Enterprising Worlds: A Geographic Perspective on Economics, Environments & Ethics (GeoJournal Library)

Enterprising Worlds

The GeoJournal Library Volume 86 Managing Editor: Max Barlow, Toronto, Canada

Founding Series Editor: Wolf Tietze, Helmstedt, Germany

Editorial Board:

Paul Claval, France Yehuda Gradus, Israel Sam Ock Park, South Korea Herman van der Wusten, The Netherlands

The titles published in this series are listed at the end of this volume.

Enterprising Worlds A Geographic Perspective on Economics, Environments & Ethics

Edited by

JAY D. GATRELL Indiana State University, Terre Haute, Indiana, USA

and

NEIL REID The University of Toledo, Ohio, USA

A C.I.P. Catalogue record for this book is available from the Library of Congress.

ISBN-10 ISBN-13 ISBN-10 ISBN-13

1-4020-5225-1 (HB) 978-1-4020-5225-5 (HB) 1-4020-5226-X (e-book) 978-1-4020-5226-2 (e-book)

Published by Springer, P.O. Box 17, 3300 AA Dordrecht, The Netherlands. www.springer.com

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All Rights Reserved © 2006 Springer No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying,microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work.

Dedications To my favorite editor, s., and our children, f., m. and e.—JDG To Lori and my beautiful daughters Kirsty and Fiona—NR

Table of Contents Acknowledgements .............................................................................................. xiii 1

Economics, Environments & Ethics J. Gatrell and N. Reid................................................................................... 1 1.1

About this book.................................................................................. 1

2

Industrial and Technology Clusters: An Everyday Topic of Popular Conversation Frank J. Calzonetti....................................................................................... 5

3

Which Mode of (CLUSTER) Promotion for which aspect of Entrepreneurship? A differentiating view on institutional support of automotive clusters M. Fromhold-Eisebith................................................................................ 13 3.1 3.2 3.3 3.4 3.5

3.6 4

The Dynamics of FDI of the TFT-LCD Cluster: A Study of Japanese Firms in Taiwan W.C. Wang.................................................................................................. 29 4.1 4.2 4.3 4.4 4.5

5

Abstract............................................................................................ 13 Introduction...................................................................................... 13 Differentiating variants of entrepreneurship .................................... 15 Differentiating types of cluster promotion....................................... 17 Impacts of public versus private cluster promotion on entrepreneurship.......................................................................... 19 3.5.1 Public top-down cluster promotion and entrepreneurship ....................................................... 21 3.5.2 Private bottom-up cluster promotion and entrepreneurship ....................................................... 23 Conclusions...................................................................................... 24

Introduction...................................................................................... 29 The Dynamics of Japanese FDI in Taiwan ...................................... 30 Methodology.................................................................................... 32 Flying-Geese Model and Scalar Fixes ............................................. 34 Conclusions...................................................................................... 36

Collaborating to Compete: The Case of Northwest Ohio’s Greenhouse Industry N. Reil and M. Carroll................................................................................ 41 5.1 5.2 5.3 5.4

Introduction...................................................................................... 41 Cluster-Based Economic Development ........................................... 42 Northwest Ohio’s Greenhouse Industry........................................... 45 The Development of Northwest Ohio’s Greenhouse Cluster........... 47 vii

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Table of Contents 5.5 5.6

6

Specialized Agriculture: Local Markets & Global Competitors in Ohio’s Greenhouse Industry E. W. LaFary, J. Gatrell, N. Reid and P. Lindquist .................................. 57 6.1 6.2 6.3

6.4 6.5

6.6 6.7 7

7.3 7.4

Introduction...................................................................................... 71 High technology and Urban Development: A Conceptual Review ...................................................................... 72 7.2.1 What is High Technology?.............................................. 72 7.2.2 High Technology in Developing countries ..................... 73 7.2.3 High Technology in India ............................................... 74 Bangalore: Transformation of a Garden City to the Silicon Valley......................................................................... 76 Conclusion ....................................................................................... 79

An Evolutional Model of U.S. Manufacturing and Services Industries J. Helsel, H. Kim and J. Lee ...................................................................... 83 8.1 8.2 8.3 8.4 8.5 8.6

9

Introduction...................................................................................... 57 Globalization, Local Dependence and Greenhouses........................ 58 The Greenhouse Industry: Background and Trends in Floriculture .................................................................................. 59 6.3.1 Floriculture Import Patterns ............................................ 60 6.3.2 Canada-US Floriculture Trade Patterns .......................... 61 Data and Methods ............................................................................ 62 Results.............................................................................................. 63 6.5.1 Globalization................................................................... 63 6.5.2 Markets and Sales ........................................................... 65 Discussion........................................................................................ 67 Conclusion ....................................................................................... 69

High Technology and Urban Development in Bangalore, India R. Kalra....................................................................................................... 71 7.1 7.2

8

Branding and Marketing: The First Cluster Project ......................... 51 Conclusion ....................................................................................... 53

Abstract............................................................................................ 83 Introduction...................................................................................... 83 Background...................................................................................... 85 Methodology.................................................................................... 87 8.4.1 Measure of Spatial Concentration ................................... 87 Analysis and Discussion .................................................................. 89 8.5.1 Industrial Profiles............................................................ 93 Concluding Remarks........................................................................ 94

Clusters and Local Economic Growth: Unpacking the Cluster Model Michael Taylor ........................................................................................... 99 9.1 9.2

Introduction...................................................................................... 99 The Processes and Drivers of the ‘Cluster’ Model ........................ 101

Table of Contents

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9.2.1

9.3

9.4 10

Towards Reconceptualising Enterprise, Entrepreneurship and Entrepreneurial Processes for Sustainable Futures: Contributions from Economic Geography R. Le Heron .............................................................................................. 119 10.1

10.2 11

Introduction.................................................................................... 119 10.1.1 Positioning my viewpoint and argument....................... 119 10.1.2 Economic and ecological processes in their institutional settings .......................................... 121 10.1.3 Competing narratives and different knowledge frontiers....................................................... 124 Further Directions .......................................................................... 127

Attitudes, Behaviours and Outcomes of Different Types of Entrepreneurs: Toward a Better Understanding of the Multiple Entrepreneurship Phenomenon C. Tamásy ................................................................................................. 131 11.1 11.2 11.3 11.4 11.5

12

The social construction of local economic processes: trust and reciprocity ...................................................... 102 9.2.2 Social capital: a chaotic concept ................................... 103 9.2.3 The over-simplification of the processes of learning, entrepreneurship and new firm formation ..................... 104 9.2.4 The fetishing of proximity ............................................ 105 9.2.5 The de-powering of network relationships.................... 106 9.2.6 The one-sided interpretation of institutional support .... 107 The deeper underlying problems of the cluster model................... 108 9.3.1 Normative instrumentalism........................................... 109 9.3.2 Time and the institutional instantaneous....................... 109 9.3.3 Complexity.................................................................... 110 Conclusion ..................................................................................... 111

Introduction.................................................................................... 131 Survey Design................................................................................ 132 Entrepreneurial attitudes and behaviours ....................................... 133 Outcomes of different types of entrepreneurs ................................ 135 Discussion...................................................................................... 141

The Business and Sustainability of Water Supply in Singapore: The Case of Hyflux S. Y. Wong ................................................................................................ 145 12.1 12.2 12.3 12.4 12.5

Introduction.................................................................................... 145 Restructuring Singapore Industry – the New industry Clusters ............................................................................ 147 The Economics and Politics of Water Supply – Catalysts of Water Industry ........................................................................... 148 The Water Solution – The Role of the State and Public-Private Partnership ..................................................................................... 150 The Birth of Hyflux – Building the Foundation from Home ......... 156

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Table of Contents 12.6 12.7 12.8

13

Entrepreneurship: New Means of Support for Community Colleges M. Rudibaugh........................................................................................... 165 13.1 13.2

13.3

13.4 13.5 14

Introduction.................................................................................... 165 Local Dependence.......................................................................... 165 13.2.1 Locality as Social Structure and Agent ......................... 166 13.2.2 Defining the terms of local dependence: Increased Partnerships................................................... 167 How Community Colleges Escape Local Dependence.................. 169 13.3.1 Customized Contract Training ...................................... 169 13.3.2 Technology Centers ...................................................... 170 13.3.3 Workforce Development Partnerships .......................... 170 13.3.4 Welfare-to-Work........................................................... 171 13.3.5 Business-Based Scholarship Programs ......................... 171 The Rise of the “Entrepreneurial” College .................................... 172 Summary and Implications ............................................................ 175

Globalization, Social Protest and the Militarized Landscape of Okinawa S. Banasick ............................................................................................... 177 14.1 14.2 14.3 14.4 14.5

15

Globalizing and Regionalizing the Technology and Services of Hyflux................................................................... 158 Hyflux and the Vision of a Global Hydro-hub............................... 161 Concluding Remarks...................................................................... 162

Introduction.................................................................................... 177 The Base Lease System and Economic Dependency..................... 178 Buying Security – the Political Economy of Compensation.......... 180 The ‘globalization’ of Nago City ................................................... 181 Conclusion ..................................................................................... 186

Paternalism and Struggle at Weirton Steel Corporation Aron Massey ............................................................................................. 191 15.1 15.2 15.3 15.4 15.5

Introduction.................................................................................... 191 Ernest Tener Weir: The Man Behind the Mill ............................... 192 E.T. Weir’s Mill Fosters Development in the Area ....................... 193 Struggle at Weirton Steel ............................................................... 196 E.T. Weir and Weirton Steel’s Struggles ....................................... 198

16

Ethics in Economic Geography Christine Tamásy...................................................................................... 201

17

Whose Development? The Tribal Involuntary Dislocation in the Sardar Sarovar Sutapa Chattopadhyay.............................................................................. 205 17.1 17.2

Abstract.......................................................................................... 205 Introduction.................................................................................... 205

Table of Contents 17.3 17.4 17.5

17.6 18

18.3

19.3

19.4

Introduction.................................................................................... 231 The conceptual framework of the institutional arrangement and regionally bounded institutions .......................... 232 Institutions relevant to microcredit in Argentina ........................... 235 19.3.1 The institutional arrangement and regionally bounded institutions ...................................................... 235 19.3.2 Microcredits .................................................................. 238 Conclusions.................................................................................... 239

Bread or Circus? The Economics of Mega-Sporting Events Jeffrey G. Owen........................................................................................ 243 20.1 20.2

21

Abstract.......................................................................................... 221 Concepts of Informality ................................................................. 222 18.2.1 International labor standards curb informalization........ 224 18.2.2 International labor standards lead to more informalization .............................................................. 225 18.2.3 Civic rights curb informalization .................................. 226 The case for a realist Marxist approach ......................................... 227

Building or Repairing Institutions: Microcredits in Argentina Martina Fuchs.......................................................................................... 231 19.1 19.2

20

Theoretical Framework.................................................................. 209 Uneven Development..................................................................... 210 Unsustainable Development .......................................................... 212 17.5.1 The people’s and NGOs resistance movements ............ 213 17.5.2 The interface between Resistance movements and Power .................................................. 215 Conclusion ..................................................................................... 216

Geographies of Informalization: Conceptual Dilemmas over Social Standards and Informalization of Labor Hege Merete Knutsen ............................................................................... 221 18.1 18.2

19

xi

Introduction.................................................................................... 243 20.1.1 The Fallacy of Economic Impact Studies ..................... 244 Conclusion ..................................................................................... 253

Social Entrepreneurship and Regional Economic Development: A Conceptual Framework Henry G. Rennie....................................................................................... 257 21.1 21.2

Abstract.......................................................................................... 257 Social Entrepreneurship and Business Entrepreneurship............... 258 21.2.1 Vision and Mission of Social Entrepreneurship............ 258 21.2.2 Strategy: Competitive versus Cooperative .................... 259 21.2.3 Governance ................................................................... 259 21.2.4 Funding ......................................................................... 259 21.2.5 Market........................................................................... 259

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21.3

21.4

21.5

Public-Private Partnerships, Externalities, & Economic Development ................................................ 260 21.2.7 Typology: Social Entrepreneurship and Business Entrepreneurship ........................................................... 260 Social Entrepreneurship and Economic Development................... 260 21.3.1 Economic Growth versus Economic Development....... 260 21.3.2 Social Welfare and Economic Development................. 261 21.3.3 Economic Efficiency..................................................... 262 21.3.4 Internalities versus Externalities and Economic Development ................................................................. 262 21.3.5 A Conceptual Framework Linking Society, Social Entrepreneurship, and Economic Development............ 262 Empirical Application of the Conceptual Framework: An Example............................................................... 263 Income and Costs of an Automotive Museum .............. 264 21.4.1 21.4.2 Economic Impact .......................................................... 265 Conclusions.................................................................................... 267 21.5.1 Conceptual Framework Applied ................................... 267 21.5.2 Social Entrepreneurship and Externalities .................... 268 21.5.3 Social Entrepreneurship Strategy and Economic Development Strategy................................................... 269

Acknowledgements The editors wish to acknowledge the assistance of the International Geographical Union’s Commission on the Dynamics of Economic Spaces, the conference sponsors (IGU, University of Toledo, Indiana State University, and Bowling Green State University), the editorial assistance of E. LaFary, the copyediting services of C. McGrew, and the financial support of the United States Department of Agriculture in association with the work of Reid, Lindquist, Carroll, Calzonetti, LaFary, and Gatrell. Additional administrative support was provided by our home institutions. Finally, the editors appreciate the support and assistance of the entire editorial team at Springer.

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1 Economics, Environments & Ethics J. Gatrell, Department of Geography, Geology & Anthropology, Indiana State University, Terre Haute, Indiana N. Reid, Department of Geography & Planning and The Urban Affairs Center, The University of Toledo, Toledo, Ohio

1.1 About this book Enterprising Worlds represents the culmination of several years of work by geographers, planners, and economists. The papers included in this volume represent the collective efforts of the International Geographical Union’s Commission on the Dynamics of Economic Spaces. This collection—like others that precede it— is the result of the 2005 annual meeting in Toledo, Ohio (USA). The papers have been selected based on their quality and potential contribution to the broader community of economic geographers and policymakers. As such, all papers have undergone peer review as part of the publication process. Finally, the papers have been selected from over 30 presented to demonstrate the inherent interconnectedness of these themes (and at times the conceptual tension that exists between ethics, economics, and the environment) insofar as these important issues shape the contours and cleavages of contemporary regional development. In particular, the papers in the collection represent the diversity of perspectives on these issues as interpreted by scholars situated around the world. While no doubt the papers are diverse, the authors provide insight into the workings of a variety of communities, regions, and nations as they seek to balance economic growth with the growing necessity to simultaneously promote ethical and sustainable regional development. As such, the collection is truly international in both scale and scope and provides the reader with a survey of emerging and established concepts, theories, and conflicts in economic geography. The collection has been organized into three broad sections. The first section examines the socio-spatial implications and policy issues surrounding “Localized Economic Development and the Cluster Approach.” The contributions are unique in that the cluster concept—adopted from economics and widely seen as a public policy panacea—is examined in place and practice from a geographic perspective. While many geographers are supportive of the notion of economic clusters, the papers illustrate that realizing promise of, and simultaneously rescaling, the concept of clusters as articulated in Porter’s (1990) The Competitive Advantage of Nations proves both difficult and problematic. Using a combination of case studies and extensive empirical analysis, economic development clusters are examined in 1 J. Gatrell and N. Reid (eds.), Enterprising Worlds, 1–4. © 2006 Springer.

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a variety of contexts and across multiple economic sectors in several papers. Each of these studies more or less benchmark industrial clusters at multiple scales—and each albeit unknowingly—demonstrates key silences within the theory that need to be addressed. For this reason, the section outlines the broad support the concept has received and its potential for unlocking a range of local economic development processes. Nevertheless, the section ends with a solid critique of the cluster approach and questions the utility of the explosion of geographic and economic literature that has emerged since the mid-1990s. Section 2—“Sustainability, Entrepreneurship, & Landscape”—examines two very distinct views of sustainable economic development. First, authors consider the classic question of the exact role of entrepreneurs in promoting and sustaining economic growth. Insofar as the role of entrepreneurs in the geography literature has been under studied, the papers explore a range of issues and considerations (conceptual, methodological, and practical) that must be addressed to articulate the uncertain and shifting geography of the entrepreneur. The papers consider the expansion of the entrepreneurial ethos in higher education, the ability of entrepreneurs to shape a single community, and sometimes serendipitous nature of the successful entrepreneur. Second, the section examines the environmental imperatives that shape local economic development and the key issue of sustainability. In once case study, the themes of the environment and the entrepreneur are considered within the context of water quality in a developing nation and enable the reader to understand the many barriers (and potential for success) that faces environmental entrepreneurs. In concert, the section provides the reader with a real sense of the breadth of research being performed under the rubric of “sustainability”. Finally, “The Impacts and Ethics of Economic Development” (Section Three) examines what an ethical economic geography might look like and how the deployment of a ethical framework might alter the economic landscape. The section begins with an examination of key concepts and contradictions that must be considered when seeking to establish an “ethical economic geography”. In a similar vein, subsequent papers examine the ethics of economic informalisation and structural reform in the developing world. The section ends with two interesting papers—both by economists—that consider the crucial question of economic development studies, their role in cementing support for costly initiatives, and their utility. Indeed, one chapter politely questions the efficacy of such studies within the context of project growth associated with the Olympic Games. In the end, Section Three identifies several themes within the nascent “ethics” literature in economic geography—transitioning economics, public policy narratives on development, and social capital—that can be used to shape future research.

1 Economics, Environments & Ethics

3

Table 1. Summary of Chapters

2 3

Author(s) Calzonetti Fromhold-Eisebith

4 5 6

Wang Reid & Carroll LaFary et al.

7 8

Kalra Helsel et al.

9 10

Taylor LeHeron

11

Tamasy

12

Yann-Wong

13 14 15 16 17

Rudibaugh Banasick Massey Tamasy Chattopadhyay

18 19

Knusten Fuchs

20

Owens

21

Rennie

Subject Clusters in Geographic Research Entrepreneurship & Clusters in the German Auto Sector Japanese FDI in the Taiwan LCD Industry Developing clusters from Scratch in Ohio Assessing and Benchmarking the Ohio Greenhouse Cluster High Technology Development in India Identifying the Geography of Manufacturing Clusters in the U.S. Questioning Clusters Reconceptualising Entrepreneurship in Economic Geography Attitudes and Behaviors of Entrepreneurs in Place An Environmental Entrepreneur in Singapore Entrepreneurial Colleges Sustainable Development in Okinawa Place-building and Industrialists Ethics in Economic Geography Development in India—Who’s Development? Informalising the Geography of Labor Volatility in Argentina Economic Institutions Economic Development Impacts Studies & The Olympics Social Capital and the Impacts of Economic Development

The 19 substantive contributions present a wide array of examples of the globalizing economy as it is experienced, charted, and assessed at multiple scales. The diversity of papers—while potentially distracting—underscore the contested definitions of ethics, environment, and development that exist in economic geography, as well as the potential to chart a new exciting research agenda for discipline. Additionally, the papers are inter-disciplinary and many are collaborative and illustrate the many skills and knowledges that are required to unpack and explore globalization.

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Finally, the intent of this volume is two fold. First, we hope the volume proves to be an interesting read that highlights the important scholarship of the authors. Second, we anticipate the volume will raise more questions than it answers and recognize that many silences (some we recognize and others that you may identify) exist within and between the papers. While any collection derived primarily from a conference is inherently uneven, the collection is thought provoking and should prove to be an engaging read for any economic geographer.

Source Porter, M. 1990. The Competitive Advantage of Nations. New York: Basic Books.

2 Industrial and Technology Clusters: An Everyday Topic of Popular Conversation Frank J. Calzonetti, The University of Toledo, Department of Geography & Planning and Office of Research, Toledo, OH

It is not often that major research themes in geography and regional science are central to national and international discussions of government leaders, the business press, and economic development practitioners working to improve national, regional, state, and local government economies. “Industry clusters,” but particularly its popular cousin “technology clusters” has moved from academia to enjoy widespread press, popular and practitioner attention in both developed and developing economies (see Taylor’s contribution in this book). This is no surprise. It is now recognized that innovation-driven sectors of the economy are yielding great returns and that many of the firms in these sectors are “clustered” in particular regions. Not only do industries in knowledge-driven sectors report higher value added than other manufacturing sectors, but wages rates and growth rates are higher as well (National Science Foundation, 2006, Chapter 6, 9). The NSF reports that over the period 1980–2003 world output by high-technology manufacturing industries grew at an inflation-adjusted average annual rate of 6.4 percent compared to 2.4 percent for other manufacturing industries. It is explained by the NSF and others that high technology industries are intensive users of research and development (R&D) that leads to innovation resulting in gains in market share, the creation of new markets, and the efficient use of resources. Regions with successful clusters are working to retain their advantage and others are seeking to create clusters as a path to economic growth and development. A cluster-based approach is now a mainstream strategy to promote regional economic development throughout all advanced economies and even by many developing countries (Martin and Sunley, 2003, 12). Although the theory and practice underlying the concept is not new to geographers and regional economists, it is not surprising that the concept is used rather loosely in the press, by those involved in economic development efforts (politicians, various board members, planners, economic development professionals), and perhaps by some in the halls of academia. Even serious scholars argue that the concept is vague and perhaps loosely applied. As shown in this book, the concept is wrapped around related concepts that may also have definitional problems or different interpretations such as “embeddedness,” “social capital,” “new economy,” “corporate complexes,” “entrepreneurship,” “spillovers,” “absorptive capacity,” “knowledge or learning regions,” and “technology-based development” to name just a few. However, most academics and practitioners do understand a cluster to be a concentration of interconnected companies, including suppliers and service providers, who are 5 J. Gatrell and N. Reid (eds.), Enterprising Worlds, 5–12. © 2006 Springer.

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supported by various governmental and non-governmental institutions (particularly universities) that both compete with and cooperate with one another within a defined region. What may not be known to the casual observer is the corpus of theory and practice behind the technology cluster concept. A good review of this theory and practice is provided by a number of manuscripts and books, such as that provided by Cooke (2002), so it is not the purpose of this brief introduction to repeat this discussion. But for those new to the topic a few pages are provided on the topic to set the stage for the more focused chapters in this book. Michael Porter is generally credited for popularizing the industrial cluster concept. Writing about conditions that explained the competitive economic position of nations, he argued through examples that much of the economic power of most advanced countries was concentrated in a few districts that often had elements within four dimensions (Porter’s diamond) that affected regional competitiveness—factor conditions; demand conditions; firm strategy and rivalry; and supporting industries (Porter, 1990). “Technology clusters,” an extension of the industrial cluster concept, have in addition to the four dimensions of the Porter diamond the following elements: entrepreneurship, a source of innovation, sources of financial capital and social capital. Social capital describes the trusting relationships among individuals within organizations in a region that promotes the exchange of information and joint action for mutual benefit (Fountain, 1998; Saxenian, 1994). However well received Porter’s his 1990 book was to geographers and regional economists, most understood that the concept of an industrial cluster has been a topic of interest and development for much of the 20th century and perhaps could be traced to Ricardo’s early 19th century concept of comparative advantage (if a country has an absolute advantage over another in two different products, it should still focus on the product in which it has the strongest advantage). If this is a stretch, Marshall’s concept of the “industrial district” that capitalized on the value of skilled labor and traditions in addition to resource endowment as fostering a concentration of industrial activity is often referenced as the earliest recognition of the industrial cluster idea (Marshall 1891). While the role of agglomeration and external economies on the concentration of industry has been an area of intense academic focus throughout the 20th century (beginning with the work of Alfred Weber, 1909), much of this work centered on the external economies of scale resulting from the clustering of activity that benefited individual enterprises. Given the difficulty economists faced in introducing “technology” into their understanding of factors contributing to per capital economic growth (not recognized until explained by the Solow residual in 1957), it is not surprising that the role of technology and innovation along with other “softer” factors on regional performance has taken decades to unravel. Well prior to Porter’s popularization of the industrial cluster concept, others following the tradition of the economist Schumpeter, argued that the role of continuous innovation was central to the performance of firms and on the growth and development of industrial districts (e.g., Piore, M. and C. Sabel 1984). However, the relationship of

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innovation and technological advances on regional competitiveness, along with an understanding of the role of social capital, entrepreneurship and government intervention in the development, continuous support, and transformation of clusters continues to offer challenging opportunities for those studying clusters and particularly those interested in creating and promoting clusters. Much of the literature on the topic, including much of Porter’s work and many government sponsored reports, newspaper and magazine articles (see, for example Strempel 2005) focuses on mapping clusters or identifying factors that have contributed to successful clusters. Hundreds of industry cluster case studies have been described in both the academic literature and in various reports printed throughout the globe that are often the result of projects commissioned by states, regions, councils, districts, or municipalities. For instance, Michael Porter’s Cluster Mapping Project (2002) identified 12 specialized regional economies in the United States1 and the Brookings Institution identified 14 U.S. metropolitan concentrations of high technology industry “most frequently mentioned in the popular literature” (Cortright and Mayer 2001, 2).2 But others (who were not Harvard economists) working independent of Porter and did not receive such popular acclaim also identified clusters of technology-related activity driven by external economies through the interaction of related firms that took advantage of a division of labor in a region and the minimization of transaction costs (Scott 1988; Scott and Kwok 1989; and Coffey and Bailly 1991). Some clusters develop without direct public policy intervention or direction. In other cases, state or regional leaders work to create a cluster in a region that does not have much industrial or supportive activity related to the future cluster. “Created” clusters are often associated with rapidly expanding knowledge-based sectors that are heavily dependent upon universities, entrepreneurship and skilled labor. But, as shown by LaFray et al in this book and other examples (see, for example, Akoorie for a good study of the New Zealand thoroughbred industry other sectors such as agriculture can be a focus of a cluster promotion program). In either case, the model is based on the notion that knowledge spills over into a local region if that region has the capacity to “absorb” the knowledge created (Breschi and Malerba 2001). Throughout the 1980s and into the 1990s many regions were aspired to create new “silicon valleys” to capture part of the information technology boom and “biotechnology clusters” became fashionable as the growth of pharmaceuticals, medical equipment, and related technologies attracted widespread attention and huge public research investment (particularly in the U.S.). The latest trend is nanotechnology that is receiving tremendous public sector investment such that some say it will define the early part of the twenty-first century. As explained by FromholdEisebith in this book, there are different approaches to cluster promotion with “public top-down” and “private bottom-up” being two major categories. A common strategy in the creation of clusters is to encourage increased agglomeration economies around a promising regional core of activities rather than to build an

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entirely new foundation from which activities can flourish. This could be a major local industry, a major federal center, or even a major university research institute. It is less common, for regions to invest efforts to create clusters in an emerging technological area that needs to overcome both technical (involving investments in R&D) and competitive market conditions before profitable returns are realized. Creating clusters is quite popular, but has a questionable record of success, particularly where the task is to transform an “old economy” (industrial plants, hierarchical, skill-based, etc.) into a “new economy” (lifelong learning, risk-taking, teaming, etc) (Cooke 2002, 131-156). Such regions include those that are tied to traditional manufacturing or extractive industries that competed on the basis on proximity to local mineral resources, transportation assets or available labor. As these regional economies suffered with global competition (particularly in the case of rock bottom wages from developing countries) or declines in the price of the local raw material, creating new a new economy around a clusters was an attractive way to revitalize and diversity the region. “Declining” manufacturing regions pose special challenges (Boschma and Lambooy 2000; Asheim and Isaken 2002). Most important, local leadership must redirect thinking away from the view that competing on the basis of low-cost manufacturing or attracting new manufacturing operations will return the area to previous greatness. Even if leaders accept that a new model of development based upon the creation and support of innovative clusters is a means for local revitalization and transformation, the challenge is great if the area does not have knowledge creation sources or entrepreneurs with experience and staying power to develop technology through R&D before it is ready for the marketplace. Likewise, such regions are likely to have sparse investment funds or venture companies who have experience dealing with the uncertainty of technological risk in addition to the expected risk for all start-up businesses. Despite these challenges, many regions have worked and continue to work on creating new economy clusters in areas in decline and areas lacking a tradition of entrepreneurship, sources of innovation, and financial capital. Success has been reported, for example, in Finland’s efforts in building clusters centered on technology parks that link university research, industry laboratories, and linked companies. For instance, the city of Oulu has been able to transition from its traditional forest products industry to a cluster focusing on telecommunications, software, sensors, optoelectronics and lasers (Cooke 2002, 169-169). Other declining areas such as Appalachia in the U. S. (Feser and Goldstein, 2002) or cities tied to “industrial age” economies in Europe of North America have embraced the cluster approach with some success. For instance, Lehigh Valley Pennsylvania has moved away from its dependence on steel to life sciences that are grounded in university research centers at Lehigh University and elsewhere (Paytas, Gradeck and Andrews 2004, 16-17). If innovation is central to successful long-lasting clusters, a major question is determining the source of continuous innovation. The likely source of new knowledge creation is from research and development activities (Audretsch 1998, 20).

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Universities are prime candidates to produce research and development (R&D), but other sources are industry R&D laboratories, federal R&D laboratories, or even “decentralized industrial creativity” within the collective capacity of small firms within a region (Bellandi 1994 from Asheim 1995). As noted by Maskell (2001), the availability of specialized knowledge and the creation of new knowledge may attract firms from elsewhere into the region, may attract entrepreneurs into the region, and may create new firms through spinoff activities. A problem is that by most measures, knowledge creation is highly concentrated in particular metropolitan areas or regions of advanced economies. A major source of innovation in the U.S. is R&D and this is highly concentrated with the top 10 states accounting for almost two-thirds of total R&D (California accounting for more than twenty percent of the total). Of the 625 institutions surveyed by the National Science Foundation, the 20 leading institutions account for almost one-third of the total academic R&D spending (Shackelford 2004). R&D for important industries are also highly concentrated. For instance, three states (California, Massachusetts and Texas) account for over half of the nation’s R&D in the computer and electronic products industry and two states (New Jersey and Pennsylvania) provide one-third of the nation’s R&D in the chemical sector (National Science Foundation 2006, Chapter 4). National Institutes of Health funding is also highly concentrated as eight states account for over 18 percent of the total NIH. Recognizing the linkage between technology clusters and R&D, technology parks have grown in popularity across the globe as a way to create sources of innovation to support clusters of activity. According to the Association of University Research Parks, in North America there are 2,900 organizations/companies located in parks that support jobs for over 235,000 people with total investment exceeding $9 billion (Dean 2005). An important component in cluster formation is entrepreneurship that is required to take new ideas forward and develop them locally so they are introduced into the marketplace (Feldman and Francis 2004, 131). Independent of clusters entrepreneurship and small and medium sized business have been shown to be a major factor in job creation in the United States (Birch, 1981; Roacha, 2004). Although research shows that entrepreneurship is positively associated with economic growth, but outstanding questions remain on the relationship between clusters and entrepreneurship and particularly how entrepreneurship is measured (Rocha 2004). But fostering entrepreneurship is generally a central feature in cluster promotion efforts. A popular way to support entrepreneurship is through business incubators that provide opportunities for collaborative research with universities and industry, assistance with business plan development, legal assistance, IT assistance, mentoring, information about opportunities, and opportunities for entrepreneurs to sharpen their argument as they approach various sources of financial capital. For the most part, however, academicians and practitioners consider entrepreneurship in the context of new firm formation and not entrepreneurship within firms, universities, or research institutes (see Fromhold-Eisebith’s contribution in this book) that can have a profound impact on regional development.

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It appears unlikely that public policy interest in clusters will diminish. What is likely to happen is that the term “clusters” will lose its fascination as communities and regions fail to achieve outcomes as development plans fall short of expectations. Regional concentrations of economic activity will continue to exist as they have for centuries, but new terminology will replace “clusters” and perhaps capture the enthusiasm of academicians and policy planners in the process. The space limitation of this brief introduction can not possibly do justice to the breadth and depth of theory and practice reported on clusters. However, a reasonable question one may ask is with so much written and spoken about clusters, why is the topic still of great academic interest? Despite the volumes written on the topic, many challenging questions still remain and some are addressed in this book. These include (1) the need for more work on clusters in sectors that are generally outside major technology-based industries (see contribution by LaFary et al in this book); (2) a need for a deeper understanding of the different types of entrepreneurship and how they are promoted by clusters and different forms of cluster promotion (see Fromhold-Eisebith in this book); (3) guidance on how to promote clusters in rural areas lacking sources of innovation; (4) more guidance on ways to change development trajectories in declining manufacturing cities toward innovation-based cluster formation; (4) models of building new clusters in emerging technological arenas to gain an national/international advantage; (5) ways to use the knowledge created by local universities in areas that are unlikely candidates to absorb this new knowledge; (6) competitiveness of clusters in an increasingly global village; and finally (7) a need for longitudinal studies that show with detailed data on new firm formation, job creation, wage rates, and development (not just growth) how clusters have developed and performed over time. These are: Atlanta (Construction Materials; Transportation and Logistics; and Business Services), Boston (Analytical Instruments; Education and Knowledge Creation; and Communications Equipment), Chicago (Communications Equipment; Processed Food; and Heavy Machinery), Denver (Leather and Sporting Goods; Oil and Gas; Aerospace Vehicles and Defense), Houston (Heavy Construction Services, Oil an Gas, Aerospace Vehicles and Defense), Los Angeles (Apparel, Building Fixtures, Equipment and Services, Entertainment), Pittsburgh (Construction Materials, Metal Manufacturing, Education and Knowledge Creation), Raleigh-Durham (Communications Equipment, Information Technology, Education and Knowledge Creation), San Diego (Leather and Sporting Goods, Power Generation, Education and Knowledge Creation), San Francisco area (Communications Equipment, Agricultural Products, Information Technology), Seattle area (Aerospace Vehicles and Defense, Fishing and Fishing Products, Analytical Instruments), Wichita (Aerospace Vehicles and Defense, Heavy Machinery, Oil and Gas).

1

2

The 14 areas identified by the Brookings Institution study does not overlap with those of Porter either on the cities mentioned or their major product specialization. Brookings identified the following metropolitan areas: Atlanta (databases), Austin

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(semiconductors, computers, SME), Boston (computers, medical devices, software), Denver (data storage, telecommunications equipment and software), Minneapolis-St. Paul (computers, peripherals, medical devices), Phoenix (semiconductors), Portland (semiconductors, display technology, SME, EDA, wafers), Raleigh-Durham (computers, databases), Sacramento (computers, semiconductors), Salt Lake City (software, medical devices), San Diego (communications equipment), San Jose (semiconductors, computers, communications equipment, SME, EDA, data storage), Seattle (software), and Washington, D.C. (databases, internet services).

Sources Akoorie, M. E. M, 2000. Organizational Clusters in Resource Based Industry: Empirical Evidence from New Zealand. In Green, M. & R.B. McNaughton (eds.) Networks and Proximity, 133-164. Hampshire: Ashgate Publishing Ltd. Asheim, B. 1995. Industrial districts as ‘learning regions: A Condition for Prosperity. Paper presented at the conference of the IGU Commission on “interdependent and uneven development: Global-local perspectives.” Seoul, S. Korea. Asheim, B. T. & Isaksen, A. 2002. Regional Innovation Systems: The Integration of Local ‘Sticky’ and Global ‘Ubiquitous’ Knowledge. Journal of Technology Transfer 27: 77-86. Audretsch, D. B. 1998. Agglomeration and the Location of Innovative Activity. Oxford Review of Economic Policy 14: 18-29. Birch, D. A. 1981. Who Creates Jobs? The Public Interest 3-41. Boschma, R. & Lambooy, J. 2000. The Prospects of an Adjustment Policy Based on Collective Learning in Old Industrial Regions. Geojournal 49: 391-399. Breschi, S. & Franco M. 2001. The Geography of Innovation and Economic Clustering: Some Introductory Comments. Industrial and Corporate Change 10: 817-833. Coffey, W. J. & Bailly, A.S. 1991. Producer Services and Flexible Production: An Exploratory Analysis. Growth and Change 22: 95-117. Cooke, P. 2002. Knowledge Economies: Clusters, Learning and Cooperative Advantage. London: Routledge. Cortright, J. & Mayer, H. 2001. High Technology Specialization: A Comparison of High Technology Centers. Washington, D.C.: The Brookings Institution. Dean, W. 2005. What is a Research Park? Paper presented at the 2005 Annual Conference of the Association of University Research Parks, Raleigh, NC. Feser, E., Goldstein, H., Renski, H. & Renault, C., 2002. Regional Technology Assets and Opportunities: The Geographic Clustering of High-Tech Industry, Science and Innovation in Appalachia. Washington, D.C.: Appalachian Regional Commission. Fountain, J. E. 1998. Social Capital: A Key Enabler of Innovation. In L. Branscomb and J. H. Keller, eds. Investing in Innovation. Cambridge: The MIT Press: 85-111. Maskell, P., 2001. Toward a Knowledge-based Theory of the Geographical Cluster. Industrial and Corporate Change 10: 921-941. Martin, R. & Sunley, P. 2003. Deconstructing Clusters: Chaotic Concept or Policy Panacea? Journal of Economic Geography 3:5-35.

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Marshall, A. 1891. The Principles of Economics. London: Macmillan. National Science Foundation. 2006. Science and Engineering Indicators. Arlington, VA: The National Science Foundation. Paytas, J. Gradeck, R. & Andrews, L. 2004. Universities and the Development of Clusters. Washington, D.C.: U.S. Economic Development Administration. Piore, M. & C. Sabel. 1984. The Second Industrial Divide: Possibilities for Prosperity. New York: Basic Books. Porter, M. 1990. The Competitive Advantage of Nations. New York: Basic Books. Porter, M. 2002. “Regional Foundations of Competitiveness,” Future Competitiveness of Wales: Innovation, Entrepreneurship, and Technological Change. Rocha, H. O. 2004. Entrepreneurship and Development: The Role of Clusters. Small Business Economics 23: 363-400. Saxenian, A. 1994. Regional Advantage: Culture and Competition in Silicon Valley and Route 128. Cambridge: The MIT Press. Scott, A. J. 1988. Metropolis: From the Division of Labor to Urban Form. Berkeley and Los Angeles: The University of California Press. Scott, A. J. & E. C. Kwok. 1989. Inter-Firm Subcontracting and Locational Agglomeration: A Case Study of the Printed Circuits Industry in Southern California. Regional Studies. 23: 405-416. Strempel, D. 2005. Tech Cluster seeks national identity. Fairfield County Business Journal (week of July 4th).

3 Which Mode of (CLUSTER) Promotion for which aspect of Entrepreneurship? A differentiating view on institutional support of automotive clusters M. Fromhold-Eisebith, Dept. of Geography & Geology, University of Salzburg, Salzburg, Austria

3.1 Abstract Entrepreneurship is a major driver of regional economic development and restructuring. For analytical and practical promotion purposes, different facets of the notion should be identified. This chapter distinguishes between new firm formation entrepreneurship and innovation based growth dynamics of existing firms. It is argued that both entrepreneurship variants differ with regard to regional support requirements, also reflecting a different role of globalization. A connection is made with the currently popular practice of cluster promotion that regards agglomerations of value chain related firms as a suitable seedbed for entrepreneurial dynamics due to collaboration and other advantages. Cluster initiatives may be institutionalized in various ways, and it is reasoned that, depending on the institutional mode, either the one or the other variant of entrepreneurship is especially supported. This is discussed with respect to the distinction between publicly dominated schemes (like official cluster policies) and efforts that are privately initiated, financed and governed by firms (like thematic regional industry association). Drawing on insights gained from two European automotive cluster initiatives (a public one in Austria and a private one in Germany) it is shown how institutional differences create different support settings for entrepreneurship. Accordingly, public approaches rather favor new firm formation whereas private initiatives better support entrepreneurial dynamics in existing firms, which is relevant for policies.

3.2 Introduction Entrepreneurship creates crucial opportunities for economic growth and renewal by newly combining production factors and know-how, potentially inciting innovation (Busenitz et al. 2003; Shane 2003; Reynolds et al. 2005). Policy relevance especially emerges from implications of globalization: In high-wage countries the out migration of firms and workplaces towards cheaper locations has started to 13 J. Gatrell and N. Reid (eds.), Enterprising Worlds, 13–28. © 2006 Springer.

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hollow out the (regional) economic base, rendering the local activation of entrepreneurship an essential compensation strategy. The question is how to effectively support desired dynamics (Sternberg 2003, 2005; Gilbert et al. 2004; Audretsch et al. 2005). Recent research emphasizes the role of entrepreneurship for regional development and, likewise, its dependence from regional contexts (Nijkamp and Stough 2002; de Groot et al. 2004; OECD 2005). Hence, promotion should target factors like localization economies, social systemic frameworks and other locally bound assets (Wagner and Sternberg 2004). Generally, entrepreneurs tend to concentrate in some places (Sternberg et al. 2004; Sternberg and Litzenberger 2004), apart from international differences (identified by the Global Entrepreneurship Monitor GEM; see Reynolds et al. 2005; Sternberg and Wennekers 2005). As certain localities offer specifically favorable settings, scholars have started to combine issues of entrepreneurship with the cluster concept (Cooper and Folta 2000; Rocha 2004; Rocha and Sternberg 2005). Commonly understood as spatial agglomerations of value chain related firms and other organizations that derive economic advantages from co-location and collaboration (Martin and Sunley 2003, 10-13), clusters apparently provide a conducive seedbed for entrepreneurship. Empirical studies indicate positive correlations (Sternberg and Litzenberger 2004; Rocha and Sternberg 2005), yet causal relationships remain to be further explored. Three major research shortcomings are tackled in this chapter: First, studies on clustering and entrepreneurship have neglected to take a differentiated view on the latter (as conceded by Rocha and Sternberg 2005, 289). Most research only addresses the founding of new firms, although entrepreneurship also encompasses innovation-based dynamics of existing firms (Reynolds et al. 2004). Second, work has disregarded the variation of clusters according to sector, time phase and institutional specifities, which probably influence entrepreneurial impacts. The chapter thus follows recommendations to ‘focus on different types of clusters’ in this respect (Rocha and Sternberg 2005, 289). Third, entrepreneurship support has insufficiently been linked with cluster promotion, both from a conceptional and empirical perspective. Suggestions for entrepreneurship policies have just vaguely and not systemically been connected with ideas on cluster measures (Sternberg 2003). And literature on cluster initiatives or policies hardly explicitly addresses issues of entrepreneurship (OECD 2001; Nolan 2002; Raines 2002a; Sölvell et al. 2003; Andersson et al. 2004). The chapter distinguishes two variants of entrepreneurship and discusses which type of cluster promotion is more supportive in the one or the other case, juxtaposing two institutional modes that significantly differ with regard to entrepreneurial effects: public cluster policies versus private initiatives (Fromhold-Eisebith and Eisebith 2005). Theoretical reasoning is substantiated by project results gained from empirically investigating one public and one private cluster initiative in

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Europe, both referring to automotive supply sectors, which may control for sector specifities.1

3.3 Differentiating variants of entrepreneurship The notion of entrepreneurship is associated with a range of issues and various definitions (for overviews see Ripsas 1998; Praag 1999; Busenitz et al. 2003; Shane 2003). Accordingly, entrepreneurs are economic agents who are ready to take up risks and uncertainty, are innovators, industrial leaders, decision makers, managers, organizers and coordinators, employers of factors of production, arbitrageurs, alert discoverers, suppliers of financial capital, and/or allocators of resources among alternative uses. Apart from classical economics, new approaches emphasize social systemic, contextual, psychological and behavioral facets of entrepreneurs, advocating interdisciplinary theorizing (Ripsas 1998; Shane 2003). This offers scope for considering spatial contexts as regions seem to be the arena where major explanatory factors of entrepreneurship are co-located (Sternberg et al. 2004; Wagner and Sternberg 2004). Especially (social) networking requirements can be highlighted, which transform over time (Chell and Baines 2000; Lechner and Dowling 2003). Partners are needed for supporting the establishment of new firms (network founding hypothesis) and even more for sustaining success of enterprises (network success hypothesis) (Brüderl and Preisendörfer 1998). There is no common theory of entrepreneurship due to its manifold qualities, which allows to just broadly conceptualize it as ‘the discovery of opportunities and the subsequent creation of new economic activity’ (Rocha and Sternberg 2005, 269); or, even more simply, ‘entrepreneurship is about creating something new’ (Reynolds et al 2005, 208). It is manifested in several forms, foremost by the formation of new small firms. But not every such venture indicates a positive effort, triggered by opportunity. Labeled necessity entrepreneurship, it may also emerge from a situation of despair and lack of other options which provides less favorable prospects for success and development impacts (Sternberg and Wennekers 2005; Reynolds et al. 2005). Additionally, entrepreneurship is also expressed in outstanding growth dynamics and innovation-based success of longer existing companies or parts of them, hence an attribute of larger corporations (Rocha and Sternberg 2005). How to exactly draw the line between both variants is a matter of debate and can not be discussed here (criterion of age, of product life cycles?). Considering them as opposite ends of a continuum may suffice to use the distinction for analysis. 1

The project, financially supported by the ‘Stiftungs- und Förderungsgesellschaft der Universität Salzburg’, investigated the publicly established AutomotiveCluster(AC)Styria initiative, Austria, and the private industry association car/ competence center automotive region Aachen/ Euregio Maas-Rhein e.V., Germany. Special thanks go to my research partner Günter Eisebith.

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Table 1. External support requirements associated with the new firm formation and dynamic growth variants of entrepreneurship Aspect Infrastructure demand Relationships to universities/ public R&D

Requirements associated with new firm formation Basic start-up infrastructure (e.g. technology centre), additional to other structural features (transport, public amenities a.o.) Basic spin-off idea; sourcing of basic qualified personnel, including student workers; initial technical support (equipment) and consulting

Relationships to suppliers of goods/services

Building up suitable dyadic relationships to reliable suppliers ‘from scratch’ based on social contacts; ‘try and error’ processes shaping the network towards functional efficiency

Relationships to finance providers

Provision of sufficient amounts of founding, venture or risk capital

Links to markets

Support to build up a first customer base; help in establishing a reputation for initial marketing purposes

Impact of globalization

Given framework that forces firms to reactively find their niche of competitiveness Source: Depiction by the author

Requirements associated with dynamic growth of existing firms Overall structural features (transport, public amenities, a.o.), not changing much by virtue of added activities (Informal) consulting regarding additional know-how requirements; sourcing of additional, specifically qualified personnel for additional tasks Transformation and modification of a pre-existing approved functional network of suppliers and co-opeting partners, due to specifities of added activities; ‘snowball’ mechanisms of extension Either no additional capital necessary or provision of capital just to support new endeavors in the firm, easy accessible Support to enlarge the market by gaining additional customers; evolution of existing reputation towards new horizons Decisive challenge that makes firms act in order to stay competitive

Both types, new business formation and entrepreneurial dynamics in incumbent firms, can induce major local development impulses. Which one should be favored depends on regional preconditions and objectives. New start-ups may be prioritized in regions that are marked by a lack of businesses and/or a dominance of ‘old industry’ sectors, calling for fundamental structural renewal and diversification. Revitalization of mature firms is required where established companies face competitive challenges from globalization which force them to evolve in leapfrogging ways in order to stay ahead of followers. These differences should be regarded when conceptualizing promotion strategies. Recent research on entrepreneurship has not equally attended to the two variants but focused on new firm formation, especially in the cluster context (Andersson et al. 2004; de Groot et al. 2004; Sternberg and Litzenberger 2004; Reynolds et al. 2005; Rocha and Sternberg 2005). This manifestation of entrepreneurship is easier to statistically identify than the other one (Reynolds et al. 2004; Sternberg et al. 2004). Policy implications of

3 Which Mode of (CLUSTER) Promotion for which aspect of Entreprenuership? 17

that distinction have hardly been solicited, and entrepreneurship support is only seen as being directed towards the promotion of new companies (Gilbert et al. 2004). Differences between new firm entrepreneurship and innovative growth dynamics of existing firms matter with respect to (cluster-oriented) promotion. The two variants vary with regard to internal processes and, accordingly, to support requirements external to the firm: setting up a new business involves other qualities of relationships than organizing an innovative shift in an incumbent company. Respective issues could be addressed by the local institutional environment, possibly via an intentional (policy) strategy. The entrepreneurship variants are assumed to differ mainly in terms of infrastructure demand, links to universities/R&D, suppliers, finance providers, markets, and impacts of globalization (table 1). Young firms have more fundamental infrastructure needs and must establish new functional relationships to partners that help them find their niche in the global economy. Mature enterprises rather extend their scope emerging from existing operations without additional infrastructure requests. They rely on established, socially embedded networks, which must be adjusted to additional or changed activities in response to global challenges. These assumptions partly reflect empirical findings: Brüderl and Preisendörfer (1998) show that social networks are more important for the continuing success than for the formation phase of firms. Lechner and Dowling (2003) prove that, over time, the relative importance of reputational networks for firms decreases and of co-opetition networks increases; relational capability evolves from egocentric to sociocentric networking. Accounting for such distinctions, the two types of entrepreneurship require different promotion approaches.

3.4 Differentiating types of cluster promotion As entrepreneurship assumingly profits from systemic advantages of industrial clustering (Rocha 2004; Sternberg and Litzenberger 2004; Rocha and Sternberg 2005), cluster initiatives should explicitly attend to entrepreneurial support, and vice versa. Before logically connecting the two strategic topics an explanation is given regarding what cluster promotion is and which institutional modes may be distinguished. Although the cluster notion and related policies are subject to fundamental criticism (Martin and Sunley 2003; Benneworth et al. 2003; Taylor in this book), the idea, popularized by Porter (1998, 2000a), has become a widely used guideline for supporting competitive, innovative regional and national economies (OECD 2001; Enright 2003; Sölvell et al. 2003; Andersson et al. 2004;). There is, nevertheless, no overarching strategic concept of cluster promotion. Approaches depend on place- and industry-specific conditions, economic history and structure, institutional and infrastructure endowments, cluster cycle phases, and national/regional

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(political) cultures (OECD 2001; Raines 2001 and 2002a; EU Commission 2002; Newlands 2003; Andersson et al. 2004). Still, it may be possible to depict ‘typical’ common features. Basically, objectives of cluster promotion draw on the conception of a cluster as a (subnational) regional agglomeration of value chain related firms and other organizations (like universities, R&D centers, public agencies) which derive economic advantages from co-location and collaboration (Martin and Sunley 2003, 10-13). Cluster advantages, on the one hand, relate to localization externalities, like specialized labor markets and infrastructure (Gordon and McCann 2000; Cooke 2002; Malmberg and Maskell 2002; Enright 2003). On the other hand, clusters favor interactive learning and knowledge creation through socially embedded, trustful linkages of involved actors (Maskell 2001; Cooke 2002; Malmberg and Maskell 2002; Wolfe and Gertler 2004). This calls for an integrated approach that combines various issues of industrial development (Nauwelaers 2001; Raines 2002b; Benneworth et al. 2003). Accordingly, cluster promotion may be defined as any coordinated set of measures that intentionally supports the development of an industrial agglomeration towards ideal features of a cluster in terms of a specialized, collectively innovative set of sector related industries and other organizations (Fromhold-Eisebith and Eisebith 2005, 1252). Implemented promotion strategies widely vary, but there are common characteristics (summarized from Boekholt and Thuriaux 1999; Cooke 2002; EU Commission 2002; Raines 2002a; Sölvell et al. 2003; Andersson et al. 2004): Usually, support builds upon and activates pre-existing potential of ‘proto cluster’ structures, notably a regional concentration of suitable actors, trying to strengthen that base. Measures facilitate the firms’ access to useful assets and include: 1. Fostering information exchange and collaboration between firms in order to encourage the pooling of resources, quality improvements and collective identities; 2. Establishing innovation-enhancing links of firms to regional universities and R&D centers that support the commercialization of research results, technology transfer, and the acquisition of highly qualified staff; 3.Actively marketing the specific industrial strengths and raising awareness inside and outside the region; 4. Locally providing specialized services and advice to firms (finance, marketing, design); and 5. Attracting selected industrial investors in order to fill identified gaps and weaknesses in local production systems; this may also include the set-up of additional infrastructure. Overall, cluster promotion focuses on ‚soft’ activities of contact facilitation, community building, moderation and consulting that address groups of firms in an integrated way and aim at improving regional systemic interaction (Boekholt and Thuriaux 1999; Nauwelaers 2001; Andersson et al. 2004). This requires participative strategies that involve public and private actors; several activities have to be combined. There is also the dynamic dimension of a ‘cluster policy cycle’ (Ben-

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neworth and Charles 2001; European Commission 2002; Sölvell et al. 2003). Often, a first diagnostic phase serves to empirically analyze cluster potential and requirements, followed by a prescriptive phase of policy design and an implementation phase (Raines 2002b). Despite of such commonalities, cluster promotion may be institutionalized in quite different ways. On the one hand, there exists a wide range of policy schemes that are imposed upon firms in a rather top-down way (Boekholt and Thuriaux 1999; Roelandt and den Hertog 1999; Porter 2000b; EU Commission 2002; Nolan 2002; Raines 2002a; Benneworth et al. 2003; Andersson et al. 2004). On the other hand, many coordinated efforts are mainly instigated, funded and governed bottom-up by companies, addressing the same set of objectives (Sölvell et al. 2003), like regional industry associations or competence networks. Thus, cluster support is not only a public domain but also emanates from local industrial communities themselves. This distinction between public (top-down) and private (bottom-up) cluster promotion affects patterns of effects because each institutional mode creates a particular governance setting, influences the behavior of cluster members, their interaction, rules of conduct, collective norms and conventions (as outlined in Fromhold-Eisebith and Eisebith 2005). The debate connects to the interesting issue whether cluster advantages are best supported by government agency at all (Formica 2003; Guinet 2003; Martin and Sunley 2003). Often, however, public and private schemes can not clearly be distinguished as they mostly combine both kinds of actors integrating their interests (Nauwelaers 2001; Raines 2001 and 2002a; EU Commission 2002; Rosenfeld 2003; Sölvell et al. 2003; Wolfe and Gertler 2004). Still, the distinction can be drawn according to which actors dominates finance and/or decision making (Fromhold-Eisebith and Eisebith 2005). How do the differences of public and private modes of cluster promotion affect the two variants of entrepreneurship distinguished before?

3.5 Impacts of public versus private cluster promotion on entrepreneurship The following sections combine theoretical reasoning with empirical findings from a recent investigation of differing patterns of effects of one top-down public and one bottom-up private automotive cluster initiative, ACStyria in Austria and car e.V. in Germany (Fromhold-Eisebith and Eisebith 2005; see also footnote 1). In both localities, representatives of 17-19 cluster member firms and 5-7 other actors (colleges/universities, chambers, support agencies) were interviewed in 2004/05. The regions are comparable in terms of population size (1.2 mio.), size of the major city (250,000 inhabitants), aspects of infrastructure endowment (technical universities) and other development features. The juxtaposed cluster initiatives, however, differ in terms of their (mainly) public or private nature and

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structural characteristics (number of members, composition, organization), which offers interesting insights. The Styrian (public) scheme, established in 1996, has gained major attention (SFG 2001; Tödtling 2001; Hartmann 2002; Sölvell et al. 2003, 66-69; Andersson et al. 2004, 190-193; Tödtling and Trippl 2004), in contrast to the German (private) one, established in 2001. Table 2. Institutional differences of public top-down and private bottom-up modes of cluster promotion Domain Institutional genesis and composition of the actor group

Structures of finance and decision making

Preferred target areas and support measures

Induced clustering effects of increased innovativeness and competitiveness

Qualities of public top-down approaches (e.g. official ‘cluster policies’) Emergence from wider public interest with regional policy objectives; good analytical and conceptual base of the initiative; inclusion of a wide range of non-networked actors within regional and sector group boundaries Public funding requires a wellprepared effort; possible attraction of additional external funds; stable financial base for a preset time period; centrally controlled by public authorities Strong strategic orientation regarding regional development; diverse set of measures enlarging the contact base, establishing infrastructure, enriching the cluster by attracting investors and newly established firms Good impact primarily on (material) agglomeration economies and on regional development as a whole; fostering of a wider scope of new contacts including a range of coordinated activities; creating possibilities of broader long term effects on innovativeness, competitiveness and restructuring in the entire region

Qualities of private bottom-up approaches (e.g. regional thematic industry associations) Emergence from perceived industrial needs; selective inclusion of ‘useful’ actors based on pre-existing contacts; network shaped according to suitable functional relationships, not formal boundaries, regarding regional and sectoral reach Private funding provides fast, flexible/volatile finance with longer term perspective; high direct involvement of members in decision making; good motivation and active participation of members Focus on determinants of success of included firms/sectors; measures effectuate functional collaborations relying on good cohesion of members; high programmatic and institutional flexibility and variability Good impact primarily on (immaterial) collective learning and socially embedded collaboration; fostering of deeper functional and innovation-related collaboration; short and longer term direct effects on innovativeness and competitiveness of the set of included firms

Source: Depiction by the author Both cluster initiatives address automotive supply firms, which possibly allows to discern differences associated with the public versus private dichotomy, controlling for the influence of sector specifities. Such specifities mark various cluster

3 Which Mode of (CLUSTER) Promotion for which aspect of Entreprenuership? 21

features like networking, structures of competition, demand for skills, for external partners, and the importance of policy and infrastructure frameworks (Andersson et al. 2004, 106f). Automotive sectors display specific organizational changes, a vertical disintegration of firms at different hierarchical ‘tiers’ of production (Hudson and Schamp 1995); and competitive pressures raise the importance of innovation, qualification and systemic collaboration of co-locating producers, suppliers and service providers (Schamp et al. 2004). Entrepreneurship is sector specific, too, as start-up opportunities, for instance, mainly exist in the provision of knowhow intensive services. In general, the distinction between public top-down and private bottom-up modes of cluster promotion affects several institutional features (table 2), influences ways of governance, rules of interaction, norms and cultures of collaboration and learning (Fromhold-Eisebith and Eisebith 2005). The next sections point out major implications for entrepreneurship. 3.5.1 Public top-down cluster promotion and entrepreneurship Public cluster support offers advantages especially for start-up entrepreneurship and can easily be combined with respective political goals. Emerging from wider interests, initiatives are designed to fulfill overarching development objectives (table 2), and for many years fostering start-ups has been particularly favored by (regional) governments (Gilbert et al. 2004). Approaches can synergistically be integrated into existing administrative structures. Yet, election- or party-related interests may bear negative impacts: Authorities, eager to create numerous new firms and glossy statistics for policy marketing reasons, neglect issues of quality and sustainability. A strategy may even be implemented just for the sake of publicity and without a real need for cluster support, which hampers success (Formica 2003). Strengths in actor inclusion add to favorable conditions for firm formation. Public schemes, as illustrated by ACStyria and its over 190 members, address a wide range of – often hitherto isolated – firms/organizations in target sectors. This expansive networking attitude corresponds to the contact requirements of new enterprises, easing their task to find business partners (table 1). They can choose from a large number of potentials which offers ‘trial and error’ options. Useful contacts, however, can only materialize when the cluster management sets the right scope of included sectors. If that scope is too small, systemic advantages will become less probable. Public promotion usually outlines the spatial reach of a cluster according to administrative boundaries (province, district) because of funding regulations. This may not comply with the ideal functional region of the cluster, and networking could be forced into non-optimal shapes. Regarding structures of finance, public cluster promotion typically relies on wellplanned efforts and sizable budgets (table 2). The venture capital needs of new enterprises (Table 1) can be tackled, additionally supported by good public contacts

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to various sources of finance. ACStyria, for instance, has acquired external (EU) funding in combination with domestic investments (SFG 2001). But public finance is usually only guaranteed for a thrust period of about three years, and the transformation into a privately (co-)funded initiative causes some rupture (as in the case of ACStyria), which could also trouble new firms. Decision structures leave little space for constructive direct participation by most member firms, which suppresses their motivation to really be active in the cluster. Often cultural barriers and a lack of trust mark the interaction of public organizers and private actors in cluster promotion (Nauwelaers 2001; Newlands 2003). This hampers positive influences especially on entrepreneurship in mature, self-confident companies. Getting to operational features, public cluster policies have a strong strategic focus and are well embedded into wider programs of locality development (Tödtling 2001; Sölvell et al. 2003). By linking different clusters in one region and building bridges to same sector initiatives in other parts of the country, they improve the base for new enterprises and networking. In the Austrian case, the automotive cluster is connected with Styrian schemes for other sectors (Tödtling and Trippl 2004) and with public automotive clusters in other states (‘triple a’; http://www.aaa.or.at/). Public programs often apply a broad, diversified set of measures including infrastructure projects like setting up education/research organizations or start-up centers. Activities of various administrative agencies can be connected in complementary ways and provide a suitable seedbed especially for new firm formation. Cluster effects like increased innovativeness, competitiveness and growth could indicate entrepreneurial achievements. To which extent do public initiatives actually promote such signs of entrepreneurship? ACStyria has in fact noticeably improved major externalities by an integrated focus on creating special infrastructure, supporting labor qualification and attracting new cluster firms, also drawing on the positive signal value of the renown scheme. Incited new contacts between clustered actors may pave the way for concrete collaboration to evolve later on. In particular young enterprises assumingly profit from offered infrastructure, new contact opportunities, and the reputation building and marketing value of the initiative. Looking at the facts, however, ACStyria has hardly created new automotive start-ups, yet acquired remarkable exogenous investments. This partly corroborates assumptions that public cluster policies encourage firm formation entrepreneurship. Contrariwise, the initiative has rarely been conducive to innovation-based entrepreneurship in mature firms. Many interviewed automotive suppliers are not driven by innovativeness and have hardly received impulses from their cluster membership. Apparently, public cluster institutions favor the creation of first hand contacts of a social rather than functional nature, which hardly triggers upgrading dynamics indicative of the second kind of entrepreneurship.

3 Which Mode of (CLUSTER) Promotion for which aspect of Entreprenuership? 23

3.5.2 Private bottom-up cluster promotion and entrepreneurship Recently, critics have contested that public agency can successfully encourage clustering (Enright 2003; Formica 2003; Guinet 2003). Private initiatives primarily funded and governed by companies, as the actual cluster agents, provide a viable alternative. Anyway, substantial shares of recorded cluster institutions have been (co-)initiated or (co-)financed by private actors (Sölvell et al. 2003, 10). These efforts address virtually the same objectives as public schemes, but a different institutional setting entails different implications and effects (table 2; Fromhold-Eisebith and Eisebith 2005). Private cluster initiatives emerge bottom-up from perceived real needs of a group of firms, which positively affects motivation and commitment of members, also stimulating entrepreneurial objectives. Right from the start a larger number of industrial actors is involved in conceptualizing and implementing the effort, in automotive sectors, for instance, producers, service providers, R&D firms and education/research organizations (as exemplified by car e.V.). Member composition and boundaries of participation tend to be less fixated in territorial and sector terms. Memberships evolve gradually by the entry of additional actors who are really interested in participating and expect to profit. The institutionalized cluster rather assumes a functional shape that reaches across sector and administrative borders, potentially benefiting its dynamics (Martin and Sunley 2003). Its form can better correspond with the ideal defined ‘by the distance and time that people are willing to travel for employment and that employees and owners of companies consider reasonable for meeting and networking’ (Rosenfeld 2003, 361). Private initiatives are also more open to extra-regional and international business contacts, which supports the firms’ innovativeness in a global-local context (Nauwelaers 2001; EU Commission 2002) and augments creative potential to be exploited via growth dynamics entrepreneurship. The attitude to mainly include ‘useful’ new actors, often based on pre-existing contacts, instigates collective efficiency and co-opetive relationships that inspire innovativeness (table 1). The resulting ‘club’ character (evident among the 60 members of car e.V.), however, may exclude promising actors. Private initiatives display a good member motivation due to participative structures of finance and decision making (table 2). In schemes like car e.V., substantial shares of actors are involved in planning activities or designing measures, trying to derive corporate advantages from that. This bolsters their identification with, and integration into the initiative, enhancing entrepreneurial effects. Funds, based on fees, increase correlated to memberships, but tend to be kept lean and require efficient spending, attentively observed by the members. The financial flexibility, however, bears dangers of volatility since the exit of members may unexpectedly reduce funds and put planned activities at risk.

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Regarding the strategic focus and measures, private initiatives are mainly driven by egotistic corporate interests. They focus on improving the regional framework of firm development, rather than strengthening the regional economy as such. Accordingly, entrepreneurship in the firm, in terms of internal dynamics, is favored against entrepreneurship in the region, in terms of new start-ups. Actors prefer measures that effectuate functional market-, cost- and innovation-oriented collaborations. They aim at modifying and enriching their networks as is required by mature enterprises (table 1). This includes connections to similar private or public cluster initiatives in other regions. There is, however, less interest to foster new firm formation or attract investors as these could be competitors: start-ups are not explicitly supported. Investment promotion and the set-up of infrastructure is left to other (public) agencies. The institutional features are reflected in outcomes like increased innovativeness and competitiveness of firms (table 2), indicating growth dynamics entrepreneurship. Private initiatives, instead of improving the material base conducive to firm formation, rather influence immaterial, systemic cluster qualities. Functional creative interaction of firms and other organizations is particularly promoted, as required for growth dynamics entrepreneurship (table 1). This is to some extent corroborated by the German case of car e.V.. The initiative especially fosters members’ motivation, participation, and the emergence of trust, sense of belonging and collaborative attitudes, which helps actors to join forces. Many firms have gained some value addition from the initiative already after a short time, like impulses on corporate innovativeness and other aspects of competitiveness (Fromhold-Eisebith and Eisebith 2005). The growth dynamic variant of entrepreneurship is particularly stimulated, whereas impacts on new firm formation entrepreneurship are practically absent.

3.6 Conclusions This chapter explores links between the topics of entrepreneurship support and cluster promotion, entertaining a differentiating view. The reasoning, first, suggests that issues of entrepreneurship should play a more important role in cluster strategies (confirming Sternberg 2003 and 2005) and vice versa, due to related regional systemic requirements. Second, it is argued that the understanding and proactive promotion of entrepreneurship should extend beyond new business formation, since crucial potential for regional development is also represented by innovation based growth dynamics of entrepreneurial incumbent firms. Third and foremost, the chapter puts forward that public (top-down) and private (bottom-up) modes of cluster promotion, marked by organizational and operational distinctions, differ in supporting those entrepreneurship variants: The material and infrastructure focus, new networking attitude and high marketing value of public cluster schemes create a good seedbed particularly for new start-ups. The good

3 Which Mode of (CLUSTER) Promotion for which aspect of Entreprenuership? 25

motivation and network effectuation yielded by private initiatives, in contrast, rather support entrepreneurial endeavors in more mature firms. This issue has mainly been discussed conceptually, while the attempt to empirically underpin assumptions by comparing two automotive cluster initiatives, a publicly established (Austrian ACStyria) and a private one (German car e.V.), has only been halfway convincing. The unexpected lack of start-up entrepreneurship also in the first case may, on the one hand, be explained by sector specifities: Currently options for new automotive firm formation are quite low in Austria or Germany because of an industrial shift towards locations in Eastern Europe and Asia. Yet, the pressure on automobile production systems to remain innovative and competitive especially encourages entrepreneurial dynamics in existing firms. On the other hand, insufficient empirical evidence may indicate that entrepreneurship has not especially been addressed by both of the cluster initiatives, hence not leading to remarkable outcomes. If this is done more consciously in the future, bearing the discussed variation of entrepreneurship in mind, results will probably improve. Eventually, it must be noted that clustering and entrepreneurship do not necessarily only represent a constructive coupling. Research also hints at cluster disadvantages, like pressured specialized local labor markets, high turnover rates and high costs, which hamper entrepreneurship (Cooper and Folta 2000). We definitely need to learn more about how cluster dynamics and variants of entrepreneurship actually interact, beyond statistical correlations, in order to get to viable policy recommendations.

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3 Which Mode of (CLUSTER) Promotion for which aspect of Entreprenuership? 27 Nauwelaers, C. 2001. Path-Dependency and the Role of Institutions in Cluster Policy Generation. In Cluster Policies – Cluster Development? ed. Mariussen, A. 93-107. Stockholm: Nordregio. Newlands, D. 2003. Competition and Cooperation in Industrial Clusters: The Implication for Public Policy. European Planning Studies, 11: 521-532. Nijkamp, P, and Stough, R. R., 2002, Editorial introduction: Special issue on Entrepreneurship and Regional Economic Development. The Annals of Regional Science, 36, 369371. Nolan, A. 2002. Public Policy on Enterprise Clusters and Networks, In Small Enterprise Development in South-East Europe: Policies for Sustainable Growth, eds. Bartlett, W., M. Bateman, M. Vehovec. 167-192. Boston: Kluwer Academic Publishers. OECD. 2001, Innovative Clusters: Drivers of National Innovation Systems. Paris: OECD. ———. 2005, Entrepreneurship: A Catalyst for Urban Regeneration. Paris: OECD. Porter, M. 1998. Clusters and the new economics of competitiveness. Harvard Business Review, December: 77-90. ———. 2000a, Locations, clusters and Company Strategy. In Oxford Handbook of Economic Geography, eds. Clark, G. L., M. P. Feldmann, M. S. Gertler. 253-274. Oxford: Oxford University Press. ———. 2000b, Clusters and government policy. Wirtschaftspolitische Blätter 47: 144-154. van Praag, C. M. 1999. Some Classic Views on Entrepreneurship. De Economist 147 (3): 311-335. Raines, P., ed. 2002a. Cluster Development and Policy. Aldershot: Ashgate. ———. 2001, The Cluster Approach and the Dynamics of Regional Policy-Making. Regional and Industrial Policy Research Paper No. 47. European Policies Research Centre. Glasgow: University of Strathclyde. ———. 2002b, Cluster policy – does it exist? In Cluster Development and Policy, ed. Raines, P. 21-33. Aldershot: Ashgate. Reynolds, P., N. Bosma, E. Autio, et al. 2005. Global Entrepreneurship Monitor: Data Collection Design and Implementation 1998-2003. Small Business Economics 24 (3): 205231. Reynolds, P., W. D. Bygrave, E. Autio, et al. 2004. Global Entrepreneurship Monitor 2003. Executive Report. Erwing and London: Babson College and London Business School, http://www.gemconsortium.org/download/1131360419062/ReplacementFINALExecut iveReport.pdf (last accessed 7 November 2005). Ripsas, S. 1998. Towards an Interdisciplinary Theory of Entrepreneurship. Small Business Economics 10: 103-115. Rocha, H. 2004. Entrepreneurship and Development: The Role of Clusters. A Literature Review. Small Business Economics 23 (5): 363-400. Rocha, H., and R. Sternberg. 2005. Entrepreneurship: The Role of Clusters. Theoretical Perspectives and Empirical Evidence from Germany. Small Business Economics 24 (3): 267-292. Roelandt, T. J. A., and P. den Hertog. 1999. Cluster Analysis and Cluster-Based Policy Making in OECD Countries. An Introduction to the Theme. In Boosting Innovation: The Cluster Approach, ed. OECD. 9-23. Paris: OECD. Rosenfeld, S. A. 2003. Expanding Opportunities: Cluster Strategies That Reach More People and More Places. European Planning Studies 11: 359-377.

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Schamp, E. W., B. Rentmeister, and V. Lo. 2004. Dimensions of Proximity in Knowledgebased Networks: The Cases of Investment Banking and Automobile Design. European Planning Studies 12: 607-624. SFG (Styrian Business Promotion Agency). 2001. Good Practice on Cluster Management. Report for the EU project ACENET – Accelerating the Establishment of Clusters and Company Networks. Graz: SFG. http://www.clusterlink.com/ACENET/new/Pdf_g_p/Styria.pdf (last accessed 7 November 2005). Shane, S. 2003. A General Theory of Entrepreneurship. The Individual-Opportunity Nexus. Cheltenham: Edgar Elgar. Sölvell, Ö., G. Lindqvist, and C. Ketels. 2003. The Cluster Initiative Greenbook. Gothenburg: Ivory Tower AB. http://www.ivorytower.se/eng/projgrnbk.htm (last accessed 7 November 2005) Sternberg, R. 2003. New Firms, Regional Development and the Cluster Approach – What Can Technology Policies Achieve? In Innovation Clusters and Interregional Competition, eds. Bröcker, J., D. Dohse, and R. Soltwedel. 347-371. Berlin: Springer. Sternberg, R. 2005. Entrepreneurship in German Regions and the Policy Dimension, In Local Heroes in the Global Village. Globalization and New Entrepreneurship Policies, eds. Audretsch, D. B., G. Heike, and C. W. Wessner. 113-144. New York: Springer. Sternberg, R., and S. Wennekers. 2005. Determinants and Effects of New Business Creation Using Global Entrepreneurship Monitor Data. Small Business Economics 24 (3): 193-203. Sternberg, R., H. Bergmann, and I. Lückgen. 2004. Global Entrepreneurship Monitor – Länderbericht Deutschland 2003. Cologne: University of Cologne. Sternberg, R., and T. Litzenberger. 2004. Regional Clusters in Germany – their Geography and their Relevance for Entrepreneurial Activities. European Planning Studies 12 (6): 767-791. Tödtling, F. 2001. Industrial Clusters and Cluster Policies in Austrian Regions. In Cluster Policies – Cluster Development? ed. Mariussen, A. 59-78. Stockholm: Nordregio. Tödtling, F., and M. Trippl. 2004. Like Phoenix from the Ashes? The Renewal of Clusters in Old Industrial Areas. Urban Studies 41: 1175-1195. Wagner, J., and R. Sternberg. 2004. Start-up Activities, Individual Characteristics, and the Regional Milieu: Lessons for Entrepreneuship Support Policies from German Micro Data. The Annals of Regional Science 38: 219-240. Wolfe, D. A., and M. Gertler. 2004. Clusters from the Inside and Out: Local Dynamics and Global Linkages. Urban Studies 41: 1071-1093.

4 The Dynamics of FDI of the TFT-LCD Cluster: A Study of Japanese Firms in Taiwan W.C. Wang, Institute of Public Affairs Management, National Sun Yat-Sen University, Taiwan

4.1 Introduction This chapter examines the dynamics of foreign direct investment (FDI) in the high tech Thin Film Transistor Liquid Crystal Display (TFT-LCD) industry. It is stretched from the case study of two global important actors of Japan and Taiwan, as the former possesses technologies of TFT-LCDs and the later strengthens in manufacturing. In the face of the global economy and intensified international competition, attracting highly qualified technology-based FDI for the ‘latecomer’ countries has, in recent years, played an important role as an increasing focus in assisting economic development (Hobday 1995a, 1997). FDI also can be built as inter-region resources sharing to establish a comparative advantage for bettering and enhancing their mutual market strength. As the TFT-LCD firms in Japan are strengthening on research and development, and Taiwan has the competitive advantage on high tech manufacturing. When these two regions connect together by the networking, FDI can bridge resources to increase both their comparative advantage to form a better competitiveness for both in the global market (Saxenian 1999). Japanese firms have long-term relationships with Taiwanese businesses pertaining to mutual international trade, and Japan is the main host of the foreign direct investors to Taiwan, such as in electronics, precision machinery, and automobile industries. Alone with the dynamics of economic development, contributions of Japanese FDI to Taiwan shift from labour intensive to more high tech industries. In 1995 Taiwan transferred technologies from Japan to commence the new industry of the TFT-LCD manufacturing. No more than a decade, Taiwan has been shifted into the world’s largest TFT-LCD producer in product value, as surpassing Japan in 2001 and overtaking South Korean in 2004. The extraordinary performance of the industrial TFT-LCD geography in Taiwan is considered that Japan’s foreign direct investors have played an important role (Hung 2002; Linden et al. 1998). However, why do Japanese firms choose Taiwan as the FDI destination to invest to? In addition, why do they particularly locate in Taiwan? What are the advantages provided by Taiwan for attracting Japanese TFT-LCDs inward investment? Also, what does Japanese FDI play a role for shaping the TFT-LCD industrial 29 J. Gatrell and N. Reid (eds.), Enterprising Worlds, 29–39. © 2006 Springer.

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clustering? To reply those questions, this paper attempts to scrutinize the dynamics of the Japanese TFT-LCD FDI firms in Taiwan. This paper is then structured as following. Next section begins with a review of academic studies, embracing to the theory of flying-geese model and political geography on scalar fixes. Section three, the methodology of the research will be detailed. The following section is the results that materials are triangulated from the fields as the analytical qualitative records are discussed. Final section puts forward some conclusions and considers the practical implications of FDI on the sustainability of industrial clusters in host nations.

4.2 The Dynamics of Japanese FDI in Taiwan After World War II, Japanese FDI to Taiwan launched in 1952 and heated up while Taiwan instituted new initiative of ‘Statute for the Encouragement of Investment’. As Taiwan founded the world first ‘export processing zone’ in 1966, Japanese FDI came to enjoy the advantages of the low labour wages, no environment control, educated stable labours, especially the hundreds of thousands of available female labour, and supportively developmental government (Castells 2000b). With the policies of economic liberalization, Japanese FDI in Taiwan is largely expanded both in varieties of industries and amounts of capitals. This is transnationalism for impelling Japanese enterprises to seek their fitting institutions and cultural space, as the place for their producing activities of the global overall arrangement (Hsu and Saxenian 2000; Ley 1999; Mitchell 1995; Olds and Yeung 1999; Zhou and Tseng 2001). In this stands, we shall revisit East Asian development of flying-geese model, and frame the political geography theory on scalar fixes to clarify the dynamics of Japanese FDI into Taiwan TFT-LCD industrial clustering. With flying-geese immigrant competence metaphor, the model developed by Akamatsu (1962) interprets Japan’s industrial development and trade situation to develop the model regarding Japan and other Asian developing countries putting forwards of industrialization. This theory points out FDI and its importance in the international economic activity of trade structure. At flying-geese framework, an industry developed experiences the stages of importing, import substitution, export direction, and finally leading others to fly ahead (Korhonen 1994; Kwan 1994; Yamazawa 1990). Under such an evolutionary, the leading head of flyinggeese highly relies on heterogeneous than getting homogenous stage of ‘latecomers’ (Hobday 1995a). Since the late 1960s, the economic development in Japan and East Asian newly industrialized economies and the Association of Southeast Asian Country and Mainland China presents a kind of specific structure in their industrialization (Brohman 1996; Hill and Fujita 1996; Kim 1993; Kwan 1994). Kotler et al. (1997) also point out that there is an adjacent relation to the flyinggeese model that the manufacturing industry appears in the region of the Asia.

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Furthermore, Edgington and Hayter (2000) argue that such evolutional model of flying-geese appears also in geopolitics of the Asian countries. However, in the relevant research on high-technology or knowledge-based industries of recent years, the model is challenged and criticized (Hart-Landsberg and Burkett 1998). Research on the electronic industries shows it cannot fall into flying-geese competent model (Hart-Landsberg and Burkett 1998; Mathews 2001; Tung 2003). Thus, flying-geese model is generally considered not to support in development of high-tech industries. Furthermore, Sikorski and Menkhoff (2000) think flying-geese model is only convincing in the situation during 1987 to 1996, as financial crisis in 1997 thereafter Asian economies cannot be explained by the model. Nevertheless, a latest interesting work on the TFT-LCD relevant industry to explain flying-geese model of Japanese FDI in Taiwan, C. Wang (2004: 20-21) claims ‘there is a lack of the solid evidence to conclude that flying-geese theory goes bankrupt’. However, he does not provide solid empirical evidences to demonstrate how and what it is not bankrupt. Linden et al. (1998) examine strategies that Korean and Taiwanese firms and governments adopted to build globally competitive advanced display manufacturing capabilities in the face of Japan’s manufacturing advantages to question, ‘are flying geese moving targets or sitting ducks?’ They observe that the lead goose appears vulnerable. Interestingly, whether the dynamic of Japanese FDI in TFT-LCD industry explains the theory of the flying-geese model remain contests and deserve further rigorous examination. Deriving from a political economy perspective of Hobdays’s (1995b) work with Japan’s historic learning-based approach to industrialization and their empirical observations, Hayter and Edgington (2003) reflect on the effectiveness, problems and dilemmas of Japanese multinational enterprises in transferring such knowhow to the region summarized as a ‘reverse product cycle model’. This model portrays FDI as a ‘bargain’ between Japanese multinational enterprises and host countries, and which becomes more difficult to negotiate on political geography as FDI moves from low-skilled manufacturing to more innovative activities. Nonetheless, in Hayter and Edgington’s paper the empirical evidence provided in the Taiwan’s section is moderately limited. More recent as known as high-technology industries development in particularly the semiconductor industry development, there are more linkages and relationships between the US (Silicon Valley) and Taiwan (Hsinchu) (Hsu and Saxenian 2000; Mathews 1997, 2001; Saxenian 1999; Saxenian and Hsu 2001; W. Wang 2005), rather than Japan played the role. In addition, the dynamics of new emerging industries, particularly in TFT-LCD developmental scenario in Taiwan, there is a lack of concrete material in the Hayter and Edgington’s analysis. Articulating the requirement of heterogeneous advantages in flying geese model in development of ‘new economic geography’, scale can be applied and understood as a partial and temporary resolution of the tension of capitalism between homogenization and differentiation (Mamadouh, Kramsch, and Van der Velde 2004). Jonas (1994: 257) notes that many of the social objects that geographers encounter

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in research of multinational corporations have well-defined ‘scale of operation’. Even if a social entity does not have an adjective with an explicitly spatial connotation, it is clear that its attributes are affected by its scale of operation. ‘Scale of organization’ is then considered as ‘an attribute of agents (individuals or institutions, capitals or noncapitals) and concerns the behaviour of each in planning and acting throughout an area’ (Collinge 1999: 564). The ‘scale of operation’ is not only determined by the ‘nature’ of a social entity (a multinational, for example, typically operates at the international level), but also by how the space in which it operates is organized (Uitermark 2002: 746-7). Therefore, ‘scalar fixes’ thus aim to continue capitalist transformation and the rescaling of capitalist accumulation and to dominate and expand the regulation of ‘scale of operation’. ‘Scalar fixes’ therefore aim to restructure the ‘local’ for articulating the industrial clustering into the ‘global’ practices (Brenner 2001; Collinge 1999, 2005; Harvey 1982, 1985, 2003; Jessop 2000; MacLeod 1997; Swyngedouw 2000, 2004; Uitermark 2002).

4.3 Methodology Since 1980, with inflammatory landscape developed by high tech industries in personal computers and semiconductors, Taiwan has become an important location for producing information and communication related products (Castells and Hall 1994; Mathews 1997, 2001). Among those products, TFT-LCDs are necessitated to fulfill the global production chain. However, all the flat panel displays were imported from Japan and South Korea. For example, 49% of global market value of laptops in 1999 was made in Taiwan, but Taiwan splurged an approximately NT$ 3 billion dollars to procure the TFT-LCDs (Lee 1999). Japan possesses the foremost technologies and has already well-constructed the industrial structure and production chain in the industry. However, Japanese firms considered that they are the ‘national treasures’, and the technologies cannot easily to be transferred to overseas. Nevertheless, since 1995 Mitsubishi (Japan) initially transferred the TFT-LCD technologies to Chunghwa Picture Tubes (Taiwan). The rest Japanese firms those who have the technologies gradually transferring them to Taiwan, and/or strategically collaborating with Taiwan firms, such as Sharp (Japan) and HannStar (Taiwan), IBM Japan and AUO (Taiwan), and Fujitsu (Japan) and Chi-Mei (Taiwan). Furthermore, as Taiwanese enterprises largely and locally invest in the TFT-LCD industry, it attracts Japanese related firm’s cross-border direct investment over. Japanese thus TFT-LCD firms started to directly invest in Taiwan since 1997. The rescaling of the industrial governance puts Taiwan on the map of the TFTLCD economic geography. Especially, Tainan, in the south Taiwan, has then been sculpted as the world largest TFT-LCD cluster since the Southern Taiwan Science Park (STSP) was initiated by the government in 1997. Launched also at the time of 2000, where Japanese FDI also has stridden over, the Tainan Technology In-

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dustrial Park (TTIP), 30 minutes drive away from the nearby STSP. Interestingly, when looking into the Japanese geographical distribution in technology parks of the Taiwan’s most important industrial initiatives, until end of 2004 more than 80% of them are located in these two Tainan industrial initiatives (TTIP and STSP) (see Table 1.). Fourteen Japanese firms have been already encamped, and amongst the FDI firms ten of them are manufacturing the TFT-LCD related key components, such as glass substrates, polarizing films, and tubes. Endorsed by the Japanese FDI firms, Tainan is shaped itself as a new emerging node of the global TFT-LCD production chains. Table 1. Japanese FDI Geographical Distribution at Technology Parks in Taiwan Place North Taiwan Central Taiwan

Name of Japanese FDI Firm

Number All

Percentage

TFT- All LCD 0 5.9%

TFTLCD 0

5.9%

8.3%

5.9%

8.3%

Hsinchu Science Park Tosh Quartz** 1 (1980)* Central Taiwan Sci- Nitto 1 1 ence Park (2002) Yunlin Technology Asahi Glass 1 1 Industrial Park (2002) South Southern Taiwan Sci- Finex, Nitto, Sumika, Ni- 9 6 Taiwan ence Park (STSP) hon, Stanley, Lindo, Ulvac, (1997) Tosh Quartz, Sekiguchi Tainan Technology Toppan, Ulcoat, Toyo Ink, 5 4 Industrial Park (TTIP) Nippon Sheet Glass, Chaohe Gas (2000) * Number in bracket is the year when the park was established. ** Those firms in underline are not belongs to the TFT-LCD industry. Sources: Each Park’s business directory (2005)

52.9% 50.0% 29.4% 33.3%

The empirical fieldwork of research implemented uses a triangulation methodology. A structured questionnaire both in Mandarin and Japanese was sent to the all Japanese FDI practitioners and collected when face-to-face interviews were conducted. And, face-to-face interviews to the all practitioners, local government, administration of two industrial parks and the related local TFT-LCD firms were simultaneously implemented between March and September 2004. However, at the beginning contact with Japanese firms is difficult; especially the Japanese businessman is fairly conservative. Through the author well-built personal networks with the local government and administration of the industrial parks, all the questionnaires are returned. About thirty respondents were interviewed, each for approximately one and a half hours.

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4.4 Flying-Geese Model and Scalar Fixes The global TFT-LCD industry currently develops mainly in these three countries of Japan, South Korea, and Taiwan. In the ‘technology’ term, Japan is generally considered as essentially the leading country in the TFT-LCD technologies. Also, with the ‘flying-geese model’, Japanese firms FDI in the East Asian countries are supported to probe into the regional industry development. In addition, C. Wang (2004) argues that Japanese TFT-LCD firms exploit the strategies of FDI, technology transfer, and/or OEM in Taiwan to obtain their own necessary in panels and relevant components. The rest key components of the Japanese TFT-LCD firms, such as substrates, polarizer, colour filter and backlight technologies, shift standardized technology to Taiwan, in order to upgrade and advance themselves R&D to higher-level products. As a Japanese manager pointed out that, at present, in the panel manufacturing technologies, Japan holds the leading positions, because we have patent rights. ….. Japan may not be certain to lose its advantages after transferring technology to Taiwan, because more advanced technology will be promoted and upgraded by Japanese firms. For example, the new technology, OLED, is developed in the world cutting-edge in Japan, and it can be made for the bending panels. Our technical development is still faster and better than South Korea and Taiwan. Although Taiwan also develops in this respect, technology advantages are belongs to Japan. (Interview ST-1, 2004/3/17) It seems that the FDI in the TFT-LCD industry from Japan to Taiwan is to accord with to flying-geese principle. This is to say that the Japanese enterprise transfers technology to other latecomers, and then upgrades itself in the higher technological development. However, in the East Asia, South Korean and Taiwan are not actually following the development of Japan in the flying-geese linear geometry, as nowadays they are the main TFT-LCD producers in the world. Firstly, in the South Korean scenario, since 1990 highly relying on the government-supported and Chaebol-led development to TFT-LCDs, the Samsung (at the beginning transferring technologies from the US’s Corning), LG (later allied with Dutch Philip as LG-Philips), and Hydix successively invest in the large size of TFT-LCD panels via their own research and development of TFT-LCD production. Drawing back to 1999, Samsung and LG were already on a par with the Japanese leaders and are ahead in terms of production processes (Lee 1999). With more up-to-date fabrication lines, the Koreans are aggressively ramping up new facilities of next-generation, larger TFT-LCD panels, and South Korea is regarded to turn to the head of ‘flying geese’ (Lee 1999; Linden et al. 1998). The industrial relations among the South Korea, US (i.e. Corning), and Europe (i.e. Philip) are globally networked in the TFT-LCD production chain, rather only Japan plays the role to Korean development alone. Rather, the East Asia’s flying geese model can be accounted for the new industrial landscape of global TFT-LCD industry. In addition, it can be found that that Japanese panel manufacturer has not chosen to make a direct investment in South Korea. In the part of direct investment to

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Mainland China by the Japanese enterprises, there are fitted into components of the production chain in terms of cost consideration for comparative advantages for facing global competition. For South Korea, there is no inevitable relation of ‘following’ Japan. Secondly, regarding the case of Taiwan, Japanese enterprises transfer technology to and collect fees of patient rights from Taiwan. By strategic alliance in panel industry to develop the TFT-LCD products, the certain proportions of these products are vended back to Japanese firms to carry on their end of production chain. The geographical strategy aims to keep their dominance globally in this industry as the strength of ‘made in Japan’. This Japan-Taiwan alliance is the mutual interdependences on both side production structures for the TFT-LCD industrial development. Executives of electronic firms in the Tainan districts regard the point of view why do Japanese enterprises transfer TFT-LCD technologies to Taiwan: … because the cost in Japan is high; the labour cost is high. In addition, Japan has already been surmounted very obviously in the competition by South Korea. South Korea regards TFT-LCD as the national undertaking. In this regard, we [Japan] have to unite the secondary enemy [Taiwan] to encounter the main enemy [South Korea] .…... Another reason is to survive. When staying in Japan can not be survival, we shall go abroad. South Korea has not bought technology from Japan. ….… However, many panel factories in Taiwan bought technologies from Japan; here gradually turns great demand naturally. We come over. (Interview ST-2, 2004/4/26) Because the production cost has been too high, Japan has faded out gradually in this industry. It is much higher than South Korea and Taiwan. The cost has no way to the situation of dropping, thus we move outside bit by bit. By doing so, I think in addition that we are forced to face the competition, because the South Korean manufacturers chase up straight. South Korea has a strong anti-Japanese complex; I find it on intimate relations in Taiwan for Japanese to transfer technologies. We do not want to let South Korea to be the largest producers alone. In 2002, South Korea had been big alone by having 40% of the TFT-LCD market values. However, Japan declined gradually, so we have to move the TFT-LCD development to Taiwan by helping Taiwan to grow up to confront with South Korea. (Interview ST-10, 2004/3/17) Allied with Taiwan to counter competition from South Korea is the main purpose that Japan comes to here. (Interview A-9 2004/9/19) Therefore, in terms of facing the robust competitor of South Korea, Japanese attempts to dominate the early entry advantage of ‘scale of economy’ in the TFTLCDs. Technology transfer to and FDI in Taiwan aims to fix their ‘scale of production’ by such a geographical strategy. The largest producer, Taiwan, has still acquired to pay to Japan with the pretty a huge amount of patent rights. Such ‘sca-

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lar fixes’ in the globalizing competition, particular facing South Korea’s threats, helps Japanese firms to ‘seek survival’ and to extend their capitalism accumulation. Indeed, Linden et al. (1998) also pointed out that South Korea’s entry let Japanese more willingness to transfer technology of ‘national treasure’ to Taiwan. Japanese enterprises face the long-term economic declines and short of production competences, and these critical reasons lead unable or unwilling to continue and keeping the competition with essential advantage in TFT-LCD for large investment locally. Japanese companies satisfy the decision by way of permitting the licenses and OEM orders in technology to collaborate with manufacturers of Taiwan for global ‘scalar fixes’. For ‘scalar fixes’, the attention of geographers shifted to its social construction by the beginning of the 1990s. Definitely, in political geography, scale making is claimed as ‘an entangled and hybrid product of negotiation and contestation’ (Newstead, Reid, and Sparke 2003: 487). Aiming to in the capitalist dominance of industrial standardization in geographical fixes both in products and production process, Japan’s historic learning-based approach to attend the position of ‘an advanced country’ is captured beyond the ‘nature’ of flying geese model. Facing the weakening domestic economy, the structural transformation in order to manipulate and dominate the various scale of production, such as international standards, codes, patients, prices, and technologies know-how via ‘scalar fixes’, possibly juxtaposes Japanese capitalist domination.

4.5 Conclusions The scalar fixes on new economic geography in the explanation leads Japanese TFT-LCD firms FDI in Taiwan. Also, because ‘Taiwan has more relevant relationships with Japan after all (interview A-1, 2004/5/4)’, the Japanese enterprises have such a cultural advantage in Taiwan for FDI strategies on new economic space to establish both sides production of interdependences. So, the Japanese firms come over to Taiwan to produce network territories and ‘scalar fixes’ for the market deeper strength to expand Japanese enterprises TFT-LCD industry on the scale of the global market to ‘encounter competition from South Korea’. This relation of interdependences cannot be explained by the single direction of flyinggeese model. The flying-geese model with its long-term history in the evolutional process seems to meet difficulties to depict Taiwan TFT-LCD industry development. However, the main reason that Japan transferred technologies is Japanese enterprises facing domestic economic recession, South Korea rousing itself to catch up, and strong appeal of markets of Taiwan. Japanese enterprises adopt the strategies of FDI for capitalism accumulation of their ‘scalar fixes’, which keep Japan to dominate as a leader in the industry. Taiwan is considered as the wing of the flying-geese model of the formation in early days for industrialization, but, in a sense, no matter Taiwan it appears to be flat to fly to the situation that even surmounts with ‘flying-geese head’ obviously on economy or technology. By utilizing various types of strategic alliances to collaborate with Taiwanese enterprises, Japan enterprises at the early time originally transferred technology to Taiwan.

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Therefore, in terms of the depressions of Japanese domestic market for producers of the Japanese key components, they have to adjust themselves for the global overall re-arrangement of the market and scalar fixes to seek the most favorable market. Nevertheless, in the Tainan districts, the points related to traditional transition and capitalist restructure, conditions, and relationships, deserve further follow-up study.

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5 Collaborating to Compete: The Case of Northwest Ohio’s Greenhouse Industry N. Reid, Department of Geography and Planning The Urban Affairs Center The University of Toledo, Toledo, Ohio M. Carroll, Department of Economics Center for Regional Development Bowling Green State University, Bowling Green, Ohio “If we don’t pull together to identify and solve our own problems, we will surely lose a number of greenhouses” 1

5.1 Introduction Faced with increasing international competition that is threatening their livelihood a number of greenhouse owners in northwest Ohio have adopted a cluster-based strategy in an attempt to remain competitive. Initiated and designed by university researchers and supported by funding from the United States Department of Agriculture this strategy centered around getting individual greenhouse owners to work collaboratively to address industry-wide challenges. The challenges addressed by this strategy are too large or too complex for individual growers to tackles by themselves. Challenges such as high energy costs and the lack of a market presence are beyond the scope of individual greenhouse owners to address. Working together with other greenhouse growers in the region and identifying collaborative solutions to these industry-wide problems is probably the only mechanism by which these, and similar challenges, can be successfully addressed. However, getting individual greenhouse owners to work collaboratively with each other is a major challenge in itself. Historically, many of the growers in northwest Ohio are fiercely independent. They are used to working by themselves. Collaboration is not part of their vocabulary. As a result, the level of trust between greenhouse owners tends to be low. Most of the growers in the region compete with each other for market share. They view each other as competitors, not collaborators. However, overcoming this resistance to collaboration was critical if a cluster-based approach to addressing the challenges facing the industry was going to take root and evolve into a viable competitive strategy. 1 Dick Bostdorff, owner, Bostdorff Greenhouse Acres, Bowling Green, Ohio (Bowling Green State University, 2005).

41 J. Gatrell and N. Reid (eds.), Enterprising Worlds, 41–56. © 2006 Springer.

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In this chapter we describe the process used to get growers to think and act in a collaborative fashion and to assess the result of these efforts to date2. Following this introductory section the remainder of this chapter is organized as follows. In section 2 we describe the philosophy underpinning cluster-based economic development. This is followed, in section 3, by a description of the major competitive challenges facing northwest Ohio’s greenhouse industry. In section 4 we describe the genesis and evolution of northwest Ohio’s greenhouse cluster. Next, in section 5, we describe the first collaborative project undertaken by the cluster – namely branding and marketing. In section 6 we conclude with some thought regarding the evolution of the cluster to date and identify some of the major challenges for its future development.

5.2 Cluster-Based Economic Development Economic development strategies organized around a cluster-based approach are increasingly common. Currently, there are over five hundred such initiatives worldwide (Solvell et al, 2003). Communities from San Diego (SANDAG 2001) to South Africa (Sunday Times, South Africa 1997) are pinning much of their economic future on what they are calling cluster-based economic development, while industries ranging from thoroughbred horses (Akoorie 2000) to Formula One racing cars (Henry and Pinch 2001) are being produced by businesses that are part of an industrial cluster. Despite the popularity of cluster-based economic development there is an emerging literature that is highly critical of this particular approach (e.g., Martin and Sunley 2003, Taylor 2005). It is not the purpose of this chapter, however, to review or assess the validity of the anti-cluster literature. Our objective, here, is to simply outline the genesis and evolution of an effort to enhance the economic competitiveness of the greenhouse industry in northwest Ohio. We use the term ‘cluster” as the organizing framework for this effort. We will leave it to others to argue over whether what we are doing in northwest Ohio is really cluster-based economic development. Having said that, we believe that it is important that we outline our understanding of cluster-based economic development, and to define the concept as we have applied it to the northwest Ohio greenhouse industry. While there are an alarmingly large number of definitions of what is meant by an industrial cluster and cluster-based economic development (Martin and Sunley 2003) we used, as our starting operational definition, that provided by Porter (1998, 78):

2

The project described in this chapter is an ongoing one. The results reported here represent the status of the project at the time of writing. For the current status of the project please contact the authors.

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“Clusters are geographic concentrations of interconnected companies and institutions in a particular field . . . they include, for example, suppliers of specialized inputs such as components, machinery, and services, and providers of specialized infrastructure . . . many clusters also include governmental and other institutions – such as universities, standards-setting agencies, think tanks, vocational training providers, and trade associations – that provide specialized training, education, information, research, and technical support”. The secret to a successful cluster-based economic development strategy, in our opinion, is to marshal all the relevant stakeholders (primary producers, suppliers, universities, training providers, etc.) to work together to help an industry become more competitive in the market place. How is this achieved? As we sifted through the literature on cluster-based economic development we identified three key characteristics that we thought would be necessary if northwest Ohio’s greenhouse industry was going to be successful in utilizing a cluster-based approach to retain its competitive edge. Collective Efficiency: Collective efficiency (Schmitz 1995) is the competitive advantage that can be attained through the combination of external economies of scale and joint action. External economies of scale are very often passive and, as such, fall into the producer’s lap. Examples of external economies of scale include the existence of a specialized labor pool and support infrastructure such as a specialized supplier base (Fromhold-Eisebith 2006). External economies of scale can also manifest themselves when a region develops a reputation for being a producer of a particular good or service (e.g. automobiles in Michigan and steel in Pennsylvania). While external economies of scale are beneficial it is only when co-located companies engage in joint action that the full benefits of being in close geographic proximity are realized. As noted by Porter (1998, 88), “the mere colocation of companies, suppliers, and institutions creates the potential for economic value; it does not necessarily ensure its realization”. Similarly, Schmitz (1999, 1628) notes that “external economies are important to growth but are not sufficient to ride out major changes in product or factor markets; that requires joint action”. Unlike external economies of scale, joint action is active and requires the conscious and deliberate collaboration of producers. Joint action on the part of producers can result in a wide variety of benefits, including improved product quality (Nadvi 1999, Schmitz 1999), reduced manufacturing costs (Wolverhampton Telford Technology Corridor 2005), the sharing of expensive infrastructure (Meyer-Stamer 1998; Kennedy 1999), and enhanced marketing prowess (Cawthorne 1995; Lundequist and Power 2002). In our opinion, collective efficiency (external economies of scale plus joint action) is the defining critical ingredient of successful cluster-based economic development initiatives. The central focus of any cluster initiative, therefore, should be getting firms to work together to identify collaborative solutions to shared problems (Diez 2001).

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Social Capital: A major barrier to joint action can be low levels of social capital within an industry. Social capital is defined by Putnam et al (1993, 67) as “features of social organization, such as trust, norms, and networks, that can improve the efficiency of society by facilitating coordinated actions”. Social capital plays a critical role in the development of any successful cluster-based economic development initiative (Hospers and Beugelsdijk 2003). For example, if competitors are going to engage in joint action it is imperative that a certain level of trust exist between them. However, it is not unusual for low levels of trust to exist between geographically proximate competitors. How can competitors be prompted into engaging in joint-action? There is growing evidence from the developing world that that an exogenous threat to the competitiveness an industry in a particular geographic region can be a catalyst for joint action to occur (e.g. see Meyer-Stamer 1998, Knorringa 1999, Rabellotti 1999, Schmitz 2000). For example, textile manufacturers in Santa Catarina, Brazil increased their level of cooperation in response to increased foreign competition that resulted from a decision by the Brazilian government to abandon its import substitution strategy and to open up its markets to foreign producers in the early 1990s (Meyer-Stamer 1998). In the footwear industry cluster in Agra, India cooperation between cluster members increased after the collapse of one of its major markets, the Soviet Union, as well as the decision by the Indian government to lower import tariffs in the early 1990s (Knorringa 1999). In the case of the surgical instruments cluster in Sialkot, Pakistan it was the need to improve quality to meet international quality assurance standards that prompted a move towards joint action (Nadvi 1999). Bottom-up Engagement: Much of the literature also emphasizes the need for a bottom-up approach to cluster-based economic development. Empowering business owners and/or decision makers to identify a collective pathway to higher levels of competitiveness is critical to cluster success (Reid and Carroll 2005). Indeed, company decision makers should be involved from the very beginning of any cluster initiative. Furthermore, they have to play a central role in design and ongoing direction of the cluster once it has been established (Cluster Navigators 2001). Unless those companies for whom the cluster strategy is designed to help play a central management and decision-making role we believe that the cluster will be doomed to failure and has little likelihood of any long-term sustainability. “Clustering is not a few deciding for many; it is an inclusive, collaborative process” (Cluster Navigators Ltd. 2001, 13). Successful clusters promote collective learning that is bottom-up and interactive in nature (Landabaso 1995).

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5.3 Northwest Ohio’s Greenhouse Industry Northwest Ohio’s greenhouse industry has a rich history, dating back to European immigrants who settled in the region during the 18th and 19th centuries. Today, the region (Figure 1) is one of the major producers of greenhouse produce in the United States. Lucas County, the center of the region’s greenhouse industry, ranks 4th in state and 94th in the nation in terms of the value of production of greenhouse produce. This places Lucas County in the top 4% statewide and the top 5% nationwide. Today, however, the economic viability of the northwest Ohio’s greenhouse industry is under threat from competing regions. In recent years, southern Ontario in Canada has emerged as major competitive threat to northwest Ohio’s greenhouse industry (Reid and Carroll 2005, LaFary et al 2006). This threat is both perceived and real. In a survey of northwest Ohio growers Canada was identified as the most significant competitor to northwest Ohio’s greenhouse industry (Reid and Carroll 2005).3 The perception that Canada is a major competitor to northwest Ohio’s greenhouse industry is validated by trade data. In 1995 Ontario had a positive trade balance with Ohio in floriculture products of $531, 186. By 2004 this trade gap had increased to 2,014,171 (Industry Canada 2005).4 Other challenges facing the industry include endemically high utility costs, the lack of a strong market presence, and the existence of price wars between local competitors. On the other hand, the industry has a number of strengths and opportunities that it could potentially capitalize on. These include a wealth of local grower knowledge and experience, considerable latent demand for the industry’s output, and the access to a significant scientific knowledge base available from locally-based university researchers, agricultural extension agents, and scientists from the USDA’s Agricultural Research Service (Table 1).

3

A mail survey of northwest Ohio greenhouse growers was conducted during the period, March-May 2004. The survey was conducted using the Dillman (1978) method. The survey was sent to all 82 growers in northwest Ohio. Twenty-seven surveys were returned, yielding a response rate of 33%.

4

All monetary values cited in this chapter are expressed in 2004 US dollars.

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Fig. 1. Northwest Ohio

Table 1. STRENGTHS

WEAKNESSES

Critical mass of growers Extensive grower experience and knowledge Predominantly family-owned and operated Large regional production capacity Access to local university, extension and Agricultural Research Service expertise

Historically, little collaboration between growers No identifiable market brands Lack of strategic marketing Small size of individual growers Generational nature of business Heavy reliance on traditional sources of fuel Old greenhouse buildings Dated production technology Limited access to capital THREATS

OPPORTUNITIES Increase collaboration with each other Capitalize on latent market demand Develop identifiable market brand and improve marketing Development of niche markets Alternative energy options available in region Facility modernization Adhere to higher quality standards

Global competition Price wars with regional competitors Big Box store purchasing agreements High utility costs

Given this competitive backdrop the authors received funding from the U.S. Department of Agriculture to assess the current economic state of northwest Ohio’s

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greenhouse industry and to identify, develop, and implement a strategy to address the competitive challenges facing the industry. After a careful assessment of the industry, and its attendant challenges, the authors identified a cluster-based approach as the most appropriate one for the industry. Would the threat posed by Canadian competition be of sufficient magnitude to constitute ‘the crises that much of the literature points to can act as a catalyst to joint action?

5.4 The Development of Northwest Ohio’s Greenhouse Cluster The decision to explore the possibility of establishing a greenhouse cluster in northwest Ohio occurred during the summer of 2004. During the previous year, a survey of northwest Ohio growers had been conducted. The survey results indicated an industry that was facing a multiplicity of competitive challenges. To respond to these challenges we decided to explore the possibility of developing a cluster-based economic development strategy for the industry.

Table 2. Year 2003 2004

Month August MarchMay August August October

2005

December January January May August August November

Milestone First year of funding received from the USDA Mail survey of 82 northwest Ohio growers completed Second year of funding received from the USDA Four-day Visit by authors to the West Midlands region of England to learn more about cluster-based economic development Presentation of cluster concept made by CST to 8 northwest Ohio growers Follow-up meeting between CST and 8 northwest Ohio growers Presentation of cluster concept by CST made to winter conference of Toledo Area Flower and Vegetable Growers Association Cluster Advisory Board established Project Manager hired Cluster Champion hired Third year of funding received from USDA Branding and Marketing consultants hired Maumee Valley Growers established

Before embarking on the development of the northwest Ohio greenhouse cluster, we spent four days in the West Midlands region of England learning about clusterbased economic development (Table 2). While we had read a considerable amount of literature (both academic and practitioner-based) on cluster-based economic development they felt that spending time in a region that was in the process of actually implementing the approach would be of great value. An existing working

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relationship between economic development agencies in both regions, the Regional Growth Partnership (www.rgp.org) in northwest Ohio and Black Country Investment (www.bci-uk.com) in the West Midlands) made it relatively easy to organize such a visit. While in the West Midlands we met with approximately twenty-five individuals associated with the region’s various cluster initiatives. This included a meeting with the leader of the region’s Cluster Strategy Team and a day in the field with the Champion of the Advanced Engineering Cluster (www.ae-cluster.co.uk). Upon returning from the West Midlands we arranged a meeting with a group of eight northwest Ohio greenhouse growers (Table 2). The purpose of this meeting was to present the concept of cluster-based economic development to the growers and to assess their interest in pursuing this as a strategy for their industry. We also presented information and data on the nature of the competitive threat posed to their livelihood from the greenhouse industry in southern Ontario. In doing so, we made the case that the future economic success (in some cases survival) of northwest Ohio greenhouse growers lay in their willingness to work together to solve commonly-shared problems. We also outlined the support infrastructure that would be necessary to support a fully functioning greenhouse cluster in northwest Ohio, including a project manager, Champion, and advisory board. The growers invited to attend this meeting were carefully chosen with assistance from locallybased Agricultural Research Service (ARS) agents. The growers in attendance had a reputation as being among the most innovative and open-minded in the region and were, therefore, most likely to be receptive to the idea of pursuing a cluster-based strategy for their industry. The meeting started off in a fairly tense fashion. Despite their open-mindedness, some of the growers in attendance were suspicious of the ability of academics to bring anything of value to the table. However, we were able to convince the growers that if they wished to consider pursuing a cluster-based strategy for their industry that it would be very much a bottom-up, grass roots initiative. In other words, we told that the growers themselves would be very much in control of the structure, direction and forward momentum of the cluster. After much discussion, the growers in the room admitted that they did face an uncertain future and that the idea of co-operating to solve industry-wide problems was worth additional consideration. Those in attendance agreed to consider the possibility of implementing a cluster-based approach to raise the competitiveness of northwest Ohio’s greenhouse industry and to reconvene in a month or so for additional discussion. This follow-up meeting occurred in December 2005 (Table 2). At that meeting the growers agreed to move forward with the implementation of the northwest Ohio greenhouse cluster. The growers suggested that we present the concept of cluster-based economic development to the winter conference of the Toledo Area Flowers and Vegetable Growers Association. This would allow a larger number and variety of growers to learn about the concept. This presentation was made in January 2005 (Table 2, Carroll and Reid 2005).

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Having received the permission of the region’s key growers to implement a cluster-based strategy with respect to the greenhouse industry the next step was to establish the infrastructure necessary to run the cluster. The basic infrastructure comprises a Cluster Strategy Team, Advisory Board, a Project Manager, and a Champion. Cluster Strategy Team – the role of the Cluster Strategy Team (CST) is to develop a vision for the cluster and to identify strategies for implementing the vision. The CST is also responsible for monitoring the progress of the cluster and making, where necessary, mid-course adjustment in both vision and strategy. Initially, the CST comprised the authors, but later grew to include the Project Manager, the Champion, and three growers. The CST meets monthly (between Advisory Board meetings). Ideas generated by the CST are taken to the Advisory Board for discussion and approval. Project Manager – the Project Manager fulfills a multiplicity of functions. His primary role, however, is to facilitate the smooth functioning of the cluster and to make sure that the all the participants (Cluster Strategy Team, Advisory Board, Champion, Growers, and any hired Consultant) are working in unison toward the common goal of advancing the cluster. He or she is responsible for ensuring that everyone is on the same page and in agreement with the overall vision, current status, and next steps in the evolution of the cluster. The Project Manager also acts as the liaison between the cluster and outside consultants (private or public sector) that are utilized by the cluster. Given these duties, the Project Manager requires a unique set of skills. He needs excellent brokering and communication skills. An understanding of the language and workings of both the public and private sectors is important. Given the structure of northwest Ohio’s greenhouse industry an intimate knowledge of the unique challenges facing small family-owned businesses is also useful. As the overall goal of the greenhouse cluster is to contribute to the economic development of northwest Ohio the Project Manager also needs a working knowledge of economic development theory and practices. The Project Manager hired for the northwest Ohio cluster is Mr. Joe Perlaky. Hired in January 2005 (Table 2), Mr. Perlaky has all the skill sets required for this position. Having run his own dry-cleaning business for almost twenty years, he understands the challenges of running a small business. He is also intimately knowledgeable of the fields of both economic development theory and practice. He is a graduate of the University of Oklahoma’s Economic Development Council Institute and has held a number of practitioner posts, including Commissioner of Economic Development for the City of Toledo. Advisory Board – the Advisory Board was established in January 2005 (Table 2) and is the decision-making body of the greenhouse cluster. The Board comprises fifteen members. Eight of the members are owners of greenhouses. The Cluster

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Strategy team and Project Manager are also members. Other stakeholders who are represented are the Regional Growth Partnership, Ohio State University Agricultural Extension Service, and Congresswoman’s Marcy Kaptur’s Office. Advisory Board meetings are held once a month. These meetings are open and are attended by a number of interested stakeholders who are not members of the Advisory Board. Average attendance at Advisory Board meetings is approximately twentyfive people. Advisory Board meetings are chaired by the Cluster Champion. The numerical dominance of growers on the Advisory Board is in keeping with the bottomup philosophy of the cluster. Only growers are eligible to vote when decisions are made with respect to cluster activities. Indeed, when a vote is called for all growers present, even those who are not members of the Advisory Board can vote. For example, when the deciTable 3. NORTHWEST OHIO GREENOUSE CLUSTER ADVISORY BOARD Name Dick Bostdorff Michael Carroll Bill Dearing Mary Donnell

Title Owner Assistant Professor Owner Director

Beth Fausey

Floriculture Program Manager Owner Owner Owner Project Manager Special Assistant Associate Professor Owner Owner Director, International Development Owner

Mark Hecklinger Tony Keil Walt Kruger Joe Perlaky Lindsay Potts Neil Reid Don Schmidlin Alan Schmidt Lee Springer Tom Wardell

Organization Bostdorff Greenhouse Acres Bowling Green State University Dearing Greenhouse Ohio State University Agricultural Business Enhancement Center Ohio State University Agricultural Business Enhancement Center Hecklinger Greenhouse Inc. Louis Keil & Sons Lakewood Greenhouse Inc. University of Toledo Congresswoman Kaptur’s Office University of Toledo Schmidlin Greenhouse Inc. Schmidt Brothers Inc. Regional Growth Partnership Wardell’s Farm Market

sion was made to engage a company to do branding and marketing for the cluster it was made by all the growers present at that particular meeting. Likewise, it was the growers who chose the individual who would function as Champion for the cluster.

Champion – the role of Champion is to work with growers to identify opportunities for collaborative problem solving. We adopted our model of the role of Cluster Champion from our visit to the West Midlands (Table 2) as well as other operational clusters that we had some familiarity with (e.g., Yorkshire Forward 2006, Nettles 2003). As such, the Champion needs to have an extensive knowledge of the greenhouse industry, must be trusted and respected by the growers, have excellent communication skills, and must be capable of innovative thinking. Much of the time of the Champion is spent in the field visiting and talking with growers.

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The individual identified by the growers to fill the role of Cluster Champion was Dr. Dean Krauskopf. Dr. Krauskopf has a Ph.D. in horticulture from North Carolina State University and has over twenty-five years experience working in the greenhouse industry. At the time of his appointment as Cluster Champion Dr. Krauskopf was employed as Integrated Crop Management Educator for Michigan State University (MSU) Agricultural Extension Service. Choosing a Michigan State University extension agent as the Champion for the northwest Ohio greenhouse cluster was intriguing and presented both challenges and opportunities. On the one hand, was there a conflict of interest in having Dr. Krauskopf serving greenhouse industries in two economically competing regions? Would the MSU Extension Service allow Dr. Krauskopf to go south of the border and assist growers in a geographically adjacent state? On the other hand, the possibility to have Dr. Krauskopf serving both northwest Ohio and southeastern Michigan’s greenhouse industries opened up the future possibility of cross-border cooperation between greenhouse growers in these geographically adjacent regions. Many of the challenges (e.g. Canadian competition and high energy costs) are faced by growers in both regions. MSU Extension Service agreed to Dr. Krauskopf serving as Champion for the northwest Ohio greenhouse cluster and he began his duties in May 2005 (Table 2)

5.5 Branding and Marketing: The First Cluster Project Having established the basic infrastructure to operate the northwest Ohio greenhouse cluster the next step was to operationalize the cluster by identifying and implementing the first cluster project. In the minds of the CST the first cluster project was critical. It had to be successful. Failure on the first project would make it extremely difficult to retain grower interest in the cluster approach (Cluster Navigators Ltd. 2001). To be deemed a success by the growers the first project had to bring demonstrated value to the industry. Just as important, it had to demonstrate the benefits of joint action. It also had to have the potential to engage as many of the region’s greenhouse growers as possible. Many growers were still not on board with the cluster initiative. If the first project could increase grower buy-in to the initiative this would increase the likelihood of success with future projects. After much discussion the growers on the Advisory Board identified branding and marketing as the focus of first project. This focus was chosen for a number of reasons. First, the growers recognized that there was a need to develop a brand for their industry and then to capitalize on that brand via a comprehensive marketing strategy. Lack of satisfactory marketing expertise had been identified as a significant barrier to expansion by 65% of the region’s growers who had responded to the 2004 survey. Second, the growers on the Advisory Board felt that the first project had to be non-threatening in nature. The level of existing joint action by

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the region’s growers was minimal. Levels of trust were low. A project requiring growers to engage in joint action that necessitated the sharing of information, for example, would have met with resistance by the vast majority of growers. Participating in the development of a joint branding and marketing strategy, however, was one that the growers felt had the greatest chance engaging the largest number of growers and had a good chance of producing results (i.e. increased sales) that would resonate positively with growers. Branding the industry was as much about building up levels of social capital and moving towards the creation of a collective identity (Fromhold-Eisebith 2006) for the industry as it was about selling more bedding plants and hanging baskets. In keeping with the cluster philosophy of solving industry-wide problems with local expertise the Advisory Board chose a locally-based branding and marketing firm to develop a brand and comprehensive marketing strategy for the cluster. The company chosen, Thread, has an impressive client list that ranges from local police departments to multinational automotive firms Thread (www.experiencethread.com) were officially engaged by the cluster in August 2005 (Table 1). The first task undertaken by Thread was to develop a brand name, logo and positioning statement for the northwest Ohio greenhouse cluster. In order to be successful in brand development it was essential that Thread had a clear understanding of the nature of northwest Ohio’s greenhouse industry. Two Thread employees, therefore, spent several weeks in the field accompanying the Cluster Champion on his visits. This gave Thread the opportunity to speak to growers, to gain insights into the nature of the industry, and to promote the branding effort. Visits to growers were followed by demographic analysis of the greenhouse industry’s customer base and the development and market testing of a variety of logos, positioning statements, and names for the cluster. Working with the cluster Advisory Board, Thread developed a name (Maumee Valley Growers), logo, and positioning statement (Choose the Very Best) for the cluster (Figure 2). Beginning in November 2005 (Table 1) the northwest Ohio greenhouse cluster started operating under the umbrella of Maumee Valley Growers (Limpf 2006, McKinnon 2005).5 The Advisory Board is now working with Thread to develop a marketing strategy for the industry. They are also in the very beginning stages of working on their second project – addressing the issue of high energy costs that are crippling the profitability of many northwest Ohio growers.

5

The appellation, Maumee Valley, refers to the valley of the Maumee River that starts in Fort Wayne, Indiana and flows through northwest Ohio before draining into Lake Erie.

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Fig. 2. Branding Logo for Northwest Ohio Greenhouse Cluster

5.6 Conclusion Greenhouse growers in northwest Ohio have taken the first steps to increasing their competitiveness by forming an industrial cluster. The essence of the cluster is to have growers engage in join action in order to address industry-wide challenges that individual greenhouse owners are incapable of addressing by themselves. The first project undertaken by the growers in the cluster was to develop a name, logo, and positioning statement that will form the foundation for the development of a recognizable brand and associated marketing strategy. The Maumee Valley Growers are now at the very beginning stages of addressing high energy costs facing the industry. Northwest Ohio has some of the highest utility costs in the country (Chavez 2005). It places growers at a significant competitive disadvantage vis-à-vis southern Ontario, other regions of Ohio, and other regions of the United States. Maumee Valley Growers have a number of challenges ahead of them. There is a need to engage more growers in the activities of the cluster. The level of knowledge about the cluster-based initiative varies significantly. Growers who are members of the Advisory Board are highly engaged and committed to the project. At the other extreme, there are some growers who have very little knowledge about the activities that have been taking place during the last twelve months. To increase interest in and commitment to the initiative Thread are supplementing the field visits of the Champion with their own visits to local greenhouses. Press coverage is also generating interest among growers (Limpf 2006, McKinnon 2005, Port Clinton News Herald 2005). Also, the decision to make energy costs the focus of the second cluster project is generating new interest. Growers who have never been at the table previously are now attending meetings because the issue of energy costs is being discussed. This suggests that grower involvement in the clus-

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ter may vary project by project. For some, Canadian competition may be the crisis that brings them to the table; for others the crisis may be high energy costs. Securing the integrity of the brand will also be a challenge for Maumee Valley Growers. The positioning statement, Choose the Very Best, implies that the product sold by a member of Maumee Valley Growers is of high quality. How, and by whom, is this quality assurance policed? This is an issue that is under discussion by the Advisory Board. Securing ongoing funding for Maumee Valley Growers is another challenge facing the cluster. At the time of writing the project has received three years of funding from the US Department of Agriculture and another year is in the latter stages of the approval process. The expectation, however, is that federal funds for this project will dry up some day. The Advisory Board is already engaged in discussion of how the Maumee Valley Growers can become a self-sustaining financial entity. It is hoped that if the value of joint action can be demonstrated by the growers that this will be sufficient to allow Maumee Valley Growers to be supported by membership fees.

Acknowledgments This research was supported by a grant from the United States Department of Agriculture. Additionally, the research is part of a larger collaborative initiative that includes partners from The University of Toledo, The Ohio State University, and Bowling Green State University. Likewise, the research team included the Toledo Botanical Gardens.

Sources Akoorie, Michele, E.M. 2000. Organizational clusters in a resource-based industry: Empirical evidence from New Zealand. In Milford B. Green and Rod B. McNaughton (eds.). Industrial networks and proximity. Burlington, VT: Ashgate, 133-164. Black Country Investment. 2006. www.bci-uk.com. Last accessed 14 February 2006. Bowling Green State University, 2005, Sowing seeds for Maumee Valley growth. Office of Marketing & Communications, BGSU, 17 November. www.bgsu.edu/offices/mc. Last accessed 14 February 2006. Carroll, M.C. and N. Reid. 2005. Competing successfully in a global marketplace. Paper presented at the Toledo Area Winter Greenhouse Conference, Monclova, Ohio, 13 January 2005. Cawthorne, P.M. 1995. Of networks and markets: The rise and rise of a south Indian town, the example of Tiruppur’s cotton knitwear industry. World Development, 23(1): 43-56.

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Chavez, J. 2005. Edison power users captive to high rates. Toledo Blade. 30 October (www.toledoblade.com) Last accessed, 14 February 2006. Cluster Navigators Ltd. 2001. Cluster Building: A Toolkit. Prepared for New Zealand Trade and Enterprise, 40pp. Diez, M.A. 2001. The evaluation of regional innovation and cluster policies: Towards a participatory approach. European Planning Studies, 9(7): 907-923. Dillman, D. 1978. Mail and Telephone Surveys: The Total Design Method. New York: Wiley. Fromhold-Eisebith, M. 2006. Which mode of (cluster) promotion for which aspect of entrepeneurship? In J.D. Gatrell and N. Reid (eds.) Enterprising Worlds: A Geographic Perspective on Economics, Environments, and Ethics, Springer: Dordrecht, xx-xx. Henry, N. and S. Pinch. 2001. Neo-Marshallian nodes, institutional thickness, and Britain’s ‘Motor Sport Valley’: Thick or thin. Environment and Planning A: 33: 1169-1183. Hospers, G. and S. Beugelsdijk. 2002. Regional cluster policies: Learning by comparing? Kylos, 55(3): 381-402. Industry Canada. 2005. Strategis: Canada’s Business and Consumer Site. http://www.strategis.gc.ca. Last accessed 14 February 2006. Kennedy, L. 1999. Cooperating for survival: Tannery pollution and joint action in the Palar Valley (India). World Development, 27(9): 1673-1691. Knorringa, P. 1999. Agra: An old cluster facing new competition. World Development, 27(9): 1587-1604. LaFary, E., J.D. Gatrell, N. Reid, and P. S. Lindquist. 2006. Green (house) industries: Local markets and global competitors. In J.D. Gatrell and N. Reid (eds.) Enterprising Worlds: A Geographic Perspective on Economics, Environments, and Ethics, Springer: Dordrecht, xx-xx. Landabaso, M. 1995. The promotion of innovation in regional community policy: Lessons and proposals for a regional innovation strategy. Paper presented at the International Workshop on Regional Science and Technology Policy. Himeji, Japan, 13-16 February. Limpf, L. 2006. Greenhouses see benefits of forming a cluster. The Press (Millbury, Ohio). (www.presspublications.com) Last accessed, 14 February 2006. Lundequist, P. and D. Power. 2002. Putting Porter into practice? Practices of regional cluster building: Evidence from Sweden. European Planning Studies, 10(6): 685-704. Martin, R. and P. Sunley. 2003. Deconstructing clusters: Chaotic concept or policy panacea. Journal of Economic Geography, 10(6): 685-704. McKinnon, J. 2005. Greenhouses in area tend to marketing. Toledo Blade, 8 December (www.toledoblade.com) Last accessed 14 February 2006. Meyer-Stamer, Jorg. 1998. Path dependence in regional development: persistence and change in three industrial clusters in Santa Catarina, Brazil. World Development, 26(8): 1495-1511. Nadvi, K. 1999. Collective efficiency and collective failure: The response of the Sialkot surgical instrument cluster to global quality pressures. World Development, 27(9): 1605-1616. Nettles, C.L. 2003. Fostering Cluster Development in Wisconin, Wisconsin Department of Commerce. Port Clinton News Herald. 2005. Growers organization put together for area. Port Clinton News Herald, 31 December (www.portclintonnewsherald.com) Last accessed, 14 February, 2006.

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Porter, M. E. 1998. Clusters and the new economics of competition. Harvard Business Review, November-December, 77-90. Putnam, R.D., R. Leonardi, and R.Y. Nanetti. 1993. Making Democracy Work. Princeton, NJ: Princeton University Press. Rabellotti, R. 1999. Recovery of a Mexican cluster: Devaluation bonanza or collective efficiency. World Development, 27(9): 1571-1585. Reid, N. and M. Carroll. 2005. Using cluster-based economic development to enhance the economic competitiveness of Northwest Ohio’s greenhouse nursery industry. Papers and Proceeding of the Applied Geography Conference 28: 309-319. Regional Growth Partnership. www.rgp.org. Last accessed 14 February 2006. SANDAG. 2001. San Diego regional employment clusters: Engines of the modern economy. SANDAG Info, No. 1, 1-31. Schmitz, H. 2000. Does local co-operation matter? Evidence from industrial clusters in South Asia and Latin America. Oxford Development Studies, 28(3): 323-336. Schmitz, H. 1999. Global competition and local cooperation: Success and failure in the Sinos Valley, Brazil. World Development, 27(9): 1627-1650. Schmitz, H. 1995. Collective efficiency: Growth path for small-scale industry. The Journal of Development Studies, 31(4): 529-566. Solvell, O., G. Lindqvist, and C. Ketels. 2003. The cluster initiative greenbook. Ivory Tower AB: Stockholm. Sunday Times, South Africa. 1997. Industry’s clusters get their act together. 17 August. www.bttimes.co.za/97/0817/survey/survey5.htm. Last accessed 14 February 2006. Taylor, M. 2006. ‘Clusters’: The mesmerizing mantra. In J.D. Gatrell and N. Reid (eds.) Enterprising Worlds: A Geographic Perspective on Economics, Environments, and Ethics, Springer: Dordrecht, xx-xx. Thread. 2006. www.experiencethread.com. Website of Thread Consulting Firm. Last accessed 14 February 2006. Wolverhampton Telford Technology Corridor (WTTC). 2005. Local companies collaborate to fight low cost, overseas competition. WTTC News Release, 24 June. www.aecluster.co.uk. Last accessed 14 February 2006. Yorkshire Forward. 2006. www.yorkshire-forward.com. Last accessed 14 February 2006.

6 Specialized Agriculture: Local Markets & Global Competitors in Ohio’s Greenhouse Industry E. W. LaFary, University of Auckland, Auckland, New Zealand J. Gatrell, Indiana State University, Department of Geography, Geology, and Anthropology, Terre Haute, Indiana N. Reid, The University of Toledo, Department of Geography & Planning and The Urban Affairs Center, Toledo, Ohio P. Lindquist, The University of Toledo, Department of Geography & Planning, Toledo, Ohio

6.1 Introduction The geography of globalization and the implications it has upon business have been widely examined. However, the examination of practices relating to local entrepreneurs has been overlooked when observed from the context of the global marketplace as well as within current literature about place competition (see Cox and Mair 1988; Cox 1998). The contradictions between the ability for capital to move freely and the place-bound character of large immobile investments are clear (Phelps and Raines 2003). Yet, not so evident are the practices of the local firm that can either take advantage of or ignore emerging global markets. The greenhouse industry has historically been reliant upon retailers and wholesalers located in close proximity. However, with the development of technologies that allow for sensitive products such as flora to be shipped at continually increasing distances1, Ohio growers now find competition from neighboring counties, states, and foreign countries--particularly Canada (LaFary et al 2005; Reid and Carroll 2005). Moreover, the industrial geographies of globalization have focused almost exclusively on mainstream economic activities such as manufacturing and/or so-called emerging new economic sectors such as information technologies. A resultant consequence is research into activities of entrepreneurs situated at the economic margins has gone unnoticed. For this reason, we investigate the local and global dynamics facing Ohio greenhouse growers and their entrepreneurial practices unlocking the existing silences observed in the literature. Ultimately, the concepts of local dependence, globalization, and operational responses from the Ohio greenhouse industry in the global marketplace will be examined.

1

See Beyers and Lindahl (1996) for a discussion of time-space compression and the ability of firms to effectively escape local dependence and/or maintain long distance transactions.

57 J. Gatrell and N. Reid (eds.), Enterprising Worlds, 57–70. © 2006 Springer.

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6.2 Globalization, Local Dependence and Greenhouses In Ohio, globalization has become synonymous with emerging trade agreements, specifically, the Central American Free Trade Agreement (CAFTA) or the earlier North American Free Trade Agreement (NAFTA). These trade partnerships (or treaties) have created an environment of uncertainty for Midwestern states traditionally touted as manufacturing centers. While much has been written on the geographies of manufacturing and the impending threats associated with access to cheap labor (think Ross Perot’s infamous “Giant Sucking Sound”), the hidden anxieties of agriculture remain understudied. But, the plight of agriculture has not gone unnoticed. Indeed, Ohioans and their congressional delegation—led by Representative Marcy Kaptur—have begun to focus energies on preserving and expanding agricultural industries as well as developing strategies to penetrate the new and restructured nature of the global agricultural marketplace. Fig 1.

As part of the policy efforts to expand agri-industries, a 2003 special research grant from the United States Department of Agriculture funded a team of scholars

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to investigate the economic conditions of the northwest Ohio greenhouse industry. The objective of the project was to benchmark the status and overall trajectory of the industry as well as elucidate the geographies of emerging and restructuring floriculture markets. In 2004, the study was expanded to include the entire state. In tota, these efforts represent an initial accounting of the state of the industry and an effort to define the industry’s potential as an “economic cluster” for the purpose of improving its overall competitiveness. This chapter will use survey data to discuss the overall degree of globalization of Ohio firms, sketch the extent of grower anxiety over broader competition (i.e., globalization), as well as detail the strategies of firms to increase productivity and overall competitiveness.

6.3 The Greenhouse Industry: Background and Trends in Floriculture The greenhouse industry is an important, however, neglected industry as seventyfive percent of all U.S. households participate in activities related to gardening. American households spent an average of $449 on lawns and gardens during 2004, resulting in annual sales of $36.8 billion. Floriculture crops include a wide range of products associated with the sector, including bedding plants, potted flowering plants, foliage plants, and cut flowers2. Like the rest of the industry, this particular segment is growing. Between 1995 and 2004 the total value of U.S. floriculture sales increased twenty-three percent to just over $5 billion (Figure 2). This evolvement is reflected in the fact that, in recent years, American households have increasingly purchased more of the industry’s products. Between 1995 and 2002 the amount of money the average household spent on floriculture crops increased more than seventeen percent from $48.34 per year in 1995 to $56.70 per year in 2002. Furthermore, it is estimated that Americans spend two to three times more on outdoor plants than consumers in other industrialized countries (AgriFood Trade Service, 2000). These characteristics make the United States an attractive target for floriculture industries in other countries.

2

Floriculture production corresponds with Harmonized System (HS) codes 0601 bulbs, tubers etc, chicory plants & roots nesoi), 0602 (live plants nesoi, cuttings etc., mushroom spawn), 0603 (cut flowers & buds for bouquet etc., prepared), and 0604 (foliage, grasses etc. for bouquets etc, prepared) . The Harmonized System is an “international commodity classification (with six digit codes) developed under the auspices of the World Customs Organization (WCO) , an independent intergovernmental body former called the Customs Cooperation Council” (Industry Canada 2005).

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Fig. 2. Value of Floriculture Sales in the United States, 1995-2004 (2004 U.S. dollars)

Sales ($ thousands)

6,000,000 5,000,000 4,000,000 3,000,000 2,000,000 1,000,000

19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04

0

Year

SOURCE: United States Department of Agriculture 2004b

6.3.1 Floriculture Import Patterns In recent years, competition within floriculture has become increasingly global in nature. Producers in one geographic region of a country are as likely to be competing with growers in another country as with firms inside their own national boundaries. Between 1994 and 2003 imports of floriculture produce increased over forty-one percent to nearly $1.3 billion (United States Department of Agriculture 2004a). The majority of floriculture imports (84%) into the United States represent only four competing countries in Canada (29.3%), Colombia (27.8%), the Netherlands (18.5%), and Ecuador (8.5%). During the period 1994-2003 the most significant gains in terms of accessing the U.S. floriculture market has been made by Canadian growers (Figure 3). Canadian floriculture exports to the United States increased from just under $140 million in 1994 to nearly $340 million in 2003--an increase of 143.4%. Furthermore, Ecuadorian floriculture exports to the United States demonstrated marked gains during the same period increasing from more than $30 million to nearly $110 million. However, Colombia and the Netherlands experienced only modest increases. U.S. floriculture imports are nearly evenly divided between nursery stock (51%) and cut flowers (49%). The origins of nursery stock and cut flower imports differ dramatically, however. The primary sources of nursery stock imports (including bedding plants, bulbs, and live trees) are Canada and the Netherlands. Canada accounts for 48.5% of nursery stock imports to the United States, while the Netherlands accounts for 25.7%. Penetration of the U.S. cut flower market is dominated by Colombia. More than fifty-six percent of U.S. cut flower imports come from Colombia. Smaller, but nevertheless significant shares come from Ecuador (17.3%) and the Netherlands (11.1%).

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600 400 200

2003

2002

2001

2000

1999

1998

1997

1996

1995

0 1994

Floriculture Imports ($millions)

Fig. 3. Origin of Floriculture Imports to the United States, 1994-2003 (2004 U.S. dollars)

Year Canada

Colombia

Netherlands

Ecuador

Source: United States Department of Agriculture 2004a

6.3.2 Canada-US Floriculture Trade Patterns The impending Canadian penetration of the U.S. floriculture market (Figure 4) is one of the most significant developments within the respective industry in recent years. The United States is, indeed, the primary destination for Canadian floriculture exports. In 2004, Canada exported $342,988,793 of floriculture crops to the United States. This represented 97.9% of Canadian floriculture exports (Industry Canada 2005). Whilst Canadian floriculture producers have successfully made inroads into the U.S. market, the same cannot be said with regards to the ability of U.S. producers to access the Canadian market. The result is an ever-increasing trade imbalance in floriculture. Between 1995 and 2004, Canada’s trade surplus with the United States in floriculture products increased from $44.6 million to $213.4 million. Canadian access to U.S. markets has been assisted by a number of factors. Initially, the 1994 passage of the North American Free Trade Agreement (NAFTA) made it easier for Canadian producers to enter the U.S. marketplace. Subsequently, Canadian penetration of the U.S. floriculture market has been aided by the fact that, during the period 1995-2002 the U.S. dollar was strong relative to the Canadian dollar. However, (2003-2005) the Canadian dollar has gained strength in terms of value compared to the U.S. dollar. The strengthening Canadian dollar coincides with a flattening-off of Canadian floriculture exports to the United States. If the Canadian dollar continues to increase its global value, the Canadian floriculture export market could be significantly depressed. The critical

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value, at which Canadian floriculture exports to the United States could be severely compromised, is generally thought to be $US1 to $C1.25 (Ontario Horticultural Crops Research and Services Committee 2003). This critical value was reached in late-October 2004 (Bank of Canada 2005). Thus, the continuation of the Ohio Greenhouse Survey is necessary to monitor the Canadian-U.S. floriculture trade dynamics.

400 300 200 100 0

19 95 19 96 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04

Value of Trade ($millions)

Fig. 4. Canada-US Floriculture Trade, 1995-2004 (2004 U.S. dollars)

Year Canada>US

US>Canada

Source: Industry Canada 2005

More than half of U.S. floriculture imports from Canada come from Ontario. Other major exporting provinces are British Columbia (19.8%), Quebec (9.5%), and New Brunswick (8.4%). These origin regions reflect the geography of Canadian floriculture production. The major U.S. destinations for Canadian floriculture exports are states concentrated around the Great Lakes region (Source: Industry Canada, 2005).

6.4 Data and Methods A sample of 500 potential respondents was extracted from OFA-an association of floriculture professional members’ mailing list. Respondents received a nominal stipend of twenty-dollars for participation. Questions were developed to unpack the current practices and to reveal the status of Ohio’s greenhouses. Production methods and materials, employment trends, as well as financial aspects, were used to derive Ohio’s greenhouse geography. The survey was comprised of 59 questions. OFA and the United States Department of Agriculture (USDA) were instrumental in developing widespread interest in the study. In particular, OFA utilized its mailing list to encourage participation from members. The Toledo

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Botanical Gardens mailed 500 copies of the survey to respondents. The response rate was 24.2% (n=121). Following the return of surveys, respondents were categorized by region. Specifically, 5 Ohio regions were identified based on the defined as Northwest (NW) (Toledo-Lima-Findlay), Northeast (NE) (ClevelandAkron-Canton), Central (Columbus-Delaware-Newark), Southeast (SE) (Cincinnati-Dayton), Southwest (SW) (Wheeling, WV; Weirton, WV; Huntington, WV; Parkersburg, WV). Finally, the responses were entered into an electronic database to enable statistical analyses.

6.5 Results The results are organized around two themes: Globalization and Markets & Sales. Each of these themes address various facets of the global conditions facing local firms and are used to elucidate firm response to changing and emerging markets as well as global competition. 6.5.1 Globalization To understand the overall perceptions of firms with respect to the trajectory of the industry and their position in the global market, key questions were selected to determine the overall perceived “degree” of competition from non-local firms with an emphasis on Canadian firms. Additionally, the survey explores the importance of and potential for Ohio growers to develop niche markets to increase the overall competitiveness of the industry. Of primary importance to this research is the perception of growers concerning the global marketplace insofar as how NAFTA—and now CAFTA—have altered the economic landscape. Specifically, we are concerned with the perceived competitive threat of non-local firms. Based on survey responses though, it is evident that all growers perceive their primary competitive to be firms located locally (Table 1). Four of five regions indicated that more than two-thirds of firms perceive local competition as moderate to high. The exception, the southwestern region, had very few respondents and thus, a lowered level of recognized competition from local businesses might be expected given the limited number of respondents (and total firms based on a survey of the OFA directory). Yet, Ohio firms do recognize the importance of non-local firms (see Table 2). The research unexpectedly indicated that the perceived competition from Canada was low to moderate. That is to Table 1 Region

Perception of Competition from Local Area Moderate 6

Total

Northwest

Low 7

High 8

21

Southwest

7

21

5

33

Northeast

9

13

10

32

Southeast

4

0

0

4

Central

4

7

6

17

Ohio

31

47

23

N= 107

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the research team—based primarily in Northwest and Central Ohio—had say, Ohio growers recognized the potential for Canadian firms to penetrate local markets—however; the overall impact was not as severe as anticipated. Indeed, expected NW growers to be especially concerned with potential competition from the north given the region’s proximity to Canada and heightened awareness of NAFTA and related trade issues. While fifty-five percent of firms in the NE see Canada as at least a moderate threat, only twenty-two percent of growers in the northwestern region have the same outlook. In fact, only six percent of NW enterprises see Canada as a highly competitive market compared to nearly a quarter of each of the southwestern, northeastern, and central regions’ greenhouse firms (Table 2). The survey further suggests that distance-decay may be a factor in terms of international competition. That is to say, surveyed firms as only fifteen percent of respondents feel that countries other than Canada compete in their markets--with Mexico being dominant. Further, only four percent of Ohio firms perceive competition from countries outside North America as high. In spite of the survey responses, the empirical evidence demonstrates that Ohio floriculture exports remain stagnant and imports—particularly from Canada and to a lesser extent Ecuador—are steadily increasing their share of U.S. floriculture markets (see Reid and Carroll 2005). In short, Ohio growers have not fully engaged in export markets and may have been slow to respond to the expansion of imported goods. Table 2 Perception of Competition from Canada

Region

Total

Low

Moderate

High

Northwest

14

3

1

19

Southwest

18

6

6

30

Northeast

14

9

8

31

Southeast

2

1

0

3

Central

8

5

4

17

Ohio

56

24

19

N= 99

One approach toward expanding the capacity to export greenhouse goods and/or improve the overall competitiveness domestically—thereby decreasing imports is the formation of a greenhouse grower co-operative. Indeed, the cooperative (or coalition) strategy has been effectively used by the Canadian industry. Traditionally, the co-operative approach has been organized around reducing input costs or coordinating market delivery (outputs). In the case of Ohio growers, either or both co-op strategies may be useful. Indeed, the internal need already exists as the respondents indicate that fuel prices (i.e., inputs) are of high concern to the respondents. In response, Ohio growers indicated they would, for the most part, utilize co-ops to purchase soils, fuels, and potting containers. However, some respondents reported the possibility of marketing and labor pooling through the

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competitive partnership. Interestingly, the desire to create a cooperative varies, in some instances, drastically by region (Table 3). Overall, about sixty-four percent of Ohio firms are interested in creating a co-op (either input or output based). Yet, a tension exists between growers insofar as they perceive each other as the primary competition—not non-local growers. For this reason, the formation of a true cooperative arrangement may prove difficult, as growers must partner with local competitors. Interestingly, those regions (i.e., northeast and central) that perceive market threats beyond the local scale appear more likely to pursue cooperative agreements. Hence, firms that have come to recognize the highly competitive and more global (or at-least less local) scale of the floriculture market appear to be taking the initial step of reconsidering the possibility of restructuring their organizations. In the end though, the survey data suggests that the implementation of a cooperative intended to further the Ohio greenhouse industry has the potential to address key concerns of growers including the development of niche markets, modernization of equipment, expansion of production capacity, and reduction of costs. Table 3 Interest in Creating a Cooperative

Total

No

Yes

Northwest

8

11

19

Southwest

12

14

26

Northeast

11

16

27

Southeast

0

4

4

Central

1

13

14

Ohio

32

58

N=90

Finally, the NW region has begun to respond to the new global environment by embracing the industrial cluster model to improve the competitiveness of the industry. The latest efforts of NW Ohio are the results of a sustained educational effort to increase awareness of new market structures and competitive structures. In future years, the NW cluster will begin aggressively “branding” the industry in an attempt to define and capture niche markets.

6.5.2 Markets and Sales More than seventy percent of growers responded that competition from the local area was at least moderate. In fact, nearly one-quarter of respondents rate local

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competition as high. These findings are expected given that nearly ninety-five percent of all Ohio greenhouse firms participating in the study sell at least thirty percent of finished products locally (Table 4). Less than one out of four firms sold products to neighboring states; while, seven percent of respondents reported selling their finished products to states not bordering Ohio. Perhaps most surprising is the finding that only one grower indicated sales outside of the United States. These findings clearly demonstrate the local dependence of the Ohio greenhouse industry. Further, these results are denotative that the treatises formed by the United States and its neighboring nation-states are having at most a moderate impact upon Ohio growers’ perceptions of the emerging, in fact existing, global marketplace. The realization that the state’s greenhouse firms are not responding to the influx of Canadian and increasingly Latin American and Scandinavian products illustrates the industry’s need to increase educational efforts as well as to explore markets outside of traditional socially constructed borders. Many firms in Ohio have attained increased sales during the past five years. More than fifty-seven percent of respondents affirmed increases during the same timespan. Ironically, production capacity and the firm’s length of operation do not, in the case of this survey, equal increased sales (Table 5). In fact, the northwest (NW) and northeast (NE) regions of the state house the enterprises with the greatest amount of production area as well as the longest running operations. However, the region with the smallest production centers, all operating less than 10 Table 4

Total

Percentage of Sales to Local Customers

<25%

25-50%

51-75%

>75%

Northwest

2

1

2

15

20

Southwest

2

1

1

29

33

Northeast

4

4

3

21

32

Southeast

0

0

0

4

4

Central

1

3

0

13

17

Ohio

9

9

6

82

N= 106

years, boasts the largest increase in sales. Three of four firms in the southeastern (SE) domain have grown sales of at least 40%. There are, of course, a number of plausible explanations. A new business has great potential to grow small sales recorded from its genesis. But more likely is that these new firms utilize the mostmodern translucent building materials as well as employ automated production methods.

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Table 5

Region

Total

Percent of Sales Increase Since 2000

No Change

Decreased

Increased

Northwest

7

2

13

22

Southwest

10

3

23

36

Northeast

7

9

16

32

Southeast

1

0

3

4

Central

4

4

9

17

Ohio

29

18

64

N= 111

6.6 Discussion As the results indicate, globalization and local responses to it are complex and inherently uneven. For this reason, the Ohio greenhouse growers have adopted a multi-pronged approach towards addressing new market structures. The mixed responses and uneven knowledge about globalization and potential competition from nearby (in relative terms) Canadian firms demonstrates the contradictory nature of capital that on the one hand produces mobile investment and on the other a sense of place that creates firm inertia—a resistance to change. Or as Phelps and Raines (2003) suggest, globalization produces a tension between mobility and embeddedness—or what Harvey has called structured coherence. The challenge facing Ohio Greenhouses and the primary problem facing the USDA research and policy team is the degree to which Ohio Growers can restructure the region’s space-economy and promote economic expansion and stability throughout the high tech agricultural sector. A result of the inherent tension between local places and global spaces, policies, and programs, research initiatives like this one emerge to re-shape, nudge, and restructure local/regional space economies. Over the past twenty-five years, this strain has been examined from a variety of perspectives and has become an increasingly nuanced conceptual terrain. In the late-1980s and early-1990s, initial responses to globalization focused on growth coalitions that partnered capital and labor to promote local investment (Cox and Mair 1988, 1991) and the general place competition (Robinson and Sadler 1985). By the 1990s, discussions of local dependence and capital investment had been re-made under the guise of the entrepreneurial state (Eisinger 1989, 1998). In the late-1990s, the competition for local

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investment benefited from a re-scaling of local politics vis-à-vis networks of association that allow localities and capital to “go global” or “go local” (Cox 1998). By the 21st century, the discussion had been influenced by the cultural turn and sought to re-interpret local politics through a cultural lens (McCann 2002; Gatrell & Reid 2002; Reese & Rosenfeld 2001; Molotch et al 2000). Concomitantly, the applied economic development community began to coalesce around the theme of industrial clusters. The cluster-approach articulated by Porter (1990) and now widely adopted by the policy community, seeks to align local resources around a single (or few) economic assets to develop a competitive advantage in the global marketplace. In many respects the applied community has now adopted Cox & Mair’s maxim of local cooperation for global competition in an attempt to maintain and expand local/regional economies.3 Despite the plethora of information on the global competition for capital investment, it is increasingly clear that the linkage between “what we know about globalization” and “what we do about ‘it’” is imprecise. That is to say, place-based policy efforts to mitigate negative externalities associated with global markets structures are often imperfect—or to use Nick Phelps’ and Andy Wood’s (2005) phrase-ology “Lost in Translation”. That is, the ability of policy makers to develop effective policy instruments is inherently limited and muted. Simultaneously, the ability of research to obtain good data on the “globalization-thing” (as one greenhouse grower referred to it) on the ground and in place is limited. For this reason, the current research—like all sectors or place-based case studies—is necessarily uneven. Whereas some firms recognize the need to modernize, invest, and create collaborative marketing or input arrangements, the impact of globalization across Ohio has produced a high level of uncertainty with respect to the development of appropriate statewide policy regimes. Moreover, the plight of the industry is further complicated by the varying levels of firm awareness of the potential impact of Canadian floriculturalists. Consequently, restructuring the space-economy of the industry requires a more precise understanding of the issues facing growers on the ground and how these issues differ within and between regions. For example, many growers see zoning (over 30 percent) and land use regulations (approximately 60 percent) as a key determinant of firm competitiveness. Similarly, local tax policies (most notably “real” property tax)—which are controlled by local governments—are a major concern for over 80 percent of growers. Yet, the “local” zoning, regulation, and tax policies of eighty-eight Ohio counties are seldom a recognized impediment to global capital as these are “too local.” At any rate, the research policies and politics of economic development are highly variable.

3

For the purposes of clarity, we have purposefully avoided the language of neo-liberalism. While the literature on neo-liberalism informs the local politics of economic development, the practices—in place—are often too far removed (in scalar terms) from policy discussion situated at the nation-state scale.

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6.7 Conclusion The research indicates that globalization has influenced the market structure, sales, and firm strategies of Ohio growers. However, the specific strategies used by firms vary somewhat between regions. While the observed regional variation is less pronounced than expected, the differences provide key insights into the highly dynamic nature of local politics and the wide-ranging factors that influence individual firms. In the end, the geography of greenhouse firms sketched in this paper demonstrates that the exact linkage between local practice and global structures is imprecise. Nevertheless, the research does demonstrate the importance of reconsidering the wisdom of deploying eighty-eight individual policy regimes and the potential importance of engineering more flexible “glocal” structures. Acknowledgments This research was supported by a grant from the United States Department of Agriculture. Additionally, the research is part of a larger collaborative initiative that includes partners from The University of Toledo, The Ohio State University, and Bowling Green State University.

Sources Agri-Food Trade Service. 2000. The U.S. Market for Floriculture and Environmental Horticulture. Agriculture and Agri-Food Canada. (http://atn-riae.agr.ca/). Last accessed July 15, 2005. Bank of Canada (http://www.bankofcanada.ca/). Last accessed 5 July 2005. Cox, K. 1998. Spaces of dependence, spaces of engagement and the politics of scale. Political Geography 17:1-28. Cox, K. & Mair, A. 1991. From localised social structures to localities as agents. Environment and Planning A 23:197-231. Cox, K. & Mair, A. 1988. Locality and community in the politics of local economic development. Annals of the Association of American Geographers 88:307-325. Eisinger, P. 1998. City politics in an era of federal devolution. Urban Affairs Review 33: 308-325. Eisinger, P. 1989. The Rise of the Entrepreneurial State. Madison: University of Wisconsin Press. Gatrell, J. & Reid, N. 2002. The cultural politics of economic development: The case of Toledo Jeep. Tijdschrift voor Economische en Sociale Geografie 93:397-411. Industry Canada. 2005. Strategis: Canada’s Business and Consumer Site. (http://www.strategis.gc.ca/). Last accessed 25 May 2005. LaFary, E., Gatrell, J., & Griffey, S. 2005. Green(house) geographies: Metropolitan and non-metropolitan differences in the Ohio Greenhouse Industry. Proceedings of the Applied Geography Conference 28: 301-308. McCann, E. 2002. The cultural politics of local economic development: meaning-making, place-making, and the urban policy process. Geoforum 33:385-398.

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Molotch, H., Freudenburg, W. & Paulsen, K. 2000. History repeats itself, but how? City character, urban tradition, and the accomplishment of place. American Sociological Review 65:791-823. Ontario Horticultural Crops Research and Services Committee. 2003. Ontario Greenhouse Floriculture Research and Services Subcommitee. Ministry of Agriculture, Food and Rural Affairs, Government of Ontario. . (http://www.gov.on.ca). Last Accessed 15 July 2005. Phelps, N. & Raines, P. The New Competition for Inward Investment. Cheltenham: Edward Elgar Publishing Limited. Phelps, N. & Wood, A. 2005. Lost in Translation. Paper presented at the annual meeting of the AAG, Denver, CO. Porter, M. 1990. The Competitive Advantage of Nations. New York: Basic Books. Reese, L. & Rosenfeld, R. 2001. Yes, But...: Questioning the Conventional Wisdom About Economic Development. Economic Development Quarterly. 15:299-312. Robinson, F. & Sadler, D. 1985. Routine action, reproduction of social relations, and the place market: Consett after closure. Society and Space 3:109-120. Reid, N. & Carroll, M. 2005. Using cluster-based economic development to enhance the economic competitiveness of Northwest Ohio’s greenhouse nursery industry. Proceedings of the Applied Geography Conference 28: 309-319. Statistics Canada. 2002. 2001 Census of Agriculture. (http://www.statcan.ca). Last Accessed 28 June 2005. Swyngedouw, E. 1997. Neither global nor local: 'Glocalization' and the politics of scale. In Cox K. (Ed.) Spaces of Globalization: Reasserting the Power of the Local. New York: Guilford. United States Department of Agriculture. 2004a. Floriculture and Nursery Crops Situation and Outlook Yearbook. Washington, D.C.: U.S. Government Printing Office. United States Department of Agriculture. 2004b. Floriculture and Nursery Crops Outlook. Electronic Outlook Report for the Economic Research Service. United States Department of Agriculture, September 23 (www.ers.usda.gov). Last accessed 25 May 2005.

7 High Technology and Urban Development in Bangalore, India R. Kalra, Department of Geography, Kent State University, Kent, Ohio

7.1 Introduction Today we are living in a global village. In such a village the distances have shrunk due to the increasing spatial interaction in terms of economic, social and political dimension at the global scale. Global village is a complex, fast paced society dependent upon extremely advanced technology, and a post materialist value system (Toffler, 1990). A characteristic of this society has been the transformation of the ‘structure’ and ‘scale’ of human relationship, that is the social, economic, political processes now operate at a global scale with a consequent reduction of other geographical scales such as national, regional or local (Johnston, 2000). The world has become a homogenized place and the term nation-state is a little irrelevant since the tastes of human beings have become analogous and are satisfied through the provision of standardized global products created by global corporations who owe no allegiance to any nation, state or place. Another dimension of this process has been the new phenomena of: ‘high technology’, ‘increased trade’, ‘concentration of capital’, ‘migration of people’, ‘development of advanced technologies’, and ‘changing values and norms’ (Marcuse and Kempen, 2000). High technology has had a major impact on the process of global urbanization. Multinational corporations have established operations in major cities around the globe to exploit the international spatial division of labor. Nations and regions have been connected in a new economic relationship and have transformed the city’s economic, urban and social structures. An impact of this global process has been the change in the mix and composition of economic activities (Malecki 1997). As part of this process, cities are being engulfed by firms located especially in the developing regions for outsourcing and back office processing jobs where there is an abundance of cheap but intellectual skilled labor creating spatial inequality within the city. The global distribution of high technology industry is an outcome of business decisions (Choi 2003). Today countries are linked through the location of various branch plants that exploit the international spatial division of labor to its fullest extent. The adoption of new technology produces ‘new structures’, ‘geographical arrangements of economic activities’, products and processes (Dickens 2003). 71 J. Gatrell and N. Reid (eds.), Enterprising Worlds, 71–81. © 2006 Springer.

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The integration of the Indian economy with the world economy manifested several spatial changes such as the increasing specialization of urban regions, growing urban interdependencies, new patterns in the spread of technologies, changes in the product-mix of regions and changes in the sectoral mix of the economy. In the process of urban economic development cities interact and transmit productivity via inter-urban and intra-urban interdependencies. Many studies have been conducted on inter-urban disparities, but, this study tries to divulge the impact of high tech firms on the city of Bangalore. It seeks to reveal the extent of high tech firms in creating a new socio-economic landscape within the second largest city of South India now often called the IT Capital of India.

7.2 High technology and Urban Development: A Conceptual Review 7.2.1 What is High Technology? High technology has largely been defined as the application of intensive research and development in the creation and manufacture of products of an advanced scientific and engineering in process. Schmookler (1996) defines technology as the social pool of knowledge of the industrial arts. The Organization for Economic Cooperation and Development (OECD) (1985) considers high tech as industries like aerospace, computers and office, communications equipment, semiconductors, electrical machinery, pharmaceuticals and science instruments. Malecki (1985, 1997) on the other hand, views high technology as technological change administered by the construction of knowledge, its application and diffusion in the economy. He argues that the intensity of research and development and the technical workers in the work force are the best indicators of high technology. So the typical high tech industry includes jobs in electronics, high tech electronics manufacturing, software and computer related services, telecommunications, data processing, information services, biomedical, electro medical services, research and development, percentage of technical workers (scientist, engineers and technicians) and the degree of novelty and invention (Atkinson and Gottleib 2001; Malecki 1997; Choi 2003). Chapple et al. (2004) defines high technology as manufacturing and service producing industries with 9 % of the workforce in science, engineering and computer professional jobs. This study defines high technology as a combination of information technology, hardware, software and services, business process outsourcing (BPO), computer chips, telecommunications, data processing, electronics industries and research and development which are reasonably predominant in the city of Bangalore.

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Technology and technological progress has always been a crucial factor in a region’s economic growth. Various empirical studies have been done to understand the role and impact of high technology in reconfiguring regional development. It has been revealed that cities with higher concentrations of skilled workers and professionals have high probabilities of high tech agglomerations. It can be argued that the impact of high technology can be visible in three different ways in terms of regional development. First, high technology activities have become major factors of employment growth in developed as well as developing nations; second, high technology industries have led to exclusive patterns of geographical development such as the coastal regions of China, California, Pacific Northwest, New England, New Jersey and Texas in the US, and selected cities in India such as Bangalore and Hyderabad are examples of exclusive centers of high technology industry location, and third within such agglomerations, specialization is often the rule as different places within these locations specialize in different high technology activities (Fellman, Getis and Getis 2004). In the modernizing world leading cities are linked to one another by the flow of goods, information and people which forms a major part of the configuration of the world urban economic structure (Shin and Timberlake, 2000). Today any hightechnology city needs to satisfy the following conditions of: 1) linkage with universities to provide highly educated and technically skilled labor, 2) a modern and developed infrastructure that includes effective telecommunication capabilities, 3) a cost effective transportation infrastructure which connects with national and international markets, 4) flow of capital to support a strong research and development base; 5) an attractive living environment and a good standard of living, and last but not the least it needs to have an assertive economic development force that comprehends how technology generates growth (Edwards, 1999). The technological revolution today is centered on information technologies and is redesigning and restructuring the society and creating a new bond between the economy, state and society (Castells 1996). 7.2.2 High Technology in Developing countries The transfer of high technology industry to developing countries has become attractive to transnational corporations. Newly industrialized countries often offer a labor force that is both educated and cheap. The corporations retain the know-how and profit of their technologies and get the labor oriented work performed for a lower cost. The diffusion of high technology in many less developed countries in Africa, Asia, and Latin America was quite low in the early 1990s, but with rising economic globalization these countries are beginning to catch up with technology. Today, many of the less developed regions have emerged in Asian countries. Thailand, Singapore, Hong Kong, Malaysia and Taiwan have become examples of such technology induced transformations. At its brightest, high technology is leading poor nations to prosperity as has been the case in China, India and Malaysia (Chesnais, 1986; Malecki, 1997). High technology has led to a decline in the

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manufacturing sector and has increased the dominance of service sector, not only in the Western world but also in many Asian cities in addition to Tokyo, Singapore, Hong Kong, Nanjing, and Shanghai. Consequently, this trend has impacted Indian cities too especially Bangalore in Karnataka and Hyderabad in Andhra Pradesh. A UNDP (United Nations Development Programme) study has identified Bangalore as one of the world class technological hubs which poses competition to the Silicon Valley (USA) and various other regions in Europe and Japan. Today high technology industries are transforming the physical, economic, cultural and also the social setup of cities. Hence, the cities are becoming wealthy; opportunities are increasing and attracting multinational firms due to various factors prevalent in that particular city. However, high technology not only transforms the region but also poses challenges for local and national government as they need to have appropriate infrastructure facilities (Udo and Edoho, 2000). Shachar and Felsentein (1992) found that high technology is located only in those regions which have the added local advantages like the availability of educational institutes. Many social scientists argue that high technology not only results in increased growth but also increased inequity and impacted innovation especially in developing countries (Kaushik et al. 2004). Several developing countries are characterized by rapid urbanization, macrocephalic urban systems, high urban densities and various socio economic and environmental problems (Scott and Storper, 2003; Lipton, 1997). As a result of these issues, high technology may not necessarily bring the same level of benefits. There are dynamic benefits in terms of Information Technology as it increases growth especially in the field of education. Pohjola’s (2000) cross country regression analysis concluded that Information technology had positive impacts on the developed (OECD) countries but not in developing countries. Today state and local governments all around the world are playing a vital role in encouraging high tech economic development (Choi, 2003). But the developing countries need to be incredibly cautious in adopting and further adapting western technology. Socio- economic and cultural conditions in the host country are distinct and so the high technology innovation may stress the existing urban and social infrastructure giving rise to a mismatch in culture (Melih, 1996). On the other hand the high-tech industries are generating and promoting regional disparities at the inter regional and intra urban level in terms of income, purchasing power, life style and other socio-economic indicators (Joseph, 2002). 7.2.3 High Technology in India India is a subcontinent with huge inter and intra- urban disparities. After India’s independence in 1947 and from the year 1951 onwards the government paid particular attention to promote a ‘balanced regional development’ through the implementation of various Five-Year Plans. The central and the state government took

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initiatives to minimize imbalances within sectors between ‘small and large manufacturing units’, ‘between small and large farmers’, between ‘lagging and fast growing regions’ by utilizing taxes, providing incentives and implementing development programs. Kurian’s (2002) analyzed the fifteen selected states of India representing 95.5 percent of the total population. The analysis was performed using various socio economic indicators and the states were divided into two groups i.e. forward (developed) and backward (less developed). The forward group comprised of Andhra Pradesh, Gujarat, Haryana, Karnataka, Kerala, Maharshtra, Punjab and Tamil nadu whereas the backward group consisted of Assam, Bihar, Madhya Pradesh, Orissa, Rajasthan, Uttar Pradesh and West Bengal. These two groups of regions were at different levels of development but efforts were being made by the public and private sectors to minimize these disparities. At the time of India’s independence, more than 80 percent of the population was employed in agriculture which has now reduced to less than 60 percent? Also the percentage of people below poverty level has declined from 51.3 in 1977-78 to 26.10 percent in 1999-2000 in India (Kurian, 2002). Urbanization in India has been on the rise since independence. As the number of cities with a million people has increased from 1 in 1901 to 23 in 1991. Of these million cities Mumbai, Kolkatta, Delhi and Chennai are the cities with high rates of urban growth. These cities are the locations where rapid urban economic development is taking place and is competing to become global cities. Also, new cities such as Hyderabad, Bangalore, and Lucknow are now rising as the new million cities (cities with million people). Indeed, development and urbanization is picking at a very fast pace but is unevenly dispersed across geographical space as some regions are growing at a faster pace whereas others are slow. The Indian economy has virtually transformed from an inward-oriented, closed economy to a liberalized and an export-oriented economy (Basu, 2004). The process of economic liberalization started in India in the year 1991 which brought about drastic changes in the Indian economy. These policies began to liberalize imports and encourage exports and led to the opening of the economy with a focus on integrating the Indian economy with the world economy especially with the system of transnational corporations engaged in finance, telecommunications and high technology sectors. It was an economic revolution which emphasized on decreasing the barriers and to set up greater public and private sector cooperation (Kuttaih et al. 2000). This is an interesting revolution which has taken place in India in terms of the development of IT (Information technology) sector. Inspite of India’s low level of income and economic development it has stood out in terms of high technology development (Information Technology) (Srinivasan, 2004). The size of Indian economy increased from $62.9 billion in the year 1970 to $532.5 billion in the year 2002. So as India deregulated its economy and attracted foreign investment it further spread inter regional disparities and uneven growth, as the regions which were economically and socially well off gained at the expense of other regional economies in India. Two cities Mumbai in the western part

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of the country, and Bangalore in the southern part (i.e. the software district of Bangalore) has done much better than the eastern half in India (Stutz and Warf, 2005). The IT (Information technology) industry reflects the tendency to agglomerate in major cities with a strong bias towards South India. According to the National Association of Software and Services (NASSCOM) analysis in 2002, Bangalore leads in terms of the numbers of Information technology headquarters. Inter regional disparities exist not only at the level of IT firms, high tech centers but also there is an unevenness in the number of engineering colleges which are leading in the southern region (Karnataka, Tamil nadu, Andhra Pradesh, and Kerala) as compared to the northwest and eastern regions in India. So one can argue that IT agglomeration in southern India is due to the abundance of the availability of skilled labor (Aranya, 2003). Currently, the number of overseas offices of Indian Information technology has increased from 167 in 1995 to around 750 in 2000 (NASSCOM). As a result of economic reforms multinationals were allowed 100 percent ownership of subsidiaries in India and this eased the entry of IBM, ORACLE, SAP, Microsoft and Sun which have established joint ventures since then. It was the economic reform which emphasized on decreasing the barriers and to set up greater public and private sector cooperation that led to such changes (Kuttiah et al. 2000). The size of Indian economy increased from $62.9 billion in the year 1970 to $532.5 billion in the year 2002.

7.3 Bangalore: Transformation of a Garden City to the Silicon Valley Amongst all the Indian cities of India, Bangalore has the largest number of high tech firms and is the fastest growing technology hub (Human Development Report, 2001). It is the capital city of Karnataka, and the fifth largest city of India. It is located in the heart of South India and was often called as the Garden city and the Pensioner’s Paradise (Census of India, 2001). It lies in the interior of the Deccan peninsula and is surrounded by cities like Chennai in East, Mysore to its South West, and Hyderabad to the North. The salubrious climate of Bangalore has played a vital role in making it the technological hub of the country. The attractive climate has induced people from other states to migrate and thus led the population of Bangalore to grow since 1901 from 228,000 to 7.5 million in the year 2001 (Census, 2001). The population density of Bangalore was 10,710 per sq km in 2001. In 1949 there were seven wards which have increased to 100 wards in 2001 census in Bangalore. Another dynamism of Bangalore is its economic structure. Since the 1990’s, Bangalore has earned the reputation of a city specializing in the areas of research and development, electronics and software production. Initially, the presence of the Indian Institute of Science (IIS) along with the increasing investments by the Central government in Research and Development establishments such as Indian

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Space Research Organization (ISRO) gave the city of Bangalore the nickname of ‘science city’ (Heitzman, 2001). The Information Technology (IT) industry has grown tremendously which reflected in its revenues which grew from $5.7 billion in the year 1991-2000 of which $4 billion represented the exports according to the National Association of Software and Services Companies industry trade group (Rosenberg, 2002). Today, Bangalore is considered to be the heart of India’s booming software industry which had an increase in its exports to the tune of $6.2 billion in 2000-01 which means that there has been an increase of around 50 percent a year from $734 million in 1995-96. Hence, Bangalore has become a very important case study to understand how these high tech firms have transformed the social and economic landscape of the city. Eisebith (2002) studied Bangalore as a model of high technology growth in India. She demonstrated that first its success is based upon the internal networks of technological actors, local relationships between innovation stimulation and support which characterizes successful regions in developed countries; second, Bangalore is an example of an unplanned technology region which shows characteristic of industrial districts as identified in developed countries; third Bangalore is a model where regional relations construct the fabric of mutual encouragement, support and social coherence in order to attain innovation based economic development. The department of Information Technology in Bangalore proposes that almost every week there are several multinational corporations either establishing a joint venture or a branch plant in Bangalore. The presence of so many foreign investors and multinational corporations has put pressure on land prices and this has led to a dramatic rise in the land values especially near the IT corridor. The government of Karnataka has demarcated this IT corridor which extends from Whitefield to Koramangala, Indiranagar, Hosur Road, HSR layout, Electronics city, J.P. Nagar and Banashankari. (Department of Information Technology, Bangalore). This has further led to rise in the real estate value in several wards of Bangalore city. In the last few years there has been a doubling of real estate prices in the central and eastern part of the city as compared to the western part. The rise in IT has also led to the rise in land prices especially between 1992 and 1996. In 1995 the land prices rose at least by 50 percent and in many areas it rose by 300-400 percent. Land opportunists were definitely behind this rise with the incoming of the non resident Indian s and employees of the multinational corporations. There was a rise of multistoried posh housing apartments which were an attraction for the new rising upper middle class. But there has been many land purchases which involved under the table land deals especially in the southern part of the city (Heitzman, 2004). The city is surrounded by various billboards which advertise luxury apartments and direct flight to Frankfurt and a range of global destinations.

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Another interesting phenomenon is to observe how the infrastructure expenses in the Bangalore Municipal Corporation have altered in these IT Corridors. The Table: 1 reveals percentage of infrastructure to total expenditure in the IT wards for the year 2002-2005 and reveals very interesting patterns. Table 1. Expenditure on Infrastructure to total expenditure in Bangalore Municipal Corporation IT Corridor JP Nagar Jayanagar Koramangala Airport Ulsoor

2002-03 74.86 77.99 23.63 95.30 93.39

2003-04 90.79 20.62 88.78 85.21 92.58

2004-05 80.90 50.79 70.87 95.95 91.23

Source: Data provided from Bangalore Mahanagar Palika, Bangalore. (Note: All numbers are in percent) First the airport ward had the maximum expenditure on the infrastructure facilities. This expenditure was the highest during 2002-03 and 2004-05. The other ward which had the highest expenditure on infrastructure was Ulsoor which was adjacent to the IT corridors. Thus, although the expenditure pattern on infrastructure varies among the wards a concentration can be observed near the airport and IT corridors. The city of Bangalore is the hot spot of IT (Information technology) headquarter location but the growth in the city of Bangalore is not equitable and is rapidly creating economic and social segregation in the various wards of the city. Madon (2001) draws attention to three major issues related to social inequities. First, there exists gross inequality between groups of diverse socio-economic status within the city of Bangalore and in the state of Karnataka. Second there is extreme poverty amongst the inhabitanats. Third, there is an acute problem of the availability of civic amenities both in the city of Bangalore as well as in the state of Karnataka which is a great cause of concern. This trend also reveals inequity in infrastrucure expenditure between wards and also differnces in land values between the wards where IT firms are located and where they are not located. Upadhaya (2003) has revealed that high technology’s well paid and cosmopolitan work force is creating a new category of enterpreneurs who are emerging from the middle class and has called them middle class millionaires. Added to this cohort are the returning Indian diaspora of high technology workers from Europe and North America bringing entrepreneurial experience, capital to invest and managerial skills. Both these groups of skilled workforce and their adeptness to western culture has led to a social transformation as the working and middle class

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are becoming suddenly rich and creating a widening gap between the work force employed in high tech and non high tech firms. This widening income disparity is revealed in the preferences, tastes and consumption patetrns of this new class of middle class millionaires who demand western styled commercial busineses outlets, large malls, recraetional facilities, and pubs, and hotels serving internatioanl cuisine. There has been an increase in the demand for western styled houses which were offered by the private builders. This has become quite evident with the rise of multinational corporations (Nair, 2005). Aranya (2002) has demarcated the inequalities in Bangalore’s urban economy and explained the transforming spatial structure of the city with the growth of the information technology sector. She has tried to shed light on the spatial disparity in the city of Bangalore and has divided the development of the information technology sector into four phases : firstly the phase of startups and location of multinational subsidaries (mid 1980’s-1990’s), second phase of the establishment of brand capability (1991-96), third phase of Y2K related boom and dot.com bust (1996-99) and finally the phase of business recovery and peripheral spatial growth (1999-till date). So, while we recognize that the high technology sector has creating significant beneficial changes, it also clearly has accentuated existing socio economic disparities and may firther widen the existing disparities. Thus, the high tech firms without question are shaping and reconstructing the urban, social and economic space of the city but at the same time it has led to an increase in the level of disparity between wards ( intra urban level).

7.4 Conclusion High technology has been defined as the application of intensive research and development in the creation and manufacture of products of an advanced scientific and engineering in nature and process. In the process of globalization the international spatial division of labor has reached beyond national boundaries to exploit the availability of low wages, skilled labor force, English speaking population, cheap land prices, low real estate values, infrastructure facilities, and attractive climate. Bangalore is an excellent example of the location of high technology where the multinationals have reached to take advantage of the benefits of such economic opportunities by setting up joint ventures and branch plants in the areas of high technology. An objective of this paper has been to analyze the impact of high technology cluster on the local social structure at the intra urban scale (wards) in Bangalore. An analysis of the expenditure pattern on infrastructure suggests that more endowed and attractive wards such as the airport and IT corridors have taken away a major share of the resources for investment. The rise of the middle class millionaire and the returning Indian Diaspora from the Western nations have created a widening disparity within the social groups by their demand for Western styled malls, shop-

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ping outlets, luxurious houses, entertainment facilities, tastes, preferences and consumption patterns. This disparity has created a ‘demonstration effect’ leading the local government to address the issue of social equity at the intra urban scale. This exploratory study suggests some future questions of research: (1) what processes explains the intra urban disparities within social groups in Bangalore city due to the location of high technology? 2) Can the extent of social inequality be measured using geographical information systems and statistical methods for analyzing the spatial pattern of social and spatial inequality? And 3) what policy suggestions can the study make to minimize the disparities between social groups at the ward level for improving the quality of life.

Sources Aranya, R. 2003. Globalization and urban restructuring of Bangalore: India. 39th ISOCARP congress. Atkinson, R.D. and Gottlieb, P.D. 2001. The metropolitan new economy index. Washington D.C: Progressive Policy institute. Basu. K (Ed.) 2004. India’s emerging economy: performance and prospects in the 1990’s and beyond. Cambridge Massachusetts: IT press Choi, B.R. 2003. High technology Development in Regional Economic Growth. England: Ashgate Publishing Company. Castells, M and Hall 1994.Technopoles of the World: the making of the 21st Century Industrial Complexes. London/New York: Routledge. Chapple. K. et al. 2004. Gauging Metropolitan “High tech” and “I Tech” Activity. Economic Development Quarterly.18 (1):10-29. Chesnais.F 1986. Science Technology and Competitiveness. STI Review (1):86129. Dickens, P 2003. Global Shift: Reshaping the Global Economy Map in the 21st Century. Guilford Publications, Inc. Fellman, J.D., A. Getis, and J. Getis 2004. Human Geography: Landscape of Human Activities, Eighth Edition, Mc Graw Hill, Boston Fromhold-Eisebith, M 2002. ‘Regional Cycles of Learning: Foreign Multinationals as Agents of Technological Upgrading in Less Developed Countries’, Environment and Planning, A 34: 2155-2173. Heitzman, J. 2001.Becoming a Silicon Valley: Bangalore as a Milieu of Innovation. Seminar. 503(July):299-330. Heitzman (2004). Network city: Planning the information society in Bangalore. New Delhi: Oxford University Press. Johnston, J. et al., (eds.) 2000. Dictionary of Human Geography, Blackwell Publishers. Joseph. K.J. 2002. Growth of ICT and ICT for development. World Institute for development economics research. Discussion paper no.2002/78.

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Melih, K. 1996. Information technology transfer to a developing country: Executive information systems in Turkey. Information Technology and People. 9 (3): 55-84. Kurian. N. J. 2002. Growing Inter state disparities. Seminar.509. Kuttaiah, K. and Sommers, G.G 2000.East meets West in Bangalore: The impact of Economic Change on the Built Environment. In Graham P. Chapman, Ashok. K. Dutt. and Robert. W. Bradnock Urban Growth and Development in Asia: Volume1: 307-322: USA. Ashgate Publishers. Madon, S. 2004. Bangalore: Internal disparities of a city caught in the Information age. In Stephen Graham(Ed). Cyber cities reader. London & New York: Routledge. Malecki, E.J 1985. Industrial Location and Corporate organization in High technology industries. Economic geography 61(4): 345-369. Malecki, E. J. 1997. Technology and Economic development. New York: John Wiley and Sons. Marcuse, P. and Kempen, R.V (Eds.) 2000.Globalizing Cities: A New Spatial order? USA: Blackwell Publishers. Nair. J. 2005. The Promise of the Metropolis: Bangalore’s twentieth century. New Delhi: Oxford University Press. Kraemer. K.L. and Dedrick. J. 2000. Information technology and economic developments: results and policy implications of cross –country studies. In M. Pohjola (Ed.), Information technology, productivity, and economic growth PP.259-279. New York: Oxford University Press. Rosenberg. D. 2002. Cloning Silicon Valley: The next generation high-tech hotspots. New York: Pearson Education Schmookler, J. 1966. Invention and Economic Growth. Cambridge, MA: Harvard University press. Scott A.J. and Storper. M. 2003. Regions, Globalization and Development. Regional Studies, 37, 6-7: 579-593. Srinivasan, T.N. 2003. Integrating India with the World Economy: Progress, Problems, and Prospects In Anne O. Krueger and Sajjid Z. Chinoy (Eds.) Reforming India's external, financial, and fiscal policies. Stanford: Stanford University Press. Stutz .F.P. and Warf, B. 2005. The World Economy; Resources location, trade and development. New Jersey: Prentice Hall. Toffler, A. 1990. Powershift: Knowledge, Wealth, Power, at the Edge of the 21st Century. New York: Bantam Books. Udo. G. and Edoho, F.M. 2000. Information technology transfer to African nations: An economic development mandate. The Journal of Technology Transfer.25 (3):329-342. Upadhaya.C. 2003. Middle class Millionaires: IT enterpreneurship and the prodcution of the global Indian. Paper presented at Hindu College,University of Delhi,India.

8 An Evolutional Model of U.S. Manufacturing and Services Industries J. Helsel, H. Kim, and J. Lee, Kent State University, Kent, Ohio

8.1 Abstract This study uses the Getis-Ord local Gi* statistic and county-level employment data from 1990, 1997, and 2003 to analyze the evolution of spatial clusters or “hotspots” in the manufacturing and services sectors. We find evidence of similar patterns of clustering in both sectors. In most cases, these clusters appear to be growing or stagnant, rather than diminishing. Interestingly, the growth of some service sector clusters appears to pre-date the growth or the decline of co-located manufacturing clusters. Finally, we include a closer examination of regional economic profiles of the Northeast Ohio cluster as an illustration for further studies of other regions.

8.2 Introduction Between 1997 and 2003, the manufacturing sector in the United States has lost more than 3 million jobs, a decrease of 16.7 per cent, and the level of manufacturing employment is now at its lowest point since 1958 (Bivens, 2004). In contrast, employment in the services sector increased by 13.2 per cent during the same period, and by 17.9 per cent from 1990 to 1997. Economists are increasingly concerned that the dramatic expansion of the services sector is at the expense of manufacturing sector, particularly as the share of total labor employed. It poses a threat to the nation’s economic strength and standard of living. This concern stems from the belief that it is the manufacturing sector, not the services sector, which drives an economy. In a study commissioned by the Council of Manufacturing Associations, Joel Popkin and Company (2003) contend that “manufacturing spawns more additional economic activity and related jobs than does any other economic sector” and that “America’s unprecedented wealth and world economic leadership are made possible by a critical mass of manufacturing.” The idea of manufacturing as the key industrial sector in determining the overall rate of economic growth is certainly not new. In the late 1960s, Cambridge economist Nicholas Kaldor formulated three propositions, usually referred to as Kaldor’s laws, which relate a well-developed manufacturing sector to higher stan83 J. Gatrell and N. Reid (eds.), Enterprising Worlds, 83–97. © 2006 Springer.

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dards of living. For example, Kaldor’s first law holds that economies with high growth in manufacturing typically experience higher economic growth than economies in which the manufacturing sector grows more slowly. Since then, many empirical investigations have been conducted to test Kaldor’s laws on country-level data. Only a few studies have used sub-national data. Among the latter, Bernat (1996) took a fresh look at the role of manufacturing using state-level data for the U.S. An important corollary contribution of Bernat’s paper was its application and economic interpretation of spatial econometric techniques to detect statistically significant clustering in the geographic distribution of the dataset. Gross state product growth rates originating in both the manufacturing and the services sectors showed evidence of spatial autocorrelation and heterogeneity. These findings have important implications for regional economic development and for the administration of appropriate public policies to spur the economic growth of lagging regions. Policymakers, as well as researchers in both regional and organizational science, have come to regard the agglomeration and clustering of economic activities as a vital source of local economic development. What makes this phenomenon so remarkable is that it represents a shift in focus from the traditional focus on the firm and firm-specific resources to inter-organizational networks, geographic proximity, and innovation through knowledge transfers. The current paper extends the previous literature on the role of manufacturing and services in regional economic development by using exploratory spatial data analysis and cluster analysis on county-level data to further investigate the spatial distribution of the manufacturing and services sectors and the formation of industrial clusters. Furthermore, we examine the evolution of these clusters over time, from 1990 to1997, and from 1997 to 2003. Finally, we zoom in on a cluster of counties in Northeast Ohio with significantly greater than national average employment levels in both manufacturing and services. This detailed profile of the evolution of industrial activities will serve as an exemplar for the direction of further research into other regions. The remainder of this paper is organized as follows: Section 2 presents an overview of some of the theories and issues that inform the formation of industrial clusters. Section 3 describes the data and methodology, including a discussion of the test statistic used to determine the presence of spatial clusters. Section 4 analyzes the results of the evolutional model. Concluding remarks and future research objectives are provided in section 5.

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8.3 Background As early as 1900 and 1905, the Census of Manufactures documented that U.S. industrial activities have a tendency to concentrate in certain geographic areas (Shelburne and Bednarzik, 1993). This spatial embeddedness was recognized by Alfred Marshall (1920), who coined the term “economies of localized industries” to describe the benefits accruing to firms located within an “industrial district,” a geographically concentrated cluster specializing in the production of a narrowly related sets of goods. According to Marshall, increasing returns can arise not only internally, but also from external sources. Firms that are clustered together have the benefit of access to specialized suppliers, skilled labor, and an environment conducive to the spillover of technological knowledge from one firm to the other. Thus, external economies accrue from the cost savings that are the result of resource-sharing and information exchange within a localized industrial environment (Cohen and Fields, 1998).1 Krugman (1991) revisits the notion of increasing returns. In his “New Economic Geography” model, opposing forces of agglomeration (also called centripetal forces) and of dispersal (also called centrifugal forces) interact to determine city size and location. Centripetal forces include market-size external economies (backward and forward linkages, thick labor markets), natural site advantages, and pure external economies (knowledge spillovers). Centrifugal forces include dispersed natural resources, market-mediated forces (transportation costs, urban land rent), and non-market forces (congestion, pollution). According to Porter (1990), firms can trace their success to the interaction of four conditions, the “Diamond of Advantage”: (1) firm strategy, structure, and rivalry; (2) factor conditions; (3) demand conditions; and (4) the presence of related and supporting industries. While his original thesis concerned the competitive advantage of nations, he soon realized that the majority of economic activity takes place at the regional level. This is reflected in his definition of industry clusters as “geographic concentrations of interconnected companies, specialized suppliers, service providers, firms in related industries, and associated institutions (e.g., universities, standard agencies, and trade associations) in particular fields that compete but also cooperate” (Porter, 1998). The regional science literature abounds with well-known industrial clusters, including computers and software in Silicon Valley, biotechnology in Boston’s Route 128, aerospace and software in Seattle, and automobiles in Detroit (Feser, Sweeney, and Renski, 2005). The relationship among firms in a cluster can be 1

The terms economies of scale, scale economies, and increasing returns (to scale) are often used interchangeably. Internal increasing returns, stemming from the internal operations of a firm, lower per-unit cost by extending the downward slope of its average long-run cost curve over a greater quantity of output. External increasing returns result in a downward shift of the average long-run cost curve.

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classified as either vertical or horizontal. A vertical association among firms exists when they engage in typical direct buyer-seller transactions, such as in supply chains. Many supply chains develop around large anchor firms. A horizontal association among firms exists when they are connected by a common set of customers, have common infrastructure needs, or share a demand for similar technologies, distribution channels, skilled workers and other resources (Carnegie Mellon, 2002). Clusters develop because they increase firms’ ability to compete in an increasingly global market. Firms recognize that they can achieve more together than they could individually. Clusters allow businesses access to more suppliers and customized support services, to better skilled and experienced labor pools, and to greater opportunities for transfer of information and knowledge. The advantages of spatial concentration of industrial activities due to scale economies are often referred to as agglomeration economies. Sohn (2004) classifies these advantages as intra-industrial and inter-industrial. Intra-industrial concentration means that firms reap the benefits of a well-established infrastructure by locating in an area where there are already a large number of establishments in the same industrial sector. Inter-industrial concentration derives its benefits from backward/forward linkages. Agglomeration economies may enhance a region’s industrial development and potential for economic growth. While many industrial clusters are self-organized, most state and local governments are actively engaged in the development of policies and strategies to capitalize on existing strengths, strengthen emerging clusters, or even build new clusters from the ground up. Increasingly, these governments partner with local colleges and universities in their development efforts. In some instances, universities independently engage in initiatives to promote cluster development in their area. Often, one of the challenges facing the successful implementation of such cluster development efforts is the ability to simply identify the locations of industry clusters. When clusters are seen as predominantly linked horizontally, research has focused on input-output analysis or similar techniques to reveal what in the strategy literature are called “value chain” linkages between firms or sectors. Qualitative research, particularly case study research, has been used to identify the codified or tacit transfer of knowledge and information among firms that would indicate the existence of industrial clusters. Only recently has there been more emphasis on research attempting to account for sub-regional localization patterns and spatial cluster analysis (Feser et al., 2001). Certainly, the crucial linkages between companies in an industrial cluster are not necessarily all location-dependent. In an increasingly global economy, many firms find that their membership in global production networks is as important to their competitiveness as their membership in any local ones. However, colocation has been identified as an important source of the externalities and spillover effects that drive industrial clusters. Our study attempts to identify geographic concentrations of manufacturing and service sector activities and analyze

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their evolution over time as a first step towards recognition and measurement of such externalities and spillover effects.

8.4 Methodology This study draws on annualized employment data obtained from the U.S. Bureau of Labor Statistics (BLS) through its Quarterly Census of Employment and Wages (QCEW) program, also known as ES-202. The QCEW program comprises those positions that are covered by unemployment insurance (UI). It measures employment by place of work, as opposed to place of residence, and may include multiple job holdings where they exist. Counties are used as the primary spatial unit of analysis. Contingent on data availability and restrictions2, employment figures were collected for the manufacturing and services sectors in more than 3,000 counties, covering the 48 continental states and the District of Columbia, for the years 1990, 1997, and 2003. In some instances, the data were modified in order to accommodate the statistical calculation of spatial autocorrelation. For example, adjustments must typically be made for states such as Virginia where a small county is located entirely within another county. The usual solution is to consider these counties as a single spatial unit for both analysis and visualization. The North American Industry Classification System (NAICS) codes were used at the 2-digit level to classify and aggregate the employment data as either manufacturing (NAICS codes 31-33) or services (51: Information; 52-53: Financial activities; 54-56: Professional and business services; 61-62: Education and health services; 72: Accommodation and food services; and 81: Other services).3 8.4.1 Measure of Spatial Concentration There are a number of exploratory spatial data analysis (ESDA) techniques that can be used to assess spatial association or spatial autocorrelation in a georeferenced dataset. Global measures of autocorrelation (e.g., Moran’s I, Geary’s C Ratio, or the general G statistic) calculate one statistic for the entire study area. However, since spatial processes are likely to be heterogeneous within the distribution itself, local indicators of spatial association (LISA) measures, which can detect spatial autocorrelation at a local scale, have gained increasing acceptance (Anselin, 1995; Unwin, 1996; Lee and Wong, 2001).

2

3

BLS withholds publication of UI-covered employment data for any industry level when necessary to protect the identity of cooperating employers. Prior to 2001, the ES-202 program used the Standard Industrial Classification (SIC) system. The data from 1990 and 1997 were reconstructed to conform to the 2002 version of the NAICS.

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The purpose of this paper is to identify geographic concentrations of counties with comparatively high levels of manufacturing and/or employment levels of service sector, and to analyze their changes over time. To do so, we use the Getis-Ord Gi* statistic, a LISA measure that is particularly suited to the detection of “hotspots” or spatial clusters around an individual location (Ratcliffe and McCullagh, 1999). The Gi* statistic is a multiplicative measurement of geographic concentration, developed by Getis and Ord (Getis and Ord, 1992, Ord and Getis, 1995; Getis and Ord, 1996). The value of Gi* for each county is based on sector employment of the county itself as well as that of neighboring counties. Thus, whereas measures such as the simple location quotient, the local Gini coefficient (Krugman, 1991), or Ellison and Glaeser’s (1997) index of localization would detect concentrations of sector activities within counties, Gi* provides a methodology that allows us to acknowledge spatial concentration that crosses county boundaries (Feser, Sweeney, and Renski, 2005). “Hotspots” in the geographic distribution of manufacturing and services activities are identified by finding the locations of clusters with high county employment values compared to the U.S. average county-level of employment for the sector in question. To calculate the Gi* statistics, we construct a symmetrical binary matrix of spatial weights (wij) to summarize the spatial association among adjacent counties. The specification of neighboring counties j to county i is based on the queen’s case of neighbor relationship, which considers all surrounding counties as neighbors of i as long as they touch each other even at a point (Lee and Wong, 2001). A value of unity is assigned to neighboring counties, and a value of zero to non-neighboring counties. The spatial weights matrix includes wii = 1. For each county, the Gi* statistic for a given industrial sector is then calculated by comparing the local mean employment (county i’s and all of its neighbors) to the global mean (for all counties in the continental U.S.), and is expressed in standard deviations from the mean, as follows:

Gi * =

∑

j

wij x j − Wi x

nS1i − Wi 2 s n −1

, for all j

(1)

where: x represents sector employment; wij is the spatial weight that defines neighboring counties j to county i; Wi is the sum of weights wij; x represents the mean of county-level sector employment for the U.S. as a whole.

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[i.e., x = (

∑

j

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x j ) /(n − 1) ];

S1i = ∑ j wij ; 2

s 2 = (∑ j x 2j / n − 1) − ( x ) 2

In essence, (and assuming Gi* is distributed close to normally), the results can be roughly interpreted as z-scores along a normal curve. Z-scores above 1.96 are statistically significant at the 0.05 alpha level, so that a county with a Gi* statistic in the manufacturing sector greater than 1.96 evidently has a higher employment level in that sector than one would expect if the overall pattern were a random one. Such a county is considered part of a “hotspot”. Counties with Gi* values between 1 and 1.96 are interpreted as being “warm” or part of a “potential hotspot”.

8.5 Analysis and Discussion In order to more effectively analyzing the results visually, Figure 1 provides a reference map of the 48 continental states and the District of Columbia. The states and the district are divided into eight regions that are commonly used by the Bureau of Economic Analysis. The results of the Gi* -based “hotspot” analysis are summarized in Figures 2 through 7. Figures 2, 3 and 4 show a temporal evolution in the distribution of hotspots and potential hotspots for the manufacturing sector. Gi* statistics are plotted for 1990, 1997, and 2003, with the darkest shaded counties indicating hotspots and the lighter shaded counties representing potential hotspots.

Far West

Rocky Mountain

New England Mideast

Plains Great Lakes

Southwest

Figure 1: Economic Regions in the U.S.

Southeast

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Manufacturing: 1990 Gi* <1 1 < Gi*< 1.96 Gi* > 1.96

Figure 2: Manufacturing Employment, 1990

Manufacturing: 1997 Gi* < 1 1 < Gi* < 1.96 Gi* > 1.96

Figure 3: Manufacturing Employment, 1997

The largest cluster, in terms of geographic area, is located in the Los Angeles/San Diego and Phoenix/Tempe areas (Far West and Southwest regions). Since our analysis did not control for the differences in the geographic areas of counties, this outcome is not surprising. It is interesting to note, however, that these clusters show

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Manufacturing: 2003 Gi* < 1 1 < Gi* < 1.96 Gi* > 1.96

Figure 4: Manufacturing Employment, 2003

consistent expansion over time, with potential hotspots heating up into hotspots farther east and north into Arizona and California, respectively, between 1990 and 1997; and again further north into California from 1997 to 2003. Furthermore, a potential hotspot is evident in 2003 north of the existing hotspot in Arizona up to the Utah border and into Nevada. Also in the Far West region, there is a manufacturing cluster in the Silicon Valley/Bay Area that has remained stable over time. On the other hand, a potential hotspot in northwest Oregon and a hotspot in

Services: 1990 Gi* < 1 1 < Gi* < 1.96 Gi* > 1.96

Figure 5: Services Employment, 1990

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Services: 1997 Gi* < 1 1 < Gi* < 1.96 Gi* > 1.96

Figure 6: Services Employment, 1997

northwest Washington show signs of increasing manufacturing employment relative to the national average over time. The Southwest region, other than the Phoenix/Tempe cluster already mentioned and significant but stable clusters in the Houston and Dallas/Fort Worth areas, is rather devoid of manufacturing clusters, as are the Rocky Mountain and Plains

Services: 2003 Gi* < 1 1 < Gi* < 1.96 Gi* > 1.96

Figure 7: Services Employment, 2003

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regions. A potential hotspot heated up into a hotspot over time in the Minneapolis/St. Paul area as well as in the Pittsburgh area. A manufacturing hotspot that shows signs of cooling down is noticeable along the border of Illinois and Missouri. Service sector clusters are shown in Figures 5 through 7. As expected, the geographic pattern of the distribution of services hotspots and potential hotspots over time and space fairly mimics that of the manufacturing sector, although the services clusters tend to be larger. As with manufacturing, the largest services clusters in terms of geographic area are found in California and Arizona, with these clusters also showing substantial evolution from potential hotspots into hotspots over time. What is interesting to note, however, is that these services hotspots and their evolution appear to pre-date the evolution in manufacturing employment. Similarly, the evolution of an expanding services hotspot in the Denver area predates a small potential manufacturing hotspot that first becomes evident there in 1997. In contrast, a potential manufacturing hotspot in northwest Utah in 1997 and 2003 coincides with the approximate geographic location of a service sector potential hotspot that does not appear until 2003. Furthermore, it should be noted that in the Pittsburgh area, where manufacturing is heating up, services appear to be cooling down. 8.5.1 Industrial Profiles Among the identified clusters, we closely examine the cluster of counties with greater than average employment in Northeast Ohio. We track changes over time for key industry groups in the manufacturing and services sectors. These industry groups are identified at the 3-digit level of the NAICS codes for manufacturing. From 1990 to 2003, Northeast Ohio has seen growth in a number of service industries, at the expense of manufacturing. As shown in Table 1, the greatest increases occurred in management services, followed first by accommodation and food services, and then by educational services. Information services declined throughout. These changes resulted in a slight shift in the relative employment shares of the services industries for these counties. Among the various manufacturing sectors, only textile mills had increased employment; however, even now their relative share in manufacturing employment for the region is insignificant. Almost without exception, other manufacturing industry groups exhibit a general trend of increasing decline. When compared to the changes in median household income in Northeast Ohio, the number of employees in manufacturing and those in the services sectors show contrasting trends. Given these trends, services sectors may have contributed more to the increase in median household income than manufacturing sectors.

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Table 1: Manufacturing and Services Hotspots in Northeast Ohio, 1990-2003

NAICS 311 312 313 315 321 322 323 324 325 326 327 331 332 333 334 335 336 337 339

1990 1997 Change 2003 Employees Share Employees Share Employees Share 1990-1997 1997-2003 1990-2003 11,393 4% 10,085 4% 10,019 5% -11% -1% -12% 2,564 1% 834 0% 1,171 1% -67% 40% -54% 86 0% 126 0% 354 0% 47% 181% 312% 2,562 1% 831 0% 675 0% -68% -19% -74% 2,040 1% 1,910 1% 1,828 1% -6% -4% -10% 8,668 3% 8,317 3% 7,324 3% -4% -12% -16% 10,672 4% 11,315 4% 8,716 4% 6% -23% -18% 5,679 2% 954 0% 593 0% -83% -38% -90% 20,870 7% 20,049 7% 18,177 8% -4% -9% -13% 28,499 9% 28,365 10% 21,025 10% 0% -26% -26% 5,054 2% 5,039 2% 3,819 2% 0% -24% -24% 27,352 9% 22,381 8% 14,217 7% -18% -36% -48% 53,320 18% 50,624 19% 41,673 19% -5% -18% -22% 34,110 11% 33,822 12% 23,915 11% -1% -29% -30% 14,700 5% 10,939 4% 8,858 4% -26% -19% -40% 13,837 5% 12,604 5% 9,083 4% -9% -28% -34% 43,367 14% 36,933 14% 28,350 13% -15% -23% -35% 5,533 2% 3,237 1% 2,879 1% -41% -11% -48% 11,922 4% 11,774 4% 11,082 5% -1% -6% -7%

Total (Manufacturing)

302,692

Median Household Income Changes Total (Services) 51 52 53 54 55 56 61 72 81

405,793 34,783 54,236 20,815 49,388 3,727 61,279 72,861 67,501 41,203

270,661

9% 13% 5% 12% 1% 15% 18% 17% 10%

510,587 31,859 62,392 20,640 61,428 22,342 85,995 78,012 100,704 47,215

214,304

6% 12% 4% 12% 4% 17% 15% 20% 9%

538,992 30,417 71,065 20,218 64,754 28,027 79,007 99,205 102,294 44,005

6% 13% 4% 12% 5% 15% 18% 19% 8%

-11%

-21%

-29%

29% 26% -8% 15% -1% 24% 499% 40% 7% 49% 15%

13% 6% -5% 14% -2% 5% 25% -8% 27% 2% -7%

46% 33% -13% 31% -3% 31% 652% 29% 36% 52% 7%

Note: The Northeast Ohio cluster includes Portage, Summit, Cuyahoga, Geauga, Medina, Lake, Lorain, and Wayne counties. As can be seen from Figures 8 and 9, Cuyahoga county is the largest employer of both manufacturing and services employees. Summit county is the second largest. However, in both counties there have been substantial reductions in manufacturing employment, offset by steady increases in services.

8.6 Concluding Remarks This study uses cluster analysis with county-level data to explore the temporal evolution of spatial hotspots and potential hotspots in the manufacturing and services sectors. With the help of the Getis-Ord Gi* statistic as a LISA measure,

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Figure 8: Northeast Ohio Cluster, Manufacturing Employment

Figure 9: Northeast Ohio Cluster, Services Employment

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existing and emerging hotspots were identified. We modeled the diffusion of manufacturing and services clusters over a geographic area over time, using discrete moments in time. It is important to realize that the multi-county spatial concentrations of manufacturing and/or services employment that were identified here provide no information concerning the economic and geographic factors behind the spatial distribution. The results are preliminary and exploratory; however, they are intended to provide important inputs into further investigation of the significance of a growing manufacturing and/or services sector for a region’s economic well-being. Using our examination of the industrial profiles in Northeast Ohio as an example, other identified clusters may be studied in a similar manner in order to identify clues to the driving forces of regional economic growth or decline. Our future research efforts related to this study are to explore data of even finer spatial resolution. In addition, we plan to take into account in the analysis both economic and regional spatial characteristics that may affect the formation of industry clusters, or conversely, the lack thereof. The refinement of the temporal resolution, perhaps using yearly data and the investigation of variables other than employment to measure manufacturing and/or services activities (e.g., value added) should reveal more clues to the dynamic inner working of regional economies at the identified clusters. While the results of our study are based on raw employment numbers, it will be desirable to expand this study by controlling the employment data by population or other economic factors so to extract clusters for more direct comparisons. Finally, we plan to carry out detailed industrial profiling of “discrete industrial complexes”, i.e., algglomerations based on value chains derived from analysis of input-output data in Feser, Sweeney and Renski (2005).

Sources Anselin, Luc. 1995. “Local Indicators of Spatial Autocorrelation – LISA,” Geographical Analysis, 27, 93-115. Bernat, G. Andrew. “Does Manufacturing Matter? A Spatial Econometric View of Kaldor’s Laws,” Journal of Regional Science, 36, 463-477. Bivens, Josh. 2004. Shifting Blame for Manufacturing Job Loss: Effect of Rising Trade Deficit Shouldn’t Be Ignored. Washington, D.C.: Economic Policy Institute (Briefing Paper #140). Carnegie Mellon Center for Economic Development. 2002. Cluster-Based Community Development Strategies: A Guide for Integrating Communities with Regional Industry Cluster Strategies. Available at <www.smartpolicy.org>. Cohen, Stephen, and Gary Fields. 1998. “Social Capital and Capital Gains, or Virtual Bowling in Silicon Valley” . Berkeley Roundtable on the International Economy. Berkeley: University of California.

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Ellison, Glenn, and Edward L. Glaeser. 1997. “Geographic Concentration in U.S. Manufacturing Industries: A Darboard Approach,” Journal of Political Economy, 105, 889927. Feser, Edward J., Kyojun Koo, Henry C. Renski, and Stewart H. Sweeney. 2001. “Incorporating Spatial Analysis in applied Industry Cluster Studies.” Working paper. Feser, Edward J., Stuart H. Sweeney, and Henry Renski. 2005. “A Descriptive Analysis of Discrete U.S. Industrial Complexes,” Journal of Regional Science, 45, 395-419. Getis, Arthur, and J. Keith Ord. 1992. “The Analysis of Spatial Association by Use of Distance Statistics,” Geographical Analysis, 24, 189-206. Getis, Arthur, and J. Keith Ord . 1996. “Local Spatial Statistics: An Overview.” In P. Longley and M. Batty (eds.), Spatial Analysis Modelling in a GIS Environment, 261282. NY: Wiley. Krugman, Paul. 1991. Geography and Trade. Cambridge, MA: MIT Press. Lee, Jay, and David W. S. Wong. 2001. Statistical Analysis with ArcView GIS. New York, NY: John Wiley & Sons. Ord, J. Keith, and Arthur Getis. 1995. “Local Spatial Autocorrelation Statistics: Distributional Issues and an Application,” Geographical Analysis, 27, 286-306. Popkin, Joel and Company. 2003. Securing America’s Future: The Case for a Strong Manufacturing Base.” Washington, D.C.: National Association of Manufacturers (White Paper). Porter, Michael E. 1990. The Competitive Advantage of Nations. New York, N.Y.: Free Press. Porter, Michael E. 1998. On Competition. Boston: Harvard Business Review Books. Ratcliffe, J. H., and M. J. McCullagh. 1999. “Hotbeds of Crime and the Search for Spatial Accuracy,” Journal of Geographical Systems, 1, 385-398. Shelburne, Robert C., and Robert W. Bednarzik. 1993. “Geographic Concentration of Trade-Sensitive Employment.” Monthly Labor Review 16, 3-13. Sohn, Jungyul. 2004. “Do Birds of a Feather Flock Together? Economic Linkage and Geographic Proximity,” Annals of Regional Science, 38, 47-73. Unwin, David J. 1996. “GIS, Spatial Analysis and Spatial Statistics,” Progress in Human Geography, 20, 440-441.

9 Clusters and Local Economic Growth: Unpacking the Cluster Model

Michael Taylor School of Geography, Earth and Environmental Science University of Birmingham, UK

9.1 Introduction In the past decade, an increasing body of research, captured under the rubric of Porter’s (1998) ‘clusters’, has built on Granovetter’s (1985) concept of embeddedness to explain the dynamics of local economies in the face of an intensifying global economy. This social-institutionalist perspective contrasts with more economistic interpretations of agglomeration and local growth (e.g. Glaeser, 2000), and emphasises the role of social relations in economic transactions, holding that anonymous markets are non-existent and that economic life and transactions are built on social connections. It has risen to become a powerful model of local economic growth that draws on a range of complementary literatures on ‘new industrial spaces’, ‘learning regions’, ‘innovative milieu’ and ‘regional innovation systems’ (e.g. MacKinnon et al., 2002; Braczyk et al., 1998; Porter, 1998; Storper, 1997) – also referred to as the ‘new regionalism’ (Rainnie and Grobbelaar, 2004). Building directly on the ideas of Granovetter, new regionalist and cluster-based writing suggests that economic growth is linked not only to market conditions, but also to repeated inter-firm interaction and knowledge exchange, learning, technological change and innovation, collaborative long-term buyersupplier relationships, and the creation of social capital (including trust, reciprocity and loyalty), bolstered by a supportive tissue of local institutional thickness (see Putnam, 1993; Maskell, 2000; Cumbers et al., 2003; Amin et al., 2003). At the very heart of these relationships are place-based business networks, with successful local economies being seen as islands of capital accumulation built on the superior local productivity that these network relationships are said to yield (Porter, 1998; Porter and Ketels, 2003). This emphasis on place-based networks has, in turn, generated renewed interest in the advantages of geographical proximity involving firms in related industries (Keeble and Nachum, 2002). This is a significant shift away from traditional understandings of agglomeration based on inputoutput relations and transaction costs, focussing instead on the social and institutional drivers of growth. Separately, the writings that contribute to and complement the ‘cluster’ perspective tend to emphasise particular drivers of local growth (Taylor and Plummer, 2001a, 2003), built on fragments of evidence and intense theoretical speculation. For example, the new industrial spaces literature tends to emphasise technological change, transaction costs and the local integration of small firms (Scott and Stor99 J. Gatrell and N. Reid (eds.), Enterprising Worlds, 99–117. © 2006 Springer.

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per, 1992). The learning regions literature emphasises firms’ competencies, knowledge transfer and processes of local learning (Maskell and Malmberg, 1999). And, the innovative milieu literature emphasises, above all else, the significance of local social configurations in creating an appropriate environment for local economic growth (Moulaert and Nussbaumer, 2005). Indeed, the literatures of the cluster perspective can be interpreted as layers of theoretical conjecture and layers of contingency built one upon another to create a very plausible fiction about the efficacy of spatially clustered local growth in the face of mounting global economic pressure. Significantly, this model of economic growth has been widely adopted by policymakers and regional development practitioners (OECD, 2001): it is a new paradigm for regional development policy. It is a set of ideas that has been adopted extensively to inform and shape local economic policy at the State level in the US. In the UK, the policies of its regional development authorities (RDAs) are now designed to facilitate clustering and inter-firm linkage through strategies such as the establishment of business parks, urban regeneration schemes, business incubators, low interest loans, and infrastructure support. As in other countries, such as Australia, the application if this new orthodoxy has often been introduced uncritically and in the absence of detailed empirical evaluation. Nevertheless, despite the popularity of this model of local economic growth, it does have significant limitations (Martin and Sunley, 2003; Taylor, 2005; Boschma and Kloosterman, 2005). The purpose of this chapter is to explore these limitations as they apply to both the principal drivers of the cluster model and to the overall configuration of the model as it has been elaborated in theory and practice. The discussion of the chapter is divided into two main sections. Following the introduction, Section 2 examines the limitations associated with the six main drivers of the broadly-based cluster model, including the model’s: • • • • • •

overwhelming preoccupation with social construction of local economic processes, use of the problematic concept of social capital; over-simplification of learning processes; exaggeration of the importance of proximity; de-powering of network relationships; and one-sided interpretation of institutional support and ‘thickness’.

The argument is not that these processes do not occur but that they occur only sometimes, in some places, and not necessarily in the combinations that the most ardent supporters of the model suggest. This aspect of the argument is elaborated in Section 3 which attributes the limitations of the model to four interrelated broader scale problems: •

the casting of the model in an essentially static, a-historic time-frame;

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the normative instrumentalism that runs through the specification of processes in the model which results in the processes being seen only as additive; and the failure of the model to engage with issues of complexity.

The conclusions drawn in Section 4 argue for a more subtle, selective and less dogmatic application of the cluster model as a foundation for the development of local economic development policy. The separate processes are not necessarily additive or synergistic, and they can run as well in reverse as they can forward. It is only when these possibilities are fully recognised that appropriate policies can be designed.

9.2 The Processes and Drivers of the ‘Cluster’ Model The ‘cluster’ model of embedded local growth sees successful local economies as islands of superior productivity within a global mosaic of production and services that fosters sustainable local accumulation. This enhanced productivity is argued to be the outcome of complex processes of ‘embedding’: the incorporation of firms into place-based networks involving trust, reciprocity, loyalty, collaboration, and co-operation (Granovetter, 1985; Storper 1997, Cooke 1998). These are processes that create ‘social capital’. They involve socially constructed relationships that create knowledge, information and ideas, and generate innovative products, processes and services that are, in turn, shared within the system rather than being appropriated by any one individual (Leborgne and Lipietz, 1992). The whole is a system of heightened place-based capacities for learning, information and knowledge exchange, building on local competencies (Maskell and Malmberg, 1999; Bergman et al, 2001). They are local knowledge networks that have the capacity to generate invention, innovation and technological change: where the tacit knowledge of the labour force gained from learning-by-doing is mobilised through paternalism rather than wage discipline, and is blended with codified knowledge (Brusco, 1996). Simultaneously, they are innovative milieus offering socially constructed environments that can nurture ideas, people and enterprise, and they are regional innovation systems driven by intense local processes of Schumpeterian creative destruction that endow locally networked firms with commercial resilience and the ability to cope with constantly shifting factor mixes. At the same time, these locally networked relationships involving firms and labour are said to be reinforced by a “... supportive tissue of local institutions” (Powell and SmithDoerr, 1994, p. 370). These institutions, it is argued, ease and network relationships and foster knowledge exchange and learning; sustaining the Marshallian ‘atmosphere’ and ‘buzz’ of an economically successful place (Amin and Thrift, 1994; Bathelt, et. al, 2004) At the core of the cluster model is, therefore, a set of stylised facts or caricatured processes that focus on the workings and interactions of: (1) trust and reciprocity; (2) social capital; (3) knowledge and learning; (4) proximity; (5) network relation-

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ships; and (6) institutional support. Whether they work in the manner they are thought to in theory is, however, open to question, and each will be explored in turn. 9.2.1 The social construction of local economic processes: trust and reciprocity In the cluster model it is fashionable to see trust, loyalty and reciprocity as basic to business practice and the workings of commercial transactions. Such an emphasis, however, denies an number of fundamental aspects of the workings of capitalism, especially the workings of the price mechanism and the generation of profits. It may well be that the emphasis on either price or trust in inter-firm relationships will vary between periods of economic buoyancy and periods of pessimism, with the focus on price sharpening as margins thin. But, price is fundamental to the earning of profits, and profits are central to capitalism. Profits provide a return on risk and allow capital to be accumulated. They also facilitate innovation, growth and change, they pay dividends to owners and investors, and they send signals to markets. A number of studies suggest, however, that the level and persistence of trust in inter-firm relationships might be rather more illusory than real. Uzzi’s investigations of the gar