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SMALL FIRMS AS COMPLEX ADAPTIVE SYSTEMS: A REVIEW
Ted Fuller and Paul Moran
Abstract
'Complexity' may best be understood as a systemic paradigm which explores the dynamics of systems which areopen and dissipative and consist of interconnected agents. The implications for addressing small business from a
complex, dynamic perspective are explored and a number of potential future directions for research are suggested
Some caveats are also raised about the dangers of simplistic 'mapping' of complexity metaphors onto the smallbusiness 'domain'; and the importance of instrumental, ontological and theoretical adequacy of the models
employed in small business research is stressed. It is argued that at this stage in the understanding of small firms,
this can best be achieved through empirical grounding in the small firms domain so as to understand the dynamics
of small business in-depth, over time and in relation to the wider business ecology.
Introduction
This paper attempts to articulate the potential relevance of the 'sciences of complexity' to the field of small busine
research. 'Complexity' is an emerging inter-disciplinary field of investigation into the behaviour of a wide range osystems in the natural and physical worlds and indeed in the silicon world inside computers (eg Casti 1997). The
field represents a 'convergence' (eg Pagels 1988) of several strands of scientific endeavour in different disciplines
and is most strongly associated with the Santa Fe Institute in the US (see Waldrop 1992, Lewin 1993) and thepublication of a growing volume of accessible works by scientists and science writers (Gell-Mann 1994, Holland
1998, Kauffman 1995, Goodwin 1994, Cohen and Stewart 1994, Prigogine 1980, Prigogine and Stengers 1984,
Coveney and Highfield 1995, Kelly 1994, Gleick 1988); including those which are somewhat sceptical/critical (eg
Horgan 1996). This might only be of passing relevance to small business researchers were it not that 'complexity'appears to have resonance with, and may have potential for crossover to, the human social and organisational
domains. A number of works have been produced exploring the application of 'complexity' models, metaphors and
methods to organisations (Stacey 1996), management (Lissack 1997) and even entrepreneurs (Rydall 1996).Whether they apply to small firms and, if so, how, is an issue yet to be addressed by those in the small business
field. The proposition which this paper attempts to explore and further elucidate is: to what extent is it useful and
appropriate to consider the 'small firm' from the perspective of 'complexity'; what insights does it provide and whaspecific researchable issues stem from it? Furthermore, what is the potential application to firms themselves in
terms of managerial tools, techniques and interventions?
Complex Adaptive Systems
A systemic paradigm
Complexity studies is a systemic paradigm, founded on observed similarities in diverse dynamical systems. Itilluminates meaning from a dynamical perspective. The essence of dynamical systems is that they are open and
dissipative, they do not follow the predictable entropic path of closed systems tending to chaos, rather they move i
patterns "at the edge of order and chaos" (Waldrop 1992). An important part of complexity research is to illuminachanges in patterns of relationships between objects in the system and provide explanations of why one pattern,
rather than another, can be detected. The similarities of different dissipative systems, such as ecologies, insect
populations, brains, etc. give rise to a number of linguistic schema or metaphors by which similarities in these
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different phenomena can be compared. These metaphors provide a language to describe patterns of behaviour in
complex adaptive systems. The metaphors are of dynamics and form.
To comprehend a system we must, as researchers cognitively construct or model them. The act of defining a syste
creates ontological closure. Social systems are open systems. Complexity theory addresses dissipative opensystems; interconnections of "agents" that can both receive and expend energy from sources external to the
"system". The flow and location of energy and its relationship with the actors or agents within the system is ofprime importance in explanations of dynamical patterns. Examples of similar patterns found in studies in many
different domains, from thermodynamics to population studies have influenced a shift in social perceptions of how
complex (adaptive) systems behave. It is important to understand however that the body of knowledge that
currently constitutes complexity studies is grounded in the natural sciences, not in the social sciences.
Complexity and scientific realism
A number of authors, e.g. McKelvey 1999, Reed and Harvey 1992, have noted the proximity of complexity to the
epistemology of scientific realism (Aronson, Harr and Way 1994, Suppe 1989), and in social sciences to criticalrealism (Bhaskar 1978, Outhwaite 1987, Sayer 1992). Realism provides philosophical principles upon whichdynamical non-linear characteristics can be understood. For example, the appearance of novel structures and
patterns can be explained in terms of the contingent or latent powers inherent in the interrelationships, rather than
by the external imposition of order. One epistemological implication is that causality is not identified from the
observation of empirical regularities per se. Causality in a specific context may be traced by theory building usingconcrete, intensive methods (Harr 1979) but does not carry the same construct of being generalisable that the
notion of causality carries in social positivism. Complexity is itself a scientific ontology.
'which fits Bhaskar's philosophical framework: one which treats nature and society as if they wereontologically open and historically constituted; hierarchically structured, yet interactively complex;
non-reductive and indeterminate, yet amenable to rational explanation; capable of seeing nature as a"self-organising" enterprise without succumbing to anthropomorphism or mystifying animism.'
(Reed and Harvey 1992:359)
The case for linking complexity to small business and entrepreneurship research
If a "system" under investigation is assumed to behave as a dissipative system, or as a complex adaptive system,then metaphors of the general dynamics of these systems may provide a conceptual framework for understanding
the dynamics of that specific system. That is, general features of dynamical systems can explain specific
corresponding instances. In this paper the idea that small firms create complex adaptive systems is taken as aproblematic, not an assertion.
Complexity studies as a general enterprise is one in which system worlds are created, their dynamics observed, andinferences drawn about real world behaviour and explanations for this. System worlds are created at varying levels
of abstraction from the reality of the objects they represent. In computer simulations for example, properties of rea
world objects are abstracted, represented and used as building blocks, becoming in effect the theory of therepresented world.
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Complex social systems
In assimilating a systemic approach into a study of the social world, there is an explicit acceptance of what Cohenargues as the "insight that organisms are systems" (Cohen 1998). For example, in a rubric to students, Axelrod
(1998) suggests that a research goal is to "discover new principles about the dynamics of complex systems,especially complex adaptive systems which are typical of social processes". Protagonists have assimilated stronglythe scientific metaphors. For example,
"The evolution of dissipative social systems is chaotically driven and is sensitive to initialconditions. The structure is generated by symmetry breaking mechanisms and is consequentlyontologically layered... These evolutionary properties establish the foundations for the historicity of
the entities and the events under consideration." (Harvey and Reed 1996:306).
And, according to Byrne, (1998b) these systemic ideas transcend the limitations of the homeostatic systems model
basic to Parsonian structural-functionalism. Complexity enables us to reflect the character of the social world as
consisting of complex nested systems with a two way system of determinant inter-relationships among the levels.Also, it
"...enables us to deal with both of the crucial problems identified for any sociological theory by
Mouzelis (1995). It provides a way of relating the macro and the micro which is not inherently
aggregative and reductionist and it provides a way of describing the relationship between agency andstructure which takes account of Elias's assertion of the fifth dimension of reflexive human
consciousness." (Byrne 1998b, Chapter 2).
The analogies with small businessOn the surface at least, the population of small firms seems to resemble the characteristics Holland ascribes to a
complex adaptive system, i.e. an:
"evolving perpetually novel world where there are many niches with no universal optimum ofcompetitor, where innovation is a regular feature and equilibrium rare and temporary and where
anticipations change the course of the system, even when they are not realized" (1995).
They can also be conceptualised to fit John Casti's working definition of a complex adaptive system (Casti 1998).
An account of this is given later, but comprises a population of "individual agents" who adapt their rules ofbehaviour over time.
If the population (or sub-populations) of small firms are analogous with notions of a complex adaptive system, the
in what ways can complexity theory inform an understanding of the dynamical behaviour of small firms? How canit help in anticipating change in the population of small firms?
Evolutionary metaphors of emergence, fitness and replication resonate with observations of the large number of
smaller firms in the economy. Small businesses are not a homogeneous population. They vary considerably in size
and sector activity, in their ownership, their location and the markets served etc. Some of the features of their
domain are shared common. Most businesses interact with key economic stakeholders, such as banks andgovernment agencies. Businesses operate in a regulated environment, providing at least some of the "rules" of
behaviour. The fundamental exogenous "energy" or resource of most businesses is cash, without which activities
usually cease.
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Are the analogies strong enough?
Prima faciecomplexity theory has something to offer small business and entrepreneurship research. But howshould this be used?
Those searching for "science" in their research of society, including the domain of business, are attracted tocomplexity because of its scientific antecedents. Complexity studies provide for the social scientist many
metaphors of dynamical systemic behaviour. Are these metaphors analogous with social "systems"? Rosenhead
(1998) and Fuller (1999) both critique the elevation of metaphors, grounded in non-analogous phenomena, to thestatus of causal reasoning in social systems.
Surface validity
In understanding the small firm, operational definitions such as its number of employees or turnover lack
ontological depth. The firm may need to be understood to exist simultaneously at many layers, possibly
unconnected, and each having different meaning and different characteristics. This is partly why it is so difficult tomake interdisciplinary research work; each is concerned with a different ontology. The strong ideas of symmetry
breaking and the creation of novel ontological layers provide a theoretical dimension to investigate multiple layer
of firm characteristics and dynamics.
One contribution that complexity theory makes to small business and entrepreneurship research is that it provides
for nested hierarchical ontological layers. It also provides concepts for making sense of changing patterns in thedata. This might be thought of as "holistic", but this word carries too many meanings to be of value in this
argument. The notions of emergence, bifurcation and symmetry breaking in complexity are all notions of the
"natural" formation of structures that behave with different characteristics from the agents that constitute the
structures. This provides, for example, general propositions for why the small firm does not behave exactly like it
owner.
It is suggested that the analogy of a complex adaptive system can provide a conceptual framework to understand o
illuminate the dynamics of small firms. Each business is different. Each has its own "initial conditions" and each
incurs a number of "accidents" in their temporal path. Given that entrepreneurs are "innovative", then manybusinesses will operate with their own "rules", as well as complying (more or less) to more general rules. There is
great deal of "replication" in the population as one firm copies another's ideas and government policy encourages
firms to adopt "best practice". However, acceptance of these analogies should be accompanied by due caution.
Critique of metaphor
There are difficulties, in epistemological principles, with this approach. It is open to a fallacy that metaphors are thsame as reality. Models are fictitious constructions; the language "as if" not "what is". (Harvey and Reed
1996:309). Complexity is a discourse of models and abstractions. Models, as opposed to theories, are well-formed
metaphors and analogies. They do not claim to express the truth of the world, merely to provide heuristic insightsFor example, how can the completeness of a "system" be verified?
At issue is the extent to which patterns identified empirically, or modelled theoretically in the physical and naturalsciences provide ontological adequacy. Is it plausible to use, in a reasoning process, metaphors of fitness, of
attractors, of emergent properties, of rules and conditions and have adequate grounding of meaning in the busines
domain?
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As Rosenhead points out in a critique of some current "complexity" management texts:
"It hardly needs saying that there is no formally validated evidence demonstrating that the
complexity theory-based prescriptions for management style, structure and process do produce the
results claimed for them" (1998:10).
The concern is that models that are grounded in natural science take on meaning in the social sciences without
theoretical or ontological adequacy. Such is the power of metaphor in language that the meaning taken from these
systemic studies is, arguably "what is", not "as if". Understanding through language is one way in which the huma
interpreting mechanisms are "coupled" to the environment. Inferences about the real world have real meaning, thecause particular sense-making (Weick 1995) and cause particular behaviour. Meanings are culturally shaped andthe power of conceptual ideas transmitted by particular linguistic allusions is important. Reflecting on phenomena
through a particular languaging gives those phenomena meaning which in turn guides behaviour. This is a far from
trivial issue. People's actions in business are shaped by the language they use.
The task therefore for complexity research in the domain of small firms, as with other social worlds, is to developontological and theoretical adequacy. This, suggests McKelvey (forthcoming), is some way off at present.
Methodology
If we are to progress beyond a mapping of natural science "complexity metaphors" onto social phenomena, then wneed to follow sound epistemological and methodological principles in order to ground theory in social worlds.
Methodology is about how we conceptualise, theorise and abstract (e.g. Sayer 1992:2); our modes of explanation,
understanding, research design and methods of analysis. The term "methods" is used here in a narrow meaning of
techniques used in the process of research. An important feature of complexity theory is that the mode ofexplanation is through dynamical models.
Model centred science
How is theoretical adequacy to be achieved? McKelvey (forthcoming) suggests that the trend in (the philosophy o
science is not to link theory with the phenomenon directly, but to link theory through models. In this so called"model-centred science", the (computational) model is linked to the phenomena. Testing for the adequacy with
which the model represents the empirical or detected reality is possible (though fallible). To link theory to the
model, counterfactual tests are applied to the model. Thus theoretical development is linked to (computational)model development to create experimental and ontological adequacy. McKelvey (forthcoming) implies that
organisation science in general has not reached this level of maturity, and comments reflexively that "the
coevolution of the theory -- model link is in its infancy" (p36).
Systemic causality
Understanding causation in a system requires a systemic approach. A focus on reduction of the system to elementis inadequate. The whole contains things which are not deducible from a description of any part of it. The issue, as
with all modelling, is the validity of the abstractions used. Allen (1998) provides a useful discussion on the issue o
ontological closure and micro-diversity or micro-states in this context. Methods adopted in complexity researchhave largely been that of observation of the effects of dynamics and experimentation through simulation to
(re)create recognisable dynamics. The nature of computer simulation, paradoxically, is that of deterministic, and
essentially closed, systems, though methods such as the introduction of errors can simulate "accidents".
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ecological process. Schendel (1996:1) suggests research in evolutionary perspectives of strategy is not well
developed in relation to how it needs to be:
"The nature of evolutionary work is its dynamic, longitudinal nature, its use of the entire population
of strategically similar organisations and its consideration of both failure and success."
Directions
Beyond metaphor
In its assimilation into the small business domain, complexity theory may become trapped in its own metaphors,but there are at least four areas in which it can move beyond the metaphor.
Firstly, the notion of the small firm, or some attribute of the small firm, as an adaptive agent, is highly resonant
with Schumpeterian notions of entrepreneurial innovation. Indeed, Schumpeter's work stimulated Nelson and
Winter's (1982) contribution to evolutionary economics. The "adaptive" (entrepreneurial) actions -- "the capacity o
seeing things in a way which afterwards proves to be true, even though it cannot be established at the moment",(Schumpeter 1934:85.) appear reflexive, i.e. taking into account the existing perspectives and external stimulus
(Lewis and Fuller 1998). This reflexivity is perhaps more likely to be understood through the investigation oflearning and social processes, rather than a two-dimensional systemic concept of adaptation. The articulation of
rule-like, reflexive behaviour, or the nature of the learning that gives rise to changes in reflexive responses has not
yet been adequately codified.
Secondly the notion of the firm as being part of a wider "ecology" or nexus of stakeholder relationships and action
(Fuller 1997) is significant in theorising the small firm. The nature of these relationships is not well articulated in
the literature. For example its representation in agency theory (Williamson 1991) as a nexus of contracts does notadequately take account of qualitative or non-economic factors. The nature of the relationship between the
environment and the small firm or various aggregations of small firms is a complex issue and not explained by anysingle substantive theory. Naman and Slevin (1993) identified a relationship between organisational complexity anenvironmental complexity. Gibb (1993) provides a descriptive model of the firm as having various "relationships"
with a range of organisations. Mitchell and Agle (1995) set these relationships in a theoretical framework as
"stakeholder relationships". Stakeholders include owners, employees, customers, suppliers, investors and lenders.Small firms are theorised as operating in "networks" by a number of authors including (Johannisson 1987, Jarillo
1988, Lorenzoni and Ornati 1988, Larson 1992, Castells 1996). These studies stress the importance of both social
and economic rationale for the relationships.
This discourse on the importance of relationships between the individual firm and other "agents'' in its environmen
is resonant with the "multi-agent space" of artificial life simulations, such as SWARM (Hiebeler 1994). However,
the nature of the relations and "coupling" between small firms and their environment is not well enough understooto have yet produced plausible complex adaptive models.
Thirdly, the notions of fitness, and the maintenance of fitness, are synonymous with "competitiveness". Life is shofor most small firms and the rate of new firm formation alters in different conditions. Which conditions favour
sustainability and which favour emergence? Different perspectives provide different answers to this. The differing
perspectives of economists seeking efficient markets, bankers seeking to minimise risk, owner managers trying noto lose money or trying to achieve personal ambitions each provide different and somewhat judgmental
interpretations. Maintaining fitness in complex adaptive systems is said to be informed by what Holland calls "loo
ahead". Lane and Maxfield (1995) address this with regard to strategy in organisations, arguing that only those
"inside" the system can have any sense of prediction of strategies. The concept of fitness and emergence in
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alternative conditions is also to be found in the work of Fuller et al (Fuller 1999) on foresighting. Their approach
uses Maturana and Varela's (1980:136) idea of structural coupling to simulating the emergence of typicality of new
firms and innovation from scenarios of alternative (future) initial conditions. In small business research, linksbetween conditions and systemic fitness is largely empirical and judgemental, with little theoretical explanation.
Fourthly, the nature of complexity theory lends itself to investigations of emergence, of innovation, of the creationof structures and the (generative) inter-relationships between firms and stakeholders. An example of linking the
analytical ontological perspective of inter-relationships with model-centred theory is in the work of Gillies et al
(1998). The significance of clustering and networks as a business strategy and an economic development (policy)strategy will attract other research into this methodology.
Two central research questions around clustering, collaboration and network formations are:
what (non-accidental) regularities are significant to the continuing existence of the cluster
and
in what ways are transitions in regularities initiated and/or sensed by the firms themselves (self-organising
systems).
Where next?
The key issue of adequacy remains. It is easy to slip into a mapping of complexity metaphors onto the domain of
small business as the past few paragraphs demonstrate. It is easy to develop a language of evolution grounded in th
natural sciences and teach business people this language. They will act on this understanding, and some will makeit work. It is simple to use complexity and complex adaptive systems as an analytical post-hoc framework to
account for regularities. Our challenge as researchers and teachers is to develop, with our colleagues in the socialsciences, instrumental, ontological and theoretical adequacy for our models.
The application of complexity to the small firms domain requires in the first instance a different way of looking at
small firms themselves, the people within them and the environment in which they operate ie the total system and
the connections between the 'parts'. In this context, some key research questions to be addressed might include thefollowing:
What effect do 'initial conditions' have on the subsequent development of the business?
In what sense are small firms 'adaptive'? How does this 'adaptiveness' come about? What is the role of theowner-manager and other stakeholders in relation to this?
Similarly, how do small firms become 'fitter'? What attributes, capabilities and resources are necessary tooptimise fitness within a particular 'landscape'?
What degree of 'connectedness' do small firms have? How important to survival and growth is this, not just
to the firm but to the whole 'ecology' of which the firm is a part? Is there an optimum degree of
connectivity?
In what sense do small firms co-evolve with one another/other stakeholders? What is the result of this co-
evolution?
How do small firms learn about their environment? How do they make use of this learning to make
'adaptive moves'?
To what extent do small firms aggregate and create self-sustaining systems (eg 'clusters')? What
evolutionary characteristics emerge within these higher order systems?
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Why do firms network? Why do these relationships continue or discontinue?
What sense-making and schema-building strategies do owner-managers use to improve the positioning of
the business and thereby increase the chances of survival?
At this stage these are open questions which constitute a possible research agenda for the study of small businesswithin the complexity framework. A number of writers have begun the task of exploring some of these issues albe
at the level of speculation and conceptualisation (Freel 1997, Fuller 1996, 1999, Garnsey 1998, Moran 1997). Whis needed are some 'real-world' empirical studies to test out some of the notions drawn from complexity with
populations of small firms. These should not necessarily be hypothesis-testing exercises but rather exploratory and
inductive research using complexity notions to orient research studies and identify complex, dynamical form orattempt to explain observed behaviour from the perspective of complexity.
The role of simulation studies in this context could be to model a process or behaviour either prior to empirical
observation or subsequently so as on the one hand to guide the empirical study or on the other to contribute tovalidation of the findings (Pagels 1998). Such iteration between grounded observations and modelling can be
informed by model-centred science.
Apart from introducing new methodologies such as simulations, the study of small firms as complex systems
imposes a requirement on researchers to work at close quarters with small firms to gain an intimate understanding
of the whole business in-depth and over time and the wider system (network/cluster/value chain) of which it is apart. This entails an emphasis on qualitative, longitudinal and 'whole system' (eg Checkland 1984, Senge 1990)
methodologies. The aim being to create new and useful knowledge about the behaviour and evolution of small
businesses as systems and the intelligent agents of which they are constituted and whose interactions create the
emergent properties of the system.
What is being advocated therefore is a paradigm for small firms research which connects it more closely to other
fields of research that are concerned with the behaviour of dynamical systems but also recognises the 'singularity'(Garnsey 1998) of small firms. Small firms are thus viewed as human systems or agents within a wider (socio-
economic) system, which inhabits the natural world and therefore should to some degree have properties of form
and function in common with it.
A particular area of connection is likely to be with the study of organisations and other human systems. The Santa
Fe Institute is involved in working with companies to introduce complexity into management. Companies such asVisa (see Tetenbaum, 1998) and SENCORP (see Mitleton-Kelly 1997) are reported to be structured and run on
complexity principles. The particular area of overlap with small firms may be in relation to the 'disaggregated' (or
networked) form of organisation which according to some writers (eg Castells 1996) is becoming the dominant
form and to which the 'connected cluster' of small firms bears a strong similarity (albeit with greater differentiatio
in the latter), thus blurring the distinction between 'small' and 'large' and the boundaries between individual firms.
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About the Authors
Ted Fuller is Director of the Foresight Research Centre at Durham University Business School, UK. Paul Moran i
Senior Tutor and Head of the Network Unit in the Small Business Centre at Durham University Business School,
UK.
Contact details:
Durham University Business School
Mill Hill Lane
Durham DH1 3LBUK
Tel: +44 (0)191 374 2237 Fax: +44 (0)191 374 3748 E-mail: [email protected]
Tel: +44 (0)191 374 2245 Fax: +44 (0)191 374 1239 E-mail: [email protected]