SPATIAL OPTIMIZATION OF CARSHARING NETWORK IN SINGAPORE

Abstract

Urban sustainability and environmental concerns have proliferated transport innovation and shared mobility systems such as carsharing in the last decade. Strategic optimization of carsharing locations is imperative to maximise resource efficiency. Hence, this study seeks to understand the locational characteristics that define and support carsharing operations and locations and if the extent of influence varies between different carsharing operational models. Core demographic, transportation infrastructure and built environment characteristics were analysed with the presence and quantity of carsharing operations in subzones. To analyse the relationships, two statistical models were used; Logistic regression to ascertain the influence of subzone characteristics with carsharing presence in subzone and Poisson regressions to analyse the influence of subzone characteristics on the quantity of carsharing operations, namely the number of stations and vehicles under different operational models. Results showed that a combination of demographics, transportation infrastructure and built environment characteristics supports greater carsharing stations and vehicles in subzones. The key subzone characteristics identified are the population proportion living in HDB flats, population density, population proportion aged 0 to 19 years old, number of MRT and LRT stations, car parks and shopping malls. Using the result findings, it was also noted that there are several other subzones with little or no carsharing presence but exhibit high similarities to those that are successful currently. Five location recommendations were made at the end of the study as potential areas for carsharing network expansion. This study will be insightful to carsharing operators on identification of locations, as well as urban planners in the planning of urban transport systems.