Understanding Willingness to Use Dockless Bike Sharing Systems Through Tree and Forest Analytics

In this paper we explore factors that affect Bike Sharing System (BSS) usage and how they differentiate between discrete groups of potential users. BSS have known a rampant growth during recent years, through technological advances, re-evaluated business models and reinvention of the mean’s utility. Yet, for a realized use of dockless BSS and a successful integration in the urban mobility ecosystem to be achieved, the factors that promote willingness to use them need to be explored. By using a sample of 500 stated preference data, classification trees and random forest models are built for three groups of potential BSS users; car users, bus users and pedestrians. Among the considered factors are BSS cost gains, BSS In Vehicle Time (IVT) and Out of Vehicle Time (OVT) gains, trip frequency, purpose and duration. More specific, it was found that BSS potential, increases for short duration trips of up to 21 min for car users. Bus users and pedestrians were found to be more likely to choose a BSS option for a higher cost up to 0,60 and 0,75 euros respectively. On the other side sociodemographic characteristics such as household income, gender, education level and occupation did not found to be the dominant factors for the mode choice decision. OVT is found only to be relatively important for bus users, while the cost gains are comparatively more significant for bus users and pedestrians.