How Do Platform Participants Respond To An Unfair Rating An Analysis Of A Ride Sharing Platform Using A Quasi Experiment

Online rating systems can lead, on occasion, to reviews that are unfair or un-representative of the true quality provided. On the one hand, receiving an unfairly low rating once, might induce someone a platform supplier to exert more effort and receive a better rating the next time. On the other hand, it might dispirit suppliers and make them exert less effort. We use data from a ride-sharing platform in India where driver ratings were made particularly salient to the driver after each trip. Our data suggests that if a customer experiences a ride cancellation, they are more likely to unfairly blame the replacement driver. We use this as a exogenous source of unfair negative ratings for the driver. We show that drivers are more likely to respond negatively to a bad rating and receive subsequently bad ratings if they were blameless for the previous negative rating. This effect is larger in contexts where there is a higher potential for an emotional response and when there is a greater need for driver skill in the subsequent ride.