  Understanding the drivers of urban mobility is vital for epidemiology, urban
planning, and communication networks. Human movements have so far been studied
by observing people's positions in a given space and time, though most recent
models only implicitly account for expected costs and returns for movements.
This paper explores the explicit impact of cost and network topology on
mobility dynamics, using data from 2 city-wide public bicycle share systems in
the USA. User mobility is characterized through the distribution of trip
durations, while network topology is characterized through the pairwise
distances between stations and the popularity of stations and routes. Despite
significant differences in station density and physical layout between the 2
cities, trip durations follow remarkably similar distributions that exhibit
cost sensitive trends around pricing point boundaries, particularly with
long-term users of the system. Based on the results, recommendations for
dynamic pricing and incentive schemes are provided to positively influence
mobility patterns and guide improved planning and management of public bicycle
systems to increase uptake.
