Paccar Hall, Room 394

SPEAKER: Chen Jin
AFFILIATION:  University of Pennsylvania
AREA:  Information Systems

TITLE:
Impact of Bilateral Rating System on Ride-Sharing Platforms

ABSTRACT:
Platforms in the sharing economy such as Uber and Lyft adopt a bilateral rating system (BRS) that allows service providers to rate and select customers based on their ratings; while in traditional online platforms (e.g., Amazon Marketplace), only customers rate sellers, i.e., a unilateral rating system (URS) is implemented. Bilateral rating systems unlock the hidden value in customers' ratings, which changes the service provider's effort structure in a fundamental way and affects the pricing policy of the platform and the welfare of service providers as well as customers. We compare URS and BRS in the context of ride-sharing service to study their impact on the decisions as well as revenue/welfare of all stakeholders. Our results show that BRS can be a double-edged sword for drivers and the platform. The underlying mechanism is that both drivers and the platform have some control over the other's decision and the relative influence of the control is moderated by customers' valuation of the service. Specifically, when customers value the service more, the value in customers' ratings is relatively less important. In this case, the drivers' "cherry-picking" behavior in selecting customers is costly from the platform's angle, which enables drivers to demand a high revenue share so that their "over-selection" behavior can be mitigated. This increases the drivers' welfare and decreases the platform's revenue compared with URS. When customers' value the service less, the value in customers' ratings is relatively more important. In this cases, the platform could reap the value in customers' ratings by increasing the commission fee, which squeezes the drivers' revenue share and forces drivers to serve only highly rated customers. This leads to reduction in both drivers' revenue share and their transaction volume, which decreases drivers' welfare but the effect of commission fee increment can exceed the effect of transaction volume reduction and hence, increases the platform's total revenue.