Re-imagining evolutionary economic geography

Full text

Cambridge Journal of Regions, Economy and Society, 2023, XX, 1–17
https://doi.org/10.1093/cjres/rsad029
Editorial
Editorial
Re-imagining evolutionary economic
geography
Dieter F.Koglera,, EmilEvenhuisb,, ElisaGiulianic,, RonMartind, ElviraUyarrae, and RonBoschmaf
aSpatial Dynamics Lab, School of Architecture, Planning and Environmental Policy, University College Dublin, Dublin, Ireland, dieter.kogler@ucd.ie
bPBL—Netherlands Environmental Assessment Agency, The Hague, Netherlands, Emil.Evenhuis@pbl.nl
cDepartment of Economics and Management, University of Pisa, Pisa, Italy, elisa.giuliani@unipi.it
dDepartment of Geography, University of Cambridge, Cambridge, UK, rlm1@cam.ac.uk
eManchester Business School, University of Manchester, Manchester, UK, Elvira.Uyarra@manchester.ac.uk
fDepartment of Human Geography and Spatial Planning, Utrecht University, Utrecht, Netherlands, r.a.boschma@uu.nl
Keywords: Evolutionary Economic Geography, EEG, paradigm, conceptual elements, ontology, development, policy,
cities, regions
JEL Classications: B52, O10, O30, R1
Re-imagining evolutionary economic
geography—why, and why now?
It is now more than two decades since the idea of adopting
evolutionary ideas in economic geography was rst
mooted (Rigby and Essletzbichler, 1997; Boschma and
Lambooy, 1999). Since then, the paradigm has developed
signicantly, both theoretically and empirically (for some
useful surveys, see, for example, Boschma and Frenken,
2006, 2018; MacKinnon et al., 2009; Boschma and Martin,
2010; Kogler, 2015; Pike et al., 2016; Henning, 2022; Martin
and Sunley, 2023). Whether or not the paradigm of evo-
lutionary economic geography (EEG) can be said to have
yet reached ‘middle age’, it is certainly the case that its
rst ush of youth is now past. It is perhaps germane,
therefore, to reect on what has been achieved, and what
remains to be done. A key question is whether the theoret-
ical and empirical scope of EEG needs adjusting so that it
is (better) suited to help understand the upheavals, crises
and transformations that confront contemporary capital-
ism and its spatial congurations, and what those adjust-
ments should be.
For the simple fact is that the circumstances under
which geographers began to explore the relevance of evo-
lutionary ideas and concepts for explaining change in eco-
nomic landscapes have themselves changed dramatically.
Since the beginning of the 21st century (if not before) the
pace, nature and direction of capitalist economic devel-
opment have been undergoing immense change: we seem
to have entered a new age in which more or less continu-
ous and momentous disruption is the ‘new normal’, what
some even refer to as a permanent state of ‘polycrisis’
(Tooze, 2022; World Economic Forum, 2023). The list of
upheavals that have combined and mutually reinforced
one another is now well rehearsed—climate change, trade
conict (especially between the USA and China), nancial
crises (in 2008, and now again in 2023), the energy price
crisis, demographic ageing, biodiversity loss, the acceler-
ating articial intelligence revolution, widespread distrust
in democratic institutions and the rise of populisms of dif-
ferent kinds, increasing geopolitical tensions (especially
Russia’s invasion of Ukraine), the COVID pandemic and
its after-effects, and the growth in social inequality. All of
these are impacting differentially not only across nations,
but also across the regions and cities within them.
Do these ‘new realities’ require revisions and
recalibrations of our concepts and theories, or are our ex-
isting explanatory frameworks entirely capable of grasping
those realities? This question applies to all of our theor-
etical frameworks and perspectives, including EEG. Thus
far, the main line of enquiry in EEG has been on industrial
and technological aspects of regional economic evolution.
More recently, the focus has also shifted downwards to
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2 | Kogler et al.
the micro-level of individual rms or technologies. There
has been much less attention, however, to such issues as
social inequalities, the public sector or to political insti-
tutions, especially the state. Equally, there has been less
attention on the ‘big processes’, ‘climacteric crises’ and
‘mega-trends’ that are arguably the key drivers of uneven
regional and city development in the contemporary era.
These are all topics in the analysis and understanding of
which EEG can potentially contribute, though arguably by
expanding its theoretical foundations and its empirical
remit. The various articles in this themed issue of the jour-
nal are, in their various ways, directed to this challenge.
But what is distinctive about EEG that makes it potentially
valuable as a paradigm for interrogating the contempor-
ary upheavals in global capitalism?
What is EEG? Clarifying its paradigmatic
features
Dening EEG is by no means a straightforward task (see
Boschma and Martin, 2010; Kogler, 2015; Martin and
Sunley, 2023). Even in evolutionary economics, there is a
plethora of self-declared approaches—what Dopfer and
Potts (2004, 195) termed a ‘massive hybridisation of the-
ory’. To some extent, evolutionary economic geographers
face a still developing corpus of ideas. However, the prin-
cipal guiding focus is on understanding how the spatial
congurations of economic activity and materiality, at all
geographical scales, changes over real historical time. As
Boschma and Martin (2010, 6–7) put it, the basic concern
of EEG is with ‘the processes by which the economic land-
scape—the spatial organisation of economic production,
circulation, exchange, distribution and consumption—is
transformed from within over time’. We need to extend
this idea by recognising that as the spatial organisation of
economic activity itself evolves and transforms, this can
in turn inuence and transform the very processes that
drive that evolution. Furthermore, the transformation of
economic landscapes can be driven by processes that are
slow and cumulative, and by those that are episodic and
highly disruptive, and of course by the interaction between
the two.
EEG, then, is concerned with theorising the evolution
of the economy over time from a geographical point of
view. It has emerged as an identiable and distinct body
of theory and empirics—a paradigm—within economic
geography. But it can also be seen in a broader sense as a
‘project’ to embed evolutionary ideas, concepts and pro-
cesses more strongly within economic geography more
generally (Martin and Sunley, 2023, 13). It should certainly
be acknowledged that within economic geography there is
a long tradition of considering the dimension of time, his-
tory and long-run regional development, especially within
strands inuenced by Marxism, Political Economy and
Institutionalism. Hence there is the potential for fruitful
exchanges of ideas and insights between EEG and these
other strands within economic geography (see MacKinnon
et al., 2009; Martin and Sunley, 2015; Essletzbichler et al.,
2023).
Another way of seeing EEG, however, is to consider it
as a distinct strand of work emerging from, and still re-
lated, to evolutionary economics, namely that which fo-
cuses on a particular aspect of economic evolution, that
is, the spatial aspect (see Metcalfe, 2023; Dopfer, 2023).
Yet another viewpoint would be to see EEG as spatially in-
ected economic history: EEG provides a set of concepts
for theorising the spatial aspects of economic history, and
economic history provides empirics and procedures to de-
velop, test and modify theories within EEG (see Martin and
Sunley, 2022; Martin et al., 2020).
These different perspectives are not exclusionary. The
perspective adopted does however shape the manner in
which one theorises the dimensions of space and time in
economic evolution (see also Martin and Sunley, 2022; Chu
and Hassink, 2023), and will also shape the cross-fertilisa-
tions with other bodies of work. Because different partici-
pants in the collective endeavour of EEG have approached
its core question (how to theorise the evolution and trans-
formation of economic activity and materiality from a geo-
graphical point of view) from different theoretical angles and
through a variety of empirical research strategies, the body
of theory within EEG has become quite diverse. It would in-
deed seem fair to characterise EEG theory as a ‘patchwork’
of concepts and ideas (Martin and Sunley, 2023).1
A key question, therefore, is whether there should and
can be a unifying theoretical framework to EEG to provide
more coherence and guidance to its conceptual ideas and
empirical enquiries. Some leading evolutionary econo-
mists—such as Geoff Hodgson, Sidney Winter, Ulrich Witt
and Jan-Willem Stoelhorst—have argued that Generalised
or Universal Darwinism provides the basis for an evolu-
tionary perspective on the economy. The suggestion is that
the three key precepts of variety, selection and retention
(VSR), can constitute a ‘general model of evolution’ (see
for example, Hodgson and Knudsen, 2010). The application
of this model to any specic eld, such as economics, will
depend on context and require ‘auxiliary’ propositions and
hypotheses in order to derive the economic equivalents of
‘population dynamics’, ‘phenotypes’ and ‘genes’ in evo-
lutionary biology. Many evolutionary economists never-
theless remain wary of abducting evolutionary biological
metaphors into economics (as indeed was Schumpeter
(1954, 789), whose work is often invoked by evolutionary
economists, and evolutionary economic geographers):
see the discussion in Lawson (2003, Ch. 5) and Feldman
(2023). In any case, most discussions of the relevance of
Generalised Darwinism as a source of metaphors and
ideas in evolutionary economics seem not to recognise
that even within evolutionary biology the VSR model has
been extended and superseded (Martin and Sunley, 2015).
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Editorial | 3
However, some evolutionary economists have moved
away from the VSR model of Generalised Darwinism to-
wards conceptual frameworks based on ‘complex adaptive
systems’ and ‘self-organisation’ (for example, Foster and
Hölz, 2004; Foster and Pyka, 2014; Witt, 2017).
What is essential to conceptualising the economic
landscape as ‘evolutionary’ is to see it as hysteretic.
That is, economic landscapes—regional and urban econ-
omies—embody the legacies of their pasts, and it is those
legacies that shape the possibilities for current and future
change and transformation. As Martin and Sunley (2022)
argue, EEG is quintessentially and necessarily an historical
science, given that it is concerned with how a particular
spatial conguration of economic activity and materiality
at any given moment has come to be what it is; that is, how
it was produced through time (Martin and Sunley, 2022).
History matters. In consequence, EEG needs to devote ser-
ious attention to the temporalities of capitalist evolution,
to the fact that different processes of (spatial) economic
change operate over different time scales, with different
rhythms and different periodicities. To date, EEG has fo-
cussed mainly on slow cumulative change, and far less on
episodic disruptions, critical events, major shocks, crises
and climacteric disjunctures. Historically, such ‘big events’
have had major transformative effects on the spatial con-
gurations and geographies of economic development.
And the fact that we are precisely in another of these his-
torical ‘hinge points’ highlights and exposes this theoret-
ical and empirical lacuna within EEG inquiry.
At least ve ‘big concepts’ or ‘conceptual building
blocks’ of an evolutionary approach to economic geog-
raphy can be identied (Figure 1), which together can
be seen as dening components of an ‘evolutionary’ ap-
proach. And underpinning and intersecting across these
conceptual pillars are some key processes that are needed
to construct evolutionary explanations (see Table 1). Not
all of the conceptual frameworks in Figure 1, have received
the same attention, and within each there remains consid-
erable scope for further elaboration and application. For
example, in terms of history, by far the primary focus has
been on the notion of path dependence (see Martin and
Sunley, 2006, for a comprehensive discussion of this con-
cept), and much less on causal history, sequence analysis
and other such ideas which highlight the value of case
studies and context-rich approaches.
Novelty—the generation of new variety—is a key con-
sideration in every evolutionary science. Likewise, it occu-
pies a central place in EEG. Indeed, it is this aspect that
has attracted by far the most attention in recent years. The
notion of ‘related variety’ seems to have become a sort of
sine qua non of EEG (Frenken et al., 2007), and is used as the
explanans of all sorts of regional economic change, from
innovation, to structural and technological diversication,
to growth.
History
The economic landscape as an
historical process, unfolding in
real historical time, with multiple
temporalities, and to varying
degrees embodying the legacies
of past outcomes
Adaptability
The capability of regional and
urban economies to adapt to
changing competitive,
technological and policy
environments
Novelty
Processes that generate new
spatial economic variety, new
forms of regional and city
economic differentiation, and the
creation of new paths of regional
development
Complexity
The economic landscape as an
open, dynamic and ‘out-of-
equilibrium’ system, with multi-
scalar, non-linear feedback
processes, and characterised by
differential adaptability
Emergence
The economic landscape as a self-
organising system emerging out
of micro-level processes, with
macro-level features not wholly
reducible to, but exerting
downward causation on, micro-
level forms and processes
Figure 1. Some key dening conceptual elements of EEG.
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4 | Kogler et al.
This particular focus on ‘related variety’ is not unprob-
lematic, however: not only are there issues as to how ‘re-
lated variety’ should be dened and measured, its causal
inuence will depend on what particular sectors or tech-
nologies are ‘related’, and on whether and when ‘related
variety’ is more important than ‘unrelated variety’ and
sectoral and technological modularity. Furthermore, ‘re-
lated variety’ is not just an independent variable, but also
a dependent one: what causes related variety to emerge,
when, and where? In any case, there is much more to the
generation of novelty and how new pathways of regional
economic development are created and evolve than can be
explained simply by ‘related variety’.
The same scope exists for expanding work on a
complex systems approach to EEG. Following the lead set
by Hildago and his associates (Hidalgo and Hausmann,
2009; Hausmann et al., 2014), thus far the idea of com-
plexity used in EEG has been that of what might be called
‘compositional complexity’, that is, on the pattern, dens-
ity and complementarities of the network congurations
of related products, industries or technologies within and
between individual regions and places. This notion of ‘eco-
nomic complexity’ is very similar to that of ‘related var-
iety’. The claim is that the greater is compositional and
congurational ‘complexity’ of a regional economy, the
more innovative, productive, prosperous and faster grow-
ing the region will be. Hidalgo (2021, 95) himself has even
gone as far as to claim that: ‘Measures of economic com-
plexity explain and predict international and regional
variations in income, economic growth, income inequal-
ity, gender inequality and greenhouse emissions’. Such
a claim is grossly exaggerated (and reductionist!). And
some see economic complexity as a ‘new paradigm’ in EEG
(Balland et al., 2022). But viewing regional economies in
terms of their ‘economic complexity’ is not the same as
viewing them as evolving, ‘complex adaptive systems’.
The latter perspective would conceptualise regional econ-
omies as highly open, interactive dynamic systems, char-
acterised by non-linear processes, differential adaptability
and emergence effects, and typically out of equilibrium
(see Martin and Sunley, 2007; also Feldman, 2023). This is
an area of EEG where much remains to be explored, yet
which again would seem of particular relevance at a time
of repeated profound systemic shocks to national and re-
gional economies alike.
Likewise, the notion of emergence, itself closely asso-
ciated with complex adaptive systems, has not received
the attention it deserves. By emergence is meant the pro-
cesses by which the macro-level features and behaviour
of a system are derived from, but are not simply reducible
to, the actions and interactions of micro-level agents (see
Sawyer, 2005). At the same time, such macro-level out-
comes exert downward causation on the system’s micro-
level components. Thus an explicit role is given not just
to the behaviour of economic agents, but to the ‘higher-
level’ context (including institutions) within which such
behaviour takes place. An emergentist view on the evo-
lution of economic landscapes thus eschews any crude
division between, or simple upward aggregation from, the
micro and the macro. Economic landscapes are character-
ised by numerous processes and forms of emergence: for
example, from markets to clusters to local entrepreneurial
Table 1. Types of processes and mechanisms of economic evolution.
Type of process Role
Mutational processes Processes that generate variation in products, processes, technologies, rms, institutions,
involving creation of new forms and destruction of old forms. This essentially is the
‘creative destruction’ described by Schumpeter.
Constraining processes Processes that restrict the kinds of variation that are possible or likely. These might
include economic factors (such as sunk capital), technological lock-in, a poorly
developed entrepreneurial culture, lack of nance, regulatory restrictions, and the like.
Structure-changing processes Processes operate to select different products, technologies, and rms, such as market
competition, trade arrangements, monopolistic and oligopolistic power, regulatory
systems, etc.
Adaptive processes Processes and factors that inuence the interaction and ‘t’ of rms, with their changing
competitive environments, including rm competencies, workforce skills, etc.
Rate determining processes Affect the rate of evolutionary change (mutation, adaptation).
Direction-determining processes Affect the direction of evolutionary change, such as major advances, shifts and
breakthroughs in technology, regulatory and other policies.
Emergence processes Processes and structures that emerge from but are not simply reducible to lower-level
entities and their interactions, including localised external economies of various
kinds, and which can exert ‘downward causation’ on lower-level entities.
Evolvability processes The evolutionary potential of economic entities (for example, rms, regions) linked to
the internal resources and external linkages of those entities.
Adapted from: Endler and McLellan (1988) and Metcalfe (1998).
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Editorial | 5
ecosystems to cities (see Martin and Sunley, 2012). How
these emerge from the individual actions of micro agents
and feed back to inuence those actions is a central di-
mension of an evolutionary approach.
Arguably, the over-riding or ultimate goal of EEG is to
explain how city and regional economies adapt over time.
The notion of ‘adaptability’ in this context is far from
straightforward, but it would surely have to do, rst, with
the capability of a region’s or city’s rms, workers and
institutions to remain well adapted to the changing com-
petitive, technological, market and regulatory/policy en-
vironment in which they operate; and second, with the
processes by which such adaptation is achieved. All of the
conceptual building blocks in Figure 1 bear on these two
interrelated notions. The differential adaptability of differ-
ent regions and cities underpins their differential devel-
opment over time. Why are some regions and cities more
successful than others in adapting to changing economic
conditions and opportunities? Does the more successful
adaptability of some regions and cities actually hinder the
adaptability of others (akin to the idea of combined and
uneven regional development)? These sorts of questions
go to the heart of an evolutionary approach to studying
economic landscapes. They also have critical implications
for policy. How cities and regions adapt to the new phase
of economic development based on green technologies
and articial intelligence technologies will almost cer-
tainly be uneven, unless policies are explicitly designed to
ensure a spatially (and socially) inclusive transition.
Re-imagining EEG in light of the
polycrisis: bringing in the state and
policy
The multiple interconnected upheavals referred to earlier,
including climate change, nancial crises, demographic
ageing, geopolitical tensions, the COVID-19 pandemic and
social inequality, have sparked a renewed interest in the
role of governance, institutions and the state. However,
the so-called polycrisis has to some extent subsequently
led to a ‘polycleavages’ predicament, that is, when highly
relevant issues dominate the general discourse simul-
taneously and as such divide rather than unify potential
stakeholders in their search for solutions (Zeitlin et al.,
2019). This is, of course, less than ideal given the signicant
transformations that are currently unfolding at an unpre-
cedented pace that might only compare to very few pre-
vious highly disruptive times, for example, the industrial
revolution. Signicant technological, and associated insti-
tutional and organisational transformation, emanating
from novel methods of production as articulated in the
notion ‘Industry 4.0’ (Lasi et al., 2014), along with the rapid
diffusion of articial intelligence-based tools across indus-
trial sectors and the public in general, further exaggerate
present uncertainties, but equally offer ample opportun-
ities to positively transform economic and social life more
generally. In order to tackle challenges and to ensure that
benets are equally distributed, that vulnerable popula-
tions are protected, and that these transformations do
not result in a collapse of the entire socio-economic fabric
which is already on unstable grounds, requires a more ac-
tive and diverse role of the state than has been previously
acknowledged, for example, as regulator, animateur, pur-
chaser and lead-user.
Although EEG scholarship has been interested in what
policy should look like, it still lacks an evolutionary con-
ception of the state. Public policy under an evolution-
ary lens needs to be tackled, not only from a normative
angle, but also a positive one that understands policy-
making and politics themselves as evolutionary pro-
cesses. Failure to do this is likely to result in unrealistic
and ineffective policy prescriptions. In much of the evo-
lutionary economics literature, and also in EEG, there is
an implicit assumption that policy is exogenous and de-
tached from evolutionary socio-economic systems, as if
performed by a rational policymaker able to control the
system by choosing from a toolbox of policy instruments,
overlooking the evolutionary dynamics of diversity, selec-
tion and path dependency in policy processes and political
systems. Similar to innovations, policies are inuenced by
pressures and constraints that determine the selection be-
tween competing ideas and solutions to problems, leading
to the legitimisation of some and the rejection of others
(John, 1999; Kerr, 2002). Policy is also subject to path de-
pendencies (Pierson, 2000) resulting from historical leg-
acies, institutional inertia, learning effects and adaptive
mutual expectations. Past policy choices shape and con-
dition future policy decisions, potentially constraining the
range of options available for policy action (Uyarra, 2010).
The exploration of policy as evolving in path-dependent
trajectories has largely been overlooked in EEG (although
see, for example, Valdaliso et al., 2014). Analysis of policy
impacts over time are often at best exercises in com-
parative statics, neglecting how ‘policy histories’ shape,
co-evolve or adapt to processes of economic and regional
structural change. This limits our ability to understand the
multiple roles the state plays in new path creation (Dawley
et al., 2014; Flanagan et al., 2023). A better understanding
of actual policy-making and policy evolution would allow a
more incisive understanding of the opportunities for policy
action available to regions within multiscalar institutional
environments. As Essletzbichler et al. (2023) suggest, the
dominant focus in EEG on micro-meso interactions at the
expense of the macro scale has led to incomplete accounts
of regional evolution and a tendency to neglect the links
between subnational and national policy contexts and act-
ors (see also MacKinnon et al., 2009; Dawley et al., 2014).
Adopting an evolutionary perspective involves a funda-
mental appraisal of policy action (Metcalfe and Georghiou,
1997), including an acknowledgement of the degrees
of freedom that policy actors have to inuence and
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6 | Kogler et al.
direct the evolution of economies (Lambooy and Boschma,
2001). Attempts at steering or control by policy actors are
made still more difcult by the fact that they are them-
selves part of the system that they are trying to inuence
(Flanagan and Uyarra, 2016, Weller and Beer, 2022). A key
implication is that, when trying to derive policy implica-
tions, EEG scholars should not ignore the complexity of
governance and politics, but instead grapple with the im-
plications of this complexity and support cautious experi-
mentation and policy learning, recognising the intricacies
and uncertainties involved, and foster open discussions
about the trade-offs and inherent conicts among policy
objectives, such as environmental sustainability, equity
and economic growth.
EEG as a driver for challenge-oriented
innovation policy
Evolutionary Economics has played a prominent role in
articulating the rationales for government intervention
in science, technology and innovation policy (Metcalfe,
1994; Nelson et al., 2018). Recent approaches to industrial
policy (Rodrik, 2007; Mazzucato, 2013), mission-oriented
policies (Mazzucato, 2018), transformative policy (Schot
and Steinmuller, 2018) and policies to tackle societal chal-
lenges (Edler and Fagerberg, 2017; Kuhlman and Rip, 2018)
have called for a more transformative agency of the state,
exercised through mixes of roles and tools, including
market shaping interventions. In these policy accounts,
however, geographical aspects of economic evolution are
often not given full consideration.
This is disappointing considering that the EEG para-
digm offers signicant insights into how the present geog-
raphies of innovation have come about and continue to
unfold, and as such provides much-needed explanations
regarding the factors that enable or prohibit place-bound
congurations of economic activity and resulting bene-
ts. Despite rather implicit contributions to fundamental
policy debates, one particular policy arena where EEG ac-
tually does excel and has been quite inuential is in re-
gional innovation policy-making.
The regional innovation system concept has been
adopted in many regions as a framework for the de-
sign and implementation of regional innovation policies
(Asheim et al., 2011; Coenen et al., 2017). More recently,
this policy interest in EEG has been given a boost by Smart
Specialisation policy in the European Union (Foray, 2015).
This represents a form of place-based innovation policy
in which sectoral-technological connectedness along with
an emphasis on structural evolution are key elements for
regional economic development. Essentially, the core idea
is to prioritise new domains of specialisation in regions
that complement and leverage their local capabilities and
related activities.
While these may be considered steps forward in policy
thinking, EEG is still struggling with crucial questions, es-
pecially where it concerns old industrial and peripheral re-
gions with weak capabilities and poor institutions (Ferreira
et al., 2021) which often nd themselves trapped in stag-
nant or declining industry sectors (Evenhuis, 2016). How to
evolve out of such ‘lock-ins’ remains a largely unresolved
issue. Economic diversication has been considered as
a potential solution for less developed regions to escape
constraints, but how the interplay of related and unrelated
varieties guided by evolutionary principles actually drives
economic growth in regions characterised by weak insti-
tutional settings, and thus a lack of policy interventions
that potentially initiate structural change, is again some-
thing the relevant literature has only began to disentan-
gle (Pylak and Kogler, 2021). One of the main questions in
this regard is to what extent can policy actions shape and
reshape evolutionary trajectories and initiate signicant
structural transformations towards more advanced devel-
opment stages? Place-based capabilities are usually rmly
grounded in the history, culture and economic activities
of a particular place and thus are difcult to change in
the short run without major interventions. Nevertheless,
paradigm shifts introduced by signicant scientic dis-
coveries or massive investments rooted in collective ac-
tions, for example, the recent push by the European Union
towards the twin green and digital transition (Muench et
al., 2022), might give rise to opportunities to escape path
dependency and diversify into novel economic activities
based on capabilities that are linked to declining sectors.
For instance, green diversication in regions is often em-
bedded in local capabilities, even those based on so-called
‘dirty’ activities, which suggests that some combination of
related and unrelated economic diversication is import-
ant for green transitions. (Tanner, 2016; Van den Berge et
al., 2020; Froy et al., 2022).
Questions have also been raised in relation to the
ability of regions to effectively implement place-based
policies. According to Foray (2019), the way the entrepre-
neurial discovery process is organised and implemented
will inuence the ability of regions to diversify success-
fully. However, there is still little understanding of how
that might work. Despite considerable efforts towards the
identication of potential diversication options, there is
increasing evidence of implementation challenges, par-
ticularly the ability of regional actors to prioritise key
sectors or technological domains (Di Cataldo et al., 2022;
Gianelle et al., 2020; Marrocu et al., 2023). Institutional
and political leaders (Battilana et al., 2009) that trigger
new initiatives, mobilise resources, promote collective ac-
tion, build legitimacy and implement institutional change
(Sotarauta and Pulkkinen, 2011; Uyarra and Flanagan,
2022), have been found to play a crucial role. Such agents
of change operate in institutional contexts that vary widely
across regions, differentiated by local governance cultures
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Editorial | 7
(Kroll, 2015) and quality of government (Rodríguez-Pose
and Di Cataldo, 2015). A better understanding is needed
of who these agents of change are, specically the role of
policy entrepreneurs and implementers, and their degrees
of freedom given the context they operate in at various
spatial scales. All of that of course places enormous de-
mands on the ability of public institutions at multiple
levels to design and implement effective innovation pol-
icies (Morgan and Marques, 2019).
There is also a need in EEG to consider broader policy
mixes that go beyond traditional supply-side interven-
tions. Societal challenges require policy intervention on
many fronts that need coordinated policy action by mul-
tiple policy actors, across multiple levels and policy do-
mains. New-generation innovation policy approaches,
such as mission oriented (Mazzucato, 2018) and trans-
formative innovation policies, place a greater focus on
the demand side, where legitimacy, demand articulation,
market formation and institutional change play key roles
(Weber and Rohracher, 2012; Boon and Edler, 2018). This
could supplement the supply-driven policy approach (with
a prime focus on local capabilities) that EEG scholars often
promote in the context of Smart Specialisation policy
(Flanagan et al., 2023). A main focus of recent approaches
is on interactions and interdependencies between differ-
ent policy domains, as they affect the feasibility and ef-
fectiveness of policy objectives. Evolutionary scholars
have been active in the policy mix literature, especially
in policies on innovation and sustainable transition (for
example, Flanagan et al., 2011; Kivimaa and Kern, 2016;
Rogge and Reichardt, 2016, Matti et al., 2017) as well as the
‘Geography of Transitions’ literature (for example, Hansen
and Coenen, 2015), but further steps are needed for it to
provide (more) useful holistic insights to address current
predicaments (Magro and Wilson, 2019).
EEG and the problem of unsustainable
development
Interesting questions arise when we consider EEG in re-
lation to the issue of sustainability. By many accounts,
sustainability problems are endogenous to a model of
capitalism that has relied, at the micro-level, on the gov-
ernance of rms based on a shareholder value maximisa-
tion approach (Friedman, 1970; Stiglitz, 2019), which has
attributed primacy of shareholder prots over the value
generated for society at large. This approach has had nega-
tive consequences for the extent to which companies are
able to contribute to equitable forms of economic devel-
opment.
On the one hand, it has led companies, especially large
multinational enterprises (MNEs), to use business models
that have proved successful because they could free ride
on environmental or social costs (Henderson, 2020), espe-
cially through operations in poorly regulated developing
countries (Giuliani and Macchi, 2014). At a macro level,
this laissez faire model was expected to create societal
well-being based on the idea that companies would pro-
mote economic growth and would also contribute to
x their negative externalities through tax payments.
However, in reality, this expectation has not been met.
Economists have recently documented that some 36% of
MNE’s prots are shifted to tax havens globally (Tørsløv et
al., 2023), suggesting that instead of seeking to minimise
their harmful impacts on society and the natural environ-
ment, for example, through proper payment of local taxes,
corporate governance decisions are more concerned with
protecting prots and shareholder value, and companies
engage in a raft of strategies so as to geographically dis-
tribute their prots in ways that minimise their tax liabil-
ities (see, for example, Pistor, 2019). As a result, valuable
resources are lost which would otherwise contribute to
expenditure on local public services.
Against this background, questions arise as to whether
EEG has so far developed a sufcient theoretical apparatus
to tackle or understand this corporate behaviour. How is
the ‘evolutionary’ approach, using notions such as path
dependency, relatedness, complexity or adaptability, t to
explain the dark side of corporate decision making? Do
we need other theories or other theoretical constructs in
combination with the conventional ones to explain these
decisions?
To start answering these questions, we should rst con-
ceptualise as ‘deviant’ (Earle et al., 2010) organisational
behaviour that deviates from established social norms
or legal prescriptions, oftentimes reected in decisions
that privilege corporate or individual gains over societal
well-being and that result in signicant collective or indi-
vidual harm—for example, environmental depletion, child
labour, slavery, exploitation of workers and discrimination,
and other forms of human rights harm. Second, we should
acknowledge that deviant behaviours are not events sim-
ply resulting from aberrant corporate CEOs or intention-
ally dishonest decision makers: we know that good rms do
bad things (Mishina et al., 2010) and that ‘deviant’ organisa-
tional conducts may be more the norm than the exception
(Palmer, 2012), depending on several conditions, including
the institutional contexts where rms operate (Giuliani et
al., 2023). Third, bad decisions at the micro-level inuence
the development path of industrial clusters, regions and
other ecosystems (Giuliani, 2016), which can thrive in cer-
tain domains (for example, innovation, product complex-
ity, growth and job opportunities) while failing in others.
Silicon Valley, economic geographers’ most acclaimed
innovation hot spot (Saxenian, 1994), is now blamed for
being a powerhouse of inequality and social injustice;
its high-tech products are questioned for the unsustain-
able sourcing of raw materials (typically critical minerals)
in developing countries, while also criticised for their
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8 | Kogler et al.
negative societal impacts (Feldman et al., 2021). Lastly,
micro-level ‘deviant’ decisions are dynamically related to
macro-level structures such as the form (‘variety’) of cap-
italism prevailing in a country (Hall and Soskice, 2001), as
well as to the type of institutions that are set up to prevent
or punish undesirable behaviours by powerful companies
or elite groups (Acemoglu and Robinson, 2012).
By considering these elements as key pillars of a new
understanding of economic spaces, we call for a reconsid-
eration of the EEG theoretical apparatus to ensure that it
is t to predict these negative effects and integrate them
with the conventional—and generally positive—view that
companies play to foster development processes within
and across geographical space. Behavioural theory, if not
some of its constructs, are particularly helpful to predict
bad decision making. While EEG is akin to behavioural
theory in considering organisations and their managers
as boundedly rational (Simon, 1955), the uncertainty of
the external environment leads decision makers to pro-
ceed via heuristics and trial-and-error, and that compan-
ies operate in their business context through the search of
a satiscing rather than an optimal goal (Cyert and March,
1963). It has generally used these conceptual pillars to pre-
dict dominant patterns (such as path dependency, devel-
opment through related vs. unrelated variety, increasing
compositional complexity) on an assumption of legitim-
ate behaviours, including innovation trajectories, location
choices, investment choices, etc. Yet, as mentioned above,
illegitimate or deviant choices are non-negligible and
largely overlooked in EEG literature. Their explanation re-
quires considering insights from other scientic domains,
focussing on micro-level behaviours, such as behavioural
psychology, as well as on disciplines taking a more macro-
level stance focussing on varieties of capitalism and insti-
tutions.
As concerns the former, recognising ethical judge-
ments in decision making is crucial. Scholars investigating
the behavioural psychology of decision making suggest
that managers are susceptible to moral or ethical dis-
sonance (Kelman and Baron, 1974), which means that a
clash may arise between the aspiration to benet from
unethical behaviour and the need to maintain a positive
moral self-image (Nieri et al., 2023). Dissonance theory
(Festinger, 1962) suggests that individuals have a natural
psychological need for consonance and consistency, which
implies that ethical dissonance is an uncomfortable state
which individuals try to lessen. This is generally done by
either reducing the behaviour—hence moderating action
in order to reduce the sensation of discomfort—or by con-
tinuing the behaviour while activating a psychological pro-
cess of self-justication or self-denial of the harm (Lowell,
2012) which leads to the perpetuation of the activity and
of its normalisation through time (Sykes and Matza, 1957).
The normalisation of deviant behaviours is one of the
reasons why certain practices are persistent and not spor-
adic, and the explanation of normalisation processes is
also not just based on individual decision making but it ra-
ther has a group-thinking and collective dimension which
reinforces normalisation processes by making ‘deviant’
or highly risky behaviour to appear as socially acceptable
and, therefore, legitimate (Janis, 1972; Vaughan, 1996). This
is highly relevant for regional or other sub-regional econ-
omies (for example, clusters) as some local normalisation
dynamics can negatively development processes (Giuliani,
2016). A clear example of ‘deviant’ behaviour is surely the
activities of banks in the years leading to the global nan-
cial crisis, when they dramatically expanded the issuance
of high-risk mortgage debt to ‘subprime’ households, bun-
dled that debt into complex securities traded on global
markets, then increased mortgage interest rates, resulting
in repayment defaults, and the potential collapse of the
banking system. Sheer avarice and greed on the part of
banks and bankers became ‘normalised’, until the boom
burst. The recession that followed impacted highly uneven
geographically, as did the decade of scal austerity im-
posed by states to recoup the cost of bailing out the banks.
More than three decades of nancial deregulation facili-
tated this reckless ‘market’ behaviour by banks.
Augmenting EEG with elements of behavioural psych-
ology seems one of the ways through which one can better
understand such events, and why some places are more
likely than others to face unsustainable development
paths. Recent EEG research has already started to point
out how personality traits can inuence urban growth, as
some traits are more likely associated with entrepreneur-
ial initiative (Garretsen et al., 2019). However, there is still
room to expand this perspective to explain unsustainable
development processes rather than growth. Moreover, at
the organisational level, scholars have used performance
feedback as a behavioural mechanism to explain why
some rms are more willing to take risky decisions lead-
ing to harmful business conducts (Harris and Bromiley,
2007; Giuliani et al., 2023), while neo-institutional the-
ory has been widely used to explain MNEs’ acceptance of
certain deviant practices as a survival strategy, especially
when they are the norm in countries with lower regulatory
standards (Surroca et al., 2013). While a full overview of
the theoretical approaches to predict companies’ socially
and environmentally unsustainable business practices is
beyond the scope of this editorial, we suggest that EEG
could benet from rening its theoretical toolbox in order
to be able to improve our understanding of the dynamics
of unsustainable decision making.
Likewise, there is scope for EEG to extend this area of re-
search by considering how varieties of capitalism or, even
more specically, varieties of neoliberalism (Birch and
Mykhnenko, 2009) shape (and are shaped by) the procliv-
ity of companies to deviate from norms. Earlier research
in business ethics has suggested that national business
contexts characterised by shareholder pre-eminence,
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Editorial | 9
typically the most advanced forms of liberal market econ-
omies, create a favourable environment for prioritising
prots over societal well-being (Matten and Moon, 2008).
However, coordinated market economies or different var-
ieties of state capitalism (Musacchio et al., 2015) may
also experience pervasive misconduct owing to the opa-
city of their institutions and to the political ties between
economic and political spheres favouring favouritism,
lobbying and. Hence, more research examining how con-
temporary varieties of capitalism, and their related dom-
inant ideologies, inuence the evolution of (un)sustainable
development patterns at regional and other geographical
spaces appears to be both timely and relevant.
An expanded ontology for re-imagining
EEG
The expansion of the theoretical remit of EEG along the
lines discussed in the previous sections, to make it more
suitable to address the key transformations of today, re-
quires a reconsideration of the paradigm’s ontological
foundations. The use of ontology here is given to mean a
particular view and interpretation of the world, or of the
system of interest, its main components, processes and
features, how these are structured and organised, how
they function, and what, therefore, requires explanation.
Every research paradigm or research programme is based
on an ontology of some sort, even if that ontology is rarely
acknowledged or explicitly specied. There are, no doubt,
some evolutionary economic geographers who will argue
that discussions of ontology are bound to be inconclu-
sive and hence it is better to just focus on doing empirical
research—a sort of position that EEG is simply what evo-
lutionary economic geographers say they are doing. This
is not an altogether satisfactory response. The topics for—
and approach to—empirical research will be guided by an
implicit view of how the world works. Moreover, ndings
from empirical research only take on signicance in light
of a broader interpretation of what is going on in the world.
The prevailing ontology in EEG emphasises activities
and processes at the micro-level (innovation, entrepre-
neurship and rm growth), which are conditioned by avail-
able technologies, skills and knowledges. These then give
rise to—and are in turn impacted by—meso-level patterns,
such as the emergence or stagnation of industries or clus-
ters in a certain region, or the long-term performance or
resilience of places. We need to expand this ontology in a
number of ways, so it provides a more appropriate basis
for theorising current trends and challenges shaping the
economic landscape. We do not offer a complete specica-
tion of this expanded ontology, but we do want to outline
three aspects of such an expanded ontology.
First, the ontology should encompass a broad view of
endogenous development within regions. The evolution
and transformation of a particular region is determined
by changes happening in many interrelated domains, not
only in the technological and industrial base, but also in
other aspects of the regional economy, such as the labour
market, institutional arrangements, and the domain of
policy-making. Table 2 offers various examples of pro-
cesses and mechanisms of evolution in different domains
of a local economy. Over the past decade or so, this agenda
has indeed been taken up within EEG, through a stream
of articles that have extended the concepts of path devel-
opment and path creation in regional economic evolution
(see for example, Hassink et al., 2019; MacKinnon et al.,
2019; Grillitsch and Sotarauta, 2020). These articles fore-
ground the different mechanisms of path dependency
(and lock-in) at play within and across various domains
and connect these to how the economy of a region evolves
(see Martin and Sunley, 2006; Martin, 2010).
Several articles within this themed issue take this
agenda forward. Frenken et al. (2023) synthesise various
insights about the development of technologies, indus-
tries and institutions into an encompassing framework
for understanding regional economic development. The
articles by Elekes et al. (2023), Henning and Kekezi (2023)
and Benner (2023), look at the interactions between labour
market dynamics and the characteristics and evolution of
other aspects of the regional economy (industrial struc-
ture, institutions and policies), Moreover, these articles
explicitly assess the outcomes in terms of addressing in-
equalities (that is, inclusion and upward mobility within
the labour market). Menzel (2023) sheds additional light
on the process of market construction, and how this im-
pacts on the evolution of industries. The article by Vela
Almeida and Karlsen (2023) shows that in some contexts
the informal economy and unpaid labour will also be rele-
vant for the evolution of the industries in a place. The
contribution by Froy (2023) makes the case to also include
the role of the spatial conguration of the (changing) built
environment into the conceptualisation of the economic
evolution of regions and cities, a hitherto neglected topic.
The commentary by Feldman (2023) suggests that EEG can
draw on the work on Entrepreneurial Ecosystems to en-
rich its conception of—and approach to—endogenous eco-
nomic development within places.
Second, the evolution of a particular region should be
considered in relation to a much broader space that en-
compasses actors, structures, ows and processes at
various levels of scale beyond the place in question (Kedron
et al., 2020). That is, the prevailing focus in conceptualising
the evolution and transformation of the spatial economy,
as mainly an interplay between activities, processes and
factors at the micro-level, with patterns at the meso-level
(that is, the evolution of a regional economy and its various
components), should be complemented by a consideration
of the relations with other places and the dynamics at the
macro-level. EEG has indeed made strides in considering
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10 | Kogler et al.
how the evolution of the economy within places is inu-
enced by the structures and relations in which a region is
embedded (for example, Kogler et al., 2023; Boschma and
Capone, 2015; Boschma, 2017; Trippl et al, 2018; Boschma,
2022, Rocchetta et al., 2022; Frenken et al., this issue). The
article by Shin et al. (2023) adds valuable new insights
into the knowledge ows between locations and the im-
pacts these have on the evolution of technological cap-
abilities within a region via the ‘innovative footprint’ of
multi-location rms, and then how this contributes to the
evolutionary diversication trajectories in their respective
home regions. The article by Morrison (2023) directs atten-
tion to the importance of ows of high-skilled migrants
between places, for the knowledge, competences and skills
available across regions, which will then have repercus-
sions for innovation and the evolution of local industries.
Nevertheless, more is required in order to adequately
conceptualise the macro-level patterns, trends, pro-
cesses, structures and upheavals in the global economy,
as the broader space in which regional economies oper-
ate, and which in turn are also shaped by what happens
within regions. Moreover, as noted earlier, also the state,
arrangements of governance and the variegated ways in
which capitalism is organised, should be accorded a place
in the extended ontology of EEG, as these cannot be seen
as separate from and outside of the economic sphere,
and are themselves subject to evolutionary processes and
mechanisms. Several calls and programmatic statements
Table 2. Some processes and mechanisms of evolution within various domains in a place.
Related to the
development of
particular technologies
in a place
• Interplay between related and unrelated technologies fostering new combinations and
innovation, enabling the emergence of new growth paths in regional economies (for example,
Neffke et al., 2011; Boschma, 2017; Whittle and Kogler, 2020).
• More open and exible relations in the exchange of knowledge, supply chains and networks
with relevant stakeholders, will facilitate innovation and reorientation among rms; while close
relations and investments in relation-specic assets will constrain technological development (for
example, Grabher, 1993; Maskell and Malmberg, 2007; Crespo et al., 2013; Rocchetta et al., 2022).
Related to the
development of
particular industries
in a place
• Various assets within and beyond a region (competencies, skills, infrastructures, natural
resources, etc.) being modied and coupled by key actors in the private and public sectors, which
facilitates the development of new industries (for example, Dawley, 2014; MacKinnon et al., 2019).
• Creating, nurturing and scaling-up a ‘new-to-the-world’ industry within a region as part of
socio-technical transitions, which may then also constitute a new growth path for the region,
will require active legitimation and market construction activities through formulating value
propositions, procurement policies, nancial support, changes in regulation, advocacy, etc. (for
example, MacKinnon et al., 2019; Heiberg et al., 2020; Binz and Gong, 2022).
Related to the
development of the
labour market in a
place
• Dominance of certain industries leads to prevalence of certain skills in the labour market, and
a distinctive culture (for example, ‘culture of dependency’), which inhibits the emergence and
growth of new industries (‘Upas Tree effect’) (Cooke and Rehfeld, 2011; Hudson, 1994; Checkland,
1976).
• Low average skill-level on a local labour market, contributes to the fact that only new economic
activities emerge or are attracted to a region that capitalise on low skills (for example, Finegold
and Soskice, 1988; Finegold, 1993; Dawley et al., 2014); or alternatively there is a large subset of
the population that is skilled and entrepreneurial which leads to a regional economy that can
constantly renew itself (for example, Glaeser, 2005).
Related to the
development of
institutions in a place
• Development of specic institutional arrangements within a local industry or cluster, that enable
adjustments and improving competitiveness (for example, Bailey et al., 2010; Harris, 2021).
• ‘Local growth coalitions’ and urban regimes with tight relations between business and politics,
which result in the protection of vested interests and support for the status quo (Grabher, 1993;
Hodgson, 1989; Settereld, 1993).
• Changes within existing institutional arrangements through (deliberate or accidental)
institutional entrepreneurship, taking the form of for example, ‘layering’, ‘conversion’,
‘displacement’, or ‘recombination’, etc. (Streeck and Thelen, 2005; Mahoney and Thelen, 2010;
Martin, 2010; Evenhuis, 2017; Grillitsch and Sotarauta, 2020).
Related to the
development of
policies
• Myopia and complacency in ‘sense-making’ in which only certain pieces of information are
picked up and given weight, instead of an on-going search for alternative options and new
possibilities (Maskell and Malmberg, 2007; Schmidt, 2008; 2010).
• ‘Escalating commitment’ in which more and more resources are committed to a certain course
of action, even though this has so far been to no avail (or even resulted in negative outcomes), in
order to prove the ultimate rationality of that course of action and/ or to ‘save face’ (Staw, 1976;
Tuchman, 1984).
Adapted from Evenhuis and Dawley (2017), Table 13.2.
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Editorial | 11
have already suggested this (see MacKinnon et al., 2009;
Essletzbichler, 2012; Martin and Sunley, 2015).
Essletzbichler et al. (2023) restate and augment these
earlier statements. Moreover, they show how patterns,
ows and processes within the global economy can be
explicitly integrated into the EEG paradigm, which then
leads to different insights into the drivers of economic de-
velopment in regions and cities. Also the contribution by
Bieri (2023) takes the conceptualisation of the nature of
the capitalist spatial economy and its evolution, in new
directions. He builds on the work of Joseph Schumpeter
to incorporate money and nance into an evolutionary
and geographically sensitive framework, which points to
promising new avenues for research within EEG given the
nancialized nature of contemporary capitalism.
Third, the ontology of re-imagined EEG needs a broad
view of the processes of evolution and transformation
within the economic landscape. That is, how the various
actors, assets, structures, ows, patterns, etc. shape the
evolution of different aspects of the spatial economy, at
different scales, and with different temporalities; and
how these processes are also interconnected. As outlined
above, a dening characteristic is that EEG is about under-
standing the dynamics of the spatial economy. History,
novelty, adaptability, complexity and emergence are key
building blocks in this respect. Furthermore, as also dis-
cussed, there is considerable promise in enriching the
micro-foundations of EEG by drawing on insights from
behavioural psychology, to account for the ways in which
actors act as they do, giving rise to the persistence of cer-
tain patterns or to unintended outcomes.
The commentaries by Metcalfe (2023) and Dopfer (2023)
outline how evolutionary economists view the processes
of evolution and transformation in the economy, and how
this view can be extended by evolutionary economic geog-
raphers. In their article Chu and Hassink (2023) on the
other hand point to the importance of rooting the theor-
isation of such dynamics within EEG, much more strongly
and more explicitly within geography. They argue that the
spatial aspects of these dynamics should be brought to the
fore, and not be treated as an afterthought.
In the past decades there have been important advances
in EEG in understanding and researching the ‘interdepend-
ence’ and ‘co-evolution’ between different processes in
various domains and/or at different scales of the spatial
economy (Schamp, 2010; Pike et al., 2016; Evenhuis, 2017;
Gong and Hassink, 2019; Frangenheim et al., 2020; Benner,
2022; Sotarauta and Grillitsch, 2023). All of the articles in
this themed issue contain, to some degree or another, new
insights on exactly this issue.
Concluding thoughts
To make EEG better suited to theorise and interrogate how
the economic landscape is being reshaped from within, as
well as from without, in light of a number of challenges,
crises and transformations, a number of adjustments
are needed in the paradigm. These adjustments concern
the conception of the state, and the role of policy to ef-
fectuate and direct the innovations and changes that are
needed to cope with the challenges and transformations
we are facing. Furthermore, also our theorisation of the
behavioural foundations needs to be expanded, to help
understand why actors act in the ways they do, including
when such actions are harmful for individual and collect-
ive well-being, and thus why it may be difcult to achieve
the outcomes we desire. Moreover, these possible advance-
ments in the body of theory of EEG will require that we ex-
pand and rene the ontological framework on which EEG
rests as a paradigm.
Underlying this call for a re-imagining of EEG is an
unequivocally normative premise, rooted in meliorism:
a belief that, like any other approach in the social sci-
ences, issues of social justice, social inclusion and sus-
tainability should underpin the questions we ask and the
explanations we construct (Martin, 2021). That is to say,
there should be an explicit axiological dimension to EEG,
a normative position that it should not only be a body of
knowledge for understanding economic growth and de-
velopment within and across regions, but founded on a
concern to explain why and when the evolutionary pro-
cesses it studies generate socially and spatially divisive
outcomes, and thence what policies are needed to avoid or
correct such inequalities. If ever such a normative dispos-
ition is required it is surely now, a time of historic turmoil
and transformation.
Acknowledgements
The authors are grateful to three referees for their com-
ments on an earlier version of this Editorial. This themed
issue on Evolutionary Economic Geography greatly bene-
ted from the presentations and vivid discussions that
took place at the dedicated workshop at University College
Dublin, June 2023. In this regard, Dieter F. Kogler would
like to acknowledge nancial support from the European
Research Council under the European Union's Horizon
2020 Research and Innovation Programme [grant agree-
ment number 715631, ERC TechEvo]. The usual disclaimer
applies.
Endnotes
1 Also, in the introduction to the Handbook of Evolutionary
Economic Geography (2010), Boschma and Martin de-
picted the theoretical foundations of EEG as a set of
distinct—albeit interacting—theoretical approaches:
Generalized Darwinism, Path Dependence Theory and
Complexity Theory.
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12 | Kogler et al.
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