Work

Scale matters – Why the efficiency of free-floating vehicle sharing systems depends on the system’s scale

Year: 2025

Type: article

Abstract: Over the past decade, free-floating vehicle sharing systems – in particular car and bike sharing – have emerged to a popular urban mobility option. However, providers struggle with efficiency and profitability, resulting in frequent mergers, acquisitions, and business discontinuations. While existing research has focused on improving operations through measures like relocation, pricing, and fleet management, the actual root causes for low system efficiency have not been analyzed in depth yet. Thus, in this work, we focus on identifying these root causes by developing a model that formalizes the mismatch between supply and demand across three different spatial aggregation levels, each referring to a different root cause of supply-demand mismatch: (1) the system’s overall limited supply or demand, (2) the positioning of vehicles on a macro-level, i.e., an unfavorable distribution of vehicles across different zones, and (3) the limited walking distances on a micro-level, i.e., within a single zone. This differentiation yields transparency and allows to derive tailored and effective counter measures. To quantify these effects, we perform an extensive numerical study based on real data. Our findings reveal that larger systems with both more supply and more demand not only achieve higher rental volumes, but also higher fleet utilization and service level. We denote this phenomenon as the matching efficiency of scale effect. Based on the numerical study, we derive valuable managerial insights for providers and policy makers – such as scaling strategies that combine fleet sizing with marketing activities, or targeted subsidies to support vehicle sharing systems. • Identification of root causes for supply-demand mismatch. • Development of a three-level matching model. • Identification of the matching efficiency of scale effect. • Demonstration of high micro matching loss impact through numerical study. • Derivation of managerial insights for providers and policy makers.

Source: Transportation Research Part C Emerging Technologies

DOI: 10.1016/j.trc.2025.105169

Authors: Lisa Urban, Alexander Baur, Matthias Soppert, Claudius Steinhardt

Institution: Universität der Bundeswehr München

Language: English

Topic: Transportation and Mobility Innovations

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $4,040