- Cities within commuting distances have varying potentials to cooperate due to their functional differences
- Highest cooperation potentials can be observed in urban networks dominated by capital cities in the Eastern and Southern Europe
- Cooperation potentials in Western Europe seem to work particularly good when the main cities are highly specialised in financial services
Observations for policy
Cities within commuting distances have varying potentials to cooperate and complement each other based on their functional differences. With regard to this, cooperation potentials can be observed in urban networks dominated by capital cities in the Eastern and Southern Europe.
City cooperation and city network constitute an important territorial cooperation arrangement for EU regional policies. This is clearly the case within the framework of EU Structural Funds, but also the EU Green Paper on territorial cohesion and the Territorial Agenda 2020.
The underlying idea is that cities can enhance their critical mass and common competitiveness, sustainability and cohesion by exploring competitive advantages together. Forming polycentric cooperation networks and joining forces can lead to added value for the entire cooperation area (i.e. in economic, ecological, social and cultural terms).
Functional variation within potential urban networks is one way to illustrate complementarities or inertias of interest of intensifying city cooperation. High degree of functional differences (complementarity) can be observed in urban networks in the Eastern and Southern Europe countries, mainly in networks dominated by capital cities. This can be seen as a confirmation of the fact that functional differentiation between the large cities and their surroundings is particularly high in Eastern Europe.
Functional differences are also notable in networks of Western Europe, in particular where the one or more dominant cities are highly specialised in financial services.
Concepts and methods
To identify potentials of complementarities and thus of cooperation between cities, first potential urban networks have been defined and then their actual potential has been measured. This is highly experimental work, and at this stage not ready usable for policy conclusions. However, it is worth considering.
Using 90-minute isochrones from city centres with more than 250,000 inhabitants ‘regional’ urban networks were identified based on ‘regional’ or ‘province’ centres as not overlapping ‘service’ territories. Whenever possible, each of the urban areas included in a given network was then approximated by a NUTS3 in order to provide access to the relevant dataset.
Data is processed through a correspondence analysis, a technique which allows visualising (dis)similarities between data points, and offers a single, summary statistic describing the differentiation within a given group of points, the inertia. When inertia is low when economic structure of the cities in a given area is similar, it is high when the structures are very different from each other.