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clusters that make them 'l uid spaces' (Mol and Law, 1994). Employing Darwinian prin-
ciples at a high level of abstraction, of which the evolutionary processes in the biological
and social realm are but specii c instances (Dennett, 1995), opens up opportunities for
exploring clusters as idiosyncratic social evolutionary systems in which macro-level insti-
tutions (MacKinnon et al., 2009) are as important as micro-level processes related to,
for example, politics (Bathelt and Taylor, 2002) or learning (Staber, 2009). The emerg-
ing view in research on clusters is that variability is a central, and often, useful feature,
produced by a dynamic mix of competition and cooperation, and framed by rules
and understandings that are continually contested and updated. Evolutionary theory,
grounded in culture rather than biology, can rei ne this view by adding improved expla-
nations of the processes of change, without neglecting patterns. Evolutionary explana-
tions shift focus from what a cluster is to how it is accomplished. As we move to a notion
of clusters as an ongoing accomplishment we need a notion of agency to match. In this
chapter, I suggested that an idea-based social constructionist approach of ers signii cant
explanatory leverage, in a way that cross-fertilizes dif erent variants of evolutionary
thinking with a systematic concern for the details of agentic orientation and action. The
challenge for researchers is to explore how ideational alternatives are constituted, how
the actors choose from a pool of ideas, and how the distribution of ideas in a bounded
system changes over time and across settings. As a general proposition, this would direct
researchers to expect a wider range of contingencies in agency. Cluster theorists would be
less concerned with deviation from a particular norm and more fascinated by variation.
To be useful for an understanding of cluster evolution, any variant of evolutionary
theory must achieve at least three objectives. First, it must explain the dynamics of how
cluster i rms and structures change over time. In doing so, it must recognize the underly-
ing variability of the components making up i rms and populations. In particular, it must
appreciate human agency, leaving room for cognitive diversity and discretionary possi-
bilities, and recognizing that human actors have both stable and l uid properties. Second,
it must show a systematic concern for the mechanisms that generate both persistence and
change, rather than merely describe statistical regularities. It must permit an analysis of
mechanisms with sui cient generality to be able to advance causal generalizations about
recurrent processes at all levels of action. And third, it must consider the ever-present
possibility that clusters evolve in ways that do not improve system performance or do
not serve the interests of all their members equally well. The explicit recognition of dys-
functional developments helps to avoid the functionalist reasoning evident in much of
the cluster literature. If one dei nes clusters by their purported functions, such as innova-
tion or knowledge sharing, there is the obvious need to explain the nonappearance of
functions as well. One would also need to suggest functional alternatives, as well as the
mechanisms by which evolutionary processes produce dif erent outcomes, both adaptive
and non-adaptive.
The focus on dif erent facets of agency, such as cognitive capacity and practices, helps
to protect against functionalist reasoning by showing that actors not only have various
kinds of ideas, often inconsistent and l eeting, but also routinely make mistakes in inter-
preting them and passing them on. Imperfections in idea transmission may not only
create new variation in the social system, but may also alter the intentions and under-
standings of individual actors in their ongoing dialogue with the situations unfolding
around them. Just because an idea is enacted on a sustained basis does not mean that it
