Fraunhofer-Institut für Produktionsanlagen und Konstruktionstechnik IPK

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Multi level network management - A method for managing inter-organizational innovation networks

2019 , Cap, J.-P. , Blaich, E. , Kohl, H. , Raesfeld, A. von , Harms, R. , Will, M.

Collaboration in inter-organizational networks is a major driver of innovation. Nevertheless, methods that practitioners can rely upon for managing innovation networks are still scarce. This research fills this gap by providing an approach that increases innovation output by intensifying collaboration in networks. An action research methodology with two cycles of action was adopted. The first cycle develops a method of network assessment designed to evaluate a network's collaboration potential. The second cycle iteratively builds on the first cycle and extends the method by a managerial approach to network management on an individual level.

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The innovation network scoreboard: Towards key performance indicators for the assessment of innovation networks

2015 , Kohl, H. , Cap, J.-P. , Blaich, E. , Raesfeld, A. von

This work operationalizes a framework for the assessment of innovation networks. While a theoretical framework provides value to scholars, practitioners require concrete methods and indicators that they can apply to their projects. Scholars face the same demand when conducting empirical research. This paper seeks to meet this demand, while also contributing to the theoretical perspective by uniting different research streams in the field of network research in one framework, the Innovation Network Scoreboard. The concept of innovation networks has gained popularity during recent years and much research has been dedicated to the relation between networks and innovation outcome. Still, scholars have criticized the field of network research for lacking academic consensus and generalizable empirical findings. These circumstances make it difficult for practitioners to apply network theories and to draw conclusions for real world networks. We suggest key performance indicators that provide practitioners with some guidance in this difficult task. The suggested measures are based on an extensive literature review. We have chosen concepts, for which to our interpretation some academic consensus has been reached. According to the previously introduced model we developed key performance indicators for the dimensions input factors of innovation networks, network characteristics in terms of network content, network structure and network atmosphere and finally innovation output. Combined, these dimensions provide a holistic overview over an innovation network and allow for a root cause analysis that provides hints on the cause of a change in innovation output. We provide quantitative measures for each dimension and summarize those in the Innovation Network Scoreboard. This tool provides a concise overview over the most important indicators of innovation networks. Furthermore, we describe concrete approaches to the measurement of each indicator. In sum a concrete method is provided to practitioners for the evaluation of innovation networks from different perspectives.

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