Prices and Subsidies in the Sharing Economy

The growth of the sharing economy is driven by the emergence of sharing platforms, e.g., Uber and Lyft, that match owners looking to share their resources with customers looking to rent them. The design of such platforms is a complex mixture of economics and engineering, and how to "optimally" design such platforms is still an open problem. In this paper, we focus on the design of prices and subsidies in sharing platforms. Our results provide insights into the tradeoff between revenue maximizing prices and social welfare maximizing prices. Specifically, we introduce a novel model of sharing platforms and characterize the profit and social welfare maximizing prices in this model. Further, we bound the efficiency loss under profit maximizing prices, showing that there is a strong alignment between profit and efficiency in practical settings. Our results highlight that the revenue of platforms may be limited in practice due to supply shortages; thus platforms have a strong incentive to encourage sharing via subsidies. We provide an analytic characterization of when such subsidies are valuable and show how to optimize the size of the subsidy provided. Finally, we validate the insights from our analysis using data from Didi Chuxing, the largest ridesharing platform in China.
Longbo Huang is an assistant professor at the Institute for Interdisciplinary Information Sciences (IIIS) at Tsinghua University, Beijing, China. He received his Ph.D. in EE from the University of Southern California in August 2011, and then worked as a postdoctoral researcher in the EECS dept. at University of California at Berkeley from July 2011 to August 2012. Dr. Huang has been a visiting scholar at the LIDS lab at MIT and at the EECS department at UC Berkeley, and a visiting professor at the Chinese University of Hong Kong, Bell-labs France and Microsoft Research Asia (MSRA). He was a visiting scientist at the Simons Institute for the Theory of Computing at UC Berkeley in Fall 2016. Dr. Huang was selected into China's Youth 1000-talent program in 2013, and received the outstanding teaching award from Tsinghua university in 2014. Dr. Huang has served as the lead guest editor for the JSAC special issue on "Human-In-The-Loop Mobile Networks" in 2016, and an associate editor for ACM Transactions on Modeling and Performance Evaluation of Computing Systems (ToMPECS) in 2017-2019. Dr. Huang's current research interests are in the areas of online learning, network optimization, online algorithm design, and sharing economy.