Date(s) - 03/12/2021
17:00 - 19:00
Categories No Categories
Speaker: Daniel Freund, MIT
Date & Time: December 3, 2021, Friday, 17:00
Abstract: Ride-hailing platforms update prices dynamically to efficiently balance supply and demand. But rapidly changing prices create incentives for riders to wait for high prices to drop. When supply builds up and prices do eventually drop, these patient customers may request en masse, causing a sharp drop in supply that triggers the pricing algorithm to increase prices. We present a simple fluid model that shows how dynamic pricing inherently creates such oscillations in supply and prices when riders are patient and strategic. Moreover, we show that these oscillations in supply levels are inherently inefficient due to the convexity of pickup times as a function of “open”
(dispatchable) supply. We then show that by changing the service model to allow riders to enter a formal FIFO-queue for low prices – instead of requiring them to engage in ad hoc waiting for the price to drop – this inefficiency can be overcome. Further, by managing the system as a spatial priority queue, the platform can operate even more efficiently than it would in the absence of patient riders. We find that this insight is robust with respect to different model assumptions, and continues to hold in stochastic simulations that supplement our analytical results. Beyond this inefficiency on the rider side, we also survey a number of inefficiencies arising from dynamic pricing on the driver side.
Bio: Daniel Freund is the Class of 1947 Career Development Professor and an Assistant Professor of Operations Management at the MIT Sloan School of Management. In his PhD he developed the analytical methods used by bike-sharing systems like New York City’s Citi Bike to inform their rebalancing. Before joining MIT he spent a year as a Research Fellow at Lyft Marketplace Labs where he developed new algorithms and market mechanisms for the ride sharing industry. He has received the 2021 APS Best Publication Award, the 2018 George B. Dantzig Dissertation Award, the 2018 Daniel H. Wagner Prize for Excellence in Operations Research, and a Best Paper Award at the 2018 ACM SIGCAS Conference. He holds a BSc in mathematics from the University of Warwick (UK), as well as an MS and a PhD in applied mathematics from Cornell University, where he was advised by Prof. David B. Shmoys.