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Knowledge creation and learning in the institutional governance of the

Italian local production systems

by F. Belussi and L. Pilotti - Padua University

Second draft

May 1999

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The theory of perfect competition is unscientific because, byassuming a world of perfect knowledge in which firms cannot

interact to change their economic environments, such a theory

imposes pompous preconditions on our subject matter: competitors

are so constrained in behaviour in which they can engage....we areprecluded from understanding economic reality or developing a

testable theory. Burton H. Klein (1977, p. 71)

1. Introduction

The aim of this paper is to present an overview about the various mechanisms ofknowledge creation, diffusion, and assimilation, which are found within the so-called

Italian local production systems. For this type of analysis we use here a wide

definition of local production systems (LPS) which includes: typical industrial

districts, multi-sectors district areas, local systems governed by large leading firms,

and various aggregations of productive systems in territorial clusters (Belussi, 1999).

This paper discusses the process of knowledge creation and learning within the

governance of the Italian LPS, and the role played by tacit and codified knowledge.

Using the seminal contribution of Polany and Nonaka, we can trace a clear cut

distinction between the two forms of knowledge above mentioned. Codification refers

to a form of objectivated knowledge (a set of justified true beliefs), thus an explicit

form of knowledge that is related to the scientific results of basic research andinnovative activity (a body of facts, information, principles and practical

understanding of science). In turn, explicit knowledge may be classified in two ways.

As disembodied, if refers to the progress of science and technology (laws, formulas,

meaningful set of information articulated in clear language including numbers or

diagrams, or scientific discoveries related to then state of organic or inorganic

substance: new compounds, new materials, etc.). Or as embodied, if it lies within

technological tools such as scientific instrumentation, new machinery, or new

information and communication technology with an enlarged computational

capability, and etc.

Intuitively, this is opposed to tacitness1, a subjective (both individual and shared)

property of knowledge, linked to the abilities that individual possesses on the basis ofpieces of knowledge developed through practical experience (unarticulated mental

models, intuitions, skills).

The idea developed in this paper, based on many pieces of empirical research

conducted by the authors over the last decade, is that the Italian LPS may be

categorised on the basis of the prevalence of the pool of knowledge they have access

to. In turn, this appears in relation with the presence of various forms of learning.

Adopting this approach we can distinguish the Italian local production systems (LPS)

into three main categories2:

1It is important to point out that tacit knowledge is not closely related to craftsmanship. Polanyi, the author who developed the

concept of tacit knowledge, based his theoretical framework on the analysis of the activities performed by a group of scientists(Polanyi, 1958). See also Ryle (1949).2

We can assume that all knowledge developed and transferred among local agents bears the characteristics of being

contextual knowledge: a collective good whose generation and expansion is the result of a process that combines pieces of

information and knowledge that are owned by a variety of parties and that cannot be traded as such (Antonelli, 1999b). This

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a) Systems based mainly on the horizontal expansion of a given stock of knowledge,

historically accumulated in particular localities, where tacit knowledge among

agents is prevailing;

b) Systems where the specialisation of the local manufacturing structure has gone

further, and it has activated a process of absorption of external knowledge. So, avertical and an horizontal process of knowledge expansion has occurred. Thus, the

stock of knowledge possessed by local firms is formed by a balanced pool of tacit

and codified knowledge.

c) Systems organised around knowledge generating firms, where the knowledge

creation process has enlarged the local (and the global) stock of knowledge. Here

we assume the presence of systematic radical innovations. The trade balance of

knowledge sees the LPS as importers of knowledge and as exporters of

knowledge. Within this group of LPS, export flows of knowledge are more

relevant than import flows: the clustering of innovations and the total amount of

knowledge embedded in local firms allow us to define these LPS as technological

districts. Here, among firms codified knowledge prevails, but tacit knowledgeremains important.

The evolutionary pattern of Italian local production systems may be fully understood if

the institutional complexity that exists behind these historical aggregations of

manufacturing firms is considered. Not only local firms are active agents in

knowledge producing, but also local institutions contribute to the process of

information and knowledge diffusion. So, in various ways, tacit and codified

knowledge is elaborated, recombined, transferred, and socialised as a circular process

between the two basic typologies.

This paper, given the debate that has arisen in recent years on codified knowledge

versus non-codified knowledge, examines the wide ranging international debate.

Theoretical knowledge in modern times has developed at a quite spectacular pace.

However, in our paper, we examine the view that the process of growth of knowledge

observable in our society might be depicted simply as a radical shift towards a

generalised process of codification.

The main purpose of the paper is to reassess the importance of tacit knowledge

in modern economic systems. We address the issue of the importance of tacit

knowledge not only in its pivotal role of (new) knowledge generation in high-tech

sectors, as in Senker (1995), or MacKenzie and Spinardi (1995).

The idea discussed throughout this essay is that tacit knowledge always plays a

significant role in firms

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, in all branches of economic activity. Despite its importance itis generally ignored in the economic literature. We believe that a proper understanding

of the tacit elements of knowledge is decisive in modelling industrial dynamics. The

role of tacit knowledge in firms is in fact central to the absorption and the practical

utilisation of external knowledge. And, because the amount of external knowledge

that firms require to operate is undoubtedly greater than the knowledge that they can

reasonably afford to produce in-house, tacit knowledge become a strategic element in

firm organisation. More specifically, in the interpretation proposed here, economic

approach follows in part the Hayekian view, where knowledge is stated as partially private, empirical, often tacit, and not all

gained through price signals (ODriscoll and Rizzo, 1985, p. 102). Then, the assumption of a world of perfect knowledge is

unrealistic; what is relevant for the economic agents is the knowledge of the particular circumstances of time and place(Hayek, 1945).3The approach presented, with some variations, is similar to one employed by Nonaka, and by the stream of studies started offafter the Nonaka contribution (Nonaka, 1993; 1995; and Nonaka, Umemoto, and Senoo, 1996).

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agents, in order to have access to the existing stock of knowledge, and to put codified

knowledge in action, need a great deal of cognitive capabilities, and informal skills.

New ideas, and new technical solutions, are continuously generated in the world, but

the process of knowledge transfer is much more complex than one portrayed by

standard theory. In order to have access to novelties, firms must be aware of them, and

then they must be able to assimilate and absorb the new knowledge generated outside.The application of new knowledge requires acceptance, adoption and inter-firm

diffusion. All these sub-processes are related to informal learning capability (Gilbert

and Cordey-Hayes, 1990). Thus, the successful management of knowledge transfer

needs firstly, a re-contextualization of external knowledge (for reconverting and

decoding the innovation), and secondly, an operational encoding of this new

knowledge into the internal firms capabilities and organisational routines. During

these different steps tacit knowledge is retained, accumulated, and spontaneously

created within organisations.

But what can we say about the relation between tacit knowledge and codified

knowledge?

David and Foray (1995) put forward the thesis that because the scope of whatcan be codified seems to be continually expanding (thanks to the new advances

produced by the scientific and technological progress), the codification of knowledge

is central to the modern process of dissemination, transfer and retention of knowledge.

Cowan and Foray (1997), linking codification with the dynamics of the firm

information structures, reinvigorate this thesis. A similar point is also outlined in

Arora and Gambardella (1994).

But should the increasing use of general and abstract knowledge mentioned

above lead us to conclude that the amount of tacit and (practice knowledge) within the

economic systems is destined to decrease?

The main issue addressed here focuses on the universal importance that tacit

knowledge still has in explaining the different performance of LPS in comparison with

the rest of the economy. The growing awareness that a fundamental part of knowledge

possessed by agents has a tacit form, leads us to speculate on the different composition

of these two forms of knowledge exhibited within the LPS.

In our view, which is based on empirical analysis, significant levels of tacit

knowledge are still at work in the territorial model of LPS. However, among them, as

we have tentatively classified in Fig.2, tacit knowledge has different relative weight.

But we do not deny that within the more innovative LPS, during the last phase of

development, a great amount of codified knowledge has not only be absorbed but also

produced.

So, is therefore the codification trend a plausible hypothesis that helps us toforecast the future changes of the LPS economies?

Within the LPS investigated, a growth of codified knowledge has been

detachable, particularly within the stronger and more organised systems. And without

fear of being contradicted, it can be said that the growing complexity of these

structures has multiplied the intelligent nodes (Albertini and Pilotti, 1996), where

codified knowledge is re-elaborated and transferred. For the reasons explained in

details in section 5, this does not occur at the expense of the stock of the existing

tacit knowledge. Tacit knowledge, as we could investigate within the LPS, not only

has not declined at all, in absolute terms, but, it is relatively becoming more important

in the mapping out the evolution of firms production networks. In comparison with the

past, the new agile relational networks built-in within the LPS during 1980s, haveexternalised and diffused the old pool of existing tacit knowledge along an enlarged

informational circuit (Belussi and Arcangeli, 1998).

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The analysis presented in the paper places the discussion of codification of

knowledge in a wide framework.

1. First, we discuss the blurring boundaries of the dichotomy between codified versus

tacit, reaffirming the fundamental role of tacit knowledge as opposed to codification.

2. Second, we emphasises the contextualization of knowledge, a process that

represents an opposing trend, juxtaposed to the previous one, and antagonistic to

generalisation and abstraction that put knowledge in action, and localised it in

specific territorial and productive contexts.

The concept of knowledge contextualization comes near to the work of Nonaka and

Konno (1998). They define extensively this concept on the base of their model of

knowledge creation. Ba can be thought as a shared space for emerging

relationships. A space that is defined in three main dimensions, structured in a

mixture of individual and/or collective knowledge:

a - physical (office, dispersed business space);b - virtual (e.g. electronic equipment, teleconference, e-mail);

c - mental (e.g. shared experienced, ideas, ideals).

The analyses of Nonaka and Konno are a useful tool which help us to describe the

dynamics of LPS. The spatial clustering of activities (and innovation processes)

defines the context where we see the creation of pieces of non codified knowledge

(tacit knowledge), and where the mixture of codified and tacit knowledge embedded in

the territory becomes a collective good, not transferable outside. However, creativity

and innovation is not simply resident in ba, but in a complex circular process between

codified and non codified knowledge at individual level or within collective

organisations (firms, networks and institutions).

The paper is organised as follows. Section 2 reviews the debate about the various

forms of knowledge. Section 3 elaborates a taxonomy of the various forms of learning,

distinguished as: instructive, adaptive and generative. In the following section we

discuss the importance of contextual knowledge. Here we argue that the spiral process

of conversion of knowledge, implied in the Nonaka model, works in part. Not all

existing codified knowledge (external knowledge) can be absorbed from outside the

LPS, and, conversely, the externalisation of knowledge is never complete outside the

LPS, because attrition and protective local institutional mechanisms, that make

localised knowledge partially tacit and difficult to replicate and imitate. In section 5

an overview of our empirical research conducted is presented. Section 6 containssome concluding remarks.

2. The generation and absorption of tacit and codified knowledge

It is common knowledge that knowledge is a very complex subject to analyse.Technological knowledge involves various degrees of complexity, specificity,

openness, cumulativeness, opportunity, transferability, appropriability, and tacitness.

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Moreover, the creation of new pieces of useful knowledge in firms, the innovation

process, requires a great deal of endogenous expertise and exogenous sources to be

included. Knowledge itself (Arrow, 1994) is an input into the production of other

goods, but it also an output: it is a function of resources devoted to knowledge as well

as a function of the existing knowledge. And it is not just the average level of

knowledge that is relevant, but also its distribution (diffusion) among agent.Not all knowledge is of such form that can be easily transferred.

Some personal knowledge or tacit knowledge related to abilities, routines, know-how,

or specific practical skills, deriving from experience cannot be codified, and thus

cannot be simply transferred.

Knowledge in practice tends to be highly tacit in nature, while abstract

knowledge scientific knowledge related to the theoretical understanding, and to the

scientific principles, has the characteristic of being fully codified.

This distinction may be clearer if we recall the Lundvall and Johnson (1994)

metaphor. While the former type of knowledge has to do with knowing how, and

includes some forms of active participation (knowing in action) of the knowledgeable

agent and relational capability know-who, the latter is related to a passive andmerely conceptual understanding of knowing what and knowing-why (speculative

awareness on the state of the world).

These two forms of knowledge do not coincide. Routinised activities, and skills may

be learned and reproduced without someone is being able to go back to their scientific

rationales4. Furthermore, it is also true that to use codified knowledge we need a

certain amount of tacit knowledge and ability. In the history of technology we observe

a path of evolution of many specific pieces of knowledge that have become over the

time fully codified (this includes many crafts products that were industrialised under

the constraint of technical progress5). But, generally speaking, different degrees of

tacitness are embodied in knowledge, in relation to the various levels of scientific and

technological activities. In pure science knowledge is typically articulated, controlled

by scientific advanced instrumentation, and formalised in written theories, formulae,

and testable falsification procedures. Nearly one hundred percent of this is codified.

The more we move away from pure science, the more we find that the degrees of

codification decline, and tacit knowledge grows in intensity. Incremental technological

activities and applied research normally contain high levels of tacit knowledge. All

thing considered, because activities related to applied research and direct production

have a large influence on the economic structure, we can infer, at least, that activities

related to tacit knowledge- are not marginal. Given the obvious difficulty in

measuring how much knowledge exists, either codified or tacit, these reflections

maintain a certain degree of abstraction and inaccuracy. (One deals with affirmationsthat have no possible practical demonstration but that have strong theoretical and

practical implications in terms of technology policy).

The discussion about codification versus tacitness has brought out some

important contrasts.

In recent years the nature of technology has come under scrutiny. In particular,

a wide-ranging debate has explored the changing nature of technological change.

Some convincing predictions see in the nearer future a possible intensification in the

4In regard to this, a few examples were reported by Nelson and Winter (1982). In short: the physiology of muscular movementmay be unknown to an athlete without affecting his or her performance.5 History is full of disquieting anecdotes. Expert systems have proved to be a complete disaster in running financial activitiesin stock markets, and during the black October 1987 they nearly provoked a catastrophe, but automatic pilots are commonlyused as a support and extension of human senses. In the ceramic industry, in Sassuolo, the knowledge of skilled pluggers is

still far superior of any computer-controlled program. At the end of a very automated production cycle, human abilities governthe cocking, times and the weight of specific ingredients. The use of computer programs for translations has produced very

poor results, while the codification of technical designs has gone further, etc.

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rate of technical change in firms, as well as an increased degree of knowledge

codification. An era of transition has been forecast towards more universal

technological systems, cast in frameworks and categories that relay on more

generalised, more transmissible abstract pieces of knowledge. Some have claimed

that, because the dominant technological paradigm is now information technology, the

distribution of knowledge between tacit and codified has dramatically changed infavour of codification: after all, information technology is about processing, storing,

and transmitting information and codified knowledge. This is for instance the position

of Cowan and Foray (1997), and Arora and Gambardella (1995).

On the contrary, more cautious remarks can be found in the contributions of

Lundvall (1995 and 1996), Senker (1995), Dosi (1996), and Breschi and Malerba

(1997).

As stated by Lundvall (1996a),

..while the codification can go very far in the field of know-what there are important

limitations for the codification in other fields of knowledge. Know-why can be fully codified only in

areas where little new knowledge is currently produced or the new knowledge is purely incremental.

When scientific principles are in a state of flux or when they are disputed within the scientific

community they cannot easily be communicated outside a narrow group of scientists. ..The work on

expert system is far from innocent There are skills of an intuitive kind which remain hidden and tacit

and which cannot be incorporated when the codification takes place. Finally it is obvious that a

register of names cannot integrate the social network of relationships which are included in the know-

who category. (p.7)

Arguments that oppose the codification trend are the following:

1. The introduction of the information technology paradigm has not just increased

the stock knowledge we can use; it has (above all) increased, to the nth degree,

the availability of data; in turn, this has also dramatically increased the circulationof unnecessary information as well. The overload of information we observe, will

oblige people to make ever greater use of their tacit knowledge, to select the

relevant information they can utilise.

2. There is a spiral of conversion of tacit into codified knowledge, but more tacit

knowledge is needed to handle this new codified knowledge. Let us take the case

of medicine. There are now more research centres, more scientific journals, more

discoveries, more instrumentation, and more cures, but the specific skills of

experts has not be undermined. So, the expansion of codified knowledge has been

a paralleled by the expansion of tacit knowledge (also among the users of the

services).

3. With the contemporary trend towards a post-Fordist society, based on skilledwork, or knowledge workers, it is the entire labour market that in fact is moving

towards activities, jobs, and tasks, where learning attributes and tacit knowledge

are becoming more important. This implies that there is little evidence of a

diminishing role of the tacit elements that form the reservoir of knowledge in

society: human capital.

4. Lundvall (1996b) has recently pointed to the dawn of the Learning Economy.

Today we find ourselves in an economy in which the competitiveness of

individuals, firms, and entire systems of innovation reflects their ability to learn.

The learning economy places emphasis on interactions (user-producer

relationships), and on knowledge sharing and networking. Both these features

represent some tacit competencies related to the expansion of tacit knowledge.

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5. The social dimension of learning is of paramount importance. The knowledge of

human knowledge (Tamborini, 1997) finds active elaboration of: mental

models6, feedback mechanisms of knowledge verification and testing (based on the

individual or on the collective experience), where, to allow the passing of the

message, common languages, meanings, metaphors, heuristics, visions7, beliefs

and conventions must shared among actors. Hence, in practice, as argued byLundvall, a symbiotic relation is established between the two form of knowledge.

Codified knowledge may be utilised only through recourse to tacit knowledge. The

decisive importance of subjective, and partial knowledge, accumulated by

individuals is that they learn only when tacit knowledge is embodied in actions 8.

Individuals are the constructors of empirical human knowledge. Tacit

knowledge is used to frame the perception of their reality (Schon, 1979), to

structure their behaviours, to select and encode the relevant information they need,

to filter and re-assemble knowledge (abstract and tacit), to receive signals and

elaborate their content, etc. Within the economic organisations, therefore,

individuals experience a continuous elaboration and exchange of codified and tacit

knowledge. But economic agents do not just act, they interact. They are able notonly to absorb codified knowledge, but also to create new knowledge (framed in a

tacit or in an explicit setting). Generative relationships are conducive to learning

procedures, to innovation activity, and to the establishment of new organisational

routines (Lane, Malerba, Maxfield, and Orsenigo, 1996). The industrial networks,

and the emerging knowledge-based organisations, must be regarded as the

classical locus where these interactions generate a new stream of localised

technical change (Antonelli, 1999a). Generative interactions use both tacit and

codified knowledge, and innovation (new pieces of knowledge) takes place among

multilevel loops, or chains, of tacit-plus-codified converting it into tacit-plus-

codified new knowledge.

In summary, in this section we have presented two antagonistic perspectives. On one

hand, we have presented the view of those who believe that codification is becoming

the essence of the economic activity, on the other hand we have put forward some

arguments, that suggest caution, and support the apparently contradictory thesis that

the impact of the 1990s changing will not change the balance between codified and

tacit knowledge very much. Following the pioneering contributions of some Italian

economists such as Antonelli, Malerba, Rullani, and Vacc, we have asserted the

permanent influence of the mechanisms which generate tacit knowledge within the

economic system, suggesting the growing importance of localised learning and open-

ended processes of conversion between tacit and codified knowledge.

3. Instructive, adaptive and generative learning

6 As argued by Denzau and North (1994), people act in part upon the basis of myths, dogmas, ideologies, and half-backedtheories. In condition of uncertainty individuals interpretation of their environment will reflect their knowledge. Individual withcommon cultural backgrounds and experience will share their knowledge. Shared mental models guide choices and the evolution

of political-economy. Mental models, institutions and ideologies all contribute to the process by which human beings interpret and

order their environment.7

In his compelling article on the existing different theories of the firm, Fransman (1994), whose aim is to describe the influenceexerted by these visions on the firm internal process of knowledge and information, presents what he calls the Ibm paradox. It isa clear case of a firm clinging to the mistaken belief in the ability of the mainframe computer to sustain profitability at least until

1991, despite the information which it possessed (and processed), contradicting this belief.8

The classical reference here is in Argyris and Schon (1974).. For an excellent survey see Tosoukas (1996).

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This section focuses on the diffusion of knowledge and the growth of human capital.

The growth and diffusion of knowledge, both tacit and codified, take places in firmsand organisation through learning activities. Economic literature has tended to

separate the growth in the stock of knowledge from its diffusion (Davies, 1979;

Mansfield, 1961; Mahajan and Wind, 1986; Rogers, 1962). This distinction, going

back to Schumpeter, has proved to be useful when a new piece of knowledge can be

identified, such as a particular invention.

However, most advances in knowledge are not achieved at once, and then slowly

adopted by potential users (Stoneman, 1983). Rather, new technical change is the

outcome of many building blocks, and it embodies many ideas. In the assembly of

innovations many agents and sources are involved. Tacit and codified knowledge is

necessary to disentangle the main research objectives, and to implement the discovery

process. If this is so, the growth of knowledge may be portrayed essentially as aninteractive process of learning and invention.

This new way of addressing the issue of the growth and diffusion of knowledge

has provoked two significant consequences at intellectual level.

Firstly, diffusion and growth may be seen as joint products: growth is often

inseparable from diffusion. The innovation process may takes place in different steps

and involving many actors.

Secondly, learning activities in firms are both devolved to absorb the existing

external knowledge (from the historically created pool of knowledge) and to create

new knowledge9.

The Arrows (1962) formulation of learning by doing shed lights on this analytical

dilemma and captures the linkage of growth and diffusion. In Arrows view, learning

(improvements in firm knowledge) is related to the accumulated experience of firms,

measured by the proxies of a) the cumulative output and, b) the growing number of

adopters.

However, if we follow the Arrows tradition, we focus our attention only to the

individual firm and its search procedures.

What is missing is that we do not deal explicitly with differences among agents. It

is the combination of different ideas that produces new knowledge. And different

ideas gives rise to better ideas because knowledge (both tacit and explicit) is unevenly

distributed among agents. If each agent knew exactly the same thing, the exchange of

information would no produce any increase on the amount of knowledge in each firm.So, learning activities may be also portrayed as a decentralised process of diffusion of

knowledge. Spillovers of knowledge depend in part on how hard firms are trying to

capture new knowledge (this may be measured by the length, extension, and

numerosity of informative channels, and by frequency with which information passes

through them). But also by the knowledge gap: the existing differences in what firms

know (some agents are rich of accumulated knowledge, and they may play the role of

activators of knowledge/competencies, within the system of relationships which they

govern).

Spillovers and learning efforts may be analysed from a territorial perspective.

By elaborating our research we have sketched three forms of learning, which take

place among the firms of the LPS analysed: instructive, adaptive and generativelearning (Fig. 1).

9This point was first treated in a satisfactory manner by Choen and Levinthal (1989).

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Fig.1 Models of learning

Type of knowledge Instructive Adaptive Generative/creative

Tacit

Codified

Instructive

This form of learning is mainly related to the transmission of simple instructions from

skilled workers to apprenticeship through (intra-firm) transfer of tacit knowledge or it

refers to the technical specification provided to subcontractors (inter-district firms).Knowledge is transfer among the production networks, where firms co-operate in

relationships more or less arm length. The modality that we have called instructive

learning refers mainly to the transfer of tacit knowledge. This, in any case, requires the

exchange of a lot of information and knowledge. Recourse to instructive learning

avoids within the various LPS avoids the degradation of the existing stock of

knowledge. This stock of knowledge, referring mainly to traditional manufacturing

activities grows slowly. Instructive learning is bounded10 by the absence of relevant

innovations (once the ability of perform a certain task is settled only minor

modification may be introduced). Craft skills form the main component of the existing

stock of knowledge that is embedded in particular LPS. These skills still seem to be

crucial in some sectors such as clothing, footwear, furniture, etc. Here firms base theircompetitiveness on traditional craft labour force skills. Given the fact that, in the

nineteenth century, many skills have been lost because of technological progress due

to the introduction of mass production, large scale industrialisation, and the

standardisation of labour tasks, the formation of the Italian LPS, and the diffusion of

instructive learning have allowed the maintenance of these tacit skills. So, while

world wide a loss of skills and an un-learning process (a forgetting of knowledge)

have occurred, in the cases studied, abilities, skills, and tacit competencies have been

kept alive thanks to this mechanism of knowledge sharing and imitating through side

to side job training of individuals and by exchange of experience which occurs along

the subcontracting chains.

10On this issue see also Young (1993).

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Adaptive

Adaptive learning characterised the type of learning that has occurred in the

Italian industrial districts during 1970s. Is stems mainly on the reduction of

transaction costs, and it is based on the imperative of making the firm organisational

design flexible. It did not involve only labour force skills but also focused on

improving product and processes. Typically it involved learning by doing, by using,

and by interacting (client-supplier relationship). The stock of knowledge grows

incrementally, with the ongoing industrial activities. The model of flexible

specialisation set the boundaries of learning activities that were initiated. Firms

learned to react and adjust to market signal, to co-operate in dense but territorially

dispersed networks, to slightly modify product and processes. When a small new pieceof knowledge is incorporated in a firm of the LPS, very soon this new knowledge

spread because imitative procedures. So, firms tend to balance their knowledge.

Adaptive learning is not just limited to the growth and diffusion of tacit knowledge, it

can involve also pieces of codified knowledge. Among firms one finds an acceleration

in the mechanisms for absorbing external tacit and codified knowledge. The

absorption of external knowledge may also be performed by local LPS institutions

like training centres, or ad-hoc laboratories. R&D activities are carried out by some

firms of the district.

Generative learning

Generative learning is the most creative form of learning we can find in LPS.

Generative learning is activated by creative agents interactions and it focuses

primarily on the creation of new knowledge. It describes the behaviour of some LPS

during 1990s, reflecting their more complete form of learning. In these LPS thepresence of firms with built-in generative learning models increase greatly the stock

of existing knowledge. The new knowledge produced here has the characteristic of

being semi-private (it is shared only within the final firms production systems). New

knowledge tends to be codified in a local rather than universal code. Generative

learning increases both tacit knowledge and codified knowledge.

In the most dynamic LPS high levels of knowledge creation occur in parallel with an

institutional complexity of the industrial structure (emerging leading firms and

dominant networks). A cognitive division of labour is emerging among firms. The

division of innovative labour crosses the entire local industrial structure. Final firms

or hub firms concentrate their activity on the strategic core of new product design,

engineering, marketing and post-sale services. Manufacturing activity (routinisedactivity) is often delegated to small local producers.

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Fig. 2 describes the historical trend of the evolutionary pattern of knowledge diffusion trajectories.At the beginning, LPS are characterised by the presence of tacit knowledge. The contextualization of

tacit knowledge prevails, as well its externalisation (among individuals or firms) through the traditional

form of learning-by-doing and instructive learning. A permanent sharing between tacit and explicit

knowledge characterises the second step. Here a process of re-contextualization of external (codified

knowledge) takes place.Adaptive learningprevails in systems where there is a balance between tacit

knowledge and codified knowledge. There is then a migration of dynamic districts towards a third level

of transformation, where we find a type of contextual knowledge that incorporates radically new

pieces of knowledge. This type of knowledge is prevalently codified and it can be transmitted outside,

through a process of de-contextualization. Generative learning is here activated. The innovation

governance of LPS is modelled by a double string:

A - contextualization- re-contextualization and de-contextualization of knowledge;B - decodified-codified-redecodified of knowledge.

This double string of transformation knowledge is directed to reinforce the local innovation process

of LPS.

In the figure we see three different types of structural evolution, depending upon the pool of

knowledge they have access to. Where the focus is on instructive systems, the single agent or small

firms are dominant. Where the focus is on adaptive systems, the grouping of firms prevails. Finally, the

focus ongenerative systems is inducing a more complex structure (networks of networks), mediated by

the presence of local or multi-localised institutions, playing the role of transferring, and re-re-

transferring knowledge.

This last level of evolution of contextual knowledge produces a virtuous integration between

codified and non codified knowledge.

The Italian LPS have experimented, firstly, a transition from a classical Smithians division of

labour(instructive learning) to a more technically based Marshallians division of labourwith agents

sharing atmospheres, signalling, and externalities, secondly, a more recent transition towards a post-

Fordist organisational model, characterised by a cognitive inter-firms division of labour (with the

sharing of tacit knowledge within the organisational nets). Leading firms, network-of-networks, and

institutions populate these districts.

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Fig. 2 The mechanisms of knowledge creation in the Italian LPS

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13

DIFFUSION OF

TACITKNOWLEDGE

CREATION OF SOME

EXPLICITKNOWLEDGE

PREVALENCEOF EXPLICIT

KNOLEDGE

TACIT

KNOWLEDGE

BALANCE

BETWEENCODIFIED

KNOWLEDGE ANDTACIT

HIGH LEVELS

OFKNOWLEDGE

CREATION

CONTEXTUALIZATIONTACIT KNOWLEDGE

SOCIALISATION

RECONTEXTUALIZATION

KNOWLEDGE ABSORPTION

ABSORPTION

DECONTEXTUALIZATIONNEW KNOWLEDGE ISCREATED AND THENCHANNELED OUTSIDE THELPS

LOCAL

KNOWLEDGEDIFFUSION

AGENTSAND LEARNING

TRAJECTORIES

FLOWS OFEXPORTS OF

KNOWLWDGE

FIRMS

LEADERS ANDGROUPING

INSTITUTIONSAND

NETWORKS

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2. From contextual to global knowledge: an incomplete mechanism of

conversion

It is useful at this point to introduce the concept of localised technical change(Antonelli, 1999a). Antonelli s perspective sets the theoretical basis for understanding

the role of tacit elements in the contextualization of knowledge.

Technological change is inherently localised in that it consists of changes in the technical capability of

structures that are limited to a well defined set of characteristicsLocalised technological change

builds upon structured information ..that, as a public good, is available to everybody with low, thoughnot negligible costs, of imitation and acquisition. Tacit knowledge instead is the result of lengthy

learning processes; it is idiosyncratic and specific to the organisation and business environment of thefirm. .. Technological change is more or less localised according to the mix of internal and external,

codified and tacit knowledge on which it depends, but neither form may be dispensed with It consistsof specific pieces of technological know-how obtained by means of learning by using and doing. It

incorporates the experience and skills of labour as well as the opportunities of improving products andproduction processes generated by highly circumstantial factors and events Since localised

knowledge is mainly tacit, because it is implicit and embedded in the memory of organisations and inthe economic, regional and industrial environment of each firm, it is difficult to learn, imitate, transfer,

adopt and use. It is more proprietary and it use is more excludable than in the Arrowian tradition.(p.5-6).

The dynamics of localised technical change provides the basis of the formation of

contextual knowledge. Contextual knowledge is embedded in the territory and it is

formed by elements of codified knowledge (absorbed also from the outside), and tacit

knowledge (developed slowly within the production process in practical experience,and internally to the networks of relationships that surround that place).

Contextual knowledge may be described as the social output of an historical

process of accumulation of technological capabilities and skills. This occurs only if in

a specific territory the mechanism of development is activated (for this reason

contextual knowledge is linked with territorial industry specialisation).

When external economic conditions are favourable, the territory becomes a

system: the model of LPS takes-off. Knowledge creation and propagation occur as a

consequence of the development of firms. But the creation of contextual knowledge

is at the same time a cause and effect of growth. In other words, a circular loop

between growth and knowledge is at work. LPS are accelerators of new technologies

in the presence of network externalities11(Belussi, 1998).The evolutionary path of growth that originates within the LPS model starts with

the grow of a restricted number of firms: the LPS founders. In these firms knowledge

and technical skills become consolidated, and contextual knowledge is promoted.

Knowledge propagation is achieved via the entrepreurialisation of technical and

professional people. Their level of professionalism allows them to leave the firms and

become small independent entrepreneurs. The industrial structure of LPS expands

through a process of firms gemmation. During the first phases, instructive and

11Technological externalities related to the rapid adoption of innovation (the bandwagon effect); externalities deriving fromthe co-ordination of investments among the firms which participate to the same production networks; externalities oftransaction costs reductions based on the social climate of trust linked to the visibility of actors, and to the social bounds of

friendships and relationships; externalities stemming from the abundance and sharing of information; externalities related to thepresence of specific centres of research or training that offer tailored specialised services and information; and externalities

deriving from the presence of specialised suppliers in the intermediate parts utilised from the final firms.

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adaptive learning behaviours diffuse. The exchange of information and knowledge

occur via the transfer of personal experience and know-how.

Subsequently, new waves of spin-offs may occur, populating the district with

small innovative producers: the frequency of contacts, and the numerosity of

exploratory searching lead, due to the law of large numbers, in the end to improved

products or processes: thus, often, generative learning is activated12

. Contextualknowledge is developed in practice by local economic agents, and new knowledge is

generated through the interactions agents (suppliers, clients, subcontractors, and local

institutions).

Looking back to the extraordinary commercial success of the Italian model,

which in our paper we have defined as the LPS, it should be saied that too much

attention (and speculation) has been made on terms like flexibility, small firms, and

etc. In the view shared by the authors of this paper, in the establishment of this type of

industrial structure the process was sustained, above all, by the existence of high

levels of contextual local knowledge. Practical and contextual knowledge was

transmitted through apprenticeship and personal contacts.

Practical and contextual knowledge, from this perspective, may be viewed asan existing strategic (but immaterial) resource, that is essentially territorial-specific.

This cognitive form of social capital, historically accumulated in the LPS model, can

be viewed as a sunk investment.

Only agents operating in the local district have access to it, and they may

further enlarge and exploit its profitability through strategies of entrepreneurial

growth. This process, thus, is highly path-dependent, and built up upon a nucleus of

original local skills and competencies.

The development of these idiosyncratic LPS is territorial-specific. This bears an

important consequence: the nature of contextual knowledge, therefore, is bound to the

spatial boundaries of the systems: contextual knowledge can not be completely

globalised. Spatial proximity and social mechanisms of sharing knowledge

facilitate its local transmission. Over long-distance (which is relational as well

spatial), frictions dominate13. It is obviously true that some innovations introduced by

the firms of LPS can be clearly codified, and imitated elsewhere. So, the codified

elements of contextual knowledge are more at risk. But, differently from what

Nonaka claimed, the conversion of tacit knowledge, into external knowledge, is far

more difficult. It follows, that on the whole, the contextual knowledge of the various

LPS can never go over the LPS walls, thus it can not be completely externalised.

The verification of this interpretation regarding the factors of competitiveness of

LPS clearly can only be indirect. However, the imitation by other countries has proved

difficult. And the areas of specialisation on which LPS compete internationally havenot varied very much over the last two decades. During this time, LPS have proved to

be quite stable structures, and not foot loose organisations. They have deepened their

roots in their territory, which is also a community of people, sharing local traditions,

habits, language, and entrepreneurial visions. The process of globalisation have passed

over them. LPS were already global in their market outlets. In nearly all LPS export

12R&D-dependent radical innovations are not typically produced within the LPS, where firms are often small sized. Radical

innovation would require the specialisation of dedication of resources to invention and innovation. But a great deal of

innovative activity is generated trough learning by interaction.13

A similar perspective is also developed in the Breschi and Malerba (1997)

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flows are quite high14 (typically 40-50%) of total firms sales, with some remarkable

peaks.15

5. A topology of Italian local production systems: towards evolutionary

governance

In Fig. 3 , using our tacit knowledge, we have sketched an evaluative map of the

topological characteristics of LPS, based on their degree of formalisation of

knowledge. The institutional complexity is placed on horizontal axis, and on the

vertical axis the balance between tacit and codified knowledge is reported. This

diagram presents three emerging models: a) with high tacit knowledge and few firms-horizontal linkages, and no specific role of institutions; b) with an equal balance

between tacit and codified knowledge, and with many leading firms (presence of

hierarchical linkages), with the addition that here many institutions provide training

and services which are related to a process of spreading tacit and codified knowledge;

c) with high levels of codified knowledge and many leading agents including global

(multinational) firms as well, and the clear presence of knowledge-intensive

institutions.

Below a topology referring to specific LPS governance is presented.

1. The first cluster represents systems where tacit knowledge among agents

predominates. Tacit knowledge is mainly embodied in the labour force skills, and in

the craft production, innovations introduced by firms are incremental. These LPS are

mainly specialised in traditional sectors, defined here as skill-intensive industry, like

clothing and knitting, in Carpi, Vicenza and Reggio Emilia, or glass making in

Murano, an island near Venice, and so on.

2 . The second cluster includes those LPS where there is a balance between tacit and

codified knowledge. These are concentrated on mechanical engineering sectors:

biomedical instruments in Mirandola, near Modena, water taps fittings in Varese,

frames for eyeglasses in Cadore, near Belluno, leather upholstery producers in the

district of Matera -Altamura-Santeramo. etc. In these LPS codified knowledge is well

developed, the sources of innovation are more formalised and located in engineering

and design departments, and product innovation is frequent; here many actors

contribute to the socialisation of knowledge and to the reinforcement of codified

knowledge, like training schools, universities or special services (supplied by the local

authorities) for small firms (servizi reali alle imprese).

14Considering the 50 product groups made in Italy localised in LPS (Montedison, 1998), we observe that these groups areresponsible for a huge positive balance of trade (in 1995: 148.015 billions of lire, which surpassed the total net balance of

67.550 billion of lire; 1996: about 125.000 on a total of 39.000). Export flows were in 1995 154.294 billions of lire and in 1996

(first nine months) 104.318. For 21 products typically manufactured in LPS, the Italian firms are first placed and Italy has thebest international trade balance, and for other 8, Italy ranks as the second or third country exporter.

15See, for instance, the packaging machinery district in Bologna (Belussi, 1999), where about 95 % of total output is exported, or

the Montebelluna district specialised on ski boots (Pilotti, 1999), that supplies 75% of the international markets.

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3. In the third cluster the dominant feature is the prevalence of codified knowledge

(however, tacit knowledge is still important). Some examples are ski boots production

Fig. 3 A topology of the Italian LP: the formation of contextual knowledge and the implementation of

learning strategies

***

**

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17

Tacit contextual

knowled e

Codified and tacitknowledge

New knowledgecreation

Instructive learning

Atomistic agents/firms

Adaptive learning

Few leaders/Horizontal grouping

Generative learning

Open networks/institutionsNetworks-of-networks

CARPI (knitting and clothing)

VICENZA (jewellery)REGGIO EMILIA (agriculture

machinery)MANZANO (chairs)

MURANO (glasses)

MANIAGO (knifemanufactures)

MIRANDOLA (medicalmachinery)

SANTERAMO(upholstered furniture)

CADORE (frame- lasses

MOTEBELLUNA (Ski-boots)

BOLOGNA (packagingmachinery)

SASSUOLO (ceramic tiles)

Up-grading of

processes and products

Introduction ofrelevant innovations

Elaboration of

formalised knowledge(original innovations in

processes and products)

Radical innovations

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in Montebelluna, the auto-components makers in the Modena-Bologna area, or the

packaging machinery industry in Bologna.

Codified knowledge in these systems seems quite developed. Here many firmshave R&D departments (but often only in the engineering department where new

product are launched). Many local institutions play the role of meta-organiser such as

the Museo dello Scarpone in Montebelluna, or the Demo center for the quick

prototyping of mechanical auto-components. In the most advanced systems the

division of labour of innovative activity is quite clear-cut: only large final firms and

local institutions devote specific resources to technical change. In the rest of the

system generative learning occurs unintentionally as a by-product of the daily

manufacturing activity.

6. Conclusions: some lessons from the Italian experience

Despite the increasing attention given to the role played by knowledge in the

economy, the current debate among economists and technologists demonstrates a quite

contradictory nature. On one side, as discussed by Cowan and Foray (1997), or Arora

and Gambardella (1994), among others, the process by which knowledge and

information evolve in the economy is described as a tendency towards a continuousprocess of knowledge codification. This is seen as the natural trajectory of scientific

progress, and as direct consequence of the development of the ICT technological

paradigm. The emphasis on tacit knowledge is found in another field of research. The

importance of tacit knowledge is underlined by those who place the characteristics of

learning, the notion of localised technical change, and the evolution of competencies

and routines in firms (the evolutionary school) at center of their interests. In this work

we have developed a methodology of analysis of this topic based on the verification of

the codified vs tacit debate within the case of the Italian LPS.

The importance of contextual knowledge has been highlighted, along with the

symbiotic relationship between tacit and codified knowledge. In our analysis of LPS

two key dimensions have been examined: the combined levels of tacit and codifiedknowledge and the institutional governance. Our result confirm, by an large, within

the analysed systems the undiminished role of tacit knowledge within the systems

analysed .

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References

Antonelli C. (1999a),The Microdynamics of Technological Change, Routledge,

London.

Antonelli C. (1999b), Communication and innovation: the evidence within

technological districts, Tser, mimeo.

Albertini S. and Pilotti L. (1996), (eds),Reti di Reti, Cedam, Padova.

Argyris C. and Schon (1974), Theory in practice, Jossey-Bass, San Francisco.

Arrow K. (1962), The economic implication of learning by doing, Review of

Economic Studies, vol. 29

Arrow K. (1994), The production and distribution of knowledge, in Silverberg G. and

Soete L. (eds), The Economics of Growth and Technical Change, Edward Elgar,

Aldershot.

Becattini G. and Rullani E. (1996), Local systems and global connections: the role of

knowledge, in Cossentino F., pyke F., and Sengenberger W., (eds), Local regional

response to global pressure: the case of Italy, Geneva, Italy.

Belussi F. (1999), The generation of localised technological change through

communication processes. The case of the packaging machinery industry in the

Bologna district, Inloco, Mimeo.

Belussi F. (1999), Policies for the development of knowledge-intensive local

production systems, Cambridge Journal of Economics, forthcoming, vol. 23, n. 6.

Belussi F. and Arcangeli F. (1998), A typology of networks: flexible and evolutionary

firms,Research Policy, vol. 27.

Breschi S. and Malerba F. (1997), Sectoral innovation systems: technological regimes,

Schumpeterian dynamics and spatial boundaries, in, Edquist C., (ed), Systems of

Innovation, Cassel, London.

Cohen W. and Levinthal D. (1989), Innovation and learning: the two faces of R&D,

Economic Journal, vol. 99.

Cohen W. and Levinthal D. (1990), Absorptive capacity: a new perspective on

learning and innovation,Administrative Science Quarterly, vol. 35.

Cowan R. and Foray D. (1997), The economics of codification and the diffusion of

knowledge.Industrial and Corporate Change, vol. 6, n. 3, pp. 595-622.

Cossentino F., Pyke F., Sengenberger W. (eds), (1996), Local and regional responseto global pressure: the case of Italy and its industrial districts , Ilo, Geneva.

20

20

7/30/2019 belussi (1)

21/24

David P. and Foray D (1995), Accessing and expanding the science and technology

knowledge-based economy, STI Review, n. 16.

Davies S. (1979), The Diffusion of Process Innovation, Cambridge Univ., Cambridge.

Denzau A. and North D. (1994), Shared mental models: ideologies and institutions,Kyklos, vol. 47n. 1, pp. 3-31.

Dosi G. et al. (1988), (eds), Technical Change and Economic Theory, Pinter, London.

Edquist C. (1997), (ed), Systems of Innovation, Cassel, London.

Foray D. and Freeman C. (1993), (eds), Technology and the Wealth of Nations. The

Dynamics of Constructed Advantages, Pinter, London.

Georghiou L. et al. (1986), Post Innovative Performance, Macmillan, London.

Fransman M. (1994), Information, knowledge, vision and theories of the firm,

Industrial and Corporate Change, vol. 3, n. 3, pp. 713-757.

Gibbons M. and Johnston R. (1974), The role of science in technological innovation,

Research Policy, vol. 3.

Gilbert M and Cordey-Hayes M. (1990), Understanding the process of knowledge

transfer to achive successful technological innovation, Technovation, vol.16, n. 6, pp.

301-312.

Gottardi G. (1996), Technology strategies and innovation without R&D, Journal of

Industry studies, vol. 2., December.

von Hayek F. (1945), The use of knowledge in society,American Economic Review,

vol. 35, pp. 519-30.

von Hippel E. (1988), The Sources of Innovation, Oxford Univ. Press, Oxford.

Imai K., Nonaka I., and Takeuchi H. (1985), Managing the new production

development, in Clark K., Hayes R., (eds), The Unease Alliance, HBS Press, Boston.

Klein B. (1977),Dynamics Economics, Harvard Univ. Press, Mass., Cambridege.

Kline S. and Rosenberg N. (1986), An overview of innovation, in Landau R. and

Rosenberg N. (eds), The Positive Sum Strategy, National Academic Press,

Washington.

Kline S. (1990), Innovation stiles in Japan and in the United States: cultural bases,

implication for competitiveness, The 1981 Thurston Lectures, Rep. Inn-3, Dep. of

Mechanical Engineeering, Stanford Univ.

Kodama F. (1992), Technology fusion and the new R&D, Harvard Business Review,July-August.

21

21

7/30/2019 belussi (1)

22/24

Lissoni F. and Metcalfe (1994), Diffusion of innovation ancient and modern. A review

of the main themes, in Dodgson M. and Rothwell R. (eds), The Handbook of

Industrial Innovation, Edward Elgar, Gower House.

Levin R., Klevorick A., Nelson R., and Winter S. (1987), Appropriating the returns

from industrial research and development, Brooking Papers on Economic Actuvity,vol. 3.

Lundvall B. (1992), National Systems of Innovation. Towards a Theory of Innovation

and Interactive Learning, Pinter, London.

Lundvall B. (1996a), The social dimension of the learning economy, Druid working

papers. 96-1, pp.22.

Lundvall B. (1996b), Information technology in the learning economy- challenges for

development strategies, memorandum for United Nations Commission for Science

and Technology, mimeo

Lundvall B. and Johnson B. (1994), The Learning Economy,Industry Studies, vol. 1,

n. 2., pp-23-42.

MacKenzieD., and Spinardi G. (1995), Tacit knowledge, weapon design and the

unconvention of nuclear weapons, American Journal of Sociology, vol. 101, n.1,

pp.44-99.

Mahajan V. and Wind Y. (1986), Innovation Diffusion of New Product Acceptance,

Ballinger Pub., Cambridge.

Malerba F. (1992), Learning by firms and incremental technical change, Economic

Journal, vol. 102.

Mansfield E. (1961), Technical change and the rate of imitation, Econometrica,

October.

Montedison Ufficio studi-Cranec Universit Cattolica di Milano (1998), Il ruolo dei

distretti industriali nel made in Italy, paper presented at conference Distretti

industriali: la via italiana al lavoro e allo sviluppo, Milano, 17th February.

Nelson R. (1993),National Systems of Innovations, Oxford Univ. Press, Oxford.

Nelson R. and Winter S. (1982), An Evolutionary Theory of Economic Change,

Harvard Univ. Press, Cambridge, Mass.

Nonaka I. (1993), On a knowledge creating organisation, mimeo, paper presented at

the Associazione nazionale Formatori, Parma, October 23th-30.

Nonaka I. (1995), The Knowledge Creating Company, Oxford Univ. Press, Oxford.

Nonaka I., Umemoto K., and Senoo D. (1996), From information processing toknowldge creation: a papradigm shift in business management, Technology in Society,

vol.18, n.2, pp.203.218.

22

22

7/30/2019 belussi (1)

23/24

Nonaka I. and Konno N. (1998), The concept of Ba: building a foundation of

knowledge creation, California Management Review, vol. 40, n. 30.

ODriscoll G. and Rizzo M. (1985), The Economics of Time and Ignorance, Basil

Blackwell, Oxford.

Pavitt K. (1984), Sectoral patterns of technical change: towards a taxonomy and a

theory,Research Policy, vol.13.

Pilotti L (1998), I distretti innovativi del nord, Sviluppo e Organizzazione, n. 187, pp.

15-32.

Polanyi M. (1958),Personal knowledge, Routledge, London

Rogers E. (1962),Diffusion of Innovations, The Free Press, New York.

Rothwell R., Townsend J., Teubal M., and Spiller P. (1977), Some methodologicalaspects of innovation research, Omega, vol. 5., n. 4.

Rothwell R. and Gardiner P. (1985), Invention, innovation, re-innovation and the role

of the user: a case study of British hovercraft development, Technovation, vol. 3.

Rothwell R. (1994), Industrial innovation: success, strategy, trends, in Dodgson M.

and Rothwell R. (eds),Handbook of Industrial Innovation, Elgar, Gower.

Ryle G. (1949), Knowing how and knowing that, in The Concept of Mind, Hutchinson

University Library, London.

Schon D. (1979), Generative Metaphor: a perspective on problem setting, in Ortony A

(ed),Metaphor and Thought, Cup, New York.

Senker J. (1995), Tacit knowledge and models of innovation, Industrial and

Corporate Change, vol. 4, n. 2.

Silberstone A. (1989), (ed) Technology and Economic Progress, Macmillan, London.

Stoneman P. (1983), The Economic Analysis of Technological Change, Oxford Univ.

Press, Oxford.

Tamborini R. (1997), Knowledge and economic behaviour, A constructivist approach,

Evolutionary Economics, vol. 7, pp. 49-72.

Teece D. (1986), Profiting from technological innovation: implication for integration,

collaboration, licensing and public policy,Research Policy, 6, vol. 5.

Tsoukas H. (1996), Forms of knowledge and forms of life in organised contexts,

Warwick Business School, n. 171, pp. 1-44

Thirtle C and Ruttan V. (1987), The Role of Supply and Demand in the Generationand Diffusion of Technical Change, Harwood Academic Publishers, London.

23

23

7/30/2019 belussi (1)

24/24

Vicari S. (1998),Limpresa creativa, Etas, Milano

Young Y. (1993), Invention and bounded learning by doing, Journal of Political

Economy, vol. 101, n. 3, pp. 443-466

24