Optimising shared electric mobility hubs: Insights from performance analysis and factors influencing riding demand

Abstract

In order to decarbonise the transport networks, systemic change is needed. One manifestation of this transformation is shared electric mobility, seeking to curtail car usage and ownership. This current case study aims to measure and optimise the operational performance of shared electric mobility hubs (eHUBs). From the performance results of eHUBs, one can get helpful insights to develop appropriate future planning and management policies for improving the transport chain. Incorporating data from September 2021 to October 2022, this research developed a novel dynamic two-stage data envelopment analysis (DEA) framework to assess the performance of the eHUB network in Inverness, Scotland. In the first stage, the DEA model computes relative efficiency scores related to the operational performance of the stations. The second stage focuses on network analysis and examining the factors that may influence the high or low obtained performance scores. Scrupulous analysis shows that the population in the catchment area of the eHUBs and the weather conditions (specifically, temperature) are among the most important factors influencing riding demand. The study also finds a weak association between eHUBs efficiency and proximity to public transport stops, suggesting that electric-assist bikes (e-bikes, pedelecs) may not strongly complement public transport, unlike bike-sharing systems. It indicates that e-bikes serve rather as a standalone mode for longer journeys. The findings of the case study can be used to improve sustainable mobility strategies, particularly related to e-bikes in other cities and urban areas.