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Published April 2017 | Published + Submitted
Book Section - Chapter Open

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 short- ages; 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.

Additional Information

© 2017 International World Wide Web Conference Committee (IW3C2), published under Creative commons CC BY 4.0 License. The work of Zhixuan Fang and Longbo Huang was supported in part by the National Natural Science Foundation of China Grants 61672316, 61303195, the Tsinghua Initiative Research Grant, and the China youth 1000-talent grant. The work of Adam Wierman was supported in part by NSF Grants AitF-1637598, CNS-1518941. The work was partially done when Longbo Huang and Adam Wierman were with the Simons institute for the Theory of Computing at Berkeley. The authors also want to thank Didi Chuxing for data usage authorization.

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Submitted - 1604.01627.pdf

Published - p53-fang.pdf


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August 19, 2023
August 19, 2023