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Abstract

This paper will discuss some introductory issues related to the role and importance of microdiversity of agents in the context of business networks. Traditional views emphasise the importance of connectivity in the making of industrial clusters, but neglect the crucial role of microdiversity. Microdiversity is important to achieve adaptive behaviour in the presence of environmental uncertainty. Diversity acts as a reservoir of potential strategies against unpredictable environments. Secondly, the formation of business networks is explained in terms of mechanisms generating diversity. Networks emerge as the organisational form in which the diversity of agents can self-organise. This paper suggests that the issue of diversity can be used to discriminate between the model of organisation based on rational allocation of resources — the firm — and the model of organisation based on emergence and self-organisation — the network. The paper concludes that the former is a diversity-reducing mechanism, whereas the latter is a diversity-enhancing mechanism.
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International Journal of Innovation Management
Vol. 5, No. 2 (June 2001) pp. 257–274
© Imperial College Press
DIVERSITY, KNOWLEDGE AND COMPLEXITY THEORY:
SOME INTRODUCTORY ISSUES
PIERPAOLO ANDRIANI
University of Durham Business School
Mill Hill Lane, Durham City
DH1 3LB
United Kingdom
e-mail: Pierpaolo.Andriani@durham.ac.uk
Received 20 November 2000
Revised 20 February 2001
Accepted 27 February 2001
This paper will discuss some introductory issues related to the role and importance of
microdiversity of agents in the context of business networks. Traditional views emphasise
the importance of connectivity in the making of industrial clusters, but neglect the crucial
role of microdiversity. Microdiversity is important to achieve adaptive behaviour in the
presence of environmental uncertainty. Diversity acts as a reservoir of potential strategies
against unpredictable environments. Secondly, the formation of business networks is ex-
plained in terms of mechanisms generating diversity. Networks emerge as the organisational
form in which the diversity of agents can self-organise. This paper suggests that the issue of
diversity can be used to discriminate between the model of organisation based on rational
allocation of resources — the firm — and the model of organisation based on emergence
and self-organisation — the network. The paper concludes that the former is a diversity-
reducing mechanism, whereas the latter is a diversity-enhancing mechanism
Keywords: complexity, knowledge, networks, microdiversity, clusters
Introduction
The study of complex systems is based on the assumption that there is more
to a system than the sum of the components and the linkages that compose
the system — be the system a city, a colony of ants, a brain’s neurons or a
cluster of firms. Systems show properties that are truly emergent, irreducible
258 P. Andriani
to explanations that take into account only lower level components’ properties.
Simple experiments (Kauffman, 1995; Nicolis & Prigogine, 1989) demonstrate
that the transition from an aggregate to a system (Juarrero, 1999) takes place
when a phase transition alters the fundamental dynamical properties of the system’s
components. This corresponds to a transition from a regime of independence,
where the components’ properties are largely independent from their context,
to a state of co-evolution. In the new state the co-dependence among components
generates a systemic context, that affects the properties of the components. As
Rescher (1979: 109) claims: “The root idea of system is of integration into
orderly whole that functions as an organic unity.” The overall set of models,
frameworks and theories inspired by the principles mentioned above are known
under the umbrella term of complexity theory.
A distinctive aspect of complexity theory concerns the dialectics between
the properties of agents and the properties of systems. A system emerges when
the self-organisation of agents generates ordered structures at the system level.
Two properties are at the base of self-organisation: connectivity and microdiversity.
Whilst the former is the object of a large literature, the latter is relatively unexplored.
This paper will focus on the role of microdiversity in the context of socio-
economic networks.
This paper is structured in the following way. In the first section, I discuss
the importance of diversity and show the centrality of diversity in networks
and complex systems. Secondly, I explain the formation of business networks
in terms of mechanisms generating diversity. Thirdly, I describe some elements
of the complexity theory and show how complexity is a useful framework to
describe the formation of networks. Fourthly, all the previous concepts are merged
around the idea of distributed systems of knowledge. Finally, there are some
concluding remarks.
The Importance of Diversity
The role of socio-economic diversity has received marginal attention in economics
(Grabher & Stark, 1997; Metcalfe, 1994; Saviotti, 1996; Saviotti & Mani, 1995;
Stirling, 1998). Diversity is seen as necessary to promote an innovative environment,
to avoid technological lock-in, to promote political representation and to balance
different political views (Stirling, 1998). In complexity theory (Holland, 1995;
Kauffman, 1995), internal diversity is seen as a fundamental requisite of systems
in order to achieve a higher rate of adaptability. Diversity is also a prerequisite
for self-organisation. I shall in the following examine these aspects of diversity.
Ashby’s (1960) principle of requisite variety states that the internal variety
of a system should match the variety of the external environment. The response
Diversity, Knowledge and Complexity Theory 259
capability of a system should be at least as varied as the set of stimuli that
the system receives from the environment. In this way, the system can successfully
respond to environmental threats and opportunities. For example, a simple
environment generates a simple set of stimuli, which in turn can be faced in
relatively simple ways by organisations. This is one dimension of diversity, a
static dimension. In stable environments, once the right degree and kind of diversity
are achieved, there is no further need to modify the system’s diversity. The
situation changes if the rate of environmental change becomes faster. In this
case, matching a fast changing environment demands adaptability, that is, the
capability to change internal functional structure at the desired rate. What becomes
critical then is the speed of change. Interestingly, in evolutionary biology, adaptability
is connected with internal diversity. For instance, Fisher’s famous evolutionary
theorem makes evolutionary rate of change (adaptability) dependent upon genetic
variance. On a similar note, Gould claims that genetic variance based on redundancy
(including the bits of DNA that seem useless) constitutes a pool of possible
responses to be activated when established co-evolutionary strategies fail.
Evolution is a messy process brimming with redundancy. An organ might
be moulded by natural selection for advantages in one role, but anything
complex has a range of other potential uses by virtue of inherited structure
… any vital function restricted to one organ gives a lineage little prospect
for long term evolutionary persistence; redundancy itself should possess
an enormous advantage” (Gould, 1993).
Therefore, a system that exhibits both diversity and redundancy (redundancy
ensures that internal diversity does not result in isolated fragments) is more
capable of adaptive behaviour than a more simple system. Internal diversity
then plays a double role: on the one hand it provides a static matching with
the environment, and, more importantly, on the other hand, it provides the key
element for matching environmental changes over time. Interestingly, when
environmental change becomes turbulent and characterised by uncertainty, even
the capability of fast tracking environmental changes may not be enough for
survival. Radical changes may demand either a structural reconfiguration of the
organisation or the emergence of new types of organisation. Under these
circumstances, a strategy based on matching predicted environmental change
turns out to be impossible to devise and implement. In this issue, Allen (2001)
introduces the law of excess diversity, that is, the idea that a sustainable and
successful evolutionary strategy requires an amount of internal diversity superior
to that of the environment. Allen suggests that agents need to have a stock
of potential strategies to be set off in the face of unpredictability in environmental
change. To conclude, diversity constitutes an important element in short- and
long-term adaptability.
260 P. Andriani
Self-organisation can be described as the establishment of coherence in the
aggregated behaviour of agents. However, in order to give rise to stable structures
of order, self-organisation requires the presence of some sort of organising principles,
able to generate an organic unity and a new level of organisation. One of such
principles is the autocatalytic set (ACS) (Eigen & Schuster, 1979; Juarrero, 1999;
Kauffman, 1993). Autocatalysis takes places in a hypothetical aggregate of agents
when a set of catalytic reactions close onto itself. For this to happen, three
conditions have to be present: (1) a sufficient amount of agents’ diversity; (2)
a mechanism that ensures interaction and feedback; and (3) a particular architecture
of the interactions able to channel and limit the potential explosion in diversity
(Ingber, 2000; Kauffman, 1993). Let us focus only on the first condition. The
chance that a particular molecule (or agent’s property) catalyses a reaction (a
social or economic interaction is catalysed when some form of increasing returns
mechanism is triggered by the catalyst) is in general relatively low. Therefore,
in order for a sufficient number of catalytic reactions to be present and achieve
closure, a critical amount of internal diversity is necessary. The closure of the
set will have two effects: (1) it will generate selective amplification at the micro
level and (2) it will cause the emergence of order creation at the macro level.
Selective amplification is a consequence of the auto-referential aspect of the
ACS. In fact, the ACS will amplify the concentration (or number) of the agents
that are part of the set and will filter out those that are not. As a result of
this, the set will transform the previously existing aggregate of agents into a
system based on the autocatalytic dynamics, which works as an autopoietic
(Maturana & Varela, 1992) organising principle. The dynamic order generated
by the double effect of the autocatalysis, that is, selection and organisation of
agents, creates at once boundary, structure, and hierarchy within the system.
The set can self-perpetuate and, under certain conditions, lead to self-replication.
The dynamics of the ACS constitutes the identity of the system, insofar it defines
the rules of development of the system and the boundary of the system. The
ACS is an example of an order creation mechanisms that depends critically
for its start on internal diversity. It is a way in which internal diversity self-
organises and causes the emergence of a system.
To summarise: (1) adaptive strategies are more successful if agents and systems
are internally diverse; (2) the transition from an aggregate to a system is also
dependent upon internal diversity. However, apart from adaptability and self-
organisation, there is another important aspect of diversity which concerns the
way in which the organisation of diversity takes place. I suggest that networks
of autonomous units constitute the organisational form that allows diversity to
self-organise. The next section will be devoted to these networks.
Diversity, Knowledge and Complexity Theory 261
The Diffusion of Geographic and Virtual Networks
It is suggested by many authors (Arthur & Rousseau, 1996; Gulati et al., 2000;
Kogut, 2000; Nohria and Eccles, 1992; Powell et al., 2000) that the fundamental
unit of analysis of organisational studies is shifting from the isolated firm to
the network of organisations. This transition reflects the widely acknowledged
phenomenon of disintegration of traditionally integrated structures of business
into more complex networks of independent parts (Eisenhardt & Galunic, 2000;
Evans & Wurster, 1999; Grabher & Stark, 1997; Malone & Laubacher, 1998;
Nishiguchi & Beaudet, 1998; Pettigrew & Fenton, 2000; Porter, 1998; Powell,
1990; Storper, 1997).
Geographic clusters represent a well-known example in economic geography
(Storper, 1997). Geographic networks of small firms emerge when the process
of vertical disintegration (triggered often by a supply or demand shock) is met
by a parallel process of agglomeration over a limited territory. This counterbalances
the increase in transaction costs and allows the coordination of a supply network
(Piore & Sabel, 1984). However, the disintegration of the traditionally integrated
structures of business is being accelerated by the digital environment. In this
context, virtual networks are emerging, facilitated by new systems of coordination
(more space and time independent) provided by information and communication
technologies (ICTs) (Romano & Passiante, 1997). These technologies have made
possible the formation of purely virtual business models, such as e-bay (Passiante
& Andriani, 2000) and Linux (Raymond, 1999), that offer a paradigmatic example
of the power of networks, provided by ICTs in cyberspace. In these virtual
networks, fluid — sometimes structured, sometimes self-organising — systems
of suppliers, distributors, commerce service providers, infrastructure providers
and customers use the Internet to create value for customers and wealth for
their stakeholders.
The main characteristic of virtual clusters is that each firm focuses on a
limited set of core activities and outsources virtually every other function; each
participant in the network adds one or more distinct aspects of product/service
value for the end customer, by exchanging information with other members (Ticoll
et al., 1998). Recent studies on virtual networks show how the ubiquity, the
bandwidth, the reliability and the new functions of the ICTs are the enabling
factors of these networking processes (Davis & Botkin, 1994; Rayport & Sviokla,
1995). Each single participant of a virtual network becomes an internetworked
enterprise (IE) (Tapscott et al., 2000), that:
— has the power and capacity to open channels of communications and
collaboration within an office, across space, and across time: collaborative
work increasingly takes place among independent team-based structures, on
high capacity networks (Tapscott, 1996);
262 P. Andriani
— has a flat organisation, which is replacing traditional vertical hierarchies
(Zenger & Hestley 1997): teams behave as suppliers and customers towards
other teams that are both internal and external to the organisation (Bartlett
& Goshal, 1995); this organisation allows the IE to become highly proactive,
responding more quickly to changes in the competitive environment and
customer demands (Valdani & Ancarani, 2000);
may be modelled as a node of a virtual network, where boundaries between
different nodes are blurring. While a traditional firm defines its assets only
in terms of the resources it owns, an IE also includes (as assets) the relational
ties of its network.
But, why do these learning networks — virtual and geographic — emerge?
They do so mainly as the response of firms and organisations to a series of
factors: increased environmental uncertainty, explosion of connectivity, gradual
disappearance of information asymmetry, and increased pace of technological
innovation.
Uncertainty
It is widely accepted that one of the effects of the communication technology
revolution of the 1990s, coupled with the forces of globalisation and liberalisation,
has been the increase in environmental risk and uncertainty that organisations
have to face. The reaction to it has widely been the disintegration into networks.
The increase in complexity of value chains has forced organisations to limit
exposure to risk and uncertainty by adopting a simultaneous strategy consisting
of, on the one hand, specialising in core competencies and, on the other hand,
increasing the number of links with suppliers, customers, partners, etc. The net
result of these processes is the formation of network within and across organisations.
Indeed, unlike the traditional industrial corporations, networks are flexible
organisations, “open systems” which adapt continuously to their changing
environment by starting new strategic alliances, by changing interactions among
network actors or by offering new products and services to network clients.
This is the result of a dense web of interactions among partners: production
and transaction processes are based on intermodality and complementarity instead
of substitution, on the assumption that the best way to handle risk is to share
it by leveraging capabilities and resources of many players. Networks are then
the global effect not of a deliberate strategy of a leader, but simply of the level
of coherence that takes place among single actors that compete in a highly
risky environment. An outstanding example is given by the networking process
that is happening in the financial industry. To face the high risks of this competitive
Diversity, Knowledge and Complexity Theory 263
space, the old integrated business model — with financial products/services realised
and delivered through proprietary distribution channels — is evolving towards
new assets, made up of a lot of autonomous small and medium enterprises (SMEs)
that compete for different financial products/services. Banks are becoming the
facilitators of the SMEs’ negotiation activities (Evans & Wurster, 1999).
Information asymmetry
Organisations are structures devoted to coordinating the flow of information
across internal boundaries (between groups, departments, divisions) and external
boundaries (suppliers, partners, customers, stakeholders). Management can be
described as the set of activities aiming at governing the processes associated
with the information flow and knowledge coordination and specialisation. As
Evans and Wurster (1997) claim: “information is the glue that holds together
the structure of all businesses. The structure, hierarchy and boundary of an
organisation have the function of protecting and maintaining the information
asymmetry that constitutes the raison d’être of the organisation. If the informational
glue that keeps organisations together disappears, then the result will be the
blowing apart (unbundling) of the organisation into its constituent functions.
Interestingly, all else being equal, the first elements to dissolve will be the centralised
coordination of the different functions that make up the organisation. This will
leave a network composed of the functional parts of the disaggregated organisations.
But this is not all. The deconstruction of organisations generates new business
niches at the interfaces between the newly interdependent companies. These
opportunities are quickly occupied by new organisations, thereby reinforcing
the tendency to network structuration.
Rate of innovation
Together with the transformation brought by uncertainty and informational changes,
the increased rate of technological innovation appears to be causing tectonic
shift in the structure of industries. Traditional boundaries between sectors are
being redefined (witness, for example, the convergence between the television,
telecoms, information technologies and entertainment industries). On the one
hand, convergence reinforces the effects of uncertainty. On the other hand, it
generates the explosive diversification of the players: (1) around the newly created
interfaces between sectors once independent; (2) around the new radical innovations
that have generated convergence in the first place. The effect of these two forces
is an enlarged technological and business opportunities landscape that organisations
can pursue.
264 P. Andriani
Change is sometimes so rapid that the analogy with chaotic ecologies holds.
The red queen tells Alice that in the Wonderland : “It takes all the running
you can do, to keep in the same place”. Thus, the red queen paradox (Kauffman,
1995) indicates that, in a network that has to bear the consequences of an explosive
increase in its internal or environmental diversity, the rate of change may become
so rapid as to inhibit the forces of selection to operate. Under these circumstances,
the speed at which the economic system continuously produces new innovations
prevents the emergence of a dominant design (Anderson & Tushman, 1997;
Gould, 1997). The system persists in the fluid phase of innovation and no freezing
around a dominant design takes place (Abernathy & Utterback, 1978). If the
effect of the learning curve (Abernathy & Wayne, 1974) is absent and if economies
of scale are prevented from operating, then the transformation of the network
structure into the more traditional integrated organisation will not take place
(Saxenian, 1994).
The three causes mentioned above; increased uncertainty, disappearance of
information asymmetry and faster rate of innovation (save the case in which
innovation leads to the emergence of a dominant design) are diversity-increasing
mechanisms. Stated another way, the same mechanisms that enhance networks
formation and expansion also act to increase diversity. This is an important
point for it suggests that the network emerges as the natural organisational form
for a diversified system. The relationship between network as an organisational
form and highly diversified systems can be extended, taking into consideration
the fact that diversity could be considered as the main differentiating factor
between firm and network.
Diversity tends to create more diversity through innovation (Grabher & Stark
1997; Kauffman 1995; Metcalfe & Gibbons, 1988; Stirling, 1998). In other words,
diversity itself, above a threshold, seems to become autocatalytic. However, an
increase in internal diversity is likely to cause both a reconfiguration of links
and the appearance of new types of agents. In so doing, it is likely to introduce
centrifugal forces that could potentially disrupt the system.
Bureaucratic organisations in general find it difficult to cope with an unplanned
increase in internal diversity. This is because the mechanism of rational allocation
of scarce resources requires knowledge of types and probability distribution of
outcomes for the planning exercise to take place. Increase in internal diversity
will create resources from the bottom that are largely unaccounted for, and regarding
which, no description is present. A bureaucratic organisation could therefore
be easily disrupted by changes in its internal diversity and will in general tend
to keep the diversity creation mechanisms under strict control. This type of
organisation can be described as a hierarchically structured closed system that
behaves as a monolithic network (Antonelli, 1995). The exploration and exploitation
Diversity, Knowledge and Complexity Theory 265
(March, 1989) of market and technological opportunities will generally take
place within a single technological trajectory (Dosi & Orsenigo, 1985) and dominant
production paradigm. Therefore, “organisation by firm is variety reducing” (Kogut,
2000).
Distributed networks obey a different logic. They are based on high amount
of redundancy and modularity. The allocation of resources is emergent, that
is, it is based on self-organisation. In clusters, either virtual, such as Linux,
or geographic, such as the districts in Italy (Piore & Sabel, 1984), evolutionary
changes are based on massive parallelism of resources and competencies. Any
increase in the degree (or kind) of internal diversity is met by a rapid reconfiguration
of links [as suggested by Arthur et al., (2001) and Maskell (2001) in this issue].
The modularity helps the system to pursue diversity increasing changes at the
agents’ level and — due to the self-organisation of links — also at the network’s
level. Essentially, a distributed self-organising network is the locus where a high
diversity of agents (organisation) coexists with the organisation of diversity (Grabher
& Stark, 1997). I suggest therefore that a distributed network based on self-
organisation principles is a diversity-increasing type of organising production
and innovation.
Complexity as a Dynamic Theory of Emergent
Order in Networks
The transformation of organisations into networks causes a coordination problem
under at least two points of view: first, the number of units to coordinate rises;
second, the autonomy and diversity of those units increases as well. Adding
technological turbulence to the picture makes the task of managing networks
a central challenge for today’s management. On the other hand, complex systems
reveal an interesting property: they seem to require less central management
as they can self-manage. The Internet is a fascinating example: nobody manages
the Internet and nobody “project managed” the Internet as a new product
development experiment. One could even suspect that had the Internet been
“managed”, it would never have seen the light of day (Malone & Laubacher,
1998). The community of Linux (Raymond, 1999) managed to develop what
is hailed as the most stable and reliable computer operating system without
being managed (in the usual sense of the term) at all. This property of large
systems to self-manage has something to do with the “invisible hand” of Adam
Smith, and is not far from the Darwinian argument of evolution by means of
massive parallelism in experimentation (Axelrod & Cohen, 1999). As this is
a crucial point, I will spend a little time on it. Self-management is a way to
describe the tendency that complex systems show to self-organise around a pattern
of relationships.
266 P. Andriani
There are really two aspects of self-organisation: first, the aspect of “generative
rules”, widely described by the Santa Fe school of complexity (Holland, 1995;
Kauffman, 1995; Resnick, 1997; Waldrop 1992). This approach, very much
bottom-up, shows that complex adaptive systems and behaviours at the system’s
level can emerge from the interactions of agents, whose behaviour is driven
by a limited set of simple rules. The example of a colony of ants (Hofstadter,
1980) is famous. This approach introduces a duality between the agent’s level
and the system’s level, characterised by a strongly anti-reductionist flavour. Complete
knowledge of the agents’ behaviour will not allow the prediction of the system’s
behaviour. On the whole, however, the “generative rules” approach overlooks
the interaction of the system with the environment. The properties of the systems
seem to be completely bottom-up and emergent, and therefore resistant to external
control and management. In addition, although the system shows the typical
dynamics of emergence of collective properties, the “generative rules” approach
has some problems in introducing reflexivity of the agents (the capability to
figure out the macro-context (Storper, 1997)) and double-loop learning (Argyris
& Schon, 1978), as a result of experiential learning. Also, this approach assumes
the homogeneity of agents. As a result, although such systems show interesting
dynamical patterns based on self-organising behaviour, the range of order creation
mechanisms they exhibit is fairly limited (Allen, 2001).
A complementary line of thought (Allen, 1997; Nicolis & Prigogine, 1989;
Prigogine & Stengers, 1997) stresses the importance of the interaction with the
system’s environment. Such systems are seen as open (dissipative); the flux
of energy/information across the boundary becomes the driver of the internal
state of organisation. The famous Bénard experiment indicates that self-organisation
depends on the constraints imposed by environmental external parameters. Self-
organisation becomes, then, a consequence of a “negentropic” process, whereby
the energy, matter and information imported from the environment drive the
selective amplification of catalytic processes within the system (McKelvey, 2001;
Nicolis & Prigogine, 1989). The dissipation of energy outside the boundary
of the system allows the emergence of order within the system. But, self-organisation
emerges only in a precise window of environmental constraints. Outside of that
window, the system goes either into a static equilibrium that implicates the inability
to change and in the long term death or into a chaotic state. In both cases,
the order that characterised the state in between, by which a coherent set of
correlations between agents allowed the emergence of collective structure,
disappears.
Diversity, Knowledge and Complexity Theory 267
Distributed Knowledge
I would like in this section to extend some of the points developed in the
previous parts to the issue of distributed knowledge systems. We have seen
that the network type of organisation is diversity increasing whereas the firm
type of organisation is diversity reducing. The two types of structures also differ
in terms of the knowledge structures they generate and the way those structures
are managed. These issues are related to two intriguing questions regarding the
locus of learning. First, does learning take place only at the level of agents
or also at the level of systems? Second, is the system’s knowledge an emergent
property of the self-organisation of the different specialisms of the individuals
composing the system?
A large part of the traditional knowledge management literature points out
that only individuals can learn (Grant, 1996; Nonaka & Takeuchi, 1995) and
that knowledge is stored in individuals’ heads. This position comes as no surprise
when one considers that knowledge management has mainly been applied to
the context of firms and used as a management tool or framework to support
the decision-making process. Knowledge is the ultimate competence (Prahalad
& Hamel, 1990; Spender, 1994) and the real terrain of competition (Davenport
& Prusak, 2000). This position represents a crucial aspect of the resource-based
view of the firm (Grant, 1991), whereby companies are endowed by their histories
with unique resources (Hall, 1992). To stay ahead of the game, firms need to
continually regenerate their dynamic capabilities and to use the newly generated
dynamic capabilities to sustain and protect existing markets and leverage, and
create new competitive niches. Knowledge management provides a powerful
framework and a set of tools to achieve that purpose. This comes in two steps:
(1) it is necessary to manage the knowledge processes (creation, codification
and diffusion) at the individual level; (2) there is a need to coordinate and
integrate the knowledge processes (achieved by means of conversion of one
type of knowledge into the other (Nonaka & Takeuchi, 1995) in order to generate
organisation-wide dynamic capabilities (Grant, 1996). Capabilities are built by
carefully integrating individual specialised knowledge into a predesigned plan
(Prahalad & Hamel, 1990). Because the mechanisms of coordination and integration
of knowledge are designed and implemented according to an explicit strategy,
an organisation develops a strong identity, based on the coordination and integration
mechanisms. This identity limits microdiversity and therefore forces the organisation
along the path of incremental innovations. The stress on individual learning
and “management” of knowledge ultimately reflects the view of management
as planning and design in centralised structures.
A different stream of the knowledge management literature (Brown & Duguid,
1991; Cook & Brown, 1999; Tsoukas, 1996; Weick & Roberts, 1993) takes
268 P. Andriani
a different view that alongside individuals, systems (firms, organisations) can
also learn. According to the latter view organisational knowledge cannot be
reduced to the sum (however coordinated) of individuals’ knowledge, but is
a fundamental property of systems. For instance, one of the major insights of
evolutionary economics (Nelson & Winter, 1982) is that organisational routines
represent the analogy of individual skills. Organisational routines are collective
and complex patterns of quasi-automatic reactions driven by a set of preselected
stimuli, operating on the basis of collective experiential learning, largely unconscious
to the individuals involved. As skills, routines are acquired via collective learning
by doing. The retention of routines is based on collective remembering by doing.
In both cases, the doing does not require full consciousness, either at the individual
(Squire & Kandel, 1999) or at the collective level.
The execution of a routine requires the spontaneous coordination and sequencing
of a set of responses with a set of stimuli (which may come in any order).
The communication system is based on a tacit language, full of locally understood
words. Finally, the environment, in which the execution of the routine is carried
out, is not separated by the routine itself, but constitutes the context in which
the interpretation of the stimuli takes place. It is this contextual element of
the organisational routine that creates the impossibility of reducing the routine
to the sum of its individual agents’ actions. Again, as for skills, the memory
of the routines is stored in a distributed social network. The contextual dimension
of organisational routines [as with similar organisational processes, such as
communities of practice (Brown & Duguid, 1991; Wenger & Snyder, 2000)]
makes them very difficult to manage, due to the inherent idiosyncrasy and diversity
with which the elements of the routine become manifest. The unpredictability
associated with diversity is disruptive to top-down management schemes. This
is why, as suggested before, diversity requires a form of organisation that can
thrive on variety, that is, the network.
The processes of knowledge creation and diffusion in a highly distributed
system, such as a cluster of small- and medium-size firms (typical examples
are Silicon Valley or the textile cluster in Prato, Italy), are largely spontaneous,
scarcely codified and very fragmented. Individual companies and free-lance agents
(Malone & Laubacher, 1998) hold only a fraction of the knowledge necessary
for the delivery of a service or the manufacturing of a product. The disintegration
of competencies (Maskell, 2001) makes the agents dependent on one another.
At the same time, it raises the issue of integration of the fragmented competencies
in a coordinated web of interactions, in relationship of competition and collaboration
with each other.
Diversity, Knowledge and Complexity Theory 269
The high social connectivity within the local system forces the rapid
embeddedness of minute improvement — the execution of a skill (Becattini,
1998), the optimisation of a measuring device, or the intuition regarding set
of colours or shape for the next fashion season — in a set of intra- and inter-
organisational routines. Innovations, big or small, become part of the local system
of knowledge via the rapid integration in the existing set of routines, belonging
to no one but to the network.
The integration of activities, processes and competencies transcends any single
organisation in the cluster and is not coordinated by any centralised authority.
This multiple-level system of knowledge emerges in the co-evolutionary dance
between the adaptive tension (McKelvey, 2001) set by the multiple set of constraints
determined by the relationships among organisations (Juarrero, 1999) and the
external set of environmental constraints set by the industry and market forces.
The tacit integration of the different packets of knowledge and information builds
a coherent system of knowledge and enables the cluster to achieve world class
performance, business resilience, adaptability and world class rate of innovation.
The three distinctive features of networks, namely, fragmentation, integration
of innovations and emergent coordination require the formulation of new
interpretative concepts to explain the spontaneous emergence of order [Kauffman’s
order for free”, (1995)], that is, the property of systems (in our case industrial
clusters) to self-organise around bottom-up emerging structures.
In contrast to command and control or bureaucratic systems, emergent
coordination does not rely on organising principles that rest outside the system
itself. Instead, it is based on the network of interactions exchanged by the agents
in a cooperative and competitive way. The structure of the coordination is then
the network itself. Most of the social transactions within the network are nothing
else but a form of knowledge exchange. As Kogut (2000) states: “the network
is knowledge, not in the sense of providing access to distributed information
and capabilities, but in representing a form of coordination guided by enduring
principles of organisation.
Concluding Remarks
What I have tried to illustrate in this paper can be synthesised in a few lines.
Microdiversity plays a crucial role in the dynamics of complex systems.
Microdiversity is necessary to achieve a balanced response to the external
environment, to enhance adaptive behaviour and speed up evolutionary behaviour.
In the presence of fast-changing environmental conditions, when uncertainty
dominates the scene and/or complex systems and environment are co-evolutionary
and chaotically linked, a strategy based on complexity matching might not be
270 P. Andriani
enough. The law of excess diversity (Allen, 2001) applies under these conditions.
In order to counterbalance environmental uncertainty, agents or systems need
a degree of internal diversity higher than that of the environment. The excess
diversity acts as a reservoir of potential strategies against unpredictable
environments. Microdiversity is also a necessary conditions for spontaneous order
creation. Stable structures of order are generated when relationships of
complementarity and redundancy are explored and established among diverse
actors. The process of order creation is therefore probabilistically dependent
upon internal diversity.
The types of structures created by self-organisation of diverse agents show
the characteristic properties of networks. Networks emerge then as the organisational
form in which the diversity of agents can organise and thrive. This paper suggests
that the issue of diversity can be used to discriminate between the model of
organisation based on rational allocation of resource — the firm — and the
model of organisation based on emergence and self-organisation — the network.
The paper concludes that the former is a diversity-reducing mechanism, whereas
the latter is a diversity-enhancing mechanism.
Acknowledgements
A special thanks to Giuseppina Passiante for her contribution to the section
on “The Diffusion of Geographic and Virtual Networks”. I am also indebted
to Michael Arthur, Richard Hall, Bill McKelvey for useful comments on this
paper.
References
Abernathy, W. J. & Wayne, K. (1974) Limits of the learning curve. Harvard Business
Review, SeptOct, 109–119
Abernathy, W. J. & Utterback J. M. (1978) Patterns of industrial innovation. In Managing
Strategic Innovation and Change: Readings in the Management of Innovation, eds.
W. Moore & M. L. Tushman, pp. 141–148. Boston: Pitman
Allen, P. (1997) Cities and Regions as Self-Organising System. Amsterdam: Gordon
and Breach Science Publisher
Allen, P. (2001). A complex systems approach to learning in adaptive networks.
International Journal of Innovation Management, 2(2), forthcoming
Anderson, P. & Tushman M. L. (1997) Managing through cycles of technological change.
In Managing Strategic Innovation and Change, ed. M. L. Tushman & P. Anderson,
pp. 45–52. Oxford: Oxford University Press
Antonelli, C. (1995) The Economics of Localised Technical Change and Industrial
Dynamics. Dordrecht: The Netherlands, Kluwer
Diversity, Knowledge and Complexity Theory 271
Argyris, C. & Schon D. A. (1978) Organisational Learning. Reading, MA: Addison-
Wesley
Arthur, M. B., DeFillippi, R. J. & Lindsay, V. J. (2001) Careers, communities, and industry
evolution: links to complexity theory. International Journal of Innovation Man-
agement, 2(2), forthcoming
Arthur, M. B. & Rousseau, D. M. (1996) The Boundaryless Career: A New Employ-
ment Principle for a New Organizational Era. Oxford: Oxford University Press
Axelrod, R. & Cohen, M. D. (1999) Harnessing Complexity: Organisational Implications
of a Scientific Frontier. New York: The Free Press
Ashby R. (1960) Design for a Brain. New York: Wiley
Bartlett, C. & Goshal, S. (1995) Managing Beyond Borders. Boston: Harvard Business
School
Becattini, G. (1998) Distretti industriali e made in Italy. Torino: Bollati Boringhieri
Brown, J. S. & Duguid P. (1991) Organisational learning and communities-of-practices:
toward a unified view of working, learning and innovation. Organisation Science
2(1), 40–57
Cook, S. D. & Brown J. S. (1999) Bridging epistemologies: the generative dance between
organizational knowledge and organizational knowing. Organization Science 10(4),
381–400
Davenport, T. H. & Prusak L. (2000) Working Knowledge: How Organizations Manage
What They Know. Boston, MA: Harvard Business School Press
Davis, S. & J. Botkin (1994) The coming of knowledge-based business. Harvard Business
Review SeptOct, 165–170
Dosi, G. & Orsenigo, L. (1985) Order and change: an exploration of markets, institutions
and technology in industrial dynamics. Brighton: SPRU, discussion paper, N. 32
Eigen M. & Schuster P. (1979) The Hypercycle. Berlin: Springer
Eisenhardt, K. M. & Galunic, D. C. (2000) Coevolving: at last, a way to make synergies
work. Harvard Business Review, JanFeb, 91–101
Evans, P. & Wurster, T. (1999) Blown to Bits. Cambridge, MA: Harvard Business
School Press
Evans, P. B. & Wurster, T. S. (1997) Strategy and the new economics of information.
Harvard Business Review, SeptOct, 71–82
Gould, S.J. (1993) Eight Little Piggies: Reflections in Natural History. New York:
Norton
Gould, S. J. (1997) The panda’s thumb of technology. In Managing Strategic Innovation
and Change, ed. M. L. Tushman & P. Anderson, pp. 68–74. Oxford: Oxford
University Press
Grabher, G. & Stark D. (1997) Organising diversity: evolutionary theory, network analysis
and postsocialism. Regional Studies 31(5), 533–544
Grant, R. (1991) The resource based theory of competitive advantage: implications for
strategy formulation. California Management Review, Spring; 114–135
Grant, R. M. (1996) Toward a knowledge-based view of the firm. Strategic Management
Journal, 17(Winter Special Issue),109–122
272 P. Andriani
Gulati, R., Nohria, N. et al. (2000) Strategic networks. Strategic Management Journal,
21(Special Issue on Strategic Networks), 213–216
Hall, R. (1992) The strategic analysis of intangible resources. Strategic Management
Journal, 13, 135–144
Hofstadter, D. R. (1980) Godel, Escher, Bach: An Eternal Golden Braid. London: Penguin
Books
Holland, J. H. (1995) Hidden Order: How Adaptation Builds Complexity. Reading, MA:
Addison Wesley
Ingber, D. E. (2000) The origin of cellular life. Bioessays 22(12), 1160–1170
Juarrero, A. (1999) Dynamics in Action. Cambridge, MA: The MIT Press
Kauffman, S. (1993) The Origin of Order. Oxford: Oxford University Press
Kauffman, S. (1995) At Home in the Universe. Oxford: Oxford University Press
Kogut, B. (2000) The network as knowledge: generative rules and the emergence of
structure. Strategic Management Journal, 21 (Special Issue on Strategic Networks),
405425
Malone, T. W. & Laubacher, R. J. (1998) The dawn of the E-lance economy. Harvard
Business Review, SeptOct, 145–152
March, J. G. (1989) Exploration and exploitation in organisational learning. Organization
Science, 2(1), 71–87
Maskell, P. (2001) Knowledge creation and diffusion in geographic clusters. International
Journal of Innovation Management, 2(2), forthcoming
Maturana H. R. & Varela F. J. (1998) The Tree of Knowledge. London: Shambala
McKelvey, B. (2001) Energising order-creating networks of distributed intelligence:
improving the corporate brain. International Journal of Innovation Management
2(2), 181–s212
Metcalfe, J. & Gibbons, M. (1988) Technology, variety and the organisation: a systematic
perspective on the competitive process. In Research on Technology and Innovation
Management Policy, ed. R. S. Rosembloom and R. A. Burgelman. Manchester, PREST:
University of Manchester
Metcalfe, J. S. (1994) Technology policy and small firms: an evolutionary perspective.
In New Technology-Based Firms in the 1990s, ed. R. Oakey, pp.157–168 London:
Paul Chapman
Nelson, R. R. & Winter, S. G. (1982) An Evolutionary Theory of Economic Change.
Cambridge, MA: Harvard University Press
Nicolis, G. & Prigogine, I. (1989) Exploring Complexity: An Introduction. New York:
W.H. Freeman & Company
Nishiguchi, T. & Beaudet, A. (1998) Fractal design: self-organised links in supply-chain
management. Conference on Knowledge Creation, University of St. Gallen, June
Nohria, N. & Eccles, R. G. (1992) Networks and Organisations: Structure, Form, and
Action. Cambridge, MA: Harvard Business School Press
Nonaka, I. & Takeuchi, H. (1995) The Knowledge-Creating Company: How Japanese
Companies Create the Dynamics of Innovation. Oxford: Oxford University Press
Diversity, Knowledge and Complexity Theory 273
Passiante, G. & Andriani, P. (2000) Modelling the learning environment of virtual
knowledge networks: some empirical evidence. International Journal of Innovation
Management, 4(1), 1–131
Passiante, G. & M. Romano (2000). Net-Economy: approcci interpretativi e modelli
di sviluppo regionale. Bari: Cacucci Editore
Pettigrew, A. M. & Fenton, E. M. (2000) The Innovating Organisation. London: Sage
Piore, M. J. & Sabel, C. F. (1984) The Second Industrial Divide: Possibilities for
Prosperity. New York: BasicBooks
Porter, M. E. (1998) Clusters and the new economics of competition. Harvard Business
Review, NovDec
Powell, W. W. (1990) Neither market nor hierarchy: the network form of organization.
Research in Organizational Behaviour, 12, 295–336
Powell, W. W., Koput, K. W. et al. (2000) Inter-organizational collaboration and the
locus of innovation: networks of learning in biotechnology. Administrative Science
Quarterly, 41; 116–145
Prahalad, G. K. & Hamel, G. (1990) The core competence of the corporation. Harvard
Business Review, 68(3); 79–91
Prigogine, I. & Stengers, I. (1997) The End of Certainty: Time, Chaos, and the New
Laws of Nature. New York: Free Press
Raymond, E. S. (1999) The Cathedral and the Bazaar: Musing on Linux and Open
Source by an Accidental Revolutionary. Cambridge, MA: O’Reilly
Rayport, J. F. & J. J. Sviokla (1995) Exploiting the virtual value chain. Harvard Business
Review, NovDec, 75 87
Reicheld, F. F. & Schefer P. (2000) E-loyalty. Harvard Business Review, JulAug,
105–114
Romano, A. G. Passiante & Elia V. (2001) New sources of clustering in the Digital
Economy. Journal of Small and Medium Enterprises, JanFeb; 19–27
Romano, A. & G. Passiante (1997) Innovation territorial system as learning organization
of local system-innovation virtual system. Proceedings of Regional Science Asso-
ciation 37th European Congress, Rome, Italy, 26–29 August
Rescher, N. (1979) Cognitive Systematization: A System-Theoretic Approach to a
Coherentist Theory of Knowledge. Totowa, NJ: Rowan and Littlefield
Resnick, M. (1997) Turtles, Termites and Traffic Jams. Cambridge, MA: The MIT Press
Saviotti, P. P. (1996) Technological Evolution, Variety and the Economy. Cheltenham:
Edward Elgar
Saviotti, P. P. & Mani, G. S. (1995) Competition, variety and technological evolution:
a replicator dynamics model. Journal of Evolutionary Economics, 5, 369–392
Saxenian, A. (1994) Regional Advantage: Culture and Competition is Silicon
Valley and Route 128. Harvard, MA: Cambridge University Press
Spender, J. C. (1994) Organisational knowledge, collective practice and Penrose rents.
International Business Review, 3(4), 1–12
Squire, L. R. & Kandel, E. R. (1999) Memory: From Mind to Molecules. New York:
Scientific American Library
274 P. Andriani
Stirling, A. (1998) On the economics and analysis of diversity. Brighton, SPRU,
http://www.susx.ac.uk/spru/publications/imprint/sewps/sewp28/sewp28.html
Storper, M. (1997) The Regional World: Territorial Development in a Global Economy.
New York: Guildford Press
Tapscott, D. (1996) The Digital Economy. New York: McGraw Hill
Tapscott, D, Ticoll, D. & Lowy, A. (2000) Digital Capital. Nicholas Brealey Publishing
Ticoll, D., Lowy, A. & Kalakota, R. (1998) Joined at the bit: the emergence of the
e-business community. In Blueprint to the Digital Economy, ed. D. Tapscott, A.
Lowy & D. Ticoll, pp. 19–34. New York: McGraw Hill
Tsoukas, H. (1996) The firm as a distributed knowledge system: a constructionist approach.
Strategic Management Journal, 17 (Winter special issue), 11–26
Valdani, E. & Ancarani F. (2000). Strategie di marketing del territorio. Milan: EGEA
Waldrop, M. M. (1992) Complexity, the Emerging Science at the Edge of Order and
Chaos. New York: Simon & Schuster
Weick, K. E. & Roberts, K. H. (1993) Collective mind in organizations: heedful inter-
relating on the flight deck. Administrative Science Quarterly, 38, 357–381
Wenger, E. C. & Snyder, W. M. (2000) Communities of practice: the organizational
frontier. Harvard Business Review, JanFeb, 139–145
Zenger, T.R. & Hestley, W.S. (1997) The disaggregation of corporations: selective
intervention, high-powered incentives and molecular units. Organization Science,
8(3), 209–222
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... From both perspectivesthe RBV and the knowledge-based view of the firmat the organisational level, knowledge is embedded and carried through policies, culture, routines, documents, systems, and mainly individuals. In fact, although KM has drawn from a wide range of established disciplines since its appearance as an emerging science (Ologbo and Nor, 2015), intellectual capital has been one of the most highlighted (Beesley and Cooper, 2008), up to the point that a large body of traditional literature on KM considers that only individuals can learn (Grant, 1996;Andriani, 2001). Similarly, Han et al. (2010) j JOURNAL OF KNOWLEDGE MANAGEMENT j conclude that some kind of the organisations' knowledge, especially the strategic knowledge, is embedded in individuals themselves. ...
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Chapter
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