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Understanding the Competition and Cooperation between Dockless Bike-Sharing and Metro Systems in View of Mobility

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  • Hanqi Tang

    (School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China)

  • Dandan Zhou

    (School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China)

Abstract

The advent of dockless bike-sharing (DBS) represents an effective solution to enhance public transportation usage. However, despite growing interest in integrating DBS with metro systems, comprehensive studies on their competitive and cooperative relationships remain limited. This study aims to analyze the spatial, temporal, and mobility characteristics of metro-related DBS to explore integration opportunities. Initially, three modes of interaction between DBS and metros are identified: strong competition, weak competition, and feeder relationships. Subsequently, based on these relationships, the analysis focuses on distance, spatio-temporal patterns, and the scope of DBS activities. Results from Beijing indicate that metro-associated DBS primarily serves as “last-mile” solutions without significant short-range competition with metro systems. Strongly competitive relationships, on the other hand, are interaction patterns due to the dense overlay of metro stations and inconvenient transfer facilities and are mainly used for non-commuting purposes. Furthermore, weakly competing and feeder DBS systems exhibit similar commuting patterns, highlighting bicycling as a viable alternative to walking within metro catchment areas and that metro catchment areas should be adapted to bicycling. Mobility communities, identified as tightly integrated cycling hubs, are proposed as strategic dispatch zones to manage peak demands and reduce operational strain on DBS fleets. These findings deepen our understanding of DBS and metro system interactions, offering insights to optimize public transport operations and enhance urban mobility solutions.

Suggested Citation

  • Hanqi Tang & Dandan Zhou, 2024. "Understanding the Competition and Cooperation between Dockless Bike-Sharing and Metro Systems in View of Mobility," Sustainability, MDPI, vol. 16(13), pages 1-16, July.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:13:p:5780-:d:1430351
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    References listed on IDEAS

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    1. Böcker, Lars & Anderson, Ellinor & Uteng, Tanu Priya & Throndsen, Torstein, 2020. "Bike sharing use in conjunction to public transport: Exploring spatiotemporal, age and gender dimensions in Oslo, Norway," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 389-401.
    2. Kevin Chan & Steven Farber, 2020. "Factors underlying the connections between active transportation and public transit at commuter rail in the Greater Toronto and Hamilton Area," Transportation, Springer, vol. 47(5), pages 2157-2178, October.
    3. Tom Thomas & Rinus Jaarsma & Bas Tutert, 2013. "Exploring temporal fluctuations of daily cycling demand on Dutch cycle paths: the influence of weather on cycling," Transportation, Springer, vol. 40(1), pages 1-22, January.
    4. Kim, Kyoungok, 2018. "Investigation on the effects of weather and calendar events on bike-sharing according to the trip patterns of bike rentals of stations," Journal of Transport Geography, Elsevier, vol. 66(C), pages 309-320.
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