CS-ECON Seminar Series
Dynamic Pricing in Rideshare Platforms
||Friday, April 1, 2016
||12:00pm - 1:00pm
||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.
Hosted by: Kamesh Munagala