Abstract: Innovations apply already since Schumpeter as the main influencing component of economic growth, employment and wealth. The diffusion of innovation is also one of the driving forces for the development of a region and for the different economic performances of different regions. Innovation depends on ideas coded in information and ideas respectively information will be created by individuals. If individuals are not connected to others (in a network) then this personal information cannot be accessed by other individuals (agents). This implies that networks are relevant for information diffusion and hence for the creation of innovation. But which network structure has which influence on the information diffusion via the network? And what are strategic positions in the network, i.e. who has which influence? Social network analysis (SNA) offers a rich variety of instruments applicable for investigating these questions given certain information and innovation networks are available. Random networks have different properties than small-world networks or scale-free networks especially with regard to the speed and the range of the information diffusion. Some agents are more central than others. Different network structures can lead to different regional growth paths. This paper investigates such network structures by using agent-based models combined with methods of SNA. The agents are interconnected in different networks which serve as the infrastructure for the innovation diffusion. Based on the structure of the network different growth paths can be identified. Methods of SNA will then be used to describe the networks and their main components. Hence the relation between the structure of the network and its performance measured by the growth paths can be analysed and evaluated.