A Pareto optimal mechanism for demand-side platforms in real time bidding advertising markets
文献类型：期刊论文
| 作者 | Qin, Rui1,2,4 ; Yuan, Yong1,2; Wang, Fei-Yue1,2,3
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| 刊名 | INFORMATION SCIENCES
 |
| 出版日期 | 2018-12-01 |
| 卷号 | 469页码:119-140 |
| 关键词 | Computational advertising Real time bidding Demand side platform Pareto optimal Mechanism design Computational experiment |
| ISSN号 | 0020-0255 |
| DOI | 10.1016/j.ins.2018.08.012 |
| 通讯作者 | Wang, Fei-Yue(feiyue.wang@ia.ac.cn) |
| 英文摘要 | Real time bidding (RTB) advertising has been widely recognized as one of the most promising big-data-driven business models, and a fast-growing research field of computational advertising in recent years. In RTB markets, each ad impression is sold through a two-stage resale auction session, in which demand side platforms (DSPs) play an important role as intermediators. Specifically, DSPs buy ad impressions from the Ad Exchange (AdX) platform and resell them to their registered advertisers, who are interested in the target audience behind the ad impressions. The mechanism design of this two-stage resale auction is a hot research topic and also a critical component in maintaining the effectiveness and efficiency of the RTB ecosystems. In this paper, we strive to identify and design a new mechanism for this auction model in stochastic market environments, with the aim of maximizing the total expected revenue of the winning advertiser and the DSP, and improving the expected revenues for both the winning advertiser and the DSP from each ad impression. Our proposed new mechanism is Pareto optimal for the advertisers and DSPs. We study the equivalent forms of our proposed mechanism in cases when the stochastic market environments can be characterized by uniformly or normally distributed random variables, respectively. We also validate our auction mechanism using the computational experiment approach. The experimental results indicate that our mechanism can make both advertisers and DSPs better off. Our work is expected to provide useful managerial insights for DSPs in RTB market practice. (C) 2018 Elsevier Inc. All rights reserved. |
| WOS关键词 | SPONSORED SEARCH AUCTIONS ; FRAMEWORK ; KEYWORDS ; DESIGN |
| 资助项目 | National Natural Science Foundation of China[71702182] ; National Natural Science Foundation of China[71472174] ; National Natural Science Foundation of China[61533019] ; National Natural Science Foundation of China[71232006] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:000448229800008 |
| 出版者 | ELSEVIER SCIENCE INC |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/21607]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队 |
| 通讯作者 | Wang, Fei-Yue |
| 作者单位 | 1.The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences 2.Qingdao Academy of Intelligent Industries 3.Research Center of Military Computational Experiments and Parallel System, National University of Defense Technology 4.Beijing Engineering Research Center of Intelligent Systems and Technology, Institute of Automation, Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Qin, Rui,Yuan, Yong,Wang, Fei-Yue. A Pareto optimal mechanism for demand-side platforms in real time bidding advertising markets[J]. INFORMATION SCIENCES,2018,469:119-140. |
| APA | Qin, Rui,Yuan, Yong,&Wang, Fei-Yue.(2018).A Pareto optimal mechanism for demand-side platforms in real time bidding advertising markets.INFORMATION SCIENCES,469,119-140. |
| MLA | Qin, Rui,et al."A Pareto optimal mechanism for demand-side platforms in real time bidding advertising markets".INFORMATION SCIENCES 469(2018):119-140. |
入库方式： OAI收割
来源：自动化研究所
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