Chen Jin, National University of Singapore; Kartik Hosanagar, Operations, Information and Decisions, The Wharton School; and Senthil Veeraraghavan, Operations, Information and Decisions, The Wharton School
Abstract: Traditional online platforms (e.g., Amazon Marketplace) use Unilateral Rating System (URS), where customers rate sellers. However, sharing economy platforms (e.g., Uber, Airbnb) have adopted Bilateral Rating System (BRS) that also allows service providers to rate customers, and even selects customers based on their ratings. BRS is often purported to be better than URS, as BRS unlocks more hidden information than URS by revealing ratings of customers to service providers before they make acceptance/rejection decisions. We compare URS and BRS in the context of the ride-sharing service to study its impact on all stakeholders in the system. Conventional wisdom suggests that BRS would harm riders, as riders can be rejected by drivers while platforms should benefit from BRS, since it unlocks the value in the riders’ rating that can be potentially extracted. We find that contrary to this intuition, BRS may increase riders’ welfare under some conditions, as drivers rejecting low-rating riders can reduce the excess demand and the associated inconvenience cost born by all riders in the system. BRS can both improve or reduce the platform’s revenue, as there is a tug-of-war between the platform and drivers on the revenue share. Under the right conditions, BRS can result in a win-win-win situation for the drivers, riders and the platform.
Watch Chen Jin discuss his research here.