Effect of built environment on shared bicycle reallocation: A case study on Nanjing, China

被引:61
|
作者
Zhao, De [1 ,2 ]
Ong, Ghim Ping [1 ]
Wang, Wei [2 ]
Hu, Xiao Jian [2 ]
机构
[1] Natl Univ Singapore, Dept Civil & Environm Engn, Block E1A,07-03,1 Engn Dr 2, Singapore 117576, Singapore
[2] Southeast Univ, Jiangsu Key Lab Urban ITS, Si Pai Lou 2, Nanjing 210096, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Built environment; Bicycle sharing; Bicycle demand; Reallocation; Zero-inflated negative binomial regression; SHARING SYSTEM; PUBLIC BIKES; IMPACT; PATTERNS; USAGE; WASHINGTON; PROGRAM; WEATHER; CHOICE; RUN;
D O I
10.1016/j.tra.2019.07.018
中图分类号
F [经济];
学科分类号
02 ;
摘要
Shared bicycles provide a convenient mobility option to commuters especially for short-distance trips. Nevertheless, it also presents a challenge to bicycle-sharing operators as they have to deal with reallocation issues, i.e. removing bicycles from parking facilities which are at or near capacity and refilling parking facilities that are in need of bicycles. Few studies in the literature have actually tried understanding why certain docking stations are prone to excessive demand or suffer from a lack of parking supply. This paper attempts to identify the demographic, built-environment and transport-infrastructure indicators that can potentially aid policy-makers and operators in identifying parking facilities prone to bicycle reallocation. In particular, we have adopted the bicycle sharing operations in Nanjing, China as a case study to understand how such indicators can be identified for appropriate parking infrastructural enhancements. To achieve this goal, this study has established zero-inflated negative binomial models using multi-source data including point-of-interest (POI), daily weather, transit stop location, demographic data and bike-share smart card data. The model results obtained from this study suggest that built environment correlates significantly to shared bicycle reallocation count. In general, bicycle docking stations with large reallocation counts are more likely to be found near residences, bus stops, metro stations, employment areas, restaurants, amenities, parks, sports facilities, and clinics/hospitals; while stations near entertainment facilities, places of attraction, hotels, shopping malls, and educational institution tend to have balanced demand and supply. Analysis on the elasticity values revealed that mean temperature and station capacity are the most influential factors in bicycle reallocation. Among all POIs, presence of restaurants and areas with high employment tend to exhibit strongly a need for morning bicycle removal and evening bicycle refilling at docked stations. Policy makers can provide actual guidelines in the planning of shared bicycle parking facilities using the findings and methodologies presented in this study.
引用
收藏
页码:73 / 88
页数:16
相关论文
共 50 条
  • [31] The Influence of Built-Environment Factors on Connectivity of Road Networks in Residential Areas: A Study Based on 204 Samples in Nanjing, China
    Zhang, Yu
    Wang, Rui
    Wu, Yue
    Chu, Guanlong
    Wu, Xiaomin
    BUILDINGS, 2023, 13 (02)
  • [32] Exploring the Effect of Bicycle Infrastructure on Car Usage: A Case Study in Huhhot, China
    Jian, Meiying
    Li, Xiaojuan
    Cao, Jinxin
    Liu, Zhenyu
    JOURNAL OF ADVANCED TRANSPORTATION, 2021, 2021
  • [33] Influence of the Built Environment on Older Adults' Travel Time: Evidence from the Nanjing Metropolitan Area, China
    Sun, Jingrui
    Zhu, Zhenjun
    Han, Ji
    He, Zhanpeng
    Xu, Xinfang
    LAND, 2023, 12 (06)
  • [34] Medical waste management in China: A case study of Nanjing
    Zhang Yong
    Xiao Gang
    Wang Guanxing
    Zhou Tao
    Jiang Dawei
    WASTE MANAGEMENT, 2009, 29 (04) : 1376 - 1382
  • [35] Potential Effect of Air Pollution on the Urban Traffic Vitality: A Case Study of Nanjing, China
    Cao, Yang
    Wu, Hao
    Wang, Hongbin
    Liu, Duanyang
    Yan, Shuqi
    ATMOSPHERE, 2022, 13 (10)
  • [36] The Effects of the Built Environment on the Mental Health of Older Adults: A Case Study in Hangzhou, China
    Kong, Xinyu
    Han, Haoying
    Zhan, Mengyao
    Chi, Fangting
    INNOVATION IN AGING, 2024, 8 (05)
  • [37] Effects of built environment on metro ridership at a microscopic scale: a case study of Xi'an, China
    Zhang, Siyi
    Wang, Yonggang
    Liu, Zixuan
    Huang, Jiazhuo
    TRANSPORTATION PLANNING AND TECHNOLOGY, 2024, 47 (01) : 42 - 61
  • [38] Impacts of Built Environment on Risk of Women's Lung Cancer: A Case Study of China
    Xie, Hongjie
    Shao, Rui
    Yang, Yiping
    Cruz, Ramio
    Zhou, Xilin
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2022, 19 (12)
  • [39] Exploring the impact of neighborhood environment on the mental health of rural migrant women: A case study in Nanjing, China
    Gu, Moli
    Tang, Shuangshuang
    Feng, Jianxi
    CITIES, 2024, 155
  • [40] Unraveling the Multi-Scale Spatial Relationship between Built Environment and Walk Access to Metro Stations: A Case Study in Nanjing
    Fei, Yue
    Wen, Xu-Li
    CICTP 2023: INNOVATION-EMPOWERED TECHNOLOGY FOR SUSTAINABLE, INTELLIGENT, DECARBONIZED, AND CONNECTED TRANSPORTATION, 2023, : 2751 - 2761