Cluster effect

The cluster effect is the effect of buyers and sellers of a particular good or service congregating in a certain place and hence inducing other buyers and sellers to relocate there as well.

The Silicon Valley case

For example in the mid- to late 1990s, several successful computer technology related companies emerged in Silicon Valley in California. This led anyone who wished to create a startup company to do so in Silicon Valley. The surge in the number of Silicon Valley startups led to a number of venture capital firms relocating to or expanding their Valley offices. This in turn encouraged more entrepreneurs to locate their startups there.

In other words, venture capitalists (sellers of finance) and dot-com startups (buyers of finance) "clustered" in and around a geographical area.

The cluster effect in the capital market also led to a cluster effect in the labor market. As an increasing number of companies started up in Silicon Valley, programmers, engineers etc realized that they would find greater job opportunities by moving to Silicon Valley. This concentration of technically skilled people in the valley meant that startups around the country knew that their chances of finding job candidates with the proper skill-sets were higher in the valley, hence giving them added incentive to move there. This in turn led to more high-tech workers moving there.

Generalization

The cluster effect can be more easily perceived in any urban agglomeration, as most kinds of commercial establishments will tend to spontaneously group themselves by category. Shoe shops (or clothes shops), for instance, are rarely isolated from their competition.^{[citation needed]} Instead, it is much more common to find whole streets of them, even though there is hardly a reason for the grouping in that specific region.

The cluster effect is similar to (but not the same as) the network effect. It is similar in the sense that the price-independent preferences of both the market and its participants are based on each one's perception of the other rather than the market simply being the sum of all its participants' actions as is usually the case. Thus, by being an effect greater than the sum of its causes, and as it occurs spontaneously, the cluster effect is a usually cited example of emergence.

Governments and companies often try to use the cluster effect to promote a particular place as good for a certain type of business. For example, the city of Bangalore, India has used the cluster effect in order to convince a number of high-tech companies to set up shop there. Similarly, the city of Las Vegas has benefitted through the cluster effect of the gambling industry.

The cluster effect does not continue forever though. Its relative influence is also dictated by other market factors such as expected revenue, strength of demand, taxes, competition and politics. In the case of Silicon Valley as stated above for example, increased crowding in the valley led to severe shortage of office and residential space which in turn forced many companies to move to alternative locations such as Austin, Texas and Raleigh-Durham, North Carolina, even though they would have liked to stay in the valley. Much work has been done on attempting to identify economic clusters. Statistical methods have been used with a great deal of success.^[1] But the underlying problem often faced is the semantics involved in the subject, with many different authors citing numerous characteristics of a cluster.

Other examples of the cluster effect

• U.S. movie production in Hollywood
• The UK post-production industry in London's Soho district
• The US automobile production plants concentration in Detroit
• The Paris fashion's industry

Sources and Further Reading

Crawley, A. & Hill, S. (2007) "Establishing the Statistical Significance of Local Sector Concentrations of Economic Activity: A Comparative Analysis of Welsh Data" Conference paper at the 37th Annual Regional Science Association British and Irish Section.

See also

• Emergence
• Network effect
• Economies of agglomeration

References

1. ^ Crawley and Hill (2007)