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Regional effectiveness of innovation – leaders and followers of the EU NUTS 0 and NUTS 2 regions

Author

Listed:
  • Agata Zoltaszek

    (Faculty of Economics and Sociology, University of Lodz)

  • Alicja Olejnik

    (Faculty of Economics and Sociology, University of Lodz)

Abstract

Innovation constitutes an important factor for growth in all EU countries. Regions of the EU play a principle role in shaping new innovation trajectories and in bringing out the hidden potential for national growth. However, it is not only the level of innovation that diversifies regions, but also the innovative potential and the level of its realization. Therefore, the aim of this paper is to assess the realization of innovative potential, defined as effectiveness, in EU NUTS 0 and, if possible, NUTS 2 regions. To accomplish this goal a relative effectiveness method in used. The DEA (Data Envelopment Analysis) makes it possible to analyse the relative technical effectiveness based on regional inputs and outputs, without incorporating the legal and technological specifications of innovations, thus treating it like a production process. The inputs of the process are employment in technology and knowledge-intensive sectors and R&D expenditure, while the outputs include the number of patents and GDP. All variables are standardized by the size of the economically active population. DEA results divide regions in to two groups – effective, being the leaders; and ineffective, or followers. The DEA approach was combined and extended by ESDA (Exploratory Spatial Data Analysis) in order to pinpoint spatial patterns of innovation efficiency across NUTS 2 regions. Defining the best practices and implementing the learning-from-the-best policy is important in the process of regional development and specialization

Suggested Citation

  • Agata Zoltaszek & Alicja Olejnik, 2017. "Regional effectiveness of innovation – leaders and followers of the EU NUTS 0 and NUTS 2 regions," Lodz Economics Working Papers 8/2017, University of Lodz, Faculty of Economics and Sociology.
    • Handle: RePEc:ann:wpaper:8/2017
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    File URL: http://dspace.uni.lodz.pl:8080/xmlui/bitstream/handle/11089/21814/LEWP_8_2017.pdf?sequence=1&isAllowed=y
    File Function: First version, 2017
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    Citations

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    Cited by:

    1. Dorota Ciołek & Anna Golejewska, 2022. "Efficiency Determinants of Regional Innovation Systems in Polish Subregions," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 24-45.

    More about this item

    Keywords

    regional innovation; effectiveness; DEA (data envelopment analysis); regional development; spatial autocorrelation; ESDA (exploratory spatial data analysis);
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O11 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Macroeconomic Analyses of Economic Development

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