The world is relational. The vast majority of objects and subjects are embedded in complex relational structures, commonly called “networks”. My research focuses on knowledge networks, i.e. networks with the objective of knowledge and information diffusing between individual actors, organisations, and regions. I am particularly invested in understanding why networks show specific structures, what factors are determine these, how do they evolve over time, and to what extent they matter economically. In the following, I list a selection of core results of my research.
1. Networks are driven by proximities
Economic entities (individuals, organisations, regions) are more likely to exchange knowledge when being proximate in one or multiple of the following dimensions: geographical, organisational, institutional, social & cognitive.
Interorganizational network of subsidized R&D collaboration. Based on BMBF subsidies data (Federal Ministry of Education and Research, Germany), see Broekel & Hartog (2012b).
2. Not all links in knowledge networks are equal
In network science links are ranked based on their structural importance, i.e. to important links are those that when removed, the “structure” of the network dramatically changes. Such links also turn out to be special also from a “real world” perspective. In inter-organisational knowledge networks, they tend to be formed between gatekeeper organisations offering related knowledge resources. They also bridge institutional distances by utilising the benefits of geographic and social proximity.
Interorganizational network of subsidized R&D collaboration. Based on BMBF subsidies data (Federal Ministry of Education and Research, Germany), see Broekel & Mueller (2016).
3. Not all networks are equal
Interorganizational knowledge networks vary in their structure in many ways. Some are more centralised others are more fragmented. But why is this the case? In my research, I identify that the type of knowledge that is diffusing in these networks relates to their structure. Networks that are dominated by firms and hence are focused on applied knowledge tend to be larger and less dense with big firms being the most central organizations. In comparison, networks dominated by public actors, i.e. those that are oriented towards basic research, are stronger centralised and involve more isolates.
Interorganizational network of subsidized R&D collaboration. Based on BMBF subsidies data (Federal Ministry of Education and Research, Germany), see Broekel & Graf (2012).