Shared Transport in a Digitalized World: A Case Study of Shared Bicycles through Data Mining and Visualization

Abstract

The shared economy is emerging dramatically in recent years including shared bicycles (Mobike/Ofo), shared accommodation (Airbnb/Xiaozhu), ridesharing (Uber and DiDi), and shared office space (Wework). Both criticisms and praises appeared to this situation. In this paper, we employ a Hadoop platform and survey to collect data of shared bikes in Chengdu, China, and then to perform data mining and cleansing, and further utilize data visualization to visualize and analyze the data. Experiments and results demonstrate the high distribution of shared bicycles in high density population area and the distribution changes between working hours and non-working hours. The individual tracking of a randomly selected bicycle indicates that the usage efficiency of shared bicycles could be improve by well management.