Abstract
In China, dockless bike-sharing programs (DBSPs) have changed people’s travel modes, alleviated urban traffic congestion, and reduced carbon emissions. However, a number of DBSPs have experienced financial crises since 2018. This means that research on DBSPs must be considered not only in terms of the environment and technology, but also in the operation of the program. In this paper, we modeled the DBSP operations in a certain area using a system dynamics simulation approach. The main purpose was to explore the dynamics of the program’s operation process and evaluate possible improvement strategies for maximizing the revenue of the overall DBSP. Specifically, the analysis focused on the economic profits of DBSPs in an environment of competition and government regulation. The research findings revealed that the dockless bike-sharing industry has great economic profits, but in the current environment, the market needs to be regulated by the local government. If a DBSP does not introduce new technologies or find new profit channels, it will be difficult to develop sustainably by only relying on riding profits. In addition, we provide a case study of Mobike’s operations in Beijing to support these findings and validate the developed model. Finally, we discuss Mobike’s possible improvement strategies.
Highlights
The history of shared bikes can be traced back to the 1960s, and the first “shared” concept bike was born in Amsterdam, the Netherlands [1]
When the Capital Pool collapses, the dockless bike-sharing programs (DBSPs) will withdraw from the regional market, which means that the target bikes quantity is equal to zero
The reasons for choosing Beijing were as follows: (1) There is fierce competition in this area where the focus is on business and large-scale investment by each DBSP; (2) Beijing is the capital of China so the DBSPs are under strict government regulation; and (3) most of the real data for this area is given
Summary
The history of shared bikes can be traced back to the 1960s, and the first “shared” concept bike was born in Amsterdam, the Netherlands [1]. 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.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
