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@ARTICLE{Rhoden:904980,
      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      = {Journal of open innovation},
      volume       = {8},
      number       = {1},
      issn         = {2199-8531},
      address      = {Basel},
      publisher    = {MDPI},
      reportid     = {FZJ-2022-00291},
      pages        = {6 -},
      year         = {2022},
      abstract     = {We apply a functional data approach for mixture model-based
                      multivariate innovation clustering to identify different
                      regional innovation portfolios in Europe, considering
                      patterns of specialization among innovation types. We
                      combine patent registration data and other innovation and
                      economic data across 225 regions, 13 years, and eight patent
                      classes. The approach allows us to form several regional
                      clusters according to their specific innovation types and
                      captures spatio-temporal dynamics too subtle for most other
                      clustering methods. Consistent with the literature on
                      innovation systems, our analysis supports the value of
                      regionalized clusters that can benefit from flexible policy
                      support to strengthen regions as well as innovation in a
                      systematic context, adding technology specificity as a new
                      criterion to consider. The regional innovation cluster
                      solutions for IPC classes for ‘fixed constructions’ and
                      ‘mechanical engineering’ are highly comparable but
                      relatively less comparable for ‘chemistry and
                      metallurgy’. The clusters for innovations in ‘physics’
                      and ‘chemistry and metallurgy’ are similar; innovations
                      in ‘electricity’ and ‘physics’ show similar temporal
                      dynamics. For all other innovation types, the regional
                      clustering is different. By taking regional profiles,
                      strengths, and developments into account, options for
                      improved efficiency of location-based regional innovation
                      policy to promote tailored and efficient
                      innovation-promoting programs can be derived.},
      cin          = {IEK-STE},
      ddc          = {650},
      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          = {10.3390/joitmc8010006},
      url          = {https://juser.fz-juelich.de/record/904980},
}