Free Rides in Dockless, Electric Vehicle Sharing Systems

44 Pages Posted: 7 Jun 2019 Last revised: 26 Jun 2019

See all articles by Bobby Nyotta

Bobby Nyotta

University of California, Los Angeles (UCLA) - Anderson School of Management

Fernanda Bravo

University of California, Los Angeles (UCLA) - Anderson School of Management

Jacob Feldman

Washington University in St. Louis - John M. Olin Business School

Date Written: May 21, 2019

Abstract

We study free-ride policies as a mechanism to incentivize users of a "dockless" or "free-floating" electric vehicle sharing system (EVSS) to park vehicles at charging stations in order to maintain a charged fleet.

A balanced system has a fleet that is adequately charged and evenly dispersed throughout the city. If left to unfold naturally, the system would fall out of balance, and revenue and customer experience might suffer. Most sharing systems use manual repositioning to achieve this balance, but we consider pricing incentives as an alternative method.

We develop an infinite horizon dynamic program to analyze free-ride policies. We focus on an EVSS that offers free rides to customers if they return vehicles to charging stations. We build on this initial formulation to construct a mixed-integer program that outputs intuitive, battery-threshold rules for when to offer free rides. We also extend the model to accommodate more general discount-based policies. In a discrete-event simulation model using real data from an EVSS, we compare the performance of this simple policy against other sophisticated policies, including the commonly used fi ne-based policy.

We fi rst find that the simple threshold-based policy performs close to a more sophisticated, black-box policy in terms of revenue. We also discover that the free-ride policies generate customer utilities that are ten times higher than fi ne-based policies, but also generate less revenue. However, free-ride policies can be less costly to implement since they rely on manual repositioning up to 65-75% less than the benchmarking policies. Our simulation reveals this three-dimensional trade-off between customer satisfaction, revenue, and operational complexity. Furthermore, we fi nd that the cost of repositioning and the customer heterogeneity in the likelihood to accept a discount are major drivers of the frequency of free-ride offers. Our results are robust under many demand patterns and under a variety of network settings.

Keywords: vehicle sharing, electric vehicles, dynamic programming, revenue management

Suggested Citation

Nyotta, Bobby and Bravo, Fernanda and Feldman, Jacob, Free Rides in Dockless, Electric Vehicle Sharing Systems (May 21, 2019). Available at SSRN: https://ssrn.com/abstract=3391937 or http://dx.doi.org/10.2139/ssrn.3391937

Bobby Nyotta (Contact Author)

University of California, Los Angeles (UCLA) - Anderson School of Management ( email )

110 Westwood Plaza
Los Angeles, CA 90095-1481
United States

Fernanda Bravo

University of California, Los Angeles (UCLA) - Anderson School of Management ( email )

110 Westwood Plaza
Los Angeles, CA 90095-1481
United States

Jacob Feldman

Washington University in St. Louis - John M. Olin Business School ( email )

One Brookings Drive
Campus Box 1133
St. Louis, MO 63130-4899
United States

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