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Exploring creative clusters using micro-geographic data


  • Stefan Rehak
  • Martin Chovanec



The paper focuses on the analysis of spatial clusters of creative industries in Slovakia using micro-geographic data. The notion of spatial clustering of creative industries is deeply embedded in the literature, showing that firms in creative industries tend to cluster mostly in large cities or directly in city centres. Recent improvements in geo-coded firm datasets resulted in re-discovery of sets of analytic techniques for identification of clusters based on distance metric. These techniques overcome the problems related with borders and scales. The paper starts with the theoretical background of creative industries, which are usually defined as a range of economic activities have their origin in individual creativity, skill and talent which have a potential for job and wealth creation through the generation and exploitation of intellectual property (DCMS 2001). Later we present main arguments of spatial concentration of firms in creative industries and methodology for identifying clusters. In our analysis we analyse 46 434 firms from the INFOSTAT registry (2010), which were geo-coded by their address. We use Nearest Neighbour Analysis and Ripley K to test the spatial concentration of firms and Nearest Neighbour Hierarchical Spatial Clustering to find clusters of creative firms. Clusters of creative industries are rather small in size and very dense. The Ripley L index was between 6.64 and 12.55 km, which indicate the urban type clusters. Our analysis showed that 44.4 % of firms are clustered in totally 86 clusters. Most of the firms in creative industries are concentrated in Bratislava and Kosice, which are two largest cities in Slovakia. Even that the micro-geographic locational analysis has still some limitation, this paper explores new promising ways of testing the spatial concentration of firms. Keywords: clusters, creative industries, micro-geographic data, Slovakia JEL Classification: R00, R12

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  • Stefan Rehak & Martin Chovanec, 2012. "Exploring creative clusters using micro-geographic data," ERSA conference papers ersa12p562, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa12p562

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    References listed on IDEAS

    1. Rafael Boix Domenech & Luciana Lazzeretti & José Luis Hervàs Oliver & Blanca De Miguel Molina & Borja Trujillo Ruiz, 2011. "Creative clusters in Europe: a microdata approach," ERSA conference papers ersa11p471, European Regional Science Association.
    2. Bastian Lange & Ares Kalandides & Birgit Stober & H. A. Mieg, 2008. "Berlin's Creative Industries: Governing Creativity?," Industry and Innovation, Taylor & Francis Journals, vol. 15(5), pages 531-548.
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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