| dc.description.abstract | The interaction between the bike-sharing behavior and public transportation system is still not fully understood. This paper aims to explore the impacts of public transportation disruption on the bike-sharing behavior utilizing the metro shutdown case in Washington, DC, in 2016. Multisource data, including bicycle trip and geographic information, was collected before, during, and after the public transportation disruption. Through the spatial-temporal analysis, it is a recurrent pattern for bike-sharing members to take their trips on weekdays and the casual users without membership to take the trips on weekends. Moreover, it is noted that the bike-sharing trips for casual user increased 191% and the variation of trip duration is insignificant on metro shutdown day. The bike-sharing stations adjacent to the metro lines are found to experience a higher trip increase. Furthermore, the complex network approach was employed to explore the bike-sharing network properties. In network perspective, the connectivity of bike-sharing network has increased due to the shifted travelers. In addition, the modularity maximization approach was also introduced to infer the community structure of bike-sharing network. The results suggest the disruption strengthen the interaction between central clusters and outer clusters. Implications for further research, policy, and design are discussed. | |
