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Moving Beyond Metaphor

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The proposal that the metaphors associated with complexity theory can inform the business world is made by several writers (Wheatley, 1992; Stacey, 1996; McMaster, 1996, Merry, 1995), but is open to critique that the metaphors are not grounded in the field of study, but in other domains that may or may not be analogous. In previous articles, the authors (Fuller, 1998, 1999; Fuller and Moran, 1999) have illustrated the apparent analogies between complex adaptive systems and the world of small firms. However, because there is no grounding of these analogies in that domain, there is no evidence that complexity theory has validity in describing or explaining empirical observation. For example, a new firm starting up may be associated with the metaphor of emergence, but whether theories of emergence as developed in thermodynamic systems have any analogous properties with a business start-up is problematic. This article investigates how complexity theory can inform an understanding of small firms, which we posit as an example of socioeconomic systems, in a more rigorous and scientific way than metaphor. Our approach to this is to investigate the possibility of a methodology that is plausible in its relationship to small firms, and developed from the conceptions and literature of complexity.
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EMERGENCE, 2(1), 50–71
Copyright © 2000, Lawrence Erlbaum Associates, Inc.
Moving Beyond Metaphor
Ted Fuller and Paul Moran
The proposal that the metaphors associated with complexity
theory can inform the business world is made by several
writers (Wheatley, 1992; Stacey, 1996; McMaster, 1996,
Merry, 1995), but is open to critique that the metaphors are
not grounded in the field of study, but in other domains that may or may
not be analogous. In previous articles, the authors (Fuller, 1998, 1999;
Fuller and Moran, 1999) have illustrated the apparent analogies between
complex adaptive systems and the world of small firms. However,
because there is no grounding of these analogies in that domain, there is
no evidence that complexity theory has validity in describing or explain-
ing empirical observation. For example, a new firm starting up may be
associated with the metaphor of emergence, but whether theories of
emergence as developed in thermodynamic systems have any analogous
properties with a business start-up is problematic.
This article investigates how complexity theory can inform an under-
standing of small firms, which we posit as an example of socioeconomic
systems, in a more rigorous and scientific way than metaphor. Our
approach to this is to investigate the possibility of a methodology that is
plausible in its relationship to small firms, and developed from the con-
ceptions and literature of complexity.
Methodology is about how we conceptualize, theorize, and abstract
(e.g., Sayer, 1992): our modes of explanation, understanding, research
design, and methods of analysis. In this article, a methodological position
is developed, grounded in the literature of complexity theory and in sub-
stantive small business research literature. The methodology embodies
philosophical principles, concepts, ontology, questions, methods, and
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ethics. The purpose of the article is to open discussion on these method-
ological aspects. The purpose of the methodology is for application to
real-world problems and issues in small business.
HOW COMPLEXITY INFORMS METHODOLOGY
Complexity is a science concerned with nonlinear dynamics and open,
dissipative systems. Central to the enterprise would seem to be analogy,
with dynamic modeling as a mode through which descriptions of dynamic
behavior are made; for example dynamics as changes in patterns of rela-
tionships, in the emergence of events or conjunctions through time
phases, and of the emergence of forms that display apparently different
characteristics from their constituent parts. Approaches to modeling are
varied, and include computer simulation (Hiebeler, 1994) and tracing of
historic evolutionary paths (Gould, 1989). Models, too, provide a mode of
explanation in terms of the results of unpredictable effects of multiple
causal powers (e.g., codified as “rules” of behavior or inheritance). The
effect on the researcher of such modeling is to create explanatory frames
of reference that guide further abstraction and modeling.
In assimilating a systemic approach into a study of the social world,
there is an explicit acceptance of what Cohen argues as the “insight that
organisms are systems” (Cohen, 1998). For example, in a rubric to stu-
dents, 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 the scientific metaphors. For example:
The evolution of dissipative social systems is chaotically driven and is
sensitive to initial conditions. The structure is generated by symmetry
breaking mechanisms and is consequently ontologically 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 (1998), these systemic ideas transcend the limi-
tations 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 interrelationships among the levels. Also, it:
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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 and
structure which takes account of Elias’s assertion of the fifth dimension of
reflexive human consciousness. (Byrne, 1998, Chapter 2)
Those searching for “science” in their research of society, including the
domain of business, are attracted to complexity because of its scientific
antecedents. Complexity studies provide the social scientist with many
metaphors of dynamical systemic behavior. Are these metaphors analo-
gous with social “systems”? Rosenhead (1998) and Fuller (1999) both cri-
tique the elevation of metaphors, grounded in nonanalogous phenomena,
to the status of causal reasoning in social systems. The approach is open
to a fallacy that metaphors are the same as reality.
The mistake here is directly to link metaphors of complexity with
empirical experience. At issue is the extent to which patterns identified
empirically, or modeled theoretically in the physical and natural sciences,
provide ontological adequacy. Is it plausible to use metaphors of fitness,
of attractors, of emergent properties, of rules and conditions, and to have
adequate grounding of meaning in the business domain?
We suggest that these metaphors do not provide ontological adequacy
per se, but have a role in informing the design of models or abstractions
that may have such adequacy. From an evolutionary perspective, this kind
of methodological positioning can legitimately be developed as poten-
tially fallible, and from a scientific perspective it requires substantive rea-
soning or evidence for its claims. One issue arising from this is, therefore,
how we test the adequacy of this work at a level of meaning. What is its
instrumental reliability? We posit methods for this later in the article,
attempting to find a starting point, with links to the empirical domain, for
an investigation of the value of complexity science to the understanding
of certain characteristics observed in small businesses.
A number of authors—e.g., McKelvey (1998); Reed and Harvey
(1992)—have noted the proximity of complexity to the epistemology of
scientific realism (Aronson, Harré, and Way, 1994; Suppe, 1989), and in
social sciences to critical realism (Bhaskar, 1978; Outhwaite, 1987; Sayer,
1992). Realism provides philosophical principles on which dynamical
nonlinear characteristics can be understood. For example, the appearance
of novel structures and patterns can be explained by a conception of con-
tingent or latent powers inherent in the interrelationships, rather than by
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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
using concrete, intensive methods (Harré, 1979), but does not carry the
same construct of being generalizable 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 were ontologically 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 anthropo-
morphism or mystifying animism. (Reed and Harvey, 1992: 359)
THE CASE FOR LINKING COMPLEXITY TO SMALL
BUSINESS AND ENTREPRENEURSHIP RESEARCH
Small firms may lend themselves particularly well to a complexity-based
research paradigm, possibly more so than large corporations, since the
latter may be “overcomplex” (“complicated”?) in the sense of Kauffman’s
notion of “complexity catastrophe” (see Kauffman, 1993, 1995). This is
because of the tendencies toward excessive (imposed) order, centraliza-
tion, overengineering etc., which can result in a reduction of the overall
fitness of the system and a thwarting of the selectionist process. As
McKelvey (1999) puts it, “internal complexity leads to complexity
catastrophe but external complexity leads away from catastrophe,” thus
pointing up the importance of decentralized, disaggregated structures,
following the logic of autonomous but co-evolving “patches” (Kauffman,
1995), which is resonant with our understanding of how small firms
behave. Organizational theorists have not been able to mount a convinc-
ing case so far that modern corporate organizations can be adequately
studied from within the paradigm of complexity, apart from in a purely
metaphorical sense. As Rosenhead points out in a critique of “complex-
ity” management texts:
It hardly needs saying that there is no formally validated evidence demon-
strating that the complexity theory-based prescriptions for management
style, structure and process do produce the results claimed for them.
(1998: 10)
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A small firm, by contrast, is relatively simple as an entity, although with
possibilities of complex behavior arising because of the influence of the
human agent (usually one person, i.e., the owner-manager/entrepre-
neur), and the high degree of interaction with other firms/agents that can
lead to the evolution of new forms of structure. Such structures may be
perceived, for example, as networks or clustering. The small firm can
thus be viewed as a (relatively) simple system and as part of a more
dynamic, complex whole, where multiple agents and interactions take
place, giving rise to phenomena such as “swarming” and other emergent
behavior.
Empirically, populations of small firms resemble the characteristics
that Holland ascribes to a complex adaptive system, that is,
[an] evolving perpetually novel world where there are many niches with
no universal optimum of competitor, 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 realised. (1995)
Evolutionary and ecological metaphors of emergence, fitness, and mim-
icry 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, the markets served, and so on. Each business is different. Each
has its own “initial conditions,” and each incurs a number of “accidents”
in its temporal path. Given that entrepreneurs are “innovative,” many
businesses will operate with their own “rules,” as well as complying
(more or less) to more general rules. Business strategies explicitly opera-
tionalize the metaphor of “niche specialization.”
Some of the features of businesses’ domain are common or shared.
They all interact with key economic stakeholders, such as banks and gov-
ernment agencies. Businesses operate in a regulated environment, pro-
viding at least some of the “rules” of behavior. The mimicry of doing busi-
ness, i.e., copycat methods and the diffusion of information through
benchmarking and best-practice guides, is ubiquitous. Swarming is com-
monplace, for example physically in business districts and clusters (e.g.,
Gillies et al., 1998), or in the use of particular technologies (e.g., North et
al., 1991). And energy, in the form of cash and perhaps technological
innovation, flows within the system, with those firms that do not maintain
cashflow or adopt new ideas ceasing to operate.
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COMPLEXITY DYNAMICAL CONCEPTS IN THE WORLD
OF SMALL BUSINESS
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 as a surface description of
observed behavior. These areas are interlinked, but conceptually
different.
Take first the notion of the small firm, or some attribute of the small
firm, as an adaptive agent; see, for example, Rydal, 1996; Casti, 1997. The
notion of an adaptive agent is highly resonant with Schumpeterian
notions of entrepreneurial innovation. Indeed, Schumpeter’s work stim-
ulated Nelson and Winter’s (1982) contribution to evolutionary econom-
ics. The “adaptive” (entrepreneurial) actions—“the capacity of 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,
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 of learning and social processes, rather than a
two-dimensional, systemic concept of adaptation. The articulation of
rule-like, reflexive behavior or the nature of the learning that gives rise to
changes in reflexive responses has not yet been adequately codified.
Adaptation is conceptualized herein as a reflexive process, one in which
the adapter exercises agency.
Second, the notion of the firm as being part of a wider system, “ecol-
ogy,” or nexus of stakeholder relationships and actions (Fuller, 1997) is
significant in theorizing the small firm. Small firms are not individual
entities per se, but part of interrelated structures of relationships. 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 not adequately take account of qualitative or non-
economic factors. Small firms are theorized as operating in “networks” by
a number of authors (e.g., Johannisson, 1987; Jarillo, 1988; Lorenzoni and
Ornati, 1988; Larson, 1992; Castells, 1996). These studies stress the
importance of both social and economic rationales for the relationships.
However, the nature of the relations and “coupling” between small firms
and their environment is not well enough understood to have yet pro-
duced plausible complex adaptive models. In the complexity literature,
relationships between the individual agent and others are often defini-
tionally implicit, yet crucial. For example, in the “Ant” rules—Coveney
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and Highfield, 1995: 250, if you find food, take it home and mark a trail;
if you cross a trail and have no food, follow the trail to the food etc.—the
crucial relationship between the ant colony, the behavior of individual
ants and food is axiomatic, and the necessary relationship between ants
and food for survival is implicit. Relationships are conceptualized herein
as interdependent powers between firms, individuals, other agencies,
and other objects or mechanisms.
Third, the notion of fitness, and the maintenance of fitness, are syn-
onymous with “competitiveness,” but also with growth or survival. Life is
short for most small firms and the rate of new firm formation alters in dif-
ferent conditions. Maintaining fitness in complex adaptive systems is said
to be informed by what Holland calls “look ahead.” Lane and Maxfield
(1995) address this with regard to strategy in organizations, arguing that
only those “inside” the system can have any sense of prediction of strate-
gies. The concept of fitness and emergence in alternative conditions is
also to be found in the work of Fuller et al. (Fuller, 1999) on foresighting.
Their approach uses the idea of structural coupling to simulate the emer-
gence of typical new firms and innovation from scenarios of alternative
(future) initial conditions.
In small business research, links between conditions and systemic fit-
ness are largely empirical and judgmental, with little theoretical explana-
tion. This leads to a critique of empirical discovery of regularities associ-
ated with “success” at any point in time. Most positivist research in the
small business field makes claims with regard to the association of
hypothesized factors and some form of success. There is no evidence that
this has any predictive capability, nor any explanatory value. There have
been some classic errors, such as Peters and Waterman (1988). From a
complexity perspective, the reason that such empirical evidence is unre-
liable as a guide to behavior is that the systemic interdependencies or
reflexive linkages between the firm and the environment are not ade-
quately understood from an external perspective. More fundamentally, in
open systems fitness is a highly dynamic and unpredictable state.
Fitness is conceptualized herein as a state of relative performance,
which may be the result of reflexive adaptation. It may be articulated or
described partly in terms of relationships, but is inherent to a firm within
its context, i.e., it is relative.
Fourth, the causal concept of structural emergence through self-
organization or autopoiesis provides a powerful methodological construct
for the investigation of change in the small firm domain. The production
of results from the Prigogine and Lefever experiments (Prigogine and
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Stengers, 1984) showed that nonlinearity occurs in a chemical reaction if
a product catalyzes its own production, a feedback process known as
autocatalysis. Prigogine introduced the term “dissipative structures” (the
dissipation of introduced energy) to emphasize the origins of self-organi-
zation in far-from-equilibrium thermodynamic processes.
This idea of a system retaining energy through the formation of addi-
tional structure resonates with Anderson’s ideas of “symmetry breaking”
(Anderson, 1972). This implies that dynamical systems do not become
ever more complex, in a “flat” sense of more features, although they do
create new structures, new ontological levels. If the systems were
entropic, then they would become more chaotic. Dissipative structures
do not necessarily become more chaotic, but dissipate entropy to outside
the system. According to Harvey and Reed (1996:306), sustainable dissi-
pative systems:
convert free energy into more elaborate forms of internal construction;
transport thermal disorder (positive entropy) out of the “system” (into
the environment);
the resulting net negative entropy gives rise to evolution;
the system is far from equilibrium.
Luhmann’s work (e.g., 1986) is seminal in linking autopoiesis to social sys-
tems. Open systems are dynamic: energy flows within them and in and
out. The precise circumstances that give rise to an ordering property are
unique, unlikely to exist more than once. The existence of novel form cre-
ates novel conditions and vice versa. The authors’ guide to theorizing,
abstracting, or conceptualizing is a sense of what Allen (1997) calls an
“evolutionary tree of successive structures.” In this context, the arrow of
time is one way, not reversible—events cannot be undone, nor ever
repeated exactly.
Such a central concept as autopoiesis we believe is significant in
developing a methodology for researching small firms in a complexity
paradigm. This is developed in the next section of the article through the
idea of ontological layers. An example of linking the analytical ontological
perspective of interrelationships with model-centered theory is in the
work of Gillies et al. (1998). However, autopoiesis may also inform an
understanding of other creative processes, for example innovation and
generative relations (Lane, 1996).
Emergence is conceptualized herein as the concrete result of a reflex-
ive or self-organized, creative or generative process, whose form may be
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empirically observed, or whose presence empirically sensed.
These four main concepts—reflexivity and learning, relationship with
the environment and other agents, fitness and innovation, and autopoietic
structural emergence—may perhaps be understood as interlinked facets
of a process of contingent adaptation and survival in a population of small
firms. The concepts inform a methodology with surface validity for inves-
tigating the dynamics of small firms. The claim for validity is that the
dynamical characteristics that the concepts label in experimental fields of
complexity have analogical or metaphorical resonance with observations
in the small firm domain.
SMALL FIRM ONTOLOGY
The central property of dynamical systems of symmetry breaking and the
creation of novel ontological layers provides a theoretical dimension to
investigate multiple layers of firm characteristics and dynamics. The firm
may need to be understood to exist simultaneously on many layers,
possibly unconnected, and each having different meaning and different
characteristics. This is partly why it is so difficult to operationalize inter-
disciplinary research work: each discipline is concerned with different,
epistemologically or ethically separated, ontology, not just different per-
spectives on the same phenomenon.
A challenge for small firm research is to define the relevant “ontolog-
ical layers” of the small firm “domain” and how these may interrelate and
possibly give rise to emergent behavior and structures. Clearly, some
ontological layers are outwith the scope of small firm research, but are
nevertheless important as influences on “micro states.” As McKelvey
(1999) points out, modeling of complex adaptive systems is focused on
how micro-state events (including human agents or firms) “self-organize
into emergent aggregate structure.” The division of structures is impor-
tant here as a means of maintaining emergent structure far from equilib-
rium (i.e., “negentropy”) and therefore a networked form of structure is
potentially more stable and adaptive over time than one based on merg-
ing structures (i.e., a large corporation) (see for example Kelly, 1995;
Castells, 1996). The latter requires large amounts of energy to sustain it
and will be incapable of rapid change; whereas the former is dynamic,
adaptive, and, because of the very nature of its structure, does not require
large overall amounts of energy to sustain it (the energy inputs are in
effect “localized” due to the independent actions of adaptive agents).
Figure 1 illustrates six theorized ontological layers, derived from the
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canon of research literature within the small firm domain, and the
“boundaries” at each end. For small firms, the relevant layers are posited
to range from “micro economies” to individual mental models and cogni-
tion (e.g., of the entrepreneur). The layers are intended to reflect key
areas of research and debate in the small business field, i.e.,
networks/clusters (e.g., Chaston, 1996; Curran et al., 1992; Hansen, 1995;
Johannisson, 1987, 1995); external relationships in the value chain (e.g.,
Hall and Andriani, 1998; Lewis and Fuller, 1998; Mitchell and Agle,
1995); business model/strategy/vision etc. (e.g., Atherton and Hannon,
1997; Gibb and Scott, 1986; Miller and Toulouse, 1986); internal
resources/processes (e.g., Garnsey, 1998; Hendry et al., 1995); capabilities
and motivations (e.g., Bellu and Sherman, 1995; Carsrud et al., 1989;
Harrison and Leitch, 1994; Miner, 1997); individual cognitions etc. (e.g.,
Chell et al., 1991; Gatewood et al., 1995; McGaffey and Christy, 1975;
Moran, 1998). Beyond the “top” boundary is where aggregations become
superordinate structures such as the macro or global economy. Below the
“bottom” boundary is where physiology, biochemistry, and so on down to
the quantum level influence individual cognitions, mental models etc.
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Layer 1 Networks/clusters/micro economies
Layer 2 Business-to-business relationships
Layer 3 Business model (concept/strategy/vision)
Layer 4 Internal "functional" activities/relationships
Layer 5 Individual capabilities/motivations
Layer 6 Individual cognitions/mental models/constructs/values
Macro economy
Physiology
etc.
Figure 1 Posited ontological layers in the small firm domain
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These are also ontologies but of different “domains,” albeit impinging on
the small firm “domain,” which is about how ways of seeing, thinking, and
so forth are manifested through successive ontological layers to result in
micro-economies of small firms existing in interrelationship with each
other. In effect, the diagram reflects how small firm “ecologies” are built
up from particular “micro states,” including individual personal charac-
teristics and attributes of human psychology, through successive emer-
gent realities.
The question arising from the above is to what extent these ontologies
(or “perspectives”) reflect real-world mechanisms with causal properties,
and how they might be operationalized in real experiments or studies.
There is an issue here about the “permeability” of the “layers” in terms of
the tendency among researchers to stay within tightly prescribed disci-
plinary boundaries. This is particularly important in this context in
exploring the interactions between layers or how emergent properties
arise from the lower-level micro-state interactions. Focusing solely within
one layer may result in a limited view of the overall phenomenon and of
how the “reality” of one layer is due to behavior or events at the layer
below reaching some critical threshold (or “phase transition”) sufficient to
create new, emergent structure or form. Thus, while the “business
model” within the small firm domain (layer 4) may be legitimately stud-
ied in its own right, only a partial understanding (in the widest sense) will
be achieved if the forces and influences that give rise to it at lower onto-
logical layers are ignored or “assumed away” as not being germane.
However, from an existential perspective, it must be remembered that a
phenomenological entity termed “a business” can only exist because of a
particular nexus of human activities and relationships, influenced them-
selves by particular competencies, drives, cognitions, and sense-making
mechanisms. This reinforces the importance of the “bottom-up” nature of
complexity science (Epstein and Axtell, 1996).
An example of research reaching down through several layers is cur-
rently in progress by one of the authors (see Moran, 1998). This research
originated in the personality profiling of owner-managers (level 6) and
how these relate to “growth orientation” (level 5). This is now being
developed through in-depth interviews to explore issues such as the
future shape and direction of the business (level 3), and key external rela-
tionships and their impact on the business (level 2). For completeness,
the internal processes and relationships should also be explored (level 4).
Being able to make connections between findings from different “layers”
for the same cohort of firms may enable the construction of systemic
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models reflecting the complex, dynamical nature of small firms arising
from particular micro-state realities, which can be tested within the
“model-based science” paradigm using simulations (see Casti, 1997).
RESEARCH QUESTIONS IN A FIELD OF STUDY
From the above analysis—i.e., four significant complexity concepts and
six small firm ontological levels that can be posited as having a hierarchi-
cal or nested relationship—a potential field of study emerges. Drawing
on the previously discussed concepts of autopoesis and symmetry break-
ing, conceptually we would expect that the dynamics associated with
complex adaptive systems would be related to the linking of hierarchical
(emergent) ontological structures. Thus we can generate a plausible field
of study by the simple cross-tabulation of these two sets of characteristics,
shown in Figure 2. The range of research questions generated in this con-
ceptual space requires further work. Some examples of substantive
issues, still largely understood only in atheoretical (empirical or heuristic)
terms in the domain of small firms, are given below (see Table 1).
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L1 Networks/clusters/
micro economies
L2 Business-to-business
relationships
L3 Business model
(concept/strategy/vision)
L4 Internal "functional"
activities/relationships
L5 Individual
capabilities/motivations
L6 Individual cognitions/
mental models/constructs/
values
Adaption
Relationships
Fitness
Emergence
1 1, 5 2 3
4
88
7
6
9
10
Figure 2 Ontological levels tabulated with complexity dynamical concepts
(numbers refer to Table 1)
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Dynamical processes can only be understood through a time dimension.
This might be historical or “real time.” We suggest that there is little or
no historic evidence available that has been gathered through the con-
ceptual framework developed in Figure 2. This requires further investi-
gation, but it is likely that a longitudinal study is required if an empirical
grounding is sought.
METHODS
The authors propose an iterative modeling/grounding approach to opera-
tionalize this research. They take the view that knowledge of the workings
of any social system (of which the small firm is posited as being part)
requires deep insight that is normally only available to its experienced
actors. The common sense that such insights might generate may be shown
ultimately to be “wrong,” but insights are, we suggest, closest to making
sense of experienced dynamical processes at the relevant ontological layer.
In such a case, the methodology demands the participation of system actors.
We further propose that in order to operationalize a methodology that
takes account of dynamical properties, some form of simulation model is
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Table 1 Some research questions relevant to the field of study generated
1 In what sense do small firms co-evolve with one another/other
stakeholders?
2 What is the result of this co-evolution?
3 To what extent do small firms aggregate and create self-sustaining
systems (e.g., “clusters”)? What evolutionary characteristics emerge
within these higher-order systems?
4 Why do firms network? Why do these relationships continue or
discontinue?
5 What are relevant boundaries to the firm?
6 What is the role of the owner-manager in the process of adaptation
in a small firm?
7 How are firms deemed to be fitter or less fit over time?
8 Does a firm’s fitness co-evolve with stakeholders?
9 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?
10 What new concepts do owner-managers develop from their
experiences?
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required. The construction of this model should be informed by
grounded theory or propositions of salient features identified initially by
inspection of the literature and by intensive (Harré, 1979) reasoning from
empirical evidence. This in itself may require considerable fieldwork, or
can draw on existing research.
Simulations may help to clarify interactions and emergent patterns
that might be fed back to assist in strategic decision making and execu-
tive action. In other words, the research enterprise would not merely be
a way of creating new knowledge and models, but of adding practical
value to the small firm community (i.e., create a “fitter” ecology from an
evolutionary perspective). This requires that results of simulations are
validated through field testing over time. The schema for this is illus-
trated in Figure 3, a Mandala or loop of modeling and testing, implying a
learning or theory-building process.
We therefore propose a method that iterates between everyday practice
and analogous modeling. The method is guided by the concept shown in
Figure 4, which places interpretation centrally, communicated through
language and shared theory in practice between researchers and actors in
the domain. Modeling provides an experimental form for scientific analy-
sis (McKelvey, 1998); practice provides a grounding and testing of the
emergent or evolving theories. In a sense this is a closely coupled micro-
cosm of social theoretical evolution.
It is important to note from Figure 3 that the intermediate step of
model building is required to “convert” observations and data into some-
thing that can be simulated in order to facilitate more in-depth under-
standing of the phenomenon. The simulation is thus only as good as the
dynamical model from which it is derived. The loop is then closed by the
testing of the outcomes of the simulation in relation to the real-world
agents from which further observations/data would continue to be
VOLUME #2, ISSUE #1
63
Dynamical model
Observations/data Simulation
Actions/strategy
(validation)
Figure 3 Generic research cycle
Issue 2-1 31/3/01 7:48 pm Page 63
collected, and the dynamical model refined accordingly for further itera-
tions of the simulation. Any such model would abstract features from the
experience of the observers, but its linkage in this process could ground
the features in the day-to-day experiences of actors, providing a sense of
salience.
We propose to use this simulation with actors (i.e., owners of small
firms) as a way of helping them understand and articulate their worlds
(i.e., the systems of which they are a part). We conceptualize that such an
action will lead to a reconceptualizing of the individual or shared “the-
ory” of the system, which in turn may lead to new strategies or behavior.
The degree of utility and resonance that the models have for these actors
will act as a test of instrumental reliability. The models themselves can be
independently tested for robustness, for example by the use of counter-
factual tests (see example below).
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Model
world
Dynamic
(modeled)
simulation
Conceptions—
expectations and
explanations
Day-to-day
practice
Representing
Testing
Sense making
Acting
Forming
"models
as theory"
Reflexes
Guiding discovery
of salience
Strategies
Experimental adequacy/
postdictive power
Metaphors, models.
language, reasoning
Figure 4 Model of evolutionary theory building through modeling,
insight, and practice
Issue 2-1 31/3/01 7:48 pm Page 64
THE ETHICAL CONSIDERATIONS OF THE
PROPOSED METHODS
This approach has ethical and practical issues associated with it. A par-
ticular perspective here emphasizes the utility of research within the
human systems domain, particularly focusing on the researcher/client
relationship. In small firm research there is the possibility of intervention
to the benefit or detriment of the firm, particularly if the researcher
appears to be a “credible” source. Being wholly detached/objective is dif-
ficult if the work involves working inside the small firm with the owner-
manager and/or other members of the company. There is certainly scope
for researcher and owner-manager (practitioner) to influence and learn
from each other through a positive feedback cycle. This is resonant with
Schon’s (1991) notion of “reflective research,” where the researcher uses
both observation and intervention to help the practitioner develop insight
and capability (“reflection-in-action”). Of course, it is also important that
the researcher recognizes when not to intervene and understands the
importance of using experimentally valid methods within the research
inquiry.
The challenge therefore is to develop a research methodology in the
small firm domain that seeks to build productive relationships with
owner-managers as clients/practitioners in order to acquire a deep(er)
understanding of systemic processes, relationships, and dynamics in
small firms. This understanding can then inform the building of improved
models, which can lead via testing to better interventions and improved
capability in the small firm domain and thus, potentially, “better” (i.e., fit-
ter) small firms.
OPERATIONALIZING THE RESEARCH
The research paradigm suggested here might be interpreted either as a
whole methodology, or as a method. From a methodological perspective,
the model could help to position and make coherent discrete research
activities. As a method, interactive modeling between researcher and
small business owner (as decision maker) is relatively novel.
Three examples of the authors’ current research are given below,
showing how the metaphors of complexity contribute to the post hoc
interpretation of present findings (rather than the framing of the original
research).
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EXAMPLE 1
The longitudinal research with owner-managers described above (Moran,
1998) is intended to explore research questions as detailed in Figure 2
(particularly 6, 7, 9, 10) concerned with the interaction of individual agent
(owner-manager) and the business “system.” The research conducted to
date has focused on developing insight into the “psychology” of a cohort
of owner-managers and linking this to an independent (quasi-perform-
ance) measure of “growth orientation” (GO). Thus, relationships can be
explored between personal characteristics and orientation toward the
business (ontological levels 5 and 6) in such a way that “rules” for adap-
tation and learning linked to the fitness of the business entity (system)
may be derived and tested further. The research is currently entering a
“grounding” phase in which actual performance and development of the
businesses can be related to the assessments of the individual owner-
managers from the initial study. This will help to ascertain the degree of
predictive validity of the previous measures and deepen our understand-
ing of the processes of change and the influence of the individual agent
on them. This move takes the research to ontological level 3, with a con-
tinuing linkage through to levels 5 and 6.
EXAMPLE 2
A study of small firm stakeholder relationships (Lewis and Fuller, 1998)
grounded a typology of relationships, through a qualitative analysis of in-
depth interviews with about 40 small firms. Some five separate
approaches to relationships were identified, which can be used to cate-
gorize individual firms in the sample. This work provides insights into the
nature of the firms’ responses to changes in the stakeholder environment,
in particular to new uses of information and communications technology.
As such, it helps to identify reflexivity, which can be conceived as agency
(causing change) in a dynamical system. Further ethnographic studies
were also carried out to discover whether an owner-manager’s perspec-
tive or relationship style was carried through in the whole business.
Conceptually, this links level 2 with level 6 in Figure 2, which may itself
present a healthy critique for the ontology per se.
EXAMPLE 3
In the development of foresight among groups of businesspeople and
their stakeholders, it is common to develop scenarios of future possible
worlds and to extrapolate from these the nature of business opportunities
and innovations. The process involves explicit “soft” modeling of the
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landscape, i.e., making assumptions about the interconnections between
different actors and the relative strengths of forces and relationships.
From the process of describing and constructing these mental landscapes,
the actors intuitively create possible strategies and rationale for these.
The soft models can be subject to some counterfactual examination of
“what ifs” (Fuller, 1999; Carrier et al., 1999).
Each of these examples informs an interpretation from a complexity per-
spective, but none employs the complete methodology in the sense out-
lined here. However, these research activities have between them many
of the methodological characteristics. For example:
Longitudinal and able thus to provide a descriptive sense of change in
the case of these businesses and owner-managers (Example 1).
An objective assessment of “initial conditions” through the employ-
ment of the GO criterion (Example 1).
Concerned with the “trajectory” of development and how this is per-
ceived and influenced by key agents in the system (Examples 1, 3).
Concerned with the agents’ perspective of the “system” in which they
operate and to what extent this perspective influences or guides their
“strategy” (adaptive moves) (Examples 1, 2, 3).
Attempts to uncover some of the “intrapersonal” influences on the
dynamics of small business development and how these inform the
owner-manager’s perspectives and actions (Examples 1, 2).
The complexity perspective is important here in introducing a theoretical
framework concerning the behavior of agent-based systems that are open,
dynamic, evolving, and sufficiently complex to be capable of “emergent”
behavior. This framework directs attention to particular aspects of the
phenomenon and provides a language for describing what is observed.
This language is in terms of dynamical systems and seems to fit intuitively
with what we know about small businesses (e.g., they are many, varied,
interconnected, and subject to rapid change, including growth, decline,
or “death”). The involvement of the human agent (i.e., the owner-
manager) entails a concern with “reflexivity” (i.e., conscious intention can
be a significant factor in the making of “adaptive moves” and these are not
wholly dependent on environmental stimuli). In principle, models can be
developed that take account of reflexivity in explaining how particular
developments and outcomes occur.
The way in which this research can be developed to further the
VOLUME #2, ISSUE #1
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methodology is of considerable interest to the authors. The aim would not
be to describe the “whole” small business system, but to focus on under-
standing the dynamics of adaptation, learning, and change at both the
individual and business level, and how they interact to produce particu-
lar outcomes. The role of adaptive agents (owner-managers) is critical
here, as are their connections (relationships) with other adaptive agents
within a networked “community.”
The selection of salient modeling features from the process of ground-
ing attributes such as personality types, typologies of rule such as
reflexive behavior, actor descriptions, and soft models of the relevant
landscapes provide a rich basis for abstraction and modeling and the pos-
sibility of scientific approaches to theory testing.
The practical output from this research could be particular “sense-
making” tools that could be used by owner-managers themselves or their
advisers to understand their situation better and improve their ability to
make better adaptive moves. There might also be the opportunity
afforded by the building of dynamical models to explore alternative “tra-
jectories” of business growth/development at particular critical junctures
in order to aid decision making. The opportunity to test out
models/processes via simulation studies might also be explored.
NOTE
The authors gratefully acknowledge the feedback on an earlier draft of this article from par-
ticipants in the EIASM Workshop on Complexity and Organisation in Brussels, Belgium,
June 25–26, 1999.
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We discuss the notion of complexity as applied to firms and corporations. We introduce the background to complex adaptive systems, and discuss whether this presents an appropriate model or metaphor to be used within management science. We consider whether a corporation should be thought of as a complex system, and conclude that a firm within an industry can be defined as a complex system within a complex system. Whether we can say that the use of complexity research will fundamentally improve firm performance will depend on the effect on success derived from its application.
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Four different aspects of the anticipation, agency, and complexity conundrum are analyzed: best practices, evidence-based policies, innovation and value creation, and pragmatic utopias. These four aspects are arranged according to their level of simplicity and contentiousness, from the simple and less contentious to the complex and highly contentious, and are related to decision-making. Although the connection is overly explicit for best practices, evidence-based policies, and innovation and value creation, it may appear less straightforward for utopias. This chapter frames utopia as the internal driver of innovation, as the sense-making process internal to decision-making that is able to keep it open.
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The transition to the knowledge economy is the most salient element of the recent transformations of the world economy. The predominant feature of this transition is the intensified use of technological and scientific knowledge in the production process. This transition is also related to a seemingly paradoxical phenomenon, the emergence of localities as focal points of economic activity in a globalizing world economy. Many see this phenomenon as an indication that the world economy is gradually shifting from a polycentric economic geography of almost self-sufficient, highly diversified, state-protected and inward-looking national production systems to one of interconnected, globally positioned and regionally embedded concentrations of specialized economic activity.
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Article Summary) Van Uden et al assert that the world is best described as being a complex system, and, through the use of the 'complexity' discourse, students of organizations--organizations being regarded as complex sub-systems of the whole--can benefit from the various complexity science research programs. They argue that complexity theory in this respect is reminiscent of postmodern organization theory. Full Text (9320 words) Copyright TamaraLand Publishers 2001 [Headnote] ABSTRACT [Headnote] In this paper we simply assert that the world is best described as being a complex system, and, through the use of the 'complexity' discourse students of organisations -organisations being regarded as complex sub-systems of the whole --can benefit from the various complexity science research programs. The paper supports a complexity-based view that essentially justifies the need for paradigmatic pluralism and boundary exploration. We argue that complexity theory in this respect is reminiscent of postmodern organisation theory, contrary to the New Reductionism of the majority of complexity writings. We will discuss some important observations in complexity theory and explore, in a rather playful fashion, how the insights could affect our understanding of organisations.