Lemon Ads: Adverse Selection in Multichannel Display Advertising Markets

逆向选择 广告 选择(遗传算法) 业务 展示广告 营销 计算机科学 在线广告 互联网 人工智能 万维网 精算学
作者
Francesco Balocco,Yixin Lu,Ting Li,Alok Gupta
出处
期刊:Management Science [Institute for Operations Research and the Management Sciences]
标识
DOI:10.1287/mnsc.2022.03407
摘要

Two auction-based channels play a crucial role in facilitating transactions of ad impressions in display advertising: real-time bidding (RTB), which is accessible to all advertisers, and private marketplace (PMP), which is restricted to a select group of advertisers through invitation-based agreements with publishers. Despite the ongoing discourse on the benefits and drawbacks of these two channels, how their coexistence influences the market dynamics and outcomes remains an open question. In this paper, we investigate this question by focusing on the welfare implications of publishers’ channel adoption. First, using a game-theoretic model, we show that publishers who use both RTB and PMP can leverage their private information on impression quality to sell lower-quality impressions at higher prices in RTB, leading to adverse selection and exposing their RTB-only counterparts to losses. To validate our theoretical prediction, we conduct an empirical analysis using a large proprietary data set. The results provide strong evidence of the presence of adverse selection. In particular, we find that, all else being equal, RTB impressions from dual-channel publishers are of significantly lower quality compared with those from single-channel publishers. Our findings shed light on the nuanced dynamics between RTB and PMP and contribute to the understanding of the complex interplay of informational and strategic factors in the display advertising market. This paper was accepted by Anindya Ghose, information systems. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03407 .
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