Development and transferability of advanced econometric models of bikesharing demand in urban settings

Bikesharing systems (BSS) are becoming increasingly popular in urban areas around the world, as demonstrated by the rapid growth of both the number and the size of these systems in recent years. Understanding and predicting BSS usage patterns is complex, especially because these patterns are often tied to local factors. This thesis aims to contribute to the existing literature on BSS in two ways. First, an econometric model featuring bicycle availability at a station level as a direct metric of analysis is developed. This behaviorally quantitative model accounts for the influence of temporal, meteorological, bicycle infrastructure, built environment and land-use attributes on bicycle availability. More specifically, an ordered regression model - panel mixed generalized ordered logit model - is estimated to accommodate for the influence of exogenous variables and station level unobserved factors. The model estimation is undertaken using BIXI-Montreal data from the summer of 2012. The results show BIXI is used more in the afternoon than in the morning, dense areas tend to be associated with lower availability levels, and interactions of time of day with land use impact availability. The estimated model is validated using a hold-out sample of data from the summer of 2013. The results clearly highlight the satisfactory performance of the proposed framework. The model developed can be employed by BSS operators to arrive at hourly system state predictions and used for rebalancing operations. To illustrate its applicability, an availability prediction exercise is also undertaken. A review of the existing BSS literature indicates that the framework presented in this thesis is the first to model bicycle availability in BSS using detailed temporal and spatial scales. As such, this thesis contributes to advancing the state-of-the-art toolkit available to BSS planners worldwide, and especially in Montreal.Second, a BSS model transferability exercise is conducted using a detailed arrivals and departures framework developed for Montreal by Faghih-Imani et al. (2014) and applying it to data from New York. This allows a direct comparison of the influence of temporal, meteorological, bicycle infrastructure, built environment and land-use variables on BSS usage in these two cities. Results show significant overlap in the influence of weather variables, bicycle infrastructure, and several land-use attributes. However, temporal trends – especially weekend usage patterns – are very different in both cities. Overall, our results are promising for the development of transferable models of bicycle flows in urban areas. It should be noted that this research effort is the first to investigate BSS model transferability between two large cities using a detailed arrivals and departures model that takes into account temporal, meteorological, bicycle infrastructure, built environment and land-use variables.

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