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Bicycle parking demand at railway stations: Capturing price-walking trade offs

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  • Molin, Eric
  • Maat, Kees

Abstract

Due to the increasing use of bicycles as an access and egress mode for train travel in the Netherlands, bicycle parking facilities at many inner city railway stations are having trouble accommodating parking demand while scare space near train platforms precludes the expansion of such facilities. A potential solution for this problem is to offer paid, high-quality parking facilities close to the train platforms and free but lower-quality parking further away. Since free parking is currently also offered close to the platforms, the question arises of how the proposed solution would affect cycling as an access and egress mode for train travel. To answer this question, the bicycle parking preferences of train travellers were examined in this paper by reporting the results of a stated choice experiment (n = 866) conducted in Delft. In this experiment, respondents chose between paid and free parking alternatives, that varied in costs, walking time to platform and the type of surveillance. To explore the effects of paid bicycle parking on the demand for bicycle parking, two base alternatives were added to each choice set, that is ‘other mode’ and ‘use another station’. Based on the observed choices in this experiment, a four-class Latent Class Model (LCM) was estimated that provides insight in the heterogeneity of the bicycle parking preferences of train travellers. The classes are labelled as ‘free facility lovers’, ‘cost sensitive cyclists’, ‘time sensitive cyclists’, and ‘paid facility lovers’. The estimated model was used to predict choice behaviour under various implementations of the new pricing policy. The results indicate that only a small proportion of the train travellers will stop cycling to and from the station. Of these, the vast majority would rather walk and a fair share would use public transport. Only a very small number would travel to the station by car. The results suggest that paid bicycle parking is a feasible solution by which to distribute scarce parking capacity at major railway stations.

Suggested Citation

  • Molin, Eric & Maat, Kees, 2015. "Bicycle parking demand at railway stations: Capturing price-walking trade offs," Research in Transportation Economics, Elsevier, vol. 53(C), pages 3-12.
    • Handle: RePEc:eee:retrec:v:53:y:2015:i:c:p:3-12
    DOI: 10.1016/j.retrec.2015.10.014
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    References listed on IDEAS

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    1. Kobus, Martijn B.W. & Gutiérrez-i-Puigarnau, Eva & Rietveld, Piet & Van Ommeren, Jos N., 2013. "The on-street parking premium and car drivers' choice between street and garage parking," Regional Science and Urban Economics, Elsevier, vol. 43(2), pages 395-403.
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    Cited by:

    1. Kim, Sung Hoo & Mokhtarian, Patricia L., 2023. "Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 134-173.
    2. Kohlrautz, David & Kuhnimhof, Tobias, 2025. "Cyclists’ heterogeneous parking preferences and their implications for bicycle parking facilities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 191(C).
    3. Liu, Yang & Feng, Tao & Shi, Zhuangbin & He, Mingwei, 2022. "Understanding the route choice behaviour of metro-bikeshare users," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 460-475.
    4. Xinwei Ma & Yanjie Ji & Yuchuan Jin & Jianbiao Wang & Mingjia He, 2018. "Modeling the Factors Influencing the Activity Spaces of Bikeshare around Metro Stations: A Spatial Regression Model," Sustainability, MDPI, vol. 10(11), pages 1-12, October.
    5. Ma, Xinwei & Ji, Yanjie & Yang, Mingyuan & Jin, Yuchuan & Tan, Xu, 2018. "Understanding bikeshare mode as a feeder to metro by isolating metro-bikeshare transfers from smart card data," Transport Policy, Elsevier, vol. 71(C), pages 57-69.
    6. Ying Ni & Jiaqi Chen, 2020. "Exploring the Effects of the Built Environment on Two Transfer Modes for Metros: Dockless Bike Sharing and Taxis," Sustainability, MDPI, vol. 12(5), pages 1-20, March.

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    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling

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