi, Song Michelle

TL;DR
This paper examines how bid information disclosure affects online advertising auctions, revealing bidder heterogeneity and proposing models to optimize disclosure policies for better platform revenue and efficiency.
Contribution
It introduces a structural equilibrium model for GSP auctions accounting for bidder heterogeneity and analyzes the impact of disclosure policies on revenue and efficiency.
Findings
Moderate information disclosure increases revenue.
Bidder strategies vary significantly, affecting optimal disclosure.
Adherence to recommendations is often suboptimal for bidders.
Abstract
Bidding is a key element of search advertising, but the variation in bidders' valuations and strategies is often overlooked. Disclosing bid information helps uncover this heterogeneity and enables platforms to tailor their disclosure policies to meet objectives like increasing consumer surplus or platform revenue. We analyzed data from a platform that provided bid recommendations based on historical bids. Our findings reveal that advertisers vary significantly in their strategies: some follow the platform's recommendations, while others create their own bids, deviating from the provided information. This highlights the need for customized information disclosure policies in online ad marketplaces. We developed an equilibrium model for Generalized Second Price (GSP) auctions, showing that adhering to bid recommendations with positive probability is suboptimal. We categorized advertisers…
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Taxonomy
TopicsConsumer Market Behavior and Pricing · Technology Adoption and User Behaviour · Digital Platforms and Economics
