Date of Award


Degree Type


Degree Name

Master of Science in Systems Engineering


Mechanical, Industrial and Systems Engineering

First Advisor

Valerie Maier-Speredelozzi


Bicycle sharing quickly became a popular mode of transportation in urban environments in the United States until the COVID-19 pandemic was officially announced. System providers have faced a severe loss in the number of individuals who used bicycle sharing systems (BSS), although cycling was recommended to engage social distancing. While other BSS met the ridership level of the previous year in the short term, the BSS Capital Bikeshare (CaBi) still can not build on prior-year numbers. Because today´s bicycle-sharing business is fiercely competitive, a high service level and customer satisfaction are keys to achieving a sustainable operation. This thesis aims to understand how usage patterns of the CaBi system changed in spatial and temporal aspects before and after the first twelve months of the COVID-19 pandemic outbreak on March 7th, 2020, which may affect the BSS’s processes.

A literature review was conducted to accomplish that goal, and data analysis approaches and clustering algorithms were applied to the time series data from March 2019 till March 2021. First, based on the literature review, the raw data was analyzed with basic statistical metrics to distinguish the number of trips and trip duration for both periods. Second, the member type of riders was analyzed, as well as the temporal distribution of trips. Applying the k-means clustering algorithm, stations with similar rental activities corresponding to the hour of the day and trip duration were categorized in the third step.

Overall, it can be said that a significant change in temporal usage patterns of the stations has been noticed, whereas the spatial clusters have not changed during the pandemic. Bicycle-sharing operators and urban planners can use those insights and the aggregated list of factors influencing BSS use to enhance inventory management, dynamic bicycle relocation, dynamic demand management, locating new stations, or planning bicycle networks for cyclists and bicycle sharing riders.



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