Competition between cities and regions in Europe. Can smart spatial planning interact with gravitational site location models for external investment?

However smart a city or a region might be, a wide range of companies (eg in retail and services) use a gravitational model for site location for new investments. If the primary choice model is a gravitational one, being smart will only matter for site location within a region. From a spatial planning point of view, the right question is ‘can we influence gravitational site location choice while applying intelligent and consistent long term planning?’. First we implement a multi-scalar gravitational analysis of the EU-28 area, allowing to define a gravitational central area. We use the population density dataset (inhabitants per hectare calculated from Corine Land Cover 2006) provided by the European Environmental Agency and Joint Research Center. Spatial statistics allow us to define areas that have significantly more inhabitants and are thus ‘gravitational centers’. By applying different influence ranges, we get four different perceptions of centrality. With an influence distance of 100km we see the european core area, while on the opposite end a 10km distance gives us a wide range of central places for services of proximity. This provides every city or region with insight in the way the gravitational choice model influences investment in regions. For spatial planning, it is almost impossible to influence this with traditional planning instruments. Competition between regions and states on the European level is mostly defined by national (tax) policy and cultural differences. In a second part, we take a closer look at the regional level. For an equal area around (1) Brussels, (2) Milano-Venezia, and (3) Wien-Bratislava we apply the same spatial statistics calculations with different influence zones. The analysis on a regional level shows clear differences in regional development and in the position of cities within the region. For the Flemish region we confront the pattern of central areas with the statistical analysis of the actual location of firms