Global Urban Analysis : A Survey of Cities in Globalization 9781849775410, 9781849712132

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Global Urban Analysis

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Global Urban Analysis A Survey of Cities in Globalization Edited by

Peter J. Taylor, Pengfei Ni, Ben Derudder, Michael Hoyler, Jin Huang and Frank Witlox

First published by Earthscan in the UK and USA in 2011 For a full list of publications please contact: Earthscan 2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN 711 Third Avenue, New York, NY 10017

Earthscan is an imprint of the Taylor & Francis Group, an informa business Copyright © Peter J. Taylor, Pengfei Ni, Ben Derudder, Michael Hoyler, Jin Huang and Frank Witlox 2011. Published by Taylor & Francis. All rights reserved. No part of this book may be reprinted or reproduced or utilised in any form or by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying and recording, or in any information storage or retrieval system, without permission in writing from the publishers. Notices Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe.

ISBN 978-1-84971-213-2 (hbk) Typeset by FiSH Books, Enfield Cover design by Yvonne Booth A catalogue record for this book is available from the British Library Library of Congress Cataloging-in-Publication Data Global urban analysis: a survey of cities in globalization / edited by Peter J. Taylor ... [et al.]. p. cm. Includes bibliographical references and index. ISBN 978-1-84971-213-2 (hbk.) 1. Urban economics. 2. Cities and towns. 3. Globalization--Economic aspects. I. Taylor, Peter J. (Peter James), 1944HT321.G553 2010 330.9173'2--dc22 2010027612

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Contents List of Figures and Tables

ix

List of Contributors

xvii

List of Acronyms and Abbreviations

xxii

Preface

xxv

1

Introduction: The GUCP/GaWC Project Peter J. Taylor, Pengfei Ni and Ben Derudder

1

PART A — GLOBAL-SCALE ANALYSES 2

Command and Control Centres in the World Economy Peter J. Taylor, Pengfei Ni, Ben Derudder, Michael Hoyler, Jin Huang, Kathy Pain, Frank Witlox, Xiaolan Yang, David Bassens and Wei Shen

17

3

Advanced Producer Service Centres in the World Economy Peter J. Taylor

22

4

Media Centres in the World Economy Allan Watson and Michael Hoyler

40

5

The Global City Process Score Pengfei Ni, Peter J. Taylor and Ben Derudder

48

PART B — WORLD–REGIONAL CONNECTIVITY ANALYSES Introduction Peter J. Taylor

59

6

Australasian Cities in Globalization Oli Mould

63

7

Pacific Asian Cities in Globalization Pengfei Ni and Xiaolan Yang

71

8

Eurasian Cities in Globalization Pengfei Ni, Guangquan Li, Kai Liu and Jin Huang

85

9

South Asian Cities in Globalization Rolee Aranya, Pengfei Ni, Zixu Cheng and Jin Huang

93

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GLOBAL URBAN ANALYSIS

10

Middle East/North African Cities in Globalization David Bassens, Ben Derudder and Frank Witlox

102

11

European Cities in Globalization Peter J. Taylor, Ben Derudder, Michael Hoyler, Kathy Pain and Frank Witlox

114

12

Sub-Saharan Cities in Globalization Ronald S. Wall

137

13

Northern American Cities in Globalization Asli Ceylan Oner

148

14

Latin American Cities in Globalization Francisco Castañeda, Jon Cloke and Ed Brown

170

Global Synthesis: Regional Geography of Global Servicing Peter J. Taylor

187

PART C — KEY COUNTRY AND SUB-REGIONAL CONNECTIVITY PROFILES Introduction Peter J. Taylor

197

15

Australian Cities Oli Mould

201

16

Chinese Cities Pengfei Ni, Xiaoyan Yue and Jin Huang

205

17

Japanese Cities Pengfei Ni, Qingbin Li and Jin Huang

212

18

Indian Cities Rolee Aranya, Pengfei Ni, Yu Zhang and Jin Huang

218

19

German Cities Michael Hoyler

224

20

French Cities Kathy Pain and Gilles Ardinat

231

21

Swiss Cities Alain Thierstein and Stefan Lüthi

236

22

Italian Cities Gilda Catalano

241

23

UK Cities Peter J. Taylor

245

24

Canadian Cities Kathy Pain and Barry E. Prentice

251

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CONTENTS

vii

25

US Cities Asli Ceylan Oner

256

26

Mexican Cities Margarita Pérez Negrete

267

27

Brazilian Cities Eliana C. Rossi

272

28

South East Asian Cities Pengfei Ni, Guangyao Xu and Jin Huang

278

29

Arabian Gulf Cities David Bassens, Ben Derudder and Frank Witlox

284

30

European Post-Soviet Cities Olga Gritsai, Pengfei Ni, Herman van der Wusten, Kai Liu, Guangquan Li and Jin Huang

288

31

Eastern European Cities Marek Ban´czyk

293

32

Nordic Cities Brita Hermelin

300

33

Benelux Cities David Bassens, Ben Derudder and Frank Witlox

306

34

Iberian Cities Simón Sánchez Moral

312

35

Southern African Cities Ronald S. Wall

318

36

Central American Cities Ed Brown, Francisco Castañeda, Jon Cloke and José Luis Rocha Gómez

324

Global Synthesis: National and Sub-Regional Contrasts Peter J. Taylor

331

Postscript: Trends and Change Ben Derudder, Michael Hoyler, Peter J. Taylor and Frank Witlox

337

Appendix A: Lists of Firms and Cities Firms listed in the Forbes Global 2000 (2006)

351

All 200 firms in the network analyses

396

All 525 cities in the network analyses

400

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GLOBAL URBAN ANALYSIS

Appendix B: Technical Appendix Data collection: manual for data collectors

412

Data transformation: network connectivity and hinterworld calculation

424

Index

427

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List of Figures and Tables Figures 2.1 2.2 5.1 5.2 PS.1 PS.2 PS.3 PS.4 PS.5 AB.1 AB.2 AB.3 AB.4 AB.5 AB.6 AB.7 AB.8 AB.9 AB.10 AB.11 AB.12 AB.13 AB.14 AB.15 AB.16 AB.17 AB.18 AB.19 AB.20 AB.21

Financial Command Index Business Command Index Constitution of the ‘Globalizing Cities Index’ (GCI) City Place Power/City Network Power differential Absolute connectivity change in 2000–2008 Relative connectivity change in 2000–2008 Changes in level of Tier 1 capital (2007–2008) Pre-tax profits/losses (2008) Performance of command and control centres in finance in the context of the financial crisis Website Ernst & Young Office locator on Deloitte website Deloitte: ‘global office’, New York Deloitte: ‘main London office’ Deloitte: main London office on Manchester page Deloitte: other London offices Deloitte: Canadian ‘national office’ in Toronto Deloitte: other Toronto offices Deloitte: Icelandic HQ office in Reykjavik Deloitte: Abidjan office with major extra-territorial function Deloitte: Tokyo offices Deloitte: Osaka offices Website Lehman Brothers Lehman Brothers: global and world-regional headquarters Lehman Brothers: offices in Europe and the Middle East Website Skadden Skadden: offices Skadden: New York office Skadden: Washington, DC office Skadden: London office Skadden: Vienna office

18 20 49 52 341 342 344 346 349 412 419 419 420 421 421 422 422 423 423 424 424 425 425 426 427 427 428 429 429 430

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Tables 2.1 2.2 3.1 3.2 3.3 3.4 3.5 3.6 3.7 4.1 4.2 5.1 5.2 5.3 6.1 6.2 6.3 6.4 6.5 6.6 6.7 7.1 7.2 7.3 7.4 7.5 7.6 7.7 8.1 8.2 8.3 8.4 8.5 8.6

Financial Command Index: the top 20 cities Business Command Index: the top 20 cities Overall network connectivity Financial network connectivity Law network connectivity Advertising network connectivity Accountancy network connectivity Management consultancy network connectivity Locational strategies of advanced producer services Media network connectivity Locational strategies of leading media firms City Place Power: the top 50 cities City Network Power: the top 50 cities Globalizing Cities Index: the top 100 cities Global network connectivity of Australasian cities Financial services network connectivity of Australasian cities Accountancy network connectivity of Australasian cities Advertising network connectivity of Australasian cities Legal services network connectivity of Australasian cities Management consultancy network connectivity of Australasian cities City hinterworlds (regional concentrations of connections) of Australasian cities Global network connectivity of Pacific Asian cities Financial services network connectivity of Pacific Asian cities Accountancy network connectivity of Pacific Asian cities Advertising network connectivity of Pacific Asian cities Legal services network connectivity of Pacific Asian cities Management consultancy network connectivity of Pacific Asian cities City hinterworlds (regional concentrations of connections) of Pacific Asian cities Global network connectivity of Eurasian cities Financial services network connectivity of Eurasian cities Accountancy network connectivity of Eurasian cities Advertising network connectivity of Eurasian cities Legal services network connectivity of Eurasian cities Management consultancy network connectivity of Eurasian cities

19 20 24 26 28 30 31 32 34 42 43 50 51 53 64 65 65 65 66 66 67 73 76 77 78 79 80 81 87 87 88 89 89 90

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LIST OF FIGURES AND TABLES

8.7 9.1 9.2 9.3 9.4 9.5 9.6 9.7 10.1 10.2 10.3 10.4 10.5 10.6 10.7 11.1 11.2 11.3 11.4 11.5 11.6 11.7 12.1 12.2 12.3 12.4 12.5 12.6 12.7 13.1 13.2

City hinterworlds (regional concentrations of connections) of Eurasian cities Global network connectivity of South Asian cities Financial services network connectivity of South Asian cities Accountancy network connectivity of South Asian cities Advertising network connectivity of South Asian cities Legal services network connectivity of South Asian cities Management consultancy network connectivity of South Asian cities City hinterworlds (regional concentrations of connections) of South Asian cities Global network connectivity of MENA cities Financial services network connectivity of MENA cities Accountancy network connectivity of MENA cities Advertising network connectivity of MENA cities Legal services network connectivity of MENA cities Management consultancy network connectivity of MENA cities City hinterworlds (regional concentrations of connections) of MENA cities Global network connectivity of European cities Financial services network connectivity of European cities Accountancy network connectivity of European cities Advertising network connectivity of European cities Legal services network connectivity of European cities Management consultancy network connectivity of European cities City hinterworlds (regional concentrations of connections) of European cities Global network connectivity of Sub-Saharan cities Financial services network connectivity of Sub-Saharan cities Accountancy network connectivity of Sub-Saharan cities Advertising network connectivity of Sub-Saharan cities Legal services network connectivity of Sub-Saharan cities Management consultancy network connectivity of Sub-Saharan cities City hinterworlds (regional concentrations of connections) of Sub-Saharan cities Global network connectivity of Northern American cities Financial services network connectivity of Northern American cities

xi

90 95 96 97 97 98 99 100 104 106 107 108 108 109 110 116 119 121 123 125 128 130 139 141 142 142 143 143 144 150 154

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13.3 13.4 13.5 13.6 13.7 14.1 14.2 14.3 14.4 14.5 14.6 14.7 B.1 B.2 B.3 B.4 B.5 B.6 B.7 B.8 15.1 15.2 15.3 15.4

16.1 16.2 16.3

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Accountancy network connectivity of Northern American cities Advertising network connectivity of Northern American cities Legal services network connectivity of Northern American cities Management consultancy network connectivity of Northern American cities City hinterworlds (regional concentrations of connections) of Northern American cities Global network connectivity of Latin American cities Financial services network connectivity of Latin American cities Accountancy network connectivity of Latin American cities Advertising network connectivity of Latin American cities Legal services network connectivity of Latin American cities Management consultancy network connectivity of Latin American cities City hinterworlds (regional concentrations of connections) of Latin American cities Regional integrations into the world city network via leading cities Financial services: regional integrations into the world city network Accountancy: regional integrations into the world city network Advertising: regional integrations into the world city network Legal services: regional integrations into the world city network Management consultancy: regional integrations into the world city network World regions: relative integrations into the world city network by service sectors Hinterworlds of leading cities by regions Global network connectivity of Australian cities Localism (relative concentration of connections within Australia) Traditional globalism through NYLON (relative concentration of connections to New York and London) New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) Global network connectivity of Chinese cities Localism (relative concentration of connections within China) Traditional globalism through NYLON (relative concentration of connections to New York and London)

156 157 159 162 163 171 175 176 178 180 181 182 188 188 189 189 190 190 191 193 202 202 203

204 207 208 209

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LIST OF FIGURES AND TABLES

16.4

17.1 17.2 17.3 17.4

18.1 18.2 18.3 18.4

19.1 19.2 19.3 19.4

20.1 20.2 20.3 20.4

21.1 21.2 21.3 21.4

22.1 22.2

xiii

New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) 210 Global network connectivity of Japanese cities 213 Localism (relative concentration of connections within Japan) 215 Traditional globalism through NYLON (relative concentration of connections to New York and London) 215 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) 216 Global network connectivity of Indian cities 220 Localism (relative concentration of connections within India) 221 Traditional globalism through NYLON (relative concentration of connections to New York and London) 222 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) 222 Global network connectivity of German cities 225 Localism (relative concentration of connections within Germany) 227 Traditional globalism through NYLON (relative concentration of connections to New York and London) 227 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) 228 Global network connectivity of French cities 232 Localism (relative concentration of connections within France) 233 Traditional globalism through NYLON (relative concentration of connections to New York and London) 233 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) 234 Global network connectivity of Swiss cities 237 Localism (relative concentration of connections within Switzerland) 238 Traditional globalism through NYLON (relative concentration of connections to New York and London) 239 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) 239 Global network connectivity of Italian cities 242 Localism (relative concentration of connections within Italy) 242

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22.3 22.4

23.1 23.2 23.3 23.4

24.1 24.2 24.3 24.4

25.1 25.2 25.3 25.4

26.1 26.2 26.3 26.4

27.1 27.2 27.3 27.4

28.1

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Traditional globalism through NYLON (relative concentration of connections to New York and London) New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) Global network connectivity of UK cities Localism (relative concentration of connections within the UK) Traditional globalism through NYLON (relative concentration of connections to New York and London) New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) Global network connectivity of Canadian cities Localism (relative concentration of connections within Canada) Traditional globalism through NYLON (relative concentration of connections to New York and London) New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) Global network connectivity of US cities Localism (relative concentration of connections within the US) Traditional globalism through NYLON (relative concentration of connections to New York and London) New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) Global network connectivity of Mexican cities Localism (relative concentration of connections within Mexico) Traditional globalism through NYLON (relative concentration of connections to New York and London) New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) Global network connectivity of Brazilian cities Localism (relative concentration of connections within Brazil) Traditional globalism through NYLON (relative concentration of connections to New York and London) New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) Global network connectivity of South East Asian cities

243

243 247 247 228

249 252 252 253

254 257 259 261

263 268 269 270

270 274 275 275

276 279

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LIST OF FIGURES AND TABLES

28.2 28.3 28.4

29.1 29.2 29.3 29.4

30.1 30.2 30.3 30.4

31.1 31.2 31.3 31.4

32.1 32.2 32.3 32.4

33.1 33.2

Localism (relative concentration of connections within South East Asia) Traditional globalism through NYLON (relative concentration of connections to New York and London) New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) Global network connectivity of Arabian Gulf cities Localism (relative concentration of connections within the Arabian Gulf) Traditional globalism through NYLON (relative concentration of connections to New York and London) New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) Global network connectivity of European post-Soviet cities Localism (relative concentration of connections within European post-Soviet cities) Traditional globalism through NYLON (relative concentration of connections to New York and London) New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) Global network connectivity of Eastern European cities Localism (relative concentration of connections within Eastern Europe–Baltic) Traditional globalism through NYLON (relative concentration of connections to New York and London) New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) Global network connectivity of Nordic cities Localism (relative concentration of connections within the Nordic region) Traditional globalism through NYLON (relative concentration of connections to New York and London) New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) Global network connectivity of Benelux cities Localism (relative concentration of connections within Benelux)

xv

281 281

282 285 286 286

287 290 291 292

292 294 296 296

297 301 303 303

304 307 308

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33.3 33.4

34.1 34.2 34.3 34.4

35.1 35.2 35.3 35.4

36.1 36.2 36.3 36.4

C.1 C.2 C.3 PS.1 PS.2 PS.3 PS.4 PS.5 PS.6 AB.1 AB.2

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Traditional globalism through NYLON (relative concentration of connections to New York and London) 309 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) 309 Global network connectivity of Iberian cities 314 Localism (relative concentration of connections within Iberia) 315 Traditional globalism through NYLON (relative concentration of connections to New York and London) 316 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) 316 Global network connectivity of Southern African cities 320 Localism (relative concentration of connections within Southern Africa) 321 Traditional globalism through NYLON (relative concentration of connections to New York and London) 322 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) 322 Global network connectivity of Central American cities 326 Localism (relative concentration of connections within Central America) 327 Traditional globalism through NYLON (relative concentration of connections to New York and London) 328 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) 328 Primacy: connectivity ratios for top two cities 332 Localism: the cities with the most ‘local’ links 334 Orientation: leading cities and the traditional and emerging core cities in the world city network 335 Sectoral distribution of GaWC data gatherings in 2000 and 2008 338 Twenty most connected cities in the world city network in 2000 and 2008 (adjusted GNC for 132 cities) 339 Major positive/negative values for relative connectivity change in 2000–2008 342 Largest changes in level of Tier 1 capital (2007–2008) 344 Largest pretax profits/losses (2008) 346 Performance of command and control centres in finance in the context of the financial crisis 348 Service value matrix (example) 425 Connectivity matrix (example) 425

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List of Contributors Rolee Aranya is an Associate Professor at the Department of Urban Design and Planning at the Norwegian University of Science and Technology, Trondheim. Her main areas of research are globalization and its impact on cities in the developing world and new forms of urban governance in response to globalization. Gilles Ardinat is a PhD Student at Paul Valéry University, Montpellier, France. Marek Ban´czyk, PhD, Poznan´ University of Economics in Poland, is a member of the Association for Cultural Economics International (ACEI) and has been consultant for several global projects on culture and creative industries (OECD, UNCTAD). He runs a private Institute for Competitive Economics of Regions (http://iker.org.pl) and participates in the Center for Metropolitan Research (Centrum Badan´ Metropolitalnych) at Adam Mickiewicz University (UAM) in Poznan´. David Bassens is Research Assistant at the Geography Department of Ghent University, Belgium, and a Research Fellow of the Globalization and World Cities (GaWC) Research Network. He holds masters degrees in Geography (Ghent University) and Social and Cultural Anthropology (KU Leuven). His PhD research is funded by the Research Foundation – Flanders (FWO). Ed Brown is Associate Director of the Sustainability Research School, and Senior Lecturer in Geography at Loughborough University, UK. His research interests include the political economy of neoliberal reforms in Central America; debates over water and energy poverty in the Global South; and critical geographies of corruption and illicit finance. Francisco Castañeda is a Lecturer in the Faculty of Economics and Business Administration at Universidad de Santiago de Chile (USACH), with research interests in economic development and industrial organization. Gilda Catalano teaches Urban Sociology at the University of Calabria (Rende, Italy), where her main research interests are concerned with rural–urban linkages within different spatial scales. Zixu Cheng is a Lecturer at Nanjing University, Nanjing, China, and a Research Fellow at the Global Urban Competitiveness Project (GUCP), Chinese Academy of Social Sciences (CASS). His research fields are macroeconomics and urban economics.

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Jonathan Cloke is a Lecturer in Human Geography at Loughborough University, UK, and Research Associate with the Globalization and World Cities (GaWC) Research Network. His research and consultancy covers a variety of urban themes, including financial services for the urban poor, and cities and gender. Ben Derudder is Lecturer in Human Geography at the Department of Geography, Ghent University, and Associate Director of the Globalization and World Cities (GaWC) Research Network. His research focuses on the conceptualization and empirical analysis of transnational urban networks; the (persisting) importance of business travel in the space economy; and spatial modelling techniques. He teaches courses on human geography, global city formation, and methods and techniques in geographical research. Olga Gritsai is an economic geographer at the Department of Geography, Planning and International Development Studies of the University of Amsterdam. She has published on the emergence of advanced producer services in Moscow and is currently coordinating the EU 6th Framework Accommodating Creative Knowledge (ACRE) project about the creative potential in 13 cities across Europe. Brita Hermelin is Associate Professor at the Department of Human Geography, Stockholm University. Her research work is primarily about the development of the service economy with a focus on the urban context for the service society. Michael Hoyler is Senior Lecturer in Human Geography at Loughborough University, UK, and Associate Director of the Globalization and World Cities (GaWC) Research Network. His main research interests are in urban economic and social geography with a focus on the transformation of European cities and metropolitan regions in contemporary globalization. Current research investigates city connectivities on the eve of the financial crisis, cities in economic expansion since 1500, and the emerging global geographies of higher education. Jin Huang is a Lecturer at Beijing University of Posts and Telecommunications, Beijing, China, and a Research Fellow at the Global Urban Competitiveness Project (GUCP), Chinese Academy of Social Sciences (CASS). His main research field is management science. Guangquan Li is a Lecturer at the College of Economics at Lanzhou University, Lanzhou, China, and a Research Fellow at the Global Urban Competitiveness Project (GUCP), Chinese Academy of Social Sciences (CASS). His main research field is regional economics.

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LIST OF CONTRIBUTORS

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Qingbin Li is a Lecturer in Economics at the Institute of Economics, Nankai University, Tianjin, China, and a Research Fellow at the Global Urban Competitiveness Project (GUCP), Chinese Academy of Social Sciences (CASS). His research fields are economic growth and development, income distribution, and urban and rural economies. Kai Liu studies international trade and the impact of transnational corporations on government policy at Zhongnan University of Economics and Law, Wuhan, China. In 2009, he was awarded two Sun Yefang Economic Science Foundation grants to support his research. Liu is also a Research Fellow at the Global Urban Competitiveness Project (GUCP), Chinese Academy of Social Sciences (CASS). Stefan Lüthi is an economic geographer and researcher at the Chair for Spatial and Territorial Development at the Technical University of Munich (TUM). Current research interests include the knowledge economy and its impact on megacity-region development, regional innovation systems and regional policy, as well as quantitative and qualitative methods of network analysis. Oli Mould is a Research Associate in the Globalization and World Cities (GaWC) Research Group at Loughborough University. He researches many aspects of the contemporary world city, including the cultural economy and urban subcultures, and conducted his PhD fieldwork on the film, television and media industries in Sydney. Pengfei Ni is Professor of Economics at the Institute of Finance and Trade Economics, Chinese Academy of Social Sciences (CASS). He is Secretary General of the Global Urban Competitiveness Project (GUCP), and Chief Editor of the Chinese Urban Competitiveness Report and the Global Urban Competitiveness Report. He specializes in theoretical and applied studies in urban economy, urban competitiveness and real estate, and received the Sun Yefang Economy Prize, the highest prize in Economics in China, in 2005. Asli Ceylan Oner is Assistant Professor in the School of Urban and Regional Planning at Florida Atlantic University. Her research interests include globalization, planning and governance of global cities, global urban networks, metropolitan decentralization, and comparative urbanization. Kathy Pain is an urban planner-geographer specializing in research on contemporary city–region transformations associated with economic globalization. She is ALDAR Professor of Real Estate Development at the University of Reading and Associate Director of Applied Studies at GaWC. Margarita Pérez Negrete is Professor of Urban Sociology and Anthropology at Universidad Iberoamericana, Mexico City. Barry E. Prentice is Professor of Supply Chain Management in the Transport Institute (where he was Director from 1996 to 2005) at the I.H. Asper School of Business, University of Manitoba, Winnipeg, Canada.

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José Luis Rocha Gómez is Senior Researcher at the Central American University (UCA) in Managua, Nicaragua and Associate Researcher with the Brooks World Poverty Institute at the University of Manchester, UK. His work focuses on issues relating to youth gangs, local government, disaster prevention and management, the coffee industry, and migration. He is a member of the editorial committees of the academic journals Envío and Encuentro, and is also the Research Coordinator of the Central American Jesuit Service for Migrants. Eliana C. Rossi is an Independent Researcher in Rio de Janeiro who has experience in the areas of Production Engineering and Geography, researching on advanced producer services, air transport and world cities. Simón Sánchez Moral is ‘Ramón y Cajal’ Researcher at the Department of Regional Geographic Analysis, Complutense University of Madrid. His research interests focus on regional–urban development models under globalization and on the knowledge-based economy. Wei Shen is an Assistant Professor at the École Supérieure des Science Commerciales d’Angers (ESSCA) Graduate School of Management in Angers, France. His main research interests include China’s global cities, international migration of students and elites, as well as transnationalism and transnational networks more generally. Peter J. Taylor is Professor of Geography and Environmental Management in the School of the Built and Natural Environment, Northumbria University, Newcastle, UK, and Director of the Globalization and World Cities (GaWC) Research Network. He is Emeritus Professor of Geography at Loughborough University, UK. A Fellow of the British Academy, he is author of over 300 publications of which 60 have been translated into one or more of 23 languages. Of his more than 20 books, his most recent are World City Network: A Global Urban Analysis (Routledge, 2004), Political Geography: World-Economy, Nation-State, Locality (Prentice Hall, 2006, 5th edition with Colin Flint) and Cities in Globalization: Practices, Policies and Theories (Routledge, 2007, edited with Ben Derudder, Pieter Saey and Frank Witlox). Alain Thierstein is an economist and Full Professor for Spatial and Territorial Development in the Faculty of Architecture at the Technical University of Munich (TUM). Current research interests include the impact of the knowledge economy on urban and megacity-region development, innovation and regional policy as well as policy evaluation. Ronald S. Wall is a South African economic geographer and urban planner in the Faculty of Applied Economics at Erasmus University Rotterdam. His work ranges from urban planning of African cities to global economic network analysis.

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LIST OF CONTRIBUTORS

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Allan Watson is a Lecturer in Human Geography at Staffordshire University, UK. He is an urban geographer with research interests in urban cultural geographies and global cities, centred on the cultural and creative economy. Frank Witlox is Professor of Economic Geography at the Geography Department of Ghent University and Associate Director of the Globalization and World Cities (GaWC) Research Network. He is also a visiting professor at the Institute of Transport and Maritime Management Antwerp (ITMMA). He holds a PhD in Urban Planning (Eindhoven University of Technology), a masters degree in Applied Economics and a masters degree in Maritime Sciences (both University of Antwerp). His research focuses on transport economics and geography, spatial modelling techniques, (city) logistics, world cities and globalization, and urban planning. Herman van der Wusten is Emeritus Professor of Political Geography at the University of Amsterdam. He has published on the political transformations in the eastern part of Europe since 1989 and currently writes on capital cities and political centres. Guangyao Xu is a Lecturer at the Institute of Economics, Shandong University, Jinan, China, and a Research Fellow at the Global Urban Competitiveness Project (GUCP), Chinese Academy of Social Sciences (CASS). His research fields are international trade and industrial economy. Xiaolan Yang is a Teaching Assistant in the Department of Geography and Resource Management, The Chinese University of Hong Kong. She is also a member of the Global Urban Competitiveness Project (GUCP), Chinese Academy of Social Sciences (CASS). Xiaoyan Yue is a Lecturer at Beijing Normal University, Beijing, China, and a Research Fellow at the Global Urban Competitiveness Project (GUCP), Chinese Academy of Social Sciences (CASS). Her main research field is regional planning. Yu Zhang is a Teaching Assistant at the Graduate School of the People’s Bank of China. She is also a member of the Global Urban Competitiveness Project (GUCP), Chinese Academy of Social Sciences (CASS).

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List of Acronyms and Abbreviations ACEI ACRE

Association for Cultural Economics International Accommodating Creative Knowledge – Competitiveness of European Metropolitan Regions within the Enlarged Union APS Advanced Producer Services ARE Swiss Federal Office for Spatial Development ARL Akademie für Raumforschung und Landesplanung ASEAN Association of Southeast Asian Nations ATM Automated Teller Machine BBR Bundesamt für Bauwesen und Raumordnung BCI Business Command Index BFI Business Fairs Index BHI Business Hotels Index BM&FBOVESPA Bolsa de Valores, Mercadorias e Futuros de São Paulo BRIC Brazil, Russia, India, China CAFTA Central American Free Trade Agreement CASS Chinese Academy of Social Sciences CBD Central Business District CIS Commonwealth of Independent States CNP City Network Power CPP City Place Power DATAR Délégation à l’Aménagement du Territoire et à l’Action Régionale DIACT Délégation Interministérielle à l’Aménagement et à la Compétitivité des Territoires DIFC Dubai International Financial Centre DR–CAFTA Dominican Republic – Central American Free Trade Agreement EAEC Eurasian Economic Community EBRD European Bank for Reconstruction and Development ECOWAS Economic Community of West African States EEA European Economic Area

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LIST OF ACRONYMS AND ABBREVIATIONS

EMR ESPON ESRC ESSCA EU EurAsEC FCI FDI FNC FTAA FWO GaWC GCI GDP GNC GNP GUAM GUCP HQ IFC IKER INSEE IT MEGA MENA Mercosur MNC MNC NAFTA NASSCOM NIDL NYLON NYSE OAU

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European Metropolitan Region European Observation Network for Territorial Development and Cohesion Economic and Social Research Council École Supérieure des Science Commerciales d’Angers European Union Eurasian Economic Community Financial Command Index Foreign Direct Investment Financial Network Connectivity Free Trade Area of the Americas Fonds Wetenschappelijk Onderzoek – Vlaanderen (Research Foundation – Flanders) Globalization and World Cities Globalizing Cities Index Gross Domestic Product Global Network Connectivity Gross National Product Organization for Democracy and Economic Development (Georgia, Ukraine, Azerbaijan, Moldova) Global Urban Competitiveness Project Headquarters International Financial Centre Instytut Konkurencyjnej Ekonomii Regionów, Poznan´ Institut National de la Statistique et des Études Économiques Information Technology Metropolitan European Growth Area Middle East and North Africa Mercado Común del Sur Media Network Connectivity Multinational Corporation North American Free Trade Agreement National Association of Software and Services Companies (India) New International Division of Labour New York–London New York Stock Exchange Organization of African Unity

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OECD OFC POLYNET R&D SAARC SADC SNC SOU STPI SWF TNC TUM UAE UAM UCA UN UNCTAD UNDP USACH USSR

Organisation for Economic Co-operation and Development Offshore Financial Centre Sustainable Management of European Polycentric Megacity Regions Research and Development South Asian Association for Regional Cooperation Southern African Development Community Service Network Connectivity Statens Offentliga Utredningar Software Technology Parks of India Sovereign Wealth Fund Transnational Corporation Technische Universität München United Arab Emirates Uniwersytet im. Adama Mickiewicza w Poznaniu Universidad Centroamericana United Nations United Nations Conference on Trade and Development United Nations Development Programme Universidad de Santiago de Chile Union of Soviet Socialist Republics

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Preface Global Urban Analysis is a unique book deriving directly from a remarkable research initiative. In 2007 the Global Urban Competitiveness Project (GUCP) at the Chinese Academy of Social Sciences (CASS, Beijing) and the Globalization and World Cities (GaWC) Research Network centred at Loughborough University (UK) agreed a memorandum of understanding for research collaboration. The first research project, in conjunction with GaWC scholars at Ghent University (Belgium), generated the results upon which this book is based. The memorandum recognized a strong research fit between GUCP and GaWC: the former in its global urban competitiveness research and the latter in its world city network research were both dedicated to producing new quantitative data for cities at a global scale. This synergy is important and is what makes this book unique. This book is constituted of myriad findings computed from customized data collected at a global scale for the project. Not many data have been collected on cities at a global scale and most of what is publicly available is demographic. Such data are important and have allowed urban researchers to trace the unprecedented growth of cities especially in poorer countries. This has generated a rich vein of studies on ‘megacities’, researching problems relating to city size and poverty. This is not the global urban analysis that we report here. We are not directly interested in the demographic sizes of cities; rather we focus on their worldwide economic functions. In this context urban areas are generally referred to as ‘world cities’ or ‘global cities’ and they are important for the way they are structuring the world economy under conditions of contemporary globalization. We consider cities as centres of business activities – housing corporate headquarters, hosting marketing fairs, providing services such as inter-jurisdictional law and global advertising, and, of course, being financial centres. Many megacities are also important world cities – Mexico City and Mumbai are examples – but we focus on just the economic functions of these urban areas alongside other world cities that are not megacities – Amsterdam and San Francisco are examples. It is because this book is about economic functions and not population sizes that we had to collect our own city data. This book is very empirical – there is a wealth of new data and results to be found throughout the chapters – but it is not, we insist, empiricist. There are numerous rankings of cities in the pages but they do not represent mere ‘list-mania’, mindless orderings with little or no theoretical underpinning. Our research is deeply embedded in the rich literature on world/global cities that has flowered in the last quarter century. We delineate command and control centres and measure city connectivities in world city networks, both of which

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are integral to understanding some of the more surprising features of economic globalization. In particular readers are invited to rethink the way the world economy works through our city-centric lenses. What we offer is a new ‘meta geography’; instead of viewing our world familiarly as a mosaic of states, we offer a different vision of the world as networks of cities. Global-scale research is a huge undertaking even for collaborating research centres. This is particularly the case when it comes to interpreting results. There is no way our two research units can have the knowledge capacity to properly explain, clarify, account for, elucidate and shed light upon the many findings covering all parts of the world – or at least the 525 cities that undergird most of our analyses. Thus we thank the many authors who responded to our invitation to help in interpreting our myriad findings. These include researchers associated with GUCP and the scholars in GaWC’s worldwide research network. It is patently obvious that without them this book could not have been produced and therefore the potential of our research initiative not realized. It should now be clear that a massive amount of effort has gone into producing this book and we hope it will be of interest to a wide range of readers: city politicians, policymakers and planners will be keen to see where their city fits into contemporary globalization and what they can do about it; practitioners in the private sector will find both our global overviews and detailed sectional findings useful for understanding and developing their approaches to contemporary globalization; and in education at all levels our results provide vast amounts of evidence for discussion of how and where pupils and students may well be living for much of their working lives. In addition, of course, we hope our fellow urban researchers will appreciate our still crude contributions to beginning the task of creating ‘urban economic studies’ geared to the challenges of the 21st century. And finally, we expect that many people without professional interest in cities but who are genuinely intrigued by this greatest of all human achievements, as expressed particularly in the cities they know, will find our large scope instructive in providing a context for making sense of contemporary cities in globalization. We began this preface claiming uniqueness for our project; at the very least this should make the resulting book intriguing. But we hope also that our excitement in producing new findings through viewing the world from our distinctive perspective will ring out from our text, tables and maps to encourage readers to think afresh about our world and where it is heading. Peter J. Taylor, Pengfei Ni, Ben Derudder, Michael Hoyler, Jin Huang and Frank Witlox Beijing, Ghent and Loughborough October, 2010

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Introduction: The GUCP/GaWC Project Peter J. Taylor, Pengfei Ni and Ben Derudder

This book presents the basic findings of a large, global research collaboration between the Global Urban Competitiveness Project (GUCP) at the Chinese Academy of Social Sciences (CASS), Beijing, and the Globalization and World Cities (GaWC) Research Network at Loughborough and Ghent Universities. The focus is on the relations between cities across the world and the result is the largest and most comprehensive study of world cities ever conducted. For instance, the global urban analyses reported below include investigation of the headquarter geography of 2000 leading firms plus estimations of intercity business connections between 525 cities. With more than 30 chapters detailing our empirical results, this book provides a unique insight into contemporary globalization through the cities within which it is organized and reproduced. Cities in globalization is a very big topic, and this book provides as comprehensive a picture of what is happening as is practically feasible in a truly global urban analysis. The joint project had two primary objectives. GUCP’s initial interest was to create a new ‘globalizing cities index’ to complement their existing research on the worldwide competitiveness of cities (Kresl and Ni, 2007). The goal was to produce results that would be conceptually and empirically an improvement on many new global rankings of cities being reported in the literature. GaWC’s initial interest was to develop and improve their existing research on the world city network (Taylor, 2004). The goal was not just to update this work, but also to put it onto a much sounder empirical foundation. After meetings and workshops in Loughborough and Beijing, the research turned into a very closely integrated work process. The key steps were as follows: 1 2 3

A Data Collection Manual was produced in Loughborough, extended in Ghent and translated in Beijing in late 2007. Data were collected in Beijing from January to May 2008. Data were checked in Ghent between June and September 2008, including numerous iterations to and from Loughborough and Beijing.

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Final datasets were produced ready for analysis in December 2008. Data analyses were carried out in the first half of 2009, and members of the worldwide GaWC research network and those at GUCP interpreted the findings to produce the chapters below in the second half of 2009.

Thus this has been an exceptionally fruitful research collaboration with researchers in Beijing, Loughborough and Ghent producing the findings and 38 scholars from across the world interpreting the results and writing them up as chapters for this book. This introduction to the project and book has three sections: 1 2 3

The research background to the project is outlined so that our results can be understood in the perspective of changing ideas on world/global cities. The specific designing of the new project is described to provide an introduction to the empirical content of the book. The organization of the book is presented to help the reader navigate what is quite a large, but carefully ordered volume.

Research Background There is a long tradition of identifying selected cities as ‘world cities’ because of their economic, political or cultural importance – Babylon, Athens, Rome, Baghdad, Paris, Hangzhou, Beijing, London, Vienna, Berlin, New York, Moscow, Tokyo and Los Angeles have all been identified as such for their ‘place and time in the sun’. The scholar who has done most to convert this general recognition of city ‘greatness’ into scholarly investigation is Peter Hall (1966, 1998). However, the specific sequence of research out of which this project has emerged, relates more to the economic changes in the world economy that have created contemporary globalization.

The discovery and identification of world/global cities In the 1970s there was a spatial restructuring of the world economy that came to be known as the New International Division of Labour (NIDL) (Fröbel et al, 1980). This involved numerous firms in the core of the world economy moving their industrial production to poorer regions to take advantage of the cheaper labour. This decentralization of production required a new centralization of control to coordinate and plan the new global production, initially recognized as new corporate centres (multinational firm headquarters) (Hymer, 1972) and international financial centres (global finance and banks) (Reed, 1981). Friedmann (1986) definitively defined a world city hierarchy wherein a limited number of major cities across the world were deemed to be ‘command and control centres’. The cities were differentiated by the scope of their command: New York and London were global but other cities, such as Madrid, Miami, Sydney and São Paulo, only had regional command areas.

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In a separate but equally influential writing, Sassen (1991) identified New York, London and Tokyo as global cities. These were the key examples of a limited number of a new type of city that had, according to Sassen, emerged to organize the new economic globalization. These global cities combined command and control functions with advanced producer services (financial, professional, creative) that enabled global capital to operate transnationally. For instance, global law firms specialized in inter-jurisdictional law contracts, global advertising agencies pioneered global marketing campaigns and global accountants diffused basic auditing standards to facilitate foreign direct investment. Her ideas were taken up by Castells (1996) for his network society thesis based upon global spaces of flows: relations between major cities constituted his prime example of a global-scale network. Between them, Friedmann, Sassen and Castells provided the conceptual framework for a world cities literature that dominated much of urban studies in the 1990s (Knox and Taylor, 1996; Brenner and Keil, 2006).

Initial limitations Three important limitations of this new literature were soon identified: an empirical deficit, restricted coverage and conceptual confusion. Short and his colleagues (1996) referred to there being ‘a dirty little secret’ in the world cities literature. They argued that the literature’s bold ideas were not supported by adequate empirical evidence. This was largely because at the scale of analysis required to study world cities there was actually very little publicly available information beyond basic demographics. Thus the majority of data employed for understanding world cities actually related to countries rather than the cities themselves (Taylor, 1999). To solve this problem required new customized data collection on world cities. A related problem concerned the focus in the literature on a limited number of major cities. As we have seen, Sassen’s global cities were illustrated using just three cities. Friedmann’s hierarchy added a few more, but understanding cities in globalization through just a dozen or so examples also seemed problematic. Robinson (2002) has been the critic of this lack of coverage; she refers to large swathes of urban dwellers being removed from the world map (e.g. in Africa). This problem can be partly traced back to the dearth of data but it is also importantly related to how world/global cities are conceptualized. The conceptual confusion may have already been recognized by the use of both ‘world cities’ and ‘global cities’ in the discussion so far. Many scholars have used the two terms interchangeably but this is not what Sassen intended: her global cities are defined to be much rarer than Friedmann’s world cities, for which there could be many levels of hierarchy. But there has been a reaction against the restriction of research to just the most important cities. Inclusive approaches have emerged that have used two related concepts: globalizing cities (Marcuse and van Kempen, 2000) and cities in globalization (Taylor et

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al, 2007). Both concepts treat the coverage problem but they do not advance far in terms of conceptual clarification. In one survey, Taylor and Lang (2004) were able to list 50 different ways that cities in globalization were described. Derudder (2008) provides a comprehensive discussion of the variety of approaches in the world city literature. The quantitative research programme at GaWC was specifically developed to try and overcome the three limitations described above.

Specifying the world city network Drawing on Sassen’s emphasis on advanced producer services and Castells’ insistence on networks, a world city network has been formally specified (Taylor, 2001). The purpose is to cut through the conceptual confusion by precisely specifying the model, and to enable its operationalization through feasible data collection on reasonably large numbers of cities. The world city network is structured as an interlocking network. Such networks are triple-layered: as well as the net-level and node-level found in all networks, there is an additional sub-nodal level. In this case the net-level is the space of flows in the world economy, the nodal level is the cities, and the subnodal level is the advanced producer service firms. It is the latter that ‘interlock’ the cities to produce the network. Note, therefore, that the agents in this model, the network-makers, are not the cities per se, but rather the firms operating through the cities. In contemporary globalization these firms typically operate through multi-city office networks. In this way they can service their business clients across the world and maintain their brand integrity. If they were to pass a client on to another firm for servicing in a city where they had no office, they lose quality control of the service and therefore, possibly, the client. Thus through the 1990s and into the new century, most large advanced producer service firms spread their office network across the world economy. It is these office networks that form the basis of the world city network: in effect we treat the latter as an amalgam of all the office networks servicing global capital. Where is the space of flows in this model? There are no easily available data on intercity flows through offices and therefore there cannot be a simple direct measurement of such flows. Instead we have to use our model to generate indirect measurement of flows, which we will call potential working flows. We focus on potential intra-firm flows; information and knowledge linking offices within a firm in the routine work of project development and execution (e.g. designing and launching an advertising campaign). The basic assumption we make is that the larger and more important an office is, the more flows of information and knowledge it will generate. Therefore, the flows between two cities both housing major offices of a firm will be much larger than flows between two cities both having minor offices of the firm. On the basis of this assumption, the model can estimate potential working flows between all pairs of cities in a firm’s office network. Aggregating all these

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estimates for all firms provides an indirect measure of total flows between every pair of cities. Adding up an individual city’s potential working flows with every other city provides an estimate of the network connectivity of that city. This is an indicator of the degree of integration of a given city into the world city network. To operationalize this model requires data on the offices of advanced producer service firms. This information is relatively easy to find. Large service firms tend to flaunt their ‘globality’ on their websites because this is what they are trying to sell to new clients. In addition, they use their globality to recruit a new cohort of professional operatives every year with a promise of global experience and learning. Thus we can use information on these websites to categorize the importance of their offices. Because all websites are different we use a common codification of offices scoring 0–5 as follows: • • • • • •

0 indicates no presence (office) in a city. 1 indicates a very minor office. 2 is a typical office of the firm. 3 is reserved for particularly large offices of the firm. 4 indicates an office with extra-city responsibilities (e.g. a regional office). 5 is scored for the city housing the firm’s headquarters.

These scores are termed the service values and measure how important a city is to a firm’s network. A service values matrix is constructed as an array of cities against firms. For instance, in the initial use of this model in 2000, 100 firms were surveyed across 315 cities, thus creating a 100  315 matrix of service values (i.e. 31,500 pieces of information as 0s, 1s, 2s, 3s, 4s and 5s). Network connectivities of cities can be computed from this matrix and they feature prominently in the results reported below.

Second limitations The UK’s Economic and Social Research Council (ESRC) funded GaWC to measure the world city network in 2000 and to repeat the exercise in 2004. When making 2000–2004 comparisons two limitations to our new methodology came to light. Basically, the nature of our choice of firms came to be seen as inadequate. The first problem was that our initial choice of firms had been largely pragmatic. We chose six sectors – accountancy, advertising, banking/finance, insurance, law and management consultancy – and selected firms that had offices in 15 or more cities with at least one office in each of the prime ‘globalization arenas’, northern America, western Europe and Pacific Asia. We called these ‘global service firms’. The pragmatic part was to favour firms with the better websites (in 2000 some websites were rather less useful). When we came to repeat the exercise in 2004 we found that 20 of the original 100 firms no longer existed (takeovers, bankruptcies, etc.) so that analysis had to be based

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upon just 80 firms. This level of erosion surprised us: it was clear that we could not continue to use the initial roster of firms in any later data collection because further wastage would be likely to bring the number of firms to too low a level. Our methodology relies on aggregation and therefore its adequacy depends on sheer number of firms to iron out the particular idiosyncrasies of individual firms. Lowering the number of firms severely limits global urban analysis. Second, the original data collection in any case had variable numbers of firms in different sectors, ranging from 23 for banking/finance to only 11 for insurance. This severely limited analysis at the sector level; as a rule of thumb, analysis using fewer than 20 firms is suspect and yet only banking/finance met this threshold. In short, a larger and more systematic selection of firms is required. This is now possible given the ubiquitous improvement in the quality and quantity of information on today’s websites compared to 2000. Thus we can dispose of our earlier pragmatism in selecting firms and make a more considered selection based upon attributes than can be easily replicated at later times. That is to say we need to set criteria for inclusion in such a way that repeating the exercise will not result in erosion of numbers of firms. The solution is to abandon the search for ‘global service firms’ and to focus on large service firms. In this way, the roster of firms can be derived by selecting a given number of the top ranked firms in each sector. Such a criterion can be used in future years to keep the same overall number of firms, while specific firms leave or enter the roster depending on their ranking in their sector. A larger and more systematic selection of firms requires much more work, hence the need to collaborate with GUCP to make this a truly global-level project. This also provided the opportunity to add new GUCP interests, specifically the command and control function, to GaWC’s initial network agenda.

Design of the New GUCP/GaWC Project The project was designed at two meetings/workshops in Loughborough and Beijing and centred on the preparation of the Manual for Data Collectors, partly reproduced in Appendix B. Two types of data were identified for collection. First, some attribute data on the importance of the cities as business centres for decision-making, or control and command centres. Second, service values data to generate relational data using the interlocking network model. Before the data collection started we used part of one workshop to define an initial roster of cities. We decided to extend the original 315 used in earlier studies and also to leave the list open to enable further cities to be added from the headquarters data (see below).

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Data for measuring control and command centres There were four data collection exercises: 1

2

3

4

Headquarter data were collected from the Forbes Global 2000 firms and the rankings of firms noted. Cities not in our initial city list but housing a Forbes Global 2000 firm headquarters were added to the list to produce a final roster of 525 cities. This data collection produced an array of 525 cities with headquarters (and their ranks) allocated to cities. Business hotel data were collected for the top 25 (in numbers of rooms) of Hotel Chains and Consortia listed in www.hotelsmag.com. Using their websites, the first task was to filter out ‘non-business’ hotels: economy, extended stay and resort hotels. Numbers of business hotels for each of our 525 cities were recorded for all chains/consortia. For business events, we used www.tssn.com, which has a database of over 15,000 shows, exhibitions, public events and conferences. These were totalled for each of our 525 cities. We collected data on science parks from the website of the International Association of Science Parks (www.iasp.ws) and although this covered parks in 74 countries, we decided, after looking at the results, that this did not provide comprehensive global coverage of the subject and therefore these data were subsequently dropped from the analyses.

The result of this data collection was three columns of data showing headquarters, business hotels and business events across the 525 cities.

Data for measuring the world city network At the workshops it was decided to collect data on 75 financial services firms (combining banking/finance and insurance from previous analyses), and 25 firms each from accountancy, advertising, law and management consultancy. In each case we would choose by size or importance (i.e. top 75 and top 25). In addition we decided to collect data on the top 25 media firms to compare a different type of networked sector with advanced producer services. Thus there were six data collection exercises in all: 1

2 3

4

We selected the top 75 ranked firms in the Forbes Global 2000 occurring in any of three categories: Banking, Insurance and Diversified Finance. Using firms’ websites, a 525  75 matrix of financial service values was created. We selected the top 25 accountancy firms/groups ranked by revenue. Using firms’ websites, a 525  25 matrix of accountancy service values was created. We selected the top 25 advertising agencies by revenue as listed by Advertising Age. Using firms’ websites, a 525  25 matrix of advertising service values was created. We selected the top 25 firms from Chambers List of Corporate Law Firms. Using firms’ websites, a 525  25 matrix of legal service values was created.

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We selected the top 25 management consultancy firms from the definitive list of ‘prestige’ derived from a large survey of professionals. Using firms’ websites, a 525  25 matrix of consultancy service values was created. We selected the top 25 media firms from Forbes Global 2000 (but omitted five advertising firms so listed since they are found elsewhere in the analysis). Using firms’ websites, a 525  25 matrix of media work values was created.

These data are used to compute general network connectivities (for all 175 service firms) and specific sector network connectivities.

Outline of the Book There are three sections to the book, organized by geographical scale.

Part A: Global-scale analysis This consists of four chapters that describe different analyses at the global scale. In Chapter 2 the results from the headquarters data of the Forbes Global 2000 are described as a geography of control and command. Chapter 3 focuses on the world city network and uses the 175 services firms to show the top ranked cities in terms of general network connectivity and for the different service sectors. The spatial structure of this servicing is also described using a factor analysis approach. Chapter 4 replicates Chapter 3’s methodologies but uses the data for the 25 media firms. Finally, in Chapter 5, these results are combined to produce a global city process score, a general assessment of cities in terms of their importance as business places (headquarters, hotels and events) and in business flows (city connectivities). The other two parts of the book focus just on the service values matrix. This is by far the largest dataset – the 525  175 matrix includes 91,875 pieces of information – which makes it feasible to disaggregate not just by sector but also geographically at scales below the global.

Part B: World–regional connectivity analyses For these analyses the world is divided into nine business activity regions. The regional framework is comprehensive (all cities are included) and is designed to reflect general business contexts in which firms operate. Defining criteria include culture, history and development level; these are regions for which some firms designate ‘regional headquarters’. There has been no attempt to make the regions comparable in size. The regions identified are as follows: • •

Australasia (largely Australia and New Zealand). Pacific Asia (from Thailand to Japan, now dominated by China). We sometimes identify this region as one of the three main ‘globalization arenas’.

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ranks two and three, followed a little further behind by Paris. These are the ‘big four’ cities identified in Chapter 2. From this point on the most notable feature is the importance of US cities spread across the whole table: four more in the top ten (Chicago, Houston, Los Angeles and Washington); five in the next ten; four in the next ten, five in the next ten; and another five in the final ten ranks. In other words a whisker under a half of City Place Power in Table 5.1 is in the US. This contrasts with Europe’s 12 cities (half the US total) and Pacific Asia featuring only eight cities (a third of the US total). This leaves just six cities for the rest of the world: three in Canada, two in Australia plus São Paulo being the sole representative of the old ‘poor’ ‘third world’ at the lowly rank of 46th. Clearly this power measure starkly picks up the rich–poor divisions of the world: overwhelmingly City Place Power is concentrated in leading cities of the rich world. Table 5.2 City Network Power: the top 50 cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

New York London Hong Kong Paris Tokyo Singapore Shanghai Beijing Milan Sydney Madrid Seoul Moscow Toronto Mumbai Taipei Brussels Chicago Kuala Lumpur Bangkok São Paulo Buenos Aires Amsterdam Zurich Mexico City

CNP 100.00 95.55 81.37 75.46 73.51 72.45 68.16 66.40 65.97 65.33 63.37 62.98 59.88 59.06 56.38 55.87 55.74 54.13 53.17 52.72 51.47 51.22 50.29 50.14 49.48

RANK

CITY

26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43= 43= 45 46 47 48 49 50

Frankfurt Dublin Warsaw Jakarta Los Angeles Istanbul Stockholm Washington Lisbon Rome Prague Athens Dubai San Francisco Manila Santiago Caracas Budapest Melbourne Atlanta Vienna Geneva Auckland Johannesburg Luxembourg

CNP 47.97 47.92 47.72 47.38 46.04 45.62 43.44 42.95 42.04 40.79 40.66 40.14 40.08 39.73 39.42 39.01 38.30 37.70 37.70 36.72 36.60 36.44 35.89 34.98 34.23

In Table 5.2, it is all change. Although New York ranks first, all other US cities fare far less well. Only five other US cities are in this table, all relatively lowly

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Five countries from Europe: Germany, France, Switzerland, Italy and the UK. Two countries from northern America: Canada and the US. Two countries from Latin America: Mexico and Brazil.

These are all medium and large city-rich states. The above countries miss out several city-rich subregions that are potentially just as interesting as the individual states. Nine such subregions have been identified: • • • •

•

•

• • •

South East Asia (from Thailand to the Philippines): interesting for its mixture of large resources and important cities. The Arabian Gulf (from Oman to Kuwait): one of the major world city growth areas. Ex-Soviet Europe (excluding the Baltic states): experienced a particular globalizing experience under Russian dominance. Eastern Europe (formerly part of the Soviet bloc): had a smoother transition than ex-Soviet states, typically consisting of early privatization of state assets followed by joining the European Union. Nordic countries (from Iceland to Finland): traditionally follow distinctive political economy paths and this has continued to a degree during globalization. Benelux countries (Belgium, the Netherlands and Luxembourg): at the core of the European Union and, like Nordic countries, rich and distinctive. Iberian countries (Spain and Portugal): late entrants to and major beneficiaries of the European Union. Southern Africa (South Africa and its neighbours): focusing on South Africa, the continent’s one potential global growth region. Central America (from Panama to Guatemala): a collection of small states, intriguing for its lack of world cities and its traditional dependence on Miami.

In these more detailed analyses, there are four sets of findings that authors interpret and discuss for each country or subregion: 1 2

3

General network connectivities, as in Part B, but for additional lessconnected cities at this lower scale. Localism, aggregating connections to other cities in the country or subregion; this is a more geographically detailed measure of localism than that measured in Part B. There is a new measure of total connectivity to London and New York (NYLON) for each city; we call this ‘traditional globalization’ since NYLON has always been the central city dyad of contemporary global-

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ization. There is a second new measure of total connectivity to Beijing, Hong Kong and Shanghai; we call this ‘new, emerging globalization’ since these Chinese cities are the fastest rising cities in the world city network – they may become the central city triad of future globalization.

The latter two measures are obviously presented for comparison; for the moment NYLON scores continue to dominate but these measures may become very interesting in future projects if the world economy shifts decisively from west to east. Further information on the data and analysis is provided in a short introduction to the section. As for Part B, the authors interpret the findings for their country or subregion in the light of its history, culture and recent development record. Part C concludes with a ‘global synthesis’ in which country and subregional comparisons are made to show how the different areas fit together in a single world economy.

Other text and materials In order to make this volume as useful as possible for readers across the world, we supplement the findings above with additional material: further text that places the 2008 results in the context of a changing world city network, plus supplementary materials upon which all the findings are based. The project generates cross-sectional data for cities in globalization in the first half of 2008. We provide a Postscript, entitled ‘Trends and Change’, which adds two new elements to the interpretation and discussion: •

•

We compare 2008 with the first world city network data collection in 2000. This shows the trends in city connectivities – which cities are becoming relatively more integrated into the world city network and which less so. The 2008 data were collected just before the financial credit crunch and subsequent economic downturn. It will be some years before the full effects of this economic restructuring are recorded in the world city network and for control and command centres. However, we can begin to glimpse changes, especially in the financial sector, and we report some preliminary findings on the different fates of control and command centres in finance.

These change results provide an opportune way to conclude the interpretation and discussion of cities in globalization in 2008. We provide a comprehensive Appendix. The purpose is to be as transparent as possible so as to ensure all readers can understand our project and its results. The following are included: •

Lists of firms and cities. Three lists are supplied: (1) all firms in the Forbes Global 2000; (2) all 200 firms in the network analyses; (3) all 525 cities in

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the network analyses. Technical appendix. This provides the details for how the data were collected (taken from the Manual for Data Collectors) and the formal specification of the interlocking network model, including the equations for computing city connectivities and hinterworlds.

Concluding Note As far as GUCP is concerned this volume is an extension of a large publishing venture; it complements the series of Global Urban Competitiveness Reports (www.gucp.org/en). For GaWC this is easily the largest publishing venture thus far. Much of the research reported here represents the culmination of a quantitative strand of work that is now over a decade old (www.lboro.ac.uk/gawc). We would never have guessed at the outset that we would have got this far and produced a truly ‘global urban analysis’ on this scale. We have always treated this quantitative research as essentially descriptive: globalization is generating a massively changing world and our job has been to try and keep pace by producing new geographies of what is a global network society. This book is that geography.

References Brenner, N. and Keil, R. (eds) (2006) The Global Cities Reader, Routledge, London Castells, M. (1996) The Rise of the Network Society, Blackwell, Oxford Derudder, B. (2008) ‘Mapping global urban networks: a decade of empirical world cities research’, Geography Compass, vol 2, pp559–574 Friedmann, J. (1986) ‘The world city hypothesis’, Development and Change, vol 17, pp69–83 Fröbel, F., Heinrichs, J. and Kreye, O. (1980) The New International Division of Labour, Cambridge University Press, Cambridge Hall, P. (1966) The World Cities, McGraw-Hill, New York, NY Hall, P. (1998) Cities in Civilization, Weidenfeld and Nicolson, London Hymer, S. (1972) ‘The multinational corporation and the law of uneven development’, in J. N. Bhagwati (ed.) Economics and World Order: from the 1970s to the 1990s. Collier-Macmillan, London, pp113–140 Knox, P. L. and Taylor, P. J. (eds) (1996) World Cities in a World-System, Cambridge University Press, Cambridge Kresl, P. K. and Ni, P. (eds) (2007) Global Competitiveness Report (2005–2006), Social Sciences Academic Press, Beijing Marcuse, P. and van Kempen, R. (eds) (2000) Globalizing Cities: A New Spatial Order?, Blackwell, Oxford Reed, H. C. (1981) The Pre-eminence of International Financial Centers, Praeger, New York, NY Robinson, J. (2002) ‘Global and world cities: a view from off the map’, International

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Journal of Urban and Regional Research, vol 26, pp531–554 Sassen, S. (1991) The Global City: New York, London, Tokyo, Princeton University Press, Princeton, NJ Short, J. R., Kim, Y., Kuus, M., and Wells, H. (1996) ‘The dirty little secret of world city research’, International Journal of Urban and Regional Research, vol 20, pp 697–717 Taylor, P. J. (1999) ‘So-called “world cities”: the evidential structure within a literature’, Environment and Planning A, vol 31, pp1901–1904 Taylor, P. J. (2001) ‘Specification of the world city network’, Geographical Analysis, vol 33, pp181–194 Taylor, P. J. (2004) World City Network: A Global Urban Analysis, Routledge, London Taylor, P. J., Derudder, B., Saey, P. and Witlox, F. (eds) (2007) Cities in Globalization: Practices, Policies and Theories, Routledge, London Taylor, P. J. and Lang, R. E. (2004) ‘The shock of the new: 100 concepts describing recent urban change’, Environment and Planning A, vol 36, pp951–958

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PART A

GLOBAL-SCALE ANALYSES

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2

Command and Control Centres in the World Economy Peter J. Taylor, Pengfei Ni, Ben Derudder, Michael Hoyler, Jin Huang, Kathy Pain, Frank Witlox, Xiaolan Yang, David Bassens and Wei Shen

In this chapter we focus on the command and control functions of cities as indicated by the headquarter locations of major firms. As described in Chapter 1, these functions were integral to Friedmann’s (1986) early work and were also a key part of Sassen’s (1991) global city concept. More recently they have been analysed in detail by Godfrey and Zhou (1999) and Alderson and Beckfield (2004). We report analyses of headquarter locations for both the leading 75 financial services firms (banks and insurance) and for the largest 2000 firms (from all sectors) as defined by the Forbes Global 2000.

Command and Control Centres in Financial Services We describe the geography of the headquarters of the 75 financial service firms in our data. The measurement of a city’s importance as a command and control centre is based upon the rankings of their financial firms by the Forbes composite index, a measure that adds together rankings for sales, profits, assets and market value. We compute a Financial Command Index (FCI) for each city as follows: • • • • • • •

Top five firm headquarters score 10 for the city they are located in. Headquarters of firms ranked 6–10 score 8. Headquarters of firms ranked 11–20 score 6. Headquarters of firms ranked 21–30 score 5. Headquarters of firms ranked 31–40 score 4. Headquarters of firms ranked 41–55 score 3. Headquarters of firms ranked 56–75 score 2.

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We sum these scores for each city and the index is then computed as percentages of the city with the highest sum; the results of this simple analysis are shown in Figure 2.1. The key finding is that this command function is highly concentrated: only 35 cities have headquarters and all but six are in North America and Europe. While New York is clearly the dominant city, it is Western Europe that stands out as the most dominant world region for command and control centres in financial services.

Figure 2.1 Financial Command Index.

The top 20 cities in terms of their FCI are listed in Table 2.1. Here we see the specific degree of New York’s dominance with only London having more than half of New York’s FCI. Tokyo’s lowly sixth ranking is a surprise; presumably this represents the relative decline of Tokyo’s banks since 1990. The other surprise is finding Charlotte and Edinburgh in the top ten; however neither is likely to retain this pre-eminence due to the more recent upheavals (see Derudder et al, 2010 and Postscript below): Charlotte has lost Wachovia as an independent bank and Edinburgh’s HBOS and Royal Bank of Scotland are Britain’s two largest bank losers. Outside the top ten, the high global ranking of Brussels (11th) and Washington, DC (13th) are also unexpected since neither political world city is internationally renowned for its banks. Again both cities’ financial headquarter status will be adjusted downwards consequent upon the demise of Fortis in Belgium and the downsizing of Freddie Mac and Fanny Mae with nationalization.

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Table 2.1 Financial Command Index: the top 20 cities. RANK

CITY

1 2 3 4 5 6 7 8 9= 9=

New York London Zurich Paris Toronto Tokyo Charlotte Edinburgh Amsterdam Beijing

FCI 100.00 60.71 37.50 35.71 30.36 28.57 26.79 25.00 23.21 23.21

RANK

CITY

11 12 13 14 15= 15= 15= 15= 15= 20

Brussels Munich Washington Basel Frankfurt Minneapolis Omaha San Francisco St Petersburg Melbourne

FCI 23.21 19.64 17.86 14.29 10.71 10.71 10.71 10.71 10.71 8.93

Command and Control Centres Across all Sectors A Business Command Index (BCI) has been calculated using the top 2000 firms in the world (again using the Forbes composite index). The BCI is computed for each city as follows: • • • • • • • • • • • •

Each city with a top 50 firm headquarters scores 12. Cities with headquarters of firms ranked 51–100 score 11. Cities with headquarters of firms ranked 101–200 score 10. Cities with headquarters of firms ranked 201–300 score 9. Cities with headquarters of firms ranked 301–400 score 8. Cities with headquarters of firms ranked 401–500 score 7. Cities with headquarters of firms ranked 501–600 score 6. Cities with headquarters of firms ranked 601–700 score 5. Cities with headquarters of firms ranked 701–800 score 4. Cities with headquarters of firms ranked 801–1200 score 3. Cities with headquarters of firms ranked 1201–1600 score 2. Cities with headquarters of firms ranked 1601–2000 score 1.

These values are summed for each city and the city’s BCI is then expressed as a percentage of the highest city sum. The findings of this research are shown in Figure 2.2. Because there are many more firms studied, the distribution of command and control is more worldwide than for financial services in Figure 2.1. However, the main globalization arenas – North America and Europe plus Pacific Asia (Japan in particular) – can now be seen as very important. But it is not broad regions that dominate this figure; it is the overwhelming importance of just four cities.

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Figure 2.2 Business Command Index.

These four cities are shown in Table 2.2. Tokyo is the leading command and control centre for business in general followed by New York, London and Paris with the latter having more than double the BCI of Houston, the next ranked city. Unlike the top four, Houston is a more specialized business centre – the world’s oil and gas control and command centre. The US, Japan and China have the most multiple entries in this table; the remainder are leading cities of medium-sized national economies where firms as ‘national champions’ qualify for the Forbes 2000. Table 2.2 Business Command Index: the top 20 cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10

Tokyo New York London Paris Houston Seoul Chicago Osaka Beijing Madrid

BCI 100.00 70.94 68.49 53.96 25.47 23.31 21.44 20.00 19.42 19.14

RANK

CITY

11 12 13 14 15 16 17 18 19 20

Stockholm Los Angeles Toronto San Jose (CA) Washington Hong Kong Sydney Dallas Taipei Melbourne

BCI 18.71 18.13 17.84 17.70 16.40 16.26 12.81 12.66 11.65 11.37

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Conclusion This chapter has illustrated the concentration of headquarter functions within the world economy. The geography of command and control in the world economy is extremely uneven, both regionally – in North America, Western Europe and Pacific Asia – and, within these regions, in just a few ‘global cities’.

Note This chapter is broadly based on Taylor et al (2009).

References Alderson, A. S. and Beckfield, J. (2004) ‘Power and position in the world city system’, American Journal of Sociology, vol 109, pp811–851 Derudder, B., Hoyler, M. and Taylor, P. J. (2010) ‘Goodbye Reykjavik: International banking centres and the global financial crisis’, Area, doi:10.1111/j.1475–4762.2010.00968.x Friedmann, J. (1986) ‘The world city hypothesis’, Development and Change, vol 17, pp69–83 Godfrey, B. J. and Zhou, Y. (1999) ‘Ranking world cities: multinational corporations and the global urban hierarchy’, Urban Geography, vol 20, pp268–281 Sassen, S. (1991) The Global City: New York, London, Tokyo, Princeton University Press, Princeton, NJ Taylor, P. J., Ni, P., Derudder, B., Hoyler, M., Huang, J., Lu, F., Pain, K., Witlox, F., Yang, X., Bassens, D. and Shen, W. (2009) ‘The way we were: command-andcontrol centres in the global space-economy on the eve of the 2008 geo-economic transition’, Environment and Planning A, vol 41, pp7–12

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3

Advanced Producer Service Centres in the World Economy Peter J. Taylor

The service sector has grown immensely in the last century and now dominates all modern economies (Bryson and Daniels, 1998). Industries in this sector can be divided into those servicing individuals (e.g. hairdressing) and households (e.g. supermarkets) and those servicing businesses (e.g. advertising). These are commonly referred to as consumer services and producer services respectively. The latter include very high value services – professional, creative and financial – that are termed advanced producer services, the subject of this chapter. Advanced producer services are very important for understanding contemporary cities in globalization. This was first clearly articulated by Saskia Sassen (1991) in her ‘global city’ thesis. She argued that there are a select number of key cities – she focused on New York, London and Tokyo – that are ‘global cities’ because they are the strategic locales of contemporary globalization. They are strategic because they house the management and servicing functions that have enabled globalization of economic activities. In particular, these cities have become both the production and innovation centres of advanced producer services, and the markets for this new service provision for large corporations. For instance, in the 1980s and 1990s leading London law firms and leading New York advertising agencies ‘went global’ as they extended their professional and creative expertise to encompass the needs of clients operating in transnational markets. Both are selling customized high-value knowledge products to global corporate clients: multi-jurisdictional law and multinational advertising are both examples of very advanced producer services, which Sassen sees as being specifically concentrated in global cities. In previous eras producer service firms were based in one city and operated primarily in that city: success meant building up a local client base. Where clients had ‘outside’ service needs, these were handled through loose partnerships or associations with firms in other cities or countries. There were numerous forms of such ‘association’, the most common being ‘correspondence banks’: selected foreign banks recommended by your home bank for

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overseas business in different countries. But as global service needs grew from the 1970s, the service firms themselves became large corporations with a consequent requirement for brand integrity: servicing became increasingly an ‘in-house’ practice. But services cannot be properly dispensed ‘at a distance’ so that ‘in house’ had to be translated into a worldwide network of offices to match the globalization of client activities. Therefore, beyond Sassen’s global cities, a world city network has developed (Taylor, 2004) physically represented by the huge tower blocks that form the familiar silhouettes of major cities across the world. These appear as powerful static structures but they function as dynamic nodal structures: from these offices electronic messages come in and out, to and from other offices in other tower blocks in other cities. Advanced servicing involves complex projects that require inputs from several locales. This creates what Castells (1996) has called spaces of flows in a new network society. The flows are primarily electronic, encompassing movement of creative ideas, financial information, professional knowledge, management instruction, team planning, client input, etc., that are supplemented by video conferencing and face-to-face meetings (physical movement of key players) to facilitate a project from initiation to completion. As described in Chapter 1, it is impossible to directly measure the myriad of service flows between cities in the contemporary global economy. Thus we rely on indirect measures derived from the size and functions of offices within the office networks of individual firms. This is modelled as the interlocking network model that has guided the data collection (see Chapter 1). Here we focus in the data upon 175 advanced producer service firms. These are made up of the top firms in five service sectors: 75 financial services firms (including insurance); and 25 each from accounting, advertising, law and management consultancy. The offices of these firms have been scored from zero to five across 525 cities depending on the importance of offices within cities (no office in a city scores zero). The result is an array of cities and firms in a 525  175 service matrix. In this chapter we report on two different analyses of these data. First, the key measurement is the network connectivity of cities. This indicates how well a city is integrated into the world city network of services. Cities housing many firms with large office networks will score high on this measure, and conversely, a city with few firms will have a lower score. To ease comparison, all network connectivities will be reported as proportions of the highest scoring city. Thus we have connectivity scales ranging from one (the highest scoring city) to zero (a city with no services recorded). Second, we apply principal components analysis to the services matrix to investigate the structure of the network – which sets of cities are more interconnected and through which particular firms. This generates sub-nets – particular regional city arenas – within the overall world city network.

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Global Network Connectivities In this section, we report on six connectivity analyses: for all 175 advanced producer service firms, and for each of the five service sectors. All network connectivities are denoted as ‘global network connectivities’ (GNC) because they encompass all 525 cities. However, to facilitate discussion in the space allocated, only connectivities of leading cities are reported here: the top 50 cities for all 175 firms and 75 financial services firms, and the top 25 cities for accountancy, advertising, law and management consultancy firms. Table 3.1 shows the overall connectivities of cities featuring all service firms.

Table 3.1 Overall network connectivity. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

London New York Hong Kong Paris Singapore Tokyo Sydney Milan Shanghai Beijing Madrid Moscow Seoul Toronto Brussels Buenos Aires Mumbai Kuala Lumpur Chicago Warsaw São Paulo Zurich Amsterdam Mexico City Jakarta Dublin Bangkok Taipei Istanbul Rome Lisbon Frankfurt

GROSS CONNECTIVITY

GNC

96,267 95,838 80,330 75,322 72,594 70,773 68,263 65,988 65,950 65,939 62,599 61,387 60,597 60,454 60,253 58,091 57,902 57,523 55,324 53,880 53,319 53,197 53,105 52,903 52,645 52,062 51,974 51,793 50,673 50,604 49,831 48,165

1.00 1.00 0.83 0.78 0.75 0.74 0.71 0.69 0.69 0.68 0.65 0.64 0.63 0.63 0.63 0.60 0.60 0.60 0.57 0.56 0.55 0.55 0.55 0.55 0.55 0.54 0.54 0.54 0.53 0.53 0.52 0.50

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33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

Stockholm Prague Vienna Budapest Athens Caracas Los Angeles Auckland Santiago Washington Melbourne Johannesburg Atlanta Barcelona San Francisco Manila Bogotá Tel Aviv

47,414 46,808 46,574 46,420 46,068 45,063 44,637 44,582 44,177 42,831 41,957 41,541 41,144 40,866 40,735 40,282 40,113 39,639

25

0.49 0.49 0.48 0.48 0.48 0.47 0.46 0.46 0.46 0.44 0.44 0.43 0.43 0.42 0.42 0.42 0.42 0.41

The following findings can be derived from this table: •

•

•

•

• •

New York and London (NYLON) are clearly the most integrated cities and have very similar high levels of connectivity. ‘NYLON’ is indisputably ‘Main Street, World Economy’. Hong Kong is ranked third, separate from both New York and London above but also from cities below. Reflecting its role as economic gateway to China, the fastest growing services market in the world, this repeats earlier findings (Taylor, 2004) and contradicts the common assumption that Tokyo is the ‘third’ most important city after New York and London. Tokyo ranks only sixth, one below Singapore, but both are part of an impressive showing by Pacific Asian cities: five in the top ten, nine in the top 25. Within this region, the rise of Shanghai and Beijing into the top ten is particularly noteworthy: the new ‘workshop of the world’ is rapidly developing the advanced producer services to complement its huge production capacity. Western European cities are well represented: three in the top ten with Paris at number four, and nine in the top 25. In contrast, for US cities New York is alone in the top ten. Chicago is the second US city and ranks 19th, with Los Angeles ranking only 39th. Washington, Atlanta and San Francisco also appear in Table 3.1, but all are in the bottom ten. This finding repeats previous analyses showing surprising low levels of connectivity for US cities (Taylor and Lang, 2005; Taylor and Aranya, 2008). It appears to be related to the high national

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•

• •

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demand for services (by far the largest market in the world) that has resulted in more local- and national-level servicing than in other countries. Beyond Pacific Asia there are numerous ‘third world’ cities represented as economic gateways to their respective countries: Buenos Aires 16th, Mumbai 17th, São Paulo 21st, Mexico City 24th, Caracas 38th, Santiago 41st, Johannesburg 44th, Manila 48th, and Bogotá 49th is an impressive list clearly showing the global dimension of the world city network. In the other ‘emerging market’ region, Eastern Europe rising from its communist past, there are four cities featured including Moscow at 12th. Finally, the ‘old’ Commonwealth is represented by Sydney, Toronto, Auckland, and Melbourne. The high ranking of Sydney, seventh, and the inclusion of Melbourne, suggests Australia is benefiting economically from its location next to Pacific Asia.

Even though we have focused on just the top 50 cities, it is remarkable how such a wide range of cities from different parts of the world is to be found. Table 3.2 shows the financial connectivities based upon 75 firms.

Table 3.2 Financial network connectivity. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

London New York Hong Kong Tokyo Singapore Paris Shanghai Sydney Seoul Madrid Milan Beijing Taipei Toronto Moscow Frankfurt Zurich Mumbai Brussels Kuala Lumpur Chicago Amsterdam Dublin Jakarta

GROSS CONNECTIVITY

GNC

26,979 26,003 24,987 22,187 22,140 21,317 20,736 20,720 18,941 18,909 18,814 18,672 17,394 17,242 16,516 16,358 16,164 15,961 15,364 15,314 15,038 15,009 14,992 14,695

1.00 0.96 0.93 0.82 0.82 0.79 0.77 0.77 0.70 0.70 0.70 0.69 0.64 0.64 0.61 0.61 0.60 0.59 0.57 0.57 0.56 0.56 0.56 0.54

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25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

São Paulo Bangkok Buenos Aires Warsaw Los Angeles Istanbul Mexico City Stockholm Dubai Manila Geneva San Francisco Luxembourg Prague Athens Lisbon Guangzhou Melbourne Santiago Rome Washington Johannesburg Atlanta Caracas Budapest Boston

14,669 14,621 13,823 13,374 13,211 13,167 12,459 11,964 11,959 11,580 11,546 11,209 11,159 10,735 10,652 10,393 10,222 10,140 10,011 9477 9365 9260 9103 9034 8971 8969

27

0.54 0.54 0.51 0.50 0.49 0.49 0.46 0.44 0.44 0.43 0.43 0.42 0.41 0.40 0.39 0.39 0.38 0.38 0.37 0.35 0.35 0.34 0.34 0.33 0.33 0.33

This contrasts with the overall connectivities (Table 3.1) in the following ways: •

•

•

• •

There is now a tri-city apex to the list, with Hong Kong joining New York and London at the top, with very similar scores. This confirms the great importance of Hong Kong, not always recognized, within the world city network. Tokyo now rises to fourth and Shanghai to sixth in a pattern where Pacific Asian cities do even better than in Table 3.1. Five are in the top ten, and nine in the top 25, plus a Chinese new entry with Guangzhou at 41st. It is Western European cities that have moved down to make way for these Asian financial centres – Paris dropping to sixth, but Frankfurt rising to 16th (from 32nd in Table 3.1). Dublin rising to 23rd (from 26th), plus Geneva and Luxembourg entering at 35th and 37th respectively, are the main exceptions. Nothing much changes for US cities – although San Francisco rises from 47th to 36th, and Boston is included at 50th. Emerging market areas continue to be represented approximately as before.

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•

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One noteworthy entry is Dubai at 33rd, the first Arab Middle Eastern city to feature so far.

In summary, this table includes mostly the same cities as Table 3.1 but with an additional emphasis on Pacific Asia. Table 3.3 shows the top 25 cities in terms of connectivity generated by law firms. Of all the services it is these firms that are generally the most concentrated in the most important cities (Taylor, 2004).

Table 3.3 Law network connectivity. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20= 20= 22 23 24 25

London New York Paris Frankfurt Washington Brussels Hong Kong Moscow Tokyo Beijing Shanghai Amsterdam Munich Milan Chicago Madrid Singapore Warsaw Düsseldorf Prague Budapest Rome Palo Alto Los Angeles San Francisco

GROSS CONNECTIVITY 4934 4368 3442 2931 2849 2640 2614 2472 2363 2219 2070 1965 1950 1911 1875 1836 1734 1657 1581 1538 1538 1470 1369 1334 1255

GNC 1.00 0.89 0.70 0.59 0.58 0.54 0.53 0.50 0.48 0.45 0.42 0.40 0.40 0.39 0.38 0.37 0.35 0.34 0.32 0.31 0.31 0.30 0.28 0.27 0.25

The main findings from this table are as follows: • •

For this service London dominates, with New York somewhat less connected but still easily ranked second. Western Europe is well represented in this table: Paris is a clear third, with Frankfurt fourth and Brussels sixth. There are another six Western

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•

•

•

•

29

European cities in the top 25 including Düsseldorf, in our lists for the first time at 19th. In contrast Pacific Asian cities are relatively less well represented: Hong Kong drops to seventh and Tokyo to ninth although Beijing and Shanghai hold up at tenth and 11th. There is only one other city from this region in the list: Singapore at a lowly 17th. On this occasion, US cities fare much better than previously with Washington at a very high fifth position, Chicago at 15th and Los Angeles and San Francisco both included in the top 25. In addition Palo Alto (Silicon Valley) enters the list. More impressive are the Eastern European cities with Moscow at eighth and Warsaw, Budapest and Prague included. This relates to international law firms’ contributions to converting state-owned economies to capitalist economies in the 1990s. However, other emerging markets are less well represented: Mumbai does not appear, and no Latin American cities are included.

Generally speaking law firms have a distinct ‘western bias’ plus an attraction to financial centres (e.g. Frankfurt) and political centres (e.g. Washington and Brussels), both of which offer specific markets for their wares. Table 3.4 shows connectivities generated by advertising firms, which tend to be more global than law firms (Taylor, 2004). Key findings are as follows: •

•

• •

• •

•

Advertising is an archetypal US industry with both its origins and development centred on New York. This is reflected here with New York being outstandingly the world centre of this service activity. However, this concentration in New York does not diffuse to other US cities: they are conspicuous by their absence from the top 25 cities listed here. London is ranked second but only just ahead of Paris; these two cities constitute a European second tier of activity in this industry. The familiar Pacific Asian trio of Hong Kong, Tokyo and Singapore come next but they lead a wide range of cities from across the world; for instance Moscow, Shanghai, Warsaw and Sydney make up the rest of the top ten. Pacific Asia dominates overall with eight of the 25 cities listed. Western Europe is relatively under-represented after London and Paris but it is interesting that new cities appear: Athens at 16th, Stockholm at 17th, Vienna at 24th and Istanbul at 25th. Non-European emerging markets are represented only by Buenos Aires at a respectable 12th.

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Table 3.4 Advertising network connectivity. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

New York London Paris Hong Kong Tokyo Singapore Moscow Shanghai Warsaw Sydney Brussels Buenos Aires Taipei Mumbai Toronto Athens Stockholm Beijing Bangkok Madrid Milan Seoul Budapest Vienna Istanbul

GROSS CONNECTIVITY

GNC

20,752 15,538 15,519 15,236 14,762 14,500 13,552 13,308 13,092 12,988 12,913 12,818 12,726 12,597 12,564 12,552 12,535 12,519 12,518 12,398 12,395 12,252 11,916 11,645 11,566

1.00 0.75 0.75 0.73 0.71 0.70 0.65 0.64 0.63 0.63 0.62 0.62 0.61 0.61 0.61 0.60 0.60 0.60 0.60 0.60 0.60 0.59 0.57 0.56 0.56

In summary, advertising activity appears to be concentrated where national TV markets are centred, usually capital cities but not always so (e.g. New York, Mumbai, Toronto and Istanbul). This produces quite a widespread distribution of this connectivity. Table 3.5 shows cities with the most connectivity due to accountancy firms. Accountancy firms appear to be the ubiquitous business service sector across the world with much larger office networks than the other services (Taylor, 2004). This has made the patterning of this service connectivity less clear-cut as the following shows: •

International spread of accountancy preceded globalization especially with respect to the old British Commonwealth, hence London easily outscores New York for this service, and Sydney at fourth and Toronto at 11th have unusually high ranks.

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Table 3.5 Accountancy network connectivity. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

London New York Hong Kong Sydney Singapore Milan Paris Beijing Buenos Aires Kuala Lumpur Toronto Tel Aviv Tokyo Shanghai Jakarta Moscow Brussels Auckland Seoul Lisbon Rome Mumbai Mexico City São Paulo Berlin

• •

•

GROSS CONNECTIVITY

GNC

40,442 32,147 29,836 27,978 27,142 27,089 26,839 25,826 25,610 25,001 24,800 24,597 24,458 24,324 24,175 24,107 23,937 23,847 23,687 23,095 23,072 23,026 22,945 22,755 22,630

1.00 0.79 0.74 0.69 0.67 0.67 0.66 0.64 0.63 0.62 0.61 0.61 0.60 0.60 0.60 0.60 0.59 0.59 0.59 0.57 0.57 0.57 0.57 0.56 0.56

New York ranks a clear second but again there are no other US cities in the top 25. Western European cities are reasonably well represented but in new ways: Milan (sixth) ranks above Paris (seventh) and Lisbon and Berlin appear in the top 25 for the first time. The remainder are a mix of cities from emerging markets with Buenos Aires and Kuala Lumpur notable at ninth and tenth. Tel Aviv is a surprising entry at 12th.

There is little pattern to these connectivities, except a tendency towards capital cities doing well, especially at the lower rankings. Table 3.6 shows the top 25 cities ranked by management consultancy connectivities.

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Table 3.6 Management consultancy network connectivity. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

New York London Paris Chicago Hong Kong Singapore Tokyo Zurich Madrid Beijing Mumbai Atlanta Washington Rome Mexico City Amsterdam Dublin Boston Frankfurt Milan Seoul Stockholm Shanghai Kuala Lumpur Munich

GROSS CONNECTIVITY

GNC

12,568 8374 8205 7739 7657 7078 7003 6893 6859 6703 6318 6309 6165 6014 5973 5960 5952 5938 5908 5779 5717 5529 5512 5450 5442

1.00 0.67 0.65 0.62 0.61 0.56 0.56 0.55 0.55 0.53 0.50 0.50 0.49 0.48 0.48 0.47 0.47 0.47 0.47 0.46 0.45 0.44 0.44 0.43 0.43

Like advertising, this is an archetypal US service that has globalized (Taylor, 2004). This is reflected in the findings: • •

•

• •

New York dominates this list of city connectivities even more so than for advertising. However, in contrast to advertising, in this case New York is not alone: Chicago is ranked a very high fourth, and Atlanta, Washington and Boston also appear in the top 25. Beyond the US, London and Paris show a European second tier of cities below New York, similar to their ranking in advertising. Nine other Western European cities are listed, most as before but with Munich included this time. Pacific Asia is again well represented with seven cities, including the usual Hong Kong, Singapore and Tokyo in the top ten. Eastern Europe is not represented; cities in other developing countries are just represented by Mumbai at 11th and Mexico City at 15th.

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In summary, this service is the one most concentrated in the main globalization arenas of Northern America, Western Europe and Pacific Asia. These six tables illustrate the complexity of the world city network: the only constant is that New York and London always hold top positions. Otherwise, different services are responding to different markets producing distinctive ranges of cities. The top ten cities of the overall pattern from Table 3.1 are found scattered throughout the other tables but beyond these ‘global cities’, as Sassen might see them, there is variety across the city lists.

Locational Strategies of Firms The complexity we have uncovered by the connectivity analyses can be investigated by returning to the service matrix, and performing a principal components analysis on it. This technique is a way of finding parsimonious results from large datasets. The idea is to find the basic dimensions in the data through reducing a large number of variables into a much smaller number of composite variables known as ‘factors’ or ‘components’. For instance, in our services matrix there are 175 variables (each firm is a variable), which can be interpreted as 175 locational strategies (of where firms choose to place offices). Every firm has its own individual strategy consisting of the list of cities in which it has offices (and its scores for those offices). Thus nearly all firms include New York and London in their locational strategies with important offices, but far fewer include Munich and Bangkok, and even fewer are to be found in Naples and Brasília. What our principal components analysis has allowed us to do is to reduce these 175 variables to just eight composite variables, components that define a common locational strategy for a specific set of firms. One further note: because the technique can be overwhelmed by large numbers of zeros in the data, only the top 250 cities ranked by overall network connectivity are included. Therefore we begin with a service matrix of 250 cities  175 firms (locational strategies) and conclude with a parsimonious 250 cities  8 locational strategies. These eight components include 52.54 per cent of the original variation in the data; that is to say, we reduce the number of variables from 175 to eight (a 95 per cent reduction) for a loss of only 47 per cent in data variability. This is a good deal statistically: it is these eight locational strategies that are described below (Table 3.7).

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Table 3.7 Locational strategies of advanced producer services. (a) The advertising sector’s global locational strategy (16.88%). CITY

SCORE

SECTOR

Buenos Aires Mexico City Mumbai Athens Istanbul Toronto Milan Sydney New York Caracas Vienna Taipei São Paulo Lisbon Santiago Moscow Dublin Stockholm Warsaw Seoul Kuala Lumpur Budapest Johannesburg Bucharest Tel Aviv

2.70 2.30 2.27 2.19 2.04 2.01 2.00 1.98 1.97 1.94 1.94 1.94 1.93 1.90 1.81 1.80 1.80 1.80 1.80 1.77 1.73 1.67 1.63 1.62 1.62

AD AD AD AD AD AD AD AD AD FS AD AD AC FS AC AD AD AC AC FS AD FS MC AD AC

Helsinki Madrid Copenhagen

1.61 1.57 1.56

AD FS AD

Zurich Chicago

1.52 1.52

AC FS

FIRM BBDO Worldwide Leo Burnett Worldwide JWT Starcom MediaVest Group OgilvyOne Worldwide Ogilvy and Mather Worldwide Grey Worldwide MindShare Worldwide Euro RSCG Worldwide American International Group Saatchi and Saatchi Publicis Horwath International American Express UHY International DraftFCB ZenithOptimedia Moore Stephens International Polaris International ING Group McCann Erickson Worldwide ABN AMRO Holding McKinsey & Company Wunderman MSI Legal & Accounting Network Worldwide TBWA Worldwide JPMorgan Chase DDB Worldwide Communications Group Nexia International Allianz

LOADING 0.811 0.809 0.806 0.797 0.795 0.778 0.742 0.740 0.709 0.707 0.700 0.700 0.676 0.674 0.674 0.669 0.663 0.663 0.659 0.653 0.646 0.627 0.618 0.614 0.612 0.607 0.604 0.594 0.588 0.586

Sectors: AC – accountancy; AD – advertising; FS – financial services; LS – legal services; MC – management consultancy. Note: Results are derived from principal components analysis with varimax rotation and components selected as in Taylor et al (2002). Scores are standardized variables (i.e. with a mean of zero) and loadings are the equivalent of correlations between variables (firms) and components (common strategies). Note that these results should be read as two separate tables brought together to simplify interpretation. Thus the first row indicates the highest scoring city (Buenos Aires) and the highest loading firm (BBDO) but does not indicate a particular relation between Buenos Aires and BBDO.

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(b) Global city articulated strategies. Legal services locational strategy articulated through New York (6.61%) CITY

SCORE

SECTOR

New York Washington London Los Angeles Paris Chicago Houston Beijing

13.67 3.26 3.18 1.81 1.08 1.03 0.77 0.68

LS LS LS MC LS LS LS LS

Hong Kong Frankfurt

0.68 0.64

LS FS

FIRM

LOADING

Cravath, Swaine & Moore LLP Wachtell, Lipton, Rosen & Katz Simpson Thacher & Bartlett LLP Katzenbach Partners LLC Davis Polk & Wardwell LLP Debevoise & Plimpton LLP Sullivan & Cromwell LLP Cleary Gottlieb Steen & Hamilton LLP Weil, Gotshal & Manges LLP Freddie Mac

0.882 0.868 0.799 0.717 0.705 0.705 0.692 0.597 0.582 0.570

Business services locational strategy articulated through London (3.11%) CITY London Boston San Francisco Mumbai Los Angeles Sydney Singapore Cape Town Munich Curitiba

SCORE 10.35 6.25 3.61 2.15 1.64 1.51 1.30 1.28 1.18 1.02

SECTOR MC MC FS FS LS MC FS MC LS FS

FIRM

LOADING

The Parthenon Group Cambridge Associates LLC Legal & General Group Old Mutual Slaughter and May L.E.K. Consulting Banco do Brasil Monitor Group Herbert Smith LLP Prudential

Sectors: AC – accountancy; AD – advertising; FS – financial services; LS – legal services; MC – management consultancy. For details of the model, see Table 3.7(a)

0.724 0.621 0.565 0.549 0.512 0.508 0.397 0.379 0.369 0.360

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(c) World–regional service strategies. Financial services Pacific Asian strategy (7.63%) CITY Tokyo Hong Kong Beijing Singapore Seoul Shanghai Bangkok Guangzhou Taipei Jakarta

SCORE 6.21 4.74 4.31 4.29 3.27 3.10 2.81 2.14 2.11 2.06

SECTOR AD FS AD FS FS FS FS FS AD FS

FIRM

LOADING

Asatsu-DK Mizuho Financial Group Hakuhodo China Construction Bank (CCB) ICBC Sumitomo Mitsui Financial Group Nomura Holdings Bank of China Dentsu Standard Chartered Group

0.761 0.708 0.689 0.689 0.682 0.680 0.646 0.586 0.569 0.561

Legal services pan-European strategy (6.62%) CITY Frankfurt London Paris Brussels Munich Düsseldorf Madrid Warsaw Moscow Hamburg

SCORE 4.78 4.70 4.33 4.03 3.35 3.22 2.79 2.38 2.36 2.24

SECTOR LS LS LS LS MC FS LS LS LS LS

FIRM

LOADING

Freshfields Bruckhaus Deringer LLP CMS Cameron McKenna LLP Linklaters Clifford Chance LLP Roland Berger Strategy Consultants Fortis Allen & Overy LLP Hengeler Mueller Ashurst White & Case LLP

0.723 0.707 0.685 0.676 0.638 0.629 0.628 0.550 0.539 0.534

Financial services United States strategy (5.75%) CITY Chicago Atlanta San Francisco Washington Dallas Los Angeles Seattle Houston Boston Minneapolis

SCORE 4.67 4.33 3.72 3.63 3.54 3.44 3.04 2.95 2.76 2.40

SECTOR FS FS FS FS FS MC FS FS MC FS

FIRM

LOADING

Traveler Cos Fannie Mae Wells Fargo Wachovia US Bancorp Watson Wyatt Worldwide Washington Mutual Bank of America Towers Perrin Berkshire Hathaway

Sectors: AC – accountancy; AD – advertising; FS – financial services; LS – legal services; MC – management consultancy. For details of the model, see Table 3.7(a)

0.755 0.726 0.722 0.618 0.597 0.563 0.559 0.550 0.547 0.520

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(d) Minor regional service strategies. Financial services Canadian strategy (3.41%) CITY

SCORE

Toronto Montreal Vancouver Ottawa Calgary Halifax Winnipeg Quebec Edmonton Hong Kong

9.99 4.82 3.98 3.68 3.55 3.47 3.05 2.92 2.89 2.51

SECTOR FS FS FS FS FS FS FS FS FS FS

FIRM

LOADING

Canadian Imperial Bank Toronto-Dominion Bank Royal Bank of Canada Bank of Montreal Manulife Financial Sun Life Financial Capital One Financial Dexia Aviva Loews

0.918 0.905 0.758 0.717 0.694 0.633 0.431 0.405 0.359 0.335

Financial services Australian strategy (3.09%) CITY

SCORE

SECTOR

Sydney Melbourne Brisbane Perth Edinburgh

5.83 5.17 3.19 3.17 2.83

FS FS FS FS MC

Adelaide London Canberra Birmingham (UK) Auckland

2.70 2.52 2.44 2.37 2.35

FS MC FS FS FS

FIRM

LOADING

National Australia Bank Commonwealth Bank Westpac Banking Group ANZ Banking Mercer Human Resource Consulting HBOS Mercer Management Consulting Royal Bank of Scotland Lloyds TSB Group Allied Irish Banks

0.768 0.635 0.618 0.501 0.463 0.441 0.441 0.415 0.406 0.377

Sectors: AC – accountancy; AD – advertising; FS – financial services; LS – legal services; MC – management consultancy. For details of the model, see Table 3.7(a)

1

The Advertising Sector’s Global Locational Strategy. This is the largest component accounting for 16.88 per cent of the overall variation. Table 3.7(a) shows its composition in terms of cities and firms. The former are ranked by their component scores, which define the new composite variable. The top 30 cities are listed. These are primarily world cities of medium importance; New York is included but is not at the top, London, Paris, Hong Kong, Tokyo, Singapore, Shanghai and Beijing are conspicuous by their absence. Firms are ranked by their component loadings – how correlated they are with the component. As can be seen, the top nine firms are from advertising, and there are another eight firms from this sector in the list. Hence, the new composite variable is interpreted as an advertising sector locational strategy that is worldwide in

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3

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scope. As noted previously, advertising is an archetypal US service with a global range, but with no US cities other than New York (Table 3.4), and this is reflected in this component. Also, there are other firms beyond advertising centred on New York but with worldwide scopes that share this strategy, such as American Express and McKinsey & Company. Global City Articulated Strategies. There are two other strategies that are global in scope but which are very different from the last strategy: in these cases both are completely dominated by a global city, one by New York and the other by London. These are shown in Table 3.7(b). The first accounts for 6.61 per cent of the overall variation with a very large score recorded for New York. Of the top ten firms listed by their loadings, eight are law firms. Therefore this is named the Legal Services Locational Strategy articulated through New York. The other cities are important, with Washington and London scoring reasonably high at ranks two and three, followed by Los Angeles, Paris and Chicago. We found in the connectivity analysis that law services were concentrated (Table 3.3); here we have a composite variable illustrating this process. The second component in Table 3.7(b) is dominated by London but on this occasion there are a variety of sectors represented in the high loading forms. This component is named the Business Services Locational Strategy articulated through London, which accounts for 3.11 per cent of the overall variation. Note that this component includes US cities, notably Boston, but not New York. This is a truly worldwide strategy with South Asia, Australasia, Pacific Asia, Sub-Saharan Africa, Western Europe and Latin America all represented. World–Regional Service Strategies. Most strategies are not global in scope; there are three that largely concentrate on just one major world region. These are shown in Table 3.7(c). The first accounts for 7.63 per cent of variation in the data and is fairly straightforward to interpret: it is made up of Pacific Asian cities, and seven of the top ten firms are in financial services. This is named the Financial Services Pacific Asian Strategy. Note that it is Tokyo and not Hong Kong that is the first ranked city in this strategy. The second strategy in Table 3.7(c) is equally easy to fathom. Here all the cities are European (two from Eastern Europe) and eight of the ten firms loading high are law firms. Thus we name this the Legal Services Pan-European Strategy, which accounts for 6.62 per cent of the overall variance. Note that Frankfurt, London, Paris and Brussels are all fairly balanced with high loading on this component. The final strategy in Table 3.7(c) consists of US cities but not including New York, and eight of the high loading firms are financial. This is, therefore, the Financial Services United States Strategy, which accounts for 5.75 per cent of the overall variation. Note that once again there is no single dominant articulator city; this role is shared by Chicago and Atlanta with other cities not far behind. Minor Regional Service Strategies. There are two unexpected strategies that are each largely based upon a single country. These are shown in Table

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3.7(d) and both are dominated in the loadings by financial service firms. In the first strategy all but one of the cities listed are Canadian. In the second strategy the top four are Australian cities, two of the other six are also from Australia, and there is one New Zealand city. Thus these components are named Financial Services Canadian Strategy and Financial Services Australian Strategy. They account for 3.41 per cent and 3.09 per cent of the overall variation in the data respectively. These really look like ‘national strategies’ with the cities in each strategy roughly ranked in terms of their importance in their respective countries. From among the complexity of 175 individual firms’ locational strategies we have found eight clear composite strategies that encompass between them more than half the original variation in the data. This has proven to be a good statistical deal as we knew from the start, but we have also learned something important about cities in globalization: the world city network is worldwide but it is constituted by distinctive sub-nets, not all of which are themselves global. The key general finding is that the composite locational strategies exist at three different scales: we have found three global strategies, three world–regional strategies and two large country strategies. Thus even after more than a quarter of a century of economic globalization, not all major advanced producer service firms are primarily worldwide in the scope of their service provision. Many, especially in financial services, continue to operate through concentrations of offices in their region/country of origin with other offices in the remainder of the world limited in number and importance.

References Bryson, J. and Daniels, P. W. (eds) (1998) Service Industries in the Global Economy, 2 vols, Edward Elgar, Cheltenham Castells, M. (1996) The Rise of the Network Society, Blackwell, Oxford Sassen, S. (1991) The Global City: New York, London, Tokyo, Princeton University Press, Princeton, NJ Taylor, P. J. (2004) World City Network: A Global Urban Analysis, Routledge, London Taylor, P. J. and Aranya, R. (2008) ‘A global “urban roller coaster”? Connectivity changes in the world city network, 2000–04’, Regional Studies, vol 42, pp1–16 Taylor, P. J., Catalano, G. and Walker, D. R. F. (2002) ‘Exploratory analysis of the world city network’, Urban Studies, vol 39, pp2377–2394 Taylor P. J. and Lang, R. E. (2005) US Cities in the ‘World City Network’, The Brookings Institution, Washington, DC (Survey Series, Metropolitan Policy Program)

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4

Media Centres in the World Economy Allan Watson and Michael Hoyler

World cities research has predominantly focused on the role of advanced producer services in the formation of world city networks. However, global networking processes involve a wider variety of economic activities than advanced producer services alone. As Krätke and Taylor (2004) assert, a diversity of globalized activities leads to multiple globalizations within world city network formation. This chapter studies an alternative dimension of world city network formation, one in which global media firms, rather than advanced producer services, perform the central role. As Krätke (2003) suggests, few forms of globalization can be observed or experienced so directly as the global circulation of symbols, images and cultural commodities. Furthermore, one of the main characteristics of the globalization of media industries is concentration in and around the key cities of global capitalism, concentrations that act as ‘local anchoring points’ in the ‘cultural metropolises’ of the global urban network. The major trends that have transformed the business world – globalization, digitization, networking and deregulation – have also affected media firms, in particular through removing most of the limits to corporate media expansion (Castells, 2009). By the end of the 1990s a major turning-point had been reached in the realm of media, and a global commercial media market had begun to emerge in full force (McChesney, 1998). Throughout the 1990s, an unprecedented wave of mergers and acquisitions took place among global media corporations. Concentration and conglomeration gave rise to oligopolistic control by a small number of giant transnational media corporations, which have developed a major economic and cultural presence on nearly every continent (Held et al, 1999) and which now rank among the largest firms in the world. The global reach of communication technologies, in particular the Internet, has given media firms the potential to compete in a market space that is potentially borderless and global (Flew, 2007). However, almost all media

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organizations are in themselves not truly global, but remain territorially anchored in their main markets (Arsenault and Castells, 2008). Rather what is global are the networks of interlocked multimedia businesses organized around strategic partnerships, cross-investments, personnel, production and distribution (Castells, 2009). The dominant nodes at the core of these global media networks are the small number of giant media corporations, whose diversified holdings and main sources of revenue span the globe. In this chapter, we focus on the global networks of 25 of the world’s largest media firms, data on which were captured during the collection exercise described in Chapter 1. As with the advanced producer services firms’ data described in Chapter 3, we report on two different analyses of these data. First, we focus on the network connectivity of cities, as a measure of how well a city is integrated into the global media network, based on the interlocking network model described in Chapter 1. Second, we apply a principal components analysis to the media matrix to investigate the structure of the network. This generates a series of media fields which exist within the wider global city network.

Global Network Connectivities In this section, we report on a connectivity analysis for 25 major media firms. All network connectivities are denoted as ‘global network connectivities’ (GNC) because they encompass all 525 cities. However, to facilitate discussion in the space allocated, only connectivities of leading cities are reported here: the top 50 cities for all 25 media firms. Table 4.1 shows the overall connectivities of cities featuring all 25 media firms. The following findings can be derived from this table: • •

•

•

•

•

New York is by far the most integrated city in the global media network. London is ranked second, separate from New York above but also well ahead of cities below. London is followed by another European capital, Paris. Tokyo is ranked fourth. Tokyo’s position is part of a very strong showing by Pacific Asian cities, with five cities present in the top ten. This mirrors the findings for advanced producer services described in Chapter 3. Joining Tokyo in the top ten are Beijing, Hong Kong, Shanghai, Seoul and Taipei, while Bangkok is ranked 11th and Singapore 15th. Pacific Asian cities are not only rapidly developing advanced producer services to complement their huge production capacity, but are also developing their media capacity. Western European cities are relatively under-represented: only two cities – London and Paris – are present in the top ten, ranked second and third respectively. These are joined by just four other cities in the top 25 – Madrid (12th), Milan (14th), Munich (23rd) and Brussels (25th). Similarly, US cities are also under-represented: only two cities are present

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Table 4.1 Media network connectivity. RANK

CITY

GNC

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21= 21= 23 24 25

New York London Paris Tokyo Washington Beijing Hong Kong Shanghai Seoul Taipei Bangkok Madrid Moscow Milan Singapore Los Angeles Chicago Mumbai Mexico City Toronto Dubai São Paulo Munich Boston Brussels

1.00 0.72 0.57 0.55 0.53 0.52 0.50 0.48 0.48 0.46 0.45 0.41 0.40 0.40 0.40 0.39 0.37 0.36 0.34 0.34 0.30 0.30 0.29 0.27 0.26

•

RANK 26 27 28 29 30 31 32 33= 33= 33= 36 37 38 39 40 41= 41= 41= 44= 44= 44= 47 48 49 50= 50= 50=

CITY

GNC

San Francisco Manila Denver Dallas Amsterdam Kuala Lumpur Atlanta Indianapolis Stockholm Sydney New Delhi Barcelona Cleveland St Louis Santiago Geneva Rotterdam Wellington Bogotá Buenos Aires Caracas Melbourne Philadelphia Rochester Edinburgh Frankfurt Vancouver

0.25 0.22 0.22 0.21 0.19 0.19 0.18 0.18 0.18 0.18 0.18 0.17 0.16 0.16 0.16 0.15 0.15 0.15 0.14 0.14 0.14 0.14 0.13 0.13 0.12 0.12 0.12

in the top ten – New York ranked first and Washington, DC ranked fifth. These two cities are joined by just three cities in the top 25, Los Angeles (16th), Chicago (17th) and Boston (24th). This finding also mirrors those for advanced producer services described in Chapter 3. This underrepresentation is thought to be due to the fact that US media firms have the historic competitive advantage of the largest indigenous media market (Herman and McChesney, 1997), and thus a high national demand for media output. US media firms have therefore been slower than others to move to a business model of transnational production and distribution. Three ‘third world’ cities appear in the top 25 of the rankings, acting as gateways for media output into their respective countries: Mumbai is ranked 18th, Mexico City ranked 19th, and São Paulo ranked joint 21st with Dubai.

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Global Media Fields So far, we have considered the connectivity of cities within global media networks. In doing so, we have already begun to uncover the spatial configuration of global media networks. It is possible to uncover more of the global-spatial configuration of these networks, by looking at the common variations in the ways in which global media firms use global cities. To do this, we employ a principal components analysis, based on the same principles as the analysis undertaken in Chapter 3. One limitation of principal components analysis is that it is sensitive to sparseness in the data, where the matrix contains a large number of zero values. To counter this difficulty, the matrix of 525 cities  25 firms was reduced to 134 cities  25 firms, by removing all cities lacking the presence of global media firms. The analysis presented here reduces the data matrix of 134 cities  25 firms to just six composite components that define a set of global media fields within the wider global media. A six-component solution was selected for two reasons. First, all components have more than one firm with a loading above 0.4. Component one has eight firms at high loadings, with the number of firms reducing through the remaining components, down to just one firm at a high loading in component six. Second, the six-component analysis is easily interpretable and gives a clear geographical meaning to the configuration of global media fields. The six components emerging from the analysis account for 59.6 per cent of the original variation in the data. The five global media fields emerging from the first five components are described below (Table 4.2). The media field emerging from the sixth component is the least clear in terms of its geographical configuration and is not described here.

Table 4.2 Locational strategies of leading media firms. (a) Tokyo articulated global media field. CITY Tokyo New York Hong Kong Paris London Beijing Shanghai Los Angeles Taipei Seoul

SCORE 4.01 3.55 3.25 3.11 2.68 2.33 2.25 2.22 2.11 1.97

For details of the model, see Table 3.7(a)

FIRM The Thomson Corporation Reuters Group The McGraw-Hill Companies Toppan Printing News Corporation Vivendi Fuji Television Network Lagardère SCA Reed Elsevier Viacom

LOADING 0.81 0.74 0.66 0.65 0.63 0.61 0.59 0.58 0.26 0.26

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(b) New York articulated global media field. CITY New York Amsterdam Chicago Santiago Shanghai Denver Dallas Miami Sacramento Seattle

SCORE 7.14 5.36 4.89 1.34 1.22 1.10 0.98 0.95 0.92 0.87

FIRM RR Donnelley & Sons Viacom Wolters Kluwer CBS Tribune Reed Elsevier Clear Channel Communications Time Warner Gannett Vivendi

LOADING 0.79 0.70 0.68 0.59 0.58 0.55 0.39 0.36 0.29 0.28

For details of the model, see Table 3.7(a)

(c) London articulated global media field. CITY London San Antonio Amsterdam Belfast Birmingham (UK) Glasgow Leeds Manchester Newcastle Norwich Nottingham Plymouth

SCORE 10.26 1.79 1.26 1.02 1.02 1.02 1.02 1.02 1.02 1.02 1.02 1.02

FIRM British Sky Broadcasting ITV Reed Elsevier Clear Channel Communications Wolters Kluwer RTL Group News Corporation Reuters Group Vivendi Toppan Printing

LOADING 0.89 0.80 0.67 0.51 0.38 0.33 0.22 0.17 0.17 0.15

For details of the model, see Table 3.7(a)

(d) Washington, DC articulated global media field. CITY Washington Denver Philadelphia Atlanta Los Angeles Phoenix San Antonio San Francisco Chicago St Petersburg

SCORE 7.50 4.07 3.17 2.14 1.87 1.58 1.32 1.29 1.23 1.22

For details of the model, see Table 3.7(a)

FIRM EchoStar Communications Gannett Comcast Tribune DirecTV Group Lagardère SCA CBS News Corporation Wolters Kluwer Time Warner

LOADING 0.69 0.61 0.57 0.48 0.45 0.32 0.28 0.25 0.24 0.18

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(e) Luxembourg articulated global media field. CITY

SCORE

Luxembourg Moscow Beijing Washington New York New Delhi Johannesburg Budapest Copenhagen Zagreb

5.21 4.92 4.09 2.78 2.59 1.70 1.63 1.22 1.22 1.22

FIRM SES Global RTL Group Time Warner Viacom Fuji Television Network Reuters Group Lagardère SCA Reed Elsevier News Corporation The McGraw-Hill Companies

LOADING 0.75 0.62 0.57 0.37 0.33 0.27 0.18 0.17 0.16 0.13

For details of the model, see Table 3.7(a)

1

2

3

Tokyo articulated global media field. This component is the most significant component in that it accounts for over 15 per cent of the total variance. Table 4.2(a) shows its composition in terms of leading cities and firms. The field contains eight major media firms with loadings above 0.4, including the Fuji Television Network and Toppan Printing with headquarters in Tokyo. Also included in the field are a number of firms headquartered in the US or Europe that have a Pacific Rim focus to their business, including News Corporation, Thomson Corporation and McGraw-Hill Companies (New York); Vivendi and Lagardère SCA (Paris); and Reuters Group (London). The media field which these firms create is global in nature, but with an orientation towards Pacific Rim cities. The field is articulated through Tokyo, although the city is far from dominant. New York, Hong Kong and Paris also appear as strong cities. The Pacific Rim orientation is further displayed by the presence of Beijing, Shanghai, Taipei and Seoul. Despite the global nature of the field, US cities are relatively unimportant in this field. New York articulated global media field. This component is the next most significant and accounts for almost 13 per cent of the total variance. As shown in Table 4.2(b), the field contains six major media firms with loadings above 0.4. Predominantly headquartered in the US and with an American focus to their business, they include Viacom and CBS (New York), RR Donnelley & Sons and Tribune (Chicago), as well as Wolters Kluwer (Amsterdam) and Reed Elsevier (London). New York is the superarticulator of this field, dominant above two other leading cities in the field, Amsterdam and Chicago. The field has a strong US orientation, with US cities accounting for seven of the top ten cities. Amsterdam aside, European cities are relatively unimportant in this field. London articulated global media field. This component accounts for just over 10 per cent of the total variation. Table 4.2(c) shows its composition

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in terms of cities and firms. The field contains four major media firms with loadings above 0.4. Three of the four have headquarters in London (British Sky Broadcasting, ITV and Reed Elsevier) while the fourth (Clear Channel Communications) is headquartered in San Antonio in the US. The corporation with the highest loading, British Sky Broadcasting, is based only in London; ITV, with the second highest loading, has a network of offices throughout the UK only. The remaining two firms have relatively limited global office networks. The media field created by these firms is completely dominated by London. Further, UK cities account for ten of the top 12 cities. Pacific Rim cities are relatively unimportant in this field. Washington, DC articulated global media field. This component accounts for over 8 per cent of the total variation and contains five firms with loadings above 0.4, as shown in Table 4.2(d). All of these firms have headquarters in the US and have a strong US focus to their business. They include EchoStar Communications (Denver), Gannett (Washington), Comcast (Philadelphia), Tribune (Chicago) and DirecTV Group (Los Angeles). The city of Washington is the super-articulator of this field, with Denver as a lower level articulator. The field is strongly orientated towards the US. Including the two articulators, there are nine US cities in the top ten for this media field. Both European and Pacific Rim cities are relatively unimportant in this field. Luxembourg articulated global media field. This component accounts for 7 per cent of the total variance. As shown in Table 4.2(e), it contains just three global media firms with loadings above 0.4. Two of the three, SES Global and RTL Group have headquarters in Luxembourg, while the third, Time Warner, has headquarters in New York. The field has three articulator cities; Luxembourg, Moscow and Beijing, with Luxembourg the highest scoring articulator. The cities of Washington and New York also appear in the top five cities in the field.

The principal components analysis has demonstrated how the global media network is constituted by a number of distinctive media fields. All of the six media fields that have been identified are global in nature, but with a focus on specific world regions, and articulated through particular key cities. Our focus solely on 25 of the top media firms and identification of just six media fields does however belie the complexity of global media networks. While a few giant media corporations form the core of global media networks, they require local partners in order to deliver customized media content to local audiences. The global media networks of the corporations therefore also consist of many partnerships and cross-investments with local, national and regional companies, which facilitate expansion into local markets (Arsenault and Castells, 2008). Hence there is much complexity to global media networks that is not captured in the analysis presented in this chapter.

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References Arsenault, A. H. and Castells, M. (2008) ‘The structure and dynamics of global multi-media business networks’, International Journal of Communication, vol 2, pp707–748 Castells, M. (2009) Communication Power, Oxford University Press, Oxford Flew, T. (2007) Understanding Global Media, Palgrave Macmillan, Basingstoke Held, D., McGrew, A., Goldblatt, D. and Perraton, J. (1999) Global Transformations: Politics, Economics and Culture, Stanford University Press, Stanford, CA Herman, E. S. and McChesney, R. W. (1997) The Global Media: The New Missionaries of Global Capitalism, Cassell, London Krätke, S. (2003) ‘Global media cities in a worldwide urban network’, European Planning Studies, vol 11, pp605–628 Krätke, S. and Taylor, P. J. (2004) ‘A world geography of global media cities’, European Planning Studies, vol 12, pp459–477 McChesney, R. W. (1998) ‘Media convergence and globalisation’, in D. K. Thussu (ed.) Electronic Empires, Arnold, London, pp27–46

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5

The Global City Process Score Pengfei Ni, Peter J. Taylor and Ben Derudder

The purpose of this chapter is to try and bring the global results together. We attempt this by creating a comprehensive index that uses nearly all the data collected. But there are dangers in such an approach; merely adding up different measures can produce meaningless results. There needs to be a good rationale for any combination or else the research degenerates into an exercise in adding apples to oranges to bananas … We call our index the Globalizing Cities Index to emphasize the fact that we are creating scores that measure a process. The process is the mechanism of becoming globalized. We use Sassen’s (1991) classic work on the global city to help understand this process. Basically she indicates that ‘global cities’ have command and control functions as well as advanced servicing functions. Today we know that these functions are not limited to just a few ‘global cities’; globalizing is a feature that all cities are experiencing, albeit in terms of many other functions. Here we will focus on the functions that Sassen identified and therefore our results should be interpreted as reflecting a global business process. But we still need clear concepts in order to empirically measure our process. The basic economic purpose of cities is to articulate space for the conduct of business. We use Castells’ (1996) theory of socially-constructed space to specify this purpose. Castells identified two fundamental categories of space: spaces of places and spaces of flows. Spaces of places are the outcome of social agents constructing a world of places, distinctive areas with specific functions in the overall scheme of things. Spaces of flows are the outcome of social agents creating dynamic worlds of flows, both infrastructure and the ongoing flows themselves: of commodities, of people, of information. Both spaces always occur together simultaneously: spaces of flows need origins and destinations where the social agents operate; spaces of places need inflow and outflow to prevent social atrophy. For the Globalizing Cities Index we will treat the control and command function as a global space of places and the servicing function as a global space of flows. Since these two spatial concepts complement each other we will weight them equally in our index.

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Figure 5.1 Constitution of the ‘Globalizing Cities Index’ (GCI).

Figure 5.1 shows the construction of the Globalizing Cities Index. Note that both constituent parts of the final index are described as measures of power. This is easy to appreciate for the command and control half: clearly these are places of decision-making. Thus we call this ‘City Place Power’ (CPP) and our measurement is intended to answer the question: ‘how much power does a given city have for moulding the world economy?’ This measure is made up overwhelmingly (80 per cent) by the Business Command Index from Chapter 2. This obviously makes sense given that this index is derived directly from headquarter functions of the Forbes 2000 top firms. However we do modify it slightly through identifying two other places within cities where important decisions are made, including those made by firms not headquartered in the city: at trade fairs, using the Business Fairs Index (BFI) and the Business Hotels Index (BHI). The data on these two functions are simply summed and weighted 10 per cent each in creating the City Place Power measure. Thus: CPP = 0.8BCI + 0.1BFI + 0.1BHI This measures the importance of a city to business as a place. The City Network Power measure (CNP) is based upon a more subtle idea of power. Instead of a sum of what is in a city, power derives from position within networks. For example, Hong Kong has relatively few headquarters of large firms but it is strategically located within global networks as a ‘gateway’ to the fast growing Chinese economy. Hong Kong is a city many firms feel they have to be located in to become serious Chinese players. To measure this ‘network power’ (Taylor et al, 2002) we use the same data as in Chapters 3 and 4. All results are based upon network connectivity measures (Taylor, 2001). In this case, financial connectivity (FNC) is weighted at 45 per cent, and the remaining advanced producer services are combined to produce a new connectivity (SNC) weighted at 40 per cent. Finally media connectivities (MNC) are included and weighted at 15 per cent. These weightings are, of

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course, somewhat arbitrary, but they broadly reflect the importance given to these sectors in the world city literature. Thus: CNP = 0.45FNC + 0.4SNC + 0.15MNC This measures the importance of a city to business as a ‘crossroads’. The key results for these two power measures are shown in Table 5.1 for place and Table 5.2 for flows. In both cases the measures have been created by dealing with all inputs as percentages and ranked accordingly; the top 50 for each power measure are listed.

Table 5.1 City Place Power: the top 50 cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Tokyo New York London Paris Chicago Houston Los Angeles Washington Madrid Toronto Seoul Dallas Atlanta Beijing San Jose (CA) Stockholm San Francisco Osaka Sydney Boston Moscow Hong Kong Las Vegas Seattle Amsterdam

CPP 100.00 82.44 81.50 69.20 33.90 33.42 31.33 29.04 27.18 26.70 25.51 24.08 23.21 22.76 21.46 21.17 20.74 20.29 18.27 18.26 17.06 16.69 16.23 16.07 15.77

RANK

CITY

26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46= 46= 48 49 50

Melbourne Minneapolis Philadelphia Rome Montreal Munich Calgary Zurich Singapore Denver San Diego Detroit Charlotte Brussels Orlando Phoenix Milan Pittsburgh Taipei Miami São Paulo San Antonio Helsinki Shanghai Baltimore

CPP 15.60 15.33 14.86 14.16 14.12 13.93 13.90 13.52 13.42 13.34 12.64 12.57 12.56 12.50 11.96 11.90 11.77 11.43 11.26 11.22 11.18 11.18 11.01 10.96 10.46

In Table 5.1, Tokyo appears as very clearly the most powerful business place in the world. It scores 100 because it ranked first on all three measures constituting City Place Power (i.e., cities are measured in terms of percentages of the highest city in each category). New York and London have similar scores at

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ranks two and three, followed a little further behind by Paris. These are the ‘big four’ cities identified in Chapter 2. From this point on the most notable feature is the importance of US cities spread across the whole table: four more in the top ten (Chicago, Houston, Los Angeles and Washington); five in the next ten; four in the next ten, five in the next ten; and another five in the final ten ranks. In other words a whisker under a half of City Place Power in Table 5.1 is in the US. This contrasts with Europe’s 12 cities (half the US total) and Pacific Asia featuring only eight cities (a third of the US total). This leaves just six cities for the rest of the world: three in Canada, two in Australia plus São Paulo being the sole representative of the old ‘poor’ ‘third world’ at the lowly rank of 46th. Clearly this power measure starkly picks up the rich–poor divisions of the world: overwhelmingly City Place Power is concentrated in leading cities of the rich world. Table 5.2 City Network Power: the top 50 cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

New York London Hong Kong Paris Tokyo Singapore Shanghai Beijing Milan Sydney Madrid Seoul Moscow Toronto Mumbai Taipei Brussels Chicago Kuala Lumpur Bangkok São Paulo Buenos Aires Amsterdam Zurich Mexico City

CNP 100.00 95.55 81.37 75.46 73.51 72.45 68.16 66.40 65.97 65.33 63.37 62.98 59.88 59.06 56.38 55.87 55.74 54.13 53.17 52.72 51.47 51.22 50.29 50.14 49.48

RANK

CITY

26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43= 43= 45 46 47 48 49 50

Frankfurt Dublin Warsaw Jakarta Los Angeles Istanbul Stockholm Washington Lisbon Rome Prague Athens Dubai San Francisco Manila Santiago Caracas Budapest Melbourne Atlanta Vienna Geneva Auckland Johannesburg Luxembourg

CNP 47.97 47.92 47.72 47.38 46.04 45.62 43.44 42.95 42.04 40.79 40.66 40.14 40.08 39.73 39.42 39.01 38.30 37.70 37.70 36.72 36.60 36.44 35.89 34.98 34.23

In Table 5.2, it is all change. Although New York ranks first, all other US cities fare far less well. Only five other US cities are in this table, all relatively lowly

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ranked at 18th, 30th, 33rd, 39th and 45th. In contrast Europe now has 20 cities in the table and Pacific Asia has 11 cities, most relatively highly ranked (including half the top 12). But the real story with City Network Power is that to be global players, firms concerned with flows need to be spread across the world. Thus cities in poorer countries beyond the three main globalization arenas are relatively well represented in this form of power: Mumbai (15th), São Paulo (21st), Buenos Aires (22nd), Mexico City (25th), Santiago (41st) and Caracas (42nd). Clearly City Network Power picks up worldwide networks: power continues to be concentrated in richer countries but not to the virtual exclusion of cities elsewhere. These differences are so marked that they warrant further illustration. Treating all cities that occur in either Tables 5.1 or 5.2, the difference between their rankings on these two measures of city power have been computed. The results are shown in Figure 5.2, which depicts an incredible acute global pattern. There are no US cities among those with a clear indication of more network power than place power. All but one of the extreme place-preponderance cities are from the US (Osaka is the exception). At the other end of the scale, network preponderance tends to feature poorer and more remote cities. These tend to be single city gateways into relatively large national economies and are spread across the world beyond the US. However, European cities are often more balanced in the relations between their place and network power capacities: they constitute a majority of the middle group. This is a most peculiar global urban geography.

Figure 5.2 City Place Power/City Network Power differential.

Finally Table 5.3 shows the Globalizing Cities Index. Since this is computed as CPP  CNP (converted into percentages of the highest scoring city), this table has a more geographically mixed pattern than the previous two. Sassen’s (1991) ‘big three’ – New York, London and Tokyo – are outstanding at the top

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of the table, and Paris is also far ahead of the rest. However, Hong Kong in fifth place is not exceptionally different from the cities ranked just below it: the city’s relative paucity of place power is the reason for this (Table 5.1). In this new geography the three globalization arenas are featured strongly (US, Europe and Pacific Asia) plus a weak ‘rest of the world’ category. It can be seen that Europe and Pacific Asia are stronger in the top 50, and the US and the rest in the second 50 ranks. There is a particularly acute contrast between Pacific Asia and the US: the former has five of the top ten cities, the US four of the bottom ten. In global business terms this means that Pacific Asia has many leading cities but with a relative paucity of medium-level cities; the US is the obverse of this. Among the rest there are eight cities from Canada and Australasia (most noticeably Toronto and Sydney ranked 11th and 12th). The remainder tend to reflect network power of major cities acting as gateways to their national economies (Table 5.2). Africa is confirmed as the continent with fewest global business cities: just one in the north (Cairo, 70th) and one in the south (Johannesburg, 61st). This contrasts with Latin America in which eight cities feature.

Table 5.3 Globalizing Cities Index: the top 100 cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

New York London Tokyo Paris Hong Kong Madrid Beijing Seoul Chicago Singapore Toronto Sydney Shanghai Milan Los Angeles Moscow Washington Brussels Taipei Amsterdam Mumbai Stockholm

CGI 100.00 97.04 95.11 79.29 53.75 49.63 48.87 48.50 48.26 47.07 47.01 45.82 43.37 42.61 42.40 42.17 39.45 37.40 36.80 36.21 36.15 35.42

RANK

CITY

51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72

Budapest Dubai Manila Berlin San Jose (CA) Miami Luxembourg Caracas Auckland Denver Johannesburg Helsinki Seattle Minneapolis Osaka Oslo Philadelphia Tel Aviv Bogotá Cairo Düsseldorf Guangzhou

CGI 22.62 22.58 22.17 21.73 21.49 21.46 21.32 21.09 20.78 20.77 20.34 20.17 20.05 19.33 19.12 18.87 18.67 18.60 18.59 18.20 18.18 17.81

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Table 5.3 Globalizing Cities Index: the top 100 cities (continued). RANK

CITY

23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

Zurich Houston São Paulo Bangkok Kuala Lumpur San Francisco Atlanta Frankfurt Mexico City Dublin Dallas Rome Buenos Aires Melbourne Istanbul Boston Jakarta Warsaw Athens Munich Lisbon Vienna Prague New Delhi Barcelona Geneva Montreal Santiago

CGI 34.89 34.47 34.35 33.35 33.25 33.14 32.84 32.00 31.82 31.78 31.09 30.12 29.47 29.22 28.91 28.31 28.06 27.04 25.63 25.40 24.87 24.61 24.44 23.48 23.33 23.07 22.80 22.78

RANK

CITY

73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91= 91= 93 94 95 96 97 98 99= 99=

Copenhagen Vancouver Bucharest Hamburg Bangalore Calgary Rio de Janeiro Lima Riyadh Detroit San Diego Shenzhen Las Vegas Columbus Karachi Birmingham (UK) Stuttgart Sofia Portland Ho Chi Minh City Edinburgh Phoenix Charlotte Cleveland Jeddah Bratislava Brisbane Manama

CGI 17.74 17.72 17.06 16.97 16.93 16.88 16.25 15.95 15.84 15.74 15.48 15.37 15.33 15.17 14.85 14.81 14.79 14.49 14.44 14.44 14.22 14.16 14.13 14.06 13.90 13.60 13.48 13.48

The Globalizing Cities Index is a considered ranking mechanism for the importance of cities in the working of the world economy. It is the end-point of one part of our global urban analysis, our attempt to provide a general ordering of cities as business centres and hubs. The discussion has provided glimpses of the geographical complexity being handled in order to produce a city ranking (see especially Figure 5.2). With the whole data it is not possible to delve further into this geography. However, the large amount of data collected for operationalizing the interlocking network model to produce network connectivities – the 525 cities  175 firms service values matrix is constituted of 91,875 pieces of information – makes this specifically available for exploring both world regional patterns (Part B) and national patterns (Part C), to which we now turn.

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References Castells, M. (1996) The Rise of the Network Society, Blackwell, Oxford Sassen, S. (1991) The Global City: New York, London, Tokyo, Princeton University Press, Princeton, NJ Taylor, P. J. (2001) ‘Specification of the world city network’, Geographical Analysis, vol 33, pp181–194 Taylor, P. J., Walker, D. R. F., Catalano, G. and Hoyler, M. (2002) ‘Diversity and power in the world city network’, Cities, vol 19, pp231–241

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Part B

WORLD– REGIONAL CONNECTIVITY ANALYSES

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Introduction Peter J. Taylor

Economic globalization includes homogenizing processes but this has in no way eliminated geographical variation across the world (see Chapter 3). In Part B we focus upon world regions in order to illustrate this geography within globalization. The analysis is now limited to connectivity analyses utilizing the 525 cities  175 firms service matrix with its 91,875 pieces of information. This introduction has three purposes: first to define and justify the regions we use; second to indicate the criteria for including cities in the analysis; and third, to describe the measures we conduct on the cities that constitute the raw material for each regional chapter. We define nine world regions. Definition is based upon our experience in researching globalization for over a decade through the world city network. From this past work we have developed a good grasp of this ‘regionality’ inherent in the way cities connect to each other. The one additional rule we have adopted is to constitute regions as groups of states (i.e. we keep to state boundaries) in order to facilitate comparison with Part C. Hence we do not divide, say, Russia and Turkey into their supposed ‘European’ and ‘Asian’ parts. The regions are: •

•

• • • •

Europe: this includes all European countries except former Soviet countries within the Commonwealth of Independent States (CIS). (This definition locates the three ex-Soviet Baltic states which are members of the European Union – Latvia, Lithuania and Estonia – within the region.) Northern America: this includes just the US and Canada. (Although Mexico is contiguous to the US and a founder member of the North American Free Trade Agreement (NAFTA), in terms of globalization its cities are more like other Latin American cities.) Pacific Asia: all Asian countries with a Pacific littoral (except Russia). Australasia: Australia, New Zealand, Papua/New Guinea, and Fiji. South Asia: India, Pakistan, Bangladesh, Sri Lanka, Afghanistan, Burma, Nepal, and Bhutan. Eurasia: ex-Soviet states in Europe and Asia (excluding Baltic states, see above) plus Mongolia.

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Middle East/North Africa (MENA): from Morocco to Iran, from Turkey to Sudan. Sub-Saharan Africa: all African states without a Mediterranean littoral (except Sudan and Eritrea) plus Mauritius. Latin America: from Mexico to Chile plus Caribbean states.

This regional framework is intended to be comprehensive in coverage: all 525 of our cities can be allocated to one of the regions. The criteria for including cities are important because cities for which there are few data can distort analyses. We decided upon one basic threshold: cities had to have a global network connectivity score (see Chapter 3) of 0.1 or above. Obviously this will generate different numbers of cities across the regions. We could have selected, say, the top 25 cities from each region but this would have resulted in some important cities missing from some regions and some unimportant cities included in other regions. However, we consider the uneven spread of cities across the regions as part of the analysis reflecting the unevenness of economic globalization. Using our threshold, 245 cities qualified, distributed across the regions as follows: Europe 74 cities, Northern America 55, Latin America 34, Pacific Asia 26, MENA 17, South Asia 12, SubSaharan Africa 11, Australasia 9, and Eurasia 7. The same tables of results were produced for each world region. The first table is a simple ranking of the cities in each region by their global network connectivity (see Chapter 3). The next five tables present results from disaggregating the global network connectivities by sectors. That is to say, the connectivities are computed just for firms in one sector. Tables show results in the following order: financial connectivities (based upon the 75 financial services firms), accountancy connectivities, advertising connectivities, legal services connectivities and management consultancies connectivities (the latter four being based upon just 25 firms each). From these results different relational geographies can be produced for each sector in each region. The final table measures the hinterworlds of the cities. The word hinterworld derives from the old concept of ‘hinterland’, the area around a city that it services. Instead of this local ‘back yard’, hinterworld looks outwards to all the other cities the city under consideration is linked to (Taylor, 2001; Taylor and Walker, 2004). Thus London’s hinterland is South East England, but its hinterworld is global with important links to all continents (New York, Hong Kong, Paris, etc.) Four hinterworld measures are presented. First, each city’s links to other cities in its region are measured – we can call this its ‘localism’. Links are then measured for each city with cities in Europe, Northern America and Pacific Asia. These three regions have been chosen because they represent the ‘globalization core regions’, the other six regions can be considered periphery or semi-periphery regions. Thus what we are measuring is the degree of a city’s connections to each of the three main regions of contemporary globalization. This will enable the orientation of cities (i.e. towards Pacific Asia or Europe or Northern America) to be assessed. To ease

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interpretation, the hinterworld results have been transformed in two ways. First, they were compared to the global network connectivities to produce ‘expected results’ (e.g. the London–New York link is expected to have a high connectivity; Seattle–Perth a somewhat smaller connectivity). It is differences from these expected values that are used; they show over-linked (more than expected) and under-linked (fewer than expected) results for every pair of cities. Second, these results are standardized so that the hinterland scores for a city will have a mean of zero, and over- and under-linkage is measured in units of standard deviation, thus making results comparable across all tables. Hinterland results can be interpreted as alternative disaggregation of a city’s global network connectivity: instead of the focus being on firms in different sectors, it is on cities in different regions.

References Taylor, P. J. (2001) ‘Urban hinterworlds: geographies of corporate service provision under conditions of contemporary globalization’, Geography, vol 86, pp51–60 Taylor, P. J. and Walker, D. R. F. (2004) ‘Urban hinterworlds revisited’, Geography, vol 96, pp145–151

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Australasian Cities in Globalization Oli Mould

The urbanity of this region is perhaps as high as anywhere in the world, with Australia and New Zealand having 90 per cent of their population in urban areas (Stimson and Baum, 2003). This high percentage is not however mirrored by the Pacific Island nations, and hence, they are not included in the datasets. Therefore, the Australasian region data contain information on nine of its world cities, six from Australia, and three from New Zealand. This reflects the dominance of Australian cities in the region, and the lack of any world cities outside these two countries. This is clearly a much lower number of cities than in most other regions analysed (the Europe chapter for example considers 74 cities; see Chapter 11), and so there is inevitably a large amount of overlap in the rankings between the different professional service sectors. The urban system in Australia, the largest country in the region, is somewhat truncated, with the state capitals the largest cities in the country, but with very few other cities or even settlements with over 100,000 population (Stein, 2002). This is in stark contrast to other regional urban hierarchies (Europe and North America for example) which have large numbers of ‘midsized’ cities, as well as the larger world and global cities. Hence, it is argued that there is ‘no true hierarchy of central places’ in Australia (Hofmeister, 1988, p74). Instead, there is a missing middle, a small number of large cities (with a high concentration of services), and a large number of smaller, semirural settlements; although the continuing urbanization of the population will see a decline in the latter type of settlement (Stimson and Baum, 2003). This phenomenon is mirrored in New Zealand with three primate cities, Auckland, Christchurch and Wellington, and then only three other settlements with a population over 100,000. Hence, both Australia and New Zealand have ‘top-heavy’ urban hierarchies which equates to little ‘movement’ in cities in the rankings, i.e. the same cities will appear in the rankings over long periods of time. This is reflected in the data, as the nine cities being analysed are the only nine Australasian cities to appear in the whole world rankings.

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Sydney dominates the region, with Auckland and Melbourne jostling for second place in the various categories of connectivity. Table 6.1 shows the collated data for global network connectivity, and as can be seen, Sydney dominates with a score of 0.71, with Auckland in second place with 0.46, and Melbourne a close third with 0.44. The rest of the cities have a connectivity score of less than 0.30. This again suggests that there is a clear triad of Australasian cities, with Sydney the standout ‘globally’ orientated city (having a global connectivity score over 0.5). Tables 6.2–6.6 show the connectivity scores for each individual professional service industry, and in each of them Sydney tops the list. In financial services (Table 6.2) and advertising (Table 6.4), Melbourne and Auckland are in second and third place. In these two criteria, Sydney is well above the other two cities, comfortably orientating itself as the region’s lead city in these services. In accountancy (Table 6.3), Auckland is second and Melbourne is third, but Sydney’s ‘lead’ is not as strong as in financial services and advertising. Indeed, Auckland’s score is over 0.5, suggesting that it has a strong regional and global orientation, the only case where a city other than Sydney scores over 0.5.

Table 6.1 Global network connectivity of Australasian cities. RANK

CITY

1 2 3 4 5 6 7 8 9

Sydney Auckland Melbourne Brisbane Perth Wellington Adelaide Canberra Christchurch

GROSS CONNECTIVITY 68,263 44,582 41,957 27,260 22,798 21,227 19,034 15,633 13,502

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.71 0.46 0.44 0.28 0.24 0.22 0.20 0.16 0.14

COUNTRY

Australia New Zealand Australia Australia Australia New Zealand Australia Australia New Zealand

For legal services (Table 6.5) and management consultancy (Table 6.6), the picture is slightly different. Sydney still tops the list, but has a significantly reduced score; 0.25 for legal services, 0.43 for management consultancy. Table 6.5, showing the scores for legal services is telling, as it shows that the region’s cities score very low. Six cities are on 0.07 (including Auckland), with Melbourne scoring only slightly better with 0.17. This indicates that the legal professional service sector is largely local in this region. In other words, most leading firms are not present in these cities, and in Christchurch’s case, they are absent altogether. For management consultancy (Table 6.6), the cities score marginally better, but the lower scores still suggest that this sector is again

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Table 6.2 Financial services network connectivity of Australasian cities. RANK

CITY

1 2 3 4 5 6 7 8 9

Sydney Melbourne Auckland Perth Brisbane Wellington Adelaide Christchurch Canberra

GROSS CONNECTIVITY 20,720 10,140 8919 5134 4616 3498 2092 1268 652

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.77 0.38 0.33 0.19 0.17 0.13 0.08 0.05 0.02

COUNTRY

Australia Australia New Zealand Australia Australia New Zealand Australia New Zealand Australia

Table 6.3 Accountancy network connectivity of Australasian cities. RANK

CITY

1 2 3 4 5 6 7 8 9

Sydney Auckland Melbourne Brisbane Perth Adelaide Canberra Christchurch Wellington

GROSS CONNECTIVITY 27978 23847 18,933 17,814 14,898 13,524 11,434 11,208 10,403

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.69 0.59 0.47 0.44 0.37 0.33 0.28 0.28 0.26

COUNTRY

Australia New Zealand Australia Australia Australia Australia Australia New Zealand New Zealand

Table 6.4 Advertising network connectivity of Australasian cities. RANK

CITY

1 2 3 4 5 6= 6= 8 9

Sydney Melbourne Auckland Wellington Brisbane Perth Adelaide Canberra Christchurch

GROSS CONNECTIVITY 12,988 7827 7597 2685 2444 1062 1062 855 0

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK) 0.63 0.38 0.37 0.13 0.12 0.05 0.05 0.04 0.00

COUNTRY

Australia Australia New Zealand New Zealand Australia Australia Australia Australia New Zealand

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mostly locally or nationally orientated. Wellington ranks second in this list, above Melbourne and Auckland, which is the only case of another city ‘breaking’ the city triad of Sydney, Melbourne and Auckland.

Table 6.5 Legal services network connectivity of Australasian cities. RANK

CITY

1 2 3= 3= 3= 3= 3= 3= 9

Sydney Melbourne Auckland Brisbane Perth Wellington Adelaide Canberra Christchurch

GROSS CONNECTIVITY 1216 832 324 324 324 324 324 324 0

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.25 0.17 0.07 0.07 0.07 0.07 0.07 0.07 0.00

COUNTRY

Australia Australia New Zealand Australia Australia New Zealand Australia Australia New Zealand

Table 6.6 Management consultancy network connectivity of Australasian cities. RANK

CITY

1 2 3 4 5 6 7 8 9

Sydney Wellington Melbourne Auckland Canberra Brisbane Adelaide Perth Christchurch

GROSS CONNECTIVITY 5361 4317 4225 3895 2368 2062 2032 1380 1026

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK) 0.43 0.34 0.34 0.31 0.19 0.16 0.16 0.11 0.08

COUNTRY

Australia New Zealand Australia New Zealand Australia Australia Australia Australia New Zealand

The orientation of Australasian cities is best exemplified in Table 6.7, which shows their hinterworlds, i.e. regional concentrations of connections. Sydney is relatively under-linked with the local region, with a score of 0.52 (Table 6.7(a)), and highly over-linked (1.85) with the Pacific Asia region (Table 6.7(d)), reflecting Sydney’s political and economic drive to be more connected with that region, specifically with cities such as Hong Kong, Shanghai and Singapore (Daly and Pritchard, 2000; Fagan, 2000). This phenomenon is exacerbated by a lower degree of over-linkage with Europe (0.63) (Table 6.7(b)), and relative under-linkage with Northern America (0.29) (Table

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6.7(c)). The federal government of Australia has made no secret of its propensity toward the Asia Pacific region; with their aid contribution of AU$1billion toward the Tsunami relief efforts in 2004 (the highest of any country in the world) symptomatic of such policies (Oloruntoba, 2005). It is worth noting however, that in other sectors not covered in this data, such as the creative and cultural industries and tourism, Sydney has strong links with European cities such as London, Dublin and Paris, and Northern American cities such as New York and Los Angeles (Mould, 2008).

Table 6.7 City hinterworlds (regional concentrations of connections) of Australasian cities. (a) Relative concentration of connections to local region. CITY Canberra Adelaide Perth Brisbane Christchurch Wellington Melbourne Auckland

INWARD 1.51 1.44 1.28 0.99 0.97 0.83 0.54 0.08

CITY Sydney

OUTWARD −0.52

(b) Relative concentration of connections to Europe. CITY Sydney Canberra Brisbane Adelaide Auckland Melbourne

MORE EUROPEAN 0.63 0.62 0.52 0.48 0.42 0.14

CITY Christchurch Wellington Perth

LESS EUROPEAN −1.57 −0.98 −0.62

(c) Relative concentration of connections to Northern America. CITY Wellington Perth

MORE NORTHERN AMERICAN 2.17 0.22

CITY Auckland Christchurch Adelaide Sydney Canberra Brisbane Melbourne

LESS NORTHERN AMERICAN −0.64 −0.51 −0.38 −0.29 −0.22 −0.15 −0.14

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(d) Relative concentration of connections to Pacific Asia. CITY Sydney Melbourne

MORE PACIFIC ASIAN 1.85 0.63

CITY Canberra Adelaide Christchurch Brisbane Wellington Perth Auckland

LESS PACIFIC ASIAN −2.09 −1.98 −1.42 −1.39 −1.22 −1.02 −0.25

All Australian cities with the exception of Perth are over-linked to Europe, whereas New Zealand’s cities, with the exception of Auckland, are relatively under-linked. There is a general trend throughout the nine Australasian cities of under-linkage to Northern America and Pacific Asia. Christchurch in particular is under-linked to all three regions, with a positive local score of 0.97. Even Melbourne and Auckland, the other two cities in the triumvirate of Australasian cities, are not particularly strongly linked to the other regions, with Auckland showing under-linkage to Northern America (−0.64) and Pacific Asia (−0.25). Auckland does however show low positive connectivity with the local region (0.08), suggestive of Auckland’s position as New Zealand’s least ‘local’ city. Unsurprisingly, Canberra, Australia’s capital city, shows the strongest local connectivity score (1.51), which is indicative of its capacity as political capital, and of its lack of economic or cultural prominence beyond the region. This is emphasized by its high negative score for the Pacific Asia region (−2.09). However, a score of 0.62 with Europe shows how a local city can have an element of connectivity to other regions through professional service sectors. Being part of the Commonwealth, the connectivity to Europe is no doubt diagnostic of links with London and other UK cities, as these firms look to service government linkages between Commonwealth cities. The one result in Table 6.7(c) that stands out is Wellington’s high positive connectivity score with Northern America (2.17; Perth is second with 0.22, with Auckland and Christchurch last and second last respectively). Wellington has negative scores with Europe and Pacific Asia, and a local score of 0.83. This implies that while it has a fairly local agenda, it is strongly established as a ‘Northern America’-focused city. As the capital of New Zealand, which is also part of the Commonwealth, this again is indication of governmentalrelated service firms in operation; however, the negative connectivity score to Europe (−0.98) would seem to negate this. Much like Australia, New Zealand has strong links to Northern America in external industrial sectors such as tourism and the creative and cultural industries, with particularly strong links in the film industry. However, the data used in this case are focused on advanced producer service firms, and Wellington is the city of choice for

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linkages with Northern American cities in these sectors. It is not unusual for world cities in a region to be orientated ‘outwardly’ towards regions other than their own (Taylor, 2004), and while this is expected of Sydney, the region’s dominant world city, it is a more surprising characteristic of a locally orientated city such as Wellington. Table 6.7 tells us that, because of the small number of cities in the Australasian region, one particular city can dominate more easily than it could in a region populated with more cities. In Europe for example, Paris and London compete in many sectors (see Chapter 11), but while London tends to win out, Paris remains more competitive with London (in terms of connectivity scores) than Melbourne and Auckland do in relation to Sydney. Sydney’s monopoly however seems to have been loosened slightly by Wellington, at least in terms of Northern American connectivity. Sydney and New South Wales government officials have been making political attempts to align the city with the Pacific Asia region (Donald and Gammack, 2007), and this orientation is also reflected in the relative over-linkage of business service connections. The only other Australian city that is relatively over-linked to Pacific Asia is Melbourne, indicating that advanced producer service firms serving the Pacific Asia region also tend to locate in these two Australian cities. However, despite Wellington’s surprisingly strong connectivity score in relation to Northern America, Australasian cities tend to be under-linked to Northern American cities. Hence, there is scope for the further development of linkages. However, any Australasian city keen to expand its international operations must first compete with the monopolistic tendencies of Sydney.

References Daly, M. and Pritchard, B. (2000) ‘Sydney: Australia’s financial and corporate capital’, in J. Connell (ed.) Sydney: The Emergence of a Global City, Oxford University Press, Melbourne, pp167–188 Donald, S. H. and Gammack, J. G. (2007) Tourism and the Branded City: Film and Identity on the Pacific Rim, Ashgate, Aldershot Fagan, R. (2000) ‘Industrial change in the global city: Sydney’s new spaces of production’, in J. Connell (ed.) Sydney: The Emergence of a Global City, Oxford University Press, Melbourne, pp144–166 Hofmeister, B. (1988) Australia and its Urban Centers, Borntraeger, Berlin Mould, O. (2008) ‘Moving images: world cities, connections and projects in Sydney’s TV production industry’, Global Networks, vol 8, pp474–495 Oloruntoba, R. (2005) ‘A wave of destruction and the waves of relief: issues, challenges and strategies’, Disaster Prevention and Management, vol 14, pp506–521 Stein, R. (2002) Sydney Globalizing: A World City in National, Pacific Asian and International Context, Bauhaus Dessau Foundation and Bauhaus Kolleg, Dessau, www.bauhaus-dessau.de/kolleg/servecity, accessed 10 March 2010

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Stimson, R. J. and Baum, S. W. (2003) ‘Cities of Australia and the Pacific Islands’, in S. D. Brunn, J. F. Williams and D. J. Zeigler (eds) Cities of the World: World Regional Urban Development, 3rd edition, Rowman & Littlefield, Lanham, MD, pp457–488 Taylor, P. J. (2004) World City Network: A Global Urban Analysis, Routledge, London

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7

Pacific Asian Cities in Globalization Pengfei Ni and Xiaolan Yang

The Pacific Asia region in this research is composed of cities in East Asia and South East Asia. Twenty-six cities from nine countries qualify to be included in the analysis: twelve cities in China, three in Japan, four in Malaysia, two in Vietnam, and one in the Philippines, South Korea, Indonesia, Thailand and Singapore respectively. Their specific distribution can be explained with reference to their locational, economic, environmental, political and developmental histories. Pacific Asia has a long history that includes the construction of prosperous agricultural civilization systems and, in South East Asia, sea trading systems. The incorporations of these societies into the modern world-system led to a variety of development patterns. Japan was forced to open its economy, and, in a few decades, by reforming and modernizing social, educational, economic, military, political and industrial systems (Meiji Restoration), it was transformed from a feudal and isolated state into a world power. China had been the most powerful country in the world with a long prosperous history, and attracted people from around the world to trade and study there. However, because of its policy of isolation, China lost this status as centre of the world as its place was taken by western countries. South Korea also suffered foreign invasion and limited development. During European colonization, many cities in South East Asia were constructed by colonizers as trading ports and they later developed as important economic and commercial centres of their country or even of the world. For example, the Dutch established the city of Batavia (now Jakarta), the British began from Penang and established Singapore. Colonial rule had a profound effect on South East Asia. While the colonial powers profited much from the region’s vast resources and large market, colonial rule did develop the region to an extent. Commercial agriculture, mining and an export based economy developed rapidly during the imperial period. During World War II, Pacific Asia suffered greatly.

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Since World War II, the Pacific Asia region has fared remarkably well in economic development, and its current uneven distribution of global cities is determined by various developing histories in different countries and regions (Lo and Yeung, 1996; Yeung and Lo, 1998). First of all, Japan, currently the second largest economy in the world, created a miracle of economic growth from the 1960s to the 1980s. At the same time, it also urbanized rapidly. By 1992, people living in urban areas accounted for 77 per cent of the total population in the whole country. Japan’s economic success was followed in Hong Kong, South Korea, Taiwan and Singapore by high growth rates and rapid industrialization from the 1960s, and they rose to global prominence in the 1970s and 1980s. These ‘New Industrial Economies’ followed open political policies, with high GDP per capita and a thriving, export-oriented economic outcome. The four ‘New Industrial Economies’ have evolved far beyond this status and have joined the ranks of developed countries. Since 1978 China has adopted economic reforms known as ‘Reform and Opening up’, generating 30 years of rapid development. China has developed from an economically isolated country into an industrial powerhouse, rapidly overtaking developed western nations in the current recession. Now China is attracting more and more attention because of its rapid economic transformation and its extraordinary growing power. In the early 1990s, Thailand, Malaysia, Indonesia and the Philippines underwent rapid economic expansion. Vietnam has in recent years also made steady progress in developing its industrial sectors. It is clear that globalization and regionalization trends have made the position of Pacific Asia increasingly important: more and more cities, especially those along the coasts, are becoming global cities (Shin and Timberlake, 2000). However, there is still a large gap between cities when they are located on global development coordinates (Douglas, 2001; Williams and Chan, 2008). In other words, cities ranking first in a country have a far higher connectivity than their second cities. Most cities in this area perform as important centres because of their taking part in the world economy mainly as manufacturing zones rather than advanced service centres. This is the reason first-ranked cities within one country usually play a dominant role for advanced services within the world economy (Daniels et al, 2005). It is an urban structure that is the opposite of ‘horizontal’ urban hierarchies such as those in Germany (see Chapter 19). Most of these cities (except in China, whose regional centres such as Shanghai are able to be world cities) are capital cities, traditional local administrative centres, as well as cultural and economic centres. Metropolitan areas are usually formed around these ‘primate cities’, such as Seoul (capital of South Korea), Tokyo (capital of Japan), Jakarta (capital of Indonesia) and Kuala Lumpur (capital of Malaysia). The results described below confirm the discussion above. To begin with, the cities with global network connectivities above 0.1 define the 26 cities that are analysed throughout the chapter. Using the actual connectivity proportions, gaps in these values are employed to identify five strata of cities

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(from which we can see an extraordinary uneven developing pattern for different areas and cities); emphasis in the discussion will be on the top ten cities, in which the connectivity value is over 0.5. The 26 cities are ranked by global network connectivity in Table 7.1. As already known, Hong Kong has by far the highest connectivity value within the Pacific-Asia region (0.83). Traditionally, Hong Kong’s capitalist economy is freer than New York and London. In addition, from a historical point of view, the global network connectivity value in Hong Kong is increasing, from 0.72 in 2000 to 0.83 in 2008: the gap to New York and London is closing (see Chapter 3). Hong Kong is the ‘place-to-be’ for servicing clients into the fast growing Chinese market (Taylor et al, 2002).

Table 7.1 Global network connectivity of Pacific Asian cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

Hong Kong Singapore Tokyo Shanghai Beijing Seoul Kuala Lumpur Jakarta Bangkok Taipei Manila Guangzhou Ho Chi Minh City Shenzhen Hanoi Osaka Chengdu Macao Tianjin Penang Nagoya Nanjing Kaohsiung Dalian Labuan Johor Baharu

GROSS CONNECTIVITY 80,330 72,594 70,773 65,950 65,939 60,597 57,523 52,645 51,974 51,793 40,282 30,814 28,887 23,648 17,256 15,939 12,891 12,133 11,263 11,196 11,110 10,875 10,726 10,688 10,094 9744

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.83 0.75 0.74 0.69 0.68 0.63 0.60 0.55 0.54 0.54 0.42 0.32 0.30 0.25 0.18 0.17 0.13 0.13 0.12 0.12 0.12 0.11 0.11 0.11 0.10 0.10

China Singapore Japan China China Korea Malaysia Indonesia Thailand China Philippines China Vietnam China Vietnam Japan China China China Malaysia Japan China China China Malaysia Malaysia

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Singapore, Tokyo, Beijing and Shanghai are on the second stratum with values between 0.68 and 0.75. Singapore, which has been rated as the most businessfriendly economy and featured as the regional headquarters of South East Asia, has maintained a steady status as a highly connected global city. Tokyo is the largest city in Japan and also ranks as one of the most important global cities (Sassen, 1991). Being the capital of China, Beijing’s special position makes it a key location for advanced service provision. Shanghai is the largest city in both population and economy within China and the government is promoting it as China’s gateway to the world economy in succession to Hong Kong. In addition, compared with their connectivity values in 2004 (0.5 and 0.46 respectively), both Chinese cities have increased sharply to nearly 0.7, which brings them closer to Tokyo and Singapore. Seoul and Kuala Lumpur are in the next stratum, both of which are capital cities and the largest cities in their countries. Below them is a stratum with global network connectives around two-thirds of the maximum, containing Jakarta, Bangkok and Taipei which are unsurprisingly either national or provincial capital cities. Manila, the capital of the Philippines, is in a class of its own. Most of the top ten cities above are capital cities, which hints at a ‘topheavy’ structure. In the next level, Guangzhou, Ho Chi Minh City and Shenzhen are found. They represent, in order, one of the most important cities in the Pearl River Delta area; the most important economic centre in Vietnam; and one of the earliest ‘open’ cities in China. Although they are not prominent enough to be named as ‘global cities’, their high position indicates their tremendous potential. The remaining 13 cities do currently have less potential to become major nodes in the world city network. Overall, among the 26 cities included in this region, there are 12 Chinese cities. In addition, in the top two strata, there are three Chinese cities (Hong Kong, Beijing and Shanghai) that qualify as top global cities (Taylor, 2006). Shenzhen and Guangzhou are becoming strong and their connectivity values bring them close to global city status. The fact that there are so many Chinese cities emerging sheds light on the country’s rise as another world economic centre. There is another point that warrants discussion: Japan is by far the second largest economy in the world, but this is not reflected in Table 7.1. Except for Tokyo ranked third (its ranking has dropped compared to 2004), the values of the other two cities, Osaka and Nagoya, are below 0.2. There are three reasons for this. First, Japan struggled with a low growth rate during the 1990s and into the current recession. Second, it has restricted foreign investment in order to protect its own companies, thus flows of foreign direct investment (FDI) from Japan to other countries have been much larger than the flows into Japan. Third, there has been a trend of corporate headquarters relocating from other Japanese cities to Tokyo since the 1960s. In Tables 7.2–7.6, the city connectivities are disaggregated by service sector producing five new rankings (for financial services, accountancy, advertising, legal services and management consultancy). These are treated in the same way

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as the gross connectivity: strata are identified in the upper echelons of ranks as leading cities in each sector. In Table 7.2 city connectivities based just upon the financial services firms are used to rank the cities. There are ten cities that stand out as ‘international financial centres’ in Pacific Asia, and Hong Kong stays on top as before but with a higher value of 0.93, moving even closer to London and New York. This is also evidence of the increasing international connectivity of China to the world, in which Hong Kong is the main gateway. In the second stratum, Shanghai again ranks above Beijing but below Tokyo and Singapore, both of which are top centres of finance in the region and the world. Shanghai, the old traditional financial centre of China, has increased its role in finance, banking and as a major destination for corporate headquarters. This is attributed to the open and friendly investment environment and the attractive market. Shanghai has the potential to catch up with Singapore and Tokyo. The third stratum includes Seoul, Beijing and Taipei, which are taking the role of important regional financial centres as well as administrative centres. The three primate cities in their own countries, Kuala Lumpur, Bangkok and Jakarta rank on the fourth stratum with the same value, almost 60 per cent of the maximum. Manila and Guangzhou have values straddling 0.4. What is particularly noteworthy is that the connectivity of cities below slips down to less than 0.3, clear evidence for the centralized structure of financial services. When we consider these positions further, Labuan stands out. With a population of just over 85,000 people, it was established as an international offshore financial centre and business services centre in 1990. Over 300 financial institutions there provide a comprehensive range of financial services, both conventional and Islamic. The next four tables show city connectivity rankings for accountancy, advertising, law and management. As described in Chapter 3, it is European cities that dominate in accountancy (Table 7.3) and legal services (Table 7.5) and the US which is the leader in advertising (Table 7.4) and management consultancy (Table 7.6). Thus, in general, cities in Pacific Asia have much weaker connectivity levels in these producer services. Hong Kong dominates other cities of this region in all four sectors. On the second stratum in accountancy (Table 7.3), we find Singapore, Beijing, Kuala Lumpur, Tokyo, Shanghai, Jakarta and Seoul with similar connectivity values. Beijing ranks third, higher than Shanghai, which may reflect Beijing as national capital attracting more headquarters of international companies than Shanghai. In the advertising sector (Table 7.4), there are cities with high connectivity values such as Tokyo and Hong Kong, as well as cities with very low connectivities including cities listed below Osaka. The last seven ranked cities (Macao, Tianjin, Penang, Kaohsiung, Dalian, Labuan and Johor Baharu) have no presence of leading advertising firms. This follows the general rule that advertising firms are focused on the national media centres (usually the capital or the leading city of a country) and notably the homes of national television

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Table 7.2 Financial services network connectivity of Pacific Asian cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

Hong Kong Tokyo Singapore Shanghai Seoul Beijing Taipei Kuala Lumpur Jakarta Bangkok Manila Guangzhou Shenzhen Hanoi Chengdu Ho Chi Minh City Labuan Tianjin Osaka Macao Kaohsiung Nagoya Nanjing Dalian Penang Johor Baharu

GROSS CONNECTIVITY 24,987 22,187 22,140 20,736 18,941 18,672 17,394 15,314 14,695 14,621 11,580 10,222 6724 6065 5995 5948 5720 5181 4768 4151 2516 2512 2009 1774 700 600

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.93 0.82 0.82 0.77 0.70 0.69 0.64 0.57 0.54 0.54 0.43 0.38 0.25 0.22 0.22 0.22 0.21 0.19 0.18 0.15 0.09 0.09 0.07 0.07 0.03 0.02

China Japan Singapore China Korea China China Malaysia Indonesia Thailand Philippines China China Vietnam China Vietnam Malaysia China Japan China China Japan China China Malaysia Malaysia

stations. Hong Kong, Tokyo and Singapore are ranked at the top all with values of 0.7 or above. Tokyo houses a large number of major companies in the advertising sector. As Sassen (1991) has long emphasized, Tokyo is much more than ‘Japan’s world city’, it has its own leading firms, mainly in banking and advertising. In the second stratum, Shanghai ranks above Taipei and Beijing; it is China’s media and culture centre and has a strong regional market in the Yangtze River Delta region. Bangkok ranks above Seoul, and Kuala Lumpur steps into the second stratum because of its more mature advertising market. The legal sector is known to be the most concentrated service among world cities, and this is illustrated in the Pacific Asian region. In Table 7.5, the

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Table 7.3 Accountancy network connectivity of Pacific Asian cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26

Hong Kong Singapore Beijing Kuala Lumpur Tokyo Shanghai Jakarta Seoul Bangkok Taipei Manila Ho Chi Minh City Shenzhen Guangzhou Hanoi Penang Osaka Kaohsiung Johor Baharu Macao Nagoya Dalian Nanjing Chengdu Tianjin Labuan

GROSS CONNECTIVITY 29,836 27,142 25,826 25,001 24,458 24,324 24,175 23,687 18,886 16,308 16,141 13,657 13,334 11,360 10,142 9470 8810 8210 8118 6956 6436 6414 6298 6294 5056 4374

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.74 0.67 0.64 0.62 0.60 0.60 0.60 0.59 0.47 0.40 0.40 0.34 0.33 0.28 0.25 0.23 0.22 0.20 0.20 0.17 0.16 0.16 0.16 0.16 0.13 0.11

China Singapore China Malaysia Japan China Indonesia Korea Thailand China Philippines Vietnam China China Vietnam Malaysia Japan China Malaysia China Japan China China China China Malaysia

connectivity of Hong Kong is about half that of London (the top-ranked city in this sector) and more than half of the cities have no connectivity. This represents countries in Pacific Asia using their national legal systems. The cities that show legal services network connectivity are capital cities plus Ho Chi Minh City and Shanghai, both of which are the leading commercial city in their countries. Table 7.6 ranks cities by management consultancy network connectivity. This lower-contribution sector (Taylor, 2004) reflects a ‘flatter’ distribution in the Pacific Asian area but with low connectivities compared to the other two globalization core areas. Hong Kong, for example, has the highest management consultancy connectivity in Pacific Asia (0.61), but this is just

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Table 7.4 Advertising network connectivity of Pacific Asian cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20= 20= 20= 20= 20= 20= 20=

Hong Kong Tokyo Singapore Shanghai Taipei Beijing Bangkok Seoul Kuala Lumpur Jakarta Manila Ho Chi Minh City Guangzhou Osaka Nagoya Chengdu Shenzhen Nanjing Hanoi Macao Tianjin Penang Kaohsiung Dalian Labuan Johor Baharu

GROSS CONNECTIVITY 15,236 14,762 14,500 13,308 12,726 12,519 12,518 12,252 11,456 9555 8414 7636 6276 1335 864 602 578 460 429 0 0 0 0 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK)

COUNTRY

0.73 0.71 0.70 0.64 0.61 0.60 0.60 0.59 0.55 0.46 0.41 0.37 0.30 0.06 0.04 0.03 0.03 0.02 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00

China Japan Singapore China China China Thailand Korea Malaysia Indonesia Philippines Vietnam China Japan Japan China China China Vietnam China China Malaysia China China Malaysia Malaysia

three-fifths that of New York. In the second stratum, Beijing follows Singapore and Tokyo, which all show strong international connectivity through management consultancy. Shanghai, ranked in the middle of the third stratum flanked by Seoul and Kuala Lumpur, has a lower network connectivity than Beijing in this sector. As noted previously, in China, Beijing attracts more international headquarters than Shanghai. In summary, the traditional city structures continue to feature very strongly locally within the world city network. Every country has an economic centre which is usually the primate city. This is always ranked in the higher strata, as the leader and driver of a country’s economy, but no other cities in these countries (with the exception of China) appear in any list of leading cities. China has more leading cities in all of these five sectors, which may

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Table 7.5 Legal services network connectivity of Pacific Asian cities. RANK

CITY

1 2 3 4 5 6 7 8= 8= 10 11= 11= 13= 13= 13= 13= 13= 13= 13= 13= 13= 13= 13= 13= 13= 13=

Hong Kong Tokyo Beijing Shanghai Singapore Bangkok Taipei Ho Chi Minh City Hanoi Jakarta Kuala Lumpur Manila Seoul Guangzhou Shenzhen Osaka Chengdu Macao Tianjin Penang Nagoya Nanjing Kaohsiung Dalian Labuan Johor Baharu

GROSS CONNECTIVITY 2614 2363 2219 2070 1734 1248 586 384 384 358 302 302 0 0 0 0 0 0 0 0 0 0 0 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.53 0.48 0.45 0.42 0.35 0.25 0.12 0.08 0.08 0.07 0.06 0.06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

China Japan China China Singapore Thailand China Vietnam Vietnam Indonesia Malaysia Philippines Korea China China Japan China China China Malaysia Japan China China China Malaysia Malaysia

imply a tendency towards a more ‘horizontal’ city structure. The ranks of cities in Vietnam is also noteworthy: even though two cities qualify for the analysis (Ho Chi Minh City and Hanoi), neither of them is ranked as a major global city for any of the service sectors. This illustrates the uneven development levels in the Pacific Asian area. Table 7.7 refers to a city’s ‘hinterworld’: the pattern of its regional concentrations of connections to other cities in the world city network. City connectivities are disaggregated by geographical orientation, showing over- or under-linkage locally (to the other Pacific Asian cities), and over- or underlinkage to the other main globalization arenas, to Northern American cities and to European cities.

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Table 7.6 Management consultancy network connectivity of Pacific Asian cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18= 18= 18= 18= 18= 23 24= 24= 24=

Hong Kong Singapore Tokyo Beijing Seoul Shanghai Kuala Lumpur Taipei Bangkok Jakarta Manila Shenzhen Guangzhou Dalian Nanjing Nagoya Ho Chi Minh City Osaka Macao Tianjin Penang Johor Baharu Hanoi Chengdu Kaohsiung Labuan

GROSS CONNECTIVITY 7657 7078 7003 6703 5717 5512 5450 4779 4701 3862 3845 3012 2956 2500 2108 1298 1262 1026 1026 1026 1026 1026 236 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK)

COUNTRY

0.61 0.56 0.56 0.53 0.45 0.44 0.43 0.38 0.37 0.31 0.31 0.24 0.24 0.20 0.17 0.10 0.10 0.08 0.08 0.08 0.08 0.08 0.02 0.00 0.00 0.00

China Singapore Japan China Korea China Malaysia China Thailand Indonesia Philippines China China China China Japan Vietnam Japan China China Malaysia Malaysia Vietnam China China Malaysia

For the relative concentration of connections to the local region (Table 7.7(a)), one minor city (Penang) has a negative connectivity value indicating significant under-linkage with the local economy. This is because of its prosperous foreign direct investments and port economy. Johor Baharu has the lowest positive value and is also outward orientated. Note that cities highly ranked in previous tables also have relatively low positive values. Cities with more links to other Pacific Asian cities are dominated by Chinese cities, including Tianjin and Dalian, which are closer to South Korea and Japan, and Chengdu and Nanjing, which are inland cities. The other cities with high positive values are two Japanese cities (Osaka and Nagoya), Labuan (Malaysia) and Hanoi (Vietnam).

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As to the connectivity to European cities (Table 7.7(b)), there is a significant pattern: the more important Pacific Asian cities tend to be over-linked and the less important under-linked, and this is especially the case with respect to financial services connectivity (Table 7.2). As we can see by comparing Table 7.2 and 7.7(b), all the top ten ranked as ‘global financial services centres’ in Table 7.2 have high connectivity with European cities in Table 7.7(b). There is no doubt that this reflects the strong connectivity between these two regions in financial services. For the relative concentration of connections to Europe, all cities with strong local inward orientations are under-linked to European cities. Most Pacific Asian cities are under-linked to Northern America (Table 7.7(c)), which is very different from European linkages. Among the cities with positive values only Beijing is known as an important global city. Hong Kong,

Table 7.7 City hinterworlds (regional concentrations of connections) of Pacific Asian cities. (a) Relative concentration of connections to local region. CITY Tianjin Chengdu Dalian Nanjing Osaka Labuan Nagoya Hanoi Guangzhou Shenzhen Tokyo Ho Chi Minh City Beijing Macao Seoul Singapore Kaohsiung Jakarta Hong Kong Shanghai Bangkok Manila Taipei Kuala Lumpur Johor Baharu

INWARD 9.24 8.20 6.63 6.53 5.22 4.88 4.55 3.99 3.66 3.59 2.44 2.36 2.30 2.30 1.98 1.63 1.62 1.60 1.51 1.49 1.49 1.39 1.31 1.21 0.90

CITY Penang

OUTWARD −0.19

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Table 7.7 Continued (b) Relative concentration of connections to Europe. CITY Shanghai Hong Kong Singapore Beijing Tokyo

MORE EUROPEAN 1.51 0.88 0.65 0.28 0.24

CITY Tianjin Dalian Osaka Chengdu Nanjing Nagoya Hanoi Penang Johor Baharu Kaohsiung Shenzhen Labuan Ho Chi Minh City Macao Jakarta Guangzhou Manila Seoul Bangkok Taipei Kuala Lumpur

LESS EUROPEAN −5.65 −4.51 −3.74 −3.66 −3.52 −3.36 −2.94 −2.52 −2.11 −1.90 −1.82 −1.19 −1.15 −1.06 −0.76 −0.66 −0.62 −0.57 −0.34 −0.28 −0.27

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Table 7.7 Continued (c) Relative concentration of connections to Northern America. CITY Labuan Dalian Penang Beijing Shenzhen Nagoya

MORE NORTHERN AMERICAN 2.46 0.71 0.39 0.08 0.02 0.01

CITY Chengdu Kaohsiung Ho Chi Minh City Hanoi Macao Johor Baharu Osaka Jakarta Tianjin Kuala Lumpur Nanjing Guangzhou Bangkok Taipei Seoul Singapore Shanghai Tokyo Manila Hong Kong

LESS NORTHERN AMERICAN −4.74 −4.26 −3.86 −3.35 −1.73 −1.67 −1.22 −1.01 −0.97 −0.89 −0.83 −0.82 −0.73 −0.62 −0.62 −0.60 −0.56 −0.35 −0.21 −0.13

Tokyo, Shanghai, Singapore, Seoul, Kuala Lumpur, Bangkok and Taipei have only low negative scores. Labuan has the strongest relative connections to Northern America. In conclusion and as expected, the Pacific Asia region, as the contemporary leader of rapid economic growth, increasingly attracts advanced producer service firms and has more and more cities integrated into the world city network (Williams and Chan, 2008). Nearly half of the cities considered are Chinese (12), and most of them have important world city network connections. Ranked first, Hong Kong has been increasing its global connectivity more than Tokyo and Singapore. Beijing and Shanghai are growing rapidly as global cities. China is becoming an important core area in the world. Japan, South Korea, Thailand, Malaysia, Indonesia and Singapore share the property of having just one major world city per country. Patterns vary between different service sectors – Hong Kong and Shanghai are particularly prominent for financial services, Beijing and Kuala Lumpur perform better for accountancy, Bangkok for advertising. The important Pacific Asian cities tend to be more over-linked to European cities than to Northern American cities.

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References Daniels, P. W., Ho, K. C. and Hutton, T. A. (eds) (2005) Service Industries and AsiaPacific Cities: New Development Trajectories, Routledge, London Douglas, M. (2001) ‘Intercity competition and the question of resilience: globalization and crisis in Asia’, in A. J. Scott (ed.) Global City-Regions, Oxford University Press, New York, NY, pp236–264 Lo, F. and Yeung, Y. (eds) (1996) Emerging World Cities in Pacific Asia, United Nations University Press, Tokyo Sassen, S. (1991) The Global City: New York, London, Tokyo, Princeton University Press, Princeton, NJ Shin, K.-H. and Timberlake, M. (2000) ‘World cities in Asia: cliques, centrality and connectedness’, Urban Studies, vol 37, pp2257–2285 Taylor, P. J. (2004) World City Network: A Global Urban Analysis, Routledge, London Taylor, P. J. (2006) Shanghai, Hong Kong, Taipei and Beijing within the World City Network: Positions, Trends and Prospects, GaWC Research Bulletin 204, www.lboro.ac.uk/gawc/rb/rb204.html, accessed 10 March 2010 Taylor, P. J., Walker, D. R. F., Catalano, G. and Hoyler, M. (2002) ‘Diversity and power in the world city network’, Cities, vol 19, pp231–241 Williams, J. F. and Chan, K. W. (2008) ‘Cities of East Asia’, in S. D. Brunn, M. HaysMitchell and D. J. Zeigler (eds) Cities of the World: World Regional Urban Development, 4th edition, Rowman & Littlefield, Lanham, MD, pp475–528 Yeung, Y. and Lo, F. (1998) ‘Globalization and world city formation in Pacific Asia’, in F. Lo and Y. Yeung (eds) Globalization and the World of Large Cities, United Nations University Press, Tokyo, pp132–154

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8

Eurasian Cities in Globalization Pengfei Ni, Guangquan Li, Kai Liu and Jin Huang

There are seven cities from six countries qualifying for inclusion in this regional chapter: Moscow and St Petersburg in Russia, Kiev in Ukraine, Almaty in Kazakhstan, Baku in Azerbaijan, Tashkent in Uzbekistan and Tbilisi in Georgia. There are three reasons for inclusion: 1

2

3

The cities above have a long historical standing as the heart of civilization in their regions. Moscow, Kiev, Almaty and St Petersburg date from 1156, 822, 1854 and 1703 respectively; and Baku, Tashkent and Tbilisi emerged during the fifth, eleventh and fourth centuries AD. Based upon these long histories, these cities have a strong tradition of ‘outside links’ involving trading. St Petersburg, for example, with little more than 200 years as capital of Russia from 1712, was the ‘window on the West’ of the Russian Empire. With the dissolution of the USSR, the Union Republics have shaken off Soviet rule and regained their independence (Graybill and Mitchneck, 2008). Capital cities of Union Republics became capitals of their respective countries and encountered new opportunities for economic development. Such cities have special service needs for their government functions, as well as very often serving as gateways to their national economies (Brunn, 2003; Derudder et al, 2007). This changing of status immensely accelerated their integration into the world city network and is also associated with the conversion to market economic regimes, with cities at the forefront of economic opening and integration into the capitalist system (EBRD, 1995). During this transition, many leading international advanced producer service firms (lacking in the old command economies) actively seized the opportunity to locate in the major cities of these countries to set up affiliated offices. The significance of strategic location has an influence on a wide range of urban connections in this region. Linking Europe to Asia, Eurasia is a key strategic core-region (Interstate Statistical Committee of the CIS, 2008). More specifically, many firms in the service industry come to target particular new market areas by selecting cities in the region. For example, lying between the Greater and Lesser Caucasus mountain ranges, Tbilisi is

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an important ‘hinge’ of connections in the Caucasus, and a strategic transCaucasian location. Hence the region and its cities have been at the forefront of the processes creating more economic opportunities in a diffusion of European economic development. There are two important regional institutions that have been established recently: the Commonwealth of Independent States (CIS), and the Eurasian Economic Community (EurAsEC or EAEC), which are implicated in the creation of a common ‘economic space’. However, countering this spatial tendency, GUAM (Georgia, Ukraine, Azerbaijan and Moldova) has shown renewed interest in joining the European Union (EU): such membership would be incompatible with the envisioned Eurasian common economic space. Thus although the regional organization of Eurasia has developed rapidly this has had a limited effect on intercity relations within Eurasia, except for Moscow as the conventional core city and headquarters of EAEC. Analysis in this chapter comprises three aspects: first, seven cities with global network connectivity above 0.1 are analysed. These cities are ranked according to proportionate connectivity. Among the ranks, cities are divided into three strata with the first stratum defining the leading Eurasian cities in the world city network. Second, treating the different service sectors (financial services, accountancy, advertising, legal services and management consultancy) separately, further city connectivities are produced to create five new rankings. As with the gross connectivity, the upper strata are identified as leading cities in each sector. Third, over- or under-linkage to cities of the local region, and to cities in the main globalization arenas (Europe, Northern America and Pacific Asia) define each city’s hinterworld – the regional concentrations of a city’s connections in the world city network. Positive values indicate over-linkage while negative values express under-linkage. The seven cities are ranked by their global network connectivities in Table 8.1; none of these seven score very highly and this reflects the relatively low global connection of the region. The top and only city in the first stratum, Moscow, only has 0.64 per cent of London’s connectivity (the highest in the analyses): clearly this reflects Moscow’s primacy both in the USSR and in today’s Russia (Brade and Rudolph, 2004; Graybill and Mitchneck, 2008). Note that its connectivity has risen dramatically since global network connectivities were first measured in 2000 (Taylor, 2004), due to its further opening up to the world economy in the last decade. No other cities score higher than 0.5. Kiev, St Petersburg and Almaty which are scored 0.33, 0.21, and 0.20 respectively are ranked in the second stratum. Kiev is the best non-Russian city in global network connectivities, and St Petersburg, the next ranked and Europe’s third largest city (by city limit) after Moscow and London, is, with Almaty the only ‘non-capital’ city in these rankings. The last three cities – Baku, Tashkent and Tbilisi – are in the third stratum. Baku is the capital, the largest city and the largest port of Azerbaijan (and the Caucasus); Tashkent is the capital of Uzbekistan and also of the Tashkent Province; Tbilisi is the capital and largest

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city of Georgia. The city was a significant industrial and cultural centre during the Soviet period but declined economically after the break-up of the USSR, partly due to frequent political crises. However, Tbilisi has developed rapidly during recent years by opening up and attracting foreign investments.

Table 8.1 Global network connectivity of Eurasian cities. RANK

CITY

1 2 3 4 5 6 7

Moscow Kiev St Petersburg Almaty Baku Tashkent Tbilisi

GROSS CONNECTIVITY 61,387 31,613 20,401 19,629 11,474 10,702 9740

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.64 0.33 0.21 0.20 0.12 0.11 0.10

Russia Ukraine Russia Kazakhstan Azerbaijan Uzbekistan Georgia

In Table 8.2 city connectivities are ranked based on financial services firms. This shows distinctive differences from the general ranking (Table 8.1). Only Moscow stands out as ‘international financial centre’ in Eurasia (above 0.5) but it is not a strong competitor to international financial centres in other world regions. The remaining cities have much lower financial connectivities (all less than 0.2). Tashkent rises in the rankings from six to four in this table as the most cosmopolitan city and the largest industrial city of Uzbekistan. It is the financial servicing of the national agricultural machinery and textile machinery production base in the country that enables it to join Kiev and Almaty in the second stratum. In contrast, St Petersburg drops to the third stratum because of its location in Moscow’s shadow.

Table 8.2 Financial services network connectivity of Eurasian cities. RANK

CITY

1 2 3 4 5 6 7

Moscow Kiev Almaty Tashkent St Petersburg Baku Tbilisi

GROSS CONNECTIVITY 16,516 4324 4305 2388 2240 1166 230

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.61 0.16 0.16 0.09 0.08 0.04 0.01

Russia Ukraine Kazakhstan Uzbekistan Russia Azerbaijan Georgia

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For the accountancy network connectivity (Table 8.3), the general rankings of Eurasian cities are higher than for finance. Apart from Moscow, which scores almost the same points as in Table 8.2, the remaining cities score much higher for this service. The reason for this is that the accountancy industry has close relations to corporations, servicing their business needs. Therefore this ranking shows similarities with Table 8.1. As we can see, Moscow is still in the first stratum, followed by Kiev and St Petersburg in the second stratum and by Baku and Almaty in the third stratum. In the last stratum the other important cities are included: one is Tbilisi, the industrial, political and cultural centre of Georgia; and the other is Tashkent in Uzbekistan.

Table 8.3 Accountancy network connectivity of Eurasian cities. RANK

CITY

1 2 3 4 5 6 7

Moscow Kiev St Petersburg Baku Almaty Tbilisi Tashkent

GROSS CONNECTIVITY 24,107 18,918 13,920 8458 8310 6282 5548

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.60 0.47 0.34 0.21 0.21 0.16 0.14

Russia Ukraine Russia Azerbaijan Kazakhstan Georgia Uzbekistan

Compared with Table 8.3, there are no surprises in Table 8.4, which shows connectivities for advertising. Moscow is ranked first again; Kiev and Almaty are in the second stratum. St Petersburg is not strong in advertising according to this table. As an important port and the second largest city in Russia, St Petersburg is not attracting many of the world’s leading advertising companies to serve its industrial or business marketing. This also reflects the fact that these advertising firms tend to locate in capitals and media centres. The remaining cities are Tbilisi, Tashkent and Baku. In general, apart from Moscow, Eurasian cities are not important in advertising networks. A glance at Table 8.5 shows that the legal services network connectivities, as in other regions, are the most concentrated among advanced producer services. Strata are thus based on lower connectivities. Unsurprisingly Moscow is clearly the top city in the first stratum; St Petersburg and Almaty are ranked in the second stratum and Tbilisi and Baku are ranked in the third stratum. Kiev and Tashkent, both scoring zero, are ranked at the bottom of this table. Kiev is the big surprise: its legal services connections do not reflect its development as an important industrial, scientific, educational and cultural centre of Eastern Europe, which is clearly indicated in other fields such as accountancy and advertising.

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Table 8.4 Advertising network connectivity of Eurasian cities. RANK

CITY

1 2 3 4 5 6 7

Moscow Kiev Almaty St Petersburg Tbilisi Tashkent Baku

GROSS CONNECTIVITY 13,552 7957 5518 2589 1878 1740 1258

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK)

COUNTRY

0.65 0.38 0.27 0.12 0.09 0.08 0.06

Russia Ukraine Kazakhstan Russia Georgia Uzbekistan Azerbaijan

Table 8.5 Legal services network connectivity of Eurasian cities. RANK

CITY

1 2 3 4 5 6= 6=

Moscow St Petersburg Almaty Tbilisi Baku Kiev Tashkent

GROSS CONNECTIVITY 2472 626 470 324 302 0 0

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.50 0.13 0.10 0.07 0.06 0.00 0.00

Russia Russia Kazakhstan Georgia Azerbaijan Ukraine Uzbekistan

Table 8.6 measures the management consultancy connectivities of Eurasian cities, and shows that all seven cities are particularly weak in this area. Moscow, for example, although in first position again, scores only 0.38, which is its lowest score of all network connectivities. The other cities also reflect weak links in management consultancy. There are four cities with identically low scores – Almaty, St Petersburg, Tashkent and Tbilisi – and Kiev and Baku just above zero are ranked at the bottom. The geographical orientation results indicating the main dimensions of city hinterworlds are shown in Table 8.7. In terms of local concentration of connections (Table 8.7(a)), two cities (Moscow and Kiev with negative values) feature as most outward in their links, especially Moscow with its more global hinterworld. In contrast, Tashkent, Baku, Tbilisi, St Petersburg and Almaty tend to be very ‘local’ in their hinterworlds. Generally, connection with European and Pacific Asian cities (Tables 8.7(b) and(d)) is higher than with Northern American cities: links with Northern America are negative (Table 8.7(c)).

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Table 8.6 Management consultancy network connectivity of Eurasian cities. RANK

CITY

GROSS CONNECTIVITY

1 2= 2= 2= 2= 6 7

Moscow St Petersburg Almaty Tashkent Tbilisi Kiev Baku

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK)

COUNTRY

0.38 0.08 0.08 0.08 0.08 0.03 0.02

Russia Russia Kazakhstan Uzbekistan Georgia Ukraine Azerbaijan

4740 1026 1026 1026 1026 414 290

Table 8.7 City hinterworlds (regional concentrations of connections) of Eurasian cities. (a) Relative concentration of connections to local region. CITY Tashkent Baku Tbilisi St Petersburg Almaty

INWARD 0.71 0.70 0.59 0.57 0.37

CITY Moscow Kiev

OUTWARD −0.74 −0.05

(b) Relative concentration of connections to Europe. CITY Kiev Almaty Moscow St Petersburg

MORE EUROPEAN 2.20 2.11 1.84 0.15

CITY Tbilisi Tashkent Baku

LESS EUROPEAN −1.48 −1.32 −0.08

(c) Relative concentration of connections to Northern America. CITY

MORE NORTHERN AMERICAN

CITY Almaty St Petersburg Kiev Tashkent Moscow Baku Tbilisi

LESS NORTHERN AMERICAN −3.92 −2.51 −2.43 −2.40 −1.73 −1.39 −1.34

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(d) Relative concentration of connections to Pacific Asia. CITY Moscow Tashkent Almaty

MORE PACIFIC ASIAN 1.37 1.26 1.19

CITY Kiev St Petersburg Baku Tbilisi

LESS PACIFIC ASIAN −1.37 −0.71 −0.55 −0.37

Moscow is the global city in the CIS. It shows a high negative score with cities of its local region (i.e. Eurasia), but its connection to Northern America, only scoring −1.73, is unexpected (Table 8.7(c)). St Petersburg in contrast shows strong localism in its connectivities. The other important CIS city, Kiev, only has one positive score as high as Moscow and that is with European cities (Table 8.7(b)). Almaty features relative over-linkage to Europe and Pacific Asia; Tashkent links strongly to Pacific Asian cities. Baku and Tbilisi have stronger relative concentrations of links to Northern America than Moscow, which may be due to their oil industry and their roles as nodes in important transit routes for global energy and trade projects. In summary, it is clear that the entire Eurasian region, with only seven cities included here, has a lower level of world city network connectivity compared to most other world regions. As the top city both in Russia and Eurasia, Moscow always features the highest global connections. The strength of inter-city connections of the remaining cities is much lower. Patterns show little variation between different service sectors: Moscow and Kiev dominate most services, but other centres (St Petersburg and Almaty) feature as relatively important in accountancy and advertising. In terms of geographical orientation, some minor cities have distinctive hinterworlds; Moscow is highly over-linked to Pacific Asian and European cities; Kiev is strongly over-linked to European cities, whereas other cities remain generally under-linked outside Eurasia.

References Brade, I. and Rudolph, R. (2004) ‘Moscow, the global city? The position of the Russian capital within the European system of metropolitan areas’, Area, vol 36, pp69–80 Brunn, S. D. (2003) ‘A note on the hyperlinks of major Eurasian cities’, Eurasian Geography and Economics, vol 44, pp321–324 Derudder, B., Devriendt, L. and Witlox, F. (2007) ‘An empirical analysis of former Soviet cities in transnational airline networks’, Eurasian Geography and Economics, vol 48, pp95–110 EBRD (1995) Transition Report: Economic Transition in Eastern Europe and the Former Soviet Union, European Bank for Reconstruction and Development, London

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Graybill, J. K. and Mitchneck, B. A. (2008) ‘Cities of Russia’, in S. D. Brunn, M. Hays-Mitchell and D. J. Zeigler (eds) Cities of the World: World Regional Urban Development, 4th edition, Rowman & Littlefield, Lanham, MD, pp255–296 Interstate Statistical Committee of the CIS (2008) Countries of Eurasian Economic Community: Belarus, Kazakhstan, Kyrgyzstan, Russia, Tajikistan and Uzbekistan, Interstate Statistical Committee of the Commonwealth of Independent States, Moscow Taylor, P. J. (2004) World City Network: A Global Urban Analysis, Routledge, London

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South Asian Cities in Globalization Rolee Aranya, Pengfei Ni, Zixu Cheng and Jin Huang

The South Asian region is home to a large number of megacities as well as half the world’s poor population. If world city ranking was based solely on population and growth rates of population, then South Asian cities would emerge on top, but this is not true for a ranking based on integration into the world city network: limited presence of global service industry firms indicates a region of relatively low global competitiveness. Hence despite the large population, there are only 12 cities that qualify for discussion below by having global network connectivities above 0.1. Economies of the South Asian region have been late entrants into the contemporary global economy. Most of the countries in the region achieved independence from colonial rule in the mid 1940s, while Bangladesh attained sovereignty as late as 1971. Post independence, most countries of the region established protectionist trade regimes in order to develop domestic industry by promoting industrial modernization. Stagnant economies and large international debt necessitated structural adjustment programmes, which led to liberalization of the South Asian economies from the late 1980s onwards, albeit at a very slow and controlled pace. The region is still characterized as having undergone ‘fractured and fragmented globalization’, where trade, finance and international investment is restricted, and foreign investment is limited to selected sectors only (Weerakoon, 2004; Khan and Larik, 2007). Another aspect of the region’s limited global economic integration is the failure to establish a strong regional trade agreement under the auspices of the South Asian Association for Regional Cooperation (SAARC) established in 1985. Unlike successful trade agreements such as the Association of Southeast Asian Nations (ASEAN) in South East Asia, the European Economic Area (EEA) in the European Union and the North American Free Trade Agreement (NAFTA) in North America, even after several attempts a regional trade agreement has not brought about significant changes in intra-regional barriers to trade, or the development of a regional identity that could promote foreign direct investment

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(FDI) (Aggarwal, 2008). The slow regional integration in South Asia has challenged the efficacy of this as a growth strategy for the region (Weerakoon, 2004). Structural weaknesses, institutional bottlenecks, political movements, narrow nationalism and mutual mistrust are cited as some of the reasons for this lack of integration (Aggarwal, 2008, pii). India is the largest country in terms of population and also the largest economy in the region. The vast difference in the scale of global integration of the Indian economy as compared to the others in the region can be judged by the fact that, in 2006, India accounted for 75 per cent of the FDI inflows in South Asia, followed by Pakistan accounting for about 20 per cent, while Bangladesh, Sri Lanka, Nepal, Maldives and Bhutan together received the remaining 5 per cent (UNCTAD, 2007). Asian urbanization is characterized by rapidly growing megacities with large urban populations in absolute numbers but relatively low levels of urbanization (i.e. share of urban population to total population) (Dutt and Noble, 2003). India and Pakistan are the only two countries with a diverse urbanization pattern, while Nepal, Bangladesh and Sri Lanka display urban primacy where their capital cities – Kathmandu, Dhaka and Colombo, respectively – have over twice the population of the second ranking cities. India and Pakistan share a similar pattern where their capital cities (Delhi and Islamabad) are the political hubs while other cities (Mumbai and Karachi) are the financial centres and the largest cities in each country. Three sets of results are presented in this chapter as follows: first, the global network connectivities of the 12 cities are discussed; second, this connectivity measure is disaggregated into its service sector components (finance, accountancy, advertising, law and management consultancy) to provide specific service connectivities; and third, the ‘hinterworlds’ of the cities are explored in terms of whether they are over-linked or under-linked to the local region, or to the three main globalization arenas (Northern America, Europe and Pacific Asia). Gross network connectivities of the top 12 cities in the region (Table 9.1) are very telling of the economic and urbanization characteristics of the region. Seven of the 12 cities are Indian; three are Pakistani, with only one each from Bangladesh and Sri Lanka. This confirms the observations made earlier that India, being the leading economy in the region, has the largest number of cities with the highest connectivity that are included in this list. Mumbai in India and Karachi in Pakistan display higher network connectivities than the national capitals in the two countries, New Delhi and Islamabad. This illustrates their roles as dominant globally connected urban centres, as opposed to the capitals, the latter performing the function of political centres – albeit with high levels of concentration of business services as compared to other cities. Urban primacy and a limited urbanization pattern in Sri Lanka and Bangladesh lead to their capital cities, Colombo and Dhaka, also being the cities that have the highest connectivity in terms of global business services in their respective countries. The end result is a regional pattern of four strata. Mumbai constitutes the top stratum. With its banks, stock exchange and corporate

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headquarters all requiring advanced servicing, Mumbai is the city by far the most connected to the world city network in the region. With a large gap in connectivity to the second ranked city in Table 9.1, Mumbai is the region’s only current candidate for ‘global city’ status. In the second stratum there are three Indian cities plus Karachi, Pakistan’s commercial centre. The Indian cities include Delhi, the capital, Bangalore, the region’s IT centre, and Chennai. Perhaps surprisingly, Calcutta is in the third stratum where it is joined by the two ‘primate’ capital cities, Colombo and Dhaka; Pakistan’s capital city, Islamabad; plus India’s Hyderabad and Pakistan’s Lahore, both important commercial centres in their respective countries. Finally, the bottom stratum, like the top one, houses just a single city, Pune with its colleges, universities and associated IT firms quite close to Mumbai.

Table 9.1 Global network connectivity of South Asian cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12

Mumbai New Delhi Bangalore Karachi Chennai Calcutta Islamabad Colombo Lahore Hyderabad Dhaka Pune

GROSS CONNECTIVITY 57,902 39,540 34,418 30,705 27,488 22,656 20,044 18,695 18,484 18,190 17,741 12,703

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.60 0.41 0.36 0.32 0.29 0.24 0.21 0.19 0.19 0.19 0.18 0.13

India India India Pakistan India India Pakistan Sri Lanka Pakistan India Bangladesh India

The ranking presented in Table 9.2, based on the connectivity of financial services, confirms the position of Mumbai as a leading financial centre in the region. Isolating financial services in overall connectivity illustrates that Bangalore, ranked second, has a gross connectivity of only 42 per cent that of Mumbai, widening the gap as compared to Table 9.1. The other strata are similar to Table 9.1 except for the following: Chennai drops out of stratum two leaving just Bangalore, Delhi and Karachi, Pune rises into stratum three and replaces two Pakistani cities, Islamabad and Lahore, which drop into the bottom stratum. The content of the latter stratum illustrates the supremacy of Karachi as the leading financial capital in Pakistan. Overall, Mumbai is the only city that approximately maintains its relative position in financial connectivity; the scores of all other cities, except for Pune, are reduced in comparison with Table 9.1.

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Table 9.2 Financial services network connectivity of South Asian cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12

Mumbai Karachi Bangalore New Delhi Calcutta Chennai Colombo Pune Dhaka Hyderabad Lahore Islamabad

GROSS CONNECTIVITY 15,961 7113 6972 6232 4614 4432 4392 3959 3605 3582 2468 1914

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.59 0.26 0.26 0.23 0.17 0.16 0.16 0.15 0.13 0.13 0.09 0.07

India Pakistan India India India India Sri Lanka India Bangladesh India Pakistan Pakistan

In terms of the connectivity articulated through presence of accountancy service firms, Table 9.3 presents only a slightly different picture. Overall gross connectivity is more evenly spread out among the cities, and the large gap between Mumbai and the city coming in second place narrows as connectivity decreases more evenly down the ranks. Islamabad fares better in terms of accountancy networks, and Dhaka and Colombo fall towards the bottom of the list. It is interesting to note that average proportional connectivity for accountancy is higher than for financial services (Table 9.2) and overall connectivity (Table 9.1). This may be explained as a legacy of colonial links rather than simply contemporary globalization, since it is UK firms that dominate this sector in the world city network. When it comes to network connectivity articulated through advertising firms (Table 9.4), the pattern is similar to overall network connectivity. Mumbai leads the ranking but a large gap exists in the connectivity of the next highest city, New Delhi. Owing to the presence of national headquarters of most corporate firms (both domestic and international) in Mumbai, and the large entertainment industry, the concentration of the advertising industry in the city is easily understandable. However, its relative position to New York remains stable when it comes to advertising (Mumbai has 61 per cent of the connectivity of New York), similar to financial services and overall connectivity. The only non-Indian city that figures in the top five is Karachi, which again corresponds to it being the leading financial centre in Pakistan. Colombo and Dhaka fare better than their positions in terms of overall connectivity. Lahore is another city that shows higher connectivity related to advertising than its overall connectivity score.

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Table 9.3 Accountancy network connectivity of South Asian cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12

Mumbai New Delhi Bangalore Karachi Islamabad Calcutta Chennai Hyderabad Lahore Dhaka Colombo Pune

GROSS CONNECTIVITY 23,026 22,317 16,724 14,066 13,909 13,272 12,914 11,706 11,638 9800 8473 6760

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.57 0.55 0.41 0.35 0.34 0.33 0.32 0.29 0.29 0.24 0.21 0.17

India India India Pakistan Pakistan India India India Pakistan Bangladesh Sri Lanka India

Table 9.4 Advertising network connectivity of South Asian cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12

Mumbai New Delhi Bangalore Karachi Chennai Colombo Dhaka Calcutta Lahore Islamabad Hyderabad Pune

GROSS CONNECTIVITY 12,597 9038 7736 7526 6972 5830 4100 3540 3352 3195 2540 814

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK)

COUNTRY

0.61 0.44 0.37 0.36 0.34 0.28 0.20 0.17 0.16 0.15 0.12 0.04

India India India Pakistan India Sri Lanka Bangladesh India Pakistan Pakistan India India

Table 9.5 shows the legal services network connectivity of cities in the region. This is a most unusual table, recording zero connectivity for all but one city; the latter, Delhi, shows a minuscule score, presumably a result of only a subsidiary office of a global firm rather than any full fledged legal presence. This absence of global legal services firms in the region can be explained by the fact that foreign direct investment in legal services is still not permitted by national investment policies (see www.investmentcommission.in/policies_ and_laws.htm for details on policy in India, and www.pakboi.gov.pk for investment policies in Pakistan).

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Table 9.5 Legal services network connectivity of South Asian cities. RANK

CITY

1 2= 2= 2= 2= 2= 2= 2= 2= 2= 2= 2=

New Delhi Mumbai Bangalore Karachi Chennai Calcutta Islamabad Colombo Lahore Hyderabad Dhaka Pune

GROSS CONNECTIVITY 62 0 0 0 0 0 0 0 0 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

India India India Pakistan India India Pakistan Sri Lanka Pakistan India Bangladesh India

Network connectivities articulated through management consultancies in the region (Table 9.6) show a relatively low level of presence as compared to finance, accountancy, advertising and overall connectivity. Although Mumbai still emerges as the leader, its score drops about 12–18 per cent as compared to these other sectors (not including law). Chennai comes in second with only half of the connectivity of Mumbai. The high rank of Chennai as compared to the other sectors is at the cost of the lower connectivity of New Delhi, which falls to fifth position. The high rank of Chennai in terms of management consultancies may be accounted for by this city being an important port for export-related consumer industry. The poorest performers in this ranking are Dhaka and Colombo, which display negligible to zero connectivity in terms of management consultancies. In terms of the geographical orientation of connections among South Asian cities (Table 9.7), all cities with the exception of Mumbai are ‘over-linked’ with the local region (Table 9.7(a)). Thus, Mumbai maintains its position as an outlier in this analysis as well. Pune has the highest positive linkage to the local region, which may be due to the fact that it is the only Indian city in the list that is not a state capital: it owes its connectivity to being a secondary city to Mumbai in Maharashtra state. The ‘localness’ of Pune can be attributed to it being associated closely with Mumbai rather than South Asia as a whole.

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Table 9.6 Management consultancy network connectivity of South Asian cities. RANK

CITY

1 2 3 4 5 6 7 8= 8= 10 11 12

Mumbai Chennai Bangalore Karachi New Delhi Calcutta Pune Islamabad Lahore Hyderabad Dhaka Colombo

GROSS CONNECTIVITY 6318 3170 2986 2000 1891 1230 1170 1026 1026 362 236 0

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK)

COUNTRY

0.50 0.25 0.24 0.16 0.15 0.10 0.09 0.08 0.08 0.03 0.02 0.00

India India India Pakistan India India India Pakistan Pakistan India Bangladesh Sri Lanka

When it comes to extra-regional orientations of South Asian cities, it is notable that all except Pune are negatively connected (under-linked) to European cities (Table 9.7(b)), which reflects a breaking of the region’s earlier colonial links. The high over-linkage of Pune to Europe may only be a result of the disproportionate presence of European firms in a small sample indicated by its overall lowest level of gross network connectivity. Also, all cities with the exception of Chennai are negatively connected (relatively under-linked) towards Northern American cities (Table 9.7(c)). Mumbai and Bangalore have the lowest under-linkage to Northern America. The Northern American orientation of Bangalore and Chennai may be attributed to the linkages formed by the concentration in these cities of software and IT service firms from the US. It is surprising that Karachi, on the other hand, shows such high negative orientation to Northern America, while Islamabad is far less underlinked to Northern America. It would be expected that owing to the close political links between Pakistan and the US, the business links would be stronger. The very negative orientation of Colombo and Dhaka to Northern American networks is interesting to note. Orientation towards Pacific Asian cities is split evenly between positive and negative values (Table 9.7(d)). The top five cities – Mumbai, New Delhi, Bangalore, Karachi and Chennai – and Dhaka are all over-linked.

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Table 9.7 City hinterworlds (regional concentrations of connections) of South Asian cities. (a) Relative concentration of connections to local region. CITY Pune Hyderabad Dhaka Chennai Colombo Lahore Karachi Calcutta Bangalore New Delhi Islamabad

INWARD 1.86 1.83 1.45 1.23 1.18 1.14 1.02 1.02 0.83 0.72 0.64

CITY Mumbai

OUTWARD −0.20

(b) Relative concentration of connections to Europe. CITY

MORE EUROPEAN

Pune

1.47

CITY New Delhi Dhaka Islamabad Chennai Lahore Calcutta Karachi Bangalore Mumbai Hyderabad Colombo

LESS EUROPEAN −1.43 −1.38 −1.24 −1.10 −0.88 −0.85 −0.69 −0.68 −0.67 −0.30 −0.03

In conclusion, South Asian cities, with the exception of Mumbai, display low overall connectivity in terms of global business services. The leading sectors so far are finance and advertising, which set the trend for overall network connectivity among the cities. Strong policy control on foreign direct investment, limiting global integration to limited sectors of business services (legal services for example are still out of bounds for FDI in most South Asian economies), has ensured that the region is characterized by only moderate to low network connectivity. Strong urban primacy in Sri Lanka and Bangladesh and the small size of the economy has limited the scope for diversified network connectivity. India and Pakistan show trends of specialization emerging in the urban economy; however, so far the leading cities are Mumbai and Karachi respectively. The region is likely to be a dynamic one as intercity competition increases and the SAARC countries renew their resolve to establish a regional trade agreement.

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Table 9.7 Continued. (c) Relative concentration of connections to Northern America. CITY Chennai

MORE NORTHERN AMERICAN 0.22

CITY Dhaka Colombo Karachi Lahore Hyderabad New Delhi Pune Islamabad Calcutta Bangalore Mumbai

LESS NORTHERN AMERICAN −5.38 −4.37 −3.56 −2.84 −2.27 −1.61 −1.51 −0.77 −0.66 −0.50 −0.41

(d) Relative concentration of connections to Pacific Asia. CITY Mumbai Dhaka New Delhi Karachi Bangalore Chennai

MORE PACIFIC ASIAN 1.62 1.34 1.28 0.84 0.33 0.14

CITY Hyderabad Colombo Pune Lahore Calcutta Islamabad

LESS PACIFIC ASIAN −0.76 −0.64 −0.57 −0.24 −0.21 −0.12

References Aggarwal, A. (2008) Regional Economic Integration and FDI in South Asia: Prospects and Problems, Working Paper 218, Indian Council for Research on International Economic Relations, New Delhi Dutt, A. K. and Noble, A.G. (2003) ‘Urban development of South Asia’, in A. K. Dutt, A. G. Noble, G. Venugopal and S. Subbiah (eds) Challenges to Asian Urbanization in the 21st Century, Kluwer Academic Publishers, Dordrecht, pp255–276 Khan, H. A. and Larik, Z. (2007) Globalization and Regional Co-operation in South Asia: A Political and Social Economy Approach, CIRJE Discussion Papers, CIRJEF-480, Tokyo UNCTAD (2007) World Investment Report 2007, United Nations, Geneva Weerakoon, D. (2004) ‘Globalisation and South Asia: the role of foreign direct investment in economic development’, South Asian Survey, vol 11, pp3–19

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Middle East/North African Cities in Globalization David Bassens, Ben Derudder and Frank Witlox

City connectivity levels in the Middle Eastern/North African (MENA) region can be examined from three historically successive but overlapping and interwoven evolutions: 1

2

During colonial occupation (up to the 1970s in the Gulf region), the region was largely peripheral to the world economy and predominantly connected to its core regions (especially Europe) through colonial dependency linkages (see Stewart, 1997, on North Africa). From this historical perspective, the MENA region has only a limited number of world cities. However, colonial presence has shaped the urban tissue in various cities (e.g. les villes européennes in North African cities) and has created an urban system bypassing existing urban patterns, through a focus on the countries’ capital and, often, port cities, which enabled the extraction and transhipment of primary goods to the home country. The discovery of oil and emergence of oil-based economies – largely from the 1960s onward – has highlighted the crucial position of the MENA region and of Gulf cities in particular. Within oil-producing countries, high oil rents have fuelled rapid urbanization processes, such as in the Gulf countries of Bahrain, Qatar, Saudi Arabia and the UAE, with villages and smaller towns booming into cities of regional and global importance (e.g. Abu Dhabi, Dubai, Doha, Kuwait City, Manama and Riyadh). Within the MENA region, they have also shaped flows of workers (Malecki and Ewers, 2007) and remittances between oil-producing countries and the others (e.g. Egypt, Jordan and Iran), and they have fuelled urbanization in these countries (e.g. Amman and Cairo). Simultaneously, outside linkages (most notably with the US) have been shaped by the production and export of oil and the import of virtually all consumer goods in the countries on the Arabian Peninsula, hampering the emergence of a fully-fledged regional economy or regional urban network, although a number of urban

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networks (see Stanley, 2005) can be identified across various scales. In a move to diversify economies away from oil, there are distinct shifts towards service economies in which advanced producer services (APS) firms play a central role.

In general, most of the countries (except, for example, Libya and Iran) have opened up their economies to a certain extent and have embraced neoliberal orthodoxy. This is clearly mirrored in the city-building projects, led by citystates such as Dubai (Pacione, 2005; Davis, 2006). The Dubai model of urbanization portrays and develops cities as knowledge-rich and service-based economies, unhindered by juridical and fiscal barriers and driven by foreign direct investments. On a physical level, this model is constructed through massive urban developments (absorbing excess oil income) by which urban policymakers actively aim to market the city to tourists and investors alike. This entrepreneurial ‘urban growth machine’ model has also been exported outside the Gulf region and influences cities such as Amman, Beirut, Cairo and Rabat (see, for example, Zemni and Bogaert, 2009), and Tunis, as they become primary targets for rising Gulf investments. Simultaneously, as cities try to connect to the world, the ‘global city’ model in particular is gaining influence in the MENA region. Gulf cities invest heavily to become turntables in the world economy, in the field of either infrastructure, such as telecommunications and air travel (O’Connell, 2006), trade, for example through the development of major ports (Jacobs and Hall, 2007), or financial services (Bassens et al, 2010, 2011). The renewed geostrategic roles of Gulf cities such as Dubai can be read from their repositioning as trade hubs between West and East (a sort of new Silk Road). Furthermore, floating on oil money, Gulf cities are benefiting from a global shift in financial power, as sovereign wealth funds (SWFs) (e.g. ADI and KIA) cash in on the global financial crisis through corporate investment in western business and financial firms such as Citigroup and Barclays (Baghat, 2008). As a result of these processes, Gulf cities in particular are likely to grow in economic importance and connectivity in the future. This analysis considers the 17 best-connected MENA cities in terms of APS firm connectivity for the year 2008. As shown in Table 10.1, it is mostly Middle Eastern cities (which constitute 14 out of the 17) that link the region with the world economy; there are only three such ‘linking’ cities in North Africa, namely Cairo, Casablanca and Tunis. As a region within the Middle East, the Gulf makes a large contribution to the global network connectivity list, with as many as eight cities.

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Table 10.1 Global network connectivity of MENA cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Istanbul Tel Aviv Dubai Riyadh Cairo Kuwait City Jeddah Beirut Casablanca Manama Amman Doha Tunis Jerusalem Ankara Muscat Abu Dhabi

GROSS CONNECTIVITY 50,673 39,639 38,935 35,602 35,382 33,811 33,163 30,792 26,897 24,872 22,171 19,995 17,036 13,019 11,267 11,129 9348

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.53 0.41 0.40 0.37 0.37 0.35 0.34 0.32 0.28 0.26 0.23 0.21 0.18 0.14 0.12 0.12 0.10

Turkey Israel UAE Saudi Arabia Egypt Kuwait Saudi Arabia Lebanon Morocco Bahrain Jordan Qatar Tunisia Israel Turkey Oman UAE

In general, Istanbul stands out as the best connected city (0.53), followed by a number of gradually less connected cities throughout the region. Istanbul’s top position reflects its leading role in Turkey’s growing economy but also hints at its historical legacy as a ‘world city’ during both the Byzantine and Ottoman empires. More fundamentally, the strategic position of Istanbul between Europe and the Middle East makes it a key site for investment into either Europe or Asia. Istanbul’s bridging role in terms of economic integration mirrors the political rapprochement between Europe and Turkey, a candidate member of the EU. For ease of analysis, we distinguish four additional strata of cities. The second and third cities on the list are Tel Aviv and Dubai, respectively. Tel Aviv acts as Israel’s main gateway, bypassing its conflict-rich capital Jerusalem (rank 14). Dubai is growing as the main business and trade hub on the Arabian Peninsula, outbidding other cities in the Gulf. Dubai’s leading role – albeit before the current slowdown – is confirmed by its overall connectivity rank. A further stratum includes five moderately connected cities, including the Saudi Arabian cities Riyadh – the inland administrative and financial centre – and Jeddah – the older commercial and trade centre on the Red Sea shore. This stratum includes also Kuwait City, which is diversifying its oil economy towards services, and Cairo, the capital of the largest North African economy. Beirut’s rank shows that this former regional financial hub is recovering only

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slowly from decades of civil war and the 2006 conflict with Israel. Regaining its position will be a challenge given the growth of other international financial centres (IFCs) in the region, such as Dubai and Manama. The next stratum comprises four less connected cities. The ranking of the Gulf cities Manama and Doha shows that these cities are making a slow start in economic diversification. Manama, however, whose oil reserves are becoming depleted, is developing into a regional centre for conventional and Islamic (interest-free) financial services, absorbing excess income from the region. Casablanca is the best-connected city in Morocco, confirming its prime role as the country’s commercial capital. In Jordan, nearly all business and service firms use the capital Amman as the main gateway into the country, receiving the support of neoliberal Jordanian policy (Parker, 2009). The final stratum consists of five marginally connected cities. The low ranking of these cities is a result of either other well-connected cities in the immediate vicinity (e.g. Dubai for Abu Dhabi and Muscat) or another national city surpassing the country’s capital (e.g. Istanbul for Ankara). In the case of Jerusalem, the contestation of the urban arena has an obvious effect on the local business climate. The ranking of Tunis shows that although Tunisia is developing this city into a specialized and financial services centre, it is only slowly becoming linked up by APS firms. Table 10.2 shows the city connectivity ranking based only on financial services firms. Again, Istanbul is the undisputed leader, confirming its strategic importance as a gateway city (see Taylor, 2001) between Europe and the Middle East. From there, the ranking takes a different outlook, with Tel Aviv losing ground and a number of booming IFCs, mainly Gulf cities, gaining strength. After Istanbul, Dubai is the main financial hub for the region. The growth of Dubai as an IFC is related to its attractive legal and fiscal environment, the importance of the DIFC (Dubai International Financial Centre) as a hub between London and Hong Kong, and other forms of global integration (e.g. the growing stake of Borse Dubai in the Nasdaq and London Stock Exchange). The next stratum consists of Cairo and Manama, which can be considered regional financial centres. The rise of Manama as a regional offshore centre is related to the decline of Beirut after the outbreak of the Lebanese civil war in 1975, when investors sought a safe haven for their investments. Furthermore, Manama benefits from its strategic location on the Saudi Arabian shore, which makes it a logical offshore centre for Saudi investors. Nowadays, Manama is also developing into a hub for Islamic financial services, with many Islamic banks, insurance firms and a number of influential regulatory bodies (Hamouche, 2004; Bassens et al, 2010, 2011). Doha and Tel Aviv form the next stratum. The results for both cities are surprises: the latter’s relative low ranking (6th) is related to political uncertainties, and Doha is evolving into a financial centre for the Gulf region. In 2008, it became involved with the New York Stock Exchange, which bought a 25 per cent stake in the Doha securities market. The final stratum comprises

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a number of cities that take their financial importance mainly from their roles in the national economy.

Table 10.2 Financial services network connectivity of MENA cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Istanbul Dubai Manama Cairo Doha Tel Aviv Beirut Riyadh Abu Dhabi Tunis Amman Casablanca Muscat Kuwait City Jeddah Ankara Jerusalem

GROSS CONNECTIVITY 13,167 11,959 8691 8326 5799 5721 5157 4826 3060 2680 2486 2158 1449 1440 1066 420 0

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.49 0.44 0.32 0.31 0.21 0.21 0.19 0.18 0.11 0.10 0.09 0.08 0.05 0.05 0.04 0.02 0.00

Turkey UAE Bahrain Egypt Qatar Israel Lebanon Saudi Arabia UAE Tunisia Jordan Morocco Oman Kuwait Saudi Arabia Turkey Israel

The next four tables show how MENA cities are connected through the other advanced producer services. We make a distinction between the Londondominated (European) services, accountancy (Table 10.3) and legal (Table 10.5) services, and the typically American (New York-dominated) services, advertising (Table 10.4) and management consultancy (Table 10.6). First, concerning the London-dominated services, the common wideranging discrepancies between accountancy and legal services are also applicable within the MENA region. While accountancy services have a ubiquitous character, with firms servicing many cities in the MENA region, legal services are concentrated in a few cities (notably Dubai, Riyadh and Cairo). The accountancy ranking (Table 10.3) shows some remarkable results. Tel Aviv is at the top of the list; Istanbul is now second. Further down the list, Dubai is ranked surprisingly low in terms of accountancy connectivity, indicating its relative importance for other services (especially financial, legal and advertising services). Kuwait City, in contrast, boasts a far better ranking (3rd) when compared with its global network connectivity (6th).

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Table 10.3 Accountancy network connectivity of MENA cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Tel Aviv Istanbul Kuwait City Jeddah Riyadh Cairo Beirut Casablanca Amman Dubai Tunis Jerusalem Doha Ankara Manama Muscat Abu Dhabi

GROSS CONNECTIVITY 24,597 22,544 22,246 21,192 20,368 17,552 16,666 16,270 14,489 13,671 12,206 11,993 10,614 9143 8426 7532 4494

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.61 0.56 0.55 0.52 0.50 0.43 0.41 0.40 0.36 0.34 0.30 0.30 0.26 0.23 0.21 0.19 0.11

Israel Turkey Kuwait Saudi Arabia Saudi Arabia Egypt Lebanon Morocco Jordan UAE Tunisia Israel Qatar Turkey Bahrain Oman UAE

Legal services are provided in only eight MENA cities, with a distinct concentration in Dubai, Riyadh and Cairo. Dubai’s lead is related to its general role as a booming business and international trade hub, while Riyadh’s position obviously derives from the fact that it is the capital of the largest oil-producing country in the region. The other cities are only marginally connected, although they hold a certain influence as capital and administrative cities (Abu Dhabi, Ankara and Tunis) or important business centres (Casablanca and Istanbul). Turning to the typically American services, we note a similar discrepancy between the more ubiquitous advertising services and the rather more concentrated management consultancy services. Advertising firms are servicing the emerging MENA market from a large array of cities. This reflects the general growth of the urban middle class throughout the region, which is often characterized by American-style consumerism, and by many cities (e.g. Dubai) marketing themselves to the world as top destinations for luxury tourism or as sites for real estate investment. Table 10.4 shows that, indeed, below Istanbul, Gulf cities (Dubai, Jeddah, Kuwait City and Riyadh) are particularly well connected. There is also a clear relation with telecommunications infrastructure (e.g. in Dubai with its Media City and Internet City). The high ranking of Jeddah (3rd) over Riyadh (6th) derives from its substantially more liberal climate in conservative Saudi Arabia.

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Table 10.4 Advertising network connectivity of MENA cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16= 16=

Istanbul Dubai Jeddah Kuwait City Tel Aviv Riyadh Beirut Cairo Casablanca Manama Amman Doha Tunis Abu Dhabi Muscat Jerusalem Ankara

GROSS CONNECTIVITY 11,566 11,358 10,905 9099 8583 8404 7653 7326 6831 6005 4960 2556 2068 1402 1122 0 0

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK)

COUNTRY

0.56 0.55 0.53 0.44 0.41 0.40 0.37 0.35 0.33 0.29 0.24 0.12 0.10 0.07 0.05 0.00 0.00

Turkey UAE Saudi Arabia Kuwait Israel Saudi Arabia Lebanon Egypt Morocco Bahrain Jordan Qatar Tunisia UAE Oman Israel Turkey

Table 10.5 Legal services network connectivity of MENA cities. RANK

CITY

1 2 3 4 5 6 7 8 9= 9= 9= 9= 9= 9= 9= 9= 9=

Dubai Riyadh Cairo Abu Dhabi Casablanca Istanbul Ankara Tunis Tel Aviv Kuwait City Jeddah Beirut Manama Amman Doha Jerusalem Muscat

GROSS CONNECTIVITY 954 688 626 392 266 250 168 82 0 0 0 0 0 0 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.19 0.14 0.13 0.08 0.05 0.05 0.03 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

UAE Saudi Arabia Egypt UAE Morocco Turkey Turkey Tunisia Israel Kuwait Saudi Arabia Lebanon Bahrain Jordan Qatar Israel Oman

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In the case of management consultancy (Table 10.6), MENA cities are substantially less connected, and firms are more concentrated in a few cities, especially in Istanbul. Although Istanbul’s top ranking reflects its global connectivity rank, the rest of the list offers a few surprises. For instance, Dubai and Tel Aviv, top cities for global network connectivity (Table 10.1), are ranked very low (12th and 13th, respectively). In Israel, Tel Aviv is even surpassed by Jerusalem (joint 8th). Jeddah, which ranks 6th on the global connectivity list, is not serviced at all. On the other hand, Manama, Ankara and Casablanca are far more important than we would expect from a global network connectivity perspective. This shows that the geographical distribution of management consultancy services differs significantly from that of all other services.

Table 10.6 Management consultancy network connectivity of MENA cities. RANK

CITY

1 2 3 4 5 6= 6= 8= 8= 8= 8= 12 13 14 15= 15= 15=

Istanbul Manama Cairo Ankara Casablanca Riyadh Beirut Kuwait City Doha Jerusalem Muscat Dubai Tel Aviv Amman Jeddah Tunis Abu Dhabi

GROSS CONNECTIVITY 3146 1750 1552 1536 1372 1316 1316 1026 1026 1026 1026 993 738 236 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK)

COUNTRY

0.25 0.14 0.12 0.12 0.11 0.10 0.10 0.08 0.08 0.08 0.08 0.08 0.06 0.02 0.00 0.00 0.00

Turkey Bahrain Egypt Turkey Morocco Saudi Arabia Lebanon Kuwait Qatar Israel Oman UAE Israel Jordan Saudi Arabia Tunisia UAE

Table 10.7 provides further insight into the geographical dimensions of MENA city connectivities, distinguishing between local linkages and linkages to Northern America, the Asia Pacific and Europe. As illustrated in Table 10.7(a), the local connections of the MENA region show a balance between inward(positive values) and outward-oriented (negative values) cities. In general, outward cities rank high on global network connectivity (GNC) (e.g. Istanbul, Tel Aviv, Dubai and Cairo), indicating that these cities are indeed the most globalized ones. Vice versa, cities with low global network connectivity are generally oriented towards the local region. However, there are notable

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exceptions in both categories: although Jerusalem and Ankara have a low GNC, they are primarily outward. Jerusalem’s outward orientated character is indicative for its isolation from urban networks on an intra-regional level, for example with cities from the Arab world. By contrast, the well-connected cities Riyadh and Jeddah have a distinct inward character, a feature that is symptomatic of the relatively closed Saudi economy.

Table 10.7 City hinterworlds (regional concentrations of connections) of MENA cities. (a) Relative concentration of connections to local region. CITY Tunis Casablanca Amman Doha Abu Dhabi Kuwait City Jeddah Riyadh Beirut Cairo Manama Muscat Tel Aviv

INWARD 1.21 1.19 1.11 1.00 0.83 0.82 0.79 0.65 0.64 0.46 0.41 0.36 0.34

CITY Jerusalem Ankara Dubai Istanbul

OUTWARD −0.43 −0.40 −0.07 −0.07

(b) Relative concentration of connections to Europe. CITY Casablanca Dubai Abu Dhabi Istanbul Ankara Riyadh Cairo Kuwait City Jeddah Muscat Tunis

MORE EUROPEAN 2.34 2.10 1.92 1.71 1.59 1.23 0.53 0.33 0.23 0.13 0.08

CITY Jerusalem Doha Manama Amman Beirut Tel Aviv

LESS EUROPEAN −1.57 −0.55 −0.23 −0.17 −0.13 −0.13

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(c) Relative concentration of connections to Northern America. CITY Jerusalem Ankara

MORE NORTHERN AMERICAN 1.34 0.21

CITY Amman Dubai Kuwait City Cairo Casablanca Manama Jeddah Riyadh Istanbul Tunis Tel Aviv Doha Beirut Abu Dhabi Muscat

LESS NORTHERN AMERICAN −4.10 −3.31 −3.14 −3.02 −2.82 −2.64 −2.54 −2.30 −1.79 −1.76 −1.50 −1.36 −1.31 −0.91 −0.77

(d) Relative concentration of connections to Pacific Asia. CITY Manama Dubai Abu Dhabi Doha

MORE PACIFIC ASIAN 2.23 2.03 0.15 0.06

CITY Ankara Casablanca Kuwait City Jerusalem Amman Muscat Riyadh Jeddah Beirut Tel Aviv Tunis Cairo Istanbul

LESS PACIFIC ASIAN −2.63 −1.88 −1.75 −1.67 −1.66 −1.63 −1.50 −1.50 −1.29 −1.20 −1.09 −0.26 −0.04

We note that overall MENA cities are under-linked with Northern America (Table 10.7(c)). Only Jerusalem and Ankara have positive scores; these are capital cities of the USA’s two closest allies in the region. Other cities less under-linked are Tel Aviv and a number of capital cities along the Mediterranean (Beirut and Tunis) and along the Gulf (Abu Dhabi, Doha and Muscat). With regard to Pacific Asia (Table 10.7(d)), there are just four overlinked cities, two heavily so (the financial centres of Manama and Dubai) and two much less so (Abu Dhabi and Doha). The remaining cities are all under-

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linked to Pacific Asia with the most interesting contrast being between Istanbul, which is only marginally negative (−0.04) and its capital city Ankara, which records the lowest negative score (−2.63). MENA cities are most connected to their neighbouring region, Europe (Table 10.7(b)). As for Europe, Casablanca, Dubai, Istanbul and Abu Dhabi are the best-connected cities. For Casablanca, this reflects a strong colonial legacy (especially with France); however, Istanbul’s position is more a result of its historical and contemporary bridging function between Europe and the Middle East. As for the Gulf cities of Dubai and Abu Dhabi, it appears that globalization from the outside tends to be led by European agency and less by North American firms. This is a consequence of both geographical proximity and the more problematic status of American presence/interference in the wider Middle East following the events of 9/11 and the war in Iraq. Jerusalem stands out as the relatively least connected city to Europe. In summary, the outward character of MENA cities has different origins for different cities. In the cases of Jerusalem and Ankara, the outward linkages are mainly with Northern American cities. For Jerusalem, this is an obvious result of US involvement in Israel’s political and economic arena. On the other hand, Dubai is significantly over-linked with Europe and Pacific Asia, and Istanbul and Cairo are relatively orientated in this manner. This supports the idea that a number of well-connected Middle Eastern cities are becoming intermediaries between the old European core and the booming Pacific Asian cities. We conclude that although the number of well-connected cities is rather small, the MENA region is in fact becoming increasingly integrated into the world economy (compare with Taylor, 2001). This integration is a result of the changing role of the region (and particularly the Gulf) in a world economy that is shifting towards the East. On the one hand, integration in the world economy is still driven by (neo)-colonial dependency linkages with the old core (Europe and North America), related to enduring oil-based economies. However, the growing importance of APS shows that a qualitative change in MENA economies, away from oil dependency, is gaining ground. The number of cities that have actually succeeded in making this shift remains, however, small. Istanbul leads the MENA region, although it increasingly appears to be becoming a ‘European’ city, through its strong linkages with European-based firms. There are a number of booming cities, almost exclusively from the Gulf region, which have climbed up the regional ranks either as all-round cities (Dubai) or as specialized financial centres (e.g. Manama). On the African continent, Cairo is becoming the main hub for advanced servicing. In light of the hinterworld analysis, the MENA region’s newly critical position between Europe and the Asia Pacific proves to be an engine for service-based urban economies and further integration into the world economy. In a way, this repositioning reflects a shift of financial power towards a number of Gulf citystates, for instance through the growing importance of SWFs as ‘lenders of the last resort’ in the current financial crisis. To what extent these evolutions will

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influence cities and urban networks in the MENA region in the future remains, however, an open question.

References Baghat, G. (2008) ‘Sovereign wealth funds: dangers and opportunities’, International Affairs, vol 84, pp1189–1204 Bassens, D., Derudder, B. and Witlox, F. (2010) ‘Searching for the Mecca of finance: Islamic financial services and the world city network’, Area, vol 42, pp35–46 Bassens, D., Derudder, B. and Witlox, F. (2011) ‘Oiling global capital accumulation: analyzing the principles, practices and geographical distribution of Islamic financial services’, Service Industries Journal, vol 31, forthcoming Davis, M. (2006) ‘Fear and money in Dubai’, New Left Review, vol 41, pp47–67 Hamouche, M. B. (2004) ‘The changing morphology of the gulf cities in the age of globalisation: the case of Bahrain’, Habitat International, vol 28, pp521–540 Jacobs, W. and Hall, P. V. (2007) ‘What conditions supply chain strategies for ports? The case of Dubai’, GeoJournal, vol 68, pp327–342 Malecki, E. J. and Ewers, M. C. (2007) ‘Labor migration to world cities: with a research agenda for the Arab Gulf’, Progress in Human Geography, vol 31, pp467–484 O’Connell, J. F. (2006) ‘The changing dynamics of the Arab Gulf based airlines and an investigation into the strategies that are making Emirates into a global challenger’, World Review of Intermodal Transportation Research, vol 1, pp94–114 Pacione, M. (2005) ‘City profile: Dubai’, Cities, vol 22, pp255–265 Parker, C. (2009) ‘Tunnel-bypasses and minarets of capitalism: Amman as neoliberal assemblage’, Political Geography, vol 28, pp110–120 Stanley, B. (2005) ‘Middle East city networks and the “new urbanism”’, Cities, vol 22, pp189–199 Stewart, D. J. (1997) ‘African urbanization: dependent linkages in a global economy’, Tijdschrift voor Economische en Sociale Geografie, vol 88, pp251–261 Taylor, P. J. (2001) ‘West Asian/North African cities in the world city network: a global analysis of dependence, integration and autonomy’, The Arab World Geographer, vol 4, pp146–159 Zemni, S. and Bogaert, K. (2009) ‘Trade, security and neoliberal politics: wither Arab reform? Evidence from the Moroccan case’, The Journal of North African Studies, vol 14, pp91–107

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11

European Cities in Globalization Peter J. Taylor, Ben Derudder, Michael Hoyler, Kathy Pain and Frank Witlox

More cities qualify for inclusion in this regional chapter than for any other. There are three broad historical reasons for this: 1

2

3

Western Europe was the cradle of the modern world-system and has continued to be one of the most important regions (in the ‘core’) of the world economy over several centuries. Therefore its cities have long traditions of ‘outside links’ involving both trading and empire-building. Hence the region and its cities have been at the forefront of the processes creating contemporary globalization, the latest phase of the worldeconomy development. The result is that 28 of the 74 cities that are treated in this chapter have strong imperial histories. Throughout the 20th century the number of states in Europe has increased, starting with the breakup of the Austro-Hungarian and German Empires after World Wars I and II, and culminating in a new bout of state-making in the aftermath of the ending of the Cold War. Thus Europe has become a continent of many states each with a capital city. Such cities have special service needs for their government functions as well as very often serving as gateways to their local national economy. The result is that 30 of the 74 cities are capital cities, both old and new. The economic globalization of the 1990s was stimulated to an important degree by the demise of the Communist states of Eastern Europe and their conversion to neo-liberal economic regimes. This provided new market opportunities for global service firms, as it facilitated the sale of state assets and the creation of new economic institutions. Foreign banks, law firms, accountancy firms and management consultancies rushed to set up offices in the major cities in this new capitalist world to take advantage of the unique circumstances. The result is that 17 of the 74 cities are from former Communist states.

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Note that the most important political process of recent European history – the rise of the institutional complex currently named the European Union (EU) – does not feature in this list of reasons for the large number of European cities included in this chapter. Although it can be argued that the EU has provided the general economic framework for the region’s cities to prosper, cities as economic units have been largely neglected in policy circles until fairly recently (Berg et al, 2007) and the ‘European spatial planning’ of late (Faludi, 2002) has only very recently begun to address questions of globalization, largely as international competitiveness. Thus although the EU now stretches across most of Europe from the Atlantic to the Black Sea, it has had little direct effect on European cities except where its major institutions are located: Brussels as ‘capital of Europe’ (Baeten, 2001; Elmhorn, 2001; Groof, 2008), and to a much lesser extent, Luxembourg, Strasbourg and Frankfurt. The evidence provided in this chapter consists of three sets of results: 1

2

3

The cities with global network connectivities above 0.1 define the 74 cities that are analysed throughout the chapter. These cities are ranked from 1 to 74 but emphasis in discussion is on the upper echelons of the list. Using the actual connectivity proportions, gaps in these values are employed to identify six strata of cities among the top 25 ranks; these are designated the ‘leading’ European cities in the world city network. The city connectivities are disaggregated by service sector producing five new rankings (for financial services, accountancy, advertising, legal services and management consultancy). These are treated in the same way as the gross connectivities: strata are identified in the upper echelons of ranks as leading cities in each sector. City connectivities are disaggregated by geographical orientation, showing over- or under-linkage locally (to other European cities), and over- or under-linkage to the other main globalization arenas, to Northern American cities and to Pacific Asian cities. These results show a city’s ‘hinterworld’: the pattern of its links to other cities in the world city network. Below they are presented as standardized scores with positive values indicating over-linkage and negative values under-linkage. In these results the focus is upon cities with values greater than 1 or less than −1.

The 74 cities are ranked by their global network connectivities in Table 11.1. As already known, London is on a par with New York and, within Europe, Paris is in a class of its own below London. Beyond these unsurprising results, the top 25 cities display a further four strata that do constitute new results for understanding contemporary European cities. Below Paris, the cities of Milan, Madrid and Brussels form a distinctive stratum with global network connectivities around two-thirds of the maximum. Brussels is not a surprise but having two southern European cities at this level is certainly less predictable. In the next stratum, Warsaw, Zurich, Amsterdam, Dublin and Rome are to be found: they represent, in order, the post-Communist rise of an Eastern

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European city, two important traditional financial centres, one of the major success stories of globalization, and the capital city of one of Europe’s four largest countries. The next stratum continues with a mix of capital cities of medium-sized countries (Lisbon, Stockholm, Vienna and Athens), including two from the former communist east (Budapest and Prague), plus Frankfurt. The latter, another traditional financial centre, is interesting as it is Germany’s first ranked city in terms of global network connectivity. Germany has by far the largest economy in Europe but has no city in the top ten in Table 11.1, reflecting the country’s very ‘horizontal’ urban hierarchy, relating to its federal political structure and the fact that its capital city, Berlin, was a divided city during the Cold War and has yet to fully recover economically (Cochrane and Jonas, 1999; Krätke 2001; see Chapter 19). Berlin appears in the next stratum along with: 1 2 3

other political capitals of much smaller countries (Helsinki, Oslo and Copenhagen) including another from the east (Bucharest); another German city (Hamburg); another traditional financial centre (Geneva).

Although strata are not identified below this level, note that there are three other German cities (Munich, Düsseldorf and Stuttgart) ranked in the next seven cities in Table 11.1 reinforcing the fact of Germany’s horizontal urban structure.

Table 11.1 Global network connectivity of European cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

London Paris Milan Madrid Brussels Warsaw Zurich Amsterdam Dublin Rome Lisbon Frankfurt Stockholm Prague Vienna Budapest

GROSS CONNECTIVITY 96,267 75,322 65,988 62,599 60,253 53,880 53,197 53,105 52,062 50,604 49,831 48,165 47,414 46,808 46,574 46,420

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 1.00 0.78 0.69 0.65 0.63 0.56 0.55 0.55 0.54 0.53 0.52 0.50 0.49 0.49 0.48 0.48

COUNTRY

UK France Italy Spain Belgium Poland Switzerland Netherlands Ireland Italy Portugal Germany Sweden Czech Republic Austria Hungary

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17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59= 59= 61

Athens Barcelona Bucharest Oslo Berlin Helsinki Geneva Copenhagen Hamburg Luxembourg Munich Düsseldorf Sofia Nicosia Bratislava Stuttgart Zagreb Ljubljana Antwerp Rotterdam Manchester Riga Edinburgh Porto Tallinn Birmingham Vilnius Glasgow Lyon Leeds Belgrade Bristol Bologna Cologne Lausanne Belfast Kraków Basel Newcastle Reykjavik Valencia Leipzig Aberdeen Dresden Marseille

46,068 40,866 38,648 38,043 37,825 37,672 36,928 35,764 35,574 34,424 33,482 30,575 30,418 29,810 28,399 26,295 25,340 24,053 22,482 22,188 21,525 21,067 20,588 20,536 20,374 19,995 18,442 17,884 16,861 16,720 16,096 15,166 15,121 14,499 14,195 12,919 12,844 12,481 12,208 12,184 11,972 11,762 11,628 11,628 11,501

0.48 0.42 0.40 0.40 0.39 0.39 0.38 0.37 0.37 0.36 0.35 0.32 0.32 0.31 0.30 0.27 0.26 0.25 0.23 0.23 0.22 0.22 0.21 0.21 0.21 0.21 0.19 0.19 0.18 0.17 0.17 0.16 0.16 0.15 0.15 0.13 0.13 0.13 0.13 0.13 0.12 0.12 0.12 0.12 0.12

Greece Spain Romania Norway Germany Finland Switzerland Denmark Germany Luxembourg Germany Germany Bulgaria Cyprus Slovakia Germany Croatia Slovenia Belgium Netherlands UK Latvia UK Portugal Estonia UK Lithuania UK France UK Serbia UK Italy Germany Switzerland UK Poland Switzerland UK Iceland Spain Germany UK Germany France

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Table 11.1 Global network connectivity of European cities (continued). RANK

CITY

62 63 64 65 66 67 68 69 70 71 72 73 74

Liverpool Southampton Seville Skopje Strasbourg Genoa Utrecht Bremen Nantes Cardiff Hannover Arhus Turin

GROSS CONNECTIVITY 11,410 10,678 10,440 10,366 10,316 10,016 9928 9916 9650 9574 9390 9350 9256

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.12 0.11 0.11 0.11 0.11 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10

UK UK Spain Macedonia France Italy Netherlands Germany France UK Germany Denmark Italy

In Table 11.2 city connectivities based just upon the financial services firms are used to rank the cities. This shows distinctive differences from the general ranking (Table 11.1). There are 20 cities that stand out as ‘international financial centres’ in Europe and the top two stay as before but with Paris somewhat closer to London in this list. The third stratum still includes Madrid and Milan but Brussels now drops below this level. The big mover is Frankfurt, up from 12 to 5 in the ranking, which joins Zurich in the fourth stratum. These six cities are Europe’s leading financial centres. The next stratum includes Brussels with Europe’s fastest rising financial centre (Dublin) and Europe’s traditional financial centre, Amsterdam. The remaining strata include capital cities of medium-sized states plus two smaller but important financial centres (Geneva and Luxembourg) plus one of Germany’s powerhouse economic cities (Munich). To reinforce the point about Germany’s horizontal structure and the limited economic success of post-Cold War Berlin, this capital city does not feature in the top 20. One final point: it is, perhaps, ironic that Reykjavik, ranked last in this list and without the presence of any leading financial institutions, is the city (and with it, its country, Iceland) brought down by its domestic banks in the recent financial crisis (Derudder et al, 2010).

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Table 11.2 Financial services network connectivity of European cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

London Paris Madrid Milan Frankfurt Zurich Brussels Amsterdam Dublin Warsaw Stockholm Geneva Luxembourg Prague Athens Lisbon Rome Budapest Vienna Munich Berlin Bucharest Barcelona Düsseldorf Bratislava Birmingham Nicosia Edinburgh Sofia Stuttgart Hamburg Basel Cologne Manchester Copenhagen Antwerp Oslo Rotterdam Bristol Helsinki

GROSS CONNECTIVITY 26,979 21,317 18,909 18,814 16,358 16,164 15,364 15,009 14,992 13,374 11,964 11,546 11,159 10,735 10,652 10,393 9477 8971 8513 7939 6234 5968 5802 5474 5276 5150 4662 4626 4394 4355 4319 4301 4234 4173 4144 4054 3780 3633 3547 3459

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 1.00 0.79 0.70 0.70 0.61 0.60 0.57 0.56 0.56 0.50 0.44 0.43 0.41 0.40 0.39 0.39 0.35 0.33 0.32 0.29 0.23 0.22 0.22 0.20 0.20 0.19 0.17 0.17 0.16 0.16 0.16 0.16 0.16 0.15 0.15 0.15 0.14 0.13 0.13 0.13

COUNTRY

UK France Spain Italy Germany Switzerland Belgium Netherlands Ireland Poland Sweden Switzerland Luxembourg Czech Republic Greece Portugal Italy Hungary Austria Germany Germany Romania Spain Germany Slovakia UK Cyprus UK Bulgaria Germany Germany Switzerland Germany UK Denmark Belgium Norway Netherlands UK Finland

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Table 11.2 Financial services network connectivity of European cities (continued). RANK

CITY

41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64= 64= 64= 67 68= 68= 70 71 72 73 74

Glasgow Bologna Newcastle Leeds Lyon Valencia Bremen Turin Genoa Cardiff Liverpool Porto Seville Leipzig Southampton Aberdeen Vilnius Utrecht Zagreb Riga Kraków Belfast Lausanne Marseille Strasbourg Nantes Tallinn Dresden Hannover Belgrade Arhus Ljubljana Skopje Reykjavik

GROSS CONNECTIVITY 3060 2720 2644 2470 2346 2106 2028 1976 1878 1844 1826 1792 1720 1686 1668 1634 1598 1534 1529 1346 1314 1276 1260 1068 1068 1068 1022 1016 1016 994 832 416 226 0

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.11 0.10 0.10 0.09 0.09 0.08 0.08 0.07 0.07 0.07 0.07 0.07 0.06 0.06 0.06 0.06 0.06 0.06 0.06 0.05 0.05 0.05 0.05 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.03 0.02 0.01 0.00

UK Italy UK UK France Spain Germany Italy Italy UK UK Portugal Spain Germany UK UK Lithuania Netherlands Croatia Latvia Poland UK Switzerland France France France Estonia Germany Germany Serbia Denmark Slovenia Macedonia Iceland

The next four tables show city connectivity rankings for the other advanced producer services. They can be divided into two sets: in accountancy (Table 11.3) and legal services (Table 11.5), London is the global leader and therefore dominates other European cities in these sectors; advertising (Table 11.4) and

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management consultancy (Table 11.6) are archetypal American contributions to the professional services and therefore New York dominates globally. In these cases Paris joins with London as the top European stratum of cities.

Table 11.3 Accountancy network connectivity of European cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

London Milan Paris Brussels Lisbon Rome Berlin Madrid Oslo Barcelona Vienna Dublin Warsaw Zurich Hamburg Athens Bucharest Prague Luxembourg Amsterdam Geneva Budapest Nicosia Helsinki Copenhagen Stockholm Sofia Porto Frankfurt Antwerp Rotterdam Stuttgart Bratislava Ljubljana Munich

GROSS CONNECTIVITY 40,442 27,089 26,839 23,937 23,095 23,072 22,630 22,597 22,425 22,204 21,315 20,870 20,661 20,209 20,090 20,076 19,545 19,509 19,190 19,179 19,119 18,887 18,714 18,184 17,080 16,246 16,224 15,859 15,552 14,884 14,751 14,732 14,209 13,916 13,689

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 1.00 0.67 0.66 0.59 0.57 0.57 0.56 0.56 0.55 0.55 0.53 0.52 0.51 0.50 0.50 0.50 0.48 0.48 0.47 0.47 0.47 0.47 0.46 0.45 0.42 0.40 0.40 0.39 0.38 0.37 0.36 0.36 0.35 0.34 0.34

COUNTRY

UK Italy France Belgium Portugal Italy Germany Spain Norway Spain Austria Ireland Poland Switzerland Germany Greece Romania Czech Republic Luxembourg Netherlands Switzerland Hungary Cyprus Finland Denmark Sweden Bulgaria Portugal Germany Belgium Netherlands Germany Slovakia Slovenia Germany

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Table 11.3 Accountancy network connectivity of European cities (continued). RANK

CITY

36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74

Zagreb Düsseldorf Manchester Lyon Edinburgh Glasgow Riga Lausanne Birmingham Tallinn Bologna Leeds Kraków Bristol Dresden Vilnius Valencia Leipzig Belgrade Belfast Newcastle Reykjavik Marseille Arhus Bremen Liverpool Hannover Southampton Strasbourg Genoa Cologne Aberdeen Basel Utrecht Nantes Seville Cardiff Skopje Turin

GROSS CONNECTIVITY 13,419 12,656 12,398 11,505 11,416 11,350 11,324 11,121 10,629 10,552 10,073 10,060 9390 9363 9234 9094 8898 8866 8380 8352 8146 8103 7797 7520 7448 7152 6986 6902 6768 6686 6552 6416 6262 6042 5946 5912 5570 5074 4816

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.33 0.31 0.31 0.28 0.28 0.28 0.28 0.27 0.26 0.26 0.25 0.25 0.23 0.23 0.23 0.22 0.22 0.22 0.21 0.21 0.20 0.20 0.19 0.19 0.18 0.18 0.17 0.17 0.17 0.17 0.16 0.16 0.15 0.15 0.15 0.15 0.14 0.13 0.12

Croatia Germany UK France UK UK Latvia Switzerland UK Estonia Italy UK Poland UK Germany Lithuania Spain Germany Serbia UK UK Iceland France Denmark Germany UK Germany UK France Italy Germany UK Switzerland Netherlands France Spain UK Macedonia Italy

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Table 11.4 Advertising network connectivity of European cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

London Paris Warsaw Brussels Athens Stockholm Madrid Milan Budapest Vienna Helsinki Lisbon Amsterdam Copenhagen Bucharest Rome Prague Dublin Zurich Sofia Ljubljana Barcelona Tallinn Zagreb Frankfurt Riga Oslo Vilnius Belgrade Bratislava Düsseldorf Hamburg Nicosia Skopje Berlin Munich Geneva Reykjavik Stuttgart Manchester

GROSS CONNECTIVITY 15,538 15,519 13,092 12,913 12,552 12,535 12,398 12,395 11,916 11,645 11,433 11,277 10,992 10,788 10,711 10,571 10,464 10,248 9445 8710 8043 8026 7774 7674 7416 7229 7219 6724 6722 6404 5808 5753 5172 5066 4713 4462 3771 2819 2748 2572

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK) 0.75 0.75 0.63 0.62 0.60 0.60 0.60 0.60 0.57 0.56 0.55 0.54 0.53 0.52 0.52 0.51 0.50 0.49 0.46 0.42 0.39 0.39 0.37 0.37 0.36 0.35 0.35 0.32 0.32 0.31 0.28 0.28 0.25 0.24 0.23 0.22 0.18 0.14 0.13 0.12

COUNTRY

UK France Poland Belgium Greece Sweden Spain Italy Hungary Austria Finland Portugal Netherlands Denmark Romania Italy Czech Republic Ireland Switzerland Bulgaria Slovenia Spain Estonia Croatia Germany Latvia Norway Lithuania Serbia Slovakia Germany Germany Cyprus Macedonia Germany Germany Switzerland Iceland Germany UK

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Table 11.4 Advertising network connectivity of European cities (continued). RANK

CITY

41 42 43 44 45 46 47= 47= 49= 49= 51 52 53 54 55 56 57 58= 58= 60= 60= 62 63 64= 64= 64= 67= 67= 67= 67= 67= 67= 67= 67=

Turin Cologne Luxembourg Edinburgh Seville Lyon Marseille Nantes Glasgow Cardiff Antwerp Strasbourg Leeds Rotterdam Porto Arhus Valencia Belfast Aberdeen Birmingham Basel Bologna Bremen Lausanne Genoa Utrecht Bristol Kraków Newcastle Leipzig Dresden Liverpool Southampton Hannover

GROSS CONNECTIVITY 2328 1994 1678 1574 1542 1438 1248 1248 1134 1134 973 908 866 792 777 636 606 604 604 530 530 490 440 426 426 426 0 0 0 0 0 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK)

COUNTRY

0.11 0.10 0.08 0.08 0.07 0.07 0.06 0.06 0.05 0.05 0.05 0.04 0.04 0.04 0.04 0.03 0.03 0.03 0.03 0.03 0.03 0.02 0.02 0.02 0.02 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Italy Germany Luxembourg UK Spain France France France UK UK Belgium France UK Netherlands Portugal Denmark Spain UK UK UK Switzerland Italy Germany Switzerland Italy Netherlands UK Poland UK Germany Germany UK UK Germany

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Table 11.5 Legal services network connectivity of European cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11= 11= 13 14 15 16 17 18 19 20 21 22 23= 23= 23= 26 27 28 29 30 31= 31= 31= 31= 31= 36= 36= 38= 38= 38=

London Paris Frankfurt Brussels Amsterdam Munich Milan Madrid Warsaw Düsseldorf Prague Budapest Rome Hamburg Vienna Antwerp Stockholm Berlin Bratislava Cologne Barcelona Bucharest Sofia Zagreb Edinburgh Zurich Oslo Luxembourg Stuttgart Dresden Manchester Birmingham Glasgow Leeds Liverpool Geneva Bologna Lyon Bristol Leipzig

GROSS CONNECTIVITY 4934 3442 2931 2640 1965 1950 1911 1836 1657 1581 1538 1538 1470 1248 1169 1143 1140 984 944 825 644 528 508 508 508 486 483 463 360 352 324 324 324 324 324 302 302 184 184 184

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 1.00 0.70 0.59 0.54 0.40 0.40 0.39 0.37 0.34 0.32 0.31 0.31 0.30 0.25 0.24 0.23 0.23 0.20 0.19 0.17 0.13 0.11 0.10 0.10 0.10 0.10 0.10 0.09 0.07 0.07 0.07 0.07 0.07 0.07 0.07 0.06 0.06 0.04 0.04 0.04

COUNTRY

UK France Germany Belgium Netherlands Germany Italy Spain Poland Germany Czech Republic Hungary Italy Germany Austria Belgium Sweden Germany Slovakia Germany Spain Romania Bulgaria Croatia UK Switzerland Norway Luxembourg Germany Germany UK UK UK UK UK Switzerland Italy France UK Germany

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Table 11.5 Legal services network connectivity of European cities (continued). RANK

CITY

38= 38= 38= 38= 45 46 47 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48= 48=

Aberdeen Seville Strasbourg Utrecht Helsinki Turin Lisbon Dublin Athens Copenhagen Nicosia Ljubljana Rotterdam Riga Porto Tallinn Vilnius Belgrade Lausanne Belfast Kraków Basel Newcastle Reykjavik Valencia Marseille Southampton Skopje Genoa Bremen Nantes Cardiff Hannover Arhus

GROSS CONNECTIVITY 184 184 184 184 168 136 132 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.04 0.04 0.04 0.04 0.03 0.03 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

UK Spain France Netherlands Finland Italy Portugal Ireland Greece Denmark Cyprus Slovenia Netherlands Latvia Portugal Estonia Lithuania Serbia Switzerland UK Poland Switzerland UK Iceland Spain France UK Macedonia Italy Germany France UK Germany Denmark

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The two London-dominated services are, however, very different in all other respects. Accountancy is the most ubiquitous of the services treated in this analysis and legal services are the most concentrated. This creates contrasting city service structures: accountancy is much ‘flatter’ than law. For instance, Berlin is treated as outside the leading cities for law in Table 11.5 despite ranking 18th and with a connectivity level of 0.2; at the same connectivity level in Table 11.3, Newcastle ranks a lowly 56th! In the concentrated legal services pattern, the stratum below Paris reflects the cities that are major legal centres: Brussels attracts law firms for its political market (the ‘capital of Europe’) and Frankfurt for its financial market. The remaining leading cities in a set of only 13 in Table 11.5 include major financial and economic centres (there are two other German cities, Munich and Düsseldorf) and capital cities, especially featuring Eastern Europe (Warsaw, Budapest and Prague), where global law firms found much work facilitating the transition to capitalism in the 1990s. Although also featuring Paris and Brussels in the second and third strata, accountancy connectivities show a different patterning of cities: Milan, for instance, is ranked above Paris in the second stratum. But this difference can be seen best in the third stratum which includes, with Brussels, Berlin. This is the only table where Germany’s capital city is ranked above all other German cities. Otherwise the accountancy rankings exhibit a mixed bag of cities with no discernible pattern. For the two New York-dominated services, Paris joins London in the top stratum as previously noted and this is due to the relatively low level of London’s connectivities for these services: London drops to Paris’s general level rather than vice versa (Table 11.4 and 11.6). Below these two cities, advertising has a more concentrated pattern that is dominated by capital cities, or more generally by cities with TV stations that are the main market for this service (Table 11.4). Management consultancies’ ‘flatter’ structure of connectivities (Table 11.6) tends to mirror the financial services connectivities (Table 11.2) with its mixture of financial centres and capital cities. One final point on these various service connectivities: the horizontal nature of Germany’s city hierarchy has been mentioned on several occasions above: the converse of this is the UK and France. Their capital cities always appear in the top two strata but no other city from either country appears in any list of leading cities right down to the lowest stratum identified. This is a classic example of historical path dependence: for all the upheaval of globalization these two national primate city structures continue to feature very strongly locally within the world city network.

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Table 11.6 Management consultancy network connectivity of European cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36= 36= 36= 39 40

London Paris Zurich Madrid Rome Amsterdam Dublin Frankfurt Milan Stockholm Munich Brussels Budapest Warsaw Düsseldorf Lisbon Prague Helsinki Barcelona Hamburg Oslo Stuttgart Vienna Copenhagen Birmingham Berlin Rotterdam Leeds Aberdeen Athens Belfast Edinburgh Zagreb Geneva Kraków Porto Liverpool Southampton Bristol Manchester

GROSS CONNECTIVITY 8374 8205 6893 6859 6014 5960 5952 5908 5779 5529 5442 5399 5108 5096 5056 4934 4562 4428 4190 4164 4136 4100 3932 3752 3362 3264 3012 3000 2790 2788 2687 2464 2210 2190 2140 2108 2108 2108 2072 2058

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK) 0.67 0.65 0.55 0.55 0.48 0.47 0.47 0.47 0.46 0.44 0.43 0.43 0.41 0.41 0.40 0.39 0.36 0.35 0.33 0.33 0.33 0.33 0.31 0.30 0.27 0.26 0.24 0.24 0.22 0.22 0.21 0.20 0.18 0.17 0.17 0.17 0.17 0.17 0.16 0.16

COUNTRY

UK France Switzerland Spain Italy Netherlands Ireland Germany Italy Sweden Germany Belgium Hungary Poland Germany Portugal Czech Republic Finland Spain Germany Norway Germany Austria Denmark UK Germany Netherlands UK UK Greece UK UK Croatia Switzerland Poland Portugal UK UK UK UK

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41 42 43 44 45 46 47 48 49 50= 50= 50= 50= 50= 50= 50= 57= 57= 59 60 61= 61= 61= 61= 61= 61= 67 68 69= 69= 71= 71= 71= 71=

Glasgow Luxembourg Bucharest Utrecht Ljubljana Bratislava Bologna Antwerp Newcastle Lyon Lausanne Basel Marseille Strasbourg Nantes Hannover Nicosia Reykjavik Riga Seville Tallinn Vilnius Leipzig Dresden Genoa Cardiff Cologne Sofia Valencia Arhus Belgrade Skopje Bremen Turin

2016 1934 1896 1742 1678 1566 1536 1428 1418 1388 1388 1388 1388 1388 1388 1388 1262 1262 1168 1082 1026 1026 1026 1026 1026 1026 894 582 362 362 0 0 0 0

0.16 0.15 0.15 0.14 0.13 0.12 0.12 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.11 0.10 0.10 0.09 0.09 0.08 0.08 0.08 0.08 0.08 0.08 0.07 0.05 0.03 0.03 0.00 0.00 0.00 0.00

129

UK Luxembourg Romania Netherlands Slovenia Slovakia Italy Belgium UK France Switzerland Switzerland France France France Germany Cyprus Iceland Latvia Spain Estonia Lithuania Germany Germany Italy UK Germany Bulgaria Spain Denmark Serbia Macedonia Germany Italy

The geographical orientation results indicating the main dimensions of city hinterworlds are shown in Table 11.7. In the lists for local concentration of connections (Table 11.7(a)) four relatively minor cities (Utrecht, Arhus, Strasbourg and Bristol) feature as most inward in their links with scores of over four. This pattern continues with the other cities scoring above 1: the only such cities that have previously been mentioned for their high connectivities are Hamburg and Munich. There are only five cities with negative values: cities with relatively fewer links to other European cities. Again minor cities dominate but in this case they include cities on the edge of Europe

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(specifically Reykjavik and Nicosia), plus London. The latter reflects the fact that generally the more important cities are relatively less ‘local’ in their intercity linkages. It is not unusual for major cities of a world region to be more orientated away from their region; this is what makes them world or global cities, and London has been so categorized previously (Taylor and Hoyler, 2000; Taylor and Derudder, 2004). In addition, several ex-COMECON cities remain relatively under-linked to the rest of Europe with lower positive scores; the East German cities of Leipzig and Dresden also feature with a negative score.

Table 11.7 City hinterworlds (regional concentrations of connections) of European cities. (a) Relative concentration of connections to local region. CITY Utrecht Arhus Strasbourg Bristol Cardiff Hamburg Lyon Munich Turin Cologne Basel Düsseldorf Leeds Birmingham Bratislava Stockholm Nantes Warsaw Manchester Edinburgh Marseille Budapest Copenhagen Valencia Bucharest Oslo Glasgow Lisbon Vienna

INWARD 8.18 4.69 4.45 4.43 3.58 3.52 3.52 3.50 3.39 3.29 3.24 3.19 3.17 3.11 3.05 2.86 2.83 2.67 2.62 2.60 2.60 2.54 2.45 2.43 2.41 2.41 2.39 2.36 2.36

CITY Reykjavik Leipzig Nicosia Dresden London

OUTWARD −0.32 −0.24 −0.24 −0.16 −0.01

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Zurich Liverpool Brussels Rome Barcelona Berlin Rotterdam Luxembourg Kraków Stuttgart Southampton Prague Sofia Frankfurt Aberdeen Newcastle Madrid Vilnius Zagreb Helsinki Lausanne Dublin Paris Seville Genoa Porto Belfast Athens Skopje Ljubljana Riga Belgrade Amsterdam Milan Hannover Bologna Bremen Tallinn Geneva Antwerp

2.27 2.27 2.20 2.14 2.14 2.09 2.03 1.95 1.89 1.87 1.85 1.84 1.83 1.75 1.66 1.64 1.62 1.59 1.37 1.33 1.30 1.27 1.17 1.17 1.16 1.12 1.06 1.02 1.01 1.00 0.99 0.99 0.93 0.80 0.75 0.62 0.45 0.39 0.14 0.11

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(b) Relative concentration of connections to Northern America. CITY Aberdeen Basel Southampton Edinburgh Antwerp Seville Leeds Birmingham Reykjavik Manchester Liverpool Belfast Lausanne Newcastle Bristol Cologne Porto Kraków Bremen Genoa Dresden Glasgow Amsterdam Marseille Hannover Munich London Milan Zurich

MORE NORTHERN AMERICAN 4.59 3.28 2.77 2.52 2.29 2.06 2.01 1.94 1.81 1.74 1.73 1.51 1.34 1.31 1.21 1.19 1.03 0.99 0.84 0.67 0.67 0.66 0.53 0.39 0.29 0.24 0.10 0.07 0.00

CITY Bratislava Zagreb Utrecht Bucharest Turin Sofia Skopje Vilnius Riga Belgrade Tallinn Ljubljana Copenhagen Budapest Luxembourg Helsinki Nicosia Arhus Vienna Athens Prague Lisbon Warsaw Barcelona Hamburg Geneva Oslo Berlin Leipzig Brussels Lyon Valencia Nantes Stockholm Düsseldorf Rome Strasbourg Frankfurt Dublin Rotterdam Cardiff

LESS NORTHERN AMERICAN −4.11 −3.58 −3.52 −3.51 −3.40 −3.34 −3.17 −2.99 −2.98 −2.93 −2.80 −2.72 −2.58 −2.53 −2.29 −2.24 −1.95 −1.91 −1.85 −1.71 −1.63 −1.61 −1.46 −1.20 −1.16 −1.14 −1.12 −1.05 −0.90 −0.87 −0.66 −0.66 −0.60 −0.57 −0.42 −0.30 −0.30 −0.23 −0.09 −0.09 −0.08

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Paris Bologna Madrid Stuttgart

−0.06 −0.04 −0.02 −0.01

(c) Relative concentration of connections to Pacific Asia. CITY Frankfurt London Paris Luxembourg Amsterdam Milan Prague Madrid Geneva Brussels Düsseldorf Dublin Warsaw

MORE PACIFIC ASIAN 2.46 1.86 1.41 1.34 1.15 0.76 0.60 0.60 0.34 0.32 0.30 0.07 0.02

CITY Lausanne Arhus Strasbourg Marseille Lyon Bremen Dresden Porto Cardiff Skopje Seville Leeds Utrecht Southampton Manchester Nantes Aberdeen Bristol Valencia Belgrade Cologne Stuttgart Hannover Liverpool Genoa Riga Reykjavik Basel Kraków Vilnius Hamburg Edinburgh Leipzig Bologna Copenhagen Antwerp

LESS PACIFIC ASIAN −3.41 −3.28 −3.20 −3.01 −2.71 −2.71 −2.60 −2.47 −2.47 −2.41 −2.40 −2.24 −2.13 −2.10 −2.08 −2.08 −2.04 −2.03 −1.87 −1.86 −1.85 −1.77 −1.75 −1.74 −1.71 −1.68 −1.67 −1.66 −1.65 −1.53 −1.48 −1.48 −1.45 −1.44 −1.42 −1.39

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(c) Relative concentration of connections to Pacific Asia (continued). CITY

MORE PACIFIC ASIAN

CITY Tallinn Sofia Helsinki Turin Ljubljana Belfast Newcastle Barcelona Oslo Nicosia Berlin Bucharest Bratislava Glasgow Birmingham Zagreb Stockholm Athens Rome Rotterdam Lisbon Munich Vienna Zurich Budapest

LESS PACIFIC ASIAN −1.39 −1.32 −1.30 −1.29 −1.28 −1.27 −1.26 −1.24 −1.23 −1.18 −1.14 −1.12 −1.08 −1.05 −0.95 −0.87 −0.76 −0.67 −0.60 −0.58 −0.57 −0.38 −0.24 −0.20 −0.07

Orientations to Northern American cities (Table 11.7(b)) show one specifically interesting result: Aberdeen stands out with by far the highest positive value reflecting its place in servicing networks for the global energy market centred on Houston. But this is also part of a larger pattern: all but one of the 12 UK cities outside London score above 1 for their over-linkage across the Atlantic. The four major cities of London, Paris, Madrid and Milan hover around zero, being neither strongly nor weakly connected to Northern American cities. High under-linkage (negative values) is recorded in particular by cities from former communist countries. However the clearest pattern in these geographical orientations is for Pacific Asia (Table 11.7(c)). Put simply, the more important European cities tend to be over-linked and the less important under-linked; and this is related to financial service connectivities (Table 11.2). Thus the 13 cities having recording positive values (i.e. having

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more connections with Pacific Asian cities) in Table 11.7(c) are ranked 1, 2, 3, 4, 5, 7, 8, 9, 10, 12, 13, 14 and 24 for financial connectivities (Table 11.2). This is quite a remarkable correlation between tables created using different criteria. Previous research has shown that Pacific Asian cities are especially strong in financial services (Taylor, 2004; see also Chapter 3) and this new finding shows how this global pattern is strongly reflected in the hinterworlds of European cities. In conclusion and as expected, Europe, as the cradle of modernity and for more contemporary reasons, has many cities well integrated into the world city network. However, the degree of integration varies greatly with London, then Paris, the most integrated cities, especially in the core world regions of economic globalization. Patterns vary between different service sectors – Frankfurt and Zurich rise for financial services, Milan and Lisbon for accountancy, Warsaw and Athens for advertising, Frankfurt and Amsterdam for law, and Zurich and Rome for management consultancy. When it comes to geographical orientations, some minor cities have distinctive hinterworlds – Utrecht is extremely over-linked to other European cities and remote Reykjavik is relatively least connected to other cities in the region; Aberdeen is strongly over-linked to Northern American cities whereas cities from former communist countries remain under-linked; and finally, connectivities to Pacific Asian cities directly reflect the pattern of financial centres in Europe. It is this finance/Pacific Asia link in city connectivities that may well be the key discriminating factor in the future economic successes of European cities.

References Baeten, G. (2001) ‘The Europeanization of Brussels and the urbanization of “Europe”’, European Urban and Regional Studies, vol 8, pp117–130 Berg, L. van den, Braun, E., Meer, J. van der and Mingardo, G. (2007) ‘The urban dimension in European policy: history, actors and programmes’, in L. van den Berg, E. Braun and J. van der Meer (eds) National Responses to Urban Challenges in Europe, Ashgate, Aldershot, pp39–62 Cochrane, A. and Jonas, A. (1999) ‘Reimagining Berlin: world city, national capital or ordinary place?’ European Urban and Regional Studies, vol 6, pp145–164 Derudder, B., Hoyler, M. and Taylor, P. J. (2010) ‘Goodbye Reykjavik: International banking centres and the global financial crisis’, Area, doi:10.1111/j.1475–4762.2010.00968.x Elmhorn, C. (2001) Brussels: A Reflexive World City, Almqvist & Wiksell International, Stockholm Faludi, A. (ed) (2002) European Spatial Planning, Lincoln Institute of Land Policy, Cambridge, MA Groof, R. de (ed.) (2008) Brussels and Europe, BRIO, Brussels Krätke, S. (2001) ‘Berlin: towards a global city?’ Urban Studies, vol 38, pp1777–1799

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Taylor, P. J. (2004) World City Network: A Global Urban Analysis, Routledge, London Taylor, P. J. and Derudder, B. (2004) ‘Porous Europe: European cities in global urban arenas’, Tijdschrift voor Economische en Sociale Geografie, vol 95, pp527–538 Taylor, P. J. and Hoyler, M. (2000) ‘The spatial order of European cities under conditions of contemporary globalisation’, Tijdschrift voor Economische en Sociale Geografie, vol 91, pp176–189

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12

Sub-Saharan Cities in Globalization Ronald S. Wall

Of all regional chapters, this chapter holds the third lowest number of cities qualifying for inclusion within the global network analysis. The relative share of connectivity that these cities hold is also comparatively small. There are several broad historical reasons for this: 1

2

Unlike Western Europe, Sub-Saharan Africa has only had a very recent history of state building and capital cities (Chandler, 1987), and hence arguably a much weaker share of global connectivity. During the Scramble for Africa at the end of the 19th century, European powers staked claims to virtually the entire continent. Before that, Europeans considered Africa more as a coastline than a continent, where besides the more established European settlements in South Africa, Rhodesia and Algeria, only small isolated trading outposts were known of. Only by 1910 had the previous terra incognita of traditional monarchies and chiefdoms been converted into a chessboard of 53 colonies/countries with designated capitals (Meredith, 2006). This means that modern African cities have only really existed for roughly 100 years, developed mainly in the interest of colonial and global powers, and hence characterized more by ‘incoming links’ than by ‘outgoing links’ (Wall, 2009). Since 1910 Africa has decolonized, but most nations have retained the frontiers arbitrarily drawn by the late 19th century European diplomats and administrators. These geometrically laid out frontiers notoriously took no account of the myriad of African societies, often dissecting individual cultures into different colonies/countries, and enclosing various cultures of diverse and independent groups (Meredith, 2006). When African colonies finally attained independence in the latter half of the 20th century, the newly formed nationalist parties generally disregarded multiparty parliamentary systems and the existence of diverse cultures within their national boundaries. When these governments proved unable or unwilling to fulfil

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popular expectations, the result was often the full-scale rebellions and military interventions that have been widespread over the past three decades (Harber and Wall, 2001). In this sense, these political instabilities and corruption have been and still are detrimental to Africa’s development within a globalizing world (Kaufmann et al, 2005). Fifty years after the beginning of the independence era, Africa’s future prospects remain questionable. Already the world’s least wealthy region, it is falling further and further behind all other regions of the world. Its average per capita national income is one-third lower than the world’s next poorest region, South Asia (Sutcliffe, 2001). Most African countries have lower per capita incomes today than they had in 1980. Half of Africa’s 880 million people live on less than US$1 per day and its share of global trade has declined to half of what it was in the 1980s (Meredith, 2006). It is the only world region where illiteracy is commonplace, and on a list drawn up by the United Nations Development Programme, the 25 least developed nations in the world are all African (Meredith, 2006). Naturally the scourge of HIV/Aids does not work in favour of African countries developing. Troubled by these unfortunate issues, Africa finds itself largely excluded from the process of globalization, generally lacking the skills and the infrastructure to attract the global headquarters and subsidiaries that drive it (Léautier and Mehta, 2006). Furthermore, the African economy is generally still centred in basic agricultural and raw material production, in which the demand for the more profitable producer services remains relatively small. The prospects of Africa escaping this precipitous decline, as former South African President Mbeki stated, depend heavily on Western assistance (Mbeki, 1998). Most states are effectively bankrupt, and since the 1990s Western aid has fallen dramatically due to scepticism whether Africa will ever deliver its side of the bargain. Furthermore, intraAfrican economic institutions such as the Economic Community of West African States (ECOWAS) and the Organization of African Unity (OAU) have not been particularly successful in improving the economic situation in Africa (Wall, 2000).

Three points can be made about the results of this analysis: 1

They provide a table concerning the gross connectivity of Sub-Saharan African cities and their proportionate connectivity relative to London (Table 12.1). In this, only 11 Sub-Saharan African cities hold total global network connectivity above 0.1, with the largest being Johannesburg at 0.43. Compared to Europe, which has been divided into six strata of connectivity (see Chapter 11), this region could only claim Johannesburg to be within their sixth stratum. All ten other cities fall below Europe’s sixth stratum. This means that only Johannesburg can be considered as a moderate global contender within the world economy, as defined within this global analysis.

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2

3

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The total city linkages have been disaggregated into five service sectors (financial services, accountancy, advertising, legal services and management consultancy) as is evident in the subsequent tables. These have been treated the same way as the gross connectivities, in which the upper echelons of ranks represent leading cities in each sector. City connectivities are disaggregated by regional geographical orientation, showing over-linked or under-linked distributions. This is shown separately for local distribution to other Sub-Saharan African cities and linkages to the main globalization arenas of Europe, Northern America and Pacific Asia. These results illustrate the ‘hinterworld’ of Sub-Saharan African cities to these other regions of the world. In the table they are presented as standardized scores with positive values indicating overlinkage and negative values under-linkage.

Table 12.1 Global network connectivity of Sub-Saharan cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11

Johannesburg Nairobi Cape Town Lagos Port Louis Accra Dar es Salaam Lusaka Durban Gaborone Harare

GROSS CONNECTIVITY 41,541 28,458 24,814 21,690 20,230 15,531 12,346 12,199 11,984 11,140 11,062

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.43 0.30 0.26 0.23 0.21 0.16 0.13 0.13 0.12 0.12 0.11

South Africa Kenya South Africa Nigeria Mauritius Ghana Tanzania Zambia South Africa Botswana Zimbabwe

In Table 12.1 the 11 cities are ranked by their total global network connectivities. As previously discussed, Johannesburg is by far the dominant city in this region, with connectivity similar to that of Barcelona. This is not odd considering that Johannesburg holds the largest gold reserves in the world and has traditionally had a relatively well-developed industrial and service sector and stock exchange. It is followed by Nairobi with connectivity similar to Bratislava. Its strength in connectivity relates to it having one of Africa’s strongest stock exchanges and being home to the United Nations office in Africa and also the UN Environmental Programme. Cape Town is in 3rd place and 4th place is held by Lagos, whose connectivity can be most related to its

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crude oil producing industries. Interestingly, Port Louis, the capital of the island of Mauritius, holds 5th place in the rankings. This is due to its fast growing manufacturing, service and tourist industries, relatively high GDP per capita, its pristine settings (known as the Hawaii of the South Africans) and its geographic isolation from the turmoils of the rest of Africa. Furthermore, three of the 11 are South African cities, which together hold 37 per cent of the total connectivity of all these Sub-Saharan cities, hereby clearly revealing the importance of South Africa within this region and its gateway function to the world. Nonetheless, this region’s total connectivity remains modest in comparison to other world regions. In fact, the combined connectivity of New York and London amounts to the entire connectivity of Sub-Saharan Africa. Other research shows similarly that Africa holds only 1 per cent of all global corporate linkages (Wall, 2009). This is unsettling when 10 per cent of the world’s population are found in Sub-Saharan Africa. Furthermore, of the 11 cities represented in this study, seven are capitals. However, when considering the fact that Lagos was the capital of Nigeria until 1991 (today it is Abuja), that Johannesburg and neighbouring administrative capital Pretoria have become one huge urban agglomeration, and that Cape Town is the legal capital of South Africa, then it is arguable that Sub-Saharan connectivity is almost fully dependent on capital cities. It is also striking that all the 11 most connected Sub-Saharan cities were formerly under British rule, in which London was the primary global city during the era of colonization, and today still remains one of the top two global cities. In this sense, it is arguable that a strong history of connectivity with a key global city such as London is beneficial to a city’s economic development. In this next section cities are ranked according to their connectivity within the financial service sector (Table 12.2). First, it is seen that Johannesburg takes the lion’s share of financial service connectivity. This is not surprising considering that Johannesburg is one of the world’s primary financial centres and is the economic and financial hub of South Africa – producing 16 per cent of South Africa’s gross domestic product. It is also the source of large scale diamond and gold trade and has the largest and busiest airport in Africa. Furthermore, the Johannesburg Greater Metropolitan area has a population of 7 million people.

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Table 12.2 Financial services network connectivity of Sub-Saharan cities. RANK

CITY

1 2 3 4 5 6 7= 7= 9 10 11

Johannesburg Nairobi Lagos Cape Town Port Louis Lusaka Accra Dar es Salaam Harare Gaborone Durban

GROSS CONNECTIVITY 9260 2860 2567 2293 2136 2002 1708 1708 1683 1200 774

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.34 0.11 0.10 0.08 0.08 0.07 0.06 0.06 0.06 0.04 0.03

South Africa Kenya Nigeria South Africa Mauritius Zambia Ghana Tanzania Zimbabwe Botswana South Africa

Second in rank is Nairobi, which is strongly related to its relatively strong stock exchange. At third rank Lagos supersedes Cape Town in financial services, when compared to the results of Table 12.1. This is due to its established banking and financial institutions, population of 8 million, its main port status, and its strength in crude oil exports. Compared to Table 12.1, Lusaka and Harare rise up a few positions in the financial service sector. Not surprisingly, Accra drops down one place, and Durban drops two places, as these cities are better known for their basic manufacturing industries than for financial services. Lastly, the three South African cities together claim 44 per cent of the Sub-Saharan financial services network connectivity, making this South Africa’s strongest sector. In Table 12.3, cities are ranked according to their strength in the accountancy sector. First it is seen that this sector claims the highest connectivity values. However, this size effect does not mean that accountancy is more powerful than the other sectors. Sectors such as financial services usually concern quite large firms carrying out complex large scale operations, while accountancy concerns larger counts of smaller firms that generally deal with smaller scale operations. This also proves to be Johannesburg’s strongest sector in terms of connectivity. South African cities claim 36 per cent of this connectivity. Together with management services this sector forms the strongest activity of Port Louis.

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Table 12.3 Accountancy network connectivity of Sub-Saharan cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11

Johannesburg Nairobi Cape Town Port Louis Lagos Durban Accra Gaborone Dar es Salaam Lusaka Harare

GROSS CONNECTIVITY 20,331 17,797 15,553 14,094 13,286 9072 7811 7144 6866 6267 5705

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.50 0.44 0.38 0.35 0.33 0.22 0.19 0.18 0.17 0.15 0.14

South Africa Kenya South Africa Mauritius Nigeria South Africa Ghana Botswana Tanzania Zambia Zimbabwe

Table 12.4 shows the ranking of Sub-Saharan cities according to the connectivity of advertising industries. This sector forms the second strongest of the five in terms of connectivity for these 11 cities. For reasons mentioned previously, this reflects the size effect of these relatively smaller-type firms. Johannesburg ranks first in this sector, followed by Cape Town. The former relates more to advertising of local firms, while the latter is known as a primary site of international advertising companies, due to this city’s unique scenic and climatic conditions. The South African cities together hold 38 per cent of all Sub-Saharan connectivity within this sector.

Table 12.4 Advertising network connectivity of Sub-Saharan cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11

Johannesburg Cape Town Nairobi Accra Lagos Harare Dar es Salaam Port Louis Lusaka Gaborone Durban

GROSS CONNECTIVITY 9220 6644 6424 4662 4460 3674 2746 2666 2580 2404 2138

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK)

COUNTRY

0.44 0.32 0.31 0.22 0.21 0.18 0.13 0.13 0.12 0.12 0.10

South Africa South Africa Kenya Ghana Nigeria Zimbabwe Tanzania Mauritius Zambia Botswana South Africa

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Only Accra, Cape Town and Lusaka show some legal services network connectivity through major global law firms (Table 12.5). The legal service sector is the only sector in which Johannesburg does not dominate. In Table 12.6 the strongest position within management consultancy is held by Johannesburg, followed by Nairobi and Lagos. This sector only holds a relatively low percentage of the connectivity of all sectors in Sub-Saharan Africa, but again this does not necessarily mean that this is a weaker sector. Management consultancy firms tend to concern much larger type, but fewer firms.

Table 12.5 Legal services network connectivity of Sub-Saharan cities. RANK

CITY

1= 1= 1= 4= 4= 4= 4= 4= 4= 4= 4=

Cape Town Accra Lusaka Johannesburg Nairobi Lagos Port Louis Dar es Salaam Durban Gaborone Harare

GROSS CONNECTIVITY 324 324 324 0 0 0 0 0 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

COUNTRY

0.07 0.07 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

South Africa Ghana Zambia South Africa Kenya Nigeria Mauritius Tanzania South Africa Botswana Zimbabwe

Table 12.6 Management consultancy network connectivity of Sub-Saharan cities. RANK

CITY

1 2= 2= 4 5= 5= 5= 8 9= 9= 9=

Johannesburg Nairobi Lagos Port Louis Accra Dar es Salaam Lusaka Gaborone Cape Town Durban Harare

GROSS CONNECTIVITY 2730 1377 1377 1334 1026 1026 1026 392 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK)

COUNTRY

0.22 0.11 0.11 0.11 0.08 0.08 0.08 0.03 0.00 0.00 0.00

South Africa Kenya Nigeria Mauritius Ghana Tanzania Zambia Botswana South Africa South Africa Zimbabwe

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The geographical orientation results indicating the main dimensions of city hinterworlds are shown in Table 12.7. This is divided into relative connections to the local Sub-Saharan region, to Europe, to Northern America and to Pacific Asia. Note that these results are relative to all cities within the global network and not only those in Sub-Saharan Africa. In the case of Johannesburg we see that it is the only city under-linked (negative score) within the Sub-Saharan region (Table 12.7(a)), underlining that it operates more at a global scale than regionally. This is emphasized by the fact that it is over-linked (positive scores) to Europe and especially Pacific Asia (Tables 12.7(b) and (d)). This can be explained by the fact that since the fall of apartheid, South Africa has focused on developing strong trading relations (particularly in raw materials) with fast growing Pacific Asia, especially China. Cape Town is the only other city with positive over-linkage to Europe. This may be due to its relatively strong historical ties with Europe, especially the Netherlands. Nairobi and all other cities prove to be under-linked (negative values) to the three globalization arenas. However, despite previous colonial ties, six of these nine cities are relatively more linked to Pacific Asia than Europe. This may be of future importance. Two further features should be noted: first, all 11 cities are relatively under-linked to Northern America (Table 12.7(c)); second, the most locally orientated cities are from central and southern Africa: Dar es Salaam, Lusaka and Harare all score above three in Table 12.7(a); in this sense these cities are far more regionally connected than globally.

Table 12.7 City hinterworlds (regional concentrations of connections) of Sub-Saharan cities. (a) Relative concentration of connections to local region. CITY Harare Lusaka Dar es Salaam Gaborone Durban Accra Lagos Nairobi Cape Town Port Louis

INWARD 4.26 3.48 3.27 2.88 2.70 2.08 1.79 1.50 1.36 1.14

CITY Johannesburg

OUTWARD −0.17

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(b) Relative concentration of connections to Europe. CITY Cape Town Johannesburg

MORE EUROPEAN 0.77 0.24

CITY Port Louis Dar es Salaam Accra Durban Nairobi Lusaka Gaborone Lagos Harare

LESS EUROPEAN −2.04 −1.97 −1.72 −1.38 −1.31 −1.02 −0.99 −0.84 −0.61

(c) Relative concentration of connections to Northern America. CITY

MORE NORTHERN AMERICAN

CITY Harare Lagos Durban Port Louis Cape Town Nairobi Lusaka Accra Dar es Salaam Gaborone Johannesburg

LESS NORTHERN AMERICAN −4.72 −3.89 −3.73 −3.23 −2.81 −2.64 −2.62 −2.56 −2.56 −2.50 −2.10

(d) Relative concentration of connections to Pacific Asia. CITY Johannesburg

MORE PACIFIC ASIAN 0.99

CITY Cape Town Durban Gaborone Accra Nairobi Harare Dar es Salaam Port Louis Lagos Lusaka

LESS PACIFIC ASIAN −2.63 −2.50 −1.33 −1.21 −1.14 −0.93 −0.92 −0.52 −0.39 −0.32

145

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To conclude, and as was expected, Sub-Saharan cities are poorly represented in the network of advanced producer services. In a region of 645 million people, only 11 cities made the list – compared to Europe’s 74 cities in a region of 732 million people. In this chapter it is argued that this under-representation is related to the relatively young history of Sub-Saharan cities; the generally weak level of urban development and attractiveness for business to locate; the conflict between formal and informal economies; the scars of colonization; the persistence of corrupt governance; and the generally poor level of economic, social, political and infrastructural development in this region. Therefore it is not surprising that the most developed nation in this region, South Africa, holds three cities which qualify for this analysis. Johannesburg in particular plays a key role in connecting to the global system of advanced producer services. This is followed at a lesser level by cities such as Nairobi and Lagos. Furthermore, it is seen in this study that cities that tend to be more weakly connected also tend to be more regionally connected, for example Harare and Lusaka. Ranking patterns tend to vary only slightly across the five different sectors, where Johannesburg, Nairobi, Lagos and Cape Town tend to dominate the upper echelon. It is these cities which modestly anchor Africa to the global service system. However, for cities in this region to improve their level of globalization, they need to strengthen their regional and global connectivity. In turn, to appeal to global firms, these cities will need to improve their reliability and attractiveness. Furthermore, because globalization tends to favour cities that are already relatively strong hubs (Léautier and Mehta, 2006), like Johannesburg, smaller cities may need to first work on improving their regional connectivity, plus their connectivity to the regional hub. However, improvement of SubSaharan African city connectivity and integration with the global system cannot come only from Africa. This region’s relative underdevelopment and increasing technological dependency make it literally impossible for African cities to compete internationally, either in manufacturing or in advanced services. Because of this inability, this region’s balance of trade becomes increasingly unsustainable (Castells, 1998). Therefore, besides African efforts, a strong global agenda is needed which focuses not only on providing aid to Africa, but more importantly, enables African cities to become more attractive sites for manufacturing and services, and thereby gradually help Africa to become more strongly connected to the world system.

References Castells. M. (1998) End of Millennium, Blackwell, Oxford Chandler, T. (1987) Four Thousand Years of Urban Growth: An Historical Census, Edwin Mellon, Lewiston, NY Harber, R. and Wall, R. S. (2001) The African City, NDR Printing, The Hague Kaufmann, D., Léautier, F., and Mastruzzi, M. (2005) Governance and the City: An Empirical Exploration into Global Determinants of Urban Performance, World Bank Policy Research Working Paper 3712, The World Bank, Washington, DC

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Léautier, F. A. and Mehta, B. (2006) ‘Urban performance profiles: the impact of globalization and the challenge for Africa’, in F. A. Léautier (ed.) Cities in a Globalizing World, The World Bank, Washington, DC, pp69–130 Mbeki, T. (1998) The African Renaissance: South Africa and the World, Speech at the United Nations University, Tokyo, 9 April 1998 Meredith, M. (2006) The State of Africa: A History of Fifty Years of Independence, The Free Press, London Sutcliffe, B. (2001) 100 Ways of Seeing an Unequal World, Zed Books, London Wall, R. S. (2000) World Trade Centre Network, The Ministry of Housing, Spatial Planning and the Environment (VROM), De Longte, Dordrecht Wall, R. S. (2009) NETSCAPE: Cities and Global Corporate Networks, ERIM Series 169, Haveka, Rotterdam

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Northern American Cities in Globalization Asli Ceylan Oner

The 55 cities included in this chapter are from two countries, the United States and Canada. There are three important developments that have shaped the North American urban system since the 1970s. These developments include: 1

2

In the early 1970s, de-industrialization and a shift of manufacturing to mainly low-cost developing countries started a new decentralization pattern in the United States (Castells, 1989; Sassen, 2001). Many remaining industries left the decaying centres of the old manufacturing belt and relocated in the Sunbelt states that offered more desirable conditions including new high-tech plants, tax breaks and less unionized labour, resulting in a process known as ‘the Sunbelt expansion’. As a result of this, employment in the United States has shifted to cities and suburbs of the south and southwest (Rice and Bernard, 1983; Clark and Roche, 1984; Macionis and Parrillo, 2004). Besides manufacturing, these cities have also become important service centres. The result is that 22 of the 55 cities included in this chapter are from the Sunbelt states. In manufacturing belt cities, much of what is left of the old industry moved out to suburban locations (Castells, 1989) resulting in a severe decline in central cities of the former manufacturing belt. On the other hand, due to their historic importance as strategic locations, cities such as New York, Chicago, Boston and Philadelphia remained as important economic centres and international hubs for service industries (Mohl, 1997). The result is that 16 of the 55 cities analysed in this chapter are from the former manufacturing belt states of the United States. The North American Free Trade Agreement (NAFTA), signed in 1993 between the United States, Canada and Mexico, had a transforming impact on the economies of Northern American cities as well as their interrelations both with each other and with cities in different parts of the world. Various cities of the United States, Canada and Mexico have

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3

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become more integrated with increased trade activity and some cities have experienced decline (Bourne and Simmons, 2003). Cities close to borders have benefited more from NAFTA than cities in the periphery. In Canada, Toronto has changed from a national trading centre to a prominent world city, linking the Canadian economy with the global economy (Newman and Thornley, 2005). East and West coast cities became gateways to the NAFTA region, reinforcing the status of such cities as Los Angeles and Miami as immigration hubs (Newman and Thornley, 2005). Current debates among European and American scholars highlight the importance of ‘trans-metropolitan’ urban areas as integration zones for the global economy (Faludi, 2002; Taylor and Lang, 2005; Lang and Dhavale, 2005; Hall and Pain, 2006; Lang and Nelson, 2007). In the United States, trans-metropolitan areas are referred to as megapolitans, large urban regions with physically interconnected metropolitan and micropolitan areas through transportation networks, constituting a functionally interdependent urban network (Lang and Dhavale, 2005). Megapolitans specialize in service sector and high-tech employment (Lang and Dhavale, 2005; Lang and Nelson, 2007). The largest and the most important metropolitan areas of the United States are located in megapolitans, which contain 67 per cent of the total population (Lang and Nelson, 2007). By 2050, it is expected that megapolitans will have more than half of the US population growth and two-thirds of its economic growth (Carbonell and Yaro, 2005). In the Canadian urban system, there are only six metropolitan areas with populations exceeding 1 million: Toronto, Montreal, Vancouver, Ottawa, Calgary and Edmonton (Charney, 2003). Around 48 per cent of the population lives in these six metropolitan areas, reflecting a huge centralization of population and employment. In Canada, as in the United States, debates related to new regionalism (Sancton, 2001) and growing metropolitan area populations led to the consolidation of continuous urbanized areas into five greater metropolitan areas: ‘greater Toronto, greater Montreal, Ottawa-Gatineau, Vancouver-Victoria and the central Alberta urban corridor’ (Bourne and Simmons, 2003, p28). The continuous region from Quebec City to Windsor, which includes the greater metropolitan areas of Quebec, Montreal, Ottawa and Toronto, is part of a bi-national ‘mega-region’ identified by Florida (2008). The megaregion concept is similar to that of megapolitans and both concepts provide an important framework in understanding the dynamics of the global connectivity of Northern American cities. The result for our analysis is that 39 of the 55 cities in this chapter belong to trans-metropolitan urban regions.

One important characteristic of the world cities in Northern America that needs to be mentioned here is that they have much less global connectivity compared to their European and Pacific Asian counterparts. This is especially surprising in the case of the United States, which is the world’s largest

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economy. According to Taylor and Lang (2005, p11), this can be explained by the less risky domestic market orientation of the US firms and ‘the shadow effect’ of New York, preventing further penetration of non-US firms into other US cities. This chapter generally focuses on 55 cities from Northern America. From this set of 55 cities, three sets of results are produced. The first set of results includes the cities at the upper levels of the echelon: 55 cities are ranked from 1 to 55 according to their gross global network connectivity. Gaps in the actual connectivity proportions are used to identify 21 cities, divided into seven strata, which are designated as the leading Northern American cities. For the second set of results, city connectivities are disaggregated by service sectors producing five additional city rankings (for financial services, accountancy, advertising, legal services and management consultancy). In these rankings, as in the previous analysis, cities are ranked according to their gross connectivities within the sector and stratified according to gaps in their connectivity proportions; the leading cities are identified according to their high rankings. The third set of results reveals the ‘hinterworlds’ of Northern American cities. City connectivities are aggregated according to the geographical orientation, showing over- or under-linkage to other Northern American cities, European cities and Pacific Asian cities. Positive values indicate over-linkage and negative values indicate under-linkage. In these results, the focus is on cities with connectivity values of more than 1 or less than −1. For the first set of results in our analysis, 21 cities out of 55 cities, stratified into seven classes, are identified as the leading world cities of Northern America (Table 13.1). Except for Minneapolis and Calgary, all cities are anchor cities of mega urban regions. In addition, except for the Sun Corridor megapolitan area in Arizona, all other mega urban regions in Canada and the United States have at least one anchor city among the 21 leading world cities, which indicates a possible competition among mega-regions in terms of gaining access to global urban networks. Phoenix, the prominent anchor city of Sun Corridor, ranks 23rd. The Northeast megapolitan region (Megalopolis) has the highest number of cities among the top 21 with New York, Washington, DC, Boston and Philadelphia.

Table 13.1 Global network connectivity of Northern American cities. RANK

CITY

1 2 3 4 5

New York Toronto Chicago Los Angeles Washington

GROSS CONNECTIVITY 95,838 60,454 55,324 44,637 42,831

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 1.00 0.63 0.57 0.46 0.44

COUNTRY

USA Canada USA USA USA

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6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

Atlanta San Francisco Dallas Boston Miami Houston Montreal Denver Vancouver Minneapolis Seattle Philadelphia Portland Detroit San Diego Calgary Columbus Phoenix Cleveland Tampa Kansas City Pittsburgh Orlando Charlotte Indianapolis Baltimore St Louis Ottawa Sacramento Milwaukee San Jose Richmond Las Vegas Memphis Hartford Nashville Honolulu Omaha Raleigh Salt Lake City Austin Winnipeg Tulsa Edmonton Rochester

41,144 40,735 33,938 33,752 32,373 31,357 28,662 26,684 26,195 24,488 24,368 22,248 21,855 21,607 20,147 19,970 19,428 18,207 18,173 17,475 16,520 16,237 16,218 15,981 15,860 15,109 14,929 14,527 14,103 13,909 13,896 13,866 13,718 13,367 12,745 12,529 12,381 12,262 12,231 11,158 11,094 11,030 10,472 10,434 10,432

0.43 0.42 0.35 0.35 0.34 0.33 0.30 0.28 0.27 0.25 0.25 0.23 0.23 0.22 0.21 0.21 0.20 0.19 0.19 0.18 0.17 0.17 0.17 0.17 0.16 0.16 0.16 0.15 0.15 0.14 0.14 0.14 0.14 0.14 0.13 0.13 0.13 0.13 0.13 0.12 0.12 0.11 0.11 0.11 0.11

USA USA USA USA USA USA Canada USA Canada USA USA USA USA USA USA Canada USA USA USA USA USA USA USA USA USA USA USA Canada USA USA USA USA USA USA USA USA USA USA USA USA USA Canada USA Canada USA

151

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Table 13.1 Global network connectivity of Northern American cities (continued). RANK

CITY

51 52 53 54 55

Halifax Birmingham Cincinnati New Orleans Quebec

GROSS CONNECTIVITY 10,094 9925 9776 9280 9183

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.10 0.10 0.10 0.10 0.10

COUNTRY

Canada USA USA USA Canada

The top three cities according to global network connectivities also constitute three distinct strata (Table 13.1). New York is at the top of the list and has a value of gross connectivity almost the same as London. The second city is Toronto, Canada’s leading global city. Since 2000, Toronto has improved its global connectivity and managed to move above Chicago and Los Angeles (Taylor and Aranya, 2008). Since NAFTA introduced open borders, Toronto has become a hub for international functions both for the Canadian economy and for US cities such as Buffalo and Detroit (Newman and Thornley, 2005). After Toronto, Chicago is found as the third ranked city, the only other city with more than half of New York’s global network connectivity. There are four more strata below Chicago as illustrated in Table 13.1. The fourth stratum contains the three most important world cities of the Sunbelt region as well as the capital of the United States. Los Angeles, Washington, DC, Atlanta and San Francisco are the cities in this layer. Located on the west coast, Los Angeles and San Francisco are the gateway cities to the Pacific Rim as well as important culture and media centres respectively. Therefore their rankings are no surprise. The interesting result to note in this stratum is that Washington, DC has a connectivity level just below that of Los Angeles. As the capital city of the most powerful national economy and the location for many international institutions, Washington, DC is clearly more than a national capital. Canada’s capital city, Ottawa, has a ranking of 33 and is not found among the top cities in terms of global connectivity. Atlanta, the ‘New York of the South’ (Taylor and Lang, 2005, p7) is also found in the fourth stratum with a higher connectivity value than San Francisco. The fifth stratum has a mix of specialized centres and regional hubs; four cities are found in this stratum with three Sunbelt cities and one regional capital including Dallas, Boston, Miami and Houston. Dallas is the fourth largest and the fastest growing metropolitan area of the United States and a regional centre for high-tech industries. Houston specializes in oil industry and is known as the ‘world’s energy capital’ (Taylor and Lang, 2005, p5). Miami, the gateway to Latin America, is also found in the fifth stratum as an important immigration hub. The immigrant population in Miami managed to establish close business links with other Latin American countries (Taylor and

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Lang, 2005), which gives a unique identity to Miami’s urban economy. Boston, a regional capital and a former manufacturing belt city with the same global connectivity as that of Dallas, is also in the fifth stratum. The mix of cities in the fourth and fifth strata clearly demonstrates the significance of the Sunbelt cities in the North American economy. The sixth and seventh strata in Table 13.1 each have five cities with equally diverse geographic mix. In the sixth stratum, there are three regional capitals from the United States: Denver, Minneapolis and Seattle. Canadian cities reappear in the sixth stratum with Montreal and Vancouver. Both Vancouver and Seattle are important port cities, but Vancouver is better connected to Pacific Asian trade links than Seattle, which is visible in their connectivity values. The seventh stratum has a mix of regional and sub-regional centres including Philadelphia, a historical manufacturing centre; Detroit, the global car capital (Taylor and Lang, 2005); Calgary, energy capital of Canada (Charney, 2003); San Diego, an immigration hub located along the Mexican border; and Portland, a sub-regional centre on the west coast. The global connectivity in this last stratum is around one-fifth of the maximum. In the second set of results city connectivities are disaggregated by service sectors producing five additional city rankings (for financial services, accountancy, advertising, legal services and management consultancy). In Table 13.2, city connectivities based on financial service firms are used to rank the cities. There are 13 cities that are identified as leading ‘international financial centres’ in Northern America, grouped into six strata. Among the 13 cities, three are from Canada and ten are from the United States. The top three cities, New York, Toronto and Chicago, remain the same as in the previous ranking, constituting three distinct strata. Los Angeles and San Francisco constitute the fourth stratum. These five cities are the leading financial centres of Northern America. There are six cities located in the fifth stratum. The surprise is the emergence of Washington, DC leading the stratum, not usually thought of as a financial centre; nevertheless this capital region has one of the fastest growing economic zones in the country. Boston also makes this level. In addition, Montreal demonstrates an important change in ranking, moving up from twelve (in Table 13.1) to ten to reach the fifth stratum. As Canada’s second largest urban economy and the second largest financial centre after Toronto, Montreal joins this stratum alongside three rising centres from the Sunbelt region: Atlanta, Houston and Dallas. The next stratum contains just two cities: Vancouver and Miami. Miami is the US banking centre for Latin America and Vancouver is similarly the Canadian banking centre for the Pacific Rim. Table 13.2 demonstrates that Detroit experienced the biggest change for financial connectivity compared to its overall connectivity (Table 13.1) dropping from 13 to 34.

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Table 13.2 Financial services network connectivity of Northern American cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

New York Toronto Chicago Los Angeles San Francisco Washington Atlanta Boston Dallas Montreal Houston Miami Vancouver Denver Seattle Portland Hartford Calgary Minneapolis Columbus Philadelphia Omaha Tampa Kansas City Las Vegas Charlotte San Diego Pittsburgh Salt Lake City Sacramento Richmond Cleveland Nashville Detroit Phoenix Orlando Milwaukee Cincinnati Honolulu San Jose

GROSS CONNECTIVITY 26,003 17,242 15,038 13,211 11,209 9365 9103 8969 8951 8804 8582 6876 6792 5288 5109 4989 4748 4726 4535 4104 3985 3742 3673 3308 3284 3220 2917 2887 2768 2757 2549 2412 2347 2345 2235 2134 2119 2076 2007 1988

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.96 0.64 0.56 0.49 0.42 0.35 0.34 0.33 0.33 0.33 0.32 0.25 0.25 0.20 0.19 0.18 0.18 0.18 0.17 0.15 0.15 0.14 0.14 0.12 0.12 0.12 0.11 0.11 0.10 0.10 0.09 0.09 0.09 0.09 0.08 0.08 0.08 0.08 0.07 0.07

COUNTRY

USA Canada USA USA USA USA USA USA USA Canada USA USA Canada USA USA USA USA Canada USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA

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41 42 43 44 45 46 47 48 49 50 51 52 53 54 55

Tulsa Rochester St Louis New Orleans Memphis Baltimore Indianapolis Austin Raleigh Quebec Birmingham Ottawa Winnipeg Halifax Edmonton

1906 1858 1849 1760 1752 1745 1691 1660 1501 1368 1355 1325 980 870 734

0.07 0.07 0.07 0.07 0.06 0.06 0.06 0.06 0.06 0.05 0.05 0.05 0.04 0.03 0.03

155

USA USA USA USA USA USA USA USA USA Canada USA Canada Canada Canada Canada

In accountancy, New York is the most connected city in Northern America, with a proportionate connectivity of over three-fourths of London (Table 13.3). Toronto is again ranked in a second stratum below New York. Compared to other sectors, accountancy has the highest bottom ranked connectivity among all service connectivities. For example, Cincinnati is ranked 55 with a connectivity in accountancy of 0.11 whereas with the same connectivity value, in advertising, Vancouver ranks 16 (Table 13.4) and in legal services, Atlanta ranks 12 (Table 13.5). This finding indicates that accountancy has a flatter structure; international accounting companies are more evenly distributed across the 55 cities compared to companies from other sectors. In accountancy, 18 out of 55 cities have proportionate connectivity values of 0.30 and above, which is the highest number of cities with this connectivity level in the studied sectors. The leading financial centres of Los Angeles and San Francisco are found in the fourth stratum below Chicago, Washington, DC and Atlanta together in the third stratum. The fourth stratum has some of the other largest and the most important world cities in the United States – Houston, Boston, Miami and Dallas – as well as Canada’s key cities below Toronto – Vancouver and Montreal. In contrast, the fifth stratum has regional centres and capitals such as Philadelphia, Seattle and Denver. Phoenix, the anchor city of the Sunbelt megapolitan area, is found in the fifth stratum demonstrating a big increase in both connectivity and ranking compared to its overall network connectivity (Table 13.1). The sixth stratum in accountancy has a mix of cities with no clear pattern including sub-regional centres (Portland and Orlando), reviving old manufacturing belt cities (Cleveland and Columbus), national and regional capitals (Ottawa and Minneapolis), and specialized regional and global centres (Calgary and Detroit). Accountancy is the only service sector in which Ottawa, Canada’s capital city, has the connectivity value high enough to be considered as a leading world city. This finding

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combined with the high ranking of Washington, DC might suggest that locational strategies of accounting firms have a pattern of proximity to governmental centres and regulatory institutions.

Table 13.3 Accountancy network connectivity of Northern American cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35

New York Toronto Chicago Washington Atlanta Los Angeles Houston Boston San Francisco Miami Dallas Vancouver Montreal Philadelphia Denver Seattle San Diego Phoenix Columbus Portland Orlando Cleveland Detroit Ottawa Minneapolis Calgary Indianapolis Tampa Richmond Charlotte Raleigh Kansas City Baltimore Pittsburgh San Jose

GROSS CONNECTIVITY 32,147 24,800 20,094 19,832 18,605 16,879 16,398 15,926 15,817 14,790 14,616 14,044 13,776 12,788 12,730 12,180 12,130 12,026 11,405 10,990 10,938 10,902 10,746 10,527 10,434 10,362 10,109 9534 9209 9011 8988 8844 8588 8482 8458

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.79 0.61 0.50 0.49 0.46 0.42 0.41 0.39 0.39 0.37 0.36 0.35 0.34 0.32 0.31 0.30 0.30 0.30 0.28 0.27 0.27 0.27 0.27 0.26 0.26 0.26 0.25 0.24 0.23 0.22 0.22 0.22 0.21 0.21 0.21

COUNTRY

USA Canada USA USA USA USA USA USA USA USA USA Canada Canada USA USA USA USA USA USA USA USA USA USA Canada USA Canada USA USA USA USA USA USA USA USA USA

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36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55

Memphis St Louis Milwaukee Winnipeg Las Vegas Nashville Edmonton Omaha Honolulu Halifax Birmingham Sacramento New Orleans Austin Rochester Hartford Tulsa Quebec Salt Lake City Cincinnati

8439 8418 8288 7942 7712 7686 7250 7204 7164 7116 7104 6918 6790 6732 6466 6247 5948 5244 5022 4604

0.21 0.21 0.20 0.20 0.19 0.19 0.18 0.18 0.18 0.18 0.18 0.17 0.17 0.17 0.16 0.15 0.15 0.13 0.12 0.11

USA USA USA Canada USA USA Canada USA USA Canada USA USA USA USA USA USA USA Canada USA USA

Table 13.4 Advertising network connectivity of Northern American cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

New York Toronto Chicago Los Angeles San Francisco Atlanta Miami Denver Minneapolis Washington Dallas Detroit Seattle Montreal Portland Vancouver Boston Baltimore

GROSS CONNECTIVITY 20,752 12,564 10,578 8257 8011 6602 6000 5115 4663 4620 3997 3752 3074 2846 2635 2347 2254 1873

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK) 1.00 0.61 0.51 0.40 0.39 0.32 0.29 0.25 0.22 0.22 0.19 0.18 0.15 0.14 0.13 0.11 0.11 0.09

COUNTRY

USA Canada USA USA USA USA USA USA USA USA USA USA USA Canada USA Canada USA USA

157

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Table 13.4 Advertising network connectivity of Northern American cities (continued). RANK

CITY

19 20 21 22 23 24 25 26 27 28 29 30 31 32 33= 33= 33= 33= 33= 33= 33= 33= 41 42 43 44= 44= 44= 44= 44= 44= 44= 44= 44= 44= 44= 44=

St Louis Kansas City Pittsburgh Sacramento Quebec Calgary Salt Lake City Houston Ottawa Indianapolis Honolulu San Diego San Jose Austin Columbus Phoenix Cleveland Tampa Orlando Memphis Birmingham New Orleans Nashville Edmonton Milwaukee Philadelphia Charlotte Richmond Las Vegas Hartford Omaha Raleigh Winnipeg Tulsa Rochester Halifax Cincinnati

GROSS CONNECTIVITY 1534 1436 1396 1306 1185 1044 970 914 903 852 782 743 652 604 440 440 440 440 440 440 440 440 388 342 236 0 0 0 0 0 0 0 0 0 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK) 0.07 0.07 0.07 0.06 0.06 0.05 0.05 0.04 0.04 0.04 0.04 0.04 0.03 0.03 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

COUNTRY

USA USA USA USA Canada Canada USA USA Canada USA USA USA USA USA USA USA USA USA USA USA USA USA USA Canada USA USA USA USA USA USA USA USA Canada USA USA Canada USA

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Table 13.5 Legal services network connectivity of Northern American cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17= 17= 17= 17= 17= 17= 17= 24 25 26 27= 27= 27= 27= 27= 27= 27= 27= 27= 27= 27= 27= 27= 27=

New York Washington Chicago Los Angeles San Francisco San Diego Dallas Baltimore Boston Miami Houston Atlanta Toronto Philadelphia Austin Cleveland Minneapolis Seattle Phoenix Tampa Sacramento Las Vegas Raleigh Columbus Pittsburgh Quebec Montreal Denver Vancouver Portland Detroit Calgary Kansas City Orlando Charlotte Indianapolis St Louis Ottawa Milwaukee San Jose

GROSS CONNECTIVITY 4368 2849 1875 1334 1255 1065 944 795 665 631 620 525 492 483 404 325 324 324 324 324 324 324 324 201 136 130 0 0 0 0 0 0 0 0 0 0 0 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.89 0.58 0.38 0.27 0.25 0.22 0.19 0.16 0.13 0.13 0.13 0.11 0.10 0.10 0.08 0.07 0.07 0.07 0.07 0.07 0.07 0.07 0.07 0.04 0.03 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

COUNTRY

USA USA USA USA USA USA USA USA USA USA USA USA Canada USA USA USA USA USA USA USA USA USA USA USA USA Canada Canada USA Canada USA USA Canada USA USA USA USA USA Canada USA USA

159

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Table 13.5 Legal services network connectivity of Northern American cities (continued). RANK

CITY

27= 27= 27= 27= 27= 27= 27= 27= 27= 27= 27= 27= 27= 27= 27=

Richmond Memphis Hartford Nashville Honolulu Omaha Salt Lake City Winnipeg Tulsa Edmonton Rochester Halifax Birmingham Cincinnati New Orleans

GROSS CONNECTIVITY 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

COUNTRY

USA USA USA USA USA USA USA Canada USA Canada USA Canada USA USA USA

In advertising, there are 12 cities divided into five strata identified as the leading world cities of Northern America with only one city (Toronto) from Canada. New York is the most connected city in the world (Table 13.4). After New York, Toronto and Chicago are found in two distinct strata. In the fourth stratum, two Sunbelt cities from the west coast, Los Angeles and San Francisco are found with connectivity values approximately two-fifths of New York. Detroit, located as the last city in the fifth stratum, is once again in the list of the leading world cities. Detroit might be dependent on other cities in financial services (Table 13.2), but because the auto industry constitutes a large proportion of national advertising, Detroit has become an important advertising centre. In this service sector, Houston experiences its biggest relative decline in rank, located as the 26th city with a network connectivity of 0.04, which is significantly lower than its connectivity values for all other sectors. This shows that ‘the world’s energy capital’ (Taylor and Lang, 2005, p5) is dependent on other cities for advertising services. Legal services are globally dominated by London, but in Northern America, New York is the dominant city (Table 13.5). Besides New York, there are ten more cities identified as the leading legal centres of Northern America. As the national capital of the United States and the anchor city for many intergovernmental and international organizations, the second city after New York is Washington, DC. In legal services, Toronto is not among the list of leading cities, it moves from second to thirteenth place with a proportionate connectivity value of 0.10. Atlanta is also not identified as a leading legal centre, with a proportionate connectivity of only 0.11. On the other hand,

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161

Baltimore and San Diego make it to the top as leading centres that attract international law firms, demonstrating a significant increase compared to their global connectivity rankings. Baltimore, a city with a reviving economy (Taylor and Lang, 2005), moves up from thirty-first to eighth place and San Diego moves up from twentieth to sixth place compared to their aggregate rankings (Table 13.1). Among the service sectors studied, advertising and legal services are the most concentrated sectors (legal services being more concentrated compared to advertising). In legal services, 43 cities out of the 55 cities have low proportionate connectivity values of 0.10 or below. Among these 43, 29 have zero proportionate connectivity meaning that there is no significant presence of international law firms in these cities (Table 13.5). In advertising, 38 of the 55 cities have proportionate connectivity values of 0.10 or below, and among these 38 cities, 12 have zero proportionate connectivity (Table 13.4). These results indicate that in Northern America, international law firms and advertising firms are concentrated in a small number of key cities, which is a general global pattern resulting from their industry characteristics. Management consultancy services demonstrate similar characteristics to accountancy in terms of having a flatter structure. Seventeen of the 55 cities have proportionate connectivity values of 0.30 and above (Table 13.6). In management consultancy, there are 20 cities identified as the leading cities in Northern America. New York is still the most connected city in Northern America and in the world followed by Chicago in the second stratum. Boston has its highest ranking in the management consultancy service sector, above Dallas and Toronto in the third stratum but below Atlanta and Washington, DC. One unanticipated finding in management consultancy is that Los Angeles and San Francisco are found in the fourth stratum and they rank with less important world cities like Philadelphia, Detroit and Minneapolis. The other surprising result is that the important Canadian world cities of Montreal and Vancouver are not among the highlighted leading cities. Instead, Calgary is found in the fifth stratum as the second leading Canadian city that attracts international management consultancy firms. The third set of results reveals the ‘hinterworlds’ of Northern American cities through geographic orientation towards the local region, Europe and Pacific Asia. Table 13.7(a) illustrates the local concentration of connections. In other regions there are some cities, typically the most important, that have negative local values indicating outward orientation. Northern America is unique in having no outward orientated city: New York is almost there with its zero score. Otherwise all Northern American cities are relatively over-linked with other cities in their own world region. However there is a strong tendency for the more important cities to be far less inwardly orientated: Toronto, Los Angeles, Chicago and Miami all score relatively low. Canadian cities appear less inward than US cities: all nine are in the lowest 20 values. In contrast to other regions there are many values in double figures with Salt Lake City, Charlotte and Las Vegas ranking as the top three. Taylor and Lang (2005)

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demonstrate that US cities are more locally oriented in their connections than cities in other parts of the world due to a less risky domestic market orientation of US companies. Thus even some of the most important world cities in the United States such as Seattle, San Diego, Portland, Baltimore and Phoenix will have very strong inward linkages.

Table 13.6 Management consultancy network connectivity of Northern American cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33=

New York Chicago Atlanta Washington Boston Dallas Toronto Philadelphia Los Angeles Houston Detroit Minneapolis San Francisco Cleveland Miami Calgary Charlotte Seattle Denver Tampa Pittsburgh San Diego Columbus Milwaukee Portland Montreal Indianapolis Phoenix St Louis Cincinnati Vancouver Kansas City Sacramento

GROSS CONNECTIVITY 12,568 7739 6309 6165 5938 5430 5356 4992 4956 4843 4764 4532 4443 4094 4076 3838 3750 3681 3551 3504 3336 3292 3278 3266 3241 3236 3208 3182 3128 3096 3012 2932 2798

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK) 1.00 0.62 0.50 0.49 0.47 0.43 0.43 0.40 0.39 0.39 0.38 0.36 0.35 0.33 0.32 0.31 0.30 0.29 0.28 0.28 0.27 0.26 0.26 0.26 0.26 0.26 0.26 0.25 0.25 0.25 0.24 0.23 0.22

COUNTRY

USA USA USA USA USA USA Canada USA USA USA USA USA USA USA USA Canada USA USA USA USA USA USA USA USA USA Canada USA USA USA USA Canada USA USA

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33= 35 36 37 38 39= 39= 41= 41= 41= 41= 41= 41= 41= 48 49 50 51 52 53 54 55

San Jose Memphis Orlando Tulsa Honolulu Las Vegas Salt Lake City Baltimore Richmond Nashville Winnipeg Edmonton Rochester Halifax Ottawa Hartford Austin Raleigh Omaha Quebec Birmingham New Orleans

2798 2736 2706 2618 2428 2398 2398 2108 2108 2108 2108 2108 2108 2108 1772 1750 1694 1418 1316 1256 1026 290

0.22 0.22 0.22 0.21 0.19 0.19 0.19 0.17 0.17 0.17 0.17 0.17 0.17 0.17 0.14 0.14 0.13 0.11 0.10 0.10 0.08 0.02

USA USA USA USA USA USA USA USA USA USA Canada Canada USA Canada Canada USA USA USA USA Canada USA USA

Table 13.7 City hinterworlds (regional concentrations of connections) of Northern American cities. (a) Relative concentration of connections to local region. CITY Salt Lake City Charlotte Las Vegas Austin Cincinnati New Orleans Nashville Cleveland Omaha Rochester Memphis Kansas City Orlando Tampa

INWARD 13.96 12.19 11.84 11.00 10.92 10.59 10.11 9.67 9.64 9.61 9.49 9.27 9.06 8.65

CITY

OUTWARD

163

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(a) Relative concentration of connections to local region (continued). CITY Pittsburgh Sacramento Richmond Seattle Phoenix Philadelphia San Diego St Louis Milwaukee Honolulu Columbus Indianapolis Tulsa Baltimore Raleigh Hartford Portland Birmingham Denver San Jose Houston Calgary Minneapolis Winnipeg Dallas Halifax Quebec Washington Atlanta Boston Edmonton San Francisco Detroit Ottawa Vancouver Montreal Miami Chicago Los Angeles Toronto New York

INWARD 8.43 8.37 8.37 8.30 8.15 7.97 7.96 7.96 7.79 7.57 7.49 7.49 7.42 7.39 7.14 7.03 6.86 6.77 6.65 6.60 6.56 6.37 6.25 6.03 5.88 5.43 4.93 4.63 4.38 4.21 4.02 3.94 3.94 3.92 3.62 3.10 2.94 2.83 2.78 0.50 0.00

CITY

OUTWARD

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(b) Relative concentration of connections to Europe. CITY New York Miami Chicago Boston

MORE EUROPEAN 1.39 0.62 0.61 0.29

CITY Omaha New Orleans Austin Las Vegas Salt Lake City Charlotte Birmingham Columbus Tampa Raleigh Sacramento Denver Nashville Richmond Cincinnati Orlando Memphis Cleveland Tulsa Indianapolis Kansas City Honolulu San Jose Rochester St Louis Houston Halifax Hartford San Francisco San Diego Seattle Portland Montreal Edmonton Quebec Phoenix Milwaukee Winnipeg Calgary Vancouver Dallas Pittsburgh

LESS EUROPEAN −4.20 −4.03 −4.00 −3.96 −3.84 −3.42 −3.15 −2.95 −2.94 −2.89 −2.74 −2.73 −2.71 −2.70 −2.68 −2.58 −2.48 −2.47 −2.47 −2.46 −2.45 −2.40 −2.23 −2.10 −2.06 −1.92 −1.83 −1.79 −1.71 −1.57 −1.54 −1.52 −1.43 −1.36 −1.35 −1.34 −1.06 −1.06 −1.04 −1.01 −1.00 −0.92

165

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(b) Relative concentration of connections to Europe (continued). CITY

MORE EUROPEAN

CITY Philadelphia Ottawa Los Angeles Atlanta Minneapolis Baltimore Washington Detroit Toronto

LESS EUROPEAN −0.76 −0.76 −0.74 −0.52 −0.41 −0.36 −0.24 −0.08 −0.02

(c) Relative concentration of connections to Pacific Asia. CITY New York Toronto Los Angeles Quebec Montreal Hartford Vancouver

MORE PACIFIC ASIAN 1.42 1.03 0.68 0.59 0.51 0.23 0.02

CITY Salt Lake City Phoenix Rochester San Diego St Louis Winnipeg Sacramento Orlando Seattle Baltimore Nashville Cleveland Philadelphia Las Vegas Detroit Richmond Cincinnati New Orleans Kansas City Minneapolis Memphis Raleigh Indianapolis Austin Milwaukee Charlotte Pittsburgh Birmingham Tampa

LESS PACIFIC ASIAN −3.09 −2.75 −2.62 −2.59 −2.57 −2.51 −2.45 −2.42 −2.38 −2.38 −2.31 −2.28 −2.17 −2.11 −2.10 −2.00 −2.00 −2.00 −1.99 −1.98 −1.96 −1.91 −1.87 −1.83 −1.79 −1.64 −1.61 −1.60 −1.50

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Omaha Miami Portland Ottawa Halifax San Jose Calgary Denver Washington Honolulu Edmonton Columbus Tulsa Dallas Houston Atlanta Boston Chicago San Francisco

167

−1.49 −1.48 −1.42 −1.41 −1.40 −1.21 −1.18 −1.17 −0.97 −0.90 −0.84 −0.78 −0.77 −0.74 −0.69 −0.68 −0.50 −0.40 −0.10

In terms of geographic orientation for Europe, there are four cities with overlinkages that have positive connectivity levels (Table 13.7(b)). Three are from the east coast, plus Chicago from the mid-west. New York is the most European-orientated city but its positive score is not very high compared to cities in other regions. There are six other cities with relatively low negative scores and therefore, in Northern American terms, are relatively over-linked to Europe. They are from similar regions as the previous set: Toronto, Detroit, Washington, DC, Baltimore and Minneapolis. The east coast and mid-west regions of Northern America have historical economic, political, social and cultural links with Europe, which still seem to be significant. However, 37 of the 55 cities have negative values below one, and three are below −4 (Omaha, New Orleans and Austin). Once more Canadian cities are distinctive as a group: eight of the nine Canadian cities are in the top 20 cities with the weakest underlinkage to Europe, again showing the strong international orientation of Canadian cities compared to the United States. In geographic orientation towards Pacific Asia, seven cities have positive connectivity values (Table 13.7 (c)). New York has the most over-linkage to Pacific Asia; four of the seven cities are from Canada. The two other US cities are Los Angeles and Hartford. The former is west coast and its neighbouring Pacific region world city, San Francisco, is the next ranked city in terms of Pacific Asian orientation (only just negative at −0.1). Canadian cities are strongly linked to Pacific Asia as well as to Europe. Unlike the European connectivity pattern, the most over-linked cities to Pacific Asia are not composed only of cities with high global connectivity. Some less important

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cities including Hartford and Quebec are among the most over-linked cities to Pacific Asia. Overall, however, and similar to the European-orientation connectivity pattern, under-linked cities to Pacific Asia are dominated by less important world cities. In conclusion, the Northern American world city network is dominated by US cities. New York is the most important world city in all studied service sectors as well as in terms of overall global connectivity. Toronto is the only city from Canada that is ranked second to New York in three of the five service sectors and in terms of global connectivity. However, Toronto’s connectivity values are much lower than New York’s and they can only be compared to cities such as Chicago, Los Angeles, Washington, DC and Atlanta. In terms of geographic orientation, Canadian cities are more outward oriented than US cities. The hinterworlds of Canadian cities are composed of strong links to Pacific Asia and Europe, whereas the cities in the United States are more inward oriented. The current global economic crisis might alter this situation as more US firms reach out to other parts of the world to increase business opportunities.

References Bourne, L. S. and Simmons, J. (2003) ‘New fault lines? Recent trends in the Canadian urban system and their implications for planning and policy’, Canadian Journal of Urban Research, vol 12, pp22–47 Carbonell, A. and Yaro, R. D. (2005) ‘American spatial development and the new megalopolis’, Land Lines, vol 17, pp1–4 Castells, M. (1989) The Informational City, Blackwell, Oxford Charney, I. (2003) ‘Spatial fix and spatial substitutability practices among Canada’s largest office development firms’, Urban Geography, vol 24, pp386–409 Clark, R. D. and Roche, J. B. (1984) ‘Functional typologies of metropolitan areas: an examination of their usefulness’, Urban Studies, vol 21, pp63–71 Faludi, A. (ed.) (2002) European Spatial Planning, Lincoln Institute of Land Policy, Cambridge, MA Florida, R. (2008) Who’s Your City? How the Creative Economy is Making Where to Live the Most Important Decision of Your Life, Basic Books, New York, NY Hall, P. and Pain, K. (eds) (2006) The Polycentric Metropolis: Learning from MegaCity Regions in Europe, Earthscan, London Lang, R. E. and Dhavale, D. (2005) Beyond Megalopolis: Exploring America’s New ‘Megapolitan’ Geography, Metropolitan Institute Census Report Series 05:01, Metropolitan Institute at Virginia Tech Lang, R. E. and Nelson, A. C. (2007) ‘America 2040: the rise of the megapolitans’, Planning Magazine of the American Planning Association, 6 January 2007 Macionis, J. and Parrillo, V. (2004) Cities and Urban Life, Prentice-Hall, Upper Saddle River, NJ Mohl, R. A. (ed.) (1997) The Making of Urban America, 2nd edition, Scholarly Resources, Wilmington, DE

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Newman, P. and Thornley, A. (2005) Planning World Cities: Globalization and Urban Politics, Palgrave Macmillan, New York, NY Rice, B. R. and Bernard, R. M. (1983) ‘Introduction’, in R. M. Bernard and B. R. Rice (eds) Sunbelt Cities: Politics and Growth Since World War II, University of Texas Press, Austin, TX, pp1–30 Sancton, A. (2001) ‘Canadian cities and the new regionalism’, Journal of Urban Affairs, vol 23, pp543–555 Sassen, S. (2001) The Global City: New York, London, Tokyo, 2nd edition, Princeton University Press, Princeton, NJ Taylor, P. J. and Aranya, R. (2008) ‘A global “urban roller coaster”? Connectivity changes in the world city network, 2000–04’, Regional Studies, vol 42, pp1–16 Taylor P. J. and Lang, R. E. (2005) US Cities in the ‘World City Network’, The Brookings Institution, Washington, DC (Survey Series, Metropolitan Policy Program)

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14

Latin American Cities in Globalization Francisco Castañeda, Jon Cloke and Ed Brown

.

Throughout the region, historically there has been a distinct lack of long-term planning in regard to the economies of Latin America. This in turn has resulted in a lack of urban planning and the subsequent uneven concentrations of rapidly-growing urban populations that have led to the current generation of megacities. These megacities act increasingly as concentrators and accumulators of the wealth of the country as a whole, dominating the national hinterland – centralization and concentration of economic and state power is a serious problem throughout Latin America and can be see in its extremes in city-regions such as Gran Caracas in Venezuela. This process of metropolitan concentration, derived to a great extent from the urban reflection of colonial and post-colonial power structures, has restricted the development of most of these cities, which might otherwise be more fully connected to global city networks – such megacities are increasingly hyper-conurbations of a differentially internally integrated character. Irrespective of the unbalanced nature of its connectivity, throughout Latin America the primal city-region has no rival in each country in terms of links to global city networks, except in the case of Brazil where, over time, São Paulo has successfully overtaken Rio de Janeiro among the top ten cities of Latin America in terms of global connectivity (Brazil itself constitutes 33 per cent of the Latin American population, including Central America (UN, 2007)). Thus, when the cities of the region are divided up in terms of connectivity, the first stratum is comprised of the cities of Buenos Aires, São Paulo and Mexico City (see Table 14.1), each at around a little more than half of the connectivity of London. In the second stratum are Caracas, Santiago and Bogotá, clearly differentiated from the top three in terms of connectivity, and in the third stratum are Lima, Montevideo, Rio de Janeiro, Panama City and Quito, again comprising a different order of connectivity with only about one-third of the global connectivity of London.

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Table 14.1 Global network connectivity of Latin American cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

Buenos Aires São Paulo Mexico City Caracas Santiago Bogotá Lima Montevideo Rio de Janeiro Panama City Quito Guatemala City San José Santo Domingo Guadalajara Guayaquil San Salvador Tegucigalpa Monterrey San Juan La Paz Asunción George Town Managua Nassau Medellín Hamilton Porto Alegre Curitiba Cali Puebla Tijuana Kingston Chihuahua

GROSS CONNECTIVITY 58,091 53,319 52,903 45,063 44,177 40,113 32,355 30,128 29,657 27,541 26,542 24,824 24,574 24,370 22,608 20,901 20,485 18,454 17,685 17,380 16,556 15,928 15,605 15,345 14,973 14,122 13,337 12,706 11,812 11,482 11,014 10,556 10,159 9208

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.60 0.55 0.55 0.47 0.46 0.42 0.34 0.31 0.31 0.29 0.28 0.26 0.26 0.25 0.23 0.22 0.21 0.19 0.18 0.18 0.17 0.17 0.16 0.16 0.16 0.15 0.14 0.13 0.12 0.12 0.11 0.11 0.11 0.10

COUNTRY

Argentina Brazil Mexico Venezuela Chile Colombia Peru Uruguay Brazil Panama Ecuador Guatemala Costa Rica Dominican Republic Mexico Ecuador El Salvador Honduras Mexico Puerto Rico Bolivia Paraguay Cayman Islands Nicaragua Bahamas Colombia Bermuda Brazil Brazil Colombia Mexico Mexico Jamaica Mexico

In terms of connectivity, then, and despite the major macroeconomic challenges that it has had to overcome in the last decade, Buenos Aires appears as the city in Latin America with the best global network connectivity, achieving not quite two-thirds of the connectivity of London. More than most

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countries of the region, Argentina has historically attempted policies that have acted to shape the economic landscape – Buenos Aires has the oldest stock exchange in Latin America, for instance, the Bolsa de Comercio de Buenos Aires (BCBA, 2009), which opened in 1854. By 1900 Argentina already had a market for early derivative instruments, and was advanced for that time in the region as well as being of great importance economically to Latin America more generally (Schwarzer, 2006). The development of a financial services sector occurred alongside the development of the agrarian sector, both being connected to and dependent on the importance of Buenos Aires as a port, a complementary factor that continues to produce important connections to global city networks. Historically, then, Buenos Aires has long had an important link with European trade by sea, in combination with its important agricultural sector and the developing financial services sector, with their internal links to the regional economy. This has allowed the development of various service industries over time, all of which are highly connected through European and US corporate offices established in Buenos Aires. The development of Mercosur (the Mercado Común del Sur, the Common Market of the South) in recent years has also reinforced some of these networks, despite various global economic crises of the past decade. São Paulo is highly connected to global cities networks through a variety of characteristics that differ from the connectivity of Buenos Aires. Brazil is the leader of Mercosur and the FTAA (the Free Trade Area of the Americas), reinforcing São Paulo as an ideal platform for business; its original wealth came from the export of coffee, and later urbanization itself was an economic engine. Currently, however, São Paulo is host to the newly-merged (2008) BM&FBOVESPA S.A., ‘the world’s third largest exchange and the second exchange in the Americas measured by market value’ (BOVESPA, 2008, p7) after the NYSE and Nasdaq, something reflected in the high degree of connection of the city’s financial services to global financial services. In terms of international, internal and regional connectivity, São Paulo contributes a substantial percentage of Brazil’s GNP; as of 2007 its millions of manufacturing workers made up about one-third of the economically active population of the metropolitan area. The growth in importance over recent years of Brazil as part of the BRIC group (Brazil, Russia, India, China) and the discovery of substantial quantities of oil off the Atlantic coast of the country, plus the increasing presence of Chinese strategic/commercial activities in the region, can only add to the degree of connectivity of São Paulo globally, especially because of the strategic importance of BM&FBOVESPA to the entire region. Mexico City is also highly connected in terms of global city networks. Its high relative connectedness to the US, relative to most other Latin American cities, is due to the historically close geographic and business interaction that Mexico City has with this country (Table 14.7(c)). It has allowed many foreign companies to anchor production in Mexico, establishing cross-border services in Mexico City due to lower operating costs. Another interesting phenomenon that has undoubtedly contributed to the developing connectivity of Mexico

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City has been the series of financial crises that the country has passed through, which in the case of the so-called ‘Tequila Crisis’ of 1994–1995 brought about a substantial increase in foreign penetration of the Mexican financial services sector. These three leading cities are also clearly distinguished by their geographical orientations (Table 14.7): 1 2 3

4

They are the only three cities that have negative values (i.e. are relatively under-linked) to other Latin American cities (Table 14.7(a)). They are the three highest positive scorers on linkages to European cities (Table 14.7(b)). They are highly ranked for Northern American links but are not overlinked like the smaller Mexican cities and the off-shore banking centres (Hamilton and Nassau) (Table 14.7(c)). São Paulo has the largest over-linkage to Pacific Asian cities but Mexico City and Buenos Aires only rank sixth and seventh respectively (Table 14.7(d)). Latin American countries of the Pacific Coast (e.g. Chile and Peru) maintain a strong public discourse about the importance of Pacific Asia to their future economic development (e.g. Biblioteca del Congreso Nacional de Chile, Portal Asia Pacífico 2009). Brazil, however is already negotiating closer integration with Northern Chile to facilitate the export of its products to Asia, a trend which involves joint public investment in motorways and ports as well as the promulgation of common phytosanitary, transport and customs regulations. Because of this increasing national proximity, São Paulo is becoming more closely connected to Pacific Asia than Santiago de Chile and Lima, ranked fourth and tenth respectively (Table 14.7(d)).

The second stratum is comprised of Caracas, Santiago de Chile and Bogotá (all with a global connectivity coefficient of between 0.4 and 0.5). In the case of Caracas (Venezuela), oil wealth has led to a multinational environment, with a full range of associated services (financial services, accountancy, banking and legal). In the case of Santiago (which city alone accounted for 35.91 per cent of the population of Chile according to the 2002 census (INE, 2002)), its connections to global city networks are smaller than those of Buenos Aires, despite exhibiting indices of economic stability, depth and growth well above average in Latin America (Schmidt-Hebbel, 2006). Chile’s pre-eminent position among the national economies of Latin America is not however reflected in the depth and degree of connectivity of Santiago city with the global city network. Connections to Pacific Asia for Santiago are stronger than for Buenos Aires and Mexico City, supporting the official discourse on the future of the Chilean economy that speaks of the importance of trading with this region: Chilean copper exports (for instance) are certainly much in demand in China. Considering the regions of the world, Santiago has more connectivity with the global city networks of Europe than Northern America.

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Bogotá exhibits a level of connectivity similar to that of Santiago de Chile but with Northern America more important than Europe (Table 14.7 (b) and (c)). With an economy derived from a wealth of natural resources but relatively low levels of development of manufacturing processing and industrial development more generally, this has led to the city developing an intermediate level of connectivity with global city networks. Moving away from consideration of just the top three strata, we can consider how cities fare when the overall connectivity is divided into its sector components. For instance, it is interesting to note (in Table 14.2) that the lower strata of cities, in terms of their connectivity, change when the sector under consideration is financial services, and in the context of regionally low degrees of connectivity outside the top eight or nine cities: the changes are very much determined by the principal economic activities and whether or not these are dominated by the extensive and complex offshore financial services sector of Latin America and the Caribbean. The top ten comprise the same cities (albeit in a different order) whereas at number 11 Nassau appears, up from 25 on the general table; George Town moves up to 14 from 23, and Hamilton to 15 from 27. This far stronger sectoral appearance is because of the importance of these cities in the offshore financial services and banking sector, which for many of them constitutes virtually their only channel of connectivity. Panama City, at 10 in the general table and 8 in the financial services table occupies an important place in both, because of its position as one of the oldest and most well-known (not to say notorious) offshore banking centres and because of the wide range of ancillary connectivity associated with the Panama Canal. Curitiba in Brazil makes a strong showing (ranked 16 in Table 14.2) because of its developing importance as a node for financial services operations, aided by the presence of numbers of multinational corporations (MNCs) attracted by its importance as a manufacturing and production centre, especially for cars; the Cidade Industrial de Curitiba hosts operational subsidiaries of Nissan, Renault, Volkswagen, Audi, Volvo, HSBC, Siemens, ExxonMobil, Electrolux and Kraft Foods. Some of the cities in the lower strata whose overall connectivity puts them in a higher rank move substantially lower in the financial services connectivity because their principal economic activities do not of necessity require an intensity of financial services presence. Thus Guadalajara (see below), Guayaquil, Quito and Santo Domingo are not as well-connected to financial services networks as some of the Caribbean cities which are economically less important to the national hinterland than they are. The Dominican Republic, for instance, is the largest economy in Central America according to the US Department of State (2009), and Santo Domingo plays a major part in this. The Dominican manufacturing sector is responsible for nearly a third of GDP, whereas the growing services sector (including tourism) is just short of 60 per cent of GDP. The fact that 75 per cent of Dominican exports go to the US and that the US is a substantial contributor to another important component of the Dominican economy, tourism, means that the Dominican economy (and by

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Table 14.2 Financial services network connectivity of Latin American cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28= 28= 28= 28= 28= 28= 28=

São Paulo Buenos Aires Mexico City Santiago Caracas Bogotá Lima Panama City Rio de Janeiro Montevideo Nassau San José Tegucigalpa George Town Hamilton Curitiba Asunción San Salvador Quito Monterrey Kingston La Paz Guatemala City Santo Domingo San Juan Porto Alegre Guayaquil Guadalajara Managua Medellín Cali Puebla Tijuana Chihuahua

GROSS CONNECTIVITY 14,669 13,823 12,459 10,011 9034 7346 7175 5733 5127 4952 3196 3074 2750 2713 2364 2114 1978 1955 1796 1762 1732 1692 1616 1584 1104 906 190 0 0 0 0 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.54 0.51 0.46 0.37 0.33 0.27 0.27 0.21 0.19 0.18 0.12 0.11 0.10 0.10 0.09 0.08 0.07 0.07 0.07 0.07 0.06 0.06 0.06 0.06 0.04 0.03 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00

COUNTRY

Brazil Argentina Mexico Chile Venezuela Colombia Peru Panama Brazil Uruguay Bahamas Costa Rica Honduras Cayman Islands Bermuda Brazil Paraguay El Salvador Ecuador Mexico Jamaica Bolivia Guatemala Dominican Republic Puerto Rico Brazil Ecuador Mexico Nicaragua Colombia Colombia Mexico Mexico Mexico

extension that of Santo Domingo) is strongly focused on the US and US transnational corporations (TNCs) (which have their own financial services provision), which would tend to explain the paucity of financial services connectivity of the republic itself.

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Some of the more interesting changes in Table 14.3 on accountancy services connectivity juxtapose relatively strong showings by these same cities, for instance Guadalajara, which with a connectivity coefficient of 0.51 moves up to 7th in the table. There are a number of reasons why Guadalajara should make such a strong showing in terms of its accountancy services network connectivity, aside from being the second most populous metropolitan area in Mexico after that of Mexico City (Consejo Nacional de Población, 2006). As well as being a substantial centre of agro-exports to the US and an important centre for pharmaceutical production, the Guadalajaran metropolitan region has become known as Mexico’s ‘Silicon Valley’. The development of software and informatics sectors in the city-region, as well as increasing foreign direct investment would explain the development of a strong accountancy services network internationally and perhaps also the strong showing in legal services connectivity (9th place in Table14.5 below).

Table 14.3 Accountancy network connectivity of Latin American cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Buenos Aires Mexico City São Paulo Caracas Bogotá Santiago Guadalajara Quito Rio de Janeiro Lima Montevideo Guayaquil Guatemala City San José Santo Domingo Panama City San Salvador La Paz Monterrey George Town Medellín San Juan Nassau Porto Alegre

GROSS CONNECTIVITY 25,610 22,945 22,755 22,488 22,243 21,157 20,593 19,146 17,760 16,882 16,352 15,780 15,480 14,994 14,720 14,013 12,624 12,378 12,135 11,747 11,574 10,510 10,400 10,192

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.63 0.57 0.56 0.56 0.55 0.52 0.51 0.47 0.44 0.42 0.40 0.39 0.38 0.37 0.36 0.35 0.31 0.31 0.30 0.29 0.29 0.26 0.26 0.25

COUNTRY

Argentina Mexico Brazil Venezuela Colombia Chile Mexico Ecuador Brazil Peru Uruguay Ecuador Guatemala Costa Rica Dominican Republic Panama El Salvador Bolivia Mexico Cayman Islands Colombia Puerto Rico Bahamas Brazil

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25 26 27 28 29 30 31 32 33 34

Puebla Tegucigalpa Curitiba Hamilton Managua Asunción Tijuana Cali Chihuahua Kingston

9870 9762 9698 9520 9409 9400 9228 9150 8906 5168

0.24 0.24 0.24 0.24 0.23 0.23 0.23 0.23 0.22 0.13

177

Mexico Honduras Brazil Bermuda Nicaragua Paraguay Mexico Colombia Mexico Jamaica

Guayaquil in Ecuador also makes a stronger showing in Table 14.3 (ranked 12th); among the reasons for a strong showing in accountancy services networks are that Guayaquil is the largest city and main port in Ecuador (and one of the busiest in South America) and an important transport node, particularly for the export of hydrocarbons from the interior of Ecuador; almost all imports to Ecuador and a substantial part of its exports pass through Guayaquil. The port of Guayaquil is also Ecuador’s most important manufacturing and processing centre, in terms of the manufacture of consumer goods as well as services for the processing of primary commodities – sawmills, foundries, tanneries and sugar refineries. Similarly Medellín shows its highest degree of connectivity in the accountancy services table (scores 0.29, ranked 21). In the strong economic recovery experienced by Colombia post-2002, Medellín played a central role in terms of its manufacturing productivity, particularly the textiles industry, of which the city is the most important Colombian centre. Puebla in Mexico also moves up the Table 14.3 (scores 0.24, ranked 25th); the state of Puebla is the seventh most important in economic terms out of all the Mexican states, producing some 3.7 per cent of Mexican GDP (INEGI, 2006) as a result of its strong manufacturing/industrial base, which includes the Mexican base for Volkswagen. Within the lower strata of city-regions there are two groups of note, one being producer/manufacturer city-regions with better accounting services connectivity, and the other being those keyed into the offshore network that have better financial services connectivity. Another port city making a stronger showing here is San Juan (Table 14.2 and 14.3), whose connectivity is due to its importance as a manufacturing and production centre as well as being a port, and which also contains a financial centre of importance throughout the Caribbean as well as being an important centre and conduit for tourism in Puerto Rico. A combination of these factors, but particularly the importance of the port for manufacture and export (chemicals, textiles and electronics, for example) are why the city-region shows up in terms of international financial and accountancy networks connectivity. The advertising networks revealed in Table 14.4 show that there are a number of cities lower down the general connectivity table and the

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manufacturer/industrial cities rank, which have stronger advertising network connectivity than particularly the financial services cities and even some of the manufacturer/industrial cities; these include Managua, San Salvador, Tegucigalpa and Asunción. It would be tempting to assume that, having lost rank for political and historical reasons and being located in the poorer countries in Central and Southern America, these cities have formed stronger advertising network links as one means by which to make themselves betterknown nationally, intra-nationally and internationally as competitive sites for doing business. Some of the more important manufacturer/industrial cityregions also perform more strongly in the advertising connectivity table for perhaps the same reason, which is to say the perceived importance of advertising in maintaining the inflow of foreign and national investment into a particular city-region. (There are obvious exceptions to this in the table, for instance Guadalajara.)

Table 14.4 Advertising network connectivity of Latin American cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Buenos Aires Mexico City Caracas São Paulo Santiago Montevideo Lima Santo Domingo Panama City Guatemala City Bogotá San Salvador San José San Juan Guayaquil Managua Tegucigalpa Quito Rio de Janeiro Asunción La Paz Monterrey Medellín Kingston

GROSS CONNECTIVITY 12,818 11,056 10,285 9837 8410 7294 6926 6804 6769 6702 6432 5906 5244 5138 4931 4910 4680 4574 4474 3524 2486 1592 1522 1520

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK) 0.62 0.53 0.50 0.47 0.41 0.35 0.33 0.33 0.33 0.32 0.31 0.28 0.25 0.25 0.24 0.24 0.23 0.22 0.22 0.17 0.12 0.08 0.07 0.07

COUNTRY

Argentina Mexico Venezuela Brazil Chile Uruguay Peru Dominican Republic Panama Guatemala Colombia El Salvador Costa Rica Puerto Rico Ecuador Nicaragua Honduras Ecuador Brazil Paraguay Bolivia Mexico Colombia Jamaica

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25= 25= 27 28 29 30= 30= 30= 30= 30=

Porto Alegre Cali Guadalajara Hamilton Puebla George Town Nassau Curitiba Tijuana Chihuahua

1306 1306 687 434 118 0 0 0 0 0

0.06 0.06 0.03 0.02 0.01 0.00 0.00 0.00 0.00 0.00

179

Brazil Colombia Mexico Bermuda Mexico Cayman Islands Bahamas Brazil Mexico Mexico

As far as legal services connectivity is concerned, the four Mexican cities of Monterrey, Tijuana, Chihuahua and Guadalajara move strongly up the table (Table 14.5), although the levels here are relatively weak (only São Paulo scores above the 0.10 level out of all the cities, and below 13th rank connectivity is zero). For the three northern cities this is almost certainly due to a combination of factors: the strategic proximity of the city-regions to the US and to the maquila (industrial) zones in Mexico, and immigration issues associated with movement into and out of the US. For Guadalajara, the importance of that cityregion as an industrial/manufacturing centre is probably central to international legal services connectivity. Management consultancy connectivity (Table 14.6) has few substantial changes; one of these however is Nassau ranked tenth, perhaps scarcely surprising given that in the economy of the Bahamas financial services are the second largest component of GDP; combined with business services, financial services constitute around 36 per cent of GDP (CIA, 2009a). The other more intriguing movement is that of Kingston in Jamaica (ranked eighth). There is a variety of reasons for this, although the pattern of connectivity of Kingston more closely conforms to that of a financial services centre, which Kingston is not, irrespective of the growth in importance of financial services there, particularly throughout the late 1990s. In the economy of Jamaica, over 64.7 per cent of GDP comes from services, of which tourism is by far the most important component, and 29.7 per cent from industry (mining, textiles, pharmaceuticals, food processing, oil refining and chemical derivatives)(CIA, 2009b). The government of Jamaica has been attempting to restructure the economy, for instance through the opening up of Free Trade Zones and by attempting to encourage foreign investment through a range of different incentives – it may well be that it is this set of initiatives that is responsible for Kingston’s relatively higher showing in the management consultancy table.

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Table 14.5 Legal services network connectivity of Latin American cities. RANK

CITY

1 2 3= 3= 5 6= 6= 6= 6= 6= 6= 6= 13 14= 14= 14= 14= 14= 14= 14= 14= 14= 14= 14= 14= 14= 14= 14= 14= 14= 14= 14= 14= 14=

São Paulo Buenos Aires Mexico City Monterrey Caracas Santiago Bogotá Rio de Janeiro Guadalajara Porto Alegre Tijuana Chihuahua Montevideo Lima Panama City Quito Guatemala City San José Santo Domingo Guayaquil San Salvador Tegucigalpa San Juan La Paz Asunción George Town Managua Nassau Medellín Hamilton Curitiba Cali Puebla Kingston

GROSS CONNECTIVITY 1020 486 470 470 450 302 302 302 302 302 302 302 184 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.21 0.10 0.10 0.10 0.09 0.06 0.06 0.06 0.06 0.06 0.06 0.06 0.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

COUNTRY

Brazil Argentina Mexico Mexico Venezuela Chile Colombia Brazil Mexico Brazil Mexico Mexico Uruguay Peru Panama Ecuador Guatemala Costa Rica Dominican Republic Ecuador El Salvador Honduras Puerto Rico Bolivia Paraguay Cayman Islands Nicaragua Bahamas Colombia Bermuda Brazil Colombia Mexico Jamaica

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Table 14.6 Management consultancy network connectivity of Latin American cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13= 13= 13= 16 17= 17= 17= 17= 17= 17= 17= 17= 17= 17= 27 28 29= 29= 29= 29= 29= 29=

Mexico City Buenos Aires São Paulo Santiago Bogotá Caracas Rio de Janeiro Kingston Monterrey Nassau Lima Montevideo San José Santo Domingo Tegucigalpa George Town Panama City Quito Guatemala City Guadalajara Asunción Managua Medellín Cali Puebla Tijuana Hamilton San Juan Guayaquil San Salvador La Paz Porto Alegre Curitiba Chihuahua

GROSS CONNECTIVITY 5973 5354 5038 4297 3790 2806 1994 1739 1726 1377 1372 1346 1262 1262 1262 1145 1026 1026 1026 1026 1026 1026 1026 1026 1026 1026 1019 628 0 0 0 0 0 0

PROPORTIONATE CONNECTIVITY (1.00 = NEW YORK) 0.48 0.43 0.40 0.34 0.30 0.22 0.16 0.14 0.14 0.11 0.11 0.11 0.10 0.10 0.10 0.09 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.08 0.05 0.00 0.00 0.00 0.00 0.00 0.00

COUNTRY

Mexico Argentina Brazil Chile Colombia Venezuela Brazil Jamaica Mexico Bahamas Peru Uruguay Costa Rica Dominican Republic Honduras Cayman Islands Panama Ecuador Guatemala Mexico Paraguay Nicaragua Colombia Colombia Mexico Mexico Bermuda Puerto Rico Ecuador El Salvador Bolivia Brazil Brazil Mexico

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Table 14.7 City hinterworlds (regional concentrations of connections) of Latin American cities. (a) Relative concentration of connections to local region. CITY Porto Alegre Curitiba La Paz San Salvador Medellín Chihuahua Santo Domingo Cali San José Guayaquil Managua San Juan Tijuana Tegucigalpa Quito Kingston Asunción Guadalajara Guatemala City Puebla Hamilton Nassau Panama City George Town Rio de Janeiro Montevideo Caracas Lima Bogotá Santiago Monterrey

INWARD 2.75 2.64 2.30 2.28 2.14 2.11 1.96 1.96 1.84 1.75 1.67 1.65 1.65 1.63 1.61 1.57 1.47 1.30 1.23 1.12 1.08 0.97 0.94 0.92 0.90 0.84 0.65 0.65 0.34 0.16 0.10

CITY Buenos Aires Mexico City São Paulo

OUTWARD −0.74 −0.66 −0.43

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(b) Relative concentration of connections to Europe. CITY Buenos Aires Mexico City São Paulo Panama City Caracas Santiago Guatemala City

MORE EUROPEAN 1.14 0.98 0.37 0.19 0.18 0.13 0.11

CITY Cali Porto Alegre Tijuana George Town Chihuahua Medellín Asunción San Salvador San José Santo Domingo Kingston Tegucigalpa Quito Hamilton Curitiba Bogotá Nassau San Juan Rio de Janeiro Guadalajara Puebla Guayaquil La Paz Monterrey Managua Lima Montevideo

LESS EUROPEAN −2.47 −1.88 −1.82 −1.81 −1.63 −1.53 −1.37 −1.23 −1.12 −1.07 −1.00 −0.99 −0.93 −0.89 −0.81 −0.71 −0.69 −0.65 −0.63 −0.53 −0.53 −0.49 −0.49 −0.41 −0.32 −0.28 −0.27

183

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(c) Relative concentration of connections to Northern America. CITY Monterrey Tijuana Puebla Guadalajara Chihuahua Nassau Porto Alegre Hamilton

MORE NORTHERN AMERICAN 3.23 1.18 0.81 0.72 0.68 0.61 0.49 0.16

CITY La Paz San Salvador Tegucigalpa Quito Asunción Santo Domingo Caracas Guayaquil Guatemala City Panama City San Juan San José Lima Montevideo Curitiba Santiago George Town Kingston Cali Managua Medellín São Paulo Mexico City Rio de Janeiro Buenos Aires Bogotá

LESS NORTHERN AMERICAN −4.05 −3.29 −3.26 −3.11 −3.07 −3.06 −2.51 −2.48 −2.39 −2.21 −2.13 −2.05 −1.96 −1.84 −1.75 −1.67 −1.40 −1.15 −0.98 −0.94 −0.93 −0.79 −0.53 −0.45 −0.44 −0.35

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(d) Relative concentration of connections to Pacific Asia. CITY São Paulo George Town Caracas Santiago Bogotá Mexico City

MORE PACIFIC ASIAN 1.09 0.77 0.28 0.26 0.24 0.04

CITY Puebla Guadalajara Chihuahua Managua Porto Alegre Hamilton San Juan Tijuana Monterrey Nassau Guayaquil Curitiba Guatemala City San Salvador Panama City La Paz Asunción Cali Santo Domingo Tegucigalpa Montevideo San José Rio de Janeiro Kingston Lima Quito Medellín Buenos Aires

LESS PACIFIC ASIAN −2.80 −2.69 −2.18 −1.97 −1.97 −1.93 −1.73 −1.70 −1.62 −1.57 −1.47 −1.45 −1.45 −1.39 −1.29 −1.09 −0.90 −0.87 −0.85 −0.74 −0.60 −0.55 −0.54 −0.50 −0.44 −0.39 −0.26 −0.09

References BCBA (2009) La Bolsa, www.bcba.sba.com.ar/institucional/labolsa.php, accessed 10 March 2010 Biblioteca del Congreso Nacional de Chile, Portal Asia Pacífico (2009) http://asiapacifico.bcn.cl/noticias/politica/cuenta-21-mayo-2009-asia-pacifico, accessed 10 March 2010 BOVESPA (2008) BOVESPA’s Facts and Figures, www.bmfbovespa.com.br/enus/bmfbovespa/download/FactsFigures.pdf, accessed 10 March 2010 CIA (2009a) ‘The Bahamas’, The World Factbook, www.cia.gov/library/publications/ the-world-factbook/geos/bf.html, accessed 10 March 2010 CIA (2009b) ‘Jamaica’, The World Factbook, www.cia.gov/library/publications/theworld-factbook/geos/jm.html, accessed 10 March 2010

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Consejo Nacional de Población, México (2006) Proyecciones de la Población de México 2005–2050, www.conapo.gob.mx/00cifras/proy/Proy05-50.pdf, accessed 10 March 2010 INE (2002) ‘Chile – proyecciones de población al 30 de junio (1990–2020): Región Metropolitana de Santiago’, Instituto Nacional de Estadisticas, www.ine.cl/canales/chile_estadistico/home.php, accessed 10 March 2010 INEGI (2006) Sistema de Cuentas Nacionales de México, Producto Interno Bruto por Entidad Federativa, 2001–2006, www.inegi.org.mx/prod_serv/contenidos/espanol/ bvinegi/productos/derivada/regionales/pib/pibe2006.pdf, accessed 10 March 2010 Schmidt-Hebbel, K. (2006) ‘Chile’s economic growth’, Cuadernos de Economía, vol 43, pp5–48 Schwarzer, J. (2006) ‘La industria argentina en la perspectiva de la historia’, in J. Gelman (ed.) La Historia Económica Argentina en la Encrucijada: Balances y Perspectivas, Prometeo Libros, Buenos Aires, pp333–350 UN (2007) Demographic Yearbook, United Nations Statistics Division, UN, http://unstats.un.org/unsd/demographic/products/dyb/dyb2007.htm, accessed 10 March 2010 US Department of State (2009) ‘Background Note: Dominican Republic’, June 2009, www.state.gov/r/pa/ei/bgn/35639.htm, accessed 10 March 2010

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Global Synthesis

Regional Geography of Global Servicing Peter J. Taylor

The nine world regions dealt with in this section are all very different in history and culture but their cities have all been experiencing some degree of ‘global servicing’ activity, as evidenced by their inclusion in the worldwide office networks of business service firms. Clearly financial, professional and creative services have become globalized. But it is also equally clear that this globalization is very uneven: there is a geography to global servicing activity. Comparing our regions provides a very basic instrument for describing this global geography and that is the task of this brief summary of Part B’s results. In the Introduction to Part B we indicated that our world regions constitute a core-periphery patterning of the world economy with Europe, Northern America and Pacific Asia between them defining the core of contemporary globalization. This is directly reflected in Table B.1 where the regions are ranked in terms of the average global network connectivity of their top five cities. This shows how the leading cities are integrating their regions into the world city network. The rank order is not surprising. The three ‘core’ regions are ranked 1, 2, 3 and Eurasia and Sub-Saharan Africa are somewhat adrift at the bottom of the table. The relatively low level of integration for Northern America can be noted again and here we can appreciate also the relatively high level for Latin America. Also, Australasia and Eurasia are by far the smallest regions and it can be suggested that these do not ‘need’ five leading cities for network integration; this might account for their relatively low rankings in the table.

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Table B.1 Regional integrations into the world city network via leading cities. WORLD REGION 1 2 3 4 5 6 7 8 9

Europe Pacific Asia Northern America Latin America Australasia Middle East/North Africa South Asia Eurasia Sub-Saharan Africa

TOP 5 CITIES MEAN GNC 0.75 0.74 0.62 0.53 0.43 0.42 0.40 0.30 0.29

The global network connectivity measures are aggregates across the five service sectors in the data. When these are disaggregated to individual sector results, different patterns occur, because firms in different services tend to have developed different global strategies (see Chapter 3). These varying geographies are shown in Tables B.2–B.6 where top five city averages are given for each service sector in each world region. Table B.2 ranks the regions for financial services connectivity of leading cities. This shows clearly the importance of Pacific Asia in financial services networks; the region is ranked first and its score of 0.81 is the highest recorded in any of the five sectors. Note that apart from the swapping positions of the two top ranked regions, the other rankings are the same as in Table B.1. However there are some relative differences in the actual scores, notably the gap between Northern America and Latin America widening, and Sub-Saharan Africa with a very low score adrift alone at the bottom. Clearly financial connectivities appear to accentuate differences between the core and the rest through their concentration in a limited number of international financial centres. Thus this sector can be summarized as a powerful discriminator along wealth lines, plus having a specific bias towards Pacific Asia.

Table B.2 Financial services: regional integrations into the world city network. WORLD REGION 1 2 3 4 5 6 7 8 9

Pacific Asia Europe Northern America Latin America Australasia Middle East/North Africa South Asia Eurasia Sub-Saharan Africa

TOP 5 CITIES AVERAGE 0.81 0.76 0.61 0.46 0.37 0.35 0.31 0.23 0.14

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Accountancy connectivities in Table B.3 seem to be the obverse of financial services. Firms in this sector tend to have very large office networks so that they link together all parts of the world economy. Thus although the ranking is a little disturbed, all world region scores are compressed, with Latin America actually catching up with Northern America for accountancy. With the squashing together of the scores, changes in ranking are not that relevant although it is noteworthy that Sub-Saharan Africa rises off the bottom, a real reflection of the worldwide scope of large accountancy firms.

Table B.3 Accountancy: regional integrations into the world city network. WORLD REGION 1 2 3= 3= 5 6 7 8 9

Europe Pacific Asia Northern America Latin America Middle East/North Africa Australasia South Asia Sub-Saharan Africa Eurasia

TOP 5 CITIES AVERAGE 0.70 0.65 0.57 0.57 0.55 0.51 0.44 0.40 0.37

Large advertising firms also tend to have worldwide networks but with concentration at the national level to capture ‘national markets’: they tend to locate in the main media city of each country. This means they are well represented in the top five cities of each region and so the connectivities in Table B.4 are again compressed, but not to the same degree as for accountancy. In addition there is a surprise at the top with Pacific Asia ranked first and Northern America third. Although advertising is an archetypal US business service, its very large firms (i.e., those included in this study) are highly concentrated in New York to the detriment of other US cities in this study. Table B.4 Advertising: regional integrations into the world city network. WORLD REGION 1 2 3 4 5 6 7 8= 8=

Pacific Asia Europe Northern America Latin America Australasia Middle East/North Africa South Asia Eurasia Sub-Saharan Africa

TOP 5 CITIES AVERAGE 0.68 0.67 0.58 0.53 0.51 0.50 0.42 0.30 0.30

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Legal services are the complete opposite of accountancy and advertising in being the services most concentrated into a limited number of leading cities. Table B.5 shows this sector to be even more concentrated in the three core regions than financial services (Table B.2). Note that Northern America and Pacific Asia swap positions for this service. But the key results are the very low scores for all the other regions. The zero score for South Asia is an artefact of their regulations keeping out foreign law firms (see Chapter 7) but on this evidence these protectionist policies hardly seem to be necessary!

Table B.5 Legal services: regional integrations into the world city network. WORLD REGION 1 2 3 4 5 6= 6= 8 9

Europe Northern America Pacific Asia Eurasia Australasia Latin America Middle East/North Africa Sub-Saharan Africa South Asia

TOP 5 CITIES AVERAGE 0.65 0.47 0.45 0.17 0.13 0.12 0.12 0.04 0.00

Management consultancy is the archetypal US-grown business service and this is reflected in Table B.6 where Northern America is ranked first for the only time in this analysis. Otherwise the regions are in their usual rankings but with relatively low scores; the latter is less the case for South Asia, which rises one rank.

Table B.6 Management consultancy: regional integrations into the world city network. WORLD REGION 1 2 3 4 5 6 7 8 9

Northern America Europe Pacific Asia Latin America Australasia South Asia Middle East/North Africa Eurasia Sub-Saharan Africa

TOP 5 CITIES AVERAGE 0.62 0.58 0.54 0.39 0.32 0.26 0.15 0.14 0.13

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These results are summarized in Table B.7, which shows service profiles of world regions. The numbers are derived from the difference between global network connectivity means in Table B.1 and the averages for each sector in Tables B.2–B.6. These differences have been standardized to ease interpretation. Taking each world region in turn the profiles are as follows: • • •

• •

• • • •

European top cities are relatively strongly connected through financial services and legal services. Pacific Asian top cities are exceptionally well connected through financial services but show no strengths elsewhere. Northern American top cities are exceptionally well connected through management consultancy, are strongly connected through legal services with strength also in financial services. Latin American top cities have relatively small connectivity strengths in accountancy and management consultancy. Australasian top cities have very strong connections in advertising and relatively strong connectivity strengths in accountancy and management consultancy. Middle East/North African top cities are relatively strongly connected through advertising and accountancy. South Asian top cities are relatively strongest in advertising connectivity and have small strengths in accountancy and management consultancy. Eurasian top cities are especially well connected through legal services with strength also in accountancy. Sub-Saharan African top cities are relatively strongly connected in accountancy and have strength in advertising. (Note: the positive value for law is an artefact of the methodology: the region cannot score as low as other regions because of its initial low global network connectivity.)

Table B.7 World regions: relative integrations into the world city network by service sectors. WORLD REGION

FINANCIAL ACCOUNTANCY ADVERTISING LEGAL MANAGEMENT SERVICES SERVICES CONSULTANCY

Europe Pacific Asia Northern America Latin America Australasia Middle East/North Africa South Asia Eurasia Sub-Saharan Africa

0.92 1.87 0.61 −0.33 −0.17 −0.33 −0.65 −0.33 −1.59

−1.05 −1.56 −1.05 0.11 0.63 1.28 0.11 0.50 1.02

−1.45 −1.10 −0.74 –0.02 1.41 1.41 0.34 –0.02 0.16

1.41 −0.28 0.97 −1.35 −0.37 −0.37 −1.26 1.15 0.08

−0.28 −0.69 2.07 0.14 0.55 −1.66 0.14 −0.14 −0.14

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In general we can conclude that there is a concentration of financial services and legal services integrating the first three regions into the world city network, and accountancy and advertising dominate the integration of the other regions into the world city network. The one exception to this generalization is the strength of legal services in Eurasian top cities; this relates to a unique legal market created by privatization of state assets in the 1990s. For the global analysis of hinterworlds the focus is on the leading city of each world region. In which direction are these cities leading their regions: east or west? Table B.8 shows the hinterworld scores for all nine leading cities. There are four general points to make initially: 1

2 3 4

With the exception of Hong Kong all leading cities score zero or negatively for relative levels of connections to their neighbouring regional cities. This shows the trans-regional, and possibly global, emphasis of their respective hinterworlds. With the exception of Mumbai, all non-European cities score positively towards Europe. With the exception of London, all non-Northern American cities score negatively towards Northern America. With the exception of small negative scores by Buenos Aires and Istanbul, all non-Pacific Asian cities score positively on Pacific Asia. Clearly this result reflects the more limited integration of US cities into the world city network identified earlier.

Considering the individual hinterland profiles of leading cities in Table B.8, the relative connectivity scores for the leading cities of the first three world regions can only be used to compare two directions: London has much stronger relative links to Pacific Asian cities over Northern American cities, whereas New York has similar strength links to European cities and Pacific Asian cities. Hong Kong has stronger links to European cities than to Northern American cities. The hinterworlds of the final six leading cities split unevenly between the three globalization core regions. Three cities have by far their strongest connectivity with Pacific Asian cities: Sydney, Mumbai and Johannesburg. This may be an important part of a reorientation process of Australasia, South Asia and Sub-Saharan Africa towards Pacific Asia. Three cities have their strongest connectivity with European cities: Buenos Aires, Istanbul and Moscow. This suggests the continuation of strong historical and cultural links. However for the latter city, Pacific Asian orientation is quite close to the European score. Overall, the main surprise in these results is the relative under-connectivity of Northern American cities (except New York) given their continuing importance in the world economy.

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London Hong Kong New York Buenos Aires Sydney Istanbul Mumbai Moscow Johannesburg

Europe Pacific Asia Northern America Latin America Australasia Middle East/North Africa South Asia Eurasia Sub-Saharan Africa

−0.01 1.51 0.00 −0.74 −0.52 −0.07 −0.20 −0.74 −0.17

RELATIVE CONCENTRATION OF CONNECTIONS TO LOCAL REGION (−0.01) 0.88 1.39 1.14 0.63 1.71 −0.67 1.84 0.24

RELATIVE CONCENTRATION OF CONNECTIONS TO EUROPE 0.10 −0.13 (0.00) −0.44 −0.29 −1.79 −0.41 −1.73 −2.10

RELATIVE CONCENTRATION OF CONNECTIONS TO NORTHERN AMERICA

Note that scores within brackets are where connectivities to Europe, Northern America or Pacific Asia are also ‘local’ scores for the city concerned.

LEADING CITY

WORLD REGION

Table B.8 Hinterworlds of leading cities by regions.

1.86 (1.51) 1.42 −0.09 1.85 −0.04 1.62 1.37 0.99

RELATIVE CONCENTRATION OF CONNECTIONS TO PACIFIC ASIA

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Part C

KEY COUNTRY AND SUB-REGIONAL CONNECTIVITY PROFILES

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Introduction Peter J. Taylor

The final section has been designed to showcase city connectivities at the state level, again based on the analysis of the 525 cities  175 firms service matrix with its 91,875 pieces of information. Although this book is a ‘global urban analysis’, this does not mean that we should neglect nation-states and their influence on intercity relations. Globalization does not mean the end of the state; rather it entails a spatial restructuring of economic activities in which the state continues to be implicated. Thus the question is how do states relate to the cities located in their territories, given the immense growth in global spaces of flows? The starting point is a negative one: we cannot continue to consider intercity relations as ‘national urban systems’, as separate urban hierarchies in each individual country. It is precisely such state-centric views of the world that are transcended by the processes creating contemporary globalization. An initial corrective has been to ‘upscale’ the argument by identifying the cities at the top of each national urban hierarchy as the ‘gateway’ linking their respective national economies to the new global economy. But no, such thinking continues a simplistic ‘international relations’ framework that misses the myriad opportunities and possibilities that constitute contemporary global spaces of flows. The global economy is so much more complex than a limited number of international links. With current communication technologies, the ‘informational economy’ that makes doing business at a global scale practical does not have to be squeezed through a single gateway to enter a country; knowledge flows can criss-cross through economic space along all manner of routes. This does not mean that the criss-crossing is not concentrated in certain favoured locales – some cities are more important than others – but that the pattern of flows is much more complex than one gateway per country. There may be ‘global cities’ that are immensely important in the global economy, and certainly such a description fits New York and London (NYLON) as shown in Part A, but there are no ‘un-global cities’. Globalization is all-encompassing, all cities are connected to all other cities, albeit most dyads do not approach the density of flows found in NYLON. Thus every city in every country is connected to the world city network; the city connectivities reported in Part C allow intra-state comparisons of cities to be made in terms of their different positions in the world city network.

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To facilitate these intra-state comparisons, the threshold for a city’s inclusion in analyses has been reduced from a connectivity of 0.1 used in Part B to a score of 0.05. Obviously this provides more cities for comparison, making country studies more interesting, but there is a downside to this extension. With such a low connectivity score, cities are included that house a relatively small number of offices from our 175 firms. This means that one or two firms could dominate the computation of a city’s connectivity. For instance, a small port city may have had its local insurance company taken over by a global insurance firm resulting in its connectivity pattern largely reflecting the latter’s one-office network. As noted in the introduction to Part A, connectivity measures are based on aggregations of office networks in order to smooth out the particularities of any one office network. However, a city connectivity of only 0.05 might be susceptible to displaying idiosyncrasies of a single office network and therefore may produce one or two ‘surprising’ results. Clearly we are at the edge of viable results from our data with this low city entry threshold. However we have experimented with this set of cities and we think ‘surprises’ will be minimal: with very few exceptions, results reported below are meaningful and provide useful insights into city connectivities at the state scale. Not all states can be included since many include too few cities with connectivies above 0.05. We have selected the 13 countries that have five or more cities above the threshold: Australia, China, Japan, India, Germany, France, Switzerland, Italy, UK, Canada, US, Mexico and Brazil. However, this selection excludes some important cities, and therefore we have added chapters on a ‘subregional’ scale where a group of countries (that do not qualify) do seem to constitute a common economic zone. Nine such sub-regions are chosen: South East Asia, Arabian Gulf cities, ex-Soviet European cities, Eastern Europe, Nordic countries, Benelux, Iberia, Southern Africa and Central America. Thus Part C consists of 22 chapters, but they are shorter than previous chapters in that the text is organized around just four tables. As with chapters in Part B, we start with the basic table showing global network connectivities of cities in the state or sub-region. Many of these cities were included in the Part B tables; here they are repeated at this lower scale, and less important cities (i.e. with connectivities between 0.05 and 0.09) are added. This table is interpreted as showing how well connected is each city into the world city network. Cities will be ranked by this measure but this does not necessarily imply a ‘national’ (or sub-regional) hierarchy; patterns are much more complicated than simple hierarchies and this is what the subsequent tables show. The second table is another measure of ‘localism’, this time at the scale of the state or sub-region. These results are produced by just summing the connections of each city only to other cities in the state or sub-region. These are relative measures and it is expected that less globally connected cities will tend to be more local in their connections. The final two tables are unique to Part C: we measure connectivity to the traditional and emerging ‘core cities’ of the global economy. As reported previously, London and New York are the most important cities in the world

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city network and these are treated as the traditional core cities. In the third table each city in a state or sub-region has its connections to these two cities aggregated to measure their current ‘core city connectivity’. This measure shows the degree of over-linkage and under-linkage of each city to NYLON in relation to what is expected in the world city network. In the fourth table this exercise is repeated, but for connections to Beijing, Shanghai and Hong Kong. The latter three cities are treated as an emerging new core city triad that could possibly rival NYLON in the world city network in the near future. Thus this measure shows how over-linked or under-linked a city is to these critical cities in the world’s fastest growing section of the global economy. Comparisons between these latter two tables will indicate the degree to which cities may be reorientating within the world city network. In and of themselves these results will not answer the question of the relation between cities and their states with which we began this introduction. All we will have provided in Part C are some new findings that will be food for thought in pondering this important question. As will soon become apparent when reading the chapters below, relations between cities and states are very contingent, depending on history and contemporary development: the purpose of Part C is to stimulate further thinking along these lines.

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15

Australian Cities Oli Mould

Australian cities continue to integrate globally, despite their relative geographical remoteness from other key global and world cities. However, the dominant primacy of Sydney in Australia and the Australasian region also continues to grow. The intense marketing by Sydney’s officials since the 2000 Olympiad has intensified to create a very definitive city ‘brand’ of Sydney, namely that of a blend of global business acumen, but also outstanding natural and manufactured aesthetic beauty. A succession of ten-year plans by the City of Sydney outlined distinct policies to propel, and then secure Sydney as a prominent city on the Pacific Rim. In 1991, the ‘Living City’ strategy encouraged high population growth in the central business district (CBD) and greater pedestrian amenities and vibrancy on the streets. Enacted in 1995, the living city programme has been heralded a success, in that Sydney has increased its dominance over Melbourne through public spaces improvement policies and a focus on the Olympics as a catalyst for improving the city’s infrastructure. The newest scheme set out by the city’s officials is the Sustainable Sydney 2030 Vision, aimed at creating a ‘green, global and connected city’ (www.cityofsydney.nsw.gov.au/2030). However, the competition between Melbourne and Sydney to be labelled Australia’s ‘global’ city has not always been led by Sydney, indeed Sydney and Melbourne have vied for pre-eminence in the Australian urban system during the last century. Melbourne was at one stage the main administrative centre and larger than Sydney but, with the shift of the Commonwealth government to Canberra, a more ‘neutral’ location after Federation, Sydney’s growth soon surpassed that of Melbourne. After Word War II, in the ‘long boom’ of the first two post-war decades, Melbourne threatened to dominate in Australia, as its growth outpaced Sydney’s partly due to the fact that Melbourne attracted more of the rapid industrial expansion that Australia experienced during that period. Thereafter however, Australia’s economy underwent significant change that included a decline in manufacturing employment, which saw Sydney’s less manufacturing-dependent population grow faster. By 1991, its population was 17 per cent larger than Melbourne (Roseman et al, 2005).

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Since the turn of the millennium, Sydney has continued to grow as Australia’s primate city, and the 2008 global connectivity figures shown in Table 15.1 again confirm Sydney’s national dominance. With a global network connectivity score of 0.71, it is by far the most global city in Australia. Melbourne’s score of 0.44 sees it comfortably as Australia’s second city, but still below 0.5. Brisbane, Perth, Adelaide, Canberra and Hobart make up the rest of the list, but these state capitals have significantly less global connectivity than Sydney. This is again shown with the data in Table 15.2, which show the cities’ localism, that is, the relative concentration of connections to other Australian cities. Hobart, the lowest ranked city in Table 15.1 (with a global network connectivity score of only 0.06) has the highest localism score of 2.36. Indeed, Table 15.2 is the exact reverse of Table 15.1 highlighting the fact that cities with global connectivity formulate this relatively at the expense of local connectivity. Indeed, Sydney’s score of −0.58 indicates that it is highly un-local; and given that Melbourne, the next lowest score, is positive (at 0.26), it would suggest that Sydney is by far the most ‘outward-looking’ city in Australia.

Table 15.1 Global network connectivity of Australian cities. RANK

CITY

1 2 3 4 5 6 7

Sydney Melbourne Brisbane Perth Adelaide Canberra Hobart

GROSS CONNECTIVITY

PROPORTIONATE CONNECTIVITY (1.00 = LONDON)

68,263 41,957 27,260 22,798 19,034 15,633 5980

0.71 0.44 0.28 0.24 0.20 0.16 0.06

Table 15.2 Localism (relative concentration of connections within Australia). RANK

CITY

1 2 3 4 5 6 7

Hobart Canberra Adelaide Perth Brisbane Melbourne Sydney

LOCALISM 2.36 0.93 0.89 0.78 0.62 0.26 −0.58

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Table 15.3 shows how each of Australia’s state capitals ranks when given a score that calculates their connectivity to the NYLON links (namely New York and London). Again, the rank is very similar, with Sydney top of the list with 0.56, and Melbourne second with 0.40. The rest of the Australian cities have negative scores, with Hobart being the most ‘unconnected’ to NYLON with a score of −0.39. Sydney’s connection with NYLON confirms it as the Australasian regional city for major financial and professional service firms. In particular, Sydney has connections with London in other areas such as the creative and cultural industries (less so with New York), suggesting that the strength of the ‘traditional globalism’ via connection to NYLON extends beyond the traditional economic variables, highlighting the breadth as well as the depth of Sydney’s connectivity. Every other city in Australia (outside Sydney and Melbourne) has a negative connection with NYLON, emphasizing their regional and national focus, outlined in Table 15.2.

Table 15.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7

Sydney Melbourne Perth Brisbane Adelaide Canberra Hobart

TRADITIONAL GLOBALISM 0.56 0.40 −0.04 −0.10 −0.32 −0.38 −0.39

In Table 15.4, the ranking is to assess the ‘new globalism’, via connections with the Chinese cities of Hong Kong, Beijing and Shanghai. Again, the top two cities are Sydney (with a score of 0.74) and Melbourne (with a score of 0.40). What is telling about these data is that Sydney is more connected to these Chinese cities than NYLON, which emphasizes Sydney’s efforts to connect with these emergent economic powers. The Australian federal government has been actively engaged in attempting to connect Sydney to Asian cities (particularly through economic and cultural activities – see Fagan, 2000 and Daly and Pritchard, 2000) and the data would reflect this leaning toward the Chinese city triad.

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Table 15.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7

Sydney Melbourne Brisbane Perth Hobart Adelaide Canberra

NEW GLOBALISM 0.74 0.40 −0.18 −0.25 −0.26 −0.42 −0.47

A recent study by the Australian Business Federation suggests that: for foreign multinational companies active in Sydney, regional headquarters and offices are typically located in Sydney or Singapore, with Hong Kong and Shanghai also being favourable locations for these offices (Australian Business Federation, 2009, p57) This again highlights the regional bias that Sydney has towards the Asia-Pacific, but also that Sydney houses mostly regional headquarters of multi-national companies. Australia then clearly has one dominant city. Sydney is by far the most ‘outwardly looking’ city, with Melbourne showing relatively weaker ties to cities outside Australia. All the other cities (state capitals) show high degrees of localism and relatively low levels of connectivity to other cities around the globe.

References Australian Business Federation (2009) Global Connections: A Study of Multinational Companies in Sydney, Australian Business Federation, Sydney Daly, M. and Pritchard, B. (2000) ‘Sydney: Australia’s financial and corporate capital’, in J. Connell (ed.) Sydney: The Emergence of a Global City, Oxford University Press, Melbourne, pp167–188 Fagan, R. (2000) ‘Industrial change in the global city: Sydney’s new spaces of production’, in J. Connell (ed.) Sydney: The Emergence of a Global City, Oxford University Press, Melbourne, pp144–166 Roseman, C. C., Laux, H. D. and Thieme, G. (eds) (2005) EthniCity, Rowman & Littlefield, Lanham, MD

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16

Chinese Cities Pengfei Ni, Xiaoyan Yue and Jin Huang

As a large country with an ancient civilization, China has a continuous experience of city networks through to modern times, when the Qing Dynasty was forced to open the country to the world economy in the second half of the 19th century following defeat in the Opium War (Taylor and Hoyler, 2008). At this time, in the course of the development of a capitalist industry and commerce, Shanghai, Tianjin, Dalian, Qingdao, Guangzhou and other modern industrial and commercial cities along the eastern coast developed rapidly, and some of them outgrew traditional inland cities such as Beijing, Nanjing and Chengdu. Furthermore, with the further development of capitalist industry and commerce, the first and most famous Yangtze River Delta metropolitan area with Shanghai as core-city developed conspicuously. During this period, dense urban economic corridors began to emerge in superior geographical locations such as the Middle-Lower Yangtze Area and the Pearl River Delta. However, urban development was very slow in the western areas of the country with its poor transportation links (Williams and Chan, 2008). After the founding of the People’s Republic of China in 1949, Chinese cities entered a new historical phase. State planning focused on the development of heavy industry and national defence, resulting in a large number of remote inland cities (such as Shenyang, Changchun, Lanzhou, Taiyuan and Chongqing) developing rapidly, based on the advantages of rich natural resources. Under national policy regulation, other inland cities also began to develop rapidly. At this time, an even urban development pattern emerged across the east and west of China. In order to achieve rapid growth of the Chinese economy, the policy of reform and opening up was implemented in 1978 (Ma, 2002; Wu et al, 2007). In 1980, Zhuhai, Shantou and Xiamen were established as economic special zones, and many favourable policies promoted rapid economic growth there. In the context of the developing eastern coastal regions, it was coastal cities that again grew rapidly in China (Wu, 2006). At the same time, a number of large scale urban agglomerations also developed in the country, in which cities were connected closely with each other (Taubmann, 1999). But in general, the

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development of central and western cities lagged behind, due to locational disadvantages and the absence of favourable and special policies. Recently, several such strategies, for example ‘western development’, ‘rise of central China’ and ‘the revitalization of the northeast’, were implemented in order to achieve sustainable and regionally balanced development. At present, in the context of regional integration, all cities have formed a network system of close linkages. However, from the perspective of the whole country, the development pace of the eastern coastal cities is faster than that of the central and western cities in the inland region (Ni, 2009). This is the context which provides the base for considering Chinese cities in the 2008 world city network analysis. Table 16.1 shows global network connectivities for the 21 Chinese cities with proportionate connectivities above 0.05, showing the connectivity of these Chinese cities with other cities in the world city network. With the development of globalization, Hong Kong, Beijing and Shanghai have been consistently dominant within China. In 2000, the proportionate connectivity of Hong Kong was 0.71, Beijing 0.42, and Shanghai 0.43. But in 2008, Hong Kong’s connectivity score rose to 0.83, Beijing’s to 0.68, and Shanghai’s to 0.69. These three cities are now widely recognized as high-level integrated cities in the world city network: Hong Kong plays an important role in global finance, Beijing is the political and cultural centre and Shanghai is the economic centre in China. The connectivities of Taipei, Guangzhou and Shenzhen are slightly lower than that of Hong Kong, Beijing and Shanghai. Guangzhou and Shenzhen are developing rapidly and have connected closely with other world cities since the reform and opening-up. It is a miracle of rapid urban development in China that Shenzhen quickly grew from a small fishing village to one of China’s leading economic development areas. The proportionate connectivity of Chengdu is higher than that of Tianjin, Nanjing, Dalian and Hangzhou because Chengdu is the economic centre of the southwest, and has a large inland economic hinterland which provides a large-scale market for its development and connectivities with other cities. At the same time, as a traffic control port of the southwest region, Chengdu is an important gateway to the eastern coast of China and the world economy. Other cities that have relatively high connectivities are either the provincial capitals, or the core cities of urban agglomerations, such as Nanjing, Dalian, Qingdao, Shenyang and Wuhan.

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Table 16.1 Global network connectivity of Chinese cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Hong Kong Shanghai Beijing Taipei Guangzhou Shenzhen Chengdu Macao Tianjin Nanjing Kaohsiung Dalian Suzhou Qingdao Xiamen Hangzhou Shenyang Fuzhou Chongqing Wuhan Xi’an

GROSS CONNECTIVITY 80,330 65,950 65,939 51,793 30,814 23,648 12,891 12,133 11,263 10,875 10,726 10,688 8231 8152 6965 6474 6151 5952 5888 5393 4548

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.83 0.69 0.68 0.54 0.32 0.25 0.13 0.13 0.12 0.11 0.11 0.11 0.09 0.08 0.07 0.07 0.06 0.06 0.06 0.06 0.05

Table 16.2 shows the domestic connectivities of different cities within China. The domestic connectivities of Xi’an and Chongqing are the highest among the 21 cities. The surprise is Chongqing. On the one hand, as a new inland municipality, urban development is very rapid and has close connections with other cities. On the other hand, Chongqing is the linking region of central and western China. So it is beneficial for Chongqing to have connections with the eastern, western, southern and northern regions through its locational advantage within China. Chengdu, as the economic, political and cultural centre in southwest China, also has good domestic links. Fuzhou and Xiamen are in the same province, but Fuzhou, as the provincial capital, has more domestic connections than Xiamen, as Table 16.2 clearly shows. In general, provincial capitals have higher relative domestic linkages than developed coastal cities in the same province.

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Table 16.2 Localism (relative concentration of connections within China). RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21

Xi’an Chongqing Wuhan Fuzhou Shenyang Xiamen Hangzhou Nanjing Suzhou Chengdu Tianjin Qingdao Dalian Shenzhen Guangzhou Macao Beijing Kaohsiung Shanghai Hong Kong Taipei

LOCALISM 10.98 9.93 9.46 8.73 8.26 7.86 6.93 5.72 5.22 5.18 4.86 4.38 3.81 2.35 2.15 1.38 1.10 1.09 0.47 0.20 −0.14

Table 16.3 shows traditional globalism by measuring combined connectivity to New York and London (NYLON). Hong Kong, Beijing and Shanghai have the strongest links of the 21 cities to NYLON. Hong Kong is keeping a close connection with western foreign cities and its open regional system provides conditions for the development of multinational companies. China is a centralized country. Beijing, as China’s political and cultural centre, can provide key information for multinational companies. Shanghai is the economic centre of the country and therefore has strong NYLON links. So Hong Kong, Beijing and Shanghai, as China’s development windows in the south, the north and centre, are strongly connected to NYLON. It is a surprising result that Chongqing and Shenyang have relatively stronger links to NYLON than Taipei. This does not mean that Taipei’s links to NYLON are less in absolute terms, but that Chongqing and Shenyang’s main orientation is to New York and London.

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Table 16.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17= 17= 19 20 21

Hong Kong Beijing Shanghai Chongqing Shenyang Taipei Wuhan Fuzhou Chengdu Nanjing Guangzhou Tianjin Xiamen Hangzhou Shenzhen Xi’an Kaohsiung Suzhou Dalian Qingdao Macao

TRADITIONAL GLOBALISM 0.87 0.82 0.76 0.59 0.52 0.50 0.36 0.25 0.15 0.11 0.10 0.01 −0.06 −0.07 −0.12 −0.19 −0.26 −0.26 −0.40 −0.51 −0.62

Table 16.4 shows the ‘new globalism’ associated with linkage to Beijing, Shanghai and Hong Kong. Of the other 18 cities, all but four have positive scores, with Shenyang, Fuzhou, Chongqing and Wuhan ranked first to fourth. These are predictable because they are major provincial capitals and the core of urban agglomerations of economically developed regions in China. As the regional centres, they have well-developed connections to the country’s global cities, Beijing, Shanghai and Hong Kong. Although cities like Suzhou, Shenzhen, Qingdao and Macao have strong economic development bases, they have relatively weak links to Beijing, Shanghai and Hong Kong. On the one hand, they are only economic centres, not integrated economic, political and cultural centres; on the other hand, they are under the shadow of the administration and geography of their provincial capitals, for example Fuzhou and Guangzhou.

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Table 16.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 – – –

Shenyang Fuzhou Chongqing Wuhan Taipei Xi’an Guangzhou Chengdu Xiamen Hangzhou Tianjin Nanjing Shenzhen Suzhou Dalian Qingdao Kaohsiung Macao Beijing Hong Kong Shanghai

NEW GLOBALISM 1.28 1.16 1.07 0.93 0.84 0.77 0.75 0.51 0.46 0.38 0.34 0.23 0.18 0.08 −0.01 −0.21 −0.28 −0.46 – – –

In conclusion, with the constant development of globalization, China’s urban development is very rapid. Many metropolises such as Hong Kong, Beijing and Shanghai, have leapt to the forefront of world cities, and now play important roles in the world economy. Hong Kong in particular is keeping up with the fastest development pace in all Chinese cities as shown in the 2008 world city network connectivity (Table 16.1). In this respect, the trends suggest that Hong Kong will play as important a role as New York and London in world economic development in the near future. Meanwhile, in the context of globalization and regional integration, China’s provincial capitals and the core cities of urban agglomerations, such as Hangzhou, Guangzhou, Fuzhou, Shenyang, Chengdu and Shenzhen, show rapid development momentum through enhancing connections and complementing each other. Although large, medium and small cities across the country are developing rapidly, eastern coastal cities are developing faster and have more connections within the world city network than inland western cities because of their excellent geographical position, convenient transportation and superior investment environment.

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References Ma, L. J. C. (2002) ‘Urban transformation in China, 1949–2000: a review and research agenda’, Environment and Planning A, vol 34, pp1545–1569 Ni, P. (2009) Annual Report on Urban Competitiveness, Social Sciences Academic Press, Beijing Taubmann, W. (1999) ‘Recent urbanization trends in China – global influences and national strategies’, in A. G. Aguilar and I. Escamilla (eds) Problems of Megacities, Universidad Nacional Autónoma de México, Mexico City, pp21–50 Taylor, P. J. and Hoyler, M. (2008) ‘Chinese cities in contemporary globalisation’, in C. Johnson, R. Hu and S. Abedin (eds) Connecting Cities: China, Metropolis Congress, Sydney, pp18–43 Williams, J. F. and Chan, K. W. (2008) ‘Cities of East Asia’, in S. D. Brunn, M. HaysMitchell and D. J. Zeigler (eds) Cities of the World: World Regional Urban Development, 4th edition, Rowman & Littlefield, Lanham, MD, pp475–428 Wu, F. (ed.) (2006) Globalization and the Chinese City, Routledge, London Wu, F., Xu, J. and Yeh, A. G. (2007) Urban Development in Post-Reform China: State, Market and Space, Routledge, London

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17

Japanese Cities Pengfei Ni, Qingbin Li and Jin Huang

Rapid industrial urbanization took off in Japan in the 1920s (Sorensen, 2002). Benefiting from governmental encouragement and support, several cities began to grow massively based on their geographical advantages. Thus Tokyo, Osaka and other national centres became ‘shining city stars’ during this period. Their links to the outside world followed the industrialization of the Japanese economy from then on. The famous four industrial zones of Japan (Keihin, Chukyo, Hanshin and Kitakyushu) had already formed by the 1930s due to industrial development and their excellent locational conditions. Japan’s economy was destroyed totally in World War II and the rebuilding process of the Japanese economy began apace in 1950–55. After the economic revival, the Japanese government promoted an imbalanced development policy by encouraging dominant industries and metropolitan concentration, which triggered the formation of the ‘Three Metropolitan Regions’ based on the four industrial zones. Tokyo, Nagoya and Osaka metropolitan regions, and also other local metropolitan regions, together constitute one of the biggest cityeconomic corridors in the world: the Pacific Belt (Choe, 1998). This city belt also became Japan’s biggest window to the outside world, especially for domestic and foreign companies. This is the city success story up to the 1970s. However, Japan’s regional economy was gradually sliding into an imbalanced situation in the rapid growth period from the 1970s to the 1980s, partly because of the economic concentration into several huge cities (Williams and Chan, 2008). Correspondingly, the long-debated regional development policy was implemented: a focus on technology innovation, resulting in the reduction of reliance on location factors. The post-industrial era witnessed a tendency for decentralization due to all these factors and the government’s endeavour to reduce regional inequalities, supporting the improvement of infrastructure constructions and people’s quality of life (Karan and Stapleton, 1997; Yi and Ren, 2003). Nevertheless, economic concentration is inevitable in modern development, and past results (in 2000 and 2004) also show that Japan has continued a tradition of one-city primacy in relation to Tokyo. Hence, the regional policies contributed more to making the basic facilities and

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public services become more balanced than to narrowing the gap between ordinary cities and those such as Tokyo (Wei and Zhao, 2005). No real progress has been made to change the dominant situation of Tokyo, and this is also confirmed by our new results. The global network connectivity measures in Table 17.1 show how well Japanese cities are integrated into the world city network (see also Haga, 1999). In total, 13 of Japan’s cities qualify for analysis with proportionate global network connectivities above 0.05. Tokyo is clearly ranked first, just as expected, but not high enough to match its earlier position among world cities, being overtaken by Singapore in the 2008 results. Osaka is ranked second but with less than one-quarter of Tokyo’s score. Tokyo and Osaka metropolitan regions have accrued a large population (25 per cent of Japan’s total) and they constitute the country’s economic engines due to the scale economy effect and other political and cultural factors. For domestic companies, Tokyo and Osaka are the first choices for headquarters; foreign companies also favour large cities, especially Tokyo. Thus Tokyo’s primacy is not expected to change in the near future. The connectivity scores of Japanese cities are not as competitive as the country’s urbanization level and economic status would suggest. This is indicated by comparing Japan’s results with those of Chinese or Indian cities. Compared to China’s 21 cities, Japan only has 13 cities above 0.05, among which 0.06 and 0.05 dominate the major distribution except for the two leading cities (the third and fourth ranked cities, Nagoya and Kyoto, score 0.12 and 0.09 respectively).

Table 17.1 Global network connectivity of Japanese cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12= 12=

Tokyo Osaka Nagoya Kyoto Sendai Chiba Fukuoka Yokohama Sapporo Kobe Hiroshima Hamamatsu Takamatsu

GROSS CONNECTIVITY 70,773 15,939 11,110 8950 5820 5722 5698 5686 5368 5024 4594 4452 4452

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.74 0.17 0.12 0.09 0.06 0.06 0.06 0.06 0.06 0.05 0.05 0.05 0.05

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The obvious feature of Table 17.1 is Tokyo’s primacy and the flat distribution for other cities – actually this is the most remarkable characteristic through all the four indicators we report. As the capital of Japan, Tokyo’s prosperity has been great due to political reasons, its economic agglomeration and regional policies. Such prosperity contributes much to the global network connectivity indicator, apparently evidenced by the results of many big cities. As regards the low flat distribution of the global network connectivities, most of the chosen cities are scoring lower than 0.1 proportionately in an approximate equal value distribution. As mentioned above, these may be related more or less to Japan’s regional policies to reduce economic development differences, but of course, Tokyo remains the great exception. While the results generally reflect our given knowledge on Japanese cities, there appears to be one surprise: two pairs of twin cities, Tokyo–Yokohama and Osaka–Kobe have very different results for each ‘twin’. This is likely to be the result of shadow effects: few companies would like to choose their neighbouring cities as another location for a big office. Just as the findings for many other countries tell us, ranks of ‘localism’ – the relative degree to which a city’s connectivity is dominated by links within the country – are largely the reverse of the general network connectivity ranks. Well-known ‘global cities’ usually do not get high scores in the ‘localism’ indicator. Table 17.2 presents the same story for Japanese cities. The most globalized city in Japan, Tokyo, is actually very ‘un-local’, recording the only negative score in the table, which means the vast majority of its connections are outside Japan. As expected, Osaka ranks next to last for local connectivity but it is positive reflecting its relative ‘localism’. All remaining cities have relatively large positive scores in largely the reverse order compared with the previous table (Table 17.1): Nagoya scores 3.42 and Kyoto 3.53, showing Japan’s third and fourth cities to be very local. Hiroshima ranks as the most ‘local’ city, related to its low rank in foreign links and its isolated location far from Japan’s economic centre. In summary, the cities of Japan appear ‘more local’ than those in many other countries. Since New York and London (NYLON) are treated as the ‘main street dyad’ of contemporary globalization in our research, we use this index of relative concentration of connections to New York and London to be a measurement of ‘traditional globalism’. Table 17.3 measures the ‘traditional globalism’ of Japanese cities by showing their relative connectivities to London and New York. After Tokyo and Osaka, the ranks here are only weakly related to the global network connectivities shown in Table 17.1. As one of the leading international financial centres, Tokyo obtains its unique positive score among Japanese cities, indicating its close connection with NYLON. All other cities score negatively, signalling a relative lack of orientation to NYLON, which is predictable since Japanese cities tend to be ‘local’ as we have seen in Table 17.2. Nagoya is among our surprise list with its third rank in Table 17.1 but the city scores as low as −0.50 in the ‘traditional’ globalism indicator. The difference between the two ranks reflects Nagoya’s own relatively high global

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connections outside NYLON. Similar to our previous finding in Table 17.1, after Tokyo, no big gap exists for this indicator either, following the flat distribution rule highlighted earlier.

Table 17.2 Localism (relative concentration of connections within Japan). RANK

CITY

1 2= 2= 4 5 6 7 8 9 10 11 12 13

Hiroshima Hamamatsu Takamatsu Sapporo Fukuoka Sendai Kobe Yokohama Chiba Kyoto Nagoya Osaka Tokyo

LOCALISM 8.23 7.85 7.85 7.35 7.00 6.56 6.37 4.73 4.55 3.53 3.42 1.68 −0.62

Table 17.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7 8 9= 9= 11= 11= 13

Tokyo Osaka Fukuoka Yokohama Sapporo Nagoya Kyoto Hiroshima Sendai Kobe Hamamatsu Takamatsu Chiba

TRADITIONAL GLOBALISM 0.87 −0.05 −0.36 −0.39 −0.48 −0.50 −0.51 −0.52 −0.58 −0.58 −0.59 −0.59 −0.75

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Table 17.4 shows city connectivities with a probable emerging ‘new globalism’ based upon the three leading Chinese cities of Beijing, Shanghai and Hong Kong. After Tokyo and Osaka, the order of the new globalism indicator is not strongly related to that of traditional globalism, which indicates differences between the traditional and new globalism connections for Japanese cities. Thus Tokyo is the most connected city to the new globalism cities with by far the highest score among the 13 Japanese cities. The second-ranked city Osaka scores 0.39, and unlike NYLON links, there are a further three cities with positive scores. Generally, Japanese cities are more Chinese orientated. Specifically, comparing new and traditional globalism measures, Sendai is a big surprise – a lower rank in the traditional NYLON measure but a higher rank in the new measure. This reflects the orientation of companies located in Sendai to Chinese cities, partly owing to the relatively closer cultural relationship.

Table 17.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3= 3= 5 6 7 8 9=9= 11 12 13

Tokyo Osaka Hiroshima Sendai Fukuoka Sapporo Yokohama Nagoya Hamamatsu Takamatsu Kyoto Kobe Chiba

NEW GLOBALISM 1.12 0.39 0.12 0.12 0.11 −0.04 −0.09 −0.10 −0.19 −0.19 −0.33 −0.65 −0.92

In conclusion, one primate city and a flat distribution of connectivity for other cities is the specific feature of Japanese cities. However, connectivity values are lower than expected given the country’s economic status. Tokyo and Osaka continue to perform reasonably well in the world city network and this would seem likely to remain unchanged in the near future.

References Choe, S. (1998) ‘Urban corridors in Pacific Asia’, in F. Lo and Y. Yeung (eds) Globalization and the World of Large Cities, United Nations University Press, Tokyo, pp155–173

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Haga, H. (1999) ‘Changing networks of Japanese banks among megacities in the world’, in A. G. Aguilar and I. Escamilla (eds) Problems of Megacities, Universidad Nacional Autónoma de México, Mexico City, pp117–130 Karan, P. P. and Stapleton, K. (eds) (1997) The Japanese City, University Press of Kentucky, Lexington, KY Sorensen, A. (2002) The Making of Urban Japan, Routledge, London Wei, W. and Zhao, G. (2005) ‘Japan’s urbanization process and corresponding supportive system’ [in Chinese], Jingji Zongheng, no 3, pp45–48 Williams, J. F. and Chan, K. W. (2008) ‘Cities of East Asia’, in S. D. Brunn, M. HaysMitchell and D. J. Zeigler (eds) Cities of the World: World Regional Urban Development, 4th edition, Rowman & Littlefield, Lanham, MD, pp475–528 Yi, B. and Ren, L. (2003) ‘On Japan’s regional economic policies and their characteristics’ [in Chinese], Contemporary Economy of Japan, no 5, pp18–23

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18

Indian Cities Rolee Aranya, Pengfei Ni, Yu Zhang and Jin Huang

India’s urbanization is often classified into three distinct phases – the precolonial or indigenous, the colonial and the post colonial or national. A more recent addition to this national phase, neoliberal globalization, has come to be known as the ‘global phase’ (Grant and Nijman, 2002; Sita and Bhagat, 2007). It was in the colonial phase that India was forcibly opened up to the emerging world economy, resulting in the port cities of Mumbai (formerly known as Bombay), Calcutta (now known as Kolkata) and Chennai (formerly known as Madras), along with the new colonial capital New Delhi, dominating the urban space economy in the period of the British Raj. With independence came extensive regulation, protectionism and public ownership resulting in slow economic growth. However these four cities were in a position to take advantage of the new large concentration of economic activity and population and came to be called the ‘four metros of India’. Economic liberalization under the structural adjustment programme, initiated in 1991, heralded the fourth ‘global phase’, which propelled India into becoming one of the fastest growing economies in the world, with fundamental implications for its cities. Large scale urbanization and a federal system of government have ensured that India never had a situation of urban primacy; however one can say that the state capitals emerged as the primate cities at sub national/state level thereby leading to local primacy. The state capitals, although important economic and administrative centres at state level, did not challenge the supremacy of the ‘four metros’ until 1991. The metros themselves were fairly evenly distributed geographically and therefore performed also as regional centres with defined functional roles. Post 1991, increasing global opportunities enabled states to champion their leading cities for global investment, thereby leading to vigorous competition and place marketing that challenged the position of the four metros. Popular Gallup polls conducted in cooperation with a leading business magazine that present the ranking of ‘Best Cities for Business in India’ indicate that the most significant changes have been:

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The emergence of Bangalore as one of the top five ranked cities ever since the first poll in 1996. The increasing significance of secondary cities in the extended urban agglomeration of the four metros, which have become equally attractive for investment given the saturation of the main cities.

In the latest rankings of 2009, Noida, Gurgaon and Chandigarh seem to be overtaking Delhi within the extended urban agglomeration, while Surat and Pune in the Mumbai urban agglomeration become significant in the rankings (Business Today, 9 June 2009). While the results from the survey are based more on the perception of surveyed business leaders and policymakers rather than objective measures of actual connectivity, they are definitely indicative of the trends. Large scale foreign investment in the Information Technology industry since the mid 1980s has brought about the creation of a new brand of ‘IT cities’ and special economic zones that compete to attract firms. The undisputed leader among these is Bangalore – commonly known as the ‘Silicon Valley of India’ – which was identified by the Human Development Report 2001 as the only global technology hub in India based on a Technology Achievement and Innovation Index (UNDP, 2001). A recent report by the National Association of Software and Services Companies suggests that Bangalore, Chennai, Hyderabad, Calcutta, Mumbai, National Capital Region of Delhi (including suburban cities of Noida and Gurgaon) and Pune (the Pune–Mumbai industrial corridor zone is especially impressive) are the leaders in terms of location of the export-oriented IT software and services industry (NASSCOM, 2008). Overall, Mumbai maintains its position as the leading city and India’s prime ‘gateway’ into the world economy. However, it is the demonstration effect of the perceived success of Bangalore in its rapid rise to becoming a globalized city through the location of an export-oriented IT industry, and thereby being a generator of prosperity for Karnataka state (of which Bangalore is the capital), that has been the driver of urban-centred industrial incentive policies in the last two decades. Table 18.1 shows the city rankings of global network connectivities, an indicator measuring how well different cities are integrated into the world city network. India is the second largest populous country with more than 100 cities but only nine of these qualify for inclusion in Table 18.1 (i.e. with connectivities above 0.05). Thus overall, the presence of Indian cities in the world city network is not impressive. Nevertheless the nine cities do show clear patterns of success: the cities ranked in Table 18.1 reflect an almost identical list as that identified by NASSCOM. Although the relative position of cities based on connectivity related to multiple business services (where IT is not included) is defined by more traditional roles, the presence of Bangalore, Hyderabad and Pune in the top seven is very highly correlated to their role in the global economic integration of India.

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Table 18.1 Global network connectivity of Indian cities. RANK

CITY

1 2 3 4 5 6 7 8 9

Mumbai New Delhi Bangalore Chennai Calcutta Hyderabad Pune Ahmedabad Cochin

GROSS CONNECTIVITY 57,902 39,540 34,418 27,488 22,656 18,190 12,703 8562 5119

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.60 0.41 0.36 0.29 0.24 0.19 0.13 0.09 0.05

The cities in Table 18.1 can be divided into four strata – the first two strata represent the old guard of the four metros with the exceptional inclusion of Bangalore. Mumbai’s leading position, by a large margin, is no surprise owing to the location of the financial industry and both the National and Bombay Stock Exchanges. Mumbai’s connectivity is growing rapidly (from just under 0.5 in 2004 (Taylor and Aranya, 2008) to over 0.6 in 2008) and it is now indisputably the ‘global city’ of India as a rising economic power. Delhi, Calcutta and Chennai already offered the agglomeration economies to attract additional investment in the ‘global phase’ of India’s urbanization. However, post 1991, large scale infrastructural investments and favourable investment policies have been used in all three cities to compete with Bangalore for the IT industry, with varying success. Delhi’s case is especially interesting with respect to the intra-regional competition generated in the National Capital Region of Delhi, with suburban cities of Gurgaon and Noida developing into ‘edge cities’ rivalling the advantages offered by Delhi. Calcutta’s position in the new global phase is a little more problematic: its global network connectivity has been declining since first measured in 2000 (Taylor, 2004). The third stratum of cities in the list – Hyderabad and Pune – have relatively low levels of connectivity as compared to the Big Five (strata 1 and 2 cities), but are emerging competitors as overcrowding and saturation in the dominant city of the region leads to negative externalities and consequently spillover effects, to the advantage of neighbouring cities. The State Government of Andhra Pradesh (the state of which Hyderabad is capital) has actively promoted Hyderabad as an alternative to Bangalore in southern India, while Pune has benefited by marketing a better quality of life than Mumbai at a commutable distance from the metropolis. Similarly, stratum 4 cities Ahmedabad and Cochin have tried to repackage their images, as traditional textile manufacturing centre in the former case and centre of the ship building industry in the latter case, and offered incentive-based policies in Special Economic Zones to attract new

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industry and global services (for example through the Software Technology Parks of India (STPI) policy). Table 18.2 ranks the nine Indian cities in terms of the relative importance of their domestic intercity relations: it is a measure of the ‘localism’ in their network connectivities. Table 18.2 presents a picture that is nearly the reverse of the overall global connectivity in Table 18.1. Generally speaking, the cities are relatively ‘local’, and all but one of the nine cities score positively. Cities within the lowest two strata of connectivity are the ones that are most locally connected. The top five cities in terms of global connectivity show lowest orientation to other Indian cities, but only Mumbai has a negative score indicating a relatively ‘un-local’ hinterworld. The large gap between Hyderabad (1.48) and Chennai (1.05) indicates that they belong to different strata in spite of both scoring above one. The next large gap occurs between New Delhi (0.50) and Mumbai (−0.12), confirming the distinctiveness of Mumbai with its wider connectivity to cities across the world.

Table 18.2 Localism (relative concentration of connections within India). RANK

CITY

1 2 3 4 5 6 7 8 9

Cochin Ahmedabad Pune Hyderabad Chennai Calcutta Bangalore New Delhi Mumbai

LOCALISM 3.18 2.48 1.64 1.48 1.05 0.86 0.76 0.50 −0.12

Tables 18.3 and 18.4 show the relative level of concentration of connections to the New York–London traditional globalism dyad (NYLON) and the Beijing–Shanghai–Hong Kong ‘new emerging globalism’ triad. The results in both tables indicate that only Mumbai, Bangalore and Cochin have a positive orientation to both global complexes. The most anomalous of these findings is the highest positive orientation of Cochin to the NYLON dyad as compared to other Indian cities. It also figures at a high third rank in the case of the ‘new globalism’. However, the results should be carefully interpreted since Cochin shows the lowest overall network connectivity: having the smallest presence of global service firms (i.e. very little data) makes this city’s scores very susceptible to the particular office patterns of just a few firms. Such possible idiosyncrasies are evened out in the case of other cities due to the presence of more firms. The factor that is more interesting to note in these geographical orientations is the growing similarity of Bangalore with the distinctiveness of

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Mumbai as compared to the other leading cities in India. Delhi’s negative scores for NYLON and fourth ranking for the Chinese triad are especially noteworthy. In contrast, Bangalore seems to be emerging as the second distinctively globally-oriented city in India, while other traditional metros are lagging behind, albeit not by a large margin. If the trend of investment in the IT industry continues in the present manner then Bangalore is likely to become increasingly distinctive in the network of Indian cities.

Table 18.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7 8 9

Cochin Mumbai Bangalore New Delhi Calcutta Chennai Pune Hyderabad Ahmedabad

TRADITIONAL GLOBALISM 0.67 0.32 0.11 −0.06 −0.09 −0.11 −0.35 −0.36 −0.40

Table 18.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8 9

Mumbai Bangalore Cochin New Delhi Chennai Calcutta Pune Hyderabad Ahmedabad

NEW GLOBALISM 0.46 0.23 0.17 0.12 −0.10 −0.11 −0.28 −0.30 −0.45

To conclude the discussion on Indian cities some broad trends and characteristics can be pointed out: 1

Mumbai is the most distinctive city in terms of global network connectivity. It is comparable in connectivity to lower third order European cities, a feat quite remarkable for a city in a developing economy.

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3

223

It is also remarkable that multiple cities in India can articulate more connectivity than provincial cities in the UK for example (see Chapter 23). Intercity competition and proactive state governments are responsible for the relatively dispersed pattern of connectivity in India. Large foreign direct investment (FDI) and outsourcing in the IT industry have been the prime drivers in the dispersal of business services to multiple cities in India. The increasing significance of Bangalore as the second most globally networked city has been a direct consequence of the concentration of the IT industry in India. Although Bangalore is in the lead in terms of agglomeration of IT firms, stiff intercity competition and negative externalities due to oversaturation may challenge this position.

Irrespective of the fate of Bangalore, global economic integration is on an upward curve in India as more and more sectors of the economy are opened up for FDI. The future is likely to produce more diversified diffusion of global services as even suburban locations of established cities such as Delhi and Mumbai become competitors in their own right.

References Business Today (2009) ‘Best cities to work, play and live’, Business Today, 9 June 2009, http://businesstoday.intoday.in/index.php?option=com_content& Itemid=1&task=view&id=11655§ionid=22&issueid=59&page=archive, accessed 10 March 2010 Grant, R. and Nijman, J. (2002) ‘Globalization and the corporate geography of cities in the less-developed world’, Annals of the Association of American Geographers, vol 92, pp320–340 NASSCOM (2008) Location Roadmap for IT BPO Growth – Assessment of Leading 50 Cities, National Association of Software and Services Companies, New Delhi Sita, K. and Bhagat, R. B. (2007) ‘Population change and economic restructuring in Indian metropolitan cities: a study of Mumbai’, in A. Shaw (ed.) Indian Cities in Transition, Orient Longman, Chennai, pp59–82 Taylor, P. J. (2004) World City Network: A Global Urban Analysis, Routledge, London Taylor, P. J. and Aranya, R. (2008) ‘A global “urban roller coaster”? Connectivity changes in the world city network, 2000–04’, Regional Studies, vol 42, pp1–16 UNDP (2001) Human Development Report 2001, Oxford University Press, New York

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19

German Cities Michael Hoyler

A long history of territorial fragmentation, division of the country and its capital Berlin during the Cold War, and the decentralized federal organization of political power have all contributed to the development of a polycentric urban system in Germany. This is characterized by complementary functional and sectoral specialization (Blotevogel, 2000): metropolitan functions are distributed across a series of mid-sized and large cities and city-regions, none of which has achieved dominance as a primate city (BBR, 2005, pp177–190). As a consequence, clusters of advanced producer services (APS) – the subject of the urban analysis presented here – can be found in varying constellations in the core cities of all major metropolitan regions and in other urban centres (Krätke, 2004a). These knowledge-intensive business services form part of a wider knowledge economy (including, for example, media and information, high-technology and creative industries) that has been recognized as a key driver of contemporary economic growth. Concerns about competitiveness in a globalizing economy have led to a gradual paradigm shift in German spatial policy in recent years, from a traditional focus on balanced economic development to a strong metropolitan discourse that emphasizes growth in key urban regions (Brenner, 2000; Blotevogel and Schmitt, 2006; Hoyler et al, 2006). Indeed, the post-unification German urban system has seen increasing economic and social disparities between successful urban regions in some parts of the country and ‘shrinking cities’ in others (particularly but not exclusively in East Germany). One outcome of the changing perspective on cities has been the normative identification of 11 ‘European Metropolitan Regions’ (EMRs) in the country as ‘engines for societal, economic, social and cultural development’ (BBR, 2005, p188). The following analysis focuses on leading cities within German EMRs rather than the wider metropolitan regions. Past research has suggested that global APS functions are predominantly found in the ‘space[s] of centrality’ (Sassen, 2001) of core cities of such regions (see also Glückler, 2007), and in particular in the ‘first cities’ in each region (Hall and Pain, 2006; Taylor et al, 2008).

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Table 19.1 shows global network connectivities for the 14 German cities with proportionate connectivities above 0.05. These are a measure of how well the different cities are integrated into the world city network. The 14 cities above the threshold are also the biggest German cities with populations over 500,000 inhabitants. However, it is not the largest city, Berlin, which is ranked first but Frankfurt am Main, the country’s leading financial centre and transportation hub (Felsenstein et al, 2002). Sometimes referred to as ‘Bankfurt’ or ‘Mainhattan’, Frankfurt shows half the connectivity of London, its erstwhile rival as European international financial centre (Beaverstock et al, 2001). The national capital Berlin and four other major cities follow closely with network connectivities that place them in the top 100 worldwide: Hamburg and Munich, the major economic centres in northern and southern Germany respectively, followed by Düsseldorf (the principal advanced producer service centre of Rhine–Ruhr) and Stuttgart, known for its high-tech industries, in the southwest of the country. These are also the leading cities in the six EMRs initially identified in 1995 (Berlin/Brandenburg, Hamburg, Munich, RhineMain, Rhine-Ruhr and Stuttgart).

Table 19.1 Global network connectivity of German cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Frankfurt Berlin Hamburg Munich Düsseldorf Stuttgart Cologne Leipzig Dresden Bremen Hannover Essen Nuremberg Dortmund

GROSS CONNECTIVITY 48,165 37,825 35,574 33,482 30,575 26,295 14,499 11,762 11,628 9916 9390 8634 8034 6856

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.50 0.39 0.37 0.35 0.32 0.27 0.15 0.12 0.12 0.10 0.10 0.09 0.08 0.07

This wide geographical distribution of cities with high global network connectivity supports the notion of a ‘horizontal’ urban system in Germany, in which key advanced producer services locate in multiple cities rather than in a single gateway to the country. Hence the global ranking of the six leading German cities (ranks 32, 55, 60, 67, 76 and 91) contrasts starkly with the primate city

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systems of the United Kingdom (London 1, Manchester 113) and France (Paris 4, Lyon 145). The remaining German cities in Table 19.1 show much lower global network connectivity for advanced producer services. Germany’s fourthlargest city, Cologne, with less than half of the connectivity of its neighbour on the Rhine, Düsseldorf, is followed closely by the East German cities of Leipzig and Dresden, the northern German cities of Bremen and Hannover, the regional centres of Essen and Dortmund in the Ruhr area, and Nuremberg in south-east Germany. Overall this table highlights the leading position of Frankfurt in advanced producer services but it indicates that other major German cities are also well integrated into the world city network. Table 19.2, showing the degree to which a city’s connectivity is dominated by links within the country (‘localism’), supports this argument: Frankfurt is the only city that stands out as ‘non-local’, albeit with a small negative score, indicating a balance of its connections within and beyond Germany. As economic centre and ‘first city’ of the Rhine-Main region, it houses clusters of advanced producer services in all the sectors analysed in this study (Hoyler et al, 2008), with particular strengths in corporate law (rank 4 globally), financial services (rank 16 globally) and management consultancy (rank 19 globally) (see Chapter 3). All other cities have positive scores indicating the importance of domestic links relative to foreign connections. However, in comparison to other countries these scores are relatively low: for example, the most local of the 14 German cities, Dortmund (1.87), is still relatively less focused on domestic linkages than provincial UK cities (e.g. the UK’s second ranked city Manchester scores 2.47; see Chapter 23). Within Germany, the contrast between ‘local’ Cologne and less local Düsseldorf highlights the different emphases of these cities in advanced service provision, confirming Düsseldorf’s global servicing function in Rhine-Ruhr (Taylor et al, 2008). Table 19.3 measures the ‘traditional globalism’ of German cities by showing their combined connectivity to New York and London (NYLON). Most major German cities are relatively over-linked to this ‘main street dyad’ of contemporary globalization, reflecting West Germany’s close post-war economic ties with the US and Western Europe. Again, Frankfurt clearly ranks top as the location of choice for many global service firms centred on NYLON, in part due to its former role as headquarters of the American military government after World War II, the subsequent location of the German Central Bank in the city, and its large airport and central location in Germany. Munich, the capital city of Bavaria, comes second, with headquarters of a number of major multinational corporations in electronics, insurance and automotive industries and a wide range of supporting advanced producer services (Lüthi et al, 2010). Surprisingly, the port and media city of Hamburg, with a long history of transatlantic shipping, falls behind Cologne and Düsseldorf in terms of relative over-linkage to NYLON. All other cities, including Berlin, have negative scores and therefore relative under-linkage in their business service connectivities to NYLON.

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Table 19.2 Localism (relative concentration of connections within Germany). RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Dortmund Cologne Nuremberg Leipzig Dresden Essen Hannover Bremen Hamburg Düsseldorf Munich Stuttgart Berlin Frankfurt

LOCALISM 1.87 1.38 1.35 1.33 1.32 1.29 1.07 1.00 0.89 0.84 0.75 0.67 0.65 −0.05

Table 19.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Frankfurt Munich Cologne Düsseldorf Hamburg Berlin Stuttgart Nuremberg Dresden Bremen Leipzig Essen Dortmund Hannover

TRADITIONAL GLOBALISM 1.29 0.90 0.49 0.48 0.12 −0.12 −0.24 −0.45 −0.66 −0.69 −0.75 −0.78 −0.82 −0.84

Table 19.4 shows city connections to a possibly emerging ‘new globalism’ based upon Beijing, Hong Kong and Shanghai. The top positions in this table are almost the same as those for NYLON: Frankfurt is ahead of Munich, followed by Düsseldorf (with established Pacific Asia links, in particular as prime location for Japanese firms in Germany), Cologne and Hamburg. These cities seem well-placed in their service connections to face the challenges of the

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rise of China for the European space-economy (Kunzmann et al, 2009). All other cities score negatively again, indicating under-linkage to the Chinese cities triad.

Table 19.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Frankfurt Munich Düsseldorf Cologne Hamburg Berlin Stuttgart Bremen Nuremberg Dortmund Leipzig Essen Dresden Hannover

NEW GLOBALISM 1.09 0.77 0.40 0.29 0.01 −0.23 −0.25 −0.64 −0.67 −0.71 −0.86 −0.94 −0.96 −1.01

In conclusion, the 2008 global urban analysis reported here has once again identified Frankfurt as primus inter pares in a city system characterized by non-primacy. The city stands out with the highest global network connectivity for advanced producer services, a dominance of non-local links, and top position in terms of over-linkage to NYLON and the emerging Chinese cities triad. However, in broader assessments of metropolitan functions based on a wide range of attribute data, Frankfurt usually falls behind Berlin and Munich in a second tier of German cities together with Hamburg (Blotevogel and Schulze, 2009). While Berlin has gained significantly as a location of political decision-making after unification, it ranks only second in overall global network connectivity (GNC), remains more local in its advanced producer service connections and is slightly under-linked to both the traditional and the emerging centres of globalization. However, this result is surprisingly good given the legacy of division and the post-unification economic difficulties that have prevented Berlin from becoming a major ‘service metropolis’ (Krätke, 2004b). In a longitudinal perspective, German cities have since 2000 experienced a relative decline in GNC that particularly affects the country’s leading international financial centre, Frankfurt (see also Engelen and Grote, 2009), and the two major cities on the Lower Rhine, Düsseldorf and Cologne (see

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Postscript, Table PS.3). As these changes took place before the current financial crisis, the full impact of the latter on the position of German cities in the world city network remains to be seen.

References BBR (Bundesamt für Bauwesen und Raumordnung) (2005) Raumordnungsbericht 2005, Bonn, BBR Beaverstock, J. V., Hoyler, M., Pain, K. and Taylor, P. J. (2001) Comparing London and Frankfurt as World Cities: A Relational Study of Contemporary Urban Change, Anglo-German Foundation, London Blotevogel, H. H. (2000) ‘Gibt es in Deutschland Metropolen? Die Entwicklung des deutschen Städtesystems und das Raumordnungskonzept der “Europäischen Metropolregionen”’, in D. Matejovski (ed.) Metropolen: Laboratorien der Moderne, Campus, Frankfurt am Main, pp179–208 Blotevogel, H. H. and Schmitt, P. (2006) ‘“European Metropolitan Regions” as a new discursive frame in strategic spatial planning and policies in Germany’, Die Erde, vol 137, pp55–74 Blotevogel, H. H. and Schulze, K. (2009) ‘Zum Problem der Quantifizierung der Metropolfunktionen deutscher Metropolregionen’, in J. Knieling (ed.) Metropolregionen: Innovation, Wettbewerb und Handlungsfähigkeit, Akademie für Raumforschung und Landesplanung (ARL), Hannover, pp30–58 Brenner, N. (2000) ‘Building “Euro-Regions”: Locational politics and the political geography of neoliberalism in post-unification Germany’, European Urban and Regional Studies, vol 7, pp319–345 Engelen, E. and Grote, M. H. (2009) ‘Stock exchange virtualisation and the decline of second-tier financial centres – the cases of Amsterdam and Frankfurt’, Journal of Economic Geography, vol 9, pp679–696 Felsenstein, D., Schamp, E. W. and Shachar, A. (eds) (2002) Emerging Nodes in the Global Economy: Frankfurt and Tel Aviv Compared, Kluwer, Dordrecht Glückler, J. (2007) ‘Geography of reputation: the city as the locus of business opportunity’, Regional Studies, vol 41, pp949–961 Hall, P. and Pain, K. (eds) (2006) The Polycentric Metropolis: Learning from MegaCity Regions in Europe, Earthscan, London Hoyler, M., Freytag, T. and Mager, C. (2006) ‘Advantageous fragmentation? Reimagining metropolitan governance and spatial planning in Rhine-Main’, Built Environment, vol 32, pp124–136 Hoyler, M., Freytag, T. and Mager, C. (2008) ‘Connecting Rhine-Main: the production of multi-scalar polycentricities through knowledge-intensive business services’, Regional Studies, vol 42, pp1095–1111 Krätke, S. (2004a) ‘Urbane Ökonomien in Deutschland: Clusterpotenziale und globale Vernetzungen’, Zeitschrift für Wirtschaftsgeographie, vol 48, pp146–163 Krätke, S. (2004b) ‘City of talents? Berlin’s regional economy, socio-spatial fabric and “worst practice” urban governance’, International Journal of Urban and Regional Research, vol 28, pp511–529

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Kunzmann, K. R., Schmid, W. A. and Koll-Schretzenmayr, M. (eds) (2009) China and Europe: The Implications of the Rise of China for European Space, Routledge, London Lüthi, S., Thierstein, A. and Goebel, V. (2010) ‘Intra-firm and extra-firm linkages in the knowledge economy: the case of the emerging mega-city region of Munich’, Global Networks, vol 10, pp114–137 Sassen, S. (2001) ‘Global cities and global city-regions: a comparison’, in A. Scott (ed) Global City-Regions: Trends, Theory, Policy, Oxford University Press, Oxford, pp78–95 Taylor, P. J., Evans, D. M. and Pain, K. (2008) ‘Application of the interlocking network model to mega-city-regions: measuring polycentricity within and beyond city-regions’, Regional Studies, vol 42, pp1079–1093

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French Cities Kathy Pain and Gilles Ardinat

The French urban space economy is best known for the international reputation of its principal business city, Paris, acknowledged as a leading ‘world city’ by John Friedmann (1986). Although Paris was not included in Saskia Sassen’s famous (1991) study, as in the case of London (Chapter 23), its role as one of Europe’s top hosts to major ‘global city’ users, advanced service firms in the global economy, has contributed to the city’s economic dominance in a highly primate and monocentric French urban structure. The Paris population is seven times that of either Lyon or Marseille, and only three French cities, apart from Paris, have a population size of more than one million (Lyon, Marseille and Lille). This territorial imbalance, specific to France within continental Europe, may be linked to a historical tendency to political centralization since the 17th century (absolute monarchy), and reinforced by the Revolution, the Napoleonic Empire and the Third Republic. Data on the global business network connectivity of French cities in 2008 reveal a similar imbalance in the domestic space economy in the contemporary era of globalization. Table 20.1 lists the cities with proportionate global network connectivity scores above 0.05 in rank order. Unsurprisingly, Paris (0.78) comes top in this ranking, but the figures emphasize the disparity in connectivity to global service networks between Paris and France’s other regional capitals represented here. With a proportionate connectivity 22 per cent of that of Paris, Lyon stands out as France’s second major global service node; however, the results for the next seven cities listed show a ‘flatter’ rank order, with the next highest proportionate score (for Marseille, ranked three) less than one-sixth that of Paris.

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Table 20.1 Global network connectivity of French cities. RANK

CITY

1 2 3 4 5 6 7 8 9

Paris Lyon Marseille Strasbourg Nantes Bordeaux Lille Montpellier Toulouse

GROSS CONNECTIVITY 75,322 16,861 11,501 10,316 9650 8938 8214 7128 6834

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.78 0.18 0.12 0.11 0.10 0.09 0.09 0.07 0.07

The 2008 figures also represent an increase in the connectivity of Paris relative to other major French regional centres since the year 2000 (Taylor, 2000): Paris 0.70–0.78, Lyon 0.24–0.18, Marseille 0.17–0.12, Strasbourg 0.16–0.11 and Bordeaux 0.14–0.09. This indicates that French state interventionist support which has tried to promote a national-scale polycentric system of cities (‘métropoles d’équilibre’) under the direction of the Délégation à l’Aménagement du Territoire et à l’action Régionale (DATAR) – the Delegation for Territorial Planning and Regional Development – has been relatively unsuccessful with regard to the distribution of advanced service economy functions. Examples of very low global business connectivity in Table 20.1 illustrate major changes in the French urban development pattern. French cities were centres of global communication in the Middle Ages (with commercial functions at Lyon and to a lesser extent at Rouen and Montpellier) and more recently (Nantes and Bordeaux have been very large ports for transatlantic trade). The heavy concentration of global functions in the Paris region also suggests the weak influence of policy attempts at economic decentralization from the 1960s (tax incentives, direct aid to business establishment outside Paris and industrial relocation). For example, only two of the 39 French multinational corporations (MNCs) listed in the 2008 Fortune 500 global ranking are headquartered outside Paris (Auchan retail at Lille and Michelin pneumatics at Clermont-Ferrand). Table 20.2 indicates the extent to which domestic service linkages are constructing French inter-urban network connectivities, that is, the degree of ‘localism’, across regional boundaries. The most striking finding here is that, in common with the result for London, Paris’s high global connectivity contrasts with a negative score for localism. Clearly, as the major French node in international service networks, it is Paris’s global connections that dominate. Apart from Paris, the other cities represented in this table have positive domestic connectivity scores (from Lille’s 1.83 to Montpellier’s 0.98). These results suggest the importance of French sub-global service network linkages.

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Table 20.2 Localism (relative concentration of connections within France). RANK

CITY

1 2 3 4 5 6 7 8 9

Lille Nantes Bordeaux Marseille Strasbourg Toulouse Lyon Montpellier Paris

LOCALISM 1.83 1.82 1.78 1.62 1.51 1.27 1.14 0.98 −1.12

While policy initiatives may have been unsuccessful in rebalancing the national geography of advanced service ‘globalism’, these positive localism scores of French provincial cities may reflect the impact of active, policy-led decentralization of administrative functions from Paris pursued from the 1980s. The increased concentration of public services and wider local powers of these cities and their ‘départements’, together with changing lifestyles (including increasing use of the car) and labour market developments during this period, have attracted people and local business to enlarged urban employment areas, or ‘bassins d’emplois’ (as defined by INSEE, the French National Institute of Statistics and Economic Studies). Looking across Tables 20.1 and 20.2 reveals some subtle and interesting changes in the order of ranking of cities when global connectedness is compared with localism. Three cities, Nantes, Bordeaux and Lille, which rank fifth, sixth and seventh respectively for global connectivity, score highest for localism. In contrast, Montpellier ranks eighth in both tables and it is of interest that its low ranking for global network connectivity is evidently not counterbalanced by increased localism. Similarly Toulouse (ranked ninth for global connectivity) ranks sixth only for localism.

Table 20.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5= 5= 7 8 9

Paris Lyon Marseille Bordeaux Strasbourg Lille Nantes Toulouse Montpellier

TRADITIONAL GLOBALISM 1.04 −0.42 −0.66 −0.67 −0.69 −0.69 −0.74 −0.84 −0.86

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Table 20.3 produces insights into the degree of connectivity of French cities to the dominant world city dyad in globalization, London–New York, known as ‘NYLON’. As would be expected, Paris is shown to be strongly integrated in this important global service network dyad. But the striking result is that, apart from Paris, all other French cities show very weak, negative, dyad connectivity. In terms of rank order, Lyon retains its place as second city to Paris in this measure, as for global integration (Table 20.1). As might be predicted, Toulouse and Montpellier have the weakest connectivity to NYLON, mirroring their rankings for global network integration. Strasbourg remains in a similar mid-ranked position in both Tables 20.1 and 20.3. Interestingly, Marseille and Bordeaux rise to third and fourth rank positions respectively, Lille and Nantes swap positions. However, Bordeaux’s historical ties with England and the proximity of Lille (in particular through the Channel Tunnel) have had very little influence on the scores of these two cities. The overall picture is of Paris leading and with exclusive orientation to NYLON in the French urban space economy. Table 20.4 shows city connections to an emergent new world city articulation in globalization involving Beijing, Shanghai and Hong Kong (Taylor, 2004). As for all other global scale connections, as expected, Paris has strong links to this important China-based triad. Mirroring the picture for links to NYLON, no other French cities have a positive orientation to the triad. Nevertheless some interesting shifts in the French urban ranking for this measure are apparent. Surprisingly Lyon’s position changes dramatically here. Whereas it is positioned next to Paris in all other measures, it has weaker links to these important Chinese cities than four other French provincial cities, Nantes, Toulouse, Bordeaux and Lille. Surprisingly the latter four cities feature in the lower rankings in Table 20.1. In particular, Toulouse shifts position from ninth for global links to third for links to the China triad. The Toulouse economy is specialized in aircraft construction, for which China is a strategic market.

Table 20.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8 9

Paris Nantes Toulouse Bordeaux Lille Lyon Marseille Strasbourg Montpellier

NEW GLOBALISM 0.92 −0.66 −0.67 −0.73 −0.74 −0.76 −0.77 −0.86 −0.90

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In conclusion, the data show that Paris remains by far the most integrated French city in the global city network; however other regional capitals have some important global network links. Lyon stands out from the crowd with nearly one-quarter of Paris’s global connectivity. Paris has the only positive orientation to the key contemporary world city constellations, NYLON and the Chinese triad. Nevertheless, other cities have important roles as regional service network nodes. The data show some interesting regional differences of service orientation that can potentially inform understanding of the French space economy, and the places where different strengths and weaknesses are present. Together, the effects of decentralization policies and globalization have led to a redefinition of urban functions within the French city network. While Paris has lost certain national administrative functions to other regional capitals, it has an increasing global role. It is fully engaged in international activities which can be construed as a national asset in the competitive political context of world cities. Meanwhile, other large cities have become the new regional centres of power, but with limited global integration and a strong orientation to local management functions. The latest industrial policies introduced by the Délégation Interministérielle à l’Aménagement et à la Compétitivité des Territoires (DIACT – the Interministerial Delegation on Territorial Planning and Competitiveness – the January 2006 successor to DATAR), have been inspired by the Michael Porter (1998) ‘clusters’ thesis. Their aim is to correct ongoing national imbalances by distributing competitiveness clusters (‘pôles des compétitivité’) across the French territory. These clusters are expected to become centres of excellence in the French economy in globalization (attracting foreign direct investment (FDI), export platforms, local branches of foreign MNCs and highly-skilled foreign workers). Of the 17 world clusters designated, just four are located in the Paris region. Thus, France retains a commitment to rebalance its urban network, but it is too early to say whether the new competitiveness clusters approach will improve the global integration of provincial French cities.

References Friedmann, J. (1986) ‘The world city hypothesis’, Development and Change, vol 17, pp69−83 Porter, M. E. (1998) ‘Clusters and the new economics of competition’, Harvard Business Review, November−December, pp77−90 Sassen, S. (1991) The Global City: New York, London, Tokyo, Princeton University Press, Princeton, NJ Taylor, P. J. (2000) Global Network Service Connectivities for 315 Cities in 2000, GaWC Data Set 12, www.lboro.ac.uk/gawc/datasets/da12.html, accessed 10 March 2010 Taylor, P. J. (2004) World City Network: A Global Urban Analysis, Routledge, London

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21

Swiss Cities Alain Thierstein and Stefan Lüthi

Switzerland, being a small and open economy, has been strongly integrated in international exchanges of goods and services for many decades. Although this is an accepted fact from an economic point of view, Switzerland’s perception of the structure and dynamics of its own territory remains inward-bound. However, over recent decades Switzerland has experienced the reorganization of its functional–territorial division of labour. The growing relevance of the knowledge economy is a driving force slowly altering regional development and spatial functional specialization. Two perspectives on the territory rival each other. The bottom-up perspective from within Switzerland is represented by official statistical definitions and identifies more than 50 agglomerations (BFS, 2004). The years after 2000, however, brought about a debate on how Switzerland’s spatial hierarchy would look from a top-down perspective. Several studies identified super structures of agglomerations, and the discussion evolved around whether there are six (Blöchliger, 2005), five (BFS, 2004), three (Diener et al, 2005) or only two of these super structures, the latter being labelled ‘megacity regions’ (Glanzmann et al, 2006). In 2004 an important contribution was made in a European Observation Network for Territorial Development and Cohesion (ESPON) study that developed a typology of Metropolitan European Growth Areas (MEGAs) that may be seen as future ‘counterweights’ to the European ‘Pentagon’ – the area delimitated by the cities of London, Hamburg, Munich, Milan and Paris (ESPON, 2004). Of the total of 64 European MEGA cities, Paris and London are considered to be the only global nodes. Zurich is labelled as category 1 MEGA, Geneva as category 2 MEGA, and Bern as category 3 MEGA (ESPON, 2004); surprisingly enough, Basel did not show up at all in these MEGA categories. Two years later, in 2006, the Sustainable Management of European Polycentric Megacity Regions (POLYNET) study (Hall and Pain, 2006) identified the emergence of two polycentric megacity regions in Switzerland: northern Switzerland with Zurich and Basel in the German speaking part (Thierstein et al, 2006) and Arc Lémanique with Geneva and Lausanne in the

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French speaking part (Comtesse and Van der Poel, 2006). Zurich and Geneva have been leading Switzerland’s network of cities for decades, but the two cities have developed somehow ‘together apart’. Zurich has become an internationally important financial place while since World War I Geneva has been a node for diplomatic and trade activities as well as private banking. It was Taylor’s first measurement of global network connectivities in 2000 that confirmed Zurich as a global city of the third category with a global connectivity of 0.49, while Geneva ranked in the fourth category with a connectivity of 0.31 (Taylor et al, 2002). Table 21.1 shows the global network connectivities in 2008 for the five Swiss cities with proportionate connectivities above 0.05, with 0.55 for Zurich and 0.38 for Geneva. These values underscore the continuing dominance of Zurich and Geneva as the two cities integrated most strongly into the world city network. When comparing Zurich in 2008 with the score in 2000 it becomes even more evident that Zurich has gained in significance as the Swiss hub for globally connected advanced producer service firms. This relative gain in importance is attributable to the entire localized system of financial intermediaries, which has developed around the stock exchange, international banks and insurance companies (Kruse, 2005). While Geneva has been able to keep its position as the second Swiss global city, Lausanne and Basel follow at a distance with similar scores of connectivity of 0.15 and 0.13. Finally, Bern – the capital city of Switzerland – displays an even lower score of 0.06. To the dedicated observer of the socioeconomic dynamics of the Swiss territory these results do not come as a surprise. International competition is turning the Swiss city network into an ever more vertically organized urban hierarchy. In short, the 2008 scores in Table 21.1 seem to be in line with the findings of the Swiss POLYNET case study, arguing that two urban super structures have emerged in Switzerland: first the megacity region of northern Switzerland with its backbone of Zurich and Basel, and second the Arc Lémanique, the megacity region that evolves around the axis of Geneva and Lausanne (Glanzmann et al, 2006; Thierstein et al, 2006).

Table 21.1 Global network connectivity of Swiss cities. RANK

CITY

1 2 3 4 5

Zurich Geneva Lausanne Basel Bern

GROSS CONNECTIVITY 53,197 36,928 14,195 12,481 5302

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.55 0.38 0.15 0.13 0.06

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Table 21.2 displays the national connectivities or the relative degree of ‘localism’ of the five cities. Most striking of course is the strong localism of Bern with a positive score of 0.78, which indicates that the national capital’s global connectivity of 0.06 is mostly due to links within Switzerland itself. Zurich, on the contrary, with its negative reverse to its global connectivity is a truly ‘un-local’ global city, at least with regard to interlocking firm networks of advanced producer services. These results seem to fit perfectly with a recent debate in Switzerland about the status of metropolitan regions. On the one hand, Basel has begun to promote itself as a metropolitan region on its own, emphasizing its international significance in pharmaceutical activities. On the other hand, the draft of the new Swiss spatial development concept denies Bern the status of a metropolitan region but instead labels the capital city of Switzerland as ‘Hauptstadtregion’ – capital city region – which has led to a certain amount of irritation for policymakers (ARE, 2008). These examples illustrate two different cases but one phenomenon: looking outwards from the inside. Both Bern and Basel perceive themselves as being strong and large enough to be called (European) metropolitan regions. Looking from outside inwards, however, plays a trick on these two cities. With regard to interlocking networks of advanced producer service firms, Bern, and to a lesser degree Basel, are cities with relatively predominant links within the country, which underlines their high degree of localism.

Table 21.2 Localism (relative concentration of connections within Switzerland). RANK

CITY

1 2 3 4 5

Bern Basel Lausanne Geneva Zurich

LOCALISM 0.78 0.51 −0.01 −0.32 −0.57

Traditional globalism in Table 21.3 shows Zurich strongly inclined towards New York and London (NYLON). Thus, Zurich’s intra-firm networks of advanced producer service firms are predominantly organized around the nodes of New York and London. Geneva in contrast has a very low score, which gives leeway to the assumption that Geneva’s interlocking firm networks are orientated to other global cities to a much lesser degree. Geneva’s global appeal derives much more from relations in trade and related financial activities with South America, Africa and the Near and Far East, while Zurich predominantly gears its relations to the English-speaking world, and of course cultural and linguistic dispositions also furnish strong explanations.

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Table 21.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5

Zurich Geneva Bern Basel Lausanne

TRADITIONAL GLOBALISM 0.51 0.03 −0.32 −0.45 −0.57

Finally, Table 21.4 could be an indicator for the emergence of a new monocentric hierarchy. In Switzerland, Zurich, with a score of 0.51, would then stand out as by far the only global city, with strong network links to the Chinese city triad of Beijing, Hong Kong and Shanghai. The main reason for this is the strong presence of firms in the financial and insurance sectors that are important elements in the financial value-added system of emerging markets. Rather astonishing is the low negative score for Geneva, which has neither overly strong connections to NYLON nor to the rapidly developing Chinese cities. Likewise the case of Lausanne is peculiar: the city ranks last among the five Swiss cities with regard to traditional NYLON globalism as well as to the new Chinese globalism. This in no way reflects Lausanne as a technological centre, with its research facilities of the Swiss Federal Institute of Technology, its high-tech firms and highly qualified labour market. It is to be assumed that if one would calculate interlocking firm connectivities for the high-tech sector of the knowledge economy, the negative global scores of Lausanne would change significantly.

Table 21.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5

Zurich Geneva Bern Basel Lausanne

NEW GLOBALISM 0.51 −0.01 −0.18 −0.27 −0.75

In conclusion, the 2008 world city analysis has generally confirmed the more discerning recent writings on the hierarchical dynamics of Swiss cities. Zurich – and to a lesser degree Geneva – dominate Switzerland’s functional urban hierarchy in globalization, with the two cities demonstrating distinct complementarities in their global connectivity patterns.

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References ARE (2008) Raumkonzept Schweiz. Eine dynamische und solidarische Schweiz. Entwurf vom 24. Juni 2008, Bundesamt für Raumentwicklung, Bern BFS (Bundesamt für Statistik) (2004) Die Raumgliederungen der Schweiz. Nachführung anhand der Resultate der Volkszählung 2000, Elektronischer Datensatz, Neuchâtel Blöchliger, H. (2005) Baustelle Föderalismus. Metropolregionen versus Kantone: Untersuchungen und Vorschläge für eine Revitalisierung der Schweiz, Verlag Neue Zürcher Zeitung, Zürich Comtesse, X. and Van der Poel, C. (2006) Le Feu au Lac. Vers une Région Métropoltaine Lémanique, Avenir Suisse, NZZ Libro, Editions du Tricorne, Zürich/Genf Diener, R., Herzog, J., Meili, M., de Meuron, P. and Schmid, C. (2005) Die Schweiz. Ein städtebauliches Porträt, Birkhäuser, Basel ESPON (2004) ESPON Project 1.1.1. The Role, Specific Situation and Potentials for Urban Areas as Nodes of Polycentric Development, Final Report, European Spatial Planning Observation Network ESPON, Luxemburg Glanzmann, L., Gabi, S., Kruse, C., Thierstein, A. and Grillon, N. (2006) ‘European Metropolitan Region Northern Switzerland: driving agents for spatial development and governance responses’, in P. Hall and K. Pain (eds) The Polycentric Metropolis: Learning from Megacity Regions in Europe, Earthscan, London, pp172–180 Hall, P. and Pain, K. (eds) (2006) The Polycentric Metropolis: Learning from Megacity Regions in Europe, Earthscan, London Kruse, C. (2005) ‘Börsengänge am Finanzplatz Schweiz. Vernetzte Finanzintermediäre als Erfolgs- oder Risikofaktor für Börsenunternehmen?’, Dissertation, Eidgenössische Technische Hochschule Zürich, Zürich Taylor, P. J., Catalano, G. and Walker, D. R. F. (2002) ‘Exploratory analysis of the world city network’, Urban Studies, vol 39, pp2377–2394 Thierstein, A., Kruse, C., Glanzmann, L., Gabi, S. and Grillon, N. (2006) Raumentwicklung im Verborgenen. Untersuchungen und Handlungsfelder für die Entwicklung der Metropolregion Nordschweiz, NZZ Buchverlag, Zürich

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22

Italian Cities Gilda Catalano

As many other European cities, major Italian cities have been undergoing significant processes of urban regeneration in recent years (Savitch and Kantor, 2002; Buck et al, 2005). This renewal has transformed some important social aspects (promoting what may be described as ‘welfare cities’) and economic elements (e.g. larger investments in finance and in the so-called creative industries) in many industrialized cities. The economic and aesthetic appeal of some cities has been improved, mirrored in increasing flows of foreign investment and numbers of tourists from abroad (Borelli, 2005). Genoa and Turin are the leading actors in these structural transformations and, probably, their new images should have facilitated a new launch on the international scene. Milan is also developing on this front (Camagni, 2007); for the forthcoming Expo in 2015, it is promoting special creative assets, even incorporating the logo ‘Slow Food’. Florence and Bologna are in a political phase of stand-by as other medium-sized cities are emerging. This is the current urban policy framework, wherein local urban changes can partially affect further processes, such as the global links of an urban centre within the world city network (AA.VV., 2006). Table 22.1 shows Milan and Rome to be the most integrated Italian cities within the global city network; there is a clear gap to the remaining six major Italian cities. Surprisingly, Bologna is in third position but, it should be noted, it is only a little higher than Turin and Genoa in its network connectivity; the latter two cities have similar scores and are ranked fourth and fifth respectively. These results can be partly explained by the above-mentioned urban regeneration processes of the last two decades, following their industrial decline in the 1970s (Perulli, 2004). In some ways, Genoa and Turin have received specific benefits from urban renewal, especially in terms of economic appeal. The lowest scores are for Florence in sixth position, just above Palermo and Trieste. These last three rankings are not surprising. First of all, Florence shares with Rome a central Italian location and therefore is in the larger city’s economic shadow; second, Palermo’s location in the Italian south limits its involvement with foreign enterprises; and Trieste is an important local gateway

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city between eastern Italy and adjacent Slavic areas. Despite Palermo and Trieste being situated at the far ends of Italy, their geographical position may become a strategic added value for urban competition in the future.

Table 22.1 Global network connectivity of Italian cities. RANK

CITY

1 2 3 4 5 6 7 8

Milan Rome Bologna Genoa Turin Florence Palermo Trieste

GROSS CONNECTIVITY 65,988 50,604 15,121 10,016 9256 7714 4934 4746

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.69 0.53 0.16 0.10 0.10 0.08 0.05 0.05

In spite of these last rankings, the overall message coming from Table 22.1 underlines the very low connectivity of Italian cities in the world city network, where Milan and Rome stand out as the only Italian cities with a modest degree of global connectivity. Below these two cities the distribution of city connectivities is relatively flat. These considerations are confirmed by Table 22.2, which illustrates the concentration of local connections within Italy. Milan, Rome and Bologna show reverse results from the previous table: their negative scores indicate varying degrees of being ‘un-local’, thus stressing their first three positions in Table 22.1. Trieste is at the top of cities listed in Table 22.2: its connections are the most locally concentrated of the cities studied.

Table 22.2 Localism (relative concentration of connections within Italy). RANK

CITY

1 2 3 4 5 6 7 8

Trieste Turin Palermo Genoa Florence Bologna Rome Milan

LOCALISM 0.82 0.64 0.54 0.36 0.33 −0.01 −0.54 –0.90

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The middle-ranked cities in the two tables require further comparisons. In Table 22.1, the fourth to sixth positions are occupied in the order Genoa, Turin, Florence; but, in Table 22.2, a new ranking of cities can be found. Comparing middle-ranked results from the two tables, it is possible to affirm that Turin is more local than Genoa; furthermore, Genoa (fourth position in both tables) is a little better connected than Florence in both tables, while Palermo outranks Florence and Genoa in its local connections. In contrast to Milan and Rome, cities such as Trieste and Palermo show a relatively higher importance of domestic links. The results from Table 22.3 confirm that Milan and Rome are the only cities relatively over-linked to the ‘traditional global dyad’ of New York and London (NYLON). Turin occupies the third position while the remaining cities have even lower scores. Palermo, Bologna and Genoa are in the three last positions. Table 22.4, where the ranking is based on relative concentration of connections to a ‘new emerging global triad’ of Beijing, Hong Kong and Shanghai, again shows Milan and Rome as the only over-linked cities. Florence and Genoa are the lowest-scoring cities, underlying their minor role in terms of these Asian connections.

Table 22.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7 8

Milan Rome Turin Trieste Florence Palermo Bologna Genoa

TRADITIONAL GLOBALISM 0.61 0.40 −0.19 −0.59 −0.62 −0.66 −0.72 −0.79

Table 22.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8

Milan Rome Turin Trieste Bologna Palermo Florence Genoa

NEW GLOBALISM 0.57 0.36 −0.07 −0.39 −0.73 −0.77 −0.91 −1.02

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Comparing the two tables, the surprise city is Trieste: fourth position in both Table 22.4 and Table 22.3, slightly more oriented to emerging global centres, outranking Palermo, Bologna, Florence and Genoa in both global orientations. In conclusion, the 2008 world city analysis has confirmed Milan and Rome as the main Italian cities in the world city network. Below these ranks there is no clear picture of the ordering of other Italian cities. Following this analysis, traditional medium-sized cities seem to have left room for emerging minor cities in the Italian urban scenario.

References AA.VV. (2006) Pianificazione strategica per la governance del territorio, Lattanzio, Milano Borelli, G. (ed.) (2005) La politica economica delle città europee. Esperienze di pianificazione strategica, Franco Angeli, Milano Buck, N., Gordon, I., Harding, A., and Turok, I. (eds) (2005) Changing Cities: Rethinking Urban Competitiveness, Cohesion and Governance, Palgrave Macmillan, Basingstoke Camagni, R. (2007) ‘L’Unione Europea e le città: linee guida per l’area metropolitana milanese’, Territorio, vol 42, pp45–49 Perulli, P. (2004) Piani strategici. Governare le città europee, Franco Angeli, Milano Savitch, H. V. and Kantor, P. (2002) Cities in the International Marketplace: The Political Economy of Urban Development in North America and Western Europe, Princeton University Press, Princeton, NJ

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23

UK Cities Peter J. Taylor

The UK space economy has long been notorious for its primate pattern of cities centred on London and the south east. For much of the 20th century, UK governments pursued regional policies specifically to counter ‘the drift to the south’ resulting from the decline of the industrial cities and towns of northern Britain from their 19th century economic prime. But such policies proved to have limited impact on the economic forces creating London’s primacy. With the rise of neoliberal globalization from the late 1970s, the prospects for the cities collectively known as ‘not-London’ seemed to have been further reduced: the demise of regional policy was followed by government policy that precipitated the City of London’s ‘Big Bang’. This opened up the City to foreign banks and other financial services to ensure London would become a key locale for on-going economic globalization, and Saskia Sassen (1991) announced that London, with New York and Tokyo, was an archetypal ‘Global City’. With this global position added to London’s national dominance, it seemed that London’s UK primacy in the new world of globalization would be greater than ever. And this was confirmed by the first measurement of global network connectivities in 2000 (Taylor et al, 2002; Taylor, 2004): London was ranked first globally and with no other UK city in the top 100 (Beaverstock et al, 2001). Other studies have highlighted the economic underperformance of UK provincial cities compared to their European counterparts (e.g. Parkinson et al, 2004, 2006). However, at the beginning of the 21st century there appeared to be a revival of provincial UK cities. New measures of global network connectivity in 2004 showed that UK cities had experienced some of the most rapid increases in global network connectivities in the world: Edinburgh, Bristol, Cardiff and Leeds being particular noteworthy in this respect (Taylor and Aranya, 2006). Further work has indicated that the UK space economy, while not becoming fully ‘balanced’, has been developing intercity networks to complement the continuing London-headed urban hierarchy. In other words, since 2000, major global service providers have found it worth their while to make use of UK provincial cities as well as London (Taylor et al, 2009, 2010). This is the context in which to consider UK cities in the 2008 world city network analysis.

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Table 23.1 shows global network connectivities for the 17 UK cities with proportionate connectivities above 0.05 – these measures show how well the different cities are integrated into the world city network. The outstanding result – the continuing dominance of London – is no surprise, and with New York it is consistently the most integrated city in the world city network. While other UK cities are still not major players in the world city network, some important world cities can now be identified. Manchester, Edinburgh and Birmingham each have at least one-fifth of the highest connectivity; Manchester and Birmingham have featured in the competition to be the UK’s ‘second city’ for more than a century and Table 23.1 shows that they have been joined by Edinburgh. The first two are centres of the two major economic regions outside the south east, the north west and west Midlands respectively, and are reinventing themselves as new European and world cities. Edinburgh is the fast riser based upon being the capital city of Scotland, the UK’s main political devolution (with its new service needs), as well as being home to successful banks (before the credit crisis when these data were collected). Glasgow has traditionally been a competitor for UK second city status but has now been overtaken by its Scottish neighbour Edinburgh; however it still remains important. The remaining cities are mainly regional centres with their importance reflecting either or both the economic importance of their region and the city’s domination of its region: Bristol and the south west; Leeds and Yorkshire; Belfast, capital of Northern Ireland with its devolved government; Newcastle and the north east; Southampton and the south coast; Cardiff, capital of Wales, the third devolution; Nottingham and the east Midlands; Norwich and East Anglia; and Plymouth and the far south west. In addition, Aberdeen is important because of its global oil industry links; and Liverpool and Sheffield are historically major centres that, like Glasgow, are being eclipsed in service industries by neighbouring cities, Manchester and Leeds respectively. The overall message of this table is not that any UK city is seriously rivalling London, but that UK cities right across the country are integrated into the world city network to varying degrees. Nevertheless, Table 23.2 indicates that we should not take this argument for worldwide integration of UK provincial cities too far. This table shows measures of ‘localism’, the degree to which a city’s connectivity is dominated by links within the country. The table largely reverses the rankings in the previous table but the key point is the separation of London from the rest. With a large negative score, London is shown to be very ‘un-local’: the vast majority of its connections are beyond the UK. All the remaining cities have positive scores indicating the importance of domestic links relative to foreign connections. In this case Manchester, with its score nearest to zero, is revealed as not as local as its provincial peers, and Glasgow appears less domestic in its links than Birmingham and Edinburgh. The surprise result when comparing these data to those in Table 23.1 is the position of Belfast as the third least local: this may reflect its close Irish links with Dublin, and hence beyond the UK.

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Table 23.1 Global network connectivity of UK cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

London Manchester Edinburgh Birmingham Glasgow Leeds Bristol Belfast Newcastle Aberdeen Liverpool Southampton Cardiff Nottingham Norwich Sheffield Plymouth

GROSS CONNECTIVITY 96,267 21,525 20,588 19,995 17,884 16,720 15,166 12,919 12,208 11,628 11,410 10,678 9574 8838 8034 7558 4334

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 1.00 0.22 0.21 0.21 0.19 0.17 0.16 0.13 0.13 0.12 0.12 0.11 0.10 0.09 0.08 0.08 0.05

Table 23.2 Localism (relative concentration of connections within the UK). RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Plymouth Nottingham Norwich Cardiff Sheffield Liverpool Southampton Newcastle Bristol Leeds Aberdeen Birmingham Edinburgh Glasgow Belfast Manchester London

LOCALISM 6.75 5.91 5.62 5.39 5.31 4.80 4.55 3.91 3.82 3.55 3.48 3.32 3.28 3.04 2.94 2.47 −1.31

247

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Table 23.3 measures the ‘traditional globalism’ of UK cities by showing their combined connectivity to London and New York (NYLON) as the ‘main street dyad’ of contemporary globalization (London is therefore omitted from this table). The rankings here are only weakly related to the global network connectivities (Table 23.1). There is a definite top three, with positive scores that includes Edinburgh and Manchester as we might expect, but they are both below top-ranked Norwich. This may reflect strong links to London, as East Anglia has shared in London and the south east’s prosperity in recent years. The five bottom-ranked cities are also not particularly predictable as they are all ‘middle-ranked’ cities in Table 23.1; Leeds is the big surprise, its recent rise as a financial centre not being associated with the importance of NYLON connections.

Table 23.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5= 5= 7 8 9 10 11 12 13 14= 14= 16 –

Norwich Edinburgh Manchester Sheffield Bristol Plymouth Glasgow Birmingham Cardiff Nottingham Aberdeen Leeds Newcastle Liverpool Belfast Southampton London

TRADITIONAL GLOBALISM 0.07 0.06 0.01 −0.08 −0.12 −0.12 −0.13 −0.17 −0.21 −0.22 −0.26 −0.34 −0.41 −0.45 −0.45 −0.46 –

Table 23.4 shows city connections to what may be an emerging new globalism based upon Beijing, Shanghai and Hong Kong. London has by far the largest connection to this Chinese triad centre, which is to be expected. The cities ranked third to seventh are also predictable – these are the major provincial cities (Table 23.1). But between London and these leading provincial UK cities we find Plymouth, ranked second and the only other UK city, apart from London, to score positively on this measure. To say that this is a major surprise is an understatement. It appears that in this case we have reached the

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limitations of our data. It can be noted that in Table 23.1 Plymouth only just qualifies for inclusion with a score of 0.05, the cut-off point. In addition, we can note that UK provincial cities have relatively weak links to Chinese cities. The combination of these two features means that the score for Plymouth in this particular table is potentially not very robust; it will be vulnerable to the effect of being based upon links from very few firms. Hence in this case, by stretching our evidence as far as it will go, we have been unlucky and produced what is almost certainly a maverick result.

Table 23.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

London Plymouth Edinburgh Bristol Glasgow Manchester Birmingham Sheffield Norwich Nottingham Leeds Aberdeen Newcastle Belfast Cardiff Liverpool Southampton

NEW GLOBALISM 0.95 0.21 0.06 −0.03 −0.05 −0.08 −0.22 −0.23 −0.27 −0.29 −0.30 −0.49 −0.50 −0.52 −0.53 −0.64 −0.65

In conclusion, the 2008 world city analysis has generally confirmed recent writings on UK cities in globalization: London continues to dominate, but some provincial cities are becoming important service nodes in their own right, with interesting domestic connectivities. The details of our new analyses allow us to pinpoint which are these newly successful UK cities in the world city network, and to locate where their particular geographical strengths and weaknesses are to be found.

References Beaverstock, J. V., Hoyler, M., Pain, K. and Taylor, P. J. (2001) Comparing London and Frankfurt as World Cities: A Relational Study of Contemporary Urban Change, Anglo-German Foundation, London

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Parkinson, M., Champion, T., Simmie, J., Turok, I., Crookston, M., Katz, B. and Park, A. (2006) State of the English Cities, Office of the Deputy Prime Minister (ODPM), London Parkinson, M., Hutchins, M., Simmie, J., Clark, G. and Herdonk. H. (2004) Competitive European Cities: Where Do the Core Cities Stand? Office of the Deputy Prime Minister (ODPM), London Sassen, S. (1991) The Global City: New York, London, Tokyo, Princeton University Press, Princeton, NJ Taylor, P. J. (2004) World City Network: A Global Urban Analysis, Routledge, London Taylor, P. J. and Aranya, R. (2006) ‘Connectivity and city revival’, Town & Country Planning, vol 75, pp309–314 Taylor, P. J., Catalano, G. and Walker, D. R. F. (2002) ‘Measurement of the world city network’, Urban Studies, vol 39, pp2367–2376 Taylor, P. J., Evans, D. M., Hoyler, M., Derudder, B. and Pain, K. (2009) ‘The UK space economy as practised by advanced producer service firms: identifying two distinctive polycentric city-regional processes in contemporary Britain’, International Journal of Urban and Regional Research, vol 33, pp700–718 Taylor, P. J., Hoyler, M., Evans, D. M. and Harrison, J. (2010) ‘Balancing London? A preliminary investigation of the “Core Cities” and “Northern Way” spatial policy initiatives using multi-city corporate and commercial law firms’, European Planning Studies, vol 18, pp1285–1299

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24

Canadian Cities Kathy Pain and Barry E. Prentice

The dominant narrative describing the Canadian urban space economy has long focused on inter-urban competition, with rivalry between major commercial centres (Montreal and Toronto) the high profile story. Prentice (2006) has linked the urban competition discourse to North America’s ‘frontier’ development as a hierarchical distribution of ‘gateway cities’ (Burghardt, 1971) connected by transportation ‘corridors’ (Whebell, 1969). For 100 years the east–west transcontinental railway secured and maintained Montreal’s role as Canada’s major financial capital, but communications developments – first long-haul trucking, then air travel and recently the digital revolution – have dramatically changed the roles, functions and connections of gateway cities (Prentice, 2006; Pain 2007a, 2007b). Toronto was classified a secondary ‘world city’ by John Friedmann (1986). By the year 2000, Toronto had achieved a score of 0.60 connectivity compared with Montreal’s 0.40 (Taylor, 2000). Table 24.1 shows the 2008 global network ranking for ten Canadian cities with proportionate connectivities above 0.05; the results indicate differences in the integration of these cities in the world city network. The ranking presents clear evidence that Toronto is now Canada’s leading global service node by some way. Montreal takes second place with just under half of Toronto’s connectivity to worldwide advanced service networks. Vancouver and Calgary rank third and fourth respectively. The rise of Vancouver and Calgary threatens to displace Montreal as ‘second city’. Already Vancouver has eclipsed Montreal as the city with the second largest Canadian airport, and Calgary has surpassed Montreal as the second location for corporate head offices. These changes can be largely explained by the development of the energy industry that is centred in Calgary and the pull of Asian demand that has made Vancouver Canada’s largest port. Table 24.2 reveals a very different picture when local connectivity within Canada is considered. Halifax, Quebec, Winnipeg and Edmonton in particular show important subglobal-scale servicing connectivities, reflecting strategic alliances associated with expansion of the new economy. These former railway gateways continue to serve their regional hinterlands. Halifax is the economic

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hub of the eastern maritime provinces. Quebec serves the francophone communities. Winnipeg is the hub of central Canada and a gateway to the eastern Arctic. Edmonton is the gateway to northern Alberta, the Yukon and North West Territories and the overland route to Alaska.

Table 24.1 Global network connectivity of Canadian cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10

Toronto Montreal Vancouver Calgary Ottawa Winnipeg Edmonton Halifax Quebec Saskatoon

GROSS CONNECTIVITY 60,454 28,662 26,195 19,970 14,527 11,030 10,434 10,094 9183 6758

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.63 0.30 0.27 0.21 0.15 0.11 0.11 0.10 0.10 0.07

Table 24.2 Localism (relative concentration of connections within Canada). RANK

CITY

1 2 3 4 5 6 7 8 9 10

Halifax Quebec Winnipeg Edmonton Ottawa Calgary Vancouver Saskatoon Montreal Toronto

LOCALISM 3.13 3.03 2.87 2.71 2.29 1.62 1.07 0.91 0.78 −0.09

A negative localism measure for Toronto (−0.09) especially, but also the low score for Montreal (0.78) indicate that global links are important relative to domestic service alliances for these cities. The low level of localism for Saskatoon (ranked 8 with a score of 0.91 in Table 24.2) and global connectivity scores (ranked 10, score 0.07 in Table 24.1) suggest the under-networked economic structure of this city. Table 24.3 indicates the proportionate connectivity of the same ten cities to what has become the established relational dyad at the centre of economic

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globalization, New York–London (NYLON). Saskia Sassen (1991) pronounced New York and London the world’s ‘global cities’ along with Tokyo, hence established (local) links between Canadian cities and New York could potentially have a bearing on present-day dyadic integration.

Table 24.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7 8 9 10

Toronto Quebec Montreal Calgary Vancouver Ottawa Winnipeg Halifax Edmonton Saskatoon

TRADITIONAL GLOBALISM 0.49 0.31 0.27 0.11 −0.05 −0.41 −0.54 −0.55 −0.61 −0.97

As would be expected from the data on global connectivity, Toronto eclipses Montreal in 2008 NYLON integration, however, a big surprise is the appearance of Quebec in second place. Quebec ranks ninth Canadian node for global connectivity (score 0.10 in Table 24.1) yet second node for links to NYLON. What is more, Quebec is also ranked second city for localism (Table 24.2). The explanation may lie in the coming of age of the La Francophonie. Quebec has become a focal point for this global network that boasts 200 million people on five continents. Just as Quebec has a strong local network within Canada’s French-speaking communities, it has global links through NYLON to the French nations worldwide. Calgary and Vancouver switch rankings between Tables 24.1 and 24.3. A probable hypothesis is that Calgary’s global connections to world financial centres is related to the huge capital needs of the energy industry. Surprisingly, Vancouver has a negative score for the NYLON measure, but this could reflect its role on the Pacific Rim, and particularly the west coast of North America. Table 24.4 shows Canada’s connections to what has become acknowledged as the new, and growing, world service triad, Beijing, Shanghai and Hong Kong, and a key urban policy driver (Gillen et al, 2007). Toronto shows good links to the triad, as might be expected, but comparison with Table 24.3 shows that in fact its degree of Chinese connectivity (0.59) exceeds its NYLON (0.49) links. The ordering of cities ranked 1–6 clearly follows that for NYLON relations but this time Montreal is closer to Toronto’s connectivity. The small negative score of Vancouver for this measure (−0.08) seems

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extremely surprising given its west coast role as gateway to Asia-Pacific flows. This may indicate a failure to engage with new economic functions governing ‘gateway city’ transcontinental connectivity.

Table 24.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8 9 10

Toronto Montreal Quebec Calgary Vancouver Ottawa Halifax Edmonton Winnipeg Saskatoon

NEW GLOBALISM 0.59 0.50 0.32 0.07 −0.08 −0.28 −0.60 −0.69 −0.75 −1.24

Calgary’s orientation to the Chinese triad is only just positive (0.07). Services linked to the energy sector at Calgary may be significant, but the flow of Asian-manufactured imports is also important. Calgary has emerged as the most important domestic distribution centre in western Canada, with Toronto serving everywhere east of Sault Ste. Marie. Saskatoon’s ranking as tenth city in Table 24.4 (−1.24) endorses its low connectivity beyond and within Canada. In conclusion, the analysis shows that cities across the Canadian territory are integrated into the world city network to varying degrees. Toronto clearly takes the lead as Canada’s international service node, and importantly its strong links to NYLON and especially to China, indicate orientations to key contemporary domains of the world economy. Montreal and Vancouver are close contenders for second, globally connected city, but Vancouver lacks Montreal’s orientation to new globalization domains, especially China. Calgary appears as an important globally oriented service node that is on the ascendancy. Quebec is the big surprise, with strong NYLON and Chinese orientations relative to its other global connections. Other regional cities have more important domestic service connections. Saskatoon emerges as poorly connected to the advanced service economy at both local and global scales. It will be interesting to see whether this changes in the future. The Province of Saskatchewan is recognized to be more resource-rich than neighbouring Alberta, and has reversed its internal population out-migration. With huge reserves of uranium, potash, coal, oil, gas and tar sands, plus agriculture, forestry and mining, Saskatoon is likely to grow significantly faster than the rest of Canada for decades to come.

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References Burghardt, A. P. (1971) ‘A hypothesis about gateway cities’, Annals of the Association of American Geographers, vol 61, pp260–285 Friedmann, J. (1986) ‘The world city hypothesis’, Development and Change, vol 17, pp69–83 Gillen, D., Parsons, G., Prentice, B. and Wallis, P. (2007) Pacific Crossroads: Canada’s Gateways and Corridors, Canada’s Asia-Pacific Gateway and Corridor Initiative, Vancouver, BC, www.gateway-corridor.com/roundconfpapers/papers.htm, accessed 10 March 2010 Pain, K. (2007a) Global Cities, Gateways and Corridors: Hierarchies, Roles and Functions, Canada’s Asia-Pacific Gateway and Corridor Initiative, Vancouver, BC, www.gateway-corridor.com/roundconfpapers/papers.htm, accessed 10 March 2010 Pain, K. (2007b) Gateways and Corridors in Globalisation: Planning Sustainable Infrastructures for Transcontinental ‘Spaces of Flows’, Canada’s Asia-Pacific Gateway and Corridor Initiative, Vancouver, BC, www.gatewaycorridor.com/roundconfpapers/papers.htm, accessed 10 March 2010 Prentice, B. E. (2006) Gateways, Corridors and Strategic City Pairs, Canadian Transportation Research Forum 41st Annual Meeting 2006, http://mpra.ub.unimuenchen.de/14625/, accessed 10 March 2010, pp520–534 Sassen, S. (1991) The Global City: New York, London, Tokyo, Princeton University Press, Princeton, NJ Taylor, P. J. (2000) Global Network Service Connectivities for 315 Cities in 2000, GaWC Data Set 12, www.lboro.ac.uk/gawc/datasets/da12.html, accessed 10 March 2010 Whebell, C. F. J. (1969) ‘Corridors: a theory of urban systems’, Annals of the Association of American Geographers, vol 59, pp1–26

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Chapter 25

US Cities Asli Ceylan Oner

The contemporary US space economy is characterized by decentralization and dominance of service industries. During the 1950s and 1960s, due to technological advances, a newly developing highway system and increased airport travel, businesses in the US could ‘decentralize their manufacturing operations yet maintain central control’ (Agnew, 1987, p119). This decentralization took place in terms of business activities moving to more peripheral locations in the US as well as overseas. Thus, starting from the 1950s, in the US, cities outside the historic industrial core started to challenge the primacy of the manufacturing belt cities (Agnew, 1987). Deindustrialization in the late 1960s and the energy crisis in the 1970s led to economic decline in manufacturing belt cities, and traditional centres such as New York and Chicago were hit especially severely (Abu-Lughod, 1999). Many firms shifted their production facilities to cities of the Sunbelt states, located in the south and southwest of the United States, that offered more favourable business and living conditions, resulting in a significant economic and population growth in these cities (Rice and Bernard, 1983; Clark and Roche, 1984; Macionis and Parrillo, 2004). After the 1980s, globalization of economic activities completely transformed the economic basis of US cities into a service and high-tech economy, in which information technology and producer service functions became the key determinants (Earle, 2004). At the beginning of the 21st century, around 80 per cent of the US economy was based on services (Cleveland, 1999). Historical industrial centres such as New York, Chicago and Boston adapted to this economic change and became ‘postindustrial production sites’ (Sassen, 2001), which contributed to their economic recovery during the 1990s. Highly developed information, communication, and transport technologies have accelerated the decentralization process dramatically in the United States (Castells, 2000). Thus, since the 1950s, the decentralization of business activities is a persistent trend in the US space economy, which is now more multi-polar than other powerful national economies (Markusen and Gwiasda, 1994). This aspect of the US economy also creates a unique environment for world cities in the United States.

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Among US cities, New York has always been the leading economic centre and a city with global functions (Abu-Lughod, 1999). Currently, in terms of global connectivity, New York is at the same level as London, as well as being the most important global city in the United States (Taylor et al, 2002; Taylor and Aranya, 2008). Between 2000 and 2008, despite the fact that other important US world cities including Chicago, Los Angeles and San Francisco experienced a decline in their world city status, New York kept its place as one of the top two global cities in the world (Taylor and Aranya, 2008; Derudder et al, 2010). The decline in global connectivities of major US cities results from the less risky domestic market orientation of US firms, which serve the world’s largest national service market. Also, in terms of foreign firms, New York is the most prestigious US location, limiting the presence of global firms in other cities (Taylor and Lang, 2005). Table 25.1 illustrates the global network connectivities for the 59 US cities with proportionate connectivities above 0.05. The high number of cities qualifying shows the multi-polar structure of the US world city network. New York is the city with the highest proportionate connectivity in the United States, broadly the same as London’s. Below New York, Chicago and Los Angeles are located in second and third place with proportionate connectivities approximately half that of New York. These three cities are the most important world cities in the United States and they are located in three separate geographic regions (the east coast, the midwest, and the west coast) that have different histories and social and economic backgrounds (AbuLughod, 1999). The east and the west coasts of the United States are the gateway regions for Europe and Pacific Asia respectively, whereas the midwest is an important centre for agriculture and manufacturing. Washington, DC, the capital city, also has a high proportionate connectivity due to the presence of international organizations and its capital city functions; it is located as the fourth city after Los Angeles. Washington, DC is followed by Atlanta, the ‘New York of the South’ (Taylor and Lang, 2005, p11). The top ten US cities in terms of proportionate connectivity are also the ten largest US office markets (Lang, 2003), which demonstrates the unique spatial requirements of world city functions. Of the 59 cities, 31 are in the Sunbelt region whereas only 17 are located in the former manufacturing belt.

Table 25.1 Global network connectivity of US cities. RANK

CITY

1 2 3 4

New York Chicago Los Angeles Washington

GROSS CONNECTIVITY 95,838 55,324 44,637 42,831

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 1.00 0.57 0.46 0.44

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Table 25.1 Global network connectivity of US cities (continued). RANK

CITY

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44

Atlanta San Francisco Dallas Boston Miami Houston Denver Minneapolis Seattle Philadelphia Portland Detroit San Diego Columbus Phoenix Cleveland Tampa Kansas City Pittsburgh Orlando Charlotte Indianapolis Baltimore St Louis Sacramento Milwaukee San Jose Richmond Las Vegas Memphis Hartford Nashville Honolulu Omaha Raleigh Salt Lake City Austin Tulsa Rochester Birmingham

GROSS CONNECTIVITY 41,144 40,735 33,938 33,752 32,373 31,357 26,684 24,488 24,368 22,248 21,855 21,607 20,147 19,428 18,207 18,173 17,475 16,520 16,237 16,218 15,981 15,860 15,109 14,929 14,103 13,909 13,896 13,866 13,718 13,367 12,745 12,529 12,381 12,262 12,231 11,158 11,094 10,472 10,432 9925

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.43 0.42 0.35 0.35 0.34 0.33 0.28 0.25 0.25 0.23 0.23 0.22 0.21 0.20 0.19 0.19 0.18 0.17 0.17 0.17 0.17 0.16 0.16 0.16 0.15 0.14 0.14 0.14 0.14 0.14 0.13 0.13 0.13 0.13 0.13 0.12 0.12 0.11 0.11 0.10

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45 46 47 48 49 50 51 52 53 54 55 56 57 58 59

Cincinnati New Orleans Buffalo Providence Jacksonville San Antonio Des Moines Little Rock Albuquerque Palo Alto Norfolk Madison Charleston Anchorage Chattanooga

9776 9280 9067 8396 8298 7512 7275 6976 6241 5900 5786 5732 5259 4600 4405

259

0.10 0.10 0.09 0.09 0.09 0.08 0.08 0.07 0.06 0.06 0.06 0.06 0.05 0.05 0.05

Table 25.2 shows how city connectivities are constituted by local links within the country. The major outcome from the table is that the cities with the highest global network connectivity scores have lower rankings in terms of relative local connections. New York is the only city with a negative connectivity score, which suggests that the majority of New York’s connections are outside of the US. Other top ten cities with high global connectivity scores (Miami, Los Angeles, Chicago, San Francisco, Atlanta, Boston, Washington, Dallas, and Houston) also have low local connectivity scores, indicating that for these cities foreign links remain very important. Among the cities with relative low scores of local connectivity, Des Moines, Iowa and Little Rock, Arkansas stand out because they also have low global connectivity scores (ranked 51 and 52 consecutively in Table 25.1). These two cities have a small number of important global firms, which are more connected to foreign economies than to the local economy. Des Moines is an important insurance and finance centre in which large global firms, including Wells Fargo, ING Group, and the Principal Financial Group, have major operations. Little Rock is also an important centre for telecommunications and information technology.

Table 25.2 Localism (relative concentration of connections within the US). RANK

CITY

1 2 3 4 5

Palo Alto Chattanooga San Antonio Salt Lake City Anchorage

LOCALISM 15.27 14.40 13.49 13.48 13.44

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Table 25.2 Localism (relative concentration of connections within the US) (continued). RANK

CITY

6 7 8 9 10 11 12 13 14= 14= 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Albuquerque Charlotte Las Vegas Norfolk Jacksonville Madison Austin Charleston Cincinnati New Orleans Nashville Omaha Cleveland Rochester Buffalo Memphis Kansas City Orlando Tampa Providence Sacramento Phoenix Pittsburgh Seattle Richmond St Louis San Diego Columbus Philadelphia Milwaukee Indianapolis Raleigh Honolulu Baltimore Hartford Tulsa Little Rock Denver Birmingham Houston Portland Minneapolis

LOCALISM 13.15 11.31 11.17 11.02 10.81 10.78 10.68 10.67 10.25 10.25 9.32 9.29 9.28 9.09 8.96 8.69 8.60 8.18 8.05 7.99 7.89 7.68 7.64 7.63 7.58 7.49 7.44 7.26 7.12 7.09 7.05 7.02 6.80 6.71 6.44 6.43 6.40 6.27 6.17 6.09 6.07 5.93

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48 49 50 51 52 53 54 55 56 57 58 59

San Jose Dallas Des Moines Washington Atlanta Boston San Francisco Detroit Los Angeles Miami Chicago New York

261

5.70 5.63 5.36 4.28 4.15 3.81 3.78 3.55 2.78 2.71 2.52 −0.13

Table 25.3 shows the relative concentrations of connections to New York and London (NYLON) since those two cities are well-established as the global city centres of the world. Only 12 of the 59 cities have positive scores. Among these 12 cities, the top ten rankings suggest that cities with high global network connectivity also have high connectivity to NYLON. Cities with lower global network connectivity have lower rankings. The interesting outcome in this table is Palo Alto in California. This has the highest local connectivity (Table 25.2) as well as being the top city in terms of connectivity to NYLON (Table 25.3). On the other hand, Palo Alto has very low global connectivity; it was ranked as 54 in Table 25.1. Palo Alto has headquarters of some of the important Silicon Valley IT firms (e.g. Hewlett Packard and Facebook). The findings suggest that only few of these firms are global, but those that are global are strongly connected to NYLON. Through these firms, Palo Alto has direct connections to the top two global cities of New York and London besides having its strong connections to the domestic economy.

Table 25.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7 8 9 10

Palo Alto Washington Boston Chicago San Francisco Los Angeles Dallas Houston Miami Atlanta

TRADITIONAL GLOBALISM 1.84 0.90 0.80 0.76 0.72 0.70 0.50 0.37 0.33 0.30

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Table 25.3 Traditional globalism through NYLON (relative concentration of connections to New York and London) (continued). RANK

CITY

11 12 13 14 15 16 17 18= 18= 18= 21 22 23 24 25= 25= 27= 27= 29 30 31= 31= 31= 34 35 36= 36= 36= 39 40= 40= 42 43 44 45 46 47 48 49 50 51

Philadelphia Seattle San Diego Minneapolis Baltimore Denver Albuquerque Portland Austin Kansas City Detroit Tampa Hartford Columbus Pittsburgh Cleveland Phoenix St Louis Las Vegas Orlando Charleston Anchorage Charlotte San Jose New Orleans Indianapolis Cincinnati Providence Salt Lake City Milwaukee Sacramento Norfolk Madison Honolulu Little Rock Richmond Des Moines Memphis Nashville Raleigh Omaha

TRADITIONAL GLOBALISM 0.25 0.23 −0.01 −0.02 −0.03 −0.04 −0.05 −0.10 −0.10 −0.10 −0.11 −0.14 −0.16 −0.18 −0.19 −0.19 −0.28 −0.28 −0.29 −0.30 −0.31 −0.31 −0.31 −0.32 −0.33 −0.34 −0.34 −0.34 −0.37 −0.38 −0.38 −0.39 −0.41 −0.44 −0.45 −0.46 −0.48 −0.50 −0.55 −0.57 −0.60

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52 53 54 55 56 57 58 –

Chattanooga San Antonio Jacksonville Tulsa Rochester Birmingham Buffalo New York

263

−0.64 −0.65 −0.66 −0.68 −0.69 −0.70 −0.87 –

Table 25.4 shows city connections to an emerging arena of globalization represented by the Chinese cities of Beijing, Shanghai, and Hong Kong. Generally, cities with lower global connectivity levels also have negative connectivity scores to these Chinese cities. There are again just 12 cities with positive scores, among which Palo Alto and New York have the largest connections; the other top ten cities in terms of global connectivity are also strongly connected to the Chinese cities. As mentioned previously, the US world city network is more multi-polar than any other national context. The top ten globally connected cities are major players in the global arena rather than having connections only to certain regions. There are three other cities with relatively good connectivity to Chinese cities that are important to mention here: Hartford, Anchorage and Des Moines. They all have negative connectivity scores to NYLON, indicating that the global links established in these three cities are oriented towards the globalization arena in Pacific Asia rather than the Atlantic coast. In terms of connectivity to Beijing, Shanghai and Hong Kong, Palo Alto still provides a surprising result since it is located above New York as the most connected city. Palo Alto’s IT-based economy has strong ties with major globalization arenas, both traditional and emerging, which suggests that Palo Alto might improve its position in terms of the global hierarchy of world cities.

Table 25.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8 9

Palo Alto New York Los Angeles Chicago Boston San Francisco Washington Atlanta Dallas

NEW GLOBALISM 0.93 0.87 0.55 0.50 0.42 0.39 0.36 0.23 0.17

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Table 25.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai) (continued). RANK

CITY

10 11 12 13 14 15 16 17= 17= 17= 20 21 22 23 24 25= 25= 27= 27= 29= 29= 31 32= 32= 34= 34= 36= 36= 38 39 40 41= 41= 41= 44= 44= 46= 46= 48= 48= 50

Miami Seattle Hartford Philadelphia Houston Anchorage Des Moines Minneapolis Albuquerque Denver Detroit Kansas City Providence Columbus Cleveland Charlotte Norfolk Cincinnati Milwaukee San Diego Omaha St Louis Portland Salt Lake City Pittsburgh Tampa Madison Baltimore Phoenix Orlando Honolulu Nashville Indianapolis Charleston New Orleans San Jose Memphis San Antonio Las Vegas Austin Chattanooga

NEW GLOBALISM 0.10 0.04 0.00 −0.01 −0.02 −0.05 −0.07 −0.10 −0.10 −0.10 −0.12 −0.19 −0.25 −0.27 −0.30 −0.31 −0.31 −0.32 −0.32 −0.37 −0.37 −0.40 −0.43 −0.43 −0.45 −0.45 −0.50 −0.50 −0.51 −0.57 −0.58 −0.59 −0.59 −0.59 −0.62 −0.62 −0.65 −0.65 −0.69 −0.69 −0.70

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51 52 53 54 55 56 57= 57= 59

Sacramento Richmond Buffalo Little Rock Rochester Birmingham Raleigh Tulsa Jacksonville

265

−0.76 −0.78 −0.82 −0.83 −0.86 −0.88 −0.91 −0.91 −1.05

In conclusion, the results of the analysis confirm that New York is the leading world city in the United States, with a connectivity level much higher than other important cities including Chicago, Los Angeles, Washington, DC, and Atlanta. Cities with high global connectivity are more ‘un-local’, their foreign links dominating the domestic ones. Besides these highly connected cities, there are also specialized centres including Palo Alto and Des Moines that do not have high global connectivity at this point, but which are strong prospects for becoming more important global hubs in the near future. The large number of cities included in the analysis demonstrates that the multi-nodality aspect of the US world city network is a key characteristic.

References Abu-Lughod, J. L. (1999) New York, Chicago, Los Angeles: America’s Global Cities, University of Minnesota Press, Minneapolis, MN Agnew, J. (1987) The United States in the World Economy: A Regional Geography, Cambridge University Press, Cambridge Castells, M. (2000) The Rise of the Network Society, Blackwell, Oxford Clark, R. D. and Roche, J. B. (1984) ‘Functional typologies of metropolitan areas: an examination of their usefulness’, Urban Studies, vol 21, pp63–71 Cleveland, D. B. (1999) The Role of Services in the Modern U.S. Economy, U.S. Department of Commerce, International Trade Administration, Office of Service Industries, http://trade.gov/td/sif/PDF/ROLSERV199.PDF, accessed 10 March 2010 Derudder, B., Taylor, P. J., Ni, P., De Vos, A., Hoyler, M., Hanssens, H., Bassens, D., Huang, J., Witlox, F., Shen, W. and Yang, X. (2010) ‘Pathways of change: shifting connectivities in the world city network, 2000–08’, Urban Studies, vol 47, pp1861–1877 Earle, C. (2004) The American Way: A Geographical History of Crisis and Recovery, Rowman & Littlefield, Lanham, MD Lang, R. E. (2003) Edgeless Cities: Exploring the Elusive Metropolis, Brookings Institution Press, Washington, DC Macionis, J. and Parrillo, V. (2004) Cities and Urban Life, Prentice-Hall, Upper Saddle River, NJ Markusen, A. and Gwiasda, V. (1994) ‘Multipolarity and the layering of functions in world cities: New York City’s struggle to stay on top’, International Journal of

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Urban and Regional Research, vol 18, pp167–193 Rice, B. R. and Bernard, R. M. (1983) ‘Introduction’, in R. M. Bernard and B. R. Rice (eds) Sunbelt Cities: Politics and Growth Since World War II, University of Texas Press, Austin, TX, pp1–30 Sassen, S. (2001) The Global City: New York, London, Tokyo, 2nd edition, Princeton University Press, Princeton, NJ Taylor, P. J. and Aranya, R. (2008) ‘A global “urban roller coaster”? Connectivity changes in the world city network, 2000–04’, Regional Studies, vol 42, pp1–16 Taylor, P. J., Catalano, G. and Walker, D. R. F. (2002) ‘Measurement of the world city network’, Urban Studies, vol 39, pp2367–2376 Taylor P. J. and Lang, R. E. (2005) US Cities in the ‘World City Network’, The Brookings Institution, Washington, DC (Survey Series, Metropolitan Policy Program)

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26

Mexican Cities Margarita Pérez Negrete

Within the Mexican urban system, Mexico City has historically been the national economic, political and cultural core. It houses most of the federal governmental institutions as well as the main agents symbolizing progress and modernity. Since the 1930s and 1940s Mexico City’s urban primacy has led it to be both a national development site as well as a pole of attraction for rural/urban migration. During this time national economic activity was strongly guided and supported by an import substitution industrialization policy, which was reflected in the dynamism of the primate city. Nevertheless, since the beginning of the 1980s, even though Mexico City continued its urban dominance at a national scale, important transformations in the political economic model have modified its internal dynamic as well as produced important urban reconfigurations at the national level. The transition from an economy oriented towards internal industrialization, to one highly intensive in services, had important effects on Mexico City’s performance as the epicentre of the national economy. As a result of these changes, a new spatial order within the Mexican urban system was created, in which Mexico City’s new specialization was fundamental to understanding the functions carried out by other cities in the national context (Pérez Negrete, 2007). While these changes were occurring, Mexico City was listed, for the first time, as a beta city integrated into the world city network (Beaverstock et al, 1999). In 2002 it was ranked in the top 20 for global network connectivity (Taylor and Catalano, 2002). This measurement places Mexico’s capital as a hinge between the Mexican and the global urban system, as well as a strategic site in which globalization processes occur. Nevertheless in 2004, when Mexico City was ranked as an alpha city (GaWC, 2009) and defined as a worldwide leading city (Taylor, 2005), other major Mexican cities were also reported as being integrated into the world city network: Guadalajara, Monterrey, Puebla and Tijuana (GaWC, 2009). The 2008 measures of global network connectivity in this chapter illustrate the performance of nine Mexican cities within the world city network. Before analysing them it is necessary to mention that since the last century, a high percentage of the national population is concentrated in

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Mexico’s main cities: at the beginning of the 2000s, Mexico City, Guadalajara, Monterrey, Puebla, Tijuana and León metropolitan areas together accounted for 47.2 per cent of the national urban population (Garza, 2001). One final point should be emphasized: since 1985 the Mexican urban system has undergone an important reconfiguration. During the period 1980–1990 Mexico City played a key role in the national economy and alone accounted for 31.4 per cent of the national population (Pérez Negrete, 2000). A series of events stemmed this growth: the Mexico City earthquake of 1985, industrial relocalization towards other urban areas and the increase of violence and insecurity. The result was that the capital city underwent a demographic decrease, which had important effects on middle-ranked cities in Mexico. Table 26.1 indicates how well a city is integrated into the world city network. This evidence shows that although Mexico City retains its traditional primacy, other key domestic actors play an important role in Mexico’s articulation into the global economy. Guadalajara and Monterrey are important in contemporary globalization; each has at least one-sixth and one-quarter, respectively, of the highest connectivity. It is hardly surprising that historically they have been, along with Puebla, the second most important cities due to their earlier industrialization and resulting population growth. Although the growth of these metropolitan areas has been slowing down since 2000, intensive migration flows from the rest of the country still continue. Therefore, it can be predicted that they will remain important economic centres for the foreseeable future.

Table 26.1 Global network connectivity of Mexican cities. RANK

CITY

1 2 3 4 5 6 7 8 9

Mexico City Guadalajara Monterrey Puebla Tijuana Chihuahua Querétaro Ciudad Juárez León

GROSS CONNECTIVITY 52,903 22,608 17,685 11,014 10,556 9208 9068 7630 7120

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.55 0.23 0.18 0.11 0.11 0.10 0.09 0.08 0.07

In Guadalajara metropolitan area, one dynamic sector during the period 1995–2000 was the fast growing electronics/telecommunications sector, accounting for 56.03 per cent of total private investment (González Rodríguez, 2008). Monterrey, recognized as the national entrepreneurial capital, as the

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most important national industrial city and as the venue of several corporate domestic headquarters, has in addition an important geostrategic position due to its location near the US border. The local government is working on the master plan ‘Monterrey: international city of knowledge’ that aims to promote Monterrey’s international status as a competitive city at the global level. On the other hand, the dynamism acquired by northern cities such as Tijuana, Chihuahua and Ciudad Juárez is due, particularly in the case of Tijuana and Ciudad Juárez, to the new trend of industrial relocalization from the centre to the north of the country. These border cities have registered great dynamism because of their maquila industry (assembly plants) oriented towards exports to the US. However, as this sector is growing, so too is organized crime: female homicides, drug trafficking and general violence means that insecurity is a key issue in these metropolitan areas, which will limit their economic development. Table 26.2 indicates how relatively local the city network links are. The rankings are quite the opposite of Table 26.1. As can be seen from the figures, Mexico City is the only city that appears with a negative score. This means that it is the least local city, with most of its connections concentrated beyond the national scope. Surprisingly, Chihuahua, Ciudad Juárez and Tijuana are ranked in the first three positions, which indicates their localism relative to external service links. This could be related to the nature of the maquila industry that creates low-paid jobs for Mexicans, but whose function is to export the finished products out of Mexico immediately.

Table 26.2 Localism (relative concentration of connections within Mexico). RANK

CITY

1 2 3 4 5 6 7 8 9

Chihuahua Ciudad Juárez Tijuana Querétaro Puebla León Guadalajara Monterrey Mexico City

LOCALISM 0.95 0.90 0.82 0.74 0.68 0.63 0.42 0.14 −0.98

Table 26.3 shows Mexican cities’ globalism as indicated by specific links to the key network dyad, London and New York (NYLON). Mexico City is the only city with a positive score that indicates its high connectivity to the ‘main street dyad’. Negative scores indicate a relative lack of connections of other cities to these nodes.

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Table 26.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7= 7= 9

Mexico City Monterrey Ciudad Juárez Guadalajara León Querétaro Chihuahua Tijuana Puebla

TRADITIONAL GLOBALISM 0.25 −0.06 −0.55 −0.58 −0.71 −0.76 −0.77 −0.77 −0.92

Table 26.4 illustrates new global links to Beijing, Shanghai and Hong Kong. This table is closely related to Table 26.3 showing the same cities ranked in the four first positions. In both tables, Mexico City confirms its traditional primacy, followed by Monterrey. In the same way, both tables show similarities with Table 26.1 in the ranking of cities. Nevertheless, Ciudad Juárez is ranked third in Table 26.4 while in Table 26.1 it is ranked eighth and in Table 26.2 it is the second most local city of the group. These results tell us something more about the nature of the particular links created by the maquila industry that articulate the city in a different way from traditional global cities processes. Moreover, León, Puebla and Querétaro ranked last in Table 26.4 are paradoxically traditional urban regional nodes.

Table 26.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8 9

Mexico City Monterrey Ciudad Juárez Guadalajara Chihuahua Tijuana León Puebla Querétaro

NEW GLOBALISM 0.41 0.00 −0.61 −0.79 −0.96 −1.00 −1.01 −1.03 −1.05

In conclusion, each table presented here confirms the fact that Mexico City is still the primate city within the Mexican urban system through playing its role in articulating the country to the world city network. But the world city

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analysis illustrates that, as time goes by, other important players are weaving their links with the global system. In their effort to be competitive, cities are developing different urbanizing strategies that in most cases, however, are reproducing negative consequences of disorganized urban policy. These include unemployment and informal jobs, unmanageable demographic growth, proliferation of housing and public spaces controlled by the private sector, and speculative and hierarchical land use. Once again Mexican urban planners, in their efforts to place cities in global competition, are employing strategies that, far from resolving patterns of historical social inequality, are reproducing persistent urban contrasts and poverty.

References Beaverstock, J. V., Smith, R. G. and Taylor, P. J. (1999) ‘A roster of world cities’, Cities, vol 16, pp445–458 Garza, G. (2001) ‘Monterrey en el contexto de la globalización económica de México’, ponencia presentada en el seminario Financiamiento para el Desarrollo Urbano Regional en México, UNAM y el Colegio Mexiquense, pp. 27–29 marzo, México www.iiec.unam.mx/actividades/seminarios/extras/SEUR-2001/13gustavo%20garza.pdf, accessed 10 March 2010 GaWC (2009) The World According to GaWC, www.lboro.ac.uk/gawc/gawcworlds.html, accessed 10 March 2010 González Rodríguez, S. M. (2008) ‘La industria electronica de la zona conurbada de Guadalajara: surgimiento, auge y declive, 1960–2004’, Tempo Revista Cultura, Tecnologia Y Patrimonio, www.thefreelibrary.com/Laindustriaelectronica delazonaconurbadadeGuadalajara%3a...-a0201371085, accessed 10 March 2010 Pérez Negrete, M. (2000) ‘Las Ciudades Latinoamericanas y el Proceso de Globalización’, Memoria 134, pp41–44 Pérez Negrete, M. (2007) La ciudad de México en la red mundial: articulación al sistema y procesos de diferenciación socio-espacial, Universidad Iberoamericana, México, D.F. Taylor, P. J. (2005) ‘Leading world cities: empirical evaluations of urban nodes in multiple networks’, Urban Studies, vol 42, pp1593−608 Taylor, P. J. and Catalano, G. (2002) ‘World city network formation in a space of flows’, in A. Mayr, M. Meurer and J. Vogt (eds) Stadt und Region: Dynamik von Lebenswelten, Deutsche Gesellschaft für Geographie, Leipzig, pp68−76

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27

Brazilian Cities Eliana C. Rossi

Throughout the 20th century, first industrialization and later services led to the urbanization of Brazil and its economy (Santos, 1993). Spatially, in the 1980s the dominant economic centre shifted from Rio de Janeiro to São Paulo and in the 1990s, particularly in the southern half of the country, decentralization policies started a process of specialization and growth of the economic importance of medium-sized cities (Santos, 1993; IPEA et al, 2001). The economic liberalization adopted by Brazil in the 1990s reduced the number of domestic banks, both public and private, and increased the number of foreign banks and their involvement in the provision of credit. In 2007, 20 banks controlled 85 per cent of the credit, allocated in equal proportions to the country’s south and southeast. There was a reduction in the total number of bank branches and simultaneous concentration of branches in the south and southeast (Pochmann, 2009). The results of the extreme concentration can be seen in the presence of 16 per cent of the country’s total bank branches in São Paulo city-region and the absence of bank branches (not counting ATMs) in 41 per cent of Brazilian cities and towns (Banco Central, 2009a). In addition, the merger of Brazilian Stock Exchanges, which started in 2000, culminated in the integration of the São Paulo Stock Exchange (BOVESPA) and the Brazilian Mercantile & Futures Exchange (BM&F) in May 2008. This resulted in Brazil having only one exchange, the second largest exchange of the Americas – the Securities, Commodities and Futures Exchange, based in São Paulo (BM&FBOVESPA, 2009). This integration has consolidated the economic leadership of São Paulo, both at home and in Latin America, and is confirmed by the city housing the headquarters of 70 of the 77 foreign banks operating in Brazil (Banco Central, 2009b). Therefore, as early as the 1980s, the city of São Paulo became attractive to the new global economic order orchestrated by advanced producer services (APS) (Kowarick and Campanario, 1986; Friedmann, 1986; Sassen, 1991). In fact, in the first study that measured the global connectivity of world cities (Taylor, 2004), São Paulo appears in 16th, and Rio de Janeiro in 69th position. Seven other major Brazilian cities are also part of the ranking (Porto Alegre,

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Belo Horizonte, Curitiba, Salvador, Brasília, Recife and Manaus), but they appear lower down the list. Thus, it is unlikely that an indicator of increased global connectivity of the city of São Paulo in more recent studies will increase its ranking in comparison to other Brazilian or continental cities. This is particularly important to understand in interpreting the data presented below, which were collected just before the start of the 2008 economic crisis. However, we can assume that the differential impact of the crisis on mature and emerging markets will have affected the global connectivity of São Paulo. This assumption is reinforced by the fact that among the 500 largest companies based in Brazil, foreign companies account for 40 per cent of the total, and most are among the top 50 (Abril, 2009), indicating that the country’s economic performance during the crisis had implications in each company’s network. Conversely, as of September 2009, the decline of important markets has impacted the export sector in which major Brazilian companies operate, a fact that has probably increased the need for credit and other services provided by APSs. Considering that the producers of goods and services are major customers of the APS firms based in Brazil, Rossi and Taylor (2005) observed that the concentration of advanced business services in only a few Brazilian cities produces a low correlation between the city markets of the 500 largest companies based in Brazil and the global connectivity of cities/city-regions. Thus, while in 2008 most of the headquarters of new entrants among the 500 largest companies based in Brazil were located in the northeast and centrewest, and some cities in the south and east are no longer the seat of companies listed among the 500 larger ones (Abril, 2003; 2009), it is expected that the global connectivity of cities in these regions has remained stable. The APS firms studied – accountancy, finance, advertising, management consultancy and law impact (in this order) on the proportionate connectivity of Brazilian cities and are either more distributed or more concentrated in the cities sampled. Accountancy is the APS that has the highest penetration and is based in every city investigated here. São Paulo and Rio de Janeiro host the other services, together with Curitiba, Belo Horizonte, Porto Alegre, Recife and Brasília, which also host financial services; Porto Alegre and Brasília also host advertising, while Salvador also hosts consultancy management and Porto Alegre also hosts law. Table 27.1 shows global network connectivities for ten Brazilian cities with proportionate connectivities above 0.05. The result was expected, as it puts São Paulo at the top and Rio de Janeiro in second place, at just over half the proportionate connectivity of São Paulo. It also shows the rise of Curitiba to fourth position, which was expected since the city housed the national headquarters of HSBC. Belo Horizonte’s fifth position shows that the city has yet to attract APSs in proportion to the size of its market, and its position tends to fall in relation to Recife. The biggest surprises are Recife, which has overtaken Brasília and Salvador and threatens Belo Horizonte, confirming that the market size is not an indicator of the global connectivity of Brazilian cities; and Fortaleza and Campinas, new entrants that are on an

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equal footing with Brasília. Fortaleza joins Recife and Salvador to service the northeast, in a geographic configuration currently more comprehensive and balanced. Campinas, which tends to assume a supportive role to São Paulo, is likely to host the latter’s surplus APS firms. Brasília is an administrative capital. Just as Washington lags behind New York in global connectivity, Brasília also lags behind other Brazilian cities and has the lowest connectivity in the table. The northern region has no cities on the map of global connectivity. The central-west participates through Brasília, which almost borders on the southeast. Geographically, in 2008 the Brazilian cities with global connectivity were in the eastern portion of the country, mostly along the coast, in the south, southeast and northeast regions, except for the Federal District, and were led by São Paulo.

Table 27.1 Global network connectivity of Brazilian cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10

São Paulo Rio de Janeiro Porto Alegre Curitiba Belo Horizonte Recife Salvador Fortaleza Campinas Brasília

GROSS CONNECTIVITY 53,319 29,657 12,706 11,812 8706 8284 7028 5812 5526 5326

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.55 0.31 0.13 0.12 0.09 0.09 0.07 0.06 0.06 0.06

Table 27.2 shows the measurements of ‘localism’ of Brazilian cities and virtually reverses what was presented in the previous table. The negative score for São Paulo and low score of Rio de Janeiro indicate that most of the connections of these two cities are transnational. However, São Paulo is much more ‘un-local’ than Rio de Janeiro. On the other hand, Brasília is by far the most ‘local’ of the Brazilian cities that have global connectivity, in other words it establishes relatively more connections within the country than outside. The positive score of Brasília indicates that this city is much more ‘local’ than São Paulo is ‘un-local’. It can also be observed that Curitiba is closer to becoming ‘un-local’ than Porto Alegre.

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Table 27.2 Localism (relative concentration of connections within Brazil). RANK

CITY

1 2 3 4 5 6 7 8 9 10

Brasília Campinas Fortaleza Salvador Recife Belo Horizonte Porto Alegre Curitiba Rio de Janeiro São Paulo

LOCALISM 4.38 2.73 2.63 2.53 2.17 1.92 1.48 1.29 0.34 −0.57

Table 27.3 shows the connectivities of Brazilian cities regarding London and New York (NYLON) as the prime dyad in the world city network. As expected, São Paulo is at the top, but it is the only Brazilian city that is positively connected to NYLON, since Rio de Janeiro scores negatively on this measure like all the remaining cities. In an interesting twist, Brasília, the most local city, is still the third most connected city to NYLON, ranking above Porto Alegre and Curitiba. This indicates that the capital city’s relatively meagre global links (Table 27.1) are highly concentrated towards these key global cities.

Table 27.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7 8 9 10

São Paulo Rio de Janeiro Brasília Porto Alegre Curitiba Recife Salvador Belo Horizonte Fortaleza Campinas

TRADITIONAL GLOBALISM 0.44 −0.32 −0.58 −0.60 −0.74 −0.78 −0.83 −0.87 −0.92 −1.08

Table 27.4 shows the relative connectivities of Brazilian cities to Beijing, Hong Kong and Shanghai as an emerging new core city triad in globalization. Again, as expected, São Paulo is on top, confirming a high global connectivity in

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relation to the leading Chinese cities, with Rio de Janeiro again second with a low negative score. The Brasília position relative to Porto Alegre and Curitiba in Table 27.3 is repeated: it seems Brasília’s global links are firmly concentrated on the very top global cities.

Table 27.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8 9 10

São Paulo Rio de Janeiro Brasília Porto Alegre Curitiba Fortaleza Recife Salvador Belo Horizonte Campinas

NEW GLOBALISM 0.66 −0.22 −0.58 −0.68 −0.70 −0.91 −0.93 −0.96 −1.07 −1.24

In conclusion, the 2008 world city analysis partially contradicts the recent literature on the globalization of Brazilian cities, as it shows that cities in northeastern Brazil are taking part in the process. On the other hand, it confirms other results and trends and provides details on the period immediately preceding the 2008 economic crisis, thus contributing to the further understanding of Brazilian cities in globalization.

References Abril (2003) EXAME Melhores e Maiores, Abril, São Paulo Abril (2009) EXAME Melhores e Maiores, Abril, São Paulo Banco Central (2009a) Agências de Instituições Bancárias sob a supervisão do BACEN, em funcionamento no país: Posição em 03.08.2009, www.bcb.gov.br/?RELAGPAB, accessed 15 August 2009 Banco Central (2009b) Relacão dos Representantes de Instituições Estrangeiras no Brasil, www.bcb.gov.br/FIS/Repif/Rel_Representantes.pdf, accessed 28 July 2009 BM&FBOVESPA (2009) Home/About BM&FBOVESPA, www.bmfbovespa.com.br/english/QuemSomos.asp, accessed 28 July 2009 Friedmann, J. (1986) ‘The world city hypothesis’, Development and Change, vol 17, pp69–83 IPEA, IBGE and UNICAMP (2001) Caracterização e tendências da rede urbana do Brasil, IPEA, Brasília Kowarick, L. and Campanario, M. (1986) ‘São Paulo: the price of world city status’, Development and Change, vol 17, pp159–174

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Pochmann, M. (2009) ‘Trajetória recente dos bancos no Brasil’, Forum, vol 74, www.revistaforum.com.br/sitefinal/EdicaoNoticiaIntegra.asp?id_artigo=6985, accessed 28 July 2009 Rossi, E. C. and Taylor, P. J. (2005) ‘Banking networks across Brazilian cities: interlocking cities within and beyond Brazil’, Cities, vol 22, pp381–393 Santos, M. (1993) A Urbanizacao Brasileira, Hucitec, São Paulo Sassen, S. (1991) The Global City: New York, London, Tokyo, Princeton University Press, Princeton, NJ Taylor, P. J. (2004) World City Network: A Global Urban Analysis, Routledge, London

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28

South East Asian Cities Pengfei Ni, Guangyao Xu and Jin Huang

Unquestionably, there are many cities in South East Asia famous for their urban landscape and culture. Historically, external connections of South East Asian cities were mainly with China. European colonialism changed the orientation westward, and before World War II, most countries of South East Asia were colonies with low economic levels of development. After the war, South East Asian countries became independent, and their economies started to recover, but cities in the region remained mostly poor and undeveloped, with relatively little contact with the outside world. During the 1950s and 1960s, because South East Asian countries are generally small and lack resources, import substitution strategies were implemented widely. The cities of South East Asia then began to open up and connect with the world economy (McGee, 1967), following Japan in a ‘wild-geese-flying pattern’ (Akamatsu, 1962). During the 1970s and 1980s, textiles, electronics and other labourintensive industries transferred to this developing region because of the rapid rise of the Japanese economy. In addition, export strategies were implemented that further increased the degree of connectivity of South East Asian cities with the world economy. Singapore was gradually to become a global financial centre (Lo and Marcotullio, 2000). After the 1990s, and notably after getting through the financial crisis of 1997, the cities of South East Asia have experienced an economic boom stimulating development of the region (Bishop et al, 2003; Tyner, 2008). Undoubtedly, the cities of South East Asia will become even more closely connected to the world economy in the future. Table 28.1 shows all the South East Asian cities with proportionate connectivity above 0.05: these measures show how well the different cities are integrated into the world city network. More than half of the listed cities are capitals of South East Asian countries. The result is no surprise: Singapore is ranked first with the highest connectivity value (0.75) of any city within South East Asia. As one of Asia’s famous ‘four little dragons’, Singapore is a very open economy with one of the lowest tax rates in the world (Lam, 2000). Besides that, it has good infrastructure and an excellent education system to generate a large number of professionals, so numerous corporations from

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around the world invest in Singapore. It is the first choice location for Asian headquarters of US, European and Japanese companies; more than one-third of the ‘Fortune 500’ companies have chosen to set up their Asian headquarters in Singapore. In Table 28.1 Singapore is followed by Kuala Lumpur, with Jakarta and Bangkok closely behind; all three cities have scores over 0.5; next comes Manila, with a relatively high 0.42. These four cities are not only capitals and the largest cities, but they are also the political and economic centres of Malaysia, Indonesia, Thailand and the Philippines respectively. These countries have been known as Asia’s ‘four tigers’ since the 1980s and their economic power is reflected in these four cities becoming open and prosperous, therefore their global network connectivity is relatively high. Ho Chi Minh City and Hanoi compose the third stratum in Table 28.1: Ho Chi Minh City is the largest city and economic centre of Vietnam located near the Mekong Delta; Hanoi is the capital and political centre. As Vietnam’s economy took off in the 1990s, following the ‘four tigers’, the global network connectivities of these cities are lower than those of the capitals of the ‘four tigers’. Penang, Labuan, Johor Baharu, Cebu, Surabaya, Phnom Penh and Bandar Seri Begawan compose the fourth stratum, with scores between 0.15 and 0.05. Among them, Penang, Labuan and Johor Baharu are Malaysian cities. Penang is the second largest city and the only free-trade port in Malaysia. Labuan is best known as an offshore financial centre, but its global network connectivity has decreased in the past eight years. Johor Baharu is very near to Singapore, on the only route to Malaysia. Their global network connectivity is relatively higher than some other cities but lower than Kuala Lumpur. Cebu City, called ‘Queen City of the South’, is the oldest and second largest Philippine city, and an important port. Surabaya is Indonesia’s second largest city, and the capital of the province of East Java. All the global network connectivities of capital cities are high, except for Phnom Penh and Bandar Seri Begawan, because the economies of Cambodia and the Sultanate of Brunei are relatively small in South East Asia. Despite this, the two cities are the most populous and capital cities of their respective countries. In summary, the scores of South East Asian cities are positively related to their countries’ economic conditions.

Table 28.1 Global network connectivity of South East Asian cities. RANK

CITY

1 2 3 4 5 6

Singapore Kuala Lumpur Jakarta Bangkok Manila Ho Chi Minh City

GROSS CONNECTIVITY 72,594 57,523 52,645 51,974 40,282 28,887

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.75 0.60 0.55 0.54 0.42 0.30

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Hanoi Penang Labuan Johor Baharu Cebu Surabaya Phnom Penh Bandar Seri Begawan

17,256 11,196 10,094 9744 9032 7626 5848 4645

0.18 0.12 0.10 0.10 0.09 0.08 0.06 0.05

Table 28.2 shows measures of ‘localism’, the degree to which a city’s connectivity is dominated by links within the region. Just as many other country results tell us, rankings by ‘localism’ are generally the reverse of the global network connectivity rankings of cities. Thus some famous cities, usually considered as ‘global cities’, will not get high scores for the ‘localism’ indicator. Table 28.2 tells the same story for South East Asian cities. The table largely reverses the rankings in Table 28.1 but the key point is the bottom ranking of Singapore: with the largest negative score, Singapore is shown to be very ‘un-local’; the vast majority of its connections are beyond South East Asia. This is likely to be related to the city being highly ranked as an international financial centre (see Chapter 3). Cebu is also very ‘un-local’; not only is it the oldest Philippine city but it is also one of the most developed provincial capitals in the Philippines, as a major centre of commerce, trade, education and industry. In addition, Kuala Lumpur, Bandar Seri Begawan, Bangkok, Penang and Jakarta score near zero and thus are to some extent ‘un-local’. The remaining cities have relatively large positive scores indicating the importance of domestic links relative to foreign connections. In this study, Labuan is found to be the most ’local’ city. As a Malaysian offshore financial centre and territory, Labuan’s offshore companies can enjoy lower tax rates in Malaysia and there are tariff agreements with neighbouring countries. Labuan has therefore become the base for foreign investment from Indonesia and other neighbouring countries. Since New York and London (NYLON) are treated as the ‘main street dyad’ of contemporary globalization in our research, we use an index of relative concentration of connections to NYLON to be a measurement of ‘traditional globalization’. Table 28.3 measures the ‘traditional globalization’ of South East Asian cities by showing their relative connectivity to London and New York. The ranking here is strongly related to the global network connectivity (Table 28.1). Four of the five top ranked cities in Table 28.3, all scoring positively for a relatively strong orientation to NYLON, are also particularly predictable as they are first and second strata cities in Table 28.1. Labuan is a big surprise, its recent rise as a financial centre being associated with the importance of NYLON connections. It not only has relatively large connectivity with NYLON but is also the most ‘local’ city in South East Asia (Table 28.2). Again, this is related to the lower tax rates of Malaysia and tariff agreements with neighbouring countries. It is not only the investment base for

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Indonesia and other neighbouring countries, but also for European crossborder investment in Asia. This is an example of a very ‘local city’ that has specific concentration of its non-local links to major cities. Most of the other scores are negative, showing a lack of relative orientation towards NYLON, which is predictable to some degree since South East Asian cities are tending to be ‘local’ as we have seen in Table 28.2.

Table 28.2 Localism (relative concentration of connections within South East Asia). RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Labuan Hanoi Surabaya Phnom Penh Ho Chi Minh City Johor Baharu Manila Jakarta Penang Bangkok Bandar Seri Begawan Kuala Lumpur Cebu Singapore

LOCALISM 1.57 1.21 0.99 0.61 0.46 0.32 0.30 0.16 0.12 0.07 0.01 −0.04 −0.35 −0.52

Table 28.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Singapore Bangkok Labuan Jakarta Kuala Lumpur Hanoi Manila Ho Chi Minh City Phnom Penh Surabaya Johor Baharu Penang Bandar Seri Begawan Cebu

TRADITIONAL GLOBALISM 0.81 0.51 0.33 0.22 0.18 0.07 0.06 −0.06 −0.17 −0.47 −0.60 −0.61 −0.72 −0.84

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Table 28.4 shows city connections to what may be an emerging new globalization based upon Beijing, Shanghai and Hong Kong. Singapore, as expected, has the largest connection to this Chinese triad centre. The cities ranked third to sixth are also predictable; these are the capital cities of different countries in South East Asia. Labuan is ranked second for reasons discussed previously for NYLON connectivities: the city as a base for foreign investment, including China. In addition, there are six cities with negative scores; these other South East Asian cities have relatively weak links to the leading Chinese cities, even including some capital cities. However, compared with Table 28.3, most of the scores are relatively higher, indicating that South East Asian cities have higher connectivities with the Chinese cities triad than with NYLON. Hence, this new globalization measure may reflect locational and cultural relationships.

Table 28.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12= 12= 14

Singapore Labuan Bangkok Jakarta Kuala Lumpur Hanoi Manila Ho Chi Minh City Phnom Penh Bandar Seri Begawan Johor Baharu Penang Surabaya Cebu

NEW GLOBALISM 1.02 0.82 0.66 0.46 0.44 0.36 0.31 0.15 −0.19 −0.60 −0.64 −0.71 −0.71 −1.07

In conclusion, the 2008 world city analysis has generally confirmed recent writings on South East Asian cities in globalization: 1 2

Overall, South East Asian cities score highly in the world city network. Singapore continues to dominate but some other capital cities are becoming important service nodes in the world city network in their own right, such as Kuala Lumpur, Jakarta, Bangkok and Manila. Furthermore, the capitals of South East Asian countries are generally the country’s political and economic centres, so their global network connectivity is much higher than that of other cities. The exception is Labuan with its specialist features, showing a higher connectivity than some capitals.

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City scores are closely related to their country’s level of economic development. Compared to the traditional global centre of NYLON, the connections of South East Asian cities are stronger with the Chinese cities triad.

References Akamatsu, K. (1962) ‘A historical pattern of economic growth in developing countries’, The Developing Economies, vol 1, pp3–25 Bishop, R., Phillips, J. and Yeo, W.-W. (2003) Postcolonial Urbanism: Southeast Asian Cities and Global Processes, Routledge, London Lam, N. M. K. (2000) ‘Government intervention in the economy: a comparative analysis of Singapore and Hong Kong’, Public Administration and Development, vol 20, pp397–421 Lo, F. and Marcotullio, P. J. (2000) ‘Globalisation and urban transformations in the Asia-Pacific region: a review’, Urban Studies, vol 37, pp77–111 McGee, T. (1967) The Southeast Asian City: A Social Geography of the Primate Cities of Southeast Asia, Praeger, New York Tyner, J. (2008) ‘Cities of Southeast Asia’, in S. D. Brunn, M. Hays-Mitchell and D. J. Zeigler (eds) Cities of the World: World Regional Urban Development, 4th edition, Rowman & Littlefield, Lanham, MD, pp429–474

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29

Arabian Gulf Cities David Bassens, Ben Derudder and Frank Witlox

During recent decades, the Arab Gulf region has been one of the fastestgrowing regions in the world economy, predominantly as the result of a number of booming city economies. Many of these urban developments are an obvious result of the vast capital accumulation from the oil economy. More recently, however, policymakers have advanced the idea of service-based economies to shift away from oil dependency. In pre-oil times, the Gulf region lacked major urbanization. Instead, small coastal villages such as Dubai or Manama were involved in the pearl trade, some agriculture and smuggling. From the 19th century onward, the Gulf region with the so-called Trucial States (the current UAE, Bahrain and Qatar) was part of the British Empire, which saw the region as an important geostrategic stronghold. Based in Bahrain, it controlled trade to other parts of the empire, such as India (Hamouche, 2004; Pacione, 2005). After the discovery of oil in the region (in Bahrain in 1932), American influence grew through a number of strategic agreements with oil-producing countries (e.g. Aramco in Saudi Arabia). Rising oil income led to rapid urbanization, transforming former villages into cities and integrating them into the world economy. This process was enhanced even further when the British left the region in 1971. To counter possible interference from their strong neighbours Iran and Saudi Arabia, some emirates formed a federation, the United Arab Emirates (UAE), although Bahrain and Qatar remained independent (Ochsenwald and Fisher, 2004). Although the oil economy is still the main force behind urbanization, giving rise to ‘oil cities’ (Khalaf, 2006), there is a growing awareness that economic development should be sustainable when oil runs out. Apart from the focus on real estate development, tourism, transportation and trade, cities are increasingly being built and transformed into business centres and also into centres for advanced servicing, especially where oil or gas will be depleted in the near future (see Oxford Business Group, 2008a, 2008b, 2008c). For instance, Dubai is growing as an all-round service centre, while Manama is developing into a regional financial hub (see Chapter 10). The connectivities

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discussed in this section reflect how ‘successful’ Gulf cities are in becoming important nodes of these networks of advanced servicing. As shown in Table 29.1, the small Gulf region is a relatively ‘dense’ region in terms of well-connected cities. One explanation for this lies in the fragmentation of the narrow strip along the Gulf into small emirates and kingdoms. Except for Dammam, all cities on the list are state capitals (Abu Dhabi, Doha, Kuwait City, Manama, Muscat) and/or emirate capitals (Abu Dhabi, Dubai), and they quite often occupy a large proportion of the state territory (except for Muscat). As a result, these cities are often the main foci of economic development and are in fact run as city-states, locked in a competition for regional dominance as nodes in global flows of capital such as the attraction of foreign direct investment (FDI), trade and tourism.

Table 29.1 Global network connectivity of Arabian Gulf cities. RANK

CITY

1 2 3 4 5 6 7

Dubai Kuwait City Manama Doha Muscat Abu Dhabi Dammam

GROSS CONNECTIVITY 38,935 33,811 24,872 19,995 11,129 9348 7344

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.40 0.35 0.26 0.21 0.12 0.10 0.08

The cities in Table 29.1 can be divided into two groups, namely oil cities and non-oil cities. While oil cities remain dependent on oil production (Abu Dhabi, and Dammam, home of the Aramco headquarters) or trade and oil (Muscat), non-oil cities have made a clear shift to services, and they score well in terms of global network connectivity (Dubai, Manama), although some oil cities (Kuwait City, Doha) have also diversified successfully. Dubai is the absolute regional leader and the best-connected city in the UAE, largely overshadowing Abu Dhabi. Abu Dhabi has, however, some importance through its administrative function – it is the seat of the president of the UAE – and its large oil income compared to other members of the UAE. More substantially, during the current financial crisis, Abu Dhabi bailed out Dubai, which was unable to repay some of its massive debts (The Economist, 29 February 2009). This leaves us to consider whether Dubai’s economy is truly a sustainable alternative to existing oil economies in the region. As can be read from Table 29.2, which shows orientation toward the local region, the ranking is the inverse of Table 29.1, indicating that the least connected cities are relatively more local in their connectivities. This is

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certainly the case for Abu Dhabi, whose role is mainly as an administrative centre for the UAE, and Dammam, as part of the relatively closed Saudi economy. On the other hand, Kuwait City, Dubai and Manama are relatively under-linked to the local region. For Dubai, this confirms the importance of its global linkages, while for Manama, this slight under-linkage reflects its connectivities with international financial centres (Taylor, 2001) outside the Gulf region. The low localism score for Kuwait City is probably a result of its eccentric geographical position (vis-à-vis the other Gulf cities) and its connectivities with other Middle Eastern cities outside the Gulf region. Table 29.2 Localism (relative concentration of connections within the Arabian Gulf). RANK

CITY

1 2 3 4 5 6 7

Abu Dhabi Doha Dammam Muscat Manama Dubai Kuwait City

LOCALISM 0.47 0.18 0.07 0.02 −0.15 −0.34 −0.41

Tables 29.3 and 29.4 illustrate how cities are over-linked or under-linked, respectively, with the traditional ‘core’ New York and London (NYLON) and the emerging Chinese cities triad of Beijing, Hong Kong and Shanghai. In general, both tables are very similar, with Dubai, Abu Dhabi and Manama being over-linked cities and the rest being under-linked. This supports the view that Gulf cities are responding to globalizing forces from both the old and the newly emerging cores simultaneously, and are becoming nodes in the flows of capital, people and goods between West and East. Furthermore, both tables show the same unexpected results for Abu Dhabi and Kuwait City, with Abu Dhabi being substantially over-linked and Kuwait City under-linked to both global arenas. In summary, it appears that the UAE cities in particular are well integrated within the network of old and emerging global cities. Table 29.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7

Dubai Abu Dhabi Manama Doha Kuwait City Muscat Dammam

TRADITIONAL GLOBALISM 0.78 0.51 0.07 −0.05 −0.38 −0.44 −0.74

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Table 29.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7

Dubai Abu Dhabi Manama Doha Kuwait City Muscat Dammam

NEW GLOBALISM 0.84 0.39 0.26 −0.22 −0.36 −0.56 −0.71

In conclusion, this analysis has shown that Gulf cities are well connected into the world city network of advanced producer services. In particular, Dubai and Manama, where fossil fuels are running out, and Kuwait City, are diversifying their economies in this direction. Dubai is the undisputed regional leader through both its strong linkages with the old core (NYLON) and the emerging Chinese triad of Beijing, Hong Kong and Shanghai. This suggests that Gulf cities in general can benefit from their strategic location and have a future as important nodes in networks of capital, people and goods in a world economy that is shifting to the East.

References Hamouche, M. B. (2004) ‘The changing morphology of the gulf cities in the age of globalisation: the case of Bahrain’, Habitat International, vol 28, pp521–540 Khalaf, S. (2006) ‘The evolution of the Gulf city type, oil, and globalization’, in J. W. Fox, N. Mourtada-Sabbah and M. al-Mutawa (eds) Globalization and the Gulf, Routledge, London, pp244–265 Ochsenwald, W. and Fisher, S. N. (2004) The Middle East: A History, 6th edition, McGraw Hill, New York Oxford Business Group (2008a) The Report Abu Dhabi 2008, Oxford Business Group, London Oxford Business Group (2008b) The Report Bahrain 2008, Oxford Business Group, London Oxford Business Group (2008c) The Report Dubai 2008, Oxford Business Group, London Pacione, M. (2005) ‘City profile: Dubai’, Cities, vol 22, pp255–265 Taylor, P. J. (2001) ‘West Asian/North African cities in the world city network: a global analysis of dependence, integration and autonomy’, The Arab World Geographer, vol 4, pp146–159 The Economist (2009) ‘Dubai’s bail-out: the outstretched palm’, www.economist.com/displaystory.cfm?story_id=13186145, accessed 30 June 2009

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30

European Post-Soviet Cities Olga Gritsai, Pengfei Ni, Herman van der Wusten, Kai Liu, Guangquan Li and Jin Huang

The cities included in this chapter are from the Commonwealth of Independent States (CIS) which brought together the ex-Soviet states (except the Baltic states) after the demise of the USSR in 1991. Eleven states joined CIS including five from central Asia that are not included in this chapter. The remaining European CIS states include seven cities that qualify for inclusion above the 0.05 connectivity threshold: these ‘European post-Soviet cities’ include five new state capitals and two non-capital cities from Russia. For several decades through most of the 20th century, Moscow, as capital city of the USSR, was the main political centre of the entire socialist bloc and the most important decision-making centre for the Soviet economy. Formally, the USSR was a federation and centres of each federal state had some nominal autonomy, but this was always severely limited by the overarching authority of the party and its organs. The same applied to the Russian Federation, by far the most important unit of the federal USSR. All political units were subject to a series of five-year plans, which engineered a massive industrialization and created an economic development that was relatively independent of the rest of the world. However, in its final years the USSR’s economy became linked in many ways to the capitalist world economy, particularly through the export of energy, the import of food and machinery and the accompanying financial flows. Nonetheless the Soviet economy was still very much organized in its own way, entirely lacking many of the advanced producer services that developed at the time in the western world to facilitate the beginnings of economic globalization. Thus hardly any of the offices of globalizing companies in that sector were to be found in the USSR: only a few of the globally operating banks had liaison offices without commercial activities in Moscow at this time. As this heavily centralized, differently organized political economy fell apart at the end of 1991 after the institutions regulating the economy had broken down, the Union’s fragments and their cities – Moscow among them – had to find new positions. Amid the ongoing struggles about a new regulatory environment, the growing presence of foreign capital brought a new quality to

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the central function of Moscow and gave new opportunities to the capital cities of the newly independent post-Soviet states and to a number of the large Russian cities. New capital cities have partly taken over representative and managerial functions with respect to links with the outside world. But the process of detachment from the former metropole takes time, due particularly to the modest size of separate national markets, and because of the political instability in some of these states. A number of large Russian cities have developed their economic links abroad, attracted foreign investments, and improved their economic profile and image. The locational strategy of the globally operating service companies in postSoviet space is crucial for understanding the pattern of connectivity of the post-Soviet cities, which until fairly recently was practically closed to foreign business. Based on data for 2003, following the initial wave of companies establishing offices in European post-Soviet cities, advisory and project-based professional services (global lawyers, management consultancies) tend to have one office in Moscow, or even elsewhere in Eastern Europe outside post-Soviet space, supervising all temporary servicing in the entire post-Soviet space. Activities that operate on a national basis (banks, advertising companies) have created more extended networks with offices in several new capital cities – mostly in Moscow, Kiev and also in Almaty (it remains to be seen what will happen after the new capital of Kazakhstan, Astana, has come to full fruition), and occasionally elsewhere (Minsk, Tbilisi, Yerevan and Baku). For the much larger Russian economy, many such companies also opened second offices in St Petersburg, or in some other locations (Novosibirsk, Yekaterinburg, Vladivostok, etc) for coordination activities in Siberia, the Urals or the Far East. Locally and regionally oriented companies (accountants, insurance companies) have a widespread geography of offices in Russia. Outside Russia their number is much smaller and they are found only in capital cities. Until recently, even for this type of company, more unstable economies (e.g. in the Caucasus) were also served from Moscow offices (Gritsai, 2004). The 2008 data for global connectivity presented in Table 30.1 show Moscow to have emerged definitely as by far the most important global service provider among the European post-Soviet cities. Over the last decade the city has also improved its global position in this network to a remarkable extent (Derudder et al, 2010), but it is unclear if this is part of an overall change for the cities in post-Soviet space or is a specific development for Moscow. Current evidence (Derudder et al, 2010) suggests it is the latter. However that may be, the city is now nearly twice as well connected within the network of global service providers as the second largest capital city of the post-Soviet space, Kiev, and three times better connected than St Petersburg, Russia’s second largest city. Undoubtedly Moscow has acquired this position on the basis of its traditional centrality in the political economy of the USSR, which proved a strong attraction for the global service companies that arrived initially. Kiev’s position can be read as a reflection of Ukraine’s relative importance in post-Soviet space, while St Petersburg’s position reflects its traditional rank as the second city of

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the USSR. It is interesting that the capital city status of Kiev counts for more in this rank order of new connectivities. In general, capital city status lifts the global connectivities in post-Soviet space, even if the other new capital cities (Tbilisi, Minsk and Chisinau) have very modest scores. Chisinau in particular would not have appeared in the ranking, if it had not been a capital. Nevertheless Tbilisi, with all its political ambitions and attention from the western world, is still very modestly linked in terms of global connectivity. Apart from St Petersburg only Novosibirsk among the non-capital Russian cities (slightly) exceeds the lower 0.05 threshold retained for this table. 5

5

Table 30.1 Global network connectivity of European post-Soviet cities. RANK

CITY

1 2 3 4 5 6 7

Moscow Kiev St Petersburg Tbilisi Minsk Chisinau Novosibirsk 5

GROSS CONNECTIVITY 61,387 31,613 20,401 9740 8804 7118 6214

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.64 0.33 0.21 0.10 0.09 0.07 0.06

An interesting question is why Novosibirsk qualifies for the list, while Yekaterinburg, according to most parameters the most successful and internationalized city after Moscow and St Petersburg, does not. Being the centre of a big and economically strong region, Yekaterinburg seems to be more advanced in all economic spheres, it attracts a lot of foreign investments and is the third city after Moscow and St Petersburg in the number of foreign consulates and representative offices of foreign companies (Kolossov and Eckert, 2007; Kolossov and Thorez, 2009). Nevertheless, in terms of linkages of locally established global producer service companies it lags behind Novosibirsk. Of course, with both cities having such small scores the presence of even one extra well-connected global company can be decisive. In the last few years a couple of global banks (apparently having investments in Siberia) have indeed opened new branches in Novosibirsk. But another reason may also be the city’s traditional openness (unlike Yekaterinburg which was for years a city closed to foreigners) (Zubarevich, 2003), plus the availability of a well-qualified labour force, underpinned by the Siberian branch of the Academy of Sciences. It also appears that the greater distance from Moscow offers Novosibirsk a slightly better chance for becoming a regional centre for services with a global market in a huge region with export-oriented companies, even if those service providers turn out to have intermediaries elsewhere in the region.

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Generally, the scores of localism (Table 30.2) are not very surprising, with Novosibirsk in particular, and also St Petersburg, being most inward-oriented, and the leading capital cities (Moscow and Kiev) – being outward-looking. The only possible surprise is Tbilisi’s position in not being more outward in its links. This specific and unusual case is discussed further below. It is also noteworthy that St Petersburg is the only city ranked relatively high in both Tables 30.1 and 30.2. As Russia’s second city and the key Russian port on the Baltic, the city seems to have balanced its global and local connections.

Table 30.2 Localism (relative concentration of connections within European post-Soviet cities). RANK

CITY

1 2 3 4 5 6 7

Novosibirsk St Petersburg Minsk Tbilisi Chisinau Kiev Moscow 5

LOCALISM 2.41 0.44 0.25 0.15 0.07 −0.21 −0.73

Tables 30.3 and 30.4 measure the ‘traditional globalism’ of Russian cities (their connectivity to London and New York) and ‘new globalism’ (relative concentration of connections to the Chinese global cities – Beijing, Hong Kong and Shanghai). These two tables look surprisingly similar with practically equal figures for Western or Eastern connectivity. Moscow is in both cases the only city with a positive score. All the other European post-Soviet cities, even the capitals, have in both tables a negative score (with Novosibirsk, Chisinau and Tbilisi at the bottom of the list). The latter suggests that global companies frequently prefer to operate their Georgian branches through intermediaries in the region, mostly in Moscow, just as in the case of Russian cities. While being for a while relatively successful in its political ambitions ‘to join the West’ and also to become the political capital of the Caucasus, Tbilisi in a paradoxical way seems still to be more dependent upon the economic networks within the post-Soviet space. More generally, in spite of the recent fragmentation of the post-Soviet urban network and re-distribution of international functions, Moscow has turned out to be the only well-connected global service centre in this region, strongly linked to the most important global cities in the West and East, and to some extent serving as the centre for the most important globally operating advanced producer services companies operating over a large part of Eurasia. The equal orientation of the post-Soviet cities to the West and the East once again shows the Eurasian characteristics of this region of the world and its complicated (or advantageous?) geopolitical location. 5

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Table 30.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7

Moscow Kiev Minsk St Petersburg Chisinau Novosibirsk Tbilisi 5

TRADITIONAL GLOBALISM 0.68 −0.18 −0.31 −0.32 −0.57 −0.64 −0.66

Table 30.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7

Moscow Kiev Minsk St Petersburg Novosibirsk Chisinau Tbilisi 5

NEW GLOBALISM 0.73 −0.10 −0.22 −0.30 −0.62 −0.73 −0.89

References Derudder, B., Taylor, P. J., Ni, P., De Vos, A., Hoyler, M., Hanssens, H., Bassens, D., Huang, J., Witlox, F., Shen, W. and Yang, X. (2010) ‘Pathways of change: shifting connectivities in the world city network, 2000–08’, Urban Studies, vol 47, pp1861–1877 Gritsai, O. (2004) ‘Global business services in Moscow: patterns of involvement’, Urban Studies, vol 41, pp2001–2024 Kolossov, V. and Eckert, D. (2007) ‘Russian regional capitals as new international actors: the case of Yekaterinburg and Rostov’, Belgeo, no 1, pp115–131 Kolossov, V. and Thorez, P. (2009) ‘Métropolisation et place des régions dans le transport aérien en Russie’, Bulletin de l’Association de géographes français, vol 86, pp496–511 Zubarevich, N. (2003) ‘The impact of globalization on the development of Russian regions: results and perspectives’, in V. Kolossov and D. Eckert (eds) Large Cities and the Challenges of Globalization, French-Russian Center on Social Sciences and Humanities in Moscow, Institute of Geography, Russian Academy of Sciences, Oycumena, Smolensk [in Russian]

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Eastern European Cities Marek Ban´czyk

The dominance of Warsaw in the main connectivity table (Table 31.1) comes as little surprise since, for the past two decades, this city has been probably the main connection between the largest national economy of Eastern Europe and the outside world. One must point out that this has been an era of unprecedented economic growth, both in the region, and especially in Poland. This was powered to a large extent by foreign investors who tend to enter emerging economies by setting up their headquarters and branch offices ‘cautiously’, that is, often preferring the national capitals above anywhere else (EBRD, 1995). This, however, tends to change over time which can also be seen in Table 31.1. The high position of Budapest is definitely a remnant from the past Communist era; Budapest then served as a gateway city to the whole Soviet bloc. It was the main meeting point between the East and the West which had added to its otherwise remarkable metropolitan scale inherited from the Habsburg Empire. The high position of Budapest in today’s global city network shows how persistent and powerful the mechanism of world city formation can be once it becomes established (Jöns, 1999). Not only can it resist changes in the international landscape and survive national economic turbulence, it can also provide some consolation in times of global crisis. Budapest remains Eastern Europe’s third ranked city. However, because of Hungary’s difficult transformation over the past ten years it has been overtaken by Prague (ranked second) with its unquestioned rise as the most fashionable Eastern European city in recent years. As mentioned above, the dominance of national capitals is not unshakeable. There is a notable presence of ‘challenger’ (non-capital) cities, such as Kraków, Wrocław or Poznan´ in the network map of Eastern Europe, which is a new phenomenon of potentially critical consequences (Müller et al, 2005). The impact of the formal role of national capitals on the location of advanced producer service firms and resulting business flows has been observed almost everywhere, but in Eastern Europe it has perhaps been stronger than elsewhere due to the still unusually strong role of the state and regulatory bodies in business life. Therefore, the appearance of non-capital

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Table 31.1 Global network connectivity of Eastern European cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Warsaw Prague Budapest Bucharest Sofia Bratislava Zagreb Ljubljana Riga Tallinn Vilnius Belgrade Kraków Skopje Poznan´ Wrocław Sarajevo Tirana Podgorica

GROSS CONNECTIVITY 53,880 46,808 46,420 38,648 30,418 28,399 25,340 24,053 21,067 20,374 18,442 16,096 12,844 10,366 8930 8177 8128 7212 4684

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.56 0.49 0.48 0.40 0.32 0.30 0.26 0.25 0.22 0.21 0.19 0.17 0.13 0.11 0.09 0.08 0.08 0.07 0.05

cities in the global network, even if not very pronounced, should not be underrated in importance as it indicates the early formation of nodes in economic flows of global value creation (Hamilton et al, 2005). In this regard, the results of the 2008 world city network connectivity analysis are very similar to the findings of an independent study conducted in 2008 and 2009 for 18 Polish cities (IKER, 2008, 2009). Moreover, Tables 31.3 and 31.4 show that in certain types of connections such as with New York and London (NYLON) or with the Chinese big three (Beijing, Shanghai and Hong Kong), challenger cities such as Poznan´ or Kraków are now at least on the map. The fact that global city network formation outside of the national capital is observable so far mainly in Poland can be explained in part by two causes: 1

Poland is the largest country of Eastern Europe, roughly the size (and business location profile) of Spain, so it should be the first country expected to produce more network nodes beyond the capital. This, however, is only a general point that may or may not have any significance. The representation of a country in the global interlocking city network is not known to be proportional to a country’s population size. In general, larger countries tend to have more global cities but a comparison of

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Germany, Russia or Indonesia shows that this tendency is far from strong and definitely not a rule. The other possible explanation of the growing global connectivity of Poland’s challenger cities rests on the very core mechanism of city networks. As stated in numerous flagship theorems of the network paradigm in city studies (e.g. Taylor, 2007), the critical processes underlying world city network formation are based on non-hierarchical and noncompeting patterns of exchange: intercity relations as a win–win scenario as opposed to a zero-sum game. This might potentially mean that there is some positive association between the position of a country’s top city in the global network and the chances that other cities from the same country connect to the network and eventually grow global, too. Since the last connectivity analysis in 2004, two new Polish challenger cities appeared (Poznan´ and Wrocław) and greatly improved the score of the existing one (Kraków, connectivity rose from 0.09 to 0.13). One must note that this coincided with the sharp rise of Warsaw in the global network (connectivity climbed from 0.43 to 0.56) through which Warsaw practically broke away from the whole Eastern European group of cities. This could mean that at least part of the stream of processes newly attracted by Warsaw was then transformed into smaller but still significant flows on the national level to the three challenger cities mentioned. Such an explanation would obviously contradict the traditional competitive approach to national city systems, as it would imply that the higher the leader, the higher the challengers.

Little can be said about intraregional networks between cities of Eastern Europe (Table 31.2). These appear negligible given the lack of a consistent pattern in the results. To put it radically, business-flow-wise, there is no such thing as Eastern Europe. The common tendency in other chapters for relatively more business links locally to be associated with fewer business links to the wider world is quite weak here. In fact the localism seems to be regional: cities of the Balkans are local, Polish cities are ‘unlocal’. More can be said about the main path of connections between Eastern European cities and the world. The comparison of global connectivity (Table 31.1) with traditional and new global connectivity paths (Tables 31.3 and 31.4) implies that both main paths are critical to the total connectivity. The dominance of Warsaw, Budapest and Prague with regard to NYLON and Beijing, Shanghai and Hong Kong (the big three of China) translates directly into their dominance in global connectivity.

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Table 31.2 Localism (relative concentration of connections within Eastern Europe–Baltic). RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Skopje Sarajevo Belgrade Vilnius Ljubljana Zagreb Riga Bratislava Tallinn Bucharest Sofia Podgorica Budapest Wrocław Tirana Prague Warsaw Poznan´ Kraków

LOCALISM 2.54 2.49 1.89 1.71 1.65 1.64 1.50 1.35 1.32 1.26 1.14 1.05 0.69 0.65 0.60 0.52 0.42 0.23 −0.41

Table 31.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6= 6= 8 9 10= 10= 12 13 14 15 16 17 18= 18=

Warsaw Budapest Prague Bratislava Bucharest Zagreb Sofia Sarajevo Tallinn Vilnius Skopje Belgrade Riga Ljubljana Wrocław Poznan´ Tirana Kraków Podgorica

TRADITIONAL GLOBALISM 0.49 0.43 0.36 0.16 0.06 −0.01 −0.01 −0.03 −0.11 −0.12 −0.12 −0.15 −0.16 −0.20 −0.32 −0.65 −0.66 −0.73 −0.73

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Table 31.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

Warsaw Budapest Prague Bratislava Bucharest Zagreb Sofia Sarajevo Ljubljana Skopje Belgrade Riga Vilnius Tallinn Wrocław Tirana Podgorica Kraków Poznan´

NEW GLOBALISM 0.43 0.33 0.32 0.11 0.04 0.00 −0.05 −0.11 −0.12 −0.16 −0.17 −0.24 −0.25 −0.28 −0.77 −0.81 −0.92 −0.95 −1.00

The hierarchy of Eastern European cities in terms of their global connectivity does not reflect the ‘general’ economic development stage as defined by classic macroeconomic figures. In this regard, the positions of Prague, Ljubljana and Tallinn, to name the most striking cases, are significantly lower than predicted by macroeconomics. On the other hand, the respective positions of Warsaw, Budapest and Bucharest are significantly higher than predicted. Such a discrepancy clearly shows that there is at least a conflict between traditional measures of economic development and the business connectivity analysis. It does not necessarily mean that either of the approaches is more or less accurate than the other. It could mean that both approaches concentrate on different aspects of socioeconomic reality and that the mutual relation between these aspects evolves over decades. This means that GDP per capita, disposable income per household or employment rate may still accurately demonstrate certain macroeconomic sides of life, but the importance of these to the whole picture might have decreased in globalization, whereas the speed and intensity of global exchange, measured by connectivity, has increased in importance. The key cities of Eastern Europe have practically all improved their global connectivity score and global network position compared to the results of 2004. The strongest growth was seen in Ljubljana, the slowest in Belgrade. This general trend, together with the very high scores of connectivity achieved

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by Warsaw, Prague and Budapest (about half the level of London), provides a good basis for forecasting further prosperity in this region of emerging economies. At the same time it clearly shows that the flow of critical processes will not be distributed evenly across the countries, and differences might increase over time; hence even if there were any traces of a regional entity of Eastern Europe, any sense of the post-bloc cohesion is about to disappear. Bearing that in mind, we should prepare for a shift in the use of the term ‘Eastern Europe’ towards a purely historical or geographical context. In terms of advanced business service links, Eastern European countries are far less connected among themselves than with the wider world. Considering the paragraph above, it would be hard to say anything about the hierarchy and network of connections within the region, since there are few. Technically, taking into consideration the main results of global connectivity (Table 31.1), one could identify four to five strata: Warsaw constituting its own alpha level, Prague and Budapest – beta, Bucharest – gamma, and so on. It is highly doubtful though that cities such as Budapest and Tirana or Skopje connect on the same level and act in the same arena. Moreover, the results of research on local connections (Table 31.2) show clearly that connections within the region are unrelated to the global connectivity score. One cannot reliably speak of Skopje as a local or intraregional node. It is rather a city most dependent on Eastern European links without further connections. Therefore, it is more accurate to conclude that within Eastern Europe there are three cities showing notable global node formation, namely Warsaw, Budapest and Prague, of which Warsaw scores highest while its global connectivity grows fastest, too. The connectivity score says very much yet it does not say it all. Even if we follow a purely Taylorean approach (Taylor, 2009) in which two major ways of city formation such as agglomeration and network are juxtaposed, the network part can be broken down into two basic aspects. Being a node does not imply being a city creating new solutions. The critical part not covered by connectivity is the direction of the flow. This observation leads to typologies based on the network flow balance; there might be cities mostly keeping the solutions in or mostly producing them and distributing into the network. Such a dissection of connectivity might be particularly important in the case of emerging economies, for example those of Eastern Europe, and might be helpful in explaining the very high score and position of Warsaw (0.56), as well as Prague and Budapest (0.49 and 0.48 respectively). For all their development, it would be rather unwise to say that these key cities of Eastern Europe influence the world at about half as much as New York or London, as the pure numbers might suggest. Certainly more studies are needed to establish knowledge on the direction of the predominant flows of processes within the interlocking network of cities as measured by global connectivity.

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References EBRD (1995) Transition Report: Economic Transition in Eastern Europe and the Former Soviet Union, European Bank for Reconstruction and Development, London Hamilton, F. E. I., Dimitrovska Andrews, K. and Pichler-Milanovic´, N. (eds) (2005) Transformation of Cities in Central and Eastern Europe: Towards Globalization, United Nations University Press, Tokyo IKER (2008) Pierwszy Ranking Metropolitalnosci Miast Polskich NORDEA METROX.2008, Instytut Konkurencyjnej Ekonomii Regionów, Poznan´ IKER (2009) 2. Ranking Metropolitalnosci Miast Polskich NORDEA METROX.2009, Instytut Konkurencyjnej Ekonomii Regionów, Poznan´ Jöns, H. (1999) ‘Foreign banks are branching out: changing geographies of Hungarian banking, 1987–1999’, in P. Meusburger and H. Jöns (eds) Transformations in Hungary, Physica-Verlag, Berlin, pp65–124 Müller, B., Finka, M. and Lintz, G. (eds) (2005) Rise and Decline of Industry in Central and Eastern Europe, Springer, Berlin Taylor, P. J. (2007) ‘Cities within spaces of flows: theses for a materialist understanding of the external relations of cities’, in P. J. Taylor, B. Derudder, P. Saey and F. Witlox (eds) Cities in Globalization: Practices, Policies and Theories, Routledge, London, pp287–297 Taylor, P. J. (2009) ‘Urban economics in thrall to Christaller: a misguided search for city hierarchies in external urban relations’, Environment and Planning A, vol 41, pp2550–2555

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Nordic Cities Brita Hermelin

This chapter will discuss the connectivity of the main cities in the Nordic countries (Norden). Modern urbanization in the Nordic countries was comparatively late, starting from the middle of the 19th century (Johansen, 2005; Clark, 2009). In 1850 Denmark was the exception to the other Nordic countries with 10 per cent of its population living in the capital region of Copenhagen compared with 1–3 per cent in Finland, Norway and Sweden (Johansen, 2005, p169). The cities discussed in this chapter are located in five countries: Sweden, Denmark, Finland, Norway and Iceland. Stockholm, Gothenburg and Malmö are located in Sweden; Copenhagen and Arhus in Denmark; Helsinki in Finland; Oslo and Bergen in Norway; and Reykjavik in Iceland. Thus, nine cities are included. The empirical base for this chapter is quantitative results for the connectivity of nine Nordic cities. The connectivity of a city reflects its external relations, and in this case, the office and workplace networks of companies in advanced services. Patterns of the location of offices and affiliates in transnational companies develop over time and in path dependency relating to the resources and preferences of individuals and firms, formal regulations, business cycles, etc. The possibilities and restraints vary between different places and cities. The empirical findings present the sum of the relations of major firms in selected advanced producer services. The difference between the cities can be understood as the outcome of the difference between the resources and trajectories of different cities, considering their role in the international structure of economic flows and relations. External relations of cities develop over time and to be able to understand the difference in connectivity of the main Nordic cities it is important to consider the development of the political geography in the region of the Nordic countries. The national borders and the constituency for these countries and thereby also the role of their cities have changed over time. From the middle of the 16th century, Sweden expanded its territory as the great power in Norden and also in the wider region of northern Europe and the Baltic. This expansion gradually changed into decline and in this process the loss of Finland to Russia in 1809 was

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a particularly dramatic moment. From 1815, Sweden and Norway became a political union until 1905, with Sweden the dominant partner (Lundén, 2010). Finland became independent from Russia in the early 20th century. Denmark has been an independent country since the Middle Ages. Norway, Finland and Iceland have more recently become sovereign nation states, Iceland as late as after the Second World War when it became independent from Denmark. The Nordic countries have small populations. They have an integrated history which has led to dense economic and social connections across the borders. One factor behind the strong dominance of the capital cities of the Nordic countries, which is also evident in Table 32.1, is the unitary nature of these nation states. The importance of their capital cities is related to the material and representative powers of the different nation states. This is reflected in Stockholm’s position as number one in the table. In the Swedish case, the primacy of Stockholm has been enhanced during the period since the Second World War (SOU, 1989). The international position of Stockholm is relatively strong if this is compared to the size of its population. This should be understood in the context of the history of Sweden as a dominating political power among the Nordic countries, and although Stockholm is not a large city compared to a wider international context, it is large in its part of the world. Stockholm is also a focal point for international connections developed from a strong tradition in the Swedish economy to produce major transnational corporations, which have important bases in raw material sectors (pulp and paper, metal production) and in the engineering industry (machinery, car industry) (Lundmark, 2010). During recent decades, inward investment has increased considerably and this is particularly evident in different service sectors. Looking at the value for connectivity and the differences between the cities, there is some distance between Stockholm and the group of Helsinki, Oslo and Copenhagen, which in turn are far more distant from the next tier of cities included in Table 32.1.

Table 32.1 Global network connectivity of Nordic cities. RANK

CITY

1 2 3 4 5 6 7 8 9

Stockholm Oslo Helsinki Copenhagen Reykjavik Arhus Bergen Gothenburg Malmö

GROSS CONNECTIVITY 47,414 38,043 37,672 35,764 12,184 9350 8499 8267 6220

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.49 0.40 0.39 0.37 0.13 0.10 0.09 0.09 0.06

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Copenhagen and Malmö (in Sweden) are closely located on each side of Öresund, a narrow passage connecting the Baltic Sea and the North Sea, and have been connected by a bridge for cars and trains since 2000. The Öresund Committee was established in 1993 to develop an integrated region on both sides of Öresund. According to this Committee’s website, this region comprises 3.7 million inhabitants; with 2.5 million on the Danish side including the Copenhagen wider region and 1.2 million on the Swedish side including Malmö and the province of Skåne (Öresundskomiteen, 2009). The integration and consolidation of this region has been supported by European Union Interreg programmes since 1994. In the Nordic context of the discourse on ‘cities in competition’, it is the Copenhagen/Öresund city-region which competes with Stockholm to be the main global hub in this part of the world. If the figures for connectivity for Copenhagen and for Malmö are combined to form the Öresund region, this city-region gains a position as number two and is close to Stockholm in Table 32.1. Table 32.2 presents figures for the relative concentration of connections within the Nordic regions and it is shown that such connections are important for second tier cities. Copenhagen, however, the capital of Denmark, has the fourth highest positive value for localism. One tentative idea about the background to these figures would be that the importance of the primary sector and the food industry for Denmark’s economy involve relatively strong regional connections for economic integration. Helsinki’s very low value for localism is likely to be due to the strong economic relations, for historical and geographical reasons, between Finland and Russia. Reykjavik also has a very low value for localism. For Reykjavik and Iceland the connections to Nordic regions are not supported by geographical proximity and easy physical access. Gothenburg, the most local city in Table 32.2, developed as a port city and an industrial town and these are still important economic bases. Thus, there are reasons to believe that the strongest position for international relations from Gothenburg may be in sectors other than advanced producer services, which are the basis for the data presented in the table (Ivarsson, 2002). It is noteworthy that a survey of all foreign-owned companies and workplaces in Gothenburg illustrated the strong dominance of Norwegian and Danish ownership (Business Region Göteborg, undated). In contrast to the connectivity values for localism, Tables 32.3 and 32.4 present values for the relative concentration of more distant connections. These two tables put Stockholm in an exclusive position compared to the other cities in the Nordic countries. They show that Stockholm is the centre in Norden for transnational firms with wide connections in advanced producer services to both NYLON (New York/London) and the new Chinese global cities triad (Beijing–Hong Kong–Shanghai). Although advanced services contribute to an important labour market in all of the capital cities – Stockholm, Helsinki, Oslo and Copenhagen – its share is highest in Stockholm. A study of advertising firms in Stockholm illustrated that almost half of the more substantial offices were comprised of US-owned companies (Hermelin,

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2009). The figures with high values for wide international connectivity for Stockholm may also be a reflection of the strong tradition in Sweden to develop major transnational firms as discussed above. The Swedish-based international corporations tend to choose to locate offices in Stockholm. Also, in recent years Stockholm-based banks have made substantial outward investments in the Baltic states, which are geographically close but not defined as the local region in Table 32.2 (Karreman, 2009).

Table 32.2 Localism (relative concentration of connections within the Nordic region). RANK

CITY

1 2 3 4 5 6 7 8 9

Gothenburg Malmö Arhus Copenhagen Oslo Bergen Reykjavik Helsinki Stockholm

LOCALISM 1.34 0.99 0.95 0.42 0.19 0.17 0.06 0.03 −0.16

Table 32.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7 8 9

Stockholm Copenhagen Helsinki Oslo Gothenburg Arhus Malmö Reykjavik Bergen

TRADITIONAL GLOBALISM 0.61 0.17 0.07 −0.03 −0.44 −0.50 −0.51 −0.58 −0.87

To a large extent the figures presented in the tables confirm a relatively established picture of the position of Nordic cities: 1

The figures confirm the primate city structure of the Nordic countries. The capital cities are distinctly more connected through their advanced producer services firms with cities outside their countries compared to the second tier cities in their respective countries. These second tier cities are primarily involved in connections within the Nordic countries.

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The results show that advanced producer services located in Stockholm are far more involved in connections to London, New York and to the Chinese cities triad, compared to the other capital cities in Norden. There are also more unexpected results presented in the data. These include the strong localism for Copenhagen and the very strong localism for Gothenburg.

Table 32.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2= 2= 4 5 6 7 8 9

Stockholm Copenhagen Helsinki Oslo Arhus Gothenburg Malmö Reykjavik Bergen

NEW GLOBALISM 0.41 0.09 0.09 −0.07 −0.42 −0.44 −0.62 −0.68 −1.11

References Business Region Göteborg (undated) ‘Foreign owned companies 2007 in the Göteborg region’, www.businessregion.se, accessed 10 March 2010 Clark, P. (2009) European Cities and Towns 400–2000, Oxford University Press, Oxford Hermelin, B. (2009) ‘Producer service firms in globalising cities: the example of advertising firms in Stockholm’, The Service Industries Journal, vol 29, pp457–471 Ivarsson, I. (2002) ‘Transnational corporations and the geographical transfer of localised technology: a multi-industry study of foreign affiliates in Sweden’, Journal of Economic Geography, vol 2, pp221–247 Johansen, H. C. (2005) ‘Scandinavian urbanisation, 1850–1970’, in M. Jerneck, M. Mörner, G. Tortella and S. Åkerman (eds) Different Paths to Modernity: A Nordic and Spanish Perspective, Nordic Academic Press, Lund, pp166–180 Karreman, B. (2009) ‘Financial geographies and emerging markets in Europe’, Tijdschrift voor Economische en Sociale Geografie, vol 100, pp260–266 Lundén, T. (2010) ‘Sweden’s territorial organization: from Viking frontier to municipal reforms’, in B. Hermelin and U. Jansson (eds) Placing Human Geography: Sweden through Time and Space, YMER 2010, Svenska Sällskapet för Antropologi och Geografi (SSAG), pp15–48 Lundmark, M. (2010) ‘Industrial development in Sweden – patterns of location, internationalization and knowledge production’, in B. Hermelin and U. Jansson (eds) Placing Human Geography: Sweden through Time and Space, YMER 2010, Svenska Sällskapet för Antropologi och Geografi (SSAG), pp223–250

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Öresundskomiteen (2009) www.oresundskomiteen.dk, accessed 10 March 2010 SOU (1989) Storstadsregioner i förändring: underlagsrapport från Storstadsutredningen, Statens offentliga utredningar 1989:69, Allmänna förl., Stockholm

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Benelux Cities David Bassens, Ben Derudder and Frank Witlox

Belgium, the Netherlands and Luxembourg have a relatively long history of economic cooperation. From 1955 onwards, this cooperation took the form of the supranational union called Benelux, which paved the way for the free movement of workers, capital and services. Thus, Benelux can be regarded as the starting point of more than 50 years of increasing economic and political integration in Europe. Self-evidently, the high levels of economic cooperation among Benelux countries have facilitated the formation of border-crossing linkages between their major urban areas (Dieleman and Faludi, 1998). In Belgium, urbanization and economic activity are concentrated around 18 cityregions (Luyten and Van Hecke, 2007), and especially within the contours of the Flemish Diamond of Antwerp–Brussels–Ghent–Leuven (see Albrechts and Lievois, 2004) and the Walloon cities of Liège and Charleroi. In the Netherlands, the polycentric Randstad region (Amsterdam–Rotterdam–The Hague–Utrecht) forms the economic heartland (Lambregts et al, 2006). The Luxembourg economy is based very much on the strength of its capital city as an international/offshore financial centre (IFC/OFC). In recent decades, the shift away from heavy industry and energy production (e.g. in the Belgian coalmines) towards a service economy, and the concomitant process of socioeconomic urban/regional restructuring (Swyngedouw, 1996; Salet, 2006), has strongly influenced the ways in which these urban arenas have been inscribed in the global economy. Being small, the Benelux countries have experienced a hollowing-out of the state at the national level, both downwards by increased regionalization (e.g. the gradual federalization of Belgium), and upwards towards the supranational level (the European Union). It has become increasingly clear that there is a territorial mismatch between state authority and network-based economic paradigms. The inability of the state to successfully influence corporate decisions, such as the general relocation of labour-intensive production by large multinational corporations (MNCs) (e.g. in the automotive industry) away from Western Europe is illustrative of this point. Nevertheless, as Table 33.1 shows, a number of Benelux cities have been particularly successful in making the shift to post-Fordist modes of production

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and have become centres of advanced servicing (see Kesteloot, 2000). While much mass production is being relocated to Eastern Europe or to countries outside Europe, cities in the Benelux region have demonstrated that they are attractive sites to govern these increasingly complex global production networks through an array of advanced producer services. This is certainly the case for the capital cities, Brussels (see Elmhorn, 1998, 2001), which is the most connected city of the Benelux countries, Amsterdam and Luxembourg. Much of Brussels’ connectivity is a result of its status as the so-called capital of Europe, hosting, among others, the seat of the European Commission, the Council of the European Union and the European Council. In the context of growing levels of supranational decision-making, proximity to these European Union bodies has been an important incentive for office location in Brussels. Furthermore, the city plays a primary role in the Belgian economy in terms of employment and GDP. Surprisingly, in contrast with earlier world city network analyses (Taylor et al, 2002), Amsterdam is now rated a clear second to Brussels in the Benelux group. Although Amsterdam still boasts a high level of connectivity, its relative loss is indicative of its decline in competitiveness as a European financial centre since the turn of the millennium, compared with other centres such as London and Frankfurt (Faulconbridge et al, 2007).

Table 33.1 Global network connectivity of Benelux cities. RANK

CITY

1 2 3 4 5 6 7 8

Brussels Amsterdam Luxembourg Antwerp Rotterdam Utrecht Liège The Hague

GROSS CONNECTIVITY 60,253 53,105 34,424 22,482 22,188 9928 7480 5156

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.63 0.55 0.36 0.23 0.23 0.10 0.08 0.05

Luxembourg is very much a second-tier city in Benelux, with substantially lower levels of connectivity. Luxembourg’s third place is based largely on the presence of financial and accountancy firms (see Chapter 11, Tables 11.2 and 11.3). Although its position as a European corporate and private tax haven was challenged by a restrictive ruling of the European Commission in 2006, Luxembourg has found (legal) ways to sustain its role as an IFC/OFC in Europe. The next most important cities are the two port cities of Antwerp and Rotterdam, which are very comparable in terms of connectivity. This reflects the degree of competition between both cities as gateways into and out of Benelux and further into the

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wider European market. A distinct package of port-related services (finance, insurance, law, logistics, etc.) is clustered in these cities and supports regional and global production networks (Jacobs et al, 2010). At the bottom of the list are a number of less-connected cities: Utrecht, which hosted a Fortis HQ before the BNP Paribas takeover in 2009; Liège, the leading Walloon service centre; and The Hague, the administrative centre of the Netherlands and home to the global headquarters of Shell, one of the leading Dutch MNCs. As can be seen from Table 33.2, most of the Benelux cities are orientated towards the local region, although Brussels and Amsterdam are notable exceptions to this observation. In general, low connectivity goes hand in hand with a more local orientation of intercity linkages. The Hague is the most local city, while at the other end Brussels and Amsterdam are significantly underlinked within the Benelux region, indicating the importance of their extra-regional linkages, and thus their global character. For the Belgian cities, this confirms the observation that Brussels’ global relations are indeed a contrast with Antwerp’s more local relations (Derudder and Taylor, 2003). Compared with Wall’s (2009) analysis of top MNCs in the Netherlands across the global, European and local (Dutch) scale, Amsterdam is indeed the only Dutch city with a global character, while Rotterdam’s and Utrecht’s localism scores sustain Wall’s conclusion that these cities operate on a more local corporate scale. Somewhat surprisingly, Luxembourg scores very low but positively for localism, which reflects its predominant role as a local offshore centre and tax haven for Belgian and Dutch firms, and private individuals.

Table 33.2 Localism (relative concentration of connections within Benelux). RANK

CITY

1 2 3 4 5 6 7 8

The Hague Utrecht Liège Antwerp Rotterdam Luxembourg Amsterdam Brussels

LOCALISM 1.88 0.90 0.49 0.25 0.18 0.03 –0.39 –0.44

Table 33.3 further enhances our understanding of the geography of the global linkages, here showing the relative concentration of connections with New York and London (NYLON), which are considered the traditional global powerhouses. Indeed, to be globalized or well connected as a city means to be able to provide a seamless service with the NYLON dyad via the intra-firm networks of available advanced producer services (APS) firms. For the Benelux region, the general observation that a high global network connectivity score comes with over-

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linkage with NYLON also holds. Both Brussels and Amsterdam are over-linked, while four other cities, including the port cities of Antwerp and Rotterdam, are under-linked. Luxembourg and The Hague, however, are relatively over-linked. The latter is unexpected given its position in Table 33.1: this result probably relates to its role as the administrative centre of the Netherlands.

Table 33.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7 8

Brussels Amsterdam The Hague Luxembourg Antwerp Rotterdam Utrecht Liège

TRADITIONAL GLOBALISM 0.70 0.54 0.30 0.24 −0.02 −0.44 −0.46 −0.78

However, in a global economy that is shifting to the East, connectivity with the emerging Chinese city-triad – Beijing, Hong Kong and Shanghai – will no doubt prove to be a crucial asset for urban economies in the future. Table 33.4 illustrates how Benelux cities are connected with these emerging Chinese cities. Again, the well-connected Benelux cities are over-linked (Brussels, Amsterdam and Luxembourg), a feature that will probably give these cities a competitive edge for the future. The Hague repeats its surprise from Table 33.3. Contrarily, Antwerp and Rotterdam, although inscribed in global networks of port cities (Verhetsel and Sel, 2009), have very low positive and negative scores respectively, suggesting that the operative field of port-related APS firms in the Benelux is regional in its character. Table 33.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8

Brussels Amsterdam Luxembourg The Hague Antwerp Rotterdam Utrecht Liège

NEW GLOBALISM 0.63 0.57 0.31 0.27 0.02 −0.22 −0.46 −0.64

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Of course, the geography of APS firms described here shows a picture of how Benelux cities fared before they were hit by the global financial crisis in 2008. In addition, there has been a major round of mergers and acquisitions in Benelux, and a (partial) nationalization of a number of financial firms. The case of Fortis Bank is illustrative of this point. Following the Belgian government bailout, the bank sold off all its foreign assets (e.g. the Dutch ABN-AMRO) and restricted its activity to the Belgian territory alone. Next, the Paris-based BNP Paribas acquired a major share of the nationalized Fortis Holding. Geographically, this means that connectivity with the Netherlands (e.g. the loss of the Utrecht headquarters) has been replaced with dependency links with France. Overall, these events will have major implications in terms of intraregional connectivities and shifting power configurations, both within Benelux and beyond.

References Albrechts, L. and Lievois, G. (2004) ‘The Flemish diamond: urban network in the making?’, European Planning Studies, vol 12, pp351–370 Derudder, B. and Taylor, P. J. (2003) ‘The global capacity of Belgium’s major cities: Antwerp and Brussels compared’, Belgeo, no 4, pp459–476 Dieleman, F. M. and Faludi, A. (1998) ‘Randstad, Rhine-Ruhr and Flemish diamond as one polynucleated macro-region?’, Tijdschrift voor Economische en Sociale Geografie, vol 89, pp320–327 Elmhorn, C. (1998) ‘Brussels in the European economic space: the emergence of a world city?’, Bevas/Sobeg, no 1, pp79–101 Elmhorn, C. (2001) Brussels: A Reflexive World City, Almqvist & Wiksell International, Stockholm Faulconbridge, J. R., Engelen, E., Hoyler, M. and Beaverstock, J. V. (2007) ‘Analysing the changing landscape of European financial centres: the role of financial products and the case of Amsterdam’, Growth and Change, vol 38, pp279–303 Jacobs, W., Ducruet, C. and de Langen, P. W. (2010) ‘Integrating world cities into production networks: the case of port cities’, Global Networks, vol 10, pp92–113 Kesteloot, C. (2000) ‘Brussels: Post-Fordist polarization in a Fordist spatial canvas’, in P. Marcuse and R. van Kempen (eds) Globalizing Cities. A New Spatial Order? Blackwell Publishers, Oxford, pp186–210 Lambregts, B., Kloosterman, R., van der Werff, M. and Kapoen, L. (2006) ‘Randstad, Holland: multiple faces of a polycentric model’, in P. Hall and K. Pain (eds) The Polycentric Metropolis: Learning from Mega-City Regions in Europe, Earthscan, London, pp137–145 Luyten, S. and Van Hecke, E. (2007) Statistics Belgium Working Paper: De Belgische Stadsgewesten 2001, Algemene Directie Statistiek en Economische Informatie, Brussel Salet, W. (2006) ‘Rescaling territorial governance in the Randstad Holland: the responsiveness of spatial and institutional strategies to changing socio-economic interactions’, European Planning Studies, vol 14, pp959–977

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Swyngedouw, E. (1996) ‘Reconstructing citizenship, the re-scaling of the state and the new authoritarianism: closing the Belgian mines’, Urban Studies, vol 33, pp1499–1521 Taylor, P. J., Catalano, G. and Walker, D. R. F. (2002) ‘Measurement of the world city network’, Urban Studies, vol 39, pp2367–2376 Verhetsel, A. and Sell, S. (2009) ‘World maritime cities: from which cities do container shipping companies make decisions?’, Transport Policy, vol 16, pp240–250 Wall, R. S. (2009) ‘The relative importance of Randstad cities within comparative worldwide corporate networks’, Tijdschrift voor Economische en Sociale Geografie, vol 100, pp250–259

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Iberian Cities Simón Sánchez Moral

The Iberian city network consists of two distinct urban systems. There seems to be a mismatch between Spanish and Portuguese cities, according to the hierarchical levels defined by their attractiveness and functionality. The Iberian city network is led by seven big urban areas, including the three metropolises of international renown (Madrid, Barcelona and Lisbon) and four regional metropolises (Valencia, Seville, Porto and Bilbao). These urban areas contain 31.9 per cent and 33.5 per cent of Spain and Portugal’s populations, respectively. In Spain it is necessary to consider the existence of other urban agglomerations throughout the country, while in Portugal the paucity of medium sized cities, up to 500,000 inhabitants, explains the strong concentration of the population in the metropolitan areas of Lisbon and Porto. In a general context of weak functional integration between both national urban systems, the described structure encourages certain competition among Iberian cities. For example, Madrid, a recognized world city of the second order, is considered by some as a threat not only to Barcelona but also to Lisbon, given its increased international dominance in this new globalization phase of the world economy. In addition Lisbon, while prevailing within its national territory, competes with other less populous Spanish metropolises. The recent evolution of Iberian cities is shaped by an intense economicterritorial restructuring process, associated with globalization and technological change. Under these circumstances, opinion about the role of cities as relevant actors in the global economy and the increasing competition among the rest of the European capitals has dominated Iberian urban policies and strategies (Méndez, 2008). Despite this, the empirical knowledge has not advanced in parallel, necessitating a deeper understanding of the integration process of Iberian cities into the world city network and the differences of the phenomenon compared with other European countries. Certainly the capital cities, especially Madrid, have for years monopolized the academic debate to focus on their world city status (often using attribute instead of relational data).

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Furthermore, Iberian cities have only marginally been considered within the international research on world cities, as shown by a review of the main published works during the 1990s. Madrid is mentioned in only eight of the 17 reviewed works, Barcelona in three, Lisbon in one, and none of the rest of the Iberian cities are mentioned (Taylor, 2004). However, thanks to the Globalization and World Cities (GaWC) Research Network this deficit has been partially mitigated. Keeping in mind the methodological differences of the research based on the study of global office networks of advanced business services, the prior empirical evidence on Spanish and Portuguese cities can be summarized in three general conclusions: 1

2

3

The first relates to the unequal position of Iberian cities within the world urban hierarchy, with Madrid the only city over the threshold arbitrarily set at 60 per cent of the connectivity compared to London and New York. The Spanish capital is considered as a major global service centre for key sectors of advertising, accounting, banking-finances and legal services (Beaverstock et al, 2000). The second relates to the more recent ranking of Madrid as the tenth placed city in global connectivity, because the service companies in Madrid are better connected than service companies in most other cities (Taylor et al, 2002). Moreover, in a general context of an increasing concentration of advanced services in leading world cities, the net connectivity gains of Madrid are confirmed against the losses of neighbouring cities, such as Lisbon or Barcelona (Taylor et al, 2003). The third relates to how the roles of Iberian cities vary along the world city network configurations in an early clustering analysis (Taylor et al, 2002). In this study, Madrid is classified within the nucleus of a ‘global route arena’ (intercontinental linkages) that includes second-order European cities and big Latin American cities. Its function as a connection node between both regions, historically supported by cultural factors, reflects the current orientation of Madrid’s financial services towards cities of Latin America and the ‘Third World’ in general (Taylor et al, 2002). Barcelona is also classified within this cluster, but as a hybrid member presenting some characteristics similar to the group of European financial centres (Paris, Frankfurt, Brussels) connected with the great banking cities of Asia Pacific (Tokyo, Hong Kong and Singapore). The rest of the Iberian cities are hybrid members of several ‘European urban arenas’ of national scope that, unlike the main economies of the continent (Germany, United Kingdom and France), do not constitute a specific cluster.

After this short review, an updated diagnosis is presented based on the new data covering 175 firms across 525 cities (see Chapter 1). According to Table 34.1, which shows the network connectivities of Spanish and Portuguese cities, only seven Iberian cities reach a global network connectivity above 0.05 (proportionally to the maximum connectivity of London). Their order within

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the table suggests the influence of position in the respective urban systems rather than population size.

Table 34.1 Global network connectivity of Iberian cities. RANK

CITY

1 2 3 4 5 6 7

Madrid Lisbon Barcelona Porto Valencia Seville Bilbao

GROSS CONNECTIVITY 62,599 49,831 40,866 20,536 11,972 10,440 9028

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.65 0.52 0.42 0.21 0.12 0.11 0.09

In accordance with the evidence presented previously, Madrid leads the connectivity of Iberian cities with nearly two-thirds of the highest global network connectivity observed. This finding is consistent with the city’s recent growth, which is relevant at a European scale. The leadership of Madrid as the centre of the Spanish economy is based upon its status as political capital and also reflects an increasing specialization in advanced tertiary activities (OECD, 2007). Indeed, in 2006 the metropolitan region housed more than 56 per cent of the foreign financial services groups located in Spain (among them HSBC, BNP Paribas and Citigroup) and close to 45 per cent in advanced business services (including the offices of leading firms such as Ernst & Young, KPMG, PWC, Deloitte and Allianz). In addition, the two biggest Spanish banks are from Madrid, namely Banco Santander Central Hispano (BSCH) and Banco Bilbao Vizcaya Argentaría (BBVA). Well aware of the importance of these activities, Madrid is developing an intense business cluster strategy, including promoting the real estate market and the related services of international fairs (Cuadrado-Roura and Rubalcaba-Bermejo, 1998; Sánchez Moral et al, 2008). Lisbon, a fair distance behind Madrid in the connectivity ranking, leads the growth of Portugal, housing the main political decision centres, the headquarters of the biggest business firms and high-value service activities. Despite being the only Portuguese city included within the OECD list of the 78 bigger metropolitan regions, Lisbon would need a substantial effort to improve its international projection (OECD, 2008). Barcelona, third in the ranking, is the other half of the traditional dual primacy pattern of the Spanish urban system, always striving to escape from the shadow of Madrid as the dominant local world city. Although competition with Madrid to attract big companies, economic institutions or international organizations seems to favour the Spanish capital as the place to locate

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nowadays, Barcelona has developed a successful urban development model. This reinforces its attractiveness for national and international advanced services firms (e.g. the recent success in attracting the R&D centre of the insurance multinational, Zurich). This model uses design and culture as the core of the urban transformation, pursuing the creation of an environment of quality for a cluster of knowledge-based industries. All the evidence suggests that these three big metropolises act as ‘classic gateway cities’ of contemporary globalization, connecting their respective national economies to the world economy (Taylor, 2004). Below them, there is a gap in the global connectivity rates of the regional metropolises, headed by Porto. This Portuguese city displays lower demographic and economic dynamism than Lisbon, as well as a different sector profile. Indeed, the main characteristic of this polycentric urban metropolis along the littoral corridor is the important activity of manufacturing firms. Despite the technological intensity and exporting propensity of many of them, the impact of these firms from the perspective of the integration of the urban area of Porto within the world city network is less relevant. The best way to approach the rest of the Iberian cities is through the alternative analysis of ‘localism’, which captures the relative concentration of domestic connections within the country (Table 34.2). Such concentration rises significantly in Bilbao, Seville, Valencia and Porto, second order metropolises displaying a certain international projection but mainly dealing with articulation at the regional level of the territory and the economy. Despite their industrial restructuring (or decline) in the recent past and the different local responses (including in some cases an orientation towards a so-called creative economy), all these cities still represent important economic centres, where advanced business services are accessible for their own industrial agglomeration and a significant part of the national territory.

Table 34.2 Localism (relative concentration of connections within Iberia). RANK

CITY

1 2 3 4 5 6 7

Bilbao Seville Valencia Porto Barcelona Lisbon Madrid

LOCALISM 0.67 0.61 0.53 0.20 −0.04 −0.30 −0.63

On the other hand, the ‘localism’ data confirm the initial diagnosis about the existence of two different urban systems, led by the only two metropolises, Madrid and Lisbon, that could be considered ‘un-local’ (negative values in the

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table). In Barcelona, only slightly negative on this score, the weight of domestic connections continues to be more important than in these two other leading cities. We conclude the analysis by looking at two additional measures that allow differentiation between the geographic orientations of network connections. The ‘traditional globalism’, calculated as the relative concentration of connections with New York and London (NYLON), the two global cities par excellence (Sassen, 2001), confirms the increase in distance between Madrid and the rest of the Iberian cities, and with Barcelona surpassing Lisbon. Porto, the second Portuguese city, drops down from its position to the level of the less populated regional Spanish metropolises (negative values in Table 34.3).

Table 34.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7

Madrid Barcelona Lisbon Seville Porto Valencia Bilbao

TRADITIONAL GLOBALISM 0.67 0.15 0.12 −0.42 −0.51 −0.55 −0.66

Table 34.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7

Madrid Lisbon Barcelona Valencia Seville Porto Bilbao

NEW GLOBALISM 0.71 0.15 0.04 −0.30 −0.35 −0.53 −0.60

In summary, a ‘national factor’ seems selectively to benefit the connections of Spanish cities with the leading centres of the global economy. Such connections in the case of Portuguese cities are less relevant, as well as those with the new economic centre of gravity represented by the Chinese cities of Beijing, Hong Kong and Shanghai. The values of ‘new globalism’ in Table 34.4 highlight an even greater dominance of Madrid in articulating the flows in this area,

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significantly ahead of Lisbon. Barcelona is only very weakly positive on this measure (it is clearly penalized by this new criterion compared with the other two big metropolises). The rest of the Iberian cities display negative values, from Valencia to Bilbao, relegated to last position.

References Beaverstock J. V., Smith, R. G., Taylor, P. J., Walker, D. R. F. and Lorimer, H. (2000) ‘Globalization and world cities: some measurement methodologies’, Applied Geography, vol 20, pp43–63 Cuadrado-Roura, J. R. and Rubalcaba-Bermejo, L. (1998) ‘Specialization and competition amongst European cities: a new approach through fair and exhibition activities’, Regional Studies, vol 32, pp133–147 Méndez, R. (2008) ‘El territorio de las nuevas economías metropolitanas’, EURE – Revista Latinoamericana de Estudios Urbano Regionales, vol 33, pp51–67 OECD (2007) OECD Territorial Reviews: Madrid, Spain, OECD, Paris OECD (2008) OECD Territorial Reviews: Portugal, OECD, Paris Sánchez Moral, S., Calatrava Andrés, A. and Melero Guilló, A. (2008) ‘Las funciones comando de Madrid en la economía global: una aproximación a través del proceso de atracción de capital extranjero’, EURE – Revista Latinoamericana de Estudios Urbano Regionales, vol 34, pp25–44 Sassen, S. (2001) The Global City: New York, London, Tokyo, 2nd edition, Princeton University Press, Princeton, NJ Taylor, P. J. (2004) World City Network: A Global Urban Analysis, Routledge, London Taylor, P. J., Catalano, G. and Gane, N. (2003) ‘A geography of global change: cities and services, 2000–2001’, Urban Geography, vol 24, pp431–441 Taylor, P. J., Catalano, G. and Walker, D. R. F. (2002) ‘Measurement of the world city network’, Urban Studies, vol 39, pp2367–2376

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35

Southern African Cities Ronald S. Wall

The African continent represents a vast area of the globe. It is three times the size of the US and its population of 800 million people is nearly equal to that of the Americas. There are 54 nations with over 1000 different languages and cultures. Yet despite its rich diversity, Africa is often treated as a monolith in which the tendency is to over-generalize Africa’s development (Chazan et al, 1999; Tordoff, 2002). Although it is true that certain common factors do exist, such as the universality of colonialism and the preponderance of underdevelopment, this obscures important regional distinctions. As noted by Chris Allen (1995, p302), ‘there are many Africas’, and in this light Southern Africa is one of the areas of the African continent that warrants systematic treatment as a region – not merely as a geopolitical division but more importantly as a socioeconomic construction (MacLean, 1999). Several traits can be identified concerning the Southern African region: 1

2

3 4

The existing states all share a common colonial and postcolonial history. The region was originally colonized by the Dutch and Portuguese – however, except for Angola, Mozambique and Namibia, the majority of this territory had been under British imperial rule towards the end of the 19th century. In fact, of the seven Southern African nations, five were governed by Britain. The English linguistic, legal, political and economic heritage prevails to this day. Colonialism lasted longer in this region than in any other – where Angola, Mozambique, Zimbabwe, Namibia and South Africa had to resort to armed struggle to finally attain independence. A disproportionate share of the wealth and productive capacity in this region is owned and controlled by the white minority. The Khoisan and Bantu people of Southern Africa are still strongly interrelated, socially, politically and culturally (Bauer and Taylor, 2005), despite the fact that colonialism had led to the imposition of arbitrary boundaries which divided ethnic groups across colonial borders. The interactions between people of different Southern African countries are

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6

319

particularly due to a region-wide migrant labour system, especially in the mining industries and for the pursuit of educational opportunities. Liberation struggles have also fostered a strong interconnectedness between people and states of the region. For instance, countries such as Angola, Mozambique and Zambia, which gained independence first, became havens in the 1970s and 1980s for rebel movements that attempted to end white minority rule in South Africa, South West Africa (Namibia) and Rhodesia (Zimbabwe). The democratic transition of the Southern African region has been without any military coup, making this region truly exceptional on the continent in this regard (Bauer and Taylor, 2005).

In terms of economy, considerable variation exists among African countries in this region, stemming from various factors: population size differences (e.g. South Africa has 45 million and Namibia and Botswana have less than 2 million people); resource endowments (e.g. Botswana, Namibia and South Africa have diamonds and other precious minerals while other countries are particularly dependent on agriculture); Zimbabwe, Zambia, Malawi and Botswana are landlocked while other countries have extensive coastlines. In 2001 the GDP per capita in the region ranged from US$570 in Malawi to US$11,290 in South Africa (UNDP, 2003). However, when combined, the neoliberal economies of this region are the strongest of the continent, exemplified by the powerful Southern African Development Community (SADC), which is considered to be the most viable economic regional community in Africa (McCarthy, 1999). Of the 11 Sub-Saharan cities with a network connectivity above 0.1 (Chapter 12, Table 12.1), six are found in the Southern African region (Table 35.1). The remaining five cities (Nairobi, Lagos, Port Louis, Accra and Dar es Salaam) are scattered across the remainder of the continent, clearly showing that no other significant regional entities exist (in terms of producer services). Four additional ‘regional’ cities with a global network connectivity lower than 0.1 – Pretoria (South Africa), Maputo (Mozambique), Windhoek (Namibia) and Blantyre (Malawi) – are included in Table 35.1. Combined, these cities only reach a global connectivity comparable to that of Cape Town (second in the list). Blantyre and Maputo are completely dependent on agricultural production, which explains their weakness in global connectivity. Windhoek, although very rich in diamonds and uranium, scores poorly in connectivity. This is arguably due to its small population and because its mining industry is mainly in the hands of the white minority. Pretoria, the de facto national capital of South Africa, ranks seventh in the list. This is not surprising seeing that this city serves mainly as the executive and administrative centre of South Africa, thereby distinguishing itself from the nearby economic powerhouse of Johannesburg. The global connectivities of the remaining six cities have been discussed previously: Johannesburg is by far the most connected African city and is a world player; in Southern Africa, only Cape Town is also strongly

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linked into the world city network (see Chapter 12). Lastly, it is interesting to note that of the ten Southern African cities listed, eight are of formerly British rule, and have all been members of the Commonwealth. From this it is evident that the strong historic ties (path dependency) with London especially (which has been a global core city for at least two centuries), has been highly influential to the development of this region. In this context, we see in Table 35.3 the relative connectivity of Southern African cities to New York and London (NYLON). In this, it is clear that Johannesburg claims the lion’s share of connectivity to the NYLON dyad, followed at a distance by Harare, Cape Town, Gaborone and Lusaka. It is particularly interesting that Harare (formerly Salisbury, Rhodesia), which is relatively far poorer than Cape Town and Gaborone, scores high – underlining its continued dependence on London, despite the fact that it has given up its Commonwealth membership. It is also clear that landlocked cities such as Johannesburg, Harare and Gaborone play an important role in the producer service sector, and thereby show that this industry is not necessarily dependent on the vicinity of maritime ports. Inversely, we see that Durban and Maputo, the biggest ports in Africa, play marginal roles within the service industry. The remaining cities reveal an under-representation of global connectivity, in which their role, as will be shown later, is more at an intraregional and local level.

Table 35.1 Global network connectivity of Southern African cities. RANK

CITY

1 2 3 4 5 6 7 8 9 10

Johannesburg Cape Town Lusaka Durban Gaborone Harare Pretoria Maputo Windhoek Blantyre

GROSS CONNECTIVITY 41,541 24,814 12,199 11,984 11,140 11,062 7764 7376 6466 5675

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.43 0.26 0.13 0.12 0.12 0.11 0.08 0.08 0.07 0.06

Where Table 35.3 reveals Southern African connectivity to previous globalism, Table 35.4 depicts the connectivity of this region to the emerging globalizing cities of China, in particular Beijing, Hong Kong and Shanghai. China has prioritized Africa as a strategic partner at both the political and economic level (SARWATCH, 2009), and in the Southern African region, China is viewed as the new ‘economic messiah’ – in a world where African governments are

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increasingly perceptive of the patronizing attitudes of the west (Muchena, 2009). China is said to be taking great advantage of this resentment and is presenting itself as an alternative. In Table 35.4, we see that Johannesburg and Harare are ranked first and second as before, on this occasion in terms of global connectivity to Chinese cities. Most striking is that Johannesburg has an exceptionally strong connectivity to Chinese cities (higher than for NYLON), which is historically new and was most certainly not the case during the apartheid regime. This is not surprising, considering the huge mineral reserves of South Africa (i.e. the producer services related to this), its gateway function to the rest of the Southern African region and its resentment towards western patronization (Muchena, 2009). Similarly, we see Zimbabwe’s mineral importance to China in the table, although at a far more moderate level. This reflects Zimbabwe’s ‘Look East’ policy and the related suspicion towards former colonial powers. In terms of producer services, it is clear that seven of the ten cities are strongly under-represented (scores below −0.25) as partners to Chinese cities. From this it is arguable that these under-represented cities play a more resource-oriented role to China – a country marked by its huge appetite for Southern African raw materials. Nonetheless, it is not only China that is benefiting from this. China’s demand for resources has driven up prices, propelling significant gains in many countries. China has educated thousands of African students, provided a large amount of medical assistance and has rehabilitated infrastructure and provided communications, which has led to the opening-up of large parts of Southern Africa. Alternatively, it can also be said that China’s investments are solely intended to gain diplomatic leverage over its client states. Whichever way we look at it, China’s geopolitical influence in Africa will have significant long-term consequences for the economic evolution of Southern African cities – and in turn upon the increase of connectivity between these regions.

Table 35.2 Localism (relative concentration of connections within Southern Africa). RANK

CITY

1 2 3 4 5 6 7 8 9 10

Windhoek Harare Gaborone Lusaka Durban Maputo Cape Town Pretoria Blantyre Johannesburg

LOCALISM 1.70 1.61 1.25 1.24 1.08 1.06 0.68 0.63 0.47 −0.16

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Table 35.2 reflects the relative level of connectivity between cities within the Southern African region. Johannesburg is the only city with a negative score; clearly cities that are more global are not necessarily equally strong in terms of local connectivity. Blantyre, Cape Town and Pretoria are the least locally orientated cities for seemingly different reasons: outer regional location, more global links and national responsibilities, respectively. In contrast, we find moderately connected cities such as Windhoek, Harare, Lusaka and Gaborone being more locally oriented.

Table 35.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6 7 8 9 10

Johannesburg Harare Cape Town Gaborone Lusaka Windhoek Durban Maputo Blantyre Pretoria

TRADITIONAL GLOBALISM 0.35 0.11 0.05 −0.05 −0.23 −0.34 −0.52 −0.53 −0.68 −0.71

Table 35.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6 7 8 9 10

Johannesburg Harare Cape Town Gaborone Durban Windhoek Lusaka Maputo Pretoria Blantyre

NEW GLOBALISM 0.42 −0.05 −0.12 −0.27 −0.50 −0.56 −0.57 −0.83 −0.91 −1.02

To conclude, it is clear from this study that Southern African cities play different global, regional and local roles within the region and the world economy. In this light, it is interesting to speculate whether increased connec-

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tivity between the Southern African region and China (and other Asian nations) will lead to prosperity for these cities, and whether the peripheral status of this region (Wallerstein, 1979; Castells, 1998) can be broken – or whether African cities will once again be at the mercy of a new colonizer from the north.

References Allen, C. (1995) ‘Understanding African politics’, Review of African Political Economy, vol 22, pp301–320 Bauer, G. and Taylor, S. (2005) Politics in Southern Africa: State and Society in Transition, Lynne Rienner, Boulder, CO Castells. M. (1998) End of Millennium, Blackwell, Oxford Chazan, N., Lewis, P., Mortimer, R., Rothchild, D. and Stedman, S. J. (1999) Politics and Society in Contemporary Africa, 3rd edition, Lynne Rienner, Boulder, CO MacLean, S. J. (1999) ‘Peacebuilding and the new regionalism in Southern Africa’, Third World Quarterly, vol 20, pp943–956 McCarthy, C. L. (1999) ‘Polarised development in a SADC free trade area’, The South African Journal of Economics, vol 67, pp211–220 Muchena, D. T. (2009) ‘China in Southern Africa’, OPENSPACE, vol 2, no 4, pp27–30 SARWATCH (2009) China and Southern Africa: Resource Management for Economic Development, www.sarwatch.org, accessed 10 March 2010 Tordoff, W. (2002) A History of Africa, Routledge, London UNDP (2003) Human Development Report 2003, Oxford University Press, New York Wallerstein, I. (1979) The Capitalist World-Economy, Cambridge University Press, Cambridge

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36

Central American Cities Ed Brown, Francisco Castañeda, Jon Cloke and José Luis Rocha Gómez

It will come as no surprise to most observers of Central American affairs that the cities of the region are, by and large, still relatively poorly connected to the global economy, at least in terms of the connectivity indicators used in this chapter. This should not, however, be taken to infer that Central American economies are somehow autarchic or inward-looking. Far from it. In fact, the region has long had a very strongly externally oriented economy, based traditionally upon the exportation of a limited number of primary commodities although more recently tourism, non-traditional agricultural exports and light industrial exports have become important, as have remittances from Central American migrants living outside the region (Robinson, 2003; Orozco, 2005; Sánchez-Ancochea, 2008). Nevertheless, while Central America continues to be a largely externally driven economy, its cities in general remain less well connected into the network of global cities formed through the offices of major advanced producer service firms than is the case for other parts of Latin America (see Chapter 14). However, the global ranking data for the Central American cities do show that this situation is changing rapidly, and the region’s cities have been moving up the global connectivity rankings between 2000 and 2008, reflecting considerable processes of economic change over this period. For example, both Guatemala City and San José have broken into the top 100 most connected cities in the 2008 data (they were ranked 142 and 145 respectively in 2000) and even Managua has increased its ranking from 323 to 159. The fact that this has occurred during a period of continued intensification of global linkages worldwide confirms that the region has indeed seen significant processes that have served to accentuate regional connectivity to the global economy since the last survey was undertaken in 2000. To some degree at least, these changes reflect the impacts of the Central American Free Trade Agreement (CAFTA) which has even more firmly enmeshed the region into the global economy and the US economy in particular (Sánchez-Ancochea, 2008). Narrowly passed by the US senate in

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2005, gradually all of the Central American republics and the Dominican Republic have ratified and enacted DR-CAFTA (the last country to follow suit was Costa Rica where it finally came into force on 1 January 2009 following considerable unrest and dissent). As Cox (2008) explains, the passing of DRCAFTA was facilitated through a complex alliance of US state officials, US-based transnational firms with existing or potential interests in the region and Central American business elites and government officials committed to the liberalization agenda. For our purposes, what is important is that DRCAFTA has effectively opened up the final parts of Central America’s service sector to global competition and investment. The investor provisions in DR-CAFTA extend to the financial services and telecommunications sectors, where US-based firms have successfully lobbied for inclusion of an easing of investment laws that will give greater access to USbased transnational corporations. Banks and insurance firms will have full rights to establish subsidiaries, joint ventures and branches in the region. Provisions target the restrictions that exist in Central America, including ‘barriers to foreign insurance companies in Guatemala; heavy regulation licensing of foreign professionals in Honduras; local partner requirement in some financial services in Nicaragua; and numerous service monopolies in Costa Rica’ (Cox, 2008, p13). Thus, it is likely that the coming years will see continued growth in the presence of global producer service companies in the region, and the competition between the cities of the region (and their political elites) to attract them will be intense. This has already been witnessed in the rapid changes experienced in the financial sector over the previous decade. When we conducted some exploratory research on the region back in 2000, we found a financial sector that was basically organized nationally, where connectivity into the global financial network was facilitated via a myriad of correspondence bank relationships largely, but not exclusively, focused around Miami (Brown et al, 2002). Today the financial sector across Central America has experienced considerable, although by no means complete, globalization. A Fitch ratings banking outlook study in November 2007 drew attention to the ongoing process of consolidation of Central American banks as they have sought to adjust to these new circumstances. It also highlights significant penetration by foreign banks which has been concentrated in Panama, Costa Rica, and particularly in El Salvador where three foreign banks (Bancolombia, Citigroup, and HSBC Group) controlled two-thirds of the industry’s assets in June 2007 (Fitch Ratings, 2007). Table 36.1 shows the overall level of global network connectivity of each of the six Central American cities found to have an overall level of proportionate connectivity of over 0.05. These cities comprise six of the seven Central American capital cities (the exception is Belmopan of Belize reflecting its small size and relative isolation, unless we count the sizeable tourist industry). The fact that no country has more than one city exhibiting this level of network connectivity reflects the small size of the Central American republics, the dominance of their capital cities and their generally weak level of integration

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into the circuits of the world city network. Even San Pedro Sula, often talked of as the real economic capital of Honduras (and the only non-capital city in Central America to have an airport), does not appear in the data. The results provide no real surprises; although given Panama City’s status as an offshore financial centre the fact that its overall connectivity is not higher and only 0.03 above that of its nearest competitors, Guatemala City and San José, is somewhat surprising and perhaps reflective of the lack of investment on the part of the Panamanian state in developing its workforce and modernizing its business environment over recent years.

Table 36.1 Global network connectivity of Central American cities. RANK

CITY

1 2 3 4 5 6

Panama City Guatemala City San José San Salvador Tegucigalpa Managua

GROSS CONNECTIVITY 27,541 24,824 24,574 20,485 18,454 15,345

PROPORTIONATE CONNECTIVITY (1.00 = LONDON) 0.29 0.26 0.26 0.21 0.19 0.16

If anything, while it remains the most connected city in Central America, Panama City has been losing ground to some of its regional rivals. Thus, in the 2000 data Panama City was 79th in the list of global cities and the next closest regional city was Guatemala City at 131. Similarly, back in 2000, the level of global connectivity for Panama City was significantly above that of the other regional cities (0.26 as opposed to 0.18 for Guatemala City and San José). Nevertheless, if we look at the figures for Panama City in the context of the rest of Latin America we find that its position is relatively constant. Thus, Panama City is ranked as the 9th most connected city in the 2000 data and the 10th most connected in the 2008 data (it has been overtaken by Lima over this period). Over the same period, Guatemala City and San José have both risen by one ranking, perhaps reflecting the fact that the rest of the region has gradually been catching up with Panama City’s previously considerably higher level of integration. It may also be true that Panama’s relatively slower growth of connectivity between 2000 and 2008 may reflect the fact that Panama has not played a major role in the rapid regional integration that has taken place over that period, and did not join the rest of the region in seeking a regional trade agreement with the US. (A bilateral agreement with Panama failed to gain approval from the US senate during the Bush presidency and is unlikely to be pursued strongly by the Obama administration: see Tharin (2009) for a critical analysis.)

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The relative position of each of the cities remains as it was when the previous connectivity exercise was conducted in 2000. Within this overall situation, it is worth highlighting that while San Salvador’s relative position in the rankings of Central American cities remains the same, its proportionate connectivity has fallen somewhat in the sense that, although in 2000 its level of connectivity was only 0.01 behind that of San José and Guatemala City (0.17 as opposed to 0.18), in 2008 it is 0.05 behind that of the other two cities (0.21 as opposed to 0.26). Tegucigalpa and Managua continue to exhibit far lower levels of connectivity than the other cities, with Managua having only just over half of the proportionate connectivity of Panama City (0.16 as opposed to 0.29) although, as pointed out earlier, even Managua has risen considerably in the rankings of global cities. Table 36.2 shows measures of ‘localism’, the degree to which a city’s connectivity is dominated by links within the region. As can be seen, these results reverse the connectivity rankings in Table 36.1; thus the lowest figure is for Panama City. This suggests that relatively more of its connections are with the wider global economy and not with the other Central American cities (a factor which may have affected its slower growth in connectivity in comparison to the other Central American cities during this recent period of rapid regional integration). San José and Guatemala City also have relatively low scores suggesting a similar relative importance of global connections over regional ones. However, these cities still have key local links. For instance, in San José there has been a leading role played by Costa Rican companies in the regional integration process. This is related to the fact that Costa Rica has maintained a stronger form of regulation of its service sector than the other countries of the region (and with stronger controls on foreign investment), although this policy has been reversed gradually over recent years (Hoffman, 2008). This lay behind the bitter struggles over the ratification of DR-CAFTA within Costa Rica where the most controversial issue was the partial privatization of the energy and telecommunications sector.

Table 36.2 Localism (relative concentration of connections within Central America). RANK

CITY

1 2 3 4 5 6

Managua Tegucigalpa San Salvador San José Guatemala City Panama City

LOCALISM 0.66 0.59 0.54 0.38 0.25 0.17

Table 36.3 measures the connectivity orientation of Central American cities by assessing the degree to which their global connections are oriented towards

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New York and London (NYLON). The results show relative under-connection for all six cities. Unsurprisingly the two least globally connected, Managua and Tegucigalpa, have the weakest orientation towards NYLON, but it is the third least globally connected city, San Salvador, which is best connected to NYLON. The latter may have some connection to the dollarization of the Salvadoran economy, the specifics of US–Salvadoran migratory dynamics (i.e. the presence of a sizeable sector of Salvadoran immigrants in Long Island) and the more advanced opening of its financial sector in particular.

Table 36.3 Traditional globalism through NYLON (relative concentration of connections to New York and London). RANK

CITY

1 2 3 4 5 6

San Salvador Guatemala City Panama City San José Tegucigalpa Managua

TRADITIONAL GLOBALISM −0.20 −0.30 −0.32 −0.33 −0.34 −0.43

Table 36.4 shifts our attention away from the traditional NYLON-orientation towards connections with the major Chinese cities of Beijing, Shanghai and Hong Kong. These results mirror those of the previous table very closely, with all six cities recording negative scores. Once again, the least connected cities are Managua and Tegucigalpa. The Central American city with the strongest connections to the Chinese cities is once again San Salvador, but this time the second most connected city is Panama City (the latter perhaps reflecting the strongest historical ties to China given the relatively high levels of Chinese migration to Panama since the late 19th century).

Table 36.4 New globalism through the Chinese cities triad (relative concentration of connections to Beijing, Hong Kong and Shanghai). RANK

CITY

1 2 3 4 5 6

San Salvador Panama City Guatemala City San José Tegucigalpa Managua

NEW GLOBALISM −0.19 −0.26 −0.32 −0.37 −0.45 −0.50

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Perhaps the most interesting thing about the NYLON dyad and the Chinese triad results is that San Salvador is found to be the most connected Central American city in both cases and yet is only ranked fourth in the global connectivity figures given in Table 36.1. There may be several explanations for these results. It may be, for example, that San Salvador has a more diverse set of connections than the other Central American cities, which have retained a greater dependency on their traditional links (e.g. to Miami), or whose links have a greater regional concentration. To come to a satisfactory answer will require a greater complexity and breadth of analysis than we have been able to attempt here, but the findings we have presented here certainly provide us with some intriguing questions to explore through further research. One outstanding issue which we were unable to explore here but is clearly of considerable interest is the degree to which the strong connectivity ties between the Central American cities and Miami (Brown et al, 2002) have receded over the past eight years. The fact that Miami’s network connectivity has fallen significantly over the period of the two surveys (Miami experienced the second highest decline in connectivity between 2000 and 2008 of any city), during a period when overall network connectivity of Central American cities has been growing so rapidly, would suggest that Miami’s prominence within the connectivity networks of Central American cities may have been receding over this period.

References Brown, E., Catalano, G. and Taylor, P. J. (2002) ‘Beyond world cities: Central America in a global space of flows’, Area, vol 34, pp139–148 Cox, R. (2008) ‘Transnational capital, the US state and Latin American trade agreements’, Third World Quarterly, vol 29, pp1527–1544 Fitch Ratings (2007) ‘Press release: Fitch Central America: Banking outlook – new players in the field’, www.bnamericas.com/research_detalle.jsp?documento= 395863&idioma=I, accessed 10 March 2010 Hoffman, B. (2008) ‘Why reform fails: the “politics of policies” in Costa Rican telecommunications liberalization’, European Review of Latin American and Caribbean Studies, vol 84, pp3–19 Orozco, M. (2005) ‘Migration, money and markets: the new realities for Central America’, in D. F. Terry and S. R. Wilson (eds) Beyond Small Change: Making Migrant Remittances Count, Inter-American Development Bank, Washington, DC, pp193–217 Robinson, W. (2003) Transnational Conflicts: Central America, Social Change, and Globalization, Verso, London Sánchez-Ancochea, D. (2008) ‘State and society: the political economy of DRCAFTA in Costa Rica, the Dominican Republic and El Salvador’, in D. SánchezAncochea and K. C. Shadlen (eds) The Political Economy of Hemispheric Integration: Responding to Globalization in the Americas, Palgrave Macmillan, Basingstoke, pp171–200

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Tharin, M. (2009) ‘Free trade with Panama: some winners and some losers’, Council on Hemispheric Affairs, www.coha.org/2009/05/the-panama-free-trade-agreementseparating-fact-from-fiction-and-the-good-from-the-bad, accessed 10 March 2010

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Global Synthesis

National and Sub-Regional Contrasts Peter J. Taylor

The chapters on countries and sub-regions have each told a separate story that relates the statistics to the context and history of particular sections of the world city network. What emerges is the diversity of city patterns in terms of general connectivities, localism and orientations towards NYLON and the emerging Chinese city triad. In this final conclusion the statistical results are compared between countries and sub-regions to provide an overview of the geography of the world city network in these key dimensions. At the national scale the discussion of urban hierarchies has focused upon the distribution of cities, usually measured by population size, in terms of how ‘vertical’ or ‘horizontal’ they appear. A vertical distribution is where one city, usually called the ‘primate city’, dominates. The dominance of the UK and France by London and Paris are classic examples of this primate city process. A more horizontal distribution results from there being several important cities in a country with no one of them dominating. Germany is often quoted as having such a patterning of cities and Chinese cities are similarly disposed. The results showing the global network connectivities have been presented as ranks and indicate different vertical and horizontal distributions that are generally in line with the traditional national urban ‘hierarchies’: connectivity within the world city network broadly adheres to the importance of a city within its country. To compare these results the ratio of connectivity between the two top-ranked cities in each country has been computed. This is a simple measure of primacy and is recorded in Table C.1(a). The results are reasonably predictable at the top with London, Paris and Tokyo each being more than four times more connected than their country’s second city. The fourth most primate country in connectivity is Mexico, and like the previous three countries, its capital city dominates. However in the remainder of the countries listed there are no capital cities that are first ranked: they are either ranked second (Delhi, Rome, Berlin and Beijing) or are outside the top two (Ottawa, Brasília, Washington, Canberra and Bern). Thus, perhaps surprisingly, capital

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cities are in a minority of the most connected cities in these 13 major countries; however where they are ranked first they are emphatically primate. The nonprimate distributions towards the bottom of the table are for countries with strong urban traditions of multiple cities as epitomized by the final three, Italy, Germany and China.

Table C.1 Primacy: connectivity ratios for top two cities. (a) By states. RANK

COUNTRY

CITIES

1= 1= 3 4 5 6 7 8 9 10 11 12 13

UK France Japan Mexico Canada Brazil USA Australia India Switzerland Italy Germany China

London/Manchester Paris/Lyon Tokyo/Osaka Mexico City/Guadalajara Toronto/Montreal São Paulo/Rio de Janeiro New York/Chicago Sydney/Melbourne Mumbai/Delhi Zurich/Geneva Milan/Rome Frankfurt/Berlin Hong Kong/Beijing

RATIO 4.47 4.47 4.44 2.34 2.11 1.80 1.73 1.63 1.46 1.44 1.30 1.27 1.22

(b) By sub-regions. RANK

COUNTRY

CITIES

1 2 3= 3= 5 6= 6= 8 9

Ex-Soviet Europe Southern Africa Iberia South East Asia Nordic Eastern Europe Arabian Gulf Benelux Central America

Moscow/Kiev Johannesburg/Cape Town Madrid/Lisbon Singapore/Kuala Lumpur Stockholm/Helsinki Warsaw/Budapest Dubai/Kuwait City Brussels/Amsterdam Panama City/Guatemala City

RATIO 1.94 1.67 1.26 1.26 1.25 1.15 1.15 1.13 1.11

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There has been less study of primacy for multi-state regions such as the nine cases studied above. The ratios of connectivities of the leading two cities in each sub-region are shown in Table C.1(b), and in contrast to the previous table, this one is dominated by capital cities: the only non-capitals are Cape Town and Dubai. As would be expected, with capital city functions distributed across states in each sub-region, there are no primacies at this level found in Table C.1(a). Hence, in the regional context, connections within the world city network are through multiple capital cities. And, in general, the larger the country the more likely it is that its capital city will feature in the table. This is very apparent with the top two primacy scores, where Russia and South Africa dominate their respective regions, so that their major cities are quite primate in nature. Other interesting cases are Singapore and Panama City, which are special cases of small countries: Singapore is a city-state whose city is a world regional centre; Panama City is an offshore financial centre in the smallest country of its region. Dubai is not the capital of the United Arab Emirates but it is the leading commercial centre of this major country of the Arabian Gulf coastal region. The ‘localism’ scores are difficult to compare because the sizes of countries and sub-regions vary: obviously in a large country with many cities the propensity for ‘internal’ connections may be accentuated by inclusion of ‘local’ firms in the analysis. The country most affected will be the US: it has most cities in its chapter and there are numerous US firms within the 175 on which this research is based. This is reflected in Table C.2(a) where the most ‘locally connected’ city in each country is listed with the US, represented by Palo Alto, far ahead of the other countries. In fact the top nine US cities for localism (Table 25.2) all score more than Xi’an, ranked second in this table, and the top 22 US cities have local scores higher than Hiroshima, ranked third here. This is another case of American exceptionalism in terms of US cities in the world city network. The remainder of the table tends to reflect country size but with the UK relatively highly ranked and Germany relatively lowly ranked. This may be related to their different levels of primacy, in particular the high connectivity of London. There is another more intriguing exception in the bottom rank: for Mexico, localness is relatively absent in connections to the world city network. This may reflect closeness to the US economy and US city servicing. Localism is much less evident in the multi-state sub-regions; see Table C.2(b). The highest localism is recorded for Eastern European and the ex-Soviet cities, the latter reflecting Moscow’s continuing dominance. Otherwise, localism scores are quite low, reflecting the inevitable economic openness traditionally found for smaller countries. In both sections of Table C.2 there are just five capital cities featured: Brasília and Bern in the first list, and The Hague, Managua and Abu Dhabi in the second. In each case their specialist political functions are reflected in relatively enhanced local economic connections.

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Table C.2 Localism: the cities with the most ‘local’ links. (a) By states. RANK

COUNTRY

CITIES

1 2 3 4 5 6 7 8 9 10 11 12 13

USA China Japan UK Brazil India Canada Australia Germany France Mexico Italy Switzerland

Palo Alto Xi’an Hiroshima Plymouth Brasília Cochin Halifax Hobart Dortmund Lille Chihuahua Trieste Bern

LOCALISM 15.27 10.98 8.23 6.75 4.38 3.18 3.13 2.36 1.87 1.83 0.95 0.82 0.78

(b) By sub-regions. RANK

COUNTRY

CITIES

1 2 3 4 5 6 7 8 9

Eastern Europe Ex-Soviet Europe Benelux Southern Africa South East Asia Nordic Iberia Central America Arabian Gulf

Skopje Novosibirsk The Hague Windhoek Labuan Gothenburg Bilbao Managua Abu Dhabi

LOCALISM 2.54 2.41 1.88 1.70 1.57 1.34 0.67 0.66 0.47

In Table C.3 the ‘globalization core’ orientations of the leading city in each country or sub-region are compared and contrasted. Remember these are relative measures showing over-linkage or under-linkage compared with what is expected in the world city network as a whole. Thus the vast majority of scores (39 of 41) in the table are positive: these leading cities are relatively over-connected to both New York/London and Beijing/Hong Kong/Shanghai. But there are important variations, and in Table C.3 the focus is upon the differences in orientations. The leading cities of countries (Table C.3(a)) and of sub-regions (Table C.3(b)) are ranked by difference between their NYLON and Chinese triad scores. In both parts of the table there is a general pattern of European leading cities being more NYLON orientated: they take the top four ranks in both parts of the table. Leading cities from the rest of the world are all more connected to the Chinese city triad. China’s neighbours (Japan and

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South East Asia) most favour the triad over NYLON. The intriguing finding is the strength of China’s lead over NYLON in both Canada and Australia, and among other emerging markets (Brazil, Mexico and India). Among the subregions, Southern Africa’s position as second only to South East Asia in favouring the triad is particularly noteworthy. Table C.3 provides an initial glimpse of the new eastern orientation in global geography.

Table C.3 Orientation: leading cities and the traditional and emerging core cities in the world city network. (a) By states. RANK

COUNTRY

LEADING CITY

1 2 3 4 5 6 7 8 9 10 – – –

Germany France Italy Switzerland Canada India Mexico Australia Brazil Japan USA* China* UK*

Frankfurt Paris Milan Zurich Toronto Mumbai Mexico City Sydney São Paulo Tokyo New York Hong Kong London

NYLON

1.29 1.04 0.61 0.51 0.49 0.32 0.25 0.56 0.44 0.87 – 0.87 –

BEIJING, DIFFERENCE HONG KONG, SHANGHAI 1.09 0.92 0.57 0.51 0.59 0.46 0.41 0.74 0.66 1.12 0.87 – 0.95

0.20 0.08 0.04 0.00 −0.10 −0.14 −0.16 −0.18 −0.22 −0.25 – – –

(b) By sub-regions. RANK

SUB-REGION

LEADING CITY

NYLON

1 2 3 4 5 6 7 8 9

Nordic Benelux Eastern Europe Iberia Ex-Soviet Europe Central America Arabian Gulf Southern Africa South East Asia

Stockholm Brussels Warsaw Madrid Moscow Panama City Dubai Johannesburg Singapore

0.61 0.70 0.49 0.67 0.68 −0.32 0.78 0.35 0.81

BEIJING, DIFFERENCE HONG KONG, SHANGHAI 0.41 0.63 0.43 0.71 0.73 −0.26 0.84 0.42 1.02

*US, China and UK include ‘core cities’ and therefore cannot be fully included in this table

0.20 0.07 0.06 −0.04 −0.05 −0.06 −0.06 −0.07 −0.21

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Postscript: Trends and Change Ben Derudder, Michael Hoyler, Peter J. Taylor and Frank Witlox

The different chapters in this book are based on cross-sectional data gathered in the first half of 2008. But the world city network is a very dynamic urban process, as the finance-led economic crisis of 2008–09 has only too clearly illustrated. Therefore we have added this postscript to our world survey so that the reader may be able to get both a feel for relatively recent change and a glimpse of where the effects of the current economic crisis may be leading. To these ends, we have included two extra elements for interpretation and discussion: 1

2

We compare the 2008 general connectivity results with the first world city network data collection in 2000 to show some key trends in city connectivities – which cities are becoming relatively more integrated into the network and which less so (Derudder et al, 2010a). We present some early analyses of the financial credit crunch and subsequent economic downturn that got underway just after the 2008 data collection. It will obviously be some years before the full effects are recorded in the world city network. However, we can begin to glimpse changes, especially in the financial sector, and we report some preliminary findings on the different fates of control and command centres in finance (Derudder et al, 2010b).

Trends in the Period 2000−2008 Data Our analysis of key trends in the period 2000−2008 is based on a systematic comparison of some of the city connectivities reported in this book with the connectivities computed on the basis of a similar data gathering carried out in the year 2000 for 315 cities and 100 firms (for details, see Taylor et al, 2002). Such a comparison of city connectivities over time requires a certain consistency in the data structure, and the following modifications were implemented to be able to compare the 2000 (315 cities, 100 firms) and 2008 (525 cities, 175 firms) measurements. In terms of cities, consistency is relatively straightforward. Global network connectivities (GNCs) were computed for the 307 cities that feature in both the

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2000 and the 2008 data. Of these 307 cities, we only retained the 132 cities with a global network connectivity of at least one-fifth of the most connected city in either year. GNCs were then recomputed, based on 132 cities and 175 firms for 2008, and 132 cities and 100 firms for 2000. In terms of firms, our main concern was that changes in the sectoral composition of the dataset might influence the results. For instance, there is larger relative weight of financial services firms in the 2008 data gathering, which may artificially boost the connectivity levels of clear-cut international financial centres such as New York when comparing unadjusted connectivity levels in 2000 with connectivity levels in 2008. To deal with this potential problem, we transformed connectivity measurements for 2000 to match the 2008 sectoral distribution (i.e. the weighting is given in the last column of Table PS.1).

Table PS.1 Sectoral distribution of GaWC data gatherings in 2000 and 2008. SECTOR Finance Accountancy Advertising Law Management consultancy

2000

2008

% 2008

34 18 15 16 17

75 25 25 25 25

42.9 14.3 14.3 14.3 14.3

Changing ranks, rising connectivity An initial overview of some of the major changes between 2000 and 2008 can be obtained by looking at: 1 2

changing ranks at the apex of the world city network; and changing average levels of connectivity in the world city network.

Table PS.2 presents an overview of the 20 cities with the largest global network connectivity in 2000 and 2008 based upon just the 132 cities common to both modified datasets. This leads to New York and London changing top position in 2008 (plus a few other minor changes in positions) compared to the results calculated for all 525 cities in Chapter 3 (Table 3.1). However this is based upon only small relative changes in levels of connectivity. Thus, a first notable feature of the geography of the world city network in this period is the stability of cities that are most integrated in the network: London, New York and Hong Kong remain the most connected cities, while Paris, Singapore and Tokyo follow, albeit with different rankings. The second notable pattern is the rise of Asian cities. Indeed, below the top six, there have been some major changes in the world city network with seven cities entering the 14 positions between 6 and 20: cities such as Los Angeles, Frankfurt and Amsterdam thereby lost out

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in favour of the likes of Shanghai, Beijing and Seoul in an ‘east–west swap’. The latter interpretation is reinforced when considering the overall make-up of the top 20: in 2000 this included five Northern American cities and five Asian cities, whereas in 2008 only three Northern American cities (New York, Toronto and Chicago) made the top 20 as opposed to nine Asian cities.

Table PS.2 Twenty most connected cities in the world city network in 2000 and 2008 (adjusted GNC for 132 cities). 2000

2008

RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

London New York Hong Kong Tokyo Paris Singapore Chicago Milan Madrid Los Angeles Sydney Frankfurt Amsterdam Toronto Brussels São Paulo San Francisco Zurich Taipei Jakarta

GNC 100.00 97.10 73.08 70.64 69.72 66.61 61.18 60.44 59.23 58.75 58.06 57.53 57.10 56.92 56.51 54.26 50.43 48.42 48.22 47.92

Cities that rise into the top 20 in 2008 22 23 27 28 29 30 37

Buenos Aires Mumbai Shanghai Kuala Lumpur Beijing Seoul Moscow

RANK

CITY

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

New York London Hong Kong Paris Singapore Tokyo Sydney Shanghai Milan Beijing Madrid Moscow Brussels Seoul Toronto Buenos Aires Mumbai Kuala Lumpur Chicago Taipei

GNC 100.00 99.32 83.41 79.68 76.15 73.62 70.93 69.06 69.05 67.65 65.95 64.85 63.63 62.74 62.38 60.62 59.48 58.44 57.57 56.07

Cities that fall out of the top 20 in 2008 46.81 46.81 43.95 43.53 43.43 42.32 40.76

21 22 25 28 31 40 46

São Paulo Zurich Amsterdam Jakarta Frankfurt Los Angeles San Francisco

55.96 55.51 54.60 53.29 51.58 45.18 41.35

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Connectivity change in the world city network is, however, much more than a matter of cities ‘rising’ or ‘falling’. This can be observed when considering Figure PS.1, which maps the geography of absolute connectivity change in the period 2000–2008 (cities are plotted in their approximate geographical position). In this period, 97 out of 132 cities witnessed connectivity gains. This quasi-general rise of connectivity indicates that the globalization of services has resulted in a dynamic and growing economic sector expanding offices in many cities and extending office networks to new cities in the period under investigation. In other words: although the NYLON dyad still dominates the network, the structure of the world city network has become more horizontal between 2000 and 2008, indicating a worldwide diffusion of globalization processes. The result has been an increasingly integrated world city network. Nonetheless, the regional pattern suggested in Table PS.2 is confirmed, with the majority of connectivity losses for Western European, Australasian and especially Northern American cities, and almost consistent connectivity gains in other parts of the world in general and in Eastern Europe and Pacific Asia specifically.

Most notable patterns of change Our final analysis of changes in the period 2000–2008 provides more details by considering which cities have witnessed the most important connectivity changes in relative terms. Although most cities have become more integrated in the office networks of leading service firms in this period, some cities have seen larger connectivity gains (or losses) than others. To examine this, we compute relative measures of connectivity change by systematically comparing a city’s absolute connectivity change (GNC2008–GNC2000) with changes in the overall connectivity distribution in the world city network. The result is a set of relative measures of change that can be interpreted as z-scores (for technical details see Derudder et al, 2010a). For instance, cities scoring more than 2 on this measure of relative connectivity change have witnessed exceptional connectivity gains compared to the rest of the world city network, while cities scoring 0 have witnessed a connectivity change equal to the average for the entire world city network. Figure PS.2 and Table PS.3 summarize this geography of relative connectivity change – the figure plots all 132 cities in their approximate geographical position, while the table features the ten cities that have witnessed the largest changes (both positive and negative). Once again, the relative decline of Western European, Australasian and especially Northern American cities becomes very clear, with not a single city in Northern America keeping up with the overall level of change in the rest of the world city network. The ten cities with the largest connectivity decline are all located in Northern America (including two offshore banking centres) and Germany. Shanghai, Beijing, Moscow and Seoul are the cities that have witnessed the largest connectivity gains. Interestingly, this suggests that although all major Chinese cities have

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become more integrated in the world city network, Beijing and Shanghai do seem to increasingly function as the major gateways between China and the world economy (alongside Hong Kong) (see Lai, 2009).

Figure PS.1 Absolute connectivity change in 2000–2008. Note: City codes: AA Amman, AD Adelaide, AK Auckland, AL Almaty, AM Amsterdam, AN Antwerp, AS Athens, AT Atlanta, BA Buenos Aires, BB Brisbane, BC Barcelona, BD Budapest, BG Bogotá, BJ Beijing, BK Bangkok, BL Berlin, BM Birmingham, BN Bangalore, BR Brussels, BS Boston, BT Beirut, BU Bucharest, BV Bratislava, CA Cairo, CC Calcutta, CG Calgary, CH Chicago, CN Chennai, CO Cologne, CP Copenhagen, CR Costa Rica, CS Casablanca, CT Cape Town, DA Dallas, DB Dublin, DH Doha, DS Düsseldorf, DT Detroit, DU Dubai, DV Denver, ED Edinburgh, FR Frankfurt, GN Geneva, GT Guatemala City, GU Guadalajara, GY Guayaquil, GZ Guangzhou, HC Ho Chi Minh City, HK Hong Kong, HL Helsinki, HB Hamburg, HM Hamilton, HS Houston, IS Istanbul, JB Johannesburg, JD Jeddah, JK Jakarta, KL Kuala Lumpur, KR Karachi, KU Kuwait City, KV Kiev, LA Los Angeles, LB Lisbon, LG Lagos, LJ Ljubljana, LM Lima, LN London, LX Luxembourg, LY Lyon, MB Mumbai, MC Manchester, MD Madrid, ME Melbourne, MI Miami, ML Milan, MM Manama, MN Manila, MP Minneapolis, MS Moscow, MT Montreal, MU Munich, MV Montevideo, MX Mexico City, NC Nicosia, ND New Delhi, NR Nairobi, NS Nassau, NY New York, OS Oslo, PA Paris, PD Portland, PE Perth, PH Philadelphia, PL Port Louis, PN Panama City, PR Prague, QU Quito, RI Riga, RJ Rio de Janeiro, RM Rome, RT Rotterdam, RY Riyadh, SA Santiago, SB St Petersburg, SD San Diego, SE Seattle, SF San Francisco, SG Singapore, SH Shanghai, SJ San José, SK Stockholm, SL St Louis, SN Santo Domingo, SO Sofia, SP São Paulo, SS San Salvador, ST Stuttgart, SU Seoul, SY Sydney, SZ Shenzhen, TA Tel Aviv, TK Tokyo, TL Tallinn, TP Taipei, TR Toronto, VI Vienna, VN Vancouver, WC Washington DC, WL Wellington, WS Warsaw, ZG Zagreb, ZU Zurich

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Figure PS.2 Relative connectivity change in 2000–2008. Note: For city codes, see figure PS.1

Table PS.3 Major positive/negative values for relative connectivity change in 2000–2008. Major negative changes Los Angeles Miami San Francisco Cologne St Louis Montreal Nassau Hamilton (Bermuda) Düsseldorf Frankfurt

SRESID −2.52 −2.31 −1.91 −1.76 −1.74 −1.73 −1.68 −1.63 −1.63 −1.48

Major positive changes Shanghai Beijing Moscow Seoul Rome Tel Aviv Bucharest Riyadh Kuwait City Kuala Lumpur

SRESID 2.76 2.64 2.62 2.12 1.89 1.84 1.44 1.39 1.38 1.37

Changes in the Context of the Financial Crisis Data The relative decline of Western cities and the concomitant rise of Asian (and particularly Chinese) cities is, as we have seen, perhaps the single most fundamental pattern emerging out of our analysis of trends in the period 2000–2008. It has frequently been suggested that the world economy is in the

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midst of a major geographical transformation from ‘West’ to ‘East’ (e.g. Frank, 1998; Arrighi, 2007), and these changes suggest that this shift is indeed unfolding in terms of urban connectivity. Interestingly, it is sometimes suggested that the recent financial crisis has been acting as a major catalyst for this larger geo-economic sea change. Although it is too soon to systematically assess changes in the world city network and the geography of command and control centres, we can begin to glimpse changes by focusing on key indicators of the performance of the world’s leading banks headquartered in the leading control and command centres in finance (Derudder et al, 2010b). We use data taken from The Banker’s annual list of the world’s 1000 leading banks, specifically those reported in the July 2008 and July 2009 issues (The Banker, 2008, 2009). These summarize the performances of the world’s leading banks in 2007 and 2008, respectively. The Banker selects banks each year based on levels of Tier 1 capital, the core measure of a bank’s financial strength from a regulator’s point of view: Tier 1 capital is the shareholders’ equity available to cover actual or potential losses and is composed of core capital. This consists primarily of common stock, disclosed reserves and retained earnings. However, it excludes cumulative preference shares, revaluation reserves, hidden reserves, and subordinated and other long-term debt. The basic story of the financial crisis in terms of aggregate levels of Tier 1 capital is that as banks have written off losses, they have also recapitalized, often with government support. Thus throughout 2008, total Tier 1 capital has actually risen 9.7 per cent to US$4276 billion. Alongside this growth in Tier 1 capital, however, there has been a remarkable collapse of profits. In the period 2003–2006 profit growth stayed above 20 per cent; in 2007 it stayed relatively flat with a loss of 0.7 per cent, but in 2008 aggregate profitability was down by 85.3 per cent. This was the first time in the history of the ‘Top 1000 World Banks’ listing that the 25 largest banks recorded a loss (in total US$32.37 billion). We have aggregated these two key indicators (Tier 1 capital and profitability) for cities in both datasets. To aid in interpretation and provide real comparisons, several decisions regarding data analysis had to be made. The most important decision was to only retain cities that met at least one of two criteria: 1 2

cities with at least three headquarters in at least one of the datasets (for instance, this keeps Reykjavik in); cities in the top 25 in terms of Tier 1 capital in at least one of the datasets (for instance, this keeps Edinburgh in).

The result is a roster of 99 cities for analysis. However, to expedite discussion, we will focus on those 52 cities with 5 per cent or more of the Tier 1 capital of the most dominant city in one of the datasets (Paris in 2007 and New York in 2008).

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Changes in the geography of command and control centres in finance Table PS.4 and Figure PS.3 describe the major changes in the level of Tier 1 capital between 2007 and 2008. The table reports the 15 largest positive and negative changes; the figure shows Tier 1 change for each of the 52 cities.

Table PS.4 Largest changes in level of Tier 1 capital (2007–2008). Rank

City

Largest positive change in tier 1 (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

San Francisco New York Singapore Charlotte Abu Dhabi Minneapolis Beijing Mumbai Shanghai Dubai Bangkok Athens Kuala Lumpur Sydney Melbourne

117.40 89.23 45.84 44.91 40.63 37.79 33.50 25.14 24.39 22.64 19.16 13.73 13.14 12.95 12.75

Rank

City

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Reykjavik Winston-Salem Seoul Manama Munich Barcelona St Petersburg Istanbul London Dublin Stuttgart Tokyo Brussels Edinburgh Kuwait City

Largest negative change in tier 1 (%) −100.00 −74.44 −30.35 −20.94 −13.44 −12.67 −11.99 −9.05 −7.83 −7.76 −6.78 −5.33 −5.20 −5.14 −5.11

Figure PS.3 Changes in level of Tier 1 capital (2007–2008).

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The top five largest positive changes are for San Francisco, New York, Singapore, Charlotte and Abu Dhabi and the top five negative changes are for Reykjavik, Winston-Salem, Seoul, Munich and Manama. For some cases, growth and decline are found to be directly interrelated. For instance, the decline of Winston-Salem can be attributed to the government-forced sale of Wachovia to San Francisco-headquartered Wells Fargo: thus the growth of San Francisco directly mirrors the fall of Winston-Salem. Also, New York’s neardoubling of its Tier 1 capital is mainly due to the new entry in The Banker’s list of New York-based investment banks (the takeover of Washington Mutual by Morgan Chase is also relevant here): after the bankruptcy of Lehman Brothers, former investment banks Goldman Sachs and Morgan Stanley, both highly ranked in 2008 (13th and 17th respectively), had to become traditional bank holding companies in September 2008. Finally, the growth of Charlotte is related to Bank of America’s acquisition of Merrill Lynch. Considering both the figure and the table, it can be clearly shown that there is a general spatial pattern featuring the decline of European cities: there are only four non-European cities recording a drop in Tier 1 capital: WinstonSalem, Seoul, Tokyo and Manama. Conversely, there is only one European city recorded in the top 15 cities in terms of positive Tier 1 capital change: Athens. However, as we subsequently found out, this Athens exception is partly due to a delayed reaction to the financial crisis: the major Athens-headquartered banks recorded good performances in 2008 because of strong credit demand in Greece. However, before the end of the year, Moody’s Investors Service suddenly changed these banks’ financial strength ratings and long-term deposit and debt ratings to negative from stable. The outcome seems to be that Athens will be more severely affected by the credit crisis than any other European city. Banks’ profits and losses are particularly volatile in time and space but aggregated levels of 2008 profits do provide another, and possibly more robust, forecast of how the geography of financial command and control centres are changing through the crisis. Table PS.5 and Figure PS.4 describe aggregated pre-tax profits at the level of the cities. To contextualize these profits/losses properly, they are presented in relation to the level of Tier 1 capital contained within a city: this generates a ‘return on capital’ ratio. The table lists the 15 cities with the highest levels of return on capital and all the 13 cities where the average shows losses. It is noteworthy that Reykjavik drops off the map: the city’s banks were wiped out in 2008.

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Table PS.5 Largest pre-tax profits/losses (2008). Rank

City

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Sydney Johannesburg Shanghai Kuala Lumpur Kuwait City Beijing Santander Montreal Riyadh Stockholm Istanbul Bangkok Mumbai Melbourne Minneapolis

Largest pretax profits/Tier 1 2008 (%) 29.9 29.8 28.0 24.6 23.8 23.5 23.4 21.5 20.6 19.8 18.5 17.6 17.0 16.1 16.1

Rank

City

1 2 3 4 5 6 7 8 9 10 11 12 13

Munich Edinburgh San Francisco Zurich Brussels Salt Lake City Stuttgart Frankfurt New York Amsterdam Manama Tokyo Copenhagen

Largest pretax losses/Tier 1 2008 (%) −57.6 −57.4 −49.2 −41.4 −35.3 −32.8 −20.3 −16.0 −11.1 −4.6 −3.6 −2.1 −0.5

Figure PS.4 Pre-tax profits/losses (2008).

Sydney, Johannesburg, Shanghai, Kuala Lumpur and Kuwait City are the five cities atop this ranking. The first three actually show returns on capital of over 25 per cent, suggesting that the banks in these cities have continued to perform at pre-crisis levels or better. For banks located in these cities, 2008 has been largely ‘business as usual’: virtually all of them posted pre-tax profit levels broadly in line with their results for 2007. Put another way, the large profits

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of banks headquartered in these cities are not based on a few exceptional results; rather the results are the product of a general communality in the performance of important banks in these cities. In addition to Reykjavik’s demise, the five cities representing the largest losses are Munich, Edinburgh, San Francisco, Zurich and Brussels. For instance, Munich’s decline as a financial centre is witnessed by bank losses of over 50 per cent of their core capital (notably by Bayerische Landesbank and Hypo Real Estate). However, the worst losses in absolute terms were for Edinburgh and San Francisco-based banks: Royal Bank of Scotland and Wells Fargo posted massive US$59.3 billion and US$47.7 billion losses, respectively.

Typology of change The message of Tier 1 changes between 2007 and 2008 and pre-tax profits/losses in 2008 is that the impact of the financial crisis on financial command and control centres has been very varied in both spatial and substantive terms. There has been no simple geographical shift from ‘West to East’ as is sometimes mooted: it is very easy to find exceptions. For instance, compare the relative performances of banks in Montreal or Toronto with those in Seoul or Manama. In addition, by comparing the figures and tables above, we can clearly see that the impact of the crisis is also sweeping in terms of its effects. San Francisco provides a good example of this. At one level, the Wachovia takeover by Wells Fargo increases the Tier 1 level of San Francisco and signifies the demise of Winston-Salem as a banking centre, but it would be wrong to designate 2008 as a ‘good year’ for San Francisco. Overall, banks in San Francisco had losses that are over 20 per cent of average Tier 1 level. This implies that in the long term the future of San Francisco as an international banking centre may be less secure than before the crisis. Thus a balanced appraisal of the impact of the financial crisis on cities implies a combined consideration of performance indicators. Therefore we have created Table PS.6 as a typology that arrays the results for Tier 1 change between 2007 and 2008 against pre-tax profits in 2008. Twelve potential city positions are defined by specifying three levels of Tier 1 change (gain, stability and loss) and four levels of return on capital (large profits, small profits, small losses and large losses). A summarizing geography of changes in financial command and control centres in the context of the crisis is presented in Figure PS.5 by combining the typology with levels of Tier 1 capital in 2008.

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Table PS.6 Performance of command and control centres in finance in the context of the financial crisis. %

Profits/Tier 1 2008

Change in Tier 1

> 20%

0–20%

−20% to 0%

< −20%

> 5%

Sydney, Shanghai, Kuala Lumpur, Beijing, Santander, Montreal, Riyadh

Bangkok, Mumbai, Melbourne, Minneapolis, Singapore, Dubai, Athens, Abu Dhabi, Toronto, Taipei, Charlotte, Tel Aviv

New York

Zurich, San Francisco

−5% to 5%

Johannesburg

Stockholm, Madrid, Lisbon, São Paulo, Milan, Moscow, Paris, Utrecht, Vienna, Düsseldorf

Copenhagen, Amsterdam, Frankfurt

Salt Lake City

< −5%

Kuwait City

Istanbul, Barcelona, Winston-Salem, Dublin, London, Seoul, St Petersburg

Tokyo, Manama

Stuttgart, Brussels, Edinburgh, Munich

Big winners Winners Mixed Losers Big losers

What the table and the figure reveal is the complexity of this particular geography. There are a number of obvious winners and losers: for example, those cities that combine pre-crisis levels of return on capital with Tier 1 growth are clear-cut winners (Sydney, Shanghai, Kuala Lumpur, Beijing, Santander, Montreal and Riyadh). Furthermore, it should be recognized that generally in these cases capital growth has been less government-based than resulting from the banks’ own efforts to raise their capital: this contrasts with the Tier 1 growth of most banks in US and European cities. The European financial centres of Edinburgh, Brussels, Stuttgart and Munich are equally clear-cut losers because in spite of capital injections by governments, capital levels have dropped severely so that future recovery of these cities as financial

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Figure PS.5 Performance of command and control centres in finance in the context of the financial crisis.

centres is uncertain given the very large losses. In our typology, most financial centres feature in the grey zone of centres that have experienced mixed results. For instance, cities such as New York, Stockholm, Frankfurt and Istanbul combine some relative stability in terms of Tier 1 capital with a relatively neutral year in terms of profitability. Last but not least, the remaining cities such as Bangkok, Johannesburg, Salt Lake City and Tokyo appear as mixed outcome because they combine a relatively good or bad performance for one of the key indicators with an average performance for the other indicator: for instance, Salt Lake City banks combine Tier 1 stability with large losses; Johannesburg banks combine Tier 1 stability with large profits.

Concluding Comments In this postscript, we have aimed to paint a picture of where the global urban geography presented in this book is heading. This discussion of recent trends and possible future changes provides a fitting way to conclude the interpretation and discussion of cities in globalization in 2008. Although the single most important feature of the different analyses of trends and recent changes is the relative decline of Northern American and European cities, and the relative rise of Asian (and in particular Chinese) cities, we have also seen that it would be wrong to simply understand this as a matter of a shift ‘from West to East’. For instance, although all Chinese cities have become more integrated in the world city network in the period 2000–2008, Beijing and Shanghai have witnessed far bigger connectivity gains in relative terms. For one thing, this points to uneven geographies within the overall pattern. Furthermore, we have

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also seen that the initial impact of the financial crisis on command and control centres in finance has been both complex and varied. Thus although most clear-cut winners are indeed not headquartered in Northern American and European cities, a number of Western financial centres such as Sydney and Santander are among the cities with the best performing banks through the crisis. A number of banks headquartered in Middle Eastern and Pacific Asian cities have bucked the general regional trend and have been hit badly by the crisis. Finally, it is important to stress that the current financial crisis is not simply an ‘event’ that can be isolated in time and space, but rather it is the latest part of a continuing bundle of processes that is economic globalization. This leaves the possibility that the patterns we have identified above may be deepened, altered or perhaps even reversed in the coming years. Of course it is hard to predict which of these changing scenarios will come to pass; we do know that we will not be able adequately to assess and interpret such changes without a good empirical grounding on the shifting financial and wider corporate landscapes in cities across the world. This whole volume of multiple ‘global urban analyses’ is one small step in understanding cities in globalization for this end.

References Arrighi, G. (2007) Adam Smith in Beijing: Lineages of the Twenty-First Century, Verso, London Derudder, B., Taylor, P. J., Ni, P., De Vos, A., Hoyler, M., Hanssens, H., Bassens, D., Huang, J., Witlox, F., Shen, W. and Yang, X. (2010a) ‘Pathways of change: shifting connectivites in the world city network, 2000–08’, Urban Studies, vol 47, pp1861–1877 Derudder, B., Hoyler, M. and Taylor, P. J. (2010b) ‘Goodbye Reykjavik: International banking centres and the global financial crisis’, Area, doi:10.1111/j.14754762.2010.00968.x Frank, A. G. (1998) ReORIENT: Global Economy in the Asian Age, University of California Press, Berkeley, CA Lai, K. P. Y. (2009) Global Cities in Competition? A Qualitative Analysis of Shanghai, Beijing and Hong Kong as Financial Centres, GaWC Research Bulletin 313, www.lboro.ac.uk/gawc/rb/rb313.html, accessed 10 March 2010 Taylor, P. J., Catalano, G. and Walker, D. R. F. (2002) ‘Measurement of the world city network’, Urban Studies, vol 39, pp2367–2376 The Banker (2008) Top 1000 World Banks, www.thebanker.com/top1000.php, accessed 20 September 2009 The Banker (2009) Top 1000 World Banks, www.thebanker.com/top1000.php, accessed 20 September 2009

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Appendix A

Lists of Firms and Cities Firms Listed in the Forbes Global 2000 (2006) COMPANY

COUNTRY

INDUSTRY

3i Group 3M 77 Bank Aareal Bank ABB Abbott Laboratories Abercrombie & Fitch Abertis Abitibi Consolidated ABN Amro Holding Accenture Acciona Accor ACE ACE Aviation Acer Acerinox Acom ACS Group Adecco Adelaide Bank Adidas Adobe Systems Advance Auto Parts Advanced Info Service Advanced Micro Advantest Aegon AEM Aeon Aéroports de Paris AES Aetna

United Kingdom United States Japan Germany Switzerland United States United States Spain Canada Netherlands Bermuda Spain France Bermuda Canada Taiwan/China Spain Japan Spain Switzerland Australia Germany United States United States Thailand United States Japan Netherlands Italy Japan France United States United States

Diversified Financials Conglomerates Banking Banking Capital Goods Drugs & Biotechnology Retailing Transportation Materials Banking Business Services & Supplies Construction Hotels, Restaurants & Leisure Insurance Transportation Technology Hardware & Equip Materials Diversified Financials Construction Business Services & Supplies Banking Household & Personal Products Software & Services Retailing Telecommunications Services Semiconductors Semiconductors Insurance Utilities Retailing Business Services & Supplies Utilities Health Care Equipment & Svcs

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COMPANY

COUNTRY

INDUSTRY

Affiliated Computer Aflac AG Edwards Agilent Technologies Agrium Ahold Aichi Bank Aiful Aioi Insurance Air China Air France-KLM Group Air Prods & Chems Aire Liquide Group Aisin Seiki Ajinomoto AK Steel Holding Akbank Aker Akita Bank Akzo Nobel Al Rajhi Bank Alcan Alcatel-Lucent Alcoa Alexander Forbes ALFA Alfresa Holdings Alinta Alitalia All Nippon Airways Allegheny Energy Allegheny Technologies Allergan Alliance & Leicester Alliance Boots Alliant Energy Allianz Allied Irish Banks Allied Waste Inds Allied World Assurance Allstate Alltel Alpha Bank Group Alps Electric Alstom

United States United States United States United States Canada Netherlands Japan Japan Japan China France United States France Japan Japan United States Turkey Norway Japan Netherlands Saudi Arabia Canada France United States South Africa Mexico Japan Australia Italy Japan United States United States United States United Kingdom United Kingdom United States Germany Ireland United States Bermuda United States United States Greece Japan France

Software & Services Insurance Diversified Financials Technology Hardware & Equip Chemicals Food Markets Banking Diversified Financials Insurance Transportation Transportation Chemicals Chemicals Consumer Durables Food Drink & Tobacco Materials Banking Oil & Gas Operations Banking Chemicals Banking Materials Technology Hardware & Equip Materials Insurance Conglomerates Health Care Equipment & Svcs Utilities Transportation Transportation Utilities Materials Drugs & Biotechnology Banking Retailing Utilities Insurance Banking Business Services & Supplies Insurance Insurance Telecommunications Services Banking Technology Hardware & Equip Conglomerates

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LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

Altadis Altana Altera Altria Group Aluminum Corp of China Amazon.com AMB Property Ambac Financial Group Amcor Amdocs AMEC Amer Eagle Outfitters Ameren América Móvil American Electric American Equity Invest American Express American Finl Group American Home Mortgage American Intl Group American Natl Ins American Standard American Tower AmeriCredit Ameriprise Financial AmerisourceBergen Amgen Amlin AMMB Holdings AMP Amphenol AMR Amvescap Anadarko Petroleum Analog Devices Angang New Steel Anglo American Anglo Irish Bank Anheuser-Busch Cos Anixter International Annaly Capital Mgmt Antarchile Antena 3 de Television Antofagasta ANZ Banking

Spain Germany United States United States China United States United States United States Australia United Kingdom United Kingdom United States United States Mexico United States United States United States United States United States United States United States United States United States United States United States United States United States United Kingdom Malaysia Australia United States United States United Kingdom United States United States China United Kingdom Ireland United States United States United States Chile Spain United Kingdom Australia

Food Drink & Tobacco Drugs & Biotechnology Semiconductors Food Drink & Tobacco Materials Retailing Diversified Financials Insurance Materials Software & Services Construction Retailing Utilities Telecommunications Services Utilities Insurance Diversified Financials Insurance Diversified Financials Insurance Insurance Capital Goods Telecommunications Services Diversified Financials Diversified Financials Health Care Equipment & Svcs Drugs & Biotechnology Insurance Banking Diversified Financials Technology Hardware & Equip Transportation Diversified Financials Oil & Gas Operations Semiconductors Materials Materials Banking Food Drink & Tobacco Technology Hardware & Equip Diversified Financials Diversified Financials Media Materials Banking

353

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COMPANY

COUNTRY

INDUSTRY

AOC Holdings Aomori Bank Aon Aozora Bank Apache Apartment Investment Apollo-Education Group Apple Applied Materials Arab Bank Aracruz Celulose Arcelor Mittal Arch Capital Group Archer Daniels Archstone-Smith Areva Group Arkema Arrow Electronics ArvinMeritor Asahi Breweries Asahi Glass Asahi Kasei ASE-Advanced Semiconductor Ashland ASML Holding Aspen Insurance Holdings Assa Abloy Assoc British Foods Associated Banc-Corp Assurant Astellas Pharma Astoria Financial AstraZeneca Astroc Mediterraneo Asustek Computer AT&T ATEbank Atlas Copco Atmos Energy Atos Origin Attijariwafa Bank AU Optronics Autodesk Autogrill Autoliv

Japan Japan United States Japan United States United States United States United States United States Jordan Brazil Netherlands Bermuda United States United States France France United States United States Japan Japan Japan Taiwan/China United States Netherlands Bermuda Sweden United Kingdom United States United States Japan United States United Kingdom Spain Taiwan/China United States Greece Sweden United States France Morocco Taiwan/China United States Italy United States

Oil & Gas Operations Banking Insurance Banking Oil & Gas Operations Diversified Financials Business Services & Supplies Technology Hardware & Equip Semiconductors Banking Materials Materials Insurance Food Drink & Tobacco Diversified Financials Materials Chemicals Technology Hardware & Equip Consumer Durables Food Drink & Tobacco Construction Chemicals Semiconductors Chemicals Semiconductors Insurance Business Services & Supplies Food Drink & Tobacco Banking Insurance Drugs & Biotechnology Banking Drugs & Biotechnology Diversified Financials Technology Hardware & Equip Telecommunications Services Banking Capital Goods Utilities Software & Services Banking Technology Hardware & Equip Software & Services Hotels, Restaurants & Leisure Consumer Durables

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LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

Automatic Data AutoNation Autostrade AutoZone Avalonbay Communities Avaya Avery Dennison Avis Budget Group Aviva Avnet Avon Products Awa Bank AXA Group Axel Springer Axis Capital Holdings Babcock & Brown BAE Systems Bajaj Auto Baker Hughes Balfour Beatty Ball Bâloise Group Banca Carige Banca CR Firenze Banca Italease Banca Lombarda Group Banca MPS Banca Popolare di Milano Banca Popolare di Sondrio Banca Popolare Italiana Banco BPI Banco Bradesco Banco de Chile Banco de Sabadell Banco de Valencia Banco do Brasil Banco Nossa Caixa Banco Pastor Banco Popular Español Banco Santander BanColombia Bangkok Bank Bank Central Asia Bank Hapoalim Bank Leumi le-Israel

United States United States Italy United States United States United States United States United States United Kingdom United States United States Japan France Germany Bermuda Australia United Kingdom India United States United Kingdom United States Switzerland Italy Italy Italy Italy Italy Italy Italy Italy Portugal Brazil Chile Spain Spain Brazil Brazil Spain Spain Spain Colombia Thailand Indonesia Israel Israel

Business Services & Supplies Retailing Transportation Retailing Diversified Financials Technology Hardware & Equip Business Services & Supplies Business Services & Supplies Insurance Technology Hardware & Equip Household & Personal Products Banking Insurance Media Insurance Diversified Financials Aerospace & Defence Consumer Durables Oil & Gas Operations Construction Materials Insurance Banking Banking Business Services & Supplies Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking

355

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COMPANY

COUNTRY

INDUSTRY

Bank Mandiri Bank of America Bank of Ayudhya Bank of Baroda Bank of China Bank of Communications Bank of East Asia Bank of Fukuoka Bank of Greece Bank of Ikeda Bank of India Bank of Ireland Bank of Iwate Bank of Kyoto Bank of Montreal Bank of Nagoya Bank of New York Bank of Nova Scotia Bank of Saga Bank of Yokohama Bank Rakyat Indonesia Bankinter BankUnited Financial Banque Nat de Belgique Baoshan Iron & Steel Barclays Barloworld Barratt Developments Barrick Gold BASF Basler Kantonalbank Baxter International Bayer Group BayWa BB&T BBVA-Banco Bilbao Vizcaya BCE BCI-Banco Credito BCP-Banco Com Português BCV Group Bear Stearns Cos Beazer Homes USA Becton, Dickinson Bed Bath & Beyond Beiersdorf

Indonesia United States Thailand India China China Hong Kong/China Japan Greece Japan India Ireland Japan Japan Canada Japan United States Canada Japan Japan Indonesia Spain United States Belgium China United Kingdom South Africa United Kingdom Canada Germany Switzerland United States Germany Germany United States Spain Canada Chile Portugal Switzerland United States United States United States United States Germany

Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Banking Materials Banking Conglomerates Construction Materials Chemicals Banking Health Care Equipment & Svcs Chemicals Food Drink & Tobacco Banking Banking Telecommunications Services Banking Banking Banking Diversified Financials Construction Health Care Equipment & Svcs Retailing Household & Personal Products

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LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

BEKB-BCBE Belgacom Benq Berkshire Hathaway Best Buy BG Group Bharat Heavy Electricals Bharat Petroleum Bharti Airtel BHP Billiton

Switzerland Belgium Taiwan/China United States United States United Kingdom India India India Australia/ United Kingdom South Africa Germany United States United States United States United States United States United States Australia Germany France Hong Kong/China Austria United States United States Sweden Canada Australia United States United States United States France United Kingdom Italy Italy Italy United Kingdom Australia/ United Kingdom Brazil Brazil Japan United States United States

Banking Telecommunications Services Technology Hardware & Equip Diversified Financials Retailing Oil & Gas Operations Capital Goods Oil & Gas Operations Telecommunications Services Materials

Bidvest Group Bilfinger & Berger Biogen Idec Biomet BJ Services BJ’s Wholesale Club Black & Decker BlackRock Bluescope Steel BMW-Bayerische Motor BNP Paribas BOC Hong Kong Boehler-Uddeholm Boeing BOK Financial Boliden Bombardier Boral BorgWarner Boston Properties Boston Scientific Bouygues Group BP BPER-Emilia Romagna BPU Banca BPVN Group Bradford & Bingley Brambles Brasil Telecom Braskem Bridgestone Brink’s Brinker International

Conglomerates Construction Drugs & Biotechnology Health Care Equipment & Svcs Oil & Gas Operations Retailing Household & Personal Products Diversified Financials Materials Consumer Durables Banking Banking Materials Aerospace & Defence Banking Materials Aerospace & Defence Construction Consumer Durables Diversified Financials Health Care Equipment & Svcs Construction Oil & Gas Operations Banking Banking Banking Banking Business Services & Supplies Telecommunications Services Chemicals Consumer Durables Business Services & Supplies Hotels, Restaurants & Leisure

357

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COMPANY

COUNTRY

INDUSTRY

Brisa Bristol-Myers Squibb British Airways British Amer Tobacco British Energy Group British Land British Sky Broadcasting Broadcom Brookfield Asset Mgmt Brother Inds Brown-Forman Brunswick BT Group Buenaventura Buhrmann Bumiputra-Commerce Bunge Bunzl Burlington Santa Fe Buzzi Unicem CA Cable & Wireless Cablevision NY Group Cadbury Schweppes Calpine Cameco Cameron International Campbell Soup Canadian Imperial Bank Canadian National Canadian Natural Res Canadian Pacific Railway Canadian Tire Canara Bank Canfor Canon Capgemini Capita Group Capital One Financial CapitaLand Capitalia CapitalSource Cardinal Health Caremark Rx Carlsberg

Portugal United States United Kingdom United Kingdom United Kingdom United Kingdom United Kingdom United States Canada Japan United States United States United Kingdom Peru Netherlands Malaysia Bermuda United Kingdom United States Italy United States United Kingdom United States United Kingdom United States Canada United States United States Canada Canada Canada Canada Canada India Canada Japan France United Kingdom United States Singapore Italy United States United States United States Denmark

Transportation Drugs & Biotechnology Transportation Food Drink & Tobacco Utilities Diversified Financials Media Semiconductors Diversified Financials Business Services & Supplies Food Drink & Tobacco Consumer Durables Telecommunications Services Materials Business Services & Supplies Banking Food Drink & Tobacco Business Services & Supplies Transportation Construction Software & Services Telecommunications Services Media Food Drink & Tobacco Utilities Materials Oil & Gas Operations Food Drink & Tobacco Banking Transportation Oil & Gas Operations Transportation Retailing Banking Materials Business Services & Supplies Software & Services Business Services & Supplies Diversified Financials Diversified Financials Banking Business Services & Supplies Health Care Equipment & Svcs Health Care Equipment & Svcs Food Drink & Tobacco

8/10/10

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LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

CarMax Carnival

United States Panama/ United Kingdom United Kingdom France Mexico Japan United States Taiwan/China Hong Kong/China Italy United States Brazil United States United States China

Retailing Hotels, Restaurants & Leisure Retailing Food Markets Telecommunications Services Technology Hardware & Equip Capital Goods Insurance Transportation Insurance Business Services & Supplies Food Markets Diversified Financials Media Banking

China United States United States Germany United States Mexico Brazil Chile United States United States Japan United Kingdom United States Spain Czech Republic United States Australia Hong Kong/China Taiwan/China United States United States Israel United States Hong Kong/China United States Taiwan/China Japan Japan

Construction Retailing Chemicals Health Care Equipment & Svcs Drugs & Biotechnology Construction Utilities Retailing Utilities Construction Transportation Utilities Telecommunications Services Oil & Gas Operations Utilities Transportation Diversified Financials Diversified Financials Banking Diversified Financials Media Software & Services Oil & Gas Operations Diversified Financials Oil & Gas Operations Technology Hardware & Equip Banking Banking

Carphone Warehouse Carrefour Group Carso Global Telecom Casio Computer Caterpillar Cathay Financial Cathay Pacific Airways Cattolica Assicurazioni CB Richard Ellis CBD-Brasil Distribuição CBOT Holdings CBS CCB-China Construction Bank CCCC-China Communications Construction CDW Celanese Celesio Celgene Cemex Cemig Cencosud CenterPoint Energy Centex Central Japan Railway Centrica CenturyTel Cepsa Cez CH Robinson Worldwide Challenger Financial Svcs Champion REIT Chang Hwa Com Bank Charles Schwab Charter Commun Check Point Software Chesapeake Energy Cheung Kong Chevron Chi Mei Optoelectronics Chiba Bank Chiba Kogyo Bank

359

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360

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GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Chicago Mercantile China Airlines China Coal Energy China Cosco Holdings China Development Finl China Intl Marine Container China Life Insurance China Merchants (International) China Merchants Bank China Minsheng Banking China Mobile China Netcom Group China Overseas Land & Inv China Resources Ent China Resources Power Holdings China Shenhua Energy China Shipping Container China Shipping Develop China Southern Airlines China Steel China Telecom China Unicom China Yangtze Power Chinatrust Financial Chinese Estates (Holdings) Christian Dior Chubb Chubu Electric Power Chugoku Bank Chugoku Electric Power Chukyo Bank Chunghwa Telecom CI Financial Income Ciba Specialty Chemicals CIC Group Cigna Cimpor-Cimentos Portugal Cincinnati Financial Cintas Circuit City Stores Cisco Systems CIT Group Citic Pacific Citic Securities Citigroup

United States Taiwan/China China China Taiwan/China China China Hong Kong/China China China Hong Kong/China Hong Kong/China Hong Kong/China Hong Kong/China Hong Kong/China China China China China Taiwan/China China Hong Kong/China China Taiwan/China Hong Kong/China France United States Japan Japan Japan Japan Taiwan/China Canada Switzerland France United States Portugal United States United States United States United States United States Hong Kong/China China United States

Diversified Financials Transportation Materials Transportation Banking Capital Goods Insurance Transportation Banking Banking Telecommunications Services Telecommunications Services Diversified Financials Conglomerates Utilities Materials Transportation Transportation Transportation Materials Telecommunications Services Telecommunications Services Utilities Banking Diversified Financials Household & Personal Products Insurance Utilities Banking Utilities Banking Telecommunications Services Diversified Financials Chemicals Banking Health Care Equipment & Svcs Construction Insurance Business Services & Supplies Retailing Technology Hardware & Equip Diversified Financials Conglomerates Diversified Financials Banking

13:13

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LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

Citizens Commun Citizens Republic Bancorp City Developments City National CJ Clariant Clear Channel Commun Clorox CLP Holdings CMPC CMS Energy Cnooc CNP Assurances CNPC (Hong Kong) Coach Coca-Cola Coca-Cola Amatil Coca-Cola Enterprises Coca-Cola HBC Cognizant Technology Coles Group Colgate-Palmolive Colonial BancGroup Colruyt Comcast Comerica Commerce Bancorp Commerce Bancshs Commercial Metals Commerzbank Commonwealth Bank Compal Electronics Compass Bancshares Compass Group Computer Sciences Con-way ConAgra Foods ConocoPhillips Conseco Consol Energy Consolidated Edison Constellation Brands Constellation Energy Continental Continental Airlines

United States United States Singapore United States South Korea Switzerland United States United States Hong Kong/China Chile United States Hong Kong/China France Hong Kong/China United States United States Australia United States Greece United States Australia United States United States Belgium United States United States United States United States United States Germany Australia Taiwan/China United States United Kingdom United States United States United States United States United States United States United States United States United States Germany United States

Telecommunications Services Banking Diversified Financials Banking Food Drink & Tobacco Chemicals Media Household & Personal Products Utilities Materials Utilities Oil & Gas Operations Insurance Oil & Gas Operations Household & Personal Products Food Drink & Tobacco Food Drink & Tobacco Food Drink & Tobacco Food Drink & Tobacco Software & Services Food Markets Household & Personal Products Banking Food Markets Media Banking Banking Banking Materials Banking Banking Technology Hardware & Equip Banking Business Services & Supplies Software & Services Transportation Food Drink & Tobacco Oil & Gas Operations Insurance Materials Utilities Food Drink & Tobacco Utilities Consumer Durables Transportation

361

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362

GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Cooper Industries Corning Corporation Mapfre Corus Group Cosco Pacific Cosmo Oil Costco Wholesale Couche Tard Countrywide Financial Coventry Health Care CPFL Energia CR Bard Credicorp Crédit Agricole Credit Saison Credit Suisse Group Credito Emiliano Credito Valtellinese CRH Crown Holdings CSL CSM CSN-Cia Siderurgica CSX Cullen/Frost Bankers Cummins CVS D’Ieteren Daegu Bank Daelim Industrial Daewoo Engineering Daewoo Intl Daewoo Securities Daewoo Ship & Marine Dai Nippon Printing Daiei Daiichi Sankyo Daikin Industries Daily Mail & General Daimaru DaimlerChrysler Dainippon Ink & Chems Daisan Bank Daishi Bank Daito Trust Construction

Bermuda United States Spain United Kingdom Hong Kong/China Japan United States Canada United States United States Brazil United States Bermuda France Japan Switzerland Italy Italy Ireland United States Australia Netherlands Brazil United States United States United States United States Belgium South Korea South Korea South Korea South Korea South Korea South Korea Japan Japan Japan Japan United Kingdom Japan Germany Japan Japan Japan Japan

Capital Goods Technology Hardware & Equip Insurance Materials Transportation Oil & Gas Operations Retailing Food Markets Diversified Financials Health Care Equipment & Svcs Utilities Health Care Equipment & Svcs Banking Banking Diversified Financials Diversified Financials Banking Banking Construction Materials Drugs & Biotechnology Food Drink & Tobacco Materials Transportation Banking Capital Goods Retailing Retailing Banking Construction Construction Trading Companies Diversified Financials Capital Goods Media Retailing Drugs & Biotechnology Construction Media Retailing Consumer Durables Chemicals Banking Banking Construction

8/10/10

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8/10/10

LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

Daiwa House Industry Daiwa Securities Dana Danaher Danske Bank Group Daqin Railway Darden Restaurants Dassault Aviation Datang Intl Power DaVita DBS Group Dean Foods Deere & Co Delhaize Group Dell Delphi Delta Air Lines Delta Electronics Denso Dentsu Depfa Bank Deutsche Bank Deutsche Boerse Deutsche Lufthansa Deutsche Post Deutsche Telekom Developers Diversified Devon Energy Dexia Diageo Diamond Lease Dillard’s DirecTV Group DnB NOR Dogan Holding Dollar General Dominion Resources Dongbu Insurance Dongfeng Motor Group Dongkuk Steel Mill Doosan Doral Financial Dover Dow Chemical Downey Financial

Japan Japan United States United States Denmark China United States France China United States Singapore United States United States Belgium United States United States United States Taiwan/China Japan Japan Ireland Germany Germany Germany Germany Germany United States United States Belgium United Kingdom Japan United States United States Norway Turkey United States United States South Korea China South Korea South Korea United States United States United States United States

Construction Diversified Financials Consumer Durables Conglomerates Banking Transportation Hotels, Restaurants & Leisure Aerospace & Defence Utilities Health Care Equipment & Svcs Banking Food Drink & Tobacco Capital Goods Food Markets Technology Hardware & Equip Consumer Durables Transportation Technology Hardware & Equip Consumer Durables Media Diversified Financials Diversified Financials Diversified Financials Transportation Transportation Telecommunications Services Diversified Financials Oil & Gas Operations Banking Food Drink & Tobacco Business Services & Supplies Retailing Media Diversified Financials Diversified Financials Retailing Utilities Insurance Consumer Durables Materials Trading Companies Banking Conglomerates Chemicals Banking

363

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364

8/10/10

GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

DR Horton Drax Group DSG International DTE Energy Duke Energy Duke Realty DVB Bank E-L Financial E-Trade Financial E.ON E.Sun Financial EADS East Japan Railway Eastman Chemical Eastman Kodak Eaton Ebay EchoStar Commun Ecolab Edison Edison International EDP-Energias de Portugal EFG Eurobank Ergasias EFG International Ehime Bank EI du Pont de Nemours Eiffage Eighteenth Bank Eisai El Paso El Puerto de Liverpool Elan Electric Power Devel Electricité de France Electrolux Group Electronic Arts Electronic Data Sys Eletrobrás Eli Lilly & Co Embarq Embraer EMC Emdeon Emerson Electric Empire

United States United Kingdom United Kingdom United States United States United States Germany Canada United States Germany Taiwan/China Netherlands Japan United States United States United States United States United States United States Italy United States Portugal Greece Switzerland Japan United States France Japan Japan United States Mexico Ireland Japan France Sweden United States United States Brazil United States United States Brazil United States United States United States Canada

Construction Utilities Retailing Utilities Utilities Diversified Financials Banking Insurance Diversified Financials Utilities Banking Aerospace & Defence Transportation Chemicals Household & Personal Products Capital Goods Retailing Media Chemicals Utilities Utilities Utilities Banking Diversified Financials Banking Chemicals Construction Banking Drugs & Biotechnology Oil & Gas Operations Retailing Drugs & Biotechnology Utilities Utilities Consumer Durables Software & Services Software & Services Utilities Drugs & Biotechnology Telecommunications Services Aerospace & Defence Technology Hardware & Equip Health Care Equipment & Svcs Conglomerates Food Markets

13:13

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8/10/10

LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

Enagas Enbridge EnBW-Energie Baden EnCana Endesa Endurance Specialty ENEL Energizer Holdings Energy East ENI Enka Ensco International Entergy Enterprise Inns EOG Resources Equity Residential Eramet ERG Erste Bank Espirito Santo Finl Esprit Holdings Essilor International Estee Lauder Cos Euler Hermes Eurazeo Euronext Everest Re Group Evergreen Marine EVN Evraz Group EW Scripps Exelon Exista Expedia Expeditors Intl Experian Group Express Scripts ExxonMobil Fadesa Inmobiliaria Fairfax Financial Falabella Family Dollar Stores Fannie Mae Fanuc Far Eastern Textile

Spain Canada Germany Canada Spain Bermuda Italy United States United States Italy Turkey United States United States United Kingdom United States United States France Italy Austria Luxembourg Hong Kong/China France United States France France Netherlands Bermuda Taiwan/China Austria Luxembourg United States United States Iceland United States United States Ireland United States United States Spain Canada Chile United States United States Japan Taiwan/China

Utilities Oil & Gas Operations Utilities Oil & Gas Operations Utilities Insurance Utilities Household & Personal Products Utilities Oil & Gas Operations Construction Oil & Gas Operations Utilities Hotels, Restaurants & Leisure Oil & Gas Operations Diversified Financials Materials Oil & Gas Operations Banking Banking Retailing Health Care Equipment & Svcs Household & Personal Products Insurance Diversified Financials Diversified Financials Insurance Transportation Utilities Materials Media Utilities Diversified Financials Business Services & Supplies Transportation Business Services & Supplies Health Care Equipment & Svcs Oil & Gas Operations Diversified Financials Insurance Retailing Retailing Diversified Financials Capital Goods Conglomerates

365

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366

GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Far EasTone Telecom Fast Retailing FCC Federal-Mogul Federated Dept Strs FedEx Femsa Fiat Group FIBI Holding Fidelity National Finl Fidelity National Info Fifth Third Bancorp Financière de l’Odet Finatis Finmeccanica First American First BanCorp First Citizens Bcshs First Data First Financial Holding First Horizon National First Marblehead FirstEnergy FirstGroup FirstRand Fiserv Flagstar Bancorp Flextronics Intl Fluor FMC Technologies Foncière des Régions Fondiaria-SAI Foot Locker Ford Motor Forest City Enterpr Forest Labs Formosa Chems & Fibre Formosa Petrochemical Formosa Plastics Fortis Fortum Fortune Brands Foster Wheeler Foster’s Group FPL Group

Taiwan/China Japan Spain United States United States United States Mexico Italy Israel United States United States United States France France Italy United States United States United States United States Taiwan/China United States United States United States United Kingdom South Africa United States United States Singapore United States United States France Italy United States United States United States United States Taiwan/China Taiwan/China Taiwan/China Netherlands Finland United States Bermuda Australia United States

Telecommunications Services Retailing Construction Consumer Durables Retailing Transportation Food Drink & Tobacco Consumer Durables Banking Insurance Business Services & Supplies Banking Transportation Trading Companies Aerospace & Defence Insurance Banking Banking Software & Services Banking Banking Business Services & Supplies Utilities Transportation Banking Software & Services Banking Technology Hardware & Equip Construction Oil & Gas Operations Diversified Financials Insurance Retailing Consumer Durables Diversified Financials Drugs & Biotechnology Chemicals Oil & Gas Operations Chemicals Diversified Financials Utilities Consumer Durables Construction Food Drink & Tobacco Utilities

8/10/10

13:13

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8/10/10

LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

France Telecom Franklin Resources Fraport Freddie Mac Freeport Copper Fremont General Fresenius Friedman Billings Friends Provident Frontier Oil Frontline Fubon Financial Fuji Electric Holdings Fuji Fire & Marine Fuji Heavy Inds Fuji Television Network Fujifilm Holdings Fujitsu Fukui Bank Fulton Financial Furukawa Electric GAIL (India) Gallaher Group Galp Energia SGPS Gamesa Gannett Gap Garmin Gas Natural SDG Gaz de France Gazprom GEA Group General Dynamics General Electric General Growth Prop General Mills General Motors Generali Group Genting Genuine Parts Genworth Financial Genzyme George Weston George Wimpey GFNorte

France United States Germany United States United States United States Germany United States United Kingdom United States Bermuda Taiwan/China Japan Japan Japan Japan Japan Japan Japan United States Japan India United Kingdom Portugal Spain United States United States Cayman Islands Spain France Russia Germany United States United States United States United States United States Italy Malaysia United States United States United States Canada United Kingdom Mexico

Telecommunications Services Diversified Financials Transportation Diversified Financials Materials Diversified Financials Health Care Equipment & Svcs Diversified Financials Insurance Oil & Gas Operations Transportation Insurance Capital Goods Insurance Consumer Durables Media Consumer Durables Technology Hardware & Equip Banking Banking Capital Goods Utilities Food Drink & Tobacco Oil & Gas Operations Capital Goods Media Retailing Technology Hardware & Equip Utilities Utilities Oil & Gas Operations Conglomerates Aerospace & Defence Conglomerates Diversified Financials Food Drink & Tobacco Consumer Durables Insurance Hotels, Restaurants & Leisure Consumer Durables Insurance Drugs & Biotechnology Food Markets Construction Banking

367

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Page 367

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368

GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Gilead Sciences Givaudan GKN GlaxoSmithKline Glitnir Bank GlobalSantaFe GOL Linhas Aéreas Gold Fields Goldcorp Golden Agri-Resources Goldman Sachs Group Goodrich Goodyear Google GPT Group Grafton Group Grant Prideco Great A&P Tea Great Eagle Holdings Greek Postal Savings Bank Group 4 Securicor Groupe Danone Grupo Bimbo Grupo Carso Grupo Elektra Grupo Ferrovial Grupo Inmocaral Grupo Mexico Grupo Modelo Grupo Televisa GS E&C GS Holdings Gunma Bank H Lundbeck H&M Hennes & Mauritz H&R Block Hachijuni Bank Hafslund Hagemeyer Halliburton Hammerson Hana Financial Group Hang Lung Group Hanjin Shipping Hankyu Hanshin

United States Switzerland United Kingdom United Kingdom Iceland Cayman Islands Brazil South Africa Canada Singapore United States United States United States United States Australia Ireland United States United States Hong Kong/China Greece United Kingdom France Mexico Mexico Mexico Spain Spain Mexico Mexico Mexico South Korea South Korea Japan Denmark Sweden United States Japan Norway Netherlands United States United Kingdom South Korea Hong Kong/China South Korea Japan

Drugs & Biotechnology Chemicals Consumer Durables Drugs & Biotechnology Banking Oil & Gas Operations Transportation Materials Materials Food Drink & Tobacco Diversified Financials Aerospace & Defence Consumer Durables Software & Services Diversified Financials Retailing Oil & Gas Operations Food Markets Hotels, Restaurants & Leisure Banking Business Services & Supplies Food Drink & Tobacco Food Drink & Tobacco Conglomerates Retailing Construction Diversified Financials Materials Food Drink & Tobacco Media Construction Diversified Financials Banking Drugs & Biotechnology Retailing Business Services & Supplies Banking Utilities Trading Companies Oil & Gas Operations Diversified Financials Banking Diversified Financials Transportation Transportation

8/10/10

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8/10/10

LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

Hannover Re Hanson Hanwa Hanwha Hanwha Chemical Harley-Davidson Harman International Harrah’s Entertain Harris Hartford Finl Service Haseko Hays HBOS HCC Insurance HDFC Bank HDFC-Housing Devel Health Care Property Health Management Health Net HeidelbergCement Heineken Holding Hellenic Petroleum Hellenic Telecom Helvetia Patria Henderson Land Henkel Group Henry Schein Hermès International Hershey Hertz Global Holdings Hess Hewlett-Packard Higashi-Nippon Bank High Tech Computer Higo Bank Hilton Hotels Hindustan Petroleum Hindustan Zinc Hiroshima Bank Hitachi HJ Heinz HK Exchanges & Clearing Hochtief Hokkaido Electric Power Hokkoku Bank

Germany United Kingdom Japan South Korea South Korea United States United States United States United States United States Japan United Kingdom United Kingdom United States India India United States United States United States Germany Netherlands Greece Greece Switzerland Hong Kong/China Germany United States France United States United States United States United States Japan Taiwan/China Japan United States India India Japan Japan United States Hong Kong/China Germany Japan Japan

Insurance Construction Trading Companies Trading Companies Chemicals Consumer Durables Technology Hardware & Equip Hotels, Restaurants & Leisure Technology Hardware & Equip Insurance Construction Business Services & Supplies Banking Insurance Banking Banking Diversified Financials Health Care Equipment & Svcs Health Care Equipment & Svcs Construction Food Drink & Tobacco Oil & Gas Operations Telecommunications Services Insurance Diversified Financials Household & Personal Products Health Care Equipment & Svcs Household & Personal Products Food Drink & Tobacco Business Services & Supplies Oil & Gas Operations Technology Hardware & Equip Banking Technology Hardware & Equip Banking Hotels, Restaurants & Leisure Oil & Gas Operations Materials Banking Technology Hardware & Equip Food Drink & Tobacco Diversified Financials Construction Utilities Banking

369

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GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Hokuetsu Bank Hokuhoku Finl Group Hokuriku Electric Power Holcim Holly Home Depot Home Retail Group Hon Hai Precision Ind Honam Petrochemical Honda Motor Honeywell International Hong Kong & China Gas Hong Leong Financial Group Hongkong Electric Hongkong Land Hormel Foods Hospira Host Hotels & Resorts Hovnanian Enterprises Hoya HSBC Holdings Hua Nan Financial Huaneng Power Intl Huaxia Bank Hudson City Bancorp Humana Huntington Bancshs Huntsman Husky Energy Husqvarna Hutchison Telecom Intl Hutchison Whampoa Hyakugo Bank Hyakujushi Bank Hynix Semiconductor Hyosung Hypo Real Estate Hyundai Eng & Const Hyundai Heavy Industries Hyundai Merchant Hyundai Mobis Hyundai Motor Hyundai Steel IAC/InterActiveCorp Iberdrola

Japan Japan Japan Switzerland United States United States United Kingdom Taiwan/China South Korea Japan United States Hong Kong/China Malaysia Hong Kong/China Hong Kong/China United States United States United States United States Japan United Kingdom Taiwan/China China China United States United States United States United States Canada Sweden Hong Kong/China Hong Kong/China Japan Japan South Korea South Korea Germany South Korea South Korea South Korea South Korea South Korea South Korea United States Spain

Banking Banking Utilities Construction Oil & Gas Operations Retailing Retailing Technology Hardware & Equip Chemicals Consumer Durables Conglomerates Utilities Banking Utilities Diversified Financials Food Drink & Tobacco Health Care Equipment & Svcs Diversified Financials Construction Technology Hardware & Equip Banking Banking Utilities Banking Banking Health Care Equipment & Svcs Banking Chemicals Oil & Gas Operations Consumer Durables Telecommunications Services Conglomerates Banking Banking Semiconductors Household & Personal Products Diversified Financials Construction Capital Goods Transportation Consumer Durables Consumer Durables Materials Retailing Utilities

13:13

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8/10/10

LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

Iberia Ibiden IBM Icap ICBC Icici Bank IDB Holding Idearc Idemitsu Kosan IFIL Group IKB Illinois Tool Works Imerys Immofinanz Impac Mortgage Holding Impala Platinum Holdings Imperial Chemical Imperial Holdings Imperial Tobacco Group IMS Health InBev Inbursa Financiero Inchcape Indian Oil Indian Overseas Bank Inditex Indl Dev Bank of India Industrial Alliance Insur Industrial Bank of Korea Industrias Peñoles Industrivarden IndyMac Bancorp Infineon Technologies Infosys Technologies ING Group Ingersoll-Rand Ingram Micro Inmobiliaria Colonial Inpex Holdings Insurance Australia Group Integrys Energy Group Intel InterContinental Hotels IntercontinentalExchange International Paper

Spain Japan United States United Kingdom China India Israel United States Japan Italy Germany United States France Austria United States South Africa United Kingdom South Africa United Kingdom United States Belgium Mexico United Kingdom India India Spain India Canada South Korea Mexico Sweden United States Germany India Netherlands Bermuda United States Spain Japan Australia United States United States United Kingdom United States United States

Transportation Technology Hardware & Equip Software & Services Diversified Financials Banking Banking Diversified Financials Media Oil & Gas Operations Diversified Financials Banking Capital Goods Construction Diversified Financials Diversified Financials Materials Chemicals Transportation Food Drink & Tobacco Health Care Equipment & Svcs Food Drink & Tobacco Banking Retailing Oil & Gas Operations Banking Household & Personal Products Banking Insurance Banking Materials Diversified Financials Banking Semiconductors Software & Services Insurance Conglomerates Technology Hardware & Equip Diversified Financials Oil & Gas Operations Insurance Utilities Semiconductors Hotels, Restaurants & Leisure Diversified Financials Materials

371

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372

GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

International Power Interpublic Group Intesa Sanpaolo Intl Game Technology Intuit Investec

United Kingdom United States Italy United States United States United Kingdom/ South Africa Sweden United States Malaysia Brazil Canada Ireland Thailand Japan Japan Israel Israel United States Japan Italy Brazil India Japan Japan United States United Kingdom Japan United Kingdom United States Japan United States Japan Japan Japan Hong Kong/China United States France Canada United States Japan Japan United States United States United Kingdom

Utilities Media Banking Hotels, Restaurants & Leisure Software & Services Diversified Financials

Investor Investors Financial IOI Corp Ipiranga Ipsco Irish Life & Permanent IRPC Isetan Ishikawajima-Harima Israel Corp Israel Discount Bank iStar Financial Isuzu Motors Italmobiliare Itaúsa ITC Itochu Itochu Enex ITT ITV Iyo Bank J Sainsbury Jabil Circuit Jaccs Jacobs Engineering Japan Airlines Japan Securities Japan Tobacco Jardine Matheson JC Penney JCDecaux Jean Coutu Group Jefferies Group JFE Holdings JFE Shoji Holdings Johnson & Johnson Johnson Controls Johnson Matthey

Diversified Financials Diversified Financials Food Drink & Tobacco Oil & Gas Operations Materials Insurance Chemicals Retailing Capital Goods Chemicals Banking Diversified Financials Consumer Durables Construction Banking Food Drink & Tobacco Trading Companies Oil & Gas Operations Conglomerates Media Banking Food Markets Technology Hardware & Equip Diversified Financials Construction Transportation Diversified Financials Food Drink & Tobacco Food Markets Retailing Media Retailing Diversified Financials Materials Trading Companies Drugs & Biotechnology Consumer Durables Materials

8/10/10

13:13

Page 372

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8/10/10

LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

Joy Global Joyo Bank JPMorgan Chase JS Group JSR Jtekt Julius Baer Holding Juniper Networks Juroku Bank Jyske Bank K Wah International Kagoshima Bank Kajima Kanematsu Kansai Electric Power Kao KarstadtQuelle Kasikornbank Kaupthing Bank Kawasaki Heavy Inds Kawasaki Kisen Kaisha Kazakhmys KB Home KBC Group KDDI Keio Keiyo Bank Kelda Group Kellogg Kensington Group Keppel Kerry Group Kesa Electricals Kesko KeyCorp Keyence KeySpan KGHM Polska Miedz Kimberly-Clark Kimberly-Clark de Mexico Kimco Realty Kinder Morgan Kingfisher Kinnevik Kintetsu

United States Japan United States Japan Japan Japan Switzerland United States Japan Denmark Hong Kong/China Japan Japan Japan Japan Japan Germany Thailand Iceland Japan Japan United Kingdom United States Belgium Japan Japan Japan United Kingdom United States United Kingdom Singapore Ireland United Kingdom Finland United States Japan United States Poland United States Mexico United States United States United Kingdom Sweden Japan

Capital Goods Banking Banking Construction Chemicals Capital Goods Diversified Financials Technology Hardware & Equip Banking Banking Diversified Financials Banking Construction Trading Companies Utilities Household & Personal Products Retailing Banking Banking Capital Goods Transportation Materials Construction Banking Telecommunications Services Transportation Banking Utilities Food Drink & Tobacco Banking Conglomerates Food Drink & Tobacco Retailing Food Markets Banking Technology Hardware & Equip Utilities Materials Household & Personal Products Household & Personal Products Diversified Financials Utilities Retailing Diversified Financials Transportation

373

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8/10/10

GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Kirin Brewery Kiyo Holdings KKPC-Korea Kumho KKR Financial KLA-Tencor Kobe Steel Koç Group Kohl’s Komatsu Kone Konica Minolta Kookmin Bank Korea Electric Power Korea Exchange Bank Korea Gas Korea Investment Holdings Korean Air Kroger Krung-Thai Bank KT KT&G Kubota Kühne & Nagel Intl Kweichow Moutai Kyocera Kyushu Electric Power Kyushu-Shinwa Holdings L-3 Communications L’Oréal Group Laboratory Corp Amer Ladbrokes Lafarge Lagardère SCA Lam Research Land Securities Group Landesbank Berlin Landsbanki Islands Lanxess Larsen & Toubro Las Vegas Sands Laurentian Bank Lear Legal & General Group Legg Mason Leggett & Platt

Japan Japan South Korea United States United States Japan Turkey United States Japan Finland Japan South Korea South Korea South Korea South Korea South Korea South Korea United States Thailand South Korea South Korea Japan Switzerland China Japan Japan Japan United States France United States United Kingdom France France United States United Kingdom Germany Iceland Germany India United States Canada United States United Kingdom United States United States

Food Drink & Tobacco Banking Chemicals Diversified Financials Semiconductors Materials Conglomerates Retailing Capital Goods Business Services & Supplies Business Services & Supplies Banking Utilities Banking Utilities Diversified Financials Transportation Food Markets Banking Telecommunications Services Food Drink & Tobacco Capital Goods Transportation Food Drink & Tobacco Semiconductors Utilities Banking Aerospace & Defence Household & Personal Products Health Care Equipment & Svcs Hotels, Restaurants & Leisure Construction Media Semiconductors Diversified Financials Banking Banking Chemicals Capital Goods Hotels, Restaurants & Leisure Banking Consumer Durables Insurance Diversified Financials Consumer Durables

13:13

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8/10/10

LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

LeGrand Lehman Bros Holdings Lend Lease Lennar Lenovo Group Leopalace21 Leucadia National Level 3 Commun Lexmark International LG Card LG Corp LG International Li & Fung Liberty Global Liberty International Liberty Media Holding Liberty Property Limited Brands Lincoln National Linde Linear Technology Link REIT Lite-On Technology Liz Claiborne Lloyds TSB Group LM Ericsson Lockheed Martin Loews LogicaCMG Lonmin Lotte Shopping Lowe’s Cos Lukoil Holding Lundbergs Luxottica Group Luzerner Kantonalbank Lyondell Chemical M-real M&T Bank Maanshan Iron & Steel Macerich Macquarie Bank Magna International Magnitogorsk Iron & Steel Makita

France United States Australia United States China Japan United States United States United States South Korea South Korea South Korea Hong Kong/China United States United Kingdom United States United States United States United States Germany United States Hong Kong/China Taiwan/China United States United Kingdom Sweden United States United States United Kingdom United Kingdom South Korea United States Russia Sweden Italy Switzerland United States Finland United States China United States Australia Canada Russia Japan

Capital Goods Diversified Financials Diversified Financials Construction Technology Hardware & Equip Diversified Financials Diversified Financials Telecommunications Services Business Services & Supplies Diversified Financials Conglomerates Trading Companies Trading Companies Media Diversified Financials Retailing Diversified Financials Retailing Insurance Conglomerates Semiconductors Diversified Financials Technology Hardware & Equip Household & Personal Products Banking Technology Hardware & Equip Aerospace & Defence Insurance Software & Services Materials Retailing Retailing Oil & Gas Operations Materials Household & Personal Products Banking Chemicals Materials Banking Materials Diversified Financials Diversified Financials Consumer Durables Materials Household & Personal Products

375

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8/10/10

GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Malayan Banking MAN Man Group Manpower Manulife Financial Marathon Oil Markel Marks & Spencer Marriott International Marsh & McLennan Marshall & Ilsley Martin Marietta Marubeni Marui Marvell Technology Group Masco MasterCard Matsushita Electric Indl Mattel Maxim Integrated Prods Maxis Communications Mazda Motor MBIA McDermott International McDonald’s McGraw-Hill Cos McKesson MDC Holdings MDU Resources MeadWestvaco Mechel Medco Health Mediaset MediaTek Mediceo Paltac Mediobanca Mediolanum Medtronic Mega Financial Holding Mellon Finl MEMC Electronic Mercantil Servicios Fin Merck Merck & Co Merrill Lynch

Malaysia Germany United Kingdom United States Canada United States United States United Kingdom United States United States United States United States Japan Japan Bermuda United States United States Japan United States United States Malaysia Japan United States Panama United States United States United States United States United States United States Russia United States Italy Taiwan/China Japan Italy Italy United States Taiwan/China United States United States Venezuela Germany United States United States

Banking Capital Goods Diversified Financials Business Services & Supplies Insurance Oil & Gas Operations Insurance Retailing Hotels, Restaurants & Leisure Insurance Banking Construction Trading Companies Retailing Semiconductors Construction Business Services & Supplies Technology Hardware & Equip Household & Personal Products Semiconductors Telecommunications Services Consumer Durables Insurance Construction Hotels, Restaurants & Leisure Media Health Care Equipment & Svcs Construction Construction Materials Materials Health Care Equipment & Svcs Media Semiconductors Health Care Equipment & Svcs Diversified Financials Insurance Health Care Equipment & Svcs Diversified Financials Diversified Financials Semiconductors Diversified Financials Drugs & Biotechnology Drugs & Biotechnology Diversified Financials

13:13

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LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

Metalurgica Gerdau Metcash Methanex MetLife Metro AG Metro Inc Metropolitan Holdings Metrovacesa Metso MGIC Investment MGM Mirage Michelin Group Michinoku Bank Microchip Technology Micron Technology Microsoft Millea Holdings Minmetals Development Mirant Mirvac Group MISC Mitchells & Butlers Mitsubishi Mitsubishi Chemical Mitsubishi Electric Mitsubishi Estate Mitsubishi Gas Chemical Mitsubishi Heavy Inds Mitsubishi Materials Mitsubishi Motors Mitsubishi UFJ Financial Mitsui & Co Mitsui Chemicals Mitsui Engineering & Ship Mitsui Fudosan Mitsui OSK Lines Mitsui Sumitomo Ins Mitsui Trust Mitsukoshi Miyazaki Bank Mizrahi Tefahot Bank Mizuho Financial Mohawk Industries MOL Molex

Brazil Australia Canada United States Germany Canada South Africa Spain Finland United States United States France Japan United States United States United States Japan China United States Australia Malaysia United Kingdom Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Israel Japan United States Hungary United States

Materials Food Markets Chemicals Insurance Food Markets Food Markets Insurance Diversified Financials Capital Goods Insurance Hotels, Restaurants & Leisure Consumer Durables Banking Semiconductors Semiconductors Software & Services Insurance Trading Companies Utilities Diversified Financials Transportation Hotels, Restaurants & Leisure Trading Companies Chemicals Capital Goods Diversified Financials Chemicals Capital Goods Materials Consumer Durables Banking Trading Companies Chemicals Capital Goods Diversified Financials Transportation Insurance Banking Retailing Banking Banking Banking Consumer Durables Oil & Gas Operations Technology Hardware & Equip

377

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COMPANY

COUNTRY

INDUSTRY

Molson Coors Brewing Monsanto Moody’s Morgan Stanley Mosaic Motorola MTN Group MTR Munich Re Murata Manufacturing Murphy Oil Musashino Bank Mxller-Maersk Mylan Labs Nabors Industries Nagoya Railroad Nan Ya Plastic Nanto Bank Naspers National Australia Bank National Bank of Canada National Bank of Greece National Bank of Pakistan National City National Grid National Oilwell Varco Nationwide Financial Natixis Natl Semiconductor Navistar Intl NCC Group NCR NEC Nelnet Neptune Orient Lines Neste Oil Nestlé Network Appliance New Century Financial New World Development New York Community Newcrest Mining Newell Rubbermaid Newfield Exploration Newmont Mining

United States United States United States United States United States United States South Africa Hong Kong/China Germany Japan United States Japan Denmark United States Bermuda Japan Taiwan/China Japan South Africa Australia Canada Greece Pakistan United States United Kingdom United States United States France United States United States Sweden United States Japan United States Singapore Finland Switzerland United States United States Hong Kong/China United States Australia United States United States United States

Food Drink & Tobacco Chemicals Business Services & Supplies Diversified Financials Chemicals Technology Hardware & Equip Telecommunications Services Transportation Insurance Technology Hardware & Equip Oil & Gas Operations Banking Transportation Drugs & Biotechnology Oil & Gas Operations Transportation Chemicals Banking Media Banking Banking Banking Banking Banking Utilities Oil & Gas Operations Insurance Banking Semiconductors Consumer Durables Construction Technology Hardware & Equip Technology Hardware & Equip Diversified Financials Transportation Oil & Gas Operations Food Drink & Tobacco Technology Hardware & Equip Diversified Financials Conglomerates Banking Materials Household & Personal Products Oil & Gas Operations Materials

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LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

News Corp Nexen Next Nidec NII Holdings NIKE Nikko Cordial Nikon Nine Dragons Paper Holdings Nintendo Nippon Express Nippon Meat Packers Nippon Mining Nippon Oil Nippon Paper Group Nippon Steel Nippon Steel Trading Nippon Telegraph & Tel Nippon Yusen Nipponkoa Insurance Nishi-Nippon City Bank NiSource Nissan Motor Nissay Dowa General Ins Nisshin Steel Nitto Denko Nobel Biocare Holding Noble Noble Energy Noble Group Nokia Nomura Holdings Nomura Real Estate Norddeutsche Affinerie Nordea Bank Nordstrom Norfolk Southern Norilsk Nickel Norsk Hydro Norske Skog Nortel Networks Northeast Utilities Northern Rock Northern Trust Northrop Grumman

United States Canada United Kingdom Japan United States United States Japan Japan Hong Kong/China Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan United States Japan Japan Japan Japan Switzerland Cayman Islands United States Hong Kong/China Finland Japan Japan Germany Sweden United States United States Russia Norway Norway Canada United States United Kingdom United States United States

Media Oil & Gas Operations Retailing Capital Goods Telecommunications Services Household & Personal Products Diversified Financials Business Services & Supplies Materials Technology Hardware & Equip Transportation Food Drink & Tobacco Oil & Gas Operations Oil & Gas Operations Materials Materials Trading Companies Telecommunications Services Transportation Insurance Banking Utilities Consumer Durables Insurance Materials Chemicals Health Care Equipment & Svcs Oil & Gas Operations Oil & Gas Operations Transportation Technology Hardware & Equip Diversified Financials Diversified Financials Materials Banking Retailing Transportation Materials Conglomerates Materials Technology Hardware & Equip Utilities Banking Banking Aerospace & Defence

379

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GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Northwest Airlines NOVA Chemicals Novartis Novatek Novelis Novo Nordisk Novolipetsk Iron & Steel NRG Energy NSK NStar NTPC Nucor Nürnberger Beteiligungs Nvidia NVR Nymex Holdings NYSE Group Obayashi Oberbank Occidental Petroleum Odakyu Electric Railway Österreichische Volksbanken Office Depot OfficeMax Ogaki Kyoritsu Bank OGE Energy OHL Oil & Gas Development Oil & Natural Gas Oita Bank Oji Paper Okaya & Co Oki Electric Industry OKO Bank Old Mutual Old Republic Intl Olympus Omnicare Omnicom Group Omron OMV Group OneBeacon Insurance Group Oneok Onex Ono Pharmaceutical

United States Canada Switzerland Russia Canada Denmark Russia United States Japan United States India United States Germany United States United States United States United States Japan Austria United States Japan Austria United States United States Japan United States Spain Pakistan India Japan Japan Japan Japan Finland United Kingdom United States Japan United States United States Japan Austria Bermuda United States Canada Japan

Transportation Chemicals Drugs & Biotechnology Oil & Gas Operations Materials Drugs & Biotechnology Materials Utilities Capital Goods Utilities Utilities Materials Insurance Semiconductors Construction Diversified Financials Diversified Financials Construction Banking Oil & Gas Operations Transportation Banking Retailing Retailing Banking Utilities Construction Oil & Gas Operations Oil & Gas Operations Banking Materials Trading Companies Technology Hardware & Equip Banking Insurance Insurance Health Care Equipment & Svcs Health Care Equipment & Svcs Media Technology Hardware & Equip Oil & Gas Operations Insurance Utilities Diversified Financials Drugs & Biotechnology

8/10/10

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LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

OOIL-Orient Overseas OPAP Oracle Orascom Construction Inds Orascom Telecom Orica Orient Oriental Bank of Commerce Oriental Land Origin Energy Orix Orkla Osaka Gas Oshkosh Truck OTP Bank Outokumpu Oversea-Chinese Banking Owens Corning Owens-Illinois Paccar Paragon Group of Cos Parker-Hannifin Parmalat PartnerRe Patterson-UTI Energy Paychex PBL-Publish & Broadcast PCCW Peabody Energy Pearson Pendragon Penn West Petroleum People’s Bank Pepco Holdings Pepsi Bottling Group PepsiCo Pernod Ricard Persimmon Petro-Canada Petrobras-Petróleo Brasil PetroChina Petrol Ofisi Petroplus Holdings Peugeot Groupe Pfizer

Hong Kong/China Greece United States Egypt Egypt Australia Japan India Japan Australia Japan Norway Japan United States Hungary Finland Singapore United States United States United States United Kingdom United States Italy Bermuda United States United States Australia Hong Kong/China United States United Kingdom United Kingdom Canada United States United States United States United States France United Kingdom Canada Brazil China Turkey Switzerland France United States

Transportation Hotels, Restaurants & Leisure Software & Services Construction Telecommunications Services Chemicals Diversified Financials Banking Media Utilities Diversified Financials Food Drink & Tobacco Utilities Capital Goods Banking Materials Banking Construction Materials Consumer Durables Diversified Financials Capital Goods Food Drink & Tobacco Insurance Oil & Gas Operations Business Services & Supplies Media Telecommunications Services Materials Media Retailing Oil & Gas Operations Banking Utilities Food Drink & Tobacco Food Drink & Tobacco Food Drink & Tobacco Construction Oil & Gas Operations Oil & Gas Operations Oil & Gas Operations Oil & Gas Operations Oil & Gas Operations Consumer Durables Drugs & Biotechnology

381

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GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

PG&E Pgnig-Polskie Górnictwo Naftowe Phelps Dodge Phoenix Cos PICC Property & Casualty Ping An Insurance Group Pinnacle West Pioneer Pioneer Natural Res Piraeus Bank Pirelli & C Pitney Bowes PKN Orlen PKO Bank Polski Plains Exploration & Production PLDT-Philippine LDT Plum Creek Timber PMI Group PNC Financial Services Pogo Producing Polo Ralph Lauren Polyus Gold Popular Porsche Portugal Telecom Posco Potash of Saskatchewan Power Corp of Canada PPG Industries PPL PPR Praxair Precision Castparts Precision Drilling Pride International Principal Financial Prisa Group Procter & Gamble Progress Energy Progressive ProLogis Promise Protective Life Prudential Prudential Financial

United States Poland United States United States China China United States Japan United States Greece Italy United States Poland Poland United States Philippines United States United States United States United States United States Russia United States Germany Portugal South Korea Canada Canada United States United States France United States United States Canada United States United States Spain United States United States United States United States Japan United States United Kingdom United States

Utilities Oil & Gas Operations Materials Insurance Insurance Insurance Utilities Technology Hardware & Equip Oil & Gas Operations Banking Consumer Durables Business Services & Supplies Oil & Gas Operations Banking Oil & Gas Operations Telecommunications Services Diversified Financials Insurance Banking Oil & Gas Operations Household & Personal Products Materials Banking Consumer Durables Telecommunications Services Materials Chemicals Diversified Financials Chemicals Utilities Retailing Chemicals Aerospace & Defence Oil & Gas Operations Oil & Gas Operations Diversified Financials Media Household & Personal Products Utilities Insurance Diversified Financials Diversified Financials Insurance Insurance Insurance

13:13

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LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

PTT Public Company Pub Svc Enterprise Public Bank Public Power Public Storage Publicis Groupe Pulte Homes Puma Punch Taverns Punjab National Bank Pusan Bank Qantas Airways QBE Insurance Group Qimonda Qualcomm Quanta Computer Quest Diagnostics Questar Qwest Communications Radian Group Raiffeisen International Bank-Holding Rakuten Randstad Holding Rashid Hussain Rautaruukki Raymond James Finl Rayong Refinery Raytheon Realogy Reckitt Benckiser Red Eléctrica de España Redwood Trust Reed Elsevier

Thailand United States Malaysia Greece United States France United States Germany United Kingdom India South Korea Australia Australia Germany United States Taiwan/China United States United States United States United States Austria

Oil & Gas Operations Utilities Banking Utilities Diversified Financials Media Construction Household & Personal Products Hotels, Restaurants & Leisure Banking Banking Transportation Insurance Semiconductors Technology Hardware & Equip Technology Hardware & Equip Health Care Equipment & Svcs Utilities Telecommunications Services Insurance Banking

Japan Netherlands Malaysia Finland United States Thailand United States United States United Kingdom Spain United States United Kingdom/ Netherlands United States India United States United States South Africa Bermuda France Norway United Kingdom Spain

Business Services & Supplies Business Services & Supplies Banking Materials Diversified Financials Oil & Gas Operations Aerospace & Defence Diversified Financials Household & Personal Products Utilities Diversified Financials Media

Regions Financial Reliance Industries Reliance Steel Reliant Energy Remgro RenaissanceRe Holdings Renault Renewable Energy Rentokil Initial Repsol-YPF

Banking Oil & Gas Operations Materials Utilities Conglomerates Insurance Consumer Durables Capital Goods Business Services & Supplies Oil & Gas Operations

383

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GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Republic Services Research In Motion Resolution Resona Holdings Reuters Group Rexam Reynolds American RH Donnelley Rhodia Richemont Ricoh Rinker Group Rio Tinto

United States Canada United Kingdom Japan United Kingdom United Kingdom United States United States France Switzerland Japan Australia United Kingdom/ Australia United States Saudi Arabia United States Switzerland United States United States Canada Japan United States United Kingdom Russia United States United Kingdom Netherlands Canada United Kingdom Liberia Netherlands Netherlands Netherlands Netherlands Netherlands United States Luxembourg Germany Ireland United States United States South Korea Turkey Brazil

Business Services & Supplies Technology Hardware & Equip Insurance Banking Media Materials Food Drink & Tobacco Media Chemicals Household & Personal Products Technology Hardware & Equip Construction Materials

Rite Aid Riyad Bank Robert Half Intl Roche Holding Rockwell Automation Rockwell Collins Rogers Communications Rohm Rohm and Haas Rolls-Royce Group Rosneft Ross Stores Royal & Sun Alliance Royal BAM Group Royal Bank of Canada Royal Bank of Scotland Royal Caribbean Royal DSM Royal Dutch Shell Royal KPN Royal Numico Royal Philips Electronics RR Donnelley & Sons RTL Group RWE Group Ryanair Holdings Ryder System Ryland Group S-Oil Sabanci Group Sabesp-Saneamento Basico

Retailing Banking Business Services & Supplies Drugs & Biotechnology Capital Goods Aerospace & Defence Telecommunications Services Semiconductors Chemicals Aerospace & Defence Oil & Gas Operations Retailing Insurance Construction Banking Banking Hotels, Restaurants & Leisure Chemicals Oil & Gas Operations Telecommunications Services Food Drink & Tobacco Conglomerates Media Media Utilities Transportation Business Services & Supplies Construction Oil & Gas Operations Conglomerates Utilities

13:13

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LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

SABMiller Sacyr Vallehermoso Safeco Safeway Safran Sage Group SAIC Saint-Gobain Salzgitter Sampo Samsung Samsung Electronics Samsung Fire & Marine Samsung Heavy Industries Samsung SDI San-Ai Oil San-In Godo Bank SanDisk Sandvik Sankyo Sanlam Sanmina-SCI Sanofi-aventis SanomaWSOY Santos Sanyo Electric SAP Sapporo Hokuyo Sara Lee Saras SAS Group Sasol Satyam Computer Services Saudi Basic Industries Saudi Electricity Saudi Telecommunications Sberbank SCA-Svenska Cellulosa Scana Scania Schering-Plough Schindler Holding Schlumberger Schneider Electric Schroders

United Kingdom Spain United States United States France United Kingdom United States France Germany Finland South Korea South Korea South Korea South Korea South Korea Japan Japan United States Sweden Japan South Africa United States France Finland Australia Japan Germany Japan United States Italy Sweden South Africa India Saudi Arabia Saudi Arabia Saudi Arabia Russia Sweden United States Sweden United States Switzerland Netherlands France United Kingdom

Food Drink & Tobacco Construction Insurance Food Markets Aerospace & Defence Software & Services Business Services & Supplies Construction Materials Insurance Trading Companies Semiconductors Insurance Capital Goods Technology Hardware & Equip Oil & Gas Operations Banking Technology Hardware & Equip Capital Goods Consumer Durables Insurance Technology Hardware & Equip Drugs & Biotechnology Media Oil & Gas Operations Technology Hardware & Equip Software & Services Banking Food Drink & Tobacco Oil & Gas Operations Transportation Oil & Gas Operations Software & Services Chemicals Utilities Telecommunications Services Banking Household & Personal Products Utilities Capital Goods Drugs & Biotechnology Capital Goods Oil & Gas Operations Capital Goods Diversified Financials

385

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386

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GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Scor Scottish & Newcastle Scottish & Southern Scottish Power Scottish Re Group Seadrill Seagate Technology Sealed Air Sears Holdings SEB-Skand Enskilda Bank Secom Securitas Sega Sammy Holdings SEI Investments Seiko Epson Sekisui Chemical Sekisui House SembCorp Industries Sempra Energy SES Global Seven & I Holdings Severn Trent Severstal SGS Shanghai Automotive Shanghai Electric Group Shanghai International Port Shanghai Pudong Dev Bk Sharp Shaw Communications Shenzhen Develop Bank Sherwin-Williams Shiga Bank Shikoku Bank Shikoku Electric Power Shimizu Shin Kong Financial Shin-Etsu Chemical Shinhan Financial Shinko Securities Shinsegae Shinsei Bank Shire Shiseido Shizuoka Bank

France United Kingdom United Kingdom United Kingdom Bermuda Bermuda Cayman Islands United States United States Sweden Japan Sweden Japan United States Japan Japan Japan Singapore United States Luxembourg Japan United Kingdom Russia Switzerland China China China China Japan Canada China United States Japan Japan Japan Japan Taiwan/China Japan South Korea Japan South Korea Japan United Kingdom Japan Japan

Insurance Food Drink & Tobacco Utilities Utilities Insurance Oil & Gas Operations Technology Hardware & Equip Materials Retailing Banking Business Services & Supplies Business Services & Supplies Consumer Durables Diversified Financials Technology Hardware & Equip Conglomerates Construction Conglomerates Utilities Media Food Markets Utilities Materials Business Services & Supplies Consumer Durables Capital Goods Transportation Banking Technology Hardware & Equip Media Banking Retailing Banking Banking Utilities Construction Diversified Financials Chemicals Banking Diversified Financials Retailing Banking Drugs & Biotechnology Household & Personal Products Banking

13:13

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LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

Shoppers Drug Mart Showa Denko Showa Shell Sekiyu Siam Cement Siam Commercial Bank Siemens Sierra Pacific Res Sigma-Aldrich Sime Darby Simon Property Group Singapore Airlines Singapore Petroleum Singapore Technologies Singapore Telecom Sino Land SinoPac Financial Holdings Sinopec-China Petroleum Sistema JSFC SK Corp Skanska SKF Group Sky Financial Group SL Green Realty Slavneft Megioneft SLM Slough Estates SMC Smith & Nephew Smith International Smithfield Foods Smiths Group Smurfit-Stone SNC-Lavalin Group SNS Reaal Société Générale Group Sodexho Alliance Softbank Sojitz Solectron Solvay Group Sompo Japan Insurance Sonae SGPS Songbird Estates Sonic Automotive Sony

Canada Japan Japan Thailand Thailand Germany United States United States Malaysia United States Singapore Singapore Singapore Singapore Hong Kong/China Taiwan/China China Russia South Korea Sweden Sweden United States United States Russia United States United Kingdom Japan United Kingdom United States United States United Kingdom United States Canada Netherlands France France Japan Japan United States Belgium Japan Portugal United Kingdom United States Japan

Retailing Chemicals Oil & Gas Operations Construction Banking Conglomerates Utilities Chemicals Conglomerates Diversified Financials Transportation Oil & Gas Operations Aerospace & Defence Telecommunications Services Diversified Financials Banking Oil & Gas Operations Telecommunications Services Oil & Gas Operations Construction Capital Goods Banking Diversified Financials Oil & Gas Operations Diversified Financials Diversified Financials Capital Goods Health Care Equipment & Svcs Oil & Gas Operations Food Drink & Tobacco Conglomerates Materials Construction Banking Banking Business Services & Supplies Software & Services Trading Companies Technology Hardware & Equip Chemicals Insurance Food Markets Diversified Financials Retailing Technology Hardware & Equip

387

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GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Soriana South Financial Group Southern Co Southwest Airlines Sovereign Bancorp Spectra Energy Sprint Nextel SPX SSAB Svenskt Stal St Galler Kantonalbank St George Bank St Jude Medical StanCorp Financial Standard Bank Group Standard Chartered Group Standard Life Stanley Works Staples Starbucks Starwood Hotels State Bank of India Group State Street Statoil Group Steel Authority of India Steel Dynamics Steinhoff Intl Holdings STMicroelectronics Stockland Stora Enso Storebrand Stryker Südzucker Suez Group Sumco Sumikin Bussan Sumitomo Sumitomo Chemical Sumitomo Electric Sumitomo Forestry Sumitomo Heavy Inds Sumitomo Metal Inds Sumitomo Metal Mining Sumitomo Mitsui Construct Sumitomo Mitsui Financial Sumitomo Realty & Dev

Mexico United States United States United States United States United States United States United States Sweden Switzerland Australia United States United States South Africa United Kingdom United Kingdom United States United States United States United States India United States Norway India United States South Africa Switzerland Australia Finland Norway United States Germany France Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan

Retailing Banking Utilities Transportation Banking Oil & Gas Operations Telecommunications Services Conglomerates Materials Banking Banking Health Care Equipment & Svcs Insurance Banking Banking Insurance Household & Personal Products Retailing Hotels, Restaurants & Leisure Hotels, Restaurants & Leisure Banking Diversified Financials Oil & Gas Operations Materials Materials Consumer Durables Semiconductors Diversified Financials Materials Insurance Health Care Equipment & Svcs Food Drink & Tobacco Utilities Semiconductors Trading Companies Trading Companies Chemicals Capital Goods Construction Capital Goods Materials Materials Construction Banking Diversified Financials

13:13

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LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

Sumitomo Rubber Sumitomo Trust & Banking Sun Hung Kai Properties Sun Life Financial Sun Microsystems Suncor Energy Suncorp-Metway Sunoco SunTrust Banks Supervalu Suramericana Surgutneftegas Suruga Bank Suzuken Suzuki Motor Svenska Handelsbanken Swatch Group Swedbank Swedish Match Swire Pacific Swiss Life Holding Swiss Re Group Swisscom Sydbank Symantec Syndicate Bank Syngenta Synnex Synovus Financial Synthes Sysco T Rowe Price T&D Holdings TabCorp Holdings Taiheiyo Cement Taisei Taishin Financial Holding Taisho Pharmaceutical Taiwan Business Bank Taiwan Cooperative Bank Taiwan Mobile Taiwan Semiconductor Takashimaya Takeda Pharmaceutical Takefuji

Japan Japan Hong Kong/China Canada United States Canada Australia United States United States United States Colombia Russia Japan Japan Japan Sweden Switzerland Sweden Sweden Hong Kong/China Switzerland Switzerland Switzerland Denmark United States India Switzerland United States United States Switzerland United States United States Japan Australia Japan Japan Taiwan Japan Taiwan/China Taiwan/China Taiwan/China Taiwan/China Japan Japan Japan

Consumer Durables Banking Diversified Financials Insurance Technology Hardware & Equip Oil & Gas Operations Diversified Financials Oil & Gas Operations Banking Food Markets Diversified Financials Oil & Gas Operations Banking Health Care Equipment & Svcs Consumer Durables Banking Household & Personal Products Banking Food Drink & Tobacco Conglomerates Insurance Insurance Telecommunications Services Banking Software & Services Banking Chemicals Software & Services Banking Health Care Equipment & Svcs Food Markets Diversified Financials Insurance Hotels, Restaurants & Leisure Construction Construction Banking Drugs & Biotechnology Banking Banking Telecommunications Services Semiconductors Retailing Drugs & Biotechnology Diversified Financials

389

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390

GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Talisman Energy Target Tata Consultancy Svcs Tata Motors Tata Steel Tate & Lyle Group Tatneft Tatung Taylor Woodrow TCF Financial TCL Corp TD Ameritrade Holding TDC Group TDK Tech Data Technip Teck Cominco TECO Energy Teekay Shipping Teijin Tele & Data Systems Tele Norte Leste Tele2 Telecom Argentina Telecom Egypt Telecom Italia Telecom of New Zealand Telefónica Teléfonos de Venezuela Telekom Austria Telekom Indonesia Telekom Malaysia Telenor Telent TeliaSonera Group Telkom Telstra Telus Temple-Inland Tenaga Nasional Tenaris Tenet Healthcare Terex Terna Ternium

Canada United States India India India United Kingdom Russia Taiwan/China United Kingdom United States China United States Denmark Japan United States France Canada United States Bahamas Japan United States Brazil Sweden Argentina Egypt Italy New Zealand Spain Venezuela Austria Indonesia Malaysia Norway United Kingdom Sweden South Africa Australia Canada United States Malaysia Luxembourg United States United States Italy Luxembourg

Oil & Gas Operations Retailing Software & Services Capital Goods Materials Food Drink & Tobacco Oil & Gas Operations Technology Hardware & Equip Construction Banking Technology Hardware & Equip Diversified Financials Telecommunications Services Technology Hardware & Equip Technology Hardware & Equip Oil & Gas Operations Materials Utilities Transportation Chemicals Telecommunications Services Telecommunications Services Telecommunications Services Telecommunications Services Telecommunications Services Telecommunications Services Telecommunications Services Telecommunications Services Telecommunications Services Telecommunications Services Telecommunications Services Telecommunications Services Telecommunications Services Technology Hardware & Equip Telecommunications Services Telecommunications Services Telecommunications Services Telecommunications Services Materials Utilities Oil & Gas Operations Health Care Equipment & Svcs Capital Goods Utilities Materials

8/10/10

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8/10/10

LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

Terumo Tesco Tesoro Teva Pharmaceutical Inds Texas Instruments Textron Thai Airways Intl Thai Oil Thales Thermo Fisher Thomson Thomson Corp Thornburg Mortgage ThyssenKrupp Group Tiffany & Co Tim Hortons Time Warner Titanium Metals TJX Cos TMB Bank TMK TNK-BP Holding TNT Tobu Railway Tochigi Bank Toho Bank Tohoku Electric Power Tokyo Electric Power Tokyo Electron Tokyo Gas Tokyo Leasing Tokyo Tomin Bank Tokyu Tokyu Land Toll Brothers Toll Holdings Tomkins TomTom Tong Yang Investment Bank Toppan Printing Toray Industries Torchmark Toronto-Dominion Bank Toshiba Tosoh

Japan United Kingdom United States Israel United States United States Thailand Thailand France United States France Canada United States Germany United States Canada United States United States United States Thailand Russia Russia Netherlands Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan Japan United States Australia United Kingdom Netherlands South Korea Japan Japan United States Canada Japan Japan

Health Care Equipment & Svcs Food Markets Oil & Gas Operations Drugs & Biotechnology Semiconductors Conglomerates Transportation Oil & Gas Operations Aerospace & Defence Health Care Equipment & Svcs Technology Hardware & Equip Media Diversified Financials Conglomerates Retailing Hotels, Restaurants & Leisure Media Materials Retailing Banking Materials Oil & Gas Operations Transportation Transportation Banking Banking Utilities Utilities Semiconductors Utilities Business Services & Supplies Banking Transportation Diversified Financials Construction Transportation Conglomerates Technology Hardware & Equip Diversified Financials Media Household & Personal Products Insurance Banking Technology Hardware & Equip Chemicals

391

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392

GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Total Towa Bank Toyo Seikan Kaisha Toyota Boshoku Toyota Industries Toyota Motor Toyota Tsusho TransCanada Transocean Travelers Cos Travis Perkins Triad Hospitals Tribune TRW Automotive Hldgs TrygVesta TUI Tüpras-Türkiye Petrol Turkcell Türkiye Garanti Bankasi Türkiye Is Bankasi Türkiye Vakıflar TXU Tyco International Tyson Foods UAL Ube Industries UBS UCB UCO Bank UES of Russia UFJ Central Leasing UGI Ultra Petroleum Umicore Uni-President Unibail Unibanco Group UniCredito Italiano Unilever

France Japan Japan Japan Japan Japan Japan Canada Cayman Islands United States United Kingdom United States United States United States Denmark Germany Turkey Turkey Turkey Turkey Turkey United States Bermuda United States United States Japan Switzerland Belgium India Russia Japan United States United States Belgium Taiwan/China France Brazil Italy Netherlands/ United Kingdom India Spain United States Italy Austria

Oil & Gas Operations Banking Materials Consumer Durables Consumer Durables Consumer Durables Trading Companies Utilities Oil & Gas Operations Insurance Retailing Health Care Equipment & Svcs Media Consumer Durables Insurance Hotels, Restaurants & Leisure Oil & Gas Operations Telecommunications Services Banking Banking Banking Utilities Conglomerates Food Drink & Tobacco Transportation Chemicals Diversified Financials Drugs & Biotechnology Banking Utilities Business Services & Supplies Utilities Oil & Gas Operations Materials Food Drink & Tobacco Diversified Financials Banking Banking Food Drink & Tobacco

Union Bank of India Unión Fenosa Union Pacific Unipol Assicurazioni Uniqa

Banking Utilities Transportation Insurance Insurance

8/10/10

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8/10/10

LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

United Auto Group United Microelectronics United Overseas Bank United Parcel Service United Rentals United Technologies United Utilities UnitedHealth Group Unitrin Universal Health Univision Commun Unum Group UNY UPM-Kymmene Ural-Siberian Bank US Airways Group US Bancorp US Steel USG Usiminas UST Vale do Rio Doce Valeo Valero Energy Valiant Holding Vallourec Van Lanschot Varian Medical Systems Vattenfall Europe Vedanta Resources Vedior Veolia Environnement Verbund VeriSign Verizon Communications Vestas Wind Systems VF Viacom Vicat Vienna Insurance Group VimpelCom Vinci Group Virgin Media Visteon Vivendi

United States Taiwan/China Singapore United States United States United States United Kingdom United States United States United States United States United States Japan Finland Russia United States United States United States United States Brazil United States Brazil France United States Switzerland France Netherlands United States Germany United Kingdom Netherlands France Austria United States United States Denmark United States United States France Austria Russia France United States United States France

Retailing Semiconductors Banking Transportation Business Services & Supplies Conglomerates Utilities Health Care Equipment & Svcs Insurance Health Care Equipment & Svcs Media Insurance Food Markets Materials Banking Transportation Banking Materials Construction Materials Food Drink & Tobacco Materials Consumer Durables Oil & Gas Operations Banking Capital Goods Diversified Financials Health Care Equipment & Svcs Utilities Materials Business Services & Supplies Utilities Utilities Software & Services Telecommunications Services Capital Goods Household & Personal Products Media Construction Insurance Telecommunications Services Construction Telecommunications Services Consumer Durables Media

393

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394

GLOBAL URBAN ANALYSIS

COMPANY

COUNTRY

INDUSTRY

Vodafone voestalpine Volkswagen Group Volvo Group Vornado Realty Vulcan Materials W Holding W&W-Wüstenrot Wachovia Wacker Chemie Wal-Mart Stores Walgreen Walt Disney Wärtsilä Washington Mutual Washington Post Waste Management Weatherford Intl Webster Financial WellPoint Wells Fargo Wendel Investissement Wesco International Wesfarmers West Japan Railway Western Digital Western Union Westfield Group Westpac Banking Group Weyerhaeuser Wharf (Holdings) Wheelock & Co Whirlpool Whitbread White Mountains Ins Whole Foods Market William Hill Williams Cos Willis Group Holdings Windstream Wing Hang Bank Wing Lung Bank Winn-Dixie Stores Wipro Wisconsin Energy

United Kingdom Austria Germany Sweden United States United States United States Germany United States Germany United States United States United States Finland United States United States United States Bermuda United States United States United States France United States Australia Japan United States United States Australia Australia United States Hong Kong/China Hong Kong/China United States United Kingdom Bermuda United States United Kingdom United States United Kingdom United States Hong Kong/China Hong Kong/China United States India United States

Telecommunications Services Materials Consumer Durables Capital Goods Diversified Financials Construction Banking Diversified Financials Banking Chemicals Retailing Retailing Media Capital Goods Banking Media Business Services & Supplies Oil & Gas Operations Banking Health Care Equipment & Svcs Banking Diversified Financials Capital Goods Conglomerates Transportation Technology Hardware & Equip Business Services & Supplies Diversified Financials Banking Materials Conglomerates Diversified Financials Consumer Durables Hotels, Restaurants & Leisure Insurance Food Markets Hotels, Restaurants & Leisure Utilities Insurance Telecommunications Services Banking Banking Food Markets Software & Services Utilities

8/10/10

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8/10/10

LISTS OF FIRMS AND CITIES

COMPANY

COUNTRY

INDUSTRY

Wm Morrison Supermarkets Wm Wrigley Jr Wolseley Wolters Kluwer Woodside Petroleum Woolworths Woori Finance Holdings World Fuel Services WPP WR Berkley Wuhan Iron & Steel Wuliangye Yibin WW Grainger Wyeth Wyndham Worldwide Wynn Resorts Xcel Energy Xerox Xilinx XL Capital Xstrata XTO Energy Yahoo Yamada Denki Yamagata Bank Yamaha Yamaha Motor Yamanashi Chuo Bank Yamato Holdings Yamazaki Baking Yanzhou Coal Mining Yara International Yell Group YIT Group YRC Worldwide YTL Yum Brands Zimmer Holdings Zinifex Zions Bancorp Zurich Financial Services

United Kingdom United States United Kingdom Netherlands Australia Australia South Korea United States United Kingdom United States China China United States United States United States United States United States United States United States Bermuda Switzerland United States United States Japan Japan Japan Japan Japan Japan Japan China Norway United Kingdom Finland United States Malaysia United States United States Australia United States Switzerland

Food Markets Food Drink & Tobacco Trading Companies Media Oil & Gas Operations Food Markets Banking Business Services & Supplies Media Insurance Materials Food Drink & Tobacco Capital Goods Drugs & Biotechnology Hotels, Restaurants & Leisure Hotels, Restaurants & Leisure Utilities Business Services & Supplies Semiconductors Insurance Materials Oil & Gas Operations Software & Services Retailing Banking Consumer Durables Consumer Durables Banking Transportation Food Drink & Tobacco Materials Chemicals Media Construction Transportation Utilities Hotels, Restaurants & Leisure Health Care Equipment & Svcs Materials Banking Insurance

395

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All 200 Firms in the Network Analyses Firms used in the network analyses were chosen by their ranking in lists of the largest firms in each sector: •

•

Financial services: the 75 most important banking, insurance and ‘diversified finance’ firms in the Forbes composite index (based on a combination of rankings for sales, profits, assets and market value lists, see www.forbes.com/lists/results) were combined. Media: we also used the Forbes composite index to single out the 25 biggest firms.

For the other four studied services – accountancy, advertising, law and management consultancy – we included the top 25 firms from different sector rankings: • • • •

Law: Chambers list of corporate law firms (www.chambersandpartners.com/global). Advertising agency networks: Advertising Age’s ranking of ‘marketing organizations’ by revenues (www.adage.com/images/random/lna2007). Accountancy firms’ networks: World Accounting Intelligence (www.worldaccountingintelligence.com), which ranks by revenues. Management consultancies: the 2007 edition of the Vault Management & Strategy Consulting Survey, which ranks firms in terms of their ‘prestige’ based on a large survey of professionals (www.vault.com).

In all cases the lists of firms selected were the latest available at the planning of the research project in 2007 and these tended to be based upon 2006 data. There was no way to overcome this two-year delay: one year was because planning the project takes time and the second year was because of a one-year time lag in reporting such data. For all lists substitute firms were identified (ranked just below 75 and 25) to cover for situations where a firm had disappeared (e.g. been taken over) in the two years before the actual data collection. The selected firms are listed below in alphabetical order.

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FINANCIAL SERVICES ABN AMRO Holding Aegon Allianz Allied Irish Banks American Express American International Group ANZ Banking Aviva AXA Group Banco Bradesco Banco do Brasil Bank of America Bank of China Bank of Montreal Bank of Nova Scotia Barclays Berkshire Hathaway BNP Paribas Canadian Imperial Bank Capital One Financial CCB-China Construction Bank Citigroup Commerzbank Commonwealth Bank Countrywide Financial Credit Suisse Group Danske Bank Group Deutsche Bank Dexia Fannie Mae Fortis Freddie Mac Generali Group Goldman Sachs Group HBOS HSBC Holdings ICBC ING Group

JPMorgan Chase KBC Group Legal & General Group Lehman Brothers Holdings Lloyds TSB Group Loews Manulife Financial Merrill Lynch MetLife Mitsubishi UFJ Financial Group Mizuho Financial Group Morgan Stanley Munich Re National Australia Bank Nomura Holdings Nordea Bank Old Mutual Prudential Royal Bank of Canada Royal Bank of Scotland Sberbank Société Générale Group Standard Chartered Group Sumitomo Mitsui Financial Group Sun Life Financial Sun Trust Banks Swiss Re Group Toronto-Dominion Bank Travelers Cos UBS UniCredito Italiano US Bancorp Wachovia Washington Mutual Wells Fargo Westpac Banking Group Zurich Financial Services

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ACCOUNTANCY AGN International Baker Tilly International BDO International BKR International CPA Associates International Deloitte Touche Tohmatsu DFK International Ernst & Young Global Grant Thornton International HLB International Horwath International KPMG International Kreston International

KS International Leading Edge Alliance Moore Stephens International Moores Rowland International Morison International MSI Legal & Accounting Network Worldwide Nexia International PKF International Polaris International PricewaterhouseCoopers International RSM International UHY International

ADVERTISING Asatsu-DK BBDO Worldwide ComVort Group DDB Worldwide Communications Group Dentsu DraftFCB Euro RSCG Worldwide Grey Worldwide Hakuhodo Havas Advertising Agencies JWT Leo Burnett Worldwide McCann Erickson Worldwide

MindShare Worldwide ODM Ogilvy and Mather Worldwide OgilvyOne Worldwide Publicis Saatchi & Saatchi Starcom MediaVest Group TBWA Worldwide Worldwide Partners Wunderman Y&R ZenithOptimedia

LEGAL SERVICES Allen & Overy LLP Ashurst Baker & McKenzie LLP Cleary Gottlieb Steen & Hamilton LLP Clifford Chance LLP CMS Cameron McKenna LLP Cravath, Swaine & Moore LLP Davis Polk & Wardwell LLP Debevoise & Plimpton LLP DLA Piper US LLP Freshfields Bruckhaus Deringer LLP Gide Loyrette Nouel AARPI Hengeler Mueller

Herbert Smith LLP Jones Day Latham & Watkins LLP Linklaters Shearman & Sterling LLP Simpson Thacher & Bartlett LLP Skadden, Arps, Slate, Meagher & Flom LLP & Affiliates Slaughter and May Sullivan & Cromwell LLP Wachtell, Lipton, Rosen & Katz Weil, Gotshal & Manges LLP White & Case LLP

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MANAGEMENT CONSULTANCY A.T. Kearney Accenture Bain & Company Booz Allen Hamilton Cambridge Associates LLC Capgemini Deloitte Consulting LLP Gartner, Inc. Hewitt Associates IBM Global Services Katzenbach Partners LLC L.E.K. Consulting Marakon Associates

McKinsey & Company Mercer Delta Organizational Consulting Mercer Human Resource Consulting Mercer Management Consulting Mercer Oliver Wyman Monitor Group Roland Berger Strategy Consultants The Boston Consulting Group The Parthenon Group Towers Perrin Watson Wyatt Worldwide ZS Associates

MEDIA British Sky Broadcasting CBS Clear Channel Communications Comcast DirecTV Group EchoStar Communications Fuji Television Network Gannett Grupo Televisa ITV Lagardère SCA News Corporation Reed Elsevier

Reuters Group RR Donnelley & Sons RTL Group SES Global The McGraw-Hill Companies The Thomson Corporation Time Warner Toppan Printing Tribune Viacom Vivendi Wolters Kluwer

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All 525 Cities in the Network Analyses The 525 cities examined in this book are the 315 used in earlier Globalization and World Cities (GaWC) analyses (see Taylor et al, 2002), complemented with an extra set of cities selected on the basis of a number of overlapping criteria: all cities with a population of more than 2 million inhabitants were included, which led to the consideration of far more cities located in China, India, Pakistan and Iran. We also included a ‘second city’ of all but the smallest states plus other important cities in larger states. The latter selection was in part based on a systematic comparison with the airline data presented in Derudder and Witlox (2005). CITY

COUNTRY

Aberdeen Abidjan Abu Dhabi Abuja Acapulco Accra Addis Ababa Adelaide Agra Ahmedabad Akita Albuquerque Alexandria Algiers Allahabad Allentown Almaty Amman Amritsar Amsterdam Anchorage Ankara Antananarivo Antwerp Arhus Asansol Ashgabat Asmara Asunción Athens Atlanta Auckland Austin Baghdad Baku Baltimore Bamako Bandar Seri Begawan

United Kingdom Côte d’Ivoire United Arab Emirates Nigeria Mexico Ghana Ethiopia Australia India India Japan United States Egypt Algeria India United States Kazakhstan Jordan India Netherlands United States Turkey Madagascar Belgium Denmark India Turkmenistan Eritrea Paraguay Greece United States New Zealand United States Iraq Azerbaijan United States Mali Brunei

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CITY

COUNTRY

Bandung Bangalore Bangkok Bangui Barcelona Barranquilla Basel Battle Creek Beijing Beirut Belém Belfast Belgrade Belo Horizonte Bentonville Bergen Berlin Bern Bhilai Bhopal Bhubaneswar Bilbao Birmingham Birmingham Bishkek Bissau Blantyre Bogotá Bologna Bordeaux Boston Brasília Bratislava Brazzaville Bremen Brisbane Bristol Brussels Bucharest Budapest Buenos Aires Buffalo Bulawayo Bursa Cairo Calcutta Calgary Cali Campinas

Indonesia India Thailand Central African Republic Spain Colombia Switzerland United States China Lebanon Brazil United Kingdom Serbia Brazil United States Norway Germany Switzerland India India India Spain United Kingdom United States Kyrgyzstan Guinea-Bissau Malawi Colombia Italy France United States Brazil Slovakia Congo Germany Australia United Kingdom Belgium Romania Hungary Argentina United States Zimbabwe Turkey Egypt India Canada Colombia Brazil

401

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CITY

COUNTRY

Canberra Cape Town Caracas Cardiff Casablanca Cebu Chandigarh Changsha Charleston Charlotte Chattanooga Chelyabinsk Chengdu Chennai Chiba Chicago Chihuahua Chisinau Chittagong Chongqing Christchurch Cincinnati Ciudad Juárez Clermont-Ferrand Cleveland Cochin Coimbatore Cologne Colombo Columbus Conakry Copenhagen Córdoba Cotonou Curitiba Daejeon Dakar Dalian Dallas Damascus Dammam Danbury Dar es Salaam Davao Dehradun Denver Des Moines Detroit Dhaka

Australia South Africa Venezuela United Kingdom Morocco Philippines India China United States United States United States Russia China India Japan United States Mexico Moldova Bangladesh China New Zealand United States Mexico France United States India India Germany Sri Lanka United States Guinea Denmark Spain Benin Brazil South Korea Senegal China United States Syria Saudi Arabia United States Tanzania Philippines India United States United States United States Bangladesh

5

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CITY

COUNTRY

Dili Djibouti Doha Donetsk Dortmund Douala Dresden Dubai Dublin Duisburg Durban Dushanbe Düsseldorf Edinburgh Edmonton Essen Faisalabad Florence Fortaleza Frankfurt Freetown Fukuoka Fuzhou Gaborone Gaza Geneva Genoa George Town Georgetown Glasgow Goiânia Gothenburg Graz Greensboro Guadalajara Guangzhou Guatemala City Guayaquil Guiyang Gujranwala Gwangju Haifa Halifax Hamamatsu Hamburg Hamilton Hangzhou Hannover Hanoi

East Timor Djibouti Qatar Ukraine Germany Cameroon Germany United Arab Emirates Ireland Germany South Africa Tajikistan Germany United Kingdom Canada Germany Pakistan Italy Brazil Germany Sierra Leone Japan China Botswana Palestine Switzerland Italy Cayman Islands Guyana United Kingdom Brazil Sweden Austria United States Mexico China Guatemala Ecuador China Pakistan South Korea Israel Canada Japan Germany Bermuda China Germany Vietnam

403

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CITY

COUNTRY

Harare Hartford Havana Hefei Heidelberg Helsinki Hiroshima Ho Chi Minh City Hobart Hong Kong Honolulu Houston Hsinchu City Hyderabad Hyderabad Ibadan Incheon Indianapolis Indore Isfahan Islamabad Istanbul Izmir Jacksonville Jaipur Jakarta Jeddah Jerusalem Jinan Johannesburg Johor Baharu Kabul Kampala Kano Kanpur Kansas City Kaohsiung Karachi Karlsruhe Kathmandu Kawasaki Kazan Kharkov Khartoum Kiev Kigali Kingston Kingston Kinshasa

Zimbabwe United States Cuba China Germany Finland Japan Vietnam Australia China United States United States Taiwan/China India Pakistan Nigeria South Korea United States India Iran Pakistan Turkey Turkey United States India Indonesia Saudi Arabia Israel China South Africa Malaysia Afghanistan Uganda Nigeria India United States Taiwan/China Pakistan Germany Nepal Japan Russia Ukraine Sudan Ukraine Rwanda Canada Jamaica Congo

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CITY

COUNTRY

Kitakyushu Kobe Kraków Krasnoyarsk Kuala Lumpur Kumasi Kunming Kuwait City Kyoto La Paz Labuan Lagos Lahore Lanzhou Las Vegas Lausanne Leeds Leicester Leipzig León Leverkusen Libreville Liège Lille Lilongwe Lima Linz Lisbon Little Rock Liverpool Ljubljana Łód´z Lomé London Los Angeles Luanda Lucknow Ludhiana Ludwigshafen Lusaka Luxembourg Lyon Macao Madison Madrid Madurai Malabo Malacca Malmö

Japan Japan Poland Russia Malaysia Ghana China Kuwait Japan Bolivia Malaysia Nigeria Pakistan China United States Switzerland United Kingdom United Kingdom Germany Mexico Germany Gabon Belgium France Malawi Peru Austria Portugal United States United Kingdom Slovenia Poland Togo United Kingdom United States Angola India India Germany Zambia Luxembourg France China United States Spain India Equatorial Guinea Malaysia Sweden

405

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CITY

COUNTRY

Managua Manama Manaus Manchester Manila Maputo Maracaibo Marseille Maseru Mashhad Mbabane Medan Medellín Meerut Melbourne Memphis Mexico City Miami Milan Milwaukee Minneapolis Minsk Mogadishu Mombasa Monrovia Monterrey Montevideo Montpellier Montreal Moscow Multan Mumbai Munich Muscat Nagoya Nagpur Naha Nairobi Nanjing Nantes Naples Nashville Nassau Ndjamena New Delhi New Orleans New York Newcastle Niamey

Nicaragua Bahrain Brazil United Kingdom Philippines Mozambique Venezuela France Lesotho Iran Swaziland Indonesia Colombia India Australia United States Mexico United States Italy United States United States Belarus Somalia Kenya Liberia Mexico Uruguay France Canada Russia Pakistan India Germany Oman Japan India Japan Kenya China France Italy United States Bahamas Chad India United States United States United Kingdom Niger

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CITY

COUNTRY

Nice Nicosia Ningbo Nizhny Novgorod Norfolk Norwich Nottingham Nouakchott Novosibirsk Nuremberg Omaha Omsk Oran Orlando Osaka Oslo Ottawa Ouagadougou Palembang Palermo Palo Alto Panama City Paramaribo Paris Patna Penang Peoria Perm Perth Peshawar Philadelphia Phnom Penh Phoenix Pittsburgh Plymouth Podgorica Pombal Port Harcourt Port Louis Port Moresby Port of Spain Port-au-Prince Portland Porto Porto Alegre Porto Novo Poznan´ Prague Pretoria

France Cyprus China Russia United States United Kingdom United Kingdom Mauritania Russia Germany United States Russia Algeria United States Japan Norway Canada Burkina Faso Indonesia Italy United States Panama Suriname France India Malaysia United States Russia Australia Pakistan United States Cambodia United States United States United Kingdom Montenegro Portugal Nigeria Mauritius Papua New Guinea Trinidad and Tobago Haiti United States Portugal Brazil Benin Poland Czech Republic South Africa

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CITY

COUNTRY

Providence Puebla Pune Pusan Pyongyang Qingdao Qiqihar Quebec Querétaro Quito Rabat Rajkot Raleigh Ranchi Rawalpindi Rayong Recife Reykjavik Richmond Riga Rio de Janeiro Riyadh Rochester Rome Rosario Rostov-na-Donu Rotterdam Sacramento Sakai Salt Lake City Salvador Samara San Antonio San Diego San Francisco San Jose San José San Juan San Salvador Sana’a Sandviken Santa Cruz Santiago Santo Domingo São Paulo Sapporo Sarajevo Saratov Saskatoon

United States Mexico India South Korea North Korea China China Canada Mexico Ecuador Morocco India United States India Pakistan Thailand Brazil Iceland United States Latvia Brazil Saudi Arabia United States Italy Argentina Russia Netherlands United States Japan United States Brazil Russia United States United States United States United States Costa Rica Puerto Rico El Salvador Yemen Sweden Bolivia Chile Dominican Republic Brazil Japan Bosnia and Herzegovina Russia Canada

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CITY

COUNTRY

Seattle Semarang Sendai Seoul Seville Shanghai Shantou Sheffield Shenyang Shenzhen Shizuoka Singapore Skopje Sofia Southampton Srinagar St Louis St Petersburg Stockholm Strasbourg Stuttgart Surabaya Surat Surgut Suva Suzhou Sydney Taipei Taiyuan Takamatsu Tallinn Tampa Tashkent Tbilisi Tegucigalpa Tehran Tel Aviv The Hague Thimphu Tianjin Tijuana Tirana Tokyo Toluca Toronto Toulouse Toyama Trieste Tripoli

United States Indonesia Japan South Korea Spain China China United Kingdom China China Japan Singapore Macedonia Bulgaria United Kingdom India United States Russia Sweden France Germany Indonesia India Russia Fiji China Australia Taiwan/China China Japan Estonia United States Uzbekistan Georgia Honduras Iran Israel Netherlands Bhutan China Mexico Albania Japan Mexico Canada France Japan Italy Libya

409

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CITY

COUNTRY

Trivandrum Tucson Tulsa Tunis Turin Ufa Ulan Bator Ulsan Urumqi Utrecht Valencia Valencia Valparaíso Vancouver Venice Victoria Vienna Vientiane Vijayawada Vilnius Vitória Vladivostok Volgograd Warsaw Washington Wellington Wenzhou Windhoek Winnipeg Wolfsburg Wrocław Wuhan Wuxi Xi’an Xiamen Yangon Yantai Yaoundé Yekaterinburg Yerevan Yokohama Zagreb Zamboanga Zhengzhou Zhuhai Zurich

India United States United States Tunisia Italy Russia Mongolia South Korea China Netherlands Spain Venezuela Chile Canada Italy Seychelles Austria Laos India Lithuania Brazil Russia Russia Poland United States New Zealand China Namibia Canada Germany Poland China China China China Myanmar China Cameroon Russia Armenia Japan Croatia Philippines China China Switzerland

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References Derudder, B. and Witlox F. (2005) ‘An appraisal of the use of airline data in assessing the world city network: a research note on data’, Urban Studies, vol 42, pp2371–2388 Taylor, P. J., Catalano, G. and Walker, D. R. F. (2002) ‘Measurement of the world city network’, Urban Studies, vol 39, pp2367–2376

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Appendix B

Technical Appendix This appendix focuses on some of the technical aspects of the data gathering and data analyses for network firms. We first provide a number of working examples of how data were in practice collected and subsequently standardized, after which we discuss the methodology used for obtaining connectivity measures from these standardized data.

Data Collection: Manual for Data Collectors The data collection procedures for financial services, accountancy, advertising, law, management consultancy and media were largely similar. In this part of the Appendix, this data collection procedure is spelled out in more detail. The starting point is the websites of the firms. These websites nearly always provide an option to search out the ‘locations’ of the firms, often with a world map of their distribution to emphasize their global presence (Figure AB.1).

Figure AB.1 Website Ernst & Young. Assessing a firm’s presence in a city is often simple enough. The problem with our particular data needs is that we also need to assess the importance of a given city to a firm’s global service provision: the websites will be different for each of the firms, and

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therefore we need to consider all relevant information to obtain usable, standardized data. Two types of information are very relevant (although other types of information are possible): • •

Information about the size of a firm’s presence in a city, such as the number of offices or the number of partners in a law firm office. Extra-territorial functions of a particular office (i.e. responsibility for services beyond the city). Global headquarter functions are the obvious example, but other characteristics such as ‘regional offices’ or ‘national offices’ are also relevant.

Generally, we use what we call the scavenger method: any information gleaned about offices is recorded as a possible way of differentiating cities. Not all information will subsequently be used for scoring cities but we do not know what will be needed while collecting data. In practice, the importance of a firm’s presence is measured through a six-point scale (0–5). The scoring procedure is as follows: 1 2 3

Based on the firm’s ‘location finder’, we record 2 for every city that houses an office of the firm. This leaves all cities without an office of this firm with 0 recorded. For the city that houses the firm’s global headquarters, we change the 2 to 5. We search for other information about offices indicating that they are not typical offices for this firm. This information will be different for every single firm, and ultimately depends on the sound judgement of the data collector. Clearly, this is the most contentious part of the data gathering, so we need to consider the nature of these changes very carefully.

The basic strategy of allocation is that there has to be a specific reason to alter a city’s score. Examples include: • • • •

•

A city where contact with its office is referred elsewhere or a city with very few practitioners compared to other offices scores 1 for that firm (size criterion). A city with multiple offices or a city with a very large office with many practitioners compared to other offices scores 3 for that firm (size criterion). A city with an office assuming the role of national HQ scores 3 for that firm (minor extra-territorial function). A city with an office assuming the role of regional HQ scores 4 for that firm (major extra-territorial function). In cases with very good information on size, this criterion is used to score a 4 for an exceptionally large office (number of practitioners). The city housing a firm’s headquarters scores 5.

Example 1: Deloitte Touche Tohmatsu Deloitte’s website has an ‘office locator’ on its front page (Figure AB.2). This points out that the firm’s global HQ (the ‘global office’) is located in New York (Figure AB.3). The first two steps, then, are straightforward: each city with a Deloitte presence is recorded as a 2, cities with no presence remain recorded as a 0, and New York is recorded as a 5.

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Figure AB.2 Office locator on Deloitte website.

Figure AB.3 Deloitte: ‘global office’, New York. The third step involves looking for cities that are ‘not typical’ in Deloitte’s global service provision. For instance, when selecting the UK in the ‘office locator’, we learn that one of the London offices acts as the HQ for the entire UK. As can be seen from the screenshots, this is not mentioned as such, but is nonetheless clear from the way in which the office is presented in the UK context (‘Our main London office is …, for other UK offices, click …’; Figure AB.4). Furthermore, the presence and the location of the ‘main London office’ are repeated on every location page for UK cities (e.g. the

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Manchester page; Figure AB.5). In addition, London is the only city that has more than one Deloitte office (Figure AB.6). Taken together, it seems reasonable to record London as a 4 (size and minor extra-territorial function); other UK cities remain recorded as a 2.

Figure AB.4 Deloitte: ‘main London office’.

Figure AB.5 Deloitte: main London office on Manchester page.

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Figure AB.6 Deloitte: other London offices. In Canada, we have a similar situation, but this is communicated in a slightly different style. When selecting Canada in the ‘office locator’, there is no explicit mentioning of a national HQ. However, in the Ontario listing, we can note the presence of a so-called ‘national office’ in Toronto (Figure AB.7), in addition to several other ‘normal’ Toronto offices (Figure AB.8). Thus Toronto may be recorded as a 4 (size and minor extraterritorial function); other Canadian cities remain recorded as a 2.

Figure AB.7 Deloitte: Canadian ‘national office’ in Toronto.

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Figure AB.8 Deloitte: other Toronto offices. In Iceland, there is a distinction between the Reykjavik office (national HQ) and the other offices (Figure AB.9). Thus although Reykjavik is the only Icelandic city in our database, it may be recorded as 3 because of a minor extra-territorial function. The Abidjan office, in turn, ‘serves all Francophone West African countries’ (Figure AB.10). This implies that Abidjan may be recorded as a 4 because of a major extra-territorial function.

Figure AB.9 Deloitte: Icelandic HQ office in Reykjavik.

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Figure AB.10 Deloitte: Abidjan office with major extra-territorial function. In Japan, we have a situation comparable to that in the UK and Canada, albeit that Deloitte’s overall presence is much more important: there are multiple cities with multiple offices, whereas the UK and Canada have only one city with multiple offices (i.e. London and Toronto). Tokyo may be recorded as a 4 because of its multiple offices and the location of the ‘head office’ (Figure AB.11); Osaka may be recorded as a 3 because of its multiple offices (Figure AB.12), while other cities with one or two offices may remain recorded as a 2.

Figure AB.11 Deloitte: Tokyo offices.

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Figure AB.12 Deloitte: Osaka offices.

Example 2: Lehman Brothers Lehman Brothers’ website has a ‘worldwide offices’ section on its front page (Figure AB.13). In this section, information is provided on the firm’s global and major regional HQs (the ‘World HQ’ is located in New York, the ‘Europe and Middle East HQ’ is located in London, the ‘Asia-Pacific HQ’ is located in Tokyo; Figure AB.14). The first two steps and part of the third step, then, are straightforward: each city with a presence is recorded as a 2, cities with no presence remain recorded as a 0, New York is recorded as a 5, and London and Tokyo are the only two cities that may be recorded as a 4.

Figure AB.13 Website Lehman Brothers.

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Figure AB.14 Lehman Brothers: global and world-regional headquarters. It can be noted that on the ‘Europe and the Middle East’ page of the ‘worldwide offices’ section, there is no obvious extra information that warrants a city’s upgrade to a 3 or a downgrade to a 1 (Figure AB.15), and further searches on the website reveal no other relevant information on the importance of the remaining offices to the firm’s global service provision. Taken together, then, this is an extremely simple example: with the exception of New York (5), London (4) and Tokyo (4), all other cities with a Lehman Brothers’ office should remain recorded as a 2.

Figure AB.15 Lehman Brothers: offices in Europe and the Middle East.

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Example 3: Skadden Skadden’s website has an ‘offices’ section on its front page (Figures AB.16 and AB.17). In this section, there are no immediate clues as to the relative importance of the 22 offices. Only the first step is straightforward: each of the 22 cities with a presence is recorded as a 2, cities with no presence remain recorded as a 0. The next two steps involve an office-by-office examination of the information mentioned on the website. In this particular case this is feasible, because in contrast to the previous example, there are clues as to the importance of the various offices. However, the qualitative nature of the information (‘nature of practice’) does not allow us to make systematic comparisons of the capabilities of the different offices, which makes the scoring procedure of this particular firm more complicated. Some examples: •

New York’s page reveals that this is the ‘HQ of the broad-based international practice’ (Figure AB.18), and the city may therefore be recorded as a 5.

Figure AB.16 Website Skadden.

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Figure AB.17 Skadden: offices.

Figure AB.18 Skadden: New York office.

•

Two other major offices are Washington, DC and London. The Washington, DC office ‘has more than 300 attorneys and is the second-largest office of the firm’, and it includes ‘the corporate/mergers and acquisitions, tax and litigation practices upon which the firm’s success and reputation have been built’ (Figure AB.19). In other words, some of the firm’s core worldwide expertise is centralized in this major office, and Washington, DC may therefore be recorded as a 4. London, in

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turn, ‘is the largest of our offices in Europe’ (Figure AB.20). However, no formal HQ function or core expertise is mentioned, and therefore London may be recorded as a 3.

Figure AB.19 Skadden: Washington DC office.

Figure AB.20 Skadden: London office.

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•

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The last example shows how careful data collectors have to be with the scoring procedure. The Vienna practice of Skadden is dubbed a ‘small office’, and it is indicated that the team only comprises ‘six Austrian attorneys aided by a group of legal assistants and support staff’ (Figure AB.21). Furthermore, the website reveals that ‘the Vienna office frequently draws on lawyers from other European offices’ to handle larger transactions in Austria if necessary. In other circumstances, the small size compared to other offices and the fact that the Vienna office needs to draw upon other offices for specific services may be reason enough to record Vienna as a 1. At the same time, however, it is mentioned that the Vienna office ‘covers the region of Central and Eastern Europe’ and ‘concentrates on crossborder mergers and acquisitions, corporate finance transactions and the privatization of state-owned enterprises’. In contrast to other offices, then, the Vienna office has an explicit extra-territorial function (servicing Central and Eastern Europe) and a specific expertise (the privatization of state-owned enterprises in Central and Eastern Europe). In other circumstances, this would be reason enough to record Vienna as a 3 or maybe even a 4! The ultimate score will have to depend on the overall approach for this firm, but in practice the best solution may be to record Vienna simply as a 2.

Figure AB.21 Skadden: Vienna office.

Data Transformation: Network Connectivity and Hinterworld Calculation This section summarizes the key methods used in this book for analysing city relations in the office networks of 175 advanced producer service firms. The first method relates to the calculation of a city’s global network connectivity (GNC). The second method focuses on the spatial makeup of a city’s overall GNC, that is, an analysis of a city’s ‘hinterworld’ (e.g. relations with European cities, relations with London/New York, etc.)

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425

Network connectivity The calculation of a city’s GNC is based on a transformation of the service value data that systematically gauge the importance of the presence of firms (175) in cities (525). For illustrative purposes, consider the following small dataset in Table AB.1, which shows service values for three cities and three firms. Table AB.1 Service value matrix (example). Firm a

Firm b

Firm c

2 3 5

5 3 3

2 2 0

Amsterdam Beijing Vienna

The basic relational element for each pair of cities derived from matrix V is: rab,j  vaj·vbj

(1)

This measure defines the relation between cities a and b in terms of firm j. The conjecture behind this calculation is that the larger the office, the more connections there are with other offices in a firm’s network. The aggregated intercity relation between cities a and b across all firms is then produced from:

rab 

r

(2)

ab,j

j

For each city there are n-1 such links, i.e. one to every other city in the dataset. Table AB.2 shows these aggregated intercity relations for the data in Table AB.1 based on (1) and (2).

Table AB.2 Connectivity matrix (example).

Amsterdam Beijing Vienna

Amsterdam

Beijing

Vienna

– (6+15+4) (10+15+0)

(6+15+4) – (15+9+0)

(10+15+0) (15+9+0) –

The global network connectivity GNC of a city can then be computed by aggregating these intercity links rab across all cities in the dataset: GNCa 

r

ai

(a≠i)

(3)

i

In our example, the GNC of Amsterdam, Beijing and Vienna is 50, 49 and 49 respectively. For reasons of clarity, and to make this measure independent of the number of cities/firms in the dataset, GNCa is expressed as the proportion of the highest connectivity in the dataset (i.e., the city with the highest connectivity has a GNC of 1). This implies that in practice Amsterdam’s GNC will be reported as 1, while Beijing and Vienna both have a GNC of 0.98.

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City hinterworld Our methodology also allows disentangling the spatial makeup of a city’s overall GNC: two cities with the same overall connectivity may well be connected to very different cities, and this geographical specificity can be measured through the concept of a city’s ‘hinterworld’. Although a hinterworld in principle refers to the spatial distribution of a city’s connectivity at large, in this book we have focused on a number of key features of this overall distribution. For instance, for each city, we calculated the relative strength of its connections with cities in different world regions, for example with the three leading Chinese cities (Hong Kong, Beijing and Shanghai). In practice, each of these specific elements of a city’s hinterworld is calculated by comparing this city’s relations with a particular set of cities with the overall connectivity of this set of cities. For instance, Brussels’ relative relations with Pacific Asian cities were computed as follows:

Brussels(Pac Asian cities) 

rBrussels–Pac Asian cities GNCBrussels



GNCPac Asian cities GNC

Connectivities to Beijing–Hong Kong–Shanghai (i.e. the so-called ‘new globalism’) were computed as follows:

Brussels(New globalism) 

rBrussels–(HK–SH–BE) GNCBrussels



GNCHK–SH–BE GNC

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Index Aberdeen 134, 135, 246 absolute connectivity change 340, 341 Abu Dhabi 112, 285, 286, 345 accountancy advanced producer services 30–31 Australasia 64, 65 data collection 7 Eurasia 88 Europe 120, 121–122, 127 firms in network analyses 396, 398 Latin America 176–177, 273 MENA 106, 107 Northern America 155–157 Pacific Asia 75, 77 regional integration 189, 191, 192 South Asia 96, 97 Sub-Saharan Africa 141–142 Adelaide 202 advanced producer services (APS) 5, 22–39, 57–193, 195–350 advertising advanced producer services 29–30, 34, 37–38 Australasia 64, 65 data collection 7 Eurasia 88, 89 Europe 120–121, 123–124, 127 firms in network analyses 396, 398 Latin America 177–179, 273 MENA 107, 108 Nordic cities 302 Northern America 157–158, 160, 161 Pacific Asia 75–76, 78 regional integration 189, 191, 192 South Asia 96, 97 Sub-Saharan Africa 142 Africa global business cities 53 MENA 9, 60, 102–113, 188–193, 420

Southern 10, 318–323, 335 Sub-Saharan 9, 60, 137–147, 188–193, 319 Ahmedabad 220 Almaty 85, 86, 289 Amman 105 Amsterdam 115, 118, 307, 308, 338 anchor cities 150, 155, 160 Anchorage 263 Ankara 105, 111–112 Antwerp 307–308, 309 APS see advanced producer services Arabian Gulf 10, 102–113, 284–287 see also Middle East/North Africa Aranya, Rolee 93–101, 218–223 Ardinat, Gilles 231–235 Argentina 172 Asia 9, 338–339, 342, 349 see also Eurasia; Pacific Asia; South Asia; South-East Asia associations 22–23 Athens 116, 135, 345 Atlanta 152, 153, 155, 160–161, 257 attribute data 6 Auckland 64, 68 Australasia 8, 59, 63–70, 188–193, 340 Australia 37, 38–39, 63, 201–204, 335 Bahamas 179 Baku 85, 86 Baltimore 161 Ban´czyk, Marek 293–299 Bangalore 95, 99, 219, 220, 221–222, 223 Bangkok 41, 74, 279, 349 banking sector see financial services Barcelona 313, 314–315, 316, 317 Basel 236, 237, 238 Bassens, David 17–21, 102–113, 284–287, 306–311 BCI see Business Command Index

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Beijing 25, 29, 41, 74, 75, 206, 340, 348 see also new globalism Beirut 104–105 Belfast 246 Benelux countries 10, 306–311 Berlin 116, 127, 224, 225, 228 Bern 238 Bilbao 315 bi-national mega-regions 149 Birmingham (UK) 246 Bogotá 170, 174 Bologna 241, 242 Bordeaux 232, 234 Boston 27, 32, 150, 153, 161, 259 Brasília 273, 274, 275, 276 Brazil 172, 173, 174, 272–277 see also Latin America Brisbane 202 Bristol 129, 245 British rule 71, 140, 218, 284, 318, 320 see also colonial rule Brown, Ed 170–186, 324–330 Brussels 18, 115, 118, 127, 307, 308, 347, 348–349 Bucharest 116, 297 Budapest 116, 127, 293, 298 Buenos Aires 26, 171–172, 173 Business Command Index (BCI) 19–20, 49 business flows 7, 8 business services locational strategies 35, 38 Cairo 53, 103, 112 Calcutta 95, 220 Calgary 153, 161, 251, 253, 254 Canada 37, 38–39, 148–169, 251–255, 335, 416, 417 see also Northern America Canberra 68, 201 Cape Town 139, 140, 142, 144, 319–320 capital 3 capital cities advertising 30 APS 302, 303 colonial rule 137, 140 dominance 72, 74, 293, 301, 312, 325, 331, 333 Europe 114, 116, 118, 127, 226, 307

IFC 306 localism 68 MENA 111–112 Northern America 152, 155–156, 257 post-Soviet 85, 288, 289, 290, 291 South East Asia 279, 282 urbanization patterns 94–95, 237, 238 capitalism 127, 205 Caracas 170, 173 Casablanca 103, 105, 112 Castañeda, Francisco 170–186, 324–330 Castells, Manuel 3, 23, 40, 41, 48 Catalano, Gilda 241–244 Cebu 279, 280 Central America 10, 324–330 see also Latin America centralization 2, 149, 170, 231 challenger cities 293, 294, 295 Charlotte 18, 161, 345 Cheng, Zixu 93–101 Chengdu 206 Chennai 98, 99, 220 Chicago 25, 51, 152, 161, 257 Chile 173 China 71, 72, 74, 75, 205–211, 321, 331, 340–341 see also Pacific Asia Chinese cities triad see new globalism Chongqing 207 Christchurch 68 CIS see Commonwealth of Independent States City Network Power (CNP) 49, 50, 51–52 City Place Power (CPP) 49, 50–51, 52 Ciudad Juárez 269, 270 Cloke, Jon 170–186, 324–330 clustering strategies 235, 313, 314 CNP see City Network Power Cochin 221 Cologne 226, 228 Colombia 174, 177 Colombo 94, 96 colonial rule accountancy 96 development patterns 71, 102, 170 extra-regional links 99, 140, 146, 320

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frontiers 137 independence 93, 218, 318 oil economies 284 suspicion of 321 see also British rule command and control centres 2–3, 7, 17–21, 48, 49, 344–349, 350 see also city place power; headquarters Commonwealth 26, 30, 68, 320 Commonwealth of Independent States (CIS) 86, 91, 288 communication technologies 40–41, 197 Communism 114 company lists 351–399 competitiveness clusters 235 composite variables 33, 39, 43 conceptual confusion 3–4 connectivity analyses 57–193, 337–350, 425 see also global network connectivity Copenhagen 300, 302 core cities 198–199, 224, 334–335 core regions 60, 187 correspondence banks 22–23 Costa Rica 327 country level cities in network analyses 400–410 company lists 351–399 connectivity profiles 9–11, 195–350 see also national level; state level coverage, restricted 3, 4 CPP see City Place Power credit crunch 11, 337 see also financial crisis cultural diversity 137, 318 Curitibia 174, 273 Dallas 152 data collection 1–2, 3, 6, 7–8, 11–12, 23, 412–426 decentralization 2, 148, 212, 224, 232, 235, 256, 272 decolonization 137 deindustrialization 148, 256 Delhi 95, 220, 222 Deloitte Touche Tohmatsu 413–419 democracy 319 Denmark 300, 301, 302 Denver 46, 153 Derudder, Ben 1–13, 17–21, 48–55,

429

102–113, 114–136, 284–287, 306–311, 337–350 Des Moines 259, 263, 265 design of GUCP/GaWC Project 6–8 Detroit 153, 160 Dhaka 94 diverse cultures 137, 318 Doha 105 domestic intercity relations see localism Dominican Republic 174–175 Dresden 226 Dubai 28, 103, 104, 105, 107, 112, 285, 286, 333 Dublin 27, 115, 118 Durban 141, 320 Düsseldorf 29, 226, 227, 228 Eastern Europe 10, 29, 32, 293–299 economic level advanced producer services centres 22–39 Benelux cities 306 Central America 324 cities’ purpose 48 command and control centres 17–21 crisis 11, 173, 273, 337, 342–349 Eurasia 85, 86, 288–289 Europe 114–115, 224, 293, 297 Latin America 170, 267, 272 media centres 40–47 MENA 112 Northern America 148–149, 256 oil 284 Pacific Asia 72, 83, 205–206, 212 South Asia 93, 218 South East Asia 278, 283 Southern Africa 319 spatial restructuring of 2 Sub-Saharan Africa 138 Ecuador 177 Edinburgh 18, 246, 347, 348–349 Edmonton 251–252 emerging economies 26, 27, 29, 30, 199, 298 empirical level 3 employment 148, 149 EMRs see European Metropolitan Regions Ernst & Young 412 EU see European Union Eurasia 9, 59, 85–92, 188–193

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Europe Australasia links 67, 68 Benelux countries 10, 306–311 Brussels 18, 115, 307, 308, 347, 348–349, 426 cities in globalization 114–136 connectivity change 345, 349 definition 9, 10, 59 Eastern 10, 29, 32, 293–299 Eurasia links 89, 90 France 127, 231–235 Germany 116, 118, 127, 224–230, 331, 333, 340 Iberian countries 10, 312–317 Italy 241–244 Latin America links 172, 173, 183 Lehman Brothers 420 MENA links 110, 112 Nordic countries 10, 300–305 Northern America links 165–166, 167, 168 Pacific Asia links 81, 82, 83 Post-Soviet 10, 288–292 power 51, 52, 53 regional integration 188–193 South Asia links 99, 100 Sub-Saharan Africa links 144, 145 Switzerland 236–240 UK 127, 134, 245–250, 333 see also Western Europe European Metropolitan Regions (EMRs) 224 European Union (EU) 86, 115, 307 Ex-Soviet Europe 10 extra-territorial functions 413, 418 FCI see Financial Command Index FDI see foreign direct investment Financial Command Index (FCI) 17–19 financial connectivity (FNC) 49 financial crisis 11, 173, 273, 337, 342–349 financial services Australasia 64, 65 Central America 325 changes 338, 342–349, 350 data collection 7 Eurasia 87 Europe 118, 119–120, 134–135, 314 firms in network analyses 396, 397 headquarters 17–19

Latin America 172, 174–175, 273 locational strategies 36–37, 38, 39 MENA 103, 105, 106 network connectivity 26–27 Northern America 153–155 Pacific Asia 75, 76, 81 regional integration 188, 191, 192 South Asia 95, 96 Sub-Saharan Africa 140–141 firms advanced producer centres 34, 35–37 list of 11, 351–399 media centres 43–45 selection of 5–6 world city networks 4 Florence 241 flows 4–5 FNC see financial connectivity Forbes Global 2000 7, 8, 49, 351–395 foreign direct investment (FDI) accountancy 176 competitiveness clusters 235 IT industry 223 Japan 74 legal services 3, 97, 98, 100 trade agreements 93–94 urbanization 103 France 127, 231–235 Frankfurt 27, 28, 116, 225, 226, 228, 349 free trade 148–149, 152, 172, 179, 324–325 Friedmann, John 2, 3, 231 frontiers 137, 251 Gaborone 320 GaWC see Globalization and World Cities Research Network general network connectivities 8, 10 Geneva 237, 238, 239 Genoa 241 geographical orientation Benelux cities 310 disaggregation 9 Europe 115, 129–135, 241–242, 289 global network society 12 Globalizing Cities Index 48–54 headquarters 17–21 Latin America 173 Northern America 150, 161–162, 163–168

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regionality 59 Sub-Saharan Africa 139, 144–145, 146 see also hinterworlds; location Georgia 291 Germany 116, 118, 127, 224–230, 331, 333, 340 Glasgow 246 global business services 100 Global City Articulated Strategies 35, 38 global level analyses 8, 15–55 cities 2–3 city status 95 financial services centres 81 headquarters 420 network society 12 service firms 5 synthesis 331–335 global network connectivity (GNC) advanced producer service centres 24–33 Arabian Gulf 285 Australia 202 Benelux cities 307–308 calculation 424–425 Central America 324–327 city inclusion 60 core regions 187 Eurasia 86, 87 Europe 115, 116–118, 289–290, 293–295 France 231–232 Germany 225–226, 228–229 global synthesis 188 Iberian cities 313–314 Italy 241–242 Japan 213–214 Latin America 170–173, 268, 273–274 media centres 41–42 MENA 104 Nordic cities 300–302 Northern America 149–152, 251, 252, 257–259 Pacific Asia 73, 206–207 South Asia 94, 95, 219–220 South East Asia 278–280 Southern Africa 319–320 state/sub-regional 198

431

Sub-Saharan Africa 137–140 Switzerland 237 trends and change 337–350 UK 245–246, 247 Global Urban Competitiveness Project (GUCP) 1–13 Globalization and World Cities (GaWC) Research Network 1–13 globalizing cities index 1, 48–54 GNC see global network connectivity Goldman Sachs 345 Gothenburg 302, 304 Gritsai, Olga 288–292 Guadalajara 176, 179, 268 Guangzhou 27, 74, 206 Guatemala City 326, 327 Guayaquil 177 GUCP see Global Urban Competitiveness Project Gulf cities 102–113 The Hague 308, 309 Halifax 251–252 Hamburg 116, 225, 226 Hanoi 79, 279 Harare 141, 320, 321 Hartford 167, 263 headquarters 7, 8, 17–21, 273, 279, 343, 413–420 see also command and control centres Helsinki 116, 302 Hermelin, Brita 300–305 hinterworlds Australasia 66–68 calculation 426 definition 60–61 Eurasia 86, 89–91 Europe 115, 129–135 Latin America 182–185 leading cities 192–193 MENA 109–112 Northern America 150, 161–162, 163–168 Pacific Asia 79–83 South Asia 98–99, 100, 221 Sub-Saharan Africa 139, 144–145, 146 see also geographical orientation Hiroshima 214 historical aspects 85, 102–103, 104, 114–115, 167

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Hobart 202 Ho Chi Minh City 74, 79, 279 Honduras 326 Hong Kong 25, 27, 49, 73, 206, 210 see also new globalism horizontal urban structures 116, 118, 127, 225, 331, 340 Houston 20, 51, 152, 160 Hoyler, Michael 17–21, 40–47, 114–136, 224–230, 337–350 Huang, Jin 17–21, 85–92, 93–101, 205–211, 212–217, 218–223, 278–283, 288–292 Hyderabad 95, 220 Iberian countries 10, 312–317 Iceland 301, 302, 417 IFC see international financial centres imperial histories 114 inclusive approaches 3–4 independence 85, 93, 137–138, 218, 278, 289, 301, 319 India 94, 218–223 see also South Asia Indonesia 279 industrialization 212, 267, 268, 288 industry company lists 351–399 information technology (IT) industry 219, 223 informational economy 197 integrated work processes 1–2 intercity flows 4–5 interlocking networks 4, 12, 23, 54 international financial centres (IFC) changes 338 concentration in 188 Eurasia 87 Europe 118, 225, 228, 306 MENA 104–105 Northern America 153 Pacific Asia 75, 214 South East Asia 280 intra-firm flows 4 intra-state comparisons 195–350 investment banks 345 Islamabad 94, 96 Istanbul 104, 105, 107, 112, 349 IT see information technology industry Italy 241–244 Jakarta 74, 75, 279

Jamaica 179 Japan 71, 72, 74, 212–217, 418 see also Pacific Asia; Tokyo Jeddah 104, 107 Jerusalem 105, 110, 112 Johannesburg 53, 138, 139, 140, 142, 144, 320, 321, 322, 346 Karachi 94, 95, 96, 99 Kiev 86, 88, 91, 289, 290 Kingston 179 knowledge economy 224, 236 Kuala Lumpur 74, 279, 346, 348 Kuwait City 104, 285, 286, 346 Kyoto 213 Labuan 75, 279, 280, 282 Lagos 139–140, 141 Lahore 95 large service firms 6 Las Vegas 161 Latin America 9, 10, 53, 60, 152–153, 170–186, 188–193, 313 see also Brazil; Central America; Mexico Lausanne 236–237, 239 leading cities advertising 75 BCI 20 Eurasia 86 Europe 127, 224, 225, 316 Global City Process 51–55 global synthesis 187, 188, 190, 334–335 GNC 24–25, 41–42 hinterworlds 192–193 Latin America 173, 267 locational strategies 43–46 Northern America 160–161 Pacific Asia 78–79, 213 primacy 331–333 ranking of 9 South Asia 100, 218, 219, 222 Sub-Saharan Africa 139 see also primacy least developed nations 138 Leeds 246, 248 legal services advanced producer service centres 28–29 Australasia 64, 66

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data collection 7 Eurasia 88, 89 Europe 120, 125–126, 127 firms in network analyses 396, 398 Latin America 179, 180, 273 locational strategies 35, 36, 38 MENA 106, 107, 108 Northern America 159–160, 160–161 Pacific Asia 76–77, 79 regional integration 190, 191, 192 South Asia 97 Sub-Saharan Africa 143 Lehman Brothers 345, 419–420 Leipzig 226 Li, Guangquan 85–92, 288–292 Li, Qingbin 212–217 Lille 232, 234 Lima 170 Lisbon 25, 116, 312, 314, 316 Little Rock 259 Liu, Kai 85–92, 288–292 localism Africa 139, 144, 321–322 Arabian Gulf 285–286 Australasia 67, 202 Benelux cities 308 Central America 327 definition 10, 60 Eurasia 89, 90 Europe 129–131, 291, 295, 296, 297 France 232–233 Germany 226, 227 global synthesis 333, 334 Iberian cities 315–316 Italy 242–243 Latin America 182, 269, 274–275 leading cities 193 MENA 109, 110 Nordic cities 302, 303 Northern America 161–162, 163–164, 251–252, 253, 259–261 Pacific Asia 80, 207–208, 214, 215 South Asia 98, 221 South East Asia 280, 281 state/sub-regional 198 Switzerland 238 UK 246, 247 location 17–21, 22, 33–39, 43–46, 85–86, 104, 148, 269, 284 see also geographical orientation

433

London 18, 20, 25, 27, 28, 29, 30, 41, 52, 115, 127, 245, 246, 248, 249, 338 see also New York–London; traditional globalism Los Angeles 25, 42, 51, 152, 257, 338 Lusaka 141, 320 Lüthi, Stefan 236–240 Luxembourg 27, 46, 118, 306, 307, 308 Lyon 231, 234, 235 Madrid 41, 115, 312, 313, 314, 316 main offices 414, 415 see also headquarters Malaysia 279 Malmö 302 management consultancy advanced producer service centres 32 Australasia 64–66 data collection 8 Eurasia 89, 90 Europe 121, 127, 128–129 firms in network analyses 396, 399 Latin America 179, 181, 273 MENA 107, 109 Northern America 161, 162–163 Pacific Asia 77–78, 80 regional integration 190, 191 South Asia 98, 99 Sub-Saharan Africa 143 Managua 178, 324, 327 Manama 105, 112, 286, 345 Manchester 246 Manila 26, 74, 279 manufacturing 148, 177, 178, 201, 256 Maputo 319, 320 Marseille 231, 234 Medellín 177 media 8, 40–47, 396, 399 see also advertising media network connectivities (MNC) 49–50 mega urban regions 93, 94, 149, 150, 170, 236–237 MEGAs see Metropolitan European Growth Areas Melbourne 26, 64, 68, 201, 202, 203, 204 MENA see Middle East/North Africa Mercosur 172 Merrill Lynch 345

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Metropolitan European Growth Areas (MEGAs) 236 Mexico 176, 177, 179, 267–271, 333 see also Latin America Mexico City 26, 42, 172–173, 267, 268, 269 Miami 152–153, 259, 329 middle classes 107 Middle East/North Africa (MENA) 9, 60, 102–113, 188–193, 420 see also Arabian Gulf Milan 115, 241, 242, 243, 244 mineral resources 319, 321 Minneapolis 153, 161 minor regional level 37, 38–39 MNC see media connectivities monocentric hierarchies 239 Monterrey 268–269 Montevideo 170 Montpellier 233, 234 Montreal 153, 251, 252, 253, 254, 348 Moody’s Investors Service 345 Morgan Stanley 345 Moscow 26, 86, 87, 91, 288, 289, 291, 333, 340 Mould, Oli 63–70, 201–204 multi-state regions 333 Mumbai 26, 42, 94–95, 96, 98, 192, 219, 220, 222 Munich 32, 41, 118, 225, 226, 345, 347, 348 Nagoya 74, 214 Nairobi 139, 141 Nantes 233, 234 Nassau 174, 179 national level 20, 30, 75–76, 96, 189, 195–350, 416 see also state level, country level neoliberalism 114, 245 net-level 4 the Netherlands 306 network connectivity 5, 8, 23, 24–33 see also global network connectivity network society 3 new globalism Arabian Gulf 286, 287 Australia 203–204 Benelux cities 309 Brazil 275–276 Brussels links 426

Canada 253–254 Central America 328–329 China 210 emerging 11 Europe 292, 295, 297–298 France 234, 235 Germany 227–228 Iberian cities 316–317 India 221 Italy 243 Japan 216 leading cities 334–335 Mexico 270 Nordic cities 302, 304 South East Asia 282 Southern Africa 320–321, 322–323 Switzerland 239 UK 248–249 US 263–265 New Industrial Economies 72 New International Division of Labour (NIDL) 2 New York 18, 20, 25, 27, 28, 29, 30, 32, 38, 41, 50, 51, 52, 152, 168, 257, 259, 261, 338, 345 see also New York–London; traditional globalism New York–London (NYLON) 25, 197, 199 see also traditional globalism New Zealand 63, 68 Ni, Pengfei 1–13, 17–21, 48–55, 71–85, 85–92, 93–101, 205–211, 212–217, 218–223, 278–283, 288–292 NIDL see New International Division of Labour node-level 4 Nordic countries 10, 300–305 Northern America Australasia links 67, 68 cities in globalization 148–169 connectivity change 339, 340, 349 defining 9, 10, 59 Eurasia links 89, 90 European links 132–133, 134 Latin America links 173, 184 MENA links 110 Pacific Asia links 81–82, 83 regional integration 188–193 South Asia links 99, 101 Sub-Saharan Africa links 144, 145

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see also Canada; United States of America Norway 300–301 Norwich 248 Novosibirsk 290 NYLON see New York–London OFC see offshore financial centres offices 4–5, 5, 198, 413, 414 offshore financial centres (OFC) 174, 279, 280, 306, 326 oil-based economies 102–103, 112, 284, 285 Oner, Asli Ceylan 148–169, 256–266 Öresund Committee 302 Osaka 74, 213, 216 Oslo 116, 301 Ottawa 152, 155 Pacific Asia advanced producer services 27, 29, 32 Australasia links 66–67, 68, 69, 204 cities in globalization 71–85 defining 8, 59 Eurasia links 89, 91 European links 133–134, 134–135, 426 Latin America links 173, 185 locational strategies 36, 38 media centres 41 MENA links 110, 111–112 Northern America links 153, 166–167, 167–168 power 51, 52, 53 regional integration 188–193 South Asia links 99, 101 Sub-Saharan Africa links 144, 145 see also China; Japan Pain, Kathy 17–21, 114–136, 231–235, 251–255 Pakistan 94, 99 Palermo 241 Palo Alto 261, 263, 265, 333 Pan-European level 36, 38 Panama City 174, 326, 327, 328, 333 Paris 20, 25, 27, 41, 115, 127, 231, 232, 233, 234, 235, 331 Pérez Negrete, Margarita 267–271 peripheral locations 60, 256 Perth 68, 202

435

Philadelphia 150, 153 Phoenix 155 planning 170, 201, 205 Plymouth 248–249 Poland 294–295 political instability 138, 146 polycentric systems 232, 236–237 population Africa 140, 318 Asia 72, 93, 94 Australasia 63 Europe 231, 312 Mexico 267–268 Northern America 149 port cities 102, 153, 177, 198, 307–308, 320 Porter, Michael 235 Port Louis 140 Porto 312, 315 Porto Alegre 273 Portugal 312–317 post-communism 114, 115–116 Post-Soviet cities 10, 288–292 postscript 337–350 poverty 52, 138, 146 power 49–53 Prague 29, 116, 293, 298 pre-tax profits/losses 346 Prentice, Barry E. 251–255 Pretoria 319 primacy Europe 127, 225–226, 245 global synthesis 331, 332 Mexico City 267, 270 Nordic cities 301, 303 Pacific Asia 72, 75, 78, 212, 213, 214, 216 South Asia 95, 218 Sydney 202 US cities 256 see also leading cities principal components analysis 23, 33, 41, 43, 46 producer service centres 22–39 profitability 343, 345, 346, 347 Puebla 177, 267–268 Pune 95, 98, 99, 220 quantitative research 12 Quebec 168, 253, 254 Quito 170, 174

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regional level 57–193, 212–213, 214, 306, 331–350 see also sub-regional level relative connectivity change 340, 341 relocalization 268, 269 research background 2–6 restricted coverage 3, 4 Reykjavik 118, 135, 302, 345 Rio de Janeiro 170, 272, 273, 274 rising connectivity 338–340 Riyadh 107, 348 Rocha Gómez, José Luis 324–330 Rome 115, 241, 242, 243, 244 Rossi, Eliana C. 272–277 Rotterdam 307–308, 309 Royal Bank of Scotland 347 Russia 333 Salvador 273 St Petersburg 85, 86, 88, 289–290, 291 Sánchez Moral, Simón 312–317 San Diego 161 San Francisco 25, 152, 257, 345, 347 San José 324, 326, 327 San Juan 177 San Pedro Sula 326 San Salvador 178, 327, 328, 329 Santander 348, 350 Santiago 26, 170, 173 Santo Domingo 174 São Paulo 26, 42, 51, 170, 172, 173, 272, 273, 274 Saskatoon 252, 254 Sassen, Saskia 3, 22, 48, 231, 245 scavenger method 413 science parks 7 Scotland 246 Seattle 153 secondary cities 219 sector level 6, 19–20, 57–193, 338 semi-peripheral regions 60 Service Network Connectivity (SNC) 49 service sector 4, 8, 22–39 see also advanced producer services service values 5, 6, 8, 425 Seville 312, 315 Shanghai 25, 27, 41, 74, 75, 206, 339, 340, 346, 348 see also new globalism Shen, Wei 17–21 Shenzhen 74, 206

Short, John Rennie 3 Singapore 25, 41, 74, 75, 278–279, 280, 282, 333, 345 Skadden 421–424 SNC see Service Network Connectivity software and services industry 99, 176, 219, 221 South Africa 142, 146, 333 South Asia 9, 59, 93–101, 188–193 see also India South East Asia 10, 278–283 South Korea 71 Southern Africa 10, 318–323, 335 Sovereign Wealth Funds (SWFs) 103, 112 Soviet economy 85, 288 spaces of flows 3, 4–5, 23, 48, 197 spaces of places 48 see also command and control Spain 312–317 spatial level 2, 8, 43–46 see also location state level 195–350 see also national level Stockholm 116, 301, 302–303 Strasbourg 115, 232 strategic locations 22, 33–39, 85–86, 104, 148, 269, 284 structural adjustment 93 Stuttgart 225, 348 sub-nets 39 sub-nodal level 4 sub-regional level 9–11, 195–350 see also regional level Sub-Saharan Africa 9, 60, 137–147, 188–193, 319 Sunbelt region 148, 152, 153, 155 Sweden 300–301, 302–303 SWFs see Sovereign Wealth Funds Switzerland 236–240 Sydney 26, 30, 64, 66, 69, 192, 201, 202, 203, 204, 346, 348, 350 Taipei 41, 74, 206, 208 Tashkent 85, 87, 88 tax havens 307 Taylor, Peter J. 1–13, 17–21, 22–39, 48–55, 59–61, 114–136, 187–193, 197–199, 245–250, 331–335, 337–350 Tbilisi 85–86, 86–87, 88, 290, 291 technical level 11–12, 412–426

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Tegucigalpa 178, 327 Tel Aviv 31, 104, 105, 106 telecommunications 107 Tequila Crisis 173 territorial aspects 224, 300–301, 318 Thailand 279 theory of socially-constructed space 48 Thierstein, Alain 236–240 third world cities 42 Tier 1 capital 343, 344, 345, 347, 348 Tijuana 269 Tokyo 18, 20, 25, 27, 41, 43, 45, 50, 74, 213, 214, 349 see also Japan Toronto 26, 30, 53, 152, 160, 168, 251, 253, 254, 339 total connectivity 10–11 Toulouse 233, 234 trade agreements 93–94, 100, 148–149, 152, 172, 324–325, 326 trade fairs 49 traditional city structures 78 traditional globalism Arabian Gulf 286, 287 Australia 203 Benelux cities 308–309 Brazil 275 Canada 252–253 Central America 328, 329 China 208–209 Europe 291, 294, 295, 296, 297–298 France 233–234, 235 Germany 226, 227 Iberian cities 316 India 221–222 Italy 243 Japan 214–215 leading cities 334–335 Mexico 269–270 Nordic cities 302, 303, 304 South East Asia 280–281 Southern Africa 320, 322 Switzerland 238–239 UK 248 US 261–263 trans-metropolitan urban areas 149 trends and change 11, 337–350 tri-city apex 27 Trieste 241–242 Tunis 105 Turin 241

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twin cities 214 UAE see United Arab Emirates UK see United Kingdom un-global cities 197 un-local cities 214, 238, 246, 265, 280, 315–316 Union of Soviet Socialist Republics (USSR) 288–289 United Arab Emirates (UAE) 284, 285, 286, 333 United Kingdom (UK) 127, 134, 245–250, 333 United States of America (US) 256–266 advanced producer service centres 25–26, 27, 29, 32, 36, 38 Central America links 324–325, 326, 328, 329 cities in globalization 148–169 localism 333 media centres 41–42 oil-based economies 284 power 51, 52, 53 see also Northern America urban hierarchies Australasia 63 Canada 251 distribution of cities 331 Eastern Europe 297 Europe 116, 127, 236, 237, 239, 245 Iberia 313 Pacific Asia 72 simplistic 197, 198 urbanization Australasia 63 Europe 300, 306 Japan 212, 213 Latin America 172, 272 MENA 102, 103, 284 South Asia 94, 218, 220 USSR see Union of Soviet Socialist Republics Utrecht 135, 308 Valencia 312 Vancouver 153, 251, 253, 254 Venezuela 173 vertical urban structures 237, 331 Vienna 116, 424 Vietnam 279

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Wachovia 347 Wall, Ronald S. 137–147, 318–323 Warsaw 29, 115, 127, 293, 295, 298 Washington, DC 18, 25, 29, 42, 46, 51, 152, 153, 160, 257 Watson, Allan 40–47 websites 5, 412–426 Wellington 68–69 Wells Fargo 347 western China 205, 206, 207 Western Europe 25, 27, 28–29, 30, 41, 114–136, 340 Windhoek 319 Winnipeg 251–252 Winston-Salem 345, 347 Witlox, Frank 17–21, 102–113, 114–136, 284–287, 306–311, 337–350

world city network 1, 2–3, 4–5, 7–8, 22–23, 188–193 world-regional level 8–9, 36–37, 57–193, 420 van der Wusten, Herman 288–292 Xu, Guangyao 278–283 Yang, Xiaolan 17–21, 71–85 Yekaterinburg 290 Yue, Xiaoyan 205–211 Zhang, Yu 218–223 Zimbabwe 321 Zurich 115, 118, 237, 238, 347

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