Research on Antecedents and Consequences of Factors Affecting the Bike Sharing System--- Lessons From Capital Bike Share Program in Washington, D.C.

Abstract

Bike sharing has drawn significant attention in academia and business. People can use bike sharing system to rent a bike at one of many rental stations traveled around the city for a short journey and return it at any station in the city. However, there have been problems raising with the application of the system. This research focuses on what factors affect the bike sharing system operation. Specifically, the research model is combined of Multiple linear regression, Poisson and Topology method. The multiple linear regression is used to analyze the qualitative data, poisson and topology method for quantitative data. Additionally, the antecedents and consequences of each aspect are examined by studying the case in 2011 Washington, D.C., the influence for each individual factor is also measured. By running the method into software R, three facets of environment are concluded as important factors for the bike sharing system. The results indicate that combination of sensory temperature, season and weather impacts the bike sharing system. At the same time, the suitable schedule for stations to reposition or repair the sharing bike can be concluded. The methodology also offers specific insights to city managers for operating the bike sharing systems.