Skip navigation
Skip navigation

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

Di Matteo, Tiziana; Aste, Tomaso; Gallegati, M

Description

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...[Show more]

dc.contributor.authorDi Matteo, Tiziana
dc.contributor.authorAste, Tomaso
dc.contributor.authorGallegati, M
dc.date.accessioned2015-12-13T22:51:45Z
dc.identifier.issn1434-6028
dc.identifier.urihttp://hdl.handle.net/1885/81240
dc.description.abstractFrom 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.
dc.publisherSpringer
dc.sourceEuropean Physical Journal B
dc.subjectKeywords: Finance; Geographical regions; Industrial management; Numerical analysis; Innovation flow; Power law; Productivity distribution; Social networks; Productivity
dc.titleInnovation flow through social networks: productivity distribution in France and Italy
dc.typeJournal article
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.citationvolume47
dc.date.issued2005
local.identifier.absfor010301 - Numerical Analysis
local.identifier.ariespublicationMigratedxPub9578
local.type.statusPublished Version
local.contributor.affiliationDi Matteo, Tiziana, College of Physical and Mathematical Sciences, ANU
local.contributor.affiliationAste, Tomaso, College of Physical and Mathematical Sciences, ANU
local.contributor.affiliationGallegati, M, Universita Politechnica delle Marche
local.description.embargo2037-12-31
local.bibliographicCitation.startpage459
local.bibliographicCitation.lastpage466
local.identifier.doi10.1140/epjb/e2005-00332-y
dc.date.updated2015-12-11T10:47:08Z
local.identifier.scopusID2-s2.0-27644581938
CollectionsANU Research Publications

Download

File Description SizeFormat Image
01_Di Matteo_Innovation_flow_through_social_2005.pdf1.6 MBAdobe PDF    Request a copy


Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  19 May 2020/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator