Mining bike-sharing travel behavior data: An investigation into trip chains and transition activities

This study aims to explore the travel behavior of bike-sharing users in Zhongshan, China. To this end, we use 5 months of trip data, which included origin and destination locations, and pickup and return time of each used bike in the system. To get a complete picture of the behavior, we distinguished between trips, trip chains, and transition activities. We categorized different trip chains and constructed transition matrices between activities. We found that almost all trips have different origin and destination stations. Two thirds of the trips are part of a trip chain consisting of multiple trips. Although users often use another station to start their next trip, a clear picture emerges in which public bikes are used as a single mode to hop from one destination to another, and at the end return more or less to the same location where the trip chain was started. Moreover, based on the trip chain matrices and transition matrices between activities, we conclude that users mainly used public bikes for commuting, and some of users went home during lunch break, while the system was also used or after-work shopping activities.