The Analysis of the Influencing Factors on the Problems of Bike-Sharing System in China

Abstract

Bike-sharing has experienced rapid growth in China since 2016. Notwithstanding the fast expansion, or possibly because it grew too fast, some bike-sharing companies have experienced setbacks and failure in 2018. This paper aims to close the gap due to the insufficient analysis on the influencing factors of the bike-sharing system problems in China. The study first used text mining of bikes-sharing related Chinese news reports and social web discussion boards. Subsequently, the study used association rule mining to explore the relationship between keywords generated by text mining of the original data sources. The results of news reports mined keywords show that problems with shared bikes deposits were closely related to the complaints of customers. In the context of social web discussion boards, the keywords relations implies that the users concern about the possible collapse of the bike-sharing companies and related management and economy issues. The information existed before the bike-sharing companies financial failure news took place. Our results also show that the association rule mining relationship of major keywords in news reports and social media can be an early warning sign of the financial failure of sharing bikes companies.