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Bike-Share Systems: Accessibility and Availability

Author

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  • Ashish Kabra

    (Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20742)

  • Elena Belavina

    (Cornell University, Ithaca, New York 14853)

  • Karan Girotra

    (Cornell University, Ithaca, New York 14853)

Abstract

The cities of Paris, London, Chicago, and New York (among many others) have set up bike-share systems to facilitate the use of bicycles for urban commuting. This paper estimates the impact of two facets of system performance on bike-share ridership: accessibility (how far the user must walk to reach stations) and bike-availability (the likelihood of finding a bicycle). We obtain these estimates from a structural demand model for ridership estimated using data from the Vélib’ system in Paris. We find that every additional meter of walking to a station decreases a user’s likelihood of using a bike from that station by 0.194% (±0.0693%), and an even more significant reduction at higher distances (>300 m). These estimates imply that almost 80% of bike-share usage comes from areas within 300 m of stations, highlighting the need for dense station networks. We find that a 10% increase in bike-availability would increase ridership by 12.211% (±1.097%), three-fourths of which comes from fewer abandonments and the rest of which comes from increased user interest. We illustrate the use of our estimates in comparing the effect of adding stations or increasing bike-availabilities in different parts of the city, at different times, and in evaluating other proposed improvements.

Suggested Citation

  • Ashish Kabra & Elena Belavina & Karan Girotra, 2020. "Bike-Share Systems: Accessibility and Availability," Management Science, INFORMS, vol. 66(9), pages 3803-3824, September.
  • Handle: RePEc:inm:ormnsc:v:66:y:2020:i:9:p:3803-3824
    DOI: 10.287/mnsc.2019.3407
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    as
    1. Peter Davis, 2006. "Spatial competition in retail markets: movie theaters," RAND Journal of Economics, RAND Corporation, vol. 37(4), pages 964-982, December.
    2. Jean‐Pierre Dubé & Jeremy T. Fox & Che‐Lin Su, 2012. "Improving the Numerical Performance of Static and Dynamic Aggregate Discrete Choice Random Coefficients Demand Estimation," Econometrica, Econometric Society, vol. 80(5), pages 2231-2267, September.
    3. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    4. Nevo, Aviv, 2001. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Econometrica, Econometric Society, vol. 69(2), pages 307-342, March.
    5. Eric T. Anderson & Gavan J. Fitzsimons & Duncan Simester, 2006. "Measuring and Mitigating the Costs of Stockouts," Management Science, INFORMS, vol. 52(11), pages 1751-1763, November.
    6. Christopher T. Conlon & Julie Holland Mortimer, 2013. "Demand Estimation under Incomplete Product Availability," American Economic Journal: Microeconomics, American Economic Association, vol. 5(4), pages 1-30, November.
    7. George, David K. & Xia, Cathy H., 2011. "Fleet-sizing and service availability for a vehicle rental system via closed queueing networks," European Journal of Operational Research, Elsevier, vol. 211(1), pages 198-207, May.
    8. Peter Davis, 2006. "Spatial competition in retail markets: movie theaters," RAND Journal of Economics, The RAND Corporation, vol. 37(4), pages 964-982, December.
    9. Raphael Thomadsen, 2005. "The Effect of Ownership Structure on Prices in Geographically Differentiated Industries," RAND Journal of Economics, The RAND Corporation, vol. 36(4), pages 908-929, Winter.
    10. Gérard P. Cachon, 2014. "Retail Store Density and the Cost of Greenhouse Gas Emissions," Management Science, INFORMS, vol. 60(8), pages 1907-1925, August.
    11. McFadden, Daniel, 1974. "The measurement of urban travel demand," Journal of Public Economics, Elsevier, vol. 3(4), pages 303-328, November.
    12. Joseph Pancras & S. Sriram & V. Kumar, 2012. "Empirical Investigation of Retail Expansion and Cannibalization in a Dynamic Environment," Management Science, INFORMS, vol. 58(11), pages 2001-2018, November.
    13. Andrés Musalem & Marcelo Olivares & Eric T. Bradlow & Christian Terwiesch & Daniel Corsten, 2010. "Structural Estimation of the Effect of Out-of-Stocks," Management Science, INFORMS, vol. 56(7), pages 1180-1197, July.
    14. Amil Petrin, 2002. "Quantifying the Benefits of New Products: The Case of the Minivan," Journal of Political Economy, University of Chicago Press, vol. 110(4), pages 705-729, August.
    15. Berry, Steven & Levinsohn, James & Pakes, Ariel, 1995. "Automobile Prices in Market Equilibrium," Econometrica, Econometric Society, vol. 63(4), pages 841-890, July.
    16. Ahmed El-Geneidy & Michael Grimsrud & Rania Wasfi & Paul Tétreault & Julien Surprenant-Legault, 2014. "New evidence on walking distances to transit stops: identifying redundancies and gaps using variable service areas," Transportation, Springer, vol. 41(1), pages 193-210, January.
    17. Gad Allon & Awi Federgruen & Margaret Pierson, 2011. "How Much Is a Reduction of Your Customers' Wait Worth? An Empirical Study of the Fast-Food Drive-Thru Industry Based on Structural Estimation Methods," Manufacturing & Service Operations Management, INFORMS, vol. 13(4), pages 489-507, October.
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    2. Ouassim Manout & Azise Oumar Diallo & Thibault Gloriot, 2023. "Implications of pricing and fleet size strategies on shared bikes and e-scooters: a case study from Lyon, France," Working Papers hal-04017908, HAL.
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    4. Dong, Zhongpeng & Fan, Zhi-Ping & Wang, Ningning, 2023. "An analysis of pricing strategy for bike-sharing services: The role of the inconvenience cost," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    5. Li, Yang & Sun, Hao & Sun, Panfei & Hou, Dongshuang, 2023. "Inhibit violations in business-to-peer product sharing via heterogeneous punishment, firm decisions and subsidies," European Journal of Operational Research, Elsevier, vol. 311(3), pages 1173-1187.
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    7. Zhang, Yu & Huang, Min & Tian, Lin & Cai, Gangshu George & Jin, Delong & Fan, Zhiping, 2023. "Manufacturer’s product line selling strategy and add-on policy in product sharing," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1332-1343.
    8. Leonardo Caggiani & Rosalia Camporeale & Zahra Hamidi & Chunli Zhao, 2021. "Evaluating the Efficiency of Bike-Sharing Stations with Data Envelopment Analysis," Sustainability, MDPI, vol. 13(2), pages 1-21, January.
    9. Saif Benjaafar & Daniel Jiang & Xiang Li & Xiaobo Li, 2022. "Dynamic Inventory Repositioning in On-Demand Rental Networks," Management Science, INFORMS, vol. 68(11), pages 7861-7878, November.
    10. Hao, Wu & Martin, Layla, 2022. "Prohibiting cherry-picking: Regulating vehicle sharing services who determine fleet and service structure," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).
    11. Ming Hu, 2021. "From the Classics to New Tunes: A Neoclassical View on Sharing Economy and Innovative Marketplaces," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1668-1685, June.
    12. Gao, Fan & Yang, Linchuan & Han, Chunyang & Tang, Jinjun & Li, Zhitao, 2022. "A network-distance-based geographically weighted regression model to examine spatiotemporal effects of station-level built environments on metro ridership," Journal of Transport Geography, Elsevier, vol. 105(C).
    13. Yang Xia & Wenjia Zeng & Xinjie Xing & Yuanzhu Zhan & Kim Hua Tan & Ajay Kumar, 2023. "Joint optimisation of drone routing and battery wear for sustainable supply chain development: a mixed-integer programming model based on blockchain-enabled fleet sharing," Annals of Operations Research, Springer, vol. 327(1), pages 89-127, August.
    14. Kim, Minjun & Cho, Gi-Hyoug, 2021. "Analysis on bike-share ridership for origin-destination pairs: Effects of public transit route characteristics and land-use patterns," Journal of Transport Geography, Elsevier, vol. 93(C).
    15. Gu, Wei & Yu, Xiaoru & Zhang, Shichen & Yan, Xiangbin & Wang, Chen, 2023. "To outsource or not: Bike-share rebalancing strategies under the service quality deviation of a third party," European Journal of Operational Research, Elsevier, vol. 310(2), pages 847-859.
    16. Morton, Craig & Kelley, Scott & Monsuur, Fredrik & Hui, Tianwen, 2021. "A spatial analysis of demand patterns on a bicycle sharing scheme: Evidence from London," Journal of Transport Geography, Elsevier, vol. 94(C).
    17. Andrea Gorrini & Rawad Choubassi & Federico Messa & Wafaa Saleh & Augustus Ababio-Donkor & Maria Chiara Leva & Lorraine D’Arcy & Francesco Fabbri & David Laniado & Pablo Aragón, 2021. "Unveiling Women’s Needs and Expectations as Users of Bike Sharing Services: The H2020 DIAMOND Project," Sustainability, MDPI, vol. 13(9), pages 1-29, May.
    18. Gu, Wei & Li, Meng & Wang, Chen & Shang, Jennifer & Wei, Lirong, 2021. "Strategic sourcing selection for bike-sharing rebalancing: An evolutionary game approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).

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