G. M. PETER SWANN

Drawing on the literature review, the aim of this chapter is to set
out a simple model of clustering in high-technology industries
that forms the basis of the empirical analysis in the later chapters.
Much analysis of clusters has focused on the initial formative
stages, or what could be called the rise of clusters. In these forma-
tive stages there is an important positive feedback mechanism
which reinforces the development of clusters. But this positive
feedback rarely continues indefinitely. Within most clusters,
even the most successful, diminishing returns are liable to set in
beyond a certain point. This means that the rate of growth of the
cluster will start to decline. Eventually, indeed, the cluster will
stop growing, and start to decline. Most analysis of cluster-ing
tends to stop there: the cluster enters a phase of decline from
which there is no apparent recovery. But this is not the inevitable
outcome. In a few cases, clusters that reach maturity do not nec-
essarily then decline into oblivion. Some of them experience a
renaissance or revival in a new age with a new set of industries.

The first section of this chapter gives an overview of the
life cycle of the industrial cluster, beyond the rise described in
Chapter 2, through its fall and to its possible rebirth. Section 3.2
summarizes the advantages and disadvantages of clustering
from the perspective of the firm trying to optimize its location.
The next three sections (3.3 to 3.5) focus in more detail on each
of these phases. Section 3.6 describes the general structure of the
econometric models that are used for empirical analysis, while
sections 3.7 and 3.8 (and Appendix 3A) give details. Section 3.9
concludes.

-52-