Exploring bikesharing travel time and trip chain by gender and day of the week

As a pinnacle of green transportation with transit attributes, bikesharing has become particularly popular since the mid-2000s. Taking the opportunity of accessing to a large-scale and smart-card-based dataset from Nanjing, China, this paper explores bikesharing travel time and trip chain patterns by gender and day of the week. Bikesharing trip chain is defined and classified into four types according to the complexity of chain. Z-score analysis and visual analytic techniques, as well as chi-statistic, are adopted to explore the variation of bikesharing travel time and trip chain. The results suggest that the residential areas are the primary fountainhead where bikesharing demands generate, whilst the rail stations are the most attractive hubs that the bikesharing trips terminate at. The travel time between the same bikesharing station can be two times longer than it is from one station to another. Bikesharing travel time also differs significantly in terms of gender and day of the week. With respect to bikesharing trip chain patterns, significant variation is observed between men and women, as well as between weekdays and weekends. Findings indicate that women are more likely to make multiple-circle bikesharing trip chains than men, especially on weekdays. Moreover, the visual analytic gives bikesharing operators direct sense of the variation of bikesharing trip chain patterns with respect to gender and day of the week. Last but not least, this paper finds that there is big gap between bikesharing demand and supply in the adjacent area of rail stations in Nanjing, in particular, during afternoon peak hours. (c) 2015 Elsevier Ltd. All rights reserved.