London and Paris In the networks of multinational firms
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1 Canterbury London and Paris In the networks of multinational firms Prof. Céline Rozenblat Institute of Geography - University of Lausanne Switzerland ESPON FOCI project Future orientation of European Cities Leader: ULB Brussels => UN Habitat annual Report DATAR project Comparizon of European Cities Leader: Paris-Est
2 Plan Comparison London ó Paris In the main system of World Cities Weigh Position Specialization Articulation of different networks Dimensions: 1. Network of multinational firms Ownership system 2. Geographical 3. Territorial 4. Activity specialisation 5. synthesis: Multi-dimensional 2
3 Space of Places and Space of Flows (M.Castells, 1996) 3
4 Space of Places and Space of Flows (M.Castells, 1996) Crossing Overlapping Intertwinning CITY: - Density of networks - Diversity of networks - Capacities to networks emergence 4 URBAN SYSTEMS: - Channeled networks - Diversity of resources - Capacities to networks emergence
5 Database The Survey * : First World Enterprises (Turnover) (=> groups) Source: Bureau Van Dijk (Paris - Brussels) *1 million subsidiaries Informations: Financial links Functions Locations by URBAN AREA Activities NACE 4 numbers * Turnover - employees 5
6 Building networks Spatial projection of networks 6
7 Individual firms networks to cities networks Nestlé Danone Kraft food Canterbury Peugeot Toyota Fiat London and Paris In the networks of multinational firms Prof. Céline Rozenblat Institute of Geography - University of Lausanne Switzerland ESPON FOCI project Future orientation of European Cities Leader: ULB Brussels => UN Habitat annual Report DATAR project Comparizon of European Cities Leader: Paris-Est Sources: Orbis, 2007
8 Position of cities in the multinational firms networks => Agregation of ties (owner-subsidiaries) 8
9 Position of cities in the multinational firms networks => Agregation of ties (owner-subsidiaries) 9
10 Distribution of links of subsidiaries according to distance between cities 10
11 Distribution of links of subsidiaries according to distance between cities (Europe) 11
12 Continental organization 12
13 13
14 14
15 15
16 Continental organization Evolution first World Groups networks INTER-CONTINENTAL URBAN LINKS 23% => 20% INTRA-CONTINENTAL URBAN LINKS 77% => 80% 16
17 Continental organization Evolution first World Groups networks INTER-CONTINENTAL URBAN LINKS 23% => 20% INTRA-NATIONAL URBAN LINKS 59% => 66% INTRA-CONTINENTAL URBAN LINKS 77% => 80% 17
18 Continental organization Evolution first World Groups networks «The local is not only a product of the global but that global itself is produced in local places» D. Massey, World City, 2007, p.107 INTRA-URBAN LINKS (29% => 25% ) INTER-CONTINENTAL URBAN LINKS 23% => 20% INTRA-NATIONAL URBAN LINKS 59% => 66% INTRA-CONTINENTAL URBAN LINKS 77% => 80% C. Rozenblat, «Opening the Black box of Agglomeration economies»,urban Studies, 47 (13), Nov
19 Position of cities in the networks of multinational firms 19
20 Position of cities in the networks of multinational firms 20
21 Position of cities in the networks of multinational firms 21
22 Position of cities in the networks of multinational firms 22
23 Parts of Paris and London in their national urban systems for the networks of multinational firms 23
24 24
25 25
26 Other Continent Inter-continental intermediaries Ron Burt, social capital of «bridges» (1992, 2005) Continent *"$, 1. Gatekeeper 2. Representative 3. Plateform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
27 1 Multi-dimensions / Multi-levels 2 Processes 3 Discussion and perspectives Other country Intra-European intermediaries Europe Country 27
28 Cities networks by activity sectors (NACE letters) Construction Public administration Health Art - Entertainment Social work Education Water Supply Extraction Mining Accommodation Food serv. IC Finance - Insurances Administration Wholesale trade Agriculture Real Estate Industry Energy supply Research 28
29 29
30 30
31 31
32 32
33 => What happens when activities and groups strategies become a part of spatial networks? (Space + institutions) Gary Gereffi, 1996: The Global value chain : 33
34 Multi-dimensional approach of cities networks new technologies can simultaneously shape and be shaped by the social networks into which they are introduced..it makes more sense to begin to treat technologies as endogenous to network relations rather than exogenous to them. In other words, instead of asking how technologies might change networks (or vice versa), perhaps the more appropriate question for our times is, What happens when a new technology becomes a part of a social network? Monge, Contractor, Leonardi, Int. Journ. Of Communication,
35 Multidimensional network of cities => 1 million links of Groups => 100 activities (NACE) => cities 35
36 C.Rozenblat, 2010: Multidimensional network of cities => 1 million links of MNF => 100 activities (NACE) => cities 36
37 Hierarchical clustering: - Strength method: local densities => Proximities between Cities/activities/groups 37
38 Conclusion Comparison London ó Paris Main common characteristics: Both central in the World city system with NYC Embedded in Europe Huge weight in their own national systems Main differences : Local networks in London (+ and -) London: Financial centre, Paris: Wholesale trade London bridge from US investments Future perspectives for both cities: In the context of the economic crisis : Both cities embedded in Europe: very vulnerable London local system and Bridge from US: even more vulnerable But Olympic games in London in
39 CITADYNE - CITies And DYnamics of NEtworks BLOG Celine.rozenblat@unil.ch Thanks for your attention 39
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