Free-Floating Bike Sharing in Jiangsu: Users’ Behaviors and Influencing Factors

Abstract

In order to explore the factors affecting users' behaviors in a free-floating bike sharing (FFBS) system in China, a survey was conducted in Jiangsu province, China in 2017, and the travel characteristics of FFBS users were analyzed. A binary logistic model was applied to quantify the impact of various variables regarding residents' usage preference based on 30401 valid questionnaires. The findings show that (1) FFBS was mainly used for short-distance travel in cities, especially for commuting and schooling, and the time period of travel in FFBS coincided with the rush-hour in urban areas; (2) a higher level of education, a higher daily transportation cost, the convenience of picking up and parking, and the contribution to users' health could promote the usage of FFBS, while malfunctioning bicycles and limited regulations were major obstacles restricting the development of FFBS; (3) interestingly, people with high-incomes rather than those with low-incomes showed an inclination for FFBS owing to the charge mode. This research provides empirical evidence to facilitate the formulation of urban transportation policies and to improve the management of FFBS for the operators.

Investigating the Influential Factors of Shared Travel Behavior: Comparison between App-Based Third Taxi Service and Free-Floating Bike Sharing in Nanjing, China

“…For travel distance and travel duration, the riding distance was concentrated in 0.8~2.8 km (mean was 2.3 km), the riding duration was concentrated in 10~25 min (mean was 20 min) [21]. With regard to travel purpose and the time period of travel, FFBS was mainly used for commuting to work, attending school, shopping, and entertainment [5,22], and the travel peaks appeared at 7:00~9:00, 12:00~14:00, and 17:00~19:00 [5,[21][22][23]. Regarding the travel position, Shen et al [15] concluded that FFBS was primarily concentrated in the peripheral residential areas with high population density and access to the mass rapid transit by analyzing the GPS data of dockless bikes in Singapore.…”

“…As of 2017, the scales of ATTS, FFBS, and car sharing users are approximately 336 million, 400 million, and 8 million, respectively, in China [1][2][3]. This means that ATTS and FFBS have become significant components of urban transportation systems [4,5]. In addition, the Chinese government pays special attention to the development of FFBS and ATTS and it has continuously formulated and updated relevant policies to regulate the operation of such enterprises since 2016 [6,7].…”

Use Frequency of Metro–Bikeshare Integration: Evidence from Nanjing, China

“…Free-floating bike sharing (FFBS) is an innovative approach to a public bike system that is station-free and incorporates Internet Plus. It has recently received increasing attention due to its flexible mobility services [1][2][3][4]. As a low-carbon, environmentally friendly, flexible and green mode of transport, FFBS has been adopted and developed rapidly in many Chinese cities since 2016, and Ofo and Mobike, the main brands of FFBS in China, have further expanded to other countries around the world such as Italy, Russia, the Netherlands and the United States [5].…”

System Dynamics Modeling of Dockless Bike-Sharing Program Operations: A Case Study of Mobike in Beijing, China

“…Several authors have conducted research on DBSPs and have focused mainly on big data and machine learning applications (e.g., the scheduling efficiency of DBSPs [9][10][11], user travel forecast [12,13], electronic fence planning [14][15][16], and changes of travel mode [17,18]); user behavior [19,20]; environmental benefits [21,22]; and the overall development of the industry [23][24][25]. Note that these studies add complexity to this field.…”