CS-ECON Seminar Series

Dynamic Pricing in Rideshare Platforms

Speaker:Siddhartha Banerjee
Date: Friday, April 1, 2016
Time: 12:00pm - 1:00pm
Location: 318 Gross Hall, Duke
Lunch will be provided.


Ride-sharing platforms such as Lyft and Uber are among the fastest growing online marketplaces. A key feature of these platforms is the implementation of fine-grained, fast-timescale dynamic pricing -- where prices can react to the instantaneous system state, and across very small geographic areas. In this talk, we will explore the value of such fast-timescale dynamic pricing, using a queueing model for ride-share platforms, which combines the stochastic dynamics of the platform's operations with strategic models of both passenger and driver behavior. Using this model, we will show that dynamic pricing is not better than the optimal static price in most settings. However, finding the optimal static price requires exact knowledge of system parameters; we will also show that dynamic pricing is much more robust to fluctuations in these parameters as compared to static prices. Thus, our work suggests that dynamic pricing does not necessarily buy more than static pricing, but rather, it lets rideshare platforms realize the benefits of optimal static pricing with imperfect knowledge of system parameters.


Sid Banerjee is Assistant Professor of Operations Research and Information Engineering at Cornell University. He received his PhD in 2013 from the ECE Department at UT Austin, and was a postdoctoral researcher in the Social Algorithms Lab at Stanford from 2013 to 2015. He was a technical consultant at Lyft in 2014, and also interned at the Technicolor Paris Research Lab and Alcatel-Lucent Bell Labs in 2011 and 2009 respectively. He is interested in stochastic modeling and the design of algorithms and incentives for large-scale settings, with applications in matching markets, social computing and socio-economic and communications networks.

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