Incorporating The Impact Of Spatio-Temporal Interactions On Bicycle Sharing System Demand: A Case Study Of New York Citibike System

Keywords

Bicycle infrastructure; Bicycle sharing systems; Citibike new york; Land use and built environment; Spatial error; Spatial lag; Spatial panel models

Abstract

Recent success of bicycle-sharing systems (BSS) have led to their growth around the world. Not surprisingly, there is increased research towards better understanding of the contributing factors for BSS demand. However, these research efforts have neglected to adequately consider spatial and temporal interaction of BSS station's demand (arrivals and departures). It is possible that bicycle arrival and departure rates of one BSS station are potentially inter connected with bicycle flow rates for neighboring stations. It is also plausible that the arrival and departure rates at one time period are influenced by the arrival and departure rates of earlier time periods for that station and neighboring stations. Neglecting the presence of such effects, when they are actually present will result in biased model estimates. The major objective of this study is to accommodate for spatial and temporal effects (observed and unobserved) for modelling bicycle demand employing data from New York City's bicycle-sharing system (CitiBike). Towards this end, spatial error and spatial lag models that accommodate for the influence of spatial and temporal interactions are estimated. The exogenous variables for these models are drawn from BSS infrastructure, transportation network infrastructure, land use, point of interests, and meteorological and temporal attributes. The results provide strong evidence for the presence of spatial and temporal dependency for BSS station's arrival and departure rates. A hold out sample validation exercise further emphasizes the improved accuracy of the models with spatial and temporal interactions.

Publication Date

6-1-2016

Publication Title

Journal of Transport Geography

Volume

54

Number of Pages

218-227

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.jtrangeo.2016.06.008

Socpus ID

84974555727 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84974555727

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