belussi (1)
TRANSCRIPT
-
7/30/2019 belussi (1)
1/24
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
1
1
-
7/30/2019 belussi (1)
2/24
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
2
2
-
7/30/2019 belussi (1)
3/24
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
3
, 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).
3
3
-
7/30/2019 belussi (1)
4/24
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).
4
4
-
7/30/2019 belussi (1)
5/24
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.
5
5
-
7/30/2019 belussi (1)
6/24
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.
6
6
-
7/30/2019 belussi (1)
7/24
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.
7
7
-
7/30/2019 belussi (1)
8/24
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).
8
8
-
7/30/2019 belussi (1)
9/24
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).
9
9
-
7/30/2019 belussi (1)
10/24
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).
10
10
-
7/30/2019 belussi (1)
11/24
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.
11
11
-
7/30/2019 belussi (1)
12/24
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.
12
12
-
7/30/2019 belussi (1)
13/24
Fig. 2 The mechanisms of knowledge creation in the Italian LPS
13
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
-
7/30/2019 belussi (1)
14/24
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.
14
14
-
7/30/2019 belussi (1)
15/24
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)
15
15
-
7/30/2019 belussi (1)
16/24
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.
16
16
-
7/30/2019 belussi (1)
17/24
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
***
**
17
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
-
7/30/2019 belussi (1)
18/24
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 .
18
18
-
7/30/2019 belussi (1)
19/24
19
19
-
7/30/2019 belussi (1)
20/24
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