Modeling network dynamics: evidence from policy-driven innovation networks

Stochastic actor oriented models (SAOM) are of growing importance to study network dynamics focusing on the theoretical micro-mechanisms that induce the evolution of relations among a set of social actors. SAOM represent a suitable methodological framework to investigate the evolution of policy-driven innovation networks among heterogeneous actors. Drawing on a set of network policies implemented in the Italian region of Tuscany during the 2000s this paper investigates the time evolution of policy-driven innovation networks at regional level. Specifically we analyse how actors' relationships have evolved according to the following aspects: (i) propensity to collaborate with actors who are part of their existing network as opposed to experimentation of new relationships outside the group (trust/reputation effect); (ii) propensity to collaborate with actors sharing similar characteristics (homophily effect); (iii) propensity to collaborate with more popular actors, leading to the formation of a core of agents "controlling" the policy programme ("Matthew" effect).