Essays in industrial organization

This dissertation consists of four chapters in Industrial Organization. Chapter 1 and 3 study optimal business models for digital goods and personalized marketing strategies on online platforms. Chapter 2 and 4 explore agents' heterogeneous performance in the marketplace. In the first chapter, along with the coauthor Jacob LaRiviere, I study optimal business models for video games using data from Xbox. Offering content via bundle-based subscription services has become a prevalent business strategy for media platforms. Despite its popularity, there is limited empirical evidence on whether the subscription model can generate better outcomes for customers and content providers than the traditional a la carte sales model. We answer this question using a novel proprietary dataset from the Xbox video game platform. We develop and estimate a model of demand and supply for individual games and the subscription service Game Pass. We find consumer surplus increases by 16% on average when Game Pass is introduced. The decomposition analysis shows that the bundling and renting features of the subscription service contribute almost equally to the surplus change. We further use the model to study alternative subscription model designs. We find that when all games are offered only via a grand subscription bundle, consumer surplus decreases by 38% from its level under the traditional sales model, with low-usage and slowly-satiated customers being the most affected. However, welfare outcomes can be greatly improved if the platform offers multiple tiers of subscription bundles for different segments of customers. On the supply side, content providers are better off under the subscription-only model if they are compensated with more than 70%--80% of the subscription revenue. In the second chapter, along with coauthors Brad Larsen and Anthony Lee Zhang, I study mediators' heterogeneous performance in the bargaining of used cars. We analyze data on tens of thousands of alternating-offer, business-to-business negotiations in the wholesale used-car market, with each negotiation mediated (over the phone) by a third-party company. The data shows the identity of the employee mediating the negotiations. We find that who intermediates the negotiation matters: high-performing mediators are 22.03 percentage points more likely to close a deal than low performers. We provide a decomposition of mediator impact and a structural model of intermediated incomplete-information bargaining. We find that effective mediators improve bargaining outcomes by helping buyers and sellers come to agreements faster, not by pushing disagreeing parties to persist, and have real effects on efficiency for some negotiations, overcoming some of the inefficiency inherent in incomplete-information settings. In the third chapter, along with coauthors Fan Zhang and Zhijie Lin, I study consumers' variety-seeking preferences and explore its implications on the design of recommendation algorithms using data from a food delivery platform. We first document that a substantial fraction of consumers is variety-seeking: they are willing to pay 19.9% more on average for switching to a different seller at the next purchase. We then study how targeted marketing strategies that account for this preference affect the platform participants. In the counterfactual analysis, we find that personalizing seller ranks based on consumers' order history and their variety-seeking preference increases revenue by 18% and consumer surplus by 14%. Furthermore, we find that the existence of consumers' variety-seeking preferences softens the price competition. Our simulated optimal targeted pricing strategy implies an increase in prices for rival sellers' consumers and a decrease in prices for the sellers' own consumers. In the fourth chapter, along with the coauthor Xinyao Qiu, I explore the gender gap in business performances among freelancers selling home-cooked meals, an area that is traditionally perceived as female-typed and involves complicated business strategy-making. Using high-quality proprietary data from a Chinese P2P online food ordering platform, we document a 12% gender gap in sellers' daily revenues. Factors highlighted in the existing literature such as working hours and experience narrow the gap by 63%. The remaining gap can be explained by male and female freelancers adopting different business strategies in pricing, positioning, and market expansion

Keywords: Economics.
Advisor: Larsen Bradley J.
Einav Liran
Yurukoglu Ali