Scientific ecosystems and decentralized orchestration: A social network analysis of the CINet conferences

This article addresses the orchestration of scientific ecosystems, which encompass a variety of competing and/or collaborating autonomous actors – including researchers, universities and industrial firms – which aim at developing theory. Scientific ecosystems are a very interesting subject to be studied because some of their features – specifically data building and sharing – are increasingly assuming importance for firms that post-COVID will have to cope with the ‘new normal’, which requires them to experiment on the basis of collectively gathered data in order to accelerate their learning “on the fly”. Specifically, business ecosystems challenged by the ‘new normal’ can leverage on the experience that scientific ecosystems have always had regarding data building and sharing.
Considering conferences as decentralized orchestrating moments capable of pulling together dispersed resources/capabilities by ensuring knowledge mobility, and building on a social network analysis of the CINet conferences between 2014 and 2017, we aim at understanding the characteristics of the CINet scientific ecosystem in order to infer how well connected and close its researchers are and how effectively information is shared among them.