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. GeelsSPRU, Science and Technology Policy ResearchUniversity of SussexUnited Kingdomf.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 under-developed 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.

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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 under-developed 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 by technological discontinuities (Figure 1). The competition between different design 1Nelson (1977; 2008b) forms one of the exceptions.

2 But see Geels and Schot (2007) for a distinction of other transition pathways besides technological substitution.

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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.

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).

5 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).

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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 neo-institutional 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).

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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) technological innovation studies, and an emerging competence/capability-based theory of the firm” (Dosi and Grazzi, 2006: 177).

8 I want to thank Mike Hobday and Ed Steinmueller for bringing this point to my attention (personal discussion).

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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 firm-specific 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:

“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.”

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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 over-emphasized 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 Strategic factorsEffective linkages with external sources of know-how

Top management commitment to, and visible support for, innovation

Effective functional integration; involving all departments in the project from its earliest stages

Long-term corporate strategy in which innovation plays a key role

Careful planning and project control procedures

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 problemIn 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” (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.

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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:

“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

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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’, 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

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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 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

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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) cultural-cognitive (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.

Figure 2: Triple embeddedness framework of industries9 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’.

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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 ISI citations

Hannan and Freeman (1984: 156)

Hierarchy of four core organizational elements1) 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 organization3) 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.

1098

Leonard-Barton (1992)

Four dimensions of core capabilities:1) values and norms2) managerial systems3) technical systems4) employee knowledge and skills

785

Tushman and Romanelli (1985: 175)

Hierarchy of five activity domains:1) core values and beliefs set constraints as to where, how, and why a firm competes2) business unit strategy defines the nature of products produced and markets served and establishes general time and technological constraints3) Intra-organization power distributions control the allocation of scarce resources4) The organization’s fundamental structure formalizes hierarchy, role relations and competitive emphases5) The nature, type and pervasiveness of control systems indicate a firm’s emphasis on efficiency

511

Levinthal (1992)

Three organizational sub-systems:1) Technical sub-system relates to skills and capabilities associated with the organization’s operating activities2) Managerial sub-system relates to coordinating and resource allocation functions3) 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

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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

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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 industry-level 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 missionIdentity 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 inward-oriented, 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 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

10 ‘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.

11 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).

12 Tushman and Romanelli (1985) describe this as ‘recreation’ of existing firms.

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2) Industry beliefs, mental maps, and cognitive framesBeliefs 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.

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, routinesTechnical 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,

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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 orientationStrategic 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 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 elementsThe 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.

13 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.

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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 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

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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.

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 neo-institutional sociologists (e.g. Powell and DiMaggio, 1983) emphasized one-way

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.

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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; 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

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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 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.

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).

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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). 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

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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.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 cultural-cognitive 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

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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). Cultural-cognitive 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). 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 special-interest 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

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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), 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 theoryBecause 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

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(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. 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 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).

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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 implicationsIn 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 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

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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 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.

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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 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

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).

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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).

Figure 6: An ideal-type phase pattern on how social problems influence industries

LimitationsAlthough 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

20 I want to thank Ed Steinmueller for drawing my attention some of the points below (personal discussion).

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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 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 multi-dimensional 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.”

21 I want to thank Mike Hobday for this point (personal discussion).

29

The neo(co)evolutionary theory aims to provide a fruitful framework for addressing these challenges.

AcknowledgementsI 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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