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Using multivariate adaptive regression splining (MARS) to identify factors affecting the performance of dock-based bikesharing: The case of Chicago’s Divvy system

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  • Smith, C. Scott
  • Schwieterman, Joseph P.

Abstract

This study explores factors contributing to the uneven success of past expansions of dock-based public bikesharing systems, in which middle- and - higher-income neighborhoods have tended to benefit considerably more than poorer neighborhoods. After a review of the differing performance of the three phases of expansion by Chicago's Divvy bikeshare system, this study uses multivariate adaptive regression splining (MARS) to select among more than 100 community- and station-level factors to explain variations in Divvy system usage at the station level. MARS demonstrates that neighborhood racial and ethnic diversity, proportion of condominium units, and job accessibility to public transit are strongly and positively correlated with total annual station trips, whereas percentage unemployed, average distance to Divvy stations, and percentage of residential foreclosures are negatively correlated. Model results are compared with those of earlier studies to foster insights into ways to more accurately predict the use of bikesharing systems across urban neighborhoods.

Suggested Citation

  • Smith, C. Scott & Schwieterman, Joseph P., 2021. "Using multivariate adaptive regression splining (MARS) to identify factors affecting the performance of dock-based bikesharing: The case of Chicago’s Divvy system," Research in Transportation Economics, Elsevier, vol. 89(C).
    • Handle: RePEc:eee:retrec:v:89:y:2021:i:c:s0739885921000044
    DOI: 10.1016/j.retrec.2021.101032
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    References listed on IDEAS

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    1. Faghih-Imani, Ahmadreza & Hampshire, Robert & Marla, Lavanya & Eluru, Naveen, 2017. "An empirical analysis of bike sharing usage and rebalancing: Evidence from Barcelona and Seville," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 177-191.
    2. Tien Dung Tran & Nicolas Ovtracht & Bruno Faivre D’arcier, 2015. "Modeling Bike Sharing System using Built Environment Factors," Post-Print halshs-01474166, HAL.
    3. Kyle Gebhart & Robert Noland, 2014. "The impact of weather conditions on bikeshare trips in Washington, DC," Transportation, Springer, vol. 41(6), pages 1205-1225, November.
    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. Xiaolu Zhou, 2015. "Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-20, October.
    6. Greg P. Griffin & Junfeng Jiao, 2019. "Crowdsourcing Bike Share Station Locations," Journal of the American Planning Association, Taylor & Francis Journals, vol. 85(1), pages 35-48, January.
    7. Zhao, Jinbao & Deng, Wei & Song, Yan, 2014. "Ridership and effectiveness of bikesharing: The effects of urban features and system characteristics on daily use and turnover rate of public bikes in China," Transport Policy, Elsevier, vol. 35(C), pages 253-264.
    8. Faghih-Imani, Ahmadreza & Eluru, Naveen, 2015. "Analysing bicycle-sharing system user destination choice preferences: Chicago’s Divvy system," Journal of Transport Geography, Elsevier, vol. 44(C), pages 53-64.
    9. Sungyop Kim & Gudmundur Ulfarsson, 2008. "Curbing automobile use for sustainable transportation: analysis of mode choice on short home-based trips," Transportation, Springer, vol. 35(6), pages 723-737, November.
    10. Schneider, Robert J., 2013. "Theory of routine mode choice decisions: An operational framework to increase sustainable transportation," Transport Policy, Elsevier, vol. 25(C), pages 128-137.
    11. Faghih-Imani, Ahmadreza & Eluru, Naveen & El-Geneidy, Ahmed M. & Rabbat, Michael & Haq, Usama, 2014. "How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal," Journal of Transport Geography, Elsevier, vol. 41(C), pages 306-314.
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