Geography Reference
In-Depth Information
organised structure that gives rise to these components. At one level, these twin concepts
would seem highly applicable to the economic landscape. Cities or clusters, for example,
would appear to be good examples of self-organised, autopoietic systems: as localised
economies, they comprise sets of components (i rms, institutions, infrastructures, people,
etc.) that generate outcomes (decisions, relations, daily behaviours, proi ts, incomes,
knowledge, and the like) that serve to reproduce the components that make up the city
or cluster. The emergence of positive localised externalities or agglomeration economies
might thus be interpreted in autopoietic terms, since they feed back to help reproduce
and maintain the economic components (i rms, workers, institutions) whose spatial jux-
taposition and inter-relationships create those very externalities. In this way, as organ-
ised (and dissipative) autopoietic systems, cities, clusters and particular types of regional
economy can remain stable for long periods of time despite people, goods, knowledge,
and money continually l owing into and out of them.
Yet there are also clearly problems using a self-organisation metaphor in economic
geography. First, there is the question of how valid it is to think of the economy of a city,
or cluster, or region in autopoietic terms. City and regional economies are not internally
coherent structures: certain components can be added or removed without necessarily
inl uencing the organisational stability of the city or region as a whole; many i rms may
have few if any links with other local i rms; and dif erent parts of the city's or region's
economy may function in dif erent ways, and be linked to the external environment
(external markets) in dif erent ways. In other words, self-organisation in the economic
landscape may not necessarily of itself equate with autopoietic dynamics.
Second, the basic assumption of distributed and dispersed control among system com-
ponents is clearly not applicable to many types of economic organisation such as cities or
regions. In fact, complexity economics says little about the power inequalities that exist
in all economic landscapes and strongly shape the selection of institutional and organi-
sational coni gurations. This has major implications, of course, as the assumption that
the connections and coni gurations that exist in economies have been selected for their
'i tness' by market processes and for their ability to maximise l ows of value, can yield a
remarkably uncritical view. In fact connections and linkages in the economy are likely
to be selected according to several dif erent criteria simultaneously, including the vested
interests of more powerful groups and their ability to channel and control these l ows.
Third, self-organisation is problematic as it is hard to identify mainly endogenous
dynamics when the boundaries of economic systems - such as regions and cities - are so
hard to identify. 16 Metcalfe, for example, argues that the economy self-transforms when
economic agents become dissatisi ed or concerned about their returns so that they search
for new ways of doing things and combine knowledge in new ways to produce new value
l ows. But it makes little sense to insist that these new bits of knowledge and problem
solutions are mainly internal to the economy as human learning is far too tangled and
unbounded for this. Furthermore, while markets may show forms of self-regulation and
coordination, it is clear that there are numerous institutional and political preconditions
which allow these coordinating ef ects to occur. 17
Fourth, there are further questions about the relationships between self-organisation,
connectivity and order in the economic landscape. Complexity theorists see self-
organisation as a critical balance between order and chaos, and, according to Potts
(2000), in the economic sphere the degree of connectedness is key to understanding the
Search WWH ::




Custom Search