Factors affecting bike-sharing behaviour in Beijing: price, traffic congestion, and supply chain

The bike-sharing boom is receiving growing attention with societies becoming more aware of active non-motorized traffic modes and their importance. However, the usage of this transport mode remains low in China, raising several concerns. The development of the bike-sharing behaviour can help to achieve sustainable development goals. Thus, this study aims to explore the impact of price, traffic congestion, and supply chain on bike-sharing selection behaviour. We employ big data technology to accurately research and evaluate usage behaviour towards bike-sharing apps in Beijing over a 4-day period. First, we administer a preliminary questionnaire survey across the country to explore factors influencing the choice of bike-sharing. Second, we perform a panel model regression to analyse the degree of impact by major factors on bike-sharing usage. The results revealed that price, traffic congestion, and supply chain affect the choice of bike-sharing and the degree of each factor’s impact differs by time of day. Drawing on these findings, we offer the following suggestions to increase the usage amount of bike-sharing and improve the operating efficiency of bike-sharing companies: (1) design time-based charging strategies (2) reasonably limit the number of shared bikes as per time of day (3) establish effective layouts for bicycle sites (4) account for maintenance time, and (5) use methods other than price wars to increase usage.