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Travel Behaviours of Sharing Bicycles in the Central Urban Area Based on geographically weighted regression: The Case of Guangzhou, China

引用

Chinese Geographical Science 2021年第1期31卷 54-69页

作者： WEI Zongcai ZHEN Feng MO Haitong WEI Shuqing PENG Danli ZHANG Yuling School of Architecture State Key Laboratory of Subtropical Building ScienceSouth China University of TechnologyGuangzhou 510641China School of Architecture and Urban Planning Nanjing UniversityJiangsu Provincial Engineering Laboratory of Smart City Design Simulation&VisualizationNanjing 210093China Guangzhou Institute of Geography Guangzhou 510070China

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.

关键词： sharing bicycles travel behaviours smart societies geographically weighted regression analysis Guangzhou,China

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