Essays on Emerging Digital Platform Policies

Abstract

This dissertation focuses on emerging policies and strategies on different digital platforms. In three different contexts, the charitable crowdfunding, the streaming media, and the knowledge sharing platform, I study the impact of platform’s policies and how the platforms should design their policy. In the first essay, I study the effect of match funds on income inequality on an educational crowdfunding platform. I build a structural model to characterize utility of donation for donors. I find that people prefer to contribute to projects with match offers, and those high-poverty projects can benefit the most from match offers. In the second essay, I investigate the content producing policies for streaming media companies. I build an analytical model and maximize the customer engagement to find optimal policies. I find that the coverage intervals of products should overlap to reach optimal profit, and products should be placed closer where the density of customers is higher. In the third essay, I examine the effect of auditions and voice features on a payment-based knowledge sharing platform. I extract voice features leveraging natural language processing techniques and construct an aggregated demand model to estimate the effects. I find that audition can boost demand, especially for those highly relevant auditions. Voice features also play important roles in attracting customers, and I also provide several related suggestions for live contributors.