PropertyValue
?:abstract
  • The explanation of different levels of innovation and their spatial distribution represents the central focus of the analysis. Theempirical literature documents the incidence of spatial autocorrelation in patenting activities and interprets them as evidence forknowledge spillovers. Alternatively, the authors propose the spatial pattern of input variables in innovation processes as drivingforces of patenting autocorrelation. They analyze 51 Nuts 1 regions in Europe and find that the high degree of spatial autocorrelationexhibited by patent applications can be explained comprehensively by the spatial location of the input factors in the knowledgeproduction function. These are traditional indicators on R&D investments and human capital from Eurostat and proxy variables onsocial capital from the European Values Study. This finding has important implications for the scope of an autonomous regionalinnovation policy (xsd:string)
?:author
?:comment
  • (EVS) (xsd:string)
?:dataSource
  • EVS-Bibliography (xsd:string)
?:dateModified
  • 2008 (xsd:gyear)
?:datePublished
  • 2008 (xsd:gyear)
?:duplicate
?:fromPage
  • 861 (xsd:string)
is ?:hasPart of
?:isPartOf
is ?:mainEntity of
?:name
  • Regional knowledge spillovers: Fact or artifact (xsd:string)
?:publicationType
  • article (xsd:string)
?:sourceInfo
  • Bibsonomy (xsd:string)
  • In Research Policy, 37, 861-874, 2008 (xsd:string)
?:studyGroup
  • European Values Study (EVS) (xsd:string)
?:tags
  • 2008 (xsd:string)
  • EVS (xsd:string)
  • EVS_input2014 (xsd:string)
  • EVS_pro (xsd:string)
  • Economic_geography (xsd:string)
  • FDZ_IUP (xsd:string)
  • Innovation (xsd:string)
  • Knowledge_spillovers (xsd:string)
  • SCOPUSindexed (xsd:string)
  • SSCIindexed (xsd:string)
  • article (xsd:string)
  • checked (xsd:string)
  • english (xsd:string)
  • indexproved (xsd:string)
  • input2014 (xsd:string)
  • reviewed (xsd:string)
  • social_capital (xsd:string)
?:toPage
  • 874 (xsd:string)
rdf:type
?:volumeNumber
  • 37 (xsd:string)