| The digital advertising phenomenon has resulted in an entire ecosystem of supply-side and demand-side players, as well as intermediaries that serve to mitigate supply-demand inefficiencies. My dissertation provides prescriptive solutions to three novel operational and strategic challenges faced by different stakeholders in this ecosystem.;The first problem arises from the misalignment of incentives between a supply-side network (a firm that monetizes events of users' visits for a diverse network of websites) and an ad aggregator (a firm that buys events of users' visits to websites or mobile applications on behalf of advertisers). This results in a situation where the supply-side network is left to optimize the click-revenue generated from the traffic (i.e., impressions) it sends to the ad aggregator without knowledge of the objective function. I develop an effective data-driven approach to solve constrained optimization problems in which the decision maker does not have an analytical form for the objective function, but knows what decision variables affect the function.;The second problem arises from the interaction between a supply-side network and advertisers. The challenge faced by the supply-side network is to manage fading ads (or fads) shown to an end user during a session of a mobile application (app). In addition to the question of what ads to show, this ad-sequencing problem also seeks the sequence in which the ads are displayed and the durations for which they are shown. I formulate this problem as a stochastic dynamic program in which uncertainty arises from two sources: the duration for which the user stays on the app and her clicking behavior. Optimal or near-optimal policies for a variety of practical settings are developed.;The third problem originates from the interaction between an ad exchange (a supply-demand matching platform where impressions are sold through real-time auctions) and its participating ad aggregators (bidders). For an impression that is being auctioned by the exchange, the ad aggregators respond with bids based on the information they receive (or possess) about that impression. I examine the impact of impression-related information: How much information should an ad exchange reveal? and a related question: Can ad exchanges make more money by hiding some pertinent attributes of impressions (e.g., identity of the publisher)? I develop good (and simple) information revelation designs and policies for ad exchanges. The welfare implications of these policies on the other stakeholders are also analyzed. |
