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Knowledge Hubs in the German Urban System: Identifying Hubs by Combining Network and Territorial Perspectives

Wissensknoten im deutschen Städtesystem. Die Identifizierung von Knoten durch Kombination territorialer und Netzwerkperspektiven

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Raumforschung und Raumordnung

Abstract

This paper identifies hubs of knowledge-based labour in the German urban system from two perspectives: the importance of a metropolitan region as a place and the importance of a metropolitan region as an organisational node. This combination of a network perspective with a territorial perspective enables the identification of hubs. From the functional perspective, hubs are understood as important nodes of national and global networks, established by flows of people, goods, capital and information as well as by organisational and power relations. From the territorial perspective, hubs are understood as spatial clusters of organisations (firms, public authorities, non-governmental organisations). The functional focus of the paper lies on knowledge-based services. Based on data about employment and multi-branch advanced producer service firms, four main types of metropolitan regions are identified: growing knowledge hubs, stagnating knowledge hubs, stagnating knowledge regions and catch-up knowledge regions. The results show an affinity between knowledge-based work and bigger metropolitan regions as well as an east-west divide in the German urban system.

Zusammenfassung

Der Beitrag befasst sich mit Knoten wissensbasierter Arbeit im deutschen Städtesystem aus der Sicht zweier Perspektiven: zum einen wird die Bedeutung von Metropolräumen als Standort und zum anderen als Ankerpunkt für Netzwerke diskutiert. Die Kombination des räumlich-territorialen Fokus mit einer Netzwerkperspektive ermöglicht die Identifizierung von Knotenpunkten. Knoten werden im Rahmen dieses Beitrags als der Teil eines Netzwerkes verstanden, der zugleich einer spezifischen Region dient. Auf der Grundlage relativer Veränderungen werden unterschiedliche Entwicklungspfade von Knotenpunkten analysiert. Im Mittelpunkt der Analyse stehen wissensbasierte Dienstleistungen. Auf der Basis von Daten über Berufstätige und Mehrbetriebsdienstleistungsunternehmen werden vier metropolräumliche Typen identifiziert: Wissensknoten, stagnierende Knoten, schrumpfende Regionen und Start-up-Regionen. Die Ergebnisse zeigen eine Affinität wissensbasierter Tätigkeiten zu großen Metropolräumen sowie ein West-Ost-Gefälle im deutschen Städtesystem.

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Notes

  1. Self-employed persons are not included. Especially with regard to creative activities this statistical restriction might underestimate the number of KBP in Germany.

  2. The occupations that are aggregated as “knowledge-based professions”—the Kldb 88 BA code is shown in brackets: accountancy (753, 771, 772), advertising (703, 833, 834, 835, 837), architecture (603, 604, 623, 624), consulting (752), consultant engineers (611, 612, 626), data management (774), finance (691, 692), ICT-services (602, 622), insurance (693, 694), law (811, 812, 813, 814), management (751), media (821, 822), real estate (704).

  3. Firms from the following economic sectors are aggregated as “knowledge-based firms”—the WZ 93 code is shown in brackets: accountancy (74121, 74122, 74123, 74124, 74125), advertising (74401, 74402, 92113), architecture (74201, 74202, 74203, 74204, 74205, 74206, 74207, 74208, 74209), consulting (74131, 74132, 74141, 74142), consultant engineers (74301,74302, 74303, 74304), data management (72100, 72201, 72202, 72203, 72301, 72303, 72304, 72400, 72500, 72601, 72602), finance (65110, 65122, 65124, 65126, 65127, 65128, 65129, 65210, 65220, 65231, 65232, 65233, 67110, 67120, 67130), ICT-Services (64201, 64202, 64203, 64204, 64205, 64206, 64207), insurance (66011, 66020, 66031, 66032, 66033), law (74111, 74112, 74114, 74115), management (74151, 74152, 74155, 74156), media (22111, 22112, 22121, 22122, 22131, 22132, 22133, 22141, 22142, 22150, 92111, 92112, 92114, 92115, 92116, 92201, 92202, 92401), real estate (70111, 70112, 70113, 70121, 70122, 70201, 70202, 70310, 70320, 74153, 74154).

  4. As an example of the measurement procedure we think of two firms A and B with locations in Berlin, Frankfurt and München (firm A) and locations in Berlin and München (firm B). Headquarter of firm A is located in Berlin. Headquarter of firm B is located in München. The following city matrix exemplifies these data:

    Flows between headquarters and branches are counted 3 (= 3 ´ 1) and flows between branches are counted 1 (= 1 ´ 1). Connectivity values are calculated by summing up all potential flows for each city. Berlin, for example, shows two flows, each with a value of 3, in firm A and one flow, also with a value of 3, in firm B. The sum of Berlins’ flows is 9. This is the connectivity value of Berlin. In this example, the percentage connectivity value, used to calculate the CI values, of Berlin is 45% of the overall connectivity.

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  1. Fakultät Raumplanung, Technische Universität Dortmund, August-Schmidt-Straße 10, 44227, Dortmund, Deutschland

    Anna Growe &  Hans H. Blotevogel

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  1. Anna Growe
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  2. Hans H. Blotevogel
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Correspondence to Anna Growe.

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Growe, A., Blotevogel, H. Knowledge Hubs in the German Urban System: Identifying Hubs by Combining Network and Territorial Perspectives. Raumforsch Raumordn 69, 175–185 (2011). https://doi.org/10.1007/s13147-011-0087-1

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