The Role of Surge Pricing on a Service Platform with Self-Scheduling Capacity

Abstract

Recent platforms, like Uber and Lyft, offer service to consumers via “self-scheduling” providers who decide for themselves how often to work. These platforms may charge consumers prices and pay providers wages that adjust based on prevailing demand conditions. For example, Uber uses “surge pricing” which pays providers a fixed commission of its dynamic price. With a stylized model that yields analytical and numerical results, we study several pricing schemes that could be implemented on a service platform, including surge pricing. Our base model places no restrictions on the platform’s dynamic pricing and waging schemes, whereas our surge pricing analogue requires wages to be a fixed fraction of dynamic prices and our traditional taxi analogue requires prices to be fixed. We show that although surge pricing is not optimal, it generally achieves nearly the optimal profit, justifying its use in practice. Despite its merits for the platform, surge pricing has been criticized due to concerns for the welfare of consumers. In our model, as labor becomes more expensive, consumers are better off with surge pricing relative to fixed pricing because they benefit both from lower prices during normal demand and expanded access to service during peak demand. We conclude, in contrast to popular criticism, that both the platform and consumers can benefit from the use of surge pricing on a platform with self-scheduling capacity.

This chapter is adapted from Cachon et al. (2017), reprinted by permission, Gerard P Cachon, Kaitlin M Daniels & Ruben Lobel, The Role of Surge Pricing on a Service Platform with Self-Scheduling Capacity, Manufacturing & Service Operations Management, 2017. Copyright 2017, the Institute for Operations Research and the Management Sciences, 5521 Research Park Drive, Suite 200, Catonsville, MD 21228 USA.