The paper applies a relational perspective to patent data in order to investigate the characteristics of innovation flows within and across 103 Italian NUTS3 regions (province). In this way it is possible to use the CRENoS database on regional patenting—built on EPO data spanning from 1978 to 2003—to investigate the scientific and technological “relations” among “invention-creating ” and “invention-adopting ” territories. In particular, patents are used as relational data connecting inventors and applicants along a dual interpretation of a “knowledge production” and a “knowledge utilization” function. In addition a gravity model is used to identify frictions and attractions of the Italian innovation system. Analytical tools, such as social network analysis, spatial econometrics and negative binomial estimation procedures, are used to map and measure the structure and the evolution of a series of innovation subsystems, both at territorial level (i.e. province) and at the industry level (i.e. five specific industries, chosen according to the Pavitt’s taxonomy, Footwear, Textiles, Machinery, Personal Computers and Chemicals).

Treating patents as relational data: Knowledge transfers and spillovers across Italian provinces

USAI, STEFANO;
2011-01-01

Abstract

The paper applies a relational perspective to patent data in order to investigate the characteristics of innovation flows within and across 103 Italian NUTS3 regions (province). In this way it is possible to use the CRENoS database on regional patenting—built on EPO data spanning from 1978 to 2003—to investigate the scientific and technological “relations” among “invention-creating ” and “invention-adopting ” territories. In particular, patents are used as relational data connecting inventors and applicants along a dual interpretation of a “knowledge production” and a “knowledge utilization” function. In addition a gravity model is used to identify frictions and attractions of the Italian innovation system. Analytical tools, such as social network analysis, spatial econometrics and negative binomial estimation procedures, are used to map and measure the structure and the evolution of a series of innovation subsystems, both at territorial level (i.e. province) and at the industry level (i.e. five specific industries, chosen according to the Pavitt’s taxonomy, Footwear, Textiles, Machinery, Personal Computers and Chemicals).
2011
Italy; Network analysis; Patents; Regional innovation system; Relational data; Spatial econometrics
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/28197
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