Learning and Structural Properties in Small Firms’ Networks: A Computational Agent-Based Model

vol.1 (27), no 1 Th is paper explores how structural properties of small fi rms ’ networks emerge from the ways fi rms exchange knowledge. In particular we are interested in analysing if and under which conditions the need for knowledge exchange within a set of co-located small fi rms is able to generate a more or less stable structure of links among fi rms. We focus on a specifi c kind of small fi rms ’ networks called Industrial Districts (IDs). One of the peculiar characteristics of IDs is fl exible specialization: small fi rms specialize in given phases of the production processes and join up production chains in a fl exible and dynamic way depending on market opportunities. Consequently, knowledge exchange is mainly related to the matching of complementary know-how and competencies. To explore the relationship between the exchange of complementary knowledge assets and network structure we developed a computational model of an ID. Th e results obtained through computer simulations of the model show that the exchange of complementary knowledge assets is able to generate stable networks and that, even with diff erent conditions, such networks evolve toward a hub and spoke confi guration with a few fi rm