Unsafe riding behaviors of shared-bicycle riders in urban China: A retrospective survey

Wu, Xiaolin; Xiao, Wangxin; Deng, Conghui; Schwebel, David C.; Hu, Guoqing

doi:10.1016/j.aap.2019.06.002

Cited by 33 publications

(34 citation statements)

References 34 publications

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“…Perceived strength is defined as individuals’ estimates of their abilities to control these factors to implement certain behavior in current conditions. Extensive research has shown that a high-level of PBC leads to stronger behavioral intention and behavior performance (Ajzen, 1991; Shi et al, 2018; Wu et al, 2019). In this study, if the user is confident enough and has strong capacities to ride sharing bikes civilly and the city provides sufficient cycling conditions (e.g., proper parking spaces), civilized cycling behaviors can be generated easily.…”

Section: Theoretical Framework and Hypotheses Developmentmentioning

confidence: 99%

“…Control variables have the potential to confound the effects of determinants on the explanatory variable (Mehta, 2015). Currently, numerous studies related to cycling behaviors have demonstrated that demographic variables have an important impact on an individual’s behavioral intention and actual behaviors (Holland and Hill, 2007; Bernhoft and Carstensen, 2008; Cordellieri et al, 2016; Wu et al, 2019). For example, Bernhoft and Carstensen (2008) found that younger people are more likely to adopt unsafe riding behaviors because they more often choose a fast passage rather than pavement.…”

Section: Theoretical Framework and Hypotheses Developmentmentioning

confidence: 99%

“…Jia et al (2018) found that cyclists with higher levels of education have better quality and control ability to use sharing bikes civilly. Also, studies have revealed that males are more prone to ride while using cell phones than females, and high-income people pay more attention to cycling safety than low-income people do (Holland and Hill, 2007; Wu et al, 2019). Therefore, we assume that gender, age, educational level, and income impact civilized cycling intention and behavior (e.g., Acheampong, 2017; Katharina, 2018).…”

Section: Theoretical Framework and Hypotheses Developmentmentioning

confidence: 99%

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Improving Cycling Behaviors of Dockless Bike-Sharing Users Based on an Extended Theory of Planned Behavior and Credit-Based Supervision Policies in China

2019

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Motivating users’ civilized cycling plays a significant role in alleviating the troubles of dockless bike-sharing programs (DBSPs) and promoting the sustainable development of bike-sharing organizations. Based on the theory of planned behavior (TPB) and observed practices in China, this study develops a theoretical framework to examine how attitudes (ATT), subjective norms (SN), perceived behavioral control (PBC), and personal norms (PN) motivate users’ civilized cycling behavior through civilized cycling intentions. Furthermore, the moderating effect of perceived policy effectiveness (PPE) between users’ civilized cycling intention and their actual behavior is tested. Using structural equation model-multiple group analysis (SEM-MGA) for a sample of 874 valid questionnaire responses in Beijing and Shanghai, China, our results reveal that (1) ATT, PBC, and PN are positively related to both users’ civilized cycling intentions and their actual behavior, while SN positively affect users’ civilized cycling intention only; (2) users’ civilized cycling intentions mediate the relationship between the four influencing factors and their actual behavior; and (3) PPE plays a moderating role for the effect of users’ civilized cycling intentions on their actual civilized cycling behavior. Our results indicate that the four influencing factors can encourage users’ civilized cycling behavior, especially when civilized cycling intention exists. Policies like credit-based supervision mechanisms could promote users’ civilized-cycling intentions, which could then be transformed into actual behavior.

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Section: Theoretical Framework and Hypotheses Developmentmentioning

confidence: 99%

Section: Theoretical Framework and Hypotheses Developmentmentioning

confidence: 99%

Section: Theoretical Framework and Hypotheses Developmentmentioning

confidence: 99%

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Improving Cycling Behaviors of Dockless Bike-Sharing Users Based on an Extended Theory of Planned Behavior and Credit-Based Supervision Policies in China

2019

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“…It is noteworthy that electric bicycles have grown rapidly in recent years, with the number of e-bikes exceeding 250 million in China [3,4]. In addition, shared bicycles also have gained tremendous popularity as a result of their convenience [5,6]. However, due to their vulnerability in a collision, cyclists are subject to higher safety risks than drivers of vehicles [7,8].…”

Section: Introductionmentioning

confidence: 99%

A Mixed-Flow Cellular Automaton Model for Vehicle Nonstrict Priority Give-Way Behavior at Crosswalks

Cheng

Lü

et al. 2020

Journal of Advanced Transportation

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The vehicle nonstrict priority give-way behavior (VNPGWB) is a common part of traffic interaction between motorized and nonmotorized vehicles in many countries. This study proposes a mixed-flow cellular automaton model to simulate the passing of vehicles in front of bicycles at crosswalks. The mixed-flow model combines a vehicle model with a bicycle model, using nonstrict priority give-way and strict give-way two driving behaviors defined as relating to the decision point rule and the launching rule, respectively. Simulation results showed that as the vehicle and bicycle inflow rates increased, a critical inflow rate divided vehicle and bicycle traffic flow into free flow and saturated flow conditions. The values of vehicle saturation flow decreased from 0.34 to 0.05, and the values of bicycle saturation flow decreased from 0.54 to 0.44, indicating that the mixed traffic flow has a negative effect on vehicle and bicycle saturated flow. Results also showed that VNPGWB effectively improves vehicle saturation flow over that of the strict give way. The advantage of VNPGWB is more signiﬁcant when vehicles and bicycles are in saturation traffic flow.

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“…Description of data collection We estimated a priori experimental needs for a one-month survey period and used an iterative sampling through a “snowball technique” recruitment strategy through a WeChat-based online survey for a month, from September 7, 2017 to October 6, 2017. Data source location Urban China Data accessibility Data are accessible with the article Related research article The associated research article to this data set is [1] . …”

mentioning

confidence: 99%

Data on unsafe riding behaviors among 1960 shared bicycle riders in urban China

Xiao

Deng

et al. 2019

Data in Brief

Self Cite

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This data article quantifies the extent of shared bicycle riding risks for shared-bicycle riders in urban China. The data were collected through a WeChat-based online survey, with a valid sample of 1960 respondents. It reports the basic descriptive statistics through eight tables concerning various unsafe shared bicycle riding behaviors, and complete frequency data from riders concerning eight unsafe riding behaviors. The data can be used for comparisons with other studies using the same outcome measures, which are valuable to generate specialized and targeted solutions to reduce unsafe riding behaviors. For further information, please refer to the full article entitled “Unsafe riding behaviors of shared-bicycle riders in urban China: A retrospective survey”.(Wu et al., 2019).

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Unsafe riding behaviors of shared-bicycle riders in urban China: A retrospective survey

Cited by 33 publications

References 34 publications

Improving Cycling Behaviors of Dockless Bike-Sharing Users Based on an Extended Theory of Planned Behavior and Credit-Based Supervision Policies in China

Improving Cycling Behaviors of Dockless Bike-Sharing Users Based on an Extended Theory of Planned Behavior and Credit-Based Supervision Policies in China

A Mixed-Flow Cellular Automaton Model for Vehicle Nonstrict Priority Give-Way Behavior at Crosswalks

Data on unsafe riding behaviors among 1960 shared bicycle riders in urban China

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