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

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