Ride-hail is front and center in the future of mobility. The last decade witnesses the spectacular rise of a disruptive innovation in this industry: the so-called e-hail service pioneered by Uber and Lyft. Unlike conventional taxis hailed off street (or s-hail), e-hail connects passengers and drivers to make exclusive personal auto trips through their smart phones. E-hail service providers are poised to dominate the era of Mobility-as-a-Service (MaaS) as they strive to replace not only taxis, but also most (if not all) private automobiles. The objective of this project is to better understand the physics and economics of ride-hail through data-driven analysis and modeling. Built on this foundation, it further aims to explore the limits of ride-hail, and analyzes operational and policy decisions prescribed to reach its full potential. The project is motivated by a surprising preliminary finding. It indicates that e-hail is a mixed blessing: the technology increases the total factor production of the industry by more than an order of magnitude, but also produce an unintended consequence that substantially reduces its returns to scale.
|Effective start/end date||9/1/19 → 8/31/22|
- National Science Foundation (CMMI-1922665)
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