How Do Platform Participants Respond to an Unfair Rating? An Analysis of a Ride-Sharing Platform Using a Quasi-Experiment
36 Pages Posted: 30 Nov 2017
Date Written: October 24, 2017
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.
Keywords: The Sharing Economy, User Generated Content, Ratings
JEL Classification: L86, M37
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