Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Uncovering round-trip patterns in bicycle sharing

Differences in short-distance travels from home-based, work-based, and river-based neighborhoods

Bibliographic Data

ID12295653
AuthorsSunjae Lee (0000-0003-0083-5369, Seoul National University), Hyunwoo Lee (0000-0002-1736-560X, Seoul National University), Sohyun Park (0000-0003-4719-6920, Seoul National University, corresponding author)
Year2025
Volume128
Pages104366-104366
Publication date2025-07-24
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Transport Geography (JOURNAL)
Journal identifiersISSN: 0966-6923 • E-ISSN: 1873-1236
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.jtrangeo.2025.104366
OpenAlexW4412640000
LanguageEN
References cited31

Analyzing neighborhood-level bicycle usage is pivotal for developing effective policies and promoting bicycle-friendly initiatives. Although data from bicycle sharing systems (BSS) have become increasingly accessible, round-trip travel remains underexamined compared to one-way or last-mile commuting trips. This study addresses that gap by investigating round-trip usage in Seoul's BSS, which adopts a low-cost, flat-rate fare structure that encourages short-distance trips. Using a Bayesian Gaussian Mixture Model (BGMM) on 347,252 GPS trajectories from round trips, we identified visited points of interest (POIs). We then analyzed travel characteristics and POI visitation patterns across three neighborhood contexts: home-based, work-based, and river-based. Round trips accounted for 11 % of BSS usage but showed longer durations (40.35 min vs. 22.47 for one-way trips) and distinct time peaks around midday and evening. POI visit patterns varied by context: 73.8 % of round trips in river-based areas led to open spaces, while home-based neighborhoods saw more visits to daily life services and education. Work-based areas had higher visitation to food-and-beverage and business facilities. A micro-scale cluster analysis revealed more dispersed POIs near river-based stations, and more concentrated ones near home- and work-based stations. These findings underscore the versatility of shared bicycles as a standalone mode of transportation beyond commuting. By clarifying how visit patterns vary by neighborhood type, this study provides actionable insights for BSS operations and urban planning, including station placement and rebalancing strategies tailored to local travel needs. • Round trips, ∼11 % of shared bike use, show much longer travel and visit durations. • Neighborhood shape round trips: river-based for leisure, others for errands or work. • POI analysis shows bicycles serve beyond commutes, supporting errands and leisure. • Micro-scale POI analysis shows river sites dispersed, work clustered, and home mixed

Bike sharing · Geography · Transport engineering · Work (physics · Engineering · Human Mobility and Location-Based Analysis · Transportation and Mobility Innovations · Urban Transport and Accessibility

  • On the Interpretation of χ 2 from Contingency Tables, and the Calculation of P

    R A Fisher•Journal Of The Royal Statistical…•1922

  • Bike-sharing

    Open Access•Paul DeMaio•Journal of Public Transportation•2009

  • Visitor bikeshare usage

    Richard J Buning, Vijay Lulla•Journal of Sustainable Tourism•2021

  • Trip chain complexity

    Open Access•Florian Schneider, Danique Ton et al.•Transportation•2021

  • Discovering spatiotemporal usage patterns of a bike-sharing system by type of pass

    Open Access•Kyoungok Kim•Transportation•2024

  • Scaling up cycling or replacing driving? Triggers and trajectories of bike–train uptake in the Randstad area

    Open Access•Samuel Nello‐deakin, Marco Te Brömmelstroet•Transportation•2021

  • Examining travel patterns and characteristics in a bikesharing network and implications for data-driven decision supports

    Open Access•Xiaofeng Xie, Zun-Jing Wang et al.•Journal of Transport Geography•2018

  • How land-use and urban form impact bicycle flows

    Open Access•Ahmadreza Faghih-Imani, Naveen Eluru et al.•Journal of Transport Geography•2014

  • Examining spatiotemporal changing patterns of bike-sharing usage during Covid-19 pandemic

    Open Access•Songhua Hu, Chenfeng Xiong et al.•Journal of Transport Geography•2021

  • Spatio-temporal patterns of a Public Bicycle Sharing Program

    Open Access•Jacqueline Corcoran, Tiebei Li et al.•Journal of Transport Geography•2014

  • Exploring travel patterns and trip purposes of dockless bike-sharing by analyzing massive bike-sharing data in Shanghai, China

    Open Access•Yingying Xing, Ke Wang et al.•Journal of Transport Geography•2020

  • Understanding the diffusion of public bikesharing systems

    Open Access•Stephen Parkes, Stephen D Parkes et al.•Journal of Transport Geography•2013

  • Associations of built environments with spatiotemporal patterns of public bicycle use

    Open Access•Hung-Chi Liu, Hung‐Chi Liu et al.•Journal of Transport Geography•2018

  • Expansion patterns of walking activity spaces in superblock neighbourhoods based on mHealth data from Jamsil

    Hyunwoo Lee, Sohyun Park•Local Environment•2025

Citation velocityhistorical
Highly citedNo

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae