the cognitive basis of system integration: redundancy of context generating knowledge massimo...

8/2/2019 The cognitive basis of system integration: redundancy of context generating knowledge Massimo Paoli

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The cognitive basis of system integration: redundancy of context generating

knowledgeMassimo PaoliUniversity of Perugia

[email protected]

8.1. The traditional concept of individual knowledge ......................................................................... 3

8.2. Assigning meanings and the concept of autopoietic system ......................................................... 9

8.3. Knowledge as process of processes involving systems of systems based on memory ............... 12

8.4. System integration....................................................................................................................... 19

8.5. The relevant strategic problem: maintain the control of system integration............................... 29

Introduction

In recent years, a management model has been globally affirmed which has

spasmodically researched the efficiency of the business system. The ideology based

on such a model recommends general principles such as frenetic cost controls, and itsupports some guiding ideas such as lean and flat organization, continuous re-

engineering, continuous rationalization, focusing on core knowledge etc. In otherwords, the most efficient but also the scarcest distribution of economic-finance and

human resources ( barely the exact ones necessary). So this gives way to outsourcing

and decentralization of everything that was not considered as core until imaginingvirtually mythical organizations (who cannot remember the icon of the so-called

“virtual company”?).

On the basis of the tasks of such management ideology businesses would however

have been able to maintain the role of integrator systems (in case they had already) orconquer it (in case they pursued it).

Of course, it was not so.The objective of this work is to leave some consideration on how the control of

system integration can really be maintained and also to innovatingly direct it towards

more conveniently retained paths. The basic idea is of redundancy, of knowledgebasis, therefore of men as profiles of adequate professional bearers of such

knowledge, but also of contexts, “organizational containers”, predisposed to allow

men and their knowledge basis to be integrated in order to construct the fundamental

business axis of system integration. This fundamental axis resides in the capability of vision-construction of change and its marching direction (a change that is used as a

“club” competitive strategy).

Inherent evolution and change in the integration system itself, a dynamic activity for

its nature and role, of system integrator, are always ready to decline in the mere

assembling of parts whose technological course is suggested by others (for example

the componers).

To develop these considerations mentioned in the first paragraph, it is necessary to

give a definition of the traditional model of individual knowledge which stays at the

basis of the paradigm of “efficiency without intelligence” and is still greatly common

sense.



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The second and third try to outline an interpretation of different human knowledge,

from whose nature other foundations descend for the choice of an “redundancy of

intelligence” paradigm as opposed to the “efficiency” one, without forgetting the

economic reasons for efficiency, but putting them back in the right place that is

always behind cognitive reasons. In the fifth we try to focus back however also on theconcept of system integration which has been reduced too often in recent years to a

mere problem of design. While in the last paragraph we try to justify on the basis of

the principle of system integration control, the superiority of the reasons of the

“redundancy of intelligence” in businesses, above all for those which want to remain

or become system integrators and through this role, and the control of the system’s

dynamic technology which derives from it, aim to stay or make a name for

themselves as true leaders, above all in new business areas that up in the systems of

integration and its wealth they can “invent” in a large variety.



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8.1. The traditional concept of individual knowledgeFew mathematical problems remain to be resolved,

in a short time we’ll resolve them all Scientific progress in physics is ended, David Hilbert we know all, there are nothing left to discover

William Thompson (Lord Kelvin)

The concept of knowledge - of man and within man - has long been the stable center

of monumental reflections in various fields.

In economy and above all in management studies, its “statute” - or in other words itscontents - has never been made overly clear.

Even today neo-classic economy, management and lastly, common sense are based

on a conception of individual knowledge which is essentially what was devised in the

twentieth century by the epistemology of neo-positivism and logic empiricism.

• Knowledge is made up of information.

• Information has the same nature of knowledge even if it is found at different

hierarchical levels of the cognitive system.

• Therefore a coherent togetherness of information (parts of a jigsaw, bits, etc)

forms a knowledge.

In other words it is enough to put the pieces of a mosaic (information) together and

knowledge appears as a result of the assembling sum of the pieces.

In the neoclassical approach and on the foundations of a managerial approach, in fact,

knowledge-information is held to be endowed with three fundamental attributes.

Indivisibility: “...there is no gain to acquire the same information twice...the production of knowledge is thus basically different from the production of goods...”

1.

There is in other words no intrinsic advantage in re-producing a unit of knowledge-

information, as its intensive utilization benefits from economies of such a scale that

any incentive to produce a new bit of the same knowledge-information is devoid of effectiveness2.

Absence of rivalry in use. The same unit of knowledge can be used by more than one

subject at a time, i.e. one bit of knowledge can be re-produced ad infinitum at

marginal costs equal to zero.

1Arrow K.J.: “Classificatory notes on the production and transmission of technological knowledge”, American

Economic Review, May 1969, pg. 30. Arrow K.J.: “Economic welfare and the allocation of resources for invention”, inNelson R.R. (Ed.): “The rate and direction of inventive activity. Economic and social factors”, Princeton University

Press, Princeton, Usa, 1962, pg 609-625.2«..the same knowledge that enables the youngest to make the first airplane (of paper) will serve him to make his sixth

or twelfth airplane...», Machlup F.: “The economics of information and human capital”, N.Y. University Press, New

York, Usa, 1984, pg. 160.



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Non-exclusiveness in use. This characteristic defines the inappropriability, i.e. the

impossibility, of exclusive use of a given bit of knowledge. Possession of the latter

does not imply its ownership, and neither of these imply exclusive use. It proves

impossible to avoid utilization by others of produced knowledge, and it is impossibleto enhance its value. In order to determine the value of a given bit of knowledge-

information, it is necessary to know its content, but once the latter is known, the

buyer would lack any incentive to pay a price to acquire that which he has already

acquired. On the other hand, refusal by the seller to disclose the content would

effectively prevent any assessment of its value (estimation of the incentives to buy)

on the part of the purchaser. And the market value of the piece of knowledge-

information risks being nil (with the supply already infinitely elastic as costs

approach zero).

By virtue of these attributes, there would be no-one with sufficient incentives to

activate processes for production of new knowledge and innovation. Without any

corrective measures, a veritable collapse of the market would ensue, and indeed does

ensue.

Scarcely any other solution would then be left but to appeal for total public funding

of the processes of new knowledge-information production, leading to the definition

of such knowledge as a pure public commodity3. Alternatively, artificial

appropriability would have to be induced by taking out patents, although a major

debate is still under way as to their true effectiveness4. We will not dwell further on

the patents debate in this paper.

An attempt to separate scientific knowledge, a public commodity, from technologicalknowledge, a commodity resulting from the application of scientific knowledge and

requiring public protection that enables it to acquire different levels of

appropriability, can be traced in the statement that “ideas (knowledge-information)

are neither public nor private nor a mixture of the two”5. Knowledge belongs to

subjects and is reproduced partly through contacts between those subjects who act as

its carriers. In this sense, knowledge is stockpiled in human capital (where it must becontinuously regenerated), and thereby partially regains private status. Knowledge is

3«The character of information as a commodity suggest that it departs considerable from the usual marketabilityassumptions about commodities», Arrow K.J.: “Uncertainty and the welfare economics of medical care”, in Rothschild

M., Diamond P. (Eds): “Uncertainty in economics”, Academic Press, Usa, 1989, pg. 347-375, in particular pg. 348.4 Starting from Arrow’s position of complete skepticism, that of eventual functionality held by Barzel or of partial

functionality held by Nelsen, on the ability of all firms, rival firms as well, to allocate R&D resources, and also

including the directing of paradigmatic paths through the supply of information on the state of the world of David and

Foray. Arrow, K.J.: “Economic welfare and the allocation of resources for invention”, in Nelson R.R.(Ed): “The rate

and direction of inventive activity. Economic and social factors”, op. cit., in particular p. 615.

Barzel Y.: “Optimal timing of innovation”, Review of Economics and Statistics, August 1968, pg. 348-355.

David P.A.: “Knowledge property and the system dynamics of technological change”, World Bank Annual Conference

on Developments Economics WBP, Washington, Usa, 1993, pg. 215-248.

David P.A., Foray D: “Institutions, incentives and the nature of externality in the process of knowledge production”,Conference G.B. Richardson, Oxford University, January 1995.

Nelson R.R.: “The simple economics of basic scientific research”, The Journal of Political Economy, n° 68, 1959, pg.297-306.5Romer P.M.: “Two strategies for economic development: using ideas vs. producing ideas”, World Bank Annual

Conference on Developments Economics WBP, Washington, Usa, 1993, pg. 63-91.



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not private, but if it is stockpiled in men, then the latter, inasmuch as they are

production factors, are to be considered to be endowed with the characteristics of

divisibility, rivalry in use and exclusiveness in use. Perfectly codified scientific

knowledge, however, remains a pure public commodity, one that is capable of

producing codifiable information (human capital); once such information has beenemployed-applied (technological knowledge), it resumes the state of being perfectly

codified, but with different degrees of appropriability depending on its being stocked

in a resource with different economic characteristics, such as human capital, or

depending on regular interventions in a failing market, such as patents.

These attempts to make a distinction share one fundamental and unwavering tenet

with the “Arrowsian” approach. Namely, they would regard it as inconceivable to

undermine the principle of the systematic reduction of knowledge to information

whereby knowledge itself can acquire the intrinsic properties that form the essence of

information, leading to several simplifications with far-reaching consequences.

Perfect explicitability. Knowledge-information can always be rendered explicit. In

this context, the condition of tacitness is essentially concerned with the cost of

explicitability-codifiability rather than with the material impossibility of explicitating.

In other words, knowledge can be defined as tacit when it would be extremely costly

to explicitate it, but given the right incentives, and the right forecast of benefit-profit

expected from the codifying operation, codification can begin immediately. It is not

the nature of knowledge-information that prevents its codification: indeed, the

opposite is true - its nature always makes codification possible (at worst, withdifferent cost levels).

Perfect decomposability. If knowledge-information is perfectly codifiable, that is tosay, representable through symbols and linguistic expressions, then it can be

decomposed at will. Consequently, it will be equally easy to decompose the processes

by means of which it has been obtained. And provided that the definition of ownership rights and of the elements forming the object of appropriability is clear,

this characteristic of decomposability of the object knowledge and of the processes

that produce it makes it feasible to devise some efficient form of division of labor inthe processes themselves

6. In the last analysis, this allows for some form of efficient

partitioning of innovative labor in general.

Perfect transferability/absorbability. In addition to decomposability, in the light of

the completely symbolic nature of knowledge-information it is obviously necessary

also to postulate its perfect transferability. But in order for this to take placeefficiently and effectively, at least two requirements must be satisfied: (1) there must

6«Stronger property rights increase the efficiency of contracts for the sale of technology, and hence, increase theincentive for firms to specialise in the production of technology.» Arora A., Gambardella A.: “The changing technology

of technological change: general and abstract knowledge and the division of innovative labour”, Research Policy, n°23,

1994, pg. 523-532, in particular 531.



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be a clear regime of appropriability of knowledge-information itself, and (2) from the

cognitive point of view (i.e. at a greater depth) there must be perfect sharing of the

syntax through which the bits of knowledge can be assembled into the “right”

meaning. Thus, just like a radio signal, knowledge-information is always ready to be

incorporated and absorbed (provided that adequate investments in R&D have beenmade in the past) on the basis of a model that revolves around the relative costs of

production or absorption (and in any case this interesting contribution of what is

known as ‘absorptive capacity’7

appears to be more an extension-generalization of

the Arrow model than a genuine alternative.

Indistinguishability of the process from the linguistic product . The neoclassical

framework has led to the conviction that knowledge is a resource given in every

equilibrium state of the system in exactly the same way as the other production

factors, the only peculiarity being that it constitutes the input for a process whose

product is once again (new) information8. The peculiarities of the process whereby

knowledge-information is produced thus ultimately correspond to the peculiar

characteristics of knowledge as an economic commodity. In other words, one finds a

systematic identification between knowledge as a process (learning) and knowledge-

information as the linguistic (symbolic) result of this process9.

The clear-cut distinguishability between scientific knowledge and technologicalknowledge. While the distinction between scientific and applicational knowledge

tends to be somewhat blurred in Arrow, inasmuch as it is “all” regarded as codified

knowledge, the 1959 contribution by Nelson10 resulted in one of the most long-lastingclassifications of the economics of innovation. On one hand (1) there is basic or

scientific knowledge-information, which remains a perfect public commodity11

,

revealing from the cognitive point of view a hierarchical super ordering as compared

to technological knowledge, of which it quite frequently acts as an input12

; on the

other side (2), one finds applied knowledge-information, whose nature is not different

from scientific knowledge, but which can be “rendered appropriable” through

7Cohen W.A., Levinthal D.A.: “Innovation and learning: the two faces of R&D”, The Economic Journal, n° 99, 1989,

pg. 569-596. Cohen W.A., Levinthal D.A.: “Absorptive capacity: a new perspective on learning and innovation”,Administrative Science Quarterly, n°35, 1990, pg. 128-152.8«...invention and research...are devoted to the production of information», Arrow, K.J.: “Economic welfare and the

allocation of resources for invention”, in Nelson R.R.(Ed): “The rate and direction of inventive activity. Economic and

social factors”, op. cit., in particular pg. 614.9 This identification is perfectly compatible with the irrelevance of system dynamics in neoclassical studies on the

equilibrium model. Arrow K.J., “Economic Welfare and the Allocation of Resources for Invention”, in Nelsen .. (Ed):

“The Rate and Direction of Inventive Activity”. Economic and Social Factors”, op. cit., in particular p. 609, where the

author states two basic assumptions on the model.10«There is a continuum spectrum of scientific activities. Moving from the applied science end of the spectrum to the

basic science end....the goals become less clearly defined and less closely tied to the solution of specific practical

problems or the creation of a particular object», Nelson R.R.: “The simple economics of basic scientific research”, op.cit., pg. 301.11«...basic scientific research is...the best example of pure public good.», Romer P.M.: “Two strategies for economicdevelopment: using ideas vs. producing ideas”, op.cit., pg. 73.12«...on Gibb’s law of phases rests the design of equipment as diverse as petroleum refining, rubber vulcanization,

nitrogen fixation....», Nelson R.R.: “The simple economics of basic scientific research”, op. cit., pg. 302.



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exogenous market-regulating policy measures (mainly patents). The impact of such

measures (degree of influence and exclusiveness of patents) should derive from a

precise definition of the extent of the incentives judged to be applicable or optimal on

a case by case basis.

All that is based on the assumption that good common sense would essentially

translate to:

• reality is outside of us and is accessible, that is to say, it informs us of its sense

(by observations or experiments).

• formal (language) systems that we use to represent theories, describe reality and

to do so in a way that the first ones to express it, do not have syntactical problems

(they can be logical or complete, it is enough to be particularly accurate in

elaborating them);

•there are no ambiguities in attributing meaning to the theories (also when theyare still hypotheses) to observations and to languages used to describe them;

therefore there are no problems attributing common and shared meanings to

theories when they become universal truths;

• from a methodological point of view it is necessary and sufficient to follow the

Aristotelian/Cartesian principles of the distribution of economy solving, or rather,

it breaks up the problem, starts to resolve the smallest and easiest problems, when

it may seem that it has resolved everything (or a considerably substantial part) it

reconstructs, given that to reconstruct is only the analogous opposite to

deconstruct (there are not any differences of quality of the process).

In the course of the twentieth century this explanatory paradigm that is still the basis

of good common sense prevalent also in management was annihilated by dynamicepistemology.

Bachelard13

has made us understand the inconsistence of the fourth point. Rebuilding

is a construction of diverse complete sense and it cannot be compared at all tobreaking it down it. Thanks to this breaking down process we will never know what

we lose from the ‘whole’ object of decomposition, given that we break things down

when we still do not know anything, while thanks to the re-adding process, re-

integration itself will give the observer/re-integrator completely new motives toattribute previously unknown meanings to the whole inconceivable before (it is in

any case the systematic principle that the ‘whole’ is more than sum of the parts).Duhem

13and Quine

14have dissolved the third point indicating the impossibility of

singularly heading the theory. Gödel15

has stripped down the second showing how

13 Bachelard G., La formation de l’esprit scientifique, Vrin, Paris, 1938. Bachelard G., Le matérialisme rationnel, PUF,

Paris, 1953. Bachelard G., Le nouvel esprit scientifique, PUF, Paris, 1996.13 Duhem P., La théorie physique: son object et sa structure, Rivière, Paris, 1914.14 Quine W.V.O., Ontological relativity and other essays, Columbia University Press, N.Y., 1969.15 Gödel K.: Über Formal Unentscheidbare Sätze der Principia Mathematica und Verwandter Systeme, I (Sulle

proposizioni formalmente indecidibili dei Principia Mathematica e dei Sistemi Affini, Proposizione IV), Monatshefte für

Mathematik und Physik, Vol. 38, 1931, pg. 173-198. Nagel E., Newman J.R.: La prova di Gödel, Bollati Boringhieri,

Torino, 1992, pg. 93 e ss.



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formal systems are complete and then are contradictory, or are not contradictory, but

then must be incomplete. Maturana and Varela have fundamentally dismissed the

first by the concepts of autopoietic system and structural coupling.

So, we find ourselves forced again to reconstruct a different sense to individual

knowledge laces, a sense exceptionally rich of implications.



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8.2. Assigning meanings and the concept of an autopoieticsystem

Everything that is said ...the reason sees onlyis said by an observer what can produce

Humberto Maturana according to her design... Immanuel Kant

An important part of modern neurophysiological studies argues that individuals areautopoietic systems16

, that is, brains and bodies that can operate only thermodynamic

exchanges with each other and with the environment. Brains are connected by filtersthat select the stimuli that the central nervous system interprets without the possibilityto access reality (i.e. the environment or the world) or the other autopoietic systems

(i.e. the other individuals). According to this view (also labelled structural coupling)

individuals can only exchange thermodynamic expressions like:

• vibrations in the air (a phenomenon perceived in a very narrow global

spectrum of audible frequencies),

• light in different wavelengths (and also in this case a phenomenon perceived ina very narrow global spectrum of visible wavelengths),

• chemical particles which compose smells,

• pressures on the skin (i.e. pressures on our tactile receptive system under the

skin).

In other words, individuals can only exchange thermodynamic impulses, supports for

“languages”.

Supports that only by an oversimplification we can consider hand in glove with the

language17

.In any case pure languages (sequences of symbols ruled syntactically) that are only

significants, linguistic expressions, such as words, images, sounds, behaviours, in

other words information18.

Information cannot give sense, they need sense.

Knowledge is your personal system of meanings.

Knowledge is the matrix that allows you:

16 Maturana H., Varela F. (1980) ‘Autopoiesis and cognition: The realization of living’, Reidel, Dordrecht.

Maturana H., Varela F. (1987) The tree of knowledge, Shambhala, Boston. Varela F., Maturana H., Uribe R. (1974)

‘Autopoiesis: The organization of living systems, its characterization and a model’, Biosystems 5 (4), pp. 187-196.17 In this chapter we have not the opportunity to develop this problematic level of the relationship between supports andlanguages.18 In this picture knowledge does not have the same nature of information. The first is pure sense and it cannot beshared, the second is language, syntax, information carried by significants without any objective sense, vehicles that

transport symbols (in any form) to which the emitting subject has applied a meaning, and to which each of the receivers

will apply his subjective meaning (too many senses = no sense).



10

• to recognize a sequence of symbols as interrelated to each other, not symbols

at random,

• to form one or more significants transporting information;

• to apply sense to the significants that transport information (process depending

on your capability to interpret, i.e. on all that you already know).These significants may become the Vivaldi’s Four Seasons or a troublesome noise,

the strange look of an anonymous face or the beautiful smile of your son, the

sumptuous perfume of a Brunello di Montalcino or the stench of rotten fish,

according to the ‘sense’ that it is given by the single individual. It is the knowledge of

the individual that gives them some meaning, and only specific meanings.

Individuals produce sense even if they do not want to (they think, they know, they

learn even if they do not want to), they survive because they produce sense

continuously, which is not necessarily the right sense, of course. An autopoietic

system can never know if it is right or not, because the sense created about anyphenomenon it interfaces is always an hypothesis of the world and it remains forever

an hypothesis, whether it is stronger or whether it is weaker. This system is

continuous and greatly independent by will because it serves the continuous acting of men, their continuous intervention on the world. In fact individuals always behave,

even when they decide not to (even in this case we cannot deepen the theme).

Individuals cannot share senses because they can only “speak about them”, they canemit significants. As a consequence of this regime of exchange, the autopoieticsystems cannot measure their semantic distance or proximity and cannot

communicate and share any meaning but only information (i.e. linguistic expressions)that do not carry any objective sense per se. In fact a significant has a sense for an

emitting system and a sense for each of the million other systems that receive the

significant. “Red” has a meaning for the emitting individual, and millions of meanings for the millions of potential or actual receivers

19; so, it can neither have

“one” meaning, nor a “shared” meaning. The autopoietic systems composing an

organization, therefore, cannot share any rule or any other organisational routine or“memory”, they cannot share any actual vision of the system (product or process),

because they do not share senses. Also, they cannot exchange meanings (not even

about “the syntax of the rules” to share in order to form an “organization”), and they

cannot exchange meanings about the distance or the proximity of their processes of convergence (if there was one) because they only produce languages, syntax,

significants in a strange spiral cycle in which the more they are aware of the

uselessness of the effort to communicate something to someone, the stronger is the

effort to communicate20

.

We cannot deepen the consequences on organization, but this phenomenon allows us

to introduce the idea that individuals in social systems (less and less systems of men,

more and more systems of contexts) do not form organization but systems of relationships among micro-meso-macro-contexts (physical, socio-technical, cultural

19 Think for example of a daltonian.20 We share Weick’s idea according to which organizations do not exist, but there is only the effort to organize (Weick

1969).



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and so on). Into the organizations the illusion of sharing is often created by the effort

to conform to what each individual believes to be dictated by the necessity of co-

ordinating behaviour21

. They are nonetheless convergent because they are originated

by the same context (constructed by each participant for himself, in parallel, but

together in the same context). At the most you have convergence, not sharing, andyou have convergence of languages (words, behaviours and so on).

It is the same process with which the operational slangs22

emerge, for example, or the

dialects that is almost transformed into common spirits, the languages of veterans, the

languages of war stories 23

.

The concept of organisation implode into its action.

The social system (ex-organization) becomes a hierarchical system of continuous

"formatting" patterns of action and not a separate entity, which applies such

patterns24

.

In this picture the system that should be integrated is not out of you, somewhere in an

objective reality. It is in your mind. Each individual that takes part in the system

integration process has a different system in mind and, most of all, has a different

vision of its conceptual and technological dynamic. It is important to not mistake the

actual sharing of significances with the convergence of linguistic behaviour. Many

times the last seems to put in common even some senses or values, but it is a pure

linguistic illusion. Language convergence does not mean that you share meanings,

and in particular that you share significances about a process like system integration

(and its dynamic).

The system you have realised (product or process) is not the product of shared meanings and it is not in an actual common vision. It lies in its specific design: amore or less sophisticated linguistic product.

Like every other linguistic product, the design is a complicated product-artefact.

System integration is a process, and above all, if you want to use it as a competitive

weapon, it is dynamic, like the conceptual and technological evolution of the system,

therefore, it is a complex process.

21 A more in-depth (and probably disruptive) line of thinking emerges from the reasoning above. Individuals as parts of

organisations (understood as social systems) have “intentions”. A financial vice-president wishes to be CEO, an

important politician, a rich man, but also a member of “Buena Vista Social Club”. It is worth noting that this feature of

“having intentions” in a social system has never been considered in social sciences. The concept of system, in fact, has

been used like a simple analogy from physics or biology. However, while physical or biological systems are composed

of parts that, although they might be other things (i.e. play other roles in different systems), are assigned to and

constrained by specific tasks. An atom of helium does not wish to be an atom of argon, our liver does not wish to be a

brain, but how many other roles is a financial vice-president wishing to interpret?22Obvious examples of slang are easily found in nearly all the specialized magazines, even designed for a popular

readership, like those which deal with microelectronics, computer science or the Internet, which have become

practically illegible for anyone not having a minimal familiarity with these technologies.23 Cohen, M.D., Burkhart, R., Dosi, G., Egidi, M., Marengo, L., Warglien, M., and Winter, S. (1996), ‘Routines and

Other Recurring Action Patterns of Organisations: Contemporary Research Issues’, Industrial and Corporate Change,5(3), pp. 653-698.24 Argyris, C. and Schon, D.A. (1978) Organisational Learning: A Theory of Action Perspective, Reading, MA:

Addison-Wesley.



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8.3. Knowledge as process of processes involving systems ofsystems based on memory

“Live on the contrary!” repeated Alice with great astonishment, “I’ve never heard such a thing”.“But it offers a great advantage” said the Queen, “which isthat memory works in all senses.”“I’m sure that mine functions in only one direction” Alicenoted “I can’t remember things before they happen”“A memory has little value if it only works for the past” said the Queen.Lewis Carrol

25.

The reflection on individual knowledge needs complexity.

Let us attempt to follow a logical, coherent line of thought, especially in trying tocompensate for and overcome the considerable difficulties and the traps set by the

limitations of any language.

A person’s knowledge is a dynamic and complex system, composed of at least four

other large systems:

1. The deep system of meanings produced in continuous and tied to the self-

reference of the psyche26

;

2. The system of memory creation-processing-activation processes (use and

production of significances);

3. The system of memory processing-activation-creation products27(fromsignificances to linguistic expressions/perceptions and vice versa);

4. The system of relationships among 1-2-3-4.

When the concept of system is given the meaning of a complex unit, because it is

intrinsically dynamic, relational (the system emerges from these, and is not seen asthe static equivalent of its parts or of its structure) and organized (again, held together

by processes), then one has a unitas multiplex28. Here the foremost and fundamental

complexity is created by conjugating, in a dynamic relational perspective, the idea of

unity with that of diversity, multiplicity, irreducibility of its characteristic unitary“system” properties to component parts, individuality combined with

decomposability (or “quasi” decomposability). The latter, however, is obtained at the

price of decomposing and transfiguring the system itself, despite the fact that such a

system cannot be reduced to its component parts29

: for on the one hand, the whole is

25Lewis Carrol is the pseudonym of mathematic logic, Sir Charles Lutwidge Dodgson known to the public for having

written stories which may appear only for children such as “Alice in Wonderland” and “Behind (or Through) the

Looking Glass”. The piece is drawn by Carroll L: (Behind the Looking Glass”, Garzanti, Milano, Italia, 1975, pg. 203.26 The sense of things with “us” at the centre (from the moment in which we are conscious we are naturally at the centreof our respective universes). Gregory R.L. Enciclopedia Oxford della Mente, Sansoni, Firenze, Italia, 1991, p. 746.

Arduini A., Fondamenti della Psiche, ETS, Pisa, Italia, Cap. 11.27 In our opinion even behaviour is a linguistic product.28 Angyal A.: “Foundations for a science of personality”, Harvard University Press, Harvard, Usa, 1941.29 The evolution of this approach consisted in a transition of the following kind:



13

more than the “sum” of its parts30

and, conversely, the parts cannot be reduced to the

system because the whole is actually less than the “sum” of the parts31

.

In order to grasp the nature of the complexity we are dealing with, it is indispensable

to appeal for what has been termed the concept of emergence32

: a phenomenon linked

to the process of transformation of the parts into a whole which, by this very process,forms and transforms (transforms and forms)33

, maintains and organizes the

complementary tendencies, creates diversity, forges links between and organizes

antagonisms, organizes antagonism within complementarities34

, controls

organizational entropy35

, allows variety to spread out and repetitive order to be re-

established and transformed into organizational reliability, i.e. is the very the survival

capacity36

of the knowledge-system itself.

In other words, knowledge is the continuous emerging sense of things, meaning that

has intrinsic value, independently of how or through what means it is created and

stored.

Sense is the cornerstone allowing construction of our interpretations of the reality

which surrounds us, without which it would be impossible to plan and evaluate our

continuous interventions in the world.

But how can we without memory?

“I don’t know – I don’t remember,” are equivalent as far as the execution of any

action in this interpreted world is concerned.37

«L’intelligibilité du compliqué se fait par simplification (le simple est toujours le simplifié - G. Bachelard,)

to L’intelligibilité complexe se fait par integration»

30 “Superadditive composition rule”, Forester H. von: “Communication amongst automata”, American Journal of Psychiatry n°118, 1962, pp.866-867.« The mere fact of analysing an organism starting from its constituents involves a loss of information about this

organism », in Atlan H., “L’Organisation biologique et la théorie de l’information”, Hermann, Paris, France, 1972, p.

262. Simon H.A.: “The architecture of complexity”, Proceedings of American Philosophical Society, n° 106, 1962,

pag.468.31 Morin E.: “ Il metodo. Ordine Disordine Organizzazione”, op. cit., pp. 145-147.

The parts are “constrained” within their role in order to reduce complexity, at least within the confines of the system;

this enables the system itself to assume and maintain its own functional identity .32 Emergence as a quality, a property, a product (of the organization in a system), globality (since it cannot be

dissociated from the systemic unit), event (it arises discontinuously once the system has been formed), novelty (in

respect of the parts), irreducibility (cannot be decomposed without the risk of its own decomposition which, as in

system decomposition, is also transformation into something else), indeducibility (cannot be deduced from the quality-

functions of the parts) and finally implexity. Morin E.: “ Il metodo. Ordine Disordine Organizzazione”, op. cit., pag.139-143. Le Moigne J.L.: “La Modélisation des Systèmes Complexes”, op. cit., pg. 48. Churchland P.S., Sejnowski

T.J.: “The computational brain”, MIT, Cambridge, Usa, 1992, pg. 13.33«Tout système complexe peut donc être représenté par un système d’actions multiples, ou par un processus qui peut

être enchevêtrement de processus......Aussi enchevêtrées a priori que soient ces actions, on peut toujours les represénter

par des compositions des foncyions temporelles et spatiales et morphologiques.... », Le Moigne J.L.: “La Modélisation

des Systèmes Complexes”, op. cit., pg. 48.34 Lupasco S.: “L’energie de la matière vivante. Antagonisme constructeur et logique de l’hétérogène”, Julliard, Paris,

1962, pg 332.35 Morin E.: “ Il metodo. Ordine Disordine Organizzazione”, op. cit., pg. 156.36On this theme, AtlanH.: “On a formal definition of organization”, Journal of Theoretical Biology, n° 45, 1974, pg. 1-

9.37 In neuropsychiatry, the very famous case of Mr. “H” deals with a man with a very serious case of epilepsy, whose

hippocampus was cut off from his cerebral cortex to prevent him from dying during a seizure. His long term memorywas separated from his short term memory. For this man, this meant the end of all learning. His psychologist continued

to visit him on a weekly basis for twelve years, yet at every visit had to introduce himself as if they were meeting for the

first time.



14

We certainly have many forms of memory, as we shall attempt to summarize in the

figure 1, but today the impression that memory-knowledge is above all “sense-

meaning” (emotional as well, obviously38

) is clearer than ever.

Declarative and procedural short-term memories tend to function both on a

prevalently syntactic basis, given the nature of their contents, most of which areexpressible and expressed, codifiable and codified. Naturally, their nature is

hybridized along the paths which lead to long-term memorization.

Long-term declarative and procedural memories, on the other hand, have been shown

to have active contents which refer prevalently to meanings, not expressed and not

expressible, nor codified or codifiable, which reveal their strong semantic orientation.

Naturally, their nature is hybridized the harder one tries to translate their contents into

action-behavior-language and, in general, communication. An inane effort for

structurally-coupled autopoietic systems, repeated again and again precisely for this

reason, probably with an intensity of effort correlated to the perceived degree of

inanity.

Short-term memories, on the whole, have active contents which refer to symbols-

signs-forms-sounds, while longer-term memories reveal active contents attributable –

on one hand – to the sense to be given to the contents of the short-term memories,

and – on the other hand – to forms of “sunken” consciousness which are absolutely

personal and non-transferable.

Human memories are fed by all the perceptive-cognitive processes and, roughly,

while declarative memories are more oriented to sustaining our capacity for inventing

associations and interpretations of the world (extracting meaning from perception),

procedural memories allow us to plan our next move (assigning meaning to actions).One fact has to be made clear: in reality we use all our memories together,

systematically and continuously, but what is really needed at the base are the contents

of sense, since we don’t use syntax either for interpreting the world or for planningour interventions in the world. Both of these are fundamental processes for existence,

and are the fruit of giving meaning, that is of “making sense” (we build a world

which is meaningful for us, through meaningful actions).Language and behavior, here generally defined as “information” (“syntax”), are tools

for producing meanings and should be the vehicles for doing so. Just think of the

difficulties involved in making them function, however – I’m not saying exactly, buteven just correctly - in order to understand the abyss existing between the world of

memories-knowledge-meanings and the world of information-syntax-language-

significants.

38 Who knows why we’ve removed emotion from the processes of knowledge production, as if a scientist, an engineeror a technician learned without emotions. It has become certain on the other hand that the most effective learning takes

place when emotions are involved. Do you remember how easy is was to “do well” in the subject taught by a friendly,

enthusiastic professor?



15

Fig. 1. Memories

Actions Conduct Language Smell, Taste, Touch, Hearing, Sight

Phyletic Memory Phyletic Memory Actions Polysensorial Memory

“Short-term” or “active”

memory “Long term” memory

Episodic

Explicit or Declarative Memory

Evocative -

Nominalistic

Tied to distinct autobiographical or

social events

Conscious registration of explicitdata codified in a language

(information):

numbers, words, images (as codes,

without meaning).

Tied to names and linguistic

attributes

Cerebral area principally activated:

hippocampus (towards the neocortex

for long-lasting learning).

Gestalt, recognition of faces – words –

contexts (set), images – words –

numbers – meanings (set)


neocortical system (which replaces the

hippocampus at the moment of memory

activation). Possible physical

modifications to the system of neuronalconnections imposed by events.

Senso-Motor

Implicit or

Procedural Memory

Interpretive

Short-term registration and

continuous repetition (for a certain

period called the initial “cognitive”

phase of learning of sensomotor or

interpretive abilities) as a rule in theform of linguistic symbols and

signs.

Cerebral areas principally activated:

hippocampus – cerebellum (towards

the neocortex and cerebellum for

long-lasting learning).

Actions in physical world

Advanced phases (use and execution

without cognition) of sensomotor

abilities. Advanced phases of abilities

regarding construction of meanings –

reality – contexts. “Wisdom,”“creativity,” “professionalism,”

“intelligence,” “intuition”

Actions in the mental world or world of

meanings.


hippocampus – cerebellum, neocortical

system.

Possible physical modifications to the

system of neuronal connections

imposed by the event.

Source: Paoli M., Grassi M.: Caught in the middle: An investigation of three recurrent controversies in the management of organizational knowledge,

Paper to EGOS International Meeting , Business Processes Resource Centre, Un. of Warwick, Conventry, UK., 2000.



16

The latter remain perceived reality, the sense of which depends on the person

attributing this sense. They are observed systems which, at the most – and only if the

rules of syntax have some probability of being used in agreement among the

observers – set off a process of meaning attribution, which in ordered to be developed

into “sense” depends totally on the structure of the meanings already processed and inthe possession of the receiver.

Memories are not files.

This metaphor, so simple that we kind of hate to abandon it, is unfortunately

completely misleading.

Memories, just like knowledge (which from this point on are always knowledge-

memories) are always active; the neuronal circuits which support memories

(especially long-term) are always active, even though the filtering involved in the

activity of producing the state of consciousness brings to our attention only what is

required (the product of this constant neuronal activity), and only when it is neededand has been evoked.

Remembering is an act of re-composing.The most suitable metaphor probably comes from “distant” paleontology.

In fact, construction of the external forms of prehistoric animals takes place through a

process of re-composition which is usually based on a few poorly-conserved fossilsof these animals’ internal structures.

The re-composition of these external forms is largely “creative” (especially if there

are very few fossils or they are in really poor shape), since it has to replace – using

admittedly ad-hoc solutions – the inevitable holes in knowledge produced by thereduced availability of fossils (and of their “internal” character).

Remembering is a similar action, re-composing what is still active about the memory,while inventing the missing “links” and inserting them for the purpose of completion.

Bringing a memory to mind is therefore an act of “constructing” sense, with certain

aspects which are completely invented, true “stopgaps” of memory activation, and

not an act of mere “reproduction.”

Construction of this largely depends on the meanings (or on the meaningful role)

which we would now (and not then) like this memory to have.

This paleontological metaphor is so appropriate that memory researchers don’t talk about forgetting as a “loss” of information from a given area or storage file, but rather

of forgetfulness as a decreased level of activity of the memory, to the extent that the

“links” or fossilized pieces of the memories are too few to make their reconstruction

possible.

But while memories based on active contents of an explicit type depend mostly on

the state of activation of the memory (it’s easier to forget), the long-term knowledge-

abilities which are activated by procedural memories are almost never forgotten; on

the contrary, even after a long period of non-utilization, when the activity is resumed,

the ability is restored – barring some initial difficulty which is rapidly overcome –

practically at the same level at which the ability was “left off.” This is true in the

motor sense – simply think of riding a bicycle – as well as in the interpretive sense;



17

just think of one’s capacity to solve polynomials or equations, or of diplomatic

mediation.

Procedural knowledge-memories (and declarative long-term memories) seem to be

more important to us, and have pre-eminence over others (always from the viewpoint

of survival of the autopoietic system), precisely because they make us “proactive”with respect to the environment itself, to such an extent that we sometimes believe we

“control” it.

Knowledge-memories either have a “sense” or they don’t survive long, or are actually

never even formed.

Just try to memorize the part of Hamlet, a challenging musical score or, on the

contrary, the telephone book. It would be an impossible job unless you “become”

Hamlet, even just a little, unless you give the music an internal meaning. On the

other hand, it’s easy to see that the telephone book cannot be memorized, precisely

because it has no meaning.

Our mind – although it uses images, language and other results of perception –

transforms everything into meaning and “lives” on these meanings.

Meanings that have a sense for the survival of the system which produces and utilizes

them.

Everything has to “mean” something, that is, be a part of the system which prefigures

human actions (interventions in the world), or it is not part of memory-knowledge,

either short-term or long-term, whether declarative or procedural, deep or not deep.

This is true regardless of the meaningful “support” (language, sounds, images,

behavior) through which perception (sight, hearing, smell or touch) or its interpretive

translation is communicated.Thus, knowledge-memory-meaning is something that makes “sense,” sense which

only subsequently and for social purposes, men attempt to transform into complicated

strings of symbols-sounds-images-behavior.The latter, as we’ve already said, are fully recognizable as “information.”

Symbolic systems without meaning of their own.

If meaning is the process of making sense of perceptions, then the transmittingsystem will attribute meaning which will never be transparent to the receiving

system, since he in turn will be attributing his own.

Let us reflect on the process (a miniscule mental experiment).A system of meanings-memories-knowledge in a person produces the need for

socialization. For example, he must warn a colleague designer of something that

seems to be an imminent danger of mistake in his role into the system integrationprocess, or of his vision in this phase of the designing process.

The person then produces an attempt to convey senses and meanings (of danger) to

another person (or a multitude of people) supposedly in danger, by means of the onlything that can come out of him, a string of sounds-symbols-behaviors.

The emission of sounds, symbols or behaviors is perceivable as information only if:

• it is codified,

• it follows several syntactic rules,



18

• such rules are part of the knowledge-memory of both parties (transmitting and

receiving), admittedly each in his own way.

If the transmitter should use an unfamiliar syntax, the string of sounds-symbols-

behaviors would become an object which the receiver will find difficult to provide asense for (much less the right sense), although this string maintains all thecharacteristics of information

39.

In order for the communication of danger to be understood as such in the “head” of

the receiver, a great number of meaningful coincidences are therefore necessary;without them, the warning will be interpreted in some other way, leading to a set of

consequences.

As already mentioned the paradox is that our process of attributing meanings – likethought, digestion or heartbeat – is removed from human will and control, so that we

think even if we don’t want to think, and we attribute meanings to our perceptions

even if we don’t want to do so.40

You attribute meanings continuously and to everything you perceive.

So what happens is that even though the string of sounds or symbols received issyntactically unknown, people still try nonetheless to find a meaning and attribute it

to the event41

and this is what often covers the vast difference between what is

knowledge-memory-meaning and what is merely information without a sense of its

own.

Everything in the end seems to have a sense, because you always attribute senses to

our perceptions, regardless of what they are. The transfer process suggests that this

sense lies in the “medium” that you have used, but it actually lies always and only inyour processes of attributing meaning, processes which are absolutely personal and

non transmittable.

If you accept this reasoning, what are the consequences for companies that aim to

control and drive the technological dynamic of their multi-tech systems’

(products/processes), or, in other words, in this regime of the nature of knowledge,

how is it possible to maintain the control of systems integration?

39 Before finding the famous Rosetta stone there had been many attempts to interpret Egyptian hieroglyphics.

Naturally, the meanings given to the signs seemed quite amusing after the stone had been found, although they hadn’tbefore.40 On this point, it is fundamental to understand that by affirming, for instance, that any given thing is non-sense, we areattributing a sense to that thing.41 It should suffice to recall the many quite representative examples concerning ambiguities in interpreting cause-effect

relationships.



19

8.4. System integration L’intelligibilité du compliqué

se fait par simplification(le simple est toujours le simplifié).

L’intelligibilité complexe se fait par integration.Gaston Bachelard

The system integration process is a meta-super-cognitive-negotiative-dynamic-

process among individuals distributed in several firms’ contexts that are composed by

specific physical attributes, but also by the knowledge of the agents themselves, their

linguistic interactions, their organizational rules, incentives, power distribution,

beliefs, myths, cultures and so on (the constituents of the "formatting" power "in" and

"of" these contexts).

Agents by which you can construct at the same time the system integration process of a multitechnological artefact (process or product) and as a consequence its global

evolutionary path.

The dynamics of the artefact-product/process-system in fact arises from the joined

and superimposed technological trajectories of the whole and its parts. Moreover, it is

the result of the multidisciplinary convergence-divergence and integration-

disintegration, both at the technological and scientific level. This phenomenon

constitutes a further level of evolution endowed with remarkable generative capacity

of: a) autonomous scientific and technological trajectories-opportunities, b)

continuous reconfiguration of the dependence and influence relationships betweenscientific-technological fields. Regarding the latter, it is worth highlighting that it

affects to a great extent the dependence and influence relationships have betweensystem, subsystems and parts.

In light of this, the evolution of the product/process-system (and therefore the activity

of system integration) can be identified as a continuous destruction-reconstruction of hierarchical and functional orders which affect over time the ways of the conceptual

and ideal decomposition42

of the product-system itself.

In this picture system integration is a macro-process of conceptualisation, by whichseveral problems for design of the product or the engineering of the manufacture may

emerge, but the relationship between the dynamic of the conceptualisation and the

following problems of design is the same as what you can observe betweenknowledge and the linguistic artefacts called information.

Thus system integration can never be reduced to a problem of design, even if it may

be expressed only by design, just like knowledge that can never be reduced toinformation-language, even if it may only be expressed by language.

42 Decomposition is conceived here as modeling: ‘Action d’elaboration et de construction intentionelle, par composition

de symboles (to which we add also non-symbolic schemes), de modèles susceptibles de rendre intelligible unphénomène perçu complexe, et d’amplifier le raisonnement de l’acteur projetant une intervention délibérée au sein du

phénomène; raisonnement visant notamment à anticiper le conséquences de ces projects d’action possibles’ that in thesystem dynamics is modeling of a complexity for which it is true the distinction: ‘Pour comprendre (donner du sens à)

un système compliqué on peut le simplifier -pour décumvrir son intellegibilité (explication). Pour comprendre un

système complexe on detruit a priori son intellegibilitè’ (Le Moigne, 1990).



20

In this framework we introduce the key distinction between the capacity of designing

and producing the product-system, which is at the most complicated 43(a

product/process design completed in every aspect is only a complicated linguistic

artefact), and the effort to master system integration and its evolutionary dynamics

which is the complex strategic problem

44

In effect the understanding of which step isbetter to do along the invented trajectories of parts, the trajectories of the system, the

trajectories of the relationships between parts and system, the trajectories of the

system integration, is actually a complex construction.

Complicated systems = fully decomposable systems;

Low complexity systems = systems almost decomposable45

into hierarchically orderable implex

levels46

;

High complexity systems = differentiatable systems, which cannot be decomposed without

significant mutilations the dynamics of which is unforeseeable;

At this point it may be useful to establish, with a certain degree of automatism, a

corresponding classification of agents' constructions. More specifically, one finds

two contrasting orders of construction/modelization for the composition of observed

systems47

:

System/Phenomenon Representation System/Phenomenon Representation

Decomposable: complicated Indecomposable: complex

By Disjunction: application/decomposition By Conjunction: combination/composition

Decomposed: simple Indecomposed: implex

43And, therefore, conceived, designed and defined.44And, therefore, non-definable, uncertain and undefined. The distinction between complicated (or hypercomplicated as

an aero engine that can have up to 22,000 components) and complex points out that the complexity is not in the reality

but in the constructions built for it at the subjective and at the organizational level. Those representations, in fact,

change according to the endowed knowledge (Paoli, 1995).45 The system can be subdivided into relatively independent parts. That is to say, it is possible to obtain an adequate

partition of the system allowing most interactions to occur within each individual component part, and not among the

parts. Interactions among the parts are weaker than interactions inside the parts. Simon H.A.: “L’architettura dellacomplessità”, in Simon H.A.: “Le scienze dell’artificiale”, Il Mulino, op.cit...

Identification of characteristics of near-decomposability of systems has an important bearing on the issue we are

analyzing because it is linked to innovative typologies of a modular nature, characterized by a degree of design

autonomy at the subsystem level. The assumption of near-decomposability is linked to the manner in which system

knowledge of a separable type is produced, that is to say to the relative independence and the possibility of

decontextualizing the cognitive foundations pertaining to the individual parts within the whole. However, as compared

to Simon’s approach, the point of view developed in this paper differs in that it more explicitly considers near-

decomposability not so much as an attribute of the system in itself, but rather as a function of the representation of the

system. For representation is subjective: it is important to observe how things are structured in order to grasp

implications. If it is true that the nature of knowledge influences the decomposability of the system, it is also true that

the manner in which the system’s representation construes its decomposability influences the nature of the knowledgerequired for its control. Dominion over the construction of representation cannot disregard the environment, but

organizational implications are relevant. If decomposability is not a function of the system as such but of representationof the system, then decomposability is generated in the context of division of labour.46 The opposite of complex is not simple, but implex (indecomposable units that cannot be reduced to a single element).47 Le Moigne J.L.: “La Modélisation des systèmes complexes”, op. cit., p. 27.



21

The complicated construction-model obtains by disjunction-decomposition the simple

view of the “fragmented” (reduced) phenomenon. The complex construction-model

obtains by composition-combination an implex vision (non decomposable) of a non

decomposed phenomenon. The former may be decomposed and the job divided (to

photocopy a great number of pages for example), the latter cannot be decomposedand it is much better if you do it by yourself (to write a paper for example).

Any process of modelization, however much it makes use of sophisticated forms of

codification and language, is an eminently and irreducibly “personal” process through

which different alternative readings-interpretations of phenomena can be created .

Since complexity is inherent in the representation, it belongs to the latter. This means

that there are no complex phenomena, but complex constructions of phenomena that

have been observed , i.e. created , (dans notre tête).

We can outline the creation process (and complexity creation) as the flow of

becoming that relinquishes the idea of analysis of something perceptible in order to

assume the idea of intentional constructive conception (deliberately systemic), which

is in turn composed of instrumental representations of phenomena created and

understood as complex and therefore indecomposable except at the risk of

mutilations. Such a process is constituted by the transition48

from the figure of the

analyst to that of the conceptualizer-constructor, from the decomposable object to the

conceivable project, from decomposition into simple passive elements to composition

of implex actions.

Firms, as social systems composed by autopoietic systems, can deal with the

problem of mastering the system integration process (and its dynamics) only by

creating complexity in the constructions49 that they build and that in some ways affectthe path (or, more precisely, the paths) of the product-system’s change.

Constructions that are results of hard, more or less chaotic/ruled negotiations among

the constructions of the agents in organization legitimated to speak about the

48 Ibidem p. 27-28.49In this chapter the notions of Program (only indirectly considered) and Representation/Construction do not have the

common meanings of cognivitism. Programs are causal micro-theories and different from the notion of programs of

computer science. No program associates completely an action to a situation. It is referred to unreal or counter-factual

situations, namely it can belong to possible states of world to which send counter-factual actions and behaviors (Elster,

1983; Von Wright, 1972; Lanzara, 1993).In this work representing means bringing to the mind-consciousness. It does not mean bringing images, schemes or

models of a perceived external environment, but cognitive structures that build the external environment by associating

meaning to the perceptions that by themselves do not have. Therefore, representations that are not based on systems of

symbols (or, better, not only on them). In this way, they avoid, and partly exceed and summarize it, the classic fourfold

taxonomy which considers them as (1) mental stuff (mirroring the mental aspect of a physical thing), (2) images as

Berkeley and Hume thought (images represent things because they look like them), (3) symbols as Hobbes and

Hugelend sustained (mental representations are linguistic symbols), (4) effective neurophysiological states

(representations as biological phenomena) (Cummins, 1993).

A good definition of representation (or view of the world) is ‘...the stage where all my actions, ideas, passions act,

guided by the same director...’ (Oliviero, 1995). On this subject see Haugeland (1985, 1989), Craik (1943). It is very

interesting the origin of the concept of scheme proposed by Bartlett (1974), the concept of frame suggested by Misky(1989) and the concept of fixed action pattern by Oliviero (1995).

In this work the concept of representation draws heavily on the so-called learning without representation approach (Von Foerster, 1987; Maturana and Varela, 1992a; Maturana and Varela , 1992b).

It has been very useful the notion of knowledge-in-action and the considerations about representation that are not based

on symbolic systems (Bamberger and Shon, 1983; Kosslyn and Hatfield, 1994; Lanzara, 1993).



22

technological trajectories that the systems (and therefore the systems integration)

potentially could assume.

For these reasons, the task of system companies is to keep in house redundant

knowledge basis. It is worth underlining, however, that the judgment on the

importance of the knowledge basis relies heavily on the complexity that the systemcompany has been able to create in the past. But it is for greater convenience that we

are using (and we shall use later on) the label "system company". In effect we are

always referring to the continuous negotiation among "visions" of individuals

(autopoietic systems) into the organizations of that firms, and the continuous dynamic

of their knowledge basis. There are not knowledge basis of "firm", there are only

knowledge basis possessed by men. The path we are referring to is the path of each of

their knowledge basis and the path of the equilibrium points on which the

negotiations among these visions into the organizations converged during the time

past.

This path, which is ex-ante uncertain and non-definable, is the process of the

evolution of the artefact envisaged by the system company and selected in the

marketplace.

Even if the historical path of the organization and the effectiveness-efficiency

achieved by the organizational mechanisms have a great importance, the latter has to

be distinguished by the technical-scientific ‘quality’ of the individuals belonging to

the organization.

The knowledge basis possessed by individuals, the history of these, the history of the

organization, found the roots to create complexity. In other words the knowledge

basis should be considered as generators of the complexity required to create theevolutionary path (or paths) of the systems-systems.

To create complexity means to generate the greater number of different potentialstates of the world , that is to say, technological alternatives for parts, subsystems, and

the whole architecture of the system, and their relationships, for the future "n" time

units, during which you imagine the evolution of the system itself.

An important part of knowledge basis is formed by expertise, that is theoreticalelaboration and hands-on knowledge and, therefore, heavily dependent on the

generative contexts to it refers50

. Moreover, in this frame, the distinction between

knowledge related to the nature of the nature (scientific knowledge usually derivingfrom fundamental or long-term research) and ways of manipulating it (technologies

50The notion of context is extremely important in this paper. A famous definition can clarify its nature: «...context as

collective locus for all the events that indicate to the organism-agent the set of options within which the latter must do

further choice. » Gregory Bateson.

‘The notion of context encompasses the implicit assumption that for an agent the sequence of actions, events and

experience is somehow segmented and divided into contexts that can be considered equal or indifferent. The sensitivity

to context, that is the ability to distinguish and recognize contexts is an essential element of the program for the action

of the actor: it is the base of the action of deciding and controlling its behavior. If the context is pre-interpreted, then

few resources will be mobilized. If, instead, the context is ambiguous, unstable, or too generic, most of the cognitivework of the actor will be aimed to ‘build meaning’, to decode and define the context in order to guide the action.’

(Lanzara, 1993).The nature of the context is somehow generative of the learning. Losing or abandoning a context entails losing its

cognitive generative capacity. In this work, we refer to the generative capacity of the research effort, but we are fully

aware that other generative context do exist, such as manufacturing activity.



23

commonly growing out of applied research and industrial development) tends to blur

and, as a consequence, gives rise to unitary and global knowledge, no longer

decomposable. This process ends up being both effect and cause of the emergence of

new concept of integrated and trandisciplinary knowledge, that merges from

methodologies and sociology of classic sciences, but it is triggered by applications

51

,to which is associated the emergence of scientific-technological disciplines (scien-tech)

52. Figure 2 may help us to better explain the concept.

This small mental experiment represents precisely what there is to know to control

the integration of a multi-tech system with barely four substantially homogeneous

subsystems from a technological point of view.

To be able to command its integration and therefore its evolution, it is necessary to:

• possess the knowledge basis regarding the subsystems;

• possess the knowledge basis regarding the architecture of the system which

represents a separate part of the system itself.

• command a base of knowledge of the interfaces among different technologies

which the system’s architecture anticipates.

But what does possessing the knowledge basis to be able to generate effective

competence and specific ‘know-how’53

mean for a business? According to the

definitions we are giving to this chapter it means that:

• in a business-organisation there are men with profound knowledge at least in thesingle and fundamental scientific-technological disciplines for the forming of

knowledge basis (of the subsystems, architecture and of interfaces);

• the organisation places at their disposal the contexts, (laboratories, product

51In this frame, it is very useful the concept of knowledge mode 2 (Gibbons et al., 1994). For instance, scientists

working in the fluid dynamics field integrate a wide range of disciplines (physics, mathematics, statistics, chemistry,

etc..), but the result of this integration is the disappearance of the distinct contributions of the above-mentioned

disciplines and the emergence of a new discipline. The latter has methodologies, experiments and, therefore, its own

and different paradigms (but analogous in the methodological essence to those disciplines converging in it), a

community of researchers that follows its own trajectories (with its own reviews, debates) which are driven by theapplications (they study for a specific application or more).52Some authors classify such disciplines as fluid dynamics and chemical engineering as transfer sciences. This a new

but still ill-defined taxonomy where there are also some disciplines with ‘scientific’ methodologies and communities,

but as said earlier, are heavily triggered in their development by the applications of principles and elaborated

knowledge. In other words, disciplines where the knowledge on the nature of the nature and on the ways of

manipulating it is blended indivisibly.

‘Transfer sciences share with pure sciences a concern for predictive sciences...their research centres are located in

technical universities...a large part of their funding comes from industry’ (Chesnais, 1992).53 We do not have here the possibility to deeply develop the articulation of knowledge (knowledge basis, competence,

expertise, skill, but we do retain that without a knowledge basis we cannot aspire to the integration system. Perhaps for

operations such as ‘editing’ or assembling only competence and know-how enough without complete theoreticreference (like for the bricklayer who does not know anything about construction science it is enough to know the

‘plumbline’ to build a good, straight wall), but not for the guide of the evolutionary dynamics of an integration system(which means to conceive new forms of walls as well as new alternatives to what forms it. Simply there would not be

sufficient complexity in the constructions of the modality of alternative integration systems, having available only

competence and know-how.



24

processes, organisational machine rules, work methodologies, incentives,

languages, schools, economic resources, power and dynamic distributions,

paradigms, myths, beliefs, stories, etc) to be able to express such knowledge (we

go from individual to multidisciplinary54

task forces, an interdisciplinary55

team, a

stable trans-disciplinary

56

group).

54 We have the multidisciplinary attitude when we are called to work, according to our own knowledge basis in a

specific area of a task with a spirit that we could define as ‘advising’, in fact everyone is responsible on their behalf

while there is normally a ‘command centre’ that integrates everyone’s work and responsibility. 55 We have the interdisciplinary attitude even if bringing our own specific knowledge, everyone’s work is however to

occupy yourself with the entire task, including the integration that is anticipated in this operative order as a collective

operation undergone by all the participants. Everyone is responsible for the task. This set up generally allows

disciplinary fusions. 56 The transdisciplinary attitude not only uses permanent work structures, but it also nourishes disciplinary fusions to

give life to knowledge bearers which are not reduced to discipline anymore. For example, in a multidisciplinary order aproblem of fluid-dynamics can be faced by statistics, physics, chemicals, mathematics, etc. In a transdisciplinary order

that has a history of interdisciplinarity before and transdisciplinarity after, the work group will be constituted only by

fluid-dynamics.



25

Fig.2. A simple abstract system and the minimum knowledge basis to support the

process of system integration (and to construct the complexity of its dynamics)

1 2

34

a b

c

d

ef

g

hi l

mn

I II

III

IV

a b

c

d

ef

g

hi i l l

mn

a b

c

d

ef

g

h

n m



26

1-4 Subsystems-parts

a-n Interfaces

Architecture of the system(relevant substantial relationships from the structure)

I-IV Knowledge basis relevant to subsystems

Knowledge basis relevant to architecture

a-n Knowledge basis relevant to interfaces

The scientific-technological discipline as a whole underlying the knowledge

relevant to subsystems-parts

The scientific-technological discipline as a whole underlying the knowledge

relevant to architecture

a-n The scientific-technological discipline as a whole underlying the knowledge

relevant to interfaces

System Integration (knowledge basis for the integration of the system

naturally emerging from the "application" of all the knowledge basis in

operative contexts in which the integration of the system is broken down)

Fonte: Paoli M., Management of complexity, complexity of management , Mimeo, SSSUP S.Anna, Pisa, Italy, 2000.



27

In any case, knowledge to support the capacity of system integration emerge from the

application of all knowledge in all effective contexts (not only in R&D, but also in

the production of the components and of the system, in the planning, etc) on the basis

of recomposition that we can imagine, given the system’s breakdown carried out to

reconstruct.All these are activities that can clearly be described as “situated”, in other words, as

the fruit of “...interactions between agents and physical systems and with other

people” in a specific context 57, namely that pertaining to the specific agent subject. If

the latter is a social system or an organization58

, then the overall picture also includes

57 Greeno J.G., Moore J.L.: “Situativity and Symbols: Response to Vera and Simon”, Cognitive Science, Special Issue:

Situated Action, vol. 17, n°1, January-March, 1993, p. 49. Although it would be beyond the scope of this paper to carry

out an in-depth study of its more profound implications, it may nevertheless be useful at this point to underline the

importance of the ongoing debate in the field of cognitive science regarding the concept of situated learning, as this

debate has made a major contribution to overcoming the traditional symbolic approach. One the one hand, eminent

scholars such as Simon continue to maintain that «human behavior can be effectively described and simulated by meansof systems of symbols», Vera A.H., Simon H.A.: “Situated action: a symbolic interpretation”, Cognitive Science,

Special Issue: Situated Action, vol. 17, n°1, January-March, 1993, pp. 46 and pg. 7.

On the other hand, total disagreement with the symbolic approach, together with some cogent arguments, is expressed

by those who propose a neuropsychological interpretation of situated action. In this regard, the contribution by W.J.

Clancey is very clear: he advances a number of criticisms against the symbolic approach, accusing the latter of

confusing neurological processes and structures with physical representations that we perceive and manipulate in our

environment, and with experiences of representation in our imagination; furthermore, Clancey contends, the symbolic

approach mistakes the deliberate action of an agent in sequences of behavior over time, for acts of coordination carried

out by the agent. Clancey then puts forward five fundamental propositions concerning situated action: the

representation of memory as a storehouse confuses brain structures with physical pictures that are created and

utilized in language, drawing, writing, etc. The assumption that the representational models and languages

hypothesized by researchers pre-exist in the human brain has led cognitive science to de-emphasize the manner in

which people create daily representations, reducing learning to a syntactic modification of the precompiled ontology of the modelizer/teacher on the standard notations; schematic models wrongly consider learning to be a secondary

phenomenon which necessarily involves representation (reflection);

the integration of perception movement and serial organization of the highest level is dialectic - coherent

subprocesses emerge together - not linearly casual or parallel. Perceiving, thinking and moving are acts that are

accomplished simultaneously in a coordinated manner. The representation may be accomplished within the brain (e. g.,

visualization), but it always involves sensory-motor aspects and it is interactive, although it may be private (in the sense

that representation can be carried out without recourse to the external environment). Furthermore, representation is an

act of perception and perception cannot be separated from movement (e. g., when one is speaking, he understands what

he is saying);

practice cannot be reduced to theory. Efficient practice precedes its theory; methodologies presuppose the application

of methods and critical investigation of which they are the product. It is for this reason that Aristotle judged his own

arguments and those of others to be at times intelligent and at times stupid. And it is for this reason that intelligent

people can carry out various types of operations, although they may be unable to consider any proposition which couldassist them in interpreting how they should be carried out;

situated learning refers to ideas in the philosophy of science concerning the nature of mechanisms and of

descriptive schemas. For an in-depth analysis of the individual propositions, which would of course be beyond the scope of this paper, see

W.J. Clancey, “Situated action: a neuropsychological interpretation. Response to Vera and Simon”, Cognitive Science,

Special Issue: Situated Action, vol. 17, n°1, January-March, 1993, pp. 87-114. Criticism of the symbolic approach has

also been expressed by J.G. Greeno, J.L. Moore, in their article “Situativity and Symbols: Response to Vera and

Simon”, Cognitive Science, Special Issue: Situated Action, vol. 17, n°1, January-March, 1993, pp. 49-59.58 It is important to note that even as far as scientific knowledge is concerned the idea of the disembodied scientist or

the organization is oversimplified. Suffice it to analyze the descriptions of scientific practice, which show how often the

scientists’ aim actually boils down to an effort to present convincing and therefore transparent reports, so that thepractice in question would be easily understandable and reproducible in conformity with an extensive series of

methodological standards. Such a result is obtained by eliminating-justifying-transforming the weighting of all thearbitrary or mythological elements, casual results, fideistic beliefs, situated practices-interactions, etc. (a sort of

theory/practice combination rationalized ex-post) that have contributed to the result. Bonaccorsi A., Pammolli F.:

“Ricerca Scientifica e Attività di Progettazione”, op,. cit., pp. 12-13.



28

the fact of its “being” history and the developmental path of its routines, of its

decision-making mechanisms and the roles of the different interest or power groups

and ideologies (taken as the ideal direction towards which visions of the future should

point) present in the organization itself 59

.

Thus if you don't keep the sufficient number , the sufficient variety the sufficientredundancy of contexts in the firm you drastically diminish your capability of system

integration (you are moving towards roles of assembling, not system integration).

But such capacity diminishes how often you gain knowledge. It diminishes without

anyone being aware of it. It is the metaphor of the blind man who does not know

what he does not see. So whoever loses contexts loses knowledge connected to them,

and becomes less and less capable to construct complexities in their interpretations of

the integration system and therefore of the evolutionary dynamics of the system, but

knows less than what he thinks he may know or know nothing at all. Awareness

appears individually when someone who we have always beaten (perhaps at chess)

finally beats us. It happens from a social point of view (perhaps playing football)

when the team who has never won before finally beats us.

But how many defeats will make it necessary to become aware that it was not fate or

anything else. Also, in a special way in the case of businesses how many signals will

be wasted before someone realises that defeats are the effects of a loss of competitive

ability due to a lack of knowledge, due to the loss of context. Perhaps in homage to

the ways of outsourcing, of core choices, of lean or flat organization. They are

certainly themes that cannot be underestimated but also bases for choices with

strategic consequences that cannot be underestimated either.

59«...knowledge is about meaning. It is context specific and relational.», Nonaka I., Tackeuchi H.: “The knowledge-

creating company”, op. cit., pg. 58.



29

8.5. The relevant strategic problem: maintaining the control ofsystem integration

Not only does knowledge tend to be represented even more in unique (transcendingthe classic dichotomy base-applied) and transdisciplinary (transcending the classic

boundaries between disciplines) ways, but it is even more important if the linguisticoutcomes of cognitive activities (not only R&D, but also design, production

marketing and so on) are more or less appropriable in economic terms, the cognitive processes that may lead to those outcomes, that is processes of production of knowledge (in its articulations, base, competences, expertise) are alwaysappropriable because they are agents-specific and therefore firm-specific. In fact,competencies and historical paths of learning are specific to each autopoietic system

forming the social group called "organization" and they are linked to the evolution of organization and to the system company’s specific organizational setting in terms of number, variety and redundancy of (cognitive) contexts and their constituents

(among which you can find not only routines’ systems and repertoire, but also

physical structures like laboratories, manufacturing environments and so on as we

have already exposed). The latter in their turn can be considered as generators of

robust views of the world or rather, of richer constructions of possible options in the

evolution. The more the processes have completely been internalized over time, the

deeper those possible options are rooted.

Bearing these things in mind, we can apply this summarizing scheme to systems

integration ‘cognitive’ strategy that we can put forward as an exemplary case.

• Given a product/process-system or its family.

• Its system integration evolutionary dynamics, conceived as an ability to

introduce innovations (to be measured not only in quantitative terms; incremental

or radical, but also in qualitative terms; modular, interface, architectural, systemic)

and, therefore, as a capacity to compete through and by means of innovation, can

be described with complex models60

. These models are specific of those particular

individuals and through organizational specifications of those particular groups in

specific organizational contexts in which those particular individuals are working.

• Τhe degree of complexity of those constructions is a function of processes of

relevant knowledge which are absolutely tacit in nature61. Moreover, complexity

60The lower the complexity of the representations, the more the loss of competitive capacity through innovation.61Intense connections can be detected here with the contributions coming from organizational learning from organizing

and strategic contingent theory. For a first look at the concept of organizational learning, see March J.G., Olsen J.P.:

“Ambiguity and Choice in Organization”, Universitetsforlaget, Bergen, Norway, 1976. It is with significant vigour that

Weick states that his concept of «enacted environment is not synonymous with the concept of a perceived environment

... to emphasize that managers construct, rearrange, single out, and demolish many objective features of their

surrounding ... the process of enacting is one in which the subject partly interacts with and constitutes the object » inWeick K.E.: “The Social Psychology of Organizing”, Addison Wesley, Reading, USA, 1979, pp. 164-165. Scott R.W.:

“Organizations”, Prentice Hall, Englewood Cliffs, USA, 1992, pp. 90-92 and p. 141. As to the strategic contingencytheory as an evolution of the contingent theory by Lawrence and Lorsch, see the important contributions of Pfeffer J.:

“The External Control of Organizations”, Harper & Row, New York, USA, 1978. Crozier M.: “The Bureaucratic

Phenomenon”, Chicago University Press, Chicago, USA, 1964.



30

depends on specific situations: (1) of the two ways (circular ) relationships between

scientific (and its state, namely descriptive, predictable, etc..), technological,

applied, and integrated knowledge62

, and (2) of elaboration of experience (all

contained in contexts).

• In any case, for the system companies abandoning activities of support tocognitive processes and contexts (R&D for example, but also manufacturing, of

components and subsystems) and shifting towards a general assembling

organization means losing the capacity of modelling the possible evolution of the

system integration. Put differently, this leads to the loss, often irreversible, of the

ability to create complexity in modelling the evolutionary path of the system, and,

as a result, to the loss of strategic control of the evolution of its integration. The

actual risk is that you could lose the role of system integrator63

becoming a simple

assembler without you realizing it64

.

Naturally, other considerations, predominantly economic or strategic, may in any

case lead to the adoption of different or alternative solutions concerning structure,

level and nature of vertical integration and/or of the various possible internalizations.

But from the point of view of experience-expertise and of the knowledge necessary

for strategic dominion over evolution of the artefact-system integration, it may prove

to be extremely dangerous to entertain the illusion that the cognitive results (of R&D

for example) can systematically be purchased-transferred (which would mean

disregarding the fact that the underlying processes cannot be bought-transferred), just

as it would be equally risky to believe that the division of innovative labor and of

labor in general, together with the sale or transfer of innovative activity and

manufacturing techniques (above all if accompanied by abandonment of research anddesign efforts) need not be systematically considered as the surrender of cognitive

processes, a transfer of generative contexts65, jeopardizing world-creating ability.

62 Reismann A., Management science knowledge, Quorum Books, Westport, Usa, 1992, p.110.63 A System integrator is whoever decides which evolutionary trajectory the system takes.64 With regard to this phenomenon it seems very representative the dynamics of the evolution of technology and in

parallel of the roles among assemblers (almost all ex-system integrators) and componentists in the automotive sector.65The abandonment of an excessively “mentalistic” approach to competence has led to an absolute enhancement of the

context as a co-generator of context. The so-called activity theory (and the multiple intelligence theory) defines

activities as syntheses of mental and behavioral processes, but it does not reduce them to mere mental or behavioral

phenomena. They are analysis units within which the agents’ competence can be assessed in socially organizedcontexts. The object of the analysis is the interaction process of the agents themselves with the reference environment.

The analysis unit is therefore practical action which incorporates (it activates, one might say) the environment-context

(which, therefore, is defined, in this work, as generative). There is no learning without context. That is to say, there

cannot be a learning dissociated from the context in which the practical action-activity will produce it.

Vigotsky L.S.: “Mind in Society”, Harvard University Press, Cambridge, US, 1978.

Leontieff A.N.: “The Problem of Activity in Psychology”, in Wertsch J.V.: “The Concept of Activity in Soviet

Psychology”, Sharpe, W. Plains, USA, pp. 37-71.

Gardner H.: “Frames of mind. The theory of multiple intelligence”, Basic Books, New York, Usa, 1983.

« In order to explain the march of the blind [and naturally explain his learning], then the road, the stick and man are

required; road, stick and man and so forth, recursively », Bateson G.: “Verso un’ecologia della mente”, op.cit., p. 470.

In this regard, it can be likened to the concept of formative contexts: each business routine refers to a formative contextfrom which it receives meaning and which makes it “natural” or “plausible”.

Lanzara G.F.: “Capacità Negativa”, op. cit., p. 38 and 63.On this issue, see also Unger R.M.: “False necessity”, Cambridge University Press, Cambridge, UK, 1987.

Ciborra C., Lanzara G.F.: “I labirinti dell’innovazione, routines organizzative e contesti formativi”, Studi Organizzativi,

n° 19, 1988, pag. 113-134.



31

Failure to realize this peril would inevitably result in diminished capacity for

“imagination-creation” of alternative paths of opportunity.

The costs and strategic implications of such transfers (or more generally, of non-

possession, even if seen in a networking context) should always be evaluated in and

by the decentralizing decision-making processes, in such a way as to mitigate theweight of “economicistic” evaluations and thereby extenuate the idea that networking

to the point of virtualizing system integration is also systematically virtuous66

.

Looking at the issue from a slightly different perspective, it is precisely thanks to

their ability to create opportunity that many leaders of former technologies

substituted by earth-shaking breakthroughs have still managed to retain institutionalcontinuity. Thus strongly rooted chemical industries have successfully survived the

radically innovative waves of synthetic products67

, becoming in their turn leaders of

new solutions, and the same is taking place in biotechnology. Some protagonists of

ICT were leaders in the field of electromechanical office machines long before they

became leaders in information technology68, although short-sightedness concerning

the implosive direction of the computer-system’s architecture within microprocessor

components-integrated circuits has meant that today they are once again experiencing

difficulties in maintaining their role as leaders in control over the evolution of ICT

products-processes system integration.

This ability to retain institutional continuity depends primarily on learning from

experience, in cumulated expertise and capacity for integration of diverse knowledge

basis69

. Such ingredients make it possible to engage in strategic elaboration in order

to overcome the distinction between content-process and context of strategic

elaboration itself 70. This is because learning about the context defines the content of innovative strategic behavior, while implementation of the latter, with the ensuing

learning, redefines, or rather, re-creates a new context, thereby blurring the

demarcation between definition of the content of technological strategy and its

implementation71

. Without experience there can be no learning (non decomposable

and therefore non sharable unitary processes), and without learning there is a failure

or at the very least a decrease in the capacity-ability to continually re-create thespectrum of exploitable opportunities along the path that is equally continually re-

created. Such a spectrum must possess the breadth required by current competition

conditions, or required by the strategic position the firm has assigned itself in a moreor less illusory fashion. This means that it could in fact be pointless for a firm to

66 Paoli M., Prencipe A.: “The Role of Knowledge Bases in Complex Product Systems: Some Empirical Evidence from

the Aero-Engine –Industry”, Journal of Management and Governance, n° 3, 1999.67 Harris R.G., Mowery D.C., Pavit K.: “Strategies for innovation: an overview”, California Management Review, n°32,

1990, pg. 23.68Pavitt K.: “ Chips and trajectories: how does the semi-conductor influence the source and direction of technological

change ?”, in MacLeod R. (Ed): “Technology and human prospect”, Pinter, London, UK, 1986, pg. 31-54.69«Whatever the source of technological breakthrough, it is company wide-ranging R&D expertise that are more likely

to recognise (to create) the significance and potential of both incremental and radical technological developments,Broad R&D competences and skills are a method of dealing with discontinuities turbulence; a way of technology

watching and keeping options open.», Dodgson M.: “Introduction: technology in a strategic perspective”, in DodgsonM. (Ed): “Technology strategy and the firm: management and public policy”, Longman, London, UK, 1989, pp. 4-5.70Ibidem pp. 1-10.71 Implementation of strategic technology is therefore an integral part of its definition.



32

specifically adopt a strategic position of being offensive, defensive, leader or

follower, broad or narrow front72

, because this will to a large extent depend on the

nature and level of integrated-accumulated knowledge basis and competences73

(held

in common, not sharable in a network) which, taken together in specific but adequate

contexts (in-house), endow a firm with greater - or lesser - capacity to maintain thecontrol and direction of system integration, to create technological and market

opportunities for subsequent exploitation as compared to its competitors, and enable

the firm to be more - or less, as the case may be - dynamic, broader or narrower in its

spectrum (different technologies, different scientific fields, integration of

technologies and spectrum, etc.).

72Harris R.G., Mowery D.C., Pavit K.: “Strategies for innovation: an overview”, op. cit., p. 24.73 “The new technologies are enormously complex (we would say that representations required to control them are

complex). Complexity results from the convergence of technologies ... companies show greater diversification in theirtechnological activities than in output because of the nature of contemporary technological interdependencies. Strategic

decisions need to be made on how to deal with this complexity (we would say how to create complexity in therepresentations of technological strategies); on how to match or better the opportunity it provides to existing or potential

competitors”. Dodgson M.: “Introduction: technology in a strategic perspective”, in Dodgson M. (Ed), “Technology

Strategy and the firm: management and public policy”, op. cit., p. 4.



33

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