Towards a Better Understanding of Effectiveness of Bike-share Programs: Exploring Factors Affecting Bikes Idle Duration

Boniphace Kutela, Emmanuel Kidando

Abstract


Bike-share program is considered effective and reliable if its stations have bikes and empty docks available at any time of a day. Few studies have considered idle bikes in the system and even lesser have glanced on modeling bikes idle duration (BID) in the bike-share system. This study applied descriptive statistics and log-logistic hazard based model on one year Seattle bike-share ridership data to quantify the BID and determine factors associated with the bikes’ idle duration. The findings of the study illustrate that the most and least effective utilized bike were used for 161 hours and 0.19 hours respectively for the entire year. Winter season, especially when raining and snowing was found to increase the likelihood of long BID. On the other end, the bikes located in commercial areas were associated with short BID compared to residential land-use. Moreover, weekend days and evening peak hours (4 p.m. to 6 p.m.) are associated with less likelihood of the BID compared with weekdays and morning peak hours respectively. These findings will facilitate procedures to identify the idle bikes for redistribution strategy and enhancing effective utilization of the bike-share system.


Keywords


Bike-share program; Bike Idle Duration (BID); Hazard based model.

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References


T. Raviv and O. Kolka, “Optimal inventory management of a bike-sharing station,” IIE Trans., vol. 45, no. 10, pp. 1077–1093, Oct. 2013.

D. Chemla, F. Meunier, and R. Wolfler Calvo, “Bike sharing systems: Solving the static rebalancing problem,” Discret. Optim., vol. 10, no. 2, pp. 120–146, 2013.

M. Kaspi, T. Raviv, and M. Tzur, “Detection of unusable bicycles in bike-sharing systems,” 2016.

P. J. Demaio, “Smart Bikes: Public Transportation for the 21st Century,” Transp. Q., vol. 57, no. 1, pp. 9–11, 2003.

C. Romero, “SpiCycles in Barcelona,” in Chamber of Commerce and Industry of Romania, 2008.

X. Wang, G. Lindsey, J. E. Schoner, and A. Harrison, “Modeling Bike-share Station Activity: Effects of Nearby Businesses and Jobs on Trips to and from Stations,” J. Urban Plan. Dev., vol. 142, no. 1, p. 4015001, Mar. 2016.

J.-R. Lin and T.-H. Yang, “Strategic design of public bicycle sharing systems with service level constraints,” Transp. Res. Part E Logist. Transp. Rev., vol. 47, no. 2, pp. 284–294, 2011.

J. Schuijbroek, R. Hampshire, and W.-J. van Hoeve, “Inventory Rebalancing and Vehicle Routing in Bike Sharing Systems,” 2013.

P. Vogel and D. C. Mattfeld, “Strategic and Operational Planning of Bike-Sharing Systems by Data Mining – A Case Study,” Springer Berlin Heidelberg, 2011, pp. 127–141.

M. Kaspi, T. Raviv, and M. Tzur, “Detection of Unusable Bicycles in Bike-Sharing Systems,” 2015.

Kalbfleisch D. John and Ross L. Prentice, The Statistical Analysis of Failure Time Data - John D. Kalbfleisch, Ross L. Prentice - Google Books. New York: John Wiley & Sons, 1980.

D. Chimba, B. Kutela, G. Ogletree, F. Horne, and M. Tugwell, “Impact of Abandoned and Disabled Vehicles on Freeway Incident Duration,” J. Transp. Eng., vol. 140, no. 3, p. 4013013, 2014.

W. Hui, “Proportional Hazard Weibull Mixtures,” Canberra, 1990.

J.-T. Lee and J. Fazio, “Influential Factors in Freeway Crash Response and Clearance Times by Emergency Management Services in Peak Periods,” Traffic Inj. Prev., vol. 6, no. 4, pp. 331–339, Dec. 2005.

S. Hasan, R. Mesa-Arango, and S. Ukkusuri, “A random-parameter hazard-based model to understand household evacuation timing behavior,” Transp. Res. Part C Emerg. Technol., vol. 27, pp. 108–116, 2013.

B. Jones, “Duration models: Parametric models,” Univ. of California, Davis, 2011.

D. Kundu, R. D. Gupta, and A. Manglick, “Discriminating between the log-normal and generalized exponential distributions,” J. Stat. Plan. Inference, vol. 127, no. 1, pp. 213–227, 2005.

D. Nam and F. Mannering, “An exploratory hazard-based analysis of highway incident duration,” Transp. Res. Part A Policy Pract., vol. 34, no. 2, pp. 85–102, 2000.

B. Ting Ma, C. Liu, and S. Erdoğan, “Bicycle Sharing and Transit: Does Capital Bike-share Affect Metrorail Ridership in Washington, D.C.?,” in 83rd Annual Meeting of the Transportation Research Board, 2015.

K. Gebhart and R. B. Noland, “The Impact of Weather Conditions on Capital Bike-share Trips.” 2013.

J. Bachand-Marleau, B. Lee, and A. El-Geneidy, “Better Understanding of Factors Influencing Likelihood of Using Shared Bicycle Systems and Frequency of Use,” Transp. Res. Rec. J. Transp. Res. Board, vol. 2314, pp. 66–71, Dec. 2012.

B. David William Daddio and N. Mcdonald, “MAXIMIZING BICYCLE SHARING: AN EMPIRICAL ANALYSIS OF CAPITAL BIKE-SHARE USAGE,” University of North Carolina at Chapel Hill, 2012.


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