Cambridge Journal of Regions, Economy and Society 2010, 3, 27–43
doi:10.1093/cjres/rsp029
Advance Access publication 6 January 2010
The economic resilience of regions: towards an
evolutionary approach
James Simmiea and Ron Martinb
a
School of the Built Environment, Oxford Brookes University, Oxford OX3 0BP, UK.
[email protected]
b
Department of Geography, University of Cambridge, Downing Place, Cambridge CB2 3EN, UK.
[email protected]
Received on May 17, 2009; accepted on November 23, 2009
In this paper, we review the different definitions of resilience and their potential application
in explaining the long-term development of urban and regional economies. We reject equilibrist versions of resilience and argue instead that we should seek an understanding of the
concept from an evolutionary perspective. After discussing a number of such perspectives,
we focus on the adaptive cycle model from panarchy theory to generate testable hypotheses
concerning urban and regional resilience. Two case study city-regional economies are used
to explore this model. We conclude that the evolutionary adaptive cycle model, though not
without problems, warrants further study as a framework for analysing regional economic
resilience.
Keywords: regional economic resilience, evolutionary theory, panarchy, adaptive cycles
JEL classifications: O14, O18, O33
Introduction
The recent interest in resilience has emerged in part
at least as a reaction to specific extraordinary events
and shocks that have prompted very particular types
of public policy response. Indeed, as Vale and
Campanella (2005) and Stehr (2006) point out,
the perceived source of a disaster can have a material impact on the forms and mechanisms of resilience, including, e.g., the scale and scope of state
response; rapid catastrophic disasters pose very
different policy and organisational challenges from
slow-paced and cumulative stresses (Foster, 2007).
Somewhat similarly, regional and local economic
development is far from a smooth and incremental
process but is subject to all sorts of interruptions
and disruptions: periodic economic recession, the
unpredictable rise of major competitors elsewhere,
unexpected plant closures, the challenges arising
from technological change and the like. How regional and local economies respond and adjust to
such disturbances and disruptions may well exert
a formative influence on how they develop and
evolve. The notion of ‘resilience’ would thus seem
to be highly relevant to understanding the process
and patterns of uneven regional development.
Of course this begs the question of what precisely we mean by regional and local economic
resilience. Partly as a result of its comparatively
Ó The Author 2010. Published by Oxford University Press on behalf of the Cambridge Political Economy Society. All rights reserved.
For permissions, please email: [email protected]
Simmie and Martin
recent emergence as an analytical concept there is,
as yet, no universally agreed definition of resilience
in economics or social science, let alone in regional
or urban studies. In fact, some even contest the
value of the notion of resilience altogether (Hanley,
1998). Some initial studies have recently appeared
that attempt to outline how the idea of resilience
might be defined in economics and in regional studies (e.g. Rose and Liao, 2005; Briguglio et al.,
2006; Foster, 2007; Pendall et al., 2008; Hill
et al., 2008; Ormerod, 2008), but this task is still
far from complete. Our focus in this paper, therefore, is to examine how the notion might be given
meaning in a regional or local economic context.
We have problems with what we might call ‘equilibrist’ definitions that restrict the idea of resilience,
explicitly or implicitly, to the ability of a system—in
our case a regional or local economy—either to
return to a pre-existing stable or equilibrium state
or to move quickly to a new one. While not denying
the value and possible relevance of such an equilibrist interpretation, our interest is much more in
how far and in what ways resilience can function
as an evolutionary concept. More specifically, we
are interested in the idea of resilience as ‘adaptive
ability’ since it is the differential ability of a region’s
or locality’s firms to adapt to changes and shocks in
competitive, market, technological, policy and related conditions that shape the evolutionary dynamics and trajectories of that regional or local economy
over time.
Thinking about regional economic
resilience
According to its strict Latin root, resilire, to leap
back or to rebound, the idea of resilience refers to
the ability of an entity or system to ‘recover form
and position elastically’ following a disturbance or
disruption of some kind. Most uses of the term in
regional or urban applications refer to this idea of
the ability of a local socio-economic system to recover from a shock or disruption. Thus, Foster
(2007, 14) defines ‘‘regional resilience as the ability
of a region to anticipate, prepare for, respond to,
and recover from a disturbance’’. Or again, Hill
28
et al. (2008, 4) see resilience as ‘‘the ability of a region . to recover successfully from shocks to its
economy that either throw it off its growth path or
have the potential to throw it off its growth path’’.
But beyond these rather broad statements, there
is much ambiguity. For one thing, should the notion
refer not just to a regional economy’s ability to recover from a shock but also to the degree of resistance to that shock in the first place? After all, a
regional economy that is hardly affected by a shock
is much more likely to recover, and more quickly,
than a regional economy that is severely weakened
or disrupted by the shock. That is to say, should
resilience also refer to the sensitivity or vulnerability of a regional economy to shocks? For another
thing, there is the issue of whether the concept
refers to the ability of a regional or urban economy
to retain its structure and function despite the shock
or disturbance to it or to the ability of a region or
urban system to change its structure and function
rapidly and successfully in response to a shock.
Often, the two senses are combined, as in Hill
et al. (2008, 4) where it is suggested that the resilience of a regional socio-economy refers to ‘‘the
extent that its social structure of accumulation
was stable or . the extent that it was able to make
a rapid transition from one social structure of accumulation to another’’. Then again, another issue is
that the resilience of a region’s economy is unlikely
to be invariant over time: it may depend on the
nature of the shock and may change over time as
the structure and nature of a region’s economy
evolves.
The ambiguity that surrounds the concept of regional economic resilience is compounded by the
fact that two definitions of the notion can be found
in the ecological literature, where the idea has perhaps been most debated. The first and more traditional definition, so-called ‘engineering resilience’,
concentrates on the stability of a system near an
equilibrium or steady state, where resistance to disturbance and the speed of return to the pre-existing
equilibrium are used to define the idea of resilience
(e.g. Holling, 1973; Pimm, 1984). This seems closest to the notion of ‘elasticity’ or the ability of a system to absorb and accommodate perturbation
The economic resilience of regions
without experiencing major structural transformation or collapse (McGlade et al., 2006). Under this
definition, therefore, regional economic resilience
would imply the retention of the region’s pre-shock
structure and function. The problem is that view
carries with it the baggage of equilibrist thinking.
Indeed, the notion of engineering resilience bears
a close affinity with the standard use of equilibrium
in mainstream economics. In this instance, a shock
or disturbance moves an economy off its equilibrium growth path, but the assumption is that selfcorrecting forces and adjustments eventually bring
it back onto that path (see Figure 1(a)). So the relative resilience of different economies would be
measured in terms of their susceptibility to being
moved off their equilibrium paths (their ‘sensitivity’ to shocks) and their response times of recovery
to equilibrium. The obvious problem with this definition is that if regional economic resilience is defined in terms of the ability of a regional economy
to retain (return to) its equilibrium form and function following a major shock, it becomes difficult to
reconcile the notion of resilience with the idea of
regional economic evolution. The implication is
that the more resilient is a regional economy, the
less it would change over time, even in the face of
various shocks. So, at best, this view of resilience
would yield an evolutionary model based on the
maintenance of structure and stability.
The second definition, so-called ‘ecological resilience’, focuses on whether disturbances and shocks
cause a system to move into another regime of behaviour. In this case, resilience refers to the magnitude of the shock of disturbance that can be absorbed
before the system changes its structure and function
and becomes shaped by a different set of processes
(Holling, 1973). According to some authors, this
definition opens up space for linking resilience with
the idea of adaptability and is thus much richer
in evolutionary scope (McGlade et al., 2006). But
the notion of ecological resilience is not unproblematic. If ecological resilience is measured by the
magnitude of the disturbance that can be absorbed
before the system changes structure, this seems to
Figure 1. Stylised Responses of a Regional Economy to a Major Shock.
Notes: (a) Return of region to its pre-existing steady growth path following the shock; (b) and (c) region fails to resume former steady
growth path after the shock, but settles on inferior path (d) region recovers from shock and assumes an improved growth path.
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Simmie and Martin
imply that the bigger the shock required to change
a system’s structure and function, the more resilient
that system would be deemed to be. So, again, a resilient regional economy would be one capable of
absorbing and accommodating extreme shocks
without any significant change to its form or function: we seem to be back to engineering resilience.
It is difficult to see how this view of resilience
imbues the construct with much evolutionary content.
If, on the other hand, resilience is interpreted in
terms of how well a system adapts its structure and
function in response to shocks, then, potentially,
this does indeed open up much more scope for
evolutionary analysis. But even here caution is
needed. McGlade et al. (2006) argue that resilience
‘‘is concerned with the role of instabilities in pushing a system beyond a threshold or bifurcation point
to a new stability domain’’ (149). The implication
seems to be that the evolutionary dynamic is periodic
in nature, in which episodic shocks cause a system to
adapt from one ‘regime of stability’ to another. It is
but a small step from this conception to the notion of
multiple equilibria used in economics, the idea that
there is no single unique equilibrium state or path of
an economy but several possible states or paths and
that an economy can be shifted from one such equilibrium to another by a shock. A resilient regional
economy would then presumably be one that adapts
successfully and either resumes, or better still
improves, its long-run equilibrium growth path (as
in Figure 1(d)). A non-resilient regional economy
would presumably be one that fails to transform
itself successfully and instead becomes ‘locked’ into an outmoded or obsolete structure, with a consequential lowering of its long-run equilibrium
growth path (Figure 1(c)).
Under this view of resilience, the argument would
seem to be that regional economic evolution follows
a process of ‘punctuated equilibrium’, a succession
of stable forms or steady growth paths the hysteretic
movement between which is triggered by periodic
shocks or major perturbations. But although the
notion of punctuated equilibrium is widely used in
discussions of biological and ecological evolution,
is it a valid or sufficient model of how economic
30
systems—national, regional or local—evolve? Indeed, are urban and regional economies ever in
any equilibrium? While ecological systems if left
undisturbed may, perhaps, attain equilibrium or stable states, economic systems are arguably different.
Economic evolution depends on the actions of individual economic agents, who can learn, innovate
and adjust their behaviour. For this reason, some
evolutionary economists would argue that economies can never be in equilibrium. As Ramlogan
and Metcalfe (2006) point out, economies are based
on and driven by knowledge, and knowledge never
stands still but constantly changes; thus economies
can never stand still—capitalism is inherently a restless process.
In fact, appeal to multiple equilibria would not
seem to be essential for developing the notion of
regional economic resilience. Certainly, regional
and urban economies exhibit stability and selforganisation. But, in line with the argument of
Ramlogan and Metcalfe (op cit), stability and selforganisation are not the same as equilibrium (see
also Martin and Sunley, 2006, 2007; Martin, 2010).
To our mind, from an evolutionary perspective, the
important attribute of regional economic resilience
is the adaptive capacity of a local economy. What
matters for the long-run success of a regional economy is the ability of the region’s industrial, technological, labour force and institutional structures to
adapt to the changing competitive, technological
and market pressures and opportunities that
confront its firms and workforce. What we have
in mind is akin to what Schumpeter referred to as
the notion of industrial ‘mutation’ that takes place
via a process of ‘creative destruction’. And as
he emphasised, industrial mutation (creative destruction) can occur both more or less ‘incessantly’
and also in rushes (gales of creative destruction).
How regional economies adapt to major shocks
thus remains of central importance; but how
regional economies respond to major shocks, such
as deep recessions, may itself be the product of
a slower, more cumulative process of adaptation
or ‘resilience building’. Put another way, any
convincing theory of regional economic resilience
must explain how a regional economy’s resilience
The economic resilience of regions
evolves as well as how its resilience impacts back
on that economy’s evolution.
Recently, some resilience theorists have begun to
move closer in this direction of an evolutionary
perspective and to consider the nature of constantly
changing non-equilibrium systems (see Carpenter
et al., 2005). Here resilience is considered as an
ongoing process rather than a recovery to a (preexisting or new) stable equilibrium state. This shifts
the theoretical analysis from questions about how
a system such as an economy is resilient to how it
adapts through time to various kinds of stress. Such
an approach does not require any necessary assumptions about equilibria and instead seeks to
understand constant change rather than stability
(Pendall et al., 2008, 127).
Regional economic resilience as an
evolutionary process: in search of
a conceptual framework
Linking the notion of regional economic resilience
to that of adaptation, and setting the analysis within
an evolutionary perspective, opens up a wide range
of possible approaches. At least four conceptual
frameworks for constructing an evolutionary account of regional economic resilience and adaptation
can be distinguished: Generalised Darwinism
(which emphasises variety, novelty and selection);
path dependence theory (which focuses on historical
continuity, ‘lock-in’ and new path creation); complexity theory (which highlights self-organisation,
bifurcations and adaptive growth) and panarchy
(which explicitly links resilience and ‘adaptive
cycles’). Though distinctive, there are certain points
of overlap between these frameworks.
An approach that draws on Generalised Darwinism would put particular stress on the role of variety
in shaping regional economic resilience, e.g. in
terms of structural (sectoral) variety and variation
in firm behaviour, including the differential adaptability of local firms. Adaptability is about the potential to adjust to changing circumstances in an
appropriate way. As Toulmin (1981) points out,
there are three basic mechanisms by which an entity, such as a local firm, can change to become
better adapted. One is the intentional response to
the perception of circumstances; a second is homeostatic, the automatic following of specific rules in
relation to target behaviours and a third is developmental, the cumulative unfolding of new behaviour
patterns (such as innovation) within a specific set of
constraints.
Variety might be expected to influence regional
economic resilience and adaptability in several
ways. In regional economics, the degree of local
sectoral variety (diversity) is often claimed to influence the vulnerability of a regional economy to
exogenous shocks, with regions having a more diversified economic structure being less prone to
shocks, or at least more able to recover from them,
than more economically specialised regions, which
are not only prone to idiosyncratic sector-specific
shocks but lack the breadth of economic activity to
offset such adverse disturbances. Sectoral variety is
also alleged to influence innovative activity among
local firms, though opinion is divided on whether
a diversified industrial structure is more conducive
to innovation than a specialised structure (the ongoing debate over the Jacobsian versus Marshall–
Arrow–Romer theories). In its turn, innovation is
key to the generation of local economic variety. The
importance of variety for understanding regional
economic resilience is that the existence of variation of types of firm and of firm behaviour in a region operates in conjunction with the mechanisms
of firm selection (the competitive survival or failure
of firms) to impart adaptation of the regional
ensemble of firms as a whole over time.
How the notion of path dependence—itself problematic (see Martin and Sunley, 2006; Martin,
2010)—bears on the question of regional resilience
and adaptation is open to different interpretations.
One of the key features of standard path dependence theory is the notion of lock-in, the process
whereby an economy—say a regional economy—
becomes ‘locked into’ in a particular trajectory of
economic development through the operation of
self-reinforcing localised increasing returns effects.
In the canonical account of this model (e.g. David,
2005, 2007), the assumption is that an external
shock is required to ‘de-lock’ the economy from
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Simmie and Martin
this path (in David’s work, such a path is assumed
to be one of a number of possible multiple equilibria). So one interpretation might be that a regional
economy is resilient if it is able to maintain its
‘locked-in’ development path even when disturbed
by an external shock of some kind: lock-in is thus
seen as a positive attribute of a regional economy.
This is akin to the notion of engineering resilience
discussed above. A different interpretation, however, would be to regard lock-in as a negative attribute, as holding back the adaptation of the regional
economy to a shock. The implication in this instance is that path-dependent lock-in undermines
a regional economy’s resilience. Whether a regional
economy suffers from ‘negative lock-in’ thus becomes an ex post matter, evident once a shock
has occurred (see also Setterfield, 1997).
There is a third way in which path dependence
might be useful in conceptualising regional economic resilience and one that has a closer bearing
on the issue of adaptation. Standard path dependence theory has relatively little to say about where
paths of regional economic development come
from, how they arise. Indeed, the typical assumption is that such paths originate in random, happenstance events—hence, the frequent argument that
path dependence is concerned with how random
or adventitious events can shape the course of history. But there is both good empirical evidence and
strong conceptual grounds for arguing that new
paths are often shaped by old paths (see Martin
and Sunley, 2006; Simmie et al., 2008; Martin,
2010). The emergence of a new local industry
may not be due to ‘chance’ or ‘historical accident’
but stimulated or enabled—at least in part—by the
pre-existing resources, competences, skills and
experiences inherited from previous local paths
and patterns of economic development. These
inherited conditions shape the environment in
which purposive or intentional experimentation
and competition occur among local agents (or
shapes its attractiveness to agents from elsewhere).
Contrariwise, in other places—precisely for reasons
arising from the specifics of their past economic
development—the local environment may be less
conducive to, perhaps even a ‘constraining’ force
32
on, the emergence of new technologies and industries. This might arise, e.g., because the specific
inherited knowledges and resources are not easily
recombined or converted into new competences
(Maskell and Malmberg, 2007) or because of their
previous success, existing industries have bid up
local land rents, prices and wages to levels that deter
new entrepreneurial activity (Brezis and Krugman,
1997). Path dependence may thus act to enable or
constrain regional economic adaptation in response
to a shock.
While these ideas from Generalised Darwinism
and path dependence theory certainly provide some
scope for thinking about regional economic resilience as adaptation, they by no means exhaust the
range of possible approaches. In fact, the logical step
is to turn to those theoretical frameworks that attempt to deal explicitly with the evolutionary dynamics of complex adaptive systems. There are
strong grounds for arguing that regional economies
represent complex adaptive systems with emergent
patterns of behaviour and organisation. Complex
adaptive systems are characterised by several key
features (Martin and Sunley, 2007). Typically such
systems have functions and relationships that are
distributed across system components at a whole variety of scales, giving the system a degree of connectivity. The boundary between a complex adaptive
system and its environment is neither fixed nor easy
to identify, making operational closure difficult, and
the system subject to constant exchange with its environment. Complex adaptive systems are characterised by non-linear dynamics because of complex
feedbacks and self-reinforcing interactions among
components, with the result that they are often characterised by path dependence. They are also characterised by emergence and self-organisation: i.e. there
is a tendency for macroscale structures and dynamics
to emerge spontaneously out of microscale behaviours and interactions of system components. And
this same process of self-organisation imbues complex systems with the potential to adapt their structures and dynamics, whether in response to changes
in the external environment (e.g. external shocks), or
from within through co-evolutionary mechanisms or
is response to ‘self-organised criticality’.
The economic resilience of regions
Certain implications are claimed to follow from
these features. Of particular relevance to the idea of
regional economic resilience is the argument that
complex adaptive systems are characterised by
two conflicting tendencies: on the one hand, there
is tendency in such systems towards increasing connectedness and order (or interrelatedness) among
system components; but, on the other hand, increasing connectedness and order tend to reduce the
adaptability of the system to changes in environmental conditions. This implies that there is
a trade-off or conflict between connectedness and
resilience: the more internally connected is a system, the more structurally and functionally rigid
and less adaptive it is.
The ecological model of ‘adaptive cycles’ seeks
to reconcile this contradiction or conflict through
the idea of ‘panarchy’, a model that posits a fourphase process of continual adjustment in ecological, social and environmental systems. Each phase
is characterised by varying levels of three dimensions of change: (i) the potential of accumulated
resources available to the system; (ii) the internal
connectedness of system actors or components and
(iii) resilience, a measure of system vulnerability to
shocks disturbances and stresses, with high resilience associated with phases of creative and flexible
response (Petersen, 2000; Holling and Gunderson,
2002; Pendall et al., 2008). Translated into a regional economic context, the accumulated resources would include the competences of individual
firms, the skills of local workers, institutional forms
and arrangements, physical and soft infrastructures
(such as business and work cultures) and the like:
these of course would depend on previous forms
and structures of economic and social development
in the region. Internal connectedness would relate
to patterns of traded and untraded interdependencies among local firms, including supply inputs,
horizontal interfirm divisions of labour in production, local networks of trust, knowledge spillover,
formal and informal business associations, interfirm
patterns of labour mobility and so on. These likewise would be shaped by previous economic developments in the region. Creative and flexible
response would depend on the innovative capacity
of local firms, on entrepreneurial capabilities and
new firm formation, institutional innovation, access
to investment and venture capital, willingness of
workers to reskill and similar factors.
The adaptive cycle model applied to a regional
economy might take the form shown in Figure 2.
The cycle has two loops: one relating to the emergence, development and stabilisation of a particular
economic structure and growth path (exploitation to
conservation) and another relating to the eventual
rigidification and decline of that structure and
growth path and the opening up of new potential
types of activity and growth sources for exploitation
(release and reorganisation). Pendall et al. (2008)
describe the movement between these phases in
a regional economy in the following way. In the
exploitation phase, regional growth develops and
productive, human and knowledge capital are accumulated as new local industries exploit comparative
advantages and various external economies of
localisation. But as this growth continues, the connectedness between the various components of the
regional economy increases, and the pattern of development becomes increasingly rigid: its resilience
to potential shocks declines (Figure 3). Thus if such
Figure 2. A four-phase adaptive cycle model of regional
economic resilience.
Source: Adapted from Holling and Gunderson (2002) and
Pendall et al. (2008).
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Simmie and Martin
Figure 3. Resilience as a process: variations in resilience across the adaptive cycle.
a shock occurs, structural decline and loss of
growth momentum are likely to follow. Firms close
or move out of the region, the degree of connectedness declines and agglomeration of localisation
economies lose their impact. Old patterns of production and institutional form unravel and resources are released. This opens up the possibility for
a second release–reorganisation loop, characterised
by innovation, experimentation and restructuring,
as new types of activity begin to emerge. Connectedness is low, the potential for the creation of new
paths high, the trajectories of development open,
and thus resilience high. As the particular forms
of new activity and new technologies are exploited,
new comparative advantages develop and a new
round of regional growth and accumulation is set
in motion.
A further, interesting feature of complex systems
under this panarchy model is linkages across scales—
across both time and space—through two principal
mechanisms. Larger scales affect smaller ones (akin
to downward causation or ‘supervenience’ in some
theories of emergence in complex systems), with longer term, region-wide processes and features (such as
local government, the region’s educational system,
physical infrastructures, etc.) shaping if not determining interactions and outcomes at smaller scales
(i.e. at the firm level). But smaller scales also act
back on larger scales, particularly during the release
phase. The resilience of a regional economy thus
depends both on the longer term, region-wide pro34
cesses and on shorter term more microscale processes
and on how these interact. For example, a failure of
a region’s workforce to upgrade its educational attainment and skill levels may hinder the local emergence of new firms orientated to new technologies
and new types of worker. In addition, conditions in
the national economy can affect those in regional
economies. A national recession can adversely affect
conditions in different regional economies. Or again,
national policies to promote entrepreneurship and
new business formation can impact on a locality’s
economic structure. And of course competitive pressures or knowledge transfers originating at the
international and global levels can stimulate local
economic change. So local variety and novelty can
be generated by processes operating at a whole range
of spatial scales.
The panarchy model of adaptive cycles is obviously highly suggestive. It has the advantage of
linking key attributes and processes of regional development, such as innovation, the dynamics of
capital accumulation and the mechanisms that generate connectedness between and among local firms
and institutions, with the notion of resilience and of
emphasising the need to examine how the processes
and mechanisms at different scales. But the model
is not without limitations and unresolved problems.
It is important to remember that the model was developed to analyse ecological systems, the evolution
of which may well be adequately conceptualised as
long periods of stability, even stasis, interrupted by
The economic resilience of regions
major external shocks. Is this a reasonable conceptualisation of how regional economies evolve?
Regional economies consist of collections of agents
and institutions that learn and can change their behaviour even in the absence of major shocks or disturbances. Further, the adaptive cycle approach to
understanding resilience implies that regional economic development has an ineluctable, inner logic:
that regional development necessarily follows the
phases that are argued to characterise adaptive
cycles and that the evolution of a regional economy
can be adequately represented in terms of such
cycles. The fact is that the adaptive cycle model
functions as a conceptual framework rather than
as a theory or a set of testable hypotheses. As Swanstrom (2008) argues, ultimately, the value of the
panarchy conceptual framework for studying regional economies for will rest on its ability to suggest new hypotheses about regional economic
resilience that can be tested by empirical case
studies. It is to some initial steps in this direction
that we now turn by briefly examining two contrasting examples of city-regional development
and adaptation.
Empirical exploration: two city region
case studies
To explore how the adaptive cycle model might
help to think about regional economic resilience,
two UK city regions were selected that have experienced quite different economic histories and outcome over the past 40–50 years. The city region of
Cambridge is widely regarded as one of the UK’s
most successful innovative, high-tech and knowledge-based local economies. It is the type of economy that might be expected to be adaptable and
resilient. The city region of Swansea, on the other
hand, has had a quite different industrial history to
that of Cambridge and has struggled to recover
from the loss of its former economic role and to
adapt to the changes taking place in the national
and global economy.
Adaptation in city-regional economies might be
expected to take years if not decades. We therefore
sketch the economic changes that have taken place
in these two city regions (defined in terms of travelto-work areas) from the 1960s until the late-2000s
(see Table 1), and attempt to categorise these
changes and developments into the four phases
postulated by the panarchy model summarised in
Figure 2. Over this time, the high-tech economy
of Cambridge developed through what can arguably be identified as three phases of the adaptive
cycle model: from the reorganisation of the local
economy around a new high-tech development path
through a phase of exploitation and growth to
a phase of conservation. In contrast, the Swansea
economy appears to have experienced six phases,
as it first lost its traditional mining industries, turned
to foreign direct investment (FDI) in electronics and
subsequently lost that as well. Further, over this 40year period both economies were subject to external
‘slow-burn’ stresses such as changes in markets,
technology and policy regimes. In addition, they
were also confronted by the shock of two national
economic recessions (early-1980s and early-1990s).
Of particular interest is how far the resilience of the
two city regions to these major downturns can be
explained in terms of the adaptive phases described
by the panarchy model.
As Table 1 shows, in the 1960s and 1970s, the
Cambridge economy was going through an historical reorganisation in the composition and orientation of its economy. The transition from being
a service-based market town and home to one of
the UK’s foremost universities to a high-tech, highgrowth and innovative economy began around
1960 with the formation of Cambridge Consultants
by a group of newly graduated scientists and engineers from the university. It was followed nearly
a decade later by the Mott report that recommended
the establishment of a science park, for which planning permission was granted in 1971. In contrast,
during the 1960s, the Swansea economy was experiencing a major phase of release and decline. By
the beginning of the 1970s, many of the area’s traditional mining industries (coal, iron, copper, tin
and zinc) that had formed the basis of its former
economic development were in steep decline or had
already closed. These closures were driven by international competition in the availability of raw
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Simmie and Martin
Table 1. Adaptive cycles in the Cambridge and Swansea city region economies, 1960–2005.
1960
1969
1970
1971
Cambridge
Swansea
1 Reorganisation phase
‘Cambridge Consultants’ formed, by group of newly
graduated scientists and engineers from the university
Mott report published, recommending the founding of
a Science Park
Decision by Trinity College to develop the country’s
first Science Park
Outline planning permission granted for Cambridge
Science Park
1 Release phase
Decline of local extractive industries
1973
1976
First company, Laser-Scan, moved onto the Science Park
1979
By end of 1970s, around 25 companies located on the
Science Park
National recession trough
1980
1981
1985
2 Exploitation phase
‘Cambridge Phenomenon’ report published by SQW
1987
St John’s Innovation Centre establishedUniversity
publishes its first IP policy for Research Council
funded research
1991
1993
National recession trough
During 1990s, cluster of hi-tech companies in the
Cambridge area grew to around 1200 companies
employing around 35,000 people
2 Reorganisation phase
FDI by Sony electronics factory at Bridgend
WDA established
FDI by Japanese electronics firms including
Hitachi and Panasonic
Last coal mine closed in Swansea County
UK’s first Enterprise Zone designated in Swansea
3 Exploitation phase
FDI in consumer electronics, e.g. Hitachi and
Panasonic
4 Conservation phase
5 Release phase
Loss of competitiveness based on low cost labour
Planned LG investment does not arrive
1996
1997
1999
2001
2004
2005
Post-2005
3 Conservation phase
Eastern Region Biotechnology Initiative established
Cambridge Network formed, as a voice for the hightechnology business communityGreater Cambridge
Partnership formed
University revises its IP policy for externally funded
research Cambridge Angels group formed
Cambridge Science Park now home to more than 70 R&D
companies on the 152-acre site, including new clusters
such as photonics, nanotechnology and materials science
New IP policy adopted by the university
WAG formed
Technium Programme launched
Publication of ‘Swansea 2020’, economic
regeneration strategy for the city
Slow down of innovation and growing concern over
growth momentum of high-tech cluster
materials and more efficient production processes
elsewhere. The closures released a pool of lowskilled, low-wage labour onto the local labour
market.
36
6 Reorganisation phase
In Cambridge, the 1970s saw the continuation of
reorganisation with the establishment of several
new high-tech enterprises and the emergence of
an identifiable high-tech cluster. The first company,
The economic resilience of regions
Laser-Scan, moved onto the new Trinity College
science park in 1973, and by the end of the
1970s, the reorientation of the Cambridge economy
around high-tech activity was well underway, with
some 30 companies located on the park. They were
mainly based on IT activities, specifically electronic
equipment and instruments. The 1970s also saw the
Swansea economy beginning to embark on a phase
of reorganisation. With the closure of its traditional
mining industries, it was forced by international
competition to seek new forms of economic activity.
It did this by turning to FDI and offering relatively
cheap land and labour. One of the first significant
inward investments in the electronics industry was
the Sony facility in Bridgend in 1973, east of Swansea. This was the first major Japanese investment in
Wales and acted as a catalyst for other inward
investors, particularly in the electronics sector.
Both economies were then subject to the external
shock of the deep national recession of the early1980s. By the onset of the recession the structure of
both economies had evolved significantly from
what they had been in the 1960s. According to
the adaptive cycle model outlined in Figure 2
above, the structural reorganisation occurring in
both economies should have led to increasing resilience to external shocks. But the two economies
reacted rather differently to the shock of the recession. Figure 4 shows how the employment growth
paths of the two city regions were affected. Just
prior to the downturn, the two city regions had
almost identical employment levels (around
215,000). The recession impacted much more severely on the Swansea economy than it did on Cambridge, and the latter recovered much more strongly
and quickly than the former. Indeed, in Swansea
employment had not fully returned to its 1980s
level even a decade later.
One of the main differences in the resilience of
the two economies following the shock of the recession can be seen in the changes taking place in
manufacturing employment (Figure 5). In Cambridge, manufacturing employment declined
slightly during and after the recession but it soon
recovered and by the mid-1980s had exceeded its
1980 level. By way of contrast, following the re-
cession, manufacturing employment in Swansea
showed no signs of regaining its pre-1980 level.
The shock of the early-1980s recession exposed
the different nature of adaptation and resilience in
the two case study economies. The steady marketled development of innovation, high-tech small and
medium sized enterprises and early cluster development in Cambridge over the 20 years from 1960
did seem to provide it with the resilience to weather
the industrial downturn of the recession. In contrast,
by the late-1970s, the economy of Swansea had not
been able to reorganise its economy sufficiently to
be able to withstand the impact of the recession.
The extent of restructuring based on the introduction of medium-sized FDI branch plants was not
sufficient to provide it with the sort of economic
base to survive the shock of the downturn, and its
manufacturing base not only declined faster but
also failed to recover. The evidence suggests that
the Swansea economy was noticeably less resilient
than its Cambridge counterpart.
Following the early-1980s recession, the economies of both Cambridge and Swansea entered
a growth phase based on the exploitation of their
existing industries. In the case of Cambridge, the
foundations proved to be far stronger than those in
Swansea. In Cambridge, the rate of high-tech new
firm formation increased significantly and was
marked by the creation of new pathways by branching out into life sciences and in particular biotechnology. This was driven by a mixture of endogenous
cutting-edge university research and organic growth
within the sector. The Swansea economy for its
part became increasingly reliant on the external
knowledge brought into the area by foreign-owned
electronics companies. Encouraged by the Welsh
Development Agency, in addition to Sony, multinational companies such as Panasonic and Hitachi
opened branch plants in the area. At the height of
this phase, some 50% of televisions and 75% of
video cassette recorders (VCRs) produced in Europe
were made in south Wales, located mainly in and
around Swansea.
This success led to a certain degree of conservation in the local Swansea economy, in the sense this
notion is used in the panarchy model. The branch
37
Simmie and Martin
Figure 4. Employment growth paths in the two city regions, 1980–2008.
Source: Cambridge Econometrics.
Figure 5. Manufacturing employment growth paths in the two city regions, 1980–2008.
Source: Cambridge Econometrics.
plants became locked into the technologies distributed to them by their Japanese-owned parent companies. Although this marked a temporary period of
stability, it was also characterised by increasing ri38
gidity in an industry driven globally by rapid technological change, which in the case of Swansea’s
production plants was in the companies’ research
laboratories located back in Japan. This local
The economic resilience of regions
technological lock-in and external dependence reduced the resilience of the local economy and soon
proved fatal to the survival of the consumer electronics industry in the Swansea area. The run up to
the 1991 recession saw the international demise of
both cathode ray tube (CRT) technology-based television and VCR-based recording devices. Sony
closed one of its Swansea plants, moving production to Barcelona where local expertise in the new
digital and plasma technology helped them respond to the changing market. This was followed
after the recession by the eventual closure of the
Panasonic and Hitachi manufacturing plants. All
that remains in Swansea today are retail outlets for
the products of these companies that are manufactured elsewhere.
The early-1990s recession impacted on both economies, as shown in Figure 3. Both areas experienced
a sharp contraction in manufacturing employment
(Figure 5), but Cambridge once again proved more
resilient, with a recovery in jobs in those sectors, at
least up to 2000. In Swansea, manufacturing employment failed to recover at all: the contraction proved
permanent. And the slowdown in service employment
growth during the recession continued until the late1990s. Only then did steady growth in this sector take
place (Figure 6). In Cambridge, although the recession halted the rapid expansion in service jobs that
occurred over the 1980s, the interruption was short
lived, and from 1992 onwards, the economy resumed
strong employment growth in this sector.
One of the key contributions to the relatively
higher adaptability and resilience in the Cambridge
economy was the ability to continually branch out of
the existing specialised industrial sectors. New development pathways were created out of a strong
endogenous knowledge platform grounded in advanced mathematics and computing. The 1990s
saw a continued growth in the high-tech economy
of the city region, with a strong upward rise in the
number of new firms formed each year (Figure 7),
and the formation of several new subcluster specialisms, including ink-jet technologies, telecoms, biosciences, informatics and clean technologies. By the
end of the decade, the high-tech cluster comprised
more than 300 such enterprises, employing perhaps
Figure 6. Service sector employment growth paths in the two city regions, 1980–2008.
Source: Cambridge Econometrics.
39
Simmie and Martin
Figure 7. Number of new firms established in the Cambridge high-tech cluster, 1970–2004.
Source: Library House.
as many as 20,000 people. There is some sign, however, that this phase of exploitation, rapid expansion
and accumulation of high-tech assets, may possibly
have come to an end and that local high-tech development may have entered a conservation phase of
distinctly slower growth. Both the rate of new firm
formation and the rate of innovation have slowed
appreciably since 2000, and local business leaders
and associations have expressed repeated concern
that the cluster seems to have lost its momentum.
The Swansea economy fared much less well following the early-1990s recession. The flow of FDI
that had begun to provide the possible basis for
a new phase of exploitation and growth ceased
and promised additional arrivals of overseas investments, such as that by the electronics giant LG, did
not take place. It is arguable whether the economy
ever embarked on a secure or sustained path of
exploitation and growth based around a new consumer electronics industry. Rather, it would seem
that this potential development path failed before it
really took off, and as a result the economy moved
quickly to a further phase of release and decline.
The FDI withdrew and the ability of the local econ40
omy to adapt to these changes was hampered by lockin to a culture of industrial subsidies dependency and
an expectation of lifetime employment in traditional
industries. This combination proved too difficult to be
overcome by free market adaptations. Instead it has
required intervention by the Welsh Assembly Government (WAG) to develop a public strategy to move
Wales (and Swansea) up the value chain, by focusing
development on the knowledge economy.
Since the end of the 1990s, in line with this wider
regional strategy, a new attempt to reorganise the
Swansea economy has been underway, initially based
on the provision of start-up incubator and support
units, an initiative called Technia, in partnership with
the Welsh Development Agency (now incorporated
into the WAG) and Swansea University. The implementation of this strategy has been slow, however,
and the first Technium was not opened in Swansea
until 2001. There are currently a total of nine across
Wales. Their aim is to provide infrastructure and business support to new innovative companies and to provide space for them to develop their ideas and grow
into successful knowledge-related businesses. The
scale of each Technium is quite small. Each of them
The economic resilience of regions
contains around only 10–12 firms. How resilient the
two city region economies will prove to be to the deep
recession of 2008–2009 remains to be seen.
Summary and conclusions
In this paper, we have sought to review and analyse the concept of regional economic resilience.
Our starting position is a rejection of equilibrist
approaches. This is because we think that the
firms, organisations and institutions that comprise
regional economies are continually changing
and adapting to their economic environments.
These changes are increasingly driven by the creation, acquisition and commercial exploitation of
new knowledge. These processes are never in
equilibrium.
Following these arguments, we turned to an evolutionary theoretical perspective. This emphasises
adaptation and change as key processes in the development of regional economies. We argue that
these processes are the bases of regional economic
resilience. For the purposes of this paper, we explored the applicability of the panarchy model, developed in ecological science, for further analysis
and developed a four-phase adaptive cycle model of
regional economic resilience. This postulated that
adaptation in regional economies follows a sequential cycle of innovation and restructuring, growth
and the seizing of opportunities, stability and increasing rigidity, followed by a release phase and
eventually the repetition of the cycle over various
periods of time. Each phase of the cycle is associated with different degrees of resilience, connectedness and capital accumulation or release.
It should be stressed that this is primarily a descriptive model and does not contain any theoretical
explanations of the causes of each phase of adaptation nor what drives an economy from one phase to
the next. To illustrate possible explanations for such
adaptation and change, we turned to two contrasting case studies. These were selected according to
their presumed illustration of contrasting degrees of
adaptation and resilience.
What we found was that over the 45-year period
of study, the Cambridge high-tech economy would
appear to have gone through only three phases
suggested by adaptive cycle model: reorganisation,
exploitation and possibly the onset of conservation. It arrived at each of the two major recessions
covered by this study having developed its resilient
capacity over the preceding one or two decades.
The long-term development of adaptive and resilience capacities in Cambridge were driven by the
conscious decisions of local entrepreneurs making
use of endogenously created new knowledge. This
was facilitated by the co-evolution of the attitude
of Cambridge University to commercial exploitation of intellectual property rights and the facilitation of the development of science parks and
incubation units on land owned by the different
colleges.
The experience of Swansea has been quite different and far less successful. The Swansea economy
seems to have gone through one and a half cycles of
the model. The first cycle, starting around the
1960s, saw the decline of the traditional extractive
industries and the loss of their endogenous knowledge base. This was followed in the 1970s by the
beginnings of reorganisation driven by the conscious decisions of public policy and based on the
attraction of FDI in the form of Japanese consumer
electronics. The FDI brought with it sufficient codified external knowledge for the establishment of
manufacturing branch plants based on VCR and
CRT technologies. According to the adaptive cycle
model, this reorganisation phase should have been
accompanied by increasing resilience. This did not
prove to be the case. The shock of the early-1980s
recession led to a decline in manufacturing employment from which the Swansea economy never fully
recovered. The exploitation of foreign-owned electronics was resumed after the recession, again
driven as much by public policy as by market
forces. This sector then entered a short conservation
phase becoming locked into increasingly outdated
technologies. As a result, it arrived at the recession
of the early-1990s with declining resilience. The
shock of the recession exposed the weakness of
relying on exogenous knowledge generated by multinational companies. Instead of transferring new
technological knowledge to Swansea, they
41
Simmie and Martin
transferred it to new plants in Spain and Eastern
Europe. As a result, manufacturing employment fell
again in Swansea as the economy entered a second
phase of capital disinvestment and release.
These case studies—albeit only briefly discussed
here—suggest that endogenous sources of new
knowledge combined with market driven and conscious entrepreneurial decisions could be among
the key factors for understanding regional economic
resilience. In addition, the co-evolution of facilitating institutional environments is also significant.
Conversely, where existing sources of knowledge
are locked into particular stable technologies, longterm adaptive capacity and resilience tend to decline.
In such circumstances, reliance on external sources
of new knowledge that come with the mass production branch plants of FDIs is likely to be only a
short-term fix. It can lead to declining or the lack
of endogenous sources of new knowledge for local
potential entrepreneurs and to a consequential decline of the capacity of the local economy to adapt
to external market forces. Institutional hysteresis and
unchanging cultures can also contribute to a lack of
economic resilience.
Our analysis suggests that further investigation of
the adaptive cycle model may be a useful way of
conceptualising and analysing regional economic
resilience. Clearly, the model is not unproblematic
or without limitations. It is of course only one way of
thinking about how a local or regional economy
evolves, and there are issues about abducting a model
from one disciplinary field, in this instance the study
of ecosystems, to another, in our case regional economic development. Regional economies may be
analogous to ecosystems in certain respects, but they
are quite different in others. Nevertheless, the model
has the virtue that it sets the issue of resilience of
a system—such as a local economy—in the context
of the evolution of that system: resilience as a process
rather than an unchanging characteristic. For this
reason alone, it seems worthwhile pursuing the panarchy adaptive cycle model in more depth, with the
aim of giving it a more explicit regional economic
form, as one way of trying to cast light on the important but somewhat elusive notion of regional economic resilience.
42
Acknowledgements
The authors gratefully acknowledge the financial support
of The National Endowment for Science, Technology
and the Arts (NESTA) for the empirical work reported
in the paper. A full exposition of this research is available from NESTA published as: Simmie, J., Carpenter, J.,
Chadwick, A. and Martin, R. (2008) History Matters:
Path Dependence and Innovation in British Cities,
London: NESTA. The authors also acknowledge the
helpful comments from two anonymous referees.
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