Revenue in First- and Second-Price Display Advertising Auctions: Understanding Markets with Learning Agents
Published Online:17 Aug 2026https://doi.org/10.1287/isre.2025.2160
References
- (2023) Artificial intelligence: Can seemingly collusive outcomes be avoided? Management Sci. 69(9):5042–5065.Link, Google Scholar
- (2019) Autobidding with constraints. Caragiannis I, Mirrokni VS, Nikolova E, eds. Web Internet Econom. 15th Internat. Conf. WINE 2019 (Springer, Cham, Switzerland), 17–30.Google Scholar
- (2024) Auto-bidding and auctions in online advertising: A survey. ACM SIGecom Exchanges 22(1):159–183.Google Scholar
- (2022) No-regret learning in repeated first-price auctions with budget constraints. Preprint, submitted May 29, https://arxiv.org/abs/2205.14572.Google Scholar
- (2021) Adjustment of bidding strategies after a switch to first-price rules. Pennock DM, Segal I, Seuken S, eds. Proc. 23rd ACM Conf. Econom. Comput. (Association for Computing Machinery, New York), 296.Google Scholar
- (2021) Learning in matrix games can be arbitrarily complex. Proc. Machine Learn. Res. 134:159–185.Google Scholar
- (2022) Artificial intelligence, algorithm design, and pricing. AEA Papers Proc. 112:452–456.Crossref, Google Scholar
- (2025) Lemon ads: Adverse selection in multichannel display advertising markets. Management Sci. 71(12):10244–10260.Link, Google Scholar
- (2022) Artificial intelligence and auction design. Pennock DM, Segal I, Seuken S, eds. Proc. 23rd ACM Conf. Econom. Comput. (Association for Computing Machinery, New York), 30–31.Google Scholar
- (2018) A principal-agent model of bidding firms in multi-unit auctions. Games Econom. Behav. 111:20–40.Crossref, Google Scholar
- (2025) Computing Bayes–Nash equilibrium strategies in auction games via simultaneous online dual averaging. Oper. Res. 73(2):1102–1127.Link, Google Scholar
- (2010) Research commentary—Designing smart markets. Inform. Systems Res. 21(4):688–699.Link, Google Scholar
- (2008) Modeling tacit collusion in auctions. J. Institutional Theoret. Econom. 164(1):163–184.Crossref, Google Scholar
- (2007) Dynamics of bid optimization in online advertisement auctions. Williamson CL, Zurko ME, Patel-Schneider P, Shenoy P, eds. Proc. 16th Internat. Conf. World Wide Web (Association for Computing Machinery, New York), 531–540.Google Scholar
- (2020) Artificial intelligence, algorithmic pricing, and collusion. Amer. Econom. Rev. 110(10):3267–3297.Crossref, Google Scholar
- (2011) An experimental study of information revelation policies in sequential auctions. Management Sci. 57(4):667–688.Link, Google Scholar
- (2013) Auctions with unique equilibria. Kearns M, McAfee P, Tardos É, eds. Proc. Fourteenth ACM Conf. Electronic Commerce (Association for Computing Machinery, New York), 181–196.Google Scholar
- (2024) The complexity of pacing for second-price auctions. Math. Oper. Res. 49(4):2109–2135.Link, Google Scholar
- (2018) Display advertising pricing in exchange markets. Working paper, Fuqua School of Business, Duke University, Durham, NC.Google Scholar
- (2020) Online display advertising markets: A literature review and future directions. Inform. Systems Res. 31(2):556–575.Link, Google Scholar
- (2022) Bypassing performance optimizers of real time bidding systems in display ad valuation. Inform. Systems Res. 33(2):399–412.Link, Google Scholar
- (2021) Tractable equilibria in sponsored search with endogenous budgets. Oper. Res. 69(1):227–244.Link, Google Scholar
- (2022) Multiplicative pacing equilibria in auction markets. Oper. Res. 70(2):963–989.Link, Google Scholar
- (2026) Artificial collusion: Examining supracompetitive pricing by Q-learning algorithms. Management Sci., ePub ahead of print June 9, https://doi.org/10.1287/mnsc.2024.08557.Google Scholar
- (2021) First-price auctions in online display advertising. J. Marketing Res. 58(5):888–907.Crossref, Google Scholar
- (2007) Internet advertising and the generalized second-price auction: Selling billions of dollars worth of keywords. Amer. Econom. Rev. 97(1):242–259.Crossref, Google Scholar
- (2022) Programmatic advertising in 2022: Digital display ads industry. Accessed June 10, 2026, https://www.insiderintelligence.com/insights/programmatic-digital-display-ad-spending/.Google Scholar
- (2003) Tacit collusion in repeated auctions: Uniform versus discriminatory. J. Indust. Econom. 51(3):271–293.Crossref, Google Scholar
- (2011) Numerical simulations of asymmetric first-price auctions. Games Econom. Behav. 73(2):479–495.Crossref, Google Scholar
- (2019) An EU competition law analysis of online display advertising in the programmatic age. Eur. Competition J. 15(1):55–96.Crossref, Google Scholar
- (2014) Economic models as analogies. Econom. J. 124(578):F513–F533.Google Scholar
- (2021) Bidders’ responses to auction format change in internet display advertising auctions. Pennock DM, Segal I, Seuken S, eds. Proc. 23rd ACM Conf. Econom. Comput. (Association for Computing Machinery, New York), 295.Google Scholar
- (2000) Shopbots and pricebots. Moukas A, Ygge F, Sierra C, eds. Agent Mediated Electronic Commerce II. AMEC 1999, Lecture Notes in Computer Science, vol. 1788 (Springer, Berlin), 1–23.Crossref, Google Scholar
- (2010) On evaluating information revelation policies in procurement auctions: A Markov decision process approach. Inform. Systems Res. 21(1):15–36.Link, Google Scholar
- (2020) Optimal no-regret learning in repeated first-price auctions. Oper. Res. 73(1):209–238.Google Scholar
- (2021) Frontiers: Algorithmic collusion: Supra-competitive prices via independent algorithms. Marketing Sci. 40(1):1–12.Link, Google Scholar
- (2015) No-regret learning in Bayesian games. Cortes C, Lawrence ND, Lee DD, Sugiyama M, Garnett R, eds. Adv. Neural Inform. Processing Systems, vol. 28 (Curran Associates Inc., Red Hook, NY), 3061–3069.Google Scholar
- (2021) Algorithmic collusion: Insights from deep learning. Preprint, submitted November 24, http://dx.doi.org/10.2139/ssrn.3785966.Google Scholar
- (2018) Real-time bidding with multi-agent reinforcement learning in display advertising. Cuzzocrea A, Allan J, Paton N, Srivastava D, Agrawal R, Broder A, Zaki M, et al., eds. Proc. 27th ACM Internat. Conf. Inform. Knowledge Management (Association for Computing Machinery, New York), 2193–2201.Google Scholar
- (2021) Autonomous algorithmic collusion: Q-learning under sequential pricing. RAND J. Econom. 52(3):538–558.Crossref, Google Scholar
- (2009) Auction Theory (Academic Press, Burlington, MA).Google Scholar
- (2024) Strategically-robust learning algorithms for bidding in first-price auctions. Bergemann D, Kleinberg R, Saban D, eds. Proc. 25th ACM Conf. Econom. Comput. (Association for Computing Machinery, New York), 893.Google Scholar
- (2020) Bandit Algorithms (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
- (2023) Online ad procurement in non-stationary autobidding worlds. Oh A, Naumann T, Globerson A, Saenko K, Hardt M, Levine S, eds. Adv. Neural Inform. Processing Systems, vol. 36 (Curran Associates, Red Hook, NY), 42552–42575.Google Scholar
- (2020) Sustaining a good impression: Mechanisms for selling partitioned impressions at ad exchanges. Inform. Systems Res. 31(1):126–147.Link, Google Scholar
- (1985) Distributional strategies for games with incomplete information. Math. Oper. Res. 10(4):619–632.Link, Google Scholar
- (1981) Optimal auction design. Math. Oper. Res. 6(1):58–73.Link, Google Scholar
- (2015) Econometrics for learning agents. Roughgarden T, Feldman M, Schwarz M, eds. Proc. Sixteenth ACM Conf. Econom. Comput. (Association for Computing Machinery, New York), 1–18.Google Scholar
- (2021) Bid prediction in repeated auctions with learning. Leskovec J, Grobelnik M, Najork M, Tang J, Zia L, eds. Proc. Web Conf. 2021 (Association for Computing Machinery, New York), 3953–3964.Google Scholar
- OECD (2017) Algorithms and collusion: Competition policy in the digital age. OECD Roundtables on Competition Policy Papers, No. 206, OECD Publishing, Paris.Google Scholar
- (2003) Managing online auctions: Current business and research issues. Management Sci. 49(11):1457–1484.Link, Google Scholar
- (2020) EU competition law in the digital era: Algorithmic collusion as a regulatory challenge. EU Comparative Law Issues Challenges Series 4, 1016–1039.Google Scholar
- (2018) The prevalence of chaotic dynamics in games with many players. Sci. Rep. 8(1):4902.Crossref, Google Scholar
- (2018) Real-time bidding in online display advertising. Marketing Sci. 37(4):553–568.Link, Google Scholar
- (2011) Online learning and online convex optimization. Foundations Trends Machine Learn. 4(2):107–194. Crossref, Google Scholar
- (2004) Tacit collusion in repeated auctions. J. Econom. Theory 114(1):153–169.Crossref, Google Scholar
- (2006) Impact of ROI on bidding and revenue in sponsored search advertisement auctions. Second Workshop Sponsored Search Auctions.Google Scholar
- (2021) Multi-armed bandits for bid shading in first-price real-time bidding auctions. J. Intelligent Fuzzy Systems 41(6):6111–6125.Google Scholar
- (2021) A near-optimal bidding strategy for real-time display advertising auctions. J. Marketing Res. 58(1):1–21.Crossref, Google Scholar
- (1961) Counterspeculation, auctions, and competitive sealed tenders. J. Finance 16(1):8–37.Crossref, Google Scholar
- (2023) Learning to bid in repeated first-price auctions with budgets. Krause A, Brunskill E, Cho K, Engelhardt B, Sabato S, Scarlett J, eds. Internat. Conf. Machine Learn. (PMLR, New York), 36494–36513.Google Scholar
- (2017) GSP: The Cinderella of mechanism design. Barrett R, Cummings R, Agichtein E, Gabrilovich E, eds. Proc. 26th Internat. Conf. World Wide Web (International World Wide Web Conferences Steering Committee, Geneva), 25–32.Google Scholar
- (1985) Game-Theoretic Analyses of Trading Processes (Institute for Mathematical Studies in the Social Sciences, Stanford University, Stanford, CA).Google Scholar
- (2014) A survey on real time bidding advertising. Proc. 2014 IEEE Internat. Conf. Service Oper. Logist. Informatics (IEEE, New York), 418–423.Google Scholar
- (2023) Online learning in contextual second-price pay-per-click auctions. Dasgupta S, Mandt S, Li Y, eds. Proc. 27th Internat. Conf. Artificial Intelligence Statist. (PMLR, New York), 2395–2403.Google Scholar
- (2022) Leveraging the hints: Adaptive bidding in repeated first-price auctions. Koyejo S, Mohamed S, Agarwal A, Belgrave D, Cho K, Oh A, eds. Adv. Neural Inform. Processing Systems, vol. 35 (Curran Associates Inc., Red Hook, NY), 21329–21341.Google Scholar

