This chapter reviews the recent developments at the intersection of personalization and AI in
marketing and related fields. We provide a formal definition of personalized policy and …

Revenue management (RM) is the application of analytical methodologies and tools that
predict consumer behavior and optimize product availability and prices to maximize a firm's …

Automated auction design aims to find empirically high-revenue mechanisms through
machine learning. Existing works on multi item auction scenarios can be roughly divided into …

In classic auction theory, reserve prices are known to be effective for improving revenue for
the auctioneer against quasi-linear utility maximizing bidders. The introduction of reserve …

We study the pricing problem faced by a firm that sells a large number of products, described
via a wide range of features, to customers that arrive over time. Customers independently …

In digital online advertising, advertisers procure ad impressions simultaneously on multiple
platforms, or so-called channels, such as Google Ads, Meta Ads Manager, etc., each of …

Stackelberg games are a canonical model for strategic principal-agent interactions.
Consider, for instance, a defense system that distributes its security resources across high …

One of the central problems in auction design is developing an incentive-compatible
mechanism that maximizes the auctioneer's expected revenue. While theoretical …

Online auctions are one of the most fundamental facets of the modern economy and power
an industry generating hundreds of billions of dollars a year in revenue. Auction theory has …

In online advertising markets, setting budget and return on investment (ROI) constraints are
two prevalent ways to help advertisers (ie buyers) utilize limited monetary resources …