CLUSTER THEORIES
(1): SPATIAL EXTERNALITIES
A recent New
Yorker magazine piece on the bunching of new restaurants in a particular
block in Brooklyn invokes Alfred Marshall’s century-old theory of industrial districts.
(Marshall 1890, 1920, pp. 267-277.) Whether for restaurants today or for
Manchester’s cotton mills in the 19th century, the same processes
can be seen.
Marshall’s basic point about why companies in the same industry
congregate still holds: industrial districts enjoy the same economies of
scale that only giant companies normally get. Specialized suppliers arrive.
Skilled workers know where to come to ply their trade. And everyone involved
benefits from the spillovers of specialized knowledge. As Marshall put it, “The
mysteries of the trade become no mysteries, but are as it were in the air.”
(James Surowiecki 2000, p. 68, emphasis added.)
Four Advantages of Localization
Something “in the air,” the first of the four ingredients in Marshall’s
district theory, can be construed to refer to knowledge spillovers (as in
conversations between people working for different companies). A second
ingredient is the common pool of the factors of production the local cluster
uses, especially labor. The greater
their supply, the lower the costs for each firm in the industry. Third, as
inputs become more specialized, they tend to become more productive, a la Adam
Smith’s legendary pin factory.
On these three supply-side counts each firm in the area will have lower
costs than if it operated in isolation. But in addition, and on the demand
side, comparison shopping becomes easier for the customer when the retail firms
are bunched—as in the Brooklyn restaurants.
All this is above and beyond any
savings in transportation costs between suppliers and buyers. When we combine
the two sets of forces, Marshall’s spatial externalities and the savings on
transportation costs when activities are concentrated, the result can be
combined under the heading of agglomeration economies. (See Chapter 5 of
Hoover and
Giarratani in this text.)
Localization
in Marshallian industrial districts happened on both side of the Atlantic in
the late 19th century. In a masterful essay on Marshall, Paul
Krugman points out that a special 1900 Census monograph, “The Localization of
Industries,” identified 15 specific concentrations in the U.S., among them
Collars and cuffs, localized in Troy,
New York; leather gloves, localized in the two neighboring New York towns of
Gloversville (sic) and Johnstown; shoes, in several cities in the northeastern
part of Massachusetts; silk goods, in Paterson, New Jersey; jewelry, in and
around Providence, Rhode Island; and agricultural machinery, in Chicago.
(Krugman 1991, p. 61.)
He
observes that in seemingly every example, localization resulted from a
combination of an initial accident in a particular location, after which
“cumulative processes took over.” (Technically, by the way, this is the
non-neoclassical language of positive feedback and path-dependency.)
A
Neoclassical Update
A good update on spatial externalities comes from Mills (1992). A
skeptic on labor pooling, he lists three other families of causation, which I paraphrase
here:
(1) Input-output clustering. With or
without economies of scale, if firm A’s input is used to produce firm B’s
output and is costly to ship, cost savings can be attained by proximity, and it
would be natural to find both A and B locating in the same metropolis. Whether
labor can be viewed in this context is open to question. Natural resources (A) and
resource-processing (B) qualify. Consider climate, as illustrated by aircraft
production in places with mild climates. In contrast, oil and gas are cheap to
transport, so processing can occur far from oil and gas fields.
(2) Comparison shopping
clusters. In New York’s high-fashion garment district, buyers
converge from all over the country to examine the wares and negotiate
face-to-face over a whole range of price, design, and production details. While
it might seem that such communication could be done via information technology,
something about the cluster makes it advantageous for buyers to come in person.
(3) Information clusters. Firms that
deal with similar kinds of information may cut costs or maximize their access
to information by locating in the same metropolis. This arises when information
has public-good attributes (with zero marginal costs) or is a joint product
linked to supplier-customer communications. Another set of issues concern the
distinctions between (a) quantitative vs. qualitative and, more cogently, (b)
ambiguous vs. unambiguous information.
Ambiguous
information in Mills’ view is information that requires face-to-face
access and hence contributes to clustering. It is any information that must, in
effect, be “negotiated” to establish its meaning.
This point
is fundamental in that it establishes a continuing need for face-to-face
access, despite the coming of the Internet.
The Difference a Century Makes (Not Much)
Now, just for the record, let’s go back and compare Marshall and Mills on
two of these three advantages of localization.
Look what Marshall had to say about comparison shopping, an issue
virtually never (except in Mills) cited in the voluminous literature:
So far we have
discussed localization from the point of view of the economy of production. But
there is also the convenience of the customer to be considered. He will go to
the nearest shop for a trifling purchase; but for an important purchase he will
take the trouble of visiting any part of the town where he knows that there are
specialty good shops for his purpose. Consequently shops which deal in expensive
and choice objects tend to congregate together; and those which supply ordinary
domestic needs do not. (Marshall 1920, p. 273.)
And what about conversations? For Mills, face-to-face access is a must
when the information to be communicated is ambiguous, a matter of calibration
or negotiation. What kinds of information did Marshall think benefited from
proximity? “When an industry has thus chosen a locality for itself,” Marshall
writes,
…The mysteries of
the trade become no mysteries; but are as it were in the air, and children
learn many of them unconsciously. Good work is rightly appreciated, inventions
and improvements…have their merits promptly discussed: if one man starts a new
idea, it is taken up by others and combined with suggestions of their own; and
thus it becomes the source of further new ideas. (Marshall, p. 271.)
Trust?
The next point to be noted concerns the uncertain
role of trust between competing firms as a factor conducive to spatial
clustering.
In The Second Industrial Divide, Piore and
Sabel (1984) highlighted "flexible specialization" as the
developmental stage succeeding "Fordism" or mass production. They emphasized the virtues of the
"Third Italy" and its industrial clusters specializing in
high-fashion, design-intensive goods.
They saw virtuous networks emerging among rival firms, which manage
to cooperate around activities of mutual benefit such as training,
marketing, and research.
By the same token, Bennett Harrison concluded
that the difference between Marshall’s model and this Italian version was
trust—an outgrowth of experience. As he
put it, this interpretation of the new wellsprings of regional growth in Italy
proceeded “from proximity to experience to trust to collaboration to enhanced
regional growth."
The Italian studies inspired scholars to look for parallels in clusters in other countries. A recent study of Danish textiles, for example, finds another industry cluster marked by trust and cooperation. (Sven Ileris 2000.) In Europe, it seems, trust based on experience may permit rival firms in the same industry to cooperate on certain common fronts.
In the U.S.,
however, the parallels have proved elusive. Did Silicon Valley measure up to
Harrison's criterion? Alas, no. The spectacle of Valley firms such as Intel
suing each other at every opportunity (usually over intellectual property
rights) rules this particular cluster out as an example of post-neoclassical
trust and harmony. In Harrison’s view, firms that rely on each other through
informal agreements and cumulative collaboration do not wind up in court.
Similarly,
a companion chapter in this textbook points out that clusters in The Third
Italy may be culture- or country-specific. As Bergman
and Feser observe, trust is relatively easy among firms and their
suppliers. A much rarer phenomenon—except in Italy—is trust between
competitors. On this and other counts
Bergman and Feser designate the Italian clusters as a distinctive type, which
they dub Italianate.
A controversy in the cluster literature concerns the roles of localization
economies (a la Marshall) and the more diverse urbanization economies that come
with large city size, often identified with Jane Jacobs (1969, 1984).
For example, Mills’ 1992 account outlined above had
been prompted in part by the findings of Henderson (1988) and O hUallachain and
Satterthwaite (1988) “that localization economies are more important than
urbanization economies. That means that growth of employment within a sector
tends to depend more on the size of the sector than on the size of the
metropolitan area” (Mills 1992, p. 3).
As it
happened, an influential journal article by Glaeser et al. that same year
(1992) reached an opposite conclusion.
The authors found that “industries grow slower in cities in which they
are heavily over-represented” (p. 1129). These findings tended to cast doubt on
localization economies as a source of growth. By implication, they also
supported Jacobs’ arguments for diversified cities as seedbeds for innovation
and rapid growth.
The
resolution of this issue can be found in a product-cycle or industry-maturity
perspective. As a recent World Development Report puts it,
Whether an industry benefits most from urbanization or localization economies depends on how innovative it is. New, dynamic industries are likely to locate in large urban centers where they can benefit from the cross-fertilization provided by diverse actors. Older, mature industries concentrate in smaller, more specialized cities, where congestion costs are low and localization economies can be high. (World Bank 2000, p. 117.)
When an
industry matures, in other words, its initial centers become vulnerable to
competition from newcomers and specialization becomes not an advantage but a
burden.
Porter: Rivalry and Information Flows
By the same token, however, innovation can maintain a
specialized cluster’s competitive advantage.
This is a useful light in which to view Porter’s influential version of
cluster theory, as introduced in The Competitive Advantage of
Nations (1990) and refined in two more recent articles. (Porter
1998, 2000.) The approach derives from
management theory, but it retains a neoclassical emphasis on competition and
rivalry rather than trust.
As Porter
puts it, "Successful firms are frequently concentrated in particular
cities or states with a nation" (1990, p. 29). Offering detailed maps of the Italian and German cluster
landscapes (pp. 155-156), he cites these additional examples as well:
British auctioneers are all within a few blocks in
London. Basel is the home base for all three Swiss pharmaceutical giants.
Danish windmill producers are centered in Herning. In America, many leading
advertising agencies are concentrated on Madison Avenue in New York City.
Large-scale computer manufacturers Control Data, Cray Research, Burroughs (now
part of Unisys) and Honeywell all are headquartered in or near Minneapolis,
Minnesota. Pharmaceutical and related companies…are based in the New
Jersey/Philadelphia area. (Porter 1990, p.155.)
Porter
explains such agglomerations in terms of his "diamond." Its four
corners are demand, factor conditions, rivalry-strategy, and industry clusters.
That is, an industry becomes internationally competitive because of
·
favorable home conditions in the markets it sells to,
·
the quality of its factor inputs,
·
the competitive pressures encouraging excellence within its
industry, and
·
the supplier and customer linkages specific to the industry,
which in practice are often traced out within specific urban agglomerations.
On this
last point, a tight geographical locale intensifies (1) information flows and
(2) rivalry between competing firms. Local media, banks, universities, bars,
and eateries enhance communication. The spatial proximity of rivals—whether
they communicate and cooperate or not—spurs competition and innovation. Trust between rivals does not enter into it.
In the
spirit of Porter’s emphasis on information flows, financial services in London
and New York City provide convincing evidence of the continuing value of face-to-face communication.
In a May
1998 article, for example Ben Edwards assessed London's staying-power as a
financial center. ("Capitals of Capital: Financial Centres Survey," The Economist, 347:8067, p. 8.) Some of
his analysis smacks of Marshall's writings a century ago on the industries of
northern England, highlighting the role of specialized skills. "Developing
financial markets requires a wide range of talents, and clusters make it easier
to co-ordinate them. Lawyers must ensure... Accountants must check.... As long as these people prefer to meet in
person to co-ordinate their work, there will be a need for financial
centres."
Even more to the point: "But even if business must be
done centrally, why do it next to your competitor?" (Edwards, p. 8.)
The answer
to this question, a matter of localization economies, not urbanization
economies, draws on Porter's theme of information flows. Being near your
competitors and mutual suppliers enhances your knowledge of their operations, a
prod to innovation on your part. It also permits raids on their employees, who
may have just the skills you are looking for. ("So, in New York, Wall
Street investment banks routinely poach credit analysts from their rating-agency
neighbors, Standard & Poor's and Moody's….")
Two distinct logics of location are emerging in London and
other financial centers. One image is hub-and-spoke. The image refers not to the relationships
between large and small firms, but to the location of activities within a firm.
"Hub businesses are centralised: strategic planning, project management,
product development, and risk-taking activities such as trading and cooking up
exotic financial derivatives. Spoke activities—such
as sales, marketing and company analysis—keep the business in touch with the
customer and with good information. With globalisation and improved
communication, spoke operations are becoming leaner."
The second location principle is to scatter whatever operations
can be scattered to lower-cost sites.
In a classic pattern reminiscent of Raymond Vernon's 1960 analysis of
New York City, back-office
(i.e., administrative and number-crunching) activities can be housed in remote
locations where wages and land rents are low and commuting is easy. Only the
functions requiring frequent face-to-face contact (mergers and acquisitions,
raising capital, fund management) must be kept in the center. A
mixed case is trading, which in the age of the Internet is up for grabs.
Two questions can be posed here about Porter’s
cluster analysis. One concerns the potential perils of clustering for member
firms, the other the role of government.
On the first matter, Porter himself now recognizes
that participation in an established cluster may not always help a firm adapt
to new circumstances. In this recent
passage, for example, it is hard to miss the influence of Porter’s Harvard
Business School colleague, Clayton Christensen (1997):
When
a cluster shares a uniform approach to competing, a sort of groupthink often
reinforces old behaviors, suppresses new ideas, and creates rigidities that
prevent adoption of improvements.
Clusters also might not support truly radical innovation, which tends
to invalidate the existing pools of talent, information, suppliers, and
infrastructure. In these
circumstances, a cluster participant….might suffer from greater barriers to
perceiving the need to change…. (Porter
2000, p. 24, emphasis added.)
This is a
pivotal issue. Proponents of cluster-based development strategies tend to
assume that fostering specialized clusters is good for an area’s growth
prospects. But students of industrial history might well differ.
After all,
what became of Marshall’s prototypical industrial district, 19th
century Manchester? The answer, in a phrase, is that “Industrial evolution is a
history of cruel fates.” (Rothschild 1973, p. 191.) Marshall’s “something in the air,” in other words, may have
become an obstacle to change.
The list
only begins with textiles in Manchester or steel in Pittsburgh, mature centers
that failed to meet the challenge of new competitors located elsewhere. (Chinitz 1961.) More recent episodes include
Boston’s Route 128 in the 1980s. Its minicomputer firms proved blind to the
need to move on to PCs. Similarly, in the Porter passage quoted earlier we find
Minneapolis cited as the home of Cray, Burroughs, and Unisys. But just as with
minicomputers, “big-iron” supercomputing proved to be a shaky base.
For both
Route 128 and Minneapolis-St. Paul what has proved decisive to future
development is the capacity to shift from dying bases to new sources of growth,
as given by universities and financial institutions at least as much as by
existing firms.
A second
ambiguity is Porter’s attitude toward government policy. On the one hand, he applauds state, local,
and national initiatives informed by cluster theory. (See Table 1 in Porter
2000, p. 31.) In his view, “clusters should represent an important component of
state and local economic policy.” (Porter 2000, p. 29.) And indeed they do. The
influence of cluster theory for policy design can be seen in this useful set of
links
on policies in individual states, as compiled by the Humphrey School of Public
Policy at the University of Minnesota.
But in the
same article, Porter takes pains to differentiate cluster strategy from
industrial policy—which is bad, he writes, because it entails picking winners,
a zero-sum game. “Although industrial policy aims to distort competition in
favor of a particular location, cluster theory focuses on removing obstacles….
The emphasis in cluster theory is not on market share but rather on dynamic
improvement.” (Porter 2000, p. 28, emphasis added.)
This will
strike some readers as a fine distinction.
To skeptics, cluster theory sometimes looks like a vehicle for state and
local government officials in search of a targeting rationale.
For example, Terry Buss offers “The Case Against Targeted
Industry Strategies.” His view:
“Targeted industry studies use poor or inappropriate data, deeply flawed social
science methods, and simplistic mathematical models in producing targets.
Targets themselves tend to be dubious” (Buss 1999, p. 343).
Why, Buss asks, are targeting strategies, including
cluster-based targeting, so widely practiced? Not because of their scientific
merit, but for political reasons. Impressive analytics can be drummed up on
demand to justify inherently political proposals. And why, when so many targeted industry strategies have failed,
do states and localities continue to rely on them? Partly because they have the appearance of scientific backing,
but mainly because of a herd effect. Once some states and localities develop
targeting strategies, others feel compelled to follow suit.
Implicit
in any such critique of targeting is the view that when it comes to
new-enterprise development, market forces provide the best mechanism for
picking winners and weeding out losers. Elementary as that proposition sounds,
it remains a useful touchstone for sorting out economic from political
dimensions in state and local economic development policies, including
cluster-based strategies.
Skepticism
about targeting is the context for Porter’s distinction between generalized
cluster strategies and local industrial policies. But what does it mean to say
as he does that a cluster-based strategy aims not for market share but for
“dynamic improvement”?
Static
spatial externalities depend on proximity among knowledge workers in a given
setting at a given time. “It is argued that knowledge for innovations resides
in the communication between skilled (knowledge) workers, and that this is
dependent on their geographical proximity.” In other words, as studies of
static externalities tend to confirm, “the capacity to receive knowledge
spillovers is influenced by distance from the knowledge source.”
(Echeverri-Carrol and Brennan 1999, p. 29.)
But while
the effects may register over time, the analysis can be viewed as inherently
static.
Nothing
that has been described in this module on neoclassical perspectives treats
history as anything but a prologue. To that extent, the conversation remains
open to other approaches, whether from evolutionary economics, path-dependency
perspectives, increasing-returns models, or network theories.
In
particular, what are dynamic agglomeration economies? How do they shape the
positions of competing centers of innovation? And how do they condition the
relative importance of proximity and long-distance networks?
Such
questions are explored in the companion module on post-neoclassical
cluster theories.