Innovation flow through social networks: productivity distribution in France and Italy

T. Di Matteo (), T. Aste and Mauro Gallegati

The European Physical Journal B: Condensed Matter and Complex Systems, 2005, vol. 47, issue 3, 459-466

Abstract: From a detailed empirical analysis of the productivity of non financial firms across several countries and years we show that productivity follows a non-Gaussian distribution with `fat tails' in the large productivity region which are well mimicked by power law behaviors. We discuss how these empirical findings can be linked to a mechanism of exchanges in a social network where firms improve their productivity by direct innovation and/or by imitation of other firm's technological and organizational solutions. The type of network-connectivity determines how fast and how efficiently information can diffuse and how quickly innovation will permeate or behaviors will be imitated. From a model for innovation flow through a complex network we show that the expectation values of the productivity of each firm are proportional to its connectivity in the network of links between firms. The comparison with the empirical distributions in France and Italy reveals that in this model, such a network must be of a scale-free type with a power-law degree distribution in the large connectivity range. Copyright EDP Sciences/Società Italiana di Fisica/Springer-Verlag 2005

Date: 2005
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DOI: 10.1140/epjb/e2005-00332-y

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