Forecasting e-scooter substitution of direct and access trips by mode and distance

Mina Lee, Joseph Y.J. Chow, Gyugeun Yoon, Brian Yueshuai He

Research output: Contribution to journalArticlepeer-review


An e-scooter trip model is estimated from four U.S. cities: Portland, Austin, Chicago and New York City. A log–log regression model is estimated for e-scooter trips based on user age, population, land area, and the number of scooters. The model predicts 75 K daily e-scooter trips in Manhattan for a deployment of 2000 scooters, which translates to 77 million USD in annual revenue. We propose a novel nonlinear, multifactor model to break down the number of daily trips by the alternative modes of transportation that they would likely substitute based on statistical similarity. The model parameters reveal a relationship with direct trips of bike, walk, carpool, automobile and taxi as well as access/egress trips with public transit in Manhattan. Our model estimates that e-scooters could replace 32% of carpool; 13% of bike; and 7.2% of taxi trips. The distance structure of revenue from access/egress trips is found to differ from that of other substituted trips.

Original languageEnglish (US)
Article number102892
JournalTransportation Research Part D: Transport and Environment
StatePublished - Jul 2021


  • E-scooter
  • Micromobility
  • New York City
  • Nonlinear multifactor model
  • Trip generation

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Transportation
  • General Environmental Science


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