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Spatial Distribution of Eco-Innovation Performance: Evidence from European Countries

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  • Tomasz Kijek
  • Anna Matras-Bolibok

Abstract

Purpose: The aim of the paper is twofold. Firstly, it attempts to assess the spatial pattern of eco-innovation performance in European countries and to identify economies which are efficient in transforming eco-innovation inputs into outputs. Secondly, it endeavours to examine eco-innovation efficiency distribution and existence of spatial externalities across European countries. Design/Methodology/Approach: The sample consists of 21 European countries. We use two eco-innovations inputs and two eco-innovation outputs to measure eco-innovation performance. To calculate eco-innovation efficiency, we apply DEA method. In our research, mapping and Moran’s I are employed to find the spatial pattern of eco-innovation performance. Findings: The results show that high and medium-high eco-innovation inputs and eco-innovation outputs are mainly concentrated in countries in the Northern and West Central Europe, while low and medium-low eco-innovation inputs and eco-innovation outputs are performed in the East Central and Southern European countries. The findings confirm the presence of a negative spatial autocorrelation process in eco-innovation efficiency. Practical Implications: Identification of the eco-innovation distribution in the spatial scope is undoubtedly of high political importance, as it should enable to adjust policy actions aimed at improving eco-innovation efficiency to spatial characteristics of a given economy. Originality/Value: Since the issue of spatial characteristics of eco-innovation is still not sufficiently explored in the relevant literature, our paper attempts to fill a cognitive and methodological gap in the investigation of the spatial aspects of eco-innovation performance in the European countries.

Suggested Citation

  • Tomasz Kijek & Anna Matras-Bolibok, 2020. "Spatial Distribution of Eco-Innovation Performance: Evidence from European Countries," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 2), pages 766-778.
    • Handle: RePEc:ers:journl:v:xxiii:y:2020:i:special2:p:766-778
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    References listed on IDEAS

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    Cited by:

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    2. Biao Hu & Kai Yuan & Tingyun Niu & Liang Zhang & Yuqiong Guan, 2022. "Study on the Spatial and Temporal Evolution Patterns of Green Innovation Efficiency and Driving Factors in Three Major Urban Agglomerations in China—Based on the Perspective of Economic Geography," Sustainability, MDPI, vol. 14(15), pages 1-28, July.

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    More about this item

    Keywords

    Eco-innovation; efficiency; DEA; spatial externalities.;
    All these keywords.

    JEL classification:

    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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