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Within this paper the global positioning system (GPS) booking data of a free-floating Bike Sharing System (BSS) in Munich is analyzed. It is illustrated in detail, where bikes can be rented and returned within a predefined operating area. Temporal and spatial booking patterns of the bike rentals are also identified. Taking into account short- and long-term weather conditions, one can forecast the expected demand and detect a possible shortage in bikes at a certain time and place. The results prepare the ground for future research, i.e. an optimization and reallocation of the fleet. To analyze the needs of the users and to verify the requirements for an advanced public BSS, an additional online survey was carried out among customers of the local Bike Sharing provider in Munich, known as Call a Bike. The survey focused on the usage, experience and performance of Bike Sharing offers as well as the appreciation of E-bikes in large German cities with BSSs.
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