Over the last decade, a vast number of public APIs have been created across many different industries. This development leads to powerful ecosystems and new business models enabling companies to develop new revenue streams. This trend is also referred to as API Economy. Within the Automotive Industry, little or no such trend can be observed. Especially modern vehicles with myriads of sensors could provide valuable data for new business models around the automotive industry. In this master thesis, current collection methods for vehicle-generated data are explored. Further, the value creation process for vehicle-generated data is analyzed in detail. The current state of the API Economy within the Automotive Industry is analyzed by gathering use-cases for vehicle-generated data from an extensive literature review and semi-structured expert interviews. Furthermore, it is analyzed which barriers are inhibiting the prevalent adoption of an API Economy within the Automotive Industry. The work eventually analyzes potential measures for advancing an API economy within the automotive industry which were gathered from the conducted interviews.

The target of this work is to provide a snapshot of current use cases for vehicle- generated data, the provisioning of vehicle-generated data through APIs provided by the automotive manufacturer and the state of a potential API economy.