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The Impact of Cost and Network Topology on Urban Mobility: A Study of Public Bicycle Usage in 2 U.S. Cities

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  • Raja Jurdak

Abstract

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.

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  • Raja Jurdak, 2013. "The Impact of Cost and Network Topology on Urban Mobility: A Study of Public Bicycle Usage in 2 U.S. Cities," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-6, November.
    • Handle: RePEc:plo:pone00:0079396
    DOI: 10.1371/journal.pone.0079396
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    1. Yanyong Guo & Jibiao Zhou & Yao Wu & Zhibin Li, 2017. "Identifying the factors affecting bike-sharing usage and degree of satisfaction in Ningbo, China," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-19, September.
    2. Mateo-Babiano, Iderlina & Bean, Richard & Corcoran, Jonathan & Pojani, Dorina, 2016. "How does our natural and built environment affect the use of bicycle sharing?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 295-307.
    3. Goodman, Brianna & Handy, Susan L, 2015. "Providing Equitable Access to Sacramento’s Bike Share System," Institute of Transportation Studies, Working Paper Series qt5h495450, Institute of Transportation Studies, UC Davis.
    4. Kou, Zhaoyu & Cai, Hua, 2019. "Understanding bike sharing travel patterns: An analysis of trip data from eight cities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 785-797.
    5. Wu, Chunliang & Kim, Inhi, 2020. "Analyzing the structural properties of bike-sharing networks: Evidence from the United States, Canada, and China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 52-71.
    6. Médard de Chardon, Cyrille & Caruso, Geoffrey, 2015. "Estimating bike-share trips using station level data," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 260-279.
    7. Hyungkyoo Kim, 2020. "Seasonal Impacts of Particulate Matter Levels on Bike Sharing in Seoul, South Korea," IJERPH, MDPI, vol. 17(11), pages 1-17, June.
    8. Konstantin Klemmer & Tobias Brandt & Stephen Jarvis, 2018. "Isolating the effect of cycling on local business environments in London," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-31, December.
    9. Shruthi Kaviti & Mohan M. Venigalla & Shanjiang Zhu & Kimberly Lucas & Stefanie Brodie, 2020. "Impact of pricing and transit disruptions on bikeshare ridership and revenue," Transportation, Springer, vol. 47(2), pages 641-662, April.

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