Conclusiones y discusión

There are many specialized business clusters in the world. The industrial district narrative concerns only some of those clusters in which cooperation between Wrms becomes an important aspect of the production, innovation, and market regulation processes. Before examining this narrative more closely, let’s clarify some basic concepts about clusters, and about cooperation between Wrms.

12.2.1. DEFINITIONS

A cluster, as I’ve used the term here, is a geographical agglomeration of business establishments in the same industry, or in related industries along a supply chain or related supply chains. Since property usually costs more in an agglomeration than it does outside of one, we assume that there is some beneWt to the business from locating in the agglomeration. We call these beneWts agglomeration economies. Hoover (1948) divided agglomeration economies into two types: urbanization economies are beneWts derived from locating in a diversiWed agglomeration, while localization economies are derived from locating close to businesses in the same industry, or along the same supply chain. Clusters, then, are taken as evidence of localization economies. I won’t deal with urbanization economies here; if you’re interested in cities in the context of international business, good places to start are Saskia Sassen’s Cities in a World Economy (2000), or the same author’s The Global City: New York, London, Tokyo (1991).

Michael Porter has done a lot to promote the concept of business clusters. Unfortu-nately, he hasn’t used the term in a consistent way. In The Competitive Advantage of Nations (1990), he said they were concentrations of interconnected companies, special-ized suppliers and service providers, Wrms in related industries, and associated institu-tions. Sometimes, he said, these clusters were also geographically concentrated, but he made a clear distinction between his concept of the cluster (which was not, then, a geographical concept), and the possibility that such a cluster might look like a cluster when plotted on a map. More recently he speciWes that clusters are

‘‘. . . geographic concentrations of interconnected companies, specialized suppliers and service providers, Wrms in related industries, and associated institutions . . .’’ (Porter 2000, p. 253;

emphasis added)

Even then, for Porter, ‘‘geographic concentration’’ is a very Xexible concept: a concen-tration might be conWned to a small city, or spread out over quite a large region. Ron Martin and Peter Sunley (2005) give him a lot of grief for this, but don’t propose any alternative.

Also, for Porter, ‘‘cluster’’ always means interconnected companies, so a bunch of companies clustered together geographically and which happen to be in the same industry is not, for Porter, necessarily a cluster. The interconnections which Porter requires to call something a cluster are similar to what others might require to call a spatial cluster an industrial district. For our purposes here, a geographical concentration of Wrms in the same or related lines of industry is a cluster, whether or not they do business with each other or have any other connections.

12.2.2. CLUSTERS EVEN WITHOUT TRUST: SIMPLE LOCALIZATION ECONOMIES

The reason for splitting this particular hair is that there are plenty of clusters in which the Wrms hardly relate to each other at all. Firms may cluster because there is some advantage to a particular location; in the city of Lampang, in northern Thailand, there are over a hundred ceramics manufacturers – largely as the result of natural deposits of clay. Of somewhat more interest are what we can call passive agglomeration economies:

beneWts from locating near to other companies in the same business. Recall, from Chapter 4, that this is a form of external economy. External economies in Marshall’s analysis of clusters included access to a pool of skilled labor and specialized suppliers;

the shared use of non-traded inputs, such as public infrastructure or services; and access to information or ideas – ‘‘knowledge in the air,’’ or what we might today call knowledge spillovers. Although these factors were not present when the Wrst ceramics factories were established in Lampang Wfty years ago, they now oVer additional reasons for ceramics manufacturers to locate there (Kamnungwut 2009).

184 THE GLOBAL ENVIRONMENT OF BUSINESS

Notice that there may also be external diseconomies to agglomeration: traYc conges-tion and air polluconges-tion are obvious examples, but there are also diseconomies that weigh directly against the purported beneWts of clustering: the Xip side of a pool of labor skilled specialized is the poaching of skilled staV by nearby competitors; knowledge in the air may be a beneWt to you, or it may be your trade secrets going out the window.

These issues are examined in detail by Ian Gordon and Philip McCann (2000).

12.2.3. COOPERATION AND TRUST

The neo-Marshallian industrial district model applies where Wrms beneWt not only from being close to each other, but from working together. But, actually, we Wnd Wrms beneWting from working together within specialized agglomerations that are not neo-Marshallian districts, as well as those that are. A neo-Marshallian district is distinguished by cooper-ation among SMEs, in the manner described in the previous section. In many clusters we have Wrms working together, but coordinated by one leading Wrm – the network of suppliers around Toyota or Boeing, for example; variants of this are referred to as the

‘‘solar’’ or ‘‘industrial complex’’ model. I’ll come back to issues growing out of the presence of one or two powerful companies within a cluster in Section 12.3. For now, I want to focus on the neo-Marshallian cluster, in which SMEs cooperate.

The purported beneWts of cooperation have been described in Section 12.1. BrieXy, we can classify them as the provision of public goods (e.g., common services in areas such as training; price- and wage-Wxing; political and regulatory advocacy on behalf of Wrms in the cluster), the creation of collective capacities (for instance, Marshall’s

‘‘industrial atmosphere’’ and ‘‘knowledge in the air’’ may not follow automatically from agglomeration, but may depend on the willingness of Wrms to share knowledge), and the reduction of transaction costs (if the conditions in the cluster somehow reduce the likelihood that Wrms will treat each other opportunistically, then greater use can be made of a division of labor between specialized Wrms). Sometimes, Wrms in clusters cooperate, sometimes they don’t. What leads to cooperation?

One source of mutual gains from repeated business is the fact that ‘‘Xexible’’ manufac-turers are never perfectly Xexible: there is often some transaction-speciWc investment. Mark Lazerson and Gianni Lorenzoni (2005) oVer an example of garment makers, who may require that the fabric for a particular line of clothing have a consistent appearance; having started the line with one fabric supplier, they then cannot change to another without a small but unacceptable change in appearance. Moreover, Lazerson and Lorenzoni argue, the equipment in industrial districts is not always Xexible, contrary to the picture presented by Piore and Sabel. Sometimes this is because old equipment remains in use, but at other times it is because, even within the range of output experienced by industrial district SMEs, the Xexible equipment has higher unit production costs than special-purpose equipment.

So, even within Xexible networks of SMEs, Williamson-type lock-ins exist, and with them the need to Wnd a governance mechanism for the transaction.

12.2.3.1. Repeated games

One way of approaching a problem is to think of the Wrms – a supplier and a customer, perhaps – as engaged in a repeated game. The prisoner’s dilemma game provides an abstract version of the problem. In this game, two players have a choice between cooperating and cheating. If the game is played just once, each of the two players will do better by cheating the other, with the perverse result that the potential mutual gains are thrown away. One solution to the problem is to bring in some form of third party enforcement – a contract that can be enforced in court, for instance. Yet this may not be necessary: if the two players think they are likely to do business again, cooperative behavior may emerge. Robert Axelrod’s The Evolution of Cooperation (1984) oVers an excellent introduction to this question.

The repeated game model obviously applies in a relatively small community of specialist SMEs: you are likely to meet the same player again, and will take this possibility into account. Moreover, there are factors at work in most such clusters that can strengthen the results of the repeated prisoner’s dilemma model. The model starts with the assumption that all you know about the other player is from your own previous meetings with that player; within a cluster, you are likely to know the player by reputation, even before you do business with her. In such settings, personal reputation becomes a form of capital. Dei Ottati (1994) argues for the importance of such reputational capital in the case of Prato. Moreover, the simple repeated game models typically assume that doing business again (or not) is a chance event; in practice, mutually beneWcial transactions lead to more business between the same partners:

Lorenz (1988) Wnds this in metalworking districts in both France and Britain, Uzzi (1997) and in garment manufacturing in New York.

The repeated game model also provides a useful way of thinking about cases in which cooperation does not occur. Mark Lazerson and Gianni Lorenzoni (2005) cite a study by Passaro (1994), of a leather tanning district in southern Italy in which much less interWrm contracting occurs than in districts in the same industry in Tuscany. Most of the Wrms in the southern district are vertically integrated – they take care of all of the relevant stages of production on their own, so they seldom need the help of other Wrms in the industry. This leaves little room for repeated games to develop.

12.2.3.2. Embeddedness and civic engagement

The standard game-theoretic approach treats each Wrm as a self-interested rational actor.

A diVerent approach is to see the choices made by each actor aVected by their social

186 THE GLOBAL ENVIRONMENT OF BUSINESS

environment. Some older traditions in sociology take this to extremes, and treat our actions as fully structurally determined – that is, they do away with ‘‘actors’’ altogether.

More recent work tries to get away from this, and to achieve some understanding of the interplay between the actor and the environment. Such an approach may help us to understand why cooperation emerges in some clusters and not in others.

Mark Granovetter (1985) sees us all as embedded in networks of social ties. These ties don’t strictly determine who we are or what we do, but they do shape us and constrain us. In some cases, they might even constrain us from cheating business partners. Robert Putnam (1993) uses Granovetter’s framework to help explain diVerences in economic performance (and, as part of this, the presence or absence of industrial districts) in diVerent parts of Italy.

Italian industrial districts are concentrated in north central and northwest Italy, and particularly in the regions of Emila-Romagna, Tuscany, and Veneto. Why there, in particular? For as long as the districts have been studied, there have been eVorts made to trace their origins to the political and social characteristics of this region. Bagnasco (1977) dubbed this area ‘‘the third Italy,’’ on the grounds that its industrial structure was distinct from both the northwest and the south. The name has stuck.

As a nation-state, Italy has existed only since 1860, and its diVerent regions bear the marks of their diVerent histories before the risorgimento. The Third Italy happens to coincide with the area which had the longest history of independent city-republics:

Florence, Pisa, Bologna, Venice, and suchlike. The northwestern areas of Piedmont and Lombardy had an early history of city-republican rule, but by 1300 were monarchies and later were absorbed for long periods by various foreign kingdoms, notably France, and Austria-Hungary. Areas to the south and east of Rome, including Naples and Sicily, were long ruled by Spain. Some areas near to Rome were ruled by the Pope, though the strength of papal authority varied.

These diVerent histories provide a good map of Italy’s socioeconomic system today. The Third Italy is home to the greatest concentration of industrial districts; in the 1970s and 1980s, as Xexible production eclipsed mass production, these regions grew rapidly and surpassed the northwest in per capita income. The northwest is also home to some industrial districts, but is far better known as the centre for business services (Milan) and mass production (Turin). The areas once ruled by Spain are by far the poorest, and their few clusters of industry generally do not share the characteristics of industrial districts.

Putnam found that political participation, involvement in voluntary civic organizations, attitudes toward government, and attitudes toward cooperation with political rivals were, generally, higher in the parts of Italy which had a long civic republican history, which is to say also those with prosperous industrial districts today; lack of participation, political polarization, and distrust, all were more prevalent in the south. Putnam’s contention is that the political and social variables he studied are measures of something he calls social capital, and that social capital contributes to economic performance. In this, he is drawing explicitly on Granovetter: businesspeople in the Third Italy are, he says, embedded in