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Inter‐organizational network management in an innovation context: Combining ego and whole network perspective

: Cap, Jan-Patrick; Blaich, Erik; Kohl, Holger; Raesfeld, Ariane von; Harms, Rainer; Will, Markus

Aaltio, I.:
11th European Conference on Innovation and Entrepreneurship 2016. Proceedings : 15-16 September 2016, Jyväskylä, Finland
Reading: ACPI, 2016
ISBN: 978-1-911218-07-4 (Print)
ISBN: 978-1-911218-08-1 (E-Book)
European Conference on Innovation and Entrepreneurship (ECIE) <11, 2016, Jyväskylä/Finland>
Conference Paper
Fraunhofer IPK ()

Although there is growing interest into the research field of inter-organizational innovation networks, few attempts have been made to develop systematic methods for the active management of such networks. This is especially true for approaches combining the view of single actors and the network as a whole. In response to this gap, this research presents a new method for the management of inter-organizational networks that can help to increase innovation outcome. The introduced approach accomplishes two goals. Firstly, it provides guidance for the measurement of the current collaboration status of a network, its optimal future collaboration status and the gap between them. Secondly, it provides systematics for the development of clear network management strategies for each network actor for closing this collaboration gap. As a result, better exploitation of existing collaboration potential is expected to increase innovation output. The method builds upon work by Kohl et al. (2015) who approached network management on a whole network level providing a solution for the management of entire networks and Ojasalo (2004) who suggested a network management method taking the perspective of a single network actor on the so called ego level. The novelty value of the presented method lies in the demonstration of how these different levels of network management can be combined. The two levels of analysis are linked through reliance on the same data set. The developed method is demonstrated through a case study. The analysis builds upon a questionnaire asking network actors for an estimation of the current collaboration status and a future collaboration potential amongst them. Social network analysis software was used to calculate network measures such as the level of density and to visualize the network graphically. As a result customized strategies for improving collaboration within the investigated network are presented.