Essays on Personalization and Market Design in Mobile Advertising
| dc.contributor.advisor | Yoganarasimhan, Hema | |
| dc.contributor.author | Rafieiankoopaei, Omid | |
| dc.date.accessioned | 2020-08-14T03:27:21Z | |
| dc.date.available | 2020-08-14T03:27:21Z | |
| dc.date.issued | 2020-08-14 | |
| dc.date.submitted | 2020 | |
| dc.description | Thesis (Ph.D.)--University of Washington, 2020 | |
| dc.description.abstract | Personalization and market design are two pillars of mobile advertising that resulted in a dramatic growth in this industry over the past few years. In this dissertation, I focus on these two topics and study the new challenges and opportunities that arise in mobile advertising industry. In particular, I study the consequences of improved user trackability and sequential ad delivery in mobile in-app advertising. Chapter 2 focuses on the former and examine the privacy implications of it in a competitive environment, whereas Chapter 3 studies the latter and quantifies the effects of variety of previous ads on users’ engagement with the next ad. In Chapters 4 and 5, I combine the findings from the first two chapters and develop an Adaptive Ad Sequencing framework that determines how a publisher can personalize a sequence of ads for a user to maximize engagement, as well as how it can monetize these sequences through auctions to optimize revenues. | |
| dc.embargo.terms | Open Access | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.other | Rafieiankoopaei_washington_0250E_21725.pdf | |
| dc.identifier.uri | http://hdl.handle.net/1773/45873 | |
| dc.language.iso | en_US | |
| dc.rights | none | |
| dc.subject | Advertising | |
| dc.subject | Dynamic Programming | |
| dc.subject | Machine Learning | |
| dc.subject | Market Design | |
| dc.subject | Personalization | |
| dc.subject | Privacy | |
| dc.subject | Marketing | |
| dc.subject.other | Business administration | |
| dc.title | Essays on Personalization and Market Design in Mobile Advertising | |
| dc.type | Thesis |
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