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@ARTICLE{Rhoden:903944,
      author       = {Rhoden, Imke and Weller, Daniel and Voit, Ann-Katrin},
      title        = {{S}patio-temporal dynamics of {E}uropean innovation - {A}n
                      exploratory approach via multivariate functional data
                      cluster analysis},
      journal      = {Ruhr economic papers},
      volume       = {12/2021},
      number       = {926},
      issn         = {1864-4872},
      address      = {Essen},
      publisher    = {RWI},
      reportid     = {FZJ-2021-05552},
      pages        = {24},
      year         = {2021},
      abstract     = {We apply a functional data approach for mixture model-based
                      multivariate innovation clustering toidentify different
                      regional innovation portfolios in Europe. Innovation
                      concentration is considered aspattern of specialization
                      among innovation types. We examine patent registration data
                      and combine themwith other innovation and economic data
                      across 225 regions, 13 years and 8 patent classes. This
                      allows usto identify innovation clusters that are supported
                      by several innovation- and economy-related variables.We are
                      able to form several regional clusters according to their
                      specific innovation types. The regionalinnovation cluster
                      solutions for IPC classes for ‘fixed constructions’ and
                      ‘mechanical engineering’ arevery comparable, and
                      relatively less comparable for ‘chemistry and
                      metallurgy’. The clusters for innovationsin ‘physics’
                      and ‘chemistry and metallurgy’ are similar; innovations
                      in ‘electricity’ and ‘physics’ showsimilar temporal
                      dynamics. For all other innovation types, the regional
                      clustering is different andinnovation concentrations in the
                      respective regions are unique within clusters. By taking
                      regional profiles,strengths and developments into account,
                      options for improved efficiency of location-based
                      regionalinnovation policy in order to promote tailored and
                      efficient innovation-promoting programs can be derived.},
      cin          = {IEK-STE},
      ddc          = {330},
      cid          = {I:(DE-Juel1)IEK-STE-20101013},
      pnm          = {1112 - Societally Feasible Transformation Pathways
                      (POF4-111)},
      pid          = {G:(DE-HGF)POF4-1112},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.4419/96973084},
      url          = {https://juser.fz-juelich.de/record/903944},
}