Examining bike share usage trends in Metropolitan cities through App based data. A case study of Chennai, India

Bicycle-sharing systems (BSSs) have emerged as an important climate-smart transportation strategy in many cities, supporting sustainable low-carbon societies. Despite becoming permanent fixtures in the Western urban landscape, bike share implementation in Asia has been disappointing, apart from China. However, future bike share growth trends indicate that Asian cities are potential hubs for bike share schemes. As a result, it is critical to investigate the current operations of bike-share schemes in these cities to understand the factors influencing bike-share use in various urban areas, which can improve system performance and encourage more use in the future. This paper investigates usage trends in a bike-sharing scheme that has been in operation in Chennai since 2019. While many studies have been conducted on how bike-sharing schemes are changing mobility in cities around the world, particularly in developed countries, few have addressed the dynamics of these schemes in cities in developing countries such as India. One of the reasons for looking at a city like Chennai is to see if metropolitan cities in developing countries benefit from bike-sharing schemes and if bike-sharing schemes can play a prominent role in these cities, as these cities face many transportation challenges such as congestion, delay, pollution, accidents, and last mile connectivity issues, among others. The study used app data to conduct an exploratory analysis to examine the impact of factors such as temporal, weather, travel characteristics, and bike type (conventional or E-bike) on bike share usage in the city. The MNL model results from this study related to bike-share ride duration (short, medium, and long) can help other cities in developing countries improve and/or expand their existing bike-share networks, as well as cities planning to launch new bike-share programs. Furthermore, examining the impact of different temporal, and weather factors on mode usage behaviour (conventional and e-bike) in bike share provides insights into user preferences and how these factors influence user mode choice behaviour in similar cities.