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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.
International Journal of Innovation Management
Vol. 5, No. 2 (June 2001) pp. 257–274
© Imperial College Press
University of Durham Business School
Mill Hill Lane, Durham City
United Kingdom
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
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
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,
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,
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.
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
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... Stemming from previous approaches, a KM system can be regarded as the way of joining the individual knowledge of employees, especially strategic knowledge, in a learning organisation. Given that the explicit knowledge could be documented and shared to encourage individuals' learning (Andriani, 2001;Grant, 1996), the way in which it is stored, used and transmitted (i.e. strategic knowledge management or SKM) may contribute to the success of the organisation (Lam, 1997). ...
... 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. ...
Purpose The purpose of this paper is to explore the relationship between the availability and use of IT solutions for strategic knowledge management (SKM) and the universities’ performance, measured in terms of scientific production. Design/methodology/approach Drawing on the resource-based view (RBV) and the knowledge-based theory, the authors develop a conceptual framework for exploring the effect of SKM based on IT on the organisation’s performance that they empirically test by applying panel data methodology to a sample of 70 Spanish universities over the period 2011-2014. Findings The authors confirm that the SKM based on IT influences the university’s performance. This effect is positive in the case of the IT solutions referred to the infrastructure of data grouping and more evident when the university’s performance is measured by indicators more directly related to scientific quality. Contrary to expected, the percentage of training and research staff that uses institutional tools of collaborative work is negatively related with the universities’ capacity of publication. Practical implications The authors followed the system dynamics approach to identify a causal diagram and a flow sequence that lets them group universities in three different profiles in the knowledge management (KM) flow diagram. Originality/value First, the authors develop a conceptual framework for exploring the effect of SKM based on IT on the organisation’s performance that could be applicable to analyse the case of other knowledge-driven organisations. Second, in contrast with the large number of studies dealing with SKM and performance focused on firms, the authors analyse universities. Third, the authors’ empirical approach used the panel data methodology with a large sample of universities over the period 2011-2014. Free access (50 copies) available at:
... In recent literature, diversity, and especially socio-economic diversity has only received marginal attention (Andriani, 2001;Grabher & Stark, 1997;Metcalfe, 1994;Saviotti, 1996;Saviotti & Mani, 1995;Stirling, 1998). Nevertheless, it is recognized as an important driver towards an innovative environment and it is therefore supposed to be an elementary component of systems (organizations) to achieve a higher rate of adaptability towards the ever-changing business environment (flexibility; Andriani, 2000;Stirling, 1998;Holland, 1995;Kauffman, 1995). ...
... Nevertheless, it is recognized as an important driver towards an innovative environment and it is therefore supposed to be an elementary component of systems (organizations) to achieve a higher rate of adaptability towards the ever-changing business environment (flexibility; Andriani, 2000;Stirling, 1998;Holland, 1995;Kauffman, 1995). Herewith, the internal variety of a system should at least match the variety of the external environment (Ashby, 1960), in order to succeed in the resonance to environmental threats and opportunities within the process of change (Andriani, 2001). Consequently, the faster the change of the environment becomes and the herewith-rising uncertainty and instability, the greater the internal diversity of an organization or system needs to be. ...
... Similarly, in the logistics field, only few authors have attempted to create a business model concept. This is because the logistics industry can be characterized in various ways, e.g. it is diverse and complex due to the increase in size of these service sectors over the past decades, and also because of the strong interaction between people and technology due to global supply chain networks and new technologies (Andriani, 2001;Hodgson, 2003). For this reason, the logistics industry is confronted with uncertainty, and it must be ready to adapt to rapid changes (Neubauer, 2011;Wytenburg, 2001). ...
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Purpose: Digital freight forwarder (DFF) start-ups and their associated business models have gained increasing attention within both academia and industry. However, there is a lack of empirical research investigating the differences between DFFs and traditional freight forwarders (TFF) and the impact of digital start-ups on incumbents' companies. In response, this study aims to examine the key business model characteristics that determine DFFs and TFFs and propose a framework illustrating the extent to which digital logistics start-ups influence incumbent logistics companies. Design/methodology/approach: Based on the primary data gathered from eight interviews with experts from start-ups' and incumbents' logistics companies, as well as secondary data, the authors identify the main factors of DFFs start-ups that have an impact on TFFs and analyze the similarities and differences in regard to the business model components' value proposition, value creation, value delivery and value capture. Findings: The results show that differences between DFFs and TFFs appear in all four business models' components: value proposition, value creation, value delivery and value capture. In particular, the authors identify three main factors that need to be considered when assessing the impact of DFFs on TFFs: (1) the company size, (2) the market cultivation strategy and (3) the transport mode. Originality/value: This is one of the first studies to specifically examine the key business model differences between DFFs and TFFs and to propose a conceptual framework for understanding the impact of digital logistics start-ups on incumbent companies.
... and complexities in their eco nomic milieu (Simon, 1985;Kaufman, 1995;Patel et al., 1996;Andriani, 2001). ...
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It is obvious that regions that are not sharing these pos it ive charac ter istics are facing ser ious obs tacles to competing and growing in the new eco nomic environ ment. The differential impacts of these factors, along with successful or less successful pol icy agendas, are the main drivers that increase spatial in equal ity and allow for a non-linear pattern of growth at the EU regional level (Petrakos, 2008;­Petrakos­&­Artelaris,­2009). The im port ant relev ance given to the regional capa city for know ledge and in nova tion as growth factors stimulated a qualit at ive change in the regional convergence liter at ure, incorporating the new para meters. The theor et ical and empirical studies that examined the issue are neither conclusive re gard ing the convergence-divergence­trends­in­the­EU­regions,­nor­give­a­clear­pic­ture­of­the­ location patterns of innov at ive activity. Furthermore, most of the econo metric studies­re­gard­ing­the­convergence-divergence­ana­lysis­tend­to­overlook­the­rel­ at­ive­ im­port­ance­or­size­of­each­region­(Doloreux­&­Bitard,­2005;­Hollanders,­ 2007). This shortcoming could produce unrealistic or misleading results. The aim of this chapter is to con trib ute to the better understanding of the formation­of­ the­new­Euro­pean­scenery­under­ the­ influence­of­ the­know­ledge­eco­ nomy. In the present study we use OLS, Panel and WLS estimators to ana lyse RRSII­data­within­208­EU25­regions­over­a­five­­year­period,­in­order­to­identi­fy­ patterns and trends of regional convergence or divergence. We argue that the Weighted Least Squares (WLS) methodology is more appropriate for models using regional data. The comparison between the methods investigates the as sump tion that when WLS methodology is used in order to account for the signific­ant­dif­fer­ences­among­Euro­pean­regions­with­respect­to­size,­a­U­­shaped­pro­ cess­could­provide­a­better­fit­to­regional­data.­The­findings,­even­if­not­conclusive,­ raise im port ant research questions that are related to the spatial footprint of the in nova tion dy namics in Europe, with sharply differing pol icy im plica tions. Do less innov at ive regions in the EU tend to catch up with more innov at ive ones? Is convergence or divergence the prevailing pattern of spatial change with respect to in nova tion? Does the mix of market forces and pol icy dy namics that shapes the innov at ive charac ter istics of regions result in convergence or a new division? The chapter is or gan ized as follows. The next section presents a brief review of recent approaches and studies re gard ing regional convergence or divergence and­ their­ relation­ to­ in­nova­tion­ ac­tiv­ities.­ Section­ 12.3­ presents­ the­ empirical­ ana­lysis­with­the­estim­ated­regressions­and­discusses­the­results,­while­the­final­ section presents conclusions.
... The diversity represents different sources of information and knowledge to resolve problems (Ruuska and Vartiainen, 2005). As proposed by some authors, the access to other practices, other knowledge and experiences express a microdiversity (Andriani, 2001;van Dick et al., 2008). That is, a very powerful source of creativity for the development of new knowledge (Cohendet and Meyer-Krahmer, 2001). ...
... The diversity represents different sources of information and knowledge to resolve problems (Ruuska and Vartiainen, 2005). As proposed by some authors, the access to other practices, other knowledge and experiences express a microdiversity (Andriani, 2001;van Dick et al., 2008). That is, a very powerful source of creativity for the development of new knowledge (Cohendet and Meyer-Krahmer, 2001). ...
The concepts of hybridity and governance have been an important line of research in the context of social companies and public institutions. The purpose of this paper is to explore these notions in the framework of hybrid communities of social innovation by showing the importance of intangible capital in the improvement of functional skills, techniques and strategies when directing people towards social innovation processes. The relevance of these skills are presented through the results of the HEDABIDE project, a piloting research experience focused on the design of hybrid communities of social innovation in the province of Gipuzkoa (Basque Country, Spain) in 2014. The results of this project show the implications of social interactive spaces in acquiring different skills, competences and capabilities for social innovation inside communities of learning and practice when addressing social problems, concluding with a series of learned lessons and new paths of future research.
... The diversity represents different sources of information and knowledge to resolve problems (Ruuska and Vartiainen, 2005). As proposed by some authors, the access to other practices, other knowledge and experiences expresses a micro-diversity (Andriani, 2001, van Dick et al., 2008. That is, a very powerful source of creativity for the development of new knowledge (Cohendet and Meyer-Krahmer, 2001). ...
Conference Paper
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The concepts of hybridity and governance have been an important line of research in the context of social companies and institutions. The purpose of this article is to explore the notions in the framework of hybrid communities of social innovation. We show, through a pilot experience in the design of hybrid communities of social innovation, the results to the project HEABIDE (Hybrid Contexts of Learning oriented towards Social Innovation) carried throughout the year 2014 in the province of Gipuzkoa (Basque Country, Spain). In this sense, social innovation communities have been structured on the basis of three different categories: gender, age, and membership associated to diverse kinds of organizations and institutions (companies, universities, NGOs, public sector). This article presents the contextual framework to the concept of social innovation community, its methodological approach through the mentioned pilot experience, as well as the obtained results. Finally, we conclude with a series of learned lessons and new paths of future research.
... But the strength resides in the internal diversity, since their accumulative experiences are integrated inside projects as heterogeneous sources of information and knowledge to solve problems (Ruuska & Vartiainen, 2005). From this perspective, projects are unstable spaces that express a micro-diversity (Andriani, 2001), as a strong source of creativity for the development of new knowledge, but they have difficulties to transfer knowledge on the long run (Cohendet and Meyer-Krahmer, 2001). ...
Conference Paper
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The article presents a model of double helix through which the absorptive capacity of knowledge allows social organizations to develop social innovations or improve their social performance. This paper contributes to the debate about the development of social innovation indicators at an organizational level by offering the results of the application of the pilot experience of a model to measure Regional Social Innovation, called RESINDEX. This model was applied to 282 organizations in the Basque Country-Spain (SINNERGIAK SOCIAL INNOVATION, 2013). Moreover, this paper analyses a series of consequences coming from this pilot experience that can guide social and regional innovation policies.
... Complex adaptive systems models of organisations suggest that this internal diversity will enhance a university's ability to adapt, but only if there are networks to link up the diverse perspectives, creating distributed cognition (van Fenema 2005). Rational allocation of resources, on the other hand, acts to reduce diversity (Andriani 2001). Some writers on complexity in organisations focus on self-organisation, questioning the viability of intentional management and giving reasons why change cannot be managed (Griffin, Shaw, and Stacey 1999;Stacey 2005). ...
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There are hopes that new learning technologies will help to transform university learning and teaching into a more engaging experience for twenty-first-century students. But since 2000 the changes in campus university teaching have been more limited than expected. I have drawn on ideas from organisational change management research to investigate why this is happening in one particular campus university context. My study examines the strategies of individual lecturers for adopting e-learning within their disciplinary, departmental and university work environments to develop a conceptual framework for analysing university learning and teaching as a complex adaptive system. This conceptual framework links the processes through which university teaching changes, the resulting forms of learning activity and the learning technologies used – all within the organisational context of the university. The framework suggests that systemic transformation of a university's learning and teaching requires coordinated change across activities that have traditionally been managed separately in campus universities. Without such coordination, established ways of organising learning and teaching will reassert themselves, as support staff and lecturers seek to optimise their own work locally. The conceptual framework could inform strategies for realising the full benefits of new learning technologies in other campus universities.
... It will show why attempts to address the problem of student attrition to date have largely failed despite the expenditure of significant effort and resources. The dominant method by which institutions approach problem solving is via plan-based, discrete projects, which assume that the problem is consistent and understandable (Andriani 2001;Beer, Jones, and Clark 2012;McConachie et al. 2005;russell 2009). This article will show that the factors that contribute to student attrition are socially complex, diverse and fluid, which means they resist mechanical, time-limited solutions (Crosling, Heagney, and Thomas 2009;Tinto 1999;Urwin et al. 2010). ...
Student attrition continues to be a significant and costly challenge for higher education institutions across the globe. In Australia, universities cite the importance of addressing student attrition through strategic statements and policy documents, and expend time and resources on the problem. Despite vast expenditures, they have made little impact on student attrition, which continues to negatively impact reputation and revenue. Using a regional Australian university as a case study, this paper analyses a student exit survey to identify the complex and inter-related array of factors that contribute to student attrition. It was found that attrition would be better conceptualised as a wicked problem, which is one that cannot be strategically addressed using traditional approaches to problem-solving. The practical implications of these findings reinforce that current approaches to attrition are likely to fail. Therefore, the wicked nature of the attrition problem needs to be taken into account when developing strategies or policies within higher education.
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Strategy has been defined as “the match an ovganization makes between its internal resources and skills … and the opportunities and risks created by its external environment.” 1 During the 1980s, the principal developments in strategy analysis focussed upon the link between strategy and the external environment. Prominent examples of this focus are Michael Porter's analysis of industry structure and competitive positioning and the empirical studies undertaken by the PIMS project. 2 By contrast, the link between strategy and the firm's resources and skills has suffered comparative neglect. Most research into the strategic implications of the firm's internal environment has been concerned with issues of strategy implementation and analysis of the organizational processes through which strategies emerge. 3
The Japanese model of long-term collaborative supplier partnerships has attracted much attention in recent years from business researchers and practitioners alike (Womack et al., 1990; Dyer and Ouchi, 1993). Several American and European vehicle-makers have attempted to emulate this model, drastically reducing their supplier base and moving toward more collaborative relationships with their best suppliers (Nishiguchi, 1994; Helper and Sako, 1995; Dyer, 1996a). As a result, early involvement of suppliers in product development and solicitation of suppliers’ suggestions for cost reduction are rapidly becoming standard practices in the automotive industry and beyond, along with several other Japanese manufacturing practices (Womack and Jones, 1996).