Analyzing External Factors on the Spatial and Temporal Demand of Car Sharing Systems

During the last decades, Car Sharing emerged as a new important type of mobility service, different systems are installed and operated today. For an efficient and economic operation of any Car Sharing system, the identification of customer demand is essential. This demand is investigated within the presented research by analyzing booking data of two Car Sharing systems. The objective is to identify different influences on the usage of Car Sharing. Parameters to investigate are manifold: they can include those easy to measure like hourly or daily changes in usage and also influences like weather or socio-demographic data. Therefore both the spatial and the temporal points of highest or lowest demand have to be identified and linked with the given data of the different parameters. This paper describes how the interdependencies can be identified. The given data is analyzed in order to identify spatial and temporal Hot-Spots and Cold-Spots with high respectively low frequency of bookings. By overlying these results with the different parameters the existence of interdependencies can be described.