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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
- A
recent study funded by the U.S. Economic Development Administration examined
seventeen cluster initiatives across the U.S. See Gollub (1997).
- 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.
- 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.
- Parts of this section and the next draw heavily on Feser
(1998).
- 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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