Prices and Subsidies in the Sharing Economy

TL;DR

This paper models sharing platforms to analyze optimal pricing and subsidies, revealing tradeoffs between profit and social welfare, and providing practical insights validated with real-world data from Didi Chuxing.

Contribution

It introduces a novel model for sharing platforms, characterizes profit and welfare-maximizing prices, and analyzes subsidy strategies to enhance sharing efficiency.

Findings

Profit and social welfare maximization prices are characterized.

Subsidies can effectively mitigate supply shortages.

Strong alignment between profit and efficiency in practical scenarios.

Abstract

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.