Innovation networks and cluster dynamics

Contributions in terms of clusters life cycle indicate that intense interactions between a variety of agents within a cluster are essential to its success. Despite being accepted by the literature, to our knowledge, this view has not yet been confirmed by analyses of large temporal networks of interactions within industrial clusters. The paper proposes to fill this gap and to show that network analysis can explain clusters success, failure, and transition from one phase of the life cycle to another. In this perspective, we build and study the innovation networks of three clusters over a 10-year period. We find that clusters’ growth is all but smooth and that low assortativity and preferential attachment among agents can constitute safeguards against clusters decline. These observations support contributions advocating for non-deterministic life cycles in which clusters can still grow, even after a period of pronounced decline.