Towards a neo(co)evolutionary theory of industry, civil
society, polity and technology:
Enriching evolutionary economics with insights from institutional theory,
organization theory, economic sociology and strategic management
Wordcount: 12.859 (excluding references)
Frank W. Geels
SPRU, Science and Technology Policy Research
University of Sussex
United Kingdom
f.w.geels@sussex.ac.uk
To be submitted to: Research Policy? Industrial and Corporate Change?
Organization Science? Journal of Evolutionary Economics?
Keywords: co-evolution, industry, embeddedness, social problems, innovation,
transitions
Abstract:
This article proposes a new co-evolutionary theory to understand how industry,
markets and technology interact with civil society and broader polity. This theory
builds on but moves beyond evolutionary economics (EE) to address several underdeveloped topics in EE that relate to a) agency (in particular strategy and
interpretation), b) environment (limited attention for civil society), and c) social
problems and normative issues. To address these problems, this article enriches EE
with insights from other disciplines and fields (such as neo-institutional sociology,
organization theory, economic sociology and strategic management) and synthesizes
these into a new co-evolutionary theory. The article develops a triple embeddedness
framework, which conceptualizes industry actors as embedded in two external (task
and institutional) environments and in an industry regime whose core elements
(technology, beliefs, mission, strategic orientation) guide actions towards the external
environments. The neo(co)evolutionary theory links the external environments to core
elements and types of action through five ‘enactment-adaptation cycles’: evolutionary
cycle (behavioural learning), sensenmaking cycle (cognitive learning), political cycle,
cultural cycle, and normative cycle. These cycles specify the recursive mechanisms
that link external pressures and endogenous (strategic) responses. Empirical
implications and propositions are specified for destabilization processes in transitions,
industry responses to social problems, and longitudinal industry trajectories.
1
1. Introduction
This article engages in new theory-building to understand how industry, markets and
technology co-evolve with civil society and broader polity. The article builds on but
moves beyond evolutionary economics (EE), which has become a successful research
programme in the Science-Technology-Innovation (STI) field, addressing topics such
as technology-based competition amongst firms; changes in industry structure
resulting from differential growth, mergers, bankruptcies, and new entrants;
innovation, R&D and technological change; organizational knowledge and
capabilities; trial and error learning; path dependence and lock-in; and the institutional
basis of innovation and technology (in particular the institutional underpinnings of
innovation systems) (Nelson and Winter, 1982, 2002; Dosi, 1982; Dosi and Nelson,
1994; Witt, 2008).
While EE has addressed interactions between industry, technology and
markets, it has paid less attention to broader co-evolution with civil society and polity.
The article therefore develops a new co-evolutionary theory that incorporates
‘institutional environments’ (see below) besides economic market environments. To
conceptualize the interactions of industry actors with multi-dimensional environments,
the article also develops a broader view on agency that incorporates routines and
capabilities/knowledge, but also acknowledges intentional strategy,
cognitions/interpretations and values/identity. Both with regard to agency and
environments, the article thus moves beyond EE. By doing so, it actually addresses
concerns that evolutionary economists themselves have raised about certain underdeveloped areas in EE (Nelson and Winter, 2002; Fagerberg, 2003; Murmann et al.,
2003; Dosi and Marengo; 2007; Nelson, 2008a). These conceptual issues, which will
be further discussed below, form one motivation for this article.
The second motivation is that EE is limitedly able to deal with normative and
social problems.1 Von Tunzelmann et al. (2008), for instance, suggest that
“Evolutionary economists will have to start to address such questions if they are to
provide a more realistic view of the world. They highlight the underdeveloped
normative and political implications that have, as of yet, not properly been developed”
(p. 479). Evaluating progress in innovation studies, Morlacchi and Martin (2009: 575)
likewise conclude that: “we still don’t have a very satisfactory theory of social change.
Our ability to improve social problems remains rather limited, and we do not know
why we appear to have only modest gains in relation to many societal problems, a
failing aptly summarised by Nelson (1977) with the simple but troubling question: “if
we can land a man on the moon, why can’t we solve the problems of the ghetto?”.
This article suggests that addressing these problems requires a broader understanding
of the co-evolution between industry and technology on one hand, and civil society
and polity on the other.
A broad neo(co)evolutionary theory would also be useful for a better
understanding of socio-technical transitions (Geels, 2002; Smith et al., 2005), which
can as a first approximation be conceptualized with punctuated equilibrium theory
(Anderson and Tushman, 1990).2 This theory suggests that long periods of
incremental change are punctuated by brief periods of rapid change that are triggered
1
Nelson (1977; 2008b) forms one of the exceptions.
2
But see Geels and Schot (2007) for a distinction of other transition pathways besides
technological substitution.
2
by technological discontinuities (Figure 1). The competition between different design
options ends with the emergence of a dominant design, which ushers in a new period
of incremental change. While technical and economic processes may be dominant
during eras of incremental change, social, political and organizational dimensions
gain more influence during actual transitions and eras of ferment.
Social,
political,
organizational
influence
Era of incremental
change
Era of
ferment
Era of incremental
change
Era of
ferment
Open
assembled
system
Closed
assembled
system
Simple
assembled
products
Nonassembled
products
Technological
discontinuity
Dominant
design
Technological
discontinuity
Figure 1: Degrees of social influences for different technologies and development
stages (Tushman and Rosenkopf, 1992: 342)
Figure 1 also suggests that broad social influences during transitions increase with
(socio)technical complexity. These influences may be relatively small for
technological discontinuities in components and products, e.g. hard disk drives,
microprocessors, steel to mention some examples from Christensen (1997).3 But they
become larger for more complex assembled products and large technical systems.4
For socio-technical transitions, which refer to shifts in transport systems, energy
systems, agri-food systems etc., broad social influences can thus be expected to be
large.
The punctuated equilibrium theory discussed above has a technology-push
logic, with new technologies ‘triggering’ eras of ferment. While this pattern certainly
exists (see also the neo-Schumpeterian literature), it need not be the only one.
Especially for transitions that are guided by social problems, which Smith et al. (2005)
called ‘purposive transitions’5, we may expect another pattern in which social,
3
The two relatively simple categories in Tushman and Rosenkopf (1992) are: a)
nonassembled products (e.g. cement, flat glass, steel) and b) simple assembled products that
are made up of a few subsystems (e.g. stoves, cans, skis, guns).
4
The two more complex categories in Tushman and Rosenkopf (1992) are: a) closed
assembled systems are made up of many interacting subsystems (watches, automobiles), b)
open systems involve combinations of artefacts and stretch geographical areas (television,
electric power, telephone).
They characterize these as transitions those that “have been deliberately intended and
pursued from the outset to reflect an explicit set of societal expectations or interests” (1502).
5
3
cultural and political processes precede technological discontinuities.6 But such
patterns are difficult to analyze within EE, because this pays little attention to civil
society and social problems.
Against this background, the article aims to develop a broad co-evolutionary
theory that: a) includes attention for civil society and polity, b) can address social
problems. There have, of course, been previous calls for broad co-evolutionary
approaches. Ziman (2000: 314-315) and his book contributors, for instance, conclude
that:
"From an evolutionary point of view, material artefacts cannot be considered in
isolation from their cognitive and social correlates. (...) The various elements in the
evolving artefact complex are often geared into other evolutionary cycles in their
larger cultural and/or intellectual domains.”
Also Dosi (2000: 365) sees co-evolution of industries and broader contexts as an
important future research topic:
"A first [important issue on the research agenda] concerns co-evolutionary processes.
(…) Co-evolution (...) is a broad area covering, for example, the interactions between
the forms of economic organization, social and political institutions and technical
change."
But such broad co-evolutionary approaches, which include civil society, have hardly
been developed. Most previous work has a supply-side focus on technology, industry,
universities and policy institutions (Nelson, 1994; Van de Ven and Garud, 1994;
Rosenkopf and Tushman, 1994). Previous work also consists mostly of perspectives
that sensitize us to general interactions between various entities. It is now time,
however, to go beyond descriptive statements of 'co-evolution', 'seamless webs', or
'complex interactions', and move towards more precise and conceptually rigorous
approaches. To signal this shift, the article aims to develop a neo(co)evolutionary
theory that articulates causal mechanisms and their interactions in co-evolution
processes.7 It thus forms an answer to Malerba’s (2006: 18) call:
"The challenge for research here is to go to a much finer analysis at both empirical and
theoretical levels, and to move from the statement that everything is coevolving with
everything else to the identification of what is coevolving with what, how intends is this
process and whether indeed there is a bi-direction of causality".
The article’s strategy is to start with evolutionary economics and identify some
underdeveloped areas which relate to agency and environment (section 2). Section 3
and 4 then mobilize insights from various disciplines and fields (such as neoinstitutional sociology, organization theory, economic sociology and strategic
management) and synthesize these into a new co-evolutionary theory. Section 3
introduces conceptual building blocks that develop the (static) outlines of a ‘triple
embeddedness framework’ of industries and distinguish several core elements of
6
The problem of climate change is a case in point.
7
I use the term ‘theory’ in this article to highlight this shift from general perspectives to
analytical approaches to social theory that emphasizes social mechanisms (Hedström and
Swedberg, 1998; Bunge, 2004; Stinchcombe, 1991; Weber, 2006).
4
industry regimes and associated types of agency. Section 4 then develops a dynamic
co-evolutionary theory that connects various types of agency with different external
environments by proposing five ‘enactment-adaptation cycles’. Section 5 discusses
the characteristics of this neo(co)evolutionary theory and implications for future
research, e.g. with regard to social problems and socio-technical transitions. The
article ends with concluding comments in section 6.
A qualifier of the synthetic multi-disciplinary theorising in this article
concerns the challenge to prevent it from becoming too eclectic, with concepts from
different theories being mixed in a confusing hotchpotch. The article addresses this
challenge by articulating some of the background debates from which concepts arise.
Space constraints, however, forbid deep coverage of these debates, which may
dissatisfy specialists in particular theories or disciplines. Although the article aims to
do justice to different theories, there inevitably remains a trade-off between depth and
breadth in multi-disciplinary theorising.
2. Evolutionary economics and underdeveloped areas
Evolutionary economics contains the following ‘hard-core’ assumptions in terms of
Lakatos’s view on research programmes (see recent overviews by Nelson and Winter
2002; Dosi and Grazzi, 2006, Witt, 2008; Alrich et al., 2008, Silva 2009).
 EE focuses on populations of agents (e.g. firms in industries) that compete for
scarce resources (money) in market environments, which thus exert selection
pressure.
 EE was developed to address weaknesses in mainstream, orthodox economics by
developing an alternative model. “Evolutionary economics has mainly used
behavioural theory as a tool for providing foundational concepts, alternative to
neoclassical theory, on which to build a theory of industry and technological
change. Routines, boundedly rational search, productive knowledge, and
unresolved conflict provide an alternative to profit maximization and optimal
agency contracts” (Dosi and Marengo, 2007: 491). Because of this orientation, EE
speaks more to (neo-classical) economics than to other social sciences.8 Because it
remains within the economic family, some debates look like family quarrels (with
a bigger brother) to other social scientists.
 Agency assumptions stem from the behavioural theory of the firm (Simon, 1957;
Cyert and March 1963), recently complemented with the resource based view of
the firm (Barney, 1991), which highlights capabilities and knowledge (Grant,
1996). The behavioural theory assumes that actors are boundedly rational, have
limited foresights, and use routines and rules of thumb for decision-making. Dosi
and Nelson (1994) distinguish three kinds of routines: a) standard operating
procedures, b) routines that determine investment behaviour of the firm, c)
deliberative processes of the firm, including those that involve innovation and
searching for better ways of doing things. During the last decade, there have been
crossovers between EE and the resource/capability based view of the firm:
“Possibly one of the most exciting, far from over, intellectual enterprises
developed over the last decade has involved the interbreeding between the
evolutionary economics research program, (largely evolutionary inspired)
8
I want to thank Mike Hobday and Ed Steinmueller for bringing this point to my attention
(personal discussion).
5
technological innovation studies, and an emerging competence/capability-based
theory of the firm” (Dosi and Grazzi, 2006: 177).
 Routines act as the retention mechanism that provides continuity over time and
ensures transmission of mutations to new generations. Nelson and Winter (1982)
therefore characterized routines as social analogue to biological genes. Agents in
populations are similar in key respects, because they share certain routines and
capabilities (‘regimes’). There is also variation because of differences in firmspecific routines and capabilities.
 Competition is technology-based (product and process). Firms can acquire
competitive advantage by offering improved products or doing things better, faster,
more efficiently, more reliably than competitors.
 Variation arises from innovation, which is a search and learning process (usually
operationalized as R&D) that is guided by routines (search heuristics) and tends to
be local and incremental, staying close to existing routines: “the probability
distribution of what is found is concentrated on techniques close to the current
one” (Nelson and Winter, 1982: 211). Capabilities and knowledge tend to
gradually accumulate over time through ‘behavioural learning’ or ‘trial-and-error
learning’ (Nelson, 2008a) with search processes providing variations to which
markets provide ‘performance feedback’ (which is a key concept in behavioural
theory (Greve, 2003)), selecting the variations with the highest fit.
Although EE has become a productive research programme, seminal evolutionary
scholars have flagged several under-developed dimensions. The subsections below
discuss these dimensions with regard to agency (2.1) and environments (2.2) and
liberally use quotes from these scholars to show internal problem recognition in EE.
2.1. Agency
Management and organization theory also contains other views on agency than the
behavioural theory and resource/knowledge based views of the firm. Dosi and
Marengo (2007: 491) therefore acknowledge that “evolutionary theory has not
developed a full-fledged theory of organizations”. Two specific topics that are
underdeveloped relate to strategy (2.1.1.) and cognition/interpretation (2.1.2.).
2.1.1. Intentionality and strategy
A recurring criticism is that the emphasis on routines leads EE to downplay
intentionality and strategic deliberation. Penrose (1952) already suggested that
theories of the firm based on biological analogies tend to pay relatively little attention
to human decisions, deliberation, purposive motivation and conscious choice. With
regard to innovation and variety-generation, Fagerberg (2003: 151) notes that:
“Firms’ actions, including search for new or improved routines if necessary, became
entirely routine-based. The question arises, however, as to the role for purposive human
actions in this approach. Is there a built-in bias against devoted ‘routine-breakers’, as one
might suspect. In that case, there may be an important source of new variety that is
overlooked.”
Winter (in Murmann et al., 2003: 31) also suggests that EE could do more to include
future orientations and choice:
6
“I think we could do a lot to advance both the evolutionary program, refining its
perspective on the role of foresight, discretion, and choice in these processes.”
Child (1997: 68) suggests that the emphasis on routines has led to a neglect of
intentions, cognitions and strategic goal-setting.
“Similarly with the question of intentionality. This is largely ignored by evolutionary
economists because they tend to concentrate their attention on essentially behavioural
routines rather than on the level of cognition and rationale. Likewise, few discussions of
organizational learning address the issue of the goals for learning by organization and
how they are established.”
Because of its focus on technological search and R&D, EE may have overemphasized the role of the engineers at the expense of (top) managers who articulate
‘strategic intent’ and decide about resource allocation to innovation ventures.
“The image of organizational action as largely driven by routines seems to negate the role
of strategic choice” (Gavetti and Levinthal, 2004: 1313).
“This article identifies gaps in the microfoundations of capabilities research, particularly
in the work that is based on the framework of evolutionary economics. It argues that such
research has focused excessively on the quasi-automatic routine-based aspect of
capability development, and largely neglected the roles played by cognition and
organizational hierarchy” (Gavetti, 2005: 599).
EE also pays limited attention to strategic reorientation in discontinuities. In his
review of EE, Fagerberg (2003: 144) notes about Nelson and Winter’s (1982) seminal
contributions: “They downplayed the importance of major discontinuities in economic
evolution, a point that was essential for Schumpeter. For better or for worse, Nelson
and Winter’s work has a much more ‘gradualist’ flavour.” In this respect Rothwell
(1992) made a relevant distinction between tactical factors and strategic factors that
influence innovation (Table 1). Regarding this distinction, I think it is fair to say that
EE has paid more attention to the tactical factors that relate to efficiency and
incremental innovation (especially regarding knowledge flows and innovation
systems) than to strategic factors that relate to more radical innovations and firm
reorientation.
Tactical factors
Effective linkages with external sources of
know-how
Effective functional integration; involving all
departments in the project from its earliest
stages
Careful planning and project control
procedures
Strategic factors
Top management commitment to, and visible
support for, innovation
Long-term corporate strategy in which
innovation plays a key role
Long-term commitment to major projects.
Table 1: Factors influencing industry innovation (based on Rothwell, 1992)
Why dynamic capabilities are not sufficient to address the strategy problem
In response, evolutionary scholars (e.g. Dosi and Grazzi, 2006) may claim that
strategy has been introduced to EE via the notion of ‘dynamic capabilities’, which
strategic management scholars conceptualize as a firm’s “capacity to renew
competences so as to achieve congruence with the changing business environment”
7
(Teece et al, 1997: 515). Variation is not blind in the dynamic capabilities approach
(DCA), because the focus is on improving the ‘fit’ between an organization’s
changing external environment and its capabilities.
But DCA only partly solves the agency problems. Firstly, it downplays
intentionality by conceptualizing dynamic capabilities as second-order routines, i.e.
routines to change first-order routines (Eisenhardt and Martin, 2000; Winter, 2003).
Secondly, strategy not only depends on having dynamic capabilities, but also on using
them appropriately, which entails judgment, vision, and creativity. If the use of
capabilities is also conceptualized as a (dynamic) capability, then the concept
becomes tautological. Thirdly, “DCA offers little explicit guidance about what
executives should actually do to bring about the envisaged match between internal
competences and the external environment” (McGuinness and Morgan, 2000: 214).
Fourthly, DCA says little about how managers perceive and interpret the external
environment, nor about how they arrive at strategies, goals or visions regarding
directions of capability development:
“In a resource based view, discerning appropriate inputs is ultimately a matter of
entrepreneurial vision and intuition; the creative act underlying such vision is a subject
that so far has not been a central focus of resource-based theory development” (Conner,
1991: 133-134).
Because of these underdeveloped aspects in DCA, strategy and intentionality remain
under-theorized in EE.
2.1.2. Cognition and interpretation
Although EE acknowledges cognitive routines and cognitive dimensions in
technological regimes and paradigms (Nelson and Winter, 1982; Dosi, 1982), it pays
little attention to the content of beliefs and how these change over time. Cognition is
mainly operationalized as knowledge or capability, not as interpretation, something
that relates to EE’s behavioural model of agency.
“The model of satisficing behaviour has been operationalized to be largely non-cognitive.
Alternatives are sampled, either randomly from the full set of possibilities or drawn from
a subpopulation of local alternatives. These alternatives are then evaluated relative to
some fixed performance criterion. The structure is a-cognitive in two important respects:
actors have no mental model of this space of latent alternatives and what might constitute
a more or less prominent option, and, conversely, the evaluation of a given focal
alternative is viewed as nonproblematic. (…) a standard treatment of this issue from the
perspective of cognitive psychology would suggest that actors’ representations or mental
models of their problem environments significantly influence both their sampling and
evaluation of alternatives” (Gavetti et al., 2007: 530).
Cognitions and interpretations are important, because they guide search and variation
processes, as Nelson (2008a) explicitly acknowledges: “human problem solving
proceeds under the guidance of cognitive maps or theories” (p. 79). He also indicates
that EE has not sufficiently incorporated this cognitive influence: “these phenomena
are clearly recognizable in some case studies of actual problem solving, but seem not
to have been effectively flagged in the theoretical literature of search under bounded
rationality” (Nelson, 2008a: 79). With regard to managerial beliefs Nelson and
Winter (2002: 33) suggest that:
8
“The idea that the habits of management thought channel strategic choices is not a
radical new discovery in the evolutionist camp. The challenge, however, is to build a
theoretical structure that is capable of making effective use of that insight (…). We
believe that evolutionary theory provides an accommodating framework for such an
effort, though most of the actual work remains to be done”.
Cognition also influences the selection process, because performance feedbacks need
to be interpreted:
“Much theorizing within the tradition of the behavioural theory of the firm (…) is
relatively silent on the issue of how alternatives are to be evaluated or issues of
cognition more generally. The result is a view in which deliberation and strategic
choice are relegated to a modest corner” (Gavetti and Levinthal, 2004: 1314).
The article aims to give more prominence to cognitive/interpretive dynamics by
distinguishing, in section 4, between an evolutionary cycle (behavioural learning) and
a sensemaking cycle (cognitive learning).
2.2. Environments and societal embeddedness
Focusing on firms, industries, markets, and technology, EE pays limited attention to
the broader societal embeddedness of industries and their relations to civil society,
public opinion, cultural beliefs, and macro-political ideologies. But influences from
broader social and historical contexts can be important for explaining long-term
dynamics in industry and innovation, as some evolutionary scholars recognize:
“One kind of glaring omission in our 1982 book was the failure to think about evolution,
and industry evolution in particular, in a historical context. (…). The realization is that if
you look at historical situations, a lot of the struggle, survival-of-the fittest kind of thing
that goes on in an industry is something that has a particular historical setting” (Winter in
Murmann et al. (2003: 28).
“We argue that, in reality, the broader currents of historical change in the socioeconomic
system are forever imposing exogenous change on the economic subsystem, posing new
and unfamiliar problems to firms. To capture the phenomena characteristic of this reality
requires a fully dynamic analysis” (Nelson and Winter, 2002: 26).
“(…) evolutionary theory should coherently embrace an ‘embeddedness’ view of
organizations, whereby the latter are not simply efficient solutions to informational
problems arising from contract incompleteness and uncertainty, but also shape the
‘visions of the world’, interaction networks, behavioral patterns, and the identity of
agents” (Dosi and Marengo, 2007: 491).
To develop this embeddedness view, the next section distinguishes several external
environments in which industries are embedded.
3. Theoretical building blocks
Section 3.1 recognizes that industries are part of larger ‘organizational fields’
(DiMaggio and Powell, 1983), which it divides into a task environment and
institutional environment. Because industries are also embedded in ‘industry regimes’,
9
i.e. industry-specific institutions, it suggests a ‘triple embeddedness framework’ that
provides a (relatively static) ontology of industries. Section 3.2 discusses the core
elements of this ‘industry regime’ and the various types of agency related to them.
While section 3 thus provides theoretical blocks, section 4 will add the dynamic
mechanisms for the neo(co)evolutionary theory.
3.1. A broader view of environments: Triple embeddedness framework
Embeddedness has become a programmatic notion in economic sociology (Krippner,
2001), which proposes that economies are embedded in larger social systems. While
Granovetter (1985) emphasized the embeddedness of economic transactions in social
structures and relations (particularly networks), Zukin and DiMaggio (1990) also
distinguish cognitive embeddedness (“regularities of mental processes”), cultural
embeddedness (collective understandings, beliefs, ideologies, norms), and political
embeddedness (legal framework, tax codes, policies). This article aims not only to
incorporate these various types of embeddedness in one framework, but also to
address interactions (section 5), thus following Dacin et al.’s (1999) suggestion that
future research should focus on “the ways in which structural, political, cognitive, and
cultural embeddedness simultaneously interact to shape economies, markets and
industries” (p. 335).
Building on neo-institutional theory (in organizational sociology), I
conceptualize industries as simultaneously operating in two kinds of selection
environments: a task environment and an institutional environment (Oliver, 1997).
The task environment, on which evolutionary economics and industrial economics
tend to focus, includes social groups that engage in economic exchanges and
transactions with industries (e.g. consumers, suppliers). Economic competitiveness,
efficiency, and financial performance are dominant selection criteria. In the task
environment, firms face Porter’s (1980) five ‘industry forces’: a) intensity of rivalry
between existing firms, b) bargaining power of suppliers, c) bargaining power of
buyers, d) new entrants, and e) threat of substitutes (new technologies that may lead to
Schumpeterian ‘waves of destruction’).
The institutional environment contains social groups that affect industries in
non-commercial ways, e.g. policy makers, social movements, the wider public, media,
public opinion. "In institutional environments, organizations compete for social
fitness rather than economic efficiency" (Powell, 1991: 184). The selection criterion
for social fitness is legitimacy, which Suchman (1995: 574) defines as follows:
“Legitimacy is a generalized perception or assumption that the actions of an entity are
desirable, proper, or appropriate within some socially constructed system of norms,
values, beliefs and definitions”. Legitimacy thus arises from the fit between
organizations or industries and social institutions. Institutions exert selection pressure,
because organizations are supposed to adhere to them. Failure to do so may lower
their legitimacy, which not only damages public acceptance (‘license to operate’) and
government protection, but also access to external capital (Aldrich and Fiol, 1994;
Lounsbury and Glynn, 2001). Because legitimacy is in the eye of relevant
stakeholders, the institutional pressures tend to be more open to negotiation and
enactment (see section 4). Still, they exert selection pressure because they influence
the fitness and survival of firms in industries.
There are various types of legitimacy (Suchman, 1995), because different
institutions exert different selection pressure. DiMaggio and Powell (1983)
distinguish three kinds of pressures to which industries conform (in a rather one-way
10
fashion): a) coercive isomorphism, exerted amongst others by government mandates
and regulations, b) normative pressures, exerted by expectations regarding appropriate
behaviour, and c) mimetic processes, by which firms model themselves after similar
organizations that they perceive to be more legitimate or successful. Scott (1995)
further elaborated and systematized these ideas, distinguishing three institutional
pillars: a) regulative (explicit rules, laws, regulations, rewards and punishments), b)
normative (values, responsibilities, prescriptions, role expectations), and c) culturalcognitive (shared conceptions that constitute the nature of social reality, frames
through which meaning is made, cultural categories, symbols, wider belief systems).9
Scott’s distinction is further used below.
Another useful distinction is that institutions are nested and exist at various
social levels. Haveman and Rao (1997: 1613) suggest that specific institutions exist at
the industry-level ("particular regulations, norms, and ideas that structure the actions
of individuals and groups") and general institutions at the societal level ("broadly
accepted norms, values and belief systems that constitute the master principles of
society"). Likewise, Robertson and Langlois (1994: 362) distinguish between
endogenous institutions (“specific to a particular firm or industry”) and exogenous
institutions (“features of the economy or society at large”).
Using these distinctions, I propose that ‘specific’ or ‘endogenous’ institutions
are mediating (not determining) factors at the industry level, which provide general
coordination and orientation. But industries also face higher-level selection pressures
from ‘general’ or ‘exogenous’ institutions (Kieser, 1989), such as macro-political
ideologies, general belief systems, social protests (e.g. from social movements) and
public opinion. The degree of match between industry-level institutions and societal
institutions influences the broader legitimacy of industries.
Combining the various concepts, I propose a triple-embeddedness model of
industries in which firms are not only embedded in two external environments, but
also in field-specific institutions (conceptualized as ‘industry regimes’ below) that
mediate actions of industry actors towards the external environments (Figure 2).
Because of this broader conception of industry environments, I also need a broader
conception of agency, something I turn to now.
9
Normative and cognitive institutions partly overlap, because normative institutions are
related to particular beliefs about what is right, wrong, appropriate or desirable. Because of
this overlap, they are sometimes conceptualized as ‘socio-cultural institutions’.
11
Industry regime
Knowledge, capabilities
(technical regime)
Beliefs,
interpretations,
Mission
Regulations
Strategic
orientation
Civil society,
social movements,
public opinion
(norms, values,
general beliefs,
discourse)
Customers
Socio-cultural
legitimacy
Industry
Regulatory
legitimacy
Suppliers
Task environment
Firms
Polity
(regulations,
laws)
Institutional
environment
Figure 2: Triple embeddedness framework of industries
3.2. A broader view on organizational core elements, ‘industry regimes’ and
agency
To develop a broader agency view, I use a pragmatic approach of distinguishing
organizational core elements. Table 2 summarizes core elements that various
management and organization scholars distinguish in some highly cited papers (from
the ISI Web of Science in October 2009).
Authors
Definition of core elements/dimensions
Hannan and
Freeman
(1984: 156)
Hierarchy of four core organizational elements
1) its stated goals, the basis on which legitimacy and other
resources are mobilized,
2) forms of authority within the organization and the basis of
exchange between members and the organization
3) core technology, especially as encoded in capital investments,
infrastructure, and the skills of members, and
4) marketing strategy in a broad sense: the kinds of clients (or
customers) to which the organization orients its production and
the ways in which it attracts resources from the environment.
Four dimensions of core capabilities:
1) values and norms
2) managerial systems
3) technical systems
4) employee knowledge and skills
Hierarchy of five activity domains:
1) core values and beliefs set constraints as to where, how, and
why a firm competes
2) business unit strategy defines the nature of products produced
and markets served and establishes general time and
technological constraints
3) Intra-organization power distributions control the allocation
of scarce resources
4) The organization’s fundamental structure formalizes
LeonardBarton
(1992)
Tushman
and
Romanelli
(1985: 175)
ISI
citations
1098
785
511
12
Levinthal
(1992)
hierarchy, role relations and competitive emphases
5) The nature, type and pervasiveness of control systems
indicate a firm’s emphasis on efficiency
Three organizational sub-systems:
1) Technical sub-system relates to skills and capabilities
associated with the organization’s operating activities
2) Managerial sub-system relates to coordinating and resource
allocation functions
3) The institutional sub-system relates to broader notions of
organizational goals and values and the legitimacy of the
organization within the society in which it operates
20
Table 2: Organizational core elements in management and organization literatures
Three considerations are used to create a set of core elements for the purposes of this
article: a) choose elements that can be linked to the two external environments, b)
choose elements that are mentioned by several authors, c) choose elements that link to
the problems discussed in section 2. Using these considerations, I distinguish the
following core elements for organizations: 1) goals, values, mission, identity (which
relate to normative pressures in the institutional environment), 2) interpretive schemes,
beliefs (which relate to cultural-cognitive pressures in the institutional environment),
3) strategy, which relates to the task environment (e.g. business model and strategic
positions) and the institutional environment (cultural and political strategies), 4)
technical knowledge and capabilities, which are internal resources that underpin the
firm’s technical functioning, and 5) organization structure, which refers to operational
processes and organizational routines.
Most of these organizational core elements can be generalized to the industrylevel where they form industry-specific institutions that collectively form ‘industry
regimes’.10 I propose this new concept to enable a more comprehensive understanding
of industry dynamics, which will be elaborated below. Industry regimes contain the
following five core elements, which relate to different types of agency.11
1) Industry identity, values and mission
Identity and mission are constituted by beliefs of industry actors about themselves and
their role in society. They refer to their self-perceptions with regard to questions such
as ‘who are we’, ‘what business are we in’, ‘what business model do we use’, and
‘what are our broader social goals and values?’ (Fiol, 1991). Identity is more inwardoriented, and influences beliefs and interpretations (Gioia and Thomas, 1996). “An
organization’s identity, or what organizational members believe to be its central,
enduring, and distinctive character (…), filters and models an organization’s
‘Industry regimes’ are broader than ‘technological regimes’, which evolutionary
economists tend to use (Nelson and Winter, 1982; Malerba and Orsenigo, 1997).
Technological regimes tend to focus on knowledge, because of EE’s underlying
knowledge/competence based view of the firm, but pay less attention to strategy, beliefs and
identity. ‘Industry regimes’ are more specific than ‘socio-technical regimes’ (Geels, 2004),
which span entire systems and various social groups.
10
I do not generalize the core element of ‘organization structure’ to the industry level. The
reason is that ‘industry structure’ would not be an institution. While I leave out ‘industry
structure, I add ‘regulatory institutions’, which are important at the industry level (but do not
form a core element at the organizational level).
11
13
interpretation of and action on an issue” (Dutton and Dukerich, 1991: 520). Mission is
more externally-oriented and signals the social purpose of industries, aiming to confer
normative legitimacy from the institutional environment. An industry’s reputation is
the perception and normative evaluation of its missions by external stakeholders
(Hoffman and Ocasio, 2001).
The core type of agency related to this core element is reputation management
(Zyglidopoulos, 2003). Branding and public relations activities are important, because
“favorable reputations may enable firms to charge premium prices, attract better
applicants, enhance their access to capital markets, and attract investors (Fombrun and
Shanley, 1990: 233). If reputations are threatened because of changes in broader
societal values, reputation management may not be enough. To secure new fit with
the institutional environment, firms may need to change their mission. Substantial
changes in mission occur relatively rarely, however, (Hannan and Freeman, 1984;
Tushman and Romanelli, 1985; Levinthal, 1992), because they usually require a
broader overhaul in organization structure, markets, technical competencies etc.12
2) Industry beliefs, mental maps, and cognitive frames
Beliefs and cognitive frames mediate how top managers interpret the signals,
opportunities, developments, and pressures from task and institutional environments.
Interpretive strategy scholars have coined various terms for this core element such as
‘industry recipe’ (Spender, 1989), ‘industry mindset’ (Philips, 1994), ‘cognitive
community’ (Porac et al., 1989), ‘strategic industry frames’ (Huff, 1982).
The literature on managerial cognition has shown that strategic choices and
decisions are embedded in and influenced by beliefs and mental models (Daft and
Weick, 1984; Isabella, 1990; Walsh, 1995; Starbuck and Mezias, 1996; Ocasio, 1997;
Weick et al., 2005; Nadkarni and Barr, 2008). The attention of managers to issues,
their interpretation of signals, and the translation into decisions are influenced and
framed by beliefs, images and identity (Hoffman and Ocasio, 2001).
I distinguish two types of agency related to this core element. The first is
sensemaking and cognitive learning (Gioia and Thomas, 1996; Weick et al, 2005).
This literature suggests that industry actors learn about their beliefs through
enactment (see also below): strategies lead to actions that produce outcomes that may
trigger reflection on the beliefs that underlie the strategy (especially if the outcomes
are surprising or disappointing). The second type is adjustment to external isomorphic
pressure from broader societal beliefs and discourses (in the institutional
environment). However, firms do not only passively adapt to this pressure. They can
also perform institutional entrepreneurship and deploy socio-cultural strategies to
influence social debates and public opinion, for instance through advertising,
information campaigns, framing, and storytelling (Lounsbury and Glynn, 2001;
Suddaby and Greenwood, 2005).
3) Regulatory institutions
Although regulations are externally imposed on industries by policy makers, they are
an important element of industry regimes, because they influence markets, innovation
processes, production decisions etc. Some examples are laws, regulations, incentive
structures such as taxes, subsidies, intellectual property rights etc.
12
Tushman and Romanelli (1985) describe this as ‘recreation’ of existing firms.
14
Although compliance is the most common type of agency (because of fear of
sanctions), firms and industries can also deploy political strategies to shape
regulations and policies, e.g. lobbying, financial contributions to political parties,
litigation, negotiations, supplying technical reports, and press conferences (Hillman
and Hitt, 1999).
4) Technical knowledge, capabilities, routines
Technical knowledge, capabilities and routines form crucial resources for firm’s
operational processes. They enable and constrain functional performance and form the
basis for technological trajectories (Dosi, 1982). At the industry level, Malerba and
Orsenigo (1997) characterize ‘technological regimes’ in terms of: a) opportunity and
appropriability conditions, b) degree of cumulativeness of technological knowledge, c)
characterization of the relevant knowledge base.
Innovation and technical change are crucial for competition between firms in
an industry. The basic type of agency is behavioural (trial-and-error) learning, as
formulated by evolutionary economics (see section 2), which includes search (R&D),
performance feedback from markets (selection), maintain the variations that work
(retention). The dynamic capabilities literature suggests further innovation
management activities such as product development, knowledge management,
alliances and joint ventures, resource allocation and investment (Eisenhardt and
Martin, 2000).
In stable situations, innovation strategies may be guided by routines (Dosi and
Nelson, 1994). But when external environments change in non-routine ways or new
technologies arise, corporate strategies also become more important for technological
change (Rothwell, 1992). Firstly, top managers can change their ‘strategic intent’ or
general goals, which alter the general directionality of innovation activities. Secondly
they exert influence through resource allocation decisions that affect the amounts of
financial resources they devote to innovative activities and the types of technologies
they invest in. Managers can thus escalate their commitment to certain technologies
(Ghemawat, 1991) and change the relative investments in (incremental) exploitation
and (radical) exploration (March, 1991).
5) Strategic orientation
Strategic orientation refers to the industry attitudes, embedded in structural relations,
regarding the external environments and industry-internal competition (orientations
and styles towards innovation). Because of industry embeddedness, strategic
orientation is multi-dimensional, oriented towards task and institutional environments
and industry-internal competition.
While strategic orientation is a structural category, strategic activities are an
actor-category, which refers to deliberate actions.13 I distinguish three main strategies,
which draw on various other regime elements. Positioning strategies focus on the
position of industry actors in the (economic) task environment. They are oriented
towards Porter’s (1980) five industry forces, and typically include supply chain
management, operations management, marketing and sales, and product-market
This ‘dual nature’ of strategy is also visible in Mintzberg et al. (1998) who distinguish five
meanings of strategy. Two of them, ‘plan’ and ‘ploy’, refer more to deliberate agency, while
the other three also have structural connotations: ‘perspective’ refers to the beliefs that guide
strategies, ‘pattern’ refers to past actions that led to the accumulation of routines and creation
of path dependence, and ‘position’ refers to structural locations in the task environment.
13
15
combinations. These strategies are informed by mission and beliefs, and constrained
by existing capabilities and technologies. “Technology defines opportunities and
constraints for corporate strategy” (Tidd et al., 2005: 224). Institutional strategies,
which include the political and cultural strategies discussed above, are oriented
towards the institutional environment (Lawrence, 1999). They draw on industry
mission and beliefs. Innovation strategies, which draw on technical competencies and
capabilities, are oriented towards industry-internal competition (see above).
Configurational relations between core elements
The core elements are internally related into semi-coherent configurations, called
‘industry regimes’. To conceptualize the form of this configuration, I build on Gavetti
and Rivkin’s (2007) proposal of a hierarchy of mental and physical elements (Figure
3). Although their model focuses on organizations rather than industries, it offers a
useful starting point because it begins to build bridges between resource based views
and evolutionary economics on the hand, and interpretive and strategic theories on the
other hand. Their hierarchy distinguishes a ‘world of cognition’, which resides in
managers’ minds and relates to deliberations and interpretations, and a ‘world of
action’ (bottom half), which relates to operational performance and the associated use
of various resources.
Values, mission,
identity, goals
World of cognition
Representation, beliefs, mindset
Strategy
(plan, heuristics)
World of action
Activities
Sensors
Stocks/resources
(production equipment, reputation, knowledge)
Figure 3: Organizational hierarchy of mental and physical elements (adapted from
Gavetti and Rivkin, 2007: 432)
Mission, beliefs and strategy provide ‘organizational templates’ (Greenwood and
Hinings, 1996) or ‘dominant logics’ (Bettis and Prahalad, 1995), because they guide
(but to not determine) the activities and resource deployments in the world of action.
The logic is not completely top-down, however, because feedbacks exist from the
world of action. “Activities generate levels or patterns of performance that are
detected selectively through sensors. Once interpreted through representations or
personal values, this feedback from the world of action can alter elements in the world
of cognition” (Gavetti and Rivkin, 2007: 432).
Although the neo(co)evolutionary, developed below, builds on this
conceptualization, it will make some adjustments. First, it will give more prominence
to technology, knowledge, and capabilities, seeing them as one of the core elements,
rather than as one of various resources. Second, it will not conceptualize ‘activities’ as
16
a core element, but as an enactment processes that is oriented towards external
environments (which are missing in Figure 3).
4. Towards a neo(co)evolutionary framework
This section develops the neo(co)evolutionary theory by linking the various pressures
from external environments (discussed in section 3.1.) to core elements and types of
agency (discussed in section 3.2.). It does so by proposing the construct of
‘enactment-adaptation cycles’, which are interactive and recursive mechanisms that
connect the external pressures from the triple embeddedness framework and to
endogenous responses and regime elements. The ‘adaptation’ part of the cycle refers
to the external pressures that stabilize or destabilize industries. The ‘enactment’ part
of the cycle refers to the strategic responses to these pressures through which actors
(partly) enact their environments by actively trying to shape them. These responses
draw on and are guided by the regime elements.
To link the various environments and core elements, the neo(co)evolutionary
theory distinguishes five ‘enactment-adaptation cycles’: 1) evolutionary cycle, which
focuses on dynamic relations between knowledge/competencies and task environment,
2) sensemaking (cognitive learning) cycle, which focuses on dynamic relations
between beliefs, strategy and external environments, 3) political cycle, which links
corporate political strategies and regulatory pressure from the institutional
environment, 4) cultural cycle, which links industry beliefs and cognitive-cultural
pressure from the institutional environment, 5) normative cycle, which links industry
mission and normative pressure from the institutional environment. Figure 4, which
for analytical and representational purposes separates task and institutional
environments, schematically represents how these cycles link regime elements to
external environments.
17
Institutional
environment
Civil society
Framing
struggles,
storytelling,
agenda
setting
Industry
regime
Interpretation
(sensemaking)
Culturalcognitive
pressure
Advertising,
PR,
information
campaigns
Normative
pressure
5
4
3
Corporate
political
strategy
Beliefs, Values,
mental identity,
models mission
Strategic orientation
(strategic intent,
resource allocation pattern)
Performance
feedback (market selection)
Regulations, incentives
(taxes, subsidies)
Regulatory
pressure
Positioning
strategy,
(trans)actions
strategic
choice
Technological competencies,
knowledge and routines
Outcomes,
responses,
experiences
Polity
Normative
values
expectations
Ideologies,
social discourse
Search,
(variation,
innovation)
1
2
Task environment
Markets, suppliers, competitors
Figure 4: Neo-evolutionary framework that connects the industry regime (triangle) to
external environments via five enactment-adaptation cycles14
The five ‘enactment-adaptation cycles’ are elaborated below by mobilizing insights
from relevant disciplines. A preliminary remark concerns the three cycles that relate
between industries and pressures from the institutional environment. Early neoinstitutional sociologists (e.g. Powell and DiMaggio, 1983) emphasized one-way
isomorphic influences that create conformity and similarity in industries. But later
neo-institutional sociologists (e.g. Scott, 2008) and organization/management scholars
shifted the focus to interactive dynamics in which firms and industries can respond
strategically to isomorphic pressures (Greenwood and Hinings, 1996, Hoffman, 1999).
Oliver (1991), for instance, distinguished acquiescence (conformity), compromise
(partially acceding to pressures), avoidance (attempting to preclude the necessity of
reform), defiance (active resistance), and manipulation (attempting to modify or alter
the pressures, e.g. through lobbying). These strategic responses are further elaborated
in the literature on ‘institutional entrepreneurship’ (Beckert, 1999; Dorado, 2005;
14
Because this article has industries as focal actor, it does not further address the relations
between policy makers and civil society (citizens, public opinion), which is still a big topic in
political science (e.g. Burnstein, 2003). This relationship is therefore represented with a
dotted arrow.
18
Garud et al., 2007). The recursive cycles, which result from external isomorphic
pressures and endogenous strategic responses, are further discussed in sections 4.3,
4.4. and 4.5.
4.1. Evolutionary (behavioural learning) cycle
The behavioural learning (trial-and-error) cycle stems from evolutionary economics,
which looks at the recursive interaction between homogenizing influences from
market selection in the task environment and variation/innovation by firms (see
section 2). The core mechanisms are competition for scarce resources, search
processes and innovation to differentiate and gain competitive advantage,
performance feedback from markets, retention of successful variations in routines and
capabilities. Based on discussions above, we can enrich the evolutionary cycle in
three ways.
First, the generation of variations (search) is not blind, but guided by strategic
orientations, which in turn are influenced by beliefs and mental models. Managers are
capable of ‘intendedly rational action’ and strategic choice (Child, 1997), which
influence directions of search and resource allocation. Second, the performance
feedback from markets may be ambiguous and require interpretation. This provides a
possible link with the sensemaking cycle (see below). Third, the performance
feedback may lead to reflections on and adjustments in the strategies and underlying
beliefs that guided the search process. Concrete innovation experiences may thus
provide ‘catalysts’ for changes in strategies and beliefs (Greve and Taylor, 2000).
This forms another possible link between the evolutionary cycle (and technological
change) and the sensemaking cycle.
4.2. Sensemaking cycle (cognitive learning, strategic choice)
The sensemaking cycle assumes an ‘attention-based view of the firm’ (Ocasio, 1997)
that conceptualizes ‘firms as interpretation systems’ (Daft and Weick, 1984) and
places cognitive dynamics and beliefs centre stage. It is based on interpretive rather
than behavioural model of agency and focuses on sense-making (Weick, 1995) and
the social construction of shared beliefs (Bijker, 1995). Interpretation and
sensemaking are ongoing processes that guide both the actions towards external
environments and the interpretation of feedbacks, experiences and results. Strategic
choice theory therefore sees strategies and deliberate choices as embedded in
sensemaking cycles. Child (1997: 70), for instance, proposes the following loop:
information evaluation  learning  strategic choice  action  outcome 
feedback of information. He further suggests that “strategic choice analysis
incorporates both subjectivist and objectivist perspectives on organizational
environment” (p. 55). The objective dimensions relate to economic and financial
performance, because firms compete in task environments where strategic choices and
competitive actions have resource implications. The subjective dimensions relate to
ideologies, beliefs, managerial cognition and perceptions of environments that
influence strategic choices.
The sensemaking (cognitive learning) cycle can be conceptualized in
evolutionary terms (Garud and Rappa, 1994; Raven and Geels, 2010), e.g. through
Weick’s ‘enactment-selection-retention model (Figure 5). Enactment contains actions
towards the environment, which are influenced by feedback loops from mental
models and beliefs. Selection consists of the interpretation of signals, which is also
19
influenced by feedback loops from beliefs (because actors use cognitive structures in
sensemaking). Actors impose meaning upon, and make sense out of, the feedback
signals from the environment, often in the form of stories. Data that fit cognitive
frames are selected, while the rest is edited out. During retention actors retain
plausible stories, link them to identity and incorporate them into mental models.
Ecological change
(context, environment)
Enactment
Selection
Retention
Feedback from identity and
beliefs on selection and enactment
Figure 5: Sensemaking as evolutionary process (Weick et al., 2005, 414)
Sensemaking at collective levels is studied by social constructivist approaches (e.g.
Bijker, 1995), who focus on the creation of shared beliefs. Because problems, threats,
opportunities and new technologies are characterized by ‘interpretive flexibility’,
social groups initially have different views and beliefs. Social interactions,
negotiations, and debates gradually lead to ‘closure’ and the emergence of shared
beliefs. The locus for selection processes are conferences, seminars, workshops, and
through technical journals, proceedings, trade journals, where ideas are proposed,
agendas are discussed, results are evaluated, views are articulated and attacked etc.
(Garud and Rappa, 1994). Power also plays a significant role at this collective level,
e.g. in creating coalitions, placing issues on or keeping them off agendas. Groups that
are “powerful, rich, and advantaged seem to have unequal access to roles and
positions to influence the construction of social reality” (Weick et al., 2005: 418).
Belief systems and sensemaking are also influenced by linkages with the
cultural-cognitive cycle in the institutional environment (cycle 4 in Figure 4).
Cultural-cognitive institutions provide categories, abstractions and typifications on
which actors draw in sensemaking activities. “At a basic level, institutions are part of
sensemaking because they shape signification (meaning-making) via interpretation
and communication. (…) In this framework, institution is akin to a coherent symbolic
code, while sensemaking is the practice of use the code” (Weber and Glynn, 2006:
1643). In their review of the sensemaking literature, Weick et al. (2005) also link
sensemaking to broader institutions: “(…) organizational members are socialized
(indoctrinated) into expected sensemaking activities and firm behaviour is shaped by
broad cognitive, normative and regulatory forces that derive from and are enforced by
powerful actors such as mass media, governmental agencies, professions, and interest
groups. (…) the media provide corporate vocabularies. (…) Thus, public discourse
appears to direct corporate attention, set agendas, and frame issues” (p. 417).
Organizational and industry beliefs are thus affected by two interacting cycles:
a) cognitive learning and sensemaking, b) cultural-cognitive pressure from the
institutional environment.
Cognitive learning usually produces incremental change, with data
accumulating within cognitive frames and existing beliefs being confirmed or
(slightly) modified. While this reproduction of beliefs creates stability and a sense of
direction, it may also produce cognitive inertia, which can lead to problems if external
environments or technologies change (Tripsas and Gavetti, 2000). Overcoming this
problem may require ‘double-loop learning’ (Argyris, 1982), which entails the
unfreezing, moving/changing, and refreezing of beliefs (Lant and Mezias, 1992).
20
Shocks, crises, external cognitive-cultural pressure, and/or reflection on persistently
low performance may trigger unfreezing, while listening to new voices, bringing in
new people or engaging in experiments that bring new experiences may facilitate
moving to new ideas.
4.3. Political cycle
The political cycle concerns the dynamic interactions between regulatory pressure and
corporate political strategy. On the one hand, laws, regulations, fiscal measures and
subsidies exert pressure on industries by shaping economic frame conditions.
Regulatory pressures thus form external incentives to which industry actors must
comply, because of coercion and threat of punishment (Powell and DiMaggio, 1983).
On the other hand, management scholars and sociologists of law suggest that
industries engage in political activities that aim at influencing the form or
implementation of policies. They identified several reasons why regulations and law
should be partly endogenized as part of ongoing struggles between policy makers and
industries. One reason is ambiguity and tensions between laws. Industries face many
regulations, subsidies, and policy programs that sometimes point in different
directions, creating opportunities for resistance. As Edelman and Suchman (1996)
conclude: “(…) empirical analyses generally suggest that legal formalist imagery is at
best an abstract ideal and that, in reality, the regulatory legal environment is often
ambiguous, contested and riddled with loopholes. (…) the overall picture is one of
non-compliance, subversion, and evasion” (p. 487).
Another reason is that states are structurally dependent on large corporations
and industries for tax revenues and economic vitality (Luger, 2000). Because
businesses are important for jobs, production, growth, the standard of living, and
economic security, policy makers often consult, deliberate and negotiate with firms
about problems and policies. Recurring interactions may lead to various types of
policy networks, which can range from state-directed, where state officials control the
policy making process, to clientele relations, where business interests control policy
(Cashore and Vertinsky, 2000). Such ‘regulatory capture’ may arise from power
imbalances (e.g. industries possessing many relevant resources such as money,
control of information, social status, expertise) or from shared beliefs, which lead
policy makers to identify themselves with the fate of certain industries (Edelman and
Suchman, 1997; Luger, 2000).
A third reason is that policy instruments are the outcome of policy processes
(e.g. problem definition, search for alternative solutions, evaluation of alternatives,
choice, implementation, evaluation). Industry actors can employ a range of activities
and tactics to influence the various phases. Building on the literature on corporate
political strategy (Miles and Cameron, 1982; Yoffie, 1988; Baron, 1995; Saloojee and
Dagli, 2000), and expanding on Hillman and Hitt’s (1999) framework, I distinguish
five general political strategies:
1) Information and framing strategy. When confronted with particular issues or
problems, industries can employ tactics such as: a) setting up research institutes that
investigate the problem and build up expertise, b) using this expertise to contest
scientific reports about the problem and draw attention to uncertainties, c)
commissioning research projects and reporting research results in order to influence
the policy framing of issues or demonstrate the (un)feasibility of possible solutions, d)
testifying as expert witnesses in policy hearings.
21
2) Financial incentives strategy. To influence policy makers, industries can: a) make
contributions to politicians or political parties, b) pay fees for speaking at conferences,
c) offer politicians lucrative jobs at the end of their career, d) bribe and corrupt
officials (illegal actions).
3) Organized pressure strategy. Industries can mobilize networks to create pressure
through: a) mobilization of employees, suppliers, customers, etc. who send letters and
pressure their representatives, b) creating fake grassroots organizations (‘astroturf’)
that claim to speak on behalf of public interests, but are funded and managed by
industries, c) create industry associations that speak for the industry.
4) Direct lobbying strategy. Industries can: a) hire lobbyists to work politicians, b)
mobilize CEOs to speak with politicians and make backroom deals. Representatives
of powerful industries (e.g. cars, oil, pharmaceuticals, ICT, banking) may even have
access to presidents or prime ministers to make their case (Yoffie, 1988).
5) Confrontational strategies. Industries can: a) openly oppose laws through litigation,
b) threaten policy makers with plant closures, layoffs, or relocation, c) refuse to
implement or obey policies, d) implement policies half-heartedly.
The political cycle implies that industries are on the one hand shaped by
policy pressures, but on the other hand use political strategies to shape particular
policies.
4.4. Cultural-cognitive cycle
Neo-institutional sociologists emphasize how cultural-cognitive institutions (‘deep
structures’) shape the beliefs and identities of industry actors by providing the cultural
categories, scripts or schemas that constitute the nature of reality and the frames
through which meaning is made (DiMaggio and Powell, 1983; Scott, 1995). These
cognitive institutions appear ‘natural’ and are often taken-for-granted. Because they
exert isomorphic pressures on industry actors, deviations appear as 'strange',
'unorthodox’ and ‘unfamiliar’. Technical innovations that do not fit in established
cognitive categories therefore tend to have low cognitive legitimacy, as
Schumpeter (1934: 86-87) already noted:
“In the breast of one who wishes to do something new, the forces of habit rise up
and bear witness against the embryonic project (...) Any deviating conduct by a
member of a social group is condemned. (...) Even a mere astonishment at the
deviation (...) exercises a pressure on the individual”.
The early neo-institutional view emphasized ‘top-down’ pressures from culturalcognitive institutions to industry beliefs and meanings. It has therefore been criticised
for determinism which leaves little room for agency and endogenous change. Later
neo-institutional scholars (DiMaggio, 1997; Dacin et al., 1999) and cultural
sociologists (Spillman, 2002) therefore performed an interpretive and discursive turn,
which argues that meaning arises from interpretation, which is an active process in
which actors draw upon cognitive deep structures. To produce meaning, actors have
to mobilize cultural institutions such as symbols and categories. Culture thus becomes
a ‘toolkit’ or ‘repertoire’ that actors use to make sense (Swidler, 1986). Culturalcognitive institutions are thus reconceptualized in more processual and performative
terms which allow for more agency: “Institutions are continually enacted and
accomplished in ongoing sensemaking processes” (Weber and Glynn, 2006: 1644).
22
Cognitive institutions form the building blocks that knowledgeable and creative actors
can mobilize in various ways, thus producing variety:
“institutions within which actors innovate (…) provide a repertoire of already existing
institutional principles (e.g. models, analogies, conventions, concepts) that actors use to
create new solutions in ways that lead to evolutionary change. Actors gradually craft
new institutional solutions by recombining these principles through an innovative
process of bricolage (…) in which bits and pieces of several legacies (or principles) are
creatively combined in a variety of new ways” (Campbell, 1997: 22; italics in original).
Ongoing sensemaking activities between actors produces ‘discourses’ as an
intermediate category between cultural deep structures and agency. A discourse is a
particular way of talking and thinking about issues, which Hajer (1995: 44) defines as:
"a specific ensemble of ideas, concepts and categorizations that are produced,
reproduced, and transformed in a particular set of practices, and through which
meaning is given to physical and social realities". Cultural deep structures thus
influence industries through being mobilized in debates and discourses about specific
issues. These debates can be about industries in general (e.g. banks, car industry),
about specific technologies and products (e.g. how the Internet will change society),
about certain problems (e.g. the seriousness of climate change and the attribution of
responsibility) or about drawbacks and promises of possible solutions (e.g. biofuels in
relation to climate change).
Industry actors, social movements, policy makers, academics, and specialinterest groups aim to shape public discourse by framing issues, problems, solutions
in various ways. The groups engage in ‘cultural entrepreneurship’ (Lounsbury and
Glynn, 2001), ‘symbolic management’ (Zott and Huy, 2007), ‘rhetorical strategies’
(Suddaby and Greenwood, 2005) and ‘storytelling’ (Zilber, 2007) on public stages
such as television, Internet, newspapers, and public debates. Various storylines,
advanced by different groups, thus compete for attention and acceptance in public
arenas (Hilgartner and Bosk, 1988). Some of these storylines become dominant and
influence public opinion and the cultural legitimacy of industries and technologies,
which in turn affect the provision of financial resources, government protection or
social support (Aldrich and Fiol, 1994; Lounsbury and Glynn, 2001). Dominant
discourses evolve over time as actors adjust their specific storylines (Hajer, 1995) to
improve their salience and resonance with wider publics (Benford and Snow, 2000).
The cultural-cognitive cycle suggests that industry actors are on the one hand
shaped by changing discourses, public opinion and cultural beliefs, while they on the
other hand aim to influence these discourses and beliefs through various cultural
strategies.
4.5. Normative cycle
Industries face general normative pressure via role expectations and behavioural
norms, e.g. that they are honest and transparent in their business dealings (no
corruption, bribing, collusion); that their products and production processes are safe,
reliable, and cause no harm to society. These general norms exert selection pressure,
because deviation can harm the reputation and social fitness of specific firms or the
normative legitimacy of entire industries.
But industries can also face specific normative pressures that are related to
certain issues. In the case of negative externalities and collective good problems,
complaints and criticisms initially come from relative outsiders (Van de Poel, 2000),
23
such as disadvantaged groups, who directly experience negative effects, or by social
movements who perceive certain general issues as problematic (Lounsbury et al.,
2003). When these groups are small, scattered and powerless, industries tend to ignore
or downplay their relevance, arguing that problems are ‘not well understood’, ‘not
caused by us’, or ‘not that bad’.
To increase normative pressures, social movement theory suggests that
activists use several strategies: a) they organize and mobilize resources such as
members, money, expertise, contacts (McCarthy and Zald, 1977), b) they draw
attention to their issue through direct actions (protest marches, boycotts, public
gatherings, petitions), c) they develop storylines and discursive frames to influence
public opinion, e.g. using dramatic examples, images and stark metaphors (Benford
and Snow, 2000); d) they ask, petition and lobby policy makers for laws, regulations
or policy programs; e) they may also nurture new technologies with solution potential
for their issue (Hess, 2005).
If these activities succeed in spreading the issue to cultural-cognitive cycles
(public discourse) or political cycles, normative pressure on industries increases.
Firms and industries may try to moderate this pressure through ‘reputations
management’ (section 3.2). But if legitimacy pressure continues to increase, firms
may (have to) change their core missions. This change process has evolutionary
characteristics if the industry front weakens and firms begin to jockey for reputational
advantage. A process of reputational competition may then lead to differentiation and
variety in missions, articulated through advertisements, public relations and annual
reports (Fombrun and Shanley, 1990). If firms that change their corporate missions
have higher fitness and performance, which depends on the strength of normative
selection pressure, other firms are likely to follow, leading to industry-wide evolution
in missions and identities.
5. Discussion
Characterizing the theory
Because of its multi-disciplinary character, the neo(co)evolutionary theory has several
important characteristics. First, it combines materialist processes (e.g. competition for
resources) with idealist processes (e.g. interpretation, struggles for legitimacy),
acknowledging both evolutionary economics and (social) constructivist theories.
Second, it incorporates endogenous and exogenous change processes in
industries, thus acknowledging both agency and structures/environments. The theory
thus navigates a middle way between under-socialized and over-socialized views of
agency (Granovetter, 1985). In fact, the theory accommodates various types of agency
and logics of action (see also Dorado, 2005): a) behavioural and routine based action
(capabilities, knowledge, standard operating procedures), b) strategic action
(‘intendedly rational’), c) sensemaking, d) institutionally shaped agency
(embeddedness). These types of agency are not an eclectic combination, but have an
underlying logic. The basis is the evolutionary economics’ view that much agency is
routine-based, giving rise to behavioural learning cycles. But actors can also become
reflexive and deliberately strategic, especially when they are faced with
environmental jolts or shocks, surprising experiences, technological threats and new
entrants, persistent low performance, new voices or outside protests. They will then
act ‘intendedly rationally’, and attempt to make ‘reasoned strategies’. These strategies
are not one-off decisions, but situated in cycles of sensemaking and interpretations.
24
Cognitions and strategies are also partly influenced by broader institutions which
indicate what is appropriate, imaginable, or formally allowed.
Third, the theory can link various degrees of innovation to types of agency and
regime elements. Incremental change relates to small changes in routines and
capabilities. Radical change and technological discontinuities involve changes in both
technological capabilities and strategy.15 Systems innovation and large-scale
transitions entail changes in all regime elements, i.e. technology, strategies, core
beliefs and mission. This kind of change also entails more institutional agency.
Fourth, the theory is both evolutionary and developmental. More specifically,
the five ‘enactment-adaptation cycles’ have an evolutionary logic, based on variation,
selection, retention mechanisms, while the overall theory is developmental, providing
explanations of industry development trajectories (see below).16 The evolutionary
logic is quite explicit for the first and second ‘enactment-adaptation cycle’
(sensemaking and evolutionary economics). But also the three cycles that relate
industries to the institutional environment have an evolutionary logic, because
institutions have been reconceptualized, not as reified static structures ‘out there’, but
as dynamic structures that are continuously enacted, leading either to reproduction or
contestation and change (Weber and Glynn, 2006; Scott, 2008). Section 4.3., 4.4. and
4.5. conceptualized these recursive cycles as a dialectic interaction between
isomorphic pressures and differentiating processes. On the one hand, institutions
create selection pressures towards conformity and similarity, thus exerting
homogenizing influences. On the other hand, industry actors respond strategically to
institutional pressures through resistance, institutional entrepreneurship, idiosyncratic
interpretations, and strategic differentiation, which create deviation, variation and
diversity within industries.17 This dialectic creates a general pattern in which
institutional selection pressures guide industry actors in some directions, but also
leave space for deviation: As Jessop (2001: 1226) concludes: “institutions select
behaviours. (…) but it is also conceded that institutions do not fully and precisely
determine the course of action. Instead, actors have some freedom to manoeuvre to
choose a path of action more or less skilfully and reflexively” (italics in original).
Successful paths and variations, which enhance social fitness, may be imitated by
other firms, leading to retention in industry regimes.
Empirical implications
In terms of empirical research, the neo(co)evolutionary theory can be particularly
useful for the following topics. First, it can be useful for comparative studies of
15
Tushman and Romanelli (1985) call this ‘reorientation’ of existing actors.
16
I want to thank Ed Steinmueller for raising this point (personal discussion).
17
With regard to regulatory pressure, for instance, Etzion (2007: 646) found that
“organizational responses are quite idiosyncratic even within a specific industry governed by
regulation that is equally applicable to all firms”. With regard to cognitive-cultural pressure,
Porac et al. (1989: 405) found that shared beliefs do not preclude cognitive variety: “it is best
to think of consensus as a set of core beliefs that are shared by many individuals within a
group but around which there exists ‘intracultural variation’”. With regard to normative
pressures variety arises from competition between firms in terms of reputation, i.e. the degree
to which they adjust their missions to societal expectations and respond to debates around
contentious issues (Zyglidopoulos, 2003).
25
longitudinal industry patterns and technological trajectories, between different
industries, between different countries for the same industry, and for changes over
time (a plausible hypothesis is that the institutional cycles have become stronger since
the 1970s). It is expected that the theory can offer more comprehensive explanations
of the directionality and speed of different patterns and trajectories by systematically
investigating: a) the strength of different cycles, b) the directionality of different
cycles (and interaction), c) the timing and sequence of different cycles.
Ad a) the cycles can have different strength or prominence, depending on the salience
of different pressure, which will influence the attention and strategic orientation of
industry actors. A plausible default position is that actors are usually more oriented
towards the economic task environment, which provides financial resources. The
evolutionary and sensemaking cycles will thus always be ‘activated’ or in the
foreground. The three institutional cycles may be backgrounded, especially during
‘periods of incremental change’ (see also Figure 1). But during ‘eras of ferment’,
background structures are opened up, leading to more prominence for the institutional
cycles. The normative and political cycles may gain strength when certain issues
become ‘hot’, influence public opinion and exert credibility pressure on policy makers
(thus ‘activating’ political cycles). The cognitive-cultural cycle is likely to become
more prominent if broader social beliefs and ideologies change, and when debates
about certain issues heat up.
Ad b) The cycles may work in different directions. Accelerations or delays in industry
patterns and technical trajectories may thus be explained by positive or negative
interactions (working in different or similar directions). With regard to climate change,
for instance, normative and political cycles generate some pressure on industries to
develop ‘green’ innovations. But public concerns do not yet translate into ‘green’
consumer choices, which means that the evolutionary cycle still stabilizes existing
(unsustainable, but cheaper and higher performance) technologies.
Ad c) Differences in the timing (when they are ‘activated’) and sequence of cycles
may explain ups and downs and twists and turns in industry patterns and technical
trajectories. Especially over longer time frames, the timing, strength and directionality
of business cycles, economic recessions, changes in political ideology and coalitions,
changes in consumer preferences, and societal debates will be useful to explain
differences between countries and industries.
The second topic for which this theory is likely to be useful is (socio)technical
transitions, because various institutional cycles are likely to become more prominent
during ‘eras of ferment’, as mentioned in the introduction. The theory may be
particularly useful to analyze the destabilization of existing regimes, which is an
important facet of transitions that has hardly been studied, because of the ‘bottom-up’
focus on radical innovations that are supposed to overthrow existing industries. While
this Schumpeterian technology-push pattern obviously exists, it is also possible that
existing regimes first destabilize and create ‘windows of opportunity’ for radical
novelties. This pattern may be more common in industries where incumbent actors
possess ‘complementary assets’ (Rothaermel, 2001). The neo(co)evolutionary theory
can explain destabilization by investigating: a) increasing strength of external
pressures, b) alignment of various pressures, c) loss of faith of industry actors in
existing regime rules.
Ad a) In the task environment, important pressures are: shrinking markets, changing
markets (shift in consumer preferences), new entrants, and technological alternatives
(see also Porter, 1980). Shrinking profits and financial losses are important indicators
26
for economic destabilization. In the institutional environment, destabilizing pressures
come from normative protests (from social movements or special-interest groups) that
damage reputations, changes in cultural beliefs and public opinion, and stricter
regulations. Loss of legitimacy is an important indicator for destabilization.
Ad b) While industries can often cope with single pressures, destabilization becomes
more likely if various pressures align and lead to a ‘perfect storm’.
Ad c) Because existing regimes create a certain ‘blindness’ (Dosi, 1982), major
changes in the environments are often associated with problems in the sensemaking
cycle. Various scholars have found that cognitive inertia, blindness, or incorrect
interpretations often delay responses or lead to wrong strategies in the case of
‘environmental jolts’ (Meyer et al., 1990), ‘unfamiliar events’ (Barr, 1998), and new
technologies (Dougherty, 1992; Tripsas and Gavetti, 2000; Kaplan et al, 2003).
Underestimating these changes, industry actors initially tend to respond with
incremental changes that stay within the bounds of existing regimes. Strategic
reorientations, turnarounds and renewals in response to external changes are therefore
often preceded by changes in interpretive schemes (Bartunek, 1984; Lant and Mezias,
1992; Barr et al. 1992). This ‘second-order learning’ in turn first requires the
unlearning existing beliefs (Starbuck and Nystrom, 1984; Tsang and Zahra, 2008) and
a loss of faith in existing regimes.
These initial ideas about interactions between external pressures, strategic
responses and regime rules can (and need) to be further elaborated. The
destabilization of existing regimes thus forms an important (and neglected) topic, for
which the neo(co)evolutionary theory can be used.
The third topic that can be better studied with this new theory is the relationship
between social problems, industries and innovation. Some basic propositions are: a)
industry actors have few incentives to address social problems, especially if these are
related to negative externalities, b) social problems are ambiguous and contested,
especially their underlying causes and associated responsibilities, c) industry actors
will not address social problems unless they are pressured to do so; d) the struggle to
address social problems is multi-dimensional, and involves normative, cultural,
political, economic and technological processes; e) normative, cultural and political
pressures are usually insufficient reason for industries to seriously address social
problems (although they may perform symbolic actions); serious industry
commitment becomes more likely if institutional pressures spill over to the task
environment, and change the economic frame conditions.
A proto-hypothesis, which needs further elaboration, is that social problems
move through several ‘enactment-adaptation cycles’ in an ideal-type pattern with the
following phases.
Phase 1: Social movements activate the normative cycle (N) by criticizing industries
for contributing to particular social problems. Industries ignore, deny or downplay the
problems.
Phase 2: Social movements mobilize resources, lobby, stage events, and articulate
particular framings to increase the salience of the issue. This way they work towards
spillovers to the cultural (C) and political (P) cycles. Firms respond by setting up
industry associations that lobby policy makers and contest the movement claims in
public debates. Discursive struggles and political contests thus become more
important.
Phase 3: If public opinion becomes more concerned about the issue, it is likely that
policy makers, who depend on voters for re-election, pay more attention to the issue
27
as well (Burnstein, 2003). Credibility pressures on policy makers may lead to early
regulations that affect the task environment. But policy makers will also be influenced
by industries, who are another important constituency, through corporate political
strategies aimed at weakening or delaying substantive regulations. As a defensive
measure, industries are also likely to adopt innovation strategies that incrementally
improve their products or processes. They may also (secretly) hedge, and begin
exploring more radical alternatives. Public concerns may also begin to spill over to
consumer preferences, although delays are to be expected because of free rider
problems.
Phase 4: If public concerns remain high, policy makers are likely to introduce tougher
regulations, create substantial subsidy schemes etc., which alter the economic frame
conditions in the task environment. The availability of feasible alternatives (either
new technologies developed by outsiders or innovations developed by incumbent)
may be a precondition for tough policy programs.18 Ongoing public debates, movies,
books, and information campaigns may also spill over to consumer preferences, and
lead to qualitative changes in market demand. Although industries continue to resist
through cultural and political strategies, the problem now begins to enter the
evolutionary and sensemaking cycles, which makes them more willing to seriously
commit to the development of technical solutions. If firms begin to jockey for position
to boost their reputation and gain first mover advantages, an innovation race may
ensue that accelerates the strategic reorientation of industries, which entails the
development of new industry missions and beliefs.
Although the phases and spillovers to cycles are enacted and contested, Figure
6 schematically represents this pattern with relatively simply arrows to reduce the
representational complexity. This pattern is an initial hypothesis that can be further
refined in several ways. Firstly, the specific mechanisms that mediate between
environmental pressures and industry responses can be elaborated. Secondly,
problems need not progress linearly through the phases (they probably rarely do).
Problems not only rise in public opinion, but can also fall, as the public gets bored or
other problems capture the headlines (Hilgartner and Bosk, 1988). Changes in
political ideology or administrations, economic cycles or setbacks in innovation
journeys may also hinder the progression of problems or lead to returns to previous
phases.19 Changes in the strength, direction and interaction of various cycles can thus
provide more sophisticated explanations of issue life cycles. Comparative case studies
of different problems, industries, and countries would be very useful to test this.
Thirdly, the pattern can be elaborated by adding the possibility that new entrants or
outsiders develop radically new technologies that offer solutions to the problem. This
may pressure incumbents to faster develop their own solutions or reorient towards the
new technologies (possibly through alliances with new entrants).
18
Some policy scientists argue that problems will not rise on public agendas until there is at
least the prospect of possible solutions (e.g. Kingdon, 1984).
19
The recession of the early 1980s, for instance, led to bailouts and rescue packages for the
American car industry, which overshadowed and hindered regulatory programs around safety,
air pollution and fuel efficiency that had started in the 1970s (Luger, 2000).
28
Phase 1: Emerging
normative pressure
Institutional
environment
N
C
P
Phase 2: Work towards
spillover to public opinion
(’culture’) and policy
C
N
P
Industry
Task
environment
Consumers,
suppliers,
economic frame
conditions
Phase 3: Early spillovers
from policy to economic
frame conditions and from
culture to consumer preferences
C
N
P
Consumers,
suppliers,
economic frame
conditions
Consumers,
suppliers,
economic frame
conditions
Phase 4: Changes in consumer
preferences and market conditions
influence industries via evolutionary
processes and sensemaking cycle
C
N
P
Consumers,
suppliers,
economic frame
conditions
Figure 6: An ideal-type phase pattern on how social problems influence industries
Limitations
Although the new theory synthesizes insights from many disciplines and approaches,
several aspects have been left out or remain underdeveloped.20 First, it does not
include psychological and biological approaches to cognition (how the mind works).
Instead, the theory is based on a more (social) constructivist view of cognition and
interpretation. Second, it does not address in any depth what goes on inside firms, and
therefore tends towards a ‘unitary actor’ perspective, which privileges the beliefs and
actions of managers at the expense of other organizational actors. The reason is that
the theory already includes three levels (firms, industry, environments). Opening up
the black box of the firm would add a fourth level and additional complexity and
theories. Still, this may be fruitful, in order to gain a deeper understanding of the
20
I want to thank Ed Steinmueller for drawing my attention some of the points below
(personal discussion).
29
internal relations between various core elements of organizations and industry
regimes (beliefs, mission, strategy, technology). Third, although power is present
(especially in the political cycle), it could be given more systematic attention, e.g.
with regard to market transitions (via resource dependence theories), sensemaking
processes and ideology. Fourth, the theory does not say much about radical
innovations and creativity.21 The theory presently focuses more on adaptation to (and
shaping of) pressures from existing environments than the creation of new
environments (e.g. around radical innovations). It also does not yet say much about
creativity and improvisation, which would require incorporation of other models of
agency (e.g. communities of practice, psychology). While some of these limitations
may form areas for future work, it is not necessary to include everything into one
theory, since this is likely to lead to an eclectic hotchpotch.
6. Concluding remarks
The article has made four contributions. Firstly, it articulated some underdeveloped
areas and problems in evolutionary economics. Secondly, it mobilized conceptual
building blocks from various literatures (neo-institutional sociology, strategic
management, economic sociology, organization theory, social movement theory) to
address these problems. Thirdly, it synthesizes these building blocks into a
neo(co)evolutionary theory that addresses interactions between industry, technology,
markets, civil society and polity. To link the influences from various external
environments to industry actors, this theory also developed a broader multidimensional view on agency, and articulated five ‘enactment-adaptation cycles’.
Fourthly, it identified several empirical topics for which this theory provides new
entrance points (e.g. destabilization processes in transitions, social problems, and
longitudinal industry trajectories) and developed several propositions.
In terms of generalizability, I expect that the theory is particularly relevant for
‘eras of ferment’, complex technologies and systems (Figure 1) and for industries
with strong political influences, high public visibility, and normative contestation (e.g.
automobiles, pharmaceuticals, oil, electricity, biotechnology, nuclear). In these
industries, the cultural, political and normative change cycles are likely to be
prominent, besides the sensemaking and evolutionary cycles.
While refinements of individual cycles remain important, a general challenge
for future research is to study the various interactions between cycles and the dynamic
patterns that result from these. As Dacin et al. (1999: 339) conclude in their review of
the embeddedness literature:
“Studies that examine the linkages between and among the different sources and
mechanisms of embeddedess are few, either across levels or combining levels and
sources/mechanisms. In fact, there is relatively little theory to guide us in designing such
studies. (... We need) more attention to interplay of multiple mechanisms of
embeddedness over long historical periods.”
The neo(co)evolutionary theory aims to provide a fruitful framework for addressing
these challenges.
Acknowledgements
21
I want to thank Mike Hobday for this point (personal discussion).
30
I want to thank Mike Hobday, Ben Martin, Caetano Penna, Ed Steinmueller, Fred
Steward, Bruno Turnheim, and Jeroen van den Bergh for their thoughtful and
stimulating feedback on previous versions of the paper. This work has been supported
by an ERC grant.
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