Abstract
The evolution of knowledge networks has recently received a lot of attention from researchers. Empirical studies have shown that different types of proximities and network structural properties play a decisive role in tie formation. The present paper contributes to this literature by arguing that while these are crucial, they do not capture the full range of localities’ influence on the evolution of knowledge networks. We support our argument with an empirical study on the development of the biotechnology knowledge network of Berlin from the early 1990s till 2016. The network was created by combining data on co-patenting, co-authorship and joint R&D projects. Forces driving the evolution of the network were identified with separable temporal exponential random graph models (STERGM). In addition to the ‘usual suspects’ (main proximity dimensions and structural factors), we found that the network is still developing in the ‘shadow of the wall’. The different social contexts in the different parts of the city of Berlin still hamper the establishment of collaborative ties between the former East and the former West Germany even 30 years after reunification.
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