Usage Patterns and Impact Factors of Public Bicycle Systems: Comparison between City Center and Suburban District in Shenzhen

Abstract

With the increasing importance of low-carbon cities, public bicycle systems (PBSs) have become more popular worldwide in recent years. This study proposes a study pipeline framework to explore the usage patterns of the PBSs and to infer critical impact factors leading to different situations. It applies time series analysis on station-based data, and then compares the two systems by using a multinomial logistic regression model to better understand the relationship between public bicycle usage daily changing patterns and underlying spatial and cultural characteristics, which is investigated in a few previous studies. Based on data for the number of available bicycles and slots across all stations, the authors identify general activity patterns and derive different station clusters. For the PBS in city center (Luohu), the general usage depicts commute patterns on working days, and stations are grouped into four clusters. The usage intensity in the nearby suburban district (Longgang) is much lower than that in the city center. Stations are also grouped into four clusters on working days, and all clusters have a smaller range of variation as compared with those in city center. According to the results of multinomial logistic regression, in Luohu, public bicycles play roles of both short distance trips and a complementary tool for vehicle transit facilities. While in Longgang the PBS only serves as a mode to get access to other public transit. The job/housing imbalance and lag in urban infrastructure have been the primary reason for the inefficient use of public bicycles in Longgang. This study provides a research framework that could be reproducible in other problems, benefit optimizing PBSs, and provide guidance for sustainable urban management.