West Virginia University
LIST OF BOOKS CONTENTS BACK TO CHAPTER ONE CHAPTER THREE CHAPTER FOUR

Authors


Edward M. Bergman




Edward J. Feser



































































































































































































































































































































































































































Industrial and Regional Clusters: Concepts and Comparative Applications
Edward M. Bergman and Edward J. Feser

CHAPTER TWO
Basic Operational Concepts and Supporting Theoretical Frameworks

2.1 Introduction

Industry clusters have become one of the most popular concepts in local and regional development research and practice. Even a cursory Internet search will turn up numerous dedicated web sites by research institutes, industry associations, consultants, and cities, states, and regions reporting cluster studies for particular localities or offering perfunctory guides to industry cluster concepts. Arizona, California, Connecticut, Florida, Minnesota, North Carolina, Ohio, Oregon, and Washington are among many states that have designed and/or implemented cluster-based economic development strategies.1 Hundreds of U.S. cities and regions have also developed cluster strategies, from Monterey Bay, California to Jacksonville, Florida. In 1999, two major U.S. associations of development practitioners (the National Association of State Development Agencies and the State Science and Technology Institute) held national day-long workshops on cluster analysis and practice.

European cities and regions have embraced the cluster concept with even more enthusiasm. Not surprising since much of the research that informs industry cluster studies originates in case studies of European regions in northern Italy, southern Germany, Great Britain, and Denmark. Industry cluster analysis informs National Innovation Systems (NIS) planning at the OECD and most members of the European Union have conducted cluster studies at the national and or industry-level (see Roelandt and den Hertog, 1999).

It seems that the question "Why study industry clusters?" could be answered simply by noting the popularity of the concept in development planning; it is clear that one cannot fully understand regional development policymaking without some knowledge, perhaps even direct experience, with industry cluster applications. But are industry clusters a passing fad, the latest craze in a field prone to embrace miracle solutions only until a more fashionable idea emerges? Certainly, at issue among some regional scholars is whether there is actually anything new or innovative about industry clusters (Enright 1996; Feser 1998).

In this monograph, we argue that the greatest value in the industry cluster concept is its capacity to help both the analyst and policymaker "see the regional economy whole." That is, industry cluster analysis is not so much an innovation in regional theory or methods, as it is a comprehensive approach for understanding regional economic conditions and trends, as well as the policy challenges and opportunities those conditions and trends portend. In large measure, industry cluster analyses and policies may be viewed as applications of a set of well-worn but rejuvenated theories of how geography helps drive economic growth and change. Industry cluster analysis can help exploit the growing wealth of regional economic data, provide a means of thinking effectively about industrial interdependence, and generate unique pictures of a regional economy that reveal more effective policy options.

Boekholt (1997, p. 1) writes that the "multitude of cluster initiatives has led to a wide spread confusion of what clusters really are, and in what way they differ from related phenomenon, such as industrial districts, technopoles, networks, and industry-research collaborations." Held (1996, p. 249) notes: "Sadly, in the rush by various governments to employ clusters, some fundamental issues have been slighted, including appropriate research methods and even the definition of the cluster itself." In this chapter, we examine the rich literature in geography, regional science, urban planning, economics and other related fields that explores core theoretical concepts on which applied and scientific industry cluster studies are based. We begin by laying out some working definitions.

2.2 What are industry clusters?

An industry clusters [link to Exhibit 2.1] may be defined very generally as a group of business enterprises and non-business organizations for whom membership within the group is an important element of each member firm’s individual competitiveness. Binding the cluster together are "buyer-supplier relationships, or common technologies, common buyers or distribution channels, or common labor pools (Enright 1996, p. 191)." Competitive firms make a competitive cluster, and, as Enright (1996) notes, economic self-interest is ultimately the glue that binds the cluster together. Though many scholars emphasize the role of trust and cooperation among cluster firms (and their role in solving joint problems and generating other benefits for cluster enterprises), in the end, a "cluster" comprised of enterprises that gain no real economic advantage from their presence in the group loses all conceptual meaning from a theoretical and policymaking perspective. Non-business organizations may include industry associations, technical and community colleges with specialized industry programs, universities, government industrial extension programs, network brokers, and the like. Such entities are frequently defined in the literature on clusters as "related and supporting institutions"; they are often a critical element in the success of the cluster.

In application, defining an industry cluster can become exceptionally difficult, particularly as competing policy objectives come into play. On the one hand, both space and time are relevant dimensions, such that the basic characteristics of the policy-relevant cluster vary widely between applications. On the other hand, data and methodological constraints may partially dictate cluster definitions. The latter is not necessarily a limitation if recognized explicitly by the analyst and policy conclusions are determined accordingly. However, if clusters are defined one way and measured another, resulting policy conclusions will clearly be tenuous.

Industry clusters may be more or less geographically concentrated. As we outline below, early regional development theories explicitly recognized that interdependence between enterprises may be distance-sensitive to varying degrees. It is entirely possible that the "binding ties" among a localized group of enterprises may very well be between a firm or firms located in a distant region. A sizable number of southern Ohio and northern Kentucky automotive components manufacturers that sell to final market assemblers in Michigan and South Carolina is one example. At one scale, an automotive cluster may appear to be concentrated in the southern Ohio-northern Kentucky region. Another level of analysis, however, might reveal an automotive cluster along the north-south axis between the traditional vehicle heartland in Michigan, concentrations of suppliers in Kentucky, Ohio, the Carolinas and Georgia, and the new southern automobile manufacturing regions in South Carolina, Alabama and Tennessee. Development officials in northern Kentucky cannot afford to ignore key linkages of local firms to enterprises farther north and south, at least if they truly want to understand what drives the competitiveness of their local industries.

Exhibit 2.2 summarizes a working set of definitions. Regional industry clusters are industry clusters that are concentrated geographically, normally within a region that constitutes a metropolitan area, labor market shed, or other functional economic unit. Regional clusters are similar, in varying respects, to Italianate industrial districts , business networks , industrial complexes of the early regional scientists (Czamanski 1976), and Maillat’s (1991, Maillat and Vasserot 1988) concept of the innovative milieu (see Enright 1996). All of those concepts hold in common the notion that geographic proximity between member enterprises lends certain competitive advantages, though the specific nature of the advantages varies slightly from concept to concept.2

Some clusters exist at the present time. Vehicle production in Detroit, computers in Silicon Valley, and flowers in The Netherlands are examples. Others may be more accurately characterized as emerging or potential . Biotechnology as a cluster is only now emerging in a limited number of regions worldwide, as advances in medicine, biology, and chemistry make it possible create entirely new products and new associations between firms, industries, universities, and other economic agents. From a policy point of view, knowing what could become a cluster (perhaps with proper policy stimulation) is frequently more critical than knowing what is a cluster. Indeed, the latter may be obvious more often than not.

Measurement issues also play some role in defining clusters. One of the only consistent and detailed sources of data on cross-industry linkages are input-output tables. Analysis of input-output patterns to identify "clusters" had its beginnings in the 1960s (see Czamanski and de Ablas, 1979, for a review), fell off in the late 1970s and 1980s, and has seen a resurgence with the recent policy interest in industry clusters. What has effectively occurred is a merging of traditional regional science methodological techniques with a conceptual framework based largely in strategic management, industrial organization, and economics proper.

This blending of perspectives and research interests has both advantages and disadvantages. On the one hand, analytical methods developed by early regional scientists and recently advanced in cluster applications lend analytical rigor to more the qualitative and pragmatic research approaches common to the strategic management and industrial organization literatures. On the other hand, partly as a result of conceptual differences and partly because of data and definitional limitations, input-output based derivations cannot fully capture the set of interrelationships specified in the modern industry cluster concept. Thus, it is important that input-output based clusters be clearly distinguished.

In this monograph, we identify value-chain industry clusters as those defined primarily on the basis of trading patterns among member enterprises.3 Trade between enterprises need not be direct (it might be indirect through tertiary partners). Moreover, it is possible (as we argue in Chapter 3), that input-output methods can identify a set of enterprises and industries that constitute the most likely candidates (or "suspects") for non-trade-based dependencies (i.e., linkages based not on trade, but rather similarities of technology or shared labor pools).

2.3 Explaining Competitive Advantage 4

Real policy interest in regional industry clusters has its origins in Michael Porter’s The Competitive Advantage of Nations, published in 1990. Porter’s readable account of the sources of national competitive advantage, which includes a key role for geographic proximity, is largely consistent with a growing body of literature on how interdependence between firms, industries, and public and quasi-public institutions affects innovation and growth in regional agglomerations. Porters’ work, which included case studies of competitiveness in multiple nations, also offered some anecdotal verification of highly theoretical research on the role of business externalities and spillovers in driving growth and innovation. Nearly every analysis of industry clusters begins with--or at least makes some mention of--Porter’s "diamond," a characterization of his four key drivers of competitiveness.

[Exhibit 2.3]

For Porter, industries’ success in international markets are the primary barometer of the competitive strength of a nation. The success of any given firm can be traced to four major factors: 1) the nature of firm strategy, structure and rivalry in the country, including attitudes toward competition, market institutions, the degree of local competition, and other cultural and historical factors affecting how firms do business with each other, their workers, and the government; 2) factor conditions, or the basic endowments or conditions on which the firm seeks to compete (e.g., cost-related basic factors such as ready supplies of natural resources or inexpensive, unskilled labor versus knowledge and/or technology related advanced factors); 3) demand conditions or the nature of local demand (e.g., the needs and wants of the consumer for foreign and domestic goods as well as the existence of local industrial demand for related intermediate goods); 4) the presence of related and supporting industries, including suppliers and successful competitors (both to stimulate cooperation, the latter to also stimulate rivalry).

Competitive companies must depend, to a degree, on the competitiveness of their intermediate input suppliers, who must depend on the capabilities of their suppliers, and so on, back through all links in the value chain. But such companies also depend on service providers (management, marketing, financing, legal, etc.), sources of basic and applied R&D (e.g., universities and/or contract research organizations), capital goods suppliers, wholesalers and distributors, and suppliers of trained workers (again, universities and colleges). Even competitors are important, including direct competitors to the company as well as competitors to the company’s suppliers, since their presence maintains pressure to continually upgrade processes and techniques and to seek new opportunities. Competitors also provide opportunities for cooperation in solving joint problems or addressing industry-wide issues (see also Best 1990).

Thus, the success of an individual company may be partly traced to the size, depth, and nature of the cluster of related and supporting enterprises--both private and public--of which it is a part. Much of Porter’s analysis focuses on outlining the basic conditions determining cluster competitiveness. His framework leads naturally to a focus on end-market sectors as the point of departure for studying clusters. But such end-market industries should not be studied in isolation; the critical function of interdependence in the process of economic growth and change–not just in terms of how it has traditionally been viewed, i.e., in technical or input-output terms--is the guiding principle in his study.

Porter does not argue that the dynamics that characterize industry clusters are necessarily localized in scope, though he does believe that clusters tend to be geographically concentrated. To complicate matters, the degree of economic and geographic clustering one observes for a particular end-market industry is relative to space, time, and scale. An end-market sector clustered geographically from a national perspective may not be spatially clustered from a regional or local one (or vice versa). Moreover, a given sector becomes more economically clustered as vertical, horizontal, and lateral linkages and relationships expand and deepen (with growth in related and supporting industries and/or the establishment of stronger ties or networking with existing enterprises). And there is no reason, a priori, to assume that clustering along either dimension need only increase over time, even with economic growth and nominal increases in various elements of the cluster. Changes in the social, cultural, or political environment could lead to altered relations between cluster firms such that the positive synergies described by Porter are reduced. Alternatively, improvements in the transportation or communication infrastructure may lead to some spatial dispersal of cluster firms and a reduction in geographic clustering. Finally, there is the element of scale. True clusters are probably large, perhaps exceeding some threshold, but size alone does not guarantee clustering.

Porter’s ideas are not without important antecedents. In the 1950s, Francois Perroux argued that to understand economic growth and change, analysts need to focus on the role of propulsive industries, those industries that dominate other sectors because of their large size, considerable market power, and/or role as lead innovators. Propulsive industries (or even individual firms) represent poles of growth which attract, focus, and direct other economic resources (Darwent 1969). Such constellations of producers, suppliers, and other economic actors sound surprisingly like clusters.

Perroux (1950) viewed economic space as the non-spatial sphere in which relations between firms and their buyers and suppliers (as well as other key economic institutions) take place. For Perroux, there is no reason why physical space should necessarily bear any relationship to economic space; enterprise linkages will extend without spatial limit throughout the globe, at least where they are economically justified. Directing one’s analysis to particular regions will only provide a distorted picture of the growth and development process (geographic space as ‘banal’).

The similarities between the cluster concept and Perroux’s theory of growth poles are readily apparent. The cluster focus on how end-market industries drive the deep and broad value chains of which they are a leading part is consistent with propulsive industries as dominant economic actors. End-market industries in given clusters transmit growth pulses through the cluster through demand for intermediate and capital goods. In addition, because they are composed of internationally competitive, best practice firms, they may play an important role as diffusers of process and product innovations. To the degree, for example, that large original equipment manufacturers (OEMs) can use their market power to dictate (or perhaps strongly encourage, even assist with) technology upgrades and improved manufacturing strategies to their suppliers, such end-market industries might be said to drive, at least in part, overall cluster competitiveness. On the other hand, one can also conceive of market power among some cluster members as exerting a detrimental influence on the overall cluster. For example, short-term, least cost-focused contracting practices of OEMs with their suppliers may actually discourage strategic thinking and investment.

Perroux’s ideas, and their extensions, are relevant for the industry cluster concept in another respect: his theory gave rise to a related regional development strategy (growth centers) that enjoyed a meteoric rise in popularity in policy circles only to eventually prove a dismal failure. While it is too soon to tell whether industry cluster policies will be similarly ineffective, the rise in their stock appears nearly as dramatic.

The failure of growth center policy is described in detail elsewhere (Higgins 1983, Higgins and Savoie 1995). But one of the most important reasons why such strategies misfired more often than they succeeded is that too little attention was paid to the economic and social pre-requisites that are necessary–at least as hypothesized in the vast theoretical literature–for growth centers to work (Malizia and Feser 1998). Most applications focused on the role that backward and forward linkages to strategic and favored sectors could play to leverage regional growth, particularly in underdeveloped areas (Hirschman 1958). But political and equity considerations often dictated, through a criterion of need rather than potential, the designation of very small and peripheral towns as "growth centers." Linkages were regarded almost mechanically, as if localized interindustry trade would automatically flow in a form resembling the average patterns observed in input-output accounts. A critical difference between growth centers and the industry cluster concept is that the latter emphasizes why businesses choose to align themselves or partner in trade (where location is only one possible reason), while the former effectively assumed such partnerships were inevitable.

Still, there is no question that industry clusters identified in practice often bear little resemblance to Porter’s ideal type. It is not uncommon for local and regional agencies to designate clusters for policy attention that are actually very poorly developed or that constitute the only viable industry in the given region (designations motivated more by limited choice sets or politics than any economic rationale; Held 1996). While most of the current cluster debate is taking place in industrialized countries with already diverse economies and relatively strong effective demand (domestic and/or international), in less developed regions a policy decision to concentrate resources on key industries, instead of more general infrastructure needs or other strategies that would serve best a broad array of industries, brings with it significant risks against which the gains remain unverified.

If one thing is clear, it is that Porter’s eloquent and convincing account of economic interdependence, geography, and competitiveness is short on specifics. As a result, most of the literature takes his concepts only as a point of departure, tapping instead a wide range of more developed ideas to explain the origins of industry clusters, the dynamics of cluster growth and change, and advantages to using clusters as a basis for regional policy. The following section outlines a set of core concepts that are frequently cited or called upon to either explain cluster dynamics or legitimate cluster-based policies.

2.4 Theoretical Foundations

Some analysts of the behavioral phenomena behind industry clusters emphasize explanations for observed spatial clustering of business enterprises (e.g., Enright 1990, 1996), with theories of business externalities, agglomeration economies, labor pooling, and knowledge spillovers the main focus. Others stress the link between innovation and clustering, drawing on theories of growth poles, development blocks, and Schumpeterian entrepreneurship (DeBresson 1996). Doeringer and Terkla (1997) specify three major drivers of industry clustering: 1) strategic business opportunities derived from specific kinds of interfirm alliances ; 2) traditional regional factor market advantages (labor pools and localized knowledge spillovers); and 3) the role of non-business institutions such as universities, colleges, trade unions, and associations. Rivalry, just-in-time trends, niche marketing, and civic capacity are among the concepts in their survey.

In the end, there is no obvious organizational scheme for laying out and drawing connections between relevant theories. Our own reading of the literature suggests that five core theoretical concepts underpin the literature on regional industry clusters: external economies, the innovation environment, cooperative competition, interfirm rivalry, and path dependence. We make no attempt to be comprehensive and exhaustive in our discussion; readers should consult the many citations to flesh out ideas in more detail.

2.4.1 External Economies

Regional scientists and geographers are keenly interested in how and why enterprises cluster in geographic space, and particularly how such clustering influences regional development paths. Two basic conceptual approaches to understanding benefits to concentration dominate the literature: industrial location theory that builds on Weber and Hoover (1937), where the benefits are called agglomeration economies, and the Marshallian perspective that takes as its point of departure Marshall’s ([1890] 1961) analysis of external scale economies and their presence in "industrial districts." In both cases, various, often anecdotal, types of externalities (or, more appropriately, sources of externalities) are cited as the reason why firms co-locate. The literatures differ somewhat in their relative emphasis on static versus dynamic externalities, while neither perspective is particularly concerned with distinguishing between pecuniary and technological externalities.

Industrial Location Theory. Weber (1929) identifies agglomeration economies–defined as cost savings firms enjoy as a result of increased spatial concentration–as one of three primary causes of spatial clustering or agglomeration. But Weber is not particularly concerned with why such agglomeration economies arise, preferring to suggest that they are simply external varieties of internal scale economies (see Weber, 1929, p. 127). In point of fact, his primary aim was to model how such economies might lead to agglomeration (rather than identify what explains the economies themselves). It was a theoretical approach and methodological emphasis that eventually became the traditional regional science/urban economics approach to the study of externalities.

Though Hoover is nearly as vague as Weber, he does introduce the now accepted distinction between urbanization and localization economies. In the cluster literature, the focus is mainly on externalities related to proximity among business enterprises (localization economies), rather than externalities associated with general urban advantages (urbanization economies). Other researchers cite particular advantages of proximity between firms, including increased market power through brokered buying and selling, the better availability and use of specialized repair facilities, shared infrastructure, reduced risk and uncertainty for aspiring entrepreneurs, and better information (Isard 1956, Lichtenberg 1960, Vernon 1960, Carlino 1979). In a recent monograph intended to guide practitioners, Rosenfeld (1995a, p. 20) cites "tailored infrastructure" as a key advantage firms in regional clusters enjoy. He uses a scale economy logic: "As industry concentration increases, individual businesses benefit from the development of sophisticated institutional and physical infrastructure tailored to the needs of specific industry." Such infrastructure includes "local product showrooms, foreign sales offices or distribution centers, supply centers, common waste treatment facilities."

Marshallian Theory. Marshall ([1890] 1961) defines external scale economies as cost savings accruing to the firm because of size or growth of output in industry generally. Such economies contrast directly with internal scale economies, which are the source of increasing returns from growth in the size of plant. Such external economies are essentially spatial externalities, which may be defined generally as economic side-effects of proximity between economic actors. They can be either negative or positive, static or dynamic, pecuniary or technological. The static variety are reversible, whereas dynamic externalities are those associated with the technological advances, increased specialization, and division of labor that accompanies and/or drives growth and development (Young 1928).

For the most part, regional scientists are interested in dynamic external economies, though this is not made explicit. A static external economy enjoyed by a firm in a given industrial district might be the lower costs it enjoys for intermediate inputs because of proximity to its suppliers (e.g., as a result of reduced shipping costs). That economy is also pecuniary and imposes no market failure since it is fully reflected in the price mechanism. There is certainly no role for government to encourage geographic clustering in this context. To the degree that such benefits outweigh any costs associated with agglomeration (congestion), enterprises will be inclined to cluster on their own.

Of most relevance for understanding industry clusters are dynamic external economies associated with learning, innovation, and increased specialization. Marshall illustrates the workings of (largely dynamic) external economies with reference to concentrated industrial districts, places where firms enjoy the benefits of large, skilled pools of labor, greater opportunities for intensive specialization (a finer social division of labor), and heightened diffusion of industry-specific knowledge and information (knowledge spillovers). Behind those dynamics is not just the size of the district alone, but social, cultural and political factors, including trust, business customs, social ties, and other institutional considerations (Bellandi 1989). Much of Marshall’s analysis is relevant to Porter’s (1990) discussion of firm structure, strategy and rivalry as one of the four determinants of competitiveness (Peneder 1995), about which we have more to say below. In effect, Marshall provides some of the first hints as to how micro-level business relationships might influence regional growth and development.5

2.4.2 The Innovation Environment

Just as enterprises do not conduct business in isolation, they do not innovate in isolation. The innovation environment constitutes research that attempts to the characteristics of "learning economies," economies that help sustain the perpetual research and innovation necessary to continually generate new products and open new markets. According to Roelandt and den Hertog (1999, p. 1):

In modern innovation theory the strategic behaviour and alliances of firms, as well as the interaction and knowledge exchange between firms, research institutes, universities and other institutions, are at the heart of the analysis of innovation processes. Innovation and the upgrading of productive capacity is seen as a dynamic social process that evolves most successfully in a network in which intensive interaction exists between those ‘producing’ and those ‘purchasing and using’ knowledge.

Industry clusters are regarded as an important tool in policies related to national innovation systems (NIS), an important theoretical framework in European national and regional policy circles. Lundvall (1992) defines NIS as "the elements and relationships which interact in the production, diffusion and use of new, and economically useful knowledge. . .that are either located within or rooted inside the borders of a nationstate (quoted in Roelandt and den Hertog 1999, p. 2). In a more recent contribution, Lundvall (1999, p. 2) argues that increases in the rate of innovation dictate important changes in national and regional policy, with particular emphasis on contributions to "the learning capability of firms, knowledge institutions and people."

Industry clusters and networks can serve as mechanisms whereby firms exchange knowledge and information that cannot be codified. Such tacit forms of knowledge are viewed as increasingly important given the rapidly changing global economic environment. Tacit knowledge must also be exchanged between individuals, not business entities, reinforcing advantages to spatial clustering (Lundvall 1999). Such advantages are likely to be strongest for technology-intensive firms, yet even traditional, design-oriented sectors such as furniture and apparel, may seek to improve flexibility and ability to innovate by clustering in particular regions. Characteristics of the regional environment may also play a role in helping firms innovate. Saxenian (1994), for example, highlights even land use and design issues in describing the unique capacity of Silicon Valley to promote innovation.

Another perspective is that of the "innovative milieu." According to Maillat (1991, p. 113):

The milieu must be envisaged in such a manner that it has a significant action on the manner of giving life to the innovation process. The milieu is not a warehouse from which one obtains supplies, it is a complex which is capable of initiating a synergetic process. From this point of view the milieu cannot be defined merely as a geographical area, it must be envisaged as an organization, a complex system made up of economic and technological interdependencies.

Like research on industrial districts, literature on the milieu focuses on the specific nature and quality of transactions, alliances and partnerships between enterprises. But the focus is less on bilateral ties than the degree to which they support a collective environment for innovation (Malecki 1997).

2.4.3 Cooperative Competition

One of the predominant themes in the industry cluster literature is "cooperative competition," the notion that the most competitive firms find ways to work together even as they go head to head in the development of new products and the battle for markets. Out is the notion that companies minimize risks and maximize their competitive position by strictly regulating any information exchange with direct competitors. Modes of cooperation based on trust, familial ties, and tradition are most often described for industrial districts in Third Italy, where they are believed to be one means by which small and medium-sized enterprises seek to counter internal scale economies enjoyed by their larger competitors (see Asheim 1997, Park and Markusen 1995, Park 1997). The new industrial districts literature, in turn, draws on theories of flexible specialization (Isaksen 1997, Asheim and Isaksen 1997, Heidenreich 1996), though the latters’ focus on substantiating a basic sea-change in the organization of production is less important for understanding the specific, micro-level relationships that undergird regional industry clusters.

Of more significance are recent efforts to clarify the general relationships between scale and scope economies (e.g., Bellandi 1996), as well as the many case studies of particular industrial districts that identify not only basic economic trends in agglomerations of smaller firms, but also social and cultural behavioral codes that govern relationships between firms in those dynamic regions (see Humphrey 1995 and related articles in World Development 23, 1). The study of the ‘social embeddedness’ of economic transactions constitutes a principle contribution of the new industrial district literature (Harrison 1992), and holds promise for making clearer the broad institutional factors Porter cites in his work.

Outside of the industrial districts literature, however, examples of cooperation between enterprises in given clusters are relatively few. Many of the characteristics of firm interdepence in Italy are culturally specific; modes of business behavior in the United States and many other industrialized countries are very different. Doeringer and Terkla (1997) offer two circumstances in which cooperation among co-located firms can payoff. The first is when just-in-time inventory and delivery systems are used. They cite the joint location choices of Japanese manufacturers and their suppliers, which is often necessary to make JIT truly work, as evidence of how cooperation drives regional industry clustering. The second example is a function of the speed and frequency of interactions between companies in a regional industry cluster. The more frequent and rapid the interaction between suppliers, the more likely companies are to identify niche markets and new specialized products. They characterize such dynamics as "collaboration economies" or "the ability to participate in, and respond rapidly to, changing design and manufacturing practices among firms that buy and sell from one another (1997, p. 182)."

The problem with both of those examples is that they apply primarily to end market producers and their suppliers, rather than between competing end market producers. As Enright (1996, p. 199) notes, the distinction between vertical and horizontal types of cooperation is important, since the potential costs and benefits of each type vary significantly. He cites lobbying, foreign market research, joint export promotion, trade fairs, and specialized infrastructure investments as typical areas in which competing producers might cooperate. On the other hand, they tend to compete in the areas of marketing, production, sales, new product development and process improvements. Contrast this view with writing on industrial districts, which focuses much attention on cooperation in production (particularly collective efforts to solve joint production problems). Ultimately, the "social embeddedness" of firm relationships means that internal dynamics of regional industry clusters are likely to vary widely between countries, and often within them.

2.4.4 Rivalry

On the face of it, the emphasis on interfirm rivalry in Porter’s analysis would seem to contradict the view that clusters are imbued with a spirit of cooperative competition. Porter adopts the traditional neoclassical view in arguing that a competitive industry structure–i.e., multiple companies competing on the same playing field–ensures continued pressure to upgrade technologies, minimize costs, innovate, and so forth. But a simple industrial concentration index is not an adequate barometer of the degree of rivalry among firms in a given industry or region. More important is the competitive ethos of the industry. Also, rivalry will likely be stronger among competing firms are geographically concentrated in a particular area. In such a case, the dimensions of competition multiply. Firms in the same region compete not just for customers, but also for labor, capital, publicity, and political support.

An early analysis of the link between market structure and geographic concentration is Chinitz’s (1961) paper on market structure as a key determinant of agglomeration economies. In a brief but rich discussion that essentially anticipates the present-day focus on how firm and industry organization influences regional development paths, Chinitz essentially draws a direct link between firm structure and rivalry and regional economic fortunes. Critiquing the agglomeration economies literature’s focus on urban and industry size, Chinitz argues that industrial structure particularly influences learning, innovation, and entrepreneurship, giving diverse, and small-firm rich places like New York a leg up over large-firm, single-industry towns like Pittsburgh. This has become an important theme in the Marshallian new industrial district theory as well.

2.4.5 Path Dependence

Polarization, core-periphery, and cumulative causation models all refer to the tendency for regional growth or decline to reinforce itself (Myrdal 1957, Friedmann 1966, Kaldor 1970). While such models emphasize disequilibrium in the space economy, with some regions establishing dominant positions vis-a-vis peripheral regions, neoclassical regional growth theory predicts that natural market mechanisms tend to gradually eliminate interregional economic disparities. The latter result is based on a constant returns world that admits no role for externalities. Neoclassical theory tended to dominate mainstream views of regional growth through the 1980s.

The debate between equilibrium and disequilibrium views of regional growth was renewed in the 1990s with recent contributions in mainstream economic growth theory that highlight the role of increasing returns. According to Krugman (1995), what accounts for the new interest in increasing returns among mainstream economists are modeling advances that permit their more rigorous and consistent treatment. New growth theory suggests that a comparative advantage established in a given region or country, perhaps by accident, chance, the distribution of natural resources, or other non-behavioral phenomena is likely to strengthen as a result of external scale economies (usually described in Marshallian terms rather than in the language of agglomeration theory).

Like the new growth theory, ‘new international economics’ also holds important implications for regional analysis. It is not that trade theory now admits a geographic dimension; trade theory has always been spatial theory (Ohlin 1933, Krugman 1991). Rather, the incorporation of increasing returns in models of trade implies the prospect of a highly concentrated geographic pattern of development (Krugman 1990), including sustained disparities in regional income and employment. Again, the focus is on knowledge-related externalities as sources of increasing returns, particularly in advanced technology industries (Krugman 1996). The process of cumulative advance in regions whose industries have established a competitive lead in given markets has been described as an example of a ‘lock-in effect’ (Arthur 1989, 1990a, 1990b). In principle, the initial lead may be as much a result of luck or historical accident as business acumen. But either way, particular ‘locational clusters’ may be able to establish a type of monopoly advantage over industries in other places. How likely or sustained such a process would be is an empirical matter (Krugman 1996).

Path dependence refers to the general notion that technological choices–even seemingly inefficient, inferior, or suboptimal ones–can assume a dominant lead over alternatives and be self-reinforcing, though not necessarily irreversible given a significant enough shock. David’s (1985) discussion of the modern keyboard is the classic example. Path dependence can have clear geographical implications by virtue of the fact that businesses, as a general rule, cluster in space. Krugman (1991, p. 60) cites the carpet industry in Dalton, Georgia. From a geographers point of view, it was certainly by chance that tufting technology was essentially invented there:

. . .in 1895 the teenaged Miss Evans made a bedspread as a gift. The recipients and their neighbors were delighted with the gift, and over the next few years Miss Evans made a number of tufted items, discovering in 1900 a trick of locking the tufts into the backing. She now began to sell the bedspreads, and she and her friends and neighbors launched a local handicraft industry that began selling items well beyond the immediate vicinity.

There was no carpet technology institute at the local university, no cluster of carpet producers in the region, and no history of carpet making among local workers. Yet Dalton became a leader in carpet production (indeed, a carpet industry cluster), scale economies and externalities reinforced its lead, and the rest is history. Because technology can be path dependent, regional development trajectories can become path dependent (see also Meyer-Stamer 1998). And stories like the one above suggest that being the first-mover can be critical to development success.

2.5 Summary

Industry clusters have become an extremely popular concept in development policy circles. This chapter presented a set of working definitions, a brief summary of Porter’s (1990) important contribution, and a discussion of five core theoretical concepts that are frequently cited in the literature as forces driving cluster change or as justifications for cluster policies.

At the present, industry cluster initiatives have seen relatively little criticism. Yet they raise fundamental empirical and policy questions (Feser 1998). On the one hand, very little evaluation of cluster-based policies has been conducted. Above we note the failure of related growth center applications. Though industry cluster policies are based on different theoretical principles in many respects, there is still evidence that the concept is often misapplied either as a sector-based approach or as wishful thinking in an underdeveloped area.

On the other hand, regional cluster initiatives, by definition, imply a policy-led attempt to strengthen regional concentrations. If industry is most competitive when geographically clustered, this may make good sense. But a traditional goal of regional policy has been to minimize regional disparities in growth and income. Unlike growth pole/growth center concepts, which at least attempted to address links between core and peripheral regions, the industry cluster theories speak very little to the spatial diffusion of growth. European unification, the North American Free Trade Agreement, and other attempts and common market creation and economic integration are bringing with them renewed focus on development imbalances. Moreover, industry clusters policies contract traditional wisdom of regional industrial diversification. While it is true that the largest places will develop multiple clusters, or specializations, the vast majority of cities and regions have little prospect of developing more than one or two viable clusters. Such issues must become central to the industry cluster debate.

End Notes

  1. A recent study funded by the U.S. Economic Development Administration examined seventeen cluster initiatives across the U.S. See Gollub (1997).
  2. Rosenfeld defines "business clusters" as a "geographically bounded concentration of similar, related, or complementary businesses, with active channels for business transactions, communications and dialogue, that share specialized infrastructure, labor markets and services, and that are faced with common opportunities and threats" (Rosenfeld 1995a. p. 13). The definition is consistent with "regional industry clusters" as defined here.
  3. Roelandt and den Hertog (1999, p. 1) define clusters as "networks of production of strongly interdependent firms (including specialized suppliers) linked to each other in a value-adding production chain. In some cases clusters also encompass strategic alliances with universities, research institutes, knowledge intensive business services, bridging institutions (brokers, consultants) and customers." The Roelandt and den Hertog definition is most consistent with an input-output based measurement approach.
  4. Parts of this section and the next draw heavily on Feser (1998).
  5. Marshall, also emphasizes how important industrial districts are for small firms, which, through a social division of labor, may enjoy the same types of benefits large firms earn through internal scale.

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