Tan, Yong YTFang, Zhen2022-07-142022-07-142022-07-142022Fang_washington_0250E_24192.pdfhttp://hdl.handle.net/1773/48858Thesis (Ph.D.)--University of Washington, 2022This 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.application/pdfen-USnoneAssortment ManagementCharitable CrowdfundingKnowledge SharingStreaming MediaStructural ModelVoice FeatureBusiness administrationManagementBusiness administrationThesis