The German Climate Action Plan targets an electric vehicle fleet of 6 million by 2030. However, from today’s perspective, we are far away from a path that is steep enough to reach this goal. In order to identify how different policy instruments can stimulate e-mobility diffusion in Germany, we build and calibrate an agent-based simulation model (ABM). The model allows for the consideration of the rich dynamics of social influence as well as the heterogeneity of actors and is flexible enough to be applied with other technologies. We simulate different policy scenarios against a business as usual (BAU) scenario. We show that with the currently implemented set of policies (BAU scenario), it is very unlikely that the envisaged goals in terms of e-mobility diffusion can be reached. Moreover, we suggest additional measures such as a carbon tax on fuel, more charging points, and higher direct subsidies, which are as a combined package likely to have a significantly positive effect on the diffusion of electric cars.

The present paper analyzes development patterns in research networks and technology as well as their co-evolution by the example of the currently highly transformative German automotive industry. We therefore introduce a consistent network-based approach for measuring change in research networks and the technological composition of patents. Our results show that the applied method is particularly useful for identifying structural similarities and main structural changes in research and patent networks. Further, the investigation of the co-evolutionary processes indicates that, regarding the German automotive industry, changes in technology lead to structural changes in the research network.