Using Field Experiments to Infer Cross-Side Network Effects in the Ride-Sharing Market : How Does Driver Supply Impact Rider Orders, Cancellations, and Customer Lifetime Value?

In the sharing economy, how do changes in supply impact demand? We study this question by collaborating with a ride-sharing platform to conduct a natural field experiment. Our experimental design employs an instrumental variable strategy: by exogenously manipulating the driver subsidy schedule, we use the subsidy as an instrumental variable to identify the cross-side network effects of driver supply on orders, cancellations, and the aggregate customer lifetime value (CLV) of users. The results show that increasing the number of drivers at work by 1% will increase the number of customer orders by 2.01% and, conditional on the orders, further reduce the cancellation rate by 0.48%. The results also imply a long-term impact on the future revenue and profitability of the platform. We find that, for a 1% increase in the number of drivers working in the afternoon or at night, the aggregate CLV of users will increase by 1.62% or 0.50%, respectively. Our findings can help platforms improve operations, adjust incentives for suppliers, and strengthen the user experience