Innovation flow through social networks: productivity distribution in France and Italy
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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.author | Di Matteo, Tiziana | |
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dc.contributor.author | Aste, Tomaso | |
dc.contributor.author | Gallegati, M | |
dc.date.accessioned | 2015-12-13T22:51:45Z | |
dc.identifier.issn | 1434-6028 | |
dc.identifier.uri | http://hdl.handle.net/1885/81240 | |
dc.description.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. | |
dc.publisher | Springer | |
dc.source | European Physical Journal B | |
dc.subject | Keywords: Finance; Geographical regions; Industrial management; Numerical analysis; Innovation flow; Power law; Productivity distribution; Social networks; Productivity | |
dc.title | Innovation flow through social networks: productivity distribution in France and Italy | |
dc.type | Journal article | |
local.description.notes | Imported from ARIES | |
local.description.refereed | Yes | |
local.identifier.citationvolume | 47 | |
dc.date.issued | 2005 | |
local.identifier.absfor | 010301 - Numerical Analysis | |
local.identifier.ariespublication | MigratedxPub9578 | |
local.type.status | Published Version | |
local.contributor.affiliation | Di Matteo, Tiziana, College of Physical and Mathematical Sciences, ANU | |
local.contributor.affiliation | Aste, Tomaso, College of Physical and Mathematical Sciences, ANU | |
local.contributor.affiliation | Gallegati, M, Universita Politechnica delle Marche | |
local.description.embargo | 2037-12-31 | |
local.bibliographicCitation.startpage | 459 | |
local.bibliographicCitation.lastpage | 466 | |
local.identifier.doi | 10.1140/epjb/e2005-00332-y | |
dc.date.updated | 2015-12-11T10:47:08Z | |
local.identifier.scopusID | 2-s2.0-27644581938 | |
Collections | ANU Research Publications |
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01_Di Matteo_Innovation_flow_through_social_2005.pdf | 1.6 MB | Adobe PDF | Request a copy |
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