Dispatching Area Identification and Tidal Effect Evaluation of Dockless Bike-Sharing During Peak Hours

Dockless bike-sharing (DBS) is popular among users because of its convenience and ready-to-stop features, however, which leads to uneven Spatial–temporal distribution. Rational dispatching helps balance the Spatio-temporal of the DBS and achieve the goal of satisfying more people’s riding needs with fewer bikes. Previous research has focused more on the establishment of dispatching models and the optimization of algorithms. However, direct programming of the entire region would ignore the effect of distance and lead to inefficient dispatching. Therefore, it is necessary to divide the area for zonal dispatching and management. In this paper, a DBS network model is constructed using the DBS order data of Beijing. The connection intensity index was established based on the Gravity model and applied to the community detection algorithm to obtain the dispatching communities. Then, the bilateral tidal degree of each community in the morning peak was evaluated based on community detection. The results show that the scale of each dispatching area is different, with an average scale of 16 km2, which is smaller than the size of the administrative districts. In addition, the bilateral tidal phenomenon is more serious in Zhongguancun, the southern part of Xicheng District, and the western part of Fengtai District. These results help managers to have a more comprehensive understanding of the tidal characteristics of the DBS, facilitating area management and bicycle dispatching.