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

Increasing Bike-Sharing Users' Willingness to Pay - A Study of China Based on Perceived Value Theory and Structural Equation Model

Bike sharing, as an innovative travel mode featured by mobile internet and sharing, offers a new transport mode for short trips and has a huge positive impact on urban transportation and environmental protection. However, bike-sharing operators face some operational challenges, especially in sustainable development and profitability. Studies show that the customers' willingness to pay is a key factor affecting bike-sharing companies' operating conditions. Based on the theories of perceived value, this study conducts an empirical analysis of factors that affect bike-sharing users' willingness to pay for bike-sharing through measurement scales, user surveys, and structural equation models. We designed a five-point Likert-type scale containing 11 latent variables affecting willingness to pay and a total of 34 measurement items. We investigate bike-sharing users in China's first and second-tier cities, with a total of 502 participants. The results show that perceived value, payment awareness, trust, and environmental awareness constitute key factors that directly affect bike-sharing users' willingness to pay. And perceived usefulness, perceived ease-of-use, perceived cost, and perceived risk indirectly affect bike-sharing users' willingness to pay. However, we found no significant effects of perceived entertainment on perceived value or word of mouth on willingness to pay. Our results are expected to provide theoretical and practical implications for bike-sharing programs.

How Does the Collaborative Economy Advance Better Product Lifetimes? A Case Study of Free-Floating Bike Sharing

The collaborative economy is considered to have great potential in promoting the circular economy. However, there is little empirical research in this field. Taking the Beijing free-floating bike sharing (FFBS) program as an example, this study develops a system dynamics (SD) model based on the product lifetime extension business model (PLEBM) framework, and the business practices of FFBS. Combined with the dynamic evolution process of the FFBS market, the impact of FFBS on bicycle lifetime and the utilization efficiency of the urban bicycle system is explored. The results show that FFBS can reduce the required supply scale of the entire bicycle system by about 21%, and increase the average daily usage of bicycles by about 27%. In addition, FFBS also can increase the average lifecycle trip volume per bike in the entire urban bicycle system from approximately 900 to 1060, an increase of 16%. In particular, this study estimates that the optimal supply scale of the FFBS market in Beijing is about 800,000. It is worth noting that although enhancing the PLE strategy can increase the contribution of FFBS to PLE, it may also deteriorate the profitability of the FFBS platform. The authorities and FFBS operators should work together to continuously improve the profitability of the platform and strengthen its innovation capabilities to promote the healthy and sustainable development of FFBS.

Shifting to Shared Wheels: Factors Affecting Dockless Bike-Sharing Choice for Short and Long Trips

In this paper, we explore users’ intentions to use bike-sharing systems (BSS) compared to traditional competitive transport modes—private car, bus and walking. Fueled by the increasingly rampant growth of shared economy and Information and Communication Technology (ICT), shared mobility is gaining increasing traction. The numbers of shared mobility schemes are rapidly growing worldwide and are accompanied by changes in the traditional vehicle ownership model. In order to pinpoint the factors that strongly affect the willingness to use BSS, a stated preference survey among car and bus users as well as pedestrians was designed and conducted. Binary logit models of the choice between the currently preferred transportation modes and BSSs were developed, for short and long-duration trips, respectively. The results highlight a distinctive set of factors and patterns affecting the willingness to adopt bike-sharing: choice is most sensitive to travel time and cost of the competitive travel options. In general, users are more willing to make the switch to a BSS, especially for short trip durations, when their typical mode of transport becomes more expensive. Bike-sharing also seems to be a more attractive option for certain user socio-demographic groups per mode and trip duration (age, education level, employment status, household income). Trip characteristics such as trip purpose and frequency were also found to affect the willingness to choose BSS. In general, BSS seem to mainly attract bus users and pedestrians, while car users may use BSS more sparingly, mainly for commuting purposes.

Where Urban Youth Work and Live: A Data-Driven Approach to Identify Urban Functional Areas at a Fine Scale

As a major labor force of cities, young people provide a huge driving force for urban innovation and development, and contribute to urban industrial upgrading and restructuring. In addition, with the acceleration of urbanization in China, the young floating population has increased rapidly, causing over-urbanization and creating certain social problems. It is important to analyze the demand of urban youth and promote their social integration. With the development of the mobile Internet and the improvement of the city express system, ordering food delivery has become a popular and convenient way to dine, especially in China. Food delivery data have a significant user attribute where the ages of most delivery customers are under 35 years old. In this paper, we introduce food delivery data as a new data source in urban functional zone detection and propose a time-series-based clustering approach to discover the urban hotspot areas of young people. The work and living areas were effectively identified according to the human behavioral characteristics of ordering food delivery. Furthermore, we analyzed the relationship between young people and the industry structure of Hangzhou and discovered that the geographical distribution of the identified work areas was similar to that of the Internet and e-commerce companies. The characteristics of the identified living areas were also analyzed in combination with the distribution of subway lines and residential communities, and it was found that the living areas were mainly distributed along subway lines and that urban villages appeared in the living hotspot regions, indicating that transportation and living cost were two important factors in the choice of residential location for young people. The findings of this paper can help urban industrial and residential planning and young population management.

Dynamic Feedback Analysis of Influencing Factors and Challenges of Dockless Bike-Sharing Sustainability in China

Dockless bike-sharing programs (DBSPs) are typical representatives of the new era of the internet economy. These schemes alleviate urban traffic congestion, reduce carbon emissions, and change people’s preferred travel modes, but they also suffer from a series of problems related to unsustainability. The sustainability performance of a DBSP is closely related to its influencing factors, which can be used to understand the main challenges of the program and consider what useful measures should be taken to overcome these issues. Therefore, it is essential to investigate the related factors that are critical to the sustainability of DBSPs from a systems-level perspective. In this paper, we explored publicly available data sources (i.e., literature, institutional reports, and announcements) to determine the intrinsic influencing factors and understand their interactions and feedback relationships. A taxonomy of the key challenges with respect to the fundamental pillars of DBSP sustainability (i.e., environment, society, and economy) was provided. System dynamics methodology was employed to map the critical factors and links in order to analyze the key challenges in facilitating the sustainability of DBSPs. Based on this approach, we put forward proposals to mitigate the severe challenges for governments and DBSP operators. The findings provide a theoretical basis and guiding role to develop improvement strategies for DBSP sustainability.

Customer Incentive Rebalancing Plan in Free-Float Bike-Sharing System with Limited Information

Free-float bike-sharing (FFBS) systems have increased in popularity as a sustainable travel mode in recent years, especially in the urban areas of China. Despite the convenience such systems offer to customers, it is not easy to maintain an effective balance in the distribution of bikes. This study considers the dynamic rebalancing problem for FFBS systems, whereby user-based tactics are employed by incentivizing users to perform repositioning activities. Motivated by the fact that the problem is frequently faced by FFBS system operators entering a new market with limited information on travel demand, we adopt the ranking and selection approach to select the optimal incentive plan. We describe the system dynamics in detail, and formulate a profit maximization problem with a constraint on customer service level. Through numerical studies, we first establish that our procedure can select the optimal incentive plan in a wide range of scenarios. Second, under our incentive plan, the profit and service level can be improved significantly compared with the scenario without incentive provision. Third, in most cases, our procedure can achieve the optimal solution with a reasonable sample size.

Designing a User Participation-Based Bike Rebalancing Service

The Bicycle-sharing System (BSS) has been globally adopted as a sustainable transportation system that helps improve air pollution, public health and traffic congestion. The increased usage of BSSs requires an increased number of rebalancing trucks to distribute bikes throughout the city. Operating rebalancing trucks is an expensive venture that requires intensive manpower that is dependent on traffic congestion. In this background, a user participation-based rebalancing service was introduced to solve the problem, but it was difficult to test the impact of the service and the estimated cost in the city. Thus, this research proposes a simulation system that tests user participation-based rebalancing services with different user parameters such as the amount of incentives, the user participation rate and extra walking distances. We conducted an incentive survey on actual BSS users to determine the accurate values of these parameters. We also identified that, among the three parameters, extra walking distance is the most influential element on which to improve the rebalance imbalance metric. We found that the incentive coefficient is an important variable in determining the estimated cost of the service. Thus, any city can utilize the proposed system to design a user participation-based rebalancing service that is suitable for their city.