The image shows the usage of shared scooters and shared bikes in the two distinct areas in Singapore Credit: Singapore-MIT Alliance for Research and Technology (SMART)

While ridesharing services like Grab, Uber and Gojek have become a pervasive part of life, many countries in the Asia Pacific are still unconvinced when it comes to micro-mobility such as bike and scooter-sharing. While convenient, especially during a pandemic, when people may be wary of crowding in busses and metro trains, there is a need for in-depth knowledge of these new transportation options to help guide policy and regulation.

A group of scientists at Future Urban Mobility (FM) Interdisciplinary Research Group (IRG) at Singapore-MIT Alliance for Research and Technology (SMART), MIT's research enterprise in Singapore, and Massachusetts Institute of Technology (MIT) set out to better understand the phenomenon and inform policymaking through a comparative analysis of bike-sharing and scooter-sharing activities in Singapore.

The researchers shared their findings in a paper titled "Understanding spatio-temporal heterogeneity of bike-sharing and scooter-sharing mobility" published in the journal Computers, Environment and Urban Systems. The study is based on real usage records containing location and time of departures and arrivals in two distinct areas in Singapore.

"We constructed historical trajectories of the bike-sharing and scooter-sharing trips and compared usage patterns of the two systems at the Marina Bay area and the NUS campus," says Dr. Rui Zhu, Postdoctoral Associate at SMART FM. "Our results showed increased sharing frequency and decreased fleet size for scooter-sharing, suggesting that it performs better than bike-sharing."

More specifically, the sharing frequency was increased from less than one time per day for bike-sharing to more than three times per day for scooter sharing, but the researchers believe that can be improved even further to create a more profitable service.

The study also found that shared scooters in Marina Bay were frequently left away from their designated or charging stations, indicating costly and manpower-intensive maintenance since employees need to collect and transport scooters between stations continuously. However, the statistics also showed that over 28% and 26% of trips departed from and arrived at non-stations respectively, suggesting that users actually used most of the inappropriately returned scooters.

In addition, the study revealed quantitative changes in trips over time, distances and duration, and the influence of weather on the demand of micro-mobilities.

"In Singapore and a few other cities, dockless bike-sharing systems rose and fell in just one year, followed by an explosion of docking scooter-sharing systems. But we didn't have the necessary insights for appropriate business and policy decisions," Dr. Zhu explains. "Our study goes deeper into the problems and possibilities of micro-mobility sharing and suggests how these services can be improved."

To facilitate a sustainable -sharing service, the researchers suggest optimizing the fleet size of stations and their locations, regulating returning behaviors more strictly, enabling scooters to have autonomous repositioning functionality, and increasing the useful battery life of scooters.

To increase battery life, they suggest installing a photovoltaic module on scooters for solar charging during trips and parking time or equipping conventional dock-based stations with grid charging or solar charging platforms, allowing for an environmentally friendly solution that will be able to reduce carbon footprints.

While the business model and user behavior greatly impact the success of mobility-sharing services, government policy also plays a significant role. Supportive policies or regulations on controlling fleet sizes and limiting usage to discrete areas are huge drivers for the sustainable development of the new transportation modes. With this study, SMART's researchers hope to fill existing gaps in knowledge about micro-mobility sharing to help inform policy decisions.

More information: Rui Zhu et al. Understanding spatio-temporal heterogeneity of bike-sharing and scooter-sharing mobility, Computers, Environment and Urban Systems (2020). DOI: 10.1016/j.compenvurbsys.2020.101483