Abstract: As platforms collect more user data, they can tailor algorithms to better match users.  At the same time, on matching platforms, users pay to be matched by the platform, while the platform makes money as long as it does not match them. This paper analyzes the matching rule of a profit-maximizing monopoly platform when the incentives between users and the platform are misaligned. Contrary to the intuition that more data about users might improve matching efficiency and speed, I show that more data allows the platform to design a matching rule that increases search time and distorts matching and sorting outcomes in the market. I demonstrate that frequently studied matching rules, such as random matching and positive assortative matching, can be suboptimal for the platform. Instead, the platform strategically lowers match quality to increase search time and thus profits, leading to unnecessary delays and potentially inefficient matches. Finally, I provide two explanations for why platforms adopt business models with misaligned incentives: targeted advertising and the presence of overconfident users. 

Abstract:  Users have an incentive to join large platforms, and hence platforms want to convince users that they have a large user base. I consider a monopolist platform's incentive and ability to signal its user base when there is uncertainty regarding the amount of potential users. The platform can signal using either fake accounts or prices. When --- as in some real-world examples --- users are naive regarding the platform's ability to use fake accounts, small platforms use them to profit from the artificial increase in demand. If users are sophisticated, larger platforms use fake profiles to differentiate themselves from smaller ones, and --- in contrast to the case of naive consumers --- platforms would benefit from a ban on such business practices. 

Abstract:  We consider a market in which sellers privately choose vertical product qualities, consumers receive information about the chosen qualities according to a predetermined information structure, and the sellers then compete à la Bertrand given consumers' posterior beliefs. We characterize the set of possible outcomes for different market and information structures. When there is a single monopoly seller, the seller-optimal information structure fully reveals the quality and incentivizes welfare-maximizing quality production. Under competition, the seller-optimal symmetric information structure is coarse and incentivizes randomization in quality choice. This leads to vertical differentiation in the buyer’s posterior beliefs resulting in inefficient allocation and quality provision.

Abstract: With two exclusive manufacturer-retailer pairs and secret contracting, we show that potential strategic misinterpretations and misunderstandings by retailers are important for the feasibility of manufacturer collusion in vertically related markets. We model the retailer’s (potentially incorrect) expectations about their competitor’s wholesale price offers. If retailer’s beliefs are stubborn and they incorrectly believe collusion to be infeasible, it is impossible for manufacturers to collude. By contrast, if retailers anticipate the collusive strategy and condition their action on past offers, collusion becomes feasible. We introduce the property of opportunism-proofness that excludes profitable joint deviations by the collusive entity and discuss adaptive beliefs.

Abstract: This paper examines the use of fake profiles by two-sided platforms to stimulate demand and increase profits. By deceiving naïve users, platforms invest into an artificial increase of the network size on one side of the market. Whereas firms are caught in a prisoner’s dilemma if users single-home on both sides of the market, users are protected by platform competition. If users on one side of the market multi-home, firms can increase their prices for the multi-homing side, and they lower their prices for the single-homing side. Investments into fake profiles stimulate demand, such that multi-homing demand and profits increase. Platforms and users as a group can profit from investments under these circumstances.