Spatial concentration of economic activity and competitiveness of Central European regions

Abstract

Abstract:The paper tackles with a still somewhat underdeveloped aspect of regional competiveness which regards to spillover effects stemming from spatial proximity of highly competitive neighbors. Although spillover effects are well recognized in the literature, we focus more on inter-regional concentration of business activity when enterprises are located in a particular district which is not far from the agglomeration center but not the center itself. We check for statistical significance of spatial autocorrelation measures (local Moran's Ii statistic) in order to identify spillovers between districts in Central European countries (Germany, Poland, Czech Republic and Slovakia). We use variables indicating Knowledge Intensive Services (KIS), in particular hi-tech KIS and information and communication services (including computer science). We compare 2009 with 2015 to notice agglomeration dynamics. We observe statistically significant spillover effects in Central European countries in urbanization-type clusters as well as strengthening of the effect over time. Taking into consideration more detailed data for Poland we conclude that while hi-tech KIS mostly spill over to neighboring districts, the reverse pattern may be observed for computer science (programming and consultancy). One explanation is that this subsector relies on highly demanded workforce and a prestigious localization (in the agglomeration centers) works as a bargaining chip to attract programmers. In order to measure the spillover effects more precisely it is recommended to define and measure the neighborhood of agglomeration centers using localization of firms based on GPS coordinates instead of centroids (geometric means) of districts -as shown in example of Poland.

Spatial Variation in Tourism and Investment Potential in the Context of Sustainable Development—A Case Study of Staszowski County

“…In addition, spatial analyses can be used to define centrographic measures and autocorrelations between features [29,31]. Thus, they provide knowledge on locations that are more and less attractive in terms of tourism, which can be very useful in tourism planning [32,33].…”

Spatial Imbalance Between Tourist Supply and Demand: The Identification of Spatial Clusters in Extremadura, Spain

“…This interdependence between regions has been analysed under the agglomeration economies approach [10][11][12], which is based on the premise that the concentration or spatial proximity of economic activities can be beneficial due to externalities of the agglomeration for the whole economy as well as for the sectors and companies grouped in a particular location, highlighting the improvement of productivity, investments, labor market, knowledge transfer, among other aspects [13]. In this line, the works carried out by Majewska [14,15] and Majewska & Trusklolaski [16], which, based on this premise, analyse the geograhics spillovers of tourism activity in Poland and countries of central Europe, identifying the existence of different hot spots that represent essential knowledge for proper planning of these destinations.…”

Spatial Intensity in Tourism Accommodation: Modelling Differences in Trends for Several Types through Poisson Models

“…From the initial studies of Wall et al [20], the amount of research pursuing this purpose as well as diversifying the techniques used for this purpose has intensified. Therefore, without wishing to be exhaustive, the work of Majewska [3,4] and of Majewska and Trukolaski [47] focusing on the analysis of the pattern of tourist activity in Poland and other countries in central Europe could be highlighted, identifying different clusters that represent important outputs for tourism management in these territories.…”