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Travel Behaviours of Sharing Bicycles in the Central Urban Area Based on Geographically Weighted Regression: The Case of Guangzhou, China
Chinese Geographical Science ( IF 3.4 ) Pub Date : 2021-01-13 , DOI: 10.1007/s11769-020-1159-3
Zongcai Wei , Feng Zhen , Haitong Mo , Shuqing Wei , Danli Peng , Yuling Zhang

Mobile information and communication technologies (MICTs) have fully penetrated everyday life in smart societies; this has greatly compressed time, space, and distance, and consequently, reshaped residents’ travel behaviour patterns. As a new mode of shared mobility, the sharing bicycle offers a variety of options for the daily travel of urban residents. Extant studies have mainly examined the travel characteristics and influencing factors of public bicycles with piles, while the travel patterns for sharing bicycles and their driving mechanisms have been largely ignored. Using one week’s travel data for Mobike, this study investigated the spatial and temporal distribution patterns of sharing bicycle travel behaviours in the central urban area of Guangzhou, China; furthermore, it identified the influences of built environment density factors on sharing bicycle travel behaviours based on the geographically weighted regression method. Obvious morning and evening peaks were observed in the sharing bicycle travel patterns for both weekdays and weekends. The old urban area, which had a high degree of mixed function, dense road networks, and cycling-friendly built environments, was the main travel area that attracted sharing bicycles on both weekdays and weekends. Furthermore, factors including the point of interest (POI) for the density of public transport stations, the functional mixing degree, and the density of residential POIs significantly affected residents’ travel behaviours. These findings could enrich discourse regarding shared mobility with a Chinese case characterised by rapidly developing MICTs and also provide references to local authorities for improving slow traffic environments.

中文翻译:

基于地理加权回归的中心城区共享单车出行行为:以广州为例

移动信息和通信技术(MICT)已完全渗透到智慧社会的日常生活中;这极大地压缩了时间、空间和距离,从而重塑了居民的出行行为模式。共享单车作为一种新型的共享出行方式,为城市居民的日常出行提供了多种选择。现有研究主要考察了带桩公共自行车的出行特征及影响因素,而在很大程度上忽略了共享单车的出行方式及其驱动机制。本研究利用摩拜单车一周的出行数据,调查了广州中心城区共享单车出行行为的时空分布格局;此外,基于地理加权回归方法识别建成环境密度因素对共享单车出行行为的影响。平日和周末的共享单车出行模式均出现明显的早晚高峰。老城区功能高度混合、路网密集、建筑环境适宜骑行,是平日和周末吸引共享单车的主要出行区域。此外,公共交通站点密度的兴趣点(POI)、功能混合程度和住宅POI密度等因素显着影响居民的出行行为。
更新日期:2021-01-13
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