Geography Reference
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develop the network perspectives deployed in parts of geography (for example, Castells,
2000; Taylor, 2003). It raises the question of whether the evolution of networks and
connections can be analysed in terms of changes in underlying generative rules. Second,
it suggests that the chreodic evolution of knowledge is the main reason why regional
economies and local economies show forms of path dependence (see Loasby, 2001).
Beinhocker (2006) proposes that human decision making is guided mainly by inductive
reasoning, so that condition-action (if-then) rules used in the past will be applied in
uncertain environments, and experienced mental models become resistant to change.
This, he contends, explains the inertia and elimination of established businesses. In
this view, the roots of path dependence in industrial clusters and regional economies
lie in human decision-making. At the same time, inertia is never inevitable because of
the diverse ways in which knowledge can change. As Ramlogan and Metcalfe (2006)
argue, innovation arises in combinatorial knowledge and that this has no rest points but
constantly undergoes chreodic change: 'It can undergo subtle changes as information
percolates across networks of relationships or it can undergo sweeping changes that take
understanding into entirely new dimensions. To this degree understanding is unstable'
(2006, p. 130). The origins of regional path creation may well lie in this instability.
Third, this knowledge-based perspective also implies that the most ef ective complex
systems are those that balance inertia and innovation. It is argued that if all the knowl-
edge and beliefs in an organisation are changing rapidly and simultaneously then it
proves impossible to exploit innovations. Complex organisations that have an interme-
diate mixture of inertia and innovativeness appear to have higher i tness (Hodgson and
Knudsen, 2006b). In Ramlogan and Metcalfe's words: 'If beliefs are too l uid, order will
descend into chaos; if beliefs are too rigid then order descends into lifeless equilibrium'
(2006, p. 118). The degree to which this also applies to regional and local economies is
an important research question. Are the most successful economies those that show the
highest rates of innovation, and highest rates of global and local search, or are they those
that are able to apply new innovations within relatively stable knowledge structures?
Fourth, the complexity paradigm also highlights some important challenges for con-
temporary economic geography relating to the importance of markets and personal
knowledge. In similar fashion to many cultural economic geographers, complexity
economists have recognised that knowledge exchange and connections fundamentally
depend on institutions and patterns of institutionalization. Institutional rules store
and communicate information and embody socially shared beliefs and understandings
(Ramlogan and Metcalfe, 2006). However, in contrast to much recent economic geogra-
phy, the complexity paradigm argues that markets play an essential and central role in
coordinating knowledge and driving the evolution of knowledge. They are a central and
distributed form of innovation system in modern capitalism. The growth of knowledge
and markets are mutually reinforcing processes as markets do not simply match but
continually reshape supply and demand. Selection processes are essentially market based
as they distinguish reliable from less reliable knowledge connections and are a means of
destroying some connections in favour of others. Markets also contain a great variabil-
ity of types of linkage and many l uxes of connections, some of which are stabilised. In
Potts' words: 'the market process is an experiment in knowledge: the creation of unfore-
seen compounds out of ephemeral elements that become obvious only after the event'
(2001, p. 422). This view implies that economic geography's recent focus on 'untraded
