This thesis is devoted to a phenomenon that is currently reshaping the global business architecture: Open innovation (OI)
networks. Managers are interested to know how to construct and manage their networks such that they are beneficial for their OI efforts.
The goal of the thesis is to determine how network characteristics influence the effectiveness of different types of OI activities and how firms can achieve a beneficial network position by engaging in OI efforts.
This thesis is based on three empirical studies that draw on social network theory as an overreaching theoretical framework. Furthermore, this thesis aligns social network theory with the relational view and the literature on distant knowledge. To provide a comprehensive understanding of OI networks, the studies in this thesis also employ different methodological approaches: Crosssectional and longitudinal analysis based on multisource and multiindustry datasets.
The key results show that in order to profit from OI firms need well-elaborated risk and network management practices that are
applied to the main decisions that managers have to make regarding firms’ entire OI efforts. In specific, network characteristics can help firms to increase the potentials of the upsides of OI and at the same time they can reduce the risks of the downsides of OI. Moreover, certain types of OI activities are more or less suitable for achieving a beneficial position in an OI network and fostering firm performance. Altogether, this thesis provides important implications for managerial practice and closes relevant gaps in the scientific research regarding OI networks
